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Understanding functional and technical aspects of Oracle Big Data 2017 Certification Implementation Specialist Certification Exam 1z0-449 Oracle Data Integrator (ODI) and Hadoop

The following will be discussed here:

• Describe how Big Data Appliance integrates with Exadata and Exalytics
• Use ODI to move data from an Oracle database to a Hadoop Distributed File System using sqoop
• Oracle Data Integrator (ODI) and Hadoop
• Implement the data flow mechanism used in Flume
• Explain the business drivers behind Big Data and NoSQL versus Hadoop Core Hadoop - Explain the Hadoop Ecosystem
• Use ODI to move data from Hive to Oracle
• Describe the importance of Namenode, Datanode, JobTracker, TaskTracker in Hadoop
• Use ODI to transform data from Hive to Hive
• Describe the architectural components of MapReduce
• Describe the differences between MapReduce and YARN
• Perform a simple Xquery using Oracle XQuery for Hadoop
• Use Flume in the Hadoop Distributed File System
• Describe Hadoop High Availability
• Identify the benefits of the Hadoop Distributed File System (HDFS)
• Use Oracle Xquery with Hadoop-Hive to map an XML file into a Hive table
• Set up Oracle Xquery for Hadoop connector
• Describe the Big Data Discovery and Big Data Spatial and Graph solutions
• Implement the Hadoop Distributed File System
• Xquery for Hadoop Connector
• Big Data Technical Overview - Describe the architectural components of the Big Data Appliance
• Configure the Oracle Data Integrator with Application Adaptor for Hadoop to interact with Hadoop
• Identify and architect the services that run on each node in the Big Data Appliance, as it expands from single to multiple nodes

Reference: https://education.oracle.com/oracle-big-data-2017-implementation-essentials/pexam_1Z0-449

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Understanding functional and technical aspects of Oracle Big Data 2017 Certification Implementation Specialist Certification Exam 1z0-449 Core Hadoop

The following will be discussed here:

• Describe the Hive architecture
• Implement the Oracle Table Access for a Hadoop Connector
• Explain the Oracle Loader for Hadoop
• Explain the Hadoop Ecosystem
• Set up Hive with formatters and SerDe
• Implement the data flow mechanism used in Flume
• Move data from a database to a Hadoop Distributed File System using Sqoop
• Load Hadoop Distributed File System Data into an Oracle database
• Describe the Impala real-time query and explain how it differs from Hive
• Configure the online and offline options for the Oracle Loader for Hadoop
• Describe the importance of Namenode, Datanode, JobTracker, TaskTracker in Hadoop
• Describe the architectural components of MapReduce
• Describe the differences between MapReduce and YARN
• Use Flume in the Hadoop Distributed File System
• Execute a Hive query
• Core Hadoop
• Describe Hadoop High Availability
• Identify the benefits of the Hadoop Distributed File System (HDFS)
• Create a database and table from a Hadoop Distributed File System file in Hive
• Cloudera Enterprise Hadoop Distribution
• Use Pig Latin to query data in HDFS
• Oracle Loader for Hadoop
• Implement the Hadoop Distributed File System

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