TGx:Packt | Apache Spark: Tips, Tricks, & Techniques [FCO]

Hot Picks

First Cam

New Movies

1080p x265

New TV

Misc

Torrent details for "Packt | Apache Spark: Tips, Tricks, & Techniques [FCO]" Log in to bookmark

Quicknav > Description Read comments 0 Post guest comment

Torrent details

Name:

Packt | Apache Spark: Tips, Tricks, & Techniques [FCO]

Controls:

Report Torrent

Torrent verified by Prom3th3uS

Category:

Other > Training

Language:

English

Total Size:

1.50 GB

Info Hash:

07515abcec14b8fb028a29b4edadfe05733c105a

Added By:

Prom3th3uS :_blocked:

Added:

21-10-2019 19:54

Views:

548

Update stats Post guest comment 0

Health:

Seeds:

Leechers:

Completed:

File	Size
0. Websites you may like/0. (1Hack.Us) Premium Tutorials-Guides-Articles & Community based Forum.url	377.00 B
0. Websites you may like/1. (FreeTutorials.Us) Download Udemy Paid Courses For Free.url	328.00 B
0. Websites you may like/2. (FreeCoursesOnline.Me) Download Udacity, Masterclass, Lynda, PHLearn, Pluralsight Free.url	286.00 B
0. Websites you may like/3. (NulledPremium.com) Download E-Learning, E-Books, Audio-Books, Comics, Articles and more... etc.url	163.00 B
0. Websites you may like/4. (FTUApps.com) Download Cracked Developers Applications For Free.url	239.00 B
0. Websites you may like/How you can help Team-FTU.txt	229.00 B
1. The Course Overview.mp4	14.62 MB
1. The Course Overview.vtt	2.25 kB
10. Immutability in the Highly Concurrent Environment.mp4	49.64 MB
10. Immutability in the Highly Concurrent Environment.vtt	4.56 kB
11. Using Dataset API in an Immutable Way.mp4	18.67 MB
11. Using Dataset API in an Immutable Way.vtt	2.73 kB
12. Detecting a Shuffle in a Processing.mp4	45.14 MB
12. Detecting a Shuffle in a Processing.vtt	4.73 kB
13. Testing Operations That Cause Shuffle in Apache Spark.mp4	44.20 MB
13. Testing Operations That Cause Shuffle in Apache Spark.vtt	4.60 kB
14. Changing Design of Jobs with Wide Dependencies.mp4	33.06 MB
14. Changing Design of Jobs with Wide Dependencies.vtt	3.30 kB
15. Using keyBy() Operations to Reduce Shuffle.mp4	38.00 MB
15. Using keyBy() Operations to Reduce Shuffle.vtt	3.81 kB
16. Using Custom Partitioner to Reduce Shuffle.mp4	33.69 MB
16. Using Custom Partitioner to Reduce Shuffle.vtt	3.82 kB
17. Saving Data in Plain Text.mp4	48.98 MB
17. Saving Data in Plain Text.vtt	5.25 kB
18. Leveraging JSON as a Data Format.mp4	42.29 MB
18. Leveraging JSON as a Data Format.vtt	4.38 kB
19. Tabular Formats – CSV.mp4	40.83 MB
19. Tabular Formats – CSV.vtt	3.60 kB
2. Using Spark Transformations to Defer Computations to a Later Time.mp4	42.57 MB
2. Using Spark Transformations to Defer Computations to a Later Time.vtt	4.67 kB
20. Using Avro with Spark.mp4	41.67 MB
20. Using Avro with Spark.vtt	4.55 kB
21. Columnar Formats – Parquet.mp4	27.33 MB
21. Columnar Formats – Parquet.vtt	4.08 kB
22. Available Transformations on KeyValue Pairs.mp4	44.43 MB
22. Available Transformations on KeyValue Pairs.vtt	4.23 kB
23. Using aggregateByKey Instead of groupBy.mp4	62.41 MB
23. Using aggregateByKey Instead of groupBy.vtt	4.85 kB
24. Actions on KeyValue Pairs.mp4	37.98 MB
24. Actions on KeyValue Pairs.vtt	3.16 kB
25. Available Partitioners on KeyValue Data.mp4	54.99 MB
25. Available Partitioners on KeyValue Data.vtt	4.26 kB
26. Implementing Custom Partitioner.mp4	52.28 MB
26. Implementing Custom Partitioner.vtt	4.99 kB
27. Separating Logic from Spark Engine – Unit Testing.mp4	37.18 MB
27. Separating Logic from Spark Engine – Unit Testing.vtt	4.17 kB
28. Integration Testing Using SparkSession.mp4	42.15 MB
28. Integration Testing Using SparkSession.vtt	3.63 kB
29. Mocking Data Sources Using Partial Functions.mp4	48.17 MB
29. Mocking Data Sources Using Partial Functions.vtt	4.22 kB
3. Avoiding Transformations.mp4	40.23 MB
3. Avoiding Transformations.vtt	3.89 kB
30. Using ScalaCheck for Property-Based Testing.mp4	47.02 MB
30. Using ScalaCheck for Property-Based Testing.vtt	3.81 kB
31. Testing in Different Versions of Spark.mp4	33.85 MB
31. Testing in Different Versions of Spark.vtt	3.65 kB
32. Creating Graph from Datasource.mp4	31.01 MB
32. Creating Graph from Datasource.vtt	3.40 kB
33. Using Vertex API.mp4	64.18 MB
33. Using Vertex API.vtt	4.48 kB
34. Using Edge API.mp4	38.90 MB
34. Using Edge API.vtt	2.96 kB
35. Calculate Degree of Vertex.mp4	44.34 MB
35. Calculate Degree of Vertex.vtt	3.79 kB
36. Calculate Page Rank.mp4	46.60 MB
36. Calculate Page Rank.vtt	4.32 kB
37. Test Your Knowledge.html	167.00 B
4. Using reduce and reduceByKey to Calculate Results.mp4	60.38 MB
4. Using reduce and reduceByKey to Calculate Results.vtt	5.16 kB
5. Performing Actions That Trigger Computations.mp4	65.21 MB
5. Performing Actions That Trigger Computations.vtt	5.24 kB
6. Reusing the Same RDD for Different Actions.mp4	42.98 MB
6. Reusing the Same RDD for Different Actions.vtt	3.76 kB
7. Delve into Spark RDDs ParentChild Chain.mp4	65.74 MB
7. Delve into Spark RDDs ParentChild Chain.vtt	6.15 kB
8. Using RDD in an Immutable Way.mp4	27.87 MB
8. Using RDD in an Immutable Way.vtt	3.31 kB
9. Using DataFrame Operations to Transform It.mp4	29.87 MB
9. Using DataFrame Operations to Transform It.vtt	3.48 kB

Description

For More Udemy Free Courses >>> https://freetutorials.us/
For more Lynda and other Courses >>> https://www.freecoursesonline.me/
Forum for discussion >>> https://1hack.us/

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.