Class SignificantTermsAggregation
java.lang.Object
co.elastic.clients.elasticsearch._types.aggregations.AggregationBase
co.elastic.clients.elasticsearch._types.aggregations.BucketAggregationBase
co.elastic.clients.elasticsearch._types.aggregations.SignificantTermsAggregation
- All Implemented Interfaces:
AggregationVariant
,JsonpSerializable
@JsonpDeserializable
public class SignificantTermsAggregation
extends BucketAggregationBase
implements AggregationVariant
- See Also:
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Nested Class Summary
Nested classes/interfaces inherited from class co.elastic.clients.elasticsearch._types.aggregations.BucketAggregationBase
BucketAggregationBase.AbstractBuilder<BuilderT extends BucketAggregationBase.AbstractBuilder<BuilderT>>
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Field Summary
Modifier and TypeFieldDescriptionstatic final JsonpDeserializer<SignificantTermsAggregation>
Json deserializer forSignificantTermsAggregation
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Method Summary
Modifier and TypeMethodDescriptionAggregation variant kind.final Query
A background filter that can be used to focus in on significant terms within a narrower context, instead of the entire index.final ChiSquareHeuristic
Use Chi square, as described in "Information Retrieval", Manning et al., Chapter 13.5.2, as the significance score.final TermsExclude
exclude()
Terms to exclude.Mechanism by which the aggregation should be executed: using field values directly or using global ordinals.final String
field()
The field from which to return significant terms.gnd()
Use Google normalized distance as described in "The Google Similarity Distance", Cilibrasi and Vitanyi, 2007, as the significance score.final TermsInclude
include()
Terms to include.final EmptyObject
jlh()
Use JLH score as the significance score.final Long
Only return terms that are found in more thanmin_doc_count
hits.Use mutual information as described in "Information Retrieval", Manning et al., Chapter 13.5.1, as the significance score.static SignificantTermsAggregation
final PercentageScoreHeuristic
A simple calculation of the number of documents in the foreground sample with a term divided by the number of documents in the background with the term.final ScriptedHeuristic
Customized score, implemented via a script.protected void
serializeInternal
(jakarta.json.stream.JsonGenerator generator, JsonpMapper mapper) protected static void
setupSignificantTermsAggregationDeserializer
(ObjectDeserializer<SignificantTermsAggregation.Builder> op) final Long
Regulates the certainty a shard has if the term should actually be added to the candidate list or not with respect to themin_doc_count
.final Integer
Can be used to control the volumes of candidate terms produced by each shard.final Integer
size()
The number of buckets returned out of the overall terms list.Methods inherited from class co.elastic.clients.elasticsearch._types.aggregations.BucketAggregationBase
setupBucketAggregationBaseDeserializer
Methods inherited from class co.elastic.clients.elasticsearch._types.aggregations.AggregationBase
meta, name, serialize, setupAggregationBaseDeserializer, toString
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
Methods inherited from interface co.elastic.clients.elasticsearch._types.aggregations.AggregationVariant
_toAggregation
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Field Details
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_DESERIALIZER
Json deserializer forSignificantTermsAggregation
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Method Details
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of
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_aggregationKind
Aggregation variant kind.- Specified by:
_aggregationKind
in interfaceAggregationVariant
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backgroundFilter
A background filter that can be used to focus in on significant terms within a narrower context, instead of the entire index.API name:
background_filter
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chiSquare
Use Chi square, as described in "Information Retrieval", Manning et al., Chapter 13.5.2, as the significance score.API name:
chi_square
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exclude
Terms to exclude.API name:
exclude
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executionHint
Mechanism by which the aggregation should be executed: using field values directly or using global ordinals.API name:
execution_hint
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field
The field from which to return significant terms.API name:
field
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gnd
Use Google normalized distance as described in "The Google Similarity Distance", Cilibrasi and Vitanyi, 2007, as the significance score.API name:
gnd
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include
Terms to include.API name:
include
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jlh
Use JLH score as the significance score.API name:
jlh
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minDocCount
Only return terms that are found in more thanmin_doc_count
hits.API name:
min_doc_count
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mutualInformation
Use mutual information as described in "Information Retrieval", Manning et al., Chapter 13.5.1, as the significance score.API name:
mutual_information
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percentage
A simple calculation of the number of documents in the foreground sample with a term divided by the number of documents in the background with the term.API name:
percentage
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scriptHeuristic
Customized score, implemented via a script.API name:
script_heuristic
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shardMinDocCount
Regulates the certainty a shard has if the term should actually be added to the candidate list or not with respect to themin_doc_count
. Terms will only be considered if their local shard frequency within the set is higher than theshard_min_doc_count
.API name:
shard_min_doc_count
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shardSize
Can be used to control the volumes of candidate terms produced by each shard. By default,shard_size
will be automatically estimated based on the number of shards and thesize
parameter.API name:
shard_size
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size
The number of buckets returned out of the overall terms list.API name:
size
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serializeInternal
- Overrides:
serializeInternal
in classAggregationBase
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setupSignificantTermsAggregationDeserializer
protected static void setupSignificantTermsAggregationDeserializer(ObjectDeserializer<SignificantTermsAggregation.Builder> op)
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