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Learning Apache Spark 2

Learning Apache Spark 2

By : Abbasi
3.8 (6)
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Learning Apache Spark 2

Learning Apache Spark 2

3.8 (6)
By: Abbasi

Overview of this book

Apache Spark has seen an unprecedented growth in terms of its adoption over the last few years, mainly because of its speed, diversity and real-time data processing capabilities. It has quickly become the preferred choice of tool for many Big Data professionals looking to find quick insights from large chunks of data. This book introduces you to the Apache Spark framework, and familiarizes you with all the latest features and capabilities introduced in Spark 2. Starting with a detailed introduction to Spark’s architecture and the installation procedure, this book covers everything you need to know about the Spark framework in the most practical manner. You will learn how to perform the basic ETL activities using Spark, and work with different components of Spark such as Spark SQL, as well as the Dataset and DataFrame APIs for manipulating your data. Then, you will perform machine learning using Spark MLlib, as well as perform streaming analytics and graph processing using the Spark Streaming and GraphX modules respectively. The book also gives special emphasis on deploying your Spark models, and how they can be operated in a clustered mode. During the course of the book, you will come across implementations of different real-world use-cases and examples, giving you the hands-on knowledge you need to use Apache Spark in the best possible manner.
Table of Contents (12 chapters)
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Security configuration in Spark

Spark currently supports two methods of authentication:

  • Kerberos
  • Shared Secret

Kerberos authentication

It is recommended to use Kerberos authentication when using Spark on YARN.

A Kerberos Principal is used in a Kerborized system to represent a unique identity. Kerberos can assign tickets to these identities, which helps them identify themselves while accessing Hadoop clusters secured by Kerberos. While the principals can generally have an arbitrary number of components, in Hadoop the principals are of the following format: username/[email protected]. Your user name here can refer to an existing account like HDFS, Mapred, or Spark.

You will need to follow the following steps:

Creation of the Spark Principal and Keytab file - You will need to create a Spark Principal and the Spark keytab file using the following commands:

Tip

FQDN is your Full Qualified Domain Name

  • Creating the Principal:
       kadmin: addprinc -randkey spark/[email protected]
  • Creating the Keytab file...
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