Query executed during pg_dump leads to excessive memory usage

[Ulf Lohbrügge <ulf.lohbruegge@xxxxxxxxx>]

Hi there,

A database cluster (PostgreSQL 12.4 running on Amazon Aurora @ db.r5.xlarge) with a single database of mine consists of 1,656,618 rows in pg_class. Using pg_dump on that database leads to excessive memory usage and sometimes even a kill by signal 9:

2021-09-18 16:51:24 UTC::@:[29787]:LOG:  Aurora Runtime process (PID 29794) was terminated by signal 9: Killed
2021-09-18 16:51:25 UTC::@:[29787]:LOG:  terminating any other active server processes

2021-09-18 16:51:27 UTC::@:[29787]:FATAL:  Can't handle storage runtime process crash

2021-09-18 16:51:31 UTC::@:[29787]:LOG:  database system is shut down

The query that is being fired by pg_dump is the following:

SELECT t.tableoid, t.oid, t.typname, t.typnamespace, (SELECT pg_catalog.array_agg(acl ORDER BY row_n) FROM (SELECT acl, row_n FROM pg_catalog.unnest(coalesce(t.typacl,pg_catalog.acldefault('T',t.typowner))) WITH ORDINALITY AS perm(acl,row_n) WHERE NOT EXISTS ( SELECT 1 FROM pg_catalog.unnest(coalesce(pip.initprivs,pg_catalog.acldefault('T',t.typowner))) AS init(init_acl) WHERE acl = init_acl)) as foo) AS typacl, (SELECT pg_catalog.array_agg(acl ORDER BY row_n) FROM (SELECT acl, row_n FROM pg_catalog.unnest(coalesce(pip.initprivs,pg_catalog.acldefault('T',t.typowner))) WITH ORDINALITY AS initp(acl,row_n) WHERE NOT EXISTS ( SELECT 1 FROM pg_catalog.unnest(coalesce(t.typacl,pg_catalog.acldefault('T',t.typowner))) AS permp(orig_acl) WHERE acl = orig_acl)) as foo) AS rtypacl, NULL AS inittypacl, NULL AS initrtypacl, (SELECT rolname FROM pg_catalog.pg_roles WHERE oid = t.typowner) AS rolname, t.typelem, t.typrelid, CASE WHEN t.typrelid = 0 THEN ' '::"char" ELSE (SELECT relkind FROM pg_class WHERE oid = t.typrelid) END AS typrelkind, t.typtype, t.typisdefined, t.typname[0] = '_' AND t.typelem != 0 AND (SELECT typarray FROM pg_type te WHERE oid = t.typelem) = t.oid AS isarray FROM pg_type t LEFT JOIN pg_init_privs pip ON (t.oid = pip.objoid AND pip.classoid = 'pg_type'::regclass AND pip.objsubid = 0);

The query plan looks like this. It takes almost 13 minutes(!) to execute that query:

                                                                  QUERY PLAN
----------------------------------------------------------------------------------------------------------------------------------------------
 Hash Left Join  (cost=4.65..8147153.76 rows=1017962 width=280) (actual time=2.526..106999.294 rows=1026902 loops=1)
   Hash Cond: (t.oid = pip.objoid)
   ->  Seq Scan on pg_type t  (cost=0.00..36409.62 rows=1017962 width=122) (actual time=0.008..8836.693 rows=1026902 loops=1)
   ->  Hash  (cost=4.64..4.64 rows=1 width=45) (actual time=2.342..41.972 rows=0 loops=1)
         Buckets: 1024  Batches: 1  Memory Usage: 8kB
         ->  Seq Scan on pg_init_privs pip  (cost=0.00..4.64 rows=1 width=45) (actual time=2.341..22.109 rows=0 loops=1)
               Filter: ((classoid = '1247'::oid) AND (objsubid = 0))
               Rows Removed by Filter: 176
   SubPlan 1
     ->  Aggregate  (cost=0.38..0.39 rows=1 width=32) (actual time=0.031..0.031 rows=1 loops=1026902)
           ->  Hash Anti Join  (cost=0.24..0.37 rows=1 width=20) (actual time=0.008..0.008 rows=0 loops=1026902)
                 Hash Cond: (perm.acl = init.init_acl)
                 ->  Function Scan on unnest perm  (cost=0.01..0.11 rows=10 width=20) (actual time=0.001..0.001 rows=2 loops=1026902)
                 ->  Hash  (cost=0.11..0.11 rows=10 width=12) (actual time=0.002..0.002 rows=2 loops=1026902)
                       Buckets: 1024  Batches: 1  Memory Usage: 9kB
                       ->  Function Scan on unnest init  (cost=0.01..0.11 rows=10 width=12) (actual time=0.001..0.001 rows=2 loops=1026902)
   SubPlan 2
     ->  Aggregate  (cost=0.38..0.39 rows=1 width=32) (actual time=0.050..0.050 rows=1 loops=1026902)
           ->  Hash Anti Join  (cost=0.24..0.37 rows=1 width=20) (actual time=0.008..0.008 rows=0 loops=1026902)
                 Hash Cond: (initp.acl = permp.orig_acl)
                 ->  Function Scan on unnest initp  (cost=0.01..0.11 rows=10 width=20) (actual time=0.001..0.001 rows=2 loops=1026902)
                 ->  Hash  (cost=0.11..0.11 rows=10 width=12) (actual time=0.002..0.002 rows=2 loops=1026902)
                       Buckets: 1024  Batches: 1  Memory Usage: 9kB
                       ->  Function Scan on unnest permp  (cost=0.01..0.11 rows=10 width=12) (actual time=0.001..0.001 rows=2 loops=1026902)
   SubPlan 3
     ->  Index Scan using pg_authid_oid_index on pg_authid  (cost=0.28..2.29 rows=1 width=64) (actual time=0.002..0.002 rows=1 loops=1026902)
           Index Cond: (oid = t.typowner)
   SubPlan 4
     ->  Index Scan using pg_class_oid_index on pg_class  (cost=0.43..2.45 rows=1 width=1) (actual time=0.003..0.003 rows=1 loops=671368)
           Index Cond: (oid = t.typrelid)
   SubPlan 5
     ->  Index Scan using pg_type_oid_index on pg_type te  (cost=0.42..2.44 rows=1 width=4) (actual time=0.020..0.020 rows=1 loops=355428)
           Index Cond: (oid = t.typelem)
 Planning Time: 0.535 ms
 Execution Time: 774011.175 ms
(35 rows)

The high number of rows in pg_class result from more than ~550 schemata, each containing more than 600 tables. It's part of a multi tenant setup where each tenant lives in its own schema.

I began to move schemata to another database cluster to reduce the number of rows in pg_class but I'm having a hard time doing so as a call to pg_dump might result in a database restart.

Is there anything I can do to improve that situation? Next thing that comes to my mind is to distribute those ~550 schemata over 5 to 6 databases in one database cluster instead of having one single database.

Best regards

Ulf