An elasticsearch query body builder. Easily build complex queries for elasticsearch with a simple, predictable api.
Check out the API documentation for details and examples.
Use https://bodybuilder.js.org/ to test your constructions.
Currently aims to support the full elasticsearch query DSL for all versions.
The elasticsearch 1.x query DSL is supported by providing a v1 argument
when calling the build function.
npm install bodybuilder --save
var bodybuilder = require('bodybuilder')
var body = bodybuilder().query('match', 'message', 'this is a test')
body.build() // Build 2.x or greater DSL (default)
body.build('v1') // Build 1.x DSLFor each elasticsearch query body, create an instance of bodybuilder, apply
the desired query/filter/aggregation clauses, and call build to retrieve the
built query body.
Try it out on the command line using the node REPL:
# Start the repl
node ./node_modules/bodybuilder/repl.js
# The builder is available in the context variable bodybuilder
bodybuilder > bodybuilder().query('match', 'message', 'this is a test').build()
bodybuilder().query([arguments])Creates a query of type queryType.
The specific arguments depend on the type of query, but typically follow this pattern:
queryType- The name of the query, such as'term'or'prefix'.fieldToQuery- The name of the field in your index to query over.searchTerm- The string to search for.
var body = bodybuilder().query('match', 'message', 'this is a test').build()
// body == {
// query: {
// match: {
// message: 'this is a test'
// }
// }
// }bodybuilder().filter([arguments])Creates a filtered query using filter of type filterType.
The specific arguments depend on the type of filter, but typically follow this pattern:
filterType- The name of the query, such as'regexp'or'exists'.fieldToQuery- The name of the field in your index to filter on.searchTerm- The string to search for.
bodybuilder().filter('term', 'message', 'test').build()
// body == {
// query: {
// bool: {
// filter: {
// term: {
// message: 'test'
// }
// }
// }
// }
// }bodybuilder().aggregation([arguments])Creates an aggregation of type aggregationType.
The specific arguments depend on the type of aggregation, but typically follow this pattern:
aggregationType- The name of the aggregation, such as'sum'or'terms'.fieldToAggregate- The name of the field in your index to aggregate over.aggregationName- (optional) A custom name for the aggregation. Defaults toagg_<aggregationType>_<fieldToAggregate>.aggregationOptions- (optional) Additional key-value pairs to include in the aggregation object.nestingFunction- (optional) A function used to define aggregations as children of the one being created. This must be the last parameter set.
var body = bodybuilder().aggregation('terms', 'user').build()
// body == {
// aggregations: {
// agg_terms_user: {
// terms: {
// field: 'user'
// }
// }
// }
// }To nest aggregations, pass a function as the last parameter in [arguments].
The function receives the recently built aggregation instance and is expected
to return an Object which will be assigned to .aggs on the current
aggregation. Aggregations in this scope behave like builders and you can call
the chainable method .aggregation([arguments]) on them just as you would on
the main bodybuilder.
var body = bodybuilder().aggregation('terms', 'code', {
order: { _term: 'desc' },
size: 1
}, agg => agg.aggregation('terms', 'name')).build()
// body == {
// "aggregations": {
// "agg_terms_code": {
// "terms": {
// "field": "code",
// "order": {
// "_term": "desc"
// },
// "size": 1
// },
// "aggs": {
// "agg_terms_name": {
// "terms": {
// "field": "name"
// }
// }
// }
// }
// }
//}bodybuilder().suggest([arguments])Creates a phrase or term suggestion.
The specific arguments depend on the type of aggregation, but typically follow this pattern:
suggestionType- This can be eitherphraseorterm.fieldToAggregate- The name of the field in your index to suggest on.options- An object of fields to include in the suggestions.text- The query to run on our suggest field.name- A custom name for the suggest clause.analyzer- The name of an analyzer to run on a suggestion.- ... other suggest specific options, see typings or the ElasticSearch suggest docs for more info
var body = bodybuilder().suggest('term', 'user', { text: 'kimchy', 'name': 'user_suggest'}).build()
// body == {
// aggregations: {
// user_suggest: {
// text: 'kimchy',
// term: {
// field: 'user'
// }
// }
// }
// }Multiple queries and filters are merged using the boolean query or filter (see Combining Filters).
var body = bodybuilder()
.query('match', 'message', 'this is a test')
.filter('term', 'user', 'kimchy')
.filter('term', 'user', 'herald')
.orFilter('term', 'user', 'johnny')
.notFilter('term', 'user', 'cassie')
.aggregation('terms', 'user')
.suggest('term', 'user', { text: 'kimchy' })
.build()
// body == {
// query: {
// bool: {
// must: {
// match: {
// message: 'this is a test'
// }
// },
// filter: {
// bool: {
// must: [
// {term: {user: 'kimchy'}},
// {term: {user: 'herald'}}
// ],
// should: [
// {term: {user: 'johnny'}}
// ],
// must_not: [
// {term: {user: 'cassie'}}
// ]
// }
// }
// },
// },
// aggs: {
// agg_terms_user: {
// terms: {
// field: 'user'
// }
// }
// }
// suggest_term_user: {
// text: 'kimchy',
// term: {
// field: 'user'
// }
// }
// }It is even possible to nest filters, e.g. when some should and must filters have to be combined.
var body = bodybuilder()
.orFilter('term', 'author', 'kimchy')
.orFilter('bool', b => b
.filter('match', 'message', 'this is a test')
.filter('term', 'type', 'comment')
)
.build()
// body == {
// query: {
// bool: {
// filter: {
// bool: {
// should: [
// { term: { author: 'kimchy' } },
// { bool: { must: [
// { match: { message: 'this is a test' } },
// { term: { type: 'comment' } }
// ] } }
// ]
// }
// }
// }
// }
// }Set a sort direction using sort(field, direction), where direction defaults to
ascending.
var body = bodybuilder()
.filter('term', 'message', 'test')
.sort('timestamp', 'desc')
.sort([{
"channel": {
"order": "desc"
}
}])
.sort([
{"categories": "desc"},
{"content": "asc"}
])
.build()
// body == {
// sort: [{
// "timestamp": {
// "order": "desc"
// }
// },
// {
// "channel": {
// "order": "desc"
// }
// },
// {
// "categories": {
// "order": "desc"
// }
// },
// {
// "content": {
// "order": "asc"
// }
// }
// ],
// query: {
// bool: {
// filter: {
// term: {
// message: 'test'
// }
// }
// }
// }
// }Advanced usage: Set a sort configuration object for the given sort field with additional sort properties.
sort(field, { sort: 'asc', mode: 'min', ...})
Set from and size parameters to configure the offset and maximum hits to be
returned.
var body = bodybuilder()
.filter('term', 'message', 'test')
.size(5)
.from(10)
.build()
// body == {
// size: 5,
// from: 10,
// query: {
// bool: {
// filter: {
// term: {
// message: 'test'
// }
// }
// }
// }
// }Set any other search request option using rawOption passing in the key-value
pair to include in the body.
var body = bodybuilder()
.filter('term', 'message', 'test')
.rawOption('_sourceExclude', 'verybigfield')
.build()
// body == {
// _sourceExclude: 'verybigfield',
// query: {
// bool: {
// filter: {
// term: {
// message: 'test'
// }
// }
// }
// }
// }Run unit tests:
npm test
Thanks goes to these wonderful people (emoji key):
 Daniel Paz-Soldan 💻 📖 🚇 🤔 |
 Nicolás Fantone 💻 |
 Nauval Atmaja 💻 |
 Ferron H 💻 |
 Dave Cranwell 💻 |
 Johannes Scharlach 💻 📖 🤔 |
 Anton Samper Rivaya 💻 📖 |
|---|---|---|---|---|---|---|
 Suhas Karanth 💬 |
 Jacob Gillespie 💻 |
This project follows the all-contributors specification. Contributions of any kind welcome!