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Understanding functional and technical aspects of Oracle Big Data 2017 Certification Implementation Specialist Certification Exam 1z0-449 Oracle NoSQL Database
The following will be discussed here:
- Use an Oracle NoSQL database
- Integrate an Oracle NoSQL database with an Oracle database and Hadoop
- Programming with R
- Install the Oracle SQL Connector for Hadoop
- Use KVLite to test NoSQL applications
- Use Oracle R Advanced Analytics for a Hadoop connector
- Set up the KVStore
- Configure an external table for HDFS using the Oracle SQL Connector for Hadoop
- Describe the architectural components (Shard, Replica, Master) of the Oracle NoSQL database
- Oracle NoSQL Database
- Implement an Oracle Database connection with Oracle R Enterprise
- Describe the architectural components of Oracle R Advanced Analytics for Hadoop
- Describe the Oracle R Advanced Analytics for a Hadoop connector
- Oracle SQL Connector for Hadoop Distributed File System (HDFS)
- Describe the Oracle SQL Connector for Hadoop Connector
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:
- Execute a Hive query
- Move data from a database to a Hadoop Distributed File System using Sqoop
- Identify the benefits of the Hadoop Distributed File System (HDFS)
- Describe Hadoop High Availability
- Describe the importance of Namenode, Datanode, JobTracker, TaskTracker in Hadoop
- Explain the Oracle Loader for Hadoop
- Create a database and table from a Hadoop Distributed File System file in Hive
- Describe the Hive architecture
- Explain the Hadoop Ecosystem
- Implement the Hadoop Distributed File System
- Oracle Loader for Hadoop
- Configure the online and offline options for the Oracle Loader for Hadoop
- Core Hadoop
- Load Hadoop Distributed File System Data into an Oracle database
- Describe the differences between MapReduce and YARN
- Describe the architectural components of MapReduce
- Use Pig Latin to query data in HDFS
- Use Flume in the Hadoop Distributed File System
- Set up Hive with formatters and SerDe
- Implement the data flow mechanism used in Flume
- Cloudera Enterprise Hadoop Distribution
- Implement the Oracle Table Access for a Hadoop Connector
- Describe the Impala real-time query and explain how it differs from Hive
Reference: https://education.oracle.com/oracle-big-data-2017-implementation-essentials/pexam_1Z0-449
For more info read reference:
1Z0-449 Official Certification Site
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Oracle 1z1-449 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Big Data Analytics and Discovery | 10% | - Analytics Tools
- 1. Data Exploration
- 2. Oracle Big Data Discovery
- 3. Data Visualization
|
| Big Data Fundamentals | 10% | - Big Data Concepts
- 1. Big Data Architecture
- 2. Characteristics of Big Data
- 3. Big Data Use Cases
|
| Oracle Big Data Platform | 15% | - Oracle Big Data Components
- 1. Oracle Big Data Discovery
- 2. Oracle Big Data Appliance
- 3. Oracle Big Data SQL
- 4. Oracle Big Data Connectors
|
| NoSQL Database | 15% | - Oracle NoSQL Database
- 1. Data Access APIs
- 2. Replication and Scalability
- 3. Key-Value Data Model
|
| Hadoop Ecosystem | 25% | - Data Processing
- 1. Batch Processing
- 2. Data Transformation
- 3. Data Ingestion
- Core Hadoop Technologies
- 1. Hive
- 2. MapReduce
- 3. YARN
- 4. HDFS
- 5. Pig
|
| Big Data Integration | 15% | - Integration Technologies
- 1. Data Movement Between Hadoop and Oracle Database
- 2. Big Data Connectors
- 3. Oracle Data Integrator
|
| Security and Administration | 10% | - Platform Management
- 1. Authentication and Authorization
- 2. Security Concepts
- 3. Cluster Administration
- 4. Monitoring and Troubleshooting
|