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Description
Pig Course
There is data explosion all around us and intelligent businesses know that this data needs to be leveraged to ensure business continuity. Apache Pig was developed to run queries on large data sets that are stored in HDFS and run on Hadoop. Apache Pig is known for its simplistic syntax and ability to decrease development time and hence is widely used by organizations that analyse Big Data.
KnowledgeHut academy brings you a comprehensive Hadoop Pig training workshop. This Pig Training will introduce you to the world of Hadoop and MapReduce. You will learn through a series of practical, hands on exercises on writing complex MapReduce transformations, about HDFSand writing scripts using the advanced features of Pig. You will execute Pig programs and learn their real world uses. By the end of the course, you will have in-depth knowledge of the pig concepts from basics to advanced. Pig certified professionals are really in high demand in industries handling large amount of data. So, register today and get certified from our institute at reasonable cost.
Here’s what you will learn!
- How Big data can change the way businesses operate
- The Hadoop ecosystem and its architecture
- To analyse large data sets using Pig Latins scripts and parallel processing using MapReduce
Is this coaching boosts your career?
This Pig training course will benefit professionals who work with Big Data or students who want to get into the field of data analytics. A typical audience mix would be:
- Analytics Professionals
- BI /ETL/DW Professionals
- Project Managers
- Testing Professionals
- Mainframe Professionals
- Software Developers and Architects
- Graduates aiming to build a career in Big Data and Hadoop
Prerequisites:
There are no prerequisites for this course.
Key Features
Curriculum
- Hadoop overview
- Surveying the Hadoop components
- Defining the Hadoop architecture
Storing data in HDFS
- Achieving reliable and secure storage
- Monitoring storage metrics
- Controlling HDFS from the Command Line
Parallel processing with MapReduce
- Detailing the MapReduce approach
- Transferring algorithms not data
- Dissecting the key stages of a MapReduce job
Automating data transfer
- Facilitating data Ingress and Egress
- Aggregating data with Flume
- Configuring data fan in and fan out
- Moving relational data with Sqoop
Describing characteristics of Apache Pig
- Contrasting Pig with MapReduce
- Identifying Pig use cases
- Pinpointing key Pig configurations
- Pig Latin: Relational Operators
- File Loaders
- Group Operator
- CO GROUP Operator
- Joins and CO GROUP
- Union, Diagnostic Operators
- Pig UDF
Structuring unstructured data
- Representing data in Pig's data model
- Running Pig Latin commands at the Grunt Shell
- Expressing transformations in Pig Latin Syntax
- Invoking Load and Store functions
Transforming data with Relational Operators
- Creating new relations with joins
- Reducing data size by sampling
- Extending Pig with user–defined functions
Filtering data with Pig
- Consolidating data sets with unions
- Partitioning data sets with splits
- Injecting parameters into Pig scripts
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Network Administrator.Frequently Asked Questions
Pig is a high level extensible language that was designed to analyse large unstructured data sets. Its ability to reduce the complexity of MapReduce jobs has made it highly preferred for big data analysis. KnowledgeHut’s Pig course is the perfect opportunity for aspiring data analyst professionals to understand about data analysis and learn Pig Latin script. The Pig training course is conducted by experienced professionals who have years of industry experience. The modules have demo and practice sessions, comprehensive courseware and lectures that have been carefully formulated for maximum learning. Enrol today and get the KnowledgeHut advantage!
- Understand why and when Pig is used and its advantages
- Learn to perform Big Data Analytics with Pig
- Make sense unstructured data without writing complex Java script
- Provide meaningful data insights for business
- Filter data with Extract–Transform–Load (ETL) operations using Pig
- Use Pig and Pig Latin to query multiple datasets
KnowledgeHut brings you online mentor driven courses that not only help professionals gain theoretical expertise but also the practical experience in a wide variety of courses including courses on Big Data such as Hadoop Administration and Apache Spark and Scala, which are very popular. The fact that our workshops are mentor driven gives us an edge over other training institutes since you can learn from industry experts about the application and challenges of upcoming technologies. We have so far trained thousands of professionals with the skills needed to land lucrative jobs and you could be next!
You will receive Apache Pig certification in the form of a course completion certificate.
Towards the end of the course, all participants will be required to work on a project to get hands on familiarity with the concepts learnt. You will write your own Pig Latin code and implement it with support from your mentors. This project, which can also be a live industry project, will be reviewed by our instructors and industry experts. On successful completion, you will be awarded a certification.
Classes are held on weekdays and weekends. You can check available schedules and choose the batch timings which are convenient for you.
You may be required to put in 10 to 12 hours of effort every week, including the live class, self study and assignments.
Your classes will be held online. All you need is a windows computer with good internet connection to attend your classes online. A headset with microphone is recommended.
You may also attend these classes from your smart phone or tablet.
Don’t worry, you can always access your class recording or opt to attend the missed session again in any other live batch.
This course will benefit professionals who work with Big Data or students who want to get into the field of data analytics such as analytics professionals, BI /ETL/DW Professionals, Project Managers, Testing Professionals, Mainframe Professionals, Software Developers and Architects and graduates aiming to build a career in Big Data and Hadoop.
- Operating system such as Mac OS X, Windows or Linux
- 4 GB RAM
- Dual Core CPU
Classes are held on weekdays and weekends. You can check available schedules and choose the batch timings which are convenient for you.