* Java SDK: Let a native Java Dag set one queue for all its tasks
Every task of a native Java Dag runs on the Java coordinator, so each one
needs a queue that queue_to_coordinator routes there. Airflow's Dag has no
queue setting, so authors had to repeat the same queue on every task. The
Go and TypeScript SDKs already take a Dag-level queue that each task
inherits unless it sets its own; this gives Java the same.
* Reject a blank Dag-level queue and fix the native Dag queue docs
A blank queue matched no coordinator, so every task stayed queued.
The parsing docs still said there was no Dag-level queue and routed a
queue the examples do not use.
* Reject a blank Dag-level queue in the annotation processor
* Carry the blank rule on the schema field, for Dag and task queues alike
* Set the queue once per Dag in the e2e native bundle
* Put the blank check on Field and tidy the comments
---------
* Java SDK: Add edge labels to native Dags
Signed-off-by: PoAn Yang <payang@apache.org>
* Apply edge labels in the order they were set
A task edge's own label always won over a group edge's label, and a
relabeled group edge kept its first position, so edge_info differed from
Python's, where the label set last wins. Also note that Python's Label
rewrites an edge when one end is in no task group.
* Java SDK: Write the edge label text before the task
Signed-off-by: PoAn Yang <payang@apache.org>
---------
Signed-off-by: PoAn Yang <payang@apache.org>
Co-authored-by: ZHE YOU LIU <zhu424.dev@gmail.com>
* Java SDK: Trigger another Dag's run from a native Java Dag
A native Java Dag could not start another Dag's run. Airflow's
TriggerDagRunOperator is Python, and a Java bundle has no Python Dag file to
declare one in, so a Java Dag that fans out to another Dag needed a Python
counterpart for that one task.
A `TriggerDagRun` passed to `dag.task` declares a task that has no Java body
to run; the Java runtime runs it as `TriggerDagRunOperator` does. Its
settings are named as Python names the operator's parameters:
```java
dag.task("trigger_downstream",
new TriggerDagRun("downstream_etl")
.config("wait_for_completion", true)
.config("conf", Map.of("rows", 2)));
```
An annotated Dag declares one from an ordinary `@Builder.Task` method that
returns a `TriggerDagRun`. The serialized Dag has to carry what is
triggered, so that method runs when the Dag is built rather than when the
task runs, and therefore takes no parameters.
The task serializes as Python's own `TriggerDagRunOperator`: its template
fields, its UI colour and extra link, and a `dag_dependencies` entry, so the
Airflow UI draws the dependency between the two Dags. Python writes only an
operator's template fields and keeps the rest in the Dag file; a Java Dag
has no such file, so every setting the author made is written too.
The runtime records the triggered run's link and ID as XComs, skips or fails
on a run that already exists, and waits for completion either by polling or,
with `deferrable`, by deferring to the Python triggerer's DagStateTrigger and
resuming from the event it fires. That makes this the first Java runtime to
emit DeferTask and a skipped TaskState.
`scripts/ci/lang_sdk_serialization/test_dags.yaml` now gives the shared
trigger Dag a real logical date instead of a Jinja template, because the SDK
takes one as a date-time. The Go SDK is making the same change in #74417;
whichever lands second drops that one line, and until then the Go
serialization conformance check reports that single difference.
* Java SDK: Point both example triggers at a Dag that triggers nothing
* Java SDK: Say why a switch cannot choose a task that triggers a Dag run
* Java SDK: Snapshot a TriggerDagRun when its task is declared
* Java SDK: Check a TriggerDagRun setting the way every other config key is checked
* Java SDK: Describe what a trigger task pushes and how it names a run
* Java SDK: Correct which runtimes already run trigger tasks
* Java SDK: Format a trigger task's date-times in one place
* Java SDK: Reject a trigger method that throws a checked exception
* Java SDK: Give the trigger fixture a logical date every SDK can write
* Java SDK: Run a trigger task through runTask in tests
* Java SDK: Check a trigger task polls the run it started
* Java SDK: Choose one of several tasks with a branch
A condition picks between two tasks, but a Dag that routes work by size or
by region needs more than two, and splitting that into nested conditions
makes the graph unreadable.
`DagDef.Branch` and `@Builder.Branch` declare a task that chooses one of
the tasks listed with `option(...)`; every other one is skipped. The chosen
task's ID becomes the branch's return value, as it does for Python's branch
operators. A branch chooses exactly one case, so a task that runs after
several of them needs a trigger rule such as
`none_failed_min_one_success`.
Each authoring style names the case in the way that style can type-check. A
`BranchTask` returns the case's own class, so javac checks it; two cases
that share a class are rejected where the second is named, since the branch
could not tell them apart. A `@Builder.Branch` method has no such class to
name -- a task method's implementation is generated -- so it returns a
`TaskId` from the generated `<Dag>Builder.TaskIds`, which holds one
constant per task of the Dag. Either way nothing hard-codes a task id
string, and the generated holder is emitted only for a Dag that declares a
branch.
* Java SDK: Name the multi-way branch Switch, as the other SDKs do
* Java SDK: Name a switch case by its task class in both styles
* Java SDK: Say when a switch rejects a choice and when it fails
* Java SDK: Cover a generated switch that names a task it cannot choose
* Java SDK: Check a switch carries the chosen task's id
* Java SDK: Let a wiring view name a switch's cases in more than one call
* Java SDK: Pick one of two tasks with a condition
A native Java Dag could only run every task it declared: it had no way to
let a task's result decide what runs next, so a Dag that loads only when
there are rows had to be split in two or fall back to a Python stub.
`DagDef.If` and `@Builder.If` declare a task whose boolean names the side
that runs; the other is skipped. The deciding task carries
`_can_skip_downstream`, so Airflow skips a cleared side again rather than
running it, and the SDK writes the `skipmixin_key` XCom before the skip, as
Python's SkipMixin does. It skips only the side not taken, so a task after
both sides needs a trigger rule such as `none_failed_min_one_success`.
`If` is capitalized because `if` is a Java keyword and `@Builder.If` reads
the same way. With no task id given, one is derived from the condition
class's simple name, so `HasRows.class` becomes `hasRows`.
The runtime reaches `SkipDownstreamTasks` through the transport client
only, never through the task-facing `Client`, so a task body cannot skip
tasks the Dag did not declare it may.
* Java SDK: Let a wiring view name a condition's sides in more than one call
* Java SDK: Reject a decider class registered as an ordinary task
* Java SDK: Name a condition's sides Then and Else
* Java SDK: Pin the order a condition skips and records what it skipped
* Java SDK: Drop the unused switch in the condition test's decider
* Java SDK: Record the class that declares each Dag and describe it on request
DagDef remembers the outermost class that built it, and a generated
@Builder.Dag builder names the annotated class instead of itself.
Server accepts --describe-sources <file> to write each Java-declared Dag's
declaring class and return without connecting, for the Gradle plugin.
* Java SDK: Pack each native Dag's source file into the bundle JAR
The packDagSources task runs mainClass in describe mode, finds each Dag's
source file through the class file's SourceFile attribute, and packs each
unique file with a sources.json mapping under META-INF/airflow/. The JAR
manifest names it with Airflow-Java-SDK-Sources.
* Java SDK: Bound the describe run and keep its payload to the bundle JAR
Every `Jar` task gained a dependency on `packDagSources`, so a sources or
javadoc JAR carried the Dag sources and claimed the
`Airflow-Java-SDK-Sources` attribute that the Python side picks a bundle
JAR out of a directory by. Only `jar` and `shadowJar` carry them now.
The describe run had no time bound, so a `main` that does not route
through `Server.create(args)` and starts serving instead held the build
open with no way out. It now runs under a timeout and falls back to
packing the entrypoint's source alone, which is what every other
describe failure already does.
Say in `serve` and `serveAsync` that a `--describe-sources` server
returns without connecting, and record in `sources.json` that its paths
are relative to the source directory, which is also where they sit under
`META-INF/airflow/sources/`.
* Java SDK: Show each Dag's own source and find it outside the package layout
The Java importer now passes the Dag ID to the source lookup, so the Code
view reads dag_source_paths instead of always showing the entrypoint.
The source locator falls back to a unique match on the SourceFile name
when the package does not match the directory, using an index built only
when the package path misses. An unresolvable entrypoint or Dag class is
now logged as a warning.
The describe task is no longer up to date after a failed run, so a
transient failure does not stick until a source changes. Its hint now
points at Server.create(args), which is what answers --describe-sources.
Add a shadowJar test, correct the comment on which JARs carry the sources
payload, and document that a Dag maps to the class that constructed it.
* Java SDK: Use a describe run's output even when the run itself failed
* Java SDK: Serve and describe sources from their own Server classes
* Java SDK: Pack the sources into the one JAR the bundle is built from
* Java SDK: Attach the plugin's documentation to the plugin class
* Java SDK: Drop the duplicated classes dir from the describe classpath
* Java SDK: Let a bundle set how long the describe run may take
* Java SDK: Serialize native Dags to DagSerialization v3 on parse requests
A Java-authored Dag could not reach the scheduler on its own: the runtime
answered task-execution requests only, so a Python stub file still had to
exist purely to describe the Dag's structure. With dependency edges and
schema-keyed configuration now recorded on the Java Dag model, the runtime
has everything it needs to answer the coordinator's DagFileParseRequest the
same way the Go SDK does, and the nativedag examples become real schedulable
Dags with no Python counterpart.
Native Java tasks deliberately emit no _arg_bindings: the execution API
delivers bindings only for Python _StubOperator tasks, and a Java task
always runs inside the JVM bundle that already holds its wired inputs, so
the runtime resolves them locally.
Cron schedules map to CronTriggerTimetable only, mirroring the Go SDK until
the supervisor forwards the [scheduler] timetable flags over the coordinator
protocol (see the TODO at the timetable serializer).
* Test that the conformance check compares Dag params
* Java SDK: Leave config-backed Dag fields for Airflow to fill in
* Java SDK: Leave out the email flags a Java task cannot act on
* Java SDK: Serialize a native Dag's task groups
* Java SDK: Write each Dag tag once, as Python does
* Java SDK: Check native Dag serialization against Airflow's
* Java SDK: Run the serialization conformance check on every file that steers it
`Bundle.register` expands the group edges, `Refs` decides which group each
task lands in, and `sdk/build.gradle.kts` generates the schema fields the
serializer writes from. All three change the serialized output, so add
them to the hook's trigger set.
Report a failed classpath build with the Gradle output instead of an
`IndexError` on an empty line list or a bare `CalledProcessError`.
* Java SDK: Build a native Dag's timetable the way Python does
Expand a cron preset before writing it, so `@daily` serializes as
`0 0 * * *` and the Dag hashes the same as the Python one. Reject a
schedule that is neither a preset nor a cron expression where the Dag is
written, rather than letting it reach a scheduler that cannot build a
timetable from it.
Take the timezone from the Dag's start date, as Python's `DAG.timezone`
does, instead of always writing UTC: a Dag started at a non-UTC offset
now fires at that offset rather than at the same wall clock in UTC.
* Java SDK: Carry a native Dag's call arguments as argument bindings
A native Dag's serialized form recorded its task edges but nothing about
what each task was called with, so changing a literal argument left the
Dag byte-identical: no new version, and nothing in the version diff.
Write the same `is_stub` flag and `_arg_bindings` spec the TypeScript SDK
writes, as ADR-0007 decision G says a natively authored Dag should. The
wiring view now passes its parameter names along with the arguments, so
each binding can name the parameter it feeds.
A Java task still resolves its arguments from the Dag in its own bundle
rather than reading the spec back: the bundle that runs the task also
holds the call that wired it, so the values never have to travel, and a
`TaskInput` keeps binding as one whole input. The spec is what Airflow
records and shows.
Since the spec travels as JSON, a literal with no JSON form is now
rejected where the Dag is parsed instead of reaching a task that cannot
receive it.
* Java SDK: Keep one unserializable Dag from failing a whole bundle's parse
A Dag that could not be serialized threw out of the parse response, so
every other Dag in the same JAR vanished with it and `import_errors` was
never filled. Report the failure under the bundle-relative path the way
the TypeScript SDK does, naming the Dag, and serialize the rest.
* Java SDK: Mark the native Dag capabilities as shipping in 3.4
`native-dag-authoring`, `task-args`, `taskflow-dependencies` and
`task-group` are new in this release, not in 3.3, which is what the
matrix's "supported since" column says.
* Java SDK: Accept every cron schedule croniter does and bind wired inputs first
The cron shape check now accepts comma lists of names, month and weekday
names, the `#`, `L` and `W` qualifiers and the `@midnight` and `@annually`
aliases, which Python stores unexpanded. Each of these previously turned
the Dag into an import error. The schema-default comment records why
explicit default values are dropped, and the timezone TODO and the Java
docs note that a cron Dag with no start date is scheduled in UTC.
A wired input wins over a runtime binding in ArgValues. The Java docs and
ADR 0007 now say so, and a test pins it.
The conformance run now passes `--supports literal_inputs` and the Java
serializer wires each task's upstream handles and literals as call
arguments, so the run exercises `_arg_bindings`. The hook's file filter
covers `internal/Fields.kt`. Selective checks skip the hook unless a
java-sdk file, Airflow's serializer or schema, or the shared harness
changed, through a new file group because serializer changes do not force
full tests.
* Java SDK: Group a native Dag's tasks with task groups
* Java SDK: Reserve the whole group view surface and pin group edge order
The reserved names of a group's wiring view are now read from Deps.TaskGroup, so
endpoints, before and after are rejected as task method names inside a group, not
only groupId and nodes. A task named before would otherwise win overload
resolution over the inherited before(Flow...) and silently register a task.
Add tests for that clash, for duplicate group IDs in one scope, and for the order
group edges resolve in: an empty group prefers an earlier edge over its parent,
and edges resolve in the order they were drawn.
Correct the Task groups docs and TaskGroupRef KDoc: only what a group holds is
read once, while edges still resolve in drawing order. Restore the missing
transform, load and audit calls in the group wiring example so it parses.
* Java SDK: Declare a Dag's task graph with @Builder.Deps
An annotated Dag class could name its tasks but not say how they connect,
so a Dag whose annotations carried everything else still needed a Python
Dag file for its graph. Declaring the graph by calling the tasks lets
javac check that each task is fed something its parameter accepts.
Bundle.register(Class) now also takes the @Builder.Dag class itself and
registers the Dag its generated builder builds, so there is still only one
name to keep in sync.
* Java SDK: Quote wired task ids as Java string literals
* Java SDK: Validate the @Builder.Deps class at compile time
* Java SDK: Reject task method names that clash with the wiring view
* Java SDK: Type a wired numeric input by its parameter's own type
* Java SDK: Register both the Dag and handlers of a class, unwrapping builder failures
* Java SDK: Reject a raw null wiring argument and test the recorder's guards
* Java SDK: Reword the native-Dag docs without em-dashes
* Java SDK: Drop Bundle tests that repeat existing coverage
* Java SDK: Require a @Builder.Deps class on every @Builder.Dag class
* Java SDK: Back the k8s test's stub tasks with task handlers
* Java SDK: Reject overloaded task and task-handler methods
* Java SDK: Fix the Dag examples a required wiring class invalidates
* Java SDK: Resolve a task's arguments from the Dag's own wiring
A Dag authored in Java has no Python call site, so the supervisor sends no
argument bindings for it and a task's data parameters had nothing to
resolve against. Where the Dag wired inputs for a task, those stand in;
a stub-backed task keeps reading its bindings, including when the call
site bound none.
The authoring surface that records those inputs lands in the next commit,
so nothing declares them yet.
* Keep taskDef out of Context's constructor and reuse resolveWiredAll
* Use ADR-0007 wording for the wired-arity warning
* Java SDK: Describe native Java Dags without reference to Python
A Dag authored entirely in Java has no Python in the picture, so teaching
its edge verbs as "Java's spelling of >> and <<" asks the reader to know a
language the feature does not involve. The mixed-language surface keeps its
Python references, because there the Python Dag file is part of what the
reader has to understand.
* Java SDK: Generate Dag and task configuration from the serialization schema
A Java-authored Dag could carry no schedule, retries, tags or any other
Airflow setting, so it could be defined but not configured. Hand-listing
those settings in Java would drift from the Python semantics they mirror,
so they are recorded and validated against Airflow's own Dag serialization
schema instead, and take effect once the runtime answers parse requests.
The `Builder` annotations are generated from a copy of that schema vendored
at java-sdk/sdk/schema/dag-schema.json, so a source release builds without
the monorepo; a prek hook keeps the copy in sync.
* Java SDK: Register tasks as first-class TaskDef objects
`dag.addTask("extract", Extract.class)` stored tasks as a plain
`Map<String, Class<out Task>>`, which leaves nowhere to hang anything
else a task needs: dependency edges, task-level configuration, and
argument wiring all have to attach to a per-task object, and a map of
classes cannot carry them. Introducing that object now keeps those
follow-ups additive instead of forcing another break of the registration
API later.
The annotation surface keeps `Builder.Dag` / `Builder.Task`, and the
interface users implement keeps the `Task` name, so the definition
objects are `DagDef` and `TaskDef` -- a pairing that stays unambiguous
next to `Task` at a use site. The SDK is pre-1.0, so the old
string-keyed overload is removed outright rather than deprecated.
The KubernetesExecutor lang-SDK example adopts the new names directly rather
than pinning to the old ones: CI now builds those artifacts from the branch
under test (#71527), so the example no longer has to compile against whatever
the SDK on main happens to expose.
* Java SDK: Clarify task ownership validation
* Java SDK: Simplify manual task registration
Manual interface-based bundles are authored directly by users, so requiring every call to wrap the task class in TaskDef adds noise to the common case while the SDK can retain first-class task definitions internally.
* Fix Java SDK numeric XCom casting
Generate accessors that widen through Number instead: primitive params use
((Number) x).intValue(), and boxed params use Optional.ofNullable(...).orElse(null)
so an absent XCom stays null. Add a java_xcom_casting_example DAG and processor
tests covering int->long->double widening and an absent boxed value.
Signed-off-by: PoAn Yang <payang@apache.org>
* Remove unused key field from Java SDK Builder.XCom annotation
Signed-off-by: PoAn Yang <payang@apache.org>
* Add float cross-type coverage to Java SDK XCom casting tests
Signed-off-by: PoAn Yang <payang@apache.org>
* Remove unused comment
Signed-off-by: PoAn Yang <payang@apache.org>
---------
Signed-off-by: PoAn Yang <payang@apache.org>
Jason(Zhe-You) Liu
PoAn Yang
Tzu-ping Chung