Course Description

This training is recommended for developers who know how to create apps in analyzing Big data stored in Apache Hadoop by utilizing Hive and Pig. The topics also coves HDFS, data ingestion, Hadoop, data ingestion and workflow definition, utilizing Pig and Hive in performing data analytics stored on Big Data. The course also covers introductory course Spark SQL and Spark Core.

Prerequisites for this training

The recommended prerequisite for this course is familiarity with software development and programming principles. However, any specific knowledge of Hadoop is not required.

Who should attend this course?

This training is intended for software developers who want to gain knowledge in developing apps for Hadoop.

Schedules

Oops! For this course, there are currently no public schedules available. Clicking on "Notify Me" will allow you to express your interest.

For dates, times, and location customization of this course, get in touch with us.

You can also speak with a learning consultant by calling 800-961-0337.

What you will learn

• Describing about YARN and utilize cases for Hadoop.
• Describing about Hadoop frameworks and ecosystem tools.
• Describing Hadoop frameworks and ecosystem tools.
• Describing about HDFS architecture.
• Utilizing the Hadoop client and input data into HDFS.
• Transferring of data between Hadoopn and relation database.
• Explaining MaoReduce architectures and YARN.
• Running MapReduce job on YARN.
• Utilizing Pig to transform and explore data in HDFS.
• Understanding about Hive Tables which are implemented and defined.
• Utilizing the functionalities used in Hive Windows.
• Utilizing Hive to analyze and explore datasets.
• Utilizing and explaining about the several Hive File Formats.
• Populating and creating a Hive table that utilized ORC file supported extension.
• Utilizing Hive to execute SQL queries in performing data analysis.
• Utilizing Hive for joining data sets and utilizing widespread techniques.
• Writing effectual Hive queries.
• Performing data analytics utilizing the DataFu Pig library.
• Explaining the purposes and utilizing HCatalog.
• Scheduling and defining about Oozie workflow.
• Presenting high-level architecture and Spark ecosystem.
• Exploring DataFrame API and Spark SQL.

With Microtek Learning, you’ll receive:

• Certified Instructor-led training
• Industry Best Trainers
• Official Training Course Student Handbook
• Pre and Post assessments/evaluations
• Collaboration with classmates (not available for a self-paced course)
• Real-world knowledge activities and scenarios
• Exam scheduling support*
• Learn and earn program*
• Practice Tests
• Knowledge acquisition and exam-oriented
• Interactive online course.
• Support from an approved expert
• For Government and Private pricing*

* For more details call: +1-800-961-0337 or Email: info@microteklearning.com

Our Clients

For many years, Microtek Learning has been helping organizations, leaders, and professionals to reach their maximum performance by addressing the challenges they are facing.

• 300+ enterprise clients
• 100,000+ professionals trained
• Service 70 of the Fortune 100
• 96% of our clients would recommend us

Our Awards

REVIEWS ON OUR POPULAR COURSES

I was sceptical at first whether to enrol with Microtek Learning or not, however, I am glad that I did- I got everything that was promised (maybe more). The trainer was very patient and knowledgeable and with his effort and mine, I was able to clear the exam with ease! Keep up the good work everyone.

MARTIN

TORONTO, CANADA

• (5)

I'm really impressed with the storytelling skills of the instructor. She makes the session exciting by keeping things simple and easy to understand.

Prince N.

Texas

• (5)

I was recommended the ITIL 4 Foundation course by an IT professional who had completed the same course at Microtek Learning. The training gave me a thorough understanding of service management that I felt I could take back to my job as an IT Project Management and apply it to improve the value of products and services.

Marsh George

Texas

• (5)

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