DELETE records which do not have a match in another table

Question

There are two tables linked by an id:

item_tbl (id)
link_tbl (item_id)

There are some records in item_tbl that don't have matching rows in link_tbl. A select which would count their amount would be:

SELECT COUNT(*)
FROM link_tbl lnk LEFT JOIN item_tbl itm ON lnk.item_id=itm.id
WHERE itm.id IS NULL

I would like to delete those orphan records (those which don't have match in the other table) from link_tbl but the only way I could think of was:

DELETE FROM link_tbl lnk
WHERE lnk.item_id NOT IN (SELECT itm.id FROM item_tbl itm)

There are
262,086,253 records in link_tbl
3,033,811 in item_tbl
16,844,347 orphan records in link_tbl.
The server has 4GB RAM and 8 core CPU.

EXPLAIN DELETE FROM link_tbl lnk
WHERE lnk.item_id NOT IN (SELECT itm.id FROM item_tbl itm)

Returns:

Delete on link lnk  (cost=0.00..11395249378057.98 rows=131045918 width=6)
->  Seq Scan on link lnk  (cost=0.00..11395249378057.98 rows=131045918 width=6)
     Filter: (NOT (SubPlan 1))
     SubPlan 1
       ->  Materialize  (cost=0.00..79298.10 rows=3063207 width=4)
             ->  Seq Scan on item itm  (cost=0.00..52016.07 rows=3063207 width=4)

The questions are:

1. Is there any better way how to delete orphan records from link_tbl?

2. How accurate is the explain above, or how long it could take to delete those records?

   • Edit: fixed according to Erwin Brandstetter comment.
     
   • Edit: PostgreSql version is 9.1
   • Edit: some parts of postgresql.config
     1. shared_buffers = 368MB
     2. temp_buffers = 32MB
     3. work_mem = 32MB
     4. maintenance_work_mem = 64MB
     5. max_stack_depth = 6MB
     6. fsync = off
     7. synchronous_commit = off
     8. full_page_writes = off
     9. wal_buffers = 16MB
     10. wal_writer_delay = 5000ms
     11. commit_delay = 10
     12. commit_siblings = 10
     13. effective_cache_size = 1600MB

Resolution:

Thank you all for your advices, it was very helpful. I finally used the delete advised by Erwin Brandstetter https://stackoverflow.com/a/15959896/1331340 but I tweaked it a little:

DELETE FROM link_tbl lnk
WHERE lnk.item_id BETWEEN 0 AND 10000
  AND lnk.item_id NOT IN (SELECT itm.id FROM item itm
                          WHERE itm.id BETWEEN 0 AND 10000)

I compared results for NOT IN and NOT EXISTS and the output is below, although I used COUNT instead of DELETE which I think should be the same (I mean in sake of relative comparison):

EXPLAIN ANALYZE SELECT COUNT(*) 
FROM link_tbl lnk
WHERE lnk.item_id BETWEEN 0 AND 20000
  AND lnk.item_id NOT IN (SELECT itm.id
                          FROM item_tbl itm
                          WHERE itm.id BETWEEN 0 AND 20000);

QUERY PLAN
Aggregate  (cost=6002667.56..6002667.57 rows=1 width=0) (actual time=226817.086..226817.088 rows=1 loops=1)
->  Seq Scan on link_tbl lnk  (cost=1592.50..5747898.65 rows=101907564 width=0) (actual time=206.029..225289.570 rows=566625 loops=1)
     Filter: ((item_id >= 0) AND (item_id <= 20000) AND (NOT (hashed SubPlan 1)))
     SubPlan 1
       ->  Index Scan using item_tbl_pkey on item_tbl itm  (cost=0.00..1501.95 rows=36221 width=4) (actual time=0.056..99.266 rows=17560 loops=1)
             Index Cond: ((id >= 0) AND (id <= 20000))
Total runtime: 226817.211 ms


EXPLAIN ANALYZE SELECT COUNT(*)
FROM link_tbl lnk WHERE lnk.item_id>0 AND lnk.item_id<20000
  AND NOT EXISTS (SELECT 1 FROM item_tbl itm WHERE itm.id=lnk.item_id);

QUERY PLAN
Aggregate  (cost=8835772.00..8835772.01 rows=1 width=0)
   (actual time=1209235.133..1209235.135 rows=1 loops=1)
->  Hash Anti Join  (cost=102272.16..8835771.99 rows=1 width=0)
   (actual time=19315.170..1207900.612 rows=566534 loops=1)
     Hash Cond: (lnk.item_id = itm.id)
     ->  Seq Scan on link_tbl lnk  (cost=0.00..5091076.55 rows=203815128 width=4) (actual time=0.016..599147.604 rows=200301872 loops=1)
           Filter: ((item_id > 0) AND (item_id < 20000))
     ->  Hash  (cost=52016.07..52016.07 rows=3063207 width=4) (actual time=19313.976..19313.976 rows=3033811 loops=1)
           Buckets: 131072  Batches: 4  Memory Usage: 26672kB
           ->  Seq Scan on item_tbl itm  (cost=0.00..52016.07 rows=3063207 width=4) (actual time=0.013..9274.158 rows=3033811 loops=1)
Total runtime: 1209260.228 ms

NOT EXISTS was 5 times slower.

The actual delete of the data didn't take so long as I was worried, I was able to delete it in 5 batches (10000-20000,20000-100000,100000-200000,200000-1000000 and 1000000-1755441). At first I found out max item_id and I only had to went through half of the table.

When I tried NOT IN or EXISTS without the range (with select count) it didn't even finish, I let it run during the night and it was still running in the morning.

I think I was looking for DELETE with USING from wildplasser's answer https://stackoverflow.com/a/15988033/1331340 but it came too late.

DELETE FROM one o
USING (
    SELECT o2.id
    FROM one o2
    LEFT JOIN two t ON t.one_id = o2.id
    WHERE t.one_id IS NULL
    ) sq
WHERE sq.id = o.id
    ;

Answer 1

I benchmarked four typical queries, with different settings for {work_mem, effective_cache_size, random_page_cost}, these settings have the largest influence on the selected plan. I first did a "run in" with my default settings to warm the cache. Note: the test-set is small enough to allow all needed pages to be present in cache.

The test-set

SET search_path=tmp;

/************************/
DROP SCHEMA tmp CASCADE;
CREATE SCHEMA tmp ;
SET search_path=tmp;

CREATE TABLE one
        ( id SERIAL NOT NULL PRIMARY KEY
        , payload varchar
        );

CREATE TABLE two
        ( id SERIAL NOT NULL PRIMARY KEY
        , one_id INTEGER REFERENCES one
        , payload varchar
        );

INSERT INTO one (payload) SELECT 'Text_' || gs::text FROM generate_series(1,30000) gs;
INSERT INTO two (payload) SELECT 'Text_' || gs::text FROM generate_series(1,30000) gs;


UPDATE two t
SET one_id = o.id
FROM one o
WHERE o.id = t.id
AND random() < 0.1;

INSERT INTO two (one_id,payload) SELECT one_id,payload FROM two;
INSERT INTO two (one_id,payload) SELECT one_id,payload FROM two;
INSERT INTO two (one_id,payload) SELECT one_id,payload FROM two;

VACUUM ANALYZE one;
VACUUM ANALYZE two;
/***************/

The queries:

\echo NOT EXISTS()
EXPLAIN ANALYZE
DELETE FROM one o
WHERE NOT EXISTS ( SELECT * FROM two t
        WHERE t.one_id = o.id
        );

\echo NOT IN()
EXPLAIN ANALYZE 
DELETE FROM one o
WHERE o.id NOT IN ( SELECT one_id FROM two t)
        ;

\echo USING (subquery self LEFT JOIN two where NULL)
EXPLAIN ANALYZE
DELETE FROM one o
USING (
        SELECT o2.id
        FROM one o2
        LEFT JOIN two t ON t.one_id = o2.id
        WHERE t.one_id IS NULL
        ) sq
WHERE sq.id = o.id
        ;

\echo USING (subquery self WHERE NOT EXISTS(two)))
EXPLAIN ANALYZE
DELETE FROM one o
USING (
        SELECT o2.id
        FROM one o2
        WHERE NOT EXISTS ( SELECT *
                FROM two t WHERE t.one_id = o2.id
                )
        ) sq
WHERE sq.id = o.id
        ;

The result (summarised)

                        NOT EXISTS()    NOT IN()        USING(LEFT JOIN NULL)   USING(NOT EXISTS)
1) rpc=4.0.csz=1M wmm=64        80.358  14389.026       77.620                  72.917
2) rpc=4.0.csz=1M wmm=64000     60.527  69.104          51.851                  51.004
3) rpc=1.5.csz=1M wmm=64        69.804  10758.480       80.402                  77.356
4) rpc=1.5.csz=1M wmm=64000     50.872  69.366          50.763                  53.339
5) rpc=4.0.csz=1G wmm=64        84.117  7625.792        69.790                  69.627
6) rpc=4.0.csz=1G wmm=64000     49.964  67.018          49.968                  49.380
7) rpc=1.5.csz=1G wmm=64        68.567  3650.008        70.283                  69.933
8) rpc=1.5.csz=1G wmm=64000     49.800  67.298          50.116                  50.345

legend: 
rpc := "random_page_cost"
csz := "effective_cache_size"
wmm := "work_mem"

As you can see, the NOT IN() variant is very sensitive to shortage of work_mem. Agreed, the setting 64(KB) is very low, but this `more or less* corresponds to large data sets, which won't fit in hashtables, either.

EXTRA: during the warm-in phase, the NOT EXISTS() query suffered from extreme FK-trigger contention. This apears to be a result of a conflict with the vacuum deamon, which is still active after the table set-up.:

PostgreSQL 9.1.2 on x86_64-unknown-linux-gnu, compiled by gcc (Ubuntu/Linaro 4.6.1-9ubuntu3) 4.6.1, 64-bit
NOT EXISTS()
                                                           QUERY PLAN
--------------------------------------------------------------------------------------------------------------------------------
 Delete on one o  (cost=6736.00..7623.94 rows=27962 width=12) (actual time=80.596..80.596 rows=0 loops=1)
   ->  Hash Anti Join  (cost=6736.00..7623.94 rows=27962 width=12) (actual time=49.174..61.327 rows=27050 loops=1)
         Hash Cond: (o.id = t.one_id)
         ->  Seq Scan on one o  (cost=0.00..463.00 rows=30000 width=10) (actual time=0.003..5.156 rows=30000 loops=1)
         ->  Hash  (cost=3736.00..3736.00 rows=240000 width=10) (actual time=49.121..49.121 rows=23600 loops=1)
               Buckets: 32768  Batches: 1  Memory Usage: 1015kB
               ->  Seq Scan on two t  (cost=0.00..3736.00 rows=240000 width=10) (actual time=0.006..33.790 rows=240000 loops=1)
 Trigger for constraint two_one_id_fkey: time=467720.117 calls=27050
 Total runtime: 467824.652 ms
(9 rows)

Answer 2

First off: your text says:

I would like to delete those orphan records from item_tbl.

But your code says:

DELETE FROM link_tbl lnk ...

Update: On rereading the Q I find it more likely you want to delete orphaned rows in link_tbl. The row-counts point in that direction. @Lucas) query would be correct in this case. But I am afraid, NOT EXISTS is actually slower than NOT IN in this case.

To verify I ran a test case, that's remotely like your setup. Couldn't make it much bigger, or SQLfiddle would run into a timeout.

-> SQLfiddle.

NOT EXISTS would be faster for the reversed case. (I tested that, too.) EXISTS is better suited for testing the "many"-side. And generally, there is more to gain with EXISTS than with NOT EXISTS - that form has to check the whole table anyway. It's much harder to prove something does not exist than to prove that something exists. This universal truth also applies to databases.

Divide and conquer

This operation is suited to be split up. Especially if you have concurrent transactions (but even without) I would consider splitting the DELETE into several slices, so that the transaction can COMMIT after a decent amount of time.

Something like:

DELETE FROM link_tbl l
WHERE  l.item_id < 1000000
AND    l.item_id NOT IN (SELECT i.id FROM item_tbl i)

Then l.item_id BETWEEN 100001 AND 200000, etc.

You cannot automate this with a function. That would wrap everything into a transaction and defy the purpose. So you'd have to script it from any client.
Or you could use ..

dblink

This additional module lets you run separate transactions in any database including the one it's running in. And that can be done via persistent connection, which should remove most of the connection overhead. For instructions how to install it:
How to use (install) dblink in PostgreSQL?

DO would do the job (PostgreSQL 9.0 or later). Running 100 DELETE commands for 50000 item_id at a time:

DO
$$
DECLARE
   _sql text;
BEGIN

PERFORM dblink_connect('port=5432 dbname=mydb');  -- your connection parameters

FOR i IN 0 .. 100
LOOP
   _sql := format('
   DELETE FROM link_tbl l
   WHERE  l.item_id BETWEEN %s AND %s
   AND    l.item_id NOT IN (SELECT i.id FROM item_tbl i)'
   , (50000 * i)::text
   , (50000 * (i+1))::text);

   PERFORM  dblink_exec(_sql);
END LOOP;

PERFORM dblink_disconnect();

END
$$

If the script should get interrupted: dblink_connect writes to the DB log what it executed, so you see what's done already.

Answer 3

Perhaps this:

DELETE FROM link_tbl lnk
WHERE NOT EXISTS
  ( SELECT 1 FROM item_tbl item WHERE item.id = lnk.item_id );

When dealing with large numbers of records, it can be much more efficient to create a temp table, perform INSERT INTO SELECT * FROM ... then drop the original table, rename the temp table, then add your indexes back...