Elasticsearch is a distributed search engine. You dump data to some elasticsearch-index, and then you can make http queries to search the data.
Under the hood, it uses Lucene(search engine library). It creates multiple Lucene indexes( or shard in elasticsearch) for data and distributes them across the nodes. To resolves the search-query sent to elasticsearch, it queries all lucene indexes and combines results and gives back the result. Link for Youtube
video for learning how elasticsearch internals.
Cluster – An Elasticsearch cluster consists of one or more nodes, working together to search and store data and is identifiable by its cluster name.
Node – A single Elasticsearch instance. In most environments, each node runs on a separate box or virtual machine.
It can be one of 4 types.
- Master – Master only node meaning it can work towards cluster related tasks such as shard allocation in the event of new machine availability and/or machine unavailability (instance failure).
- Data – This node can only store data. This is a worker node which just work on indexing data and returning search results.
- Client(Not master neither data) – This node never stores any data and never becomes a master, it works as a load balancer. It accepts incoming query requests and routes to a data node. Fetches data from nodes, aggregates results.
- Master and Data – This is the default setting. A node stores data and is capable of becoming a master node.
It is controlled by 2 values in config value
- An index is a collection of documents that have somewhat similar characteristics.
- Analogy can be what index is to elasticsearch is what database to RDBMS.
- Within index we store multiple kinds of data.
- Data coming to specific index is stored in elasticsearch using a mapping that elasticsearch does dyanmically of us, we can(should) do it manually too.
- An index is a logical namespace which points to primary and replica shards.
- If you’re using ES for some logging or purpose where we have archival data, usually daily or some time-based index are created, which makes archival easy as we can archive last 10-days index as index as time-based.
- We can query ES for searching from index with specific pattern.
- Within index we can have documents of multiple type.
- Type you can think as a table in RDBMS.
- Type has a name and a mapping and each document belongs to some index and is of certain type.
- A document is a basic unit of information, json data you see is a document.
- Shard is basically lucene index(not elasticsearch index).
- Shards are shared across the node to provide distributed search(they’re are part of a index).
- Shards are of two types; Primay, Replica.
- Primary’s are the one that you can specify only once while creating the index, and replica’s are copy of primary shards, which can be altered after index creation.
- Every time you index a document, elasticsearch will decide which primary shard is supposed to hold that document and will index it there. Primary shards are not copy of the data, they are the data!
- Every elasticsearch index is composed of at least one primary shard, since that’s where the data is stored.
- Replica is shard which is exact copy of primary shard i.e. it’ll contain the same data.
- Replicas are used to increase search performance or for fail-over purpose.
- Replica is never allocated on the same node where their primary is.
- We don’t play with shard directly other than specifiying config values for primary shard and replicas
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