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Getting Started with Painless

Painless is a simple, secure scripting language designed specifically for use with Elasticsearch. It is the default scripting language for Elasticsearch and can safely be used for inline and stored scripts. For a detailed description of the Painless syntax and language features, see the {painless}/painless-lang-spec.html[Painless Language Specification].

You can use Painless anywhere scripts can be used in Elasticsearch. Painless provides:

  • Fast performance: Painless scripts run several times faster than the alternatives.

  • Safety: Fine-grained whitelist with method call/field granularity. See the {painless}/painless-api-reference.html[Painless API Reference] for a complete list of available classes and methods.

  • Optional typing: Variables and parameters can use explicit types or the dynamic def type.

  • Syntax: Extends Java’s syntax to provide Groovy-style scripting language features that make scripts easier to write.

  • Optimizations: Designed specifically for Elasticsearch scripting.

Painless Examples

To illustrate how Painless works, let’s load some hockey stats into an Elasticsearch index:

PUT hockey/player/_bulk?refresh
{"index":{"_id":1}}
{"first":"johnny","last":"gaudreau","goals":[9,27,1],"assists":[17,46,0],"gp":[26,82,1],"born":"1993/08/13"}
{"index":{"_id":2}}
{"first":"sean","last":"monohan","goals":[7,54,26],"assists":[11,26,13],"gp":[26,82,82],"born":"1994/10/12"}
{"index":{"_id":3}}
{"first":"jiri","last":"hudler","goals":[5,34,36],"assists":[11,62,42],"gp":[24,80,79],"born":"1984/01/04"}
{"index":{"_id":4}}
{"first":"micheal","last":"frolik","goals":[4,6,15],"assists":[8,23,15],"gp":[26,82,82],"born":"1988/02/17"}
{"index":{"_id":5}}
{"first":"sam","last":"bennett","goals":[5,0,0],"assists":[8,1,0],"gp":[26,1,0],"born":"1996/06/20"}
{"index":{"_id":6}}
{"first":"dennis","last":"wideman","goals":[0,26,15],"assists":[11,30,24],"gp":[26,81,82],"born":"1983/03/20"}
{"index":{"_id":7}}
{"first":"david","last":"jones","goals":[7,19,5],"assists":[3,17,4],"gp":[26,45,34],"born":"1984/08/10"}
{"index":{"_id":8}}
{"first":"tj","last":"brodie","goals":[2,14,7],"assists":[8,42,30],"gp":[26,82,82],"born":"1990/06/07"}
{"index":{"_id":39}}
{"first":"mark","last":"giordano","goals":[6,30,15],"assists":[3,30,24],"gp":[26,60,63],"born":"1983/10/03"}
{"index":{"_id":10}}
{"first":"mikael","last":"backlund","goals":[3,15,13],"assists":[6,24,18],"gp":[26,82,82],"born":"1989/03/17"}
{"index":{"_id":11}}
{"first":"joe","last":"colborne","goals":[3,18,13],"assists":[6,20,24],"gp":[26,67,82],"born":"1990/01/30"}

Accessing Doc Values from Painless

Document values can be accessed from a Map named doc.

For example, the following script calculates a player’s total goals. This example uses a strongly typed int and a for loop.

GET hockey/_search
{
  "query": {
    "function_score": {
      "script_score": {
        "script": {
          "lang": "painless",
          "source": """
            int total = 0;
            for (int i = 0; i < doc['goals'].length; ++i) {
              total += doc['goals'][i];
            }
            return total;
          """
        }
      }
    }
  }
}

Alternatively, you could do the same thing using a script field instead of a function score:

GET hockey/_search
{
  "query": {
    "match_all": {}
  },
  "script_fields": {
    "total_goals": {
      "script": {
        "lang": "painless",
        "source": """
          int total = 0;
          for (int i = 0; i < doc['goals'].length; ++i) {
            total += doc['goals'][i];
          }
          return total;
        """
      }
    }
  }
}

The following example uses a Painless script to sort the players by their combined first and last names. The names are accessed using doc['first'].value and doc['last'].value.

GET hockey/_search
{
  "query": {
    "match_all": {}
  },
  "sort": {
    "_script": {
      "type": "string",
      "order": "asc",
      "script": {
        "lang": "painless",
        "source": "doc['first.keyword'].value + ' ' + doc['last.keyword'].value"
      }
    }
  }
}
Missing values

If you request the value from a field field that isn’t in the document, doc['field'].value for this document returns:

  • 0 if a field has a numeric datatype (long, double etc.)

  • false is a field has a boolean datatype

  • epoch date if a field has a date datatype

  • null if a field has a string datatype

  • null if a field has a geo datatype

  • "" if a field has a binary datatype

Important
Starting in 7.0, doc['field'].value throws an exception if the field is missing in a document. To enable this behavior now, set a {ref}/jvm-options.html[jvm.option] -Des.scripting.exception_for_missing_value=true on a node. If you do not enable this behavior, a deprecation warning may be logged when painless processes a missing value.

To check if a document is missing a value, you can call doc['field'].size() == 0.

Updating Fields with Painless

You can also easily update fields. You access the original source for a field as ctx._source.<field-name>.

First, let’s look at the source data for a player by submitting the following request:

GET hockey/_search
{
  "query": {
    "term": {
      "_id": 1
    }
  }
}

To change player 1’s last name to hockey, simply set ctx._source.last to the new value:

POST hockey/player/1/_update
{
  "script": {
    "lang": "painless",
    "source": "ctx._source.last = params.last",
    "params": {
      "last": "hockey"
    }
  }
}

You can also add fields to a document. For example, this script adds a new field that contains the player’s nickname, hockey.

POST hockey/player/1/_update
{
  "script": {
    "lang": "painless",
    "source": """
      ctx._source.last = params.last;
      ctx._source.nick = params.nick
    """,
    "params": {
      "last": "gaudreau",
      "nick": "hockey"
    }
  }
}

Dates

Date fields are exposed as ReadableDateTime, so they support methods like getYear, getDayOfWeek or e.g. getting milliseconds since epoch with getMillis. To use these in a script, leave out the get prefix and continue with lowercasing the rest of the method name. For example, the following returns every hockey player’s birth year:

GET hockey/_search
{
  "script_fields": {
    "birth_year": {
      "script": {
        "source": "doc.born.value.year"
      }
    }
  }
}

Regular expressions

Note
Regexes are disabled by default because they circumvent Painless’s protection against long running and memory hungry scripts. To make matters worse even innocuous looking regexes can have staggering performance and stack depth behavior. They remain an amazing powerful tool but are too scary to enable by default. To enable them yourself set script.painless.regex.enabled: true in elasticsearch.yml. We’d like very much to have a safe alternative implementation that can be enabled by default so check this space for later developments!

Painless’s native support for regular expressions has syntax constructs:

  • /pattern/: Pattern literals create patterns. This is the only way to create a pattern in painless. The pattern inside the /'s are just Java regular expressions. See [pattern-flags] for more.

  • =~: The find operator return a boolean, true if a subsequence of the text matches, false otherwise.

  • ==~: The match operator returns a boolean, true if the text matches, false if it doesn’t.

Using the find operator (=~) you can update all hockey players with "b" in their last name:

POST hockey/player/_update_by_query
{
  "script": {
    "lang": "painless",
    "source": """
      if (ctx._source.last =~ /b/) {
        ctx._source.last += "matched";
      } else {
        ctx.op = "noop";
      }
    """
  }
}

Using the match operator (==~) you can update all the hockey players whose names start with a consonant and end with a vowel:

POST hockey/player/_update_by_query
{
  "script": {
    "lang": "painless",
    "source": """
      if (ctx._source.last ==~ /[^aeiou].*[aeiou]/) {
        ctx._source.last += "matched";
      } else {
        ctx.op = "noop";
      }
    """
  }
}

You can use the Pattern.matcher directly to get a Matcher instance and remove all of the vowels in all of their last names:

POST hockey/player/_update_by_query
{
  "script": {
    "lang": "painless",
    "source": "ctx._source.last = /[aeiou]/.matcher(ctx._source.last).replaceAll('')"
  }
}

Matcher.replaceAll is just a call to Java’s Matcher’s replaceAll method so it supports `$1 and \1 for replacements:

POST hockey/player/_update_by_query
{
  "script": {
    "lang": "painless",
    "source": "ctx._source.last = /n([aeiou])/.matcher(ctx._source.last).replaceAll('$1')"
  }
}

If you need more control over replacements you can call replaceAll on a CharSequence with a Function<Matcher, String> that builds the replacement. This does not support $1 or \1 to access replacements because you already have a reference to the matcher and can get them with m.group(1).

Important
Calling Matcher.find inside of the function that builds the replacement is rude and will likely break the replacement process.

This will make all of the vowels in the hockey player’s last names upper case:

POST hockey/player/_update_by_query
{
  "script": {
    "lang": "painless",
    "source": """
      ctx._source.last = ctx._source.last.replaceAll(/[aeiou]/, m ->
        m.group().toUpperCase(Locale.ROOT))
    """
  }
}

Or you can use the CharSequence.replaceFirst to make the first vowel in their last names upper case:

POST hockey/player/_update_by_query
{
  "script": {
    "lang": "painless",
    "source": """
      ctx._source.last = ctx._source.last.replaceFirst(/[aeiou]/, m ->
        m.group().toUpperCase(Locale.ROOT))
    """
  }
}

Note: all of the _update_by_query examples above could really do with a query to limit the data that they pull back. While you could use a {ref}/query-dsl-script-query.html[script query] it wouldn’t be as efficient as using any other query because script queries aren’t able to use the inverted index to limit the documents that they have to check.

How painless dispatches functions

Painless uses receiver, name, and arity for method dispatch. For example, s.foo(a, b) is resolved by first getting the class of s and then looking up the method foo with two parameters. This is different from Groovy which uses the runtime types of the parameters and Java which uses the compile time types of the parameters.

The consequence of this that Painless doesn’t support overloaded methods like Java, leading to some trouble when it whitelists classes from the Java standard library. For example, in Java and Groovy, Matcher has two methods: group(int) and group(String). Painless can’t whitelist both of these methods because they have the same name and the same number of parameters. So instead it has group(int) and namedGroup(String).

We have a few justifications for this different way of dispatching methods:

  1. It makes operating on def types simpler and, presumably, faster. Using receiver, name, and arity means that when Painless sees a call on a def object it can dispatch the appropriate method without having to do expensive comparisons of the types of the parameters. The same is true for invocations with def typed parameters.

  2. It keeps things consistent. It would be genuinely weird for Painless to behave like Groovy if any def typed parameters were involved and Java otherwise. It’d be slow for it to behave like Groovy all the time.

  3. It keeps Painless maintainable. Adding the Java or Groovy like method dispatch feels like it’d add a ton of complexity which’d make maintenance and other improvements much more difficult.

Painless Debugging

Debug.Explain

Painless doesn’t have a REPL and while it’d be nice for it to have one day, it wouldn’t tell you the whole story around debugging painless scripts embedded in Elasticsearch because the data that the scripts have access to or "context" is so important. For now the best way to debug embedded scripts is by throwing exceptions at choice places. While you can throw your own exceptions (throw new Exception('whatever')), Painless’s sandbox prevents you from accessing useful information like the type of an object. So Painless has a utility method, Debug.explain which throws the exception for you. For example, you can use {ref}/search-explain.html[_explain] to explore the context available to a {ref}/query-dsl-script-query.html[script query].

PUT /hockey/player/1?refresh
{"first":"johnny","last":"gaudreau","goals":[9,27,1],"assists":[17,46,0],"gp":[26,82,1]}

POST /hockey/player/1/_explain
{
  "query": {
    "script": {
      "script": "Debug.explain(doc.goals)"
    }
  }
}

Which shows that the class of doc.first is org.elasticsearch.index.fielddata.ScriptDocValues.Longs by responding with:

{
   "error": {
      "type": "script_exception",
      "to_string": "[1, 9, 27]",
      "painless_class": "org.elasticsearch.index.fielddata.ScriptDocValues.Longs",
      "java_class": "org.elasticsearch.index.fielddata.ScriptDocValues$Longs",
      ...
   },
   "status": 500
}

You can use the same trick to see that _source is a LinkedHashMap in the _update API:

POST /hockey/player/1/_update
{
  "script": "Debug.explain(ctx._source)"
}

The response looks like:

{
  "error" : {
    "root_cause": ...,
    "type": "illegal_argument_exception",
    "reason": "failed to execute script",
    "caused_by": {
      "type": "script_exception",
      "to_string": "{gp=[26, 82, 1], last=gaudreau, assists=[17, 46, 0], first=johnny, goals=[9, 27, 1]}",
      "painless_class": "java.util.LinkedHashMap",
      "java_class": "java.util.LinkedHashMap",
      ...
    }
  },
  "status": 400
}

Once you have a class you can go to [painless-api-reference] to see a list of available methods.

Painless execute API

experimental[The painless execute api is new and the request / response format may change in a breaking way in the future]

The Painless execute API allows an arbitrary script to be executed and a result to be returned.

Table 1. Parameters
Name Required Default Description

script

yes

-

The script to execute

context

no

painless_test

The context the script should be executed in.

context_setup

no

-

Additional parameters to the context.

Contexts

Contexts control how scripts are executed, what variables are available at runtime and what the return type is.

Painless test context

The painless_test context executes scripts as is and do not add any special parameters. The only variable that is available is params, which can be used to access user defined values. The result of the script is always converted to a string. If no context is specified then this context is used by default.

Example

Request:

POST /_scripts/painless/_execute
{
  "script": {
    "source": "params.count / params.total",
    "params": {
      "count": 100.0,
      "total": 1000.0
    }
  }
}

Response:

{
  "result": "0.1"
}
Filter context

The filter context executes scripts as if they were executed inside a script query. For testing purposes a document must be provided that will be indexed temporarily in-memory and is accessible to the script being tested. Because of this the _source, stored fields and doc values are available in the script being tested.

The following parameters may be specified in context_setup for a filter context:

document

Contains the document that will be temporarily indexed in-memory and is accessible from the script.

index

The name of an index containing a mapping that is compatible with the document being indexed.

Example
PUT /my-index
{
  "mappings": {
    "_doc": {
      "properties": {
        "field": {
          "type": "keyword"
        }
      }
    }
  }
}

POST /_scripts/painless/_execute
{
  "script": {
    "source": "doc['field'].value.length() <= params.max_length",
    "params": {
      "max_length": 4
    }
  },
  "context": "filter",
  "context_setup": {
    "index": "my-index",
    "document": {
      "field": "four"
    }
  }
}

Response:

{
  "result": true
}
Score context

The score context executes scripts as if they were executed inside a script_score function in function_score query.

The following parameters may be specified in context_setup for a score context:

document

Contains the document that will be temporarily indexed in-memory and is accessible from the script.

index

The name of an index containing a mapping that is compatible with the document being indexed.

query

If _score is used in the script then a query can specified that will be used to compute a score.

Example
PUT /my-index
{
  "mappings": {
    "_doc": {
      "properties": {
        "field": {
          "type": "keyword"
        },
        "rank": {
          "type": "long"
        }
      }
    }
  }
}


POST /_scripts/painless/_execute
{
  "script": {
    "source": "doc['rank'].value / params.max_rank",
    "params": {
      "max_rank": 5.0
    }
  },
  "context": "score",
  "context_setup": {
    "index": "my-index",
    "document": {
      "rank": 4
    }
  }
}

Response:

{
  "result": 0.8
}