Skip to content
Data
Skill

/authoring-java-sdk-tasks

Writes Airflow task logic in Java, Kotlin, or any JVM language using the Airflow Java SDK. Use when the user wants to implement Airflow tasks in Java/JVM, asks about `@Builder.Dag`/`@Builder.Task`/`@Builder.XCom`, the `Task`/`BundleBuilder` interfaces, reading

From plugin
astronomer-data
45935 skills3 commands

Claude Code

$ npx -y skills add astronomer/agents --skill authoring-java-sdk-tasks --agent claude-code

SKILL.md

authoring-java-sdk-tasks.SKILL.md
name: authoring-java-sdk-tasks
description: Writes Airflow task logic in Java, Kotlin, or any JVM language using the Airflow Java SDK. Use when the user wants to implement Airflow tasks in Java/JVM, asks about `@Builder.Dag`/`@Builder.Task`/`@Builder.XCom`, the `Task`/`BundleBuilder` interfaces, reading connections/variables/XComs from Java, the JSON-to-Java type mapping, or logging from Java tasks. This skill covers the Java-specific native API; the shared Python-stub pattern and conceptual model live in authoring-language-sdk-tasks. For building/shipping the bundle see deploying-java-sdk-bundles; for coordinator config see configuring-airflow-language-sdks.

Authoring Java SDK Tasks

The Airflow Java SDK implements the language-SDK model for the JVM: your DAG stays in Python, and each task instance runs in a short-lived JVM subprocess. This skill covers the **Java-specific** native API. The shared model — the Python `@task.stub` pattern, ID matching, and the XCom-as-JSON contract — lives in **authoring-language-sdk-tasks**; read that first if you're new to language SDKs.

> **Experimental.** The Java SDK is in preview. Artifact coordinates and APIs may change.

> **Related skills:** **authoring-language-sdk-tasks** (shared Python stub + concepts), **configuring-airflow-language-sdks** (route the queue to `JavaCoordinator`), **deploying-java-sdk-bundles** (compile and ship the JAR).

---

Recap: the Python side

Java tasks are paired with Python stubs that carry no logic — they declare the task, queue, dependency graph, and retries. IDs must match the Java annotations exactly, and an upstream argument on a stub only declares the dependency (the value is fetched in Java). Full rules are in **authoring-language-sdk-tasks**; the minimal shape:

from airflow.sdk import dag, task


@dag
def sales_pipeline():                     # dag_id "sales_pipeline" -> @Builder.Dag(id="sales_pipeline")
    @task.stub(queue="java")
    def extract(): ...                    # task_id "extract" -> @Builder.Task(id="extract")

    @task.stub(queue="java")
    def transform(extracted): ...

    transform(extract())


sales_pipeline()

---

Java side: two APIs

Both APIs produce identical runtime behavior; pick by style, and you can mix them in one bundle.

Annotation-based API (recommended)

Annotate a plain class; an annotation processor generates the wiring (`<ClassName>Builder`) at compile time.

import static java.lang.System.Logger.Level.INFO;
import org.apache.airflow.sdk.*;

@Builder.Dag(id = "sales_pipeline")          // must match the Python dag_id
public class SalesPipeline {
  private static final System.Logger log = System.getLogger(SalesPipeline.class.getName());

  @Builder.Task(id = "extract")              // must match the Python @task.stub name
  public long extract(Client client) {
    var conn = client.getConnection("sales_db");
    log.log(INFO, "connected to {0}", conn.host);
    return 42L;                              // return value is pushed as the return_value XCom
  }

  @Builder.Task(id = "transform")
  public long transform(
      Client client,
      @Builder.XCom(task = "extract") long recordCount) {  // pulls extract's return_value
    var threshold = (String) client.getVariable("transform_threshold");
    return recordCount * 2;
  }

  @Builder.Task   // id omitted -> the method name "load" is used
  public void load(Context context, @Builder.XCom(task = "transform") long transformed) {
    log.log(INFO, "attempt {0}, value {1}", context.ti.tryNumber, transformed);
  }
}

Annotation reference:

| Annotation | Purpose | |------------|---------| | `@Builder.Dag(id = "...")` | Marks the class as a task container. `id` must match the Python `dag_id`; if omitted, the class name is used. Optional `to = "..."` renames the generated builder (default `<ClassName>Builder`). | | `@Builder.Task(id = "...")` | Marks a method as a task. `id` must match the Python `@task.stub` function name; if omitted, the method name is used. | | `@Builder.XCom(task = "...", key = "...")` | Injects an upstream task's XCom as a parameter. `task` defaults to the parameter name; `key` defaults to the producing task's `return_value`. The parameter type must be compatible with the stored JSON value. |

A task method's return value is automatically pushed as that task's `return_value` XCom. A method may declare `throws Exception`; any uncaught exception fails the task instance (which triggers retries if the stub configured them).

Interface-based API

Implement `Task` directly when you want full control over registration and XCom handling.

import org.apache.airflow.sdk.*;

public class ExtractTask implements Task {
  @Override
  public void execute(Context context, Client client) throws Exception {
    var conn = client.getConnection("sales_db");
    // ... do work ...
    client.setXCom(42L);   // push return_value explicitly
  }
}

Register tasks manually in a `Dag` and expose it through a `BundleBuilder`:

public class MyBundle implements BundleBuilder {
  @Override
  public Iterable<Dag> getDags() {
    var dag = new Dag("sales_pipeline");      // DAG ID matches Python
    dag.addTask("extract", ExtractTask.class);
    dag.addTask("transform", TransformTask.class);
    return java.util.List.of(dag);
  }
}

Each `Task` class needs a public no-arg constructor. Task IDs must be unique within a DAG, and DAG IDs unique within a bundle.

---

The entry point

Every bundle has a `main` that hands your DAGs to the SDK server. The server connects to the coordinator, runs one task instance, and exits.

import java.util.List;
import org.apache.airflow.sdk.*;

public class Main implements BundleBuilder {
  @Override
  public Iterable<Dag> getDags() {
    // With the annotation API, the *Builder classes are generated at compile time.
    return List.of(SalesPipelineBuilder.build());
  }

  public static void main(String[] args) {
    Se
Read more
@astronomer
Ships withastronomer-data

AI agent tooling for data engineering workflows. Includes an MCP server for Airflow, a CLI tool (af) for interacting with Airflow from your terminal, and skills that extend AI coding agents with specialized capabilities for working with Airflow and data

Stars on GitHub

Momentum

stars in total
459
Star history of astronomer/agents on GitHub, a chart by star-history.com

Other skills on astronomer-data.

airflow-hitl

airflow-hitl

Builds human-in-the-loop (HITL) Airflow workflows - approval gates, form input, and human-driven branching. Use when a DAG needs…

airflow

airflow

Queries, manages, and troubleshoots Apache Airflow using the `af` CLI. Use when working with anything related to Airflow - a DAG,…

More skills from other plugins.

context-loader
Auto-invoked

context-loader

Search memories from earlier Pi sessions in this repository. Use it when earlier work may already explain the code, error,…

mem05d69k
@mem0ai@mem0aiInstall Skill
analyzing-ai-citations

analyzing-ai-citations

Answer AI citation and answer engine optimization (AEO) questions in PostHog: whether AI answer engines (ChatGPT, Claude, and an…

posthog12d41k
@posthog@posthogInstall Skill

Questions about authoring-java-sdk-tasks.

Which coding agents can use authoring-java-sdk-tasks?
authoring-java-sdk-tasks installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.