Udemy - PySpark - Build DataFrames with Python, Apache Spark and SQL

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Udemy - PySpark - Build DataFrames with Python, Apache Spark and SQL (Size: 2.1 GB)
  0 12.1 KB
  1. About Mammoth Interactive.mp4 8.7 MB
  1. About Mammoth Interactive.srt 1.4 KB
  1. Intro To Course And Python.mp4 57.3 MB
  1. Project Preview.mp4 26.3 MB
  1. Project Preview.srt 3.2 KB
  1. Start A Spark Session.mp4 23.6 MB
  1 439.9 KB
  1. Intro To Course And Python.srt 15.3 KB
  1. Start A Spark Session.srt 4.9 KB
  2 94 KB
  3 340.2 KB
  4 46 KB
  10. Conditionals.mp4 38.1 MB
  10. Conditionals.srt 10.5 KB
  11. If Statement Examples.mp4 118 MB
  11. If Statement Examples.srt 34.3 KB
  12. Loops.mp4 167.1 MB
  12. Loops.srt 46.4 KB
  13. Functions.mp4 86.5 MB
  13. Functions.srt 27 KB
  14. Parameters And Return Values Examples.mp4 78.6 MB
  14. Parameters And Return Values Examples.srt 21.8 KB
  15. Classes And Objects.mp4 223.4 MB
  15. Classes And Objects.srt 53.9 KB
  16. Inheritance Examples.mp4 130.7 MB
  16. Inheritance Examples.srt 27.4 KB
  17. Static Members Examples.mp4 78.5 MB
  17. Static Members Examples.srt 16.5 KB
  18. Summary And Outro.mp4 20.9 MB
  18. Summary And Outro.srt 6.1 KB
  2. How To Learn Online Effectively.mp4 74.1 MB
  2. How To Learn Online Effectively.srt 19.8 KB
  2. Load Data As A CSV.mp4 41.2 MB
  2. Load Data As A CSV.srt 7.5 KB
  2. Variables.mp4 106.5 MB
  2. Variables.srt 30.6 KB
  2. What Is Apache Spark.mp4 13.5 MB
  2. What Is Apache Spark.srt 3.2 KB
  3. Perform Basic Dataframe Operations.mp4 32.3 MB
  3. Perform Basic Dataframe Operations.srt 5.4 KB
  3. Source Files.html 0 B
  3. Type Conversion Examples.mp4 59.8 MB
  3. Type Conversion Examples.srt 16.2 KB
  3. What Are Resilient Distributed Datasets.mp4 7.4 MB
  3. What Are Resilient Distributed Datasets.srt 1.3 KB
  3.1 Source Files.zip 2.1 MB
  4. Format Dataframe Table.mp4 39 MB
  4. Format Dataframe Table.srt 6.2 KB
  4. Operators.mp4 161.4 MB
  4. Operators.srt 44.4 KB
  4. What Is A Dataframe.mp4 8.6 MB
  4. What Is A Dataframe.srt 2.2 KB
  5. Collections.srt 13.2 KB
  5 115.8 KB
  5. Collections.mp4 41.6 MB
  5. Perform Dataframe Math Operations.mp4 62.8 MB
  5. Perform Dataframe Math Operations.srt 8.6 KB
  5. What You'll Need.mp4 8.6 MB
  5. What You'll Need.srt 2.2 KB
  6. List Examples.mp4 109.9 MB
  6. List Examples.srt 31 KB
  6. Perform Dataframe Queries.mp4 88 MB
  6. Perform Dataframe Queries.srt 17.8 KB
  6. Source Files.html 0 B
  6.1 Source Files.zip 3 MB
  7. Tuples Examples.srt 13.5 KB
  [TGx]Downloaded from torrentgalaxy.to .txt 614.4 B
  6 499.8 KB
  7. Build SQL Queries With Spark.mp4 44.2 MB
  TutsNode.com.txt 102.4 B
  7 492.6 KB
  7. Build SQL Queries With Spark.srt 8.6 KB
  7. Tuples Examples.mp4 52.5 MB
  8. Dictionaries Examples.mp4 87.3 MB
  8. Dictionaries Examples.srt 22.6 KB
  8. Source Files.html 0 B
  8 163.7 KB
  8.1 Source Files.zip 59.3 KB
  9. Ranges Examples.mp4 53.2 MB
  9. Ranges Examples.srt 13.5 KB
  9 506.7 KB
  10 455 KB
  11 461.7 KB
  12 448.6 KB
  13 204.8 KB
  14 155.2 KB
  15 254.1 KB
  16 294.6 KB
  17 48.9 KB
  18 334.5 KB
  19 368.7 KB
  20 356.2 KB
  21 27.5 KB
  22 459.5 KB
  23 231.8 KB
  24 237.9 KB
  25 447.7 KB
  26 147 KB
  27 48.6 KB
  28 356.5 KB
  29 373.5 KB
  30 374.3 KB
  31 73.7 KB
  32 48.4 KB
  ▲ 105 total files

Description


Description

This course covers all the fundamentals about Apache Spark streaming with Python and teaches you everything you need to know about developing Spark streaming applications using PySpark, the Python API for Spark. At the end of this course, you will gain in-depth knowledge about Spark streaming and general big data manipulation skills to help your company to adapt Spark Streaming for building big data processing pipelines and data analytics applications. This course will be absolutely critical to anyone trying to make it in data science today.

Spark can perform up to 100x faster than Hadoop MapReduce, which has caused an explosion in demand for this skill! Because the Spark 2.0 DataFrame framework is so new, you now have the ability to quickly become one of the most knowledgeable people in the job market!

This course will teach the basics with a crash course in Python, continuing on to learning how to use Spark DataFrames with the latest Spark 2.0 syntax! Once we’ve done that we’ll go through how to use the MLlib Machine Library with the DataFrame syntax and Spark. All along the way, you’ll have exercises and Mock Consulting Projects that put you right into a real-world situation where you need to use your new skills to solve a real problem!

We also cover the latest Spark Technologies, like Spark SQL, Spark Streaming, and advanced models like Gradient Boosted Trees! After you complete this course you will feel comfortable putting Spark and PySpark on your resume! This course also has a full 30-day money-back guarantee and comes with a LinkedIn Certificate of Completion!

If you’re ready to jump into the world of Python, Spark, and Big Data, this is the course for you!
Who this course is for:

Someone who knows Python and would like to learn how to use it for Big Data
Someone who is very familiar with another programming language and needs to learn Spark
Developers transferring from other languages
Python Developers looking to get better at Data Streaming
Spark Developers eager to expand their skills.

Requirements

No necessary experience needed

Last Updated 2/2021

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