Elasticsearch Indexing Use Cases

Elasticsearch indexing of MapR-DB binary table are useful for full-text searches and geospatial searches.

Indexing MapR-DB binary tables with Elasticsearch makes possible these use cases:

Full-text searches

Client applications can run queries against text documents to search for specific words.

For example, a web-based travel agency could allow customers to search for destinations based on keywords. The travel agency indexes text documents that describe hotels, their location, their accommodations, and nearby attractions. So, a customer could search on the terms “Costa Rica”, “spa”, and “monkeys” to try finding a hotel in Costa Rica that offers a spa and is near businesses that give jungle tours in which the customer can see monkeys.

To enable full-text search in your existing MapR-DB applications, you do not need to add complex code for indexing data. Instead, you add code for searching with Elasticsearch and let the integration of MapR-DB with Elasticsearch handle indexing.

Geospatial searches

Enable geospatial searches by indexing location information (latitude and longitude). For example, indexed Elasticsearch documents might represent restaurants. If those documents contained location information, end users could use query filters to search for all restaurants within a certain radius of their current location.