mirror of https://github.com/apache/lucene.git
SOLR-13911: add support for missing aggregation in JSON facet module
* This missing aggregation is equivalent to StatsComponent's missing
This commit is contained in:
Munendra S N
parent
3fb39b2960
commit
0602956a44
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@ -126,6 +126,8 @@ New Features
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* SOLR-10786: Add DBSCAN clustering Streaming Evaluator (Joel Bernstein)
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* SOLR-13911: Add 'missing' aggregation in JSON FacetModule (hossman, Munendra S N)
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Improvements
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---------------------
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@ -59,6 +59,7 @@ import org.apache.solr.search.facet.AvgAgg;
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import org.apache.solr.search.facet.CountAgg;
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import org.apache.solr.search.facet.HLLAgg;
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import org.apache.solr.search.facet.MinMaxAgg;
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import org.apache.solr.search.facet.MissingAgg;
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import org.apache.solr.search.facet.PercentileAgg;
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import org.apache.solr.search.facet.StddevAgg;
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import org.apache.solr.search.facet.SumAgg;
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@ -1014,6 +1015,13 @@ public abstract class ValueSourceParser implements NamedListInitializedPlugin {
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return new StddevAgg(fp.parseValueSource());
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}
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});
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addParser("agg_missing", new ValueSourceParser() {
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@Override
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public ValueSource parse(FunctionQParser fp) throws SyntaxError {
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return new MissingAgg(fp.parseValueSource(FunctionQParser.FLAG_DEFAULT | FunctionQParser.FLAG_USE_FIELDNAME_SOURCE));
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}
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});
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/***
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addParser("agg_multistat", new ValueSourceParser() {
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@ -0,0 +1,81 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.solr.search.facet;
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import java.io.IOException;
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import java.util.function.IntFunction;
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import org.apache.lucene.queries.function.ValueSource;
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import org.apache.lucene.queries.function.valuesource.QueryValueSource;
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import org.apache.lucene.search.DocValuesFieldExistsQuery;
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import org.apache.lucene.search.Query;
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import org.apache.solr.schema.SchemaField;
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import org.apache.solr.search.function.FieldNameValueSource;
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/**
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* {@link AggValueSource} to compute missing counts for given {@link ValueSource}
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*/
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public class MissingAgg extends SimpleAggValueSource {
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public MissingAgg(ValueSource vs) {
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super("missing", vs);
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}
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@Override
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public SlotAcc createSlotAcc(FacetContext fcontext, int numDocs, int numSlots) throws IOException {
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ValueSource vs = getArg();
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if (vs instanceof FieldNameValueSource) {
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String field = ((FieldNameValueSource)vs).getFieldName();
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SchemaField sf = fcontext.qcontext.searcher().getSchema().getField(field);
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if (sf.multiValued() || sf.getType().multiValuedFieldCache()) {
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Query query = null;
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if (sf.hasDocValues()) {
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query = new DocValuesFieldExistsQuery(sf.getName());
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} else {
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query = sf.getType().getRangeQuery(null, sf, null, null, false, false);
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}
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vs = new QueryValueSource(query, 0.0f);
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} else {
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vs = sf.getType().getValueSource(sf, null);
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}
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}
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return new MissingSlotAcc(vs, fcontext, numSlots);
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}
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@Override
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public FacetMerger createFacetMerger(Object prototype) {
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return new FacetLongMerger();
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}
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class MissingSlotAcc extends LongFuncSlotAcc {
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public MissingSlotAcc(ValueSource values, FacetContext fcontext, int numSlots) {
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super(values, fcontext, numSlots, 0);
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}
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@Override
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public void collect(int doc, int slot, IntFunction<SlotContext> slotContext) throws IOException {
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if (!values.exists(doc)) {
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result[slot]++;
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}
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}
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}
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}
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@ -1191,6 +1191,9 @@ public class QueryEqualityTest extends SolrTestCaseJ4 {
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assertFuncEquals("agg_percentile(foo_i,50)", "agg_percentile(foo_i,50)");
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assertFuncEquals("agg_variance(foo_i)", "agg_variance(foo_i)");
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assertFuncEquals("agg_stddev(foo_i)", "agg_stddev(foo_i)");
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assertFuncEquals("agg_missing(foo_i)", "agg_missing(foo_i)");
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assertFuncEquals("agg(missing(foo_i))", "agg(missing(foo_i))");
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assertFuncEquals("agg_missing(field(foo_i))", "agg_missing(field(foo_i))");
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// assertFuncEquals("agg_multistat(foo_i)", "agg_multistat(foo_i)");
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}
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@ -42,9 +42,9 @@ import org.junit.Test;
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*/
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public class DistributedFacetSimpleRefinementLongTailTest extends BaseDistributedSearchTestCase {
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// TODO: SOLR-11695: need "num_values" and "missing"...
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// TODO: SOLR-11695: need "num_values"
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// TODO: add hll & variance - update all assertions to test their values (right after any mention of 'stddev')
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private static List<String> ALL_STATS = Arrays.asList("min", "max", "sum", "stddev", "avg", "sumsq", "unique");
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private static List<String> ALL_STATS = Arrays.asList("min", "max", "sum", "stddev", "avg", "sumsq", "unique", "missing");
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private String STAT_FIELD = "stat_i1";
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private String ALL_STATS_JSON = "";
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@ -81,7 +81,7 @@ public class DistributedFacetSimpleRefinementLongTailTest extends BaseDistribute
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final SolrClient shard0 = clients.get(0);
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final SolrClient shard1 = clients.get(1);
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final SolrClient shard2 = clients.get(2);
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// the 5 top foo_s terms have 100 docs each on every shard
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for (int i = 0; i < 100; i++) {
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for (int j = 0; j < 5; j++) {
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@ -91,7 +91,7 @@ public class DistributedFacetSimpleRefinementLongTailTest extends BaseDistribute
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}
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}
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// 20 foo_s terms that come in "second" with 50 docs each
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// 20 foo_s terms that come in "second" with 50 docs each
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// on both shard0 & shard1 ("bbb_")
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for (int i = 0; i < 50; i++) {
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for (int j = 0; j < 20; j++) {
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@ -141,7 +141,7 @@ public class DistributedFacetSimpleRefinementLongTailTest extends BaseDistribute
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shardFooBuckets[i] = (List<NamedList>)
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((NamedList<NamedList>)clients.get(i).query( req ).getResponse().get("facets")).get("foo").get("buckets");
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}
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// top 5 same on all shards
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for (int i = 0; i < 3; i++) {
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assertEquals(10, shardFooBuckets[i].size());
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@ -187,7 +187,7 @@ public class DistributedFacetSimpleRefinementLongTailTest extends BaseDistribute
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private void checkRefinementAndOverrequesting() throws Exception {
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// // distributed queries // //
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{ // w/o refinement, the default overrequest isn't enough to find the long 'tail' *OR* the correct count for 'bbb0'...
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List<NamedList> foo_buckets = (List<NamedList>)
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((NamedList<NamedList>)
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@ -200,13 +200,13 @@ public class DistributedFacetSimpleRefinementLongTailTest extends BaseDistribute
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assertTrue(bucket.toString(), bucket.get("val").toString().startsWith("aaa"));
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assertEquals(bucket.toString(), 300L, bucket.get("count"));
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}
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// this will be short the "+1" fo the doc added to shard2...
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NamedList bucket = foo_buckets.get(5);
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assertTrue(bucket.toString(), bucket.get("val").equals("bbb0")); // 'tail' is missed
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assertEquals(bucket.toString(), 100L, bucket.get("count")); // will not include the "+1" for the doc added to shard2
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}
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// even if we enable refinement, we still won't find the long 'tail' ...
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// regardless of wether we use either the default overrequest, or disable overrequesting...
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for (String over : Arrays.asList( "", "overrequest:0,")) {
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@ -231,7 +231,7 @@ public class DistributedFacetSimpleRefinementLongTailTest extends BaseDistribute
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assertEquals(-2L, bucket.get("min")); // this min only exists on shard2
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assertEquals(1L, bucket.get("max"));
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// assertEquals(101L, bucket.get("num_values")); // TODO: SOLR-11695
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// assertEquals(0L, bucket.get("missing")); // TODO: SOLR-11695
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assertEquals(0L, bucket.get("missing"));
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assertEquals(48.0D, bucket.get("sum"));
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assertEquals(0.475247524752475D, (double) bucket.get("avg"), 0.1E-7);
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assertEquals(54.0D, (double) bucket.get("sumsq"), 0.1E-7);
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@ -244,7 +244,7 @@ public class DistributedFacetSimpleRefinementLongTailTest extends BaseDistribute
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// this is because of how the "simple" refinement process works: the "top buckets" are determined based
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// on the info available in the first pass request.
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//
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// Even though 'tail' is returned in the top6 for shard2, the cummulative total for 'bbb0' from shard0 and shard1 is
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// Even though 'tail' is returned in the top6 for shard2, the cumulative total for 'bbb0' from shard0 and shard1 is
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// high enough that the simple facet refinement ignores 'tail' because it assumes 'bbb0's final total will be greater.
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//
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// Meanwhile, for the sub-facet on 'bar', a limit==6 means we should correctly find 'tailB' as the top sub-term of 'tail',
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@ -261,14 +261,14 @@ public class DistributedFacetSimpleRefinementLongTailTest extends BaseDistribute
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"{ foo: { type:terms, limit:6, overrequest:20, refine:simple, field:foo_s, facet:{ " +
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" bar: { type:terms, limit:6, " + bar_opts + " field:bar_s }}}}"
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) ).getResponse().get("facets")).get("foo").get("buckets");
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assertEquals(6, buckets.size());
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for (int i = 0; i < 5; i++) {
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NamedList bucket = buckets.get(i);
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assertTrue(bucket.toString(), bucket.get("val").toString().startsWith("aaa"));
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assertEquals(bucket.toString(), 300L, bucket.get("count"));
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}
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NamedList bucket = buckets.get(5);
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assertEquals(bucket.toString(), "tail", bucket.get("val"));
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assertEquals(bucket.toString(), 135L, bucket.get("count"));
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@ -320,8 +320,8 @@ public class DistributedFacetSimpleRefinementLongTailTest extends BaseDistribute
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assertEquals(bucket.toString(), 14L, bucket.get("count"));
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}
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}
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// however: with a lower sub-facet limit==5, and overrequesting disabled,
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// however: with a lower sub-facet limit==5, and overrequesting disabled,
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// we're going to miss out on tailB even if we have refinement
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for (String bar_opts : Arrays.asList( "refine:none, overrequest:0,",
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"refine:simple, overrequest:0," )) {
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@ -351,7 +351,7 @@ public class DistributedFacetSimpleRefinementLongTailTest extends BaseDistribute
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assertEquals(bucket.toString(), 14L, bucket.get("count"));
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}
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}
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}
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private void checkSubFacetStats() throws Exception {
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@ -390,7 +390,7 @@ public class DistributedFacetSimpleRefinementLongTailTest extends BaseDistribute
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assertEquals(-99L, aaa0_Bucket.get("min"));
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assertEquals(693L, aaa0_Bucket.get("max"));
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// assertEquals(300L, aaa0_Bucket.get("num_values")); // TODO: SOLR-11695
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// assertEquals(0L, aaa0_Bucket.get("missing")); // TODO: SOLR-11695
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assertEquals(0L, aaa0_Bucket.get("missing"));
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assertEquals(34650.0D, aaa0_Bucket.get("sum"));
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assertEquals(115.5D, (double) aaa0_Bucket.get("avg"), 0.1E-7);
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assertEquals(1.674585E7D, (double) aaa0_Bucket.get("sumsq"), 0.1E-7);
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@ -404,7 +404,7 @@ public class DistributedFacetSimpleRefinementLongTailTest extends BaseDistribute
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assertEquals(0L, tail_Bucket.get("min"));
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assertEquals(44L, tail_Bucket.get("max"));
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// assertEquals(90L, tail_Bucket.get("num_values")); // TODO: SOLR-11695
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// assertEquals(45L, tail_Bucket.get("missing")); // TODO: SOLR-11695
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assertEquals(45L, tail_Bucket.get("missing"));
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assertEquals(1980.0D, tail_Bucket.get("sum"));
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assertEquals(22.0D, (double) tail_Bucket.get("avg"), 0.1E-7);
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assertEquals(58740.0D, (double) tail_Bucket.get("sumsq"), 0.1E-7);
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@ -420,7 +420,7 @@ public class DistributedFacetSimpleRefinementLongTailTest extends BaseDistribute
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assertEquals(35L, tailB_Bucket.get("min"));
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assertEquals(40L, tailB_Bucket.get("max"));
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// assertEquals(12L, tailB_Bucket.get("num_values")); // TODO: SOLR-11695
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// assertEquals(5L, tailB_Bucket.get("missing")); // TODO: SOLR-11695
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assertEquals(5L, tailB_Bucket.get("missing"));
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assertEquals(450.0D, tailB_Bucket.get("sum"));
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assertEquals(37.5D, (double) tailB_Bucket.get("avg"), 0.1E-7);
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assertEquals(16910.0D, (double) tailB_Bucket.get("sumsq"), 0.1E-7);
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@ -1125,8 +1125,6 @@ public class TestJsonFacets extends SolrTestCaseHS {
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client.commit();
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// test for presence of debugging info
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ModifiableSolrParams debugP = params(p);
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debugP.set("debugQuery","true");
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@ -1256,12 +1254,13 @@ public class TestJsonFacets extends SolrTestCaseHS {
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// test sorting by other stats
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client.testJQ(params(p, "q", "*:*"
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, "json.facet", "{f1:{${terms} type:terms, field:'${cat_s}', sort:'x desc', facet:{x:'min(${num_d})'} }" +
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" , f2:{${terms} type:terms, field:'${cat_s}', sort:'x desc', facet:{x:'max(${num_d})'} } " +
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" , f3:{${terms} type:terms, field:'${cat_s}', sort:'x desc', facet:{x:'unique(${where_s})'} } " +
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" , f4:{${terms} type:terms, field:'${cat_s}', sort:'x desc', facet:{x:'hll(${where_s})'} } " +
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" , f5:{${terms} type:terms, field:'${cat_s}', sort:'x desc', facet:{x:'variance(${num_d})'} } " +
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" , f6:{type:terms, field:${num_d}, limit:1, sort:'x desc', facet:{x:'hll(${num_i})'} } " + // facet on a field that will cause hashing and exercise hll.resize on numeric field
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, "json.facet", "{f1:{${terms} type:terms, field:'${cat_s}', sort:'x desc', facet:{x:'min(${num_d})'} }" +
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" , f2:{${terms} type:terms, field:'${cat_s}', sort:'x desc', facet:{x:'max(${num_d})'} } " +
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" , f3:{${terms} type:terms, field:'${cat_s}', sort:'x desc', facet:{x:'unique(${where_s})'} } " +
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" , f4:{${terms} type:terms, field:'${cat_s}', sort:'x desc', facet:{x:'hll(${where_s})'} } " +
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" , f5:{${terms} type:terms, field:'${cat_s}', sort:'x desc', facet:{x:'variance(${num_d})'} } " +
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" , f6:{type:terms, field:${num_d}, limit:1, sort:'x desc', facet:{x:'hll(${num_i})'} } " + // facet on a field that will cause hashing and exercise hll.resize on numeric field
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" , f7:{type:terms, field:${cat_s}, limit:2, sort:'x desc', facet:{x:'missing(${sparse_num_d})'} } " +
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"}"
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)
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, "facets=={ 'count':6, " +
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@ -1271,6 +1270,7 @@ public class TestJsonFacets extends SolrTestCaseHS {
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", f4:{ 'buckets':[{ val:'A', count:2, x:2 }, { val:'B', count:3, x:2 }]} " +
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", f5:{ 'buckets':[{ val:'B', count:3, x:74.6666666666666 }, { val:'A', count:2, x:1.0 }]} " +
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", f6:{ buckets:[{ val:-9.0, count:1, x:1 }]} " +
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", f7:{ buckets:[{ val:B, count:3, x:3 },{ val:A, count:2, x:0 }]} " +
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"}"
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);
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@ -1284,6 +1284,50 @@ public class TestJsonFacets extends SolrTestCaseHS {
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", f2:{ 'buckets':[{ val:'B', count:3, n1:-2.0}, { val:'A', count:2, n1:6.0 }]} }"
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);
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// test sorting by missing stat with function
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client.testJQ(params(p, "q", "*:*"
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, "json.facet", "{f1:{terms:{${terms} field:'${cat_s}', sort:'n1 desc', facet:{n1:'missing(field(${sparse_num_d}))'} }}" +
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" , f2:{terms:{${terms} field:'${cat_s}', sort:'n1 asc', facet:{n1:'missing(field(${sparse_num_d}))'} }} }"
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)
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, "facets=={ 'count':6, " +
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" f1:{ 'buckets':[{ val:'B', count:3, n1:3 }, { val:'A', count:2, n1:0}]}" +
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", f2:{ 'buckets':[{ val:'A', count:2, n1:0}, { val:'B', count:3, n1:3 }]} }"
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);
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// test sorting by missing stat with domain query
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client.testJQ(params(p, "q", "-id:*"
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, "json.facet", "{f1:{terms:{${terms} field:'${cat_s}', domain:{query:'*:*'}, sort:'n1 desc', facet:{n1:'missing(field(${sparse_num_d}))'} }}" +
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" , f2:{terms:{${terms} field:'${cat_s}', domain:{query:'*:*'}, sort:'n1 asc', facet:{n1:'missing(field(${sparse_num_d}))'} }} }"
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)
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, "facets=={ 'count':0, " +
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" f1:{ 'buckets':[{ val:'B', count:3, n1:3 }, { val:'A', count:2, n1:0}]}" +
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", f2:{ 'buckets':[{ val:'A', count:2, n1:0}, { val:'B', count:3, n1:3 }]} }"
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);
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// test with sub-facet aggregation with stat on field
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client.testJQ(params(p, "q", "*:*"
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, "json.facet", " {f1:{terms:{${terms}, field:'${cat_s}', " +
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"facet:{f2:{terms:{${terms}, field:${where_s}, sort:'index asc', " +
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"facet:{n1:'missing(${sparse_num_d})'}}}}}}}"
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)
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, "facets=={ 'count':6, " +
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" f1:{ 'buckets':[{ val:'B', count:3, f2:{'buckets':[{val:'NJ', count:2, n1:2},{val:'NY', count:1, n1:1}]} }," +
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" { val:'A', count:2, f2:{'buckets':[{val:'NJ', count:1, n1:0},{val:'NY', count:1, n1:0}]}}]}" +
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"}"
|
||||
);
|
||||
|
||||
// test with sub-facet aggregation with stat on func
|
||||
client.testJQ(params(p, "q", "*:*"
|
||||
, "json.facet", " {f1:{terms:{${terms}, field:'${cat_s}', " +
|
||||
"facet:{f2:{terms:{${terms}, field:${where_s}, sort:'index asc', " +
|
||||
"facet:{n1:'missing(field(${sparse_num_d}))'}}}}}}}"
|
||||
)
|
||||
, "facets=={ 'count':6, " +
|
||||
" f1:{ 'buckets':[{ val:'B', count:3, f2:{'buckets':[{val:'NJ', count:2, n1:2},{val:'NY', count:1, n1:1}]} }," +
|
||||
" { val:'A', count:2, f2:{'buckets':[{val:'NJ', count:1, n1:0},{val:'NY', count:1, n1:0}]}}]}" +
|
||||
"}"
|
||||
);
|
||||
|
||||
// facet on numbers to test resize from hashing (may need to be sorting by the metric to test that)
|
||||
client.testJQ(params(p, "q", "*:*"
|
||||
, "json.facet", "{" +
|
||||
|
|
@ -1697,7 +1741,7 @@ public class TestJsonFacets extends SolrTestCaseHS {
|
|||
", numwhere:'unique(${where_s})', unique_num_i:'unique(${num_i})', unique_num_d:'unique(${num_d})', unique_date:'unique(${date})'" +
|
||||
", where_hll:'hll(${where_s})', hll_num_i:'hll(${num_i})', hll_num_d:'hll(${num_d})', hll_date:'hll(${date})'" +
|
||||
", med:'percentile(${num_d},50)', perc:'percentile(${num_d},0,50.0,100)', variance:'variance(${num_d})', stddev:'stddev(${num_d})'" +
|
||||
", mini:'min(${num_i})', maxi:'max(${num_i})'" +
|
||||
", mini:'min(${num_i})', maxi:'max(${num_i})', missing:'missing(${sparse_num_d})'" +
|
||||
" }"
|
||||
)
|
||||
, "facets=={ 'count':6, " +
|
||||
|
|
@ -1705,7 +1749,7 @@ public class TestJsonFacets extends SolrTestCaseHS {
|
|||
", numwhere:2, unique_num_i:4, unique_num_d:5, unique_date:5" +
|
||||
", where_hll:2, hll_num_i:4, hll_num_d:5, hll_date:5" +
|
||||
", med:2.0, perc:[-9.0,2.0,11.0], variance:49.04, stddev:7.002856560004639" +
|
||||
", mini:-5, maxi:7" +
|
||||
", mini:-5, maxi:7, missing:4" +
|
||||
"}"
|
||||
);
|
||||
|
||||
|
|
@ -1762,16 +1806,19 @@ public class TestJsonFacets extends SolrTestCaseHS {
|
|||
|
||||
// test unique on multi-valued field
|
||||
client.testJQ(params(p, "q", "*:*"
|
||||
, "json.facet", "{" +
|
||||
"x:'unique(${multi_ss})'" +
|
||||
",y:{query:{q:'id:2', facet:{x:'unique(${multi_ss})'} }} " +
|
||||
",x2:'hll(${multi_ss})'" +
|
||||
",y2:{query:{q:'id:2', facet:{x:'hll(${multi_ss})'} }} " +
|
||||
|
||||
" }"
|
||||
, "json.facet", "{" +
|
||||
"x:'unique(${multi_ss})'" +
|
||||
",z:'missing(${multi_ss})'" +
|
||||
",z1:'missing(${num_is})'" +
|
||||
",y:{query:{q:'id:2', facet:{x:'unique(${multi_ss})'} }} " +
|
||||
",x2:'hll(${multi_ss})'" +
|
||||
",y2:{query:{q:'id:2', facet:{x:'hll(${multi_ss})'} }} " +
|
||||
" }"
|
||||
)
|
||||
, "facets=={count:6 " +
|
||||
",x:2" +
|
||||
",z:2" +
|
||||
",z1:1" +
|
||||
",y:{count:1, x:2}" + // single document should yield 2 unique values
|
||||
",x2:2" +
|
||||
",y2:{count:1, x:2}" + // single document should yield 2 unique values
|
||||
|
|
@ -2049,12 +2096,12 @@ public class TestJsonFacets extends SolrTestCaseHS {
|
|||
// multi-valued integer
|
||||
client.testJQ(params(p, "q", "*:*"
|
||||
, "json.facet", "{ " +
|
||||
" c1:'unique(${num_is})', c2:'hll(${num_is})'" +
|
||||
" c1:'unique(${num_is})', c2:'hll(${num_is})', c3:'missing(${num_is})'" +
|
||||
",f1:{${terms} type:terms, field:${num_is} } " +
|
||||
"}"
|
||||
)
|
||||
, "facets=={ count:6 " +
|
||||
", c1:5, c2:5" +
|
||||
", c1:5, c2:5, c3:1" +
|
||||
", f1:{ buckets:[ {val:-1,count:2},{val:0,count:2},{val:3,count:2},{val:-5,count:1},{val:2,count:1} ] } " +
|
||||
"} "
|
||||
);
|
||||
|
|
@ -2062,12 +2109,12 @@ public class TestJsonFacets extends SolrTestCaseHS {
|
|||
// multi-valued float
|
||||
client.testJQ(params(p, "q", "*:*"
|
||||
, "json.facet", "{ " +
|
||||
" c1:'unique(${num_fs})', c2:'hll(${num_fs})'" +
|
||||
" c1:'unique(${num_fs})', c2:'hll(${num_fs})', c3:'missing(${num_fs})', c4:'agg(missing(${num_fs}))'" +
|
||||
",f1:{${terms} type:terms, field:${num_fs} } " +
|
||||
"}"
|
||||
)
|
||||
, "facets=={ count:6 " +
|
||||
", c1:5, c2:5" +
|
||||
", c1:5, c2:5, c3:1, c4:1" +
|
||||
", f1:{ buckets:[ {val:-1.5,count:2},{val:0.0,count:2},{val:3.0,count:2},{val:-5.0,count:1},{val:2.0,count:1} ] } " +
|
||||
"} "
|
||||
);
|
||||
|
|
@ -2119,11 +2166,11 @@ public class TestJsonFacets extends SolrTestCaseHS {
|
|||
// currently non-sorting stats.
|
||||
client.testJQ(params(p, "q", "*:*"
|
||||
, "json.facet", "{f1:{type:terms, field:'${cat_s}', facet:{h:'hll(${where_s})' , u:'unique(${where_s})', mind:'min(${num_d})', maxd:'max(${num_d})', mini:'min(${num_i})', maxi:'max(${num_i})'" +
|
||||
", sumd:'sum(${num_d})', avgd:'avg(${num_d})', variance:'variance(${num_d})', stddev:'stddev(${num_d})' } }}"
|
||||
", sumd:'sum(${num_d})', avgd:'avg(${num_d})', variance:'variance(${num_d})', stddev:'stddev(${num_d})', missing:'missing(${multi_ss})'} }}"
|
||||
)
|
||||
, "facets=={ 'count':6, " +
|
||||
"'f1':{ buckets:[{val:B, count:3, h:2, u:2, mind:-9.0, maxd:11.0, mini:-5, maxi:7, sumd:-3.0, avgd:-1.0, variance:74.66666666666667, stddev:8.640987597877148}," +
|
||||
" {val:A, count:2, h:2, u:2, mind:2.0, maxd:4.0, mini:2, maxi:3, sumd:6.0, avgd:3.0, variance:1.0, stddev:1.0}] } } "
|
||||
"'f1':{ buckets:[{val:B, count:3, h:2, u:2, mind:-9.0, maxd:11.0, mini:-5, maxi:7, sumd:-3.0, avgd:-1.0, variance:74.66666666666667, stddev:8.640987597877148, missing:0}," +
|
||||
" {val:A, count:2, h:2, u:2, mind:2.0, maxd:4.0, mini:2, maxi:3, sumd:6.0, avgd:3.0, variance:1.0, stddev:1.0, missing:1}] } } "
|
||||
|
||||
);
|
||||
|
||||
|
|
|
|||
|
|
@ -573,6 +573,7 @@ Unlike all the facets discussed so far, Aggregation functions (also called *face
|
|||
|avg |`avg(popularity)` |average of numeric values
|
||||
|min |`min(salary)` |minimum value
|
||||
|max |`max(mul(price,popularity))` |maximum value
|
||||
|missing |`missing(author)` |number of documents which do not have value for given field or function
|
||||
|unique |`unique(author)` |number of unique values of the given field. Beyond 100 values it yields not exact estimate
|
||||
|uniqueBlock |`uniqueBlock(\_root_)` |same as above with smaller footprint strictly for <<json-faceting-domain-changes.adoc#block-join-domain-changes,counting the number of Block Join blocks>>. The given field must be unique across blocks, and only singlevalued string fields are supported, docValues are recommended.
|
||||
|hll |`hll(author)` |distributed cardinality estimate via hyper-log-log algorithm
|
||||
|
|
|
|||
Loading…
Reference in New Issue