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Learning Spark SQL

You're reading from  Learning Spark SQL

Product type Book
Published in Sep 2017
Publisher Packt
ISBN-13 9781785888359
Pages 452 pages
Edition 1st Edition
Languages
Author (1):
Aurobindo Sarkar Aurobindo Sarkar
Profile icon Aurobindo Sarkar
Toc

Table of Contents (19) Chapters close

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Getting Started with Spark SQL 2. Using Spark SQL for Processing Structured and Semistructured Data 3. Using Spark SQL for Data Exploration 4. Using Spark SQL for Data Munging 5. Using Spark SQL in Streaming Applications 6. Using Spark SQL in Machine Learning Applications 7. Using Spark SQL in Graph Applications 8. Using Spark SQL with SparkR 9. Developing Applications with Spark SQL 10. Using Spark SQL in Deep Learning Applications 11. Tuning Spark SQL Components for Performance 12. Spark SQL in Large-Scale Application Architectures

Visualizing Spark application execution


In this section, we will present the key details of the SparkUI interface, which is indispensable for tuning tasks. There are several approaches to monitoring Spark applications, for example, using web UIs, metrics, and external instrumentation. The information displayed includes a of scheduler stages and tasks, a summary of RDD sizes and memory usage, environmental information, and information about the running executors.

This interface can be accessed by simply opening http://<driver-node>:4040 (http://localhost:4040) in a web browser. Additional SparkContexts running on the host bind to successive ports: 4041, 4042, and so on.

Note

For a more detailed coverage of monitoring and instrumentation in Spark, refer to https://spark.apache.org/docs/latest/monitoring.html.

We will explore Spark SQL execution visually using two examples. First, we create the two sets of Datasets. The difference between the first set (t1, t2, and t3) and the second set...

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