On May 12, 1:40 am, Rhamphoryncus <[EMAIL PROTECTED]> wrote:
> On May 11, 10:16 am,skunkwerk<[EMAIL PROTECTED]> wrote:
>
>
>
> > On May 10, 1:31 pm, Dennis Lee Bieber <[EMAIL PROTECTED]> wrote:
>
> > > On Fri, 9 May 2008 08:40:38 -0700 (PDT),skunkwerk<[EMAIL PROTECTED]>
> > > declaimed the following in comp.lang.python:
>
> > > Coming in late...
>
> > > > On May 9, 12:12 am, John Nagle <[EMAIL PROTECTED]> wrote:
> > > > >skunkwerkwrote:
> > > > > > i've declared a bunch of workerthreads(100) and a queue into which
> > > > > > new requests are inserted, like so:
>
> > > <snip>
>
> > > > > > queue = Queue.Queue(0)
> > > > > > WORKERS=100
> > > > > > for i in range(WORKERS):
> > > > > > thread = SDBThread(queue)
> > > > > > thread.setDaemon(True)
> > > > > > thread.start()
>
> > > > > > the thread:
>
> > > > > > class SimpleDBThread ( threading.Thread ):
> > > > > > def __init__ ( self, queue ):
> > > > > > self.__queue = queue
>
> > > Note: double-leading __ means "name mangling" -- typically only
> > > needed when doing multiple layers of inheritance where different parents
> > > have similar named items that need to be kept independent; a single _ is
> > > the convention for "don't touch me unless you know what you are doing"
>
> > > > > > threading.Thread.__init__ ( self )
> > > > > > def run ( self ):
> > > > > > while 1:
> > > > > > item = self.__queue.get()
> > > > > > if item!=None:
> > > > > > model = domain.get_item(item[0])
> > > > > > logger.debug('sdbthread item:'+item[0])
> > > > > > title = model['title']
> > > > > > scraped = model['scraped']
> > > > > > logger.debug("sdbthread title:"+title)
>
> > > > > > any suggestions?
> > > > > > thanks
>
> > > <snip>
>
> > > > thanks John, Gabriel,
> > > > here's the 'put' side of the requests:
>
> > > > def prepSDBSearch(results):
> > > > modelList = [0]
> > > > counter=1
> > > > for result in results:
> > > > data = [result.item, counter, modelList]
> > > > queue.put(data)
> > > > counter+=1
> > > > while modelList[0] < len(results):
> > > > print 'waiting...'#wait for them to come home
> > > > modelList.pop(0)#now remove '0'
> > > > return modelList
>
> > > My suggestion, if you really want diagnostic help -- follow the
> > > common recommendation of posting the minimal /runable (if erroneous)/
> > > code... If "domain.get_item()" is some sort of RDBM access, you might
> > > fake it using a pre-loaded dictionary -- anything that allows it to
> > > return something when given the key value.
>
> > > > responses to your follow ups:
> > > > 1) 'item' in thethreadsis a list that corresponds to the 'data'
> > > > list in the above function. it's not global, and the initial values
> > > > seem ok, but i'm not sure if every time i pass in data to the queue it
> > > > passes in the same memory address or declares a new 'data' list (which
> > > > I guess is what I want)
>
> > > Rather confusing usage... In your "put" you have a list whose
> > > first
> > > element is "result.item", but then in the work thread, you refer to the
> > > entire list as "item"
>
> > > > 3) the first item in the modelList is a counter that keeps track of
> > > > the number ofthreadsfor this call that have completed - is there any
> > > > better way of doing this?
>
> > > Where? None of your posted code shows either "counter" or
> > > modelList
> > > being used by thethreads.
>
> > > And yes, if you havethreadstrying to update a shared mutable, you
> > > have a race condition.
>
> > > You also have a problem if you are using "counter" to define where
> > > in modelList a thread is supposed to store its results -- as you can not
> > > access an element that doesn't already exist...
>
> > > a = [0]
> > > a[3] = 1 #failure, need to create elements 1, 2, 3 first
>
> > > Now, if position is irrelevant, and a thread just appends its
> > > results to modelList, then you don't need some counter, all you need is
> > > to check the length of modelList against the count expected.
>
> > > Overall -- even though you are passing things via the queue, the
> > > contents being pass via the queue are being treated as if they were
> > > global entities (you could make modelList a global, remove it from the
> > > queue entries, and have the same net access)...
>
> > > IOWs, you have too much coupling between thethreadsand the feed
> > > routine...
>
> > > As for me... I'd be using a second queue for return values...
>
> > > WORKERTHREADS = 100
> > > feed = Queue.Queue()
> > > result = Queue.Queue()
>
> > > def worker():
> > > while True:
> > > (ID, item) = feed.get() #I leave the
> > > queues globals
> > >
> > > #since they perform locking
> > >
> > > #internally
> > > model = domain.get_item(item)
> > > results.put( (ID, model["title"], model["scraped"]) )
>
> > > for i in range(WORKERTHREADS):
> > > aThread = threading.Thread(target=worker)
> > > #overkill to subclass as there is now no specialized init
> > > #and if I really wanted to make the queues non-global
> > > #I'd pass them as arguments:
> > > # threading.Thread(target=worker, args=(feed,
> > > results))
> > > #where worker is now
> > > # def worker(feed, results):
> > > aThread.setDaemon(True)
> > > aThread.start()
>
> > > ...
>
> > > def prepSearch(searches):
> > > modelList = []
> > > counter = 0
> > > for searchItem in searches:
> > > feed.put( (counter, searchItem) )
> > > counter += 1
> > > modelList.append(None) #extend list one element per
> > > search
> > > while counter:
> > > (ID, title, scraped) = results.get()
> > > modelList[ID] = (title, scraped)
> > > counter -= 1
> > > return modelList
>
> > > The only place counter and modelList are modified are within the
> > > prepSearch. I'm passing counter out and back to use as an ID value if
> > > the final results are supposed to be in order -- that way if one thread
> > > finishes before another, the items can be placed into the list where
> > > they'd have been sequentially.
>
> > > I can only hope that "domain.get_item" is an activity that is I/O
> > > bound AND that it supports parallel accesses... Otherwise the above
> > > workerthreadsseem to be adding a lot of overhead for queue I/O and
> > > threading swaps for what is otherwise a rather linear process.
>
> > > Perhaps your posts don't reveal enough... Maybe you have multiple
> > > mainthreadsthat are posting to the worker feed queue (and you were
> > > using separate mutables for storing the results). In this situation, I'd
> > > remove the results queue from being a global entity, create one queue
> > > per main processing thread, and pass the queue as one of the parameters.
> > > This way, a worker can return data to any source thread by using the
> > > supplied queue for the return...
>
> > > Modify prepSearch with:
>
> > > myQueue = Queue.Queue()
> > > ...
> > > feed.put( (counter, searchItem, myQueue) )
> > > ...
> > > (ID, title, scraped) = myQueue.get()
>
> > > Modify worker with:
>
> > > (ID, item, retqueue) = feed.get()
> > > ...
> > > retqueue.put( (ID, model["title"], model["scraped"]) )
>
> > wow. thanks for the help.
> > i seem to have fixed my problem though - it turns out
> > domain.get_item was not thread safe as it was using the underlying
> > httplib. the solution was to create a new connection to the database
> > for each thread (which is ok as the database is meant to be queried in
> > a massively paralell fashion). the missing part of the code included
> > a part where i inserted the results at the given position into the
> > list.
>
> > the only issue i have now is that it takes a long time for 100 threads
> > to initialize that connection (>5 minutes) - and as i'm doing this on
> > a webserver any time i update the code i have to restart all those
> > threads, which i'm doing right now in a for loop. is there any way I
> > can keep the thread stuff separate from the rest of the code for this
> > file, yet allow access? It wouldn't help having a .pyc or using
> > psycho, correct, as the time is being spent in the runtime? something
> > along the lines of 'start a new thread every minute until you get to a
> > 100' without blocking the execution of the rest of the code in that
> > file? or maybe any time i need to do a search, start a new thread if
> > the #threads is <100?
>
> $ python2.5 -m timeit -s 'import threading' 't = threading.Thread();
> t.start(); t.join()'
> 10000 loops, best of 3: 131 usec per loop
>
> Clearly it is not the threads themselves, but something else which is
> expensive.
>
> It's not clear why you need threads at all. Unless you've got a lot
> of cpus/cores running that DBMS, or it's got fairly high latency (and
> no way to pipeline), attacking it with more threads isn't gonna give
> significant speedups.
correct. the threads themselves are not taking up the time, but the
initialization of each thread (which includes making a new connection
to the database) - typically this is ~3 seconds. The database is
amazon's simpleDB, which is meant to support massively parallel
queries. once the connection has been made, queries are very fast.
thanks
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