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Troubleshooting Apache Spark
Troubleshooting Apache Spark

Troubleshooting Apache Spark: Solve Common Spark problems with well-proven solutions

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Profile Icon Tomasz Lelek
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€8.99 €112.99
Video Nov 2018 1hr 43mins 1st Edition
Video
€8.99 €112.99
Subscription
Free Trial
Renews at €18.99p/m
Arrow left icon
Profile Icon Tomasz Lelek
Arrow right icon
€8.99 €112.99
Video Nov 2018 1hr 43mins 1st Edition
Video
€8.99 €112.99
Subscription
Free Trial
Renews at €18.99p/m
Video
€8.99 €112.99
Subscription
Free Trial
Renews at €18.99p/m

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Key benefits

  • • Optimize resources and costs by utilizing Spark's speed
  • • Troubleshoot the Spark execution DAG by exploring Spark logical and physical query plans to perform the same logic on fewer executors and machines
  • • Solve the problem of slow-running jobs by speeding up feedback loops by creating efficient transformations and joins using Spark APIs

Description

Apache Spark has been around quite some time, but do you really know how to solve the development issues and problems you face with it? This course will give you new possibilities and you'll cover many aspects of Apache Spark; some you may know and some you probably never knew existed. If you take a lot of time learning and performing tasks on Spark, you are unable to leverage Apache Spark's full capabilities and features, and face a roadblock in your development journey. You'll face issues and will be unable to optimize your development process due to common problems and bugs; you'll be looking for techniques which can save you from falling into any pitfalls and common errors during development. With this course you'll learn to implement some practical and proven techniques to improve particular aspects of Apache Spark with proper research You need to understand the common problems and issues Spark developers face, collate them, and build simple solutions for these problems. One way to understand common issues is to look out for Stack Overflow queries. This course is a high-quality troubleshooting course, highlighting issues faced by developers in different stages of their application development and providing them with simple and practical solutions to these issues. It supplies solutions to some problems and challenges faced by developers; however, this course also focuses on discovering new possibilities with Apache Spark. By the end of this course, you will have solved your Spark problems without any hassle. All the code and supporting files for this course are available on Github at https://github.com/PacktPublishing/Troubleshooting-Apache-Spark

Who is this book for?

If you are an Apache Spark developer at the beginning of your journey and experience a lot of hard problems when using it, this course is for you. You will learn how to solve the most common problems of Apache Spark users

What you will learn

  • • Solve long-running computation problems by leveraging lazy evaluation in Spark
  • • Avoid memory leaks by understanding the internal memory management of Apache Spark
  • • Rework problems due to not-scaling out pipelines by using partitions
  • • Debug and create user-defined functions that enrich the Spark API
  • • Choose a proper join strategy depending on the characteristics of your input data
  • • Troubleshoot APIs for joins - DataFrames or DataSets
  • • Write code that minimizes object creation using the proper API
  • • Troubleshoot real-time pipelines written in Spark Streaming

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Nov 28, 2018
Length: 1hr 43mins
Edition : 1st
Language : English
ISBN-13 : 9781789805253
Vendor :
Apache
Category :
Languages :
Concepts :

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Product Details

Publication date : Nov 28, 2018
Length: 1hr 43mins
Edition : 1st
Language : English
ISBN-13 : 9781789805253
Vendor :
Apache
Category :
Languages :
Concepts :

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Frequently bought together


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Apache Spark: Tips, Tricks, & Techniques
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Troubleshooting Apache Spark
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Table of Contents

5 Chapters
Common Problems and Troubleshooting the Spark Distributed Engine Chevron down icon Chevron up icon
Distributed DataFrames Optimization Pitfalls Chevron down icon Chevron up icon
Distributed Joins in Cluster Chevron down icon Chevron up icon
Solving Problems with Non-Efficient Transformations Chevron down icon Chevron up icon
Troubleshooting Real-Time Processing Jobs in Spark Streaming Chevron down icon Chevron up icon
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