Hi
I am trying to update some audiences (email/phone matches) from BigQuery to
Google Ads
The largest are in the millions of rows, but less than 10 million for now
I am chunking them up to 1m row chunks but sometimes loading these
consecutively takes a long time.
I have been dabbling with threading, trying to load different chunks of an
audience concurrently & getting some XML_STREAM_EXC errors
I couldn't find much about this error but as things work without threading,
I assume it's driven by trying to do much at once for the API to handle, or
some mistake in the code on my part.
Is this threaded approach possible? Or is there another way to get to the
same result (faster loads)? Below is what I got to, which didn't work.
Thanks
Stephen
# here's what we're going to do to each chunk
def google_stuff(chunkStart,chunkEnd):
add_to_audience = gAudienceService.mutateMembers([{'operand':
{'userListId': this_audience_id,'membersList': [json.loads(x) for x in
add_query_data[chunkStart:chunkEnd].to_dict(orient='list')['GOOGLE']]},'operator':
'ADD'}])
# Chunk up the volume
chunkStart = 0
chunkIncrement = 100
chunkEnd = chunkStart+chunkIncrement
threads = []
counter = 0
# make some threads
while True:
if add_len > 0 and chunkStart < add_len:
this_thread_name = 'add_users_'+str(counter)
this_thread = threading.Thread(name=this_thread_name, target=google_stuff,
args=(chunkStart,chunkEnd,))
threads.append(this_thread)
this_thread.start()
time.sleep(5)
chunkStart += chunkIncrement
chunkEnd += chunkIncrement
counter += 1
else:
break
# wait till they all finish
for t in threads:
t.join()
--
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