Re: Out of Memory and Configuration Problems (Big Computer)

On 5/28/10 8:43:48 PM, Tom Wilcox wrote:
> I ran this query:
>
> EXPLAIN ANALYZE UPDATE nlpg.match_data SET org = org;
>
> And I got this result:
>
> "Seq Scan on match_data (cost=0.00..9762191.68 rows=32205168 width=206)
> (actual time=76873.592..357450.519 rows=27777961 loops=1)"
> "Total runtime: 8028212.367 ms"

That would seem to indicate that the problem is in your Python
functions.

Some ideas for next steps:
* Perhaps it's just a few rows that have data in them that the
function has difficulty with. Add some debugging/logging to
the function and see if the row it bombs on has anything unusual
in it (such as a very large text field)
* While large, that function is fairly simplistic. You may want
to consider rewriting it as an SQL function, which should be
more efficient in any event.

>
>
> On 28 May 2010 19:39, Tom Wilcox <hungrytom(at)googlemail(dot)com
> <mailto:hungrytom(at)googlemail(dot)com>> wrote:
>
> Oops. Sorry about that.
>
> I am having this problem with multiple queries however I am
> confident that a fair number may involve the custom plpython
> "normalise" function which I have made myself. I didn't think it
> would be complicated enough to produce a memory problem.. here it is:
>
> -- Normalises common address words (i.e. 'Ground' maps to 'grd')
> CREATE OR REPLACE FUNCTION normalise(s text) RETURNS text AS $$
> ADDR_FIELD_DELIM = ' '
>
> # Returns distinct list without null or empty elements
> def distinct_str(list):
> seen = set()
> return [x for x in list if x not in seen and not seen.add(x)
> and x!=None and len(x)>0]
>
> # normalise common words in given address string
> def normalise(match_data):
> if match_data==None: return ''
> import re
> # Tokenise
> toks = distinct_str(re.split(r'\s', match_data.lower()))
> out = ''
> for tok in toks:
> ## full word replace
> if tok == 'house' : out += 'hse'+ADDR_FIELD_DELIM
> elif tok == 'ground' : out += 'grd'+ADDR_FIELD_DELIM
> elif tok == 'gnd' : out += 'grd'+ADDR_FIELD_DELIM
> elif tok == 'front' : out += 'fnt'+ADDR_FIELD_DELIM
> elif tok == 'floor' : out += 'flr'+ADDR_FIELD_DELIM
> elif tok == 'floors' : out += 'flr'+ADDR_FIELD_DELIM
> elif tok == 'flrs' : out += 'flr'+ADDR_FIELD_DELIM
> elif tok == 'fl' : out += 'flr'+ADDR_FIELD_DELIM
> elif tok == 'basement' : out += 'bst'+ADDR_FIELD_DELIM
> elif tok == 'subbasement' : out += 'sbst'+ADDR_FIELD_DELIM
> elif tok == 'bsmt' : out += 'bst'+ADDR_FIELD_DELIM
> elif tok == 'lbst' : out += 'lower bst'+ADDR_FIELD_DELIM
> elif tok == 'street' : out += 'st'+ADDR_FIELD_DELIM
> elif tok == 'road' : out += 'rd'+ADDR_FIELD_DELIM
> elif tok == 'lane' : out += 'ln'+ADDR_FIELD_DELIM
> elif tok == 'rooms' : out += 'rm'+ADDR_FIELD_DELIM
> elif tok == 'room' : out += 'rm'+ADDR_FIELD_DELIM
> elif tok == 'no' : pass
> elif tok == 'number' : pass
> elif tok == 'and' : out += '&'+ADDR_FIELD_DELIM
> elif tok == 'rear' : out += 'rr'+ADDR_FIELD_DELIM
> elif tok == 'part' : out += 'pt'+ADDR_FIELD_DELIM
> elif tok == 'south' : out += 's'+ADDR_FIELD_DELIM
> elif tok == 'sth' : out += 's'+ADDR_FIELD_DELIM
> elif tok == 'north' : out += 'n'+ADDR_FIELD_DELIM
> elif tok == 'nth' : out += 'n'+ADDR_FIELD_DELIM
> elif tok == 'west' : out += 'w'+ADDR_FIELD_DELIM
> elif tok == 'wst' : out += 'w'+ADDR_FIELD_DELIM
> elif tok == 'east' : out += 'e'+ADDR_FIELD_DELIM
> elif tok == 'est' : out += 'e'+ADDR_FIELD_DELIM
> elif tok == 'first' : out += '1st'+ADDR_FIELD_DELIM
> elif tok == 'second' : out += '2nd'+ADDR_FIELD_DELIM
> elif tok == 'third' : out += '3rd'+ADDR_FIELD_DELIM
> elif tok == 'fourth' : out += '4th'+ADDR_FIELD_DELIM
> elif tok == 'fifth' : out += '5th'+ADDR_FIELD_DELIM
> elif tok == 'sixth' : out += '6th'+ADDR_FIELD_DELIM
> elif tok == 'seventh' : out += '7th'+ADDR_FIELD_DELIM
> elif tok == 'eighth' : out += '8th'+ADDR_FIELD_DELIM
> elif tok == 'ninth' : out += '9th'+ADDR_FIELD_DELIM
> elif tok == 'tenth' : out += '10th'+ADDR_FIELD_DELIM
> elif tok == 'eleventh' : out += '11th'+ADDR_FIELD_DELIM
> elif tok == 'twelfth' : out += '12th'+ADDR_FIELD_DELIM
> elif tok == 'thirteenth' : out += '13th'+ADDR_FIELD_DELIM
> elif tok == 'fourteenth' : out += '14th'+ADDR_FIELD_DELIM
> elif tok == 'fifteenth' : out += '15th'+ADDR_FIELD_DELIM
> elif tok == 'sixteenth' : out += '16th'+ADDR_FIELD_DELIM
> elif tok == 'seventeenth' : out += '17th'+ADDR_FIELD_DELIM
> elif tok == 'eighteenth' : out += '18th'+ADDR_FIELD_DELIM
> elif tok == 'nineteenth' : out += '19th'+ADDR_FIELD_DELIM
> elif tok == 'twentieth' : out += '20th'+ADDR_FIELD_DELIM
> # numbers 0 - 20
> elif tok == 'one' : out += '1'+ADDR_FIELD_DELIM
> elif tok == 'two' : out += '2'+ADDR_FIELD_DELIM
> elif tok == 'three' : out += '3'+ADDR_FIELD_DELIM
> elif tok == 'four' : out += '4'+ADDR_FIELD_DELIM
> elif tok == 'five' : out += '5'+ADDR_FIELD_DELIM
> elif tok == 'six' : out += '6'+ADDR_FIELD_DELIM
> elif tok == 'seven' : out += '7'+ADDR_FIELD_DELIM
> elif tok == 'eight' : out += '8'+ADDR_FIELD_DELIM
> elif tok == 'nine' : out += '9'+ADDR_FIELD_DELIM
> elif tok == 'ten' : out += '10'+ADDR_FIELD_DELIM
> elif tok == 'eleven' : out += '11'+ADDR_FIELD_DELIM
> elif tok == 'twelve' : out += '12'+ADDR_FIELD_DELIM
> elif tok == 'thirteen' : out += '13'+ADDR_FIELD_DELIM
> elif tok == 'fourteen' : out += '14'+ADDR_FIELD_DELIM
> elif tok == 'fifteen' : out += '15'+ADDR_FIELD_DELIM
> elif tok == 'sixteen' : out += '16'+ADDR_FIELD_DELIM
> elif tok == 'seventeen' : out += '17'+ADDR_FIELD_DELIM
> elif tok == 'eighteen' : out += '18'+ADDR_FIELD_DELIM
> elif tok == 'nineteen' : out += '19'+ADDR_FIELD_DELIM
> elif tok == 'twenty' : out += '20'+ADDR_FIELD_DELIM
> # town dictionary items
> elif tok == 'borough' : pass
> elif tok == 'city' : pass
> elif tok == 'of' : pass
> elif tok == 'the' : pass
> # a few extras (from looking at voa)
> elif tok == 'at' : pass
> elif tok == 'incl' : pass
> elif tok == 'inc' : pass
> else: out += tok+ADDR_FIELD_DELIM
> return out
>
> return normalise(s)
> $$ LANGUAGE plpythonu;
>
>
> Here's the create script for the table from pgAdmin (I hope that
> will be good enough instead of \d as I can't do that right now)..
>
> -- Table: nlpg.match_data
>
> -- DROP TABLE nlpg.match_data;
>
> CREATE TABLE nlpg.match_data
> (
> premise_id integer,
> usrn bigint,
> org text,
> sao text,
> "level" text,
> pao text,
> "name" text,
> street text,
> town text,
> pc postcode,
> postcode text,
> match_data_id integer NOT NULL DEFAULT
> nextval('nlpg.match_data_match_data_id_seq1'::regclass),
> addr_str text,
> tssearch_name tsvector,
>
> CONSTRAINT match_data_pkey1 PRIMARY KEY (match_data_id)
> )
> WITH (
> OIDS=FALSE
> );
> ALTER TABLE nlpg.match_data OWNER TO postgres;
> ALTER TABLE nlpg.match_data ALTER COLUMN "name" SET STATISTICS 10000;
>
>
> -- Index: nlpg.index_match_data_mid
>
> -- DROP INDEX nlpg.index_match_data_mid;
>
> CREATE INDEX index_match_data_mid
> ON nlpg.match_data
> USING btree
> (match_data_id);
>
> -- Index: nlpg.index_match_data_pc
>
> -- DROP INDEX nlpg.index_match_data_pc;
>
> CREATE INDEX index_match_data_pc
> ON nlpg.match_data
> USING btree
> (pc);
>
> -- Index: nlpg.index_match_data_pid
>
> -- DROP INDEX nlpg.index_match_data_pid;
>
> CREATE INDEX index_match_data_pid
> ON nlpg.match_data
> USING btree
> (premise_id);
>
> -- Index: nlpg.index_match_data_tssearch_name
>
> -- DROP INDEX nlpg.index_match_data_tssearch_name;
>
> CREATE INDEX index_match_data_tssearch_name
> ON nlpg.match_data
> USING gin
> (tssearch_name);
>
> -- Index: nlpg.index_match_data_usrn
>
> -- DROP INDEX nlpg.index_match_data_usrn;
>
> CREATE INDEX index_match_data_usrn
> ON nlpg.match_data
> USING btree
> (usrn);
>
> As you can see, no FKs or triggers..
>
> I am running: EXPLAIN ANALYZE UPDATE nlpg.match_data SET org = org;
>
> However, as it should take around 90mins (if it is linear) then I
> thought I would send this now and follow up with the results once it
> finishes. (Has taken 2hours so far..)
>
> Thanks very much for your help.
>
> Tom
>
>
> On 28 May 2010 17:54, "Bill Moran" <wmoran(at)potentialtech(dot)com
> <mailto:wmoran(at)potentialtech(dot)com>> wrote:
>>
>> In response to Tom Wilcox <hungrytom(at)googlemail(dot)com
>> <mailto:hungrytom(at)googlemail(dot)com>>:
>>
>> > In addition, I have discovered that the update query that runs
>> on each row
>> > of a 27million row ta...
>>
>> You're not liable to get shit for answers if you omit the mailing
>> list from
>> the conversation, especially since I know almost nothing about tuning
>> PostgreSQL installed on Windows.
>>
>> Are there multiple queries having this problem? The original
>> query didn't
>> have normalise() in it, and I would be highly suspicious that a custom
>> function may have a memory leak or other memory-intensive
>> side-effects.
>> What is the code for that function?
>>
>> For example, does:
>> UPDATE nlpg.match_data SET org = org WHERE match_data_id;
>> finish in a reasonable amount of time or exhibit the same out of
>> memory
>> problem?
>>
>> It'd be nice to see a \d on that table ... does it have any
>> triggers or
>> cascading foreign keys?
>>
>> And stop
>>
>> --
>>
>> Bill Moran
>> http://www.potentialtech.com
>> http://people.collaborativefusion.com/~wmoran/
>> <http://people.collaborativefusion.com/%7Ewmoran/>
>>
>

--
Bill Moran