In this chapter, we talked about general shards and the index architecture. We chose the right amount of shards and replicas for our deployment, and we used routing during indexing and querying and in conjunction with aliases. We also discussed shard-allocation behavior adjustments, and finally, we looked at what query execution preference can bring us.

In the next chapter, we will take a deeper look, altering the Apache Lucene scoring mechanism by providing different similarity models. We will adjust our inverted index format by using codecs. We will discuss near real-time indexing and querying, flush and refresh operations, and transaction log configuration. We will talk about throttling and segment merges. Finally, we will discuss Elasticsearch caching—field data, filter, and query shard caches.