Apache HBase Training

Course Modules

• Introduction to Apache HBase

  • Overview of HBase and its role in the Hadoop ecosystem
  • Key features and advantages of using HBase for big data applications
  • Understanding HBase architecture and design principles

• Setting Up and Configuring HBase

  • Installation and configuration of HBase on a Hadoop cluster
  • HBase vs. HDFS: Key differences and when to use each
  • Configuring HBase for performance, scalability, and fault tolerance

• HBase Data Model and Storage

  • Understanding HBase data model (tables, rows, columns, and cells)
  • Managing schema design and using HBase’s key-value store model
  • Designing efficient HBase tables for high-performance queries

• CRUD Operations in HBase

  • Performing Create, Read, Update, Delete (CRUD) operations using HBase APIs
  • Inserting and retrieving data using Java API and shell commands
  • Optimizing data write and read operations for speed and scalability

• Advanced HBase Concepts

  • Working with HBase filters and scans to enhance query capabilities
  • Implementing HBase counters for efficient data aggregation
  • HBase column families, versioning, and managing data consistency

• Integrating HBase with Hadoop Ecosystem

  • Integrating HBase with Apache Hive, Apache Pig, and Apache Spark
  • Using HBase as a storage backend for other big data applications
  • Configuring data pipelines for batch and real-time processing

• HBase Performance Tuning and Optimization

  • Best practices for optimizing HBase performance
  • Tuning HBase regions, memstore, and write-ahead logs (WAL)
  • Monitoring HBase clusters and managing large-scale data sets

• HBase Security and Management

  • Implementing security features (authentication, authorization, and encryption)
  • Managing HBase backups and data recovery
  • Monitoring and troubleshooting common issues in HBase clusters