Complete ElasticSearch with LogStash, Hive, Pig, MR & Kibana

Complete ElasticSearch with LogStash, Hive, Pig, MR & Kibana

Complete ElasticSearch tutorial for beginners to advanced level professionals.

Learn how to use ElasticSearch with Apache Hadoop and build various real world big data applications.

This comprehensive course focuses on building real world like data applications to move data from one system to another. A common practice for any data engineer today. No other course can cover so much ground as you will do in this one.

In this course you will learn:

Section 1 – Ingestion Flows (Hadoop to ElasticSearch)

In this section of the course, you will learn to move data from various Hadoop applications (such as Hive, Pig, MR) & LogStash into an ElasticSearch index. This is an ideal business use case to prepare data for business analytics. Here are four major topics that will be covered in this section of the course:

• Learn how to install Apache Hive on your computer. Then read data from a hive table and load it into ElasticSearch

• Learn how to install Apache PIG on your computer and index data into ElasticSearch using Apache PIG

• Create a MapReduce program (Java code) and load data into an ElasticSearch index

• Learn how to move data using LogStash into an ElasticSearch index

Section 2 – Egression Flows (ElasticSearch to Hadoop)

In this section of the course, you will learn to use indexed data from an ElasticSearch cluster and load it back into Hadoop cluster. After data is loaded back into Hadoop, you will learn how to directly import it into Hive, Pig, M/R or LogStash. Here are four major topics that we will cover under this section:

• Learn how to import an ElasticSearch index directly into Apache Hive table

• Learn how to import an ElasticSearch indexed data into Hadoop using Apache PIG scripts

• Learn how to import an ElasticSearch indexed data into Hadoop using Java MapReduce program

• Learn how to import an ElasticSearch indexed data using LogStash application

Section 3 – Data Visualization (Business Intelligence)

In part of the course, you will learn how to use indexed data from an ElasticSearch cluster and create dynamic dashboards using Kibana.

This will be a very important lesson for Data Analysts and Data Scientists.

Section 4 – Production Cluster Monitor tool (Administration)

No knowledge is complete without learning how to maintain an application in production. In this section of the course, you will learn how to monitor your ElasticSearch cluster using Marvel plugins. Here are few things that you will learn:

• Cluster Health monitoring at Index, Shard, Node levels

• Parsing ElasticSearch Cluster statistics using Linux utilities

• Setting up wait-for-trigger mechanism and much more

Section 5 - Searching an ElasticSearch Index

• Learn about awesome search capabilities offered by ElasticSearch

• How to search something from an ElasticSearch index in real time.
  

We will cover lots of basics to build foundation required to understand ElasticSearch. You will also learn about behind the scenes on how a search engine and specifically ElasticSearch works in a single or multiple node cluster.

You will also get step by step instructions for installing all required tools and components on your machine in order to run  all examples provided in this course. Each video will explain entire process in detail and easy to understand manner.

You will get access to working code for you to play with it and expand on it. All code examples are working and will be demonstrated in video lessons.

Windows users will need to install virtual machine on their PC to setup single node hadoop cluster. Detailed Instructions are available inside the course.

ELK Stack (ElasticSearch - LogStash - Kibana) including hands-on practicals with Apache Hadoop, Hive, PIG & MapReduce

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What you will learn

• Advance your career in Big data by learning how to integrate ElasticSearch on Hadoop Ecosystem and create real world data pipelines for your big data applications.
• Develop sound understanding of data ingestion, integration across systems, full text search & data analytics.
• Develop in demand skills for building Data Pipelines using Apache Hive, Pig, MapReduce (Java), & LogStash to index data into ElasticSearch clusters for quick data analytics and text searching.

Rating: 2.75

Level: All Levels

Duration: 6 hours

Instructor: DataShark Academy