You could:
1. cut out the transaction and continue along the same lines
2. select into a temporary table and calculate 's' at the same time
then update using the temporary table
3. do an inline update to simply use an SQL statement to update opace
directly
Since 2 and 3 one can do directly in psql you don't need to do much,
other than wait; assuming 's' isn't complicated to calculate.
By the way the namedtuple cursor
(http://initd.org/psycopg/docs/extras.html#namedtuple-cursor)
I find much more convenient, and allows one to do something like
record = records.address2
-- although I find your variable naming a bit confusing!
Rory
On 09/06/15, Dan Sawyer (dansawyer@earthlink.net) wrote:
> Below is a snip it of python/psycopg2 code. It is inefficient when compared
> with parallel logic that creates a file and then updates the table in
> postgres sql from the file. In a test data base it takes 24 seconds to
> update 100,000 records. The actual database is over 5,000,000 records. The
> data base is on a solid state drive, I would imagine it would be very
> inefficient on a hard drive.
>
> # init lines
> conn_string = "host='localhost' dbname='opace0421' user='dan' port=5432"
> print ("Connecting to database\n ->%s" % (conn_string))
> conn = psycopg2.connect(conn_string)
> cursori = conn.cursor(cursor_factory=psycopg2.extras.DictCursor)
> cursoro = conn.cursor(cursor_factory=psycopg2.extras.DictCursor)
> work_mem = 2048
> cursori.execute('SET work_mem TO %s', (work_mem,))
> cursori.execute('select address_2, row_num from opace')
> i = 1
> while i != 100000:
> records = cursori.fetchone()
> record = records['address_2']
> rn = str(records['row_num'])
>
> #python code to create replacement string s
>
> cursoro.execute("UPDATE opace SET p_norm_add = %s WHERE row_num =
> %s", (s, rn,))
> i = i+1
> conn.commit()
>
>
>
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