Indexing MapR-DB Binary Tables with Elasticsearch

This section discusses using Elasticsearch to index MapR-DB binary tables.

You can create external indexes for your MapR-DB binary tables by indexing columns, column families, or entire tables with Elasticsearch. When client applications update data in a source table, MapRDB replicates the update to the Elasticsearch type that is associated with it.

Updates to indexes happen in near real-time because individual updates to your MapR-DB source binary tables are replicated to Elasticsearch. There is no batching of updates, which would lead to recurring times where data is available in MapR-DB but not searchable in your indexes. Therefore, there is minimal latency between the availability of data in MapR-DB and the searchability of that data by end users.

The MapR distribution does not include Elasticsearch, which you can get from MapR-DB works with Elasticsearch version 2.2.

Note: Indexing data with Elasticsearch is not supported for MapR-DB JSON tables and MapR streams.