Simple language
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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 Hive to Oracle
- Describe the importance of Namenode, Datanode, JobTracker, TaskTracker in Hadoop
- Use Oracle Xquery with Hadoop-Hive to map an XML file into a Hive table
- Use ODI to move data from an Oracle database to a Hadoop Distributed File System using sqoop
- Configure the Oracle Data Integrator with Application Adaptor for Hadoop to interact with Hadoop
- Describe the architectural components of MapReduce
- Describe the Big Data Discovery and Big Data Spatial and Graph solutions
- Identify the benefits of the Hadoop Distributed File System (HDFS)
- Identify and architect the services that run on each node in the Big Data Appliance, as it expands from single to multiple nodes
- Use Flume in the Hadoop Distributed File System
- Use ODI to transform data from Hive to Hive
- Set up Oracle Xquery for Hadoop connector
- Describe how Big Data Appliance integrates with Exadata and Exalytics
- Describe Hadoop High Availability
- Oracle Data Integrator (ODI) and Hadoop
- Big Data Technical Overview - Describe the architectural components of the Big Data Appliance
- Implement the Hadoop Distributed File System
- Explain the business drivers behind Big Data and NoSQL versus Hadoop Core Hadoop - Explain the Hadoop Ecosystem
- Xquery for Hadoop Connector
- Describe the differences between MapReduce and YARN
- Perform a simple Xquery using Oracle XQuery for Hadoop
- Implement the data flow mechanism used in Flume
Understanding functional and technical aspects of Oracle Big Data 2017 Certification Implementation Specialist Certification Exam 1z0-449 Big Data Technical Overview
The following will be discussed here:
- Describe the Big Data Discovery and Big Data Spatial and Graph solutions
- Identify and architect the services that run on each node in the Big Data Appliance, as it expands from single to multiple nodes
- Describe how Big Data Appliance integrates with Exadata and Exalytics
- Describe the architectural components of the Big Data Appliance
- Big Data Technical Overview
- Explain the business drivers behind Big Data and NoSQL versus Hadoop
Reference: https://education.oracle.com/oracle-big-data-2017-implementation-essentials/pexam_1Z0-449
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Oracle 1z1-449 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Big Data Technical Overview | 15% | - Business drivers for Big Data and NoSQL - Hadoop ecosystem fundamentals - Big Data Appliance architecture and components |
| Topic 2: Oracle NoSQL Database | 20% | - Architecture: Shard, Replica, Master - KVStore setup and configuration - Integration with Oracle Database and Hadoop |
| Topic 3: Core Hadoop | 25% | - Hive, Impala, Pig usage - Data ingestion with Flume and Sqoop - MapReduce vs YARN - HDFS architecture and high availability |
| Topic 4: Big Data SQL & Integration | 20% | - XQuery with Hadoop-Hive - Oracle Loader for Hadoop - Oracle Table Access for Hadoop Connector - Integration with Exadata and Exalytics |
| Topic 5: Advanced Analytics & Security | 20% | - LDAP/Active Directory authentication - Oracle R Advanced Analytics for Hadoop - Security and access control |








