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2nd pass of modifying various places which obtain the next power
of 2 of a number and make them use the new functions added in
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dependencies.c | ||
extended_stats.c | ||
Makefile | ||
mcv.c | ||
mvdistinct.c | ||
README | ||
README.dependencies | ||
README.mcv |
Extended statistics =================== When estimating various quantities (e.g. condition selectivities) the default approach relies on the assumption of independence. In practice that's often not true, resulting in estimation errors. Extended statistics track different types of dependencies between the columns, hopefully improving the estimates and producing better plans. Types of statistics ------------------- There are currently two kinds of extended statistics: (a) ndistinct coefficients (b) soft functional dependencies (README.dependencies) (c) MCV lists (README.mcv) Compatible clause types ----------------------- Each type of statistics may be used to estimate some subset of clause types. (a) functional dependencies - equality clauses (AND), possibly IS NULL (b) MCV lists - equality and inequality clauses (AND, OR, NOT), IS [NOT] NULL Currently, only OpExprs in the form Var op Const, or Const op Var are supported, however it's feasible to expand the code later to also estimate the selectivities on clauses such as Var op Var. Complex clauses --------------- We also support estimating more complex clauses - essentially AND/OR clauses with (Var op Const) as leaves, as long as all the referenced attributes are covered by a single statistics object. For example this condition (a=1) AND ((b=2) OR ((c=3) AND (d=4))) may be estimated using statistics on (a,b,c,d). If we only have statistics on (b,c,d) we may estimate the second part, and estimate (a=1) using simple stats. If we only have statistics on (a,b,c) we can't apply it at all at this point, but it's worth pointing out clauselist_selectivity() works recursively and when handling the second part (the OR-clause), we'll be able to apply the statistics. Note: The multi-statistics estimation patch also makes it possible to pass some clauses as 'conditions' into the deeper parts of the expression tree. Selectivity estimation ---------------------- Throughout the planner clauselist_selectivity() still remains in charge of most selectivity estimate requests. clauselist_selectivity() can be instructed to try to make use of any extended statistics on the given RelOptInfo, which it will do if: (a) An actual valid RelOptInfo was given. Join relations are passed in as NULL, therefore are invalid. (b) The relation given actually has any extended statistics defined which are actually built. When the above conditions are met, clauselist_selectivity() first attempts to pass the clause list off to the extended statistics selectivity estimation function. This functions may not find any clauses which is can perform any estimations on. In such cases these clauses are simply ignored. When actual estimation work is performed in these functions they're expected to mark which clauses they've performed estimations for so that any other function performing estimations knows which clauses are to be skipped. Size of sample in ANALYZE ------------------------- When performing ANALYZE, the number of rows to sample is determined as (300 * statistics_target) That works reasonably well for statistics on individual columns, but perhaps it's not enough for extended statistics. Papers analyzing estimation errors all use samples proportional to the table (usually finding that 1-3% of the table is enough to build accurate stats). The requested accuracy (number of MCV items or histogram bins) should also be considered when determining the sample size, and in extended statistics those are not necessarily limited by statistics_target. This however merits further discussion, because collecting the sample is quite expensive and increasing it further would make ANALYZE even more painful. Judging by the experiments with the current implementation, the fixed size seems to work reasonably well for now, so we leave this as future work.