/** Creates a Flink program that uses the specified spouts and bolts. */
private void translateTopology() {
unprocessdInputsPerBolt.clear();
outputStreams.clear();
declarers.clear();
availableInputs.clear();
// Storm defaults to parallelism 1
env.setParallelism(1);
/* Translation of topology */
for (final Entry<String, IRichSpout> spout : spouts.entrySet()) {
final String spoutId = spout.getKey();
final IRichSpout userSpout = spout.getValue();
final FlinkOutputFieldsDeclarer declarer = new FlinkOutputFieldsDeclarer();
userSpout.declareOutputFields(declarer);
final HashMap<String, Fields> sourceStreams = declarer.outputStreams;
this.outputStreams.put(spoutId, sourceStreams);
declarers.put(spoutId, declarer);
final HashMap<String, DataStream<Tuple>> outputStreams =
new HashMap<String, DataStream<Tuple>>();
final DataStreamSource<?> source;
if (sourceStreams.size() == 1) {
final SpoutWrapper<Tuple> spoutWrapperSingleOutput =
new SpoutWrapper<Tuple>(userSpout, spoutId, null, null);
spoutWrapperSingleOutput.setStormTopology(stormTopology);
final String outputStreamId = (String) sourceStreams.keySet().toArray()[0];
DataStreamSource<Tuple> src =
env.addSource(
spoutWrapperSingleOutput, spoutId, declarer.getOutputType(outputStreamId));
outputStreams.put(outputStreamId, src);
source = src;
} else {
final SpoutWrapper<SplitStreamType<Tuple>> spoutWrapperMultipleOutputs =
new SpoutWrapper<SplitStreamType<Tuple>>(userSpout, spoutId, null, null);
spoutWrapperMultipleOutputs.setStormTopology(stormTopology);
@SuppressWarnings({"unchecked", "rawtypes"})
DataStreamSource<SplitStreamType<Tuple>> multiSource =
env.addSource(
spoutWrapperMultipleOutputs,
spoutId,
(TypeInformation) TypeExtractor.getForClass(SplitStreamType.class));
SplitStream<SplitStreamType<Tuple>> splitSource =
multiSource.split(new StormStreamSelector<Tuple>());
for (String streamId : sourceStreams.keySet()) {
SingleOutputStreamOperator<Tuple, ?> outStream =
splitSource.select(streamId).map(new SplitStreamMapper<Tuple>());
outStream.getTransformation().setOutputType(declarer.getOutputType(streamId));
outputStreams.put(streamId, outStream);
}
source = multiSource;
}
availableInputs.put(spoutId, outputStreams);
final ComponentCommon common = stormTopology.get_spouts().get(spoutId).get_common();
if (common.is_set_parallelism_hint()) {
int dop = common.get_parallelism_hint();
source.setParallelism(dop);
} else {
common.set_parallelism_hint(1);
}
}
/**
* 1. Connect all spout streams with bolts streams 2. Then proceed with the bolts stream already
* connected
*
* <p>Because we do not know the order in which an iterator steps over a set, we might process a
* consumer before its producer ->thus, we might need to repeat multiple times
*/
boolean makeProgress = true;
while (bolts.size() > 0) {
if (!makeProgress) {
StringBuilder strBld = new StringBuilder();
strBld.append("Unable to build Topology. Could not connect the following bolts:");
for (String boltId : bolts.keySet()) {
strBld.append("\n ");
strBld.append(boltId);
strBld.append(": missing input streams [");
for (Entry<GlobalStreamId, Grouping> streams : unprocessdInputsPerBolt.get(boltId)) {
strBld.append("'");
strBld.append(streams.getKey().get_streamId());
strBld.append("' from '");
strBld.append(streams.getKey().get_componentId());
strBld.append("'; ");
}
strBld.append("]");
}
throw new RuntimeException(strBld.toString());
}
makeProgress = false;
final Iterator<Entry<String, IRichBolt>> boltsIterator = bolts.entrySet().iterator();
while (boltsIterator.hasNext()) {
final Entry<String, IRichBolt> bolt = boltsIterator.next();
final String boltId = bolt.getKey();
final IRichBolt userBolt = copyObject(bolt.getValue());
final ComponentCommon common = stormTopology.get_bolts().get(boltId).get_common();
Set<Entry<GlobalStreamId, Grouping>> unprocessedBoltInputs =
unprocessdInputsPerBolt.get(boltId);
if (unprocessedBoltInputs == null) {
unprocessedBoltInputs = new HashSet<>();
unprocessedBoltInputs.addAll(common.get_inputs().entrySet());
unprocessdInputsPerBolt.put(boltId, unprocessedBoltInputs);
}
// check if all inputs are available
final int numberOfInputs = unprocessedBoltInputs.size();
int inputsAvailable = 0;
for (Entry<GlobalStreamId, Grouping> entry : unprocessedBoltInputs) {
final String producerId = entry.getKey().get_componentId();
final String streamId = entry.getKey().get_streamId();
final HashMap<String, DataStream<Tuple>> streams = availableInputs.get(producerId);
if (streams != null && streams.get(streamId) != null) {
inputsAvailable++;
}
}
if (inputsAvailable != numberOfInputs) {
// traverse other bolts first until inputs are available
continue;
} else {
makeProgress = true;
boltsIterator.remove();
}
final Map<GlobalStreamId, DataStream<Tuple>> inputStreams = new HashMap<>(numberOfInputs);
for (Entry<GlobalStreamId, Grouping> input : unprocessedBoltInputs) {
final GlobalStreamId streamId = input.getKey();
final Grouping grouping = input.getValue();
final String producerId = streamId.get_componentId();
final Map<String, DataStream<Tuple>> producer = availableInputs.get(producerId);
inputStreams.put(streamId, processInput(boltId, userBolt, streamId, grouping, producer));
}
final SingleOutputStreamOperator<?, ?> outputStream =
createOutput(boltId, userBolt, inputStreams);
if (common.is_set_parallelism_hint()) {
int dop = common.get_parallelism_hint();
outputStream.setParallelism(dop);
} else {
common.set_parallelism_hint(1);
}
}
}
}
/** Tests whether parallelism gets set. */
@Test
public void testParallelism() {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
DataStreamSource<Tuple2<Long, Long>> src = env.fromElements(new Tuple2<>(0L, 0L));
env.setParallelism(10);
SingleOutputStreamOperator<Long, ?> map =
src.map(
new MapFunction<Tuple2<Long, Long>, Long>() {
@Override
public Long map(Tuple2<Long, Long> value) throws Exception {
return null;
}
})
.name("MyMap");
DataStream<Long> windowed =
map.windowAll(GlobalWindows.create())
.trigger(PurgingTrigger.of(CountTrigger.of(10)))
.fold(
0L,
new FoldFunction<Long, Long>() {
@Override
public Long fold(Long accumulator, Long value) throws Exception {
return null;
}
});
windowed.addSink(new NoOpSink<Long>());
DataStreamSink<Long> sink =
map.addSink(
new SinkFunction<Long>() {
private static final long serialVersionUID = 1L;
@Override
public void invoke(Long value) throws Exception {}
});
assertEquals(1, env.getStreamGraph().getStreamNode(src.getId()).getParallelism());
assertEquals(10, env.getStreamGraph().getStreamNode(map.getId()).getParallelism());
assertEquals(1, env.getStreamGraph().getStreamNode(windowed.getId()).getParallelism());
assertEquals(
10, env.getStreamGraph().getStreamNode(sink.getTransformation().getId()).getParallelism());
env.setParallelism(7);
// Some parts, such as windowing rely on the fact that previous operators have a parallelism
// set when instantiating the Discretizer. This would break if we dynamically changed
// the parallelism of operations when changing the setting on the Execution Environment.
assertEquals(1, env.getStreamGraph().getStreamNode(src.getId()).getParallelism());
assertEquals(10, env.getStreamGraph().getStreamNode(map.getId()).getParallelism());
assertEquals(1, env.getStreamGraph().getStreamNode(windowed.getId()).getParallelism());
assertEquals(
10, env.getStreamGraph().getStreamNode(sink.getTransformation().getId()).getParallelism());
try {
src.setParallelism(3);
fail();
} catch (IllegalArgumentException success) {
// do nothing
}
DataStreamSource<Long> parallelSource = env.generateSequence(0, 0);
parallelSource.addSink(new NoOpSink<Long>());
assertEquals(7, env.getStreamGraph().getStreamNode(parallelSource.getId()).getParallelism());
parallelSource.setParallelism(3);
assertEquals(3, env.getStreamGraph().getStreamNode(parallelSource.getId()).getParallelism());
map.setParallelism(2);
assertEquals(2, env.getStreamGraph().getStreamNode(map.getId()).getParallelism());
sink.setParallelism(4);
assertEquals(
4, env.getStreamGraph().getStreamNode(sink.getTransformation().getId()).getParallelism());
}