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Advanced Certification in Hadoop

Big data skills are in high demand. Now business users can profile, transform and cleanse data – on Hadoop or anywhere else it may reside – using an intuitive user interface. Why Hadoop is important: Ability to store and process huge amounts of any kind of data, quickly, Computing power, Fault tolerance, Flexibility, Low cost, and scalability.

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Why should you take Python?

In 2018, the global Big Data and business analytics market stood at US$ 169 billion and by 2022, it is predicted to grow to US$ 274 billion. Moreover, a PwC report predicts that by 2020, there will be around 2.7 million job postings in Data Science and Analytics in the US alone.

There is a huge scope of beginning a career in Big Data. Today Big data Hadoop is leading everywhere. Big data Hadoop career opportunities are on the rise and there are fewer skilled candidates available for Big data Hadoop.

Cloudrea, Hortonworks and MapR Tech are the most popular Hadoop distributions in the world. The global Hadoop market is valued at 1700 million USD in 2018 and is expected to reach 9400 million USD by the end of 2024.

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Course Syllabus

Module 2

About HDFS, Hadoop and RDBMS differentiate, HDFS Components, The NameNode, The DataNodes, DataNode Failure, HDFS Commands

Module 3

  • Examples of HDFS Commands, HDFS File Permissions, Options for Data Input, The Hadoop Client, Web HDFS, A Flume Example
  • Overview of Sqoop, The Sqoop Import Tool, Importing a Table, Importing Specific Columns, Importing from a Query, The Sqoop Export Tool, Exporting to a Table.
  • Lab: Importing RDBMS Data into HDFS
  • Lab: Exporting HDFS Data to an RDBMS

Module 4

  • Understanding MapReduce, The Key/Value Pairs of MapReduce, WordCount in MapReduce
  • Demo: Understanding MapReduce
  • Lab: Running a MapReduce Job

Module 5

  • About Pig, Pig Latin
  • The Grunt Shell
  • Demo: Understanding Pig
  • Pig Latin Relation Names
  • Pig Latin Field Names& Data Types
  • Pig Complex Types
  • Defining a Schema
  • Lab: Getting Started with Pig
  • The GROUP Operator, GROUP ALL, Relations without a Schema, The FOREACH…GENERATE Operator, Specifying Ranges in FOREACH, Field Names in FOREACH, FOREACH with Groups, The FILTER Operator, The LIMIT Operator
  • Lab: Exploring Data with Pig

Module 6

  • The ORDER BY Operator, The CASE Operator, Parameter Substitution, DISTINCT, PARALLEL, FLATTEN, Operator, Performing an Inner and outer Join, Invoking a UDF, Tips for Optimizing Pig Scripts
  • Lab: Joining Datasets
  • Preparing Data for Hive

Module 7

  • About Hive, Comparing Hive to SQL, Hive Architecture, Submitting Hive Queries, Defining a Hive-Managed Table, Defining an External Table, Defining a Table LOCATION, Loading Data into Hive, Performing Queries
  • Understanding Hive Tables, Hive Partitions, Hive Buckets, Skewed Tables, Demo: Understanding Partitions and Skew, Using Distribute By, Storing Results to a File, Specifying MapReduce Properties
  • Lab: Analyzing Big Data with Hive
  • Lab: Understanding MapReduce in Hive
  • Hive Join Strategies, Shuffle Joins, Map (Broadcast) Joins, Sort-Merge-Bucket Joins, Invoking a Hive UDF, Computing programs in Hive
    Demo: Computing programs

Module 8

  • About Hcatalog, HCatalog in the Ecosystem
  • Defining a New Schema
  • Using HCatLoader with Pig
  • Using HCatStorer with Pig, The Pig SQL Command
  • Lab: Using HCatalog with Pig

Module 9

  • Performing a Multi-Table/File Insert
  • Understanding Views, Defining Views, Using Views, The TRANSFORM Clause, The OVER Clause, Using Windows, Hive Analytics Function Lab: Advanced Hive Programming
  • Hive File Formats, Hive SerDes, Hive ORC Files, Computing Table Statistics, Hive Cost-Based Optimization (CBO), Using Hive CBO, Vectorization, Using HiveServer2, Understanding Hive on Tez, Using Tez for Hive Queries
  • Demo: Hive Optimizations
  • Hive Optimization Tips, Hive Query Tunings, Lab: Streaming Data with Hive and Python

Module 10

  • About HDFS Federation, Multiple Federated NameNodes, Multiple Namespaces
  • Overview of HDFS HA, Quorum Journal Manager, Configuring Automatic Failover
  • About YARN, Open-source YARN Use Cases
  • The Components of YARN
  • The life cycle of a YARN Application
  • A Cluster View Example

Module 11

  • Submitting a Workflow Job, Fork and Join Nodes
  • Defining an Oozie Coordinator Job
  • Schedule a Job Based on Time
  • Schedule Based on Data Availability
  • Lab: Defining an Oozie Workflow

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The constructs of this Python Language make it easier for a non-technical person to understand and grab it . Python is is definitely one of the easiest programming languages to learn. This is infact the best first language to learn. Even the learners from a non-technical background will start liking the language after a while.

Today, while Python becoming the de facto industry standard in financial analysis, e-commerce, retail business, many found the jobs required it as a core competency and charted a learning path with us while learning in classroom or online mode. Students at our institute comes from varied background and learn to not only code fluently but build solutions finding them a space in analytics companies as data analysts. Many have turned to be full-stack developers and business analysts.

Yes, All our courses at Python Training institute are available on both Weekdays as well as on Weekends mode. Infact most of our courses are available in Online mode as well.

There are usually 7-8 students in a batch.

Although you will get an Autonomous certificate from Python Training institute, and additionally students will also get a certification from Microsoft after passing out the exam successfully.

All our courses comes with Projects and Assignments at various stages of the course curriculum. You can refer the course syllabus for the same.

Yes, at Python Training institute we are pleased to offer you one Demo and Trial Class for better understanding about course flow, teaching style of trainer and to get acquainted with learning atmosphere.

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I wanted to thank everyone for helping me a lot. Before I started a course, I was not confident in myself. From the beginning of the course, they have shown great professionalism, patience, and encouragement. They helped me a lot on my first job. They showed me a great path.
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Approvi Mittal

I think the Python classes very well structured in terms of the content that was going to be taught every class. hats off to Uttam Saxena sir. He was very patient – especially since I had no experience with programming and it was my first time. Hoping to come back to learn more course was completed.
- Approvi Mittal

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I got good and sufficient knowledge from Python Training Institute in python. Also, training environment was very good.Best training institute ever.
- Manjeet Kaur
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