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[ML][FEATURE] Fix build failure after merging master #39743

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Mar 6, 2019
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[ML][FEATURE] Fix build failure after merging master #39743

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4 changes: 2 additions & 2 deletions ...l/src/main/java/org/elasticsearch/xpack/ml/dataframe/process/AnalyticsProcessManager.java
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Original file line number Diff line number Diff line change
Expand Up @@ -55,7 +55,7 @@ public void runJob(long taskAllocationId, DataFrameAnalyticsConfig config, DataF
DataFrameDataExtractor dataExtractor = dataExtractorFactory.newExtractor(false);
AnalyticsProcess process = createProcess(config.getId(), createProcessConfig(config, dataExtractor));
processContextByAllocation.putIfAbsent(taskAllocationId, new ProcessContext());
ExecutorService executorService = threadPool.executor(MachineLearning.AUTODETECT_THREAD_POOL_NAME);
ExecutorService executorService = threadPool.executor(MachineLearning.JOB_COMMS_THREAD_POOL_NAME);
DataFrameRowsJoiner dataFrameRowsJoiner = new DataFrameRowsJoiner(config.getId(), client,
dataExtractorFactory.newExtractor(true));
AnalyticsResultProcessor resultProcessor = new AnalyticsResultProcessor(processContextByAllocation.get(taskAllocationId),
Expand Down Expand Up @@ -136,7 +136,7 @@ private void writeHeaderRecord(DataFrameDataExtractor dataExtractor, AnalyticsPr

private AnalyticsProcess createProcess(String jobId, AnalyticsProcessConfig analyticsProcessConfig) {
// TODO We should rename the thread pool to reflect its more general use now, e.g. JOB_PROCESS_THREAD_POOL_NAME
ExecutorService executorService = threadPool.executor(MachineLearning.AUTODETECT_THREAD_POOL_NAME);
ExecutorService executorService = threadPool.executor(MachineLearning.JOB_COMMS_THREAD_POOL_NAME);
AnalyticsProcess process = processFactory.createAnalyticsProcess(jobId, analyticsProcessConfig, executorService);
if (process.isProcessAlive() == false) {
throw ExceptionsHelper.serverError("Failed to start data frame analytics process");
Expand Down