Oracle Big Data 2017 Implementation Essentials 

Содержание

Exam Topics:

Big Data Technical Overview

• 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

Core Hadoop

• Explain the Hadoop Ecosystem
• Implement the Hadoop Distributed File System
• Identify the benefits of the Hadoop Distributed File System (HDFS)
• Describe the architectural components of MapReduce
• Describe the differences between MapReduce and YARN
• Describe Hadoop High Availability
• Describe the importance of Namenode, Datanode, JobTracker, TaskTracker in Hadoop
• Use Flume in the Hadoop Distributed File System
• Implement the data flow mechanism used in Flume

Oracle NoSQL Database

• Use an Oracle NoSQL database 
• Describe the architectural components (Shard, Replica, Master) of the Oracle NoSQL database
• Set up the KVStore
• Use KVLite to test NoSQL applications
• Integrate an Oracle NoSQL database with an Oracle database and Hadoop

Cloudera Enterprise Hadoop Distribution

• Describe the Hive architecture
• Set up Hive with formatters and SerDe
• Implement the Oracle Table Access for a Hadoop Connector
• Describe the Impala real-time query and explain how it differs from Hive
• Create a database and table from a Hadoop Distributed File System file in Hive
• Use Pig Latin to query data in HDFS
• Execute a Hive query
• Move data from a database to a Hadoop Distributed File System using Sqoop

Programming with R

• Describe the Oracle R Advanced Analytics for a Hadoop connector
• Use Oracle R Advanced Analytics for a Hadoop connector
• Describe the architectural components of Oracle R Advanced Analytics for Hadoop
• Implement an Oracle Database connection with Oracle R Enterprise

Oracle Loader for Hadoop

• Explain the Oracle Loader for Hadoop
• Configure the online and offline options for the Oracle Loader for Hadoop
• Load Hadoop Distributed File System Data into an Oracle database

Oracle SQL Connector for Hadoop Distributed File System (HDFS)

• Configure an external table for HDFS using the Oracle SQL Connector for Hadoop
• Install the Oracle SQL Connector for Hadoop
• Describe the Oracle SQL Connector for Hadoop Connector

Oracle Data Integrator (ODI) and Hadoop

• Use ODI to transform data from Hive to Hive
• Use ODI to move data from Hive to Oracle
• 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

Big Data SQL

• Explain how Big Data SQL is used in a Big Data Appliance/Exadata architecture
• Set up and configure Oracle Big Data SQL
• Demonstrate Big Data SQL syntax used in create table statements
• Access NoSQL and Hadoop data using a Big Data SQL query

Xquery for Hadoop Connector

• Set up Oracle Xquery for Hadoop connector
• Perform a simple Xquery using Oracle XQuery for Hadoop
• Use Oracle Xquery with Hadoop-Hive to map an XML file into a Hive table

Securing Hadoop

• Describe Oracle Big Data Appliance security and encryption features
• Set up Kerberos security in Hadoop
• Set up the Hadoop Distributed File System to use Access Control Lists
• Set up Hive and Impala access security using Apache Sentry
• Use LDAP and the Active directory for Hadoop access control