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Elasticsearch presentation 1

  1. Elasticsearch (Presentation 01) By Maruf Hassan Email: maruf571@gmail.com
  2. Contents ● Introduction ● Installation ● Configuration ● Tools(plugin) ● Terms used in Elasticsearch ● Talking with Elasticsearch ● Indexing data ● Retrieving data
  3. Introduction What is Elasticsearch? ● Elasticsearch is an open-source search engine ● Elasticsearch is written in Java ● Built on top of Apache Lucene™ ● A distributed real-time document store where every field is indexed and searchable ● A distributed search engine with real-time analytics
  4. Installation Setup ● Download zip file for elasticsearch web site (https://www.elastic.co/downloads/elasticsearch) ● Unzip it anywhere in you pc Run ● Go to unzip directory & run the following command ./bin/elasticsearch Test ● To test installation hit on browser @ http://localhost:9200/?pretty or curl 'http://localhost:9200/?pretty' “You Know, for Search” Yahoo! everything is file :)
  5. Configuration ● elasticsearch.yml file is the main configuration file in the config directory ● Need restart Elasticsearch to perform update configuration(if you edit elasticsearch.yml )
  6. Tools(plugin) Installation ● Marvel (plugin) is a monitoring tools, to install ./bin/plugin -i elasticsearch/marvel/latest ● Sense is interactive console inside Marvel.(I like it very much) ● Elasticsearch-head is a document browser, to install ./bin/plugin -install mobz/elasticsearch-head Run ● To run marvel hit brouwser @ http://localhost:9200/_plugin/marvel/ ● To run sence hit brouwser @ http://localhost:9200/_plugin/marvel/sense/ ● To run head hit brouwser @ http://localhost:9200/_plugin/head/
  7. Terms used in Elasticsearch ● node: running instance of Elasticsearch ● cluster: group of nodes with the same cluster name ● elasticsearch = relational DB ● indices = databases ● types = tables ● documents = rows
  8. Terms used in Elasticsearch ● fields = columns ● index (noun) = like a database in a traditional relational database ● Index (verb) = to index a document is to store a document in an index (noun) ● Inverted index = relational databases add an index, such as a B-tree index, to specific columns in order to improve the speed of data retrieval. Elasticsearch and Lucene use a structure called an inverted index for exactly the same purpose.
  9. Talking to Elasticsearch Two way for java. Node client & Transport client 1. Node client: Work as a node in local cluster, but don’t hold any data 2. Transport client: Send request to remote cluster, don’t join One way for all ● RESTful API with JSON over HTTP Port ● Both Java clients talk to the cluster over port 9300 ● All other languages can communicate with Elasticsearch over port 9200 using RESTful API
  10. Indexing data ● PUT verb used for indexing(inserting data) ● URL path contains three pieces of information index_name/type_name/id_of_document ● PUT body contain the document as a json Example: PUT /cefalo/employee/1 { "first_name" : "Maruf", "last_name" : "Hassan", "age" : 28, "about" : "Happy to help", "interests": [ "science", "music", "internet" ] }
  11. Retrieve data Two way to retrieve data from Elasticsearch. Search Lite & Query DSL Search Lite ● allows us to build ad hoc searches ● parameters to be passed in the query string ● Used only for test environment Query DSL ● allows us to build much more complicated, robust queries ● expects a JSON request body and uses a rich search language called the query DSL ● Used for production environment
  12. Retrieve data(Search Lite) ● Search for all employees in the index cefalo GET /cefalo/employee/_search ● searching for employees with their last name in cefalo index GET /cefalo/employee/_search? q=last_name:hassan
  13. Retrieve data(Query DSL) ● Search for all employees in the cefalo index GET /cefalo/employee/_search{ } ● Searching for employees with their last name in the cefalo index GET /cefalo/employee/_search { "query" : { "match" : { "last_name" : "Hassan" } } }
  14. Thanks &
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