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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:
- Oracle Loader for Hadoop
- Identify the benefits of the Hadoop Distributed File System (HDFS)
- Describe the Impala real-time query and explain how it differs from Hive
- Create a database and table from a Hadoop Distributed File System file in Hive
- Configure the online and offline options for the Oracle Loader for Hadoop
- Set up Hive with formatters and SerDe
- Use Flume in the Hadoop Distributed File System
- Implement the Hadoop Distributed File System
- Implement the data flow mechanism used in Flume
- Explain the Hadoop Ecosystem
- Describe the architectural components of MapReduce
- Describe the importance of Namenode, Datanode, JobTracker, TaskTracker in Hadoop
- Cloudera Enterprise Hadoop Distribution
- Describe the Hive architecture
- Describe Hadoop High Availability
- Describe the differences between MapReduce and YARN
- Implement the Oracle Table Access for a Hadoop Connector
- Use Pig Latin to query data in HDFS
- Explain the Oracle Loader for Hadoop
- Move data from a database to a Hadoop Distributed File System using Sqoop
- Load Hadoop Distributed File System Data into an Oracle database
- Execute a Hive query
- Core Hadoop
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:
- Explain the business drivers behind Big Data and NoSQL versus Hadoop Core Hadoop - Explain the Hadoop Ecosystem
- Identify the benefits of the Hadoop Distributed File System (HDFS)
- Xquery for Hadoop Connector
- Perform a simple Xquery using Oracle XQuery for Hadoop
- Configure the Oracle Data Integrator with Application Adaptor for Hadoop to interact with Hadoop
- Describe how Big Data Appliance integrates with Exadata and Exalytics
- Set up Oracle Xquery for Hadoop connector
- Use Flume in the Hadoop Distributed File System
- Implement the Hadoop Distributed File System
- Describe the Big Data Discovery and Big Data Spatial and Graph solutions
- Implement the data flow mechanism used in Flume
- Use ODI to move data from an Oracle database to a Hadoop Distributed File System using sqoop
- Describe the architectural components of MapReduce
- Describe the importance of Namenode, Datanode, JobTracker, TaskTracker in Hadoop
- 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 ODI to transform data from Hive to Hive
- Use ODI to move data from Hive to Oracle
- 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
Oracle 1z1-449 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Security and Administration | 10% | - Platform Management
|
| NoSQL Database | 15% | - Oracle NoSQL Database
|
| Oracle Big Data Platform | 15% | - Oracle Big Data Components
|
| Big Data Fundamentals | 10% | - Big Data Concepts
|
| Big Data Integration | 15% | - Integration Technologies
|
| Hadoop Ecosystem | 25% | - Core Hadoop Technologies
|
| Big Data Analytics and Discovery | 10% | - Analytics Tools
|
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