Extract common reduce logic from InternalTerms for reuse

server/src/main/java/org/elasticsearch/search/aggregations/bucket/terms/AbstractInternalTerms.java

@@ -0,0 +1,336 @@
+/*
+ * Licensed to Elasticsearch under one or more contributor
+ * license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright
+ * ownership. Elasticsearch licenses this file to you under
+ * the Apache License, Version 2.0 (the "License"); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.elasticsearch.search.aggregations.bucket.terms;
+
+import org.apache.lucene.util.PriorityQueue;
+import org.elasticsearch.Version;
+import org.elasticsearch.common.io.stream.StreamInput;
+import org.elasticsearch.search.aggregations.AggregationExecutionException;
+import org.elasticsearch.search.aggregations.BucketOrder;
+import org.elasticsearch.search.aggregations.InternalAggregation;
+import org.elasticsearch.search.aggregations.InternalAggregations;
+import org.elasticsearch.search.aggregations.InternalMultiBucketAggregation;
+import org.elasticsearch.search.aggregations.InternalOrder;
+import org.elasticsearch.search.aggregations.bucket.IteratorAndCurrent;
+
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Comparator;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+import static org.elasticsearch.search.aggregations.InternalOrder.isKeyAsc;
+import static org.elasticsearch.search.aggregations.InternalOrder.isKeyOrder;
+
+/**
+ * Base class for terms and multi_terms aggregation that handles common reduce logic
+ */
+public abstract class AbstractInternalTerms<
+    A extends AbstractInternalTerms<A, B>,
+    B extends AbstractInternalTerms.AbstractTermsBucket
+    > extends InternalMultiBucketAggregation<A, B> {
+
+    public AbstractInternalTerms(String name,
+                                 Map<String, Object> metadata) {
+        super(name, metadata);
+    }
+
+    protected AbstractInternalTerms(StreamInput in) throws IOException {
+
+        super(in);
+    }
+
+    public abstract static class AbstractTermsBucket extends InternalMultiBucketAggregation.InternalBucket {
+
+        protected abstract void updateDocCountError(long docCountErrorDiff);
+
+        protected abstract void setDocCountError(long docCountError);
+
+        protected abstract boolean getShowDocCountError();
+
+        protected abstract long getDocCountError();
+    }
+
+    /**
+     * Create an array to hold some buckets. Used in collecting the results.
+     */
+    protected abstract B[] createBucketsArray(int size);
+
+    /**
+     * Creates InternalTerms at the end of the merge
+     */
+    protected abstract A create(String name, List<B> buckets, BucketOrder reduceOrder, long docCountError, long otherDocCount);
+
+    protected abstract int getShardSize();
+
+    protected abstract BucketOrder getReduceOrder();
+
+    protected abstract BucketOrder getOrder();
+
+    protected abstract long getSumOfOtherDocCounts();
+
+    protected abstract long getDocCountError();
+
+    protected abstract void setDocCountError(long docCountError);
+
+    protected abstract long getMinDocCount();
+
+    protected abstract int getRequiredSize();
+
+    abstract B createBucket(long docCount, InternalAggregations aggs, long docCountError, B prototype);
+
+    @Override
+    public B reduceBucket(List<B> buckets, ReduceContext context) {
+        assert buckets.size() > 0;
+        long docCount = 0;
+        // For the per term doc count error we add up the errors from the
+        // shards that did not respond with the term. To do this we add up
+        // the errors from the shards that did respond with the terms and
+        // subtract that from the sum of the error from all shards
+        long docCountError = 0;
+        List<InternalAggregations> aggregationsList = new ArrayList<>(buckets.size());
+        for (B bucket : buckets) {
+            docCount += bucket.getDocCount();
+            if (docCountError != -1) {
+                if (bucket.getShowDocCountError() == false || bucket.getDocCountError() == -1) {
+                    docCountError = -1;
+                } else {
+                    docCountError += bucket.getDocCountError();
+                }
+            }
+            aggregationsList.add((InternalAggregations) bucket.getAggregations());
+        }
+        InternalAggregations aggs = InternalAggregations.reduce(aggregationsList, context);
+        return createBucket(docCount, aggs, docCountError, buckets.get(0));
+    }
+
+    private BucketOrder getReduceOrder(List<InternalAggregation> aggregations) {
+        BucketOrder thisReduceOrder = null;
+        for (InternalAggregation aggregation : aggregations) {
+            @SuppressWarnings("unchecked")
+            A terms = (A) aggregation;
+            if (terms.getBuckets().size() == 0) {
+                continue;
+            }
+            if (thisReduceOrder == null) {
+                thisReduceOrder = terms.getReduceOrder();
+            } else if (thisReduceOrder.equals(terms.getReduceOrder()) == false) {
+                return getOrder();
+            }
+        }
+        return thisReduceOrder != null ? thisReduceOrder : getOrder();
+    }
+
+    private long getDocCountError(A terms) {
+        int size = terms.getBuckets().size();
+        if (size == 0 || size < terms.getShardSize() || isKeyOrder(terms.getOrder())) {
+            return 0;
+        } else if (InternalOrder.isCountDesc(terms.getOrder())) {
+            if (terms.getDocCountError() > 0) {
+                // If there is an existing docCountError for this agg then
+                // use this as the error for this aggregation
+                return terms.getDocCountError();
+            } else {
+                // otherwise use the doc count of the last term in the
+                // aggregation
+                return terms.getBuckets().stream().mapToLong(AbstractTermsBucket::getDocCount).min().getAsLong();
+            }
+        } else {
+            return -1;
+        }
+    }
+
+    private List<B> reduceMergeSort(List<InternalAggregation> aggregations,
+                                    BucketOrder thisReduceOrder, InternalAggregation.ReduceContext reduceContext) {
+        assert isKeyOrder(thisReduceOrder);
+        final Comparator<Bucket> cmp = thisReduceOrder.comparator();
+        final PriorityQueue<IteratorAndCurrent<B>> pq = new PriorityQueue<>(aggregations.size()) {
+            @Override
+            protected boolean lessThan(IteratorAndCurrent<B> a, IteratorAndCurrent<B> b) {
+                return cmp.compare(a.current(), b.current()) < 0;
+            }
+        };
+        for (InternalAggregation aggregation : aggregations) {
+            @SuppressWarnings("unchecked")
+            A terms = (A) aggregation;
+            if (terms.getBuckets().isEmpty() == false) {
+                pq.add(new IteratorAndCurrent<>(terms.getBuckets().iterator()));
+            }
+        }
+        List<B> reducedBuckets = new ArrayList<>();
+        // list of buckets coming from different shards that have the same key
+        List<B> currentBuckets = new ArrayList<>();
+        B lastBucket = null;
+        while (pq.size() > 0) {
+            final IteratorAndCurrent<B> top = pq.top();
+            assert lastBucket == null || cmp.compare(top.current(), lastBucket) >= 0;
+            if (lastBucket != null && cmp.compare(top.current(), lastBucket) != 0) {
+                // the key changes, reduce what we already buffered and reset the buffer for current buckets
+                final B reduced = reduceBucket(currentBuckets, reduceContext);
+                reducedBuckets.add(reduced);
+                currentBuckets.clear();
+            }
+            lastBucket = top.current();
+            currentBuckets.add(top.current());
+            if (top.hasNext()) {
+                top.next();
+                assert cmp.compare(top.current(), lastBucket) > 0 : "shards must return data sorted by key";
+                pq.updateTop();
+            } else {
+                pq.pop();
+            }
+        }
+
+        if (currentBuckets.isEmpty() == false) {
+            final B reduced = reduceBucket(currentBuckets, reduceContext);
+            reducedBuckets.add(reduced);
+        }
+        return reducedBuckets;
+    }
+
+    private List<B> reduceLegacy(List<InternalAggregation> aggregations, InternalAggregation.ReduceContext reduceContext) {
+        Map<Object, List<B>> bucketMap = new HashMap<>();
+        for (InternalAggregation aggregation : aggregations) {
+            @SuppressWarnings("unchecked")
+            A terms = (A) aggregation;
+            if (terms.getBuckets().isEmpty() == false) {
+                for (B bucket : terms.getBuckets()) {
+                    bucketMap.computeIfAbsent(bucket.getKey(), k -> new ArrayList<>()).add(bucket);
+                }
+            }
+        }
+        List<B> reducedBuckets = new ArrayList<>();
+        for (List<B> sameTermBuckets : bucketMap.values()) {
+            final B b = reduceBucket(sameTermBuckets, reduceContext);
+            reducedBuckets.add(b);
+        }
+        return reducedBuckets;
+    }
+
+    public InternalAggregation reduce(List<InternalAggregation> aggregations, InternalAggregation.ReduceContext reduceContext) {
+        long sumDocCountError = 0;
+        long otherDocCount = 0;
+        A referenceTerms = null;
+        for (InternalAggregation aggregation : aggregations) {
+            @SuppressWarnings("unchecked")
+            A terms = (A) aggregation;
+            if (referenceTerms == null && terms.isMapped()) {
+                referenceTerms = terms;
+            }
+            if (referenceTerms != null && referenceTerms.getClass().equals(terms.getClass()) == false && terms.isMapped()) {
+                // control gets into this loop when the same field name against which the query is executed
+                // is of different types in different indices.
+                throw new AggregationExecutionException("Merging/Reducing the aggregations failed when computing the aggregation ["
+                    + referenceTerms.getName() + "] because the field you gave in the aggregation query existed as two different "
+                    + "types in two different indices");
+            }
+            otherDocCount += terms.getSumOfOtherDocCounts();
+            final long thisAggDocCountError = getDocCountError(terms);
+            if (sumDocCountError != -1) {
+                if (thisAggDocCountError == -1) {
+                    sumDocCountError = -1;
+                } else {
+                    sumDocCountError += thisAggDocCountError;
+                }
+            }
+            setDocCountError(thisAggDocCountError);
+            for (B bucket : terms.getBuckets()) {
+                // If there is already a doc count error for this bucket
+                // subtract this aggs doc count error from it to make the
+                // new value for the bucket. This then means that when the
+                // final error for the bucket is calculated below we account
+                // for the existing error calculated in a previous reduce.
+                // Note that if the error is unbounded (-1) this will be fixed
+                // later in this method.
+                 bucket.updateDocCountError(-thisAggDocCountError);
+            }
+        }
+
+        final List<B> reducedBuckets;
+        /**
+         * Buckets returned by a partial reduce or a shard response are sorted by key since {@link Version#V_7_10_0}.
+         * That allows to perform a merge sort when reducing multiple aggregations together.
+         * For backward compatibility, we disable the merge sort and use ({@link #reduceLegacy} if any of
+         * the provided aggregations use a different {@link #reduceOrder}.
+         */
+        BucketOrder thisReduceOrder = getReduceOrder(aggregations);
+        if (isKeyOrder(thisReduceOrder)) {
+            // extract the primary sort in case this is a compound order.
+            thisReduceOrder = InternalOrder.key(isKeyAsc(thisReduceOrder));
+            reducedBuckets = reduceMergeSort(aggregations, thisReduceOrder, reduceContext);
+        } else {
+            reducedBuckets = reduceLegacy(aggregations, reduceContext);
+        }
+        final B[] list;
+        if (reduceContext.isFinalReduce()) {
+            final int size = Math.min(getRequiredSize(), reducedBuckets.size());
+            // final comparator
+            final BucketPriorityQueue<B> ordered = new BucketPriorityQueue<>(size, getOrder().comparator());
+            for (B bucket : reducedBuckets) {
+                if (sumDocCountError == -1) {
+                    bucket.setDocCountError(-1);
+                } else {
+                    bucket.updateDocCountError(sumDocCountError);
+                }
+                if (bucket.getDocCount() >= getMinDocCount()) {
+                    B removed = ordered.insertWithOverflow(bucket);
+                    if (removed != null) {
+                        otherDocCount += removed.getDocCount();
+                        reduceContext.consumeBucketsAndMaybeBreak(-countInnerBucket(removed));
+                    } else {
+                        reduceContext.consumeBucketsAndMaybeBreak(1);
+                    }
+                } else {
+                    reduceContext.consumeBucketsAndMaybeBreak(-countInnerBucket(bucket));
+                }
+            }
+            list = createBucketsArray(ordered.size());
+            for (int i = ordered.size() - 1; i >= 0; i--) {
+                list[i] = ordered.pop();
+            }
+        } else {
+            // we can prune the list on partial reduce if the aggregation is ordered by key
+            // and not filtered (minDocCount == 0)
+            int size = isKeyOrder(getOrder()) && getMinDocCount() == 0 ? Math.min(getRequiredSize(), reducedBuckets.size()) :
+                reducedBuckets.size();
+            list = createBucketsArray(size);
+            for (int i = 0; i < size; i++) {
+                reduceContext.consumeBucketsAndMaybeBreak(1);
+                list[i] = reducedBuckets.get(i);
+                if (sumDocCountError == -1) {
+                    list[i].setDocCountError(-1);
+                } else {
+                    list[i].updateDocCountError(sumDocCountError);
+                }
+            }
+        }
+        long docCountError;
+        if (sumDocCountError == -1) {
+            docCountError = -1;
+        } else {
+            docCountError = aggregations.size() == 1 ? 0 : sumDocCountError;
+        }
+        return create(name, Arrays.asList(list), reduceContext.isFinalReduce() ? getOrder() : thisReduceOrder, docCountError,
+            otherDocCount);
+    }
+
+}

server/src/main/java/org/elasticsearch/search/aggregations/bucket/terms/BucketPriorityQueue.java

@@ -22,7 +22,7 @@
 
 import java.util.Comparator;
 
-public class BucketPriorityQueue<B extends Terms.Bucket> extends PriorityQueue<B> {
+public class BucketPriorityQueue<B> extends PriorityQueue<B> {
 
     private final Comparator<? super B> comparator;