- Elasticsearch Guide: other versions:
- Getting Started
- Set up Elasticsearch
- Installing Elasticsearch
- Configuring Elasticsearch
- Important Elasticsearch configuration
- Important System Configuration
- Bootstrap Checks
- Heap size check
- File descriptor check
- Memory lock check
- Maximum number of threads check
- Maximum size virtual memory check
- Max file size check
- Maximum map count check
- Client JVM check
- Use serial collector check
- System call filter check
- OnError and OnOutOfMemoryError checks
- Early-access check
- G1GC check
- Stopping Elasticsearch
- Upgrade Elasticsearch
- Set up X-Pack
- Breaking changes
- Breaking changes in 6.0
- Aggregations changes
- Analysis changes
- Cat API changes
- Clients changes
- Cluster changes
- Document API changes
- Indices changes
- Ingest changes
- Java API changes
- Mapping changes
- Packaging changes
- Percolator changes
- Plugins changes
- Reindex changes
- REST changes
- Scripting changes
- Search and Query DSL changes
- Settings changes
- Stats and info changes
- Breaking changes in 6.1
- Breaking changes in 6.0
- X-Pack Breaking Changes
- API Conventions
- Document APIs
- Search APIs
- Aggregations
- Metrics Aggregations
- Avg Aggregation
- Cardinality Aggregation
- Extended Stats Aggregation
- Geo Bounds Aggregation
- Geo Centroid Aggregation
- Max Aggregation
- Min Aggregation
- Percentiles Aggregation
- Percentile Ranks Aggregation
- Scripted Metric Aggregation
- Stats Aggregation
- Sum Aggregation
- Top Hits Aggregation
- Value Count Aggregation
- Bucket Aggregations
- Adjacency Matrix Aggregation
- Children Aggregation
- Composite Aggregation
- Date Histogram Aggregation
- Date Range Aggregation
- Diversified Sampler Aggregation
- Filter Aggregation
- Filters Aggregation
- Geo Distance Aggregation
- GeoHash grid Aggregation
- Global Aggregation
- Histogram Aggregation
- IP Range Aggregation
- Missing Aggregation
- Nested Aggregation
- Range Aggregation
- Reverse nested Aggregation
- Sampler Aggregation
- Significant Terms Aggregation
- Significant Text Aggregation
- Terms Aggregation
- Pipeline Aggregations
- Avg Bucket Aggregation
- Derivative Aggregation
- Max Bucket Aggregation
- Min Bucket Aggregation
- Sum Bucket Aggregation
- Stats Bucket Aggregation
- Extended Stats Bucket Aggregation
- Percentiles Bucket Aggregation
- Moving Average Aggregation
- Cumulative Sum Aggregation
- Bucket Script Aggregation
- Bucket Selector Aggregation
- Bucket Sort Aggregation
- Serial Differencing Aggregation
- Matrix Aggregations
- Caching heavy aggregations
- Returning only aggregation results
- Aggregation Metadata
- Returning the type of the aggregation
- Metrics Aggregations
- Indices APIs
- Create Index
- Delete Index
- Get Index
- Indices Exists
- Open / Close Index API
- Shrink Index
- Split Index
- Rollover Index
- Put Mapping
- Get Mapping
- Get Field Mapping
- Types Exists
- Index Aliases
- Update Indices Settings
- Get Settings
- Analyze
- Index Templates
- Indices Stats
- Indices Segments
- Indices Recovery
- Indices Shard Stores
- Clear Cache
- Flush
- Refresh
- Force Merge
- cat APIs
- Cluster APIs
- Query DSL
- Mapping
- Analysis
- Anatomy of an analyzer
- Testing analyzers
- Analyzers
- Normalizers
- Tokenizers
- Token Filters
- Standard Token Filter
- ASCII Folding Token Filter
- Flatten Graph Token Filter
- Length Token Filter
- Lowercase Token Filter
- Uppercase Token Filter
- NGram Token Filter
- Edge NGram Token Filter
- Porter Stem Token Filter
- Shingle Token Filter
- Stop Token Filter
- Word Delimiter Token Filter
- Word Delimiter Graph Token Filter
- Stemmer Token Filter
- Stemmer Override Token Filter
- Keyword Marker Token Filter
- Keyword Repeat Token Filter
- KStem Token Filter
- Snowball Token Filter
- Phonetic Token Filter
- Synonym Token Filter
- Synonym Graph Token Filter
- Compound Word Token Filters
- Reverse Token Filter
- Elision Token Filter
- 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
- Delimited Payload Token Filter
- Keep Words Token Filter
- Keep Types Token Filter
- Classic Token Filter
- Apostrophe Token Filter
- Decimal Digit Token Filter
- Fingerprint Token Filter
- Minhash Token Filter
- Character Filters
- Modules
- Index Modules
- Ingest Node
- Pipeline Definition
- Ingest APIs
- Accessing Data in Pipelines
- Handling Failures in Pipelines
- Processors
- Append Processor
- Convert Processor
- Date Processor
- Date Index Name Processor
- Fail Processor
- Foreach Processor
- Grok Processor
- Gsub Processor
- Join Processor
- JSON Processor
- KV Processor
- Lowercase Processor
- Remove Processor
- Rename Processor
- Script Processor
- Set Processor
- Split Processor
- Sort Processor
- Trim Processor
- Uppercase Processor
- Dot Expander Processor
- URL Decode Processor
- Monitoring Elasticsearch
- X-Pack APIs
- Info API
- Explore API
- Machine Learning APIs
- Close Jobs
- Create Datafeeds
- Create Jobs
- Delete Datafeeds
- Delete Jobs
- Delete Model Snapshots
- Flush Jobs
- Forecast Jobs
- Get Buckets
- Get Overall Buckets
- Get Categories
- Get Datafeeds
- Get Datafeed Statistics
- Get Influencers
- Get Jobs
- Get Job Statistics
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- Get Records
- Open Jobs
- Post Data to Jobs
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- Revert Model Snapshots
- Start Datafeeds
- Stop Datafeeds
- Update Datafeeds
- Update Jobs
- Update Model Snapshots
- Security APIs
- Watcher APIs
- Migration APIs
- Deprecation Info APIs
- Definitions
- X-Pack Commands
- How To
- Testing
- Glossary of terms
- Release Notes
- 6.1.4 Release Notes
- 6.1.3 Release Notes
- 6.1.2 Release Notes
- 6.1.1 Release Notes
- 6.1.0 Release Notes
- 6.0.1 Release Notes
- 6.0.0 Release Notes
- 6.0.0-rc2 Release Notes
- 6.0.0-rc1 Release Notes
- 6.0.0-beta2 Release Notes
- 6.0.0-beta1 Release Notes
- 6.0.0-alpha2 Release Notes
- 6.0.0-alpha1 Release Notes
- 6.0.0-alpha1 Release Notes (Changes previously released in 5.x)
- X-Pack Release Notes
WARNING: Version 6.1 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.
Accessing document fields and special variables
editAccessing document fields and special variables
editDepending on where a script is used, it will have access to certain special variables and document fields.
Update scripts
editA script used in the update,
update-by-query, or reindex
API will have access to the ctx
variable which exposes:
|
Access to the document |
|
The operation that should be applied to the document: |
|
Access to document meta-fields, some of which may be read-only. |
Search and Aggregation scripts
editWith the exception of script fields which are executed once per search hit, scripts used in search and aggregations will be executed once for every document which might match a query or an aggregation. Depending on how many documents you have, this could mean millions or billions of executions: these scripts need to be fast!
Field values can be accessed from a script using
doc-values, or
stored fields or _source
field, which are explained below.
Accessing the score of a document within a script
editScripts used in the function_score
query,
in script-based sorting, or in
aggregations have access to the _score
variable which
represents the current relevance score of a document.
Here’s an example of using a script in a
function_score
query to alter the
relevance _score
of each document:
PUT my_index/my_type/1?refresh { "text": "quick brown fox", "popularity": 1 } PUT my_index/my_type/2?refresh { "text": "quick fox", "popularity": 5 } GET my_index/_search { "query": { "function_score": { "query": { "match": { "text": "quick brown fox" } }, "script_score": { "script": { "lang": "expression", "source": "_score * doc['popularity']" } } } } }
Doc Values
editBy far the fastest most efficient way to access a field value from a
script is to use the doc['field_name']
syntax, which retrieves the field
value from doc values. Doc values are a columnar field value
store, enabled by default on all fields except for analyzed text
fields.
PUT my_index/my_type/1?refresh { "cost_price": 100 } GET my_index/_search { "script_fields": { "sales_price": { "script": { "lang": "expression", "source": "doc['cost_price'] * markup", "params": { "markup": 0.2 } } } } }
Doc-values can only return "simple" field values like numbers, dates, geo- points, terms, etc, or arrays of these values if the field is multi-valued. It cannot return JSON objects.
Doc values and text
fields
The doc['field']
syntax can also be used for analyzed text
fields
if fielddata
is enabled, but BEWARE: enabling fielddata on a
text
field requires loading all of the terms into the JVM heap, which can be
very expensive both in terms of memory and CPU. It seldom makes sense to
access text
fields from scripts.
Stored Fields and _source
editStored fields — fields explicitly marked as
"store": true
— can be accessed using the
_fields['field_name'].value
or _fields['field_name'].values
syntax.
The document _source
, which is really just a
special stored field, can be accessed using the _source.field_name
syntax.
The _source
is loaded as a map-of-maps, so properties within object fields
can be accessed as, for example, _source.name.first
.
Prefer doc-values to stored fields
Stored fields (which includes the stored _source
field) are much slower than
doc-values. They are optimised for returning several fields per result,
while doc values are optimised for accessing the value of a specific field in
many documents.
It makes sense to use _source
or stored fields when generating a
script field for the top ten hits from a search
result but, for other search and aggregation use cases, always prefer using
doc values.
For instance:
PUT my_index { "mappings": { "my_type": { "properties": { "title": { "type": "text" }, "first_name": { "type": "text", "store": true }, "last_name": { "type": "text", "store": true } } } } } PUT my_index/my_type/1?refresh { "title": "Mr", "first_name": "Barry", "last_name": "White" } GET my_index/_search { "script_fields": { "source": { "script": { "lang": "painless", "source": "params._source.title + ' ' + params._source.first_name + ' ' + params._source.last_name" } }, "stored_fields": { "script": { "lang": "painless", "source": "params._fields['first_name'].value + ' ' + params._fields['last_name'].value" } } } }
The |
|
The |
Stored vs _source
The _source
field is just a special stored field, so the performance is
similar to that of other stored fields. The _source
provides access to the
original document body that was indexed (including the ability to distinguish
null
values from empty fields, single-value arrays from plain scalars, etc).
The only time it really makes sense to use stored fields instead of the
_source
field is when the _source
is very large and it is less costly to
access a few small stored fields instead of the entire _source
.
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