Learning Hadoop

Learn all the essentials of Hadoop, a key tool for processing and understanding big data.

Introduction

• What and why Hadoop?
• What you should know
• Use cloud services

1. Set Up Cloud Hadoop

• What is Hadoop?
• Review Hadoop distributions and cloud services
• Set up GCP Dataproc Metastore and VM cluster
• Verify GCP Dataproc VM cluster

2. Understand Hadoop Core Components

• Understand Hadoop components
• Understand Java virtual machines (JVMs)
• Explore Hadoop file systems: HDFS
• Explore Hadoop file systems: AWS S3
• Review Hadoop cluster components

3. Set Up and Verify Development Environment

• Review test jobs
• Review job output
• Verify Hadoop web interfaces in your test environment
• Verify Hadoop Spark web interfaces in your test environment
• Use the Jupyter interface for Hadoop

4. Understand MapReduce

• What is MapReduce?
• What is MapReduce word count?
• Review MapReduce word count job
• Prepare for MapReduce Java coding
• Review MapReduce WordCount job code

5. Tune MapReduce

• Tune by physical methods
• Tune a Mapper
• Understanding data types
• Tune a Reducer
• Use MR 2.0 and 3.0
• Review MR optimization examples

6. Scale Cloud Hadoop

• Migrate to Cloud Hadoop
• Scale VM-based Clusters
• Use autoscale policies
• Scale Kubernetes Spark clusters

7. Use Hive, Pig, and Spark

• Understand Hive and HBase
• Create and query tables with Hive
• Understand Pig
• Run WordCount using Pig
• Review Spark architecture
• Scale a Spark job to calculate Pi

Conclusion

• Learn more about using Hadoop