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[ML] Fix ML memory tracker for old jobs (#37311) 

Jobs created in version 6.1 or earlier can have a
null model_memory_limit.  If these are parsed from
cluster state following a full cluster restart then
we replace the null with 4096mb to make the meaning
explicit.  But if such jobs are streamed from an
old node in a mixed version cluster this does not
happen.  Therefore we need to account for the
possibility of a null model_memory_limit in the ML
memory tracker.
This commit is contained in:
David Roberts 2019-01-10 17:28:00 +00:00 committed by GitHub
parent a433c4012c
commit b65006e8cd
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3 changed files with 17 additions and 12 deletions
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2
x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/ml/job/config/AnalysisLimits.java
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@ -36,7 +36,7 @@ public class AnalysisLimits implements ToXContentObject, Writeable {
* the old default value should be used. From 6.3 onwards, the value will always be explicit.
*/
public static final long DEFAULT_MODEL_MEMORY_LIMIT_MB = 1024L;
static final long PRE_6_1_DEFAULT_MODEL_MEMORY_LIMIT_MB = 4096L;
public static final long PRE_6_1_DEFAULT_MODEL_MEMORY_LIMIT_MB = 4096L;
public static final long DEFAULT_CATEGORIZATION_EXAMPLES_LIMIT = 4;

14
x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/process/MlMemoryTracker.java
View File

@ -20,6 +20,7 @@ import org.elasticsearch.persistent.PersistentTasksCustomMetaData;
import org.elasticsearch.threadpool.ThreadPool;
import org.elasticsearch.xpack.core.ml.MlTasks;
import org.elasticsearch.xpack.core.ml.action.OpenJobAction;
import org.elasticsearch.xpack.core.ml.job.config.AnalysisLimits;
import org.elasticsearch.xpack.core.ml.job.config.Job;
import org.elasticsearch.xpack.ml.MachineLearning;
import org.elasticsearch.xpack.ml.job.JobManager;
@ -269,15 +270,16 @@ public class MlMemoryTracker implements LocalNodeMasterListener {
private void setJobMemoryToLimit(String jobId, ActionListener<Long> listener) {
jobManager.getJob(jobId, ActionListener.wrap(job -> {
Long memoryLimitMb = job.getAnalysisLimits().getModelMemoryLimit();
if (memoryLimitMb != null) {
Long memoryLimitMb = (job.getAnalysisLimits() != null) ? job.getAnalysisLimits().getModelMemoryLimit() : null;
// Although recent versions of the code enforce a non-null model_memory_limit
// when parsing, the job could have been streamed from an older version node in
// a mixed version cluster
if (memoryLimitMb == null) {
memoryLimitMb = AnalysisLimits.PRE_6_1_DEFAULT_MODEL_MEMORY_LIMIT_MB;
}
Long memoryRequirementBytes = ByteSizeUnit.MB.toBytes(memoryLimitMb) + Job.PROCESS_MEMORY_OVERHEAD.getBytes();
memoryRequirementByJob.put(jobId, memoryRequirementBytes);
listener.onResponse(memoryRequirementBytes);
} else {
memoryRequirementByJob.remove(jobId);
listener.onResponse(null);
}
}, e -> {
if (e instanceof ResourceNotFoundException) {
// TODO: does this also happen if the .ml-config index exists but is unavailable?

9
x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/process/MlMemoryTrackerTests.java
View File

@ -123,9 +123,10 @@ public class MlMemoryTrackerTests extends ESTestCase {
return null;
}).when(jobResultsProvider).getEstablishedMemoryUsage(eq(jobId), any(), any(), any(Consumer.class), any());
long modelMemoryLimitMb = 2;
boolean simulateVeryOldJob = randomBoolean();
long recentJobModelMemoryLimitMb = 2;
Job job = mock(Job.class);
when(job.getAnalysisLimits()).thenReturn(new AnalysisLimits(modelMemoryLimitMb, 4L));
when(job.getAnalysisLimits()).thenReturn(simulateVeryOldJob ? null : new AnalysisLimits(recentJobModelMemoryLimitMb, 4L));
doAnswer(invocation -> {
@SuppressWarnings("unchecked")
ActionListener<Job> listener = (ActionListener<Job>) invocation.getArguments()[1];
@ -141,7 +142,9 @@ public class MlMemoryTrackerTests extends ESTestCase {
assertEquals(Long.valueOf(modelBytes + Job.PROCESS_MEMORY_OVERHEAD.getBytes()),
memoryTracker.getJobMemoryRequirement(jobId));
} else {
assertEquals(Long.valueOf(ByteSizeUnit.MB.toBytes(modelMemoryLimitMb) + Job.PROCESS_MEMORY_OVERHEAD.getBytes()),
long expectedModelMemoryLimit =
simulateVeryOldJob ? AnalysisLimits.PRE_6_1_DEFAULT_MODEL_MEMORY_LIMIT_MB : recentJobModelMemoryLimitMb;
assertEquals(Long.valueOf(ByteSizeUnit.MB.toBytes(expectedModelMemoryLimit) + Job.PROCESS_MEMORY_OVERHEAD.getBytes()),
memoryTracker.getJobMemoryRequirement(jobId));
}
} else {