Optimizing Database I/O

Transcription

1 High Performance Oracle Optimizing Database I/O Dave Pearson Quest Software Copyright 2006 Quest Software

2 The Impact of Poor Performance Diagnostics and Optimization

3 The Impact of Poor Performance Diagnostics and Optimization

4 Quest Application Advantage Quest Application Advantage allows application teams to deliver, manage and control complex application environments Only Quest provides the deepest understanding of the application - from the end user to the database

5 Managing Production I/O Performance

6 Managing Production I/O Performance RESOLVE DISCOVER DIAGNOSE

7 Manage Discover, Diagnose and Resolve Poor Performance Database I/O

8 Database Sub-Systems Instance Transaction Configuration Storage

9 Poor I/O Performance Inefficient SQL generates excessive I/O Missing indexes spawn full table scans I/O hotspots cause CBC latch waits

10 Performance Analysis Indicates I/O Waits I/O waits are the primary contributor to overall performance degradation

11 Performance Analysis Indicates I/O Waits Sequential reads indicates index lookups

12 Database Sub-Systems Instance Transaction Configuration Storage

13 Poor I/O Performance Inefficient cache & pool sizes Inappropriate DB block size Sort area size set too low Slow redo log configuration Too few DBWR processes

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16 Database Sub-Systems Instance Transaction Configuration Storage

17 Poor I/O Performance Wasted block space Index stagnation Row chaining Excessive extents Outdated statistics Default storage settings Index / Table Contention

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19 Database Sub-Systems Instance Transaction Configuration Storage

20 Potential Causes of Poor I/O Performance Inefficient SQL Missing indexes I/O hot spots Inefficient cache & pool sizes Inappropriate DB block size Sort area size set too low Slow redo log configuration Too few DBWR processes Wasted block space Index stagnation Row chaining Excessive extents Outdated statistics Default storage settings Index / Table Contention Transaction Configuration Storage

21 Performance Resolution Workflow Instance Transaction Configuration Storage

22 Quest Central Performance Products Transaction Configuration Storage

23 Quest Central Performance Products Transaction Configuration Storage

24 Storage Optimization

25 Storage Optimization Analyze and Plan Capacity Predict Future Storage Needs Chart Trends in Capacity Usage Identify Storage Management Issues Overallocated Tablespaces Fastest Growing Datafiles Impending Out of Space Conditions Optimize Database Storage Identify Fragmentation within Tablespaces Reorganize Objects and Reclaim Space Optimize Storage Performance w/out Downtime Restructure for Improved I/O Balance

26 Storage Optimization Analyze and Plan Capacity Predict Future Storage Needs Chart Trends in Capacity Usage Identify Storage Management Issues Overallocated Tablespaces Fastest Growing Datafiles Impending Out of Space Conditions

27 Capacity Manager for Oracle Single view of storage across all databases, based on priority and/or criticality

28 Aggregate Allocation and Largest Databases

29 Database Allocation and Largest Tablespaces

30 Aggregate Growth and Fastest Growing Databases

31 Database Growth and Fastest Growing Tablespaces

32 Aggregate Allocation by Segment Type

33 What If Analysis Expected Changes

34 User Interface Print and save reports

35 In-Context Launch of LiveReorg

36 Storage Optimization Analyze and Plan Capacity Predict Future Storage Needs Chart Trends in Capacity Usage Identify Storage Management Issues Overallocated Tablespaces Fastest Growing Datafiles Impending Out of Space Conditions Optimize Database Storage Identify Fragmentation within Tablespaces Reorganize Objects and Reclaim Space Optimize Storage Performance w/out Downtime Restructure for Improved I/O Balance

37 Oracle Fragmentation Oracle databases experience 3 types of fragmentation Segment, Block and Row Segment Fragmentation Excessive extents place a load on the data dictionary Affects free space as well as allocated space Resolved with the adoption of LMT (locally managed tablespaces) in release 8i Note: LMT still not deployed in most SAP deployments

38 Block Fragmentation Block Fragmentation HWM (high water mark) vs Actual Used Wasted Space causes excessive I/O Excessive I/O slows query performance and application response time Before Reorg After Reorg

39 Affects of Block Fragmentation SAP Table: ANLV Table Size: 37.07MB Oracle: Block Fragmentation: 59.25% Row Fragmentation: 0.0% Performance Metric Before Reorg After Reorg Percentage Difference Transactions Per Sec (TPS) % Rows Returned During Test 6,678 11, % Average Time %

40 Row Fragmentation Row Fragmentation Chained rows reside in multiple Oracle blocks The data in chained rows exceeds the block size, causing relocation of these rows to a new block Accessing chained rows requires traversal of each block in each chain A query to a chained row generates at least 100% more overhead than a query to an unchained row

41 Affects of Row Fragmentation Environment SAP Report: Tables Accessed: 10 Reorg Table: ZLSDRS0039 VBAP Oracle: Table Size: 25.27GB Block Fragmentation: 0.00% Row Fragmentation: 3.96% Results Report generation time improved by an average of 27.90% (conducted over four runs)

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44 How to LiveReorg a Database

45 How to LiveReorg a Database Reorg Table 1 Production Table 1. Create a copy of the table 2 2. Queue change transactions

46 How to LiveReorg a Database Reorg Table Production Table 1. Create a copy of the table 2. Queue change transactions and synch reorg table upon completion of table copy 2

47 How to LiveReorg a Database Production Table Original Table 1. Create a copy of the table 2. Queue change transactions and synch reorg table upon completion of table copy 3. Switch users to the new table by renaming the reorg table to the production name

48 Live Space Management Analysis and management of database storage Capacity planning and trending Exception reporting of space problems Before... Fast isolation of storage inefficiencies Live reorganisation and restructure

49 Live Space Management Analysis and management of database storage Capacity planning and trending Exception reporting of space problems... After! Fast isolation of storage inefficiencies Live reorganisation and restructure

50 Avoiding Downtime with LiveReorg SAP Table (DBERDZ) 1.86TB of data, 312GB of indexes Live Transactions Processed Inserts: 7,236,202 Updates: 5,276,000 Deletes: 90,492 Duration of Reorg (downtime saved) Table Copy: 95 hours Index Creation: 33 hours LiveReorg Continuous Performance Over 12.6M transactions No Downtime Eliminated 5.3 days of outage

51 Saving Storage with LiveReorg SAP Table (DBERCHZ) Aggressively archived database purge Storage Footprint Before Reorg: 2,986 GB (data and index) After Reorg: 2,084 GB (data and index) Storage Savings: 902 GB in a single reorg ( = 30%) Performance Total Reorg Time: 12.5 hours

52 Quest Space Manager with LiveReorg Performance and Storage Improved response times for online users Faster run times for large report jobs Optimised storage allocation Low Impact Light-weight collection of changed data Protects Availability Zero-downtime with online switch Validated by SAP proven scalability and support

53 Case Studies LiveReorg Customers Copyright 2006 Quest Software

54 I/O Performance... Airline: Resolving Row Fragmentation Environment SAP Report: Tables Accessed: 10 Reorg Table: ZLSDRS0039 VBAP Oracle: Table Size: 25.27GB Block Fragmentation: 0.00% Row Fragmentation: 3.96% Results (after eliminating row chains) Report generation time improved by an average of 27.90% conducted over four runs

55 I/O Performance... Retail: Data Warehouse Elevated I/O Waits (single-block reads) over a sustained period Associated increase in Buffer Busy Waits Event Sec Waited Waits/Sec Waits single block read buffer busy multi-block read latch direct path read direct path write

56 I/O Performance... Retail: Data Warehouse Buffer Busy Waits Undo header or block Configure more rollback segments Data block Verify transactions that are run against the affected object INSERTs Increase freelists on the affected object, reorg to apply to historical data (that preceded the decision to change value) SELECTs Optimise the storage of the affected object: minimise the number of extents and reorg the objects

57 I/O Performance... Telco: Billing Database Performance spike in Latch Free waits cache buffer chains latch free waits = hot blocks! Latch Sleeps Gets Misses Miss Rate Sleep Rate cache buffers chains library cache messages cache buffers lru chain shared pool

58 Cache Buffer Chain Latch Waits Contention for CBC latches occurs when one or more of the following occur: Several users are frequently accessing the same data block Several users are frequently accessing several data blocks protected by the same CBC latch Frequently accessed cache buffers chains contain a large number of data block headers, slowing their scan time, and causing the CBC latch to be held for an excessive duration Potential Solutions Rewrite the application code to avoid hot blocks in the database Reorganise the objects with a higher PCTFREE to reduce the data density in each block Add more CBC latches

59 I/O Performance... Banking: ERP Application Elevated I/O Waits single-block reads + multi-block reads Increased Buffer Busy Waits

60 I/O Performance... University: E-Learning System Unbalanced I/O peaks indicate I/O imbalance indicator line set at 15 I/Os per second

61 I/O Performance... University: E-Learning System Unbalanced I/O resolved! I/O is balanced and peaks are eliminated after resolution

62 Quest Application Advantage Quest Application Advantage allows application teams to deliver, manage and control complex application environments Only Quest provides the deepest understanding of the application - from the end user to the database

63 Questions?

64 Thank You Copyright 2006 Quest Software