[Last updated 11/2023] The Ultimate Hands-On Hadoop: Tame your Big Data! (Udemy – Vietsub and Engsub)

About Course

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What you’ll learn:
Design distributed systems that manage “big data” using Hadoop and related data engineering technologies.
Use HDFS and MapReduce for storing and analyzing data at scale.
Use Pig and Spark to create scripts to process data on a Hadoop cluster in more complex ways.
Analyze relational data using Hive and MySQL
Analyze non-relational data using HBase, Cassandra, and MongoDB
Query data interactively with Drill, Phoenix, and Presto
Choose an appropriate data storage technology for your application
Understand how Hadoop clusters are managed by YARN, Tez, Mesos, Zookeeper, Zeppelin, Hue, and Oozie.
Publish data to your Hadoop cluster using Kafka, Sqoop, and Flume
Consume streaming data using Spark Streaming, Flink, and Storm

Link gốc:
https://www.udemy.com/course/the-ultimate-hands-on-hadoop-tame-your-big-data/

Time Course:
14.5 hours (105 Lectures + Documents)

Instructor
: Frank Kane
Total Weight:
6.75 GB
** Note
:

Chú ý:

Course Content

01 – Learn all the buzzwords! And install the Hortonworks Data Platform Sandbox

001 Udemy 101 Getting the Most From This Course.mp4

02:10
002 Tips for Using This Course.mp4

01:09
005 Installing Hadoop [Step by Step].mp4

17:44
006 The Hortonworks and Cloudera Merger, and how it affects this course.mp4

03:01
007 Hadoop Overview and History.mp4

07:44
008 Overview of the Hadoop Ecosystem.mp4

16:46

02 – Using Hadoop’s Core HDFS and MapReduce

001 HDFS What it is, and how it works.mp4

13:53
003 Installing the MovieLens Dataset.mp4

06:20
004 [Activity] Install the MovieLens dataset into HDFS using the command line.mp4

07:50
005 MapReduce What it is, and how it works.mp4

10:40
006 How MapReduce distributes processing.mp4

12:57
007 MapReduce example Break down movie ratings by rating score.mp4

11:35
009 [Activity] Installing Python, MRJob, and nano.mp4

13:19
010 [Activity] Code up the ratings histogram MapReduce job and run it.mp4

07:36
011 [Exercise] Rank movies by their popularity.mp4

07:06
013 [Activity] Check your results against mine!.mp4

08:23

03 – Programming Hadoop with Pig

04 – Programming Hadoop with Spark

001 Why Spark.mp4

10:06
002 The Resilient Distributed Dataset (RDD).mp4

10:14
003 [Activity] Find the movie with the lowest average rating – with RDD’s.mp4

15:33
004 Datasets and Spark 2.0.mp4

06:28
005 [Activity] Find the movie with the lowest average rating – with DataFrames.mp4

10:00
006 [Activity] Movie recommendations with MLLib.mp4

12:43
007 [Exercise] Filter the lowest-rated movies by number of ratings.mp4

02:51
008 [Activity] Check your results against mine!.mp4

06:40

05 – Using relational data stores with Hadoop

001 What is Hive.mp4

06:31
002 [Activity] Use Hive to find the most popular movie.mp4

10:45
003 How Hive works.mp4

09:10
004 [Exercise] Use Hive to find the movie with the highest average rating.mp4

01:55
005 Compare your solution to mine.mp4

04:10
006 Integrating MySQL with Hadoop.mp4

08:00
008 [Activity] Install MySQL and import our movie data.mp4

07:45
009 [Activity] Use Sqoop to import data from MySQL to HFDSHive.mp4

07:01
010 [Activity] Use Sqoop to export data from Hadoop to MySQL.mp4

07:16

06 – Using non-relational data stores with Hadoop

001 Why NoSQL.mp4

13:54
002 What is HBase.mp4

12:55
003 [Activity] Import movie ratings into HBase.mp4

13:28
004 [Activity] Use HBase with Pig to import data at scale.mp4

11:19
005 Cassandra overview.mp4

14:50
007 [Activity] Installing Cassandra.mp4

10:53
008 [Activity] Write Spark output into Cassandra.mp4

11:00
009 MongoDB overview.mp4

17:19
010 [Activity] Install MongoDB, and integrate Spark with MongoDB.mp4

12:44
011 [Activity] Using the MongoDB shell.mp4

07:48
012 Choosing a database technology.mp4

15:59
013 [Exercise] Choose a database for a given problem.mp4

05:00

07 – Querying your Data Interactively

001 Overview of Drill.mp4

07:55
002 [Activity] Setting up Drill.mp4

10:58
003 [Activity] Querying across multiple databases with Drill.mp4

07:07
004 Overview of Phoenix.mp4

08:55
005 [Activity] Install Phoenix and query HBase with it.mp4

07:02
006 [Activity] Integrate Phoenix with Pig.mp4

11:45
007 Overview of Presto.mp4

06:39
008 [Activity] Install Presto, and query Hive with it.mp4

12:26
009 [Activity] Query both Cassandra and Hive using Presto.mp4

09:01

08 – Managing your Cluster

001 YARN explained.mp4

10:01
002 Tez explained.mp4

04:56
003 [Activity] Use Hive on Tez and measure the performance benefit.mp4

08:35
004 Mesos explained.mp4

07:13
005 ZooKeeper explained.mp4

13:10
006 [Activity] Simulating a failing master with ZooKeeper.mp4

06:47
007 Oozie explained.mp4

11:56
008 [Activity] Set up a simple Oozie workflow.mp4

16:54
009 Zeppelin overview.mp4

05:01
010 [Activity] Use Zeppelin to analyze movie ratings, part 1.mp4

12:27
011 [Activity] Use Zeppelin to analyze movie ratings, part 2.mp4

09:46
012 Hue overview.mp4

08:07
013 Other technologies worth mentioning.mp4

04:35

09 – Feeding Data to your Cluster

10 – Analyzing Streams of Data

11 – Designing Real-World Systems

12 – Learning More

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About Course

Course Content

01 – Learn all the buzzwords! And install the Hortonworks Data Platform Sandbox

001 Udemy 101 Getting the Most From This Course.mp4

002 Tips for Using This Course.mp4

005 Installing Hadoop [Step by Step].mp4

006 The Hortonworks and Cloudera Merger, and how it affects this course.mp4

007 Hadoop Overview and History.mp4

008 Overview of the Hadoop Ecosystem.mp4

02 – Using Hadoop’s Core HDFS and MapReduce

001 HDFS What it is, and how it works.mp4

003 Installing the MovieLens Dataset.mp4

004 [Activity] Install the MovieLens dataset into HDFS using the command line.mp4

005 MapReduce What it is, and how it works.mp4

006 How MapReduce distributes processing.mp4

007 MapReduce example Break down movie ratings by rating score.mp4

009 [Activity] Installing Python, MRJob, and nano.mp4

010 [Activity] Code up the ratings histogram MapReduce job and run it.mp4

011 [Exercise] Rank movies by their popularity.mp4

013 [Activity] Check your results against mine!.mp4

03 – Programming Hadoop with Pig

001 Introducing Ambari.mp4

002 Introducing Pig.mp4

003 Example Find the oldest movie with a 5-star rating using Pig.mp4

004 [Activity] Find old 5-star movies with Pig.mp4

005 More Pig Latin.mp4

006 [Exercise] Find the most-rated one-star movie.mp4

007 Pig Challenge Compare Your Results to Mine!.mp4

04 – Programming Hadoop with Spark

001 Why Spark.mp4

002 The Resilient Distributed Dataset (RDD).mp4

003 [Activity] Find the movie with the lowest average rating – with RDD’s.mp4

004 Datasets and Spark 2.0.mp4

005 [Activity] Find the movie with the lowest average rating – with DataFrames.mp4

006 [Activity] Movie recommendations with MLLib.mp4

007 [Exercise] Filter the lowest-rated movies by number of ratings.mp4

008 [Activity] Check your results against mine!.mp4

05 – Using relational data stores with Hadoop

001 What is Hive.mp4

002 [Activity] Use Hive to find the most popular movie.mp4

003 How Hive works.mp4

004 [Exercise] Use Hive to find the movie with the highest average rating.mp4

005 Compare your solution to mine.mp4

006 Integrating MySQL with Hadoop.mp4

008 [Activity] Install MySQL and import our movie data.mp4

009 [Activity] Use Sqoop to import data from MySQL to HFDSHive.mp4

010 [Activity] Use Sqoop to export data from Hadoop to MySQL.mp4

06 – Using non-relational data stores with Hadoop

001 Why NoSQL.mp4

002 What is HBase.mp4

003 [Activity] Import movie ratings into HBase.mp4

004 [Activity] Use HBase with Pig to import data at scale.mp4

005 Cassandra overview.mp4

007 [Activity] Installing Cassandra.mp4

008 [Activity] Write Spark output into Cassandra.mp4

009 MongoDB overview.mp4

010 [Activity] Install MongoDB, and integrate Spark with MongoDB.mp4

011 [Activity] Using the MongoDB shell.mp4

012 Choosing a database technology.mp4

013 [Exercise] Choose a database for a given problem.mp4

07 – Querying your Data Interactively

001 Overview of Drill.mp4

002 [Activity] Setting up Drill.mp4

003 [Activity] Querying across multiple databases with Drill.mp4

004 Overview of Phoenix.mp4

005 [Activity] Install Phoenix and query HBase with it.mp4

006 [Activity] Integrate Phoenix with Pig.mp4

007 Overview of Presto.mp4

008 [Activity] Install Presto, and query Hive with it.mp4

009 [Activity] Query both Cassandra and Hive using Presto.mp4

08 – Managing your Cluster

001 YARN explained.mp4

002 Tez explained.mp4

003 [Activity] Use Hive on Tez and measure the performance benefit.mp4

004 Mesos explained.mp4

005 ZooKeeper explained.mp4

006 [Activity] Simulating a failing master with ZooKeeper.mp4

007 Oozie explained.mp4

008 [Activity] Set up a simple Oozie workflow.mp4

009 Zeppelin overview.mp4