Con7091 sql tuning for expert db as-oow17_oct2_1507314871265001m0x4

Copyright © 2017, Oracle and/or its affiliates. All rights reserved. |
SQL Tuning for Expert DBAs
GP (Gongloor Prabhaker)
Senior Director of Product Management
Oracle Management Cloud, Oracle Corporation
Konstantin Kerekovski,
DBA, Raymond James Financial Inc.
Oct 03, 2017
Confidential – Oracle Internal/Restricted/Highly Restricted

Safe Harbor Statement
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information purposes only, and may not be incorporated into any contract. It is not a
commitment to deliver any material, code, or functionality, and should not be relied upon
in making purchasing decisions. The development, release, and timing of any features or
functionality described for Oracle’s products remains at the sole discretion of Oracle.
Confidential – Oracle Internal/Restricted/Highly Restricted 3

Program Agenda
SQL Tuning: Challenges and existing solutions
Proactive approach and tips
Reactive approach and tips
Customer Case study
1
2
3
4
Please visit us at Demo Grounds:
Moscone West, SOA-052, Database Monitoring and Performance
Management with Oracle Enterprise Manager

Copyright © 2017, Oracle and/or its affiliates. All rights reserved. |Copyright © 2017, Oracle and/or its affiliates. All rights reserved. |
SQL Tuning: Challenges and existing
solutions

Program Agenda
Customer Case study
1
2
3
4

SQL Tuning: Why is guess work involved?
Lack of Automated , E2E
and scalable solution
Resource ContentionOptimizer Related Application Specific
Issues
End-user Expertise

SQL Performance Issues: Broad categories
OptimizerRelated
• Stale/Missing
statistics
• Incomplete
statistics
• Improper
optimizer
configuration
• Upgraded
Database:
new
optimizer
• Rapidly
changing data
• Stale/Missing
statistics
• Incomplete
statistics
• Improper
optimizer
configuration
• Upgraded
Database:
new
optimizer
• Rapidly
changing data
ResourceRelated
•Hardware
resource
crunch
•Contention
(row lock/ block
contention)
•Not parallelized
(no scaling to
large data)
•Improperly
parallelized
(partially
parallelized,
skews)
•Hardware
resource
crunch
•Contention
(row lock/ block
contention)
•Not parallelized
(no scaling to
large data)
•Improperly
parallelized
(partially
parallelized,
skews)
ApplicationIssues
• Missing
access
structures
• Poorly
written SQL
statements
• Bind-sensitive
SQL with bind
peeking
(Cursor
Sharing)
• Literal usage
• Missing
access
structures
• Poorly
written SQL
statements
• Bind-sensitive
SQL with bind
peeking
(Cursor
Sharing)
• Literal usage
LackofSQL&OptimizerExpertise
• Limited
knowledge of
SQL and
Optimizer
• Tunes
individual or
few
statements
vs. entire
workload
• Limited
knowledge of
SQL and
Optimizer
• Tunes
individual or
few
statements
vs. entire
workload
LackofAutomation
• Manual
effort, time
consuming
• Lack of
scalability
with high
volume SQL
(100K)
• Unintuitive
techniques
and point
solutions
• Manual
effort, time
consuming
• Lack of
scalability
with high
volume SQL
(100K)
• Unintuitive
techniques
and point
solutions

SQL Tuning: Existing solutions
• How DBAs tune SQL today?
– Use SQL Trace to identify offending SQL solution
• Prohibitive on production
– Disable index access by modifying predicates (to_char, to_number)
– Change init.ora parameters (optimizer_..)
– Adding indexes
• Most apps are already over-indexed
– Materialized Views
– Partitioning, etc.
• Existing solutions have severe limitations, are not scalable and mostly
reactive in nature, use trial and error methodology

Program Agenda
Customer Case study
1
2
3
4

Copyright © 2017, Oracle and/or its affiliates. All rights reserved. | 12
Proactive Approach
Become the “Proactive DBA” using Oracle’s rich tool set!
• A DBA has Oracle’s rich tool set available to identify problems and remediate problems
before they happen in production.
• Proactive DBA should use the following tools:
– ADDM to detect systemic problems and remediate them by following ADDM recommendations*
– Automatic SQL Tuning advisor to tune high load SQL statements over time – it is available out of the
box*
– SQL Access Advisor to make sure your application has optimal access structures (indexes and type,
MVs, MV logs, etc.) and partitioning scheme, tune entire workload*
– SPA Quick in production environments to quickly assess impact of routine system changes (for e.g., SQL
Profile validation, optimizer related changes, optimizer refresh statistics) without impacting
production*
– SPA to validate system changes such as migration to Oracle Database Cloud, Exadata Cloud Machine,
etc.* *OOW 2016: Eliminating Guesswork from SQL Tuning [CON6975]

SQL Performance Analyzer
Analysis Report
Compare SQL
Performance
Post-change TrialPre-change Trial
SQL Plans + Statistics SQL Plans + Statistics
– Helps users predict the impact of
system changes on SQL workload
– Low overhead capture of SQL workload
to SQL Tuning Set (STS) on production
system
– Build different SQL trials (experiments)
of SQL statements performance by test
execution or explain plan
– Integrated with STS, SQL Plan
Baselines, & SQL Tuning Advisor to
form an end-to-end solution

DBCS Migration Use Case
• As a DBA, you have been tasked by management to migrate your 11.2
database to the latest Cloud DB release. At the same time, the requirement
is to make sure the performance is same or better than before, how can I
accomplish this?

Validate Cloud Migration with SPA
On-Premise Oracle Cloud
15
Trial 2: Test Execute or
Explain Plan
Step 1: Capture representative workload to STS
Step 2: Clone On-premise database to Cloud
Analysis Report
Step 3b: Generate SPA Report and
fix regressions
Trial 1: Build (Convert)
from STS
Step3a: Conduct SPA trials
SPA Task

SPA - Concurrent SQL Execution
• SPA trials are currently executed serially one statement at a time
– When SQL Tuning Sets contain a large number of statements, the trial could take
significant time. For example, EBS suite may have 1 million unique SQL statements
– Under utilized server if using large system
• Concurrent SQL execution within a SPA trial reduces duration to complete
the trial, therefore reduces testing time
– User specifies degree of parallelism with SPA parameter TEST_EXECUTE_DOP
– For example, a SQL Tuning Set with 125,000 statements reduced testing from
12.5 hours to 2 hours with a degree of parallelism of 8
• Tip: Use SPA concurrent SQL execution in test environment for STS with a
large number (thousands or higher) of SQL statements
New in
18.1

SPA – Result Set Validation
• Result set validation required for certain environments – e.g. government
drug research trials, pharma industries, etc. An additional assurance that
SQL produces correct results with new environment / software
• SPA report can be generated for before and after change trials comparing
whether identical result sets were produced
• SPA result set validation enabled with SPA parameter COMPARE_RESULTSET
(defaults to true)
• Tip: Run before and after trials with exact same dataset for result set
validation
• If result sets differ with same input dataset – contact Oracle Support
New in
18.1

Program Agenda
Proactive Approach and tips
Reactive Approach and tips
Customer Case study
1
2
3
4

SQL Tuning Tips - Reactive Approach
• Proactive SQL Tuning should resolve most of your day-to-day issues,
however sometimes reactive tuning is needed
• DBA should use the following tools for reactive SQL Tuning:
– ASH Analytics for transient performance analysis and drilling down on SQL dimensions (by execution
plan operation, SQL_ID, PDB, Action, Module, etc.)
– SQL Monitor for complex run-time execution statistics on long running or Parallel executions such as
which plan operation line that consumes resources such as CPU and I/O, overall PGA usage and Parallel
distribution
– SQL Tuning Advisor getting comprehensive analysis and recommendations on problematic SQL
statements such as profiles, statistics and new access structure

Tip: Use Real-Time SQL Monitoring For Detailed Execution
Statistics On Long Running Or Parallel Executions
• Enabled out-of-the-box with no performance impact
• Automatically monitors SQL executions that:
– Consume more than 5 seconds of CPU or I/O time
– Are running parallel: PQ, PDML, PDDL
• Monitors each execution independently
• Exposes monitoring statistics at multiple levels
– Global execution level
– Plan operation level (Plan Tuning)
– Parallel Execution level (PX Tuning)
• Guides your tuning efforts
• SQL level metrics
—CPU, I/O requests, throughput, PGA, temp space
• Graphical explain plan
• I/O statistics for each operation
Looking inside the SQL

Real-Time SQL Monitoring

• Can also be accessed via
– ASH Analytics -> Select an SQL ID -> Select SQL Monitor from Detail section.

• Case Study 1 – Adaptive Plans
• Case Study 2 – Long Execution plan
• Case Study 3 – PL/SQL Monitoring
• Case Study 4 – Poor indexing
• Case Study 5 – Parallel Execution Downgrade
Use cases

Copyright © 2016, Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal 29
Real-time SQL Monitoring with
Adaptive Plans
Generate script for problem SQL
with binds and execute
(6 min)

SQL Monitoring Case Study 1
Case Study 1: Adaptive Plans
• How can I determine if a query has self tuned with the adaptive plan feature?
• Can I identify the values of my bind variables?

SQL Monitoring Use Cases
Case Study 1: Adaptive Plans

• Comprehensive view of execution plan
• Easy to pinpoint operations and objects that consume
the most resources
Case Study 2: Analyzing Large SQL Execution Plans

SELECT /*+ MONITOR */ avg(ss_quantity),avg(ss_ext_sales_price),avg(ss_ext_wholesale_cost),sum(ss_ext_wholesale_cost)
from store_sales ,store ,customer_demographics ,household_demographics,customer_address,date_dim
where s_store_sk = ss_store_sk
and ss_sold_date_sk = d_date_sk and d_year = 2001
and (
(ss_hdemo_sk=hd_demo_sk and cd_demo_sk = ss_cdemo_sk and cd_marital_status = 'M’
and cd_education_status = '4 yr Degree‘ and ss_sales_price between 100.00 and 150.00 and hd_dep_count = 3 )
or
(ss_hdemo_sk=hd_demo_sk and cd_demo_sk = ss_cdemo_sk and cd_marital_status = 'D’ and cd_education_status = 'Primary'
and ss_sales_price between 50.00 and 100.00 and hd_dep_count = 1 )
or
(ss_hdemo_sk=hd_demo_sk and cd_demo_sk = ss_cdemo_sk and cd_marital_status = 'U’
and cd_education_status = 'Advanced Degree‘ and ss_sales_price between 150.00 and 200.00 and hd_dep_count = 1 )
)
and(
(ss_addr_sk = ca_address_sk and ca_country = 'United States‘ and ca_state in ('KY', 'GA', 'NM')
and ss_net_profit between 100 and 200 )
or
(ss_addr_sk = ca_address_sk and ca_country = 'United States‘ and ca_state in ('MT', 'OR', 'IN')
or
(ss_addr_sk = ca_address_sk and ca_country = 'United States‘ and ca_state in ('WI', 'MO', 'WV')
)
• Q: I have a complex query with a complex query plan, how can I identify which
operations and objects consume the most resources?

• Solution: All activity is against STORE_SALES. Consider partitioning the table.

Real-Time PL/SQL Monitoring
• PL/SQL execution no longer a “black box”
– Answers questions like “why did my DBMS_STATS job take twice as long this time?”
• Shows global (PL/SQL) and SQL level statistics
• Each SQL called by PL/SQL recursively monitored
• Drill-down to slow SQL for diagnosing unexpected PL/SQL behavior

Case Study 3: Real-Time PL/SQL Monitoring
• Q: I have a PL/SQL procedure that takes a long time, can I identify which SQL statement
that is my largest resource consumer?

Most elapsed time
Highest CPU usage
• Q: I have a PL/SQL procedure that takes a long time, can I
identify which SQL statement that is my largest resource
consumer?

• Initial Query
• Q: I have added many indexes to my database. I still have several queries with bad
performance. Can I determine if my indexes are used efficiently?
Case Study 4: Poor Indexing

• Q:I have added a large amount of indexes to my database. I still have several queries
with bad performance. Can I identify that my indexes are used efficient?
• Initial Query • Tuned Query

• Q: I have added many indexes to my database. I still have several queries with bad
performance. Can I determine if my indexes are used efficiently?
• Initial Query • Tuned Query • Tuned Query / Cached

Case Study 5: Parallel Execution Downgrade
• Query requests parallel degree 4. Why is it downgraded to parallel degree 2?

select qksxareasons,indx
from x$qksxa_reason
where qksxareasons like '%DOP downgrade%’;
QKSXAREASONS INDX
------------------------------------------------------------ ----------
DOP downgrade due to adaptive DOP 351
DOP downgrade due to resource manager max DOP 352
DOP downgrade due to insufficient number of processes 353
DOP downgrade because slaves failed to join 354

• Solution: Consider changing the maximum DOP on Resource Consumer Group

SQL Tuning Advisor Exadata Enhancement
• SQL Tuning Advisor detects if SQL is executing on
Exadata
• SQL Tuning Advisor privately gathers system statistics
and does analysis with and without these statistics
• If a better execution plan is found with these system
statistics, an Exadata-aware SQL Profile is recommended
• Can result in 10x or better performance improvement
for SQLs which can benefit from Exadata hardware - e.g.
cell smart scans
NEW IN
18.1

SQL Tuning Advisor Exadata Enhancement
NEW IN
18.1
Without Exadata aware SQL Profile – 1.9 minutes:
With-Exadata aware SQL Profile – 13 seconds:

Program Agenda
Proactive Approach and tips
Reactive Approach and tips
Customer Case study
1
2
3
4

Customer Case study

RAYMOND JAMES FINANCIAL
HTTPS://WWW.RAYMONDJAMES.COM/
57

KONSTANTIN KEREKOVSKI
58
Work Experience:
American Express – Senior Oracle DBA, 11g, 12c, RAC, GG, ADG
Raymond James – Senior Oracle DBA, 11g, 12c, Exadata, ODA, RAC, GG, ADG
LinkedIn: www.linkedin.com/in/konstantin-kerekovski-34740071
Speaker:
IOUG Collaborate 2017
SOUG (Suncoast Oracle User Group)
NYOUG (New York Oracle User Group)

THE PROBLEM
59
• Production Oracle Data Integrator (ODI) jobs are running slowly due
to suboptimal execution plans on INSERT INTO XYZ SELECT….
queries.
• The INSERT queries cannot be readily altered due to declarative
nature of ODI and internal Change Management process.
• The business is being impacted because multiple other ETL and
batch jobs depend on the completion of ODI jobs.

PROBLEM IDENTIFICATION
60
The problem was clearly evident in the Top Activity page of OEM for the
database in question.

THE SOLUTION
SQL TUNING ADVISOR
61

IMPLEMENTATION
63
The implementation of the SQL Profiles and/or statistics gathering is as
simple as following the guided instructions from the OEM SQL Tuning
recommendations screen.

TOP ACTIVITY BEFORE TUNING
64
TOP ACTIVITY AFTER TUNING

THE IMPACT OF SQL TUNING ADVISOR
65
• The long running ODI job’s runtime improved dramatically.
• No development effort was necessary, thus saving money on labor
costs on tuning efforts and regression testing efforts.
• The change was easily implementable and because SQL Profiles
can easily be disabled, the change can be backed out if any issues
arise.
• The change can be easily propagated throughout the entire SDLC
due to the portable nature of SQL Profiles.
• Business processes which depend on ODI jobs to complete were no
longer impacted and completed ahead of schedule.

66
 What is it?
- Extra information to be
used by the optimizer
during parsing.
 When do I use it?
- When you just want to help
the optimizer with extra
information without
dictating a specific
execution plan.
- When SQL Execution
Plans are unstable and
changing adversely due to
issues such as
inaccurate/stale Optimizer
Statistics, bind variable
peeking, etc.
TIP
SHOULD I USE SQL BASELINES OR SQL
PROFILES ?
SQL PROFILE
 What is it?
- A set of stored, approved
execution plans for a given
SQL statement that are used
instead of plans obtained
during normal hard parsing.
 When do I use it?
- During Database Upgrades
for the purpose of avoiding
performance regression due
to new optimizer features (
E.G. Adaptive Plans in 12.1),
missing statistics, etc.
- When you only want one
specific execution plan to be
used.
SQL BASELINE

SQL Tuning for Expert DBAs: Summary
• Become the proactive DBA, use:
– ADDM to detect systemic problems and remediate
them by following ADDM recommendations
– Automatic SQL Tuning Advisor to tune high load SQL
statements over time
– SQL Access Advisor to assure that your application
has optimal access structures (indexes and type,
MVs, MV logs, etc.). Tunes the entire workload
– SPA Quick Check in production environments to
quickly assess impact of routine system changes (for
e.g., optimizer refresh statistics)
– SPA to validate system changes such as migration to
Oracle Database Cloud, Exadata Cloud Machine, etc.
• If you have to perform reactive SQL
tuning, use:
– ASH Analytics to identify your top resource
consumers
– SQL Monitor for detailed execution statistics on
long running or parallel executions
– SQL Tuning Advisor to identify and remediate:
– Stale statistics
– Incorrect cardinality estimations
– Data correlations

Con7091 sql tuning for expert db as-oow17_oct2_1507314871265001m0x4

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