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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:
- Implement the Hadoop Distributed File System
- Describe the differences between MapReduce and YARN
- Load Hadoop Distributed File System Data into an Oracle database
- Create a database and table from a Hadoop Distributed File System file in Hive
- Describe the architectural components of MapReduce
- Configure the online and offline options for the Oracle Loader for Hadoop
- Cloudera Enterprise Hadoop Distribution
- Explain the Oracle Loader for Hadoop
- Use Pig Latin to query data in HDFS
- Explain the Hadoop Ecosystem
- Describe the Hive architecture
- Describe the importance of Namenode, Datanode, JobTracker, TaskTracker in Hadoop
- Execute a Hive query
- Set up Hive with formatters and SerDe
- Identify the benefits of the Hadoop Distributed File System (HDFS)
- Oracle Loader for Hadoop
- Use Flume in the Hadoop Distributed File System
- Move data from a database to a Hadoop Distributed File System using Sqoop
- Describe Hadoop High Availability
- Implement the data flow mechanism used in Flume
- Describe the Impala real-time query and explain how it differs from Hive
- Implement the Oracle Table Access for a Hadoop Connector
- Core Hadoop
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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:
- Use ODI to move data from an Oracle database to a Hadoop Distributed File System using sqoop
- Implement the Hadoop Distributed File System
- Describe the differences between MapReduce and YARN
- Describe how Big Data Appliance integrates with Exadata and Exalytics
- Describe the architectural components of MapReduce
- Big Data Technical Overview - Describe the architectural components of the Big Data Appliance
- Use ODI to move data from Hive to Oracle
- Set up Oracle Xquery for Hadoop connector
- Explain the business drivers behind Big Data and NoSQL versus Hadoop Core Hadoop - Explain the Hadoop Ecosystem
- Configure the Oracle Data Integrator with Application Adaptor for Hadoop to interact with Hadoop
- Xquery for Hadoop Connector
- Describe the importance of Namenode, Datanode, JobTracker, TaskTracker in Hadoop
- Use ODI to transform data from Hive to Hive
- Identify the benefits of the Hadoop Distributed File System (HDFS)
- Oracle Data Integrator (ODI) and Hadoop
- Use Flume in the Hadoop Distributed File System
- Describe Hadoop High Availability
- Implement the data flow mechanism used in Flume
- Use Oracle Xquery with Hadoop-Hive to map an XML file into a Hive table
- Describe the Big Data Discovery and Big Data Spatial and Graph solutions
- Perform a simple Xquery using Oracle XQuery for 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
