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坚持小班授课，为保证培训效果，增加互动环节，每期人数限3到5人。 |
| 上课时间和地点 |
上课地点：【上海】：同济大学(沪西)/新城金郡商务楼(11号线白银路站) 【深圳分部】：电影大厦(地铁一号线大剧院站)/深圳大学成教院 【北京分部】：北京中山学院/福鑫大楼 【南京分部】：金港大厦(和燕路) 【武汉分部】：佳源大厦（高新二路） 【成都分部】：领馆区1号（中和大道） 【沈阳分部】：沈阳理工大学/六宅臻品 【郑州分部】：郑州大学/锦华大厦 【石家庄分部】：河北科技大学/瑞景大厦 【广州分部】：广粮大厦 【西安分部】：协同大厦
最近开课时间(周末班/连续班/晚班）：即将开课，详情请咨询客服！ |
| 实验设备 |
☆资深工程师授课
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| 质量保障 |
1、培训过程中，如有部分内容理解不透或消化不好，可免费在以后培训班中重听；
2、课程完成后,授课老师留给学员手机和Email,保障培训效果,免费提供半年的技术支持。
3、培训合格学员可享受免费推荐就业机会。 |
课程大纲 |
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- Cloudera Developer Training for Apache Hadoop培训
Cloudera Developer Training for Apache Hadoop培训
- 培训大纲：
1. Motivation for Hadoop
Problems with Traditional Large-Scale Systems
Requirements for a New Approach
2. Hadoop: Basic Concepts
Hadoop Distributed File System (HDFS)
MapReduce
Anatomy of a Hadoop Cluster
Other Hadoop Ecosystem Components
3. Writing a MapReduce Program
MapReduce Flow
Examining a Sample MapReduce Program
Basic MapReduce API Concepts
Driver Code
Mapper
Reducer
Streaming API
Using Eclipse for Rapid Development
New MapReduce API
4. Integrating Hadoop into the Workflow
Relational Database Management Systems
Storage Systems
Importing Data from a Relational Database Management System with Sqoop
Importing Real-Time Data with Flume
Accessing HDFS Using FuseDFS and Hoop
5. Delving Deeper into the Hadoop API
ToolRunner
Testing with MRUnit
Reducing Intermediate Data with Combiners
Configuration and Close Methods for Map/Reduce Setup and Teardown
Writing Partitioners for Better Load Balancing
Directly Accessing HDFS
Using the Distributed Cache
6. Common MapReduce Algorithms
Sorting and Searching
Indexing
Machine Learning with Mahout
Term Frequency
Inverse Document Frequency
Word Co-Occurrence
7. Using Hive and Pig
Hive Basics
Pig Basics
8. Practical Development Tips and Techniques
Debugging MapReduce Code
Using LocalJobRunner Mode for Easier Debugging
Retrieving Job Information with Counters
Logging
Splittable File Formats
Determining the Optimal Number of Reducers
Map-Only MapReduce Jobs
9. Advanced MapReduce Programming
Custom Writables and WritableComparables
Saving Binary Data Using SequenceFiles and Avro Files
Creating InputFormats and OutputFormats
10. Joining Data Sets in MapReduce
Map-Side Joins
Secondary Sort
Reduce-Side Joins
11. Graph Manipulation in Hadoop
Graph Techniques
Representing Graphs in Hadoop
Implementing a Sample Algorithm: Single Source Shortest Path
12. Creating Workflows with Oozie
Motivation for Oozie
Workflow Definition Format
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