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Introduction to Hadoop and Big Data:
• What is Big Data?
• What are the challenges for processing big data?
• What technologies support big data?
• What is Hadoop?
• Why Hadoop?
• History of Hadoop
• Use cases of Hadoop
• RDBMS vs Hadoop
• When to use and when not to use Hadoop
• Ecosystem tour
• Vendor comparison
• Hardware Recommendations & Statistics
HDFS: Hadoop Distributed File System: – Significance of HDFS in Hadoop • Features of HDFS • 5 daemons of Hadoop 1.Name Node and its functionality 2.Data Node and its functionality 3.Secondary Name Node and its functionality 4.Job Tracker and its functionality 5.Task Tracker and its functionality • Data Storage in HDFS 1.Introduction about Blocks 2.Data replication • Accessing HDFS 1.CLI (Command Line Interface) and admin commands 2.Java Based Approach • Fault tolerance • Download Hadoop • Installation and set-up of Hadoop 1.Start-up & Shut down process • HDFS Federation Map Reduce: • Map Reduce Story • Map Reduce Architecture • How Map Reduce works • Developing Map Reduce • Map Reduce Programming Model 1.Different phases of Map Reduce Algorithm. 2.Different Data types in Map Reduce. 3.how Write a basic Map Reduce Program. • Driver Code • 3Mapper • Reducer • Creating Input and Output Formats in Map Reduce Jobs 1.Text Input Format 2.Key Value Input Format 3.Sequence File Input Format • Data localization in Map Reduce • Combiner (Mini Reducer) and Partitioner • Hadoop I/O • Distributed cache
PIG: • Introduction to Apache Pig • Map Reduce Vs. Apache Pig • SQL vs. Apache Pig • Different data types in Pig • Modes of Execution in Pig • Grunt shell • Loading data • Exploring Pig • Latin commands
HIVE: • Hive introduction • Hive architecture • Hive vs RDBMS • HiveQL and the shell • Managing tables (external vs managed) • Data types and schemas • Partitions and buckets
HBASE: • Architecture and schema design • HBase vs. RDBMS • HMaster and Region Servers • Column Families and Regions • Write pipeline • Read pipeline • HBase commands SQOOP Flume zookeeper
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