This course is designed for developers who need to create applications to analyze Big Data stored in Apache Hadoop using Pig and Hive. Topics include: Hadoop, YARN, HDFS, MapReduce, data ingestion, workflow definition, using Pig and Hive to perform data analytics on Big Data and an introduction to Spark Core and Spark SQL.
Target Audience
Software developers who need to understand and develop applications for Hadoop.
Prerequisites:
Students should be familiar with programming principles and have experience in software development. SQL knowledge is also helpful. No prior Hadoop knowledge is required.
Course Objectives- Describe Hadoop, YARN and use cases for Hadoop
- Describe Hadoop ecosystem tools and frameworks
- Describe the HDFS architecture
- Use the Hadoop client to input data into HDFS
- Transfer data between Hadoop and a relational database
- Explain YARN and MaoReduce architectures
- Run a MapReduce job on YARN
- Use Pig to explore and transform data in HDFS
- Understand how Hive tables are defined and implemented
- Use Hive to explore and analyze data sets
- Use the new Hive windowing functions
- Explain and use the various Hive file formats
- Create and populate a Hive table that uses ORC file formats
- Use Hive to run SQL-like queries to perform data analysis
- Use Hive to join datasets using a variety of techniques
- Write efficient Hive queries
- Create ngrams and context ngrams using Hive
- Perform data analytics using the DataFu Pig library
- Explain the uses and purpose of HCatalog
- Use HCatalog with Pig and Hive
- Define and schedule an Oozie workflow
- Present the Spark ecosystem and high-level architecture
- Perform data analysis with Spark's Resilient
- Distributed Dataset API-Explore Spark SQL and the DataFrame API
Format
50% Lecture/Discussion
50% Hands-on Labs
School Notes:
Important:
All Sunset Learning Institute classes are taught in an instructor-led, live virtual environment. This price includes a facility fee of $300 (except Reston,VA or Denver, CO) to allow you to take it in a classroom-type environment. If you prefer to take the class from home, the $300 fee will be waived and refunded.