What is the main use of Elasticsearch?
Elasticsearch is used for a lot of different use cases: “classical” full-text search, analytics store, auto-completer, spell checker, alerting engine, and as a general-purpose document store.
Why is Elasticsearch so fast?
Elasticsearch is fast.
Because Elasticsearch is built on top of Lucene, it excels at full-text search. Elasticsearch is also a near real-time search platform, meaning the latency from the time a document is indexed until it becomes searchable is very short — typically one second.
What is an Elasticsearch shard?
The shard is the unit at which Elasticsearch distributes data around the cluster. The speed at which Elasticsearch can move shards around when rebalancing data, e.g. following a failure, will depend on the size and number of shards as well as network and disk performance.
When should Elasticsearch be used?
You want Elasticsearch when you’re doing a lot of text search, where traditional RDBMS databases are not performing really well (poor configuration, acts as a black-box, poor performance). Elasticsearch is highly customizable, extendable through plugins. You can build robust searches without much knowledge quite fast.
What is an index in Elasticsearch?
An index can be thought of as an optimized collection of documents and each document is a collection of fields, which are the key-value pairs that contain your data. By default, Elastic search indexes all data in every field, and each indexed field has a dedicated, optimized data structure.
What is the Elasticsearch cluster?
An Elasticsearch cluster is a group of nodes that have the same cluster. name attribute. As nodes join or leave a cluster, the cluster automatically reorganizes itself to evenly distribute the data across the available nodes. If you are running a single instance of Elasticsearch, you have a cluster of one node.
What is Elasticsearch architecture?
The Elasticsearch architecture is designed to support the retrieval of documents, which are stored as JSON objects. Elasticsearch supports nested structures, which helps handle complex data and queries. To track information, Elasticsearch uses keys prepended with an underscore, which represents metadata.
Where is the data stored in Elasticsearch?
By default, Elasticsearch indexes all data in every field and each indexed field has a dedicated, optimized data structure. For example, text fields are stored in inverted indices, and numeric and geo fields are stored in BKD trees.
What is special about Elasticsearch?
Speed. Speaking of performance, ElasticSearch is able to execute complex queries extremely fast. It also caches almost all of the structured queries commonly used as a filter for the result set and executes them only once. For every other request containing a cached filter, it checks the result from the cache.