elastic-builder
A Node.js implementation of the Elasticsearch DSL for use with the official elasticsearch javascript client with builder syntax.
Check out the API reference documentation.
Elasticsearch compatibility
elastic-builder
was built for 5.x query DSL. However, the library should be usable with
2.x as well. For older versions of the DSL, you can try
elastic.js
or bodybuilder
Install
npm install elastic-builder --save
Usage
const bob = require('elastic-builder');
const requestBody = bob.requestBodySearch()
.query(bob.matchQuery('message', 'this is a test'));
const requestBody = new bob.RequestBodySearch()
.query(new bob.MatchQuery('message', 'this is a test'));
requestBody.toJSON()
{
"query": {
"match": {
"message": "this is a test"
}
}
}
For each class, MyClass
, a utility function myClass
has been provided which
contructs the object for us without the need for new
keyword.
REPL
Try it out on the command line using the node REPL:
# Start the repl
node ./node_modules/elastic-builder/repl.js
# The builder is available in the context variable bob
elastic-builder > bob.prettyPrint(bob.requestBodySearch().query(bob.matchQuery('message', 'this is a test')));
Motivation
Elasticsearch only provides a low level client for making requests.
elastic.js
was a relatively popular library for building the request search body.
However, this project is not being maintained nor is the fork.
There were several changes
in the 5.0 release which make the older libraries unusable.
This library is a port of elastic.js
to es6 with elasticsearch 5.x compatibility.
API Reference
API reference can be accessed here - http://elastic-builder.js.org/docs.
The docs include examples ported from the official elasticsearch reference.
API documentation was generated using documentation.js.
It is being hosted with help from this awesome project - https://github.com/js-org/dns.js.org
Recipes
The library has a few helper recipes:
const qry = bob.cookMissingQuery('user');
qry.toJSON();
{
"bool": {
"must_not": {
"exists": { "field": "user" }
}
}
}
Check out the reference docs for more examples.
If you have any recipes, please do share or better yet, create a pull request :smile:.
Examples
const requestBody = bob.requestBodySearch()
.query(
bob.boolQuery()
.must(bob.matchQuery('last_name', 'smith'))
.filter(bob.rangeQuery('age').gt(30))
)
requestBody.toJSON()
{
"query": {
"bool": {
"must": {
"match": { "last_name": "smith" }
},
"filter": {
"range": { "age": { "gt": 30 } }
}
}
}
}
const requestBody = bob.requestBodySearch()
.query(
bob.multiMatchQuery(['title', 'body'], 'Quick brown fox')
.type('best_fields')
.tieBreaker(0.3)
.minimumShouldMatch('30%')
);
requestBody.toJSON()
{
"multi_match": {
"query": "Quick brown fox",
"type": "best_fields",
"fields": ["title", "body"],
"tie_breaker": 0.3,
"minimum_should_match": "30%"
}
}
const requestBody = bob.requestBodySearch()
.size(0)
.agg(bob.termsAggregation('popular_colors', 'color'));
requestBody.toJSON()
{
"size": 0,
"aggs": {
"popular_colors": {
"terms": { "field": "color" }
}
}
}
const requestBody = bob.requestBodySearch()
.size(0)
.agg(
bob.termsAggregation('colors', 'color')
.agg(bob.avgAggregation('avg_price', 'price'))
.agg(bob.termsAggregation('make', 'make'))
);
requestBody.toJSON()
{
"size": 0,
"aggs": {
"colors": {
"terms": { "field": "color" },
"aggs": {
"avg_price": {
"avg": { "field": "price" }
},
"make": {
"terms": { "field": "make" }
}
}
}
}
}
const agg = new bob.TermsAggregation('countries', 'artist.country')
.order('rock>playback_stats.avg', 'desc')
.agg(
new bob.FilterAggregation(
'rock',
new bob.TermQuery('genre', 'rock')
).agg(new bob.StatsAggregation('playback_stats', 'play_count'))
)
.toJSON();
agg.toJSON()
{
"countries": {
"terms": {
"field": "artist.country",
"order": { "rock>playback_stats.avg": "desc" }
},
"aggs": {
"rock": {
"filter": {
"term": { "genre": "rock" }
},
"aggs": {
"playback_stats": {
"stats": { "field": "play_count" }
}
}
}
}
}
}
const requestBody = bob.requestBodySearch()
.query(
bob.boolQuery()
.filter(bob.termQuery('message', 'test'))
)
.sort(bob.sort('timestamp', 'desc'))
.sorts([
bob.sort('channel', 'desc'),
bob.sort('categories', 'desc'),
bob.sort('content'),
bob.sort('price').order('desc').mode('avg')
]);
requestBody.toJSON()
{
"query": {
"bool": {
"filter": {
"term": { "message": "test" }
}
}
},
"sort": [
{ "timestamp": { "order": "desc" } },
{ "channel": { "order": "desc" } },
{ "categories": { "order": "desc" } },
"content",
{ "price": { "order": "desc", "mode": "avg" } }
]
}
const requestBody = bob.requestBodySearch()
.query(bob.matchAllQuery())
.size(5)
.from(10);
requestBody.toJSON()
{
"query": { "match_all": {} },
"size": 5,
"from": 10
}
For more examples, check out the reference docs.
Validation
elastic-builder
provides lightweight validation where ever possible:
$ node ./node_modules/elastic-builder/repl.js
elastic-builder > bob.multiMatchQuery().field('title').field('body').query('Quick brown fox').type('bwst_fields')
See https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-multi-match-query.html
Got 'type' - bwst_fields
Error: The 'type' parameter should belong to Set {
'best_fields',
'most_fields',
'cross_fields',
'phrase',
'phrase_prefix' }
at MultiMatchQuery.type (E:\Projects\repos\elastic-builder\lib\queries\full-text-queries\multi-match-query.js:134:23)
at repl:1:77
at ContextifyScript.Script.runInContext (vm.js:35:29)
at REPLServer.defaultEval (repl.js:342:29)
at bound (domain.js:280:14)
at REPLServer.runBound [as eval] (domain.js:293:12)
at REPLServer.<anonymous> (repl.js:538:10)
at emitOne (events.js:96:13)
at REPLServer.emit (events.js:188:7)
at REPLServer.Interface._onLine (readline.js:239:10)
Tests
Run unit tests:
npm test
Credits
elastic-builder
is heavily inspired by elastic.js
and the fork by Erwan Pigneul.
bodybuilder for documentation style, build setup, demo page.
License
MIT