oracle database 11g - self management features ... · pdf fileoracle database 11g - self...
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Oracle Database 11g - Self Management Features, Diagnostics & Tuning
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Zohar Elkayam, Service Director: Database Solutions
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Agenda
• Automatic Workload Repository – AWR • Active Session History - ASH • Automatic Database Diagnostic Monitor – ADDM • Automatic Storage Management - ASM • Automatic Memory Management - AMM • Automatic SQL Tuning: Tuning Advisor, Automatic Tuning
Optimizer, Baselines, SQL Tuning Sets and SQL Profiles • Automatic Maintenance Tasks and Tools • Automatic DOP and Parallel Statement Queuing • Backup, Recovery and Flashback
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?מי אני
ראש תחום בסיסי נתונים ויועץ , זהר אלקיים•
GlassHouse Technologies-אורקל בכיר ב
•DBA (תשתיתי ואפליקטיבי)1998אורקל מאז
יכולות Oracle SQL"הספר העורך הטכני של •
"המדריך לשולף המהיר, מתקדמות
zoharelkayam.wordpress.com :בלוגר•
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About GlassHouse Technologies
• We provides IT Infrastructure services & solutions in most fields: storage, OS, virtualization, backup and databases
• Worldwide operations: US, UK, Swiss, Israel, Turkey and Australia
• Over 200 employees in Israel alone and ~1000 worldwide.
• Formally known as Integrity systems, in the databases business since 1995
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Who Tunes?
The people who are involved with tuning: • Database administrators
• Application architects
• Application designers
• Application developers
• System administrators
• Storage administrators
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What Does the DBA Tune?
Performance tuning areas: • Application:
• SQL statement performance • Change management
• Instance tuning: • Memory • Database structure • Instance configuration
• Operating system interactions: • I/O • Swap • Parameters
Shared with developers
Shared with SA
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General Tuning Session
All tuning sessions have the same procedure: 1. Define the problem and state the goal. 2. Collect current performance statistics. 3. Consider some common performance errors. 4. Build a trial solution. 5. Implement and measure the change. 6. Decide: “Did the solution meet the goal?”
• No? Then go to step 3 and repeat. • Yes? Then create a new baseline.
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Effective Tuning Goals
Effective tuning goals are:
– Specific
– Measurable
– Achievable
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How to Tune
The procedures used to tune depend on the tool. – Basic tools:
• Dynamic performance views • Statistics • Metrics • Enterprise Manager pages
– AWR or Statspack – Automatic Database Diagnostic Monitor (ADDM) – Various custom DBA scripts
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Using Features of the Packs
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AWR – Automatic Workload Repository
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Automatic Workload Repository
• Performance Data Warehouse for 10g/11g • AWR collects and stores performance data
– In-memory component (V$/Metric views) – “Persisted” in WR tables (SYSAUX) – 162 tables – WRI$, WRH$, WRM$
• Self managing “out of the box” • Set retention, frequency, baseline
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AWR – “Statspack on Steroids”
• Similar to STATSPACK “snapshots”
• AWR snapshot automatically analyzed
• Accessible via GUI and API/SQL
• Reportable – AWRRPT.SQL
• High-impact SQL captured differently
• Stores session level info as well
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Automatic Workload Repository: Overview
SGA
V$ DBA_*
ADDM Self-tuning component
Self-tuning component
… Internal clients
External clients EM SQL*Plus …
Efficient in-memory
statistics collection
AWR
snapshots MMON
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What does the AWR collect?
Advisor
results
AWR
SQL
statistics
Base
statistics
Metrics ASH
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Database Control and AWR
Edit snapshot parameters
Run AWR report
Manage snapshots
Manage baselines
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Generating AWR Reports in EM
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Generating AWR Reports in EM
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API - DBMS_WORKLOAD_REPOSITORY
• Scripts in $OH/rdbms/admin – awrrpt.sql AWR report (STATSPACK)
– awrddrpt.sql AWR Diff-Diff report
– awrextr.sql frontends a DataPump dump
– awrinfo.sql Space usage by AWR/ASH
– awrsqrpt.sql Execution statistics for specific SQL statement
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Generating AWR Reports in SQL*Plus
• We can use AWRRPT.SQL if we have access to it (usually server side script)
• We can use the actual procedures for HTML or TEXT output:
DBMS_WORKLOAD_REPOSITORY.AWRRPT_REPORT_TEXT (
L_DBID NUMBER IN,
L_INST_NUM NUMBER IN,
L_BID NUMBER IN,
L_EID NUMBER IN,
L_OPTIONS NUMBER IN DEFAULT NULL);
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Manual AWRRPT command
Set heading off
Set trimspool off
Set linesize 80
Set feedback off
Set termout on
Spool awr_from_console.txt
select output from
table(dbms_workload_repository.awr_report_text(
&dbid, &inst_num, &bid, &eid));
spool off;
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SQL> Spool awr_from_console.txt
SQL> select output from table(dbms_workload_repository.awr_report_text(&dbid,
&inst_num, &bid, &eid));
Enter value for dbid: 2492639615
Enter value for inst_num: 1
Enter value for bid: 953
Enter value for eid: 954
old 1: select output from
table(dbms_workload_repository.awr_report_text(&dbid, &inst_num, &bid, &eid))
new 1: select output from
table(dbms_workload_repository.awr_report_text(2492639615, 1, 953, 954))
WORKLOAD REPOSITORY report for
DB Name DB Id Instance Inst Num Startup Time Release RAC
------------ ----------- ------------ -------- --------------- ----------- ---
GHTEST 2492639615 ghtest 1 15-Aug-11 09:18 11.2.0.1.0 NO
[…awr report…]
SQL> spool off
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Reading AWR report
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How to read AWR?
• Depends on the type of application – OLTP – OLAP/DWH
• Depends on the problem – I/O – is it reading? Is it writing? – Long queries? – Is it a memory problem? – Is it high CPU load?
• Everyone has their own reading style
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Where to start? AWR Header
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The Main Report Menu
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Top 5 Timed Events
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Time Model Statistics
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Foreground Wait Class
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Foreground and Background Wait Events
• Breakdown of wait class
• Shows where the waits are
• Usually TMI but sometimes important
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SQL Statistics Menu
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Top SQL Reports SQL by Elapsed Time
SQL by CPU Time
SQL by Executions
SQL by Buffer Gets
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IO Stats
• Tablespace IO Stats
• File IO Stats
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Segment Stats - Reads
• Top Logical reads
• Top Physical reads
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Segment Stats - Writes
• Segments by Physical Writes
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Common Tuning Problems
• The most common tuning problems: – Inefficient or high-load SQL statements – Suboptimal use of Oracle Database by the application – Undersized memory structures – Concurrency issues – I/O issues – Database configuration issues – Short-lived performance problems – Degradation of database performance over time – Unexpected performance regression after environment changes – Locking issues
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Tip: Using AWR Formatter add-on
• AWR Formatter 1.6 by Tyler Muth is a great add-on for Chrome browser that helps reading AWR html reports
• It allows "Smart Text" conversion of gets / reads / bytes to KB / MB / GB / TB. You can click the orange text to cycle through these units
• Combined view of key Top SQL sections • Link to MOS note for "PX" events • I/O Graphs of tablespace activity • … and more
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Short Demo for AWR and AWR formatter
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Workload Repository Snapshot
SYSAUX
SGA
In-memory statistics
6:00 a.m. 7:00 a.m.
8:00 a.m.
Snapshot 1 Snapshot 2 Snapshot 3
Snapshot 4 9:00 a.m.
9:30 a.m.
ADDM finds
top problems. MMON
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AWR Snapshot Settings DBMS_WORKLOAD_REPOSITORY.MODIFY_SNAPSHOT_SETTINGS (
retention IN NUMBER DEFAULT NULL,
interval IN NUMBER DEFAULT NULL,
topnsql IN NUMBER DEFAULT NULL);
DBMS_WORKLOAD_REPOSITORY.MODIFY_SNAPSHOT_SETTINGS (
retention => 30 * 24 * 60,
interval => 15);
AWR Snapshot Settings best practice:
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ASH - Active Session History
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ASH – What’s up with sessions
• Historical view of active sessions
• V$ACTIVE_SESSION_HISTORY
• Active sessions sampled every second
• Stored in circular memory buffer
• Every 10th sample persisted in AWR
• Enables “after-the-fact” analysis!!!
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ASH – Session states exposed!
• “On-the-spot” analysis • Retroactive analysis
– From memory buffer (V$ACTIVE_SESSION_HISTORY) – From persisted AWR data
(WRH$_ACTIVE_SESSION_HISTORY connected via SNAP_ID) • High load SQL execution behavior • Determine Blocking sessions and “hot”
segments • SESSION_STATE : “ON CPU” or “WAITING”
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Active Session History: Mechanics
SGA
Statistics
V$SESSION
ASH
Recent history
Rolling
buffer
Workload repository
1sec
1sec
1sec
Every
60 minutes
MMON
MMNL
When 66% full
V$ACTIVE_SESSION_HISTORY
WRH$_ACTIVE_SESSION_HISTORY (partitioned)
No use
of SQL
Direct path
inserts
DBA_HIST_ACTIVE_SESSION_HISTORY
1 out
of 10
Viewers go
unlatched.
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ASH – What is happening to me?!
SQL> select event, seq#, p1, p2, p3, blocking_session
2 from v$active_session_history
3 where session_id = 113 and session_serial# = 333;
EVENT Seq# P1 P2 P3 BlkSess
---------------------------- ------- ------------ ------------ ------------ ------
db file sequential read 34786 29 182279 1 0
db file scattered read 34870 19 103899 8 0
db file sequential read 34954 29 183370 1 0
db file scattered read 35040 19 102299 8 0
enq: TX - row lock contention 35119 1415053318 524322 11255 142
db file scattered read 35204 19 99643 8 0
db file scattered read 35207 19 102371 8 0
enq: TX - row lock contention 35220 1415053318 524322 11255 142
db file scattered read 35232 19 100019 8 0
enq: TX - row lock contention 35243 1415053318 524322 11255 142
db file scattered read 35256 19 102747 8 0
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ASH Report
• Summary of all user activity over the selected period
• Drill down to a more granular period • List details of only a Session, SQL ID, Wait
Class, Service, Module or Client ID over a particular period
• “Top” Background events, P1-P3 values, etc. • $OH/rdbms/admin/ashrpt.sql + GUI
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Generating ASH Reports
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ASH in Wait Drilldown
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ASH Report: General Section
V$ACTIVE_SESSION_HISTORY
DBA_HIST_ACTIVE_SESSION_HISTORY
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ASH Report Structure
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ASH Report: Activity Over Time
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ASH Text report Activity Over Time -> Analysis period is divided into smaller time slots -> Top 3 events are reported in each of those slots -> 'Slot Count' shows the number of ASH samples in that slot -> 'Event Count' shows the number of ASH samples waiting for that event in that slot -> '% Event' is 'Event Count' over all ASH samples in the analysis period Slot Event Slot Time (Duration) Count Event Count % Event -------------------- -------- ------------------------------ -------- ------- 19:50:18 (42 secs) 86 enq: TX - row lock contention 43 8.10 db file scattered read 39 7.34 CPU + Wait for CPU 4 0.75 19:51:00 (1.0 min) 119 enq: TX - row lock contention 58 10.92 db file scattered read 50 9.42 CPU + Wait for CPU 11 2.07 19:52:00 (1.0 min) 126 enq: TX - row lock contention 60 11.30 db file scattered read 50 9.42 CPU + Wait for CPU 13 2.45 19:53:00 (1.0 min) 123 enq: TX - row lock contention 59 11.11 db file scattered read 49 9.23 CPU + Wait for CPU 15 2.82 19:54:00 (38 secs) 77 enq: TX - row lock contention 37 6.97 db file scattered read 36 6.78 CPU + Wait for CPU 3 0.56
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ADDM - Automatic Database Diagnostic Monitor
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ADDM – Your unpaid Tuning Expert!
• Should be the starting point for most investigations
• Runs after every AWR snapshot
• Determines and records performance issue
• Recommends corrective action
• Generates probable benefit
• Suggest use of other advisors
• Common currency - “DB Time” (qualitative!)
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ADDM Performance Monitoring layout
Snapshots
ADDM
In-memory
statistics
AWR
SGA
60 minutes
ADDM results
MMON
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Database Control and ADDM Findings
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ADDM Analysis Results
1
2
3
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ADDM Recommendations
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Database Control and ADDM Task
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Top Performance Issues Detected
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ADDM – Findings/Recommendations
• Hardware changes
• Database-configuration changes
• Schema-level changes
• Application changes
• Using other advisors (for example) – SQL Tuning / Access Advisor
– Segment Advisor
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ADDM – Accessing “ADDuM”
• GUI! (easiest because of linkage) • $OH/rdbms/admin/addmrpt.sql • API – DBMS_ADVISOR In-built PL/SQL • Look at following views
– DBA_ADVISOR_LOG – DBA_ADVISOR_FINDINGS – DBA_ADVISOR_RECOMMENDATIONS – DBA_ADVISOR_ACTIONS – DBA_ADVISOR_RATIONALE
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SELECT dbms_advisor.GET_TASK_REPORT(task_name)
FROM dba_advisor_tasks
WHERE task_id = (
SELECT max(t.task_id)
FROM dba_advisor_tasks t,
dba_advisor_log l
WHERE t.task_id = l.task_id AND
t.advisor_name = 'ADDM' AND
l.status = 'COMPLETED');
SQL> @?/rdbms/admin/addmrpt
…
Enter value for begin_snap: 8
Enter value for end_snap: 10
…
Enter value for report_name:
Generating the ADDM report for this analysis ...
Retrieving ADDM Reports by Using SQL
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ADDM – Don’t stare at the screen!
SQL> select type, count(*) from dba_advisor_findings
where task_id in
(select task_id from dba_advisor_log
where execution_start > sysdate - 1)
group by type;
TYPE COUNT(*)
----------- --------
INFORMATION 46
WARNING 1
SYMPTOM 49
PROBLEM 79
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ADDM – Don’t stare at the screen! SQL> select count(*) count, message from dba_advisor_findings
where task_id in
(select task_id from dba_advisor_log
where execution_start > sysdate - 1)
and type = 'PROBLEM‘ group by message order by 1 desc;
COUNT MESSAGE
----- -----------------------------------------------------------------
24 SQL statements consuming significant database time were found.
24 SQL statements were found waiting for row lock waits.
24 Individual database segments responsible for significant user I/O wait were found.
4 The execution plan of this statement can be improved by creating one or more indices
1 PL/SQL execution consumed significant database time.
1 Significant virtual memory paging was detected on the host operating system.
1 The throughput of the I/O subsystem was significantly lower than expected
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ASM – Automatic Storage Management
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Predictably Delivers
on Performance &
Availability
SLA’s
Increases Storage
Utilization and Agility
Simplifies and Automates
Database Storage
Management
Automatic Storage Management
• A storage manager designed to manage Oracle 10g/11g database files – offered at no additional cost – Volume Manager
– File System
– Clustering capabilities
Cost and Complexity Without Compromising Performance or Availability
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Why use ASM?
• Fully Oracle integrated storage management system
• Provide an easy flexible layer to control your files & storage
• Provide more redundancy layer over your storage system
• Provide an integrated cluster file system for HA use
• Automatic tasks – Auto rebalancing (RBAL), auto striping - SAME
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ASM Enhancements in 11gR2
• Improved Management – ASM Install & Configuration
Assistant (ASMCA)
– Full Featured ASMCMD
– ASM File Access Control
– ASM Disk Group Rename
– Datafile to Disk Mapping
• Tunable Performance – Intelligent Data Placement
Infrequently Accessed
Data
Frequently Accessed
Data
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Automatic rebalancing
• ASM automatically rebalances when the configuration of a disk group changes. By default, the ALTER DISKGROUP statement does not wait until the operation is complete before returning. Query the V$ASM_OPERATION view to monitor the status of this operation.
• ASM automatically redistributes the file contents and eliminates the need for downtime when redistributing the content
• Control Rebalancing using the REBALANCE POWER clause in statements that add, drop, or resize disks.
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Checking Rebalancing Operations
• ASM_POWER_LIMIT -The maximum power for a rebalancing operation on an ASM instance. The valid values range from 0 to 11, with 1 being the default.
• The higher the limit the more resources are allocated resulting in faster rebalancing operations
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select GROUP_NUMBER, OPERATION, STATE, POWER, ACTUAL, SOFAR, ST_WORK,
EST_RATE, EST_MINUTES from v$asm_operation;
GROUP_NUMBER OPERA STAT POWER ACTUAL SOFAR EST_WORK EST_RATE
EST_MINUTES
------------ ----- ---- ---------- ---------- ---------- ---------- ----------
2 REBAL RUN 1 1 2364 15437 300 43
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Oracle Managed Files
• OMF automatically creates files in designated locations. OMF also names files and removes them while releasing space when tablespaces or files are deleted
• Alter tablespace my_tbs add datafile size 5G;
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AMM - Automatic Memory Management
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Oracle Database Architecture
Spfile
Temp
Data file
Undo
PMON SMON RECO MMON
MMNL
PSP0
MMAN DBWn LGWR CKPT
CJQ0
S000
D000 QMNC
Qnnn FMON
ARCn CTWR
RVWR
Fixed
size
Large
pool
Java
pool
Streams
pool
Default
buffer
cache
Keep
buffer
cache
Recycle
buffer
cache
nK
buffer
caches
Redo
log
buffer
ASH
buffer
Sort
extent
pool
Global
context
pool
SGA
Flash
back
buffer
Instance
Flashback
logs
Redo log
files
Archive
log files
Control
files
SYSTEM
SYSAUX Change
tracking
file
Password
file
Shared
pool
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Dynamic SGA • Implements an infrastructure to allow the server to
change its SGA configuration without shutting down the instance
• SGA size is limited by SGA_MAX_SIZE, which:
– Reserves virtual memory address space at instance startup
– Cannot be changed dynamically
• Allows for certain SGA components to be dynamically resized
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Memory Advisories • Buffer Cache Advice (introduced in 9i R1):
– V$DB_CACHE_ADVICE
– Predicts physical reads for different cache sizes
• Shared Pool Advice (introduced in 9i R2): – V$SHARED_POOL_ADVICE
– Predicts parse time savings from having different sizes of the shared pool
• Java Pool Advice (introduced in 9i R2): – V$JAVA_POOL_ADVICE
– Predicts Java class load time savings from having different sizes of Java pool
• Streams Pool Advice (introduced in 10g R2) – V$STREAMS_POOL_ADVICE
– Predicts spill and unspill activity for various sizes
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Automatic Shared Memory Management: Overview
• Uses dynamic SGA and memory advisors to automatically adapt to workload changes
• Maximizes memory utilization • Helps eliminate
out-of-memory errors
• Avoids relearning when using SPFILE
Online users Batch jobs
Buffer cache
Large pool
Shared pool
Java pool
Buffer cache
Large pool
Shared pool
Java pool
Online users Batch jobs
Streams pool Streams pool
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SGA Sizing Parameters: Overview • With ASMM, five important SGA components can be
automatically sized.
• Nondefault buffer pools are not auto-tuned
• Log buffer is not a dynamic component but has a good default.
DB_KEEP_CACHE_SIZE
DB_RECYCLE_CACHE_SIZE
DB_nK_CACHE_SIZE
RESULT_CACHE_MAX_SIZE
SGA_TARGET
LOG_BUFFER SHARED_POOL_SIZE
DB_CACHE_SIZE
LARGE_POOL_SIZE
JAVA_POOL_SIZE
STREAMS_POOL_SIZE
Auto-tuned
parameters
Manual
dynamic parameters
Manual
static parameters
SGA_MAX_SIZE
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Dynamic SGA Transfer Modes
• ASMM IMMEDIATE transfer mode: – Out-of-memory (ORA-04031) errors – Partial granules can be used.
• ASMM DEFERRED transfer mode: – Transparently executed in the background – Partial granules can be used.
• MANUAL transfer mode: – Used with ALTER SYSTEM commands – Resize must use full granules.
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Memory Broker Architecture Statistic
deltas across
different time
periods Circular SGA
buffer of stats
captured by
MMON
Memory Broker Policy Module
Add two granules to shared pool.
Output: resize
requests Trade-off
different
components
benefit/lost
MMAN transfers
the memory.
resize
queue
MMAN
MMON
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Behavior of Auto-Tuned SGA Parameters
• When SGA_TARGET is not set or is set to zero: – Auto-tuned parameters are explicitly set – Note: SHARED_POOL_SIZE includes internal startup
overhead. Value may need to be increased from previous releases.
• When SGA_TARGET is set to a nonzero value and auto-tuned parameters are: – Not set, the auto-tuned parameters default to zero – Set, a nonzero value is a lower bound
• When automatically adjusted. Current values in megabytes are shown by:
SELECT component, current_size/1024/1024 FROM V$SGA_DYNAMIC_COMPONENTS;
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Behavior of Manually Tuned SGA Parameters
• Manually tuned components are: – KEEP and RECYCLE buffer caches
– Nondefault block size caches
– LOG_BUFFER
• Manually tuned components are user specified.
• Manually tuned components are included in SGA_TARGET to precisely control the SGA size.
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Resizing SGA_TARGET
• The SGA_TARGET initialization parameter: – Is dynamic – Can be increased up to SGA_MAX_SIZE – Can be reduced until all components reach minimum size – Changes affect only automatically sized components
• SGA_TARGET includes everything in the SGA: – Fixed SGA and other internal allocations – Automatically sized SGA components – Manual SGA components
• SGA_TARGET allows precise sizing of the total shared memory allocation by the Oracle server
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Disabling Automatic Shared Memory Management
• Setting SGA_TARGET to zero disables auto-tuning.
• Auto-tuned parameters are set to their current sizes.
• SGA size as a whole is unaffected.
SGA size = 8 GB
Parameters: SGA_TARGET = 8G
SHARED_POOL_SIZE=1G
SGA size = 8 GB
Original values
SGA_TARGET=0
Parameters: SGA_TARGET = 0
DB_CACHE_SIZE = 4G
SHARED_POOL_SIZE = 1.5G
LARGE_POOL_SIZE = 512M
JAVA_POOL_SIZE = 512M
STREAMS_POOL_SIZE = 512M
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Automatic Memory Management: Overview AMM Disabled AMM Enabled
Untunable
PGA
Free
Buffer cache
Large pool
Shared pool
Java pool
Streams pool
SQL areas
Other SGA
SGA target
PGA target
OLTP BATCH
Buffer cache
Large pool
Shared pool
Java pool
Streams pool
SQL areas
Other SGA
Untunable
PGA
Free
BATCH
Buffer cache
Large pool
Shared pool
Java pool
Streams pool
Other SGA
SQL areas
Untunable
PGA
Memory target
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Automatic Memory Management: Overview AMM
Memory target
Memory
max target
250 MB
350 MB
ALTER SYSTEM SET
MEMORY_TARGET=300M;
AMM
Memory target
Memory
max target
300 MB
350 MB
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Oracle Database Memory Parameters
DB_KEEP_CACHE_SIZE
DB_RECYCLE_CACHE_SIZE
DB_nK_CACHE_SIZE
LOG_BUFFER
RESULT_CACHE_SIZE
SHARED_POOL_SIZE
DB_CACHE_SIZE
LARGE_POOL_SIZE
JAVA_POOL_SIZE
STREAMS_POOL_SIZE
SGA_TARGET
SGA_MAX_SIZE MEMORY_MAX_TARGET
MEMORY_TARGET
Others
PGA_AGGREGATE_TARGET
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Automatic Memory Parameter Dependency
ST+PAT<=MT<=MMT
MT>0
ST>0 & PAT>0
ST>0 & PAT=0 PAT=MT-ST
ST=0 & PAT>0 ST=min(MT-PAT,SMS)
ST=60%MT
PAT=40%MT
MMT>0 MT=0
MMT=MT MMT=0
MT=0
Y Y N
N
Y
Both SGA and PGA can grow and shrink automatically.
ST>0
SGA and PGA are separately
auto-tuned.
Y
Only PGA is auto-tuned.
N
MT can be
dynamically
changed later.
SGA and PGA cannot
grow and shrink automatically.
Minimum possible values N
N
N
Y
Y
Y
N
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Enabling Automatic Memory Management
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Monitoring Automatic Memory Management
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Monitoring Automatic Memory Management
• To monitor the decisions made by Automatic Memory Management, use the following views: – V$MEMORY_DYNAMIC_COMPONENTS (displays the
current status of all memory components) – V$MEMORY_RESIZE_OPS (displays a circular history
buffer of the last 800 completed memory resize requests) – V$MEMORY_CURRENT_RESIZE_OPS (displays current
memory resize operations)
• All SGA and PGA equivalents are still in place for backward compatibility.
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SQL Tuning: SQL Tuning Advisor, Automatic SQL Tuning and
SQL Plan Management
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SQL Tuning Loop: SQL Tuning in Oracle 10g Some meaningful automation
but the DBA is still required
Workload
SQL Tuning Candidates SQL Tuning
Advisor
ADDM
AWR
one hour
Generate
Recommendations
DBA
Invoke Advisor
Implement
DBA
Evaluate
Recommendations
DBA
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SQL Tuning Advisor: Overview
• Comprehensive SQL tuning
– Detect stale or missing statistics
– Tune the SQL plan (SQL profile)
– Add missing indexes
– Restructure SQL statements SQL Tuning Advisor
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Using the SQL Tuning Advisor
• Use the SQL Tuning Advisor to analyze SQL statements and obtain performance recommendations.
• Sources for SQL Tuning Advisor to analyze: – Top Activity: Analyzes the top SQL statements currently
active – SQL tuning sets: Analyzes a set of SQL statements you
provide – Historical SQL (AWR): Analyzes SQL statements from
statements collected by AWR snapshots
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SQL Tuning Advisor Options
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SQL Tuning Advisor Recommendations
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Using the SQL Tuning Advisor: Example
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Using the SQL Access Advisor Specify the scope
Review the selected options
Specify the workload
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View Recommendations
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View Recommendation Details
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SQL Tuning Loop: SQL Tuning in Oracle 11g
It’s Automatic!
Choose
Candidate
SQL
one
week
Workload
SQL Tuning
Candidates
Test SQL Profiles Implement
SQL Profiles
Generate
Recommendations
or SQL Profiles
AWR DBA
View Reports /
Control
Process
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Automatic SQL Tuning: Overview
• Automatic SQL Tuning automates the entire SQL tuning process and replaces manual SQL tuning.
• Optimizer modes: – Normal mode
– Tuning mode or Automatic Tuning Optimizer (ATO)
• SQL Tuning Advisor is used to access tuning mode.
• You should use tuning mode only for high-load SQL statements.
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Automatic SQL Tuning Advisor
• Runs nightly – Scheduling handled by Automated Maintenance Task (AUTOTASK)
framework • Uses scheduler’s Maintenance Window • Uses DEFAULT_MAINTENANCE_PLAN (25% CPU) • DBA_AUTOTASK_* views and DBMS_AUTO_TASK_ADMIN package
– By default job is enabled on new installs, disabled on upgrades • Configurable
– DBA_ADVISOR_* views and DBMS_SQLTUNE package – ACCEPT_SQL_PROFILE, MAX_SQL_PROFILES_PER_EXEC,
MAX_AUTO_SQL_PROFILES, EXECUTION_DAYS_TO_EXPIRE, TIME_LIMIT, LOCAL_TIME_LIMIT, TEST_EXECUTE, etc.
• Can automatically implement plans with 3x improvement
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SQL Statement Profiling • Statement statistics are key inputs to the optimizer.
• ATO verifies statement statistics such as:
– Predicate selectivity
– Optimizer settings (FIRST_ROWS versus ALL_ROWS)
• Automatic Tuning Optimizer (ATO) uses:
– Dynamic sampling
– Partial execution of the statement
– Past execution history statistics of the statement
• ATO builds a profile if statistics were generated:
exec :profile_name := -
dbms_sqltune.accept_sql_profile( -
task_name =>'my_sql_tuning_task');
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Plan Tuning Flow and SQL Profile Creation
Optimizer (Tuning mode)
Create Submit
Output
SQL
profile
SQL Tuning
Advisor
Database
users
Well-tuned
plan
Optimizer (Normal mode)
Use
No application
code change
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Automatic SQL Tuning Advisor
1. Identify candidates for SQL Tuning
2. Tune each statement individually by calling the SQL Tuning Advisor
3. Test SQL Profiles by executing the SQL statement
4. Optionally, automatically implement SQL Profiles with 3x improvement
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Picking candidate SQL
AWR
Average Exec Hourly
1. Pull the top queries from the past week into four buckets:
Top for the past week
Top for any day in the past week
Top in any hour (single snapshot)
Top by average single execution
2. Combine four buckets into one, assigning weights
3. Cap at 150 queries per bucket
Candidate List
Daily Weekly
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Automatic SQL Tuning Advisor
• Some SQL is ineligible for automatic tuning (they can still be manually submitted to the SQL Tuning Advisor)
– Parallel queries – Ad-hoc/rarely repeated queries (not repeated within a
week) – Long-running queries – Recursive SQL – DML (insert/update) or DDL (create table as select) – Statements that were recently processed (within the
past month)
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SQL Plan Management: Overview
• SQL Plan Management is automatically controlled SQL plan evolution.
• Optimizer automatically manages SQL plan baselines. – Only known and verified plans are used. – Automatic plan verification requires SQL Tuning Pack License!
• Plan changes are automatically verified by default (can be changed manual). – Only comparable or better plans are subsequently used.
• The plan baseline can be seeded for critical SQL with SQL tuning set (STS) from SQL Performance Analyzer.
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SQL Plan Management
• Next generation of Stored Outlines (Outlines are officially deprecated in 11g but can be converted to baselines): – CONTROLS plan evolution – GURANTEES plan stability
• Works hand-in-hand with Automatic SQL Tuning Advisor • Optimizer remembers SQL Plans
– Only known and verified plans are used – Plan changes can be tested and verified automatically or manually – Actually runs the statement to verify execution – evaluates real-
world performance – Plans can be transported between databases (e.g. QA -> Prod)
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SQL Plan Management: When to use?
Protects against execution plan changes in many situations: • Database Upgrades
– Use OPTIMIZER_FEATURES_ENABLE
• System and Data Changes – Object or System Statistics – Session or System Parameters – Schema Changes (e.g. add index)
• Deployment of new application module – Can import plans that were pre-verified on a test system
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SQL Plan Baseline: Tuning in 10g
1. First SQL Execution: Hard Parse
2. Environmental Change: stats job, smaller UGA, etc. 1. Plan Invalidated: Hard Parse results in new plan
HJ
HJ
GB
Parse Execute Good Plan
NL
NL
GB
Parse Execute Bad Plan!
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SQL Plan Baseline: when using 11g 1. First SQL Execution: Hard Parse, STORE “BASELINE”
Parse
HJ
HJ
GB
Statement log
Plan history
HJ
HJ
GB
Plan baseline
Execute Good Plan
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SQL Plan Baseline: when using 11g 2. Environmental Change, Plan Invalidated, Hard Parse – NEW PLAN IS NOT
EXECUTED BUT MARKED FOR VERIFICATION
Statement log
Plan history
HJ
HJ
GB
Plan baseline
NL
NL
GB
Parse
GB
NL
NL
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SQL Plan Baseline: when using 11g 3. BASELINE (ORIGINAL) PLAN IS EXECUTED
Execute Good Plan!
Parse
HJ
HJ
GB
Statement log
Plan history
HJ
HJ
GB
Plan baseline GB
NL
NL
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SQL Plan Baseline: when using 11g 4. AFTER LATER VERIFICATION, PLANS THAT IMPROVE PERFORMANCE
AUTOMATICALLY ADDED TO BASELINE
Statement log
Plan history
HJ
HJ
GB
Plan baseline GB
NL
NL
DBA Invoke or schedule
verification
Optimizer
checks if new
plan is as well
as or better
than old plan
Statement log
Plan history
Plan baselines
GB
NL
NL
HJ
HJ
GB
Plans which perform as well as or
better than original plan are added to
the plan baseline
GB
NL
NL
Plans which don’t
perform as well as the
original plan stay in the
plan history and are
marked unaccepted
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SQL Plan Baseline: Architecture
SQL management base
Statement log
SYSAUX
Plan verification before integration to baseline
Repeatable
SQL
statement
SQL
profile
Automatic
SQL tuning
task
Plan history
HJ
GB
HJ
HJ
GB
HJ
HJ
GB
HJ
…
Plan
baseline
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Loading SQL Plan Baselines
DBA
OPTIMIZER_CAPTURE_SQL_PLAN_BASELINES=TRUE
Plan history
1
2
3
4
Plan history dbms_spm
Staging
table
HJ
GB
HJ
Cursor
cache
Plan history
A
B
HJ
GB
HJ
HJ
GB
HJ
HJ
GB
HJ
HJ
GB
HJ
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Evolving SQL Plan Baselines
Plan history
Automatic
SQL Tuning
DBA
SQL
Tuning
Advisor
>? HJ
GB
HJ
HJ
GB
HJ
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--------------------------------------------------------------------------------
Evolve SQL Plan Baseline Report
--------------------------------------------------------------------------------
Inputs:
-------
SQL_HANDLE = SYS_SQL_593bc74fca8e6738
PLAN_NAME =
TIME_LIMIT = DBMS_SPM.AUTO_LIMIT
VERIFY = YES
COMMIT = YES
Plan: SYS_SQL_PLAN_ca8e6738a57b5fc2
-----------------------------------
Plan was verified: Time used .07 seconds.
Passed performance criterion: Compound improvement ratio >= 7.32.
Plan was changed to an accepted plan.
Baseline Plan Test Plan Improv. Ratio
------------- --------- -------------
Execution Status: COMPLETE COMPLETE
Rows Processed: 40 40
Elapsed Time(ms): 23 8 2.88
CPU Time(ms): 23 8 2.88
Buffer Gets: 450 61 7.38
Disk Reads: 0 0
Direct Writes: 0 0
Fetches: 0 0
Executions: 1 1
-------------------------------------------------------------------------------
Report Summary
-------------------------------------------------------------------------------
Number of SQL plan baselines verified: 1.
Number of SQL plan baselines evolved: 1.
SQL Plan Management
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Important Baseline SQL Plan Attributes
select signature, sql_handle, sql_text, plan_name, origin, enabled,
accepted, fixed, autopurge
from dba_sql_plan_baselines;
SIGNATURE SQL_HANDLE SQL_TEXT PLAN_NAME ORIGIN ENA ACC FIX AUT
--------- ------------ -------- ---------------- ------------ --- --- --- ---
8.062E+18 SYS_SQL_6fe2 select.. SYS_SQL_PLAN_1ea AUTO-CAPTURE YES NO NO YES
8.062E+18 SYS_SQL_6fe2 select.. SYS_SQL_PLAN_4be AUTO-CAPTURE YES YES NO YES
…
exec :cnt := dbms_spm.alter_sql_plan_baseline(-
sql_handle => 'SYS_SQL_37e0168b0…3efe', -
plan_name => 'SYS_SQL_PLAN_8dfc352f359901ea',-
attribute_name => 'ENABLED', attribute_value => 'NO');
Plan history
Enabled but
not accepted Enabled and
accepted HJ
GB
HJ
HJ
GB
HJ
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SQL Plan Selection
Plan part
of history? No HJ
GB
HJ
HJ
GB
HJ
HJ
GB
HJ > HJ
GB
HJ
No HJ
GB
HJ
Yes
Plan history
Plan
baseline
HJ
GB
HJ
HJ
GB
HJ
… HJ
GB
HJ
Yes
Plan part
of baseline? Yes
optimizer_use_sql_
plan_baselines=true? Yes
HJ
GB
HJ
No
No
Select baseline plan
with lowest best-cost
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Possible SQL Plan Manageability Scenarios
DBA
Plan history
HJ
GB
HJ
Database Upgrade
Oracle Database 10g
Oracle Database 11g
HJ
GB
HJ
Well-
tuned
plan
No plan
regressions
HJ
GB
HJ
Plan history
HJ
GB
HJ
New Application Deployment Production database
No plan
regressions
HJ
GB
HJ
HJ
GB
HJ
Development database
Well-tuned
plan
HJ
GB
HJ
Baseline
plans
staging table
DBA
Plan history
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SQL Performance Analyzer and SQL Plan Baseline Scenario
Plan history
HJ
GB
HJ
Oracle Database 10g
Oracle Database 11g
HJ
GB
HJ Well-tuned
plans
HJ
GB
HJ
HJ
GB
HJ
O_F_E=10
O_F_E=11
Regressing
statements
Before
change
After
change
HJ
GB
HJ
No plan
regressions
optimizer_features_enable
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Loading a SQL Plan Baseline Automatically
Oracle Database 10g
Well-
tuned
plans
Oracle Database 11g
optimizer_features_enable=10.2.0.2 optimizer_capture_sql_plan_baselines=true
Plan history
Plan
baseline
HJ
GB
HJ
HJ
GB
HJ
No plan
regressions Oracle Database 11g
optimizer_features_enable=11.1.0.1 optimizer_capture_sql_plan_baselines=true
Plan history
Plan
baseline
HJ
GB
HJ
HJ
GB
HJ
No plan
regressions
HJ
GB
HJ
New plan
waiting
verification
HJ
GB
HJ
HJ
GB
HJ
Oracle Database 11g
optimizer_features_enable=11.1.0.1 optimizer_capture_sql_plan_baselines=true
Plan history
Better
plans
HJ
GB
HJ
HJ
GB
HJ
HJ
GB
HJ
Plan baseline
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Purging SQL Management Base Policy
SQL> exec :cnt := dbms_spm.drop_sql_plan_baseline('SYS_SQL_37e0168b04e73efe');
SYSAUX
20% 1% 50% space
time
105
53
SQL Management
Base
Alert log
10%
SQL> exec dbms_spm.configure('SPACE_BUDGET_PERCENT',20);
SQL> exec dbms_spm.configure('PLAN_RETENTION_WEEKS',105);
DBA_SQL_MANAGEMENT_CONFIG
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Automatic Maintenance Tasks
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Automated Maintenance Tasks
• Default Autotask maintenance jobs: – Gathering optimizer statistics – Automatic segment advisor – Automatic SQL advisor
• Autotask Maintenance process: 1. The maintenance window opens. 2. The Autotask background process schedules jobs. 3. The Scheduler initiates jobs. 4. Resource Manager limits the impact of Autotask jobs.
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Automatic Optimizer Statistics Collection
• Collects optimizer statistics for all schema objects in the database for which there are no statistics or only stale statistics.
• The statistics gathered by this task are used by the SQL query optimizer to improve the performance of SQL execution.
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Statistic Gathering Options
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Setting Statistic Preferences
ESTIMATE_PERCENT
NO_INVALIDATE
METHOD_OPT
GRANULARITY
INCREMENTAL
PUBLISH
STALE_PERCENT
DATABASE LEVEL
SCHEMA LEVEL
TABLE LEVEL
STATEMENT LEVEL
GLOBAL LEVEL
PREFERENCES
SCOPE
exec dbms_stats.set_table_prefs('SH','SALES','STALE_PERCENT','13');
DBA DBMS_STATS
set | get | delete | export | import
Optimizer
statistics
gathering
task
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Restore Statistics • The DBMS_STATS package allows statistics to be restored as of a
timestamp using the RESTORE_*_STATS procedures.
– RESTORE_FIXED_OBJECTS_STATS
– RESTORE_SCHEMA_STATS
– RESTORE_SYSTEM_STATS
– RESTORE_TABLE_STATS
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TEST
PROD
PUBLISH=FALSE
+
GATHER_*_STATS
EXPORT_PENDING_STATS
IMPORT_TABLE_STATS
expdp/impdp
ALTER SESSION SET OPTIMIZER_USE_PENDING_STATISTICS=TRUE
PUBLISH_PENDING_STATS
Dictionary
statistics Pending
statistics
DBA_TAB_PENDING_STATS
Deferred Statistics Publishing: Overview
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Automatic Segment Advisor
• Identifies segments that have space available for reclamation, and makes recommendations on how to defragment those segments.
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Segment Advisor
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Automatic DOP and Parallel Statement Queuing
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Automated Degree of Parallelism
• Oracle determine the degree of parallelism on each table/query based on a set of criteria and some initialization parameter settings
• Features of Oracle 11g Release 2
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Automated Degree of Parallelism Settings
• To enable use the parallel_degree_policy parameter (by default this stuff is off - parameter is set to manual)
• For Auto DOP, setting this to LIMITED is sufficient
• For more functionality (in-memory parallel processing and parallel statement queuing) parallel_degree_policy should be set to AUTO
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Automated Degree of Parallelism Settings
• The parameter for the threshold of parallel query evaluation is parallel_min_time_threshold. The default of this parameter is 10 seconds (set lower to allow more parallel queries evaluations)
• The maximum DOP that can be used is set by Parallel_degree_limit. By default this is set to the value of “CPU” multiplied with the value of the parameter parallel_threads_per_cpu
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Automated Degree of Parallelism How it works
SQL
statement
Statement is hard parsed
And optimizer determines
the execution plan
Statement
executes serially
Statement
executes in parallel
Optimizer determines
ideal DOP
If estimated time
greater than threshold
Actual DOP = MIN(default DOP, ideal DOP) If estimated time less
than threshold PARALLEL_MIN_TIME_THRESHOLD
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Parallel Statement Queuing
• Because of the expected behavior of more statements running in parallel it becomes more important to manage the usage of the parallel resources.
• Queries that does not have enough resources can put on “hold” until enough resources are available
• Oracle maintains FIFO queue for the waiting statements
• Use NO_STMT_QUEUING hint to avoid the queue
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Parallel Statement Queuing Settings
• parallel_degree_policy must be set to AUTO
• The parameter for enabling the parallel statement query evaluation is parallel_server_target The default value is 4 times the default DOP.
• To avoid an arbitrary number of parallel processes to be running on a system, which may overload that system, the parameter parallel_max_servers provides a hard upper boundary
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When the required
number of parallel servers
become available the first
stmt on the queue is
dequeued and executed
128
16 32 64
Parallel Statement Queuing How it works
SQL
statements
Statement is parsed
and Oracle automatically
determines DOP
If enough parallel
servers available
execute immediately
If not enough parallel
servers available queue
128 16 32 64
8
FIFO Queue
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Parallel Statement Queuing Monitoring
• Monitoring can be done using Enterprise Manager SQL Monitor.
• Monitoring can also be done by using: SELECT s.sql_id, s.sql_text
FROM v$SQL_MONITOR m, v$SQL s
WHERE m.status='QUEUED'
AND m.sql_id = s.sql_id;
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Backup, Recovery and Flashback
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Flashback Technologies Error Detection & Correction
• Flashback revolutionizes error recovery – View ‘good’ data as of a past point-in-time – Simply rewind data changes – Time to correct error equals time to make error
• Low impact • Excellent tool for configuring QA, Dev and Training databases • Flashback is easy – simple commands, no complex procedure
Correction Time = Error Time + f(DB_SIZE)
0
20
40
60
80
Rec
ove
ry T
ime
Traditional Recovery
Flashback
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Flashback Technologies
• Flashback Query
• Flashback Table
• Flashback Drop
• Flashback Transaction Query
• Flashback Database
• Flashback Data Archive
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Flashback Query or Table
• Flashback Query: – SQL> SELECT .. FROM.. AS OF…. WHERE
• Flashback Table – SQL> flashback table … to timestamp … – SQL> flashback table … to SCN …
• Flashback Drop – Use of Recycle Bin – flashback table … to before drop;
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Error Correction with Flashback • Flashback Database – restore
database to any point in time
• Flashback Table – restore contents of tables to any point in time (undo-based)
• Flashback Drop – restore accidentally dropped tables (based on free space in tablespace)
• Flashback Transaction – back out transaction and all subsequent conflicting transactions (redo-based)
Order
Database
Customer
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Data Files Flashback Log
New Block Version
Disk Write
Old Block Version
• Fast point-in-time recovery strategy
• Eliminate the need to restore a whole database backup
• Continuous data protection for database
– Optimized, before-change block logging
– Restores just changed blocks
– Replay log to restore DB to desired time
• It’s fast - recover in minutes, not hours
• It’s easy - single command restore
Flashback Database
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Flashback Database
• Flashback Database – can even go through RESETLOGS
• Can be done to Restore Points – create restore point PREQA_TESTING;
– create restore point PREQA_TESTING guarantee flashback database;
– drop restore point PREQA_TESTING;
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Flash Recovery Area Prerequisites
• Archiving must be enabled • Flash recovery area must be configured using
– DB_RECOVERY_FILE_DEST_SIZE - size of flashback recovery area in bytes
– DB_RECOVERY_FILE_DEST - location of flashback recovery area
• For example:
SQL> ALTER SYSTEM SET db_recovery_file_dest_size = 10G;
SQL> ALTER SYSTEM SET db_recovery_file_dest = '/oradata/recovery';
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Flashback Database Configuration
• To enable flashback logging database must be mounted but not open
• To disable flashback logging use:
• To check if flashback is currently enabled:
SQL> STARTUP MOUNT
SQL> ALTER DATABASE FLASHBACK ON;
SQL> ALTER DATABASE OPEN;
SQL> SELECT flashback_on FROM v$database;
FLASHBACK_ON
------------
YES
SQL> ALTER DATABASE FLASHBACK OFF;
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Flashback Database Parameters
• One supported parameter: – DB_FLASHBACK_RETENTION_TARGET
• Specifies upper limit on how far back in time database may be flashed back
• Specified time in minutes - default value is 1440 minutes (24 hours)
• Affects number of flashback logs retained in flash recovery area
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Flashback Data Archive Improved Time Travel in 11g
• Flashback Data Archive: query data as of 5 days, 5 weeks, 5 months, 5 years – whatever – in the past
• How does it work…
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How Does Flashback Data Archive Work?
• Primary source for history is the undo data
• History is stored in automatically created history tables inside the archive
• Transactions and its undo records on tracked tables marked for archival
– Undo records not recycled until history is archived
• History is captured asynchronously by new background process (fbda)
– Default capture interval is 5 minutes
– Capture interval is self-tuned based on system activities
– Process tries to maximize undo data reads from buffer cache for better performance
– INSERTs do not generate history records
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Total Recall • Alter base table – history table automatically adjusts
– Drop, Rename, Modify Column – Drop, Truncate Partition – Rename, Truncate Table
• Flashback query supported across DDL changes
• Complex DDL changes (e.g. table split) accommodated – Associate/Diassociate history table via DBMS_FLASHBACK_ARCHIVE package
Dro
p
Co
lum
n
Ad
d
Co
lum
n
time Flashback Version Query
Ad
d
Co
lum
n
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Flashback Data Archive Setup
• Create a Flashback Archive tablespace:
• Set the table to use the flashback archive:
ALTER TABLE hr.employees FLASHBACK ARCHIVE fla1;
Table altered.
CREATE FLASHBACK ARCHIVE DEFAULT fla1 TABLESPACE
flasharch1
QUOTA 20G
RETENTION 1 YEAR;
Flashback archive created.
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Best Practices – Undo-based Flashback (Table/Query)
• Use Undo Advisor (available through Enterprise Manager) to get recommendations on available undo retention for various sizes.
• Use fixed size undo – Undo retention automatically tuned for best possible
retention based on tablespace size and current system load.
• Be aware of DDL restrictions – not possible to query in the past if table structure is modified (e.g. drop/modify column, move table, etc.)
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Undo Advisor
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Best Practices – Flashback Database
• Tune FRA storage – Use ASM, configure enough disk spindles, etc.
• Use physical standby database to test Flashback logging • Use V$FLASHBACK_DATABASE_LOG to size log
space, after running workload > duration of Flashback retention period.
• Create Guaranteed Restore Point (GRP) without enabling Flashback logging – Saves disk space for workloads where same blocks are
repeatedly updated – Drop GRP to immediately reclaim space
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Summary
• We talked about various automatic tuning and maintenance tools in Oracle 10g and 11g
• We talked about tuning of the database
• We talked about Flashback feature
• There are MORE automatic features and advisories we didn’t talk about (for example: ASSM)
• More info will be available on my blog:
ZoharElkayam.wordpress.com
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Questions and Answers
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