Book Image

Learning Apache Spark 2

Book Image

Learning Apache Spark 2

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)

Running Spark in YARN


In the previous section, we covered Spark working in a Standalone cluster, and while on-premises deployment on Standalone clusters accounts for 42% of all Spark deployments, Spark deployment on YARN accounts for 36% of all on-premises deployments. These figures were taken from the Apache Spark survey report published by data bricks in June of 2016.

Figure 8.15: YARN deployments - Databricks survey report: Page 10 (Databricks.com)

YARN has been supported since 0.6 release of Apache Spark. In order to run your application on YARN you need to ensure you have the correct configuration files for your Hadoop cluster, and the following environment variables point towards the right location of these files:

  • HADOOP_CONF_DIR
  • YARN_CONF_DIR

These configuration files will be shipped to the YARN cluster and then distributed to all the containers running the application to make sure that they use same configuration.

When you run an application on YARN you have two deployment modes each...