Apache Spark and Scala

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01 - Module-1 Introduction to Big data, Hadoop and Spark

001 1.1 Overview of Big Data.mp4

03:27

002 1.2 Introduction to Apache Hadoop.mp4

02:29

003 1.3 Hadoop Distributed File System.mp4

05:00

004 1.4 Hadoop Map Reduce.mp4

03:34

005 1.5 Introduction to Apache Spark.mp4

05:13

006 1.6 Characteristics of Apache Spark.mp4

02:44

007 1.7 Users and Use Cases of Apache Spark.mp4

07:45

008 1.8 Job Execution Flow and Spark Execution.mp4

01:12

009 1.9 Spark Unified Stack.mp4

01:08

010 1.10 Complete Picture of Apache Spark.mp4

06:38

011 1.11 Why Spark with Scala.mp4

02:12

012 1.12 Apache spark Architecture.mp4

02:17

02 - Module 2 Introduction to Scala Programming Language

001 2.1 Introduction to Scala.mp4

10:15

001 2.1-Introduction-to-Scala.pptx

002 2.2 Scala Basic Syntax.mp4

05:11

002 2.2-Scala-Basic-Syntax.pptx

003 2.3 Scala Class and Objects.mp4

04:03

003 2.3-Scala-Class-and-Objects.pptx

004 2.4 If else Statements in Scala.mp4

08:31

004 2.4-If-else-Statements-in-Scala.pptx

005 2.5 Loops in Scala.mp4

09:33

005 2.5-Loops-in-Scala.pptx

03 - Module 3 Advanced Scala Programming

001 3.1 Functions and Procedures in Scala.mp4

08:19

001 3.1-Functions-and-Procedures-in-Scala.pptx

002 3.2 Access Modifiers.mp4

06:25

002 3.2-Access-Modifiers.pptx

003 3.3 Strings and Arrays.mp4

10:45

003 3.3-String-and-Arrays.pptx

004 3.4 Scala Collections.mp4

14:30

004 3.4-Scala-Collections.pptx

005 3.5 Scala Traits.mp4

03:58

005 3.5-Scala-Traits.pptx

006 3.6 Pattern Matching.mp4

07:25

006 3.6-Pattern-Matching.pptx

007 3.7 Scala Extractors.mp4

05:42

007 3.7-Scala-Extractors.pptx

008 3.8 Scala Exception Handling.mp4

03:29

008 3.8-Scala-Exception-Handling.pptx

009 3.9 Scala Files IO.mp4

09:26

009 3.9-Scala-Files-IO.pptx

04 - Module 4 Apache Spark RDDs

001 4.1 Programming with RDDs.mp4

02:33

002 4.2 Starting with Spark.mp4

02:16

002 4.2-Starting-with-spark.pptx

003 4.3 Creating RDDs.mp4

02:10

003 4.3-Creating-RDDs.pptx

004 4.4 RDD Operations.mp4

03:36

004 4.4-RDD-Operations.pptx

005 4.5 Lifecycle of Spark.mp4

01:41

005 4.5-Lifecycle-of-Spark.pptx

05 - Module 5 Apache Spark RDDs II

001 5.1 Spark Caching.mp4

03:12

001 5.1.Spark-caching.pptx

002 5.2 Common Transformations and Actions.mp4

06:03

002 5.2.Common-Transformations-and-Actions.pptx

003 5.3 Spark Functions.mp4

13:56

003 5.3-spark-Functions.pptx

004 5.4 Some more Spark functions.mp4

10:15

06 - Module 6 Working with Key-Value pairs

001 6.1 Key Value Pairs.mp4

05:24

001 6.1-Key-value-pairs.pptx

002 6.2 Aggregate Functions.mp4

10:55

002 6.2-Aggregate-Functions.pptx

003 6.3 Working with Aggregate Functions.mp4

20:01

004 6.3-Joins-in-Spark.pptx

004 6.4 Joins in Spark.mp4

18:44

005 6.4-Practical-on-Word-count-example.pptx

005 6.5 Practical on Word count example.mp4

07:39

07 - Module 7 Advanced Spark Programming

001 7.1 Spark Shared Variables.mp4

13:47

001 7.1-Spark-shared-variables.pptx

002 7.2 Spark and Fault Tolerance.mp4

01:53

002 7.2-Spark-and-fault-tolerance.pptx

003 7.3 Broadcast variables.mp4

11:17

003 7.3-Broadcast-variables.pptx

004 7.4 Numeric RDD Operations.mp4

03:18

004 7.4-Numeric-RDD-Operations.pptx

005 7.5 Per-Partition Operations.mp4

11:23

005 7.5-Per-Partition-Operations.pptx

08 - Module 8 Running Spark jobs on Cluster

001 8.1 Spark Runtime Architecture.mp4

02:45

001 8.1-Spark-Runtime-Architecture.pptx

002 8.2 Spark Driver.mp4

03:41

002 8.2-Spark-Driver.pptx

003 8.3 Executors.mp4

01:07

003 8.3-Executors.pptx

004 8.4 Cluster Managers.mp4

06:11

004 8.4-Cluster-Managers.pptx

005 8.5 Cluster Managers II.mp4

03:14

005 8.5-Cluster-Managers-II.pptx

09 - Module 9 Spark SQL

001 9.1 Introduction to Spark SQL.mp4

04:59

001 9.1-Introduction-to-Spark-SQL.pptx

002 9.2 Starting Point-SQL Context.mp4

07:42

002 9.2-Starting-Point-SQL-Context.pptx

003 9.3 Hive with Spark SQL.mp4

10:20

003 9.4-Hive-with-spark-SQL.pptx

004 9.4 Spark SQL Caching.mp4

10:28

004 9.5-Spark-SQL-caching.pptx

10 - Module 10 Spark Streaming

001 People.json, Employee.json.html

external-links.zip

11 - Module 11 Machine Learning in Spark

001 11.1 machine learning with mllib.mp4

06:07

002 11.2 MLib Data Types.mp4

10:07

003 11.3 labeled point data types.mp4

08:05

004 11.4 Local Matrices in mllib.mp4

06:25

005 11.5 MLib Algorithms.mp4

09:45

006 11.6 Classification and Regression.mp4

07:58

007 11.7 Clustering.mp4

12:44

12 - Module 12 GraphX in Spark

001 12.1 GraphX Introduction.mp4

08:14

002 12.2 Creating Graphs.mp4

17:04

003 12.3 Graph Operators.mp4

08:55

004 12.4 Subgraph Transformation.mp4

09:12

005 12.5 Computation with map reduce triplets.mp4

03:43

Description

A complete Guide for Processing Big Data with Spark

What You'll Learn?

Understand the limitations of Hadoop mapreduce and how Spark overcomes these limitations
Gain expertise in Scala programming language and its characteristics
Able to work with RDDs' and create applications in Spark
A thorough understanding about Spark SQL by using SQL queries in Spark

Who is this for?

Students who aspire to gain a deep understanding of Apache Spark

Professionals looking for a career in real time big data analytics

Big Data and Hadoop Developers who want to analyze data faster

More details

Description
This course on Apache Spark and Scala aims at providing an advanced expertise in big data Hadoop ecosystem. This course will provide a standard skillset which helps one become a specialist on the top of Big data Hadoop developer.Â
The course starts with a detailed description on limitations of mapreduce and how Spark can help overcome them.Â Further it covers a deeper dive into the Scala programming language.
Moving on it covers Spark as a standalone cluster and an understanding of ResiliientÂ Distributed Datasets.
The course also covers concepts of Spark SQL using SQL queries through SQL context and Hive Queries through Hive context.
This course certainly provides material required for building a career path from Big data Hadoop developer to BIg data Hadoop architect.

Who this course is for:
Students who aspire to gain a deep understanding of Apache Spark
Professionals looking for a career in real time big data analytics
Big Data and Hadoop Developers who want to analyze data faster

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