In this tutorial, Elasticsearch Tutorial for Beginners, Udemy instructor, Frank Kane will cover Elasticsearch, the Elastic Stack, Kibana, Beats, and Logstash in depth.

This free online tutorial has been updated for Elasticsearch 6! Elasticsearch is an important tool in your big data and data processing arsenal – often, it can return results in milliseconds when it would take Apache Spark or Hadoop hours!

Elasticsearch is not just for search, it is a full featured data analytics and visualization ecosystem that aggregate and analyze massive data sets very quickly.

To learn more, explore the full course on Udemy. Get a discount by using the following link: https://bit.ly/2s6ahiK

We will start with a high level overview of the Elastic Stack ecosystem, and how its components (Elasticsearch, Beats, Logstash, and Kibana) all fit together, and how they are used.

Next we will cover how Elasticsearch organizes data, using documents, types, and indices.

Also covered:

• Inverted Indexes and the fundamentals of search engines
• TF/IDF (Term Frequency / Inverse Document Frequency)
• Elasticsearch APIs including REST, client APIs, and webbased UIs such as Kibana
• Sharding and how indices are hashed into shards
• Replication across primary and replica shards

You will learn what the Elastic Stack is all about, and how it achieves its high scalability and resiliency to failure at very low latencies. Understanding Elasticsearch architecture is the first step toward becoming a developer or administrator of an Elasticsearch cluster. You may find that an Elasticsearch cluster is a great complement to your Spark or Hadoop clusters, and it’s especially well suited for collecting and analyzing web log data.

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