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What you'll learn?
- In late 1990s, Developers and Programmers were generating data through coding, in late 2000s everyone on Social media generating data on FB, Twitter, Insta etc and these days Machines are generating data which overall creating a Huge Volume of data which cannot be handled easily through traditional databases, so after completion of this course you'll be able to do that using HADOOP as your platform and also Able to crack Cloudera CCA 175 Certification
Course Overview
This is an interactive lecture of one of my Big data and Hadoop class where everything is covered from the scratch and also you will see students asking doubts so you can clear those concepts here as well.
Students will be Able to crack Cloudera CCA 175 Certification after successful completion and with little practice.
Tools covered :
1. Sqoop
2. Flume
3. MapReduce
4. Hive
5. Impala
6. Beeline
7. Apache Pig
8. HBase
9. OOZIE
10. Project on a real data set.
Pre-requisites
- A Laptop, 6 GB RAM (at least), 100 GB FREE HDD
Target Audience
- Students who want to step into Big Data, want to know how to Analyse, work on and manage it.
Curriculum 26 Lectures 00:01:29
-
Section 1 : All about BIG DATA
- Lecture 2 :
- Hadoop framework
- Lecture 3 :
- Hadoop Ecosystem
- Lecture 4 :
- HDFS
- Lecture 5 :
- Magic Boxes, Sqoop and Flume
- Lecture 6 :
- NameNode, DataNode, JournalNode
- Lecture 7 :
- Input output operations, Ram and HDD, pros and cons
- Lecture 8 :
- Mapreduce Theory 1.1
- Lecture 9 :
- Mapreduce Theory 1.2
- Lecture 10 :
- Mapreduce Theory 1.3
- Lecture 11 :
- Combiner Approach in MapReduce
- Lecture 12 :
- Coding : Sqoop with SQL
- Lecture 13 :
- Visit to Cloudera Machine
- Lecture 14 :
- Sqoop commands with introduction to Linux commands as well
- Lecture 15 :
- Sqoop commands
- Lecture 16 :
- Basics of core Java, introduction to eclipse, MapReduce Coding
- Lecture 17 :
- Coding : MapReduce
- Lecture 18 :
- Hive Theory
- Lecture 19 :
- Hive: connecting, loading, defining delimiters
- Lecture 20 :
- Coding : Hive
- Lecture 21 :
- Hive to Impala and Beeline
- Lecture 22 :
- Hive : Partitioning
- Lecture 23 :
- Hive Bucketing
- Lecture 24 :
- YARN, HBASE, OOZIE
- Lecture 25 :
- FINAL PROJECT ON REAL DATA SET
- Lecture 26 :
- Assignment on DataNodes
Our learners work at
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Instructor
256144 Course Views
6 Courses
Hello guys, How are you all doing? So a quick introduction of me, well I am a Big Data Expert and Data Scientist, I have 3 years of experience on these domain in companies as well as a trainer.
My teaching method is completely different than others like I am not a slide reader, I use analogies and examples a lot to explain things and mostly try to be practical which you'll see in the course.
Hope to see you all in the lectures, Good Luck!
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