Explanation:
In Elasticsearch, a shard can be either a primary shard or a replica shard.
When an index is created, it is divided into a configurable number of primary shards, each of which is a self-contained index. Primary shards are responsible for handling all write requests to the index and are responsible for splitting the indexing workload across the cluster. The number of primary shards in an index is fixed at index creation time and cannot be changed later.
Explanation:
Yes, that is correct. If a document is indexed in Elasticsearch without specifying an ID, Elasticsearch will automatically generate a unique ID for the document. The generated ID is a 20-character string in hexadecimal format, based on the current timestamp and a node-specific identifier.
Elasticsearch assigns a unique ID to each document to enable efficient retrieval, update, and deletion of individual documents. IDs are also used to ensure that duplicate documents are not indexed and to enforce versioning and concurrency control.
Explanation:
Each shard in Elasticsearch is a Lucene index.
Lucene is an open-source search engine library written in Java that provides the core indexing and search functionality used by Elasticsearch. Elasticsearch is built on top of Lucene and extends its capabilities to provide distributed search and analytics features.
Explanation:
In Elasticsearch, documents are not strictly immutable, but they are treated as such by default.
When a document is indexed in Elasticsearch, it is stored as an immutable JSON object. Any subsequent updates to the document will create a new version of the document with a new ID, leaving the original document intact. The new version of the document is treated as a completely separate document and can be accessed and searched independently of the original version.
Explanation:
Each segment in Elasticsearch is a self-contained inverted index.
Inverted indexing is a data structure used by search engines to store and quickly search through text-based data. It works by creating an index that maps each term in the data to the documents that contain it. This index is typically stored in memory or on disk as a set of inverted lists, which can be searched efficiently using techniques such as binary search and merge operations.
Explanation:
Replica shards are exact copies of the primary shard. When an index is created, each primary shard in the index is assigned one or more replica shards. Replica shards are created by copying the primary shard's data, and they are kept in sync with the primary shard through a process called replication.
Explanation:
An index in Elasticsearch can be split into multiple shards.
Sharding is the process of breaking down a large index into smaller, more manageable pieces called shards. Each shard is a self-contained index that can be stored and searched independently on any node in the Elasticsearch cluster. By dividing the index into shards, Elasticsearch can distribute the search and indexing workload across multiple nodes, providing faster search response times and higher indexing throughput.
