From 0 to 1: Hive for Processing Big Data

Learn all about end-to-end Hive including UDFs, Windowing, Optimization HQL, Partitioning, Bucketing Map Joins, & Indexes

 Enrolling into this course will give you hands-on expertise in:

• Writing complicated analytical queries on data in Hive & uncover insights
• Generating and implementing ideas of partitioning, bucketing in order to optimize queries in Hive
• Customizing hive with user defined functions in Java and Python
• Understanding what goes on under the hood of Hive with HDFS and Map Reduce

Some basic requirements for enrollment in this course are:-

• SQL Knowledge
• Java concept clarity

Hive can be considered as the new face of SQL and this course will prove to be the best possible practical guide in using Hive for Big Data Processing. Hive will be highly helpful in leveraging the power of distributed computing and Hadoop for analytical processing.

This course covers the following topics:-

• Analytical processing including Joins, Sub-queries, Views, Table Generating Functions, Explode, Lateral View, Windowing and more
• Hive Tuning including Partitioning, Bucketing, Join Optimizations, Map Side Joins, Indexes, Writing custom User Defined functions in Java. UDF, UDAF, Generic UDF, Generic UDTF,  Custom functions in Python,  Implementation of MapReduce for Select, Group by and Join

Some exceptional benefits associated with this course enrollment are:

• Quality course material
• Instant & free course updates
• Access to all Questions & Answers initiated by other students as well
• Personalized support from the instructor’s end on any issue related to the course
• Few free lectures for a quick overview

This course has 87 videos in total and will take you through all of these in maximum 16 hours. You can watch the videos at your own pace and accordingly can raise doubts or questions if you get stuck. The course is apt for Analysts and Engineers who look forward to manage Hive for data warehousing solution

 Grab the opportunity and enroll today!