These checks build and run each SDK's serializer, so as prek hooks they needed a full
Go, Java or Node toolchain and took minutes on every commit touching Airflow's
serializer. They are tests, not static checks, so they now run as a CI test job that
sets up only the toolchain of the SDK it checks, for the SDKs whose inputs changed.
* Java SDK: Rewrite the user docs around Dag definition
Reorder the Java SDK guide to start from a Dag defined in Java, document
conditions, switches and TriggerDagRun, and add a table of how stub task
arguments bind. Split the README into a user landing page and
DEVELOPMENT.md, and add an example README.
* Add Logback and appender to the docs spelling wordlist
* Address review: Dag-level queue, version sync, dropped constraints
Set the queue once on the Dag in every example, now that a Java Dag takes
one, and bump the documented version to 1.0.0-beta2 everywhere. Add a prek
hook that fails when the guide, the README and the Dokka landing page name
different versions. Restore the TaskInput constraints, correct the
LocalExecutor wording, and drop the Python Label comparison.
* Generate the quick start of the Java SDK README and Dokka page
The quick start appears on three pages. The guide owns it now, between
SHARED SNIPPET markers, and the sync-java-sdk-docs hook copies it into the
other two and still checks that all three install the same version.
* Address review: install a version placeholder, not a release
The three pages that show how to install the SDK pinned a release that is
not out yet, which also held the PR back. They now install `<version>` and
link to Maven Central, and the sync hook fails when a page names a release
instead. The parse-failure bullet leads with the SDK release a JAR was built
with, and keeps the supervisor schema version as the explanation.
---------
* 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: 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.
Pierre Jeambrun
Jason(Zhe-You) Liu
PoAn YangandZHE YOU LIU
Tzu-ping Chung