use of org.elasticsearch.search.aggregations.bucket.terms.TermsAggregator.BucketCountThresholds in project elasticsearch by elastic.
the class SignificantTermsAggregatorFactory method doCreateInternal.
@Override
protected Aggregator doCreateInternal(ValuesSource valuesSource, Aggregator parent, boolean collectsFromSingleBucket, List<PipelineAggregator> pipelineAggregators, Map<String, Object> metaData) throws IOException {
if (collectsFromSingleBucket == false) {
return asMultiBucketAggregator(this, context, parent);
}
numberOfAggregatorsCreated++;
BucketCountThresholds bucketCountThresholds = new BucketCountThresholds(this.bucketCountThresholds);
if (bucketCountThresholds.getShardSize() == SignificantTermsAggregationBuilder.DEFAULT_BUCKET_COUNT_THRESHOLDS.getShardSize()) {
// The user has not made a shardSize selection .
// Use default heuristic to avoid any wrong-ranking caused by
// distributed counting
// but request double the usual amount.
// We typically need more than the number of "top" terms requested
// by other aggregations
// as the significance algorithm is in less of a position to
// down-select at shard-level -
// some of the things we want to find have only one occurrence on
// each shard and as
// such are impossible to differentiate from non-significant terms
// at that early stage.
bucketCountThresholds.setShardSize(2 * BucketUtils.suggestShardSideQueueSize(bucketCountThresholds.getRequiredSize(), context.numberOfShards()));
}
if (valuesSource instanceof ValuesSource.Bytes) {
ExecutionMode execution = null;
if (executionHint != null) {
execution = ExecutionMode.fromString(executionHint);
}
if (!(valuesSource instanceof ValuesSource.Bytes.WithOrdinals)) {
execution = ExecutionMode.MAP;
}
if (execution == null) {
if (Aggregator.descendsFromBucketAggregator(parent)) {
execution = ExecutionMode.GLOBAL_ORDINALS_HASH;
} else {
execution = ExecutionMode.GLOBAL_ORDINALS;
}
}
assert execution != null;
DocValueFormat format = config.format();
if ((includeExclude != null) && (includeExclude.isRegexBased()) && format != DocValueFormat.RAW) {
throw new AggregationExecutionException("Aggregation [" + name + "] cannot support regular expression style include/exclude " + "settings as they can only be applied to string fields. Use an array of values for include/exclude clauses");
}
return execution.create(name, factories, valuesSource, format, bucketCountThresholds, includeExclude, context, parent, significanceHeuristic, this, pipelineAggregators, metaData);
}
if ((includeExclude != null) && (includeExclude.isRegexBased())) {
throw new AggregationExecutionException("Aggregation [" + name + "] cannot support regular expression style include/exclude " + "settings as they can only be applied to string fields. Use an array of numeric values for include/exclude clauses used to filter numeric fields");
}
if (valuesSource instanceof ValuesSource.Numeric) {
if (((ValuesSource.Numeric) valuesSource).isFloatingPoint()) {
throw new UnsupportedOperationException("No support for examining floating point numerics");
}
IncludeExclude.LongFilter longFilter = null;
if (includeExclude != null) {
longFilter = includeExclude.convertToLongFilter(config.format());
}
return new SignificantLongTermsAggregator(name, factories, (ValuesSource.Numeric) valuesSource, config.format(), bucketCountThresholds, context, parent, significanceHeuristic, this, longFilter, pipelineAggregators, metaData);
}
throw new AggregationExecutionException("significant_terms aggregation cannot be applied to field [" + config.fieldContext().field() + "]. It can only be applied to numeric or string fields.");
}
use of org.elasticsearch.search.aggregations.bucket.terms.TermsAggregator.BucketCountThresholds in project elasticsearch by elastic.
the class TermsAggregatorFactory method doCreateInternal.
@Override
protected Aggregator doCreateInternal(ValuesSource valuesSource, Aggregator parent, boolean collectsFromSingleBucket, List<PipelineAggregator> pipelineAggregators, Map<String, Object> metaData) throws IOException {
if (collectsFromSingleBucket == false) {
return asMultiBucketAggregator(this, context, parent);
}
BucketCountThresholds bucketCountThresholds = new BucketCountThresholds(this.bucketCountThresholds);
if (!(order == InternalOrder.TERM_ASC || order == InternalOrder.TERM_DESC) && bucketCountThresholds.getShardSize() == TermsAggregationBuilder.DEFAULT_BUCKET_COUNT_THRESHOLDS.getShardSize()) {
// The user has not made a shardSize selection. Use default
// heuristic to avoid any wrong-ranking caused by distributed
// counting
bucketCountThresholds.setShardSize(BucketUtils.suggestShardSideQueueSize(bucketCountThresholds.getRequiredSize(), context.numberOfShards()));
}
bucketCountThresholds.ensureValidity();
if (valuesSource instanceof ValuesSource.Bytes) {
ExecutionMode execution = null;
if (executionHint != null) {
execution = ExecutionMode.fromString(executionHint);
}
// In some cases, using ordinals is just not supported: override it
if (!(valuesSource instanceof ValuesSource.Bytes.WithOrdinals)) {
execution = ExecutionMode.MAP;
}
final long maxOrd;
final double ratio;
if (execution == null || execution.needsGlobalOrdinals()) {
ValuesSource.Bytes.WithOrdinals valueSourceWithOrdinals = (ValuesSource.Bytes.WithOrdinals) valuesSource;
IndexSearcher indexSearcher = context.searcher();
maxOrd = valueSourceWithOrdinals.globalMaxOrd(indexSearcher);
ratio = maxOrd / ((double) indexSearcher.getIndexReader().numDocs());
} else {
maxOrd = -1;
ratio = -1;
}
// Let's try to use a good default
if (execution == null) {
// ordinals would be sparse so we opt for hash
if (Aggregator.descendsFromBucketAggregator(parent) || (includeExclude != null && includeExclude.isPartitionBased())) {
execution = ExecutionMode.GLOBAL_ORDINALS_HASH;
} else {
if (factories == AggregatorFactories.EMPTY) {
if (ratio <= 0.5 && maxOrd <= 2048) {
// 0.5: At least we need reduce the number of global
// ordinals look-ups by half
// 2048: GLOBAL_ORDINALS_LOW_CARDINALITY has
// additional memory usage, which directly linked to
// maxOrd, so we need to limit.
execution = ExecutionMode.GLOBAL_ORDINALS_LOW_CARDINALITY;
} else {
execution = ExecutionMode.GLOBAL_ORDINALS;
}
} else {
execution = ExecutionMode.GLOBAL_ORDINALS;
}
}
}
SubAggCollectionMode cm = collectMode;
if (cm == null) {
cm = SubAggCollectionMode.DEPTH_FIRST;
if (factories != AggregatorFactories.EMPTY) {
cm = subAggCollectionMode(bucketCountThresholds.getShardSize(), maxOrd);
}
}
DocValueFormat format = config.format();
if ((includeExclude != null) && (includeExclude.isRegexBased()) && format != DocValueFormat.RAW) {
throw new AggregationExecutionException("Aggregation [" + name + "] cannot support regular expression style include/exclude " + "settings as they can only be applied to string fields. Use an array of values for include/exclude clauses");
}
return execution.create(name, factories, valuesSource, order, format, bucketCountThresholds, includeExclude, context, parent, cm, showTermDocCountError, pipelineAggregators, metaData);
}
if ((includeExclude != null) && (includeExclude.isRegexBased())) {
throw new AggregationExecutionException("Aggregation [" + name + "] cannot support regular expression style include/exclude " + "settings as they can only be applied to string fields. Use an array of numeric values for include/exclude clauses used to filter numeric fields");
}
if (valuesSource instanceof ValuesSource.Numeric) {
IncludeExclude.LongFilter longFilter = null;
SubAggCollectionMode cm = collectMode;
if (cm == null) {
if (factories != AggregatorFactories.EMPTY) {
cm = subAggCollectionMode(bucketCountThresholds.getShardSize(), -1);
} else {
cm = SubAggCollectionMode.DEPTH_FIRST;
}
}
if (((ValuesSource.Numeric) valuesSource).isFloatingPoint()) {
if (includeExclude != null) {
longFilter = includeExclude.convertToDoubleFilter();
}
return new DoubleTermsAggregator(name, factories, (ValuesSource.Numeric) valuesSource, config.format(), order, bucketCountThresholds, context, parent, cm, showTermDocCountError, longFilter, pipelineAggregators, metaData);
}
if (includeExclude != null) {
longFilter = includeExclude.convertToLongFilter(config.format());
}
return new LongTermsAggregator(name, factories, (ValuesSource.Numeric) valuesSource, config.format(), order, bucketCountThresholds, context, parent, cm, showTermDocCountError, longFilter, pipelineAggregators, metaData);
}
throw new AggregationExecutionException("terms aggregation cannot be applied to field [" + config.fieldContext().field() + "]. It can only be applied to numeric or string fields.");
}
Aggregations