Optimizing SQL query on table of 10 million rows: neverending query - sql

Question

I have two tables:
CREATE TABLE routing
(
id integer NOT NULL,
link_geom geometry,
source integer,
target integer,
traveltime_min double precision,
CONSTRAINT routing_pkey PRIMARY KEY (id)
)
WITH (
OIDS=FALSE
);
CREATE INDEX routing_id_idx
ON routing
USING btree
(id);
CREATE INDEX routing_link_geom_gidx
ON routing
USING gist
(link_geom);
CREATE INDEX routing_source_idx
ON routing
USING btree
(source);
CREATE INDEX routing_target_idx
ON routing
USING btree
(target);
and
CREATE TABLE test
(
link_id character varying,
link_geom geometry,
id integer NOT NULL,
.. (some more attributes here)
traveltime_min double precision,
CONSTRAINT id PRIMARY KEY (id),
CONSTRAINT test_link_id_key UNIQUE (link_id)
)
WITH (
OIDS=FALSE
);
ALTER TABLE test
OWNER TO postgres;
and I am trying to appy the follwing query:
update routing
set traveltime_min = t2.traveltime_min
from test t2
where t2.id = routing.id
Both tables have near 10 millions rows. The problem is that this query runs neverending. Here what 'EXPLAIN' shows:
Update on routing (cost=601725.94..1804772.15 rows=9712264 width=208)
-> Hash Join (cost=601725.94..1804772.15 rows=9712264 width=208)
Hash Cond: (routing.id = t2.id)"
-> Seq Scan on routing (cost=0.00..366200.23 rows=9798223 width=194)"
-> Hash (cost=423414.64..423414.64 rows=9712264 width=18)"
-> Seq Scan on test t2 (cost=0.00..423414.64 rows=9712264 width=18)"
I cannot understand what might cause the problem of such a slow response.
Is it possible to be a problem caused from the server settings? The thing is that i use the default postgrSQL 9.3 settings.

Answer 1

Drop all indexes on routing before you run the UPDATE and add them again afterwards. That will bring a huge improvement.
Set work_mem high in the session where you run the UPDATE. That will help with the hash.
Set shared_buffers to ¼ of the available memory, but not more than 1GB.

Answer 2

If not all the rows are actually changed by the UPDATE (if the get the same value as they had) , you should avoid these idempotent updates.
if you expect the query to affect every row, the query plan is not important. [except, maybe, for the case of overflowing hash tables ...]
-- these could be needed if the update would be more selective...
VACUUM analyze routing;
VACUUM analyze test;
UPDATE routing dst
SET traveltime_min = src.traveltime_min
FROM test src
WHERE dst.id = src.id
-- avoid useless updates and row-versions
AND dst.traveltime_min IS DISTINCT FROM src.traveltime_min
;
-- VACUUM analyze routing;