About Professional Hadoop Development
Takes a participant from no knowledge of Hadoop to being able to develop with Hadoop professionally. It covers the main technologies of Hadoop: HDFS and MapReduce. There is an in-depth coverage of essential Big Data and Hadoop ecosystem technologies. The class ends with a consideration of how to architect Big Data solutions with Hadoop and its ecosystem.
Duration: 4 days
Intended Audience: Technical, Software Engineers, QA, Analysts
Prerequisites: Intermediate-Level Java
You Will Learn
- What exists in the Big Data ecosystem so you can use the right tool for the right job.
- An understanding of how HDFS works and how to interact with it.
- An understanding of how MapReduce works and how each phase works.
- The basics of coding a MapReduce job with Java to build your Big Data foundation.
- What the advanced features of the MapReduce API that only the true experts know.
- How Apache Crunch gives you a very different API from MapReduce and gives you a more Java-centric API.
- How to use Apache Crunch to do the things not humanly possible in MapReduce like joining datasets and performing secondary sorts.
- The simple and advanced SQL-like commands available in Hive.
- How to extend Hive commands with custom non-Java code to do company or use case specific queries.
- How to move data out of and into relational databases like MySQL and Oracle from Hadoop/Spark using Apache Sqoop.
- How to move files and network data from many different computers to Hadoop using Apache Flume.
- What is Hue and how it aids in creating browser-based data products.
- How Apache Oozie makes it possible to create repeatable workflows that enterprises need.
- How all of these technologies come together as a solution for ETL, click stream, and sessionization use cases.
- The steps and iterations to take when creating a Big Data solution.
Professional Hadoop Development
Thinking in Big Data
Introducing Big Data
What is Hadoop?
Introduction to HDFS
Introduction to MapReduce
Coding with MapReduce
Using Apache Maven
Advanced MapReduce Classes
MapReduce and Avro
Coding With Crunch
Crunch API Pipelines
Augmenting Hive With UDFs and Transforms
Moving and Accessing Data
Hue and Oozie
- Apache Hadoop
- Apache Spark
- Apache Hive
- Apache Pig
- Apache HBase
- Apache Impala
- Apache Kafka
- Apache Crunch
- Apache Oozie