Chapter 6. Improving Solr Performance

In this chapter, we will cover the following topics:

  • Handling deep paging efficiently
  • Configuring the document cache
  • Configuring the query result cache
  • Configuring the filter cache
  • Improving Solr query performance after the start and commit operations
  • Lowering the memory consumption of faceting and sorting
  • Speeding up indexing with Solr segment merge tuning
  • Avoiding caching of rare filters to improve the performance
  • Controlling the filter execution to improve expensive filter performance
  • Configuring numerical fields for high-performance sorting and range queries

Introduction

The performance of an application is one of the most important factors. Of course, there are other factors such as usability and availability—we can recite much more, but one of the most crucial and major factors is the performance. Even if our application is perfectly done in terms of usability, the users won't be able to use it if they have to wait for minutes for the search results.

The standard Solr deployment is fast enough, but sooner or later a time will come when you will have to optimize your deployment. The recipes in this chapter will try to help you optimize Solr deployment.

If your business depends on Solr, you should keep monitoring it even after optimization. You can see how your environment works, the state of Solr nodes, the number of queries that run, its speed, and so on. There are numerous solutions available on the market, from the generic and open sourced ones such as Ganglia (http://ganglia.sourceforge.net/) to specific ones such as SPM Performance Monitoring & Alerting (http://www.sematext.com/spm/index.html) from the Sematext group.

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