Examples with EventJournalMapEvent com.hazelcast.map.EventJournalMapEvent used on opensource projects

Example 1 with EventJournalMapEvent

use of com.hazelcast.map.EventJournalMapEvent in project hazelcast by hazelcast.

the class AsyncTransformUsingServiceBatchP_IntegrationTest method test_pipelineApi_mapNotPartitioned.

@Test
public void test_pipelineApi_mapNotPartitioned() {
    Pipeline p = Pipeline.create();
    p.readFrom(Sources.mapJournal(journaledMap, START_FROM_OLDEST, EventJournalMapEvent::getNewValue, alwaysTrue())).withoutTimestamps().mapUsingServiceAsyncBatched(serviceFactory, 128, transformNotPartitionedFn(i -> i + "-1")).setLocalParallelism(2).writeTo(Sinks.list(sinkList));
    instance().getJet().newJob(p, jobConfig);
    assertResult(i -> Stream.of(i + "-1"), NUM_ITEMS);
}

Example 2 with EventJournalMapEvent

use of com.hazelcast.map.EventJournalMapEvent in project hazelcast by hazelcast.

the class AsyncTransformUsingServiceBatchP_IntegrationTest method stressTestInt.

private void stressTestInt(boolean restart) {
    /*
        This is a stress test of the cooperative emission using the DAG api. Only through DAG
        API we can configure edge queue sizes, which we use to cause more trouble for the
        cooperative emission.
         */
    // add more input to the source map
    int numItems = 10_000;
    journaledMap.putAll(IntStream.range(NUM_ITEMS, numItems).boxed().collect(toMap(i -> i, i -> i)));
    DAG dag = new DAG();
    Vertex source = dag.newVertex("source", throttle(streamMapP(journaledMap.getName(), alwaysTrue(), EventJournalMapEvent::getNewValue, START_FROM_OLDEST, eventTimePolicy(i -> (long) ((Integer) i), WatermarkPolicy.limitingLag(10), 10, 0, 0)), 5000));
    BiFunctionEx<ExecutorService, List<Integer>, CompletableFuture<Traverser<String>>> flatMapAsyncFn = transformNotPartitionedFn(i -> traverseItems(i + "-1", i + "-2", i + "-3", i + "-4", i + "-5")).andThen(r -> r.thenApply(results -> traverseIterable(results).flatMap(Function.identity())));
    ProcessorSupplier processorSupplier = AsyncTransformUsingServiceBatchedP.supplier(serviceFactory, DEFAULT_MAX_CONCURRENT_OPS, 128, flatMapAsyncFn);
    Vertex map = dag.newVertex("map", processorSupplier).localParallelism(2);
    Vertex sink = dag.newVertex("sink", SinkProcessors.writeListP(sinkList.getName()));
    // Use a shorter queue to not block the barrier from the source for too long due to
    // the backpressure from the slow mapper
    EdgeConfig edgeToMapperConfig = new EdgeConfig().setQueueSize(128);
    // Use a shorter queue on output from the mapper so that we experience backpressure
    // from the sink
    EdgeConfig edgeFromMapperConfig = new EdgeConfig().setQueueSize(10);
    dag.edge(between(source, map).setConfig(edgeToMapperConfig)).edge(between(map, sink).setConfig(edgeFromMapperConfig));
    Job job = instance().getJet().newJob(dag, jobConfig);
    for (int i = 0; restart && i < 5; i++) {
        assertNotNull(job);
        assertTrueEventually(() -> {
            JobStatus status = job.getStatus();
            assertTrue("status=" + status, status == RUNNING || status == COMPLETED);
        });
        sleepMillis(100);
        try {
            job.restart();
        } catch (IllegalStateException e) {
            assertTrue(e.toString(), e.getMessage().startsWith("Cannot RESTART_GRACEFUL"));
            break;
        }
    }
    assertResult(i -> Stream.of(i + "-1", i + "-2", i + "-3", i + "-4", i + "-5"), numItems);
}

Example 3 with EventJournalMapEvent

use of com.hazelcast.map.EventJournalMapEvent in project hazelcast by hazelcast.

the class AsyncTransformUsingServiceP_IntegrationTest method test_pipelineApi_mapPartitioned.

@Test
public void test_pipelineApi_mapPartitioned() {
    Pipeline p = Pipeline.create();
    p.readFrom(Sources.mapJournal(journaledMap, START_FROM_OLDEST, EventJournalMapEvent::getNewValue, alwaysTrue())).withoutTimestamps().groupingKey(i -> i % 10).mapUsingServiceAsync(serviceFactory, transformPartitionedFn(i -> i + "-1")).setLocalParallelism(2).writeTo(Sinks.list(sinkList));
    instance().getJet().newJob(p, jobConfig);
    assertResultEventually(i -> Stream.of(i + "-1"), NUM_ITEMS);
}

Example 4 with EventJournalMapEvent

use of com.hazelcast.map.EventJournalMapEvent in project hazelcast by hazelcast.

the class AsyncTransformUsingServiceP_IntegrationTest method test_pipelineApi_mapNotPartitioned.

@Test
public void test_pipelineApi_mapNotPartitioned() {
    Pipeline p = Pipeline.create();
    p.readFrom(Sources.mapJournal(journaledMap, START_FROM_OLDEST, EventJournalMapEvent::getNewValue, alwaysTrue())).withoutTimestamps().mapUsingServiceAsync(serviceFactory, transformNotPartitionedFn(i -> i + "-1")).setLocalParallelism(2).writeTo(Sinks.list(sinkList));
    instance().getJet().newJob(p, jobConfig);
    assertResultEventually(i -> Stream.of(i + "-1"), NUM_ITEMS);
}

Example 5 with EventJournalMapEvent

use of com.hazelcast.map.EventJournalMapEvent in project hazelcast by hazelcast.

the class AsyncTransformUsingServiceP_IntegrationTest method stressTestInt.

private void stressTestInt(boolean restart) {
    /*
        This is a stress test of the cooperative emission using the DAG api. Only through DAG
        API we can configure edge queue sizes, which we use to cause more trouble for the
        cooperative emission.
         */
    // add more input to the source map
    int numItems = 10_000;
    journaledMap.putAll(IntStream.range(NUM_ITEMS, numItems).boxed().collect(toMap(i -> i, i -> i)));
    DAG dag = new DAG();
    Vertex source = dag.newVertex("source", throttle(streamMapP(journaledMap.getName(), alwaysTrue(), EventJournalMapEvent::getNewValue, START_FROM_OLDEST, eventTimePolicy(i -> (long) ((Integer) i), WatermarkPolicy.limitingLag(10), 10, 0, 0)), 5000));
    BiFunctionEx<ExecutorService, Integer, CompletableFuture<Traverser<String>>> flatMapAsyncFn = transformNotPartitionedFn(i -> traverseItems(i + "-1", i + "-2", i + "-3", i + "-4", i + "-5"));
    ProcessorSupplier processorSupplier = ordered ? AsyncTransformUsingServiceOrderedP.supplier(serviceFactory, DEFAULT_MAX_CONCURRENT_OPS, flatMapAsyncFn) : AsyncTransformUsingServiceUnorderedP.supplier(serviceFactory, DEFAULT_MAX_CONCURRENT_OPS, flatMapAsyncFn, identity());
    Vertex map = dag.newVertex("map", processorSupplier).localParallelism(2);
    Vertex sink = dag.newVertex("sink", SinkProcessors.writeListP(sinkList.getName()));
    // Use a shorter queue to not block the barrier from the source for too long due to
    // the backpressure from the slow mapper
    EdgeConfig edgeToMapperConfig = new EdgeConfig().setQueueSize(128);
    // Use a shorter queue on output from the mapper so that we experience backpressure
    // from the sink
    EdgeConfig edgeFromMapperConfig = new EdgeConfig().setQueueSize(10);
    dag.edge(between(source, map).setConfig(edgeToMapperConfig)).edge(between(map, sink).setConfig(edgeFromMapperConfig));
    Job job = instance().getJet().newJob(dag, jobConfig);
    for (int i = 0; restart && i < 5; i++) {
        assertJobStatusEventually(job, RUNNING);
        sleepMillis(100);
        job.restart();
    }
    assertResultEventually(i -> Stream.of(i + "-1", i + "-2", i + "-3", i + "-4", i + "-5"), numItems);
}