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elasticmagic-js - JS/Typescript DSL for Elasticsearch

The project is still very much a work in progress and in an alpha state, api may/will change; input and contributions welcome!

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Elasticmagic is an Elasticsearch query builder and ORM for JavaScript/Typescript.

It helps you easily build queries which are typed and safe.

You do not need to remember how to write json DSL for Elasticsearch, Elasticmagic will do it for you.

This lib is a port of original library written in python by @anti-social

Versions

Supports Elasticsearch version 6.x

Docs

Docs - https://elasticmagic.js.org/

Changelog - https://elasticmagic.js.org/docs/changelog

Installation

To install Elasticmagic via NPM:

npm install --save elasticmagic

Also you need an Elasticseach official js client

npm install --save @elastic/elasticsearch

Getting Started

Query building

import { Client } from '@elastic/elasticsearch';
import { 
  Cluster,
  Field,
  IntegerType,
  Doc,
  Bool,
} from "elasticmagic-js";


/**
 * Here we creating our document which maps structure of same document in Elasticsearch.  
 * 
 * We will use this class as our query builder.
 * Also when we will get result from elasticsearch, we instantiate this class
 * and populate it with data from Elasticsearch hits.
 * 
 * First we declare docType - it must be the same as document in Elasticsearch mapping. 
 * 
 * Then we declare static fields that will be user to build our queries. 
 * As we do not need an instance of this class to build queries, the fields are static.
 * 
 * Next, conventionaly, we declare instance properties, as you can see, with almost same name. 
 * Then lettercase is same as fields in Elasticseach mapping
 * 
 * And thats is.  
 */
class OrderDoc extends Doc {
  public static docType: string = 'order';

  public static userId = new Field(IntegerType, 'user_id', OrderDoc);
  public user_id?: number;

  public static status = new Field(IntegerType, 'status', OrderDoc);
  public status?: number;

  public static source = new Field(IntegerType, 'source', OrderDoc);
  public source?: number;

  public static price = new Field(IntegerType, 'price', OrderDoc);
  public price?: number;

  public static dateCreated = new Field(DateType, 'date_created', OrderDoc);
  public date_created?: Date;
}

// Create a Elasticsearch client which will be passed to cluster.
const client = new Client({ node: 'http://es6-test:9200' });
// Create cluster instance. Its an entrypiint for interacting with Elasticsearch.
const cluster = new Cluster(client, 'test_order_index');


// Lets start building our query.
// Calling searchQuery method we start creating new query.
// We using builder pattern, so you can chain any amount of methods
const query = cluster.searchQuery({ routing: 1 })
  .source(true)
  .filter(
    Bool.must(
      OrderDoc.userId.in([1]),
      OrderDoc.status.in([1, 2]),
      OrderDoc.source.not(1),
      OrderDoc.dateCreated.lte(new Date().toISOString())
    )
  );

// To make a query to Elasticsearch we calling getResult.
const result = await query.getResult<OrderDoc>();
console.log(result.getIds()); // prints ["1"]

const hit = result.hits[0];
console.log(hit.user_id); // prints 1

We can check what query Elasticmagic will build for us.

console.log(query.toJSON()) 
// to see prettified query
console.log(query.toPrettyJSON());

Aggregations

const query = searchQuery
  .source(false)
  .filter(
    Bool.must(
      OrderDoc.userId.in([1]),
      OrderDoc.status.in([OrderStatus.new, OrderStatus.handled, OrderStatus.paid]),
      OrderDoc.source.not(OrderSource.mobile),
      OrderDoc.dateCreated.lte(new Date().toISOString()),
    )
  )
  .aggregations({
    usersOrders: new agg.Terms({
      field: OrderDoc.userId,
      size: 1,
      aggs: {
        total: new agg.Filter({
          filter: OrderDoc.conditionSourceDesktop(),
          aggs: {
            selled: new agg.Filter({
              filter: Bool.must(
                OrderDoc.status.in([OrderStatus.paid, OrderStatus.handled]),
              ),
              aggs: {
                paid: new agg.Filter({
                  filter: OrderDoc.status.eq(OrderStatus.paid)
                }), 
                handled: new agg.Filter({
                  filter: OrderDoc.status.eq(OrderStatus.handled)
                }),
              }
            }),
            canceled: new agg.Filter({
              filter: OrderDoc.status.eq(OrderStatus.canceled),
            }),
            new: new agg.Filter({
              filter: OrderDoc.status.eq(OrderStatus.new)
            })
          }
        }),
        lowcost: new agg.Filter({
          filter: OrderDoc.conditionLowPrice()
        })
      }
    })
  });

Now you can get aggregation data

const result = await query.getResult<OrderDoc>();

const usersOrders = result.getAggregation("usersOrders");
console.log(usersOrders.buckets[0].key) // prints 1
console.log(usersOrders.buckets[0].docCount) // prints 1

const total = usersOrders.buckets[0].getAggregation("total")
console.log(total.docCount) // prints 1

Tests

Run all tests

make test

Run one test

make test TEST=tests/testSearchQuery.spec.ts
# or
make test TEST=testSearchQuery.spec.ts

TODO

Document API (CRUD)

  • Index API
  • Get API
  • Delete API
  • Delete By Query API
  • Update API
  • Update By Query API
  • Multi Get API
  • Bulk API
  • Reindex API

Query DSL

  • searchQuery
  • aggregations
  • Match All Query
  • Match All Query
  • Full text queries
    • Match Query
    • Match Phrase Query
    • Match Phrase PrefixQuery
    • Multi Match Query
    • Common Terms Query
    • Query String Query
    • Simple Query String Query
  • Term level queries
    • Term Query
    • Terms Query
    • Terms Set Query
    • Range Query
    • Exists Query
    • Prefix Query
    • Wildcard Query
    • Regexp Query
    • Fuzzy Query
    • Type Query
    • Ids Query
  • Compound queries
    • Constant Score Query
    • Bool Query
    • Dis Max Query
    • Function Score Query
    • Boosting Query
  • Joining queries
    • Nested Query
    • Has Child Query
    • Has Parent Query
    • Parent Id Query
  • Specialized queries
    • Distance Feature Query
    • More Like This Query
    • Script Query
    • Script Score Query
    • Percolate Query
  • Sorting
    • Sort by score
    • Sort by field
    • Sort by geo distance
    • Sort by script
    • Sort by doc

Search APIs (

  • Multi Search
  • Search Shards API
  • Multi Search API
  • Count API
  • Validate API
  • Explain API
  • Profile API

Elasticsearch versions interop

  • add support for elasticsearch 5, 7 versions, compilers for different es versions

Development

  • precommit hooks
  • fix integration tests by randomly creating indexes, so tests can be run in parallel
  • add documentation to methods
  • generate api docs (typedoc)

cat APIs

Other

  • Post filters
  • Rescores
  • Scroll
  • Pagination
  • QueryFilters
  • Sub document in field
  • Sub field in field
  • Highlight