IMPORTANT: No additional bug fixes or documentation updates
will be released for this version. 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(ScoreScript.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)) {
ScoreScript.Factory factory = new PureDfFactory();
return context.factoryClazz.cast(factory);
}
throw new IllegalArgumentException("Unknown script name "
+ scriptSource);
}
@Override
public void close() {
// optionally close resources
}
@Override
public Set<ScriptContext<?>> getSupportedContexts() {
return Set.of(ScoreScript.CONTEXT);
}
private static class PureDfFactory implements ScoreScript.Factory,
ScriptFactory {
@Override
public boolean isResultDeterministic() {
// PureDfLeafFactory only uses deterministic APIs, this
// implies the results are cacheable.
return true;
}
@Override
public LeafFactory newFactory(
Map<String, Object> params,
SearchLookup lookup
) {
return new PureDfLeafFactory(params, lookup);
}
}
private static class PureDfLeafFactory implements LeafFactory {
private final Map<String, Object> params;
private final SearchLookup lookup;
private final String field;
private final String term;
private PureDfLeafFactory(
Map<String, Object> params, SearchLookup lookup) {
if (params.containsKey("field") == false) {
throw new IllegalArgumentException(
"Missing parameter [field]");
}
if (params.containsKey("term") == false) {
throw new IllegalArgumentException(
"Missing parameter [term]");
}
this.params = params;
this.lookup = lookup;
field = params.get("field").toString();
term = params.get("term").toString();
}
@Override
public boolean needs_score() {
return false; // Return true if the script needs the score
}
@Override
public ScoreScript newInstance(DocReader docReader)
throws IOException {
DocValuesDocReader dvReader = DocValuesDocReader) docReader); PostingsEnum postings = dvReader.getLeafReaderContext() .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 ScoreScript(params, lookup, docReader) {
@Override
public double execute(
ExplanationHolder explanation
) {
return 0.0d;
}
};
}
return new ScoreScript(params, lookup, docReader) {
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 execute(ExplanationHolder explanation) {
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);
}
}
};
}
}
}
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"
}
}
}
}
]
}
}
}