Slow query on large table with GROUP BY and ORDER BY I have a table with 7.2 million tuples which looks like this:

                               table public.methods
 column |          type         |                      attributes
--------+-----------------------+----------------------------------------------------
 id     | integer               | not null DEFAULT nextval('methodkey'::regclass)
 hash   | character varying(32) | not null
 string | character varying     | not null
 method | character varying     | not null
 file   | character varying     | not null
 type   | character varying     | not null
Indexes:
    "methods_pkey" PRIMARY KEY, btree (id)
    "methodhash" btree (hash)


Now I want to select some values but the query is incredibly slow:

db=# explain 
    select hash, string, count(method) 
    from methods 
    where hash not in 
          (select hash from nostring) 
    group by hash, string 
    order by count(method) desc;
                                            QUERY PLAN
----------------------------------------------------------------------------------------
 Sort  (cost=160245190041.10..160245190962.07 rows=368391 width=182)
   Sort Key: (count(methods.method))
   -&gt;  GroupAggregate  (cost=160245017241.77..160245057764.73 rows=368391 width=182)
       -&gt;  Sort  (cost=160245017241.77..160245026451.53 rows=3683905 width=182)
             Sort Key: methods.hash, methods.string
             -&gt;  Seq Scan on methods  (cost=0.00..160243305942.27 rows=3683905 width=182)
                   Filter: (NOT (SubPlan 1))
                   SubPlan 1
                   -&gt;  Materialize  (cost=0.00..41071.54 rows=970636 width=33)
                     -&gt;  Seq Scan on nostring  (cost=0.00..28634.36 rows=970636 width=33)


The hash column is the md5 hash of string and has an index. So I think my problem is that the whole table is sorted by id and not by hash, so it takes a while to sort it first and then group it?

The table nostring contains only a list of hashes I don't want to have. But I need both tables to have all values. So it's not an option to delete these.

additional info: none of the columns can be null (fixed that in the table definition) and i'm using postgresql 9.2.
The LEFT JOIN in @dezso's answer should be good. An index, however, will hardly be useful (per se), because the query has to read the whole table anyway - the exception being index-only scans in Postgres 9.2+ and favorable conditions, see below.

SELECT m.hash, m.string, count(m.method) AS method_ct
FROM   methods m
LEFT   JOIN nostring n USING (hash)
WHERE  n.hash IS NULL
GROUP  BY m.hash, m.string 
ORDER  BY count(m.method) DESC;


Run EXPLAIN ANALYZE on the query. Several times to exclude cashing effects and noise. Compare the best results.

Create a multi-column index that matches your query:

CREATE INDEX methods_cluster_idx ON methods (hash, string, method);


Wait? After I said an index wouldn't help? Well, we need it to CLUSTER the table:

CLUSTER methods USING methods_cluster_idx;
ANALYZE methods;


Rerun EXPLAIN ANALYZE. Any faster? It should be.

CLUSTER is a one-time operation to rewrite the whole table in the order of the used index. It is also effectively a VACUUM FULL. If you want to be sure, you'd run a pre-test with VACUUM FULL alone to see what can be attributed to that.

If your table sees a lot of write operations, the effect will degrade over time. Schedule CLUSTER at off-hours to restore the effect. Fine tuning depends of your exact use-case. The manual about CLUSTER.

CLUSTER is a rather crude tool, needs an exclusive lock on the table. If you can't afford that, consider pg_repack which can do the same without exclusive lock. More in this later answer:


Configuring PostgreSQL for read performance




If the percentage of NULL values in the column method is high (more than ~ 20 percent, depending on actual row sizes), a partial index should help:

CREATE INDEX methods_foo_idx ON methods (hash, string)
WHERE method IS NOT NULL;


(Your later update shows your columns to be NOT NULL, so not applicable.)

If you are running PostgreSQL 9.2 or later (as @deszo commented) the presented indexes may be useful without CLUSTER if the planner can utilize index-only scans. Only applicable under favorable conditions: No write operations that would effect the visibility map since the last VACUUM and all columns in the query have to be covered by the index. Basically read-only tables can use this any time, while heavily written tables are limited. More details in the Postgres Wiki.

The above mentioned partial index could be even more useful in that case.

If, on the other hand, there are no NULL values in column method, you should
1.) define it NOT NULL and
2.) use count(*) instead of count(method), that's slightly faster and does the same in the absence of NULL values.

If you have to call this query often and the table is read-only, create a MATERIALIZED VIEW.



Exotic fine point:
Your table is named nostring, yet seems to contain hashes. By excluding hashes instead of strings, there is a chance that you exclude more strings than intended. Extremely unlikely, but possible.