Description

Introduction:
This training provides Big Data engineers with practical skills to integrate HBase seamlessly with Hadoop, Spark, and Hive for building scalable, high-performance data pipelines. It covers architecture, data modeling, APIs, and hands-on workflows to optimize real-time and batch processing.

Prerequisites:
Basic knowledge of Hadoop ecosystem
Familiarity with SQL and NoSQL concepts
Experience with Java or Python (preferred)

Table of Contents:
1. Understanding HBase Fundamentals
1.1 HBase architecture and components
1.2 HDFS integration and storage model
1.3 Data model: tables, column families, versions
1.4 Region servers and master operations
2. HBase Operations & Data Management
1.1 Creating, updating and scanning tables
1.2 Filters, counters, timestamps and scans
1.3 Schema design and row key strategies
1.4 Bulk data loading and MapReduce integration
3. Integrating HBase with Hadoop
3.1 HBase as a source and sink in Hadoop jobs
3.2 Using MapReduce with TableInputFormat and TableOutputFormat
3.3 HBase advanced operations in Hadoop workflows
4. Integrating HBase with Spark
4.1 Connecting Spark with HBase using Spark-HBase connector
4.2 Reading and writing HBase tables with RDDs and DataFrames
4.3 Optimizing Spark-HBase jobs
4.4 Real-time analytics using Spark Streaming + HBase
5. Integrating HBase with Hive
5.1 Hive-HBase storage handlers
5.2 Creating external Hive tables mapped to HBase
5.3 Querying HBase via HiveQL
5.4 Performance considerations for Hive + HBase
6. HBase Performance, Monitoring & Security
6.1 Tuning region splits, compactions and memory usage
6.2 Using HBase metrics and monitoring tools
6.3 Securing HBase with Kerberos, ACLs and encryption
7. Real-World Use Cases & Project Implementation
7.1 Time-series data pipelines
7.2 Log analytics and fraud detection
7.3 Building end-to-end project: Hadoop → Spark → HBase → Hive

This course equips Big Data engineers to build high-performance, scalable applications leveraging HBase with Hadoop, Spark, and Hive. By the end, participants can confidently design, integrate, and optimize HBase-based data pipelines for real-world use.