- Elasticsearch Guide: other versions:
- Getting Started
- Setup
- Breaking changes
- Breaking changes in 2.0
- Removed features
- Network changes
- Multiple
path.data
striping - Mapping changes
- CRUD and routing changes
- Query DSL changes
- Search changes
- Aggregation changes
- Parent/Child changes
- Scripting changes
- Index API changes
- Snapshot and Restore changes
- Plugin and packaging changes
- Setting changes
- Stats, info, and
cat
changes - Java API changes
- Breaking changes in 2.0
- API Conventions
- Document APIs
- Search APIs
- Aggregations
- Metrics Aggregations
- Bucket Aggregations
- Children Aggregation
- Date Histogram Aggregation
- Date Range Aggregation
- Filter Aggregation
- Filters Aggregation
- Geo Distance Aggregation
- GeoHash grid Aggregation
- Global Aggregation
- Histogram Aggregation
- IPv4 Range Aggregation
- Missing Aggregation
- Nested Aggregation
- Range Aggregation
- Reverse nested Aggregation
- Sampler Aggregation
- Significant Terms Aggregation
- Terms Aggregation
- Pipeline Aggregations
- Caching heavy aggregations
- Returning only aggregation results
- Aggregation Metadata
- Indices APIs
- Create Index
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- cat APIs
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- Mapping
- Field datatypes
- Meta-Fields
- Mapping parameters
analyzer
boost
coerce
copy_to
doc_values
dynamic
enabled
fielddata
format
geohash
geohash_precision
geohash_prefix
ignore_above
ignore_malformed
include_in_all
index
index_options
lat_lon
fields
norms
null_value
position_increment_gap
precision_step
properties
search_analyzer
similarity
store
term_vector
- Dynamic Mapping
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- Analyzers
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- Standard Token Filter
- ASCII Folding Token Filter
- Length Token Filter
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- Uppercase Token Filter
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- Reverse Token Filter
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- Truncate Token Filter
- Unique Token Filter
- Pattern Capture Token Filter
- Pattern Replace Token Filter
- Trim Token Filter
- Limit Token Count Token Filter
- Hunspell Token Filter
- Common Grams Token Filter
- Normalization Token Filter
- CJK Width Token Filter
- CJK Bigram Token Filter
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- Keep Words Token Filter
- Keep Types Token Filter
- Classic Token Filter
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- Character Filters
- ICU Analysis Plugin
- Modules
- Index Modules
- Testing
- Glossary of terms
- Release Notes
WARNING: Version 2.0 of Elasticsearch has passed its EOL date.
This documentation is no longer being maintained and may be removed. If you are running this version, we strongly advise you to upgrade. For the latest information, see the current release documentation.
Top hits Aggregation
editTop hits Aggregation
editA top_hits
metric aggregator keeps track of the most relevant document being aggregated. This aggregator is intended
to be used as a sub aggregator, so that the top matching documents can be aggregated per bucket.
The top_hits
aggregator can effectively be used to group result sets by certain fields via a bucket aggregator.
One or more bucket aggregators determines by which properties a result set get sliced into.
Options
edit-
from
- The offset from the first result you want to fetch. -
size
- The maximum number of top matching hits to return per bucket. By default the top three matching hits are returned. -
sort
- How the top matching hits should be sorted. By default the hits are sorted by the score of the main query.
Supported per hit features
editThe top_hits aggregation returns regular search hits, because of this many per hit features can be supported:
Example
editIn the following example we group the questions by tag and per tag we show the last active question. For each question only the title field is being included in the source.
{ "aggs": { "top-tags": { "terms": { "field": "tags", "size": 3 }, "aggs": { "top_tag_hits": { "top_hits": { "sort": [ { "last_activity_date": { "order": "desc" } } ], "_source": { "include": [ "title" ] }, "size" : 1 } } } } } }
Possible response snippet:
"aggregations": { "top-tags": { "buckets": [ { "key": "windows-7", "doc_count": 25365, "top_tags_hits": { "hits": { "total": 25365, "max_score": 1, "hits": [ { "_index": "stack", "_type": "question", "_id": "602679", "_score": 1, "_source": { "title": "Windows port opening" }, "sort": [ 1370143231177 ] } ] } } }, { "key": "linux", "doc_count": 18342, "top_tags_hits": { "hits": { "total": 18342, "max_score": 1, "hits": [ { "_index": "stack", "_type": "question", "_id": "602672", "_score": 1, "_source": { "title": "Ubuntu RFID Screensaver lock-unlock" }, "sort": [ 1370143379747 ] } ] } } }, { "key": "windows", "doc_count": 18119, "top_tags_hits": { "hits": { "total": 18119, "max_score": 1, "hits": [ { "_index": "stack", "_type": "question", "_id": "602678", "_score": 1, "_source": { "title": "If I change my computers date / time, what could be affected?" }, "sort": [ 1370142868283 ] } ] } } } ] } }
Field collapse example
editField collapsing or result grouping is a feature that logically groups a result set into groups and per group returns
top documents. The ordering of the groups is determined by the relevancy of the first document in a group. In
Elasticsearch this can be implemented via a bucket aggregator that wraps a top_hits
aggregator as sub-aggregator.
In the example below we search across crawled webpages. For each webpage we store the body and the domain the webpage
belong to. By defining a terms
aggregator on the domain
field we group the result set of webpages by domain. The
top_docs
aggregator is then defined as sub-aggregator, so that the top matching hits are collected per bucket.
Also a max
aggregator is defined which is used by the terms
aggregator’s order feature the return the buckets by
relevancy order of the most relevant document in a bucket.
{ "query": { "match": { "body": "elections" } }, "aggs": { "top-sites": { "terms": { "field": "domain", "order": { "top_hit": "desc" } }, "aggs": { "top_tags_hits": { "top_hits": {} }, "top_hit" : { "max": { "script": "_score" } } } } } }
At the moment the max
(or min
) aggregator is needed to make sure the buckets from the terms
aggregator are
ordered according to the score of the most relevant webpage per domain. The top_hits
aggregator isn’t a metric aggregator
and therefore can’t be used in the order
option of the terms
aggregator.
top_hits support in a nested or reverse_nested aggregator
editIf the top_hits
aggregator is wrapped in a nested
or reverse_nested
aggregator then nested hits are being returned.
Nested hits are in a sense hidden mini documents that are part of regular document where in the mapping a nested field type
has been configured. The top_hits
aggregator has the ability to un-hide these documents if it is wrapped in a nested
or reverse_nested
aggregator. Read more about nested in the nested type mapping.
If nested type has been configured a single document is actually indexed as multiple Lucene documents and they share
the same id. In order to determine the identity of a nested hit there is more needed than just the id, so that is why
nested hits also include their nested identity. The nested identity is kept under the _nested
field in the search hit
and includes the array field and the offset in the array field the nested hit belongs to. The offset is zero based.
Top hits response snippet with a nested hit, which resides in the third slot of array field nested_field1
in document with id 1
:
... "hits": { "total": 25365, "max_score": 1, "hits": [ { "_index": "a", "_type": "b", "_id": "1", "_score": 1, "_nested" : { "field" : "nested_field1", "offset" : 2 } "_source": ... }, ... ] } ...
If _source
is requested then just the part of the source of the nested object is returned, not the entire source of the document.
Also stored fields on the nested inner object level are accessible via top_hits
aggregator residing in a nested
or reverse_nested
aggregator.
Only nested hits will have a _nested
field in the hit, non nested (regular) hits will not have a _nested
field.
The information in _nested
can also be used to parse the original source somewhere else if _source
isn’t enabled.
If there are multiple levels of nested object types defined in mappings then the _nested
information can also be hierarchical
in order to express the identity of nested hits that are two layers deep or more.
In the example below a nested hit resides in the first slot of the field nested_grand_child_field
which then resides in
the second slow of the nested_child_field
field:
... "hits": { "total": 2565, "max_score": 1, "hits": [ { "_index": "a", "_type": "b", "_id": "1", "_score": 1, "_nested" : { "field" : "nested_child_field", "offset" : 1, "_nested" : { "field" : "nested_grand_child_field", "offset" : 0 } } "_source": ... }, ... ] } ...
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