Slow recursive CTE query questions, with row estimate and n_distinct issues
Hi, I have a performance problem with a query. I've uploaded it, along with the EXPLAIN ANALYZE output here [1]. 1: https://explain.depesz.com/s/w5vP I think the query is taking longer than I'd like, as PostgreSQL is not generating a great plan, in particular the estimated rows in parts of the plan are way off from the actual number of rows produced, and I think PostgreSQL might pick a better approach if it made more reasonable estimates. Looking at the row numbers on [1], I think things start to go wrong at row 11. The first part of the recursive CTE is estimated to generate 22,122 rows, and this isn't far off the 15,670 rows it generates. The WorkTable scan expects to generate 10x that though, at 221,220. Maybe that's reasonable, I'm unsure? Things seem to continue getting out of hand from this point. The nested loop on line 10 generates 232x less rows than expected, and this results in an overall overestimate of 4,317x. My theory as to why the row estimates is way off is that the planner is using the n_distinct counts for the derivation_inputs table, and they are way off [2]. I've set the stats target to the highest value for this table, so I'm unsure what I can do to improve these estimates? I've included relevant numbers for the two important tables below [2][3], as well as descriptions of the tables [4][5]. Does anyone know if my theory as to why the row estimates in the plan is right, or have any ideas as how I can make the query more performant? Thanks, Chris 2: derivation_inputs: COUNT(*): 285422539 reltuples: 285422528 derivation_id: COUNT(DISTINCT): 7508610 n_distinct: 4336644 (~57% of the true value) derivation_output_id: COUNT(DISTINCT): 5539406 n_distinct: 473762 (~8% of the true value) derivation_outputs: COUNT(*): 8206019 reltuples: 8205873 3: guix_data_service=> SELECT attname, n_distinct::integer FROM pg_stats WHERE tablename = 'derivation_outputs'; attname| n_distinct --+ derivation_id| -1 name | 54 derivation_output_details_id | 372225 id | -1 (4 rows) 4: guix_data_service@[local]:5432/patches_guix_data_service> \d+ derivation_inputs Table "guix_data_service.derivation_inputs" ┌──┬─┬───┬──┬─┬─┬──┬─┐ │Column│ Type │ Collation │ Nullable │ Default │ Storage │ Stats target │ Description │ ├──┼─┼───┼──┼─┼─┼──┼─┤ │ derivation_id│ integer │ │ not null │ │ plain │ 1│ │ │ derivation_output_id │ integer │ │ not null │ │ plain │ 1│ │ └──┴─┴───┴──┴─┴─┴──┴─┘ Indexes: "derivation_inputs_pkey" PRIMARY KEY, btree (derivation_id, derivation_output_id) WITH (fillfactor='100') "derivation_inputs_derivation_output_id_idx" btree (derivation_output_id) WITH (fillfactor='100') Foreign-key constraints: "derivation_id_fk" FOREIGN KEY (derivation_id) REFERENCES derivations(id) "derivation_output_id_fk" FOREIGN KEY (derivation_output_id) REFERENCES derivation_outputs(id) Access method: heap Options: autovacuum_vacuum_scale_factor=0.01, autovacuum_analyze_scale_factor=0.01 5: guix_data_service@[local]:5432/patches_guix_data_service> \d+ derivation_outputs Table "guix_data_service.derivation_outputs" ┌──┬───┬───┬──┬──┬──┬──┬─┐ │Column│ Type│ Collation │ Nullable │ Default│ Storage │ Stats target │ Description │ ├──┼───┼───┼──┼──┼──┼──┼─┤ │ derivation_id│ integer │ │ not null │ │ plain│ │ │ │ name │ character varying │ │ not null │ │ extended │ │ │ │ derivation_output_details_id │ integer │ │ not null │ │ plain│ │ │ │ id │ integer │ │ not null │ generated always as identity │ plain│ │ │ └──┴───┴───┴──┴──┴──┴──┴─┘ Indexes: "derivation_outputs_pkey" PRIMARY KEY, btree (derivation_id,
Re: Slow recursive CTE query questions, with row estimate and n_distinct issues
On Mon, Dec 28, 2020 at 7:51 AM Christopher Baines wrote: > derivation_inputs: > COUNT(*): 285422539 > reltuples: 285422528 > > derivation_id: > COUNT(DISTINCT): 7508610 > n_distinct: 4336644 (~57% of the true value) > > derivation_output_id: > COUNT(DISTINCT): 5539406 > n_distinct: 473762 (~8% of the true value) > If you expect the ratio of distinct of derivation_output_id values to be roughly linear going forward, you can set a custom value for n_distinct on the column (currently seems like -.0194, aka distinct count of derivation_output_id divided by reltuples of the table). You could also do this analysis every month or six and set the custom value as needed. https://www.postgresql.org/docs/current/sql-altertable.html I am not sure if it will resolve your query problems though.
Re: Slow recursive CTE query questions, with row estimate and n_distinct issues
On Mon, Dec 28, 2020 at 7:51 AM Christopher Baines wrote: > Hi, > > I have a performance problem with a query. I've uploaded it, along with > the EXPLAIN ANALYZE output here [1]. > > 1: https://explain.depesz.com/s/w5vP > > I think the query is taking longer than I'd like, as PostgreSQL is not > generating a great plan, in particular the estimated rows in parts of > the plan are way off from the actual number of rows produced, and I > think PostgreSQL might pick a better approach if it made more reasonable > estimates. > > Looking at the row numbers on [1], I think things start to go wrong at > row 11. The first part of the recursive CTE is estimated to generate > 22,122 rows, and this isn't far off the 15,670 rows it generates. The > WorkTable scan expects to generate 10x that though, at 221,220. Maybe > that's reasonable, I'm unsure? > > Things seem to continue getting out of hand from this point. The nested > loop on line 10 generates 232x less rows than expected, and this results > in an overall overestimate of 4,317x. > > My theory as to why the row estimates is way off is that the planner is > using the n_distinct counts for the derivation_inputs table, and they > are way off [2]. I've set the stats target to the highest value for this > table, so I'm unsure what I can do to improve these estimates? > > I've included relevant numbers for the two important tables below > [2][3], as well as descriptions of the tables [4][5]. > > Does anyone know if my theory as to why the row estimates in the plan is > right, or have any ideas as how I can make the query more performant? > > Thanks, > > Chris > > Hi Chris What is your realistic target maximum execution time for the query? Ideas off the top of my head sans all the usual tuning of shared_buffers et al... When was the last time autovacuum vacuumed and analyzed the source tables? Can you leverage a materialized view refreshing when necessary? Thinking for the 3 joined tables but could be applied to the whole result. If you can guarantee no duplicate rows before and after current UNION, change to UNION ALL. If you have the luxury of faster disk, such as NVMe, create a tablespace and move data and/or indexes there. Adjust storage planner options accordingly. Personally, I like to see guardrails on RECURSIVE CTE's but you know your data and clients better than I so may not be necessary. Suggestions include: 1. Limit recursion depth. It does not seem to be the intent here though but ask if really the whole is necessary. Not knowing the application but say 10 deep is all that is needed initially. If the need for more is required, run the query again but has a different guix_revisions.commit starting point. Think of it as pagination. 2. Cycle detection / prevention but depends on the hierarchy represented by the data. Doesn't seem to be the case here since the query as-is does return. HTH. -Greg
