[ML] Throttle the delete-by-query of expired results (#47177)

Due to #47003 many clusters will have built up a
large backlog of expired results. On upgrading to
a version where that bug is fixed users could find
that the first ML daily maintenance task deletes
a very large amount of documents.

This change introduces throttling to the
delete-by-query that the ML daily maintenance uses
to delete expired results to limit it to deleting an
average 200 documents per second. (There is no
throttling for state/forecast documents as these
are expected to be lower volume.)

Additionally a rough time limit of 8 hours is applied
to the whole delete expired data action. (This is only
rough as it won't stop part way through a single
operation - it only checks the timeout between
operations.)

Relates #47103

x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/ml/action/DeleteExpiredDataAction.java

@@ -65,6 +65,10 @@ public Response(StreamInput in) throws IOException {
             deleted = in.readBoolean();
         }
 
+        public boolean isDeleted() {
+            return deleted;
+        }
+
         @Override
         public void writeTo(StreamOutput out) throws IOException {
             out.writeBoolean(deleted);

x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/MlDailyMaintenanceService.java

@@ -116,7 +116,13 @@ private void triggerTasks() {
         LOGGER.info("triggering scheduled [ML] maintenance tasks");
         executeAsyncWithOrigin(client, ML_ORIGIN, DeleteExpiredDataAction.INSTANCE, new DeleteExpiredDataAction.Request(),
                 ActionListener.wrap(
-                        response -> LOGGER.info("Successfully completed [ML] maintenance tasks"),
+                        response -> {
+                            if (response.isDeleted()) {
+                                LOGGER.info("Successfully completed [ML] maintenance tasks");
+                            } else {
+                                LOGGER.info("Halting [ML] maintenance tasks before completion as elapsed time is too great");
+                            }
+                        },
                         e -> LOGGER.error("An error occurred during maintenance tasks execution", e)));
         scheduleNext();
     }

x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/action/TransportDeleteExpiredDataAction.java

@@ -26,34 +26,54 @@
 import org.elasticsearch.xpack.ml.notifications.AnomalyDetectionAuditor;
 import org.elasticsearch.xpack.ml.utils.VolatileCursorIterator;
 
+import java.time.Clock;
+import java.time.Duration;
+import java.time.Instant;
 import java.util.Arrays;
 import java.util.Iterator;
 import java.util.List;
+import java.util.function.Supplier;
 
 public class TransportDeleteExpiredDataAction extends HandledTransportAction<DeleteExpiredDataAction.Request,
         DeleteExpiredDataAction.Response> {
 
+    // TODO: make configurable in the request
+    static final Duration MAX_DURATION = Duration.ofHours(8);
+
     private final ThreadPool threadPool;
+    private final String executor;
     private final Client client;
     private final ClusterService clusterService;
+    private final Clock clock;
 
     @Inject
     public TransportDeleteExpiredDataAction(ThreadPool threadPool, TransportService transportService,
                                             ActionFilters actionFilters, Client client, ClusterService clusterService) {
-        super(DeleteExpiredDataAction.NAME, transportService, actionFilters, DeleteExpiredDataAction.Request::new);
+        this(threadPool, MachineLearning.UTILITY_THREAD_POOL_NAME, transportService, actionFilters, client, clusterService,
+            Clock.systemUTC());
+    }
+
+    TransportDeleteExpiredDataAction(ThreadPool threadPool, String executor, TransportService transportService,
+                                     ActionFilters actionFilters, Client client, ClusterService clusterService, Clock clock) {
+        super(DeleteExpiredDataAction.NAME, transportService, actionFilters, DeleteExpiredDataAction.Request::new, executor);
         this.threadPool = threadPool;
+        this.executor = executor;
         this.client = ClientHelper.clientWithOrigin(client, ClientHelper.ML_ORIGIN);
         this.clusterService = clusterService;
+        this.clock = clock;
     }
 
     @Override
     protected void doExecute(Task task, DeleteExpiredDataAction.Request request,
                              ActionListener<DeleteExpiredDataAction.Response> listener) {
         logger.info("Deleting expired data");
-        threadPool.executor(MachineLearning.UTILITY_THREAD_POOL_NAME).execute(() -> deleteExpiredData(listener));
+        Instant timeoutTime = Instant.now(clock).plus(MAX_DURATION);
+        Supplier<Boolean> isTimedOutSupplier = () -> Instant.now(clock).isAfter(timeoutTime);
+        threadPool.executor(MachineLearning.UTILITY_THREAD_POOL_NAME).execute(() -> deleteExpiredData(listener, isTimedOutSupplier));
     }
 
-    private void deleteExpiredData(ActionListener<DeleteExpiredDataAction.Response> listener) {
+    private void deleteExpiredData(ActionListener<DeleteExpiredDataAction.Response> listener,
+                                   Supplier<Boolean> isTimedOutSupplier) {
         AnomalyDetectionAuditor auditor = new AnomalyDetectionAuditor(client, clusterService.getNodeName());
         List<MlDataRemover> dataRemovers = Arrays.asList(
                 new ExpiredResultsRemover(client, auditor),
@@ -62,25 +82,32 @@ private void deleteExpiredData(ActionListener<DeleteExpiredDataAction.Response>
                 new UnusedStateRemover(client, clusterService)
         );
         Iterator<MlDataRemover> dataRemoversIterator = new VolatileCursorIterator<>(dataRemovers);
-        deleteExpiredData(dataRemoversIterator, listener);
+        deleteExpiredData(dataRemoversIterator, listener, isTimedOutSupplier, true);
     }
 
-    private void deleteExpiredData(Iterator<MlDataRemover> mlDataRemoversIterator,
-                                   ActionListener<DeleteExpiredDataAction.Response> listener) {
-        if (mlDataRemoversIterator.hasNext()) {
+    void deleteExpiredData(Iterator<MlDataRemover> mlDataRemoversIterator,
+                           ActionListener<DeleteExpiredDataAction.Response> listener,
+                           Supplier<Boolean> isTimedOutSupplier,
+                           boolean haveAllPreviousDeletionsCompleted) {
+        if (haveAllPreviousDeletionsCompleted && mlDataRemoversIterator.hasNext()) {
             MlDataRemover remover = mlDataRemoversIterator.next();
             ActionListener<Boolean> nextListener = ActionListener.wrap(
-                    booleanResponse -> deleteExpiredData(mlDataRemoversIterator, listener), listener::onFailure);
+                    booleanResponse -> deleteExpiredData(mlDataRemoversIterator, listener, isTimedOutSupplier, booleanResponse),
+                    listener::onFailure);
             // Removing expired ML data and artifacts requires multiple operations.
             // These are queued up and executed sequentially in the action listener,
             // the chained calls must all run the ML utility thread pool NOT the thread
             // the previous action returned in which in the case of a transport_client_boss
             // thread is a disaster.
-            remover.remove(new ThreadedActionListener<>(logger, threadPool, MachineLearning.UTILITY_THREAD_POOL_NAME, nextListener,
-                    false));
+            remover.remove(new ThreadedActionListener<>(logger, threadPool, executor, nextListener, false),
+                isTimedOutSupplier);
         } else {
-            logger.info("Completed deletion of expired data");
-            listener.onResponse(new DeleteExpiredDataAction.Response(true));
+            if (haveAllPreviousDeletionsCompleted) {
+                logger.info("Completed deletion of expired ML data");
+            } else {
+                logger.info("Halted deletion of expired ML data until next invocation");
+            }
+            listener.onResponse(new DeleteExpiredDataAction.Response(haveAllPreviousDeletionsCompleted));
         }
     }
 }

x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/job/persistence/JobDataDeleter.java

@@ -23,6 +23,7 @@
 import org.elasticsearch.index.reindex.DeleteByQueryRequest;
 import org.elasticsearch.xpack.core.ml.datafeed.DatafeedTimingStats;
 import org.elasticsearch.xpack.core.ml.job.persistence.AnomalyDetectorsIndex;
+import org.elasticsearch.xpack.core.ml.job.persistence.ElasticsearchMappings;
 import org.elasticsearch.xpack.core.ml.job.process.autodetect.state.ModelSnapshot;
 import org.elasticsearch.xpack.core.ml.job.results.Result;
 
@@ -79,6 +80,9 @@ public void deleteModelSnapshots(List<ModelSnapshot> modelSnapshots, ActionListe
             .setIndicesOptions(IndicesOptions.lenientExpandOpen())
             .setQuery(new IdsQueryBuilder().addIds(idsToDelete.toArray(new String[0])));
 
+        // _doc is the most efficient sort order and will also disable scoring
+        deleteByQueryRequest.getSearchRequest().source().sort(ElasticsearchMappings.ES_DOC);
+
         try {
             executeAsyncWithOrigin(client, ML_ORIGIN, DeleteByQueryAction.INSTANCE, deleteByQueryRequest, listener);
         } catch (Exception e) {
@@ -101,6 +105,10 @@ public void deleteResultsFromTime(long cutoffEpochMs, ActionListener<Boolean> li
                 .filter(QueryBuilders.rangeQuery(Result.TIMESTAMP.getPreferredName()).gte(cutoffEpochMs));
         deleteByQueryHolder.dbqRequest.setIndicesOptions(IndicesOptions.lenientExpandOpen());
         deleteByQueryHolder.dbqRequest.setQuery(query);
+
+        // _doc is the most efficient sort order and will also disable scoring
+        deleteByQueryHolder.dbqRequest.getSearchRequest().source().sort(ElasticsearchMappings.ES_DOC);
+
         executeAsyncWithOrigin(client, ML_ORIGIN, DeleteByQueryAction.INSTANCE, deleteByQueryHolder.dbqRequest,
                 ActionListener.wrap(r -> listener.onResponse(true), listener::onFailure));
     }
@@ -116,6 +124,9 @@ public void deleteInterimResults() {
         QueryBuilder qb = QueryBuilders.termQuery(Result.IS_INTERIM.getPreferredName(), true);
         deleteByQueryHolder.dbqRequest.setQuery(new ConstantScoreQueryBuilder(qb));
 
+        // _doc is the most efficient sort order and will also disable scoring
+        deleteByQueryHolder.dbqRequest.getSearchRequest().source().sort(ElasticsearchMappings.ES_DOC);
+
         try (ThreadContext.StoredContext ignore = client.threadPool().getThreadContext().stashWithOrigin(ML_ORIGIN)) {
             client.execute(DeleteByQueryAction.INSTANCE, deleteByQueryHolder.dbqRequest).get();
         } catch (Exception e) {
@@ -134,6 +145,9 @@ public void deleteDatafeedTimingStats(ActionListener<BulkByScrollResponse> liste
             .setIndicesOptions(IndicesOptions.lenientExpandOpen())
             .setQuery(new IdsQueryBuilder().addIds(DatafeedTimingStats.documentId(jobId)));
 
+        // _doc is the most efficient sort order and will also disable scoring
+        deleteByQueryRequest.getSearchRequest().source().sort(ElasticsearchMappings.ES_DOC);
+
         executeAsyncWithOrigin(client, ML_ORIGIN, DeleteByQueryAction.INSTANCE, deleteByQueryRequest, listener);
     }
 

x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/job/retention/AbstractExpiredJobDataRemover.java

@@ -22,6 +22,7 @@
 import java.util.Iterator;
 import java.util.List;
 import java.util.concurrent.TimeUnit;
+import java.util.function.Supplier;
 import java.util.stream.Collectors;
 
 /**
@@ -40,11 +41,12 @@ abstract class AbstractExpiredJobDataRemover implements MlDataRemover {
     }
 
     @Override
-    public void remove(ActionListener<Boolean> listener) {
-        removeData(newJobIterator(), listener);
+    public void remove(ActionListener<Boolean> listener, Supplier<Boolean> isTimedOutSupplier) {
+        removeData(newJobIterator(), listener, isTimedOutSupplier);
     }
 
-    private void removeData(WrappedBatchedJobsIterator jobIterator, ActionListener<Boolean> listener) {
+    private void removeData(WrappedBatchedJobsIterator jobIterator, ActionListener<Boolean> listener,
+                            Supplier<Boolean> isTimedOutSupplier) {
         if (jobIterator.hasNext() == false) {
             listener.onResponse(true);
             return;
@@ -56,13 +58,19 @@ private void removeData(WrappedBatchedJobsIterator jobIterator, ActionListener<B
             return;
         }
 
+        if (isTimedOutSupplier.get()) {
+            listener.onResponse(false);
+            return;
+        }
+
         Long retentionDays = getRetentionDays(job);
         if (retentionDays == null) {
-            removeData(jobIterator, listener);
+            removeData(jobIterator, listener, isTimedOutSupplier);
             return;
         }
         long cutoffEpochMs = calcCutoffEpochMs(retentionDays);
-        removeDataBefore(job, cutoffEpochMs, ActionListener.wrap(response -> removeData(jobIterator, listener), listener::onFailure));
+        removeDataBefore(job, cutoffEpochMs,
+            ActionListener.wrap(response -> removeData(jobIterator, listener, isTimedOutSupplier), listener::onFailure));
     }
 
     private WrappedBatchedJobsIterator newJobIterator() {

x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/job/retention/ExpiredForecastsRemover.java

@@ -32,6 +32,7 @@
 import org.elasticsearch.threadpool.ThreadPool;
 import org.elasticsearch.xpack.core.ml.job.config.Job;
 import org.elasticsearch.xpack.core.ml.job.persistence.AnomalyDetectorsIndex;
+import org.elasticsearch.xpack.core.ml.job.persistence.ElasticsearchMappings;
 import org.elasticsearch.xpack.core.ml.job.results.Forecast;
 import org.elasticsearch.xpack.core.ml.job.results.ForecastRequestStats;
 import org.elasticsearch.xpack.core.ml.job.results.Result;
@@ -44,6 +45,7 @@
 import java.util.ArrayList;
 import java.util.List;
 import java.util.Objects;
+import java.util.function.Supplier;
 
 /**
  * Removes up to {@link #MAX_FORECASTS} forecasts (stats + forecasts docs) that have expired.
@@ -71,10 +73,10 @@ public ExpiredForecastsRemover(Client client, ThreadPool threadPool) {
     }
 
     @Override
-    public void remove(ActionListener<Boolean> listener) {
+    public void remove(ActionListener<Boolean> listener, Supplier<Boolean> isTimedOutSupplier) {
         LOGGER.debug("Removing forecasts that expire before [{}]", cutoffEpochMs);
         ActionListener<SearchResponse> forecastStatsHandler = ActionListener.wrap(
-                searchResponse -> deleteForecasts(searchResponse, listener),
+                searchResponse -> deleteForecasts(searchResponse, listener, isTimedOutSupplier),
                 e -> listener.onFailure(new ElasticsearchException("An error occurred while searching forecasts to delete", e)));
 
         SearchSourceBuilder source = new SearchSourceBuilder();
@@ -84,13 +86,16 @@ public void remove(ActionListener<Boolean> listener) {
         source.size(MAX_FORECASTS);
         source.trackTotalHits(true);
 
+        // _doc is the most efficient sort order and will also disable scoring
+        source.sort(ElasticsearchMappings.ES_DOC);
+
         SearchRequest searchRequest = new SearchRequest(RESULTS_INDEX_PATTERN);
         searchRequest.source(source);
         client.execute(SearchAction.INSTANCE, searchRequest, new ThreadedActionListener<>(LOGGER, threadPool,
                 MachineLearning.UTILITY_THREAD_POOL_NAME, forecastStatsHandler, false));
     }
 
-    private void deleteForecasts(SearchResponse searchResponse, ActionListener<Boolean> listener) {
+    private void deleteForecasts(SearchResponse searchResponse, ActionListener<Boolean> listener, Supplier<Boolean> isTimedOutSupplier) {
         List<ForecastRequestStats> forecastsToDelete;
         try {
             forecastsToDelete = findForecastsToDelete(searchResponse);
@@ -99,6 +104,11 @@ private void deleteForecasts(SearchResponse searchResponse, ActionListener<Boole
             return;
         }
 
+        if (isTimedOutSupplier.get()) {
+            listener.onResponse(false);
+            return;
+        }
+
         DeleteByQueryRequest request = buildDeleteByQuery(forecastsToDelete);
         client.execute(DeleteByQueryAction.INSTANCE, request, new ActionListener<BulkByScrollResponse>() {
             @Override
@@ -157,6 +167,10 @@ private DeleteByQueryRequest buildDeleteByQuery(List<ForecastRequestStats> forec
         }
         QueryBuilder query = QueryBuilders.boolQuery().filter(boolQuery);
         request.setQuery(query);
+
+        // _doc is the most efficient sort order and will also disable scoring
+        request.getSearchRequest().source().sort(ElasticsearchMappings.ES_DOC);
+
         return request;
     }
 }

x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/job/retention/ExpiredModelSnapshotsRemover.java

@@ -23,6 +23,7 @@
 import org.elasticsearch.xpack.core.ml.action.DeleteModelSnapshotAction;
 import org.elasticsearch.xpack.core.ml.job.config.Job;
 import org.elasticsearch.xpack.core.ml.job.persistence.AnomalyDetectorsIndex;
+import org.elasticsearch.xpack.core.ml.job.persistence.ElasticsearchMappings;
 import org.elasticsearch.xpack.core.ml.job.process.autodetect.state.ModelSnapshot;
 import org.elasticsearch.xpack.core.ml.job.process.autodetect.state.ModelSnapshotField;
 import org.elasticsearch.xpack.ml.MachineLearning;
@@ -88,7 +89,7 @@ protected void removeDataBefore(Job job, long cutoffEpochMs, ActionListener<Bool
                 .mustNot(activeSnapshotFilter)
                 .mustNot(retainFilter);
 
-        searchRequest.source(new SearchSourceBuilder().query(query).size(MODEL_SNAPSHOT_SEARCH_SIZE));
+        searchRequest.source(new SearchSourceBuilder().query(query).size(MODEL_SNAPSHOT_SEARCH_SIZE).sort(ElasticsearchMappings.ES_DOC));
 
         client.execute(SearchAction.INSTANCE, searchRequest, new ThreadedActionListener<>(LOGGER, threadPool,
                 MachineLearning.UTILITY_THREAD_POOL_NAME, expiredSnapshotsListener(job.getId(), listener), false));

x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/job/retention/ExpiredResultsRemover.java

@@ -19,6 +19,7 @@
 import org.elasticsearch.xpack.core.ml.job.config.Job;
 import org.elasticsearch.xpack.core.ml.job.messages.Messages;
 import org.elasticsearch.xpack.core.ml.job.persistence.AnomalyDetectorsIndex;
+import org.elasticsearch.xpack.core.ml.job.persistence.ElasticsearchMappings;
 import org.elasticsearch.xpack.core.ml.job.process.autodetect.state.ModelSizeStats;
 import org.elasticsearch.xpack.core.ml.job.results.Forecast;
 import org.elasticsearch.xpack.core.ml.job.results.ForecastRequestStats;
@@ -88,13 +89,21 @@ private DeleteByQueryRequest createDBQRequest(Job job, long cutoffEpochMs) {
         DeleteByQueryRequest request = new DeleteByQueryRequest();
         request.setSlices(AbstractBulkByScrollRequest.AUTO_SLICES);
 
+        // Delete the documents gradually.
+        // With DEFAULT_SCROLL_SIZE = 1000 this implies we spread deletion of 1 million documents over 5000 seconds ~= 83 minutes.
+        request.setBatchSize(AbstractBulkByScrollRequest.DEFAULT_SCROLL_SIZE);
+        request.setRequestsPerSecond(AbstractBulkByScrollRequest.DEFAULT_SCROLL_SIZE / 5);
+
         request.indices(AnomalyDetectorsIndex.jobResultsAliasedName(job.getId()));
         QueryBuilder excludeFilter = QueryBuilders.termsQuery(Result.RESULT_TYPE.getPreferredName(),
                 ModelSizeStats.RESULT_TYPE_VALUE, ForecastRequestStats.RESULT_TYPE_VALUE, Forecast.RESULT_TYPE_VALUE);
         QueryBuilder query = createQuery(job.getId(), cutoffEpochMs)
                 .filter(QueryBuilders.existsQuery(Result.RESULT_TYPE.getPreferredName()))
                 .mustNot(excludeFilter);
         request.setQuery(query);
+
+        // _doc is the most efficient sort order and will also disable scoring
+        request.getSearchRequest().source().sort(ElasticsearchMappings.ES_DOC);
         return request;
     }
 

x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/job/retention/MlDataRemover.java

@@ -7,6 +7,8 @@
 
 import org.elasticsearch.action.ActionListener;
 
+import java.util.function.Supplier;
+
 public interface MlDataRemover {
-    void remove(ActionListener<Boolean> listener);
+    void remove(ActionListener<Boolean> listener, Supplier<Boolean> isTimedOutSupplier);
 }