Examples with FlatMap org.apache.beam.sdk.extensions.euphoria.core.client.operator.FlatMap used on opensource projects

Example 1 with FlatMap

use of org.apache.beam.sdk.extensions.euphoria.core.client.operator.FlatMap in project beam by apache.

the class DocumentationExamplesTest method wordCountExample.

@Ignore("We do not want to actually write output files from this test.")
@Test
public void wordCountExample() {
    final PipelineOptions options = PipelineOptionsFactory.create();
    Pipeline pipeline = Pipeline.create(options);
    // Use Kryo as coder fallback
    KryoCoderProvider.of().registerTo(pipeline);
    // Source of data loaded from Beam IO.
    PCollection<String> lines = pipeline.apply(Create.of(textLineByLine)).setTypeDescriptor(TypeDescriptor.of(String.class));
    // FlatMap processes one input element at a time and allows user code to emit
    // zero, one, or more output elements. From input lines we will get data set of words.
    PCollection<String> words = FlatMap.named("TOKENIZER").of(lines).using((String line, Collector<String> context) -> {
        for (String word : Splitter.onPattern("\\s+").split(line)) {
            context.collect(word);
        }
    }).output();
    // Now we can count input words - the operator ensures that all values for the same
    // key (word in this case) end up being processed together. Then it counts number of appearances
    // of the same key in 'words' dataset and emits it to output.
    PCollection<KV<String, Long>> counted = CountByKey.named("COUNT").of(words).keyBy(w -> w).output();
    // Format output.
    PCollection<String> output = MapElements.named("FORMAT").of(counted).using(p -> p.getKey() + ": " + p.getValue()).output();
    // Now we can again use Beam transformation. In this case we save words and their count
    // into the text file.
    output.apply(TextIO.write().to("counted_words"));
    pipeline.run();
}