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 Details

ISBN 139781787125018
Course Length1 hour and 31 minutes

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.

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 and 31 minutes
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