IT COURSESOnline live classeswww.imaginelife.inPH:8499068708 :8341832707EMAIL:suport@imaginelife.in

Hadoop

Topics To Be covered in Hadoop courseIntroduction to Big Data & Hadoop

1.what is Big data?2.what are the challenges for processing big data?3.what is Hadoop?4.way Hadoop?5.History of Hadoop6.Use cases of Hadoop7.Hadoop eco System8.HDFS9.Mapreduce10.Statistics

Understanding the cluster1.Typical workflow2.Writing files to HDPS3.Reading files from HDFS4.Rack Awareness5.5 Daemons6.HDFS commands HANDS-onInstalling the cluster1.CDH4 Pseudo cluster2.CDH4 Multi node cluster3.configuration4.cluster on EC2 cloud5.How to use AWS EMR6.Hands –on Exercises

Routine Admin and Monitoring Activities1.Meta Data and Data Backups2.commissioning and Decommissioning nodes3.Recover from Namenode Failure4.Namenode High Availability5.Monitoring using ganglia and NagiosLet’s talk MapReduce1.Before MapReduce2.MapReduce Overview3.word count problem4.word count flow and solution5.MapReduce flow6.Algorithms for simple problems7.Algorithms for complex problems

Developing the MapReduce Application1.Data types2.File Formats3.Explain the Driver,Mapper and Reducer code4. configuring Development environment-Eclipse5.Writing Unit Test6.Running locally7.Hands –on exercisesHow Map Reduce Works1.Anatomy of map Reduce job run2.Job Submission3.Job initialization4.Task Assignment5.Job completion

6.Job Scheduling7.Job Failures8.shuffle and sort9.Oozie Workflows10.Hands –on ExercisesMapReduce Types and Formats1.MapReduce Types3.output Formats –text Output, binary output,multiple outputs4.Lazy output and database output5.Hands-on Exercises

MapReduce Features1.Counters2.Joins-map side and Reduce Side3.Sorting4.MapReduce combiner5.MapReduce partitioner6.MapReduce Distributed Cache7.Hands-on ExercisesHive1. What is Hive?2.what Hive is not?3.Hive Architecture4.SQL vs Hive QL5.Data Types6.Managed Tables and External Tables7.partitions8.Buckets

9.Storage formats10.serDes11.importing Data12.Joins-map side and Reduce Side13. UDFs14.Hands-on ExercisesImapla1.Need for RTQ2.impala Overview3.Impala Architecture4.Hands-on Exercises

Pig1.What is Pig? Why Pig?2.Running pig3.Data4.pig Latin Statements5.Schemas6.Validations7.Functions and Macros8.UDFs9.When to Use pig and HIVE10.Hands-on Exercises

NoSQL and HBase1.Why noSQL?2.Problems with RDBMS3.cap theorem4.HBase Concepts5.Use Cases for HBase6.HBase Data Model7.HBase Shell8.HBase Architecture9.Minor & major Compaction10.Bloom Filter&Block cache11.Schema Design12.Hands-0n Exercises

Sqoop1.What is Sqoop?2.Motivation3.Sqoop Commands4.Importing Data toHDFSHIVEHBase5.Exposing Data6.Sqoop Connectors7.Hands on ExercisesFLUME1.What is Flume?2.Use Cases3.Flume Topology –Source,Channel and Sink4.Hands-on Execises –Ingest Data from twitter and Analyze With Hive

Machine Learning and Mahout1.3Cs of Machine Learning2.Introduction to Mahout3.Hands-on Exercise:Build a Recommendation System using MahoutPOCs1.Banking Use case2.Telecom Use case