Examples with HASH_CODE com.hazelcast.jet.core.Partitioner.HASH_CODE used on opensource projects

Example 1 with HASH_CODE

use of com.hazelcast.jet.core.Partitioner.HASH_CODE in project hazelcast-jet-reference-manual by hazelcast.

the class TfIdfCoreApi method createDag.

private static DAG createDag() {
    DistributedFunction<Entry<Entry<?, String>, ?>, String> byWord = item -> item.getKey().getValue();
    DistributedBiFunction<Long, Object, Long> counter = (count, x) -> count + 1;
    DAG dag = new DAG();
    Vertex stopwordSource = // tag::s2[]
    dag.newVertex("stopword-source", StopwordsP::new);
    // end::s2[]
    Vertex docSource = // tag::s1[]
    dag.newVertex("doc-source", readMapP(DOCID_NAME));
    // end::s1[]
    Vertex docCount = // tag::s4[]
    dag.newVertex("doc-count", Processors.aggregateP(counting()));
    // end::s4[]
    // tag::s5[]
    Vertex docLines = dag.newVertex("doc-lines", nonCooperativeP(flatMapP((Entry<Long, String> e) -> traverseStream(docLines("books/" + e.getValue()).map(line -> entry(e.getKey(), line))))));
    // end::s5[]
    Vertex tokenize = // tag::s6[]
    dag.newVertex("tokenize", TokenizeP::new);
    // end::s6[]
    Vertex tf = // tag::s9[]
    dag.newVertex("tf", aggregateByKeyP(singletonList(wholeItem()), counting(), Util::entry));
    // end::s9[]
    Vertex tfidf = // tag::s10[]
    dag.newVertex("tf-idf", TfIdfP::new);
    // end::s10[]
    Vertex sink = // tag::s12[]
    dag.newVertex("sink", SinkProcessors.writeMapP(INVERTED_INDEX));
    // end::s12[]
    stopwordSource.localParallelism(1);
    docSource.localParallelism(1);
    docCount.localParallelism(1);
    docLines.localParallelism(1);
    // tag::s8[]
    dag.edge(between(stopwordSource, tokenize).broadcast().priority(-1)).edge(from(docLines).to(tokenize, 1));
    return dag.edge(between(docSource, docCount).distributed().broadcast()).edge(from(docSource, 1).to(docLines)).edge(between(tokenize, tf).partitioned(wholeItem(), HASH_CODE)).edge(between(docCount, tfidf).broadcast().priority(-1)).edge(from(tf).to(tfidf, 1).distributed().partitioned(byWord, HASH_CODE)).edge(between(tfidf, sink));
}