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     班级规模及环境--热线:4008699035 手机:15921673576( 微信同号)
         每期人数限3到5人。
     上课时间和地点
  上课地点:【上海】:同济大学(沪西)/新城金郡商务楼(11号线白银路站) 【深圳分部】:电影大厦(地铁一号线大剧院站)/深圳大学成教院 【北京分部】:北京中山学院/福鑫大楼 【南京分部】:金港大厦(和燕路) 【武汉分部】:佳源大厦(高新二路) 【成都分部】:领馆区1号(中和大道) 【沈阳分部】:沈阳理工大学/六宅臻品 【郑州分部】:郑州大学/锦华大厦 【石家庄分部】:河北科技大学/瑞景大厦 【广州分部】:广粮大厦 【西安分部】:协同大厦
最近开课时间(周末班/连续班/晚班):2020年3月16日
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课程大纲
   
 
  • 课程介绍
           Students learn about Oracle’s Database partitioning architecture and identify the benefits of partitioning. Students also use parallel operations to reduce response time for data-intensive operations. Participants extract, transform, and load data into an Oracle database warehouse. Students also use materialized views to improve the data warehouse performance. Students also learn how query rewrite can improve a query’s performance. Students use the SQL Access Advisor to optimize the entire workload. Finally, students learn how to tune materialized views for fast refresh and query rewrite and how to use the compression and resumable sessions features.
           Learn to:
           Implement partitioning
           Use parallel operations to reduce response time
           Extract, Transform, and Load data
           Create, use, and refresh materialized views to improve the data warehouse performance
           Use Query rewrite to quickly answer business queries using materialized views
           Use SQL Access Advisor and PL/SQL procedures to tune materialized views for fast refresh and query rewrite

    课程对象
           Application Developers
           Data Warehouse Administrator Data Warehouse Developer Database Administrators Support Engineer
           Technical Consultant

  • 课程大纲:

                •Development Tools
                •Oracle SQL Developer
                •Enterprise Manager
                •Sample Schemas used
           Data Warehouse Design: Overview
                •Characteristics of a Data Warehouse
                •Comparing OLTP and Data Warehouses
                •Data Warehouse Architectures
                •Data Warehouse Design
                •Data Warehouse objects
                •Data Warehouse Schemas
           Data Warehouse Tuning Considerations
                •Optimizing Star Queries
                •Introducing Bitmap Join Indexes
                •Understanding Star Query Optimization and Bitmap Joined Index Optimization
           Partitioning Basics
                •Partitioned Tables and Indexes
                •Partitioning Methods
                •Partitioning Types
                •Partition Pruning and Star queries
           Parallelism Concepts
                •Operations That Can Be Parallelized
                •How Parallel Execution Works
                •Degree of Parallelism
                •Parallel execution plan
                •Automatice Parallelism
           Parallel Operations in Data Warehouses
                •Parallel Query
                •Parallel DDL
                •Parallel DML
                •Tuning Parameters for Parallel Execution
                •Balancing the Workload
           ETL: Extraction and Transportation
                •Extraction Methods
                •Capturing Data With Change Data Capture
                •Sources and Modes of Change Data Capture
                •Publish and Subscribe Model: The Publisher and the Subscriber
                •Synchronous and Asynchronous CDC
                •Asynchronous AutoLog Mode and Asynchronous HotLog Mode
                •Transportation in a Data Warehouse
                •Transportable Tablespaces
           ETL: Loading
                •Loading Mechanisms
                •Applications of External Tables
                •Defining external tables with SQL*Loader
                •Populating external tables with Data Pump
                •Other Loading Methods
           ETL: Transformation
                •Data transformation
                •Transformation Mechanisms
                •Transformation Using SQL
                •Table Functions
                •DML error logging
           Materialized Views
                •The Need for Summary Management
                •Types of Materialized Views
                •Using Materialized Views for Summary Management
                •Materialized View Dictionary views
           Refreshing Materialized Views
                •Refresh Options
                •Refresh Modes
                •Conditions That Effect Possibility of Fast Refresh
                •Materialized View Logs
                •Partition Change Tracking (PCT) Refresh
                •Refresh Performance Improvements
           Working With Dimensions
                •What Are Dimensions
                •Creating Dimensions and Hierarchies
                •Dimensions and Privileges
                •Dimension Restrictions
                •Verifying Relationships in a Dimension
                •Dimension Invalidation
           Query Rewrite
                •Query Rewrite: Overview
                •What Can be Rewritten
                •Conditions Required for Oracle to Rewrite a Query
                •Query Rewrite guidelines
                •Setting Initialization Parameters for Query Rewrite
                •Query Rewrite Methods
                •Partition Change Tracking (PCT) and Query Rewrite
                •Query Rewrite Enhancement to Support Queries Containing Inline Views
           Using the SQL Access Advisor, Compression, and Resumable Sessions
                •SQL Access Advisor: Usage Model
                •Setting Initial Options
                •Specifying the Workload Source
                •Recommendation Options
                •Schedule and Review
                •PL/SQL Procedure Flow
                •Tuning Materialized Views for Fast Refresh and Query Rewrite
                •Table Compression and Resumable Sessions

 

 
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