- Elasticsearch Guide: other versions:
- Getting Started
- Setup Elasticsearch
- Breaking changes
- Breaking changes in 5.0
- Search and Query DSL changes
- Mapping changes
- Percolator changes
- Suggester changes
- Index APIs changes
- Document API changes
- Settings changes
- Allocation changes
- HTTP changes
- REST API changes
- CAT API changes
- Java API changes
- Packaging
- Plugin changes
- Filesystem related changes
- Path to data on disk
- Aggregation changes
- Script related changes
- Breaking changes in 5.0
- 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
- Children 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
- 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
- Serial Differencing Aggregation
- Matrix Aggregations
- Caching heavy aggregations
- Returning only aggregation results
- Aggregation Metadata
- Metrics Aggregations
- Indices APIs
- Create Index
- Delete Index
- Get Index
- Indices Exists
- Open / Close Index API
- Shrink Index
- Rollover Index
- Put Mapping
- Get Mapping
- Get Field Mapping
- Types Exists
- Index Aliases
- Update Indices Settings
- Get Settings
- Analyze
- Index Templates
- Shadow replica indices
- 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
- Tokenizers
- Token Filters
- Standard Token Filter
- ASCII Folding 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
- 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
- Compound Word Token Filter
- 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
- Lowercase Processor
- Remove Processor
- Rename Processor
- Script Processor
- Set Processor
- Split Processor
- Sort Processor
- Trim Processor
- Uppercase Processor
- Dot Expander Processor
- How To
- Testing
- Glossary of terms
- Release Notes
- 5.0.2 Release Notes
- 5.0.1 Release Notes
- 5.0.0 Combined Release Notes
- 5.0.0 GA Release Notes
- 5.0.0-rc1 Release Notes
- 5.0.0-beta1 Release Notes
- 5.0.0-alpha5 Release Notes
- 5.0.0-alpha4 Release Notes
- 5.0.0-alpha3 Release Notes
- 5.0.0-alpha2 Release Notes
- 5.0.0-alpha1 Release Notes
- 5.0.0-alpha1 Release Notes (Changes previously released in 2.x)
WARNING: Version 5.0 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.
Lucene Expressions Language
editLucene Expressions Language
editLucene’s expressions compile a javascript
expression to bytecode. They are
designed for high-performance custom ranking and sorting functions and are
enabled for inline
and stored
scripting by default.
Performance
editExpressions were designed to have competitive performance with custom Lucene code. This performance is due to having low per-document overhead as opposed to other scripting engines: expressions do more "up-front".
This allows for very fast execution, even faster than if you had written a native
script.
Syntax
editExpressions support a subset of javascript syntax: a single expression.
See the expressions module documentation for details on what operators and functions are available.
Variables in expression
scripts are available to access:
-
document fields, e.g.
doc['myfield'].value
-
variables and methods that the field supports, e.g.
doc['myfield'].empty
-
Parameters passed into the script, e.g.
mymodifier
-
The current document’s score,
_score
(only available when used in ascript_score
)
You can use Expressions scripts for script_score
, script_fields
, sort scripts, and numeric aggregation
scripts, simply set the lang
parameter to expression
.
Numeric field API
editExpression | Description |
---|---|
|
The value of the field, as a |
|
A boolean indicating if the field has no values within the doc. |
|
The number of values in this document. |
|
The minimum value of the field in this document. |
|
The maximum value of the field in this document. |
|
The median value of the field in this document. |
|
The average of the values in this document. |
|
The sum of the values in this document. |
When a document is missing the field completely, by default the value will be treated as 0
.
You can treat it as another value instead, e.g. doc['myfield'].empty ? 100 : doc['myfield'].value
When a document has multiple values for the field, by default the minimum value is returned.
You can choose a different value instead, e.g. doc['myfield'].sum()
.
When a document is missing the field completely, by default the value will be treated as 0
.
Boolean fields are exposed as numerics, with true
mapped to 1
and false
mapped to 0
.
For example: doc['on_sale'].value ? doc['price'].value * 0.5 : doc['price'].value
Date field API
editDate fields are treated as the number of milliseconds since January 1, 1970 and support the Numeric Fields API above, plus access to some date-specific fields:
Expression | Description |
---|---|
|
Century (1-2920000) |
|
Day (1-31), e.g. |
|
Day of the week (1-7), e.g. |
|
Day of the year, e.g. |
|
Era: |
|
Hour (0-23). |
|
Milliseconds within the day (0-86399999). |
|
Milliseconds within the second (0-999). |
|
Minute within the day (0-1439). |
|
Minute within the hour (0-59). |
|
Month within the year (1-12), e.g. |
|
Second within the day (0-86399). |
|
Second within the minute (0-59). |
|
Year (-292000000 - 292000000). |
|
Year within the century (1-100). |
|
Year within the era (1-292000000). |
The following example shows the difference in years between the date
fields date0 and date1:
doc['date1'].date.year - doc['date0'].date.year
geo_point
field API
editExpression | Description |
---|---|
|
A boolean indicating if the field has no values within the doc. |
|
The latitude of the geo point. |
|
The longitude of the geo point. |
The following example computes distance in kilometers from Washington, DC:
haversin(38.9072, 77.0369, doc['field_name'].lat, doc['field_name'].lon)
In this example the coordinates could have been passed as parameters to the script, e.g. based on geolocation of the user.
Limitations
editThere are a few limitations relative to other script languages:
- Only numeric, boolean, date, and geo_point fields may be accessed
- Stored fields are not available