use of io.cdap.cdap.etl.spark.SparkTransformExecutorFactory in project cdap by caskdata.
the class MultiSinkFunction method initializeBranchExecutors.
private void initializeBranchExecutors() {
emitter = new DefaultEmitter<>();
PipelinePluginInstantiator pluginInstantiator = new PipelinePluginInstantiator(pipelineRuntime.getPluginContext(), pipelineRuntime.getMetrics(), phaseSpec, new SingleConnectorFactory());
MacroEvaluator macroEvaluator = new DefaultMacroEvaluator(pipelineRuntime.getArguments(), pipelineRuntime.getLogicalStartTime(), pipelineRuntime.getSecureStore(), pipelineRuntime.getServiceDiscoverer(), pipelineRuntime.getNamespace());
executorFactory = new SparkTransformExecutorFactory(pluginInstantiator, macroEvaluator, null, collectors, dataTracers, pipelineRuntime, emitter);
/*
If the dag is:
|--> t1 --> k1
s1 --|
|--> k2
^
s2 ---|
the group is t1, k1, and k2.
*/
PipelinePhase pipelinePhase = phaseSpec.getPhase();
branchExecutors = new HashMap<>();
inputConnections = new HashMap<>();
for (String groupSource : group) {
// group "sources" are stages in the group that don't have an input from another stage in the group.
if (Sets.difference(pipelinePhase.getStageInputs(groupSource), group).isEmpty()) {
continue;
}
// get the branch by taking a subset of the pipeline starting from the "source".
// with the example above, the two branches are t1 -> k1, and k2.
PipelinePhase branch;
if (pipelinePhase.getSinks().contains(groupSource)) {
// pipelinePhase.subsetFrom() throws an exception if the new "source" is also a sink,
// since a Dag cannot be a single node. so build it manually.
branch = PipelinePhase.builder(pipelinePhase.getPluginTypes()).addStage(pipelinePhase.getStage(groupSource)).build();
} else {
branch = pipelinePhase.subsetFrom(Collections.singleton(groupSource));
}
try {
branchExecutors.put(groupSource, executorFactory.create(branch));
} catch (Exception e) {
throw new IllegalStateException(String.format("Unable to get subset of pipeline starting from stage %s. " + "This indicates a planning error. Please report this bug and turn off stage " + "consolidation by setting %s to false in the runtime arguments.", groupSource, Constants.CONSOLIDATE_STAGES), e);
}
/*
create a mapping from possible inputs to "group sources". This will help identify which incoming
records should be sent to which branch executor.
for example, the pipeline may look like:
|port a --> k1
s --> split --|
|port b --> k2
In this scenario, k1, and k2, are all in the same group, so the map contains:
{ stageName: split, port: a, type: output } -> [k1]
{ stageName: split, port: b, type: output } -> [k2]
A slightly more complicated example:
|--> k1
s1 --> transform --|
| |--> k2
|
|--> error collector --> k3
In this scenario, k1, k2, k3, and error collector are in the same group, so the map contains:
{ stageName: transform, type: output } -> [k1, k2]
{ stageName: transform, type: error } -> [k3]
*/
String groupSourceType = pipelinePhase.getStage(groupSource).getPluginType();
RecordType recordType = ErrorTransform.PLUGIN_TYPE.equals(groupSourceType) ? RecordType.ERROR : RecordType.OUTPUT;
for (String inputStage : pipelinePhase.getStageInputs(groupSource)) {
Map<String, StageSpec.Port> ports = pipelinePhase.getStage(inputStage).getOutputPorts();
String port = ports.get(groupSource).getPort();
InputInfo inputInfo = new InputInfo(inputStage, recordType, port);
Set<String> groupSources = inputConnections.computeIfAbsent(inputInfo, key -> new HashSet<>());
groupSources.add(groupSource);
}
}
}
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