- 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 6.0
- 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
- 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
- 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
- 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
- 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
- Get Buckets
- Get Categories
- Get Datafeeds
- Get Datafeed Statistics
- Get Influencers
- Get Jobs
- Get Job Statistics
- Get Model Snapshots
- Get Records
- Open Jobs
- Post Data to Jobs
- Preview Datafeeds
- 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
- X-Pack Release Notes
WARNING: Version 6.0 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.
Advanced scripts using script engines
editAdvanced scripts using script engines
editA ScriptEngine
is a backend for implementing a scripting language. It may also
be used to write scripts that need to use advanced internals of scripting. For example,
a script that wants to use term frequencies while scoring.
The plugin documentation has more information on
how to write a plugin so that Elasticsearch will properly load it. To register
the ScriptEngine
, your plugin should implement the ScriptPlugin
interface
and override the getScriptEngine(Settings settings)
method.
The following is an example of a custom ScriptEngine
which uses the language
name expert_scripts
. It implements a single script called pure_df
which
may be used as a search script to override each document’s score as
the document frequency of a provided term.
private static class MyExpertScriptEngine implements ScriptEngine { @Override public String getType() { return "expert_scripts"; } @Override public <T> T compile(String scriptName, String scriptSource, ScriptContext<T> context, Map<String, String> params) { if (context.equals(SearchScript.CONTEXT) == false) { throw new IllegalArgumentException(getType() + " scripts cannot be used for context [" + context.name + "]"); } // we use the script "source" as the script identifier if ("pure_df".equals(scriptSource)) { SearchScript.Factory factory = (p, lookup) -> new SearchScript.LeafFactory() { final String field; final String term; { if (p.containsKey("field") == false) { throw new IllegalArgumentException("Missing parameter [field]"); } if (p.containsKey("term") == false) { throw new IllegalArgumentException("Missing parameter [term]"); } field = p.get("field").toString(); term = p.get("term").toString(); } @Override public SearchScript newInstance(LeafReaderContext context) throws IOException { PostingsEnum postings = context.reader().postings(new Term(field, term)); if (postings == null) { // the field and/or term don't exist in this segment, so always return 0 return new SearchScript(p, lookup, context) { @Override public double runAsDouble() { return 0.0d; } }; } return new SearchScript(p, lookup, context) { int currentDocid = -1; @Override public void setDocument(int docid) { // advance has undefined behavior calling with a docid <= its current docid if (postings.docID() < docid) { try { postings.advance(docid); } catch (IOException e) { throw new UncheckedIOException(e); } } currentDocid = docid; } @Override public double runAsDouble() { if (postings.docID() != currentDocid) { // advance moved past the current doc, so this doc has no occurrences of the term return 0.0d; } try { return postings.freq(); } catch (IOException e) { throw new UncheckedIOException(e); } } }; } @Override public boolean needs_score() { return false; } }; return context.factoryClazz.cast(factory); } throw new IllegalArgumentException("Unknown script name " + scriptSource); } @Override public void close() { // optionally close resources } }
You can execute the script by specifying its lang
as expert_scripts
, and the name
of the script as the script source:
POST /_search { "query": { "function_score": { "query": { "match": { "body": "foo" } }, "functions": [ { "script_score": { "script": { "source": "pure_df", "lang" : "expert_scripts", "params": { "field": "body", "term": "foo" } } } } ] } } }