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java-development

Guides Java SDK development in Apache Beam, including building, testing, running examples, and understanding the project structure. Use when working with Java code in sdks/java/, runners/, or examples/java/.

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name java-development description Guides Java SDK development in Apache Beam, including building, testing, running examples, and understanding the project structure. Use when working with Java code in sdks/java/, runners/, or examples/java/. Java Development in Apache Beam Project Structure Key Directories sdks/java/core - Core Java SDK (PCollection, PTransform, Pipeline) sdks/java/harness - SDK harness (container entrypoint) sdks/java/io/ - I/O connectors (51+ connectors including BigQuery, Kafka, JDBC, etc.) sdks/java/extensions/ - Extensions (SQL, ML, protobuf, etc.) runners/ - Runner implementations: runners/direct-java - Direct Runner (local execution) runners/flink/ - Flink Runner runners/spark/ - Spark Runner runners/google-cloud-dataflow-java/ - Dataflow Runner examples/java/ - Java examples including WordCount Build System Apache Beam uses Gradle with a custom BeamModulePlugin . Every Java project's build.gradle starts with: apply plugin: 'org.apache.beam.module' applyJavaNature( ... ) Common Commands Build Commands # Compile a specific project ./gradlew -p sdks/java/core compileJava # Build a project (compile + tests) ./gradlew :sdks:java:harness:build # Run WordCount example ./gradlew :examples:java:wordCount Running Unit Tests # Run all tests in a project ./gradlew :sdks:java:harness: test # Run a specific test class ./gradlew :sdks:java:harness: test --tests org.apache.beam.fn.harness.CachesTest # Run tests matching a pattern ./gradlew :sdks:java:harness: test --tests *CachesTest # Run a specific test method ./gradlew :sdks:java:harness: test --tests *CachesTest.testClearableCache Running Integration Tests Integration tests have filenames ending in IT.java and use TestPipeline . # Run I/O integration tests on Direct Runner ./gradlew :sdks:java:io:google-cloud-platform:integrationTest # Run with custom GCP project ./gradlew :sdks:java:io:google-cloud-platform:integrationTest \ -PgcpProject=<project> -PgcpTempRoot=gs://<bucket>/path # Run on Dataflow Runner ./gradlew :runners:google-cloud-dataflow-java:examplesJavaRunnerV2IntegrationTest \ -PdisableSpotlessCheck= true -PdisableCheckStyle= true -PskipCheckerFramework \ -PgcpProject=<project> -PgcpRegion=us-central1 -PgcsTempRoot=gs://<bucket>/tmp Code Formatting # Format Java code ./gradlew spotlessApply Writing Integration Tests @Rule public TestPipeline pipeline = TestPipeline.create(); @Test public void testSomething () { pipeline.apply(...); pipeline.run().waitUntilFinish(); } Set pipeline options via -DbeamTestPipelineOptions='[...]' : -DbeamTestPipelineOptions= '["--runner=TestDataflowRunner","--project=myproject","--region=us-central1","--stagingLocation=gs://bucket/path"]' Using Modified Beam Code Publish to Maven Local # Publish a specific module ./gradlew -Ppublishing -p sdks/java/io/kafka publishToMavenLocal # Publish all modules ./gradlew -Ppublishing publishToMavenLocal Building SDK Container # Build Java SDK container (for Runner v2) ./gradlew :sdks:java:container:java11:docker # Tag and push docker tag apache/beam_java11_sdk:2.XX.0.dev \ "us-docker.pkg.dev/your-project/beam/beam_java11_sdk:custom" docker push "us-docker.pkg.dev/your-project/beam/beam_java11_sdk:custom" Building Dataflow Worker Jar ./gradlew :runners:google-cloud-dataflow-java:worker:shadowJar Test Naming Conventions Unit tests: *Test.java Integration tests: *IT.java JUnit Report Location After running tests, find HTML reports at: <project>/build/reports/tests/test/index.html IDE Setup (IntelliJ) Open /beam (the repository root, NOT sdks/java ) Wait for indexing to complete Find examples/java/build.gradle and click Run next to wordCount task to verify setup
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nameSkill name
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descriptionDescription
categoryCategories (array)
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examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
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Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

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