Big Data Analytics for Non Programmers

Big Data Analytics for Non Programmers

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  wwww.edureka.co/big-data-and-hadoop Big Data Analyticsfor Non-Programmers
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  wwww.edureka.co/big-data-and-hadoop Agenda for theday  Can Hadoop be learnt without knowing Java?  How Pig can be used in place of MapReduce ?  Querying data with HiveQL
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  wwww.edureka.co/big-data-and-hadoop Can Hadoop belearnt without knowing Java?
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  wwww.edureka.co/big-data-and-hadoop YES !! Hadoop canbe learnt without knowing Java
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  wwww.edureka.co/big-data-and-hadoop Pig & Hive Toolslike 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.
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  wwww.edureka.co/big-data-and-hadoop Why Pig?
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  wwww.edureka.co/big-data-and-hadoop But why Pig? Pigsimplifies 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…
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  wwww.edureka.co/big-data-and-hadoop Why Pig? Provides commondata 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. Structured data Semi-Structured data Unstructured data Similar to SQL Reads like a series of steps Java Python JavaScript Ruby 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
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  wwww.edureka.co/big-data-and-hadoop Why Hive?
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  wwww.edureka.co/big-data-and-hadoop Why Hive? Defines SQL-Like Query Language called HiveQL Data Warehouse Infrastructure Allows programmers to plug-incustom mappers and reducers Provides tools to enable easy ETL
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  wwww.edureka.co/big-data-and-hadoop Features of Hive Youcan 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
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  wwww.edureka.co/big-data-and-hadoop Demo
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  wwww.edureka.co/big-data-and-hadoop Thank You Questions/Queries/Feedback Recording andpresentation will be made available to you within 24 hours