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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  • Hey Sankalp, I will definitely share a slide regarding what is the advantages of elasticsearch over shared database and other search techniques.
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  • Hey Roopendra, the slides are awesome and they exactly say as there title , quick start up indeed.Keep sharing the stuff. If you can help us know some clarity on Why elastic search? (Though having sharded database), it would be great.
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  • 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