Search in Elasticsearch

Elasticsearch is a high-performance open source search engine used for indexing and searching large amounts of data. Elasticsearch uses a distributed architecture that allows data to be stored and processed on multiple nodes in a cluster.

Query types

Elasticsearch searches are performed using queries that can be sent to the Elasticsearch server. Queries can be executed using the Elasticsearch API or using tools such as Kibana or Logstash. The main types of queries in Elasticsearch are:

1. Query DSL is a query language that allows you to specify criteria for searching and filtering data. Query DSL supports many operators and functions to refine your data search.
2. Filters - A special type of query that allows you to target queries to retrieve a specific amount of data. Filters are used to set certain limits on queries, which reduces the load on the system and speeds up data retrieval.
3. Aggregations - queries that allow you to analyze data and return it in an ordered form. Aggregations are used to process large amounts of data and provide the ability to analyze and evaluate data more accurately.

Overall, Elasticsearch is a great solution for searching and analyzing large amounts of data, and it allows you to quickly and accurately find data in clusters of data of varying complexity.

How searches are performed

Full-text search: Elasticsearch allows you to search by word and phrase across large volumes of textual data, including structured and unstructured data.

1. Data Aggregation: allows you to create summary tables, group data and read statistics for large amounts of data.
2. Distributed search: can run on multiple nodes to spread the load and process large amounts of data.
3. Data analysis: allows you to analyze data, identify trends, evaluate performance, improve quality, and more.
4. Monitoring: Elasticsearch can be used to monitor systems, applications, and infrastructure to detect and resolve issues quickly and efficiently.

It follows from all this that planning, designing and developing Elasticsearch-based applications requires designing a competent architecture and being able to utilize the full range of Elasticsearch tools and features.