What to increase search speed in Elasticsearch?

To increase search speed in Elasticsearch, you can consider the following points:

• Shard and Index Sizing: Effective indexing and shard sizing are crucial. Aim for fewer large shards, ideally between 20GB and 40GB, rather than numerous small ones to minimize overhead. Avoid creating overly large indices; instead, split data into smaller, logically grouped indices, such as one per year or month.
• Field Data Types: Make sure you understand the field data types and use the appropriate one for your data. For instance, use structured data types for the fields that will be used in filtering and sorting, such as the “keyword” option, while using “text” for full-text search fields. Any field that does not require analysis should not at all be analyzed.
• Field Mappings: This is particularly important because mappings often fail, and, when they do, it is better to find out during development than in a live environment. For instance, for fields that do not require it, one could disable norms and docValues because they minimize memory and enhance the speed of searching.
• Caching: Caching is one of the powerful tuning parameters you should enable and tune the several caching mechanisms in Elasticsearch these are field data cache, query cache, and the request cache. For repetitive queries, caching can go a long way in improving efficiency and performance is a critical factor in this aspect.
• Pagination and Scrolling: When the result set being returned is huge use the most appropriate pagination or scrolling methodology to avoid the nature of a single large query overwhelming the cluster.
• Querying Techniques: Implement the intelligent query system rules like filtering before querying, prefix queries auto-complete, avoid using wildcards in querying.
• Hardware Resources: This is particularly important for big production environments; make sure your Elasticsearch cluster has enough CPU, RAM, and fast disks (SSDs are preferred). Elasticsearch is a relatively expensive service in terms of CPU and memory utilization and having enough resources at its disposal can help a lot.
• Cluster Health and Monitoring: Ensure that you have the aspects of your Elasticsearch cluster in check such as disk usage, heap usage, or other as may be required. This will help keep the system in check to ensure it is always running optimally by addressing any issues as they arise.

There is a software platform called Elasticsearch oriented on search and analytics of the large flows of the data which is an open-source and has recently gained widespread.

Yet, as data volumes and consumers increase and technologies are adopted, enterprises encounter performance and scalability issues with Elasticsearch implementations. In this article, they will discuss some of the familiar performance and scalable issues and offer recommendations on how to deal with them.