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SQL Plan Directives explained

Session describes Oracle SQL Plan Directives feature introduced in 12.1. The focus in what the feature is meant of address and how its lifecycle

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SQL Plan Directives explained

  1. 1. SQL Plan Directives Explained Mauro Pagano
  2. 2. Mauro Pagano • Consultant, working with both DBA and Devs • Oracle  Enkitec  Accenture • DBPerf and SQL Tuning • Training, Workshops, OUG • Free Tools (SQLd360, TUNAs360, Pathfinder) 2
  3. 3. Some background • CBO makes mistakes – Complex code with challenging job – Based on • Statistical formula, not perfect in 100% cases • Partial knowledge of the data (stats) • Mistakes can translate into poor plans • Poor plans usually lead to poor performance 3
  4. 4. How to avoid mistakes? • Improve quality of the model (Oracle) – Hard, lots of corner cases for CBO to handle • Improve quality of stats (kind of you) – Hard, need knowledge of data and queries • Reactively, learn from them to avoid next time – Allow to adapt to specific situation – Requires mistake to be made first though 4
  5. 5. Cardinality Feedback • Oracle attempt of making CBO learning from its own mistakes – Introduced in 11.2 (11.1 as one-off) – Enhanced in 12.1 to deal with joins (but disabled in 12.2) • Might take a bit to learn – Kind of iterative approach, up to 5 “refined” attempts • Lessons learned as OPT_ESTIMATE hints (like STA), very specific – Not persisted to dictionary (same mistakes over time) • Few initial bugs gave it a bad reputation – SQL runs fine the first time, run again and runs slow! – Supposed to be transparent, not good when gives troubles  – Some people got burned, decided to turn off system-wise 5
  6. 6. Table TAB1 drop table tab1; create table tab1 (n1 number, n2 number, n3 number); -- the data is strongly correlated insert into tab1 select mod(rownum, 100), mod(rownum, 100), mod(rownum, 100) from dual connect by rownum <= 100000; commit; exec dbms_stats.gather_table_stats(user,'TAB1'); 6
  7. 7. Cardinality Feedback select count(*) from tab1 where n1 = 1 and n2 = 1 and n3 = 1 ---------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | ---------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 1 | | 1 | SORT AGGREGATE | | 1 | 1 | 1 | |* 2 | TABLE ACCESS STORAGE FULL| TAB1 | 1 | 1 | 1000 | ---------------------------------------------------------------------- ---------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | ---------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 1 | | 1 | SORT AGGREGATE | | 1 | 1 | 1 | |* 2 | TABLE ACCESS STORAGE FULL| TAB1 | 1 | 1000 | 1000 | ---------------------------------------------------------------------- Note ----- - statistics feedback used for this statement OPT_ESTIMATE (@"SEL$1" TABLE "TAB1"@"SEL$1" ROWS=1000.000000 ) 7 P(A and B and C) = P(A) * P(B) * P(C)
  8. 8. SQL Plan Directives • New feature introduced in 12.1 – Several changes introduced in 12.2 • Designed to be transparent – SPDs are CBO generated – SPDs are leveraged by CBO once in place • Enabled by default in 12.1 • Disabled by default in 12.2 8 
  9. 9. What’s the goal? • Help CBO make better estimations • Not SQL-specific – Can be re-used by similar SQLs • No specific adjustments like CFB • Keep track of ”risky paths” • Determine when to leverage other features – Dynamic Statistics – Instruct DBMS_STATS to create Column Groups 9
  10. 10. What does SPD track? • Cardinality misestimates (usually underestimates) • “Risky paths” are – Data correlation on multi-column filter predicates – Uncommon join correlation – Data correlation on columns in GROUP BY • Potentially other paths can be tracked – For example, cardinality estimation at query block level • Many TYPEs could be supported – As of today, only existing TYPE is DYNAMIC_SAMPLING (*) 10
  11. 11. How does SPD track them? • Entry in the data dictionary – opt_directive$, opt_finding_obj$ – Externalized as DBA views • Records table / columns involved – Different SQLs on same objects can use same SPD • Info read at hard parse and consumed accordingly – For example, triggering dynamic sampling • Used as warning “watch out when estimating X” 11
  12. 12. SPD creation example select count(*) from tab1 where n1 = 1 and n2 = 1 and n3 = 1; (from 10053) SINGLE TABLE ACCESS PATH Single Table Cardinality Estimation for TAB1[TAB1] Table: TAB1 Alias: TAB1 Card: Original: 100000.000000 Rounded: 1 Computed: 0.100000 Non Adjusted: 0.10 … SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 135446, objtyp = 1, vecsize = 4, colvec = [1, 2, 3, ], fid = 29…48 SPD: Inserted felem, fid=29…48, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0,… 12 Mistake! We know it’s 1K rows
  13. 13. SPD creation example select directive_id, type, reason, notes from dba_sql_plan_directives where directive_id in (select directive_id from dba_sql_plan_dir_objects where owner = sys_context('userenv', 'session_user') and object_name = 'TAB1'); DIRECTIVE_ID TYPE REASON -------------------------- ---------------- ------------------------------------ 1149064327055029475 DYNAMIC_SAMPLING SINGLE TABLE CARDINALITY MISESTIMATE NOTES ----------------------------------------------------- <spd_note> <internal_state>NEW</internal_state> <redundant>NO</redundant> <spd_text>{EC(MPAGANO.TAB1)[N1, N2, N3]}</spd_text> </spd_note> 13
  14. 14. SPD creation example select * from dba_sql_plan_dir_objects where owner = sys_context('userenv', 'session_user') and object_name = 'TAB1'; SUBOBJECT_NAME OBJECT ---------------- ------ N1 COLUMN N2 COLUMN N3 COLUMN TABLE  NOTES is at the TABLE level NOTES -------------------------------------------------------------------------- <obj_note> <equality_predicates_only>YES</equality_predicates_only> <simple_column_predicates_only>YES</simple_column_predicates_only> <index_access_by_join_predicates>NO</index_access_by_join_predicates> <filter_on_joining_object>NO</filter_on_joining_object> </obj_note> 14
  15. 15. SPD creation (another) example DIRECTIVE_ID TYPE REASON --------------------- ---------------- ------------------------------------ 7426975260533728013 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE NOTES --------------------------------------------------------------------------------- <spd_note> <internal_state>NEW</internal_state> <redundant>NO</redundant> <spd_text>{(SYS.OPT_DIRECTIVE$) - (SYS.OPT_FINDING_OBJ$)}</spd_text> </spd_note> DIRECTIVE_ID OBJECT_NAME OBJECT NOTES --------------------- ---------------- ------ ------------------------------------ 7426975260533728013 OPT_DIRECTIVE$ TABLE <obj_note> EVERYTHING NO </obj_note> 7426975260533728013 OPT_FINDING_OBJ$ TABLE <obj_note> EVERYTHING NO </obj_note> 15
  16. 16. SPD creation example • SPD_TEXT reports the “risky path” – Specific format within { }, built on the fly – One or more tables – Columns included for single table – Format includes flag on predicate (where applicable) • E = Equality predicates • C = Simple column predicates • J = Index access by join predicates • F = Filter on joining object 16
  17. 17. SPD creation example • INTERNAL_STATE shows where in the lifecycle SPD is – NEW – SPD just created (flushed to disk), not used by SQLs yet – MISSING_STATS – CBO used to help estimations, likely used ADS – HAS_STATS – Stats (likely Column Group) helped CBO, SPD “off” – PERMANENT – Stats not enough, SPD will stay “on” (ADS) • First two states are transitory • Last two states are definitive – HAS_STATS -> PERMANENT if stats don’t help “enough” – SPD goes trough HAS_STATS before PERMANENT 17
  18. 18. How does CBO use SPD? • During hard parse applicable SPDs are looked at – Search done at multiple levels – Objects looked up by obj# • Many SPDs are not “current” anymore – Obsoleted / Superseded • The valid ones are used – Action triggered at the specific level – As of today only CBO action is Dynamic Sampling (ADS) 18
  19. 19. SPD usage example – single table select count(*) from tab1 where n1 = 1 and n2 = 1 and n3 = 1; Query Block SEL$1 (#0) Applicable DS directives: dirid = 16004857199080262683, state = 1, flags = 1, loc = 1 {EC(135484)[1, 2, 3]} … SINGLE TABLE ACCESS PATH Single Table Cardinality Estimation for TAB1[TAB1] SPD: Directive valid: dirid = 16004857199080262683, state = 1, flags = 1, loc = 1 {EC(135484)[1, 2, 3]} … Table: TAB1 Alias: TAB1 Card: Original: 100000.000000 >> Single Tab Card adjusted from 0.100000 to 1000.000000 due to adaptive dynamic sampling Rounded: 1000 Computed: 1000.000000 Non Adjusted: 0.100000 19
  20. 20. SPD usage example – single table select count(*) from tab1 where n1 = 1 and n2 = 1 and n3 = 1; (from 10046 during hard parse) PARSING IN CURSOR #140175694530408 … SELECT /* DS_SVC */ /*+ … result_cache(snapshot=3600) */ SUM(C1) FROM (SELECT /*+ qb_name("innerQuery") NO_INDEX_FFS( "TAB1")*/ 1 AS C1 FROM "TAB1" "TAB1" WHERE ("TAB1"."N1"=1) AND ("TAB1"."N2"=1) AND ("TAB1"."N3"=1) ) InnerQuery STAT #140175694530408 id=1 cnt=1 op='RESULT CACHE 145cmpkvg18at78z0dz8ptfwfw STAT #140175694530408 id=2 cnt=1 op='SORT AGGREGATE STAT #140175694530408 id=3 cnt=1000 op='TABLE ACCESS FULL TAB1 20
  21. 21. Use of SPD – single table conclusions • Allows CBO to get better estimation on the fly • Cool but not the best approach in the long run – ADS even if fast still takes some time (overhead) – Longer parses cause most of the troubles in real-life • Same result achieved with Column Group (often) • Real goal is – Put a band-aid until Column Group in place – Instruct DBMS_STATS to collect Column Groups – Verify if Column Group helped, if not keep SPD active 21
  22. 22. SPD usage example – join select … from dba_sql_plan_directives a, dba_sql_plan_dir_objects b where a.directive_id = b.directive_id and a.created >= sysdate-1/24 order by a.create Query Block SEL$AF75E632 (#0) Applicable DS directives: dirid = 10275726999217578058,state = 1,flags = 1,loc = 1{(612)[7]} dirid = 13360472976608779416,state = 1,flags = 1,loc = 1{(612)[]} dirid = 7426975260533728013,state = 1,flags = 1,loc = 2{(612)[]; (608)[]} dirid = 4318109285801377208,state = 1,flags = 1,loc = 1{(608)[]} dirid = 1215330379436061558,state = 1,flags = 1,loc = 2{(608)[]; (22)[]} dirid = 17607835686132426105,state = 5,flags = 1,loc = 1{C(22)[1]} dirid = 17030158486626056340,state = 1,flags = 1,loc = 2{(612)[];(608)[]; (22)[]} 22
  23. 23. SPD usage example – join (from 10053) SPD: Directive valid: dirid = 7426975260533728013,…,loc = 2 {(612)[]; (608)[]} … Join Card: 13.000000 = outer (9.000000) * inner (13.000000) * sel (0.111111) >> Join Card adjusted from 13.000000 to 16.000000 due to adaptive dynamic sampling, prelen=2 Adjusted Join Cards: adjRatio=1.230769 cardHjSmj=16.000000 … Join Card - Rounded: 16 Computed: 16.000000 (from 10046) PARSING IN CURSOR #139704599064112 SELECT /* DS_SVC */ /*+ … result_cache(snapshot=3600) */ SUM(C1) FROM (SELECT /*+ qb_name("innerQuery") NO_INDEX_FFS( "F#0") */ 1 AS C1 FROM "SYS"."OPT_FINDING$" "F#0", "SYS"."OPT_DIRECTIVE$" "D#1" WHERE ("D#1"."F_ID"="F#0"."F_ID") ) innerQuery 23
  24. 24. Use of SPD – join conclusions • Allows CBO to get better estimations for joins – Provide adjustment ratio – No stored stats provide this info (really cool) – OPT_ESTIMATE is the closest thing, but still different • Suffers from same side effects of single table – Magnified by longer ADS on joins – SPD from joins can be SUPERSEDED (HAS_STATS) too (*) 24
  25. 25. What happens to SPD after usage? (from 10053 of the second parse) SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 135484, objtyp = 1, vecsize = 4, colvec = [1, 2, 3, ], fid = 108…890 SPD: Inserted felem, fid=108…890,ftype = 0,freason = 0,dtype = 1,dstate = 2,… SPD: qosdRecDSDirChange dirid = 16004857199080262683, retCode = UPDATED (from dictionary) NOTES ---------------------------------------------------- <spd_note> <internal_state>MISSING_STATS</internal_state> <redundant>NO</redundant> <spd_text>{EC(MPAGANO.TAB1)[N1, N2, N3]}</spd_text> </spd_note> 25 CBO is aware there is a “weak path” and it had to use ADS in order to limit the damage
  26. 26. SPD instructs DBMS_STATS (from 10046 during parse) merge into sys.col_group_usage$ d using (select :1 obj#, :2 cols from dual) s on (d.obj# = s.obj# and d.cols = s.cols) when matched then update set d.timestamp = :3, d.flags = d.flags + :4 - bitand(d.flags, :4) when not matched then insert (obj#, cols, timestamp, flags) values (:1,:2,:3,:4) :1 -> 135484 :2 -> “1,2,3” :3 -> ”1/12/2017 8:33:7” :4 -> 17 (from 10046 during DBMS_STATS run) SELECT ... FROM SYS.COL_GROUP_USAGE$ CU … UPDATE SYS.COL_GROUP_USAGE$ C SET C.FLAGS = FLAGS + 8 - BITAND(FLAGS, 8) WHERE OBJ# = :B2 AND COLS = :B1 COLUMN_NAME DATA_DEFAULT NUM_DISTINCT HISTOGRAM ------------------------------ ------------------------------------ ------------ --------- SYS_STSOYQUEIAZ7FI9DV53VLN$$$0 SYS_OP_COMBINED_HASH("N1","N2","N3") 100 FREQUENCY 26
  27. 27. Then what happens to SPD? SINGLE TABLE ACCESS PATH Single Table Cardinality Estimation for TAB1[TAB1] SPD: Directive valid: dirid=160…83,state=2,flags=1,loc=1{EC(…)[1, 2, 3]} ... ColGroup (#1, VC) SYS_STSOYQUEIAZ7FI9DV53VLN$$$0 Col#: 1 2 3 … Table: TAB1 Alias: TAB1 Card: Original: 100000.000000 Rounded: 1000 Computed: 1000.000000 … SPD: Inserted felem, fid=10…890,…,dtype = 1, dstate = 3, dflag = 1,… … NOTES ------------------------------------------------------ <spd_note> <internal_state>HAS_STATS</internal_state> <redundant>NO</redundant> <spd_text>{EC(MPAGANO.TAB1)[N1, N2, N3]}</spd_text> </spd_note> 27 If the CG doesn’t help then SPD is marked as PERMANENT and behaves like MISSING_STATS (ADS used) No mistake 
  28. 28. SPD DS results • DS results are stored – Multiple SQL IDs (different parse) would trigger same DS SQL • In 12.1 Result Cache is used – Results have lifetime of 3600 secs – Result Cache itself had some troubles in the past • Mostly latch contention under heavy load • In 12.2 SPD repository itself used to store results – Makes them more permanent – Search in the repo based on ADS recursive SQL ID 28
  29. 29. Is my SQL using SPD? • Many SPDs can reference just a few objects – Even simple SQL can use many SPDs • CBO looks into them and pick up valid – A subset of Valid are Used • OTHER_XML reports #valid/#used • DBMS_XPLAN to show if SQL is using SPDs – DISPLAY (explain plan) reports which ones – DISPLAY_CURSOR (execution) reports just #used 29
  30. 30. DBMS_SPD • Oracle seeded package to manage SPDs • Move via pack/unpack in stgtab like baselines – Base 12.1.0.2 has bugs that impact xfr of SPDs • Allow to manually flush SPDs to disk – Instead of waiting 15 minutes • Can set basic preferences – For example, retention period before auto drop 30
  31. 31. Why the bad reputation? • Some issues caused large negative impact – Hard to spot when the feature is “transparent” – Main symptoms mutex / latch contention • SPDs generated based on workload – Performance tends get better “with time” • Makes performance in Prod bad on day 1 • Even though it was great in Test on day 200 – Upgrades need extra steps (move SPDs) • Limited number of Column Groups per table – Less useful CG could be created instead of useful ones 31
  32. 32. Most common problems • Most issues are ultimately caused by ADS – ADS running for too long – ADS executed even for small app SQLs (no need) • Longer parse caused by sampling – Parse is a serialized operation, parser hold X mutex – Other sessions with same SQL are stuck – Easy for snowball effect to trigger • Result Cache maybe not the best decision? 32
  33. 33. Solutions? • I’m personally a big fan of SPD – But I’m not a Production DBA  • Many products require to turn it off in 12.1 – Bad habit was to turn off all Adaptive Features via parameter – Oracle patch split parameter in two (AdaptPlans vs AdaptStats) • So just SPD and ADS can be disabled, Adaptive Plans stay ON • Oracle recommended solution in 12.1, SPD OFF with patch+param • Disabled by default in 12.2 – When enabled it seems a bit more conservative – Too early to judge how it will behave in 12.2 prod 33
  34. 34. Summary • Goal is improve CBO estimations over time – Tracking correlation in many areas – Putting stats / ADS in place to catch that • Might take time and introduce instability – Makes comparing two systems harder • Generated issues in 12.1 – Oracle recommends to disable by default – Enable back specific systems might be beneficial 34
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  36. 36. Contact Information • http://mauro-pagano.com – Email • mauro.pagano@gmail.com – Free tools to download • SQLd360 • TUNAs360 • PAthfinder 36

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