Search results for testing
component-runtime-junit is a test library that allows you to validate simple logic based on the Talend Component Kit tooling.
To import it, add the following dependency to your project:
This dependency also provides mocked components that you can use with your own component to create tests.
The mocked components are provided under the test family:
emitter : a mock of an input component
collector : a mock of an output component
The collector is "per thread" by default. If you are executing a Beam (or concurrent) job, it will not work. To switch to a JVM wide storage, set the talend.component.junit.handler.state system property to static (default being thread). You can do it in a maven-surefire-plugin execution.
You can define a standard JUnit test and use the SimpleComponentRule rule:
The rule can also be defined as a @ClassRule to start it once per class and not per test as with @Rule.
To go further, you can add the ServiceInjectionRule rule, which allows to inject all the component family services into the test class by marking test class fields with @Service:
The JUnit 5 integration is very similar to JUnit 4, except that it uses the JUnit 5 extension mechanism.
The entry point is the @WithComponents annotation that you add to your test class, and which takes the component package you want to test. You can use @Injected to inject an instance of ComponentsHandler - which exposes the same utilities than the JUnit 4 rule - in a test class field :
If you use JUnit 5 for the first time, keep in mind that the imports changed and that you need to use org.junit.jupiter.api.Test instead of org.junit.Test. Some IDE versions and surefire versions can also require you to install either a plugin or a specific configuration.
As for JUnit 4, you can go further by injecting test class fields marked with @Service, but there is no additional extension to specify in this case:
Streaming components have the issue to not stop by design. The Job DSL exposes two properties to help with that issue:
streaming.maxRecords: enables to request a maximum number of records
streaming.maxDurationMs: enables to request a maximum duration for the execution of the input
You can set them as properties on the job:
Using the test://collector component as shown in the previous sample stores all records emitted by the chain (typically your source) in memory. You can then access them using theSimpleComponentRule.getCollectedData(type).
Note that this method filters by type. If you don’t need any specific type, you can use Object.class.
The input mocking is symmetric to the output. In this case, you provide the data you want to inject:
The component configuration is a POJO (using @Option on fields) and the runtime configuration (ExecutionChainBuilder) uses a Map
The following tutorials are designed to help you understand the main principles of component development using Talend Component Kit. With this set of tutorials, get your hands on project creation using the Component Kit Starter and implement the logic of different types of components. Creating your first component Generating a project from the starter Creating a Hazelcast input component Creating a Hazelcast output component Creating a Zendesk REST API connector Handling component version migration With this set of tutorials, learn the different approaches to test the components created in the previous tutorials. testing a Zendesk REST API connector testing a Hazelcast component testing in a continuous integration environment
This section mainly concerns tools that can be used with JUnit. You can use most of these best practices with TestNG as well. Parameterized tests are a great solution to repeat the same test multiple times. This method of testing requires defining a test scenario (I test function F) and making the input/output data dynamic. Here is a test example, which validates a connection URI using ConnectionService: The testing method is always the same. Only values are changing. It can therefore be rewritten using JUnit Parameterized runner, as follows: You don’t have to define a single @Test method. If you define multiple methods, each of them is executed with all the data. For example, if another test is added to the previous example, four tests are executed - 2 per data). With JUnit 5, parameterized tests are easier to use. The full documentation is available at junit.org/junit5/docs/current/user-guide/#writing-tests-parameterized-tests. The main difference with JUnit 4 is that you can also define inline that the test method is a parameterized test as well as the values to use: However, you can still use the previous behavior with a method binding configuration: This last option allows you to inject any type of value - not only primitives - which is common to define scenarios. Add the junit-jupiter-params dependency to benefit from this feature.
This tutorial focuses on writing unit tests for the input component that was created in this previous tutorial. This tutorial covers: How to load components in a unit test. How to create a job pipeline. How to run the test in standalone mode. The test class is as follows:
Several data generators exist if you want to populate objects with a semantic that is more evolved than a plain random string like commons-lang3: github.com/Codearte/jfairy github.com/DiUS/java-faker github.com/andygibson/datafactory etc. Even more advanced, the following generators allow to directly bind generic data on a model. However, data quality is not always optimal: github.com/devopsfolks/podam github.com/benas/random-beans etc. There are two main kinds of implementation: Implementations using a pattern and random generated data. Implementations using a set of precomputed data extrapolated to create new values. Check your use case to know which one fits best. An alternative to data generation can be to import real data and use Talend Studio to sanitize the data, by removing sensitive information and replacing it with generated or anonymized data. Then you just need to inject that file into the system. If you are using JUnit 5, you can have a look at glytching.github.io/junit-extensions/randomBeans.
Developing new components includes testing them in the required execution environments. Use the following articles to learn about the best practices and the available options to fully test your components. Component testing best practices Component testing kit Beam testing testing in multiple environments Reusing Maven credentials Generating data for testing Simple/Test Pipeline API Beam Pipeline API
You can reuse Maven settings.xml server files, including the encrypted ones. org.talend.sdk.component.maven.MavenDecrypter allows yo to find a username/password from a server identifier: It is very useful to avoid storing secrets and to perform tests on real systems on a continuous integration platform. Even if you do not use Maven on the platform, you can generate the settings.xml and`settings-security.xml` files to use that feature. See maven.apache.org/guides/mini/guide-encryption.html for more details.
TCOMP-2241: [Runtime convergence] : Join connector fails - No translator known api beam
TCOMP-2303: Pattern validation error in JsonSchemaValidatorExt component-form
TCOMP-2304: talend-component:web goal may fail with java >= 17 maven-plugin
TCOMP-2277: Complete the TCK schema’s entry properties schema-record
TCOMP-2285: Support of qualifier in version of connectors to be loaded by the component manager component-manager
TCOMP-2291: Provide to streaming connectors the stop strategy applied component-manager
TCOMP-2297: Support flow return var for tck connector in studio studio studio-integration
TCOMP-2236: Streaming stop strategy in livy jobs beam component-manager
TCOMP-2265: Upgrade beam to 2.37.0 beam
TCOMP-2272: Use java 17 TSBI image for component-server component-server starter tsbi
TCOMP-2294: Upgrade batik to 1.16 maven-plugin
TCOMP-2295: Upgrade tomcat to 9.0.68 component-server
TCOMP-2296: Upgrade jsoup to 1.15.3 documentation
TCOMP-2298: Upgrade netty to 4.1.85.Final testing
TCOMP-2303: Pattern validation error in JsonSchemaValidatorExt component-form
TCOMP-2241: [Runtime convergence] : Join connector fails - No translator known api beam
TCOMP-2236: Streaming stop strategy in livy jobs beam component-manager
TCOMP-2289: Payload validator fails on regexp matching component-manager
TCOMP-2186: Guess schema service for processors api schema-record
TCOMP-2276: Make Streaming stop strategy configurable component-manager studio
TCOMP-1998: Remove component-server-vault-proxy from cloud environments component-server component-server-vault-proxy helm-charts vault-client
TCOMP-2256: Replace nashorn javascript engine by rhino component-manager studio
TCOMP-2259: Support db column name/length/precision with guess schema for all types studio
TCOMP-2268: Upgrade jib to 0.22.0 remote-engine-customizer starter tsbi
TCOMP-2273: Upgrade TSBI to 3.0.8-20220928070500 component-server starter tsbi
TCOMP-2274: Move component-starter-server to TSBI starter
TCOMP-2275: Use java 17 TSBI image for CI build build tsbi
TCOMP-2286: Upgrade jackson to 2.13.4
TCOMP-2287: Upgrade commons-text to 1.10.0 documentation
TCOMP-2276: Make Streaming stop strategy configurable component-manager studio
TCOMP-2239: Fix Record.Builder interface to avoid API break schema-record
TCOMP-2226: Implement a default UI for streaming sources for user configuration of a StopStrategy component-form component-manager
TCOMP-2234: Override blocking read process in streaming connectors component-manager studio
TCOMP-2258: @Documentation to tooltips in uiSchema component-form component-server
TCOMP-2147: Decrease log level for blacklisted dependencies component-manager
TCOMP-2228: Upgrade git-commit-id-plugin to 4.9.10
TCOMP-2232: Upgrade slf4j to 1.7.34
TCOMP-2238: Upgrade jib-core to 0.16.0
TCOMP-2249: Upgrade johnzon to 1.2.19
TCOMP-2251: Upgrade jackson to 2.13.3
TCOMP-2252: MavenRepositoryResolver call fallback only it’s needed component-manager
TCOMP-2257: Upgrade meecrowave to 1.2.14 component-manager
TCOMP-2263: Upgrade openwebbeans-se to 2.0.27 component-manager
TCOMP-2264: Upgrade TSBI to 3.0.5-20220907120958 tsbi
TCOMP-2239: Fix Record.Builder interface to avoid API break schema-record
TCOMP-2182: Guess Schema in Studio always uses version of component 1 studio studio-integration
TCOMP-2190: Handle partial messages for large payloads in websocket communications component-server studio
TCOMP-2107: Implement a stop strategy for streaming input connectors component-manager studio
TCOMP-2177: Suppress illegal reflective access operation has occurred warnings component-manager
TCOMP-2163: [QA] Component Runtime API test Framework testing
TCOMP-2187: Introduce IntegerConstraintEnricher component-form
TCOMP-2204: Upgrade netty to 4.1.79.Final
TCOMP-2205: Upgrade crawler-commons to 1.3
TCOMP-2206: Upgrade guava to 31.1-jre
TCOMP-2207: Upgrade maven to 3.8.6
TCOMP-2208: Upgrade maven-shade-plugin to 3.3.0 build
TCOMP-2209: Upgrade junit5 to 5.9.0
TCOMP-2210: Upgrade tomcat to 9.0.63
TCOMP-2211: Upgrade cxf to 3.5.2
TCOMP-2212: Upgrade bndlib to 5.2.0
TCOMP-2217: Update rat-plugin to 0.14 build
TCOMP-2219: Add API to convert data in Record schema-record
TCOMP-2223: Upgrade log4j to 2.18.0
TCOMP-2227: Upgrade commons-io to 2.9.0
TCOMP-2229: Upgrade jcommander to 1.81
TCOMP-2230: Allow specific context UI
TCOMP-2233: support decimal type
TCOMP-2190: Handle partial messages for large payloads in websocket communications component-server studio
TCOMP-2177: Suppress illegal reflective access operation has occurred warnings component-manager
TCOMP-2177: Suppress illegal reflective access operation has occurred warnings component-manager
TCOMP-2176: Record : Infinite loop schema-record
TCOMP-2146: Car bundler improvements car-bundler maven-plugin
TCOMP-2151: Add documentation translation to metadata component-server
TCOMP-2132: Optimisation for preparation schema-record
TCOMP-2143: [JDBC TCK]: Support MODULE_LIST field for studio in tck connector ui for driver jars choose studio
TCOMP-2152: Upgrade jackson to 2.13.2 beam bom maven-plugin
TCOMP-2153: Bump netty to 4.1.77.Final due to CVE CVE-2022-24823 testing
TCOMP-2154: Upgrade maven-settings to 3.8.5 due to CVE-2021-26291 build
TCOMP-2155: Upgrade jdom2 to 2.0.6.1 due to CVE-2021-33813 beam
TCOMP-2164: Ensure that decryption is done only on credential fields component-server vault-client
TCOMP-2171: Add component type to ComponentIndex component-server
TCOMP-2152: Upgrade jackson to 2.13.2 beam bom maven-plugin
TCOMP-2146: Car bundler improvements car-bundler maven-plugin
TCOMP-2111: [Runtime convergence] : Join connector fails in cloud environment with hybrid tck/beam connectors api beam
TCOMP-2123: Bug on order columns for Avro Impl beam schema-record
TCOMP-2127: Fix avro records where array contains nullable array beam schema-record
TCOMP-2131: starter-toolkit fails when generating a connector from openapi description starter
TCOMP-2133: component-registry uses detailed version not baseVersion in snapshot case build maven-plugin
TCOMP-2134: Activate intellij plugin by default intellij starter
TCOMP-2138: starter-toolkit github repository creation process fails starter
TCOMP-2135: Component web tester in non interactive mode component-server maven-plugin testing
TCOMP-2126: give default implementation to Record.Builder to not break api api
TCOMP-2130: Add git informations in starter-toolkit’s environment starter
TCOMP-2127: Fix avro records where array contains nullable array beam schema-record
TCOMP-2130: Add git informations in starter-toolkit’s environment starter
TCOMP-2126: give default implementation to Record.Builder to not break api api
TCOMP-2085: Add extras manipulations on Record BuilderImpl beam schema-record
TCOMP-2102: Wrong maven resolution with car when using snapshot in prepare-repository goal build maven-plugin
TCOMP-2119: Avro Record : array containing Null. beam schema-record
TCOMP-2112: [JDBC] discover schema API is failing on production. build maven-plugin
TCOMP-2103: Link affected jira components to issue in changelog as keywords for search documentation
TCOMP-2098: Improve m2 discovery process documentation
TCOMP-2104: Header link should be linked to latest path documentation
TCOMP-2105: Upgrade Tomcat to 9.0.60 component-server maven-plugin starter
TCOMP-2108: Upgrade maven plugins
TCOMP-2109: Upgrade git-commit-id-plugin to 4.0.5
TCOMP-2110: Replace log4j by reload4j stitch
TCOMP-2114: Upgrade TSBI to 2.9.27-20220331162145 component-server component-server-vault-proxy starter tsbi
TCOMP-2115: Upgrade jackson to 2.12.6 due to CVE-2020-36518 bom
TCOMP-2116: Upgrade log4j2 to 2.17.2
TCOMP-2117: Upgrade slf4j to 1.7.33
TCOMP-2118: Upgrade tomcat to 9.0.62 (mitigation for CVE-2022-22965) component-server component-server-vault-proxy starter
TDI-47693 : fix misaligned openwebbeans-spi dependency studio
TCOMP-2003: Maven dependency classifier considered as version in dependencies.txt by Studio
TCOMP-2096: Support BigDecimal type in DI integration
TCOMP-2087: Upgrade Tomcat to 9.0.59 due to CVE-2022-23181
TCOMP-2088: Upgrade OpenWebBeans to 2.0.26
TCOMP-2089: Upgrade meecrowave to 1.2.13
TCOMP-2090: Upgrade johnzon to 1.2.16
TCOMP-2091: Upgrade Beam to 2.36.0
TCOMP-2092: MvnCoordinateToFileConverter fakes classifiers' support
TCOMP-2093: Improve component-runtime documentation site
TCOMP-2097: Upgrade cxf to 3.5.1
TCOMP-1803: RecordBuilder.withRecord(final String name, final Record value) doesn’t accept null value
TCOMP-2079: Intellij plugin fails on plugin startup
TCOMP-2080: AvroRecord refuses Union[null, RecordSchema]
TCOMP-2082: ComponentManager’s findDefaultM2 method takes comment as granted
TCOMP-2058: Add dependencies on config
TCOMP-2074: Change JSON log format to conform to ECS
TCOMP-2083: Give component-runtime version on ComponentManager startup
TCOMP-2084: Allow use of i18n in connectors' metadata for custom labels
TCOMP-2079: Intellij plugin fails on plugin startup
TCOMP-2080: AvroRecord refuses Union[null, RecordSchema]
TCOMP-2082: ComponentManager’s findDefaultM2 method takes comment as granted
TCOMP-2063: Avro Record Constructor
TCOMP-2064: NPE with lookup missconfiguration in Join processor
TCOMP-2067: Bug on order columns
TCOMP-2071: Define default methods on Schema / Entry / Record interfaces
TCOMP-2045: Pass and read meta information about columns.
TCOMP-2072: Ligthen parameters for component-server docker image
TCOMP-2057: AvroSchema : optimize getType by using type fields
TCOMP-2060: Upgrade log4j2 to 2.17.0 due to CVE-2021-45105
TCOMP-2061: Upgrade netty to 4.1.72.Final due to CVE-2021-43797
TCOMP-2065: Internationalized Services as Serializable
TCOMP-2068: Upgrade log4j2 to 2.17.1 due to CVE-2021-44832
TCOMP-2069: Create a latest tag for component-runtime images
TCOMP-2070: Upgrade TSBI to 2.9.18-20220104141654
TCOMP-2073: Upgrade maven-core to 3.8.4 due to CVE
TCOMP-2047: RecordBuilder in RowstructVisitor keeps values
TCOMP-2048: RowstructVisitor should respect case in member not java convention
TCOMP-2049: Incompatible class change on Entry
TCOMP-2053: Migration failing when using custom java code in configuration
TCOMP-2018: Optimize Avro Record
TCOMP-2054: Upgrade log4j2 to 2.16.0 due to CVE-2021-44228
TCOMP-2053: Migration failing when using custom java code in configuration
TCOMP-2054: Upgrade log4j2 to 2.16.0 due to CVE-2021-44228
TCOMP-2049: Incompatible class change on Entry
TCOMP-2047: RecordBuilder in RowstructVisitor keeps values
TCOMP-2048: RowstructVisitor should respect case in member not java convention
TCOMP-2019: Sanitized columns name collision support
TCOMP-2021: Missing logic when handling null date values in Record
TCOMP-2046: Rowstruct visitor recreates schema at each incoming row
TCOMP-2004: [Runtime convergence] New tck/API to retrieve dataset full content
TCOMP-2008: Add ability to insert a schema entry on Record BuilderImpl
TCOMP-1924: Support Java 17 runtime
TCOMP-2023: Upgrade gradle to 6.9.1
TCOMP-2024: Upgrade maven-bundle-plugin to 4.2.1
TCOMP-2025: Upgrade documentation to latest
TCOMP-2027: Upgrage junit to 5.8.1
TCOMP-2028: Provide nashorn scripting engine when using java15+
TCOMP-2029: Upgrade jaxb to 2.3.5
TCOMP-2030: Upgrade Tomcat to 9.0.54 due to CVE-2021-42340
TCOMP-2031: Upgrade Beam to 2.33.0
TCOMP-2032: Upgrade Spark to 3.2.0
TCOMP-2035: Check build w/ Java 17 on CI
TCOMP-2036: Upgrade cxf to 3.4.5
TCOMP-2037: Upgrade johnzon to 1.2.15
TCOMP-2038: Upgrade bouncycastle to 1.69
TCOMP-2042: Return a key related to version of connector services and its content
TCOMP-2043: Upgrade spotless to 2.17.3 and talend-java-formatter to 0.2.2
TCOMP-2044: Upgrade TSBI to 2.9.2-20211106085418
TCOMP-2294: Upgrade batik to 1.16 maven-plugin
TCOMP-2295: Upgrade tomcat to 9.0.68 component-server
TCOMP-2045: Pass and read meta information about columns. studio-integration
TCOMP-2096: Support BigDecimal type in DI integration schema-record studio studio-integration
TCOMP-2070: Upgrade TSBI to 2.9.18-20220104141654 build component-server component-server-vault-proxy tsbi
TCOMP-2105: Upgrade Tomcat to 9.0.60 component-server maven-plugin starter
TCOMP-2030: Upgrade Tomcat to 9.0.54 due to CVE-2021-42340
TCOMP-2053: Migration failing when using custom java code in configuration
TCOMP-2054: Upgrade log4j2 to 2.16.0 due to CVE-2021-44228
TCOMP-2048: RowstructVisitor should respect case in member not java convention
TCOMP-2047: RecordBuilder in RowstructVisitor keeps values
TCOMP-2046: Rowstruct visitor recreates schema at each incoming row
TCOMP-1963: Missing IMetaDataColumn fields in guess schema
TCOMP-1987: Avro record : Array of Array of records issue
TCOMP-1988: Unable to run component-runtime connectors in Studio with JDK 17
TCOMP-2005: Non defined columns appear in schema
TCOMP-2006: Support empty values for Numbers case
TCOMP-2010: Error on Documentation build on "less" usage
TCOMP-2020: talend-component-kit-intellij-plugin module build fails using Bintray (decomissioned)
TCOMP-1900: Create jenkins release process for component-runtime
TCOMP-1997: Enable plugins reloading according criteria
TCOMP-2000: Upgrade netty to 4.1.68.Final
TCOMP-2001: Upgrade Beam to 2.32.0
TCOMP-2007: connectors as a json object in Environment
TCOMP-2009: Upgrade dockerfile-maven-plugin to 1.4.13
TCOMP-2016: UiSchema can’t hold advanced titleMap for more advanded datalist widgets
TCOMP-2007: connectors as a json object in Environment
TCOMP-1957: Avro schema builder issue
TCOMP-1994: WebSocketClient$ClientException when executing action in Studio
TCOMP-1923: Record : add metadata
TCOMP-1990: Update jsoup to 1.14.2 due to CVE-2021-37714
TCOMP-1991: Update groovy to 3.0.9 due to CVE-2021-36373 / CVE-2021-36374
TCOMP-1992: Update lombok to 1.18.20
TCOMP-1993: Update TSBI to 2.9.0-20210907155713
TCOMP-1995: Expose the connectors (global) version in the "Environment" response
TCOMP-1996: BaseService must not define equals & hashcode
TCOMP-1994: WebSocketClient$ClientException when executing action in Studio
TCOMP-1904: Delegate Avro record in AvroRecord seems to be invalid
TCOMP-1967: goal uispec generation failure
TCOMP-1983: fix module inclusion in dependencies.txt when build is java9+
TCOMP-1981: Allow to filter artifacts in car file generation
TCOMP-1982: Allow to include extra artifacts in car file generation
TCOMP-1876: Make schemaImpl immutable
TCOMP-1885: Service Serializable
TCOMP-1906: Redefine equals on RecordImpl
TCOMP-1955: Upgrade cxf to 3.4.4 due to CVE-2021-30468
TCOMP-1966: Upgrade Tomcat to 9.0.50 due to CVE-2021-33037
TCOMP-1968: Upgrade maven to 3.8.1
TCOMP-1969: Upgrade Beam to 2.31.0
TCOMP-1970: Upgrade jackson to 2.12.1
TCOMP-1971: Upgrade Junit to 5.8.0-M1
TCOMP-1972: Upgrade slf4j to 1.7.32
TCOMP-1973: Upgrade log4j to 2.14.1
TCOMP-1974: Upgrade commons-compress to 1.21 due to CVE-2021-36090
TCOMP-1975: Upgrade TSBI to 2.8.2-20210722144648
TCOMP-1976: Upgrade meecrowave to 1.2.11
TCOMP-1977: Upgrade OpenWebBeans to 2.0.23
TCOMP-1978: Upgrade tomcat to 9.0.44
TCOMP-1979: Upgrade xbean to 4.20
TCOMP-1980: Upgrade meecrowave to 1.2.12
TCOMP-1967: goal uispec generation failure
TCOMP-1935: After Variables doesn’t support custom object types
TCOMP-1941: Maven goal talend-component:web fails on startup
TCOMP-1947: Implement a retry strategy on failure in vault-client
TCOMP-1948: Raised exception in component-server(s) should be serialized in json
TCOMP-1952: IllegalArgumentException when the http response return duplicated header.
TCOMP-1939: Upgrade TSBI to Talend 2.7.2-20210616074048
TCOMP-1940: Upgrade Beam to 2.30.0
TCOMP-1941: Maven goal talend-component:web fails on startup
TCOMP-1939: Upgrade TSBI to Talend 2.7.2-20210616074048
TCOMP-1919: Sanitize must force encoding file
TCOMP-1925: Incorrect mapping of the parameters after arrays
TCOMP-1937: Classpath not fully parsed in TSBI images
TCOMP-1917: Add DatasetDiscovery annotation
TCOMP-1707: Upgrade Geronimo :: Simple JCache to 1.0.5
TCOMP-1850: component-server with vault feature
TCOMP-1907: Service monitor implementation & cleaning of grafana dashboard
TCOMP-1921: Upgrade TSBI to 2.7.0-20210527090437
TCOMP-1930: Remove jsoup 1.7.x transitive dependency due to CVE-2015-6748
TCOMP-1936: Extend properties in Schema to use JsonValue
TCOMP-1938: Add the german locale in the locale mapping
TCOMP-1938: Add the german locale in the locale mapping
TCOMP-1937: Classpath not fully parsed in TSBI images
TCOMP-1919: Sanitize must force encoding file
TCOMP-1886: Errors on Schema.sanitizeConnectionName
TCOMP-1905: component-runtime fails to build with Java 11
TCOMP-1893: Upgrade to Beam 2.29.0 and use Beam’s Spark 3 specific module
TCOMP-705: Support After variables
TCOMP-1898: Add method to Record.Builder
TCOMP-1910: Upgrade commons-io to 2.8.0 due to CVE-2021-29425
TCOMP-1911: Upgrade cxf to 3.4.3 due to CVE-2021-22696
TCOMP-1912: Upgrade TSBI to 2.6.7-20210503202416
TCOMP-1938: Add the german locale in the locale mapping
TCOMP-1937: Classpath not fully parsed in TSBI images
TCOMP-1880: Engine Server returns binary data instead of json (aka does not respect the compressed header)
TCOMP-1886: Errors on Schema.sanitizeConnectionName
TCOMP-1815: Support of ComponentException in migration
TCOMP-1873: Add method getEntry on TCK Record Schema class
TCOMP-1892: Upgrade Spark to 3.0.1
TCOMP-1888: Remove/change validation of ComponentException
TCOMP-1894: Uniformize docker images entrypoints
TCOMP-1895: Enhance coercion in RecordConverters
TCOMP-1896: Upgrade TSBI to 2.6.4-20210331133410
TCOMP-1806: Double values are rounded to 5 decimal places in studio
TCOMP-1851: HttpClient implementation class is a Service with State
TCOMP-1864: JsonSchemaConverter and johnzon-jsonschema 1.2.9+ look incompatible
TCOMP-1866: Invalid number coercion on primitive type
TCOMP-1869: byte[] handling is incorrect in dynamic column
TCOMP-1871: Dynamic metadata name is not sanitized
TCOMP-1861: Add a 'props' property in the Schema
TCOMP-1863: Upgrade batik-codec to 1.14 due to CVE-2020-11988
TCOMP-1865: Upgrade cxf to 3.4.2
TCOMP-1867: Upgrade Apache Beam to 2.28.0
TCOMP-1878: Upgrade TSBI to 2.6.3-20210304090015
TCOMP-1688: Rewrite JsonSchema required rules to reflect component’s validation rules
TCOMP-1857: Pojo conversion don’t support nested Objects
TCOMP-1841: Add a SPI that would allow to add metadata to components
TCOMP-1847: Upgrade Apache Beam to 2.27.0
TCOMP-1848: Upgrade bouncycastle to 1.68 due to CVE 2020-28052
TCOMP-1849: Proxify metrics component-server’s endpoint
TCOMP-1852: Upgrade netty to v4.1.58.Final and ensure default http testing module is java 11 friendly over ssl
TCOMP-1854: Upgrade netty to 4.1.59.Final due to CVE-2021-21290
TCOMP-1855: Upgrade johnzon to 1.2.10
TCOMP-1856: Upgrade tomcat to 9.0.43
TCOMP-1841: Add a SPI that would allow to add metadata to components
TCOMP-1852: Upgrade netty to v4.1.58.Final and ensure default http testing module is java 11 friendly over ssl
TCOMP-1854: Upgrade netty to 4.1.59.Final due to CVE-2021-21290
TCOMP-1848: Upgrade bouncycastle to 1.68 due to CVE 2020-28052
TCOMP-1839: Tomcat websocket server fails to start after tomcat 9.0.40 and meecrowave 1.2.10
TCOMP-1836: Upgrade OpenWebBeans to 2.0.20
TCOMP-1837: Upgrade xbean to 4.18
TCOMP-1838: Upgrade cxf to 3.4.1
TCOMP-1840: Upgrade tomcat to 9.0.41
TCOMP-1842: Upgrade jgit to 5.10.0.202012080955-r
TCOMP-1844: Upgrade johnzon to 1.2.9
TCOMP-1845: Upgrade guava to 30.1-jre due to CVE-2020-8908
TCOMP-1848: Upgrade bouncycastle to 1.68 due to CVE 2020-28052
TCOMP-1839: Tomcat websocket server fails to start after tomcat 9.0.40 and meecrowave 1.2.10
TCOMP-1836: Upgrade OpenWebBeans to 2.0.20
TCOMP-1837: Upgrade xbean to 4.18
TCOMP-1827: Upgrade lombok to 1.18.16
TCOMP-1828: Change project’s versioning scheme
TCOMP-1829: Upgrade TSBI to 2.5.3-20201201131449
TCOMP-1830: Upgrade Apache Beam to 2.26.0
TCOMP-1832: Upgrade httpclient to 4.5.13 due to CVE-2020-13956
TCOMP-1833: Upgrade spark to 2.4.7
TCOMP-1834: Upgrade groovy to 3.0.7 due to CVE-2020-17521
TCOMP-1787: ComponentManager can’t be re-created after it’s been closed
TCOMP-1788: Invalid properties validation
TCOMP-1801: Can’t look for resources in the classpath on Windows
TCOMP-1761: Support of complete schema definition
TCOMP-1725: Upgrade Tomcat to 9.0.40
TCOMP-1792: Uniform error message on component validation
TCOMP-1808: Upgrade log4j2 to 2.14.0
TCOMP-1809: Update CXF to 3.3.8 due to CVE-2020-13954
TCOMP-1812: Upgrade junit to 4.13.1 due to CVE-2020-15250
TCOMP-1813: Upgrade jupiter to 5.7.0
TCOMP-1816: Apache Maven Shared Utils: OS Command Injection in Talend/component-runtime (master) and Talend/cloud-components
TCOMP-1817: Upgrade gmavenplus-plugin to 1.11.0
TCOMP-1722: REST - Last / in endpoint is removed
TCOMP-1757: Studio - context not set when call a @suggestable service
TCOMP-1772: Code widget doesn’t allow multiline text
TCOMP-1726: Update logos and colors
TCOMP-1771: Record builder optimization (with static schema)
TCOMP-1773: Upgrade log4j2 to 2.13.3
TCOMP-1774: Upgrade johnzon to 1.2.8
TCOMP-1775: Upgrade commons-lang3 to 3.11
TCOMP-1776: Upgrade commons-codec to 1.15
TCOMP-1777: Upgrade jgit to 5.9.0.202009080501-r
TCOMP-1778: Upgrade jib-core to 0.15.0
TCOMP-1779: Upgrade batik to 1.13
TCOMP-1780: Upgrade TSBI to 2.4.0-20200925092052
TCOMP-1781: Upgrade asciidoctorj to 2.4.1
TCOMP-1782: Upgrade rrd4j to 3.7
TCOMP-1783: Upgrade netty to 5.0.0.Alpha2
TCOMP-1784: Upgrade ziplock to 8.0.4
TCOMP-1785: Upgrade JRuby to 9.2.13.0
TCOMP-1786: Upgrade to Apache Beam 2.24.0
TCOMP-1804: Upgrade to Apache Beam 2.25.0
TCOMP-1805: Upgrade TSBI to 2.5.0-20201030171201
TCOMP-1770: Performance loss on Ouput components in Studio
TCOMP-1750: Deadlock at TPD job startup using the Component SDK and using the Workday component
TCOMP-1759: Guess schema mixes columns returned by tck service
TCOMP-1752: Make component-runtime class loader find classes in RemoteEngine JobServer
TCOMP-1764: Upgrade to Apache Beam 2.23.0
TCOMP-1719: Header responses for icon not propagated correctly from Component-server-vault-proxy
TCOMP-1733: NPE in Studio metadata connection with activeif on different layouts
TCOMP-1734: Studio froze when installing a patch with azure-dls-gen2-1.10.0-component.car
TCOMP-1736: JobImpl retrieves more than streaming.maxRecords parameter
TCOMP-1739: Use scala version defined on parent for Spark related components
TCOMP-1695: Support List type in Studio
TCOMP-1737: Allow to force installation of an already existing component with the car bundle
TCOMP-1728: Enforce use of the defined error contract in connectors
TCOMP-1731: Make connectors docker image TSBI compliant
TCOMP-1738: Upgrade to Apache Beam 2.22.0
TCOMP-1742: Upgrade johnzon to 1.2.7
TCOMP-1727: WebSocketContainer not present in ServletContext
TCOMP-1696: Definition of an error contract to handle expected errors
TCOMP-1729: Upgrade to Apache Beam 2.21.0
TCOMP-1730: Upgrade johnzon to 1.2.6
TCOMP-1719: Header responses for icon not propagated correctly from Component-server-vault-proxy
TCOMP-1649: Tomcat bump to 9.0.31 broke talend-component:web goal
TCOMP-1676: Starter-toolkit mvn package throws error when running for the first time
TCOMP-1677: Using other types than String in Studio’s context values causes compilation error
TCOMP-1679: Combination of @Required and @Suggestable on a field creates strange behaviour
TCOMP-1682: Remove key attribute in UISchema for containers
TCOMP-1686: antora helper function relativize corrupts documentation
TCOMP-1694: [MAVEN PLUGIN] validateSvg argument is ineffective
TCOMP-1698: UiSpecService injects a wrong property for suggestions and dynamic_values
TCOMP-1718: Duplicated code in RecordConverters
TCOMP-1702: Improve columns name
TCOMP-1655: Upgrade jib-core to 0.13.1
TCOMP-1656: Upgrade log4j2 to 2.13.1
TCOMP-1657: Upgrade maven to 3.6.3
TCOMP-1658: Upgrade groovy to 3.0.2
TCOMP-1659: Upgrade lombok to 1.18.12
TCOMP-1660: Upgrade commons-compress to 1.20
TCOMP-1661: Upgrade commons-codec to 1.14
TCOMP-1662: Upgrade guava to 28.2-jre
TCOMP-1663: Upgrade ziplock to 8.0.1
TCOMP-1664: Upgrade asciidoctorj to 2.2.0 and its dependencies
TCOMP-1665: Upgrade jackson to 2.10.3
TCOMP-1666: Upgrade batik-codec to 1.12
TCOMP-1667: Upgrade jgit to 5.6.1.202002131546-r
TCOMP-1668: Upgrade junit to 4.13
TCOMP-1669: Upgrade bouncycastle to 1.64
TCOMP-1670: Upgrade spark-core_2.11 to 2.4.5
TCOMP-1671: Upgrade maven-shade-plugin to 3.2.2
TCOMP-1672: Upgrade httpclient to 4.5.12
TCOMP-1673: Upgrade component-runtime-testing dependencies
TCOMP-1674: Upgrade tomitribe-crest to 0.14
TCOMP-1678: Upgrade jgit to 5.7.0.202003090808-r
TCOMP-1685: Provide docker images based on TSBI
TCOMP-1687: More explicit exception messsage on reflection for findField
TCOMP-1690: Upgrade netty to 4.1.48.Final
TCOMP-1692: Update CXF to 3.3.6 due to CVE-2020-1954
TCOMP-1697: Update BouncyCastle to 1.65
TCOMP-1703: Upgrade log4j-2 to 2.13.2
TCOMP-1705: Upgrade to Apache Beam 2.20.0
TCOMP-1706: Upgrade OpenWebBeans to 2.0.16
TCOMP-1708: Upgrade groovy to 3.0.3
TCOMP-1710: Upgrade johnzon to 1.2.5
TCOMP-1711: Upgrade guava to 29.0-jre
TCOMP-1712: Upgrade commons-lang3 to 3.10
TCOMP-1713: Upgrade jackson to 2.11.0
TCOMP-1714: Upgrade junit to 5.7.0-M1
TCOMP-1716: Upgrade maven shade plugin to 3.2.3 and misc libs
TCOMP-1639: component-server incorrect response set in request
TCOMP-1640: Ensure Intellij plugin works with Intellij Idea IU-201
TCOMP-1641: Upgrade OpenWebBeans to 2.0.15
TCOMP-1642: Upgrade Groovy to 3.0.1
TCOMP-1643: Add automatic scheduling eviction system on LocalCache
TCOMP-1644: Upgrade log4j to 2.13.0
TCOMP-1645: Ensure correct wording is used in @Documentation
TCOMP-1647: Upgrade netty to 4.1.45.Final
TCOMP-1648: Unsafe Dependancy Resolution on jcommander
TCOMP-1638: Inject services to delegate in proxy
TCOMP-1619: Handle correctly DATETIME field type on AvroRecord
TCOMP-1622: [DOC] @Icon is not supported on datastore/dataset
TCOMP-1623: Change scheme for maven repos
TCOMP-1628: Manage BigDecimal in RecordConverter
TCOMP-1629: Ensure LocalConfiguration environment source replace dot with _
TCOMP-1630: Avoid NPE when configurationByExample() is called in a list of primitive without values
TCOMP-1631: int attribute in pojo is transformed to double in a Record
TCOMP-1632: Add a way to evict cached data from LocalCache
TCOMP-1616: Upgrade OpenWebBeans to 2.0.14 in component-server and component-server-vault-proxy
TCOMP-1617: Move mocked api results to github pages
TCOMP-1618: Upgrade Junit to 5.6.0
TCOMP-1620: Upgrade to Apache Beam 2.18.0
TCOMP-1621: Upgrade to Johnzon 1.2.3
TCOMP-1624: @Service does not support list injections
TCOMP-1625: Upgrade to xbean 4.16
TCOMP-1626: Ensure ContainerListenerExtensions can be sorted
TCOMP-1627: Upgrade to Apache Beam 2.19.0
TCOMP-1633: Upgrade Groovy to 3.0.0
TCOMP-1634: Upgrade tomcat to 9.0.31
TCOMP-1596: Windows URI are broken
TCOMP-1597: Httpclient does not support multi query parameters
TCOMP-1598: validator task uses ENGLISH locale to validate instead of root one
TCOMP-1612: Starter toolkit shouldn’t use the default 'STAR' icon in demo component
TCOMP-1585: Upgrade netty to 4.1.43.Final
TCOMP-1586: Upgrade ziplock to v8.0.0
TCOMP-1587: Upgrade jib to v0.12.0
TCOMP-1588: Upgrade JRuby to v9.2.9.0
TCOMP-1589: Upgrade crest to v0.11.0
TCOMP-1591: Update to Tomcat 9.0.29
TCOMP-1592: Update to Johnzon 1.2.2
TCOMP-1593: Update to OpenWebBeans 2.0.13
TCOMP-1595: Infinite partitionmapper shouldn’t require assesor
TCOMP-1599: More unsafe usage tolerance on JVM versions
TCOMP-1600: Upgrade to Tomcat 9.0.30
TCOMP-1606: Ensure job dsl can stop infinite inputs
TCOMP-1608: Upgrade geronimo openapi to 1.0.12
TCOMP-1609: Ensure Intellij plugin works with Intellij Idea 2019
TCOMP-1611: Upgrade to Apache Beam 2.17.0
TCOMP-1613: Upgrade cxf to 3.3.5
TCOMP-1614: Upgrade groovy to 3.0.0-rc3
TCOMP-1615: Upgrade OpenWebBeans to 2.0.14
TCOMP-1752: Make component-runtime class loader find classes in RemoteEngine JobServer
TCOMP-1560: Min and Max error message during configuration validation are reversed
TCOMP-1563: Web Tester does not work anymore (maven/gradle goal/task)
TCOMP-1573: Body encoder is called twice for each query
TCOMP-1582: Deploy to Nexus 3.15 caused "Provided url doesn’t respond neither to Nexus 2 nor to Nexus 3 endpoints"
TCOMP-1576: Add the possibility to desactivate http client redirection in HTTP Configurer
TCOMP-1559: Support configuration of the maxBatchSize enablement
TCOMP-1561: Custom action type shouldn’t need to be enforced to define a family method
TCOMP-1562: Support JsonObject type in actions
TCOMP-1564: Move to java.nio.Path instead of java.io.File in component-runtime-manager stack where possible
TCOMP-1565: Upgade to Junit Jupiter 5.6.0-M1
TCOMP-1566: Don’t compute jvmMarkers per component module but once for all
TCOMP-1567: Cache Artifact path in case of reuse
TCOMP-1568: Lazily create the container services
TCOMP-1569: Upgrade starter to gradle 6.0-rc1
TCOMP-1570: Ensure starter adds _placeholder entries in Messages.properties
TCOMP-1571: Support [length] syntax to change array configuration
TCOMP-1572: Validate that @Option is not used on final fields
TCOMP-1574: Upgrade to CXF 3.3.4
TCOMP-1575: Upgrade to Spark 2.4.4
TCOMP-1577: Upgrade to xbean 4.15
TCOMP-1578: Upgrade asciidoctor-pdf to v1.5.0-beta.7
TCOMP-1581: Support JUnit5 meta annotations for our extensions
TCOMP-1702: Improve columns name
TCOMP-1685: Provide docker images based on TSBI
TCOMP-1558: org.talend.sdk.component.api.service.record.RecordService must be serializable
TCOMP-1548: Basic Remote Engine Customizer
TCOMP-1550: Component configuration instantiation can be slow for complex configurations
TCOMP-1551: ObjectFactory should default to fieldproperties when field injection is activated
TCOMP-1553: Simplify and widden excluded classes for with transformer support
TCOMP-1555: Upgrade to Tomcat 9.0.27
TCOMP-1556: Studio short, byte, BigDecimal and char types are wrong handled
TCOMP-1557: Upgrade to Beam 2.16.0
TCOMP-1509: Intellij plugin does not declare java module preventing the plugin to run under last versions
TCOMP-1526: Upgrade talend UI bundle (js) to 4.6.0
TCOMP-1533: JSON-B API does not enable to combine multiple adapters or (de)serializers in JsonbConfig
TCOMP-1536: @DefaultValue ignored in documentation generation
TCOMP-1541: Studio integration enforces JSON<→Record conversion instead of relying on rowStruct making number precision lost
TCOMP-1542: Validator plugin uses family instead of pluginId (artifactId) to validate local-configuration
TCOMP-1508: Don’t let Talend Starter Toolkit loose state on Enter in intellij
TCOMP-1543: Add a uispec mapper
TCOMP-1544: Update Geronimo JSON-P spec bundle to v1.3
TCOMP-1545: Update OpenWebBeans to version 2.0.12
TCOMP-1546: Update Meecrowave to 1.2.9
TCOMP-1547: Update Johnzon to 1.2.1
TCOMP-1279: Rewrite the pojo <→ record mapping to keep number types
TCOMP-1504: Apache Beam 2.14.0 upgrade
TCOMP-1505: Upgrade jackson-databind to 2.9.9.3
TCOMP-1506: Enable actions in bulk endpoint
TCOMP-1507: Upgrade to johnzon 1.1.13
TCOMP-1511: Upgrade cxf to v3.3.3
TCOMP-1513: Upgrade to Tomcat 9.0.24
TCOMP-1514: Provide a RecordService to simplify record enrichment coding in processors
TCOMP-1515: Record visitor API
TCOMP-1517: Use netty 4.1.39.Final in junit http tools
TCOMP-1518: Upgrade to slf4j 1.7.28
TCOMP-1519: Upgrade to jib-core 0.10.1
TCOMP-1520: Don’t use JsonNode with Avro Fields anymore
TCOMP-1521: Upgrade to Beam 2.15.0
TCOMP-1522: Basic singer/tap/stitch integration with kit components
TCOMP-1523: Upgrade Apache Geronimo OpenAPI to v1.0.11
TCOMP-1524: Upgrade starter to gradle 5.6
TCOMP-1525: Upgrade commons-compress to v1.19
TCOMP-1527: Remove beam Mapper/Processor wrapping support
TCOMP-1528: Upgrade to maven 3.6.2
TCOMP-1529: Asciidoctor 2.1.0 upgrade
TCOMP-1530: geronimo-annotation 1.2 upgrade
TCOMP-1532: Upgrade to Junit 5.5.2
TCOMP-1535: Upgrade to johnzon 1.2.0
TCOMP-1537: Upgrade to Tomcat 9.0.26
TCOMP-1538: Upgrade to jackson 2.9.10
TCOMP-1539: Rework default direct runner/spark classloader rules
TCOMP-1540: Ensure Asciidoctor documentation rendering releases properly JRuby threads (main usage only)
TCOMP-1478: /documentation/component/{id} internationalization does not work when embedded
TCOMP-1479: When generating the documentation, it can happen the lang is wrong due to ResourceBundle usage
TCOMP-1480: Servers docker images don’t have curl or wget available
TCOMP-1497: POJO to Record mapping is not supported in processors
TCOMP-1498: SVG2Mojo wrongly log the source file as being created
TCOMP-1499: component-form does not support array of object of object if 2 levels use the same field name
TCOMP-1500: Ensure component-form button have a key to have an id and propagate errors in the front
TCOMP-1503: EnvironmentSecuredFilter not working on /environment/
TCOMP-1482: Enable web tester to switch the language
TCOMP-1483: Enable to expose the documentation through the web tester
TCOMP-1485: Asciidoctor documentation does not enable titles (component name and configuration ones) to be translated
TCOMP-1486: Ensure locale mapping is configurable in component-server
TCOMP-1484: Junit 5.5.0 upgrade
TCOMP-1487: AsciidocMojo should only use ROOT locale by default
TCOMP-1488: Enable to translate gridlayout names
TCOMP-1489: Upgrade Tomcat to v9.0.22
TCOMP-1491: Upgrade JIB to v1.4.0
TCOMP-1492: Upgrade jackson-databind to 2.9.9.1
TCOMP-1493: Rewrite component exception to ensure they can be loaded after a serialization
TCOMP-1494: Upgrade to junit jupiter 5.5.1
TCOMP-1495: Upgrade to Geronimo OpenAPI 1.0.10
TCOMP-1496: [testing tool] MainInputFactory does not support Record
TCOMP-1501: Remove generate mojo
TCOMP-1502: [maven plugin] upgrade jib-core to 0.10.0
TCOMP-1469: Studio maven repository not found OOTB
TCOMP-1472: Connectors maven goal does not work in 1.1.10
TCOMP-1473: Docker image text log setup should use ISO8601 and not HH:mm:ss.SSS
TCOMP-1470: Upgrade Tomcat to v9.0.21
TCOMP-1471: Upgrade Geronimo OpenAPI to v1.0.9
TCOMP-1474: Ensure proxies definition are java >=11 friendly
TCOMP-1425: Spark classes not excluded anymore in component-runtime-beam leading to classloading issues
TCOMP-1427: dependencies.txt mojo uses timestamped versions for snapshots instead of just -SNAPSHOT
TCOMP-1431: [maven] Asciidoctor files should be attached with adoc extension and not jar one
TCOMP-1433: [form-model] itemwidget ignored from uischema builder
TCOMP-1438: Index cache can lead to invalid index list of component
TCOMP-1440: Bulk components without @ElementListener when used with component-extension (default in the server)
TCOMP-1441: Missing parameter init in the UiSchema Trigger builder
TCOMP-1446: Rework gradle lifecycle
TCOMP-1419: Upgrade build to groovy 2.5.7
TCOMP-1420: Upgrade maven compiler to 3.1.2
TCOMP-1422: Filter allowed beam classes in component-server image
TCOMP-1423: Enable to customize studio maven repository for deploy-studio maven and gradle goal/task
TCOMP-1426: Ensure Spark rule and @WithSpark uses a default version consistent with the runtime
TCOMP-1430: Deprecate built-in icons in favor of vendor specific icons
TCOMP-1432: basic dita generation for the component documentation
TCOMP-1434: [form-model] Add withCondition to UISchema builder
TCOMP-1435: Dont use beam_sdks_java_core shaded libraries
TCOMP-1437: Add infinite metadata to ComponentDetail
TCOMP-1444: Remove KnownJarsFilter since it is no more used to discover components
TCOMP-1445: Icon must support SVG
TCOMP-1448: [starter] provide a basic OpenAPI integration
TCOMP-1449: Upgrade XBean to v4.14
TCOMP-1450: Add a read-only bulk endpoint in component-server
TCOMP-1451: [upgrade] Johnzon 1.1.12
TCOMP-1452: [upgrade] Meecrowave 1.2.8
TCOMP-1453: Upgrade to CXF 3.3.2
TCOMP-1455: Prepare DateTime support in configurations
TCOMP-1457: Upgrade to Apache Beam 2.13.0
TCOMP-1458: Ensure _placeholder presence is encouraged and validated
TCOMP-1459: Experimental way to patch a component dependency
TCOMP-1461: Extension API for the validator plugin
TCOMP-1462: Validate through the corresponding build task provided SVG
TCOMP-1464: Upgrade to OpenWebBeans 2.0.11
TCOMP-1465: Upgrade to JUnit 5.5.0-RC1
TCOMP-1466: Upgrade to ziplock 8.0.0-M2
TCOMP-1467: Upgrade mock server (testing tool) to netty 5.0.0.Alpha2
TCOMP-1468: Support docker-compose >= 1.23 in vault-proxy
TCOMP-1374: ensure Utf8 avro strings don’t leak in AvroRecord API, even using get(Object.class, …)
TCOMP-1375: When two sources use the same dataset and one source has additional required parameter the validation fails
TCOMP-1384: Enhance studio guess schema algorithm to find implicitly the action to call if needed
TCOMP-1388: Can’t change the dataset name in starter
TCOMP-1389: Intellij starter fails to generate a project
TCOMP-1398: Using after option of @updateable can lead to a null pointer exception in component-form
TCOMP-1401: Documentation table is broken
TCOMP-1407: Databricks: interface javax.json.stream.JsonGeneratorFactory is not visible from class loader
TCOMP-1386: Add withRecord(String,Record) in Record.Builder
TCOMP-1387: Use icon bundle version 3.1.0
TCOMP-1412: Add rest and couchbase icon to component api
TCOMP-1376: Upgrade jupiter to 5.4.2
TCOMP-1385: talend.component.server.component.registry must be a list
TCOMP-1390: Move component-api to component-runtime repository
TCOMP-1392: Tomcat 9.0.19 upgrade
TCOMP-1402: Provide a placeholder for classpath extensions in docker images
TCOMP-1403: Upgrade asciidoctor to 2.0.0 and asciidoctor-pdf to alpha17
TCOMP-1404: Upgrade to Apache Beam 2.12.0
TCOMP-1408: Starter does not support types starting with a lowercase
TCOMP-1411: ComponentManager relies on beam jar name. This is unlikely and should move to beam integration module.
TCOMP-1417: Upgrade to Geronimo OpenAPI 1.0.8
TCOMP-1326: Avro Schema is not serializable as JSON so guess schema action does not work when compoennt-runtime-beam is present
TCOMP-1330: Shade extensions don’t inherit from pluginrepositories
TCOMP-1340: Tools webapp (talend-component:web) does not support changing the locale anymore
TCOMP-1343: Use LogicalTypes.timestampMillis() on DATETIME for avro record builder
TCOMP-1360: Renaming an option (@Option("custom")) does not work on fields of type object
TCOMP-1370: ImageM2Mojo does not set timestamp in the docker image leading to component-server having a wrong lastUpdated value
TCOMP-1372: Nested components don’t expose their doc deterministicly until it is overriden
TCOMP-1341: Register deploy in studio task OOTB in gradle extension
TCOMP-1325: Upgrade CXF to 3.3.1
TCOMP-1327: /environment iterates over deployed plugin for each call, this is not needed
TCOMP-1328: Upgrade to Beam 2.11.0
TCOMP-1329: Lazy initialize parameter model to have a quicker cold start in plain main(String[])
TCOMP-1331: Use java 8u191 as base docker image
TCOMP-1332: Provide a simple way to filter configurations and component on /index endpoints
TCOMP-1334: Add a mojo to generate the list of components/services classes
TCOMP-1335: Add in doc mojo table the type of configuration the parameter belongs to
TCOMP-1336: Allow output processors to only have an @AfterGroup taking the list of record of the group in parameter
TCOMP-1346: Upgrade to Tomcat 9.0.17
TCOMP-1347: Upgrade to Slf4j 1.7.26
TCOMP-1348: [form-core] Ensure suggestions trigger is bound to "change" event too
TCOMP-1349: [form-core] When a tab is empty, don’t show it
TCOMP-1350: talend.component.server.component.registry should support glob pattern
TCOMP-1351: Upgrade jsoup for Spark Cluster testing module
TCOMP-1353: component-server must not use TALEND-INF/dependencies.txt but another path
TCOMP-1354: Enforce services to belong to the delcaring service class
TCOMP-1361: Upgrade to asciidoctorj 2.0.0-RC.1
TCOMP-1362: Beam Wrapped Components should throw shared exception types
TCOMP-1366: Upgrade to XBean 4.13 to not track all classes scanned
TCOMP-1371: Upgrade to Apache Geronimo OpenAPI 1.0.7
TCOMP-1307: support char and character types in configuration.
TCOMP-1312: Component-form-core shouldn’t trigger validation of object due to conditional visibility (only individual fields are validable)
TCOMP-1314: category field of the starter is broken
TCOMP-1316: [build] Ensure snapshot use timestamped versions in dependencies.txt
TCOMP-1306: Add RecordPointerFactory to enable to extract data from Record using json pointer spec
TCOMP-1315: Ensure @Internationalized can use shortnames too in Messages.properties
TCOMP-1303: Support docker configs/secrets in docker images
TCOMP-1304: Vault proxy should support token configuration
TCOMP-1305: Upgrade to beam 2.10.0
TCOMP-1308: Upgrade to Talend UI 2.6.0
TCOMP-1309: Upgrade to Component API 1.1.5
TCOMP-1310: Ensure there is a basic secured mecanism to store configuration data
TCOMP-1317: Use Apache Geronimo Microprofile Config extensions (docker and secured string)
TCOMP-1318: Upgrade to Apache Meecrowave 1.2.7
TCOMP-1319: Upgrade Apache Geronimo Metrics to 1.0.3
TCOMP-1320: Upgrade to Apache Geronimo OpenAPI 1.0.6
TCOMP-1321: Upgrade to Apache Geronimo OpenTracing 1.0.2
TCOMP-1322: Upgrade to Apache Geronimo Config 1.2.2
TCOMP-1263: When using @Updateable(after=xxx) the visibility condition (@ActiveIf) of the after field shouldn’t be inherited
TCOMP-1264: AvroSchema does not unwrap null(able types) to map to Schema model
TCOMP-1265: dataset / datastore cloud validation : allow nested configuration types
TCOMP-1267: /documentation does not filter properly component
TCOMP-1281: Add jackson-mapper-asl in docker image of the server
TCOMP-1298: Support restricted lists for @Proposable
TCOMP-1297: make max batch size property configurable for family and components through LocalConfiguration
TCOMP-1266: Enhance starter to support dataset and datastore
TCOMP-1268: Ensure /environment is not callable if not local or secured
TCOMP-1269: Ensure ErrorReportValve does not leak Tomcat version OOTB
TCOMP-1271: Upgrade to talend UI 2.3.0
TCOMP-1272: Move multiSelectTag to multiSelect for web environment
TCOMP-1273: [build/dev plugin] Automatically open the browser for talend-component:web task/goal
TCOMP-1276: Exclude xerces from component loadable resources for XMLReaderFactory
TCOMP-1282: Upgrade meecrowave to 1.2.6
TCOMP-1283: Upgrade cxf to 3.3.0
TCOMP-1284: Upgrade to johnzon 1.1.11
TCOMP-1292: Provide a vault friendly integration for the server
TCOMP-1293: Upgrade to Tomcat 9.0.16
TCOMP-1295: Ensure local-configuration.properties of a container are merged
TCOMP-1296: Ensure user can enrich families with custom jar+configuration
TCOMP-1245: Provided services (SPI) by tacokit not available
TCOMP-1246: Rework docker image setup to use jib
TCOMP-1247: Upgrade geronimo metrics to 1.0.2
TCOMP-1248: Upgrade to geronimo opentracing 1.0.3
TCOMP-1249: Provide segment extractor for doc endpoint
TCOMP-1250: Make component documentation (@Documentation on component) i18n friendly
TCOMP-1251: cache avrocoders used in SchemaRegistryCoder
TCOMP-1252: Remove html support in documentation endpoint
TCOMP-1253: Refine OpenAPI documentation
TCOMP-1256: Add mapDescriptorToClassLoader to create a classloader from a list of gav
TCOMP-1258: Support to build a Record from a provided Schema
TCOMP-1259: Add getOptional to Record
TCOMP-1223: byte[] not supported in AvroRecord (beam)
TCOMP-1222: Ensure @WithComponents and @Environment are compatible
TCOMP-1234: Upgrade to beam 2.9.0
TCOMP-1235: Upgrade to antora 2
TCOMP-1237: Upgrade component-api to 1.1.2
TCOMP-1238: Upgrade metrics and opentracing microprofile libraries in docker image to use Geronimo extensions
TCOMP-1239: OpenWebBeans 2.0.9 upgrade
TCOMP-1240: Johnzon 1.1.11 upgrade
TCOMP-1242: Runtime validation error message wrongly interpolated
TCOMP-1243: Ensure component classloader isolates the system classloader resources except for the JVM ones
TCOMP-1170: [regression] http testing module pom imports netty and jsonb stack
TCOMP-1181: tacokit can’t pass the long type field from ui rightly
TCOMP-1187: Job DSL does not support correctly parameters when they are URI/URL
TCOMP-1189: Ensure primitive are not nullable in Record model (builder)
TCOMP-1191: [beam] BeamIOTransformer does not support serialization of complex objects correctly
TCOMP-1192: Ensure Avro schema union is interpreted as nullable in Record Schema model
TCOMP-1194: [testing] Ensure BeamEnvironment adds component-runtime-beam
TCOMP-1196: Nested maven repository not used for component module
TCOMP-1197: Tacokit beam tests. NPE when creating the schema with RECORD type.
TCOMP-1198: Tacokit beam tests. SchemaParseException ⇒ drop unsupported characters
TCOMP-1200: Packages not defined from nested repository classes
TCOMP-1201: includeTransitiveDependencies option of nested-maven-repository does not work
TCOMP-1202: Refine avro classloading exclusion to accept hadoop and mapred packages
TCOMP-1205: Empty JSon object lead to NPE
TCOMP-1209: Ensure SerializableCoder is replaced with a contextual version to support Talend Component Kit classloading model
TCOMP-1210: BeamComponentExtension should let the exception go back to the caller when the transform fails
TCOMP-1215: Nested maven repository in jars don’t go through transformers
TCOMP-1218: Record entries order shouldn’t be sorted by the runtime
TCOMP-1185: Support maxBatchSize in Job test runner for standalone mode
TCOMP-1171: Remove component proxy server from the project
TCOMP-1182: Ensure the property editor for the configuration registers the default converters
TCOMP-1183: Upgrade JRuby to 9.2.4.0
TCOMP-1184: Avoid to do a group by key in BeamExecutor (job DSL) when not needed
TCOMP-1188: Tolerate null for dates in Records
TCOMP-1190: Enable secure processing for DocumentBuilderFactory instances
TCOMP-1193: Add injectable ContainerInfo with the containerId (plugin) in services
TCOMP-1195: Enable user to extend BeamEnvironment test tempalte more easily
TCOMP-1199: Nested repository not used when the classpath is not composed of a single jar
TCOMP-1204: [dependency upgrade] XBean 4.12
TCOMP-1207: [beam] add ContextualSerializableCoder
TCOMP-1213: Upgrade guava to v27 for testing modules
TCOMP-1216: Take into account the visibility for the parameter validation
TCOMP-1217: Add JVM system property talend.component.runtime.serialization.java.inputstream.whitelist for our custom object input stream
TCOMP-1219: Upgrade starter to gradle 5
TCOMP-1220: Upgrade Maven to 3.6.0 in starter
TCOMP-1121: [tacokit proxy] suggestion trigger creation issue
TCOMP-1122: [tacokit proxy] slefRefrence filter configuration type by name, type and family
TCOMP-1123: Processor component onNext duplicate columns in record for rowStructs
TCOMP-1126: UiSpecService shouldn’t show the documentation by default
TCOMP-1129: form core - $selfReference breaks triggers
TCOMP-1130: component form - default value of maxBatchSize prop loose it type.
TCOMP-1131: [beam integration] Ensure Coder is contextual (classloader)
TCOMP-1132: Ensure beam custom Coders implement equals.hashCode for beam contract
TCOMP-1148: Asciidoctor documentation fails for collection of objects
TCOMP-1149: [testing] BeamEnvironment does not reset PipelineOptionsFactory properly for beam > 2.4
TCOMP-1155: [proxy server] arrays not supporting null values in ConfigurationFormatter
TCOMP-1159: AvroSchema does not support DATETTIME type (beam module)
TCOMP-1168: Avro record implementation ignores nullable/union
TCOMP-1143: Ensure icons are validated and fail the build if a custom one is missing (validate mojo)
TCOMP-1112: Let beam PTransform define an @ElementListener method to set the component design (inputs/outputs)
TCOMP-1113: Simplify the scanning by assuming there is a TALEND-INF/dependencies.txt in components
TCOMP-1120: BeamMapperImpl.isStream not accurate for UnboundedSource
TCOMP-1124: Add /metrics endpoint
TCOMP-1125: Extend CustomPropertyConverter to pass the convertion context
TCOMP-1127: Record doesn’t support null values
TCOMP-1133: CXF 3.2.7 upgrade
TCOMP-1134: Ensure any input/output have a dataset
TCOMP-1135: Ensure any dataset has a datastore
TCOMP-1136: deprecate "generate" mojo
TCOMP-1145: [dependency upgrade] Beam 2.8.0
TCOMP-1146: implement infinite=true in PartitionMapper/Input
TCOMP-1150: Upgrade rat plugin to 0.13
TCOMP-1154: Required validation at runtime ignores lists and nested objects
TCOMP-1157: [dependency upgrade] Tomcat 9.0.13
TCOMP-1158: Enable JUnit test collector to use a static storage instead of thread related one
TCOMP-1160: Upgrade spark to 2.4.0
TCOMP-1161: Upgrade shade plugin to 3.2.1
TCOMP-1162: Upgrade nested-maven-repository shade transformers to support last maven versions
TCOMP-1163: Upgrade openwebbeans to 2.0.8
TCOMP-1164: Validate mojo does not log any success information
TCOMP-1165: Dependency mojo does not log any success information
TCOMP-1166: Documentation mojo does not log generated files properly
TCOMP-1167: Beam-Avro record name generation should use avro fingerprint to be more unique than current logic
TCOMP-1086: Fix documentation about DiscoverSchema
TCOMP-1064: Update action can’t receive List
The Remote Engine is a key piece for executing components with Talend Pipeline Designer. To customize it for testing purposes, a helper tool is available. The following content and the tool it describes are not officially supported as a Talend Cloud feature and are provided "as it" without any guarantee. The remote-engine-customizer is a simple tool that reads the Remote Engine docker-compose.yml file, extracts the connectors image and rebuilds it adding configured connectors to the image. By default, it replaces the original image with the newly built one and saves the old file in the .remote_engine_customizer/backup/ directory of the Remote Engine. The customizer is provided as a docker container. You can run the tool using the register-component-archive command: You can get more details about the tool with the following command: You can find out all the available versions at hub.docker.com/r/tacokit/remote-engine-customizer/tags. The command accepts the following parameters: When running using the docker container, you must mount several files/folders. For example: Once you have built the new image, you must restart the Remote Engine. You can verify that the new image is available by running docker run --entrypoint sh -it [newimage] before.
testing code that consumes REST APIs can sometimes present many constraints: API rate limit, authentication token and password sharing, API availability, sandbox expiration, API costs, and so on. As a developer, it becomes critical to avoid those constraints and to be able to easily mock the API response. The component framework provides an API simulation tool that makes it easy to write unit tests. This tutorial shows how to use this tool in unit tests. As a starting point, the tutorial uses the component that consumes Zendesk Search API and that was created in a previous tutorial. The goal is to add unit tests for it. For this tutorial, four tickets that have the open status have been added to the Zendesk test instance used in the tests. To learn more about the testing methodology used in this tutorial, refer to Component JUnit testing. Create a unit test that performs a real HTTP request to the Zendesk Search API instance. You can learn how to create a simple unit test in this tutorial. the authentication configuration using Zendesk instance URL and credentials. the search query configuration to get all the open ticket, ordered by creation date and sorted in descending order. The test is now complete and working. It performs a real HTTP request to the Zendesk instance. As an alternative, you can use mock results to avoid performing HTTP requests every time on the development environment. The real HTTP requests would, for example, only be performed on an integration environment. To transform the unit test into a mocked test that uses a mocked response of the Zendesk Search API: Add the two following JUnit rules provided by the component framework. JUnit4HttpApi: This rule starts a simulation server that acts as a proxy and catches all the HTTP requests performed in the tests. This simulation server has two modes : capture : This mode forwards the captured HTTP request to the real server and captures the response. simulation : this mode returns a mocked response from the responses already captured. This rule needs to be added as a class rule. JUnit4HttpApi: This rule has a reference to the first rule. Its role is to configure the simulation server for every unit test. It passes the context of the running test to the simulation server. This rule needs to be added as a simple (method) rule. Example to run in a simulation mode: Make the test run in capture mode to catch the real API responses that can be used later in the simulated mode. To do that, set a new talend.junit.http.capture environment variable to true. This tells the simulation server to run in a capture mode. The captured response is saved in the resources/talend.testing.http package in a JSON format, then reused to perform the API simulation.
JUnit (4 or 5) already provides ways to parameterize tests and execute the same "test logic" against several sets of data. However, it is not very convenient for testing multiple environments.
For example, with Beam, you can test your code against multiple runners. But it requires resolving conflicts between runner dependencies, setting the correct classloaders, and so on.
To simplify such cases, the framework provides you a multi-environment support for your tests, through the JUnit module, which works with both JUnit 4 and JUnit 5.
The MultiEnvironmentsRunner executes the tests for each defined environments. With the example above, it means that it runs test1 for Env1 and Env2.
By default, the JUnit4 runner is used to execute the tests in one environment, but you can use @DelegateRunWith to use another runner.
The multi-environment configuration with JUnit 5 is similar to JUnit 4:
The main differences are that no runner is used because they do not exist in JUnit 5, and that you need to replace @Test by @EnvironmentalTest.
With JUnit5, tests are executed one after another for all environments, while tests are ran sequentially in each environments with JUnit 4. For example, this means that @BeforeAll and @AfterAll are executed once for all runners.
The provided environment sets the contextual classloader in order to load the related runner of Apache Beam.
Package: org.talend.sdk.component.junit.environment.builtin.beam
the configuration is read from system properties, environment variables, ….
_class: ContextualEnvironment.
_class: DirectRunnerEnvironment.
_class: FlinkRunnerEnvironment.
_class: SparkRunnerEnvironment.
If the environment extends BaseEnvironmentProvider and therefore defines an environment name - which is the case of the default ones - you can use EnvironmentConfiguration to customize the system properties used for that environment:
If you set the
This tutorial walks you through the creation, from scratch, of a complete Talend input component for Hazelcast using the Talend Component Kit (TCK) framework.
Hazelcast is an in-memory distributed system that can store data, which makes it a good example of input component for distributed systems. This is enough for you to get started with this tutorial, but you can find more information about it here: hazelcast.org/.
A TCK project is a simple Java project with specific configurations and dependencies. You can choose your preferred build tool from Maven or Gradle as TCK supports both. In this tutorial, Maven is used.
The first step consists in generating the project structure using Talend Starter Toolkit .
Go to starter-toolkit.talend.io/ and fill in the project information as shown in the screenshots below, then click Finish and Download as ZIP.
image::tutorial_hazelcast_generateproject_1.png[] image::tutorial_hazelcast_generateproject_2.png[]
Extract the ZIP file into your workspace and import it to your preferred IDE. This tutorial uses Intellij IDE, but you can use Eclipse or any other IDE that you are comfortable with.
You can use the Starter Toolkit to define the full configuration of the component, but in this tutorial some parts are configured manually to explain key concepts of TCK.
The generated pom.xml file of the project looks as follows:
Change the name tag to a more relevant value, for example:
If you want to make sure that your component works in Beam and don’t want to use Spark, you can try with the Direct Runner. Check beam.apache.org/contribute/testing/ for more details.
This tutorial shows how to adapt the test configuration of the Zendesk search component that was done in this previous tutorial to make it work in a Continuous Integration environment.
In the test, the Zendesk credentials are used directly in the code to perform a first capture of the API response. Then, fake credentials are used in the simulation mode because the real API is not called anymore.
However, in some cases, you can require to continue calling the real API on a CI server or on a specific environment.
To do that, you can adapt the test to get the credentials depending on the execution mode (simulation/passthrough).
These instructions concern the CI server or on any environment that requires real credentials.
This tutorial uses:
A Maven server that supports password encryption as a credential provider. Encryption is optional but recommended.
The MavenDecrypterRule test rule provided by the framework. This rule lets you get credentials from Maven settings using a server ID.
To create encrypted server credentials for the Zendesk instance:
Create a master password using the command: mvn --encrypt-master-password
Some recommendations apply to the way component packages are organized: Make sure to create a package-info.java file with the component family/categories at the root of your component package: Create a package for the configuration. Create a package for the actions. Create a package for the component and one sub-package by type of component (input, output, processors, and so on). It is recommended to serialize your configuration in order to be able to pass it through other components. When building a new component, the first step is to identify the way it must be configured. The two main concepts are: The DataStore which is the way you can access the backend. The DataSet which is the way you interact with the backend. For example: Example description DataStore DataSet Accessing a relational database like MySQL JDBC driver, URL, username, password Query to execute, row mapper, and so on. Accessing a file system File pattern (or directory + file extension/prefix/…) File format, buffer size, and so on. It is common to have the dataset including the datastore, because both are required to work. However, it is recommended to replace this pattern by defining both dataset and datastore in a higher level configuration model. For example: Input and output components are particular because they can be linked to a set of actions. It is recommended to wire all the actions you can apply to ensure the consumers of your component can provide a rich experience to their users. The most common actions are the following ones: This action exposes a way to ensure the datastore/connection works. Configuration example: Action example: Until the studio integration is complete, it is recommended to limit processors to one input. Configuring processor components is simpler than configuring input and output components because it is specific for each component. For example, a mapper takes the mapping between the input and output models: It is recommended to provide as much information as possible to let the UI work with the data during its edition. Light validations are all the validations you can execute on the client side. They are listed in the UI hint section. Use light validations first before going with custom validations because they are more efficient. Custom validations enforce custom code to be executed, but are heavier to execute. Prefer using light validations when possible. Define an action with the parameters needed for the validation and link the option you want to validate to this action. For example, to validate a dataset for a JDBC driver: You can also define a Validable class and use it to validate a form by setting it on your whole configuration: The parameter binding of the validation method uses the same logic as the component configuration injection. Therefore, the @Option method specifies the prefix to use to reference a parameter. It is recommended to use @Option("value") until you know exactly why you don’t use it. This way, the consumer can match the configuration model and just prefix it with value. to send the instance to validate. Validations are triggers based on "events". If you mark part of a configuration as @Validable but this configuration is translated to a widget without any interaction, then no validation will happen. The rule of thumb is to mark only primitives and simple types (list of primitives) as @Validable. It can be handy and user-friendly to provide completion on some fields. For example, to define completion for available drivers: Each component must have its own icon: You can use talend.surge.sh/icons/ to find the icon you want to use. It is recommended to enforce the version of your component, event though it is not mandatory for the first version. If you break a configuration entry in a later version; make sure to: Upgrade the version. Support a migration of the configuration. testing your components is critical. You can use unit and simple standalone JUnit tests, but it is also highly recommended to have Beam tests in order to make sure that your component works in Big Data.
This tutorial is the continuation of Talend Input component for Hazelcast tutorial. We will not walk through the project creation again, So please start from there before taking this one. This tutorial shows how to create a complete working output component for Hazelcast As seen before, in Hazelcast there is multiple data source type. You can find queues, topics, cache, maps… In this tutorials we will stick with the Map dataset and all what we will see here is applicable to the other types. Let’s assume that our Hazelcast output component will be responsible of inserting data into a distributed Map. For that, we will need to know which attribute from the incoming data is to be used as a key in the map. The value will be the hole record encoded into a json format. Bu that in mind, we can design our output configuration as: the same Datastore and Dataset from the input component and an additional configuration that will define the key attribute. Let’s create our Output configuration class. Let’s add the i18n properties of our configuration into the Messages.properties file The skeleton of the output component looks as follows: @Version annotation indicates the version of the component. It is used to migrate the component configuration if needed. @Icon annotation indicates the icon of the component. Here, the icon is a custom icon that needs to be bundled in the component JAR under resources/icons. @Processor annotation indicates that this class is the processor (output) and defines the name of the component. constructor of the processor is responsible for injecting the component configuration and services. Configuration parameters are annotated with @Option. The other parameters are considered as services and are injected by the component framework. Services can be local (class annotated with @Service) or provided by the component framework. The method annotated with @PostConstruct is executed once by instance and can be used for initialization. The method annotated with @PreDestroy is used to clean resources at the end of the execution of the output. Data is passed to the method annotated with @ElementListener. That method is responsible for handling the data output. You can define all the related logic in this method. If you need to bulk write the updates accordingly to groups, see Processors and batch processing. Now, we will need to add the display name of the Output to the i18n resources file Messages.properties Let’s implement all of those methods We will create the outpu contructor to inject the component configuration and some additional local and built in services. Built in services are services provided by TCK. Here we find: configuration is the component configuration class hazelcastService is the service that we have implemented in the input component tutorial. it will be responsible of creating a hazelcast client instance. jsonb is a built in service provided by tck to handle json object serialization and deserialization. We will use it to convert the incoming record to json format before inseting them into the map. Nothing to do in the post construct method. but we could for example initialize a hazle cast instance there. but we will do it in a lazy way on the first call in the @ElementListener method Shut down the Hazelcast client instance and thus free the Hazelcast map reference. We get the key attribute from the incoming record and then convert the hole record to a json string. Then we insert the key/value into the hazelcast map. Let’s create a unit test for our output component. The idea will be to create a job that will insert the data using this output implementation. So, let’s create out test class. Here we start by creating a hazelcast test instance, and we initialize the map. we also shutdown the instance after all the test are executed. Now let’s create our output test. Here we start preparing the emitter test component provided bt TCK that we use in our test job to generate random data for our output. Then, we use the output component to fill the hazelcast map. By the end we test that the map contains the exact amount of data inserted by the job. Run the test and check that it’s working. Congratulation you just finished your output component.
To develop new components, Talend Component Kit requires a build tool in which you will import the component project generated from the starter.
You will then be able to install and deploy it to Talend applications. A Talend Component Kit plugin is available for each of the supported build tools.
talend-component-maven-plugin helps you write components that match best practices and generate transparently metadata used by Talend Studio.
You can use it as follows:
This plugin is also an extension so you can declare it in your build/extensions block as:
Used as an extension, the goals detailed in this document will be set up.
The Talend Component Kit plugin integrates some specific goals within Maven build lifecycle. For example, to compile the project and prepare for deploying your component, run mvn clean install. Using this command, the following goals are executed:
The build is split into several phases. The different goals are executed in the order shown above. Talend Component Kit uses default goals from the Maven build lifecycle and adds additional goals to the building and packaging phases.
Goals added to the build by Talend Component Kit are detailed below. The default lifecycle is detailed in Maven documentation.
The Talend Component Kit plugin for Maven integrates several specific goals into Maven build lifecycle.
To run specific goals individually, run the following command from the root of the project, by adapting it with each goal name, parameters and values:
The first goal is a shortcut for the maven-dependency-plugin. It creates the TALEND-INF/dependencies.txt file with the compile and runtime dependencies, allowing the component to use it at runtime:
The scan-descriptor goal scans the current module and optionally other configured folders to precompute the list of interesting classes for the framework (components, services). It allows to save some bootstrap time when launching a job, which can be useful in some execution cases:
Configuration - excluding parameters used by default only:
Name
Description
User property
Default
output
Where to dump the scan result. Note: It is not supported to change that value in the runtime.
talend.scan.output
${project.build.outputDirectory}/TALEND-INF/scanning.properties
scannedDirectories
Explicit list of directories to scan.
talend.scan.scannedDirectories
If not set, defaults to ${project.build.outputDirectory}
scannedDependencies
Explicit list of dependencies to scan - set them in the groupId:artifactId format. The list is appended to the file to scan.
talend.scan.scannedDependencies
-
The svg2png goal scans a directory - default to target/classes/icons - to find .svg files and copy them in a PNG version size at 32x32px and named with the suffix _icon32.png to enable the studio to read it:
Configuration:
Name
Description
User property
Default
icons
Where to scan for the SVG icons to convert in PNG.
talend.icons.source
${project.build.outputDirectory}/icons
workarounds
By default the shape of the icon will be enforce in the RGB channels (in white) using the alpha as reference. This is useful for black/white images using alpha to shape the picture because Eclipse - Talend Studio - caches icons using RGB but not alpha channel, pictures not using alpha channel to draw their shape should disable that workaround.
talend.icons.workaround
true
if you use that plugin, ensure to set it before the validate mojo otherwise validation can miss some png files.
This goal helps you validate the common programming model of the component. To activate it, you can use following execution definition:
It is bound to the process-classes phase by default. When executed, it performs several validations that can be disabled by setting the corresponding flags to false in the
The Component Kit Starter lets you design your components configuration and generates a ready-to-implement project structure. The Starter is available on the web or as an IntelliJ plugin. This tutorial shows you how to use the Component Kit Starter to generate new components for MySQL databases. Before starting, make sure that you have correctly setup your environment. See this section. When defining a project using the Starter, do not refresh the page to avoid losing your configuration. Before being able to create components, you need to define the general settings of the project: Create a folder on your local machine to store the resource files of the component you want to create. For example, C:/my_components. Open the Starter in the web browser of your choice. Select your build tool. This tutorial uses Maven, but you can select Gradle instead. Add any facet you need. For example, add the Talend Component Kit testing facet to your project to automatically generate unit tests for the components created in the project. Enter the Component Family of the components you want to develop in the project. This name must be a valid java name and is recommended to be capitalized, for example 'MySQL'. Once you have implemented your components in the Studio, this name is displayed in the Palette to group all of the MySQL-related components you develop, and is also part of your component name. Select the Category of the components you want to create in the current project. As MySQL is a kind of database, select Databases in this tutorial. This Databases category is used and displayed as the parent family of the MySQL group in the Palette of the Studio. Complete the project metadata by entering the Group, Artifact and Package. By default, you can only create processors. If you need to create Input or Output components, select Activate IO. By doing this: Two new menu entries let you add datasets and datastores to your project, as they are required for input and output components. Input and Output components without dataset (itself containing a datastore) will not pass the validation step when building the components. Learn more about datasets and datastores in this document. An Input component and an Output component are automatically added to your project and ready to be configured. Components added to the project using Add A Component can now be processors, input or output components. A datastore represents the data needed by an input or output component to connect to a database. When building a component, the validateDataSet validation checks that each input or output (processor without output branch) component uses a dataset and that this dataset has a datastore. You can define one or several datastores if you have selected the Activate IO step. Select Datastore. The list of datastores opens. By default, a datastore is already open but not configured. You can configure it or create a new one using Add new Datastore. Specify the name of the datastore. Modify the default value to a meaningful name for your project. This name must be a valid Java name as it will represent the datastore class in your project. It is a good practice to start it with an uppercase letter. Edit the datastore configuration. Parameter names must be valid Java names. Use lower case as much as possible. A typical configuration includes connection details to a database: url username password. Save the datastore configuration. A dataset represents the data coming from or sent to a database and needed by input and output components to operate. The validateDataSet validation checks that each input or output (processor without output branch) component uses a dataset and that this dataset has a datastore. You can define one or several datasets if you have selected the Activate IO step. Select Dataset. The list of datasets opens. By default, a dataset is already open but not configured. You can configure it or create a new one using the Add new Dataset button. Specify the name of the dataset. Modify the default value to a meaningful name for your project. This name must be a valid Java name as it will represent the dataset class in your project. It is a good practice to start it with an uppercase letter. Edit the dataset configuration. Parameter names must be valid Java names. Use lower case as much as possible. A typical configuration includes details of the data to retrieve: Datastore to use (that contains the connection details to the database) table name data Save the dataset configuration. To create an input component, make sure you have selected Activate IO. When clicking Add A Component in the Starter, a new step allows you to define a new component in your project. The intent in this tutorial is to create an input component that connects to a MySQL database, executes a SQL query and gets the result. Choose the component type. Input in this case. Enter the component name. For example, MySQLInput. Click Configuration model. This button lets you specify the required configuration for the component. By default, a dataset is already specified. For each parameter that you need to add, click the (+) button on the right panel. Enter the parameter name and choose its type then click the tick button to save the changes. In this tutorial, to be able to execute a SQL query on the Input MySQL database, the configuration requires the following parameters:+ a dataset (which contains the datastore with the connection information) a timeout parameter. Closing the configuration panel on the right does not delete your configuration. However, refreshing the page resets the configuration. Specify whether the component issues a stream or not. In this tutorial, the MySQL input component created is an ordinary (non streaming) component. In this case, leave the Stream option disabled. Select the Record Type generated by the component. In this tutorial, select Generic because the component is designed to generate records in the default Record format. You can also select Custom to define a POJO that represents your records. Your input component is now defined. You can add another component or generate and download your project. When clicking Add A Component in the Starter, a new step allows you to define a new component in your project. The intent in this tutorial is to create a simple processor component that receives a record, logs it and returns it at it is. If you did not select Activate IO, all new components you add to the project are processors by default. If you selected Activate IO, you can choose the component type. In this case, to create a Processor component, you have to manually add at least one output. If required, choose the component type: Processor in this case. Enter the component name. For example, RecordLogger, as the processor created in this tutorial logs the records. Specify the Configuration Model of the component. In this tutorial, the component doesn’t need any specific configuration. Skip this step. Define the Input(s) of the component. For each input that you need to define, click Add Input. In this tutorial, only one input is needed to receive the record to log. Click the input name to access its configuration. You can change the name of the input and define its structure using a POJO. If you added several inputs, repeat this step for each one of them. The input in this tutorial is a generic record. Enable the Generic option and click Save. Define the Output(s) of the component. For each output that you need to define, click Add Output. The first output must be named MAIN. In this tutorial, only one generic output is needed to return the received record. Outputs can be configured the same way as inputs (see previous steps). You can define a reject output connection by naming it REJECT. This naming is used by Talend applications to automatically set the connection type to Reject. Your processor component is now defined. You can add another component or generate and download your project. To create an output component, make sure you have selected Activate IO. When clicking Add A Component in the Starter, a new step allows you to define a new component in your project. The intent in this tutorial is to create an output component that receives a record and inserts it into a MySQL database table. Output components are Processors without any output. In other words, the output is a processor that does not produce any records. Choose the component type. Output in this case. Enter the component name. For example, MySQLOutput. Click Configuration Model. This button lets you specify the required configuration for the component. By default, a dataset is already specified. For each parameter that you need to add, click the (+) button on the right panel. Enter the name and choose the type of the parameter, then click the tick button to save the changes. In this tutorial, to be able to insert a record in the output MySQL database, the configuration requires the following parameters:+ a dataset (which contains the datastore with the connection information) a timeout parameter. Closing the configuration panel on the right does not delete your configuration. However, refreshing the page resets the configuration. Define the Input(s) of the component. For each input that you need to define, click Add Input. In this tutorial, only one input is needed. Click the input name to access its configuration. You can change the name of the input and define its structure using a POJO. If you added several inputs, repeat this step for each one of them. The input in this tutorial is a generic record. Enable the Generic option and click Save. Do not create any output because the component does not produce any record. This is the only difference between an output an a processor component. Your output component is now defined. You can add another component or generate and download your project. Once your project is configured and all the components you need are created, you can generate and download the final project. In this tutorial, the project was configured and three components of different types (input, processor and output) have been defined. Click Finish on the left panel. You are redirected to a page that summarizes the project. On the left panel, you can also see all the components that you added to the project. Generate the project using one of the two options available: Download it locally as a ZIP file using the Download as ZIP button. Create a GitHub repository and push the project to it using the Create on Github button. In this tutorial, the project is downloaded to the local machine as a ZIP file. Once the package is available on your machine, you can compile it using the build tool selected when configuring the project. In the tutorial, Maven is the build tool selected for the project. In the project directory, execute the mvn package command. If you don’t have Maven installed on your machine, you can use the Maven wrapper provided in the generated project, by executing the ./mvnw package command. If you have created a Gradle project, you can compile it using the gradle build command or using the Gradle wrapper: ./gradlew build. The generated project code contains documentation that can guide and help you implementing the component logic. Import the project to your favorite IDE to start the implementation. The Component Kit Starter allows you to generate a component development project from an OpenAPI JSON descriptor. Open the Starter in the web browser of your choice. Enable the OpenAPI mode using the toggle in the header. Go to the API menu. Paste the OpenAPI JSON descriptor in the right part of the screen. All the described endpoints are detected. Unselect the endpoints that you do not want to use in the future components. By default, all detected endpoints are selected. Go to the Finish menu. Download the project. When exploring the project generated from an OpenAPI descriptor, you can notice the following elements: sources the API dataset an HTTP client for the API a connection folder containing the component configuration. By default, the configuration is only made of a simple datastore with a baseUrl parameter.
A Processor is a component that converts incoming data to a different model.
A processor must have a method decorated with @ElementListener taking an incoming data and returning the processed data:
Processors must be Serializable because they are distributed components.
If you just need to access data on a map-based ruleset, you can use Record or JsonObject as parameter type. From there, Talend Component Kit wraps the data to allow you to access it as a map. The parameter type is not enforced. This means that if you know you will get a SuperCustomDto, then you can use it as parameter type. But for generic components that are reusable in any chain, it is highly encouraged to use Record until you have an evaluation language-based processor that has its own way to access components.
For example:
A processor also supports @BeforeGroup and @AfterGroup methods, which must not have any parameter and return void values. Any other result would be ignored. These methods are used by the runtime to mark a chunk of the data in a way which is estimated good for the execution flow size.
Because the size is estimated, the size of a group can vary. It is even possible to have groups of size 1.
It is recommended to batch records, for performance reasons:
You can optimize the data batch processing by using the maxBatchSize parameter. This parameter is automatically implemented on the component when it is deployed to a Talend application. Only the logic needs to be implemented. You can however customize its value setting in your LocalConfiguration the property _maxBatchSize.value - for the family - or ${component simple class name}._maxBatchSize.value - for a particular component, otherwise its default will be 1000. If you replace value by active, you can also configure if this feature is enabled or not. This is useful when you don’t want to use it at all. Learn how to implement chunking/bulking in this document.
In some cases, you may need to split the output of a processor in two or more connections. A common example is to have "main" and "reject" output connections where part of the incoming data are passed to a specific bucket and processed later.
Talend Component Kit supports two types of output connections: Flow and Reject.
Flow is the main and standard output connection.
The Reject connection handles records rejected during the processing. A component can only have one reject connection, if any. Its name must be REJECT to be processed correctly in Talend applications.
You can also define the different output connections of your component in the Starter.
To define an output connection, you can use @Output as replacement of the returned value in the @ElementListener:
Alternatively, you can pass a string that represents the new branch:
Having multiple inputs is similar to having multiple outputs, except that an OutputEmitter wrapper is not needed:
@Input takes the input name as parameter. If no name is set, it defaults to the "main (default)" input branch. It is recommended to use the default branch when possible and to avoid naming branches according to the component semantic.
Batch processing refers to the way execution environments process batches of data handled by a component using a grouping mechanism.
By default, the execution environment of a component automatically decides how to process groups of records and estimates an optimal group size depending on the system capacity. With this default behavior, the size of each group could sometimes be optimized for the system to handle the load more effectively or to match business requirements.
For example, real-time or near real-time processing needs often imply processing smaller batches of data, but more often. On the other hand, a one-time processing without business contraints is more effectively handled with a batch size based on the system capacity.
Final users of a component developed with the Talend Component Kit that integrates the batch processing logic described in this document can override this automatic size. To do that, a maxBatchSize option is available in the component settings and allows to set the maximum size of each group of data to process.
A component processes batch data as follows:
Case 1 - No maxBatchSize is specified in the component configuration. The execution environment estimates a group size of 4. Records are processed by groups of 4.
Case 2 - The runtime estimates a group size of 4 but a maxBatchSize of 3 is specified in the component configuration. The system adapts the group size to 3. Records are processed by groups of 3.
Batch processing relies on the sequence of three methods: @BeforeGroup, @ElementListener, @AfterGroup, that you can customize to your needs as a component Developer.
The group size automatic estimation logic is automatically implemented when a component is deployed to a Talend application.
Each group is processed as follows until there is no record left:
The @BeforeGroup method resets a record buffer at the beginning of each group.
The records of the group are assessed one by one and placed in the buffer as follows: The @ElementListener method tests if the buffer size is greater or equal to the defined maxBatchSize. If it is, the records are processed. If not, then the current record is buffered.
The previous step happens for all records of the group. Then the @AfterGroup method tests if the buffer is empty.
You can define the following logic in the processor configuration:
You can also use the condensed syntax for this kind of processor:
When writing tests for components, you can force the maxBatchSize parameter value by setting it with the following syntax:
Processors and output components are the components in charge of reading, processing and transforming data in a Talend job, as well as passing it to its required destination.
Before implementing the component logic and defining its layout and configurable fields, make sure you have specified its basic metadata, as detailed in this document.
A Processor is a component that converts incoming data to a different model.
A processor must have a method decorated with @ElementListener taking an incoming data and returning the processed data:
Processors must be Serializable because they are distributed components.
If you just need to access data on a map-based ruleset, you can use Record or JsonObject as parameter type. From there, Talend Component Kit wraps the data to allow you to access it as a map. The parameter type is not enforced. This means that if you know you will get a SuperCustomDto, then you can use it as parameter type. But for generic components that are reusable in any chain, it is highly encouraged to use Record until you have an evaluation language-based processor that has its own way to access components.
For example:
A processor also supports @BeforeGroup and @AfterGroup methods, which must not have any parameter and return void values. Any other result would be ignored. These methods are used by the runtime to mark a chunk of the data in a way which is estimated good for the execution flow size.
Because the size is estimated, the size of a group can vary. It is even possible to have groups of size 1.
It is recommended to batch records, for performance reasons:
You can optimize the data batch processing by using the maxBatchSize parameter. This parameter is automatically implemented on the component when it is deployed to a Talend application. Only the logic needs to be implemented. You can however customize its value setting in your LocalConfiguration the property _maxBatchSize.value - for the family - or ${component simple class name}._maxBatchSize.value - for a particular component, otherwise its default will be 1000. If you replace value by active, you can also configure if this feature is enabled or not. This is useful when you don’t want to use it at all. Learn how to implement chunking/bulking in this document.
In some cases, you may need to split the output of a processor in two or more connections. A common example is to have "main" and "reject" output connections where part of the incoming data are passed to a specific bucket and processed later.
Talend Component Kit supports two types of output connections: Flow and Reject.
Flow is the main and standard output connection.
The Reject connection handles records rejected during the processing. A component can only have one reject connection, if any. Its name must be REJECT to be processed correctly in Talend applications.
You can also define the different output connections of your component in the Starter.
To define an output connection, you can use @Output as replacement of the returned value in the @ElementListener:
Alternatively, you can pass a string that represents the new branch:
Having multiple inputs is similar to having multiple outputs, except that an OutputEmitter wrapper is not needed:
@Input takes the input name as parameter. If no name is set, it defaults to the "main (default)" input branch. It is recommended to use the default branch when possible and to avoid naming branches according to the component semantic.
Batch processing refers to the way execution environments process batches of data handled by a component using a grouping mechanism.
By default, the execution environment of a component automatically decides how to process groups of records and estimates an optimal group size depending on the system capacity. With this default behavior, the size of each group could sometimes be optimized for the system to handle the load more effectively or to match business requirements.
For example, real-time or near real-time processing needs often imply processing smaller batches of data, but more often. On the other hand, a one-time processing without business contraints is more effectively handled with a batch size based on the system capacity.
Final users of a component developed with the Talend Component Kit that integrates the batch processing logic described in this document can override this automatic size. To do that, a maxBatchSize option is available in the component settings and allows to set the maximum size of each group of data to process.
A component processes batch data as follows:
Case 1 - No maxBatchSize is specified in the component configuration. The execution environment estimates a group size of 4. Records are processed by groups of 4.
Case 2 - The runtime estimates a group size of 4 but a maxBatchSize of 3 is specified in the component configuration. The system adapts the group size to 3. Records are processed by groups of 3.
Batch processing relies on the sequence of three methods: @BeforeGroup, @ElementListener, @AfterGroup, that you can customize to your needs as a component Developer.
The group size automatic estimation logic is automatically implemented when a component is deployed to a Talend application.
Each group is processed as follows until there is no record left:
The @BeforeGroup method resets a record buffer at the beginning of each group.
The records of the group are assessed one by one and placed in the buffer as follows: The @ElementListener method tests if the buffer size is greater or equal to the defined maxBatchSize. If it is, the records are processed. If not, then the current record is buffered.
The previous step happens for all records of the group. Then the @AfterGroup method tests if the buffer is empty.
You can define the following logic in the processor configuration:
You can also use the condensed syntax for this kind of processor:
When writing tests for components, you can force the maxBatchSize parameter value by setting it with the following syntax:
Batch processing refers to the way execution environments process batches of data handled by a component using a grouping mechanism.
By default, the execution environment of a component automatically decides how to process groups of records and estimates an optimal group size depending on the system capacity. With this default behavior, the size of each group could sometimes be optimized for the system to handle the load more effectively or to match business requirements.
For example, real-time or near real-time processing needs often imply processing smaller batches of data, but more often. On the other hand, a one-time processing without business contraints is more effectively handled with a batch size based on the system capacity.
Final users of a component developed with the Talend Component Kit that integrates the batch processing logic described in this document can override this automatic size. To do that, a maxBatchSize option is available in the component settings and allows to set the maximum size of each group of data to process.
A component processes batch data as follows:
Case 1 - No maxBatchSize is specified in the component configuration. The execution environment estimates a group size of 4. Records are processed by groups of 4.
Case 2 - The runtime estimates a group size of 4 but a maxBatchSize of 3 is specified in the component configuration. The system adapts the group size to 3. Records are processed by groups of 3.
Batch processing relies on the sequence of three methods: @BeforeGroup, @ElementListener, @AfterGroup, that you can customize to your needs as a component Developer.
The group size automatic estimation logic is automatically implemented when a component is deployed to a Talend application.
Each group is processed as follows until there is no record left:
The @BeforeGroup method resets a record buffer at the beginning of each group.
The records of the group are assessed one by one and placed in the buffer as follows: The @ElementListener method tests if the buffer size is greater or equal to the defined maxBatchSize. If it is, the records are processed. If not, then the current record is buffered.
The previous step happens for all records of the group. Then the @AfterGroup method tests if the buffer is empty.
You can define the following logic in the processor configuration:
You can also use the condensed syntax for this kind of processor:
When writing tests for components, you can force the maxBatchSize parameter value by setting it with the following syntax:
Talend Component Kit provides a migration mechanism between two versions of a component to let you ensure backward compatibility. For example, a new version of a component may have some new options that need to be remapped, set with a default value in the older versions, or disabled. This tutorial shows how to create a migration handler for a component that needs to be upgraded from a version 1 to a version 2. The upgrade to the newer version includes adding new options to the component. This tutorial assumes that you know the basics about component development and are familiar with component project generation and implementation. To follow this tutorial, you need: Java 8 A Talend component development environment using Talend Component Kit. Refer to this document. Have generated a project containing a simple processor component using the Talend Component Kit Starter. First, create a simple processor component configured as follows: Create a simple configuration class that represents a basic authentication and that can be used in any component requiring this kind of authentication. Create a simple output component that uses the configuration defined earlier. The component configuration is injected into the component constructor. The version of the configuration class corresponds to the component version. By configuring these two classes, the first version of the component is ready to use a simple authentication mechanism. Now, assuming that the component needs to support a new authentication mode following a new requirement, the next steps are: Creating a version 2 of the component that supports the new authentication mode. Handling migration from the first version to the new version. The second version of the component needs to support a new authentication method and let the user choose the authentication mode he wants to use using a dropdown list. Add an Oauth2 authentication mode to the component in addition to the basic mode. For example: The options of the new authentication mode are now defined. Wrap the configuration created above in a global configuration with the basic authentication mode and add an enumeration to let the user choose the mode to use. For example, create an AuthenticationConfiguration class as follows: Using the @ActiveIf annotation allows to activate the authentication type according to the selected authentication mode. Edit the component to use the new configuration that supports an additional authentication mode. Also upgrade the component version from 1 to 2 as its configuration has changed. The component now supports two authentication modes in its version 2. Once the new version is ready, you can implement the migration handler that will take care of adapting the old configuration to the new one. What can happen if an old configuration is passed to the new component version? It simply fails, as the version 2 does not recognize the old version anymore. For that reason, a migration handler that adapts the old configuration to the new one is required. It can be achieved by defining a migration handler class in the @Version annotation of the component class. An old configuration may already be persisted by an application that integrates the version 1 of the component (Studio or web application). Add a migration handler class to the component version. Create the migration handler class MyOutputMigrationHandler. the incoming version, which is the version of the configuration that we are migrating from a map (key, value) of the configuration, where the key is the configuration path and the value is the value of the configuration. You need to be familiar with the component configuration path construction to better understand this part. Refer to Defining component layout and configuration. As a reminder, the following changes were made since the version 1 of the component: The configuration BasicAuth from the version 1 is not the root configuration anymore, as it is under AuthenticationConfiguration. AuthenticationConfiguration is the new root configuration. The component supports a new authentication mode (Oauth2) which is the default mode in the version 2 of the component. To migrate the old component version to the new version and to keep backward compatibility, you need to: Remap the old configuration to the new one. Give the adequate default values to some options. In the case of this scenario, it means making all configurations based on the version 1 of the component have the authenticationMode set to basic by default and remapping the old basic authentication configuration to the new one. if a configuration has been renamed between 2 component versions, you can get the old configuration option from the configuration map by using its old path and set its value using its new path. You can now upgrade your component without losing backward compatibility.
Talend Component Kit is a Java framework designed to simplify the development of components at two levels: The Runtime, that injects the specific component code into a job or pipeline. The framework helps unifying as much as possible the code required to run in Data Integration (DI) and BEAM environments. The Graphical interface. The framework helps unifying the code required to render the component in a browser or in the Eclipse-based Talend Studio (SWT). Most part of the development happens as a Maven or Gradle project and requires a dedicated tool such as IntelliJ. The Component Kit is made of: A Starter, that is a graphical interface allowing you to define the skeleton of your development project. APIs to implement components UI and runtime. Development tools: Maven and Gradle wrappers, validation rules, packaging, Web preview, etc. A testing kit based on JUnit 4 and 5. By using this tooling in a development environment, you can start creating components as described below. Developing new components using the Component Kit framework includes: Creating a project using the starter or the Talend IntelliJ plugin. This step allows to build the skeleton of the project. It consists in: Defining the general configuration model for each component in your project. Generating and downloading the project archive from the starter. Compiling the project. Importing the compiled project in your IDE. This step is not required if you have generated the project using the IntelliJ plugin. Implementing the components, including: Registering the components by specifying their metadata: family, categories, version, icon, type and name. Defining the layout and configurable part of the components. Defining the execution logic of the components, also called runtime. testing the components. Deploying the components to Talend Studio or Cloud applications. Optionally, you can use services. Services are predefined or user-defined configurations that can be reused in several components. There are four types of components, each type coming with its specificities, especially on the runtime side. Input components: Retrieve the data to process from a defined source. An input component is made of: The execution logic of the component, represented by a Mapper or an Emitter class. The source logic of the component, represented by a Source class. The layout of the component and the configuration that the end-user will need to provide when using the component, defined by a Configuration class. All input components must have a dataset specified in their configuration, and every dataset must use a datastore. Processors: Process and transform the data. A processor is made of: The execution logic of the component, describing how to process each records or batches of records it receives. It also describes how to pass records to its output connections. This logic is defined in a Processor class. The layout of the component and the configuration that the end-user will need to provide when using the component, defined by a Configuration class. Output components: Send the processed data to a defined destination. An output component is made of: The execution logic of the component, describing how to process each records or batches of records it receives. This logic is defined in an Output class. Unlike processors, output components are the last components of the execution and return no data. The layout of the component and the configuration that the end-user will need to provide when using the component, defined by a Configuration class. All input components must have a dataset specified in their configuration, and every dataset must use a datastore. Standalone components: Make a call to the service or run a query on the database. A standalone component is made of: The execution logic of the component, represented by a DriverRunner class. The layout of the component and the configuration that the end-user will need to provide when using the component, defined by a Configuration class. All input components must have a datastore or dataset specified in their configuration, and every dataset must use a datastore. The following example shows the different classes of an input components in a multi-component development project: Setup your development environment Generate your first project and develop your first component
Talend Component scanning is based on plugins. To make sure that plugins can be developed in parallel and avoid conflicts, they need to be isolated (component or group of components in a single jar/plugin).
Multiple options are available:
Graph classloading: this option allows you to link the plugins and dependencies together dynamically in any direction. For example, the graph classloading can be illustrated by OSGi containers.
Tree classloading: a shared classloader inherited by plugin classloaders. However, plugin classloader classes are not seen by the shared classloader, nor by other plugins. For example, the tree classloading is commonly used by Servlet containers where plugins are web applications.
Flat classpath: listed for completeness but rejected by design because it doesn’t comply with this requirement.
In order to avoid much complexity added by this layer, Talend Component Kit relies on a tree classloading. The advantage is that you don’t need to define the relationship with other plugins/dependencies, because it is built-in.
Here is a representation of this solution:
The shared area contains Talend Component Kit API, which only contains by default the classes shared by the plugins.
Then, each plugin is loaded with its own classloader and dependencies.
This section explains the overall way to handle dependencies but the Talend Maven plugin provides a shortcut for that.
A plugin is a JAR file that was enriched with the list of its dependencies. By default, Talend Component Kit runtime is able to read the output of maven-dependency-plugin in TALEND-INF/dependencies.txt. You just need to make sure that your component defines the following plugin:
Once build, check the JAR file and look for the following lines:
What is important to see is the scope related to the artifacts:
The APIs (component-api and geronimo-annotation_1.3_spec) are provided because you can consider them to be there when executing (they come with the framework).
Your specific dependencies (awesome-project in the example above) are marked as compile: they are included as needed dependencies by the framework (note that using runtime works too).
the other dependencies are ignored. For example, test dependencies.
Even if a flat classpath deployment is possible, it is not recommended because it would then reduce the capabilities of the components.
The way the framework resolves dependencies is based on a local Maven repository layout. As a quick reminder, it looks like:
This is all the layout the framework uses. The logic converts t-uple {groupId, artifactId, version, type (jar)} to the path in the repository.
Talend Component Kit runtime has two ways to find an artifact:
From the file system based on a configured Maven 2 repository.
From a fat JAR (uber JAR) with a nested Maven repository under MAVEN-INF/repository.
The first option uses either ${user.home}/.m2/repository (default) or a specific path configured when creating a ComponentManager. The nested repository option needs some configuration during the packaging to ensure the repository is correctly created.
To create the nested MAVEN-INF/repository repository, you can use the nested-maven-repository extension:
Plugins are usually programmatically registered. If you want to make some of them automatically available, you need to generate a TALEND-INF/plugins.properties file that maps a plugin name to coordinates found with the Maven mechanism described above.
You can enrich maven-shade-plugin to do it:
Here is a final job/application bundle based on maven-shade-plugin:
The configuration unrelated to transformers depends on your application.
ContainerDependenciesTransformer embeds a Maven repository and PluginTransformer to create a file that lists (one per line) artifacts (representing plugins).
Both transformers share most of their configuration:
session: must be set to ${session}. This is used to retrieve dependencies.
scope: a comma-separated list of scopes to include in the artifact filtering (note that the default will rely on provided but you can replace it by compile, runtime, runtime+compile, runtime+system or test).
include: a comma-separated list of artifacts to include in the artifact filtering.
exclude: a comma-separated list of artifacts to exclude in the artifact filtering.
userArtifacts: set of artifacts to include (groupId, artifactId, version, type - optional, file - optional for plugin transformer, scope - optional) which can be forced inline. This parameter is mainly useful for PluginTransformer.
includeTransitiveDependencies: should transitive dependencies of the components be included. Set to true by default. It is active for userArtifacts.
includeProjectComponentDependencies: should component project dependencies be included. Set to false by default. It is not needed when a job project uses isolation for components.
With the component tooling, it is recommended to keep default locations. Also if you need to use project dependencies, you can need to refactor your project structure to ensure component isolation. Talend Component Kit lets you handle that part but the recommended practice is to use userArtifacts for the components instead of project
Components are designed to manipulate data (access, read, create). Talend Component Kit can handle several types of data, described in this document. By design, the framework must run in DI (plain standalone Java program) and in Beam pipelines. It is out of scope of the framework to handle the way the runtime serializes - if needed - the data. For that reason, it is critical not to import serialization constraints to the stack. As an example, this is one of the reasons why Record or JsonObject were preferred to Avro IndexedRecord. Any serialization concern should either be hidden in the framework runtime (outside of the component developer scope) or in the runtime integration with the framework (for example, Beam integration). Record is the default format. It offers many possibilities and can evolve depending on the Talend platform needs. Its structure is data-driven and exposes a schema that allows to browse it. Projects generated from the Talend Component Kit Starter are by default designed to handle this format of data. Record is a Java interface but never implement it yourself to ensure compatibility with the different Talend products. Follow the guidelines below. You can build records using the newRecordBuilder method of the RecordBuilderFactory (see here). For example: In the example above, the schema is dynamically computed from the data. You can also do it using a pre-built schema, as follows: The example above uses a schema that was pre-built using factory.newSchemaBuilder(Schema.Type.RECORD). When using a pre-built schema, the entries passed to the record builder are validated. It means that if you pass a null value null or an entry type that does not match the provided schema, the record creation fails. It also fails if you try to add an entry which does not exist or if you did not set a not nullable entry. Using a dynamic schema can be useful on the backend but can lead users to more issues when creating a pipeline to process the data. Using a pre-built schema is more reliable for end-users. You can access and read data by relying on the getSchema method, which provides you with the available entries (columns) of a record. The Entry exposes the type of its value, which lets you access the value through the corresponding method. For example, the Schema.Type.STRING type implies using the getString method of the record. For example: The Record format supports the following data types: String Boolean Int Long Float Double DateTime Array Bytes Record A map can always be modelized as a list (array of records with key and value entries). For example: For example, you can use the API to provide the schema. The following method needs to be implemented in a service. Manually constructing the schema without any data: Returning the schema from an already built record: MyDataset is the class that defines the dataset. Learn more about datasets and datastores in this document. Entry names for Record and JsonObject types must comply with the following rules: The name must start with a letter or with _. If not, the invalid characters are ignored until the first valid character. Following characters of the name must be a letter, a number, or . If not, the invalid character is replaced with . For example: 1foo becomes foo. f@o becomes f_o. 1234f5@o becomes ___f5_o. foo123 stays foo123. Each array uses only one schema for all of its elements. If an array contains several elements, they must be of the same data type. For example, the following array is not correct as it contains a string and an object: The runtime also supports JsonObject as input and output component type. You can rely on the JSON services (Jsonb, JsonBuilderFactory) to create new instances. This format is close to the Record format, except that it does not natively support the Datetime type and has a unique Number type to represent Int, Long, Float and Double types. It also does not provide entry metadata like nullable or comment, for example. It also inherits the Record format limitations. The runtime also accepts any POJO as input and output component type. In this case, it uses JSON-B to treat it as a JsonObject.
The entry point of the API is the ContainerManager. It allows you to define what is the Shared classloader and to create children: how to resolve dependencies for plugins from the plugin file/location how to configure the classloaders (what is the parent classloader, how to handle the parent first/last delegation, and so on). It is recommended to keep the manager running if you can reuse plugins in order to avoid recreating classloaders and to mutualize them. What the shared classloader is Which classes are loaded from the shared loader first (intended to be used for API which should not be loaded from the plugin loader) Which classes are loaded from the parent classloader. This can be useful to prevent loading a "common" library from the parent classloader. For instance, it can be neat for guava, commons-lang3, an so on). Once you have defined a manager, you can create plugins: To create the plugin container, the Resolver resolves the dependencies needed for the plugin, then the manager creates the plugin classloader and registers the plugin Container. Some actions are needed when a plugin is registered or unregistered. For that purpose, you can use ContainerListener: Plugins are directly registered on the manager:
From the version 7.0 of Talend Studio, Talend Component Kit becomes the recommended framework to use to develop components.
This framework is being introduced to ensure that newly developed components can be deployed and executed both in on-premise/local and cloud/big data environments.
From that new approach comes the need to provide a complete yet unique and compatible way of developing components.
With the Component Kit, custom components are entirely implemented in Java. To help you get started with a new custom component development project, a Starter is available. Using it, you will be able to generate the skeleton of your project. By importing this skeleton in a development tool, you can then implement the components layout and execution logic in Java.
With the previous Javajet framework, metadata, widgets and configurable parts of a custom component were specified in XML. With the Component Kit, they are now defined in the
Since the 1.1.25 release, the dynamic column feature is supported in Studio with component-runtime components.
Dynamic column is available with Enterprise versions of Talend Studio only.
In Studio, we can define for each component a schema with associated metadata.
To access those informations in your component, you’ve to do a few things:
Using the @Structure annotation
API: @org.talend.sdk.component.api.configuration.ui.widget.Structure
According the specified field type, you will acess to
the column names list with List
The component configuration is defined in the
Developing new components using the Component Kit framework includes: Creating a project using the starter or the Talend IntelliJ plugin. This step allows to build the skeleton of the project. It consists in: Defining the general configuration model for each component in your project. Generating and downloading the project archive from the starter. Compiling the project. Importing the compiled project in your IDE. This step is not required if you have generated the project using the IntelliJ plugin. Implementing the components, including: Registering the components by specifying their metadata: family, categories, version, icon, type and name. Defining the layout and configurable part of the components. Defining the execution logic of the components, also called runtime. testing the components. Deploying the components to Talend Studio or Cloud applications. Optionally, you can use services. Services are predefined or user-defined configurations that can be reused in several components.
It is possible to extend the Component API for custom front features. What is important here is to keep in mind that you should do it only if it targets not portable components (only used by the Studio or Beam). It is recommended to create a custom xxxx-component-api module with the new set of annotations. To extend the UI, add an annotation that can be put on @Option fields, and that is decorated with @Ui. All its members are then put in the metadata of the parameter. For example:
This tutorial shows how to create components that consume a REST API. The component developed as example in this tutorial is an input component that provides a search functionality for Zendesk using its Search API. Lombok is used to avoid writing getter, setter and constructor methods. You can generate a project using the Talend Components Kit starter, as described in this tutorial. The input component relies on Zendesk Search API and requires an HTTP client to consume it. The Zendesk Search API takes the following parameters on the /api/v2/search.json endpoint. query : The search query. sort_by : The sorting type of the query result. Possible values are updated_at, created_at, priority, status, ticket_type, or relevance. It defaults to relevance. sort_order: The sorting order of the query result. Possible values are asc (for ascending) or desc (for descending). It defaults to desc. Talend Component Kit provides a built-in service to create an easy-to-use HTTP client in a declarative manner, using Java annotations. No additional implementation is needed for the interface, as it is provided by the component framework, according to what is defined above. This HTTP client can be injected into a mapper or a processor to perform HTTP requests. This example uses the basic authentication that supported by the API. The first step is to set up the configuration for the basic authentication. To be able to consume the Search API, the Zendesk instance URL, the username and the password are needed. The data store is now configured. It provides a basic authentication token. Once the data store is configured, you can define the dataset by configuring the search query. It is that query that defines the records processed by the input component. Your component is configured. You can now create the component logic. Mappers defined with this tutorial don’t implement the split part because HTTP calls are not split on many workers in this case. Once the component logic implemented, you can create the source in charge of performing the HTTP request to the search API and converting the result to JsonObject records. You now have created a simple Talend component that consumes a REST API. To learn how to test this component, refer to this tutorial.
A Partition Mapper (PartitionMapper) is a component able to split itself to make the execution more efficient. This concept is borrowed from big data and useful in this context only (BEAM executions). The idea is to divide the work before executing it in order to reduce the overall execution time. The process is the following: The size of the data you work on is estimated. This part can be heuristic and not very precise. From that size, the execution engine (runner for Beam) requests the mapper to split itself in N mappers with a subset of the overall work. The leaf (final) mapper is used as a Producer (actual reader) factory. This kind of component must be Serializable to be distributable. A partition mapper requires three methods marked with specific annotations: @Assessor for the evaluating method @Split for the dividing method @Emitter for the Producer factory The Assessor method returns the estimated size of the data related to the component (depending its configuration). It must return a Number and must not take any parameter. For example: The Split method returns a collection of partition mappers and can take optionally a @PartitionSize long value as parameter, which is the requested size of the dataset per sub partition mapper. For example: The Emitter method must not have any parameter and must return a producer. It uses the partition mapper configuration to instantiate and configure the producer. For example:
Input components are the components generally placed at the beginning of a Talend job. They are in charge of retrieving the data that will later be processed in the job.
An input component is primarily made of three distinct logics:
The execution logic of the component itself, defined through a partition mapper.
The configurable part of the component, defined through the mapper configuration.
The source logic defined through a producer.
Before implementing the component logic and defining its layout and configurable fields, make sure you have specified its basic metadata, as detailed in this document.
A Partition Mapper (PartitionMapper) is a component able to split itself to make the execution more efficient.
This concept is borrowed from big data and useful in this context only (BEAM executions). The idea is to divide the work before executing it in order to reduce the overall execution time.
The process is the following:
The size of the data you work on is estimated. This part can be heuristic and not very precise.
From that size, the execution engine (runner for Beam) requests the mapper to split itself in N mappers with a subset of the overall work.
The leaf (final) mapper is used as a Producer (actual reader) factory.
This kind of component must be Serializable to be distributable.
A partition mapper requires three methods marked with specific annotations:
@Assessor for the evaluating method
@Split for the dividing method
@Emitter for the Producer factory
The Assessor method returns the estimated size of the data related to the component (depending its configuration). It must return a Number and must not take any parameter.
For example:
The Split method returns a collection of partition mappers and can take optionally a @PartitionSize long value as parameter, which is the requested size of the dataset per sub partition mapper.
For example:
The Emitter method must not have any parameter and must return a producer. It uses the partition mapper configuration to instantiate and configure the producer.
For example:
The Producer defines the source logic of an input component. It handles the interaction with a physical source and produces input data for the processing flow.
A producer must have a @Producer method without any parameter. It is triggered by the @Emitter method of the partition mapper and can return any data. It is defined in the
The Job builder lets you create a job pipeline programmatically using Talend components (Producers and Processors). The job pipeline is an acyclic graph, allowing you to build complex pipelines.
Let’s take a simple use case where two data sources (employee and salary) are formatted to CSV and the result is written to a file.
A job is defined based on components (nodes) and links (edges) to connect their branches together.
Every component is defined by a unique id and an URI that identify the component.
The URI follows the form [family]://[component][?version][&configuration], where:
family is the name of the component family.
component is the name of the component.
version is the version of the component. It is represented in a key=value format. The key is __version and the value is a number.
configuration is component configuration. It is represented in a key=value format. The key is the path of the configuration and the value is a `string' corresponding to the configuration value.
URI example:
configuration parameters must be URI/URL encoded.
Job example:
It has some starting components (components that don’t have a from connection and that need to be of the producer type).
There are no cyclic connections. The job pipeline needs to be an acyclic graph.
All components used in the connections are already declared.
Each connection is used only once. You cannot connect a component input/output branch twice.
In this version, the execution of the job is linear. Components are not executed in parallel even if some steps may be independents.
Depending on the configuration, you can select the environment which you execute your job in.
To select the environment, the logic is the following one:
If an org.talend.sdk.component.runtime.manager.chain.Job.ExecutorBuilder class is passed through the job properties, then use it. The supported types are an ExecutionBuilder instance, a Class or a String.
If an ExecutionBuilder SPI is present, use it. It is the case if component-runtime-beam is present in your classpath.
Else, use a local/standalone execution.
In the case of a Beam execution, you can customize the pipeline options using system properties. They have to be prefixed with talend.beam.job.. For example, to set the appName option, you need to use -Dtalend.beam.job.appName=mytest.
The job builder lets you set a key provider to join your data when a component has multiple inputs. The key provider can be set contextually to a component or globally to the job.
If the incoming data has different IDs, you can provide a complex global key provider that relies on the context given by the component id and the branch name.
For Beam case, you need to rely on Beam pipeline definition and use the component-runtime-beam dependency, which provides Beam bridges.
org.talend.sdk.component.runtime.beam.TalendIO provides a way to convert a partition mapper or a processor to an input or processor using the read or write methods.
org.talend.sdk.component.runtime.beam.TalendFn provides the way to wrap a processor in a Beam PTransform and to integrate it into the pipeline.
The multiple inputs and outputs are represented by a Map element in Beam case to avoid using multiple inputs and outputs.
You can use ViewsMappingTransform or CoGroupByKeyResultMappingTransform to adapt the input/output format to the record format representing the multiple inputs/output, like Map
In order to use Talend Component Kit, you need the following tools installed on your machine: Java JDK 1.8.x. You can download it from Oracle website. Talend Open Studio to integrate your components. A Java Integrated Development Environment such as Eclipse or IntelliJ. IntelliJ is recommended as a Talend Component Kit plugin is available. Optional: If you use IntelliJ, you can install the Talend Component Kit plugin for IntelliJ. Optional: A build tool: Apache Maven 3.5.4 is recommended to develop a component or the project itself. You can download it from Apache Maven website. You can also use Gradle, but at the moment certain features are not supported, such as validations. It is optional to install a build tool independently since Maven and Gradle wrappers are already available with Talend Component Kit.
The HTTP API intends to expose most Talend Component Kit features over HTTP. It is a standalone Java HTTP server.
The WebSocket protocol is activated for the endpoints. Endpoints then use /websocket/v1 as base instead of /api/v1. See WebSocket for more details.
Browse the API description using interface.
To make sure that the migration can be enabled, you need to set the version the component was created with in the execution configuration that you send to the server (component version is in component the detail endpoint). To do that, use tcomp::component::version key.
Endpoints that are intended to disappear will be deprecated. A X-Talend-Warning header will be returned with a message as value.
You can connect yo any endpoint by:
Replacing /api with /websocket
Appending /
Before implementing a component logic and configuration, you need to specify the family and the category it belongs to, the component type and name, as well as its name and a few other generic parameters. This set of metadata, and more particularly the family, categories and component type, is mandatory to recognize and load the component to Talend Studio or Cloud applications. Some of these parameters are handled at the project generation using the starter, but can still be accessed and updated later on. The family and category of a component is automatically written in the package-info.java file of the component package, using the @Components annotation. By default, these parameters are already configured in this file when you import your project in your IDE. Their value correspond to what was defined during the project definition with the starter. Multiple components can share the same family and category value, but the family + name pair must be unique for the system. A component can belong to one family only and to one or several categories. If not specified, the category defaults to Misc. The package-info.java file also defines the component family icon, which is different from the component icon. You can learn how to customize this icon in this section. Here is a sample package-info.java: Another example with an existing component: Components can require metadata to be integrated in Talend Studio or Cloud platforms. Metadata is set on the component class and belongs to the org.talend.sdk.component.api.component package. When you generate your project and import it in your IDE, icon and version both come with a default value. @Icon: Sets an icon key used to represent the component. You can use a custom key with the custom() method but the icon may not be rendered properly. The icon defaults to Check. Replace it with a custom icon, as described in this section. @Version: Sets the component version. 1 by default. Learn how to manage different versions and migrations between your component versions in this section. For example: Every component family and component needs to have a representative icon. You have to define a custom icon as follows: For the component family the icon is defined in the package-info.java file. For the component itself, you need to declare the icon in the component class. Custom icons must comply with the following requirements: Icons must be stored in the src/main/resources/icons folder of the project. Icon file names need to match one of the following patterns: IconName.svg or IconName_icon32.png. The latter will run in degraded mode in Talend Cloud. Replace IconName by the name of your choice. Icons must be squared, even for the SVG format. Note that SVG icons are not supported by Talend Studio and can cause the deployment of the component to fail. If you aim at deploying a custom component to Talend Studio, specify PNG icons or use the Maven (or Gradle) svg2png plugin to convert SVG icons to PNG. If you want a finer control over both images, you can provide both in your component. Ultimately, you can also remove SVG parameters from the talend.component.server.icon.paths property in the HTTP server configuration. Note that SVG icons are not supported by Talend Studio and can cause the deployment of the component to fail. If you aim at deploying a custom component to Talend Studio, specify PNG icons or use the Maven (or Gradle) svg2png plugin to convert SVG icons to PNG. If you want a finer control over both images, you can provide both in your component. Ultimately, you can also remove SVG parameters from the talend.component.server.icon.paths property in the HTTP server configuration. For any purpose, you can also add user defined metadatas to your component with the @Metadatas annotation. Example: You can also use a SPI implementing org.talend.sdk.component.spi.component.ComponentMetadataEnricher. Methodology for creating components Generating a project using the starter Managing component versions Defining an input component Defining a processor or output component Defining a driver runner component Defining component layout and configuration Best practices
Once you have generated a project, you can start implementing the logic and layout of your components and iterate on it. Depending on the type of component you want to create, the logic implementation can differ. However, the layout and component metadata are defined the same way for all types of components in your project. The main steps are: Defining family and component metadata Defining an input component logic Defining a processor/output logic Defining a standalone component logic Defining component layout and configuration In some cases, you will require specific implementations to handle more advanced cases, such as: Internationalizing a component Managing component versions Masking sensitive data Implementing batch processing Implementing streaming on a component You can also make certain configurations reusable across your project by defining services. Using your Java IDE along with a build tool supported by the framework, you can then compile your components to test and deploy them to Talend Studio or other Talend applications: Building components with Maven Building components with Gradle Wrapping a Beam I/O In any case, follow these best practices to ensure the components you develop are optimized. You can also learn more about component loading and plugins here: Loading a component
This tutorial walks you through the most common iteration steps to create a component with Talend Component Kit and to deploy it to Talend Open Studio.
The component created in this tutorial is a simple processor that reads data coming from the previous component in a job or pipeline and displays it in the console logs of the application, along with an additional information entered by the final user.
The component designed in this tutorial is a processor and does not require nor show any datastore and dataset configuration. Datasets and datastores are required only for input and output components.
To get your development environment ready and be able to follow this tutorial:
Download and install a Java JDK 1.8 or greater.
Download and install Talend Open Studio. For example, from Sourceforge.
Download and install IntelliJ.
Download the Talend Component Kit plugin for IntelliJ. The detailed installation steps for the plugin are available in this document.
The first step in this tutorial is to generate a component skeleton using the Starter embedded in the Talend Component Kit plugin for IntelliJ.
Start IntelliJ and create a new project. In the available options, you should see Talend Component.
Make sure that a Project SDK is selected. Then, select Talend Component and click Next. The Talend Component Kit Starter opens.
Enter the component and project metadata. Change the default values, for example as presented in the screenshot below:
The Component Family and the Category will be used later in Talend Open Studio to find the new component.
Project metadata is mostly used to identify the project structure. A common practice is to replace 'company' in the default value by a value of your own, like your domain name.
Once the metadata is filled, select Add a component. A new screen is displayed in the Talend Component Kit Starter that lets you define the generic configuration of the component. By default, new components are processors.
Enter a valid Java name for the component. For example, Logger.
Select Configuration Model and add a string type field named level. This input field will be used in the component configuration for final users to enter additional information to display in the logs.
In the Input(s) / Output(s) section, click the default MAIN input branch to access its detail, and make sure that the record model is set to Generic. Leave the Name of the branch with its default MAIN value.
Repeat the same step for the default MAIN output branch.
Because the component is a processor, it has an output branch by default. A processor without any output branch is considered an output component. You can create output components when the Activate IO option is selected.
Click Next and check the name and location of the project, then click Finish to generate the project in the IDE.
At this point, your component is technically already ready to be compiled and deployed to Talend Open Studio. But first, take a look at the generated project:
Two classes based on the name and type of component defined in the Talend Component Kit Starter have been generated:
LoggerProcessor is where the component logic is defined
LoggerProcessorConfiguration is where the component layout and configurable fields are defined, including the level string field that was defined earlier in the configuration model of the component.
The package-info.java file contains the component metadata defined in the Talend Component Kit Starter, such as family and category.
You can notice as well that the elements in the tree structure are named after the project metadata defined in the Talend Component Kit Starter.
These files are the starting point if you later need to edit the configuration, logic, and metadata of the component.
There is more that you can do and configure with the Talend Component Kit Starter. This tutorial covers only the basics. You can find more information in this document.
Without modifying the component code generated from the Starter, you can compile the project and deploy the component to a local instance of Talend Open Studio.
The logic of the component is not yet implemented at that stage. Only the configurable part specified in the Starter will be visible. This step is useful to confirm that the basic configuration of the component renders correctly.
Before starting to run any command, make sure that Talend Open Studio is not running.
From the component project in IntelliJ, open a Terminal and make sure that the selected directory is the root of the project. All commands shown in this tutorial are performed from this location.
Compile the project by running the following command: mvnw clean install. The mvnw command refers to the Maven wrapper that is embedded in Talend Component Kit. It allows to use the right version of Maven for your project without having to install it manually beforehand. An equivalent wrapper is available for Gradle.
Once the command is executed and you see BUILD SUCCESS in the terminal, deploy the component to your local instance of Talend Open Studio using the following command: mvnw talend-component:deploy-in-studio -Dtalend.component.studioHome="
Integrate components you developed using Talend Component Kit to Talend Studio in a few steps. Also learn how to enable the developer and debugging modes to iterate on your component development. The version of Talend Component Kit you need to use to develop new components depends on the version of Talend Studio in which components will be integrated. Refer to this document to learn about compatibility between Talend Component Kit and the different versions of Talend applications. Learn how to build and deploy components to Talend Studio using Maven or Gradle Talend Component Kit plugins. This can be done using the deploy-in-studio goal from your development environment. If you are unfamiliar with component development, you can also follow this example to go through the entire process, from creating a project to using your new component in Talend Studio. The Studio integration relies on the Component Server, that the Studio uses to gather data about components created using Talend Component Kit. You can change the default configuration of component server by modifying the $STUDIO_HOME/configuration/config.ini file. The following parameters are available: Name Description Default component.environment Enables the developer mode when set to dev - component.debounce.timeout Specifies the timeout (in milliseconds) before calling listeners in components Text fields 750 component.kit.skip If set to true, the plugin is not enabled. It is useful if you don’t have any component developed with the framework. false component.java.arguments Component server additional options - component.java.m2 Maven repository that the server uses to resolve components Defaults to the global Studio configuration component.java.coordinates A list of comma-separated GAV (groupId:artifactId:version) of components to register - component.java.registry A properties file with values matching component GAV (groupId:artifactId:version) registered at startup. Only use slashes (even on windows) in the path. - component.java.port Sets the port to use for the server random components.server.beam.active Active, if set to true, Beam support (Experimental). It requires Beam SDK Java core dependencies to be available. false component.server.jul.forceConsole Adds a console handler to JUL to see logs in the console. This can be helpful in development because the formatting is clearer than the OSGi one in workspace/.metadata/.log. It uses the java.util.logging.SimpleFormatter.format property to define its format. By default, it is %1$tb %1$td, %1$tY %1$tl:%1$tM:%1$tS %1$Tp %2$s%n%4$s: %5$s%6$s%n, but for development purposes [%4$s] %5$s%6$s%n is simpler and more readable. false Here is an example of a common developer configuration/config.ini file: The developer mode is especially useful to iterate on your component development and to avoid closing and restarting Talend Studio every time you make a change to a component. It adds a Talend Component Kit button in the main toolbar: When clicking this button, all components developed with the Talend Component Kit framework are reloaded. The cache is invalidated and the components refreshed. You still need to add and remove the components to see the changes. To enable it, simply set the component.environment parameter to dev in the config.ini configuration file of the component server. Several methods allow you to debug custom components created with Talend Component Kit in Talend Studio. From your development tool, create a new Remote configuration, and copy the Command line arguments for running remote JVM field. For example, -agentlib:jdwp=transport=dt_socket,server=y,suspend=n,address=*:5005, where: the suspend parameter of the -agentlib argument specifies whether you want to suspend the debugged JVM until the debugger attaches to it. Possible values are n (no, default value) or y (yes). the address parameter of the -agentlib argument is the port used for the remote configuration. Make sure this port is available. Open Talend Studio. Create a new Job that uses the component you want to debug or open an existing one that already uses it. Go to the Run tab of the Job and select Use specific JVM arguments. Click New to add an argument. In the popup window, paste the arguments copied from the IDE. Enter the corresponding debug mode: To debug the runtime, run the Job and access the remote host configured in the IDE. To debug the Guess schema option, click the Guess schema action button of the component and access the remote host configured in the IDE. From your development tool, create a new Remote configuration, and copy the Command line arguments for running remote JVM field. For example, -agentlib:jdwp=transport=dt_socket,server=y,suspend=n,address=*:5005, where: suspend defines whether you need to access the defined configuration to run the remote JVM. Possible values are n (no, default value) or y (yes). address is the port used for the remote configuration. Make sure this port is available. Access the installation directory of your Talend Sutdio. Open the .ini file corresponding to your Operating System. For example, TOS_DI-win-x86_64.ini. Paste the arguments copied from the IDE in a new line of the file. Go to Talend Studio to use the component, and access the host host configured in the IDE. If you run multiple Studio instances automatically in parallel, you can run into some issues with the random port computation. For example on a CI platform. For that purpose, you can create the $HOME/.talend/locks/org.talend.sdk.component.studio-integration.lock file. Then, when a server starts, it acquires a lock on that file and prevents another server to get a port until it is started. It ensures that you can’t have two concurrent processes getting the same port allocated. However, it is highly unlikely to happen on a desktop. In that case, forcing a different value through component.java.port in your config.ini file is a better solution for local installations.
This gallery shows how widgets and validations are rendered in both Studio and web environments, along with sample implementation code. You can also find sample working components for each of the configuration cases below: ActiveIf: Add visibility conditions on some configurations. Checkbox: Add checkboxes or toggles to your component. Code: Allow users to enter their own code. Credential: Mark a configuration as sensitive data to avoid displaying it as plain text. Datastore: Add a button allowing to check the connection to a datastore. Datalist: Two ways of implementing a dropdown list with predefined choices. Integer: Add numeric fields to your component configuration. Min/Max: Specify a minimum or a maximum value for a numeric configuration. Multiselect: Add a list and allow users to select multiple elements of that list. Pattern: Enforce rules based on a specific a pattern to prevent users from entering invalid values. Required: Make a configuration mandatory. Suggestions: Suggest possible values in a field based on what the users are entering. Table: Add a table to your component configuration. Textarea: Add a text area for configurations expecting long texts or values. Input: Add a simple text input field to the component configuration Update: Provide a button allowing to fill a part of the component configuration based on a service. Validation: Specify constraints to make sure that a URL is well formed. Widgets allow to easily implement different types of input fields to your components. Studio Rendering Web Rendering Studio Rendering Web Rendering Studio Rendering Web Rendering Studio Rendering Web Rendering Studio Rendering Web Rendering Datetime fields rely on the Java Date Time API, including LocalTime, LocalDate, LocalDateTime and ZonedDateTime classes. Studio Rendering Web Rendering or Studio Rendering Web Rendering Studio Rendering Web Rendering Studio Rendering Web Rendering Studio Rendering Web Rendering Studio Rendering Web Rendering Validations help restricting what can be entered or selected in an input field, to make sure that the value complies with the expected type of information. Studio Rendering Web Rendering Studio Rendering Web Rendering Studio Rendering Web Rendering You can also use other types of validation that are similar to @Pattern: @Min, @Max to specify a minimum and maximum value for numerical fields. @Uniques for collection values. @Required for a required configuration.
By default, input components are designed to receive a one-time batch of data to process. By enabling the streaming mode, you can instead set your component to process a continuous incoming flow of data. When streaming is enabled on an input component, the component tries to pull data from its producer. When no data is pulled, it waits for a defined period of time before trying to pull data again, and so on. This period of time between tries is defined by a strategy. This document explains how to configure this strategy and the cases where it can fit your needs. Before enabling streaming on your component, make sure that it fits the scope and requirements of your project and that regular batch processing cannot be used instead. Streaming is designed to help you dealing with real-time or near real-time data processing cases, and should be used only for such cases. Enabling streaming will impact the performance when processing batches of data. You can enable streaming right from the design phase of the project by enabling the Stream toggle in the basic configuration of your future component in the Component Kit Starter. Doing so adds a default streaming-ready configuration to your component when generating the project. This default configuration implements a constant pause duration of 500 ms between retries, with no limit of retries. You can add configuration that help you to stop the data reading in your input component when it reaches required limitations: max duration and max records. To do it you need to set true in PartitionMapper#stoppable. An important condition is that PartitionMapper#infinite should also be true. You can also pass those limits inside @PostConstruct method with @Option annotation. Available options: Option.MAX_DURATION_PARAMETER, Option.MAX_RECORDS_PARAMETER. By default in the setting those values are set to -1. It means "infinity" behavior. If streaming was not enabled at all during the project generation or if you need to implement a more specific configuration, you can change the default settings according to your needs: Add the infinite=true parameter to your component class. Define the number of retries allowed in the component family LocalConfiguration, using the talend.input.streaming.retry.maxRetries parameter. It is set by default to Integer.MAX_VALUE. Define the pausing strategy between retries in the component family LocalConfiguration, using the talend.input.streaming.retry.strategy parameter. Possible values are: constant (default). It sets a constant pause duration between retries. exponential. It sets an exponential backoff pause duration. See the tables below for more details about each strategy. Parameter Description Default value talend.input.streaming.retry.constant.timeout Pause duration for the constant strategy, in ms. 500 Parameter Description Default value talend.input.streaming.retry.exponential.exponent Exponent of the exponential calculation. 1.5 talend.input.streaming.retry.exponential.randomizationFactor Randomization factor used in the calculation. 0.5 talend.input.streaming.retry.exponential.maxDuration Maximum pausing duration between two retries. 5*60*1000 (5 minutes) talend.input.streaming.retry.exponential.initialBackOff Initial backoff value. 1000 (1 second) The values of these parameters are then used in the following calculations to determine the exact pausing duration between two retries. For more clarity in the formulas below, parameter names have been replaced with variables. First, the current interval duration is calculated: \$A = min(B xx E^I, F)\$ Where: A: currentIntervalMillis B: initialBackOff E: exponent I: current number of retries F: maxDuration Then, from the current interval duration, the next interval duration is calculated: \$D = min(F, A + ((R xx 2-1) xx C xx A))\$ Where: D: nextBackoffMillis F: maxDuration A: currentIntervalMillis R: random C: randomizationFactor
Talend Component Kit is a toolkit based on Java and designed to simplify the development of components at two levels: Runtime: Runtime is about injecting the specific component code into a job or pipeline. The framework helps unify as much as possible the code required to run in Data Integration (DI) and BEAM environments. Graphical interface: The framework helps unify the code required to be able to render the component in a browser (web) or in the Eclipse-based Studio (SWT). The Talend Component Kit framework is made of several tools designed to help you during the component development process. It allows to develop components that fit in both Java web UIs. Starter: Generate the skeleton of your development project using a user-friendly interface. The Talend Component Kit Starter is available as a web tool or as a plugin for the IntelliJ IDE. Component API: Check all classes available to implement components. Build tools: The framework comes with Maven and Gradle wrappers, which allow to always use the version of Maven or Gradle that is right for your component development environment and version. testing tools: Test components before integrating them into Talend Studio or Cloud applications. testing tools include the Talend Component Kit Web Tester, which allows to check the web UI of your components on your local machine. You can find more details about the framework design in this document. The Talend Component Kit project is available on GitHub in the following repository
Learn about the latest news or go deeper in the framework with the following articles. Changelog Creating plugins Running Component Kit components on a Remote Engine
This part is limited to specific kinds of Beam PTransform:
PTransform
Before being able to develop components using Talend Component Kit, you need the right system configuration and tools. Although Talend Component Kit comes with some embedded tools, such as Maven and Gradle wrappers, you still need to prepare your system. A Talend Component Kit plugin for IntelliJ is also available and allows to design and generate your component project right from IntelliJ. System requirements Installing the IntelliJ plugin
In some cases you can need to add some actions that are not related to the runtime. For example, enabling users of the plugin/library to test if a connection works properly. To do so, you need to define an @Action, which is a method with a name (representing the event name), in a class decorated with @Service: Services are singleton. If you need some thread safety, make sure that they match that requirement. Services should not store any status either because they can be serialized at any time. Status are held by the component. Services can be used in components as well (matched by type). They allow to reuse some shared logic, like a client. Here is a sample with a service used to access files: The service is automatically passed to the constructor. It can be used as a bean. In that case, it is only necessary to call the service method. Some common actions need a clear contract so they are defined as API first-class citizen. For example, this is the case for wizards or health checks. Here is the list of the available actions: Mark an action works for closing runtime connection, returning a close helper object which do real close action. The functionality is for the Studio only, studio will use the close object to close connection for existed connection, and no effect for cloud platform. Type: close_connection API: @org.talend.sdk.component.api.service.connection.CloseConnection Returned type: org.talend.sdk.component.api.service.connection.CloseConnectionObject Sample: Mark an action works for creating runtime connection, returning a runtime connection object like jdbc connection if database family. Its parameter MUST be a datastore. Datastore is configuration type annotated with @DataStore. The functionality is for the Studio only, studio will use the runtime connection object when use existed connection, and no effect for cloud platform. Type: create_connection API: @org.talend.sdk.component.api.service.connection.CreateConnection This class marks an action that explore a connection to retrieve potential datasets. Type: discoverdataset API: @org.talend.sdk.component.api.service.discovery.DiscoverDataset Returned type: org.talend.sdk.component.api.service.discovery.DiscoverDatasetResult Sample: Mark a method as being useful to fill potential values of a string option for a property denoted by its value. You can link a field as being completable using @Proposable(value). The resolution of the completion action is then done through the component family and value of the action. The callback doesn’t take any parameter. Type: dynamic_values API: @org.talend.sdk.component.api.service.completion.DynamicValues Returned type: org.talend.sdk.component.api.service.completion.Values Sample: This class marks an action doing a connection test Type: healthcheck API: @org.talend.sdk.component.api.service.healthcheck.HealthCheck Returned type: org.talend.sdk.component.api.service.healthcheck.HealthCheckStatus Sample: Mark an action as returning a discovered schema. Its parameter MUST be a dataset. Dataset is configuration type annotated with @DataSet. If component has multiple datasets, then dataset used as action parameter should have the same identifier as this @DiscoverSchema. Type: schema API: @org.talend.sdk.component.api.service.schema.DiscoverSchema Returned type: org.talend.sdk.component.api.record.Schema Sample: Mark a method as returning a Schema resulting from a connector configuration and some other parameters.Parameters can be an incoming schema and/or an outgoing branch.`value' name should match the connector’s name. Type: schema_extended API: @org.talend.sdk.component.api.service.schema.DiscoverSchemaExtended Returned type: org.talend.sdk.component.api.record.Schema Sample: Mark a method as being useful to fill potential values of a string option. You can link a field as being completable using @Suggestable(value). The resolution of the completion action is then done when the user requests it (generally by clicking on a button or entering the field depending the environment). Type: suggestions API: @org.talend.sdk.component.api.service.completion.Suggestions Returned type: org.talend.sdk.component.api.service.completion.SuggestionValues Sample: This class marks an action returning a new instance replacing part of a form/configuration. Type: update API: @org.talend.sdk.component.api.service.update.Update Extension point for custom UI integrations and custom actions. Type: user API: @org.talend.sdk.component.api.service.Action Mark a method as being used to validate a configuration. this is a server validation so only use it if you can’t use other client side validation to implement it. Type: validation API: @org.talend.sdk.component.api.service.asyncvalidation.AsyncValidation Returned type: org.talend.sdk.component.api.service.asyncvalidation.ValidationResult Sample: These actions are provided - or not - by the application the UI runs within. always ensure you don’t require this action in your component. Mark the decorated field as supporting suggestions, i.e. dynamically get a list of valid values the user can use. It is however different from @Suggestable by looking up the implementation in the current application and not the services. Finally, it is important to note that it can do nothing in some environments too and that there is no guarantee the specified action is supported. API: @org.talend.sdk.component.api.configuration.action.BuiltInSuggestable Internationalization is supported through the injection of the $lang parameter, which allows you to get the correct locale to use with an @Internationalized service: You can combine the $lang option with the @Internationalized and @Language parameters.
Components built using Talend Component Kit can be shared as component archives (.car). These CAR files are executable files allowing to easily deploy the components it contains to any compatible version of Talend Studio. Component developers can generate .car files from their projects to share their components and make them available for other users, as detailed in this document. This document assumes that you have a component archive (.car) file and need to deploy it to Talend Studio. The component archive (.car) is executable and exposes the studio-deploy command which takes a Talend Studio home path as parameter. When executed, it installs the dependencies into the Studio and registers the component in your instance. For example: You can also upload the dependencies to your Nexus server using the following command: In this command, Nexus URL and repository name are mandatory arguments. All other arguments are optional. If arguments contain spaces or special symbols, you need to quote the whole value of the argument. For example: Talend Studio allows you to share components you have created using Talend Component Kit to other users working on the same remote project. Remote projects are available with Enterprise versions of Talend Studio only. Also, note that this feature has been removed in Studio since 7.3 release. Make sure you are connected to a remote project and the artifact repository for component sharing has been properly configured. On the toolbar of the Studio main window, click or click File > Edit Project Properties from the menu bar to open the Project Settings dialog box. In the tree view of the dialog box, select Repository Share to open the corresponding view. Select the Propagate components update to Artifact Repository check box. In the Repository ID field, specify the artifact repository configured for component sharing, and then click Check connection to verify the connectivity. Click Apply and Close to validate the settings and close the dialog box. Create a folder named patches at the root of your Talend Studio installation directory, then copy the .car files of the components you want share to this folder. Restart your Talend Studio and connect to the remote project. The components are deployed automatically to the repository and available in the Palette for other users when connected to a remote project with the same sharing repository configuration. My custom component builds correctly but does not appear in Talend Studio, how to fix it? This issue can be caused by the icon specified in the component metadata. Make sure to specify a custom icon for the component and the component family. These custom icons must be in PNG format to be properly handled by Talend Studio. Remove SVG parameters from the talend.component.server.icon.paths property in the HTTP server configuration. Refer to this section. Learn more about defining custom icons for components in this document.
The first step when developing new components is to create a project that will contain the skeleton of your components and set you on the right track. The project generation can be achieved using the Talend Component Kit Starter or the Talend Component Kit plugin for IntelliJ. Through a user-friendly interface, you can define the main lines of your project and of your component(s), including their name, family, type, configuration model, and so on. Once completed, all the information filled are used to generate a project that you will use as starting point to implement the logic and layout of your components, and to iterate on them. Using the starter Using the IntelliJ plugin Once your project is generated, you can start implementing the component logic.
The Talend Component Kit IntelliJ plugin is a plugin for the IntelliJ Java IDE. It adds support for the Talend Component Kit project creation. Main features: Project generation support. Internationalization completion for component configuration. In the Intellij IDEA: Go to File > Settings… On the left panel, select Plugins. Access the Marketplace tab. Enter Talend in the search field and Select Talend Component Kit. Select Install. Click the Restart IDE button. Confirm the IDEA restart to complete the installation. The plugin is now installed on your IntelliJ IDEA. You can start using it. The plugin offers auto-completion for the configuration internationalization. The Talend component configuration lets you setup translatable and user-friendly labels for your configuration using a property file. Auto-completion in possible for the configuration keys and default values in the property file. For example, you can internationalize a simple configuration class for a basic authentication that you use in your component: This configuration class contains three properties which you can attach a user-friendly label to. For example, you can define a label like My server URL for the url option: Locate or create a Messages.properties file in the project resources and add the label to that file. The plugin automatically detects your configuration and provides you with key completion in the property file. Press Ctrl+Space to see the key suggestions.
You can integrate and start using components developed using Talend Component Kit in Talend applications very easily. As both the development framework and Talend applications evolve over time, you need to ensure compatibility between the components you develop and the versions of Talend applications that you are targeting, by making sure that you use the right version of Talend Component Kit. The version of Talend Component Kit you need to use to develop new components depends on the versions of the Talend applications in which these components will be integrated. Talend product Talend Component Kit version Talend Studio 8.8.8 (aka master) latest release Talend Studio 8.0.1 latest release QA approved Talend Studio 7.3.1 Framework until 1.38.x Talend Studio 7.2.1 Framework until 1.1.10 Talend Studio 7.1.1 Framework until 1.1.1 Talend Studio 7.0.1 Framework until 0.0.5 Talend Cloud latest release QA and cloud teams approved More recent versions of Talend Component Kit contain many fixes, improvements and features that help developing your components. However, they can cause some compatibility issues when deploying these components to older/different versions of Talend Studio and Talend Cloud. Choose the version of Talend Component Kit that best fits your needs. Creating a project using the Component Kit Starter always uses the latest release of Talend Component Kit. However, you can manually change the version of Talend Component Kit directly in the generated project. Go to your IDE and access the project root .pom file. Look for the org.talend.sdk.component dependency nodes. Replace the version in the relevant nodes with the version that you need to use for your project. You can use a Snapshot of the version under development using the -SNAPSHOT version and Sonatype snapshot repository.
To be able to see and use your newly developed components, you need to integrate them to the right application. Currently, you can deploy your components to Talend Studio as part of your development process to iterate on them: Iterating on component development with Talend Studio You can also share your components externally and install them using a component archive (.car) file. Sharing and installing components in Talend Studio Check the versions of the framework that are compatible with your version of Talend Studio in this document. If you were used to create custom components with the Javajet framework and want to get to know the new approach and main differences of the Component Kit framework, refer to this document.
Standalone components are the components without input or output flows. They are designed to do actions without reading or processing any data. For example standalone components can be used to create indexes in databases. Before implementing the component logic and defining its layout and configurable fields, make sure you have specified its basic metadata, as detailed in this document. A Driver Runner (DriverRunner) is a standalone component which doesn’t process or return any data. A Driver runner must have a @RunAtDriver method without any parameter.
The component API is declarative (through annotations) to ensure it is: Evolutive. It can get new features without breaking old code. As static as possible. Because it is fully declarative, any new API can be added iteratively without requiring any change to existing components. For example, in the case of Beam potential evolution: would not be affected by the addition of the new Timer API, which can be used as follows: The intent of the framework is to be able to fit in a Java UI as well as in a web UI. It must be understood as colocalized and remote UI. The goal is to move as much as possible the logic to the UI side for UI-related actions. For example, validating a pattern, a size, and so on, should be done on the client side rather than on the server side. Being static encourages this practice. The other goal of being static in the API definition is to ensure that the model will not be mutated at runtime and that all the auditing and modeling can be done before, at the design phase. Being static also ensures that the development can be validated as much as possible through build tools. This does not replace the requirement to test the components but helps developers to maintain components with automated tools. Refer to this document. The components must be able to execute even if they have conflicting libraries. For that purpose, classloaders must be isolated. A component defines its dependencies based on a Maven format and is always bound to its own classloader. The definition payload is as flat as possible and strongly typed to ensure it can be manipulated by consumers. This way, consumers can add or remove fields with simple mapping rules, without any abstract tree handling. The execution (runtime) configuration is the concatenation of framework metadata (only the version) and a key/value model of the instance of the configuration based on the definition properties paths for the keys. It enables consumers to maintain and work with the keys/values according to their need. The framework not being responsible for any persistence, it is very important to make sure that consumers can handle it from end to end, with the ability to search for values (update a machine, update a port and so on) and keys (for example, a new encryption rule on key certificate). Talend Component Kit is a metamodel provider (to build forms) and a runtime execution platform. It takes a configuration instance and uses it volatilely to execute a component logic. This implies it cannot own the data nor define the contract it has for these two endpoints and must let the consumers handle the data lifecycle (creation, encryption, deletion, and so on). A new mime type called talend/stream is introduced to define a streaming format. It matches a JSON object per line: Icons (@Icon) are based on a fixed set. Custom icons can be used but their display cannot be guaranteed. Components can be used in any environment and require a consistent look that cannot be guaranteed outside of the UI itself. Defining keys only is the best way to communicate this information. Once you know exactly how you will deploy your component in the Studio, then you can use `@Icon(value = CUSTOM, custom = "…") to use a custom icon file.
Each type of component has its own execution logic. The same basic logic is applied to all components of the same type, and is then extended to implement each component specificities. The project generated from the starter already contains the basic logic for each component. Talend Component Kit framework relies on several primitive components. All components can use @PostConstruct and @PreDestroy annotations to initialize or release some underlying resource at the beginning and the end of a processing. In distributed environments, class constructor are called on cluster manager nodes. Methods annotated with @PostConstruct and @PreDestroy are called on worker nodes. Thus, partition plan computation and pipeline tasks are performed on different nodes. All the methods managed by the framework must be public. Private methods are ignored. The framework is designed to be as declarative as possible but also to stay extensible by not using fixed interfaces or method signatures. This allows to incrementally add new features of the underlying implementations.
This document explains how Asciidoctor is used in the context of Talend Component Kit as well as the specific processes in place.
For general guidelines about Asciidoctor, refer to the Asciidoc Syntax quick reference page.
There are two ways to suggest modifications or new content. Both of the options below require you to have a GitHub account created.
On every page of the Talend Component Kit Developer Guide, a Suggest and edit button is available. It allows you to access the corresponding source file on GitHub and to create a pull request with the suggested edits. The pull request is then assessed by the team in charge of the project.
Fork the Runtime repository of the Talend Component Kit project and edit .adoc files located under documentation\src\main\antora\modules\ROOT\pages. Make sure to follow the guidelines outlined in the current document, especially for large modifications or new content, to make sure it can properly be rendered. When done, create a pull request that will be assessed by the team in charge of the project.
The documentation is made of:
Documentation files manually written under documentation\src\main\antora\modules\ROOT\pages.
Documentation files automatically generated from the source code under documentation\src\main\antora\modules\ROOT\pages\_partials. These files are individually called in manually written files through includes.
Assets, especially images, stored in the documentation\src\main\antora\modules\ROOT\assets folder. Some subfolders exist to categorize the assets.
Each file has a unique name and is rendered as a unique HTML page. Some of the files are prefixed to help identifying the type of content it contains. Most common examples are:
index- for pages referenced from the main index page. These pages also contain specific attributes to be correctly rendered on the main index page (see 'List of metadata attributes' below).
tutorial- for tutorials/guided examples.
generated_ for pages generated from the source code. These pages are generally stored in the _partials folder.
For all pages:
:page-partial indicates that the current .adoc file can be included in another document using an include::. This attribute has no value.
:page-talend_skipindexation: indicates that the current .adoc file must not be indexed. This attribute has no value. Add it to files that should not be returned in the search, like index files that only contain includes.
:description: is the meta description of the file. Each .adoc file is rendered as an HTML file.
:keywords: is the list of meta keywords relevant for the current .adoc file. Separate keywords using simple commas.
:page-talend_stage: draft indicates that the current document is a draft and is not final even if published. It triggers the display of a small banner indicating the status of the page. Remove this attribute once the page is final.
For pages that should appear as a tile on the index page:
:page-documentationindex-index: is the weight of the page. A low weight indicates that the page should be one of the first tiles to appear. A high weight will push the tile towards the end of the list in the index page.
:page-documentationindex-label: is the title of the tile in the index page.
:page-documentationindex-icon: is the icon of the tile in the index page. The value of this attribute should be the name of a free icon on fontawesome.
:page-documentationindex-description: is a short description of the page that will be displayed in the tile under its title.
For pages containing API descriptions:
:page-talend_swaggerui: true indicates that the page contains some API reference that should be displayed using Swagger UI
The Talend Component Kit documentation is published as HTML and PDF. Some parts can differ between these two versions, such as lists of links, that are not functional in the PDF version.
To avoid this, it is possible to define some conditionality to have some content only displaying in one of the output formats only. For example:
Every .adoc file can only contain one 'level 1' title (=). It is the title of the page and is located at the top of the document. It is a best practices that all sublevels added to the document are kept consistent. For example, don’t use a 'level 3' (===) section directly inside a 'level 1'.
When possible, avoid going lower than section 2 (===) to keep the page readable. In the HTML output, the document title is renderedh1, section 1 titles as h2, etc. The "in-page" navigation available on the right side of the HTML rendering only considers h2 and h3 elements. Other levels are ignored to keep the navigation readable and simple.
It is possible to reuse content through "includes". Includes can be used to reuse entire files in other files, allowing to avoid copy pasting.
When using an 'include' (calling an .adoc file from another .adoc file), you can specify a level offset to keep the hierarchy consistent in the current document. Avoid using includes if not absolutely necessary. An include can be done as follows:
In this case, both doc1.adoc and doc2.adoc are rendered in the same page and their content is offset by one level, meaning that the document title of doc1 becomes a section 1 title (h2) instead of an h1 in the final rendering, and so on.
Note that both doc1.adoc and doc2.adoc will in addition be rendered as standalone pages (doc1.html and doc2.html).
All images are stored under documentation > src > main > antora > modules > ROOT > assets > images. Relatively to .adoc files, it can be ../assets/images/ or ../../assets/images for _partials (automatically generated from code) pages. To avoid handling different relative paths, the backend already resolves directly image: to the image folder. Hence, paths to images should start with the following:
image:(
The Producer defines the source logic of an input component. It handles the interaction with a physical source and produces input data for the processing flow.
A producer must have a @Producer method without any parameter. It is triggered by the @Emitter method of the partition mapper and can return any data. It is defined in the
singer-java module provide a Java API to write a custom singer. To import it, add the following dependency: Then you have access to the Singer class and its companion which provides the primitives to output properly the data: To build schema, keys, bookmarks, json and state which are all either JsonObject or JsonArray you can rely on JsonBuilderFactory which can be instantiated with this snippet: component-kitap is the name of the integration between singer-java and Talend Component Kit. It enables to run native Talend Component Kit components through a tap. The module relies on a proper setup of the component and classpath: Classpath is well setup - composed of component-kitap with a default SLF4J binding configured to log only errors on stderr. For convenience, you can use the all in one bundle provided by the module: org.talend.sdk.component:component-kitapp:${kit.version}:fatjar. Component is "deployed" - i.e. its maven repository is set provisionned with its dependencies. If you downloaded a component as a .car then you can run the car to do it. You can enforce the maven location through the system property talend.component.manager.m2.repository. Regarding SLF4J, the fatjar uses slf4j-standard of the framework which enables to set the logged level to error through a system property: -Dorg.talend.sdk.component.slf4j.StdLogger.level=err. To automatically register a component plugin/family you must add to the classpath a TALEND-INF/plugins.properties: The file only need to contain the registration of the plugin jar: Therefore the launch command can look like: Alternatively you can use org.talend.sdk.component.singer.kitap.Carpates main to launch the application, it differs from Kitap in the sense it takes a .car as option and avoids to pre-build the m2 repository: Here is an example with a real component: The config.json must respect this format: in some environment, such a JSON is not desirable, it is possible to put component_config attribute as a string containing the full json (escaped indeed) too.
Datasets and datastores are configuration types that define how and where to pull the data from. They are used at design time to create shared configurations that can be stored and used at runtime. All connectors (input and output components) created using Talend Component Kit must reference a valid dataset. Each dataset must reference a datastore. Datastore: The data you need to connect to the backend. Dataset: A datastore coupled with the data you need to execute an action. Make sure that: a datastore is used in each dataset. each dataset has a corresponding input component (mapper or emitter). This input component must be able to work with only the dataset part filled by final users. Any other property implemented for that component must be optional. These rules are enforced by the validateDataSet validation. If the conditions are not met, the component builds will fail. Make sure that: a datastore is used in each dataset. each dataset has a corresponding input component (mapper or emitter). This input component must be able to work with only the dataset part filled by final users. Any other property implemented for that component must be optional. These rules are enforced by the validateDataSet validation. If the conditions are not met, the component builds will fail. A datastore defines the information required to connect to a data source. For example, it can be made of: a URL a username a password. You can specify a datastore and its context of use (in which dataset, etc.) from the Component Kit Starter. Make sure to modelize the data your components are designed to handle before defining datasets and datastores in the Component Kit Starter. Once you generate and import the project into an IDE, you can find datastores under a specific datastore node. Example of datastore: A dataset represents the inbound data. It is generally made of: A datastore that defines the connection information needed to access the data. A query. You can specify a dataset and its context of use (in which input and output component it is used) from the Component Kit Starter. Make sure to modelize the data your components are designed to handle before defining datasets and datastores in the Component Kit Starter. Once you generate and import the project into an IDE, you can find datasets under a specific dataset node. Example of dataset referencing the datastore shown above: The display name of each dataset and datastore must be referenced in the message.properties file of the family package. The key for dataset and datastore display names follows a defined pattern: ${family}.${configurationType}.${name}._displayName. For example: These keys are automatically added for datasets and datastores defined from the Component Kit Starter. When deploying a component or set of components that include datasets and datastores to Talend Studio, a new node is created under Metadata. This node has the name of the component family that was deployed. It allows users to create reusable configurations for datastores and datasets. With predefined datasets and datastores, users can then quickly fill the component configuration in their jobs. They can do so by selecting Repository as Property Type and by browsing to the predefined dataset or datastore. Studio will generate connection and close components auto for reusing connection function in input and output components, just need to do like this example: Then the runtime mapper and processor only need to use @Connection to get the connection like this: The component server scans all configuration types and returns a configuration type index. This index can be used for the integration into the targeted platforms (Studio, web applications, and so on). Mark a model (complex object) as being a dataset. API: @org.talend.sdk.component.api.configuration.type.DataSet Sample: Mark a model (complex object) as being a datastore (connection to a backend). API: @org.talend.sdk.component.api.configuration.type.DataStore Sample: Mark a model (complex object) as being a dataset discovery configuration. API: @org.talend.sdk.component.api.configuration.type.DatasetDiscovery Sample: The component family associated with a configuration type (datastore/dataset) is always the one related to the component using that configuration. The configuration type index is represented as a flat tree that contains all the configuration types, which themselves are represented as nodes and indexed by ID. Every node can point to other nodes. This relation is represented as an array of edges that provides the child IDs. As an illustration, a configuration type index for the example above can be defined as follows: