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Oracle Big Data 2017 Implementation Essentials

Код: | 1Z0-449 |
продолжительность: | 120 минут |
Язык обучения: | English |
Тестовая система: | Pearson VUE |
Филиал: | Москва |
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
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