Difficulty in Attempting Oracle Big Data 2017 Certification Implementation Specialist Certification Exam 1z0-449
If the user has successfully passed the 1Z0-449 practice exam and has been through 1Z0-449 exam dumps then the certification exam will not be too much difficult as the user has shown aptitude for understanding complicated processes.
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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 Oracle Data Integrator (ODI) and Hadoop
The following will be discussed here:
- Describe Hadoop High Availability
- Describe the differences between MapReduce and YARN
- Big Data Technical Overview - Describe the architectural components of the Big Data Appliance
- Use Flume in the Hadoop Distributed File System
- Use ODI to move data from an Oracle database to a Hadoop Distributed File System using sqoop
- Set up Oracle Xquery for Hadoop connector
- Implement the data flow mechanism used in Flume
- Describe the Big Data Discovery and Big Data Spatial and Graph solutions
- Use ODI to move data from Hive to Oracle
- Implement the Hadoop Distributed File System
- Describe how Big Data Appliance integrates with Exadata and Exalytics
- Configure the Oracle Data Integrator with Application Adaptor for Hadoop to interact with Hadoop
- Explain the business drivers behind Big Data and NoSQL versus Hadoop Core Hadoop - Explain the Hadoop Ecosystem
- Identify and architect the services that run on each node in the Big Data Appliance, as it expands from single to multiple nodes
- Use Oracle Xquery with Hadoop-Hive to map an XML file into a Hive table
- Oracle Data Integrator (ODI) and Hadoop
- Use ODI to transform data from Hive to Hive
- Describe the architectural components of MapReduce
- Identify the benefits of the Hadoop Distributed File System (HDFS)
- Perform a simple Xquery using Oracle XQuery for Hadoop
- Xquery for Hadoop Connector
- Describe the importance of Namenode, Datanode, JobTracker, TaskTracker in Hadoop

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