Big Data Analytics for Non-Programmers

If you like this presentation – show it...

Slide 0

Big Data Analytics for Non-Programmers

Slide 1

Agenda for the day Can Hadoop be learnt without knowing Java? How Pig can be used in place of MapReduce ? Querying data with HiveQL

Slide 2

Can Hadoop be learnt without knowing Java?

Slide 3

YES !! Hadoop can be learnt without knowing Java

Slide 4

Pig & Hive Tools like Pig and Hive that are built on top of Hadoop, offer high-level languages for working with data If you want to write MapReduce program, then you can use Pig and Pig Latin for which knowledge of Java is not required. If you want to view data in HDFS in a readable form you can use Hive which again does not require any knowledge of Java.

Slide 5

Why Pig?

Slide 6

But why Pig? Pig simplifies complex MapReduce programs by using Pig Latin Additionally, If you want to write your own MapReduce code, you can do so in any language (e.g. Perl, Python, Ruby, C, etc.) But the most attractive features of Pig are: 10 lines of PIG = 200 lines of Java Built in operations like: Join Group Filter Sort and more…

Slide 7

Why Pig? Provides common data operations filters, joins, ordering, etc. and nested data types tuples, bags, and maps missing from MapReduce. It is Open source and is actively supported by a community of developers. An ad-hoc way of creating and executing map-reduce jobs on very large data sets Can take any data Easy to learn, Easy to read and write Extensible by UDF (User Defined Functions) Java not required

Slide 8

Why Hive?

Slide 9

Why Hive? Defines SQL-Like Query Language called HiveQL

Slide 10

Features of Hive You can use HIVE to read and write files on Hadoop and run your reports from a BI tool Predictive Modeling & Hypothesis Testing Document Indexing Customer-facing Business Intelligence Log Processing Data Mining HIVE Applications

Slide 11


Slide 12

Thank You Questions/Queries/Feedback Recording and presentation will be made available to you within 24 hours