big data hadoop training course
DESCRIPTION
Big Data Hadoop Training Course Agenda Please contact [email protected]TRANSCRIPT
@RMSSoftwareTech [email protected]
http://www.rmssoftwaretech.com
Apache Hadoop (Big Data)
Big Data Training
2 © 2014 RMS Software Tech (rmssoftwaretech.com)
Logo’s & Trademarks
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Profile : RMS Software Technologies
• About us : ◦ Leading provider of Software solutions, System integration Services and
Professional Training ◦ Based in San Jose, CA & Mumbai, India started in 2012.
• Professional Courses : ◦ Expert Training team of 10 people who provide training in various leading
technologies like iPhone iOS, Android, Java, Big Data Hadoop, QA & Agile Scrum Methodologies.
◦ Team of developers using AngularJS at the client projects. ◦ Focused on Interns and engineers looking to learn new exciting technologies.
• Track Record: ◦ We work with emerging technologies to create mobile applications, rich-client desktop
software, and large-scale systems (CRM, ERP). ◦ We create high quality solutions for hard problems, to help our customers thrive ◦ We can share this expertise with you developers, in the form of workshop style, hands-on
training classes.
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Course : Prerequisites and Equipment
• Prerequisites : ◦ Students should have experience with Database (DBMS) like Oracle,
Informix, Sybase. No prior experience of Big Data or NOSQL and Hadoop is required for the course.
• Equipment : ◦ Please use - Laptop (Windows, Linux, or Mac).
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Training Agenda
Training Schedule & Agenda
Week 1 : Hadoop Overview
Week 2 : HDFS Deep Dive
Week 3 : MapReduce and Pig
Week 4 : Hive and HBase
Week 5 : Zookeeper, Oozie, Flume, Talend
Week 6 : Practice Questions, Q & A with Final Project We believe this curriculum covers the basics well, and positions students to use Hadoop effectively and efficiently. It provides a good overview on Hadoop and Big Data
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Week 1 : Hadoop Overview
• Brief History of Hadoop
• RDBMS/SQL vs. Hadoop
• Structured vs. Unstructured data
• Introduction to Hadoop Ecosystem (HDFS, MapReduce, Pig, Hive, HBase)
• HDFS Overview (NameNode vs. DataNode)
• MapReduce overview (JobTracker vs. TaskTracker)
• Hadoop XML files for configuration
• Hadoop Ecosystem (Hive, Pig, Hbase, Zookeeper, Mahout, Oozie, Talend, Scoop, Flume)
• Lab #1 Virtual Machine Setup
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Week 2 : HDFS Deep Dive
• NameNode Architecture
• DataNode Architecture
• Write Pipeline
• Read Pipeline
• HDFS Disk space quotas and number of file quotas
• Quick Intro to Java API interface
• Lab #2.
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Week 3 : MapReduce and Pig
• MapReduce Architecture
• Combiner, Partitioner
• JobTracker & TaskTracker
• Job Scheduling
• Distributed Cache
• Counters
• MapReduce configuration files
• Simple MapReduce example : WordCount
• Next Gen MapReduce : YARN.
• Lab #3 : MapReduce
• Lab #4 : Pig
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Week 4: Hive and HBase
• Hive architecture.
• Hive vs. RDBMS.
• HiveQL and Hive. Shell
• Managing Tables
• Querying Data
• Data Types and Schemas
• Introduction to UDF (User Defined Functions)
• HBase Architecture
• HBase vs. Cassandra
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Week 4: HBase
• Bloom Filters and Block indexes
• Table Scans and Filters
• Lab # Intro to HBase command line.
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Week 5: Zookeeper, Oozie, Flume, Sqoop, Talend
• Flume overview
• Flume usage
• Sqoop overview
• Sqoop usage
• Hadoop workflow
• Jobcontrol
• Oozie
• Talend
• Sqoop
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Week 6: Project and Practice Questions
• Sample Project
• Practice Questions
• Q & A