索引被分解成碎片，以便分布它们和扩展它们。

副本是碎片的副本。

节点是弹性搜索的一个运行实例，属于一个集群。

集群由一个或多个具有相同集群名称的节点组成。每个集群都有一个由集群自动选择的主节点，如果当前的主节点发生故障，可以将其替换。

Elasticsearch is superbly scalable with all the credit goes to its distributed architecture. It is made possible due to Sharding. Now, before moving further into it, let us consider a simple and very common use case. Let us suppose, you have an index which contains a hell lot of documents, and for the sake of simplicity, consider that the size of that index is 1 TB (i.e, Sum of sizes of each and every document in that index is 1 TB). Also, assume that you have two Nodes each with 512 GB of space available for storing data. As can be seen clearly, our entire index cannot be stored in any of the two nodes available and hence we need to distribute our index among these Nodes.

在这种情况下，索引的大小超过了单个节点的硬件限制，Sharding就可以发挥作用。Sharding通过将索引划分为更小的块来解决这个问题，这些块被命名为Shards。

索引被分解成碎片，以便分布它们和扩展它们。

副本是分片的副本，在节点丢失时提供可靠性。这个数字经常会引起混淆，因为副本计数== 1意味着集群必须有可用的分片的主副本和复制副本才能处于绿色状态。

为了创建副本，您的集群中必须至少有2个节点。

你可能会发现这里的定义更容易理解: http://www.elasticsearch.org/guide/reference/glossary/

不是答案，而是ElasticSearch的核心概念的另一个参考，我认为它们非常清楚地补充了@javanna的答案。

碎片

An index can potentially store a large amount of data that can exceed the hardware limits of a single node. For example, 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. To solve this problem, Elasticsearch provides the ability to subdivide your index 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.

副本

In a network/cloud environment where failures can be expected anytime, it is very useful and highly recommended to have a failover mechanism in case a shard/node somehow goes offline or disappears for whatever reason. To this end, Elasticsearch allows you to make one or more copies of your index’s shards into what are called replica shards, or replicas for short. 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.

用最简单的术语来说，碎片只是存储在磁盘上一个分离文件夹中的索引的一部分:

这个截图显示了整个Elasticsearch目录。

如您所见，所有数据都进入data目录。

通过检查索引C-mAfLltQzuas72iMiIXNw，我们看到它有五个碎片(文件夹0到4)。

另一方面，JH_A8PgCRj-GK0GeQ0limw索引只有一个碎片(0文件夹)。

pri表示碎片的总数。

索引被分解成碎片，以便分布它们和扩展它们。

副本是碎片的副本。

节点是弹性搜索的一个运行实例，属于一个集群。

集群由一个或多个具有相同集群名称的节点组成。每个集群都有一个由集群自动选择的主节点，如果当前的主节点发生故障，可以将其替换。