Udemy | Learn Apache Spark with Python [FTU]

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1. Module 1 Introduction to Spark with Python
  • 1. Introduction to the Module.mp4 (2.3 MB)
  • 2. What is PySpark.mp4 (9.6 MB)
  • 3. PySpark in Industry.mp4 (17.1 MB)
  • 4. Why to go for Python.mp4 (4.9 MB)
2. Module 2 Introduction to Big Data and Hadoop
  • 10. HDFS Daemons and Mapreduce daemons.mp4 (24.4 MB)
  • 11. HADOOP CLUSTER ARCHITECTURE.mp4 (26.1 MB)
  • 12. Top Reasons Why you should Learn Hadoop.mp4 (61.1 MB)
  • 13. Hadoop distributions and compatibilities.mp4 (5.9 MB)
  • 14. Hadoop Ecosystem in Detail.mp4 (138.3 MB)
  • 15. Hadoop Distributed File System.mp4 (37.8 MB)
  • 16. HDFS Files and Blocks.mp4 (32.5 MB)
  • 17. HDFS components and architecture.mp4 (62.9 MB)
  • 18. HDFS File Read and Write.mp4 (92.6 MB)
  • 1. Big Data Overview.mp4 (23.2 MB)
  • 2. Facts about Big Data.mp4 (38.2 MB)
  • 3. Big Data Scenarios.mp4 (17.4 MB)
  • 4. Apache Hadoop Framework.mp4 (15.2 MB)
  • 5. Top Hadoop Users.mp4 (17.3 MB)
  • 6. HISTORY OF HADOOP.mp4 (13.7 MB)
  • 7. Difference between RDBMS and Hadoop.mp4 (9.9 MB)
  • 8. Cluster Modes in Hadoop.mp4 (7.8 MB)
  • 9. Hadoop Ecosystem.mp4 (41.8 MB)
3. Module 3 Apache Spark Framework
  • 10. Top Companies Using Spark.mp4 (26.7 MB)
  • 1. Batch and Real Time Analytics.mp4 (34.0 MB)
  • 2. Why Spark when Hadoop is Already there.mp4 (12.5 MB)
  • 3. Introduction to Apache Spark.mp4 (27.0 MB)
  • 4. Features of Apache Spark.mp4 (19.6 MB)
  • 5. Users and Use Cases of Apache Spark.mp4 (49.7 MB)
  • 6. Job Execution Flow and Spark Execution.mp4 (5.6 MB)
  • 7. Spark Unified Stack.mp4 (54.9 MB)
  • 8. Complete Picture of Apache Spark.mp4 (20.0 MB)
  • 9. Apache spark Architecture.mp4 (32.3 MB)
4. Module 4 Python Programming Language
  • 10. Variables and assignment.mp4 (137.3 MB)
  • 11. Hands-On.mp4 (156.7 MB)
  • 12. Hands-On.mp4 (98.5 MB)
  • 13. Hands-On.mp4 (161.8 MB)
  • 14. Hands-On.mp4 (138.5 MB)
  • 15. Hands-On.mp4 (34.1 MB)
  • 1. Getting Started with Python.mp4 (1.1 MB)
  • 2. Introduction to Python.mp4 (82.4 MB)
  • 3. Advantages and facts about python.mp4 (93.6 MB)
  • 4. First python program.mp4 (14.1 MB)
  • 5. Program execution and python IDE.mp4 (61.6 MB)
  • 6. Built in types in python.mp4 (34.0 MB)
  • 7. Numbers Data Type in Python.mp4 (52.0 MB)
  • 8. String and List Data Type.mp4 (139.6 MB)
  • 9. Dictionary, Tuples and Sets.mp4 (160.9 MB)
5. Module 5 Advanced Part of Apache Spark with Python
  • 10. Filtering RDD using an example.mp4 (80.7 MB)
  • 11. Finding maximum temperature by location.mp4 (30.4 MB)
  • 12. Map vs FlatMap.mp4 (6.8 MB)
  • 13. Understanding FlatMap using Word Count example.mp4 (59.4 MB)
  • 14. Sorting the word count results.mp4 (40.2 MB)
  • 15. Total Amount Spent Example.mp4 (47.1 MB)
  • 16. Sorting the Total Amount Spent Example result.mp4 (21.0 MB)
  • 1. Downloading and Installing Enthought Canopy.mp4 (18.8 MB)
  • 2. Downloading and Installing jdk.mp4 (19.2 MB)
  • 3. Downloading and Installing Spark.mp4 (23.4 MB)
  • 4. Downloading and Setup of winutils.mp4 (9.2 MB)
  • 5. Setting up Environment Variables.mp4 (17.7 MB)
  • 6. Running the first Spark Program.mp4 (11.6 MB)
  • 7. Downloading and Extracting movie ratings datasets.mp4 (15.1 MB)
  • 8. Running Ratings Counter Spark Program.mp4 (33.4 MB)
  • 9. Understanding key value pairs with an example.mp4 (66.6 MB)
  • vz (0.0 KB)
6. Module 6 Deep Dive Into Spark with Python
  • 1. Most popular movie example.mp4 (52.5 MB)
  • 2. Understanding Broadcast Variables with an example.mp4 (78.4 MB)
  • 3. Finding Similar Movies Example.mp4 (190.9 MB)
  • 4. Finding Most Popular Superhero example.mp4 (99.5 MB)
  • 5. Superhero Degrees of Separation Part1.mp4 (38.7 MB)
  • 6. Superhero Degrees of Separation Part 2.mp4 (142.0 MB)
7. Module 7 SparkSQL in Apache Spark with Python
  • 1. Executing SQL commands.mp4 (64.2 MB)
  • 2. Using SQL style functions instead of queries.mp4 (26.4 MB)
  • 3. Using DataFrames instead of RDDs.mp4 (65.3 MB)
8. Module 8 MLib in Apache Spark with Python
  • 1. Using MLlib to produce movie recommendations.mp4 (101.3 MB)
  • 2. Using Dataframe with MLlib using an example.mp4 (132.4 MB)

Description



A Complete Guide and Integration of Apache Spark Framework and Python Programming

Created by : Edulearners Technologies
Last updated : 2/2019
Language : English
Torrent Contains : 81 Files, 9 Folders
Course Source : https://www.udemy.com/learn-apache-spark-with-python/

What you'll learn

• Introduction to Pyspark
• Filtering RDDs
• Install and run Apache Spark on a desktop computer or on a cluster
• Understand how Spark SQL lets you work with structured data
• Understanding Spark with Examples and many more

Requirements

• Basic Knowledge of Big Data
• Basics of Java and OOPs
• Basic Computer Programming Terminologies

Description

Apache Spark is the hottest Big Data skill today. More and more organizations are adapting Apache Spark for building their big data processing and analytics applications and the demand for Apache Spark professionals is sky rocketing. Learning Apache Spark is a great vehicle to good jobs, better quality of work and the best remuneration packages.

You might already know Apache Spark as a fast and general engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing. It’s well-known for its speed, ease of use, generality and the ability to run virtually everywhere. And even though Spark is one of the most asked tools for data engineers, also data scientists can benefit from Spark when doing exploratory data analysis, feature extraction, supervised learning and model evaluation.

The course will cover many more topics of Apache Spark with Python including-

• What makes Spark a power tool of Big Data and Data Science?
• Learn the fundamentals of Spark including Resilient Distributed Datasets, Spark Actions and Transformations
• Explore Spark SQL with CSV, JSON and mySQL (JDBC) data sources
• Convenient links to download all source code

Who this course is for :

• Java Developers who want to upgrade their skills to light weight language python to handle Big data.
• Hadoop developers who want to learn a fast processing engine SPARK
• Python developers who want to upgrade their skills to handle and process Big data using Apache Spark.
• Any professionals or students who want to learn Big data.

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Our Forum for discussion >>> https://discuss.ftuforum.com/





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Udemy | Learn Apache Spark with Python [FTU]

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3.8 GB
seeders:15
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Udemy | Learn Apache Spark with Python [FTU]

Torrent hash: F1AB66648FEF8125DA22F2879B98894D1C2DC112