The shards index fragmentation of ElasticSearch can break up and distribute index data to different nodes.

Question

Options

• ATrue
• BFalse

• A
  78% (35)
• B
  22% (10)

Explanation

Sharding in Elasticsearch does exactly this - when you create an index, Elasticsearch divides it into shards, which are fully functional, independent Lucene indices. Each shard can be assigned to a different node in the cluster, allowing both data storage and query processing to be distributed horizontally across machines. This is the foundational mechanism behind Elasticsearch's scalability and fault tolerance.

Why B is wrong: Sharding is not just a theoretical concept - it is actively enforced at index creation time (defaulting to 1 primary shard in recent versions, configurable up to hundreds), and those shards are physically placed on separate nodes when a cluster has multiple nodes available.

Memory tip: Think of an Elasticsearch index like a book - shards are the individual chapters torn out and handed to different team members to read simultaneously. "Shards Split, Scatter, Scale" captures the three things they do: break data apart, distribute it across nodes, and enable horizontal scaling.

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