Outils logiciels pour les cours Paris II

Cours Paris II

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Elasticsearch

Data Analysis with NoSQL Databases

Prerequisite :

  • Java 8 or 9
  • Root access

ElasticSearch

Elastic Search is an open source, RESTful distributed and scalable search engine. Elastic search is extremely fast in fetching results for simple or complex queries on large amounts of data (Petabytes) because of it’s simple design and distributed nature. It is also much easier to work with than a conventional database constrained by schemas, tables.

Elastic Search provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents.

Installation of ElasticSearch

Installation and initialization is quite simple and it is as follows:

Elasticsearch instance should be running at http://localhost:9200 in your browser if you run with default configuration.

Keep the terminal open where elastic search is running to be able to keep the instance running. you could also use nohup mode to run the instance in the background.

Kibana

Kibana is an open source data exploration and visualization tool built on Elastic Search to help you understand data better. It provides visualization capabilities on top of the content indexed on an Elasticsearch cluster. Users can create bar, line and scatter plots, or pie charts and maps on top of large volumes of data.

Installation of Kibana

Installation and initialization is similar to that of Elasticsearch:

  • Download and unzip Kibana https://www.elastic.co/fr/downloads/kibana
  • Open config / Kibana.yml in an editor and Set elasticsearch.url to point at your Elasticsearch instance
  • Change the directory to Kibana folder
  • Run bin/Kibana (or bin\Kibana.bat on Windows) with root access

Kibana instance should be running at http://localhost:5601 in your browser if you run with default configuration.

Keep the terminal open where Kibana was run to be able to keep the instance running. you could also use nohup mode to run the instance in the background.

Data Ingestion in NoSql Databases

  • Twitter example:

Create Visualizations into Kibana

  • Click on Visualize > Create a Visualization > Select the Visualization type > Select the index (Datasource) > Build
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