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Thursday, February 19, 2015

Learn Hadoop MapReduce and BigData Video Training DVD Rs 400/-




Index of Video Lessons

SECTION 1: Introduction to Big Data
1 Introduction to the Course 04:55
Introduction to the Course
2 Why Hadoop, Big Data and Map Reduce Part - A 10:44
Introduction to Big Data, Hadoop and Map Reduce
3 Why Hadoop, Big Data and Map Reduce Part - B 10:22
4 Why Hadoop, Big Data and Map Reduce Part - C 12:34
5 Architecture of Clusters 19:09
Lecture to help you understand the server cluster architecture
6 Virtual Machine (VM), Provisioning a VM with vagrant and puppet 15:54
Learn all about virtual machine provisioning

SECTION 2: Hadoop Architecture
7 Set up a single Node Hadoop pseudo cluster Part - A 11:08
Learn to setup the single node cluster
8 Set up a single Node Hadoop pseudo cluster Part - B 12:34
9 Set up a single Node Hadoop pseudo cluster Part - c 12:07
10 Clusters and Nodes, Hadoop Cluster Part - A 13:23
Learn to set up a Hadoop Cluster
11 Clusters and Nodes, Hadoop Cluster Part - B 14:15
12 NameNode, Secondary Name Node, Data Nodes Part - A 11:05 
Lecture about Node Hiearchy
13 NameNode, Secondary Name Node, Data Nodes Part - B 10:14 
14 Running Multi node clusters on Amazons EMR Part - A 10:09
Learn to use Amazon web services for running multi node cluster
15 Running Multi node clusters on Amazons EMR Part - B 14:23
16 Running Multi node clusters on Amazons EMR Part - C 15:23
17 Running Multi node clusters on Amazons EMR Part - D 09:32
18 Running Multi node clusters on Amazons EMR Part - E 14:21

SECTION 3: Distributed file systems
19 Hdfs vs Gfs a comparison - Part A 13:17
A comparison between HDFS and GFS file systems
20 Hdfs vs Gfs a comparison - Part B 06:12
21 Run hadoop on Cloudera, Web Administration 17:32
Learn to Run Hadoop on Cloudera
22 Run hadoop on Hortonworks Sandbox 19:14
Learn to run Hadoop on Hortonworks
23 File system operations with the HDFS shell Part - A 14:03
Learn to perform file system operations using HDFS Shell
24 File system operations with the HDFS shell Part - B 19:37
25 Advanced hadoop development with Apache Bigtop Part - A 13:12
Learn all about Hadoop development using Apache Bigtop
26 Advanced hadoop development with Apache Bigtop Part - B 07:10

SECTION 4: Mapreduce Version 1
27 MapReduce Concepts in detail Part - A 13:12
Learn the underlying concepts of the Map Reduce algorithm
28 MapReduce Concepts in detail Part - B 10:55
29 Jobs definition, Job configuration, submission, execution and monitoring Part -A 09:39
Learn to create Hadoop Jobs
30 Jobs definition, Job configuration, submission, execution and monitoring Part -B 10:44
31 Jobs definition, Job configuration, submission, execution and monitoring Part -C 16:48
32 Hadoop Data Types, Paths, FileSystem, Splitters, Readers and Writers Part A 09:32
Learn the basic syntax of Hadoop
33 Hadoop Data Types, Paths, FileSystem, Splitters, Readers and Writers Part B 10:39
34 Hadoop Data Types, Paths, FileSystem, Splitters, Readers and Writers Part C 18:52
35 The ETL class, Definition, Extract, Transform, and Load Part - A 15:14
Learn all about the ETL class definition, transformation and load
36 The ETL class, Definition, Extract, Transform, and Load Part - B 24:14
37 The UDF class, Definition, User Defined Functions Part - A 12:18
Learn the basics of User defined class and functions
38 The UDF class, Definition, User Defined Functions Part - B 13:01

SECTION 5: Mapreduce with Hive ( Data warehousing )
39 Schema design for a Data warehouse Part - A 13:28
Learn the schema design for data warehousing
40 Schema design for a Data warehouse Part - B 12:00
41 Hive Configuration 17:53
Introduction to Hive and its use for Data Warehousing
42 Hive Query Patterns Part - A 13:52
Learn all about Hive Query Patterns
43 Hive Query Patterns Part - B 12:54
44 Hive Query Patterns Part - C 16:42
45 Example Hive ETL class Part - A 14:02
A live example to implement Hive ETL class
46 Example Hive ETL class Part - B 11:11

SECTION 6: Mapreduce with Pig (Parallel processing)
47 Introduction to Apache Pig Part - A 12:17
Introduction to Parallel Processing using Apache Pig
48 Introduction to Apache Pig Part - B 13:45
49 Introduction to Apache Pig Part - C 09:07
50 Introduction to Apache Pig Part - D 10:09
51 Pig LoadFunc and EvalFunc classes 13:28
Advance Pig features and usage of LoadFunc and EvalFunc Class 
52 Example Pig ETL class Part - A 12:40
A working example of PIG ETL class
53 Example Pig ETL class Part - B 14:11

SECTION 7: The Hadoop Ecosystem 54
Introduction to Crunch Part - A 15:20
A brief intro to Hadoop ecosystem and detail discussion on Crunch
55 Introduction to Crunch Part - B 12:52
56 Introduction to Avro 15:18
Learn all about the Arvo hadoop component
57 Introduction to Mahout Part - A 12:51
Lecture discussing the use and implementation of Mahout
58 Introduction to Mahout Part - B 13:05
59 Introduction to Mahout Part - C 13:32

SECTION 8: Mapreduce Version 2 60
Apache Hadoop 2 and YARN Part - A 12:44
Introduction to Yarn and its usage in hadoop 2
61 Apache Hadoop 2 and YARN Part - B 08:23
62 Yarn Examples 14:51
Yarn Implementation examples for beginners.

SECTION 9: Putting it all together
63 Amazon EMR example Part - A 12:03
Implementing the concepts on Amazon web services.
64 Amazon EMR example Part - B 11:46
65 Amazon EMR example Part - C 08:26
66 Amazon EMR example Part - D 10:18
67 Apache Bigtop example Part - A 12:46
A live example implementation of Apache Bigtop
68 Apache Bigtop example Part - B 13:01
69 Apache Bigtop example Part - C 13:27
70 Apache Bigtop example Part - D 13:54
71 Apache Bigtop example Part - E 13:06
72 Apache Bigtop example Part - F 13:45
73 Course Summary 04:40



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This DVDs are only suitable for a PC/laptop/Mac; it WILL NOT play on a TV 

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