Querying values in an array field in Elasticsearch

Elasticsearch allows indexing multiple values into a field, and to query on that field to find documents with matching values. This post explores some different ways of querying values, including approaches for matching values in the last position.


Favouring exact matches in Elasticsearch

Ice cream!

I recently came across a question on Stack Overflow asking about Boosting elasticsearch results with NEST when a secondary field is a specific value. I thought the question was interesting enough to warrant a blog post, the first I've written in a while!


Optimistic Concurrency with Elasticsearch and NEST

In my last post I gave an example of how to use the bulk api to index many documents at a time into Elasticsearch. Once all of the documents have been indexed, it is very likely that we'll want to update individual documents within the index; In this post, we'll look at how to do this and some of the features available to manage multiple concurrent update requests to a given document.


Geospatial search with Elasticsearch and NEST

'Australia in 1897, etc' from the British Library - https://www.flickr.com/photos/britishlibrary/11243694643

In this blog post I’m going to show you how to get started with geospatial search with Elasticsearch, using the official and fantastic .NET client for Elasticsearch, NEST.  An example like this is best served with real data, so given this post was written from Australia, we’ll use the State Suburbs (SSC) from 2006 provided by the Australian Bureau of Statistics as the data of interest; it's provided in ESRI Shapefile format and contains a collection of all the Australian Suburbs, each with a name, code and geometry; We’ll need to extract each suburb from the Shapefile and serialize them to a format that can be persisted to Elasticsearch and so that we can query them.


I’ve put together a demo application to illustrate geospatial search using Elasticsearch and NEST..