A Brief Painless Walkthrough
editA Brief Painless Walkthrough
editTo illustrate how Painless works, let’s load some hockey stats into an Elasticsearch index:
PUT hockey/_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
editDocument 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
editdoc['field'].value throws an exception if
the field is missing in a document.
To check if a document is missing a value, you can call
doc['field'].size() == 0.
Updating Fields with Painless
editYou 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/_update/1
{
"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/_update/1
{
"script": {
"lang": "painless",
"source": """
ctx._source.last = params.last;
ctx._source.nick = params.nick
""",
"params": {
"last": "gaudreau",
"nick": "hockey"
}
}
}
Dates
editDate fields are exposed as
ZonedDateTime, 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
editRegexes are enabled by default as the Setting script.painless.regex.enabled
has a new option, limited, the default. This defaults to using regular expressions
but limiting the complexity of the regular expressions. Innocuous looking regexes
can have staggering performance and stack depth behavior. But still, they remain an
amazingly powerful tool. In addition, to limited, the setting can be set to true,
as before, which enables regular expressions without limiting them.To enable them
yourself set script.painless.regex.enabled: true in elasticsearch.yml.
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 aboolean,trueif a subsequence of the text matches,falseotherwise. -
==~: The match operator returns aboolean,trueif the text matches,falseif it doesn’t.
Using the find operator (=~) you can update all hockey players with "b" in
their last name:
POST hockey/_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/_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/_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/_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).
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/_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/_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
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.