Building a Big Data Analytics Stack [Video]

Building a Big Data Analytics Stack [Video]

Tomasz Lelek

Learn about Big Data tools needed to create Big Data Stack
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Video Description

Building a Big Data ecosystem is hard. There are a variety of technologies available and every one of them has its pros and cons. When building a big data pipeline for software engineers, we need to use more low-level tools and APIs such as HBase and Apache Spark.

In this course, we’ll check out HBase, a database built by optimizing on the HDFS. Moving on, we’ll have a bit of fun with Spark MLlib. Finally, you’ll get an understanding of ETL and deploy a Hadoop project to the cloud. Building Big Data Ecosystem is hard. There are a variety of technologies available and every one of them has own pros and cons. Software Engineers we need to use more low-level tools and APIs like HBase and Apache Spark while building big data pipeline.

By the end of the course, you’ll be able to use more high-level tools that have more user-friendly, declarative APIs such as Pig and Hive.

Style and Approach

This course will give you both a knowledge-based understanding and practical hands-on experience of Hadoop 2.7. It also looks at Spark, Pig, Hive, HBase, and YARN, so you can understand how to implement these components while using Hadoop clusters.

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What You Will Learn

  • Use Pig and Hive in a non-Java way to understand the power of Hadoop
  • Explore Spark and use it to stream and batch process
  • Use HBase database from Java application
  • Find out more about the machine learning toolkit and its use with Spark
  • Know how to leverage the pros of Big Data tools

Authors

Video Details

ISBN 139781787125018
Course Length1 hour 31 minutes
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