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Copyright © 2015, Oracle and/or its affiliates. All rights reserved. |
Oracle DB 12c 加速企业转型之十大功能
Copyright © 2015, Oracle and/or its affiliates. All rights reserved. |
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Safe Harbor Statement
The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.
3
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Oracle多年持续的革新
Oracle Database 10g
Oracle Database 11g
Oracle Exadata
Oracle9i Database Real Application Clusters
Database Services CPU Resource Management
Automatic Storage Management Dynamic Database Services
Server Pools Instance Caging
Advanced Compression Active Data Guard
I/O Resource Management
Multitenant Smart Flash Cache
Hybrid Columnar Compression
In-memory Option Oracle Database 12c Hybrid Cloud offering
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | 5
Oracle Database 12c 势头 – 持续快速创新
下载量 服务请求
Up 29% in 2015 compared to 2014
Up to 29.8% of all service requests (end april 2016)
新的选件
Over 5X greater than first 2.75 years of new 11g options
Oracle Confidential – Highly Restricted
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Public 6
Oracle Database 12c Top 10新功能 Oracle 12c 新功能 描述
1- 多租户 Multitenant Database (new DB Option)
2- 内存数据库 In-Memory Option
3- 高可用性 Far Sync and Global Data Services (Part of Active Data Guard)
4- 数据分析 Oracle Advanced Analytics (new DB Option replaces Data Mining)
5- 存储优化 Heat Map, Automatic Data Optimization (Part of Advanced Compression)
6- 数据保护 Application Continuity (Part of Active Data Guard and Real Application Cluster)
7- 数据安全 Data Redaction, Privilege Analysis,
8-事务增强 Transaction Guard:a reliable protocol and API that returens the outcome of the last transaction
9-数据脱敏 Data Masking at source
10-大数据增强 In-Database MapReduce / Pattern Matching
超过 500 个新功能
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
特性一:多租户架构
7
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
System Resources
Oracle 12c Multitenant整合数据库 多租户架构简化整合操作,提高整合密度
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
公共数据字典 12.1之前: Oracle 和用户元数据随着时间的推移混合
Database Created
Data D
ictio
nary
User Data
Meta D
ata
Mature Database
Data D
ictio
nary
User Data
Meta D
ata
Tables, Code, Data added
Data D
ictio
nary
User Data
Meta D
ata
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
OBJ$ TAB$ SOURCE$
…
Oracle数据和用户数据
OBJ$ TAB$ SOURCE$
…
EMP DEPT
…
OBJ$ TAB$ SOURCE$
…
多租户修复:
水平的-分区的数据字典
仅保留Oracle系统定义
Oracle和客户元数据混在一起
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Oracle 使用多租户数据库架构的目的
•降低成本 •数据以及代码更容易且更快捷地移动 •更容易管理和监控 •数据和代码分离 •更少的修补程序和升级
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
DB12c多租户架构简化数据库升级及补丁维护 只需一次更改,所有可插拔数据库均会更新
ERP CRM DW
Upgrade
in-place
12.1 12.1 12.1 12.X 12.X 12.X
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
ERP CRM DW
在可插拔数据库级别下进行时间点恢复
一个备份(CDB级别)
DB12c多租户架构简化整合后的数据库管理 统一备份多个数据库;在可插拔数据库级别执行恢复
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
特性二:内存选件
14
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
$$$
更快的OLTP混合工作负载
透明: 无需改变应用
更合理的成本效益
Oracle Database In-Memory 目标
100倍
15
$ 2-10倍 简单
实时分析获得几个数量级的性能
提升
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
在此之前,客户需要选择适合存储格在此之前, 客户必须选择行或列其中的一种,牺牲另一方面的性能
Oracle 12c:两种数据存储格式并存
16
行式
在行格式下事务处理运行快 – 快速处理少量行,多个列 – 例如:插入或者查询一个销售订单
列式
在列格式下分析的更快 – 快速处理少量列、大量行
– 举例:基亍亍销售汇总的报表
ORDER
SALES
SALES
STATE
行式数据库vs. 列式数据库 Row Format vs. Column Format
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
同一张表在内存中同时支持行和列两种格式
同时激活并且保持事务一致性
分析和报表使用新的列格式
OLTP使用行格式
Oracle数据库In-Memory选件
列格式 ( Column
Format)
内存Memory
行格式 (Row
Format)
内存Memory
分析 联机事务处理OLTP
Sales Sales
行、列双格式的In-Memory内存数据库
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
In-Memory 选件优势(一)
• Oracle统一处理,仅存储一份数据,没有额外的存储成本和同步问题
• 数据库自动维护行列格式一致性,就像维护表和索引的一致性一样
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
In-Memory选件优势(二)
• 优化器了解列格式 –分析类查询自动路由到列格式
–OLTP自动路由到行格式
–不需要修改应用,没有性能和数据一致性问题
优化器
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
特性三:Far Sync支持
20
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
主数据库 备用数据库 异步
发生灾难时有丢失数据的风险
Data Guard 异步 - 现在
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
主数据库 备用数据库
远程同步
实例
操作流程
Active Data Guard 远程同步
异步
同步
Commit Ack
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
主数据库 备用数据库
远程同步
实例
操作流程(续)
Active Data Guard 远程同步
无需权衡可用性与性能!
异步
同步
零数据损失
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
特性四: Oracle Advanced Analytics
24
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | STRUCTURED DATA UNSTRUCTURED DATA Source: IDC 2011 Content Provided By Cloudera.
2005 2015 2010
More than 90% is unstructured data
Approx. 500 quadrillion files
Quantity doubles every 2 years
1.8 trillion gigabytes of data was created in 2011…
10,000
5,000
0
“There was 5 exabytes of information created between the dawn of civilization through 2003, but that much information is now created every 2 days, and the pace is increasing.” - Google CEO Eric Schmidt
Requires capability to rapidly:
Collect and integrate data
Understand data & their relationships
Respond and take action
GIG
AB
YTE
S O
F D
ATA
) C
REA
TED
(I
N B
ILLI
ON
S)
“Big Data” “Big Data Analytics”
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Oracle Exadata
Oracle Exalytics
Oracle Big Data Platform
Stream Acquire Organize Discover & Analyze
Oracle Big Data Appliance
Oracle Big Data
Connectors Optimized for Analytics & In-Memory Workloads
“System of Record” Optimized for DW/OLTP
Optimized for Hadoop, R, and NoSQL Processing
Oracle Enterprise
Performance Management
Oracle Business Intelligence
Applications
Oracle Business Intelligence
Tools
Oracle Endeca Information
Discovery
Hadoop
Open Source R
Applications
Oracle NoSQL Database
Oracle Big Data Connectors
Oracle Data Integrator
In-D
atab
ase
An
alyt
ics
Data Warehouse
Oracle Advanced Analytics
Oracle Database
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Oracle R Enterprise
• 开源统计分析编程语言与环境 • 直接在Oracle库对象上的R分析 • 与OracleDB集成以获得扩展性 • 广泛的统计与高级分析函数 • 将R分析迁入到应用或者BI工具 • 探索性数据分析 • 扩展的可视化图形 • 可与Hadoop集成
Oracle Data Mining
• 完整的库内数据挖掘解决方案 • 自动化数据库内的知识发现过程 • 12个内置的核心数据挖掘算法 • 支持基于文本的挖掘-利用非结构化数据 • 利用数据挖掘进行预测分析 • 基于传统与星型模型的数据挖掘 • 利用Exadata卸载数据模型的评分过程 • 全新的图形化ODM GUI环境 • 与OBIEE完美集成
R
Oracle高级分析选件支持企业级挖掘分析 满足不同角色需求,合理的成本投入带来数据收益最大化
常客特征分组 常客流失预测
客户价值分组
产品购买关联
客户价值预测
航线人数预测
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Oracle Advanced Analytics 定位
在数据库中实现高扩展性的R语言
数据准备过程是自动化的
在数据库中,使用高扩展性,分布式并行执行的机器自动学习技术
数据仍然在数据库中
S avings
灵活的接口 – SQL, R, IDE, GUI
快速灵活的分析部署选件
• 价值定位 • 快速从数据到展现转化
• Fastest analytical development • Fastest in-database scoring engine on the planet
• 灵活的分析部署选件 • 通过消除数据重复,实现最低的TCO • 安全,高扩展,高管理性
可以导入第三方模块
Model “Scoring” Embedded Data Prep
Data Preparation
Model Building
Oracle Advanced Analytics
Secs, Mins or Hours
R
Traditional Analytics
Hours, Days or Weeks
Data Extraction
Data Prep & Transformation
Data Mining Model Building
Data Mining Model “Scoring”
Data Preparation and
Transformation
Data Import
Source Data
Dataset s/ Work
Area
Analytic al
Process ing
Process Output
Target
R
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
特性五: 自动优化数据
29
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
简化数据的生命周期
自劢优化数据
• 内存中热图可跟踪对段和块的访问 – 数据定期写到磁盘
– 可通过视图或存储过程访问信息
• 用户可以将策略添加到表,以便根据对数据的访问将数据压缩或分层
– 表或分区可以在压缩级别之间移动,在这个过程中仍然可以访问数据
Po licy 1
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
将压缩策略和分层策略添加到表
自劢优化数据
按时间分区
最旧数据 最新数据
Po licy 1
Po licy 2
如果 30 天内未修改分区中的数据,则使用行压缩 压缩这些分区
如果180天内未修改分区中的数据,则使用混合列压缩压缩这些分区
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
热图可跟踪活动的段和块
自劢优化数据
32
按时间分区
最旧数据 最新数据
Po licy 1
Po licy 2
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
策略自动应用到表
自劢优化数据
按时间分区
最旧数据 最新数据
Po licy 1
Po licy 2
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
策略自动应用到表
自劢优化数据
按时间分区
最旧数据 最新数据
Po licy 1
Po licy 2
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
策略自动应用到表
自劢优化数据
按时间分区
最旧数据 最新数据
Po licy 1
Po licy 2
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
减少存储空间占用,更快读取压缩数据
自劢优化数据
按时间分区
最旧数据 最新数据
Po licy 1
Po licy 2
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
利用自动数据分层降低存储成本
自劢优化数据
按时间分区
最旧数据 最新数据
Po licy 1
Po licy 2
Po licy 3
如果表空间接近填满,则会使用归档混合列压缩将最旧的分区压缩,并将该分区移到第 2 层存储
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
热图(Heat Map) 如何启用
活动的
频繁访问的
偶尔访问的
静止的
SQL> alter system set
heat_map=‘ON’
scope=both;
启用Heat Map
SQL> alter system set
heat_map=‘OFF’
scope=both;
禁用Heat Map
• 最近插入, 积极更新 • OLTP 压缩 (2-4x) • 缓存在DRAM & Flash
• 很少更新, 频繁报表访问 • DW高性能(10x) • 高性能存储
• 很少访问 • DW高压缩(10x) • 低成本存储
• 长期分析和遵守公司政策的保留 • 归档压缩(15-50x) • 归档存储(数据库或磁带)
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
特性六:数据保护
39
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
数据库中断可能导致丢失进行中的工作,使用户和应用程序处于不确定状态
通常导致
用户问题
重复提交
重新启动中间层
开发人员问题
现状 不确定的工作:应对中断
应用
服务器
数据库
服务器
最终用户
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
• 采用重放技术恢复错误
• 屏蔽硬件,软件,网络,存储中断等错误
• 提高终端用户体验
Application Continuity
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
解决应用程序连续性问题
事务防护
可靠的协议和 API,返回最后一次事务的结果
API 提供每个事务的已知提交结果
若无事务防护,重试事务可能导致逻辑损坏
使用事务防护,应用程序可以正确处理错误
支持 JDBC-thin、OCI、OCCI、ODP.net
12.1 中的 XA 除外
可供应用程序连续性功能透明使用
应用程序连续性
在中断和计划操作之后,可以安全地尝试重放进行中的工作
遇可恢复错误时重放进行中的工作
成功时可屏蔽许多硬件、软件、网络、存储错误和中断
提升最终用户体验和生产效率,无需定制应用程序开发
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
特性七:数据安全增强
43
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Data Redaction 实时数据遮蔽
ASO的好处
应用透明
性能影响低
内建密钥管理
降低数据泄密的机会
挑战
加密敏感数据
遮蔽敏感数据
不更改应用
管理简单
ASO的功能
透明数据加密
备份加密
导出加密
实时数据遮蔽 Redaction*
客服中心
工资处理
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Oracle 数据编辑 新的预防性控制
信用卡号 4451-2172-9841-4368
5106-8395-2095-5938
7830-0032-0294-1827
策略
• 基于上下文对敏感数据进行实时编辑
• 对应用程序透明,无需更改代码
• 数据库内实施一致
• 无需更改常规数据库操作
呼叫中心应用程序
信用卡处理
xxxx-xxxx-xxxx-4368
4451-2172-9841-4368
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
权限使用分析 减小受攻击面
• 报告在数据库中使用的实际权限和角色
• 根据需要撤销不必要的权限和角色
• 帮劣执行最小权限并降低风险
权限
分析
Create …
Select …
Update …
DBA 角色
APPADMIN 角色
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
权限分析 使用的系统权限
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
权限分析 要撤销的未使用权限?
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
特性八:事务增强
49
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
• 支持每一个事务可预料的结果
• 支持JDBC-Thin,
C/C++(OCI/OCCI),ODP.Net API
• 可由Application Continuity用于at-
most-once 应用执行
• 可独立于Application Continuity使用
• 如果没有Transaction Guard,重新尝试可能导致逻辑错乱
Transaction Guard(事务防护)
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Transaction Guard(事务防护)
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
特性九:数据脱敏
52
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
基亍数据源的数据脱敏 Maximum Compliance with PCIDSS
数据先复制到中间库,然后进行数据脱敏.
010010110010101001001001001001001001001001001000100101010010010010011100100100100100100100001001001011100100101010010010101010011010100101010010
Production Test
Clone-and-Mask
Before
敏感数据在生产库端脱敏,然后再Pump到测试库.
010010110010101001001001001001001001001001001000100101010010010010011100100100100100100100001001001011100100101010010010101010011010100101010010
At-Source-Masking
Masked Data Pump File
Production Test
NEW
Consolidation
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
部署方式
Production Perimeter
Production (Financials)
Dev’t
Test
Clone
Staging (Financials)
Production (Financials)
Dev’t
Test
Export & Mask
• (+) 对生产库最小化影响
• (-) 需要建立单独的中间库
(+) 无需中间库
(-) 对生产库有一定性能影响
Data Pump File
“At-Source Masking”
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
特性十:大数据增强
55
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Oracle In-Database MapReduce
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Oracle In-Database MapReduce
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Oracle In-Database MapReduce
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | 59
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