Reputation: 1352
I am using psycopg2 (2.6) connect to PostgreSQL database in a multi-threading python program.
When queue size in program increase, select queries get error "no results to fetch", but inserts records to db works very well.
example code:
class Decoders(threading.Thread):
def __init__(self, queue):
threading.Thread.__init__(self)
self.queue = queue
def run(self):
self.decode()
def decode(self):
queue = self.queue
db = Database()
while queue.qsize() > 0:
# calling db methods, just an example
temp = queue.get()
db.select_records()
db.insert_record(temp)
and:
Decoders(queue).start()
Decoders(queue).start()
note: I don't have this problem with multiprocessing.
Edit:
When I start only one thread, the program doesn't have any problem.
database class:
class Database:
db = object
cursor = object
def __init__(self):
self.db = connect(host=conf_hostname,
database=conf_dbname,
user=conf_dbuser,
password=conf_dbpass,
port=conf_dbport)
self.db.autocommit = True
self.cursor = self.db.cursor()
def select_records(self):
self.cursor.execute(simple select)
return self.cursor.fetchall()
def insert_record(self, temp):
# insert query
Upvotes: 2
Views: 13666
Reputation: 156
We can create multiple cursor using single connection in psql.
Please use the below code
#!/usr/bin/env python
import psycopg2
from config import config
from psycopg2.pool import ThreadedConnectionPool
from multiprocessing import Process
import time
import threading
from multiprocessing import Queue
data_queque = Queue() # reader reads data from queue
SELECT_QUERY = 'Select something from some_table limit %s offset %s ';
INSERT_QUERY = "Insert INTO sometable (col1, col2, col3) values "
# writer write data to queue
class PsqlMultiThreadExample(object):
_select_conn_count = 10;
_insert_conn_count = 10;
_insert_conn_pool = None;
_select_conn_pool = None;
def __init__(self):
self = self;
def postgres_connection(self):
""" Connect to the PostgreSQL database server """
conn = None
try:
# read connection parameters
params = config()
# connect to the PostgreSQL server
print('Connecting to the PostgreSQL database...')
conn = psycopg2.connect(**params)
# create a cursor
cur = conn.cursor()
# execute a statement
print('PostgreSQL database version:')
cur.execute('SELECT version()')
# display the PostgreSQL database server version
db_version = cur.fetchone()
print(db_version)
# close the communication with the PostgreSQL
cur.close()
except (Exception, psycopg2.DatabaseError) as error:
print(error)
finally:
if conn is not None:
conn.close()
print('Database connection closed.')
def check_connection(self):
""" Checking the postgres database connection"""
conn = None;
try:
conn = PsqlMultiThreadExample._select_conn_pool.getconn()
# create a cursor
cur = conn.cursor()
# execute a statement
print('PostgreSQL database version:')
cur.execute('SELECT version()')
# display the PostgreSQL database server version
db_version = cur.fetchone()
print(db_version)
# close the communication with the PostgreSQL
cur.close()
except (Exception, psycopg2.DatabaseError) as error:
print(error)
finally:
if conn is not None:
conn.close()
print('Database connection closed.')
def create_connection_pool(self):
""" Create the thread safe threaded postgres connection pool"""
# calculate the max and min connection required
max_conn = PsqlMultiThreadExample._insert_conn_count + PsqlMultiThreadExample._select_conn_count;
min_conn = max_conn / 2;
params = config()
# creating separate connection for read and write purpose
PsqlMultiThreadExample._insert_conn_pool = PsqlMultiThreadExample._select_conn_pool \
= ThreadedConnectionPool(min_conn, max_conn, **params);
def read_data(self):
"""
This read thedata from the postgres and shared those records with each
processor to perform their operation using threads
Here we calculate the pardition value to help threading to read data from database
:return:
"""
pardition_value = 805000 / 10; # Its total record
# this helps to identify the starting number to get data from db
start_index = 1
for pid in range(1, 11):
# Getting connection from the connection pool
select_conn = PsqlMultiThreadExample._select_conn_pool.getconn();
insert_conn = PsqlMultiThreadExample._insert_conn_pool.getconn();
#setting auto commit true
insert_conn.autocommit = 1;
# insert_conn.set_isolation_level(ISOLATION_LEVEL_AUTOCOMMIT)
#Creating 10 process to perform the operation
ps = Process(target=self.process_data, args=(data_queque, pid, (start_index - 1) * pardition_value,
start_index * pardition_value, select_conn, insert_conn))
start_index = start_index + 1;
ps.daemon = True;
ps.start();
_start = time.time()
ps.join()
print "Process %s took %s seconds" % (pid, (time.time() - _start))
def process_data(self, queue, pid, start_index, end_index, select_conn, insert_conn):
"""
Here we process the each process into 10 multiple threads to do data process
:param queue:
:param pid:
:param start_index:
:param end_index:
:param select_conn:
:param insert_conn:
:return:
"""
print "\n";
print(" \n Started processing record from %s to %s" % (start_index, end_index))
pardition_value = (end_index - start_index) / 10;
for tid in range(1, 11):
ins_cur = insert_conn.cursor();
worker = threading.Thread(target=self.process_thread, args=(
queue, pid, tid, start_index, (start_index + pardition_value), select_conn.cursor(), ins_cur,
threading.Lock()))
start_index = start_index + pardition_value;
worker.daemon = True;
worker.start();
worker.join()
def process_thread(self, queue, pid, tid, start_index, end_index, sel_cur, ins_cur, lock):
"""
Thread read data from database and doing the elatic search to get
experience have the same data
:param queue:
:param pid:
:param tid:
:param start_index:
:param end_index:
:param sel_cur:
:param ins_cur:
:param lock:
:return:
"""
limit = end_index - start_index;
sel_cur.execute(SELECT_QUERY, (limit, start_index,))
rows = sel_cur.fetchall();
records.append(ins_cur.mogrify("(%s,%s,%s)", (row[0], row[1], row[2],)));
self.write_data(records, ins_cur, lock)
def write_data(self, records, ins_cur, lock):
"""
Insert the data with experience id
:param records:
:param ins_cur:
:param lock:
:return:
"""
lock.acquire()
if records and records != '':
ins_cur.execute(INSERT_QUERY + records)
lock.release()
if __name__ == '__main__':
_start = time.time()
cmp_clener = PsqlMultiThreadExample();
#Craeting database connection pool to help connection shared along process
cmp_clener.create_connection_pool()
cmp_clener.read_data();
print('Total Processing time %s seconds' % (time.time() - _start))
Upvotes: 0
Reputation: 2358
Are you creating a connection for each thread? If you have multiple threads you need a connection for each one (or a pool with locking mechanisms around the connections) otherwise you will have all sorts of weird issues.
Which is why you would not have issues in multiprocessing, since each process will be creating its own connection.
Upvotes: 6