Advanced Hadoop for Developers

• comfortable with Java programming language (most programming exercises are in java)
• comfortable in Linux environment (be able to navigate Linux command line, edit files using vi / nano)
• a working  knowledge of Hadoop.

Lab environment

Zero Install: There is no need to install hadoop software on students’ machines! A working hadoop cluster will be provided for students.

Students will need the following

• an SSH client (Linux and Mac already have ssh clients, for Windows Putty is recommended)
• a browser to access the cluster. We recommend Firefox browser

Apache Hadoop is one of the most popular frameworks for processing Big Data on clusters of servers. This course delves into data management in HDFS, advanced Pig, Hive, and HBase.  These advanced programming techniques will be beneficial to experienced Hadoop developers.

Audience: developers

Duration: three days

Format: lectures (50%) and hands-on labs (50%).

Section 1: Data Management in HDFS

• Various Data Formats (JSON / Avro / Parquet)
• Compression Schemes
• Data Masking
• Labs : Analyzing different data formats;  enabling compression

Section 2: Advanced Pig

• User-defined Functions
• Introduction to Pig Libraries (ElephantBird / Data-Fu)
• Loading Complex Structured Data using Pig
• Pig Tuning
• Labs : advanced pig scripting, parsing complex data types

Section 3 : Advanced Hive

• User-defined Functions
• Compressed Tables
• Hive Performance Tuning
• Labs : creating compressed tables, evaluating table formats and configuration

Section 4 : Advanced HBase

• Advanced Schema Modelling
• Compression
• Bulk Data Ingest
• Wide-table / Tall-table comparison
• HBase and Pig
• HBase and Hive
• HBase Performance Tuning
• Labs : tuning HBase; accessing HBase data from Pig & Hive; Using Phoenix for data modeling