use of org.apache.beam.sdk.transforms.windowing.GlobalWindows in project beam by apache.
the class RepeatedlyStateMachineTest method testRepeatedlyProcessingTime.
@Test
public void testRepeatedlyProcessingTime() throws Exception {
SimpleTriggerStateMachineTester<GlobalWindow> tester = TriggerStateMachineTester.forTrigger(RepeatedlyStateMachine.forever(AfterProcessingTimeStateMachine.pastFirstElementInPane().plusDelayOf(Duration.standardMinutes(15))), new GlobalWindows());
GlobalWindow window = GlobalWindow.INSTANCE;
tester.injectElements(1);
assertFalse(tester.shouldFire(window));
tester.advanceProcessingTime(new Instant(0).plus(Duration.standardMinutes(15)));
assertTrue(tester.shouldFire(window));
tester.fireIfShouldFire(window);
assertFalse(tester.shouldFire(window));
}
use of org.apache.beam.sdk.transforms.windowing.GlobalWindows in project beam by apache.
the class CombineTest method testGlobalCombineWithDefaultsAndTriggers.
@Test
@Category(ValidatesRunner.class)
public void testGlobalCombineWithDefaultsAndTriggers() {
PCollection<Integer> input = pipeline.apply(Create.of(1, 1));
PCollection<String> output = input.apply(Window.<Integer>into(new GlobalWindows()).triggering(Repeatedly.forever(AfterPane.elementCountAtLeast(1))).accumulatingFiredPanes().withAllowedLateness(new Duration(0))).apply(Sum.integersGlobally()).apply(ParDo.of(new FormatPaneInfo()));
// The actual elements produced are nondeterministic. Could be one, could be two.
// But it should certainly have a final element with the correct final sum.
PAssert.that(output).satisfies(new SerializableFunction<Iterable<String>, Void>() {
@Override
public Void apply(Iterable<String> input) {
assertThat(input, hasItem("2: true"));
return null;
}
});
pipeline.run();
}
use of org.apache.beam.sdk.transforms.windowing.GlobalWindows in project beam by apache.
the class PTransformMatchersTest method classEqualToDoesNotMatchUnrelatedClass.
@Test
public void classEqualToDoesNotMatchUnrelatedClass() {
PTransformMatcher matcher = PTransformMatchers.classEqualTo(ParDo.SingleOutput.class);
AppliedPTransform<?, ?, ?> application = getAppliedTransform(Window.<KV<String, Integer>>into(new GlobalWindows()));
assertThat(matcher.matches(application), is(false));
}
use of org.apache.beam.sdk.transforms.windowing.GlobalWindows in project beam by apache.
the class WriteFiles method createWrite.
/**
* A write is performed as sequence of three {@link ParDo}'s.
*
* <p>This singleton collection containing the WriteOperation is then used as a side
* input to a ParDo over the PCollection of elements to write. In this bundle-writing phase,
* {@link WriteOperation#createWriter} is called to obtain a {@link Writer}.
* {@link Writer#open} and {@link Writer#close} are called in
* {@link DoFn.StartBundle} and {@link DoFn.FinishBundle}, respectively, and
* {@link Writer#write} method is called for every element in the bundle. The output
* of this ParDo is a PCollection of <i>writer result</i> objects (see {@link FileBasedSink}
* for a description of writer results)-one for each bundle.
*
* <p>The final do-once ParDo uses a singleton collection asinput and the collection of writer
* results as a side-input. In this ParDo, {@link WriteOperation#finalize} is called
* to finalize the write.
*
* <p>If the write of any element in the PCollection fails, {@link Writer#close} will be
* called before the exception that caused the write to fail is propagated and the write result
* will be discarded.
*
* <p>Since the {@link WriteOperation} is serialized after the initialization ParDo and
* deserialized in the bundle-writing and finalization phases, any state change to the
* WriteOperation object that occurs during initialization is visible in the latter
* phases. However, the WriteOperation is not serialized after the bundle-writing
* phase. This is why implementations should guarantee that
* {@link WriteOperation#createWriter} does not mutate WriteOperation).
*/
private PDone createWrite(PCollection<T> input) {
Pipeline p = input.getPipeline();
if (!windowedWrites) {
// Re-window the data into the global window and remove any existing triggers.
input = input.apply(Window.<T>into(new GlobalWindows()).triggering(DefaultTrigger.of()).discardingFiredPanes());
}
// Perform the per-bundle writes as a ParDo on the input PCollection (with the
// WriteOperation as a side input) and collect the results of the writes in a
// PCollection. There is a dependency between this ParDo and the first (the
// WriteOperation PCollection as a side input), so this will happen after the
// initial ParDo.
PCollection<FileResult> results;
final PCollectionView<Integer> numShardsView;
Coder<BoundedWindow> shardedWindowCoder = (Coder<BoundedWindow>) input.getWindowingStrategy().getWindowFn().windowCoder();
if (computeNumShards == null && numShardsProvider == null) {
numShardsView = null;
results = input.apply("WriteBundles", ParDo.of(windowedWrites ? new WriteWindowedBundles() : new WriteUnwindowedBundles()));
} else {
List<PCollectionView<?>> sideInputs = Lists.newArrayList();
if (computeNumShards != null) {
numShardsView = input.apply(computeNumShards);
sideInputs.add(numShardsView);
} else {
numShardsView = null;
}
PCollection<KV<Integer, Iterable<T>>> sharded = input.apply("ApplyShardLabel", ParDo.of(new ApplyShardingKey<T>(numShardsView, (numShardsView != null) ? null : numShardsProvider)).withSideInputs(sideInputs)).apply("GroupIntoShards", GroupByKey.<Integer, T>create());
shardedWindowCoder = (Coder<BoundedWindow>) sharded.getWindowingStrategy().getWindowFn().windowCoder();
results = sharded.apply("WriteShardedBundles", ParDo.of(new WriteShardedBundles()));
}
results.setCoder(FileResultCoder.of(shardedWindowCoder));
if (windowedWrites) {
// When processing streaming windowed writes, results will arrive multiple times. This
// means we can't share the below implementation that turns the results into a side input,
// as new data arriving into a side input does not trigger the listening DoFn. Instead
// we aggregate the result set using a singleton GroupByKey, so the DoFn will be triggered
// whenever new data arrives.
PCollection<KV<Void, FileResult>> keyedResults = results.apply("AttachSingletonKey", WithKeys.<Void, FileResult>of((Void) null));
keyedResults.setCoder(KvCoder.of(VoidCoder.of(), FileResultCoder.of(shardedWindowCoder)));
// Is the continuation trigger sufficient?
keyedResults.apply("FinalizeGroupByKey", GroupByKey.<Void, FileResult>create()).apply("Finalize", ParDo.of(new DoFn<KV<Void, Iterable<FileResult>>, Integer>() {
@ProcessElement
public void processElement(ProcessContext c) throws Exception {
LOG.info("Finalizing write operation {}.", writeOperation);
List<FileResult> results = Lists.newArrayList(c.element().getValue());
writeOperation.finalize(results);
LOG.debug("Done finalizing write operation");
}
}));
} else {
final PCollectionView<Iterable<FileResult>> resultsView = results.apply(View.<FileResult>asIterable());
ImmutableList.Builder<PCollectionView<?>> sideInputs = ImmutableList.<PCollectionView<?>>builder().add(resultsView);
if (numShardsView != null) {
sideInputs.add(numShardsView);
}
// Finalize the write in another do-once ParDo on the singleton collection containing the
// Writer. The results from the per-bundle writes are given as an Iterable side input.
// The WriteOperation's state is the same as after its initialization in the first
// do-once ParDo. There is a dependency between this ParDo and the parallel write (the writer
// results collection as a side input), so it will happen after the parallel write.
// For the non-windowed case, we guarantee that if no data is written but the user has
// set numShards, then all shards will be written out as empty files. For this reason we
// use a side input here.
PCollection<Void> singletonCollection = p.apply(Create.of((Void) null));
singletonCollection.apply("Finalize", ParDo.of(new DoFn<Void, Integer>() {
@ProcessElement
public void processElement(ProcessContext c) throws Exception {
LOG.info("Finalizing write operation {}.", writeOperation);
List<FileResult> results = Lists.newArrayList(c.sideInput(resultsView));
LOG.debug("Side input initialized to finalize write operation {}.", writeOperation);
// We must always output at least 1 shard, and honor user-specified numShards if
// set.
int minShardsNeeded;
if (numShardsView != null) {
minShardsNeeded = c.sideInput(numShardsView);
} else if (numShardsProvider != null) {
minShardsNeeded = numShardsProvider.get();
} else {
minShardsNeeded = 1;
}
int extraShardsNeeded = minShardsNeeded - results.size();
if (extraShardsNeeded > 0) {
LOG.info("Creating {} empty output shards in addition to {} written for a total of {}.", extraShardsNeeded, results.size(), minShardsNeeded);
for (int i = 0; i < extraShardsNeeded; ++i) {
Writer<T> writer = writeOperation.createWriter();
writer.openUnwindowed(UUID.randomUUID().toString(), UNKNOWN_SHARDNUM);
FileResult emptyWrite = writer.close();
results.add(emptyWrite);
}
LOG.debug("Done creating extra shards.");
}
writeOperation.finalize(results);
LOG.debug("Done finalizing write operation {}", writeOperation);
}
}).withSideInputs(sideInputs.build()));
}
return PDone.in(input.getPipeline());
}
use of org.apache.beam.sdk.transforms.windowing.GlobalWindows in project beam by apache.
the class SimpleDoFnRunnerTest method testOnTimerExceptionsWrappedAsUserCodeException.
@Test
public void testOnTimerExceptionsWrappedAsUserCodeException() {
ThrowingDoFn fn = new ThrowingDoFn();
DoFnRunner<String, String> runner = new SimpleDoFnRunner<>(null, fn, NullSideInputReader.empty(), null, null, Collections.<TupleTag<?>>emptyList(), mockStepContext, WindowingStrategy.of(new GlobalWindows()));
thrown.expect(UserCodeException.class);
thrown.expectCause(is(fn.exceptionToThrow));
runner.onTimer(ThrowingDoFn.TIMER_ID, GlobalWindow.INSTANCE, new Instant(0), TimeDomain.EVENT_TIME);
}
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