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[FreeCoursesOnline.Me] [Packt] Apache Spark Tips, Tricks, & Techniques [FCO]

[FreeCoursesOnline.Me] [Packt] Apache Spark Tips, Tricks, & Techniques [FCO]

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Description
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By : Tomasz Lelek
Released : November 30, 2018
Torrent Contains : 79 Files, 1 Folders
Caption (CC) : Included
Course Source : https://www.packtpub.com/application-development/apache-spark-tips-tricks-techniques-video

Discover proven techniques to create testable, immutable, and easily parallelizable Spark jobs

Video Details

ISBN 9781789801125
Course Length 2 hours 26 minutes

Table of Contents

• Transformations and Actions
• Immutable Design
• Avoid Shuffle and Reduce Operational Expenses
• Saving Data in the Correct Format
• Working with Spark Key/Value API
• Testing Apache Spark Jobs
• Leveraging Spark GraphX API

Learn

• Compose Spark jobs from actions and transformations
• Create highly concurrent Spark programs by leveraging immutability
• Ways to avoid the most expensive operation in the Spark API—Shuffle
• How to save data for further processing by picking the proper data format saved by Spark
• Parallelize keyed data; learn of how to use Spark's Key/Value API
• Re-design your jobs to use reduceByKey instead of groupBy
• Create robust processing pipelines by testing Apache Spark jobs
• Solve repeated problems by leveraging the GraphX API

About

Apache Spark has been around for quite some time, but do you really know how to get the most out of Spark? This course aims at giving you new possibilities; you will explore many aspects of Spark, some you may have never heard of and some you never knew existed.

In this course you'll learn to implement some practical and proven techniques to improve particular aspects of programming and administration in Apache Spark. You will explore 7 sections that will address different aspects of Spark via 5 specific techniques with clear instructions on how to carry out different Apache Spark tasks with hands-on experience. The techniques are demonstrated using practical examples and best practices.

By the end of this course, you will have learned some exciting tips, best practices, and techniques with Apache Spark. You will be able to perform tasks and get the best data out of your databases much faster and with ease.

All the code and supporting files for this course are available on Github at https://github.com/PacktPublishing/Apache-Spark-Tips-Tricks-Techniques

Style and Approach

This step-by-step and fast-paced guide will help you learn different techniques you can use to optimize your testing time, speed, and results with a practical approach, take your skills to the next level, and get you up-and-running with Spark.

Features:

• Speed up your Spark jobs by reducing shuffles
• Leverage the Key/Value API in your big data processing to make your jobs work faster with lower network traffic
• Test Spark jobs using the unit, integration, and end-to-end techniques to make your data pipeline robust and bullet proof

Author

Tomasz Lelek

Tomasz Lelek is a software engineer who programs mostly in Java and Scala. He has worked with the core Java language for the past six years. He has developed multiple production Java software projects that work in a reactive way. He is passionate about nearly everything associated with software development and believes that we should always try to consider different solutions and approaches before solving a problem. Recently, he was a speaker at conferences in Poland, at JDD (Java Developers Day), and at Krakow Scala User Group. He has also conducted a live coding session at Geecon Conference. He is a co-founder of initLearn, an e-learning platform that was built with the Java language. He has also written articles about everything related to the Java world.




File list
  • [FreeCoursesOnline.Me] [Packt] Apache Spark Tips, Tricks, & Techniques [FCO]
  • 0. Websites you may like/How you can help Team-FTU.txt 229 B
  • 1. The Course Overview.mp4 14.6 MB
  • 1. The Course Overview.vtt 2.2 KB
  • 10. Immutability in the Highly Concurrent Environment.mp4 49.6 MB
  • 10. Immutability in the Highly Concurrent Environment.vtt 4.6 KB
  • 11. Using Dataset API in an Immutable Way.mp4 18.7 MB
  • 11. Using Dataset API in an Immutable Way.vtt 2.7 KB
  • 12. Detecting a Shuffle in a Processing.mp4 45.1 MB
  • 12. Detecting a Shuffle in a Processing.vtt 4.7 KB
  • 13. Testing Operations That Cause Shuffle in Apache Spark.mp4 44.2 MB
  • 13. Testing Operations That Cause Shuffle in Apache Spark.vtt 4.6 KB
  • 14. Changing Design of Jobs with Wide Dependencies.mp4 33.1 MB
  • 14. Changing Design of Jobs with Wide Dependencies.vtt 3.3 KB
  • 15. Using keyBy() Operations to Reduce Shuffle.mp4 38 MB
  • 15. Using keyBy() Operations to Reduce Shuffle.vtt 3.8 KB
  • 16. Using Custom Partitioner to Reduce Shuffle.mp4 33.7 MB
  • 16. Using Custom Partitioner to Reduce Shuffle.vtt 3.8 KB
  • 17. Saving Data in Plain Text.mp4 49 MB
  • 17. Saving Data in Plain Text.vtt 5.2 KB
  • 18. Leveraging JSON as a Data Format.mp4 42.3 MB
  • 18. Leveraging JSON as a Data Format.vtt 4.4 KB
  • 19. Tabular Formats – CSV.mp4 40.8 MB
  • 19. Tabular Formats – CSV.vtt 3.6 KB
  • 2. Using Spark Transformations to Defer Computations to a Later Time.mp4 42.6 MB
  • 2. Using Spark Transformations to Defer Computations to a Later Time.vtt 4.7 KB
  • 20. Using Avro with Spark.mp4 41.7 MB
  • 20. Using Avro with Spark.vtt 4.6 KB
  • 21. Columnar Formats – Parquet.mp4 27.3 MB
  • 21. Columnar Formats – Parquet.vtt 4.1 KB
  • 22. Available Transformations on KeyValue Pairs.mp4 44.4 MB
  • 22. Available Transformations on KeyValue Pairs.vtt 4.2 KB
  • 23. Using aggregateByKey Instead of groupBy.mp4 62.4 MB
  • 23. Using aggregateByKey Instead of groupBy.vtt 4.8 KB
  • 24. Actions on KeyValue Pairs.mp4 38 MB
  • 24. Actions on KeyValue Pairs.vtt 3.2 KB
  • 25. Available Partitioners on KeyValue Data.mp4 55 MB
  • 25. Available Partitioners on KeyValue Data.vtt 4.3 KB
  • 26. Implementing Custom Partitioner.mp4 52.3 MB
  • 26. Implementing Custom Partitioner.vtt 5 KB
  • 27. Separating Logic from Spark Engine – Unit Testing.mp4 37.2 MB
  • 27. Separating Logic from Spark Engine – Unit Testing.vtt 4.2 KB
  • 28. Integration Testing Using SparkSession.mp4 42.1 MB
  • 28. Integration Testing Using SparkSession.vtt 3.6 KB
  • 29. Mocking Data Sources Using Partial Functions.mp4 48.2 MB
  • 29. Mocking Data Sources Using Partial Functions.vtt 4.2 KB
  • 3. Avoiding Transformations.mp4 40.2 MB
  • 3. Avoiding Transformations.vtt 3.9 KB
  • 30. Using ScalaCheck for Property-Based Testing.mp4 47 MB
  • 30. Using ScalaCheck for Property-Based Testing.vtt 3.8 KB
  • 31. Testing in Different Versions of Spark.mp4 33.8 MB
  • 31. Testing in Different Versions of Spark.vtt 3.7 KB
  • 32. Creating Graph from Datasource.mp4 31 MB
  • 32. Creating Graph from Datasource.vtt 3.4 KB
  • 33. Using Vertex API.mp4 64.2 MB
  • 33. Using Vertex API.vtt 4.5 KB
  • 34. Using Edge API.mp4 38.9 MB
  • 34. Using Edge API.vtt 3 KB
  • 35. Calculate Degree of Vertex.mp4 44.3 MB
  • 35. Calculate Degree of Vertex.vtt 3.8 KB
  • 36. Calculate Page Rank.mp4 46.6 MB
  • 36. Calculate Page Rank.vtt 4.3 KB
  • 37. Test Your Knowledge.html 167 B
  • 4. Using reduce and reduceByKey to Calculate Results.mp4 60.4 MB
  • 4. Using reduce and reduceByKey to Calculate Results.vtt 5.2 KB
  • 5. Performing Actions That Trigger Computations.mp4 65.2 MB
  • 5. Performing Actions That Trigger Computations.vtt 5.2 KB
  • 6. Reusing the Same RDD for Different Actions.mp4 43 MB
  • 6. Reusing the Same RDD for Different Actions.vtt 3.8 KB
  • 7. Delve into Spark RDDs ParentChild Chain.mp4 65.7 MB
  • 7. Delve into Spark RDDs ParentChild Chain.vtt 6.1 KB
  • 8. Using RDD in an Immutable Way.mp4 27.9 MB
  • 8. Using RDD in an Immutable Way.vtt 3.3 KB
  • 9. Using DataFrame Operations to Transform It.mp4 29.9 MB
  • 9. Using DataFrame Operations to Transform It.vtt 3.5 KB

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