SlideShare ist ein Scribd-Unternehmen logo
1 von 67
Downloaden Sie, um offline zu lesen
Exadata and Database Machine Overview

金江 @Channel Sales Consultant
jenkin.jin@oracle.com 13701864820
26-Jan-2010
革命性产品 - Exadata
• Exadata存储服务器和数据库一体机

• V1比普通数据仓库性能快10到100倍 ;V2再次加速并创造TCP-C新世界纪录

• 最优异的扩展性,容量,带宽和处理能力
Agenda议程

             • Overview

             • Exadata Based Product Offerings

             • Exadata Architecture and Features

             • Best Data Warehousing Machine

             • Best OLTP Machine

             • Best Consolidation Machine



Copyright © 2009, Oracle Corporation and/or its affiliates   – 3–
产品推出
                Exadata Storage Server & Database Machine

• Exadata Storage Server                                     • Sun Oracle Database Machine
       – 专为Oracle数据库优化的存储产品                                    – 预配好的高性能
       – 极限 I/O 和 SQL 处理性能                                     – 平稳的性能配置
       – 硬件和软件的组合                                              – 在构建Oracle部署过程中远离不定
• Exadata Storage Server Software                                因素
                                                             • Exadata Storage Server Software
                                                             • Oracle Database 11.2




Copyright © 2009, Oracle Corporation and/or its affiliates                                 – 4–
挑战 – 诸多瓶颈




                             • 目前由于存储引起数据库性能的情况较多
                                     –    存储系统限制了从存储到服务器的数据带宽
                                     –    存储阵列内部瓶颈
                                     –    SAN的瓶颈
                                     –    由于物理磁盘速度引起的随机I/O瓶颈
                             • 数据带宽严重限制了数据仓库的性能
                             • 随机 I/O 瓶颈限制了OLTP应用的性能

Copyright © 2009, Oracle Corporation and/or its affiliates      – 5–
Exadata Storage Server
               数据带宽瓶颈解决方案




                                     • 增加更多信道
                                     • 增宽信道
                                     • 通过信道传送较少数据

Copyright © 2009, Oracle Corporation and/or its affiliates   – 6–
Exadata Smart Storage
               打破数据带宽和随机I/O 的瓶颈

                                                                   Exadata Storage Cells
   • Oracle 解决数据带宽瓶颈三种手段                                                存储单元
          – 大量的并行存储网格 of high performance Exadata
            storage servers (cells).
             • Data bandwidth scales with data volume
          – 数据密集处理 runs in Exadata storage.
             • Queries run in storage as data streams from disk,
                offloading database server CPUs
          – 列压缩减少数据容量 up to 10x
             • Exadata Hybrid Columnar Compression provides 10x
                lower cost, 10x higher performance


   • 利用Exadata智能闪存缓冲卡来解决随机I/O瓶颈
          – Increase random I/Os by factor of 20X




Copyright © 2009, Oracle Corporation and/or its affiliates                          – 7–
<Insert Picture Here>


            Exadata Based Product Offerings




Copyright © 2009, Oracle Corporation and/or its affiliates                  – 8–
Sun Oracle Database Machine
     • 网格是未来架构
            • Highest performance, lowest cost, redundant, incrementally scalable
     • Exadata数据库机是完全满足所有数据管理需求的第一款全面的网格架构




   RAC Database Server Grid
   • 8 High-performance low-cost                             Exadata Storage Server Grid
     compute servers
                                                             • 14 High-performance low-cost
   • 2 Intel quad-core Xeons each                              storage servers
                                                             • 100 TB raw SAS disk storage
   InfiniBand Network                                                       or
   • 40 Gb/sec fault-tolerant unified                           336 TB raw SATA disk storage
     server and storage network                              • 5TB+ flash storage!




Copyright © 2009, Oracle Corporation and/or its affiliates                                 – 9–
Sun Oracle Database Machine

                                                             性能提高到极致


  RAC Database Server Grid
  • Millions of transactions                                      Exadata Storage Server Grid
    per minute
                                                                  • 21 GB/sec disk bandwidth
  • Tens of millions of queries
                                                                  • 50 GB/sec flash bandwidth
    per minute
                                                                  • 1 million I/Os per second
  • Billions of rows per minute


  InfiniBand Network
  • 880 Gb/sec aggregate throughput




Copyright © 2009, Oracle Corporation and/or its affiliates                                      – 10 –
可扩展的性能和容量




     • 扩展性                                                   • 冗余和容错
            – Scales to 8 rack database machine               – Failure of any component is tolerated
              by just adding wires
                                                              – Data is mirrored across storage
               • More with external InfiniBand switches
                                                                servers
            – Scales to hundreds of storage servers
               • Multi-petabyte databases




Copyright © 2009, Oracle Corporation and/or its affiliates                                      – 11 –
大大简化部署


                                                             • 数据库机消除了部署数据库系统的复杂性
                                                              – Months of configuration, troubleshooting, tuning


                                                             • 数据库机当天即用
                                                              – Pre-built, tested, standard, supportable configuration
                                                              – Runs existing applications unchanged



                                                             • 即用的极致性能

                  数月到数天




Copyright © 2009, Oracle Corporation and/or its affiliates                                                               – 12 –
Sun Exadata Storage Server Hardware
         Sun Exadata Storage                                 • 大量Exadata并行且网格化的存储块
           Server Hardware                                      – Up to 1.5 GB/sec raw data bandwidth per cell
                                                                – Up to 75,000 IOPS with Flash
                                                             • Sun Fire™ X4275 服务器
                                                                – 2 Quad-Core Intel® Xeon® E5540 Processors
                                                                – 24GB RAM
                                                                – Dual-port 4X QDR (40Gb/s) InfiniBand card
                                                                – Disk Options
                  硬件提供商                                            • 12 x 600 GB SAS disks (7.2 TB total)
                                                                   • 12 x 2TB SATA disks (24 TB total)
                                                                – 4 x 96 GB Sun Flash PCIe Cards (384 GB total)
                                                             • 预装软件
                                                                – Oracle Exadata Storage Server Software
                                                                – Oracle Enterprise Linux
                                                                – Drivers, Utilities
                  软件提供商                                      • Oracle统一提供支持
                                                                – 3 year, 24 x 7, 4 Hr On-site response




Copyright © 2009, Oracle Corporation and/or its affiliates                                                        – 13 –
Sun Exadata Storage Server Hardware

            Dual-redundant, hot-
                                                              24 GB DRAM
          swappable power supplies



          ILOM

 Disk Controller
 HBA with 512M                                                                              12 x 3.5” Disk Drives
 battery backed
 cache


                                                                                               2 Quad-Core Intel®
                                                                                               Xeon® Processors


                                                                           预装软件:
   InfiniBand QDR                                                            • Oracle Exadata Storage Server Software
   (40Gb/s) dual
                                                   4 x 96GB Sun
   port card                                                                 • Oracle Enterprise Linux
                                                   Flash PCIe
                                                   Cards                     • Drivers


Copyright © 2009, Oracle Corporation and/or its affiliates                                                          – 14 –
Sun Oracle Database Machine Full Rack
                Pre-Configured for Extreme Performance

          • 8 Sun Fire™ X4170 Oracle Database servers
          • 14 Exadata Storage Servers (All SAS or all SATA)
          • 3 Sun Datacenter InfiniBand Switch 36
                 – 36-port Managed QDR (40Gb/s) switch
          •    1 “Admin” Cisco Ethernet switch
          •    Keyboard, Video, Mouse (KVM) hardware
          •    Redundant Power Distributions Units (PDUs)
          •    Single Point of Support from Oracle
                – 3 year, 24 x 7, 4 Hr On-site response




                                 Add more racks for additional scalability

Copyright © 2009, Oracle Corporation and/or its affiliates                   – 15 –
Sun Oracle Database Machine Half Rack
                 Pre-Configured for Extreme Performance

         • 4 Sun Fire™ X4170 Oracle Database servers
         • 7 Exadata Storage Servers (All SAS or all
           SATA)
         • 2 Sun Datacenter InfiniBand Switch 36
                 – 36-port Managed QDR (40Gb/s) switch
         •    1 “Admin” Cisco Ethernet switch
         •    Keyboard, Video, Mouse (KVM) hardware
         •    Redundant PDUs
         •    Single Point of Support from Oracle
               – 3 year, 24 x 7, 4 Hr On-site response




                                                      Can Upgrade to a Full Rack

Copyright © 2009, Oracle Corporation and/or its affiliates                         – 16 –
Sun Oracle Database Machine Quarter Rack
                Pre-Configured for Extreme Performance

         • 2 Sun Fire™ X4170 Oracle Database servers
         • 3 Exadata Storage Servers (All SAS or all
           SATA)
         • 2 Sun Datacenter InfiniBand Switch 36
            – 36-port Managed QDR (40Gb/s)
              InfiniBand switch
         • 1 “Admin” Cisco Ethernet switch
         • Keyboard, Video, Mouse (KVM) hardware
         • Redundant PDUs
         • Single Point of Support from Oracle
            – 3 year, 24 x 7, 4 Hr On-site response


                                                   Can Upgrade to an Half Rack

Copyright © 2009, Oracle Corporation and/or its affiliates                       – 17 –
Sun Oracle Database Machine Basic System
              Entry Level non-HA Configuration

         • 1 Sun Fire™ X4170 Oracle Database servers
         • 1 Exadata Storage Servers (All SAS or all
           SATA)
         • 1 Sun Datacenter InfiniBand Switch 36
            – 36-port Managed QDR (40Gb/s) InfiniBand
               switch
         • InfiniBand Cables
         • Installed in Customer supplied Rack
         • Customer supplied Ethernet and KVM
           Infrastructure
         • Single Point of Support from Oracle
            – 3 year, 24 x 7, 4 Hr On-site response



Copyright © 2009, Oracle Corporation and/or its affiliates   – 18 –
Standalone Exadata Storage Servers


      • Purchase Exadata Storage Servers from Oracle
              – Customer supplied standard 19 inch rack
      • Customer supplied x86 64-bit Linux Database
        Servers
      • Hardware installation more complex
      • No single point of support for entire deployment




Copyright © 2009, Oracle Corporation and/or its affiliates   – 19 –
Exadata 产品的容量




                                                             Single Server   Quarter Rack   Half Rack        Full Rack

                                           SAS                  7.2 TB          21 TB        50 TB             100 TB
          Raw        Disk1
                                           SATA                 24 TB           72 TB        168 TB            336 TB

          Raw Flash1                                           384 GB           1.1 TB       2.6 TB            5.3 TB

          User Data2                       SAS                   2 TB           6 TB         14 TB             28 TB
          (assuming no
          compression)                     SATA                  7 TB           21 TB        50 TB             100 TB


           1 – Raw capacity calculated using 1 GB = 1000 x 1000 x 1000 bytes and 1 TB = 1000 x 1000 x 1000 x 1000 bytes.
           2 - User Data: Actual space for end-user data, computed after single mirroring (ASM normal redundancy) and after
           allowing space for database structures such as temp, logs, undo, and indexes. Actual user data capacity varies by
           application. User Data capacity calculated using 1 TB = 1024 * 1024 * 1024 * 1024 bytes.



Copyright © 2009, Oracle Corporation and/or its affiliates                                                                 – 20 –
Exadata 产品的性能


                                                             Single Server   Quarter Rack   Half Rack          Full Rack

      Raw Disk Data                                  SAS       1.5 GB/s        4.5 GB/s     10.5 GB/s          21 GB/s
      Bandwidth1,4                                   SATA     0.85 GB/s        2.5 GB/s      6 GB/s            12 GB/s

      Raw Flash Data Bandwidth1,4                              3.6 GB/s        11 GB/s      25 GB/s            50 GB/s

      Max User Data Bandwidth2,4
      (10x compression & Flash)
                                                               36 GB/s        110 GB/s      250 GB/s           500 GB/s

                                                     SAS        3,600          10,800        25,000             50,000
      Disk IOPS3,4
                                                     SATA       1,440           4,300        10,000             20,000
      Flash IOPS3,4                                             75,000         225,000      500,000            1,000,000
      Data Load Rate4                                         0.65 TB/hr       1 TB/hr      2.5 TB/hr           5 TB/hr
             1 – Bandwidth is peak physical disk scan bandwidth, assuming no compression.
             2 - Max User Data Bandwidth assumes scanned data is compressed by factor of 10 and is on Flash.
             3 – IOPs – Based on IO requests of size 8K
             4 - Actual performance will vary by application.


Copyright © 2009, Oracle Corporation and/or its affiliates                                                            – 21 –
<Insert Picture Here>


            Exadata Architecture and Features




Copyright © 2009, Oracle Corporation and/or its affiliates                 – 22 –
Exadata的配置
                                       Single-Instance Database             RAC Database




                                                             InfiniBand Switch/Network


                                                 Exadata Cell   Exadata Cell         Exadata Cell




      • 每个Exadata 单元是拥有磁盘存储且运行Exadata软件的自我控制服务器

      • Oracle数据库跨越不同Exadata单元进行部署

      • Oracle数据库与Exadata存储服务器之间增强协作

      • 在网格架构内没有实际的Exadata单元的限制

Copyright © 2009, Oracle Corporation and/or its affiliates                                          – 23 –
Exadata的架构

                        Single-Instance                                 RAC
                           Database                                   Database
                          DB Server                           DB Server      DB Server
                           DB Instance                        DB Instance         DB Instance           Enterprise
                                 DBRM                               DBRM                DBRM             Manager

                              ASM                                ASM                 ASM

                                                                                                iDB Protocol over
                                                      InfiniBand Switch/Network                   InfiniBand with
                                                                                                   Path Failover

                                    OEL                          OEL                 OEL
                         CELLSRV   MS                        CELLSRV MS       CELLSRV MS                   Cell
                           IORM    RS                        IORM    RS       IORM    RS                  Control
                                                                                                           CLI
                           Exadata Cell                      Exadata Cell     Exadata Cell


                                           …                           …                …




Copyright © 2009, Oracle Corporation and/or its affiliates                                                           – 24 –
Exadata软件的特性
        • Exadata Smart Scans 智能扫描
                – 10X or greater reduction in data sent to database servers
        • Exadata Storage Indexes 存储索引
                – Eliminate unnecessary I/Os to disk
        • Hybrid Columnar Compression (HCC) 混合列压缩
                – Efficient compression increases effective storage capacity and increases
                  user data scan bandwidths by a factor of 10X
        • Exadata Smart Flash Cache 智能闪存缓存
                – Breaks random I/O bottleneck by increasing IOPs by 20X
                – Doubles user data scan bandwidths
        • I/O Resource Manager (IORM) 资源管理
                – Enables storage grid by prioritizing I/Os to ensure predictable performance
        • Inter-leaved Grid Disks 交错网格硬盘
                – Enables storage grid that allows multiple applications to place frequently
                  accessed data on faster portions of the disk



Copyright © 2009, Oracle Corporation and/or its affiliates                                     – 25 –
Exadata Smart Scan 智能扫描

          • Exadata 存储单元通过扫描卸载大大减少了传送到
            数据库服务器的数据
          –            Row filtering based on “where” predicate
          –            Column filtering
          –            Join filtering
          –            Incremental backup filtering
     11.2
          –            Scans on encrypted data
     11.2 –            Data Mining model scoring


          • 正常情况下减少10x 数据量

          • 完全应用透明
                  – Even if cell or disk fails during a query



Copyright © 2009, Oracle Corporation and/or its affiliates        – 26 –
传统的扫描过程

       
                                                                    
                                                                                   • 智能扫描举例:
     SELECT
                                                               Rows Returned          – 寻找消费超过$200手机用户
 customer_name
   FROM calls                                                                         – 用户信息仅占用1T表中的
WHERE amount >                                                                          2M空间
      200;
                                                                                     • 传统存储情况下,所有的数据
                                                                 DB Host reduces        库智能操作都在数据库节点中
                                                             terabyte of data to 1000 完成
           
                                                              customer names that
         Table
                                                               are returned to client
        Extents                                                                    • 来源于存储的数据被数据库主
       Identified                                                                    机大部分所丢弃

                                                                                   • 大量的废弃数据占用了宝贵的
                                                                                   数据库主机资源,严重影响任
     I/Os Issued                                               I/Os Executed:        务执行
                                                              1 terabyte of data
                                                              returned to hosts



Copyright © 2009, Oracle Corporation and/or its affiliates                                         – 27 –
Exadata 智能扫描过程
         
       SELECT
   customer_name                                                                 • 仅关心相关列
     FROM calls                                               Rows Returned        – customer_name
  WHERE amount >                                                                   and required rows
        200;
                                                                                   – where amount>200
                                                                                   are are returned to hosts
                                                                     
                                                              Consolidated       • 条件评估消耗的CPU 可卸载到
    Smart Scan                                                  Result Set          Exadata
  Constructed And                                              Built From All
   Sent To Cells                                                    Cells
                                                                                  • 从数据库节点上移除扫描进程已
                                                                                    获得更多可用CPU资源,消除大
                                                                                    量无价值消息
         
     Smart Scan                                                                    – Returns the needle, not the entire
                                                                                    hay stack
identifies rows and
                                                                2MB of data
  columns within
                                                             returned to server
 terabyte table that
   match request

Copyright © 2009, Oracle Corporation and/or its affiliates                                                      – 28 –
智能扫描的透明特性
                                            • 对应用完全透明
                                                   – No application or SQL changes required
                                                   – Returned data is fully consistent and transactional
                                                   – If a cell dies during a smart scan, the uncompleted portions
                                                     of the smart scan are transparently routed to other cells
                                                     containing a replica of the data

                                            • 能正常处理复杂的场景包括
                                                   –    Uncommitted data and locked rows
                                                   –    Chained rows
                                                   –    Compressed tables
                                                   –    National Language Processing
                                                   –    Date arithmetic
                                                   –    Regular expression searches
                                                   –    Partitioned tables

                                                             高吞吐量, 低开销, 无需复杂优化

Copyright © 2009, Oracle Corporation and/or its affiliates                                                    – 29 –
Exadata Smart Scans:
                                                                           11.2
               卸载data mining scoring


        • Data mining scoring executed in Exadata:

          select cust_id
          from customers
          where region = ‘US’                                        Scoring function
          and prediction_probability(churnmod, ‘Y’ using *) > 0.8;     executed in
                                                                        Exadata


        • All data mining scoring functions offloaded to Exadata
        • Up to 10x performance gains
        • Reduced CPU utilization on Database Server




Copyright © 2009, Oracle Corporation and/or its affiliates                      – 30 –
Exadata Storage Index 存储索引                                                                        11.2
                无成本的透明消除I/O

        Table                            Index               • Exadata Storage Indexes maintain summary
    A B C D                                                    information about table data in memory
                                                               – Store MIN and MAX values of columns
             1                                                 – Typically one index entry for every MB of disk
                                          Min B = 1
             3
                                          Max B =5 • Eliminates disk I/Os if MIN and MAX can never
             5                                       match “where” clause of a query
             5
             8                             Min B = 3 • Completely automatic and transparent
                                           Max B =8
             3


                     Select * from Table where B<2 - 只有第一个集合能匹配


Copyright © 2009, Oracle Corporation and/or its affiliates                                                          – 31 –
Exadata Hybrid Columnar Compression
                混合列压缩
                                                                     11.2
        • 数据在列级存储然后再压缩

        • 查询模式 针对数据仓库
                – Optimized for speed
                – 10X compression ratio is typical           Up To


                                                             50X
                – Scans improve proportionally

        • 归档模式 针对不常查询的数据
                – Optimized to reduce space
                – 15X compression is typical
                – Up to 50X for some data




Copyright © 2009, Oracle Corporation and/or its affiliates             – 32 –
Exadata Hybrid Columnar Compression
              如何工作
          Compression
             Unit                                            • Tables are organized into sets of a few thousand
                                                               rows called Compression Units (CUs)

                                                             • Within Compression Unit, data is Organized by
                                                               Column and then compressed
                                                                – Column organization brings similar values close
                                                                  together, enhancing compression
              Reduces
             Table Size
            4x to 50x                                        • Useful for data that is bulk loaded and queried
              4x to 40x
            Reduction                                           – Update activity is light




Copyright © 2009, Oracle Corporation and/or its affiliates                                                          – 33 –
Exadata Hybrid Columnar Compression
                数据仓库型和归档型


             Warehouse Compression                                   Archive Compression
                                     针对速度优化                                 针对空间优化
         • 10x average storage savings                             • 15x average storage savings
         • 10x Scan I/O reduction                                     – Up to 50x on some data
                                                                   • Some access overhead
                                                                   • For cold or historical data


                        Smaller Warehouse                             Reclaim 93% of Disks
                        Faster Performance                             Keep Data Online

                                         Can mix compression types by partition for ILM

Copyright © 2009, Oracle Corporation and/or its affiliates                                         – 34 –
真实场景中的压缩比
                                       Oracle Production E-Business Suite Tables
                                                                                                                    52
                                      50   OLTP Compression (avg=3.3)
                                                                                                               43
     Size Reduction Factor by Table




                                      45   Query Compression (avg=14.6)
                                      40   Archive Compression (avg=22.6)
                                      35                                                                  29
                                      30
                                      25                                         19   19   19   20   21
                                      20                                    16
                                      15       10     10      10     11
                                      10
                                       5
                                       0




                                                    • Columnar compression ratios
                                                       • Query = 14.6X
                                                       • Archive = 22.6X
                                                       • Vary by application and table

Copyright © 2009, Oracle Corporation and/or its affiliates                                                          – 35 –
磁盘随机 I/O 瓶颈

          300 I/O per Sec                                    • 磁盘存放海量数据
                                                              – But are limited to about 300 I/Os per second


                                                             • 闪存技术存放较少数据
                                                              – But can run tens of thousands of I/Os
                                                                per second


                                                             • 理想的解决方式
                                                              – Keep most data on disk for low cost
     10000X I/O’s per Sec                                     – Transparently move hot data to flash
                                                              – Use flash cards instead of flash disks to avoid disk
                                                                controller limitations
                                                              – Flash cards in Exadata storage
                                                                 • High bandwidth, low latency interconnect




Copyright © 2009, Oracle Corporation and/or its affiliates                                                         – 36 –
Exadata Smart Flash Cache
                智能闪存缓存
                                                                          11.2
       • 在4快Flash卡中透明的缓存热数据


       • 使用基于快捷PCI的Flash卡来获得更大的吞吐
         量和IOPs,并规避磁盘控制器的限制


       • 智能缓存
         – Smarter than basic LRU algorithm
         – Knows when to skip caching objects to             4 x 96 GB Flash Cards
           avoid polluting or flushing the cache

       • 允许应用显式优化缓存



Copyright © 2009, Oracle Corporation and/or its affiliates                       – 37 –
Flash Cache对SGA的透明扩展
             4. User Process                                           Extended Buffer Cache
                  reads blocks
                    from SGA
                  (copied from
                 Flash Cache if
                   not in SGA)

                       Hot Data                                                                          Warm Data
                                         16 GB                                                     120 GB
                                       SGA Memory                            3. Clean blocks    Flash Cache
                                                                                 moved to
                                                                                Flash Cache
                                                                                  based on
                                                                                    LRU*

                                                    1. Blocks read 2. Dirty blocks flushed to
                                                         into buffer           disk
                                                           cache




                     Cold Data                                                                  * Headers for Flash
                                           360 GB
                                        Magnetic Disks                                          Cached blocks kept in
                                                                                                        SGA




Copyright © 2009, Oracle Corporation and/or its affiliates                                                              – 38 –
Exadata I/O Resource Management
               混合工作负载环境

        • 传统存储环境中,同数据库中的用户或共享子存储的多个数据库由于应
          用处理无法平衡,从而束缚了共享存储的创建和管理
                – Hardware isolation is the approach to ensure separation

        • Exadata I/O 资源管理确保一个数据库内的不同用户和任务可分配相对合
          理的 I/O 资源

        • 举例:
                – Interactive: 50% of I/O resources                                          Database
                                                                                              Server
                – Reporting: 30% of I/O resources
                – ETL: 20% of I/O resources
                                                                        InfiniBand Switch/Network


                                                             Exadata Cell   Exadata Cell        Exadata Cell




Copyright © 2009, Oracle Corporation and/or its affiliates                                              – 39 –
Exadata I/O Resource Management
                多个数据库环境

         • 确保不同的数据库可分配相对合理的I/O 带宽
                 – Database A: 33% I/O resources
                 – Database B: 67% I/O resources

         • 确保一个数据库内不同的用户和任务可分配相对合理的I/O 带宽
                 – Database A:
                    • Reporting: 60% of I/O resources
                                                                Database A          Database B
                    • ETL: 40% of I/O resources
                 – Database B:
                    • Interactive: 30% of I/O resources
                    • Batch: 70% of I/O resources                       InfiniBand Switch/Network


                                                             Exadata Cell   Exadata Cell        Exadata Cell




Copyright © 2009, Oracle Corporation and/or its affiliates                                            – 40 –
Exadata 可扩展的存储网格
      • 使用Automatic Storage Management实现动态虚拟化存储
              – Simple and non-intrusive resource allocation, and reallocation, enabling true
                enterprise grid storage
              – Database work spread across storage resources for optimal performance


      • 强大的存储分配手段和管理机制
              – Flexible configuration for performance and availability



             Single-Instance Database                                                                   RAC Database


                                                                      InfiniBand Switch/Network


                                                       Exadata Cell       Exadata Cell            Exadata Cell




Copyright © 2009, Oracle Corporation and/or its affiliates                                                             – 41 –
Exadata 存储层级

           • Physical disks map to Cell Disks
           • Cell Disks partitioned into one or multiple Grid Disks
           • Grid Disks created in order of “hottest” first to “coldest” portion of the
             disk last
           • ASM diskgroups created from Grid Disks
           • Transparent above the ASM layer



                                                                                      ASM disk
                                                                        Grid Disk 1
                                                              Cell
                     Physical                                              …
                      Disk                                    Disk
                                                                                      ASM disk
                                                                        Grid Disk n
                                                             Sys Area    Sys Area




Copyright © 2009, Oracle Corporation and/or its affiliates                                   – 42 –
Exadata 存储层级示例
                ASM 镜像和容错设计



     ASM                                                                                           ASM
Failure Group                                Exadata Cell                      Exadata Cell   Failure Group


                             Hot                     Hot         Hot    Hot       Hot           Hot

                            Cold                    Cold     …   Cold   Cold     Cold     …     Cold


       • Example shows cell disks divided into two grid disks               ASM
             – hot and cold                                              Disk Group
       •    Two ASM disk groups created across the two sets of grid disks
       •    ASM striping evenly distributes I/O across the disk groups
       •    ASM mirroring is used to protect against disk failures
       •    ASM failure groups are used to protect against cell failures

Copyright © 2009, Oracle Corporation and/or its affiliates                                             – 43 –
Interleaved Grid Disks                                         11.2
                交错网格硬盘
                                                                Grid Disk 1
                                                              Hot Data, Cold Data

          • Grid disks are optionally split and interleaved
            to place frequently accessed data in all grid
            disks on higher performing outer tracks

          • All applications benefit from higher
            performance outer tracks of disks




                                                                Grid Disk 2
                                                              Hot Data, Cold Data


Copyright © 2009, Oracle Corporation and/or its affiliates                          – 44 –
Exadata 存储的管理

          • Enterprise Manager
                 – Manage & administer Database and ASM
          • Exadata Storage Plug-in ( > 10.2.0.3)
                 – Enterprise Manager Grid Control Plug-in to monitor & manage
                   Exadata Storage Cells
          • Comprehensive CLI
                 – Local Exadata Storage cell management
                 – Distributed shell utility to execute CLI across multiple cells
          • Sun Embedded Integrated Lights Out Manager (ILOM)
                 – Remote management and administration of hardware




Copyright © 2009, Oracle Corporation and/or its affiliates                          – 45 –
数据保护的有效手段
 • All single points of failure eliminated by the Exadata Storage architecture
 • Hardware Assisted Resilient Data (HARD) built in to Exadata Storage
               – Prevent data corruption before it happens
 • Data Guard provides disaster protection and data corruption protection
               – Automatically maintains one or more copies of the database
 • Flashback provides human error protection
               – Snapshot-like capabilities to rewind database to before error
 • Recovery Manager (RMAN) provides backup to disk
               – Archiving and corruption protection
               – Can be used with Oracle Secure Backup (OSB) or third party tape
                 backup software
 • These work just as they do for traditional non-Exadata storage
               – Users and database administrator use familiar tools




Copyright © 2009, Oracle Corporation and/or its affiliates                         – 46 –
Exadata 共存与迁移

          • 数据库可并存部署在Exadata和传统存储上
                  – Tablespaces can exist on Exadata storage, traditional torage, or a combination of the
                    two, and is transparent to database applications
                  – SQL offload processing requires all pieces of a tablespace reside on Exadata


          • 如果当前使用ASM及ASM冗余可以在线迁移
                                                                                           Database
          • 可使用RMAN或Data Guard来完成迁移                                                         Server




                                                                      Exadata             Non-Exadata




                                                                          Online Migration

Copyright © 2009, Oracle Corporation and/or its affiliates                                            – 47 –
<Insert Picture Here>


            Best Data Warehouse Machine




Copyright © 2009, Oracle Corporation and/or its affiliates                 – 48 –
Best Data Warehouse Machine

                                                             • 大量高容量的硬件并行加速处理海量数据
                                                              – Exadata runs data intensive processing
                                      OLAP                      directly in storage


                                                             • 最全面的分析能力
                                                              – OLAP, Statistics, Spatial, Data Mining, Real-time
                                                                transactional ETL, Efficient point queries

                                        ETL
                                                             • 强大的数据仓库特别优化手段
                                                              – Flexible Partitioning, Bitmap Indexing, Join indexing,
                                                                Materialized Views, Result Cache


                             Data Mining
                                                             • 卓越的新数据仓库功能
                                          New



Copyright © 2009, Oracle Corporation and/or its affiliates                                                          – 49 –
Exadata 存储特性

        • Exadata 智能扫描
                – 10X or greater reduction in data sent to database servers


        • Exadata 存储索引
                – Eliminate unnecessary I/Os to disk


        • Hybrid Columnar Compression 混合列压缩
                – Efficient compression increases user data scan rates


        • Exadata 闪存
                – Combined with Hybrid Columnar Compression, scan rate
                  is 20X more




Copyright © 2009, Oracle Corporation and/or its affiliates                    – 50 –
内存中并行执行

     SQL                             确定所查询表的大小                      如果表非常适用于   将表的各部分读到每个
     语句                                                              内存中并行执行   节点的缓冲区缓存中




                                                             表非常大
                 表非常小



                                                                                只有同一RAC 节点
                                  读到任意节点的                                       上的并行服务器可
                                                                                 以访问每个部分
                                  缓冲区缓存中                            直接从磁盘读取



Copyright © 2009, Oracle Corporation and/or its affiliates                              – 51 –
内存中并行执行                                                                                                                                         11.2


                                                                              • 单个数据库一体机拥有400GB的可缓存内存
                      QphH: 1 TB TPC-H

                                                         1,166,976

                                1,018,321                                     • 数据库版本11.2 引入了对内存缓冲数据的并
                                                                                行查询处理
                                                                                    – Harnesses memory capacity of entire database
                                                                                      cluster for queries
                                                                                    – Foundation for world record 1TB TPC-H

         315,842
                                                                              • Exadata混合列压缩实现了将多个T级表或分
                                                                                区缓存在内存中

        ParAccel                  Exasol              Oracle & HP
                                                       Exadata
                                                                                      Memory has 100x more bandwidth than Disk
        比特定的内存数据仓库还快


                                                             Source: Transaction Processing Council, as of 9/14/2009:
                                                             Oracle on HP Bladesystem c-Class 128P RAC, 1,166,976 QphH@1000GB, $5.42/QphH@1000GB, available 12/1/09.
Copyright © 2009, Oracle Corporation and/or its affiliates   Exasol on PRIMERGY RX300 S4, 1,018,321 QphH@1000GB, $1.18/QphH@1000GB, available 08/01/08.                – 52 –
                                                             ParAccel on SunFire X4100 315,842 QphH@1000GB, $4.57 /QphH@1000GB, available 10/29/07.
大型扫描获得多级收益




           10 TB 用户数据需要                                       1 TB     100 GB
               10 TB 的IO                                      压缩       分区裁剪


                                                                       亚秒级
                                                                     On Database
                                                                      Machine
                         20 GB                                5 GB
                        存储索引                                 智能扫描


                                                  数据减少10倍,扫描加快2000倍

Copyright © 2009, Oracle Corporation and/or its affiliates                         – 53 –
DBFS – 可扩展共享的文件系统
                                                                                                   11.2
           • Database Machine comes with DBFS shared Linux file system
                  – Shared storage for ETL staging, scripts, reports and other application files

           • Files stored as SecureFile LOBs in database tables stored in Exadata
                  – Protected like any DB data – mirroring, DataGuard, Flashback, etc.

           • 5 to 7 GB/sec file system I/O throughput


                                                             使用外部表来加载数据


                ETL Files in DBFS                                                    ETL

                                                        比高端NAS文件系统更高的吞吐量


Copyright © 2009, Oracle Corporation and/or its affiliates                                          – 54 –
<Insert Picture Here>


            Best OLTP Machine




Copyright © 2009, Oracle Corporation and/or its affiliates                 – 55 –
Best OLTP Machine


                                                             • 仅Oracle能运行“基于网格”的真实商业应用

                                                             • 特有的可容错可扩展 OLTP 数据库
                                                              – RAC, Data Guard, Online Operations


                                                             • 特有的可容错可扩展,适配OLTP的存储
                                                              – ASM, Exadata


                                                             • 卓越的新 OLTP 能力




Copyright © 2009, Oracle Corporation and/or its affiliates                                           – 56 –
Exadata Flash                                                                     11.2
                解决随机I/O瓶颈

                                                             •Sun Oracle 数据库一体机拥有5+TB
                                                             闪存存储
                                                             •Exadata Smart Cache 缓存热点数据
                                                             •数据库一体机能实现:
                                                               – 20x more random I/Os
                                                                   • Over 1 million per second
                                                               – 2x faster sequential query I/O
                                                                   • 50 GB/sec
                                                               – 10x better I/O response time
                                                                   •Sub-millisecond
                                                               – Greatly Reduced Cost
         第一款实现闪存优化的                                                • 10x fewer disks for IOPS
            数据库
                                                                   • Lower Power

Copyright © 2009, Oracle Corporation and/or its affiliates                                          – 57 –
Complete, Open, Integrated Availability
              Maximum Availability Architecture最大可用性架构

                  Real                                                                                Active
               Application                                                                          Data Guard
                Clusters



           ASM
                                                                                   WAN
            Fast                                             Secure
                                                             Backup
        Recovery Area


          • Protection from                                  • Real-time remote standby open for queries
                  –    Server Failures                       • Human error correction
                  –    Storage Failures                         – Database, table, row, transaction level
                  –    Network Failures                      • Online indexing and table redefinition
                  –    Site Failures                         • Online patching and upgrades


Copyright © 2009, Oracle Corporation and/or its affiliates                                                       – 58 –
Complete, Open, Integrated Security

            监控                                               Audit
                                      Configuration          Vault    Total
                                      Management                      Recall

            访问控制

                                      Database                        Label
                                      Vault                           Security

             加密和屏蔽


                                      Advanced                        Data
                                                             Secure
                                      Security                        Masking
                                                             Backup


Copyright © 2009, Oracle Corporation and/or its affiliates                       – 59 –
<Insert Picture Here>


            Best Consolidation Machine




Copyright © 2009, Oracle Corporation and/or its affiliates                 – 60 –
整合架构

                                                                      ERP
                                                                      CRM

                                             ERP                       CRM
                                                                   Warehouse              HR


                                                                    Data Mart
                                                             Warehouse HR     Data Mart


              • 融合到数据库一体机
                     –     High performance for all applications
                     –     Low cost platform for all applications
                     –     Predictable response times in a shared environment
                     –     Handles all data management needs
                     –     Complete, Open, Integrated


Copyright © 2009, Oracle Corporation and/or its affiliates                                     – 61 –
Consolidate Storage
                                                             • Exadata和ASM可跨多个数据库共享所有的存储
                                                               服务器

                                                             • 配置共享
                      ERP
                                                              – Advanced data striping spreads every database
                                                                across all storage servers
                     CRM
                                                              – Eliminates hot-spots and captive unused space
                                                              – Full storage grid performance available to all
             Warehouse                                          databases
                                                              – Database or cluster level storage security
               Data Mart
                                                             • 可预测性能
                       HR
                                                              – Exadata I/O resource manager prioritizes I/Os to
                                                                ensure predictable performance
                                                                   • At user, job, application, or database level
                                                              – No need for isolated storage islands


Copyright © 2009, Oracle Corporation and/or its affiliates                                                          – 62 –
Consolidate Servers

                                                             • 多个数据库可运行在多个数据库一体机上


          ERP
                                                             • 配置共享
                                  CRM                         – Applications connect to a database service that
                                                                runs on one or more database nodes
                                                                 • Services can grow, shrink, & move dynamically
              Warehouse                                       – Large databases can span nodes using RAC
                                                              – Multiple small databases can run on a single node

                                                             • 可预测性能
           HR                    Data
                                                              – Instance caging provides predictable CPU
                                  Mart                          resources when multiple databases run on the
                                                                same node
                                                                 • Restricts a database to subset of processors




Copyright © 2009, Oracle Corporation and/or its affiliates                                                        – 63 –
Best Consolidation Machine


                                                             • 在单一系统里整合不同工作负载
                                                              – Warehouse oriented bulk data processing
                      ERP                                     – OLTP oriented random updates
                                                              – Multimedia oriented streaming files
                     CRM
                                                             • Sun Oracle数据库一体机以极致性能处理任何
             Warehouse                                         混合后的工作负载
                                                              – And predictable response times
               Data Mart
                                                             • 卓越的新混合能力
                       HR




Copyright © 2009, Oracle Corporation and/or its affiliates                                                – 64 –
Exadata的价值主张


                 • 极限性能

                 • 线性扩展

                 • 企业即用

                 • 开放标准



Copyright © 2009, Oracle Corporation and/or its affiliates   – 65 –
未来的架构
                                                             大规模的并行网格


                                                               Best for Data Warehousing
                                                               Best for OLTP
                                                               Best for Consolidation




Copyright © 2009, Oracle Corporation and/or its affiliates                              – 66 –
Q&A

Weitere ähnliche Inhalte

Was ist angesagt?

Oracle Exadata 1Z0-485 Certification
Oracle Exadata 1Z0-485 CertificationOracle Exadata 1Z0-485 Certification
Oracle Exadata 1Z0-485 CertificationExadatadba
 
Oracle Exadata Performance: Latest Improvements and Less Known Features
Oracle Exadata Performance: Latest Improvements and Less Known FeaturesOracle Exadata Performance: Latest Improvements and Less Known Features
Oracle Exadata Performance: Latest Improvements and Less Known FeaturesTanel Poder
 
Parallel Query on Exadata
Parallel Query on ExadataParallel Query on Exadata
Parallel Query on ExadataEnkitec
 
Exadata x4 for_sap
Exadata x4 for_sapExadata x4 for_sap
Exadata x4 for_sapFran Navarro
 
Oracle Exadata Maintenance tasks 101 - OTN Tour 2015
Oracle Exadata Maintenance tasks 101 - OTN Tour 2015Oracle Exadata Maintenance tasks 101 - OTN Tour 2015
Oracle Exadata Maintenance tasks 101 - OTN Tour 2015Nelson Calero
 
Optimize and Simplify Oracle 12C RAC using dNFS, ZFS and OISP
Optimize and Simplify Oracle 12C RAC using dNFS, ZFS and OISPOptimize and Simplify Oracle 12C RAC using dNFS, ZFS and OISP
Optimize and Simplify Oracle 12C RAC using dNFS, ZFS and OISPSecure-24
 
What's So Special about the Oracle Database Appliance?
What's So Special about the Oracle Database Appliance?What's So Special about the Oracle Database Appliance?
What's So Special about the Oracle Database Appliance?O-box
 
Running E-Business Suite Database on Oracle Database Appliance
Running E-Business Suite Database on Oracle Database ApplianceRunning E-Business Suite Database on Oracle Database Appliance
Running E-Business Suite Database on Oracle Database ApplianceMaris Elsins
 
Whitepaper: Running Oracle e-Business Suite Database on Oracle Database Appli...
Whitepaper: Running Oracle e-Business Suite Database on Oracle Database Appli...Whitepaper: Running Oracle e-Business Suite Database on Oracle Database Appli...
Whitepaper: Running Oracle e-Business Suite Database on Oracle Database Appli...Maris Elsins
 
Drilling Deep Into Exadata Performance
Drilling Deep Into Exadata PerformanceDrilling Deep Into Exadata Performance
Drilling Deep Into Exadata PerformanceEnkitec
 
Indexing in Exadata
Indexing in ExadataIndexing in Exadata
Indexing in ExadataEnkitec
 
How to Modernize Your Database Platform to Realize Consolidation Savings
How to Modernize Your Database Platform to Realize Consolidation SavingsHow to Modernize Your Database Platform to Realize Consolidation Savings
How to Modernize Your Database Platform to Realize Consolidation SavingsIsaac Christoffersen
 
Tuning SQL for Oracle Exadata: The Good, The Bad, and The Ugly Tuning SQL fo...
 Tuning SQL for Oracle Exadata: The Good, The Bad, and The Ugly Tuning SQL fo... Tuning SQL for Oracle Exadata: The Good, The Bad, and The Ugly Tuning SQL fo...
Tuning SQL for Oracle Exadata: The Good, The Bad, and The Ugly Tuning SQL fo...Enkitec
 
Exadata Performance Optimization
Exadata Performance OptimizationExadata Performance Optimization
Exadata Performance OptimizationEnkitec
 
Understanding Query Optimization with ‘regular’ and ‘Exadata’ Oracle
Understanding Query Optimization with ‘regular’ and ‘Exadata’ OracleUnderstanding Query Optimization with ‘regular’ and ‘Exadata’ Oracle
Understanding Query Optimization with ‘regular’ and ‘Exadata’ OracleGuatemala User Group
 
All Oracle DBAs have to know about Unix Memory Monitoring
All Oracle DBAs have to know about Unix Memory MonitoringAll Oracle DBAs have to know about Unix Memory Monitoring
All Oracle DBAs have to know about Unix Memory MonitoringYury Velikanov
 
Managing Exadata in the Real World
Managing Exadata in the Real WorldManaging Exadata in the Real World
Managing Exadata in the Real WorldEnkitec
 
Using VirtualBox - Learn Oracle Database 12c and EBS R12
Using VirtualBox - Learn Oracle Database 12c and EBS R12Using VirtualBox - Learn Oracle Database 12c and EBS R12
Using VirtualBox - Learn Oracle Database 12c and EBS R12Biju Thomas
 
MIgrating to RAC using Dataguard
MIgrating to RAC  using Dataguard MIgrating to RAC  using Dataguard
MIgrating to RAC using Dataguard Fuad Arshad
 
My First 100 days with an Exadata (WP)
My First 100 days with an Exadata  (WP)My First 100 days with an Exadata  (WP)
My First 100 days with an Exadata (WP)Gustavo Rene Antunez
 

Was ist angesagt? (20)

Oracle Exadata 1Z0-485 Certification
Oracle Exadata 1Z0-485 CertificationOracle Exadata 1Z0-485 Certification
Oracle Exadata 1Z0-485 Certification
 
Oracle Exadata Performance: Latest Improvements and Less Known Features
Oracle Exadata Performance: Latest Improvements and Less Known FeaturesOracle Exadata Performance: Latest Improvements and Less Known Features
Oracle Exadata Performance: Latest Improvements and Less Known Features
 
Parallel Query on Exadata
Parallel Query on ExadataParallel Query on Exadata
Parallel Query on Exadata
 
Exadata x4 for_sap
Exadata x4 for_sapExadata x4 for_sap
Exadata x4 for_sap
 
Oracle Exadata Maintenance tasks 101 - OTN Tour 2015
Oracle Exadata Maintenance tasks 101 - OTN Tour 2015Oracle Exadata Maintenance tasks 101 - OTN Tour 2015
Oracle Exadata Maintenance tasks 101 - OTN Tour 2015
 
Optimize and Simplify Oracle 12C RAC using dNFS, ZFS and OISP
Optimize and Simplify Oracle 12C RAC using dNFS, ZFS and OISPOptimize and Simplify Oracle 12C RAC using dNFS, ZFS and OISP
Optimize and Simplify Oracle 12C RAC using dNFS, ZFS and OISP
 
What's So Special about the Oracle Database Appliance?
What's So Special about the Oracle Database Appliance?What's So Special about the Oracle Database Appliance?
What's So Special about the Oracle Database Appliance?
 
Running E-Business Suite Database on Oracle Database Appliance
Running E-Business Suite Database on Oracle Database ApplianceRunning E-Business Suite Database on Oracle Database Appliance
Running E-Business Suite Database on Oracle Database Appliance
 
Whitepaper: Running Oracle e-Business Suite Database on Oracle Database Appli...
Whitepaper: Running Oracle e-Business Suite Database on Oracle Database Appli...Whitepaper: Running Oracle e-Business Suite Database on Oracle Database Appli...
Whitepaper: Running Oracle e-Business Suite Database on Oracle Database Appli...
 
Drilling Deep Into Exadata Performance
Drilling Deep Into Exadata PerformanceDrilling Deep Into Exadata Performance
Drilling Deep Into Exadata Performance
 
Indexing in Exadata
Indexing in ExadataIndexing in Exadata
Indexing in Exadata
 
How to Modernize Your Database Platform to Realize Consolidation Savings
How to Modernize Your Database Platform to Realize Consolidation SavingsHow to Modernize Your Database Platform to Realize Consolidation Savings
How to Modernize Your Database Platform to Realize Consolidation Savings
 
Tuning SQL for Oracle Exadata: The Good, The Bad, and The Ugly Tuning SQL fo...
 Tuning SQL for Oracle Exadata: The Good, The Bad, and The Ugly Tuning SQL fo... Tuning SQL for Oracle Exadata: The Good, The Bad, and The Ugly Tuning SQL fo...
Tuning SQL for Oracle Exadata: The Good, The Bad, and The Ugly Tuning SQL fo...
 
Exadata Performance Optimization
Exadata Performance OptimizationExadata Performance Optimization
Exadata Performance Optimization
 
Understanding Query Optimization with ‘regular’ and ‘Exadata’ Oracle
Understanding Query Optimization with ‘regular’ and ‘Exadata’ OracleUnderstanding Query Optimization with ‘regular’ and ‘Exadata’ Oracle
Understanding Query Optimization with ‘regular’ and ‘Exadata’ Oracle
 
All Oracle DBAs have to know about Unix Memory Monitoring
All Oracle DBAs have to know about Unix Memory MonitoringAll Oracle DBAs have to know about Unix Memory Monitoring
All Oracle DBAs have to know about Unix Memory Monitoring
 
Managing Exadata in the Real World
Managing Exadata in the Real WorldManaging Exadata in the Real World
Managing Exadata in the Real World
 
Using VirtualBox - Learn Oracle Database 12c and EBS R12
Using VirtualBox - Learn Oracle Database 12c and EBS R12Using VirtualBox - Learn Oracle Database 12c and EBS R12
Using VirtualBox - Learn Oracle Database 12c and EBS R12
 
MIgrating to RAC using Dataguard
MIgrating to RAC  using Dataguard MIgrating to RAC  using Dataguard
MIgrating to RAC using Dataguard
 
My First 100 days with an Exadata (WP)
My First 100 days with an Exadata  (WP)My First 100 days with an Exadata  (WP)
My First 100 days with an Exadata (WP)
 

Andere mochten auch

Presentation capacity management for oracle exadata database machine v2
Presentation   capacity management for oracle exadata database machine v2Presentation   capacity management for oracle exadata database machine v2
Presentation capacity management for oracle exadata database machine v2xKinAnx
 
Exalogic workshop overview__hardwarev4
Exalogic workshop overview__hardwarev4Exalogic workshop overview__hardwarev4
Exalogic workshop overview__hardwarev4Fran Navarro
 
Colvin exadata and_oem12c
Colvin exadata and_oem12cColvin exadata and_oem12c
Colvin exadata and_oem12cEnkitec
 
Open world exadata_top_10_lessons_learned
Open world exadata_top_10_lessons_learnedOpen world exadata_top_10_lessons_learned
Open world exadata_top_10_lessons_learnedchet justice
 
Oracle ORAchk & EXAchk, What's New in 12.1.0.2.7
Oracle ORAchk & EXAchk, What's New in 12.1.0.2.7Oracle ORAchk & EXAchk, What's New in 12.1.0.2.7
Oracle ORAchk & EXAchk, What's New in 12.1.0.2.7Gareth Chapman
 
Monitor Engineered Systems from a Single Pane of Glass: Oracle Enterprise Man...
Monitor Engineered Systems from a Single Pane of Glass: Oracle Enterprise Man...Monitor Engineered Systems from a Single Pane of Glass: Oracle Enterprise Man...
Monitor Engineered Systems from a Single Pane of Glass: Oracle Enterprise Man...Alfredo Krieg
 
Oracle Enterprise Manager 12c: updates and upgrades.
Oracle Enterprise Manager 12c: updates and upgrades.Oracle Enterprise Manager 12c: updates and upgrades.
Oracle Enterprise Manager 12c: updates and upgrades.Rolta
 
Expert performance tuning tips for Oracle RAC
Expert performance tuning tips for Oracle RACExpert performance tuning tips for Oracle RAC
Expert performance tuning tips for Oracle RACSolarWinds
 
Oracle RAC 12c Best Practices with Appendices DOAG2013
Oracle RAC 12c Best Practices with Appendices DOAG2013Oracle RAC 12c Best Practices with Appendices DOAG2013
Oracle RAC 12c Best Practices with Appendices DOAG2013Markus Michalewicz
 
Architecture of exadata database machine – Part II
Architecture of exadata database machine – Part IIArchitecture of exadata database machine – Part II
Architecture of exadata database machine – Part IIParesh Nayak,OCP®,Prince2®
 
Simplify IT: Oracle SuperCluster
Simplify IT: Oracle SuperCluster Simplify IT: Oracle SuperCluster
Simplify IT: Oracle SuperCluster Fran Navarro
 
Desvendando Oracle Exadata X2-2
Desvendando Oracle Exadata X2-2Desvendando Oracle Exadata X2-2
Desvendando Oracle Exadata X2-2Rodrigo Almeida
 
A Second Look at Oracle RAC 12c
A Second Look at Oracle RAC 12cA Second Look at Oracle RAC 12c
A Second Look at Oracle RAC 12cLeighton Nelson
 
Windows Azure Security & Compliance
Windows Azure Security & ComplianceWindows Azure Security & Compliance
Windows Azure Security & ComplianceNuno Godinho
 

Andere mochten auch (20)

Presentation capacity management for oracle exadata database machine v2
Presentation   capacity management for oracle exadata database machine v2Presentation   capacity management for oracle exadata database machine v2
Presentation capacity management for oracle exadata database machine v2
 
Exalogic workshop overview__hardwarev4
Exalogic workshop overview__hardwarev4Exalogic workshop overview__hardwarev4
Exalogic workshop overview__hardwarev4
 
Exadata
ExadataExadata
Exadata
 
Oracle Gsop
Oracle GsopOracle Gsop
Oracle Gsop
 
Colvin exadata and_oem12c
Colvin exadata and_oem12cColvin exadata and_oem12c
Colvin exadata and_oem12c
 
Open world exadata_top_10_lessons_learned
Open world exadata_top_10_lessons_learnedOpen world exadata_top_10_lessons_learned
Open world exadata_top_10_lessons_learned
 
Oracle ORAchk & EXAchk, What's New in 12.1.0.2.7
Oracle ORAchk & EXAchk, What's New in 12.1.0.2.7Oracle ORAchk & EXAchk, What's New in 12.1.0.2.7
Oracle ORAchk & EXAchk, What's New in 12.1.0.2.7
 
Monitor Engineered Systems from a Single Pane of Glass: Oracle Enterprise Man...
Monitor Engineered Systems from a Single Pane of Glass: Oracle Enterprise Man...Monitor Engineered Systems from a Single Pane of Glass: Oracle Enterprise Man...
Monitor Engineered Systems from a Single Pane of Glass: Oracle Enterprise Man...
 
Rac 12c optimization
Rac 12c optimizationRac 12c optimization
Rac 12c optimization
 
Oracle Enterprise Manager 12c: updates and upgrades.
Oracle Enterprise Manager 12c: updates and upgrades.Oracle Enterprise Manager 12c: updates and upgrades.
Oracle Enterprise Manager 12c: updates and upgrades.
 
Expert performance tuning tips for Oracle RAC
Expert performance tuning tips for Oracle RACExpert performance tuning tips for Oracle RAC
Expert performance tuning tips for Oracle RAC
 
Oracle RAC 12c Best Practices with Appendices DOAG2013
Oracle RAC 12c Best Practices with Appendices DOAG2013Oracle RAC 12c Best Practices with Appendices DOAG2013
Oracle RAC 12c Best Practices with Appendices DOAG2013
 
Super cluster oracleday cl 7
Super cluster oracleday cl 7Super cluster oracleday cl 7
Super cluster oracleday cl 7
 
Architecture of exadata database machine – Part II
Architecture of exadata database machine – Part IIArchitecture of exadata database machine – Part II
Architecture of exadata database machine – Part II
 
Simplify IT: Oracle SuperCluster
Simplify IT: Oracle SuperCluster Simplify IT: Oracle SuperCluster
Simplify IT: Oracle SuperCluster
 
Desvendando Oracle Exadata X2-2
Desvendando Oracle Exadata X2-2Desvendando Oracle Exadata X2-2
Desvendando Oracle Exadata X2-2
 
Oracle super cluster m7
Oracle super cluster m7Oracle super cluster m7
Oracle super cluster m7
 
Security in windows azure
Security in windows azureSecurity in windows azure
Security in windows azure
 
A Second Look at Oracle RAC 12c
A Second Look at Oracle RAC 12cA Second Look at Oracle RAC 12c
A Second Look at Oracle RAC 12c
 
Windows Azure Security & Compliance
Windows Azure Security & ComplianceWindows Azure Security & Compliance
Windows Azure Security & Compliance
 

Ähnlich wie Sun Oracle Exadata Technical Overview V1

Miro Consulting Oracle Exadata Database Machine Offering
Miro Consulting  Oracle Exadata Database Machine OfferingMiro Consulting  Oracle Exadata Database Machine Offering
Miro Consulting Oracle Exadata Database Machine Offeringgarylcoleman
 
Oracle en Entel Summit 2010
Oracle en Entel Summit 2010Oracle en Entel Summit 2010
Oracle en Entel Summit 2010Entel
 
Presentacion oracle exadata & exalogic f. podesta -yatch club 19 de abril 2012
Presentacion oracle exadata & exalogic   f. podesta -yatch club 19 de abril 2012Presentacion oracle exadata & exalogic   f. podesta -yatch club 19 de abril 2012
Presentacion oracle exadata & exalogic f. podesta -yatch club 19 de abril 2012ValeVilloslada
 
Oracle Exadata Version 2
Oracle Exadata Version 2Oracle Exadata Version 2
Oracle Exadata Version 2Jarod Wang
 
PDoolan Oracle Overview
PDoolan Oracle OverviewPDoolan Oracle Overview
PDoolan Oracle OverviewPeter Doolan
 
Big Data: Business Opportunities, Requirements and Approach
Big Data: Business Opportunities, Requirements and ApproachBig Data: Business Opportunities, Requirements and Approach
Big Data: Business Opportunities, Requirements and ApproachEnkitec
 
Oracle Exadata Database
Oracle Exadata DatabaseOracle Exadata Database
Oracle Exadata Databaselanka76
 
Exadata architecture and internals presentation
Exadata architecture and internals presentationExadata architecture and internals presentation
Exadata architecture and internals presentationSanjoy Dasgupta
 
A5 oracle exadata-the game changer for online transaction processing data w...
A5   oracle exadata-the game changer for online transaction processing data w...A5   oracle exadata-the game changer for online transaction processing data w...
A5 oracle exadata-the game changer for online transaction processing data w...Dr. Wilfred Lin (Ph.D.)
 
Exadata 11-2-overview-v2 11
Exadata 11-2-overview-v2 11Exadata 11-2-overview-v2 11
Exadata 11-2-overview-v2 11Oracle BH
 
Eng systems oracle_overview
Eng systems oracle_overviewEng systems oracle_overview
Eng systems oracle_overviewFran Navarro
 
Oracleonoracle dec112012
Oracleonoracle dec112012Oracleonoracle dec112012
Oracleonoracle dec112012patmisasi
 
Oracle strategy for_information_management
Oracle strategy for_information_managementOracle strategy for_information_management
Oracle strategy for_information_managementInSync Conference
 
Collier exadata technical overview presentation 4 14-10
Collier exadata technical overview presentation 4 14-10Collier exadata technical overview presentation 4 14-10
Collier exadata technical overview presentation 4 14-10xKinAnx
 
Exadata x3 workshop
Exadata x3 workshopExadata x3 workshop
Exadata x3 workshopFran Navarro
 
Sun Storage F5100 Flash Array, Redefining Storage Performance and Efficiency-...
Sun Storage F5100 Flash Array, Redefining Storage Performance and Efficiency-...Sun Storage F5100 Flash Array, Redefining Storage Performance and Efficiency-...
Sun Storage F5100 Flash Array, Redefining Storage Performance and Efficiency-...Agora Group
 
OSS Presentation by Bryan Badger
OSS Presentation by Bryan BadgerOSS Presentation by Bryan Badger
OSS Presentation by Bryan BadgerOpenStorageSummit
 
Emerging Tech Showcase Oracle
Emerging Tech Showcase OracleEmerging Tech Showcase Oracle
Emerging Tech Showcase OracleServium
 

Ähnlich wie Sun Oracle Exadata Technical Overview V1 (20)

Miro Consulting Oracle Exadata Database Machine Offering
Miro Consulting  Oracle Exadata Database Machine OfferingMiro Consulting  Oracle Exadata Database Machine Offering
Miro Consulting Oracle Exadata Database Machine Offering
 
Oracle en Entel Summit 2010
Oracle en Entel Summit 2010Oracle en Entel Summit 2010
Oracle en Entel Summit 2010
 
Presentacion oracle exadata & exalogic f. podesta -yatch club 19 de abril 2012
Presentacion oracle exadata & exalogic   f. podesta -yatch club 19 de abril 2012Presentacion oracle exadata & exalogic   f. podesta -yatch club 19 de abril 2012
Presentacion oracle exadata & exalogic f. podesta -yatch club 19 de abril 2012
 
Oracle Exadata Version 2
Oracle Exadata Version 2Oracle Exadata Version 2
Oracle Exadata Version 2
 
PDoolan Oracle Overview
PDoolan Oracle OverviewPDoolan Oracle Overview
PDoolan Oracle Overview
 
Big Data: Business Opportunities, Requirements and Approach
Big Data: Business Opportunities, Requirements and ApproachBig Data: Business Opportunities, Requirements and Approach
Big Data: Business Opportunities, Requirements and Approach
 
Oracle Exadata Database
Oracle Exadata DatabaseOracle Exadata Database
Oracle Exadata Database
 
Exadata architecture and internals presentation
Exadata architecture and internals presentationExadata architecture and internals presentation
Exadata architecture and internals presentation
 
A5 oracle exadata-the game changer for online transaction processing data w...
A5   oracle exadata-the game changer for online transaction processing data w...A5   oracle exadata-the game changer for online transaction processing data w...
A5 oracle exadata-the game changer for online transaction processing data w...
 
Exadata 11-2-overview-v2 11
Exadata 11-2-overview-v2 11Exadata 11-2-overview-v2 11
Exadata 11-2-overview-v2 11
 
Eng systems oracle_overview
Eng systems oracle_overviewEng systems oracle_overview
Eng systems oracle_overview
 
Oracleonoracle dec112012
Oracleonoracle dec112012Oracleonoracle dec112012
Oracleonoracle dec112012
 
Oow Ppt 2
Oow Ppt 2Oow Ppt 2
Oow Ppt 2
 
Oracle strategy for_information_management
Oracle strategy for_information_managementOracle strategy for_information_management
Oracle strategy for_information_management
 
Collier exadata technical overview presentation 4 14-10
Collier exadata technical overview presentation 4 14-10Collier exadata technical overview presentation 4 14-10
Collier exadata technical overview presentation 4 14-10
 
Exadata x3 workshop
Exadata x3 workshopExadata x3 workshop
Exadata x3 workshop
 
Sun Storage F5100 Flash Array, Redefining Storage Performance and Efficiency-...
Sun Storage F5100 Flash Array, Redefining Storage Performance and Efficiency-...Sun Storage F5100 Flash Array, Redefining Storage Performance and Efficiency-...
Sun Storage F5100 Flash Array, Redefining Storage Performance and Efficiency-...
 
ZFS appliance
ZFS applianceZFS appliance
ZFS appliance
 
OSS Presentation by Bryan Badger
OSS Presentation by Bryan BadgerOSS Presentation by Bryan Badger
OSS Presentation by Bryan Badger
 
Emerging Tech Showcase Oracle
Emerging Tech Showcase OracleEmerging Tech Showcase Oracle
Emerging Tech Showcase Oracle
 

Kürzlich hochgeladen

20230202 - Introduction to tis-py
20230202 - Introduction to tis-py20230202 - Introduction to tis-py
20230202 - Introduction to tis-pyJamie (Taka) Wang
 
COMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online CollaborationCOMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online Collaborationbruanjhuli
 
UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7DianaGray10
 
Bird eye's view on Camunda open source ecosystem
Bird eye's view on Camunda open source ecosystemBird eye's view on Camunda open source ecosystem
Bird eye's view on Camunda open source ecosystemAsko Soukka
 
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdfUiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdfDianaGray10
 
Comparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and IstioComparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and IstioChristian Posta
 
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...Aggregage
 
AI You Can Trust - Ensuring Success with Data Integrity Webinar
AI You Can Trust - Ensuring Success with Data Integrity WebinarAI You Can Trust - Ensuring Success with Data Integrity Webinar
AI You Can Trust - Ensuring Success with Data Integrity WebinarPrecisely
 
Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )Brian Pichman
 
Introduction to Matsuo Laboratory (ENG).pptx
Introduction to Matsuo Laboratory (ENG).pptxIntroduction to Matsuo Laboratory (ENG).pptx
Introduction to Matsuo Laboratory (ENG).pptxMatsuo Lab
 
Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024D Cloud Solutions
 
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCostKubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCostMatt Ray
 
VoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBXVoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBXTarek Kalaji
 
COMPUTER 10 Lesson 8 - Building a Website
COMPUTER 10 Lesson 8 - Building a WebsiteCOMPUTER 10 Lesson 8 - Building a Website
COMPUTER 10 Lesson 8 - Building a Websitedgelyza
 
Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Commit University
 
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesAI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesMd Hossain Ali
 
NIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 WorkshopNIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 WorkshopBachir Benyammi
 
How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?IES VE
 
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDE
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDEADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDE
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDELiveplex
 

Kürzlich hochgeladen (20)

20230202 - Introduction to tis-py
20230202 - Introduction to tis-py20230202 - Introduction to tis-py
20230202 - Introduction to tis-py
 
COMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online CollaborationCOMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online Collaboration
 
UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7
 
Bird eye's view on Camunda open source ecosystem
Bird eye's view on Camunda open source ecosystemBird eye's view on Camunda open source ecosystem
Bird eye's view on Camunda open source ecosystem
 
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdfUiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
 
20230104 - machine vision
20230104 - machine vision20230104 - machine vision
20230104 - machine vision
 
Comparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and IstioComparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and Istio
 
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
 
AI You Can Trust - Ensuring Success with Data Integrity Webinar
AI You Can Trust - Ensuring Success with Data Integrity WebinarAI You Can Trust - Ensuring Success with Data Integrity Webinar
AI You Can Trust - Ensuring Success with Data Integrity Webinar
 
Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )
 
Introduction to Matsuo Laboratory (ENG).pptx
Introduction to Matsuo Laboratory (ENG).pptxIntroduction to Matsuo Laboratory (ENG).pptx
Introduction to Matsuo Laboratory (ENG).pptx
 
Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024
 
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCostKubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
 
VoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBXVoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBX
 
COMPUTER 10 Lesson 8 - Building a Website
COMPUTER 10 Lesson 8 - Building a WebsiteCOMPUTER 10 Lesson 8 - Building a Website
COMPUTER 10 Lesson 8 - Building a Website
 
Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)
 
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesAI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
 
NIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 WorkshopNIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 Workshop
 
How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?
 
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDE
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDEADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDE
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDE
 

Sun Oracle Exadata Technical Overview V1

  • 1. Exadata and Database Machine Overview 金江 @Channel Sales Consultant jenkin.jin@oracle.com 13701864820 26-Jan-2010
  • 2. 革命性产品 - Exadata • Exadata存储服务器和数据库一体机 • V1比普通数据仓库性能快10到100倍 ;V2再次加速并创造TCP-C新世界纪录 • 最优异的扩展性,容量,带宽和处理能力
  • 3. Agenda议程 • Overview • Exadata Based Product Offerings • Exadata Architecture and Features • Best Data Warehousing Machine • Best OLTP Machine • Best Consolidation Machine Copyright © 2009, Oracle Corporation and/or its affiliates – 3–
  • 4. 产品推出 Exadata Storage Server & Database Machine • Exadata Storage Server • Sun Oracle Database Machine – 专为Oracle数据库优化的存储产品 – 预配好的高性能 – 极限 I/O 和 SQL 处理性能 – 平稳的性能配置 – 硬件和软件的组合 – 在构建Oracle部署过程中远离不定 • Exadata Storage Server Software 因素 • Exadata Storage Server Software • Oracle Database 11.2 Copyright © 2009, Oracle Corporation and/or its affiliates – 4–
  • 5. 挑战 – 诸多瓶颈 • 目前由于存储引起数据库性能的情况较多 – 存储系统限制了从存储到服务器的数据带宽 – 存储阵列内部瓶颈 – SAN的瓶颈 – 由于物理磁盘速度引起的随机I/O瓶颈 • 数据带宽严重限制了数据仓库的性能 • 随机 I/O 瓶颈限制了OLTP应用的性能 Copyright © 2009, Oracle Corporation and/or its affiliates – 5–
  • 6. Exadata Storage Server 数据带宽瓶颈解决方案 • 增加更多信道 • 增宽信道 • 通过信道传送较少数据 Copyright © 2009, Oracle Corporation and/or its affiliates – 6–
  • 7. Exadata Smart Storage 打破数据带宽和随机I/O 的瓶颈 Exadata Storage Cells • Oracle 解决数据带宽瓶颈三种手段 存储单元 – 大量的并行存储网格 of high performance Exadata storage servers (cells). • Data bandwidth scales with data volume – 数据密集处理 runs in Exadata storage. • Queries run in storage as data streams from disk, offloading database server CPUs – 列压缩减少数据容量 up to 10x • Exadata Hybrid Columnar Compression provides 10x lower cost, 10x higher performance • 利用Exadata智能闪存缓冲卡来解决随机I/O瓶颈 – Increase random I/Os by factor of 20X Copyright © 2009, Oracle Corporation and/or its affiliates – 7–
  • 8. <Insert Picture Here> Exadata Based Product Offerings Copyright © 2009, Oracle Corporation and/or its affiliates – 8–
  • 9. Sun Oracle Database Machine • 网格是未来架构 • Highest performance, lowest cost, redundant, incrementally scalable • Exadata数据库机是完全满足所有数据管理需求的第一款全面的网格架构 RAC Database Server Grid • 8 High-performance low-cost Exadata Storage Server Grid compute servers • 14 High-performance low-cost • 2 Intel quad-core Xeons each storage servers • 100 TB raw SAS disk storage InfiniBand Network or • 40 Gb/sec fault-tolerant unified 336 TB raw SATA disk storage server and storage network • 5TB+ flash storage! Copyright © 2009, Oracle Corporation and/or its affiliates – 9–
  • 10. Sun Oracle Database Machine 性能提高到极致 RAC Database Server Grid • Millions of transactions Exadata Storage Server Grid per minute • 21 GB/sec disk bandwidth • Tens of millions of queries • 50 GB/sec flash bandwidth per minute • 1 million I/Os per second • Billions of rows per minute InfiniBand Network • 880 Gb/sec aggregate throughput Copyright © 2009, Oracle Corporation and/or its affiliates – 10 –
  • 11. 可扩展的性能和容量 • 扩展性 • 冗余和容错 – Scales to 8 rack database machine – Failure of any component is tolerated by just adding wires – Data is mirrored across storage • More with external InfiniBand switches servers – Scales to hundreds of storage servers • Multi-petabyte databases Copyright © 2009, Oracle Corporation and/or its affiliates – 11 –
  • 12. 大大简化部署 • 数据库机消除了部署数据库系统的复杂性 – Months of configuration, troubleshooting, tuning • 数据库机当天即用 – Pre-built, tested, standard, supportable configuration – Runs existing applications unchanged • 即用的极致性能 数月到数天 Copyright © 2009, Oracle Corporation and/or its affiliates – 12 –
  • 13. Sun Exadata Storage Server Hardware Sun Exadata Storage • 大量Exadata并行且网格化的存储块 Server Hardware – Up to 1.5 GB/sec raw data bandwidth per cell – Up to 75,000 IOPS with Flash • Sun Fire™ X4275 服务器 – 2 Quad-Core Intel® Xeon® E5540 Processors – 24GB RAM – Dual-port 4X QDR (40Gb/s) InfiniBand card – Disk Options 硬件提供商 • 12 x 600 GB SAS disks (7.2 TB total) • 12 x 2TB SATA disks (24 TB total) – 4 x 96 GB Sun Flash PCIe Cards (384 GB total) • 预装软件 – Oracle Exadata Storage Server Software – Oracle Enterprise Linux – Drivers, Utilities 软件提供商 • Oracle统一提供支持 – 3 year, 24 x 7, 4 Hr On-site response Copyright © 2009, Oracle Corporation and/or its affiliates – 13 –
  • 14. Sun Exadata Storage Server Hardware Dual-redundant, hot- 24 GB DRAM swappable power supplies ILOM Disk Controller HBA with 512M 12 x 3.5” Disk Drives battery backed cache 2 Quad-Core Intel® Xeon® Processors 预装软件: InfiniBand QDR • Oracle Exadata Storage Server Software (40Gb/s) dual 4 x 96GB Sun port card • Oracle Enterprise Linux Flash PCIe Cards • Drivers Copyright © 2009, Oracle Corporation and/or its affiliates – 14 –
  • 15. Sun Oracle Database Machine Full Rack Pre-Configured for Extreme Performance • 8 Sun Fire™ X4170 Oracle Database servers • 14 Exadata Storage Servers (All SAS or all SATA) • 3 Sun Datacenter InfiniBand Switch 36 – 36-port Managed QDR (40Gb/s) switch • 1 “Admin” Cisco Ethernet switch • Keyboard, Video, Mouse (KVM) hardware • Redundant Power Distributions Units (PDUs) • Single Point of Support from Oracle – 3 year, 24 x 7, 4 Hr On-site response Add more racks for additional scalability Copyright © 2009, Oracle Corporation and/or its affiliates – 15 –
  • 16. Sun Oracle Database Machine Half Rack Pre-Configured for Extreme Performance • 4 Sun Fire™ X4170 Oracle Database servers • 7 Exadata Storage Servers (All SAS or all SATA) • 2 Sun Datacenter InfiniBand Switch 36 – 36-port Managed QDR (40Gb/s) switch • 1 “Admin” Cisco Ethernet switch • Keyboard, Video, Mouse (KVM) hardware • Redundant PDUs • Single Point of Support from Oracle – 3 year, 24 x 7, 4 Hr On-site response Can Upgrade to a Full Rack Copyright © 2009, Oracle Corporation and/or its affiliates – 16 –
  • 17. Sun Oracle Database Machine Quarter Rack Pre-Configured for Extreme Performance • 2 Sun Fire™ X4170 Oracle Database servers • 3 Exadata Storage Servers (All SAS or all SATA) • 2 Sun Datacenter InfiniBand Switch 36 – 36-port Managed QDR (40Gb/s) InfiniBand switch • 1 “Admin” Cisco Ethernet switch • Keyboard, Video, Mouse (KVM) hardware • Redundant PDUs • Single Point of Support from Oracle – 3 year, 24 x 7, 4 Hr On-site response Can Upgrade to an Half Rack Copyright © 2009, Oracle Corporation and/or its affiliates – 17 –
  • 18. Sun Oracle Database Machine Basic System Entry Level non-HA Configuration • 1 Sun Fire™ X4170 Oracle Database servers • 1 Exadata Storage Servers (All SAS or all SATA) • 1 Sun Datacenter InfiniBand Switch 36 – 36-port Managed QDR (40Gb/s) InfiniBand switch • InfiniBand Cables • Installed in Customer supplied Rack • Customer supplied Ethernet and KVM Infrastructure • Single Point of Support from Oracle – 3 year, 24 x 7, 4 Hr On-site response Copyright © 2009, Oracle Corporation and/or its affiliates – 18 –
  • 19. Standalone Exadata Storage Servers • Purchase Exadata Storage Servers from Oracle – Customer supplied standard 19 inch rack • Customer supplied x86 64-bit Linux Database Servers • Hardware installation more complex • No single point of support for entire deployment Copyright © 2009, Oracle Corporation and/or its affiliates – 19 –
  • 20. Exadata 产品的容量 Single Server Quarter Rack Half Rack Full Rack SAS 7.2 TB 21 TB 50 TB 100 TB Raw Disk1 SATA 24 TB 72 TB 168 TB 336 TB Raw Flash1 384 GB 1.1 TB 2.6 TB 5.3 TB User Data2 SAS 2 TB 6 TB 14 TB 28 TB (assuming no compression) SATA 7 TB 21 TB 50 TB 100 TB 1 – Raw capacity calculated using 1 GB = 1000 x 1000 x 1000 bytes and 1 TB = 1000 x 1000 x 1000 x 1000 bytes. 2 - User Data: Actual space for end-user data, computed after single mirroring (ASM normal redundancy) and after allowing space for database structures such as temp, logs, undo, and indexes. Actual user data capacity varies by application. User Data capacity calculated using 1 TB = 1024 * 1024 * 1024 * 1024 bytes. Copyright © 2009, Oracle Corporation and/or its affiliates – 20 –
  • 21. Exadata 产品的性能 Single Server Quarter Rack Half Rack Full Rack Raw Disk Data SAS 1.5 GB/s 4.5 GB/s 10.5 GB/s 21 GB/s Bandwidth1,4 SATA 0.85 GB/s 2.5 GB/s 6 GB/s 12 GB/s Raw Flash Data Bandwidth1,4 3.6 GB/s 11 GB/s 25 GB/s 50 GB/s Max User Data Bandwidth2,4 (10x compression & Flash) 36 GB/s 110 GB/s 250 GB/s 500 GB/s SAS 3,600 10,800 25,000 50,000 Disk IOPS3,4 SATA 1,440 4,300 10,000 20,000 Flash IOPS3,4 75,000 225,000 500,000 1,000,000 Data Load Rate4 0.65 TB/hr 1 TB/hr 2.5 TB/hr 5 TB/hr 1 – Bandwidth is peak physical disk scan bandwidth, assuming no compression. 2 - Max User Data Bandwidth assumes scanned data is compressed by factor of 10 and is on Flash. 3 – IOPs – Based on IO requests of size 8K 4 - Actual performance will vary by application. Copyright © 2009, Oracle Corporation and/or its affiliates – 21 –
  • 22. <Insert Picture Here> Exadata Architecture and Features Copyright © 2009, Oracle Corporation and/or its affiliates – 22 –
  • 23. Exadata的配置 Single-Instance Database RAC Database InfiniBand Switch/Network Exadata Cell Exadata Cell Exadata Cell • 每个Exadata 单元是拥有磁盘存储且运行Exadata软件的自我控制服务器 • Oracle数据库跨越不同Exadata单元进行部署 • Oracle数据库与Exadata存储服务器之间增强协作 • 在网格架构内没有实际的Exadata单元的限制 Copyright © 2009, Oracle Corporation and/or its affiliates – 23 –
  • 24. Exadata的架构 Single-Instance RAC Database Database DB Server DB Server DB Server DB Instance DB Instance DB Instance Enterprise DBRM DBRM DBRM Manager ASM ASM ASM iDB Protocol over InfiniBand Switch/Network InfiniBand with Path Failover OEL OEL OEL CELLSRV MS CELLSRV MS CELLSRV MS Cell IORM RS IORM RS IORM RS Control CLI Exadata Cell Exadata Cell Exadata Cell … … … Copyright © 2009, Oracle Corporation and/or its affiliates – 24 –
  • 25. Exadata软件的特性 • Exadata Smart Scans 智能扫描 – 10X or greater reduction in data sent to database servers • Exadata Storage Indexes 存储索引 – Eliminate unnecessary I/Os to disk • Hybrid Columnar Compression (HCC) 混合列压缩 – Efficient compression increases effective storage capacity and increases user data scan bandwidths by a factor of 10X • Exadata Smart Flash Cache 智能闪存缓存 – Breaks random I/O bottleneck by increasing IOPs by 20X – Doubles user data scan bandwidths • I/O Resource Manager (IORM) 资源管理 – Enables storage grid by prioritizing I/Os to ensure predictable performance • Inter-leaved Grid Disks 交错网格硬盘 – Enables storage grid that allows multiple applications to place frequently accessed data on faster portions of the disk Copyright © 2009, Oracle Corporation and/or its affiliates – 25 –
  • 26. Exadata Smart Scan 智能扫描 • Exadata 存储单元通过扫描卸载大大减少了传送到 数据库服务器的数据 – Row filtering based on “where” predicate – Column filtering – Join filtering – Incremental backup filtering 11.2 – Scans on encrypted data 11.2 – Data Mining model scoring • 正常情况下减少10x 数据量 • 完全应用透明 – Even if cell or disk fails during a query Copyright © 2009, Oracle Corporation and/or its affiliates – 26 –
  • 27. 传统的扫描过程   • 智能扫描举例: SELECT Rows Returned – 寻找消费超过$200手机用户 customer_name FROM calls – 用户信息仅占用1T表中的 WHERE amount > 2M空间 200;  • 传统存储情况下,所有的数据 DB Host reduces 库智能操作都在数据库节点中 terabyte of data to 1000 完成  customer names that Table are returned to client Extents • 来源于存储的数据被数据库主 Identified 机大部分所丢弃 • 大量的废弃数据占用了宝贵的   数据库主机资源,严重影响任 I/Os Issued I/Os Executed: 务执行 1 terabyte of data returned to hosts Copyright © 2009, Oracle Corporation and/or its affiliates – 27 –
  • 28. Exadata 智能扫描过程  SELECT customer_name  • 仅关心相关列 FROM calls Rows Returned – customer_name WHERE amount > and required rows 200; – where amount>200 are are returned to hosts   Consolidated • 条件评估消耗的CPU 可卸载到 Smart Scan Result Set Exadata Constructed And Built From All Sent To Cells Cells • 从数据库节点上移除扫描进程已 获得更多可用CPU资源,消除大 量无价值消息  Smart Scan – Returns the needle, not the entire  hay stack identifies rows and 2MB of data columns within returned to server terabyte table that match request Copyright © 2009, Oracle Corporation and/or its affiliates – 28 –
  • 29. 智能扫描的透明特性 • 对应用完全透明 – No application or SQL changes required – Returned data is fully consistent and transactional – If a cell dies during a smart scan, the uncompleted portions of the smart scan are transparently routed to other cells containing a replica of the data • 能正常处理复杂的场景包括 – Uncommitted data and locked rows – Chained rows – Compressed tables – National Language Processing – Date arithmetic – Regular expression searches – Partitioned tables 高吞吐量, 低开销, 无需复杂优化 Copyright © 2009, Oracle Corporation and/or its affiliates – 29 –
  • 30. Exadata Smart Scans: 11.2 卸载data mining scoring • Data mining scoring executed in Exadata: select cust_id from customers where region = ‘US’ Scoring function and prediction_probability(churnmod, ‘Y’ using *) > 0.8; executed in Exadata • All data mining scoring functions offloaded to Exadata • Up to 10x performance gains • Reduced CPU utilization on Database Server Copyright © 2009, Oracle Corporation and/or its affiliates – 30 –
  • 31. Exadata Storage Index 存储索引 11.2 无成本的透明消除I/O Table Index • Exadata Storage Indexes maintain summary A B C D information about table data in memory – Store MIN and MAX values of columns 1 – Typically one index entry for every MB of disk Min B = 1 3 Max B =5 • Eliminates disk I/Os if MIN and MAX can never 5 match “where” clause of a query 5 8 Min B = 3 • Completely automatic and transparent Max B =8 3 Select * from Table where B<2 - 只有第一个集合能匹配 Copyright © 2009, Oracle Corporation and/or its affiliates – 31 –
  • 32. Exadata Hybrid Columnar Compression 混合列压缩 11.2 • 数据在列级存储然后再压缩 • 查询模式 针对数据仓库 – Optimized for speed – 10X compression ratio is typical Up To 50X – Scans improve proportionally • 归档模式 针对不常查询的数据 – Optimized to reduce space – 15X compression is typical – Up to 50X for some data Copyright © 2009, Oracle Corporation and/or its affiliates – 32 –
  • 33. Exadata Hybrid Columnar Compression 如何工作 Compression Unit • Tables are organized into sets of a few thousand rows called Compression Units (CUs) • Within Compression Unit, data is Organized by Column and then compressed – Column organization brings similar values close together, enhancing compression Reduces Table Size 4x to 50x • Useful for data that is bulk loaded and queried 4x to 40x Reduction – Update activity is light Copyright © 2009, Oracle Corporation and/or its affiliates – 33 –
  • 34. Exadata Hybrid Columnar Compression 数据仓库型和归档型 Warehouse Compression Archive Compression 针对速度优化 针对空间优化 • 10x average storage savings • 15x average storage savings • 10x Scan I/O reduction – Up to 50x on some data • Some access overhead • For cold or historical data Smaller Warehouse Reclaim 93% of Disks Faster Performance Keep Data Online Can mix compression types by partition for ILM Copyright © 2009, Oracle Corporation and/or its affiliates – 34 –
  • 35. 真实场景中的压缩比 Oracle Production E-Business Suite Tables 52 50 OLTP Compression (avg=3.3) 43 Size Reduction Factor by Table 45 Query Compression (avg=14.6) 40 Archive Compression (avg=22.6) 35 29 30 25 19 19 19 20 21 20 16 15 10 10 10 11 10 5 0 • Columnar compression ratios • Query = 14.6X • Archive = 22.6X • Vary by application and table Copyright © 2009, Oracle Corporation and/or its affiliates – 35 –
  • 36. 磁盘随机 I/O 瓶颈 300 I/O per Sec • 磁盘存放海量数据 – But are limited to about 300 I/Os per second • 闪存技术存放较少数据 – But can run tens of thousands of I/Os per second • 理想的解决方式 – Keep most data on disk for low cost 10000X I/O’s per Sec – Transparently move hot data to flash – Use flash cards instead of flash disks to avoid disk controller limitations – Flash cards in Exadata storage • High bandwidth, low latency interconnect Copyright © 2009, Oracle Corporation and/or its affiliates – 36 –
  • 37. Exadata Smart Flash Cache 智能闪存缓存 11.2 • 在4快Flash卡中透明的缓存热数据 • 使用基于快捷PCI的Flash卡来获得更大的吞吐 量和IOPs,并规避磁盘控制器的限制 • 智能缓存 – Smarter than basic LRU algorithm – Knows when to skip caching objects to 4 x 96 GB Flash Cards avoid polluting or flushing the cache • 允许应用显式优化缓存 Copyright © 2009, Oracle Corporation and/or its affiliates – 37 –
  • 38. Flash Cache对SGA的透明扩展 4. User Process Extended Buffer Cache reads blocks from SGA (copied from Flash Cache if not in SGA) Hot Data Warm Data 16 GB 120 GB SGA Memory 3. Clean blocks Flash Cache moved to Flash Cache based on LRU* 1. Blocks read 2. Dirty blocks flushed to into buffer disk cache Cold Data * Headers for Flash 360 GB Magnetic Disks Cached blocks kept in SGA Copyright © 2009, Oracle Corporation and/or its affiliates – 38 –
  • 39. Exadata I/O Resource Management 混合工作负载环境 • 传统存储环境中,同数据库中的用户或共享子存储的多个数据库由于应 用处理无法平衡,从而束缚了共享存储的创建和管理 – Hardware isolation is the approach to ensure separation • Exadata I/O 资源管理确保一个数据库内的不同用户和任务可分配相对合 理的 I/O 资源 • 举例: – Interactive: 50% of I/O resources Database Server – Reporting: 30% of I/O resources – ETL: 20% of I/O resources InfiniBand Switch/Network Exadata Cell Exadata Cell Exadata Cell Copyright © 2009, Oracle Corporation and/or its affiliates – 39 –
  • 40. Exadata I/O Resource Management 多个数据库环境 • 确保不同的数据库可分配相对合理的I/O 带宽 – Database A: 33% I/O resources – Database B: 67% I/O resources • 确保一个数据库内不同的用户和任务可分配相对合理的I/O 带宽 – Database A: • Reporting: 60% of I/O resources Database A Database B • ETL: 40% of I/O resources – Database B: • Interactive: 30% of I/O resources • Batch: 70% of I/O resources InfiniBand Switch/Network Exadata Cell Exadata Cell Exadata Cell Copyright © 2009, Oracle Corporation and/or its affiliates – 40 –
  • 41. Exadata 可扩展的存储网格 • 使用Automatic Storage Management实现动态虚拟化存储 – Simple and non-intrusive resource allocation, and reallocation, enabling true enterprise grid storage – Database work spread across storage resources for optimal performance • 强大的存储分配手段和管理机制 – Flexible configuration for performance and availability Single-Instance Database RAC Database InfiniBand Switch/Network Exadata Cell Exadata Cell Exadata Cell Copyright © 2009, Oracle Corporation and/or its affiliates – 41 –
  • 42. Exadata 存储层级 • Physical disks map to Cell Disks • Cell Disks partitioned into one or multiple Grid Disks • Grid Disks created in order of “hottest” first to “coldest” portion of the disk last • ASM diskgroups created from Grid Disks • Transparent above the ASM layer ASM disk Grid Disk 1 Cell Physical … Disk Disk ASM disk Grid Disk n Sys Area Sys Area Copyright © 2009, Oracle Corporation and/or its affiliates – 42 –
  • 43. Exadata 存储层级示例 ASM 镜像和容错设计 ASM ASM Failure Group Exadata Cell Exadata Cell Failure Group Hot Hot Hot Hot Hot Hot Cold Cold … Cold Cold Cold … Cold • Example shows cell disks divided into two grid disks ASM – hot and cold Disk Group • Two ASM disk groups created across the two sets of grid disks • ASM striping evenly distributes I/O across the disk groups • ASM mirroring is used to protect against disk failures • ASM failure groups are used to protect against cell failures Copyright © 2009, Oracle Corporation and/or its affiliates – 43 –
  • 44. Interleaved Grid Disks 11.2 交错网格硬盘 Grid Disk 1 Hot Data, Cold Data • Grid disks are optionally split and interleaved to place frequently accessed data in all grid disks on higher performing outer tracks • All applications benefit from higher performance outer tracks of disks Grid Disk 2 Hot Data, Cold Data Copyright © 2009, Oracle Corporation and/or its affiliates – 44 –
  • 45. Exadata 存储的管理 • Enterprise Manager – Manage & administer Database and ASM • Exadata Storage Plug-in ( > 10.2.0.3) – Enterprise Manager Grid Control Plug-in to monitor & manage Exadata Storage Cells • Comprehensive CLI – Local Exadata Storage cell management – Distributed shell utility to execute CLI across multiple cells • Sun Embedded Integrated Lights Out Manager (ILOM) – Remote management and administration of hardware Copyright © 2009, Oracle Corporation and/or its affiliates – 45 –
  • 46. 数据保护的有效手段 • All single points of failure eliminated by the Exadata Storage architecture • Hardware Assisted Resilient Data (HARD) built in to Exadata Storage – Prevent data corruption before it happens • Data Guard provides disaster protection and data corruption protection – Automatically maintains one or more copies of the database • Flashback provides human error protection – Snapshot-like capabilities to rewind database to before error • Recovery Manager (RMAN) provides backup to disk – Archiving and corruption protection – Can be used with Oracle Secure Backup (OSB) or third party tape backup software • These work just as they do for traditional non-Exadata storage – Users and database administrator use familiar tools Copyright © 2009, Oracle Corporation and/or its affiliates – 46 –
  • 47. Exadata 共存与迁移 • 数据库可并存部署在Exadata和传统存储上 – Tablespaces can exist on Exadata storage, traditional torage, or a combination of the two, and is transparent to database applications – SQL offload processing requires all pieces of a tablespace reside on Exadata • 如果当前使用ASM及ASM冗余可以在线迁移 Database • 可使用RMAN或Data Guard来完成迁移 Server Exadata Non-Exadata Online Migration Copyright © 2009, Oracle Corporation and/or its affiliates – 47 –
  • 48. <Insert Picture Here> Best Data Warehouse Machine Copyright © 2009, Oracle Corporation and/or its affiliates – 48 –
  • 49. Best Data Warehouse Machine • 大量高容量的硬件并行加速处理海量数据 – Exadata runs data intensive processing OLAP directly in storage • 最全面的分析能力 – OLAP, Statistics, Spatial, Data Mining, Real-time transactional ETL, Efficient point queries ETL • 强大的数据仓库特别优化手段 – Flexible Partitioning, Bitmap Indexing, Join indexing, Materialized Views, Result Cache Data Mining • 卓越的新数据仓库功能 New Copyright © 2009, Oracle Corporation and/or its affiliates – 49 –
  • 50. Exadata 存储特性 • Exadata 智能扫描 – 10X or greater reduction in data sent to database servers • Exadata 存储索引 – Eliminate unnecessary I/Os to disk • Hybrid Columnar Compression 混合列压缩 – Efficient compression increases user data scan rates • Exadata 闪存 – Combined with Hybrid Columnar Compression, scan rate is 20X more Copyright © 2009, Oracle Corporation and/or its affiliates – 50 –
  • 51. 内存中并行执行 SQL 确定所查询表的大小 如果表非常适用于 将表的各部分读到每个 语句 内存中并行执行 节点的缓冲区缓存中 表非常大 表非常小 只有同一RAC 节点 读到任意节点的 上的并行服务器可 以访问每个部分 缓冲区缓存中 直接从磁盘读取 Copyright © 2009, Oracle Corporation and/or its affiliates – 51 –
  • 52. 内存中并行执行 11.2 • 单个数据库一体机拥有400GB的可缓存内存 QphH: 1 TB TPC-H 1,166,976 1,018,321 • 数据库版本11.2 引入了对内存缓冲数据的并 行查询处理 – Harnesses memory capacity of entire database cluster for queries – Foundation for world record 1TB TPC-H 315,842 • Exadata混合列压缩实现了将多个T级表或分 区缓存在内存中 ParAccel Exasol Oracle & HP Exadata Memory has 100x more bandwidth than Disk 比特定的内存数据仓库还快 Source: Transaction Processing Council, as of 9/14/2009: Oracle on HP Bladesystem c-Class 128P RAC, 1,166,976 QphH@1000GB, $5.42/QphH@1000GB, available 12/1/09. Copyright © 2009, Oracle Corporation and/or its affiliates Exasol on PRIMERGY RX300 S4, 1,018,321 QphH@1000GB, $1.18/QphH@1000GB, available 08/01/08. – 52 – ParAccel on SunFire X4100 315,842 QphH@1000GB, $4.57 /QphH@1000GB, available 10/29/07.
  • 53. 大型扫描获得多级收益 10 TB 用户数据需要 1 TB 100 GB 10 TB 的IO 压缩 分区裁剪 亚秒级 On Database Machine 20 GB 5 GB 存储索引 智能扫描 数据减少10倍,扫描加快2000倍 Copyright © 2009, Oracle Corporation and/or its affiliates – 53 –
  • 54. DBFS – 可扩展共享的文件系统 11.2 • Database Machine comes with DBFS shared Linux file system – Shared storage for ETL staging, scripts, reports and other application files • Files stored as SecureFile LOBs in database tables stored in Exadata – Protected like any DB data – mirroring, DataGuard, Flashback, etc. • 5 to 7 GB/sec file system I/O throughput 使用外部表来加载数据 ETL Files in DBFS ETL 比高端NAS文件系统更高的吞吐量 Copyright © 2009, Oracle Corporation and/or its affiliates – 54 –
  • 55. <Insert Picture Here> Best OLTP Machine Copyright © 2009, Oracle Corporation and/or its affiliates – 55 –
  • 56. Best OLTP Machine • 仅Oracle能运行“基于网格”的真实商业应用 • 特有的可容错可扩展 OLTP 数据库 – RAC, Data Guard, Online Operations • 特有的可容错可扩展,适配OLTP的存储 – ASM, Exadata • 卓越的新 OLTP 能力 Copyright © 2009, Oracle Corporation and/or its affiliates – 56 –
  • 57. Exadata Flash 11.2 解决随机I/O瓶颈 •Sun Oracle 数据库一体机拥有5+TB 闪存存储 •Exadata Smart Cache 缓存热点数据 •数据库一体机能实现: – 20x more random I/Os • Over 1 million per second – 2x faster sequential query I/O • 50 GB/sec – 10x better I/O response time •Sub-millisecond – Greatly Reduced Cost 第一款实现闪存优化的 • 10x fewer disks for IOPS 数据库 • Lower Power Copyright © 2009, Oracle Corporation and/or its affiliates – 57 –
  • 58. Complete, Open, Integrated Availability Maximum Availability Architecture最大可用性架构 Real Active Application Data Guard Clusters ASM WAN Fast Secure Backup Recovery Area • Protection from • Real-time remote standby open for queries – Server Failures • Human error correction – Storage Failures – Database, table, row, transaction level – Network Failures • Online indexing and table redefinition – Site Failures • Online patching and upgrades Copyright © 2009, Oracle Corporation and/or its affiliates – 58 –
  • 59. Complete, Open, Integrated Security 监控 Audit Configuration Vault Total Management Recall 访问控制 Database Label Vault Security 加密和屏蔽 Advanced Data Secure Security Masking Backup Copyright © 2009, Oracle Corporation and/or its affiliates – 59 –
  • 60. <Insert Picture Here> Best Consolidation Machine Copyright © 2009, Oracle Corporation and/or its affiliates – 60 –
  • 61. 整合架构 ERP CRM ERP CRM Warehouse HR Data Mart Warehouse HR Data Mart • 融合到数据库一体机 – High performance for all applications – Low cost platform for all applications – Predictable response times in a shared environment – Handles all data management needs – Complete, Open, Integrated Copyright © 2009, Oracle Corporation and/or its affiliates – 61 –
  • 62. Consolidate Storage • Exadata和ASM可跨多个数据库共享所有的存储 服务器 • 配置共享 ERP – Advanced data striping spreads every database across all storage servers CRM – Eliminates hot-spots and captive unused space – Full storage grid performance available to all Warehouse databases – Database or cluster level storage security Data Mart • 可预测性能 HR – Exadata I/O resource manager prioritizes I/Os to ensure predictable performance • At user, job, application, or database level – No need for isolated storage islands Copyright © 2009, Oracle Corporation and/or its affiliates – 62 –
  • 63. Consolidate Servers • 多个数据库可运行在多个数据库一体机上 ERP • 配置共享 CRM – Applications connect to a database service that runs on one or more database nodes • Services can grow, shrink, & move dynamically Warehouse – Large databases can span nodes using RAC – Multiple small databases can run on a single node • 可预测性能 HR Data – Instance caging provides predictable CPU Mart resources when multiple databases run on the same node • Restricts a database to subset of processors Copyright © 2009, Oracle Corporation and/or its affiliates – 63 –
  • 64. Best Consolidation Machine • 在单一系统里整合不同工作负载 – Warehouse oriented bulk data processing ERP – OLTP oriented random updates – Multimedia oriented streaming files CRM • Sun Oracle数据库一体机以极致性能处理任何 Warehouse 混合后的工作负载 – And predictable response times Data Mart • 卓越的新混合能力 HR Copyright © 2009, Oracle Corporation and/or its affiliates – 64 –
  • 65. Exadata的价值主张 • 极限性能 • 线性扩展 • 企业即用 • 开放标准 Copyright © 2009, Oracle Corporation and/or its affiliates – 65 –
  • 66. 未来的架构 大规模的并行网格 Best for Data Warehousing Best for OLTP Best for Consolidation Copyright © 2009, Oracle Corporation and/or its affiliates – 66 –
  • 67. Q&A

Hinweis der Redaktion

  1. Showcased at Oracle World 2008 was the Exadata Storage Server and Database Machine. These two offerings address the issues of insufficient bandwidth between storage and hosts by providing beefing up the storage interconnect infrastructure and moving less data between host and storage.