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:
- Explain the Hadoop Ecosystem
- Oracle Loader for Hadoop
- Use Flume in the Hadoop Distributed File System
- Describe the Impala real-time query and explain how it differs from Hive
- Configure the online and offline options for the Oracle Loader for Hadoop
- Core Hadoop
- Explain the Oracle Loader for Hadoop
- Implement the Oracle Table Access for a Hadoop Connector
- Describe the Hive architecture
- Set up Hive with formatters and SerDe
- Implement the data flow mechanism used in Flume
- Use Pig Latin to query data in HDFS
- Describe the importance of Namenode, Datanode, JobTracker, TaskTracker in Hadoop
- Move data from a database to a Hadoop Distributed File System using Sqoop
- Implement the Hadoop Distributed File System
- Execute a Hive query
- Describe the architectural components of MapReduce
- Describe the differences between MapReduce and YARN
- Load Hadoop Distributed File System Data into an Oracle database
- Describe Hadoop High Availability
- Create a database and table from a Hadoop Distributed File System file in Hive
- Identify the benefits of the Hadoop Distributed File System (HDFS)
- Cloudera Enterprise Hadoop Distribution
Average Salary of Oracle Big Data 2017 Certification Implementation Specialist Certification Exam 1z0-449 Certified Professionals
The average salary:
- Europe - 100,440 EURO
- England - 75,267 POUND
- United State - 151,682 USD
- India - 6,71,117 INR
Oracle 1z1-449 Exam Syllabus Topics:
| Topic | Details |
|---|
| Topic 1 | - Describe the architectural components of MapReduce
- Identify the benefits of the Hadoop Distributed File System (HDFS)
|
| Topic 2 | - Describe Oracle Big Data Appliance security and encryption features
- Implement the Hadoop Distributed File System
|
| Topic 3 | - Integrate an Oracle NoSQL database with an Oracle database and Hadoop
- Describe how Big Data Appliance integrates with Exadata and Exalytics
|
| Topic 4 | - Describe the Oracle R Advanced Analytics for a Hadoop connector
- Implement the data flow mechanism used in Flume
|
| Topic 5 | - Use LDAP and the Active directory for Hadoop access control
- Describe the architectural components of the Big Data Appliance
|
| Topic 6 | - Describe the Big Data Discovery and Big Data Spatial and Graph solutions
- Implement an Oracle Database connection with Oracle R Enterprise
|
| Topic 7 | - Demonstrate Big Data SQL syntax used in create table statements
- Implement the Oracle Table Access for a Hadoop Connector
|
| Topic 8 | - Describe the architectural components of Oracle R Advanced Analytics for Hadoop
- Describe the Impala real-time query and explain how it differs from Hive
|
| Topic 9 | - Describe the importance of Namenode, Datanode, JobTracker, TaskTracker in Hadoop
- Describe the differences between MapReduce and YARN
|
Reference: https://education.oracle.com/oracle-big-data-2017-implementation-essentials/pexam_1Z0-449
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