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In [distributed-cluster], we introduced the shard, and described it as a low-level ``worker unit''. But what exactly is a shard and how does it work? In this chapter we will answer these questions:
Why is search near real-time?
Why are document CRUD (create-read-update-delete) operations real-time?
How does Elasticsearch ensure that the changes you make are durable, that they won’t be lost if there is a power failure?
Why does deleting documents not free up space immediately?
What do the refresh, flush, and optimize APIs do, and when should
you use them?
The easiest way to understand how a shard functions today is to start with a history lesson. We will look at the problems that needed to be solved in order to provide a distributed durable datastore with near real-time search and analytics.
The information presented below is for your interest. You are not required to understand and remember all the detail in order to use Elasticsearch. Read the section to gain a taste for how things work, and to know where the information is in case you need to refer to it in the future, but don’t be overwhelmed by the detail.
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