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Learn Hadoop, MapReduce and BigData from Scratch
Introduction to Big Data
Introduction to the Course (4:55)
Why Hadoop, Big Data and Map Reduce Part - A (11:55)
Why Hadoop, Big Data and Map Reduce Part - B (11:56)
Why Hadoop, Big Data and Map Reduce Part - C (12:26)
Architecture of Clusters (20:43)
Virtual Machine (VM), Provisioning a VM with vagrant and puppet (17:39)
Hadoop Architecture
Set up a single Node Hadoop pseudo cluster Part - A (13:07)
Set up a single Node Hadoop pseudo cluster Part - B (13:40)
Set up a single Node Hadoop pseudo cluster Part - c (14:31)
Clusters and Nodes, Hadoop Cluster Part - A (16:30)
Clusters and Nodes, Hadoop Cluster Part - B (15:54)
NameNode, Secondary Name Node, Data Nodes Part - A (11:55)
NameNode, Secondary Name Node, Data Nodes Part - B (11:15)
Running Multi node clusters on Amazons EMR Part - A (18:12)
Running Multi node clusters on Amazons EMR Part - B (14:59)
Running Multi node clusters on Amazons EMR Part - C (14:26)
Running Multi node clusters on Amazons EMR Part - D (13:50)
Running Multi node clusters on Amazons EMR Part - E (13:21)
Distributed file systems
Hdfs vs Gfs a comparison (20:00)
Run hadoop on Cloudera, Web Administration (18:04)
Run hadoop on Hortonworks Sandbox (19:17)
File system operations with the HDFS shell Part - A (19:57)
File system operations with the HDFS shell Part - B (17:08)
Advanced hadoop development with Apache Bigtop Part - A (11:13)
Advanced hadoop development with Apache Bigtop Part - B (11:24)
Mapreduce Version 1
MapReduce Concepts in detail Part - A (13:12)
MapReduce Concepts in detail Part - B (10:55)
Jobs definition, Job configuration, submission, execution and monitoring Part -A (9:39)
Jobs definition, Job configuration, submission, execution and monitoring Part -B (10:44)
Jobs definition, Job configuration, submission, execution and monitoring Part -C (16:48)
Hadoop Data Types, Paths, FileSystem, Splitters, Readers and Writers Part A (9:32)
Hadoop Data Types, Paths, FileSystem, Splitters, Readers and Writers Part B (10:39)
Hadoop Data Types, Paths, FileSystem, Splitters, Readers and Writers Part C (18:52)
The ETL class, Definition, Extract, Transform, and Load Part - A (15:14)
The ETL class, Definition, Extract, Transform, and Load Part - B (24:14)
The UDF class, Definition, User Defined Functions Part - A (12:18)
The UDF class, Definition, User Defined Functions Part - B (13:01)
Mapreduce with Hive ( Data warehousing )
Schema design for a Data warehouse Part - A (15:41)
Schema design for a Data warehouse Part - B (16:20)
Hive Configuration (24:10)
Hive Query Patterns Part - A (16:50)
Hive Query Patterns Part - B (17:15)
Hive Query Patterns Part - C
Hive Query Patterns Part - D (12:18)
Example Hive ETL class Part - A (12:15)
Example Hive ETL class Part - B (13:28)
Example Hive ETL class Part - D
Mapreduce with Pig (Parallel processing)
Introduction to Apache Pig Part - A (12:18)
Introduction to Apache Pig Part - B (13:45)
Introduction to Apache Pig Part - C (9:07)
Introduction to Apache Pig Part - D (10:09)
Pig LoadFunc and EvalFunc classes (13:28)
Example Pig ETL class Part - A (12:40)
Example Pig ETL class Part - B (14:11)
The Hadoop Ecosystem
Introduction to Crunch Part - A (15:20)
Introduction to Crunch Part - B (12:52)
Introduction to Arvo (15:19)
Introduction to Mahout Part - A (12:51)
Introduction to Mahout Part - B (13:05)
Introduction to Mahout Part - C (13:32)
Mapreduce Version 2
Apache Hadoop 2 and YARN Part - A (12:44)
Apache Hadoop 2 and YARN Part - B (8:23)
Yarn Examples (14:51)
Putting it all together
Amazon EMR example Part - A (12:03)
Amazon EMR example Part - B (11:46)
Amazon EMR example Part - C (8:26)
Amazon EMR example Part - D (10:18)
Apache Bigtop example Part - A (12:46)
Apache Bigtop example Part - B (13:01)
Apache Bigtop example Part - C (13:27)
Apache Bigtop example Part - D (13:54)
Apache Bigtop example Part - E (13:06)
Apache Bigtop example Part - F (13:45)
Course Summary (4:41)
References
Example Hive ETL class Part C (8:50)
Set up a single Node Hadoop pseudo cluster Part - c
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