public static Map<String, Object> convertEdgeProperty(EdgeProperty edge) {
Map<String, Object> jsonDescriptor = new HashMap<String, Object>();
jsonDescriptor.put(DATA_MOVEMENT_TYPE_KEY, edge.getDataMovementType().name());
jsonDescriptor.put(DATA_SOURCE_TYPE_KEY, edge.getDataSourceType().name());
jsonDescriptor.put(SCHEDULING_TYPE_KEY, edge.getSchedulingType().name());
jsonDescriptor.put(EDGE_SOURCE_CLASS_KEY, edge.getEdgeSource().getClassName());
jsonDescriptor.put(EDGE_DESTINATION_CLASS_KEY, edge.getEdgeDestination().getClassName());
String history = edge.getEdgeSource().getHistoryText();
if (history != null) {
jsonDescriptor.put(OUTPUT_USER_PAYLOAD_AS_TEXT, history);
}
history = edge.getEdgeDestination().getHistoryText();
if (history != null) {
jsonDescriptor.put(INPUT_USER_PAYLOAD_AS_TEXT, history);
}
EdgeManagerPluginDescriptor descriptor = edge.getEdgeManagerDescriptor();
if (descriptor != null) {
jsonDescriptor.put(EDGE_MANAGER_CLASS_KEY, descriptor.getClassName());
if (descriptor.getHistoryText() != null && !descriptor.getHistoryText().isEmpty()) {
jsonDescriptor.put(USER_PAYLOAD_AS_TEXT, descriptor.getHistoryText());
}
}
return jsonDescriptor;
}
public InputSpec getDestinationSpec(int destinationTaskIndex) {
return new InputSpec(
sourceVertex.getName(),
edgeProperty.getEdgeDestination(),
edgeManager.getNumDestinationTaskInputs(
sourceVertex.getTotalTasks(), destinationTaskIndex));
}
/**
* Compute optimal parallelism needed for the job
*
* @return true (if parallelism is determined), false otherwise
*/
@VisibleForTesting
boolean determineParallelismAndApply() {
if (numBipartiteSourceTasksCompleted == 0) {
return true;
}
if (numVertexManagerEventsReceived == 0) {
return true;
}
int currentParallelism = pendingTasks.size();
/**
* When overall completed output size is not even equal to desiredTaskInputSize, we can wait for
* some more data to be available to determine better parallelism until max.fraction is reached.
* min.fraction is just a hint to the framework and need not be honored strictly in this case.
*/
boolean canDetermineParallelismLater =
(completedSourceTasksOutputSize < desiredTaskInputDataSize)
&& (numBipartiteSourceTasksCompleted
< (totalNumBipartiteSourceTasks * slowStartMaxSrcCompletionFraction));
if (canDetermineParallelismLater) {
LOG.info(
"Defer scheduling tasks; vertex="
+ getContext().getVertexName()
+ ", totalNumBipartiteSourceTasks="
+ totalNumBipartiteSourceTasks
+ ", completedSourceTasksOutputSize="
+ completedSourceTasksOutputSize
+ ", numVertexManagerEventsReceived="
+ numVertexManagerEventsReceived
+ ", numBipartiteSourceTasksCompleted="
+ numBipartiteSourceTasksCompleted
+ ", maxThreshold="
+ (totalNumBipartiteSourceTasks * slowStartMaxSrcCompletionFraction));
return false;
}
long expectedTotalSourceTasksOutputSize =
(totalNumBipartiteSourceTasks * completedSourceTasksOutputSize)
/ numVertexManagerEventsReceived;
int desiredTaskParallelism =
(int)
((expectedTotalSourceTasksOutputSize + desiredTaskInputDataSize - 1)
/ desiredTaskInputDataSize);
if (desiredTaskParallelism < minTaskParallelism) {
desiredTaskParallelism = minTaskParallelism;
}
if (desiredTaskParallelism >= currentParallelism) {
return true;
}
// most shufflers will be assigned this range
basePartitionRange = currentParallelism / desiredTaskParallelism;
if (basePartitionRange <= 1) {
// nothing to do if range is equal 1 partition. shuffler does it by default
return true;
}
int numShufflersWithBaseRange = currentParallelism / basePartitionRange;
remainderRangeForLastShuffler = currentParallelism % basePartitionRange;
int finalTaskParallelism =
(remainderRangeForLastShuffler > 0)
? (numShufflersWithBaseRange + 1)
: (numShufflersWithBaseRange);
LOG.info(
"Reduce auto parallelism for vertex: "
+ getContext().getVertexName()
+ " to "
+ finalTaskParallelism
+ " from "
+ pendingTasks.size()
+ " . Expected output: "
+ expectedTotalSourceTasksOutputSize
+ " based on actual output: "
+ completedSourceTasksOutputSize
+ " from "
+ numVertexManagerEventsReceived
+ " vertex manager events. "
+ " desiredTaskInputSize: "
+ desiredTaskInputDataSize
+ " max slow start tasks:"
+ (totalNumBipartiteSourceTasks * slowStartMaxSrcCompletionFraction)
+ " num sources completed:"
+ numBipartiteSourceTasksCompleted);
if (finalTaskParallelism < currentParallelism) {
// final parallelism is less than actual parallelism
Map<String, EdgeProperty> edgeProperties =
new HashMap<String, EdgeProperty>(bipartiteSources);
Iterable<Map.Entry<String, SourceVertexInfo>> bipartiteItr = getBipartiteInfo();
for (Map.Entry<String, SourceVertexInfo> entry : bipartiteItr) {
String vertex = entry.getKey();
EdgeProperty oldEdgeProp = entry.getValue().edgeProperty;
// use currentParallelism for numSourceTasks to maintain original state
// for the source tasks
CustomShuffleEdgeManagerConfig edgeManagerConfig =
new CustomShuffleEdgeManagerConfig(
currentParallelism,
finalTaskParallelism,
basePartitionRange,
((remainderRangeForLastShuffler > 0)
? remainderRangeForLastShuffler
: basePartitionRange));
EdgeManagerPluginDescriptor edgeManagerDescriptor =
EdgeManagerPluginDescriptor.create(CustomShuffleEdgeManager.class.getName());
edgeManagerDescriptor.setUserPayload(edgeManagerConfig.toUserPayload());
EdgeProperty newEdgeProp =
EdgeProperty.create(
edgeManagerDescriptor,
oldEdgeProp.getDataSourceType(),
oldEdgeProp.getSchedulingType(),
oldEdgeProp.getEdgeSource(),
oldEdgeProp.getEdgeDestination());
edgeProperties.put(vertex, newEdgeProp);
}
getContext().reconfigureVertex(finalTaskParallelism, null, edgeProperties);
updatePendingTasks();
configureTargetMapping(finalTaskParallelism);
}
return true;
}