Davidjhon Posted August 6, 2016 Report Posted August 6, 2016 We Provide Online Training|Training|Support on Hadoop Development with Real Time Experts Cours Outline: The Motivation for Hadoop Problems with Traditional Large-Scale Systems *Introducing Hadoop Hadoopable Problems Hadoop: Basic Concepts and HDFS *The Hadoop Project and Hadoop Components *The Hadoop Distributed File System Introduction to MapReduce *MapReduce Overview Example: WordCountMappersReducers Hadoop Clusters and the Hadoop Ecosystem *Hadoop Cluster Overview Hadoop Jobs and Tasks Other Hadoop Ecosystem Components Writing a MapReduce Program in Java *Basic MapReduce API Concepts Differences Between the Old and New MapReduce APIs *Writing a MapReduce Program Using Streaming *Writing Mappers and Reducers with the Streaming API Unit Testing MapReduce Programs *Unit Testing The JUnit and MRUnit Testing Framework.s Writing Unit Tests with MRUnit Decreasing the Amount of Intermediate Data with Combiners*Accessing HDFS ProgrammaticallyUsing The Distributed Cache Using the Hadoop API’s Library of Mappers, Reducers, and Partitioners Common MapReduce Algorithms *Sorting and Searching Large Data SetsIndexing DataComputing Term Frequency — Inverse Document Frequency *Calculating Word Co-OccurrencePerforming Secondary SortJoining Data Sets in MapReduce Jobs*Writing a Map-Side JoinWriting a Reduce-Side Joinintegrating Hadoop into the Enterprise Workflow *Integrating Hadoop into an Existing Enterprise Loading Data from an RDBMS into HDFS by Using Sqoop An Introduction to Hive, Imapala, and PigThe Motivation for Hive, Impala, and Pig. You can reach us @ 3092003878 or Email us: [email protected] Quote
Butterthief Posted August 6, 2016 Report Posted August 6, 2016 1 minute ago, Davidjhon said: We Provide Online Training|Training|Support on Hadoop Development with Real Time Experts Cours Outline: The Motivation for Hadoop Problems with Traditional Large-Scale Systems *Introducing Hadoop Hadoopable Problems Hadoop: Basic Concepts and HDFS *The Hadoop Project and Hadoop Components *The Hadoop Distributed File System Introduction to MapReduce *MapReduce Overview Example: WordCount Mappers Reducers Hadoop Clusters and the Hadoop Ecosystem *Hadoop Cluster Overview Hadoop Jobs and Tasks Other Hadoop Ecosystem Components Writing a MapReduce Program in Java *Basic MapReduce API Concepts Differences Between the Old and New MapReduce APIs *Writing a MapReduce Program Using Streaming *Writing Mappers and Reducers with the Streaming API Unit Testing MapReduce Programs *Unit Testing The JUnit and MRUnit Testing Framework.s Writing Unit Tests with MRUnit Decreasing the Amount of Intermediate Data with Combiners *Accessing HDFS Programmatically Using The Distributed Cache Using the Hadoop API’s Library of Mappers, Reducers, and Partitioners Common MapReduce Algorithms *Sorting and Searching Large Data Sets Indexing Data Computing Term Frequency — Inverse Document Frequency *Calculating Word Co-Occurrence Performing Secondary Sort Joining Data Sets in MapReduce Jobs *Writing a Map-Side Join Writing a Reduce-Side Join integrating Hadoop into the Enterprise Workflow *Integrating Hadoop into an Existing Enterprise Loading Data from an RDBMS into HDFS by Using Sqoop An Introduction to Hive, Imapala, and Pig The Motivation for Hive, Impala, and Pig. You can reach us @ 3092003878 or Email us: [email protected] ok Quote
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