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Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
Elasticsearch Introduction
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Elasticsearch Introduction

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This is presentation I have prepare to understand elasticsearch overview and quick start up. Hopefully it will help to understand basic

This is presentation I have prepare to understand elasticsearch overview and quick start up. Hopefully it will help to understand basic

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Transcript

  • 1. Introduction and quick startup http://www.elasticsearch.org/
  • 2. Topics to cover • Elasticsearch and its introduction – – – – Cluster Node Index Shards • Primary • secondary • Installation • Setup and configuration – Data Node – Master Node – Serving Node • Queries – Varies Queries
  • 3. What is Elasticsearch? • Elasticsearch is a search server based on Lucene. It provides a distributed, multitenantcapable full-text search engine with a RESTful web interface and schema-free JSON documents. Elasticsearch is developed in Java and is released as open source under the terms of the Apache License.
  • 4. What is Apache Lucene • Apache LuceneTM is a high-performance, fullfeatured text search engine library written entirely in Java. It is a technology suitable for nearly any application that requires full-text search, especially cross-platform.
  • 5. Features • Real time analytics • Distributed • High availability – Automatic discovery of peers in a cluster • • • • • • • Multi tenant architecture Full text Document oriented Schema free RESTful API Per-operation persistence Easy to extend with a plugin system for new functionality
  • 6. Terminology Relation Databases • Database • Table • Row • Column • Schema Elasticsearch Index Type Document Fields Mapping
  • 7. Document $ curl -XGET http://localhost:9200/gems/document/pry-0.5.9 In ElasticSearch, everything is stored as a Document. Document can be addressed and retrieved by querying their attributes.
  • 8. Document Types Lets us specify document properties, so we can differentiate the objects Shard Each Shard is a separate native Lucene Index.
  • 9. Replica An exact copy of primary Shard. Helps in setting up High Availability, increases query throughput.
  • 10. Index • ElasticSearch stores its data in logical Indices. Think of a table,collection or a database. • An Index has atleast 1 primary Shard, and 0 or more Replicas.
  • 11. Cluster A collection of cooperating ElasticSearch nodes. Gives better availability and performance via Index Sharding and Replicas.
  • 12. Installation • Download and unzip the latest Elasticsearch distribution – http://www.elasticsearch.org/download/ • Run bin/elasticsearch -f on Unix, or bin/elasticsearch.bat on Windows • Run curl -X GET http://localhost:9200/ Note:ElasticSearch is built using Java, and requires at least Java 6 in order to run.
  • 13. RESTful interface
  • 14. You can check also
  • 15. How to add Index • To index that we decide on an index name ("movies"), a type name ("movie") and an id ("1") and make a request following the pattern described above with the JSON object in the body. curl -XPUT "http://localhost:9200/movies/movie/1" -d' { "title": "The Godfather", "director": "Francis Ford Coppola", "year": 1972 }'
  • 16. The _search endpoint • http://serverName:9200/_search • Search across all indexes and all types. • http://serverName:9200/indexname/_search • Search across all types in the indexname index. • http://serverName:9200/indexname/post/_search • - Search explicitly for documents of type indexname within the post index
  • 17. Basic Queries Using Only the Query String {endpoint}/_search?q=fashion&size=5 e.g http://fullservername.com/_search?q=fashion&size=5 curl -XGET {endpoint}/_search -d 'Query-as-JSON' For example: curl -XGET {endpoint}/_search -d '{ "query" : { "term" : { "user": "kimchy" } } } 17
  • 18. Match all / Find Everything { "query": { "match_all": {} } }
  • 19. Classic Search-Box Style Full-Text Query { "query": { "query_string": { "query": {query string} } } }
  • 20. Thanks for reading it – Roopendra Vishwakarma

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