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How does es-hadoop work with elasticsearch and hadoop?


Asked by Callahan Nicholson on Dec 04, 2021 Hadoop



With dynamic extensions to existing Hadoop APIs, ES-Hadoop lets you easily move data bi-directionally between Elasticsearch and Hadoop while exposing HDFS as a repository for long-term archival. Partition awareness, failure handling, type conversions, and co-location are all done transparently.
Just so,
ElasticSearch is a JSON database popular with log processing systems. For example, organizations often use ElasticSearch with logstash or filebeat to send web server logs, Windows events, Linux syslogs, and other data there. Then they use the Kibana web interface to query log events. All of this is important for cybersecurity, operations, etc.
In this manner, Elasticsearch is a full-text, distributed NoSQL database. In other words, it uses documents rather than schema or tables. It's a free, open source tool that allows for real-time searching and analyzing of your data.
Subsequently,
Hadoop is a natural technology to support an analytics platform. Its parallel processing capabilities make it a powerful and blazing fast engine for analytics. With Hadoop and analytics software, you can easily build predictive models—using data not only to see what happened but what is likely to occur and what’s the best course of action.
Consequently,
Elasticsearch is a search engine based on the Lucene library. It provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents.