Book Image

Learning Elasticsearch

By : Abhishek Andhavarapu
Book Image

Learning Elasticsearch

By: Abhishek Andhavarapu

Overview of this book

Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. You can use Elasticsearch for small or large applications with billions of documents. It is built to scale horizontally and can handle both structured and unstructured data. Packed with easy-to- follow examples, this book will ensure you will have a firm understanding of the basics of Elasticsearch and know how to utilize its capabilities efficiently. You will install and set up Elasticsearch and Kibana, and handle documents using the Distributed Document Store. You will see how to query, search, and index your data, and perform aggregation-based analytics with ease. You will see how to use Kibana to explore and visualize your data. Further on, you will learn to handle document relationships, work with geospatial data, and much more, with this easy-to-follow guide. Finally, you will see how you can set up and scale your Elasticsearch clusters in production environments.
Table of Contents (11 chapters)
10
Exploring Elastic Stack (Elastic Cloud, Security, Graph, and Alerting)

Post Filter

You can tell Elasticsearch to run an expensive query, such as a script or geolocation, using post filter. The query in the post filter is only executed after the main query is executed so that the number of documents the expensive query has to be executed on is minimum. In the following query, we will run the script query as post filter:

POST chapter7/product/_search
{
"query": {
"match": {
"product_name": "iphone"
}
},
"post_filter": {
"script": {
"script": {
"lang": "painless",
"inline": "params._source.containsKey('variations') && params._source.variations.length > params.num_of_variations",
"params": {
"num_of_variations": 1
}
}
}
...