Mongo to Elastic

Sync MongoDB to Elasticsearch

import elasticsearch from '@elastic/elasticsearch'
import { default as Redis } from 'ioredis'
import { crate, initSync } from 'mongo2crate'
import { MongoClient } from 'mongodb'
import retry from 'p-retry'

const client = await MongoClient.connect()
const db = client.db()

const elastic = new elasticsearch.Client()

const sync = initSync(new Redis(), db.collection('myCollection'), elastic, {
  omit: ['password', 'unneededStuff'],
})
// Log events
sync.emitter.on('process', console.info)
sync.emitter.on('error', console.error)
sync.emitter.on('cursorError', () => process.exit(1))
// Create index with ignore_malformed enabled
await sync.createIndexIgnoreMalformed().catch(console.warn)
// Create mapping
const schema = await sync.getCollectionSchema(db)
if (schema) {
  await sync.createMappingFromSchema(schema)
}
// Process change stream events
const changeStream = await sync.processChangeStream()
changeStream.start()
// Detect schema changes and stop change stream if detected
const schemaChange = await sync.detectSchemaChange(db)
schemaChange.start()
sync.emitter.on('schemaChange', changeStream.stop)
// Run initial scan of collection batching documents by 1000
const options = { batchSize: 1000 }
const initialScan = await sync.runInitialScan(options)
initialScan.start()

Run the tests locally

Create a .env file with the following variables set to the appropriate values:

MONGO_CONN="mongodb+srv://..."
ELASTIC_NODE='https://elastic-node-url-here.com'
ELASTIC_USERNAME="username-here"
ELASTIC_PASSWORD="password-here"

Then run npm test to run the tests.

Schema Conversion Example

The convertSchema function transforms MongoDB JSON schemas into Elasticsearch mappings. Here's an example showing how to use the helper functions and features:

Input MongoDB Schema

const mongoSchema = {
  bsonType: 'object',
  additionalProperties: false,
  properties: {
    _id: {
      bsonType: 'objectId',
    },
    name: {
      bsonType: 'string',
    },
    email: {
      bsonType: 'string',
    },
    location: {
      bsonType: 'string', // Will be converted to geo_point
    },
    tags: {
      bsonType: 'array',
      items: {
        bsonType: 'string',
      },
    },
    comments: {
      bsonType: 'array',
      items: {
        bsonType: 'object',
        additionalProperties: false,
        properties: {
          text: {
            bsonType: 'string',
          },
          author: {
            bsonType: 'string',
          },
        },
      },
    },
  },
}

Conversion with Helper Functions

import { convertSchema, copyTo, isStringLike, setESType } from 'mongo2elastic'

const options = {
  overrides: [
    // Copy all string-like fields to a searchable 'all' field
    copyTo('*', 'all', isStringLike),
    // Copy name and email to a 'contact_info' field for grouped searching
    copyTo('name', 'contact_info'),
    copyTo('email', 'contact_info'),
    // Convert location field to geo_point type
    setESType('location', 'geo_point'),
    // Make comments array use nested type for complex queries
    { path: 'comments', nested: true },
  ],
}

const elasticMapping = convertSchema(mongoSchema, options)

Generated Elasticsearch Mapping

{
  properties: {
    _mongoId: {
      type: 'keyword'
    },
    name: {
      type: 'text',
      fields: {
        keyword: {
          type: 'keyword',
          ignore_above: 256
        }
      },
      copy_to: ['all', 'contact_info']
    },
    email: {
      type: 'text',
      fields: {
        keyword: {
          type: 'keyword',
          ignore_above: 256
        }
      },
      copy_to: ['all', 'contact_info']
    },
    location: {
      type: 'geo_point'
    },
    tags: {
      type: 'text',
      fields: {
        keyword: {
          type: 'keyword',
          ignore_above: 256
        }
      },
      copy_to: ['all']
    },
    comments: {
      type: 'nested',
      properties: {
        text: {
          type: 'text',
          fields: {
            keyword: {
              type: 'keyword',
              ignore_above: 256
            }
          },
          copy_to: ['all']
        },
        author: {
          type: 'text',
          fields: {
            keyword: {
              type: 'keyword',
              ignore_above: 256
            }
          },
          copy_to: ['all']
        }
      }
    }
  }
}

Key Features Demonstrated

• copyTo('*', 'all', isStringLike): Copies all string-like fields to an 'all' field for full-text search
• copyTo('name', 'contact_info'): Groups specific fields for targeted searching
• setESType('location', 'geo_point'): Converts a string field to a specialized Elasticsearch type
• { path: 'comments', nested: true }: Converts array of objects to nested type for complex queries
• Automatic text field enhancement: String fields get both text and keyword sub-fields
• Field renaming: _id is automatically renamed to _mongoId