Elastic Search Basics

It’s a collection of one or more nodes and holds entire data and provides indexing & search capabilities.
Nodes can join a cluster by cluster’s name.

A node is a single server(part of the cluster) and participates in indexing and search capabilities.
Node can be configured to join specific cluster by the cluster name.

Deprecated in 6.0.0
A type used to be a logical category/partition of your index to allow you to store different types of documents in the same index

Basic unit of JSON blog that can be indexed. One might say it’s like a tuple(row) in db table.
Within an index, you can store as many documents as you want.

Index can store large amounts of data, which can exceed hardware limits of a single node.
A single index of a billion documents taking up 1TB of disk space may not fit on the disk of a single node or may be too slow to serve search requests from a single node alone.
An index can be subdivide into multiple pieces called shards.
When you create an index, you can simply define the number of shards that you want
Each shard is in itself a fully-functional and independent “index” that can be hosted on any node in the cluster.
Sharding is important for two primary reasons:
- It allows you to horizontally split/scale your content volume
- It allows you to distribute and parallelize operations across shards (potentially on multiple nodes) thus increasing performance/throughput

Replication is important for two primary reasons:
- It provides high availability in case a shard/node fails. For this reason, it is important to note that a replica shard is never allocated on the same node as the original/primary shard that it was copied from.
- It allows you to scale out your search volume/throughput since searches can be executed on all replicas in parallel.