我的多处理程序遇到问题,恐怕这是一个相当简单的修复程序,而我只是没有正确正确地实现多处理程序。我一直在研究可能导致问题的原因,但我真正发现的是人们建议使用队列来防止这种情况发生,但这似乎并不能阻止它(再次,我可能只是在实现队列不正确),我已经来了几天,希望能得到一些帮助。提前致谢!
import csv
import multiprocessing as mp
import os
import queue
import sys
import time
import connections
import packages
import profiles
def execute_extract(package, profiles, q):
# This is the package execution for the extract
# It fires fine and will print the starting message below
started_at = time.monotonic()
print(f"Starting {package.packageName}")
try:
oracle_connection = connections.getOracleConnection(profiles['oracle'], 1)
engine = connections.getSQLConnection(profiles['system'], 1)
path = os.path.join(os.getcwd(), 'csv_data', package.packageName + '.csv')
cursor = oracle_connection.cursor()
if os.path.exists(path):
os.remove(path)
f = open(path, 'w')
chunksize = 100000
offset = 0
row_total = 0
csv_writer = csv.writer(f, delimiter='^', lineterminator='\n')
# I am having to do some data cleansing. I know this is not the most efficient way to do this, but currently
# it is what I am limited too
while True:
cursor.execute(package.query + f'\r\n OFFSET {offset} ROWS\r\n FETCH NEXT {chunksize} ROWS ONLY')
test = cursor.fetchone()
if test is None:
break
else:
while True:
row = cursor.fetchone()
if row is None:
break
else:
new_row = list(row)
new_row.append(package.sourceId[0])
new_row.append('')
i = 0
for item in new_row:
if type(item) == float:
new_row[i] = int(item)
elif type(item) == str:
new_row[i] = item.encode('ascii', 'replace')
i += 1
row = tuple(new_row)
csv_writer.writerow(row)
row_total += 1
offset += chunksize
f.close()
# I know that execution is at least reaching this point. I can watch the CSV files grow as more and more
# rows are added to the for all the packages What I never get are either the success message or error message
# below, and there are never any entries placed in the tables
query = f"BULK INSERT {profiles['system'].database.split('_')[0]}_{profiles['system'].database.split('_')[1]}_test_{profiles['system'].database.split('_')[2]}.{package.destTable} FROM \"{path}\" WITH (FIELDTERMINATOR='^', ROWTERMINATOR='\\n');"
engine.cursor().execute(query)
engine.commit()
end_time = time.monotonic() - started_at
print(
f"{package.packageName} has completed. Total rows inserted: {row_total}. Total execution time: {end_time} seconds\n")
os.remove(path)
except Exception as e:
print(f'An error has occured for package {package.packageName}.\r\n {repr(e)}')
finally:
# Here is where I am trying to add an item to the queue so the get method in the main def will pick it up and
# remove it from the queue
q.put(f'{package.packageName} has completed')
if oracle_connection:
oracle_connection.close()
if engine:
engine.cursor().close()
engine.close()
if __name__ == '__main__':
# Setting mp creation type
ctx = mp.get_context('spawn')
q = ctx.Queue()
# For the Etl I generate a list of class objects that hold relevant information profs contains a list of
# connection objects (credentials, connection strings, etc) packages contains the information to run the extract
# (destination tables, query string, package name for logging, etc)
profs = profiles.get_conn_vars(sys.argv[1])
packages = packages.get_etl_packages(profs)
processes = []
# I'm trying to track both individual package execution time and overall time so I can get an estimate on rows
# per second
start_time = time.monotonic()
sqlConn = connections.getSQLConnection(profs['system'])
# Here I'm executing a SQL command to truncate all my staging tables to ensure they are empty and will not
# generate any key violations
sqlConn.execute(
f"USE[{profs['system'].database.split('_')[0]}_{profs['system'].database.split('_')[1]}_test_{profs['system'].database.split('_')[2]}]\r\nExec Sp_msforeachtable @command1='Truncate Table ?',@whereand='and Schema_Id=Schema_id(''my_schema'')'")
# Here is where I start generating a process per package to try and get all packages to run simultaneously
for package in packages:
p = ctx.Process(target=execute_extract, args=(package, profs, q,))
processes.append(p)
p.start()
# Here is my attempt at managing the queue. This is a monstrosity of fixes I've tried to get this to work
results = []
while True:
try:
result = q.get(False, 0.01)
results.append(result)
except queue.Empty:
pass
allExited = True
for t in processes:
if t.exitcode is None:
allExited = False
break
if allExited & q.empty():
break
for p in processes:
p.join()
# Closing out the end time and writing the overall execution time in minutes.
end_time = time.monotonic() - start_time
print(f'Total execution time of {end_time / 60} minutes.')
我不确定您为什么会遇到死锁(我完全不相信这与您的队列管理有关),但是我可以肯定地说,如果您执行以下两种操作之一,则可以简化队列管理逻辑:
方法1
确保您的辅助函数execute_extract
即使在发生异常的情况下也将某些东西放在结果队列中(我建议您将Exception
对象本身放置)。然后,while True:
可以将尝试开始以获取结果的整个主过程循环替换为:
results = [q.get() for _ in range(len(processes))]
您可以确保队列中的消息数量固定为等于创建的进程数。
方法2(甚至更简单)
只需颠倒您等待子流程完成并处理结果队列的顺序。您不知道队列中将有多少条消息,但是直到所有进程都返回后,您才开始处理队列。因此,无论队列中有多少条消息,您将获得的全部。只需检索它们,直到队列为空:
for p in processes:
p.join()
results = []
while not q.empty():
results.append(q.get())
在这一点上,我通常建议您使用一个多处理池类,例如,multiprocessing.Pool
它不需要显式队列即可检索结果。但是,请进行以下任一更改(我建议使用方法2,因为此时只有主进程正在运行,我无法看到它如何导致死锁),然后查看问题是否消失。但是,我不能保证您的问题不在代码中。虽然您的代码过于复杂且效率低下,但显然不是“错误”。至少您会知道您的问题是否在其他地方。
还有我要问的问题:使用购买的上下文ctx = mp.get_context('spawn')
而不是仅调用multiprocessing
模块本身上的方法,它能使您做什么呢?如果您的平台支持fork
呼叫(这是默认上下文),您是否不想使用它?
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