Course Code

hbasedev

Duration

21 hours (usually 3 days including breaks)

Requirements

comfortable with Java programming language
comfortable in Java programming language (navigate Linux command line, edit files with vi / nano)
A Java IDE like Eclipse or IntelliJ

Lab environment:

A working HBase cluster will be provided for students. Students would need an SSH client and a browser to access the cluster.

Zero Install : There is no need to install HBase software on students’ machines!

Overview

이 과정에서는 Hadoop 위에 SQL Store가없는 HBase를 소개합니다. 이 과정은 HBase를 사용하여 응용 프로그램을 개발할 개발자와 HBase 클러스터를 관리 할 관리자를 대상으로합니다.

우리는 HBase에서 HBase 아키텍처와 데이터 모델링 및 애플리케이션 개발을 통해 개발자를 안내 할 것입니다. 또한 HBase와 함께 MapReduce를 사용하는 방법과 성능 최적화와 관련된 몇 가지 관리 항목에 대해서도 설명합니다. 이 과정은 실습을 통해 많은 실습을 제공합니다.

소요 시간 : 3 일

대상 : 개발자 및 관리자

Machine Translated

Course Outline

Section 1: Introduction to Big Data & NoSQL
- Big Data ecosystem
- NoSQL overview
- CAP theorem
- When is NoSQL appropriate
- Columnar storage
- HBase and NoSQL
Section 2 : HBase Intro
- Concepts and Design
- Architecture (HMaster and Region Server)
- Data integrity
- HBase ecosystem
- Lab : Exploring HBase
Section 3 : HBase Data model
- Namespaces, Tables and Regions
- Rows, columns, column families, versions
- HBase Shell and Admin commands
- Lab : HBase Shell
Section 3 : Accessing HBase using Java API
- Introduction to Java API
- Read / Write path
- Time Series data
- Scans
- Map Reduce
- Filters
- Counters
- Co-processors
- Labs (multiple) : Using HBase Java API to implement time series , Map Reduce, Filters and counters.
Section 4 : HBase schema Design : Group session
- students are presented with real world use cases
- students work in groups to come up with design solutions
- discuss / critique and learn from multiple designs
- Labs : implement a scenario in HBase
Section 5 : HBase Internals
- Understanding HBase under the hood
- Memfile / HFile / WAL
- HDFS storage
- Compactions
- Splits
- Bloom Filters
- Caches
- Diagnostics
Section 6 : HBase installation and configuration
- hardware selection
- install methods
- common configurations
- Lab : installing HBase
Section 7 : HBase eco-system
- developing applications using HBase
- interacting with other Hadoop stack (MapReduce, Pig, Hive)
- frameworks around HBase
- advanced concepts (co-processors)
- Labs : writing HBase applications
Section 8 : Monitoring And Best Practices
- monitoring tools and practices
- optimizing HBase
- HBase in the cloud
- real world use cases of HBase
- Labs : checking HBase vitals