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Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
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Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open

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  • 1. Click to edit Master subtitle style 1 Query Planning Gone Wrong Robert Haas Chief Architect, Database Server
  • 2. Why This Talk? ● 2010: The PostgreSQL Query Planner (Robert Haas) ● How does the query planner actually work from a user perspective? What does it really do? ● Very common audience question: What do I do when the query planner fails? How do I fix my query? ● 2011: Hacking the Query Planner (Tom Lane) ● How does the query planner actually work from a developer perspective? What does it *really* do? ● Plea for help to improve the query planner. ● But... what should we be improving?
  • 3. Methodology: Which Problems Matter? ● Read hundreds of email threads on pgsql-performance over a period of almost two years. ● Disregarded all those that were not about query performance problems. ● Decided what I thought the root cause (or, occasionally, causes) of each complaint was. ● Skipped a very small number where I couldn't form an opinion. ● Counted the number of times each problem was reported.
  • 4. Methodology: Possible Critiques ● The problems reported on pgsql-performance aren't necessarily representative of all the problems PostgreSQL users encounter (reporting bias). ● In particular, confusing problems might be more likely to be reported. ● I might not have correctly identified the cause of each problem (researcher bias). ● Others?
  • 5. Statistically Speaking, Why Is My Query Slow? (168) ● Settings (23). Includes anything you can fix with postgresql.conf changes, DDL, or operating systems settings changes. ● Just Plain Slow (23). Includes anything that amounts to an unreasonable expectation on the part of the user. These are often questions of the form “why is query A slower than query B?” when A is actually doing something much more expensive than B. ● We're Bad At That (22). Includes anything that could be faster in some other database product, but isn't fast in PostgreSQL for some reason (not implemented yet, or architectural artifact). ● Planner Error (83). Bad decisions about the cost of one plan vs. another plan due to limitations of the optimizer. ● Bugs (14). Bugs in the query planner, or in one case, the Linux kernel. ● User Error (3). User got confused and did something illogical.
  • 6. Settings (23) ● Planner Cost Constants (8). Adjustments needed to seq_page_cost, random_page_cost, and perhaps cpu_tuple_cost to accurately model real costs. ● Missing Index (4) ● Cost for @@ Operator Is Too Low (2) ● work_mem Too Low (2) ● Statistics Target Too Low (2) ● Statistics Target Too High (1) ● n_distinct Estimates Aren't Accurate On Large Tables (1) ● Not Analyzing Tables Often Enough (1) ● TOAST Decompression is Slow (1) ● vm.zone_reclaim_mode = 1 Causes Extra Disk I/O (1)
  • 7. Just Plain Slow (23) ● It Takes a While to Process a Lot of Data (6) ● Disks Are Slower Than Memory (6) ● Clauses Involving Multiple Tables Can't Be Pushed Down (2) ● Random I/O is Slower Than Sequential I/O (1) ● Linearly Scanning an Array is O(n) (1) ● One Regular Expression is Faster Than Two (1) ● Can't Figure Out Which Patterns Match a String Without Trying Them All (1) ● xmlagg Is Much Slower Than string_agg (1) ● Scanning More Tables is Slower Than Scanning Fewer Tables (1) ● Replanning Isn't Free (1) ● Repeated Concatenation Using xmlconcat Is Slow (1) ● UNION is Slower than UNION ALL (1)
  • 8. We're Bad At That (22) ● Plan Types We Can't Generate (11) ● Parameterized Paths (7). Two of these are post-9.2 complaints, involving cases where 9.2 can't parameterize as needed. ● Merge Append (3). Fixed in 9.1. ● Batched Sort of Data Already Ordered By Leading Columns (1). ● Executor Limitations (3) ● Indexing Unordered Data Causes Random I/O (1) ● <> is Not Indexable (1) ● DISTINCT + HashAggregate Reads All Input Before Emitting Any Results (1). This matters if there is a LIMIT. ● Architecture (8) ● No Parallel Query (2), Table Bloat (1), Backend Startup Cost (1), Redundant Updates Are Expensive (1), AFTER Trigger Queue Size (1), On-Disk Size of numeric (1), Autovacuum Not Smart About Inherited Tables (1)
  • 9. Planner Errors (83) ● Any guesses?
  • 10. Planner Errors (83) ● Conceptual Errors (28). The planner isn't able to recognize that two different queries are equivalent, so it doesn't even consider the best plan. ● Estimation Errors (55). The planner considers the optimal plan, but rejects it as too expensive. ● Row Count Estimation Errors (48). The planner mis-estimates the number of rows that will be returned by some scan, join, or aggregate. ● Cost Estimation Errors (7). The planner estimates the row count correctly but incorrectly estimates the relative cost.
  • 11. Grand Prize Winners ● Selectivity of filter conditions involving correlated columns is estimated inaccurately (13) ● Suppose we want all the rows from a table where a = 1 and b = 1 and c = 1 and d = 1 and e = 1. The planner must estimate the number of rows that will match, but only has statistics on each column individually. ● Planner incorrectly thinks that “SELECT * FROM foo WHERE a = 1 ORDER BY b LIMIT n” will fill the limit after reading a small percentage of the index (11) ● It can scan an index on b and filter for rows where a = 1. ● Or it can scan an index on a, find all rows where a = 1, and perform a top-N sort. ● It often prefers the former when the latter would be faster. ● Can often be worked around with a composite or functional index.
  • 12. Planner Error: Row Count Estimation – Others (24) ● Using WITH Results in a Bad Plan (5). Some of these are query fattening issues, while others result from failure to dig out variable statistics. ● Generic Plans Can Have Wildly Wrong Estimates (4). Improved. ● Selectivity Estimates on Arbitrary Estimates are Poor (4) ● Join Selectivity Doesn't Know about Cross-Table Correlations (3) ● Uncommitted Tuples Don't Affect Statistics (2) ● No Stats for WITH RECURSIVE (1) or GROUP BY (1) Results ● Redundant Equality Constraints Not Identified As Such (1) ● IN/NOT IN Estimation Doesn't Assume Array Elements Distinct (1). Fixed. ● Histogram Bounds Can Slide Due to New Data (1). Fixed. ● Inheritance Parents Aren't Assumed to be Completely Empty (1). Fixed.
  • 13. Planner Error: Cost Estimation (7) ● Planner doesn't account for de-TOASTing cost (4) ● Plan change causes volume of data to exceed server memory (2) ● Hash join sometimes decides to hash the larger table when it should probably be hashing the smaller one (1)
  • 14. Planner Error: Conceptual (28) ● Cross-data type comparisons are not always indexable (3) ● Inlining the same thing multiple times can lose (3) ● NOT IN is hard to optimize – and we don't try very hard (3) ● Target lists are computed too early or unnecessary targets are computed (3) ● Can't rewrite SELECT max(a) FROM foo WHERE b IN (…) as max of index scans (2) ● Can't rearrange joins and aggregates relative to one another (2) ● Can't deduce implied inequalities (2) ● Ten other issues that came up once each
  • 15. Thank You ● Any questions?

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