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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 data flow mechanism used in Flume
Move data from a database to a Hadoop Distributed File System using Sqoop
Describe the importance of Namenode, Datanode, JobTracker, TaskTracker in Hadoop
Create a database and table from a Hadoop Distributed File System file in Hive
Cloudera Enterprise Hadoop Distribution
Describe the differences between MapReduce and YARN
Describe the Impala real-time query and explain how it differs from Hive
Describe the Hive architecture
Core Hadoop
Implement the Hadoop Distributed File System
Describe the architectural components of MapReduce
Explain the Oracle Loader for Hadoop
Identify the benefits of the Hadoop Distributed File System (HDFS)
Use Flume in the Hadoop Distributed File System
Explain the Hadoop Ecosystem
Use Pig Latin to query data in HDFS
Implement the Oracle Table Access for a Hadoop Connector
Set up Hive with formatters and SerDe
Load Hadoop Distributed File System Data into an Oracle database
Execute a Hive query
Oracle Loader for Hadoop
Configure the online and offline options for the Oracle Loader for Hadoop
Describe Hadoop High Availability

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 architectural components of the Big Data Appliance
Describe how Big Data Appliance integrates with Exadata and Exalytics
Identify and architect the services that run on each node in the Big Data Appliance, as it expands from single to multiple nodes
Describe the Big Data Discovery and Big Data Spatial and Graph solutions
Explain the business drivers behind Big Data and NoSQL versus Hadoop
Big Data Technical Overview