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:

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

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:

• Integrate an Oracle NoSQL database with an Oracle database and Hadoop
• Configure an external table for HDFS using the Oracle SQL Connector for Hadoop
• Describe the architectural components of Oracle R Advanced Analytics for Hadoop
• Describe the Oracle SQL Connector for Hadoop Connector
• Oracle NoSQL Database
• Oracle SQL Connector for Hadoop Distributed File System (HDFS)
• Set up the KVStore
• Describe the architectural components (Shard, Replica, Master) of the Oracle NoSQL database
• Describe the Oracle R Advanced Analytics for a Hadoop connector
• Use KVLite to test NoSQL applications
• Use an Oracle NoSQL database
• Implement an Oracle Database connection with Oracle R Enterprise
• Install the Oracle SQL Connector for Hadoop
• Programming with R
• Use Oracle R Advanced Analytics for a Hadoop connector

How much Oracle Big Data 2017 Certification Implementation Specialist Certification Exam 1z0-449 costs

• Examination Fees: $245 USD
• Examination Name: Oracle Big Data 2017 Certification Implementation Specialist Certification Exam 1z0-449
• Passing Score: 75% or higher
• Types of questions: Performance Based Questions
• No. of Questions: 76 Questions
• Length of Exam: 120 min

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:

• Oracle Data Integrator (ODI) and Hadoop
• Explain the business drivers behind Big Data and NoSQL versus Hadoop Core Hadoop - Explain the Hadoop Ecosystem
• Configure the Oracle Data Integrator with Application Adaptor for Hadoop to interact with Hadoop
• Use ODI to move data from an Oracle database to a Hadoop Distributed File System using sqoop
• Xquery for Hadoop Connector
• Describe the architectural components of MapReduce
• Describe Hadoop High Availability
• Identify and architect the services that run on each node in the Big Data Appliance, as it expands from single to multiple nodes
• Identify the benefits of the Hadoop Distributed File System (HDFS)
• Use ODI to transform data from Hive to Hive
• Perform a simple Xquery using Oracle XQuery for Hadoop
• Implement the data flow mechanism used in Flume
• Describe the Big Data Discovery and Big Data Spatial and Graph solutions
• Describe the importance of Namenode, Datanode, JobTracker, TaskTracker in Hadoop
• Describe how Big Data Appliance integrates with Exadata and Exalytics
• Use Flume in the Hadoop Distributed File System
• Use ODI to move data from Hive to Oracle
• Use Oracle Xquery with Hadoop-Hive to map an XML file into a Hive table
• Describe the differences between MapReduce and YARN
• Big Data Technical Overview - Describe the architectural components of the Big Data Appliance
• Set up Oracle Xquery for Hadoop connector
• Implement the Hadoop Distributed File System

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