1 Who should attend?
- Those who interested in cloud computing, distributed data storage and processing, big data
- Managers who are in charge of traditional database, such as Oracle, MaySQL, DB2 etc.
- Developers forany programming language, for example: Java, C etc.
- Server-side developer site
- Cloud computing / Big data practitioners;
- Familiar with Hadoop ecosystem, and want to learn Hadoop and Spark integration in enterprise application
- System architect, system analyst, senior programmer, senior developer
- Director who engaged in processingcenter operation, planning .designing of big data,
- Head ofwork unit-large data sources, such as Government , financial insurance, mobile and Internet company
- Project manager involved in big data and distributed data processing inColleges and research institutes
- Data modeling manager, analysis and developers, system manager, database manager and others who interested in data warehouse;
- 对云计算、分布式数据存储于处理、大数据等感兴趣的朋友
- 传统的数据库，例如Oracle、MaySQL、DB2等的管理人员
- Java、C等任意一门编程语言的开发者；
- 网站服务器端的开发人员
- 在校大学生、中专生或者刚毕业的学生
- 云计算大数据从业者；
- 熟悉Hadoop生态系统，想了解和学习Hadoop与Spark整合在企业应用实战案例的朋友；
- 系统架构师、系统分析师、高级程序员、资深开发人员；
- 牵涉到大数据处理的数据中心运行、规划、设计负责人；
- 政府机关，金融保险、移动和互联网等大数据来源单位的负责人；
- 高校、科研院所涉及到大数据与分布式数据处理的项目负责人；
- 数据仓库管理人员、建模人员，分析和开发人员、系统管理人员、数据库管理人员以及对数据仓库感兴趣的其他人员；
2 Training Objectives
- Comprehend basic technology and thinking model of big data
- Experience of marketing change driven by bigdata and actual cases sharing
- Sensebig data value from the situation of new companies such as e-commerce company
- Realize technical capabilitiesrepresented by Hadoop
- 了解大数据时代的基础技术和思维
- 体会大数据驱动下的营销变革与实战分享
- 能从电子商务等新型企业的大数据应用情况和案例中理解大数据价值，分享大数据应用案例，培养听众对大数据挖掘与分析的认识
- 掌握以Hadoop为代表的大数据平台实现技术能力。
3 Training Content
Topic 1: Big data ecosystem and case shares
- Concept of Big data (What is big data’s thinking model and value?Hot spots, developmentand prospect of Big Data)
- Relation between Big data and cloud computing (Application and fieldof big data and cloud computing)
- Technology overview ofBig data ( Technology classification; The mainstream of big data technology)
- Domestic and overseas application status of Big data and development direction
第1个主题：大数据生态圈和案例介绍
- 认识大数据（大数据时代的思维，价值体现是什么，大数据应用的热点、发展、展望）
- 大数据与云计算（大数据与云计算的关系是什么，大数据云计算的应用和领域）
- 大数据技术概述（大数据技术的分类有哪些，大数据的主流技术有哪些）
- 国外、国内大数据应用情况现状以及发展方向（其他行业大数据案例分享，国内大型互联网公司案例分享）
Topic 2: Hadoop 3Qs (Thoroughly comprehend Hadoop)
- WhyHadoop isthe standard software framework in cloud computing
- How does Hadoop specifically work?
- What isHadoop system and what is the function of eachmodule?
第2个主题：Hadoop三问（彻底理解Hadoop）
- Hadoop为什么是云计算分布式大数据的事实开源标准软件框架？
- Hadoop的具体是如何工作？
- Hadoop的生态架构和每个模块具体的功能是什么？
Topic 3: Thoroughly master HDFS
- Analysis HDFS
- Best practicesof title node
- The principle of the Block division and the specific storage of data node
第3个主题：彻底掌握HDFS(深入理解HDFS)
- HDFS体系架构剖析
- 名称节点、数据节点、辅助名称节点架构
- 名称节点的高可靠性最佳实践
- 数据节点中Block划分的原理和具体存储方式
Topic 4: Comprehend MapReduce
- Classic steps to perform MapReduce
- Analysis Operation process of Wordcount
- Analysis differences between Mapper and Reducer
第4个主题：彻底掌握MapReduce（剖析MapReduce执行）
- MapReduce执行的经典步骤
- wordcount运行过程解析
- Mapper和Reducer剖析
Topic 5: YARN
- Design idea of YARN
- Core element of YARN
- Total set process of YARN
- Application Program Compile
第5个主题：YARN（理解和使用YARN）
- YARN的设计思想
- YARN的核心组件
- YARN的共组过程
- YARN应用程序编写
Topic 6: Grasp the realization of the Hive data warehouse queries
- Data platformframework based on Hadoop
- Hive's application environment
- The role and principleof the Hive
- Cases and demonstrate
- Deployment and installation of Hive
- Parameter optimization of Hive
- Hive Actual Operation
- Cooperative relationship between Hadoop warehouse and traditional data warehouse
第6个主题：深入理解Hive(掌握Hive数据仓库的实现查询)
- 了解基于Hadoop的数据平台架构
- 了解Hive的应用环境
- 了解Hive的作用及原理
- 案例和演示
- Hive部署及安装
- Hive的参数优化
- Hive命令实际操作
- Hadoop仓库和传统数据仓库的协作关系
Topic 7: Master the principle and application scenario of HBase data warehouse
- HBase Introduction and framework
- Core element of HBase
- Advanced Application HBase
- HBase Installation and deployment, Start
- Case Studies
- Contrast of NoSQL database and relational database
- NoSQL Based on the list of clusters
- Basic Concept OF HBase
- HBaselogical structure Introduction
- Compare HBasewith NoSQL
第7个主题：深入理解 HBase(掌握 HBase数据仓库的原理及应用场景)
- HBase简介和架构
- HBase核心知识点
- HBase高级应用
- HBase安装、部署、启动
- 案例和演示
- NoSQL数据库与关系数据库的对比
- 基于列簇的NoSQL
- HBase基本概念
- HBase应用场景
- HBase架构和核心模块介绍
- HBase存储逻辑结构介绍
- HBase与其他NoSQL的比较
Topic 8: Deep understanding to Zookeeper
- Introduction and framework of Zookeeper
- Core knowledge of Zookeeper
- Use Zookeeper to Implement the Name Node in high availability
第8个主题：深入理解 Zookeeper(掌握 Zookeeper的原理及应用场景)
- Zookeeper简介和架构
- Zookeeper核心知识点
- 使用Zookeeper实现Name Node高可用
Topic 9: Spark’s framework design (Spark’s platform and application)
- Spark System analysis
- Spark Framework design analysis
- RDD Calculation flow analysis
- Excellent Fault Tolerance of Spark
- Case Studies
第9个主题：Spark的架构设计（理解Spark平台和应用场景）
- Spark生态系统剖析
- Spark的架构设计剖析
- RDD计算流程解析
- Spark的出色容错机制
- 案例分享
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Terms & Conditions
Trainings have very limited seating so to ensure your attendance we encourage advance online registration and payment. We cannot guarantee entry to anyone not registered in advance.
The training is held in English.
Cancellation Policy
If you cannot attend the training for which you have registered, please cancel your registration no later than one business day prior to the event. If you fail to notify us of your cancellation in a timely fashion, you will be charged for event costs.
To cancel you can: 1) email jli@europeanchamber.com.cn, or 2) cancel online if you registered for the event through the website.
