读accumlator
JobManager
在job finish的时候会汇总accumulator的值,
newJobStatus match { case JobStatus.FINISHED => try { val accumulatorResults = executionGraph.getAccumulatorsSerialized() val result = new SerializedJobExecutionResult( jobID, jobInfo.duration, accumulatorResults) jobInfo.client ! decorateMessage(JobResultSuccess(result)) }
在client请求accumulation时,
public Map<String, Object> getAccumulators(JobID jobID, ClassLoader loader) throws Exception { ActorGateway jobManagerGateway = getJobManagerGateway(); Future<Object> response; try { response = jobManagerGateway.ask(new RequestAccumulatorResults(jobID), timeout); } catch (Exception e) { throw new Exception("Failed to query the job manager gateway for accumulators.", e); }
消息传到job manager
case message: AccumulatorMessage => handleAccumulatorMessage(message)
private def handleAccumulatorMessage(message: AccumulatorMessage): Unit = { message match { case RequestAccumulatorResults(jobID) => try { currentJobs.get(jobID) match { case Some((graph, jobInfo)) => val accumulatorValues = graph.getAccumulatorsSerialized() sender() ! decorateMessage(AccumulatorResultsFound(jobID, accumulatorValues)) case None => archive.forward(message) } }
ExecuteGraph
获取accumulator的值
/** * Gets a serialized accumulator map. * @return The accumulator map with serialized accumulator values. * @throws IOException */ public Map<String, SerializedValue<Object>> getAccumulatorsSerialized() throws IOException { Map<String, Accumulator<?, ?>> accumulatorMap = aggregateUserAccumulators(); Map<String, SerializedValue<Object>> result = new HashMap<String, SerializedValue<Object>>(); for (Map.Entry<String, Accumulator<?, ?>> entry : accumulatorMap.entrySet()) { result.put(entry.getKey(), new SerializedValue<Object>(entry.getValue().getLocalValue())); } return result; }
execution的accumulator聚合,
/** * Merges all accumulator results from the tasks previously executed in the Executions. * @return The accumulator map */ public Map<String, Accumulator<?,?>> aggregateUserAccumulators() { Map<String, Accumulator<?, ?>> userAccumulators = new HashMap<String, Accumulator<?, ?>>(); for (ExecutionVertex vertex : getAllExecutionVertices()) { Map<String, Accumulator<?, ?>> next = vertex.getCurrentExecutionAttempt().getUserAccumulators(); if (next != null) { AccumulatorHelper.mergeInto(userAccumulators, next); } } return userAccumulators; }
具体merge的逻辑,
public static void mergeInto(Map<String, Accumulator<?, ?>> target, Map<String, Accumulator<?, ?>> toMerge) { for (Map.Entry<String, Accumulator<?, ?>> otherEntry : toMerge.entrySet()) { Accumulator<?, ?> ownAccumulator = target.get(otherEntry.getKey()); if (ownAccumulator == null) { // Create initial counter (copy!) target.put(otherEntry.getKey(), otherEntry.getValue().clone()); } else { // Both should have the same type AccumulatorHelper.compareAccumulatorTypes(otherEntry.getKey(), ownAccumulator.getClass(), otherEntry.getValue().getClass()); // Merge target counter with other counter mergeSingle(ownAccumulator, otherEntry.getValue()); } } }
更新accumulator
JobManager
收到task发来的heartbeat,其中附带accumulators
case Heartbeat(instanceID, metricsReport, accumulators) => updateAccumulators(accumulators)
根据jobid,更新到ExecutionGraph
private def updateAccumulators(accumulators : Seq[AccumulatorSnapshot]) = { accumulators foreach { case accumulatorEvent => currentJobs.get(accumulatorEvent.getJobID) match { case Some((jobGraph, jobInfo)) => future { jobGraph.updateAccumulators(accumulatorEvent) }(context.dispatcher) case None => // ignore accumulator values for old job } } }
根据ExecutionAttemptID, 更新Execution中
/** * Updates the accumulators during the runtime of a job. Final accumulator results are transferred * through the UpdateTaskExecutionState message. * @param accumulatorSnapshot The serialized flink and user-defined accumulators */ public void updateAccumulators(AccumulatorSnapshot accumulatorSnapshot) { Map<AccumulatorRegistry.Metric, Accumulator<?, ?>> flinkAccumulators; Map<String, Accumulator<?, ?>> userAccumulators; try { flinkAccumulators = accumulatorSnapshot.deserializeFlinkAccumulators(); userAccumulators = accumulatorSnapshot.deserializeUserAccumulators(userClassLoader); ExecutionAttemptID execID = accumulatorSnapshot.getExecutionAttemptID(); Execution execution = currentExecutions.get(execID); if (execution != null) { execution.setAccumulators(flinkAccumulators, userAccumulators); } } }
对于execution,只要状态不是结束,就直接更新
/** * Update accumulators (discarded when the Execution has already been terminated). * @param flinkAccumulators the flink internal accumulators * @param userAccumulators the user accumulators */ public void setAccumulators(Map<AccumulatorRegistry.Metric, Accumulator<?, ?>> flinkAccumulators, Map<String, Accumulator<?, ?>> userAccumulators) { synchronized (accumulatorLock) { if (!state.isTerminal()) { this.flinkAccumulators = flinkAccumulators; this.userAccumulators = userAccumulators; } } }
再看TaskManager如何更新accumulator,并发送heartbeat,
/** * Sends a heartbeat message to the JobManager (if connected) with the current * metrics report. */ protected def sendHeartbeatToJobManager(): Unit = { try { val metricsReport: Array[Byte] = metricRegistryMapper.writeValueAsBytes(metricRegistry) val accumulatorEvents = scala.collection.mutable.Buffer[AccumulatorSnapshot]() runningTasks foreach { case (execID, task) => val registry = task.getAccumulatorRegistry val accumulators = registry.getSnapshot accumulatorEvents.append(accumulators) } currentJobManager foreach { jm => jm ! decorateMessage(Heartbeat(instanceID, metricsReport, accumulatorEvents)) } } }
可以看到会把每个running task的accumulators放到accumulatorEvents,然后通过Heartbeat消息发出
而task的accumlators是通过,task.getAccumulatorRegistry.getSnapshot得到
看看
AccumulatorRegistry
/** * Main accumulator registry which encapsulates internal and user-defined accumulators. */ public class AccumulatorRegistry { protected static final Logger LOG = LoggerFactory.getLogger(AccumulatorRegistry.class); protected final JobID jobID; //accumulators所属的Job protected final ExecutionAttemptID taskID; //taskID /* Flink's internal Accumulator values stored for the executing task. */ private final Map<Metric, Accumulator<?, ?>> flinkAccumulators = //内部的Accumulators new HashMap<Metric, Accumulator<?, ?>>(); /* User-defined Accumulator values stored for the executing task. */ private final Map<String, Accumulator<?, ?>> userAccumulators = new HashMap<>(); //用户定义的Accumulators /* The reporter reference that is handed to the reporting tasks. */ private final ReadWriteReporter reporter; /** * Creates a snapshot of this accumulator registry. * @return a serialized accumulator map */ public AccumulatorSnapshot getSnapshot() { try { return new AccumulatorSnapshot(jobID, taskID, flinkAccumulators, userAccumulators); } catch (IOException e) { LOG.warn("Failed to serialize accumulators for task.", e); return null; } } }
snapshot的逻辑也很简单,
public AccumulatorSnapshot(JobID jobID, ExecutionAttemptID executionAttemptID, Map<AccumulatorRegistry.Metric, Accumulator<?, ?>> flinkAccumulators, Map<String, Accumulator<?, ?>> userAccumulators) throws IOException { this.jobID = jobID; this.executionAttemptID = executionAttemptID; this.flinkAccumulators = new SerializedValue<Map<AccumulatorRegistry.Metric, Accumulator<?, ?>>>(flinkAccumulators); this.userAccumulators = new SerializedValue<Map<String, Accumulator<?, ?>>>(userAccumulators); }
最后,我们如何将统计数据累加到Accumulator上的?
直接看看Flink内部的Accumulator是如何更新的,都是通过这个reporter来更新的
/** * Accumulator based reporter for keeping track of internal metrics (e.g. bytes and records in/out) */ private static class ReadWriteReporter implements Reporter { private LongCounter numRecordsIn = new LongCounter(); private LongCounter numRecordsOut = new LongCounter(); private LongCounter numBytesIn = new LongCounter(); private LongCounter numBytesOut = new LongCounter(); private ReadWriteReporter(Map<Metric, Accumulator<?,?>> accumulatorMap) { accumulatorMap.put(Metric.NUM_RECORDS_IN, numRecordsIn); accumulatorMap.put(Metric.NUM_RECORDS_OUT, numRecordsOut); accumulatorMap.put(Metric.NUM_BYTES_IN, numBytesIn); accumulatorMap.put(Metric.NUM_BYTES_OUT, numBytesOut); } @Override public void reportNumRecordsIn(long value) { numRecordsIn.add(value); } @Override public void reportNumRecordsOut(long value) { numRecordsOut.add(value); } @Override public void reportNumBytesIn(long value) { numBytesIn.add(value); } @Override public void reportNumBytesOut(long value) { numBytesOut.add(value); } }
何处调用到这个report的接口,
对于in, 在反序列化到record的时候会统计Bytesin和Recordsin
AdaptiveSpanningRecordDeserializer
public DeserializationResult getNextRecord(T target) throws IOException { // check if we can get a full length; if (nonSpanningRemaining >= 4) { int len = this.nonSpanningWrapper.readInt(); if (reporter != null) { reporter.reportNumBytesIn(len); } if (len <= nonSpanningRemaining - 4) { // we can get a full record from here target.read(this.nonSpanningWrapper); if (reporter != null) { reporter.reportNumRecordsIn(1); }
所以对于out,反之则序列化的时候写入
SpanningRecordSerializer
@Override public SerializationResult addRecord(T record) throws IOException { int len = this.serializationBuffer.length(); this.lengthBuffer.putInt(0, len); if (reporter != null) { reporter.reportNumBytesOut(len); reporter.reportNumRecordsOut(1); }
使用accumulator时,需要首先extends RichFunction by callinggetRuntimeContext().
addAccumulator