Automating Execution Plan Analysis

Comprehensive Performance with
Automated Execution Plan
Analysis (ExecStats)
Joe Chang
jchang6 @ yahoo
About Joe
SQL Server consultant since 1999
Query Optimizer execution plan cost formulas (2002)
True cost structure of SQL plan operations (2003?)
Database with distribution statistics only,
– no data 2004
• Decoding statblob-stats_stream
– writing your own statistics
• Disk IO cost structure
• Tools for system monitoring, execution plan analysis
See ExecStats
• Complexities & depth SQL performance
– Cause and Effect
• Focus on the execution plan
– Inefficient plans – missing indexes
– very large estimate/actual row discrepancies
• Comprehensive Index Strategy
– few good indexes, but no more than necessary
• List of rules to be followed blindly
• without consideration for the underlying reason
• and whether rule actually applies in the
current circumstance
DBA skill: cause and effect analysis & assessment
Preliminary: Correct Results
• Normalization
– Data stored once, avoid anomalies
• Unique Keys
– Avoid duplicate rows
• Foreign Keys
– Avoid orphaned rows
Incorrect architecture requires use of SELECT DISTINCT etc.
to correct architecture deficiencies
Which may cause performance problems as well
Correct action is to address the architecture mistakes
before the performance issue.
Performance Factors
natural keys
Parallel plans
& Compile
Row estimate
temp table /
table variable
Tables and SQL combined
implement business logic
Natural keys with unique
indexes, not SQL
Index and Statistics
maintenance policy
1 Logic may need more than
one execution plan?
Compile cost versus
execution cost?
Plan cache bloat?
The Execution Plan links all the elements of performance
Index tuning alone has limited value
Over indexing can cause problems as well
Performance Strategy
• Tables – support business logic
– Normalization, uniqueness etc.
• SQL – clear SARG, Query optimizer interpretable
– 1 Logic maps to X Execution plans
• Indexes – good cluster key choice
– Good nonclustered indexes, no more than necessary
• Statistics – sample strategy & update frequency
• Compile parameter strategy
• Temp table / Table variable strategy: Recompile & Row est. prop. error
• Parallel execution plans: DOP and CTOP strategy
Indexing Principles
• Good cluster key choice
– Grouping + unique, not too wide
• Good nonclustered indexes
– For key queries, not necessarily every query
– Covered indexes were practical (update overhead)
– Create and drop custom indexes for maintenance ops
• No more indexes than necessary
– Update overhead
– Compile overhead
– May tolerate occasional scans to avoid update maintenance
Note emphasis on good, not perfect
Comprehensive Strategy
• Identify (weight) important SQL statements
– stored procedure: parameter values & code path
• Recompile impact for temp tables
• Execution plan cross references SQL & indexes
– Actual plan is better than estimate plan
– Compile parameters & skewed statistics
• Temp tables - Recompile impact
Automate Execution Plan analysis to fully cross-reference
SQL to index usage
Using DMVs – Execution Plan
System views
Execution Plan
Indexes, joins
Compile parameters
Indexes, key columns,
Include list, filter, XML,
Columns store etc.
STATS_DATE(object_id, stats_id)
2014 Real time query progress?
sys.dm_db_stats_properties, is available in SQL
Server 2012 starting with Service Pack 1 and in
SQL Server 2008 R2 starting with Service Pack 2.
last_updated, rows, rows_sampled, steps, unfiltered_rows,
Using DMVs – Execution Plan
System views
Execution Plan
Indexes, joins
Compile parameters
Indexes, key columns,
Include list, filter, XML,
Columns store etc.
2014 Real time query progress?
STATS_DATE(object_id, stats_id)
sys.dm_db_stats_properties, is available in SQL
Server 2012 starting with Service Pack 1 and in
SQL Server 2008 R2 starting with Service Pack 2.
last_updated, rows, rows_sampled, steps, unfiltered_rows,
SQL & Execution Plan Sources
• Estimated Execution Plan
– dm_exec_query_stats
• Contents of plan cache + execution statistics
– List of stored procedures
• SELECT name FROM sys.procedures
• Any SQL list
– Plans not in cache, to be generated
– Can also execute SQL for actual plans
• sql_handle
– token for batch or stored procedure
• statement_start_offset
– sql_handle + offset = SQL statement
• plan_handle
– SQL (batch) can have multiple plans on recompile
• query_hash
– identify queries with similar logic,
– differing only by literal values
• Get list of stored procedures in database
– functions are called from procedure?
• Generate estimated execution plan for each
– Default parameters
• Full map of index usage to stored procedure
• No trigger details in estimated plan
SQL List
• Configuration file has SQL to retrieve SQL list
– Can be
• explicit SQL
• or stored procedures with parameters
– Same procedure, multiple parameter set
• To expose different code path (actual plan)
• EXEC proc WITH @P1 RECOMPILE (estimated plan)
About ExecStats
• General information
• Execution plan sources
list of all stored procedures (estimated)
List of SQL in table (estimated or actual plan)
Trace file
Correlates execution plans to index usage
Procedures, functions and triggers
Rollup file IO stats by DB, filegroup, disk/vol, data/log
Distribution Statistics
Output to Excel, sqlplan file, (sql in txt file)
ExecStats Output Files
Txt – runtime info
Log – abbreviated SQL error logs
Excel –
Missing Indexes DMV
SQL plan directory
This can be sent to someone who can identify and fix your problem
Important Items
• Query cost – plan efficiency? Recompiles?
– Compile parameters – skewed statistics
• CPU versus Duration (worker – elapsed time)
– Disk IO, network transmission, parallel plan?
• Execution count – network roundtrip?
• Plan cost – Parallelism
– High volume of quick queries is bad, so is excessive DOP
• Index – current rows, rows at time stats generated,
sample rows & date
Execution Plans
• Estimated
• Actual: estimated cost, actual rows, DOP
– Executed stored procedure once for each possible
code path – with appropriate parameters
Execution Plans
• Pay attention to:
– Compile parameters
– Large table scans: how many rows output?
– Predicate
• search condition without suitable index
– Rebinds and Rewinds – key lookup
– Parallelism
Index Usage – missing IX, excess IX?
• Index usage – seek, scan, lookup & update
– Unused indexes (infrequent code?) can be dropped
– Infrequent usage: check plan references
– Similar indexes (leading keys)
• Same keys, different order
• Check plan reference – consolidate if possible
• Scans to large tables or even nonclustered IX
– Is it real (SELECT TOP 1 may not be a real scan)
• Lookups – can these be reduced?
SQL Server Skills & Roles
Data Architect
Table structure,
unique keys
SQL code
Index + Statistics
& Storage
• .
SQL Server Performance History
• Before DMVs (SQL Server 2000)
– Profiler/Trace to get top SQL
– Execution plans – not really exportable
– Which indexes are actually used?
• Today
– Trace/Extended Events sometimes not necessary
• If the dm_exec_query_stats content is good
– Execution plans are exportable
– Index Usage Stats
How much can be automated?
• Data collection
all, of course
– Top resource consumers, etc.
• Assessment
– Is there a problem
– Can it be fixed or improved
• Fix/Change
– Indexes
– SQL – sometimes
– Table structure, architecture
If problems could be solved by pushing a button,
what would be the skill requirements to be a DBA?
Great accomplishments – 99%
perspiration 1% inspiration
Performance Approaches
• Check against list of “Best Practices”
• Manual DMV scripts approach
– Find Top 5 or 10 SQL
– Fix it if/when there is a problem
• All Indexes and procedures/SQL
– Examine the complete set of stored procedures
– Or the full list of SQL statements
– Good indexes for all SQL, no more indexes than
Why bother when there are no problems?
• No problems for over 1 year
– Never bothered to collect performance baseline
• Problem Today – Find it with DMV, fix it
– the problem was xxx
– but why did it occur today & not before?
• Probably statistics or compile parameters, but prove it?
• Why ExecStats
– SQL scripts? – too much manual work
– Third party tools? – only find problem
Rigorous Optimization
• Table structure, SQL, Client-side
• Cluster Key
• Good (nonclustered) Indexes
– All indexes are actually used
• No more indexes than necessary
– Consolidate similar indexes
• same keys, same order, or reverse order?
– What SQL is impacted?
• Statistics update
• Index maintenance
Must consider the full set of
SQL/procedures in removing
SQL versus programming languages
• SQL – great for data access
– Not good for everything else
– When SQL becomes horribly complicated
– What would the code looks like in VB/Java/Cxx
Client-side program C#
Performance Information
• Server, Storage
• OS & SQL Server Settings
• SQL Server
– SQL, query execution statistics, execution plan
– Compile parameters
– Indexes and index usage statistics
– Statistics sampling – when? percentage? skew?
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