Speed up database inserts from ORM
I have a Django view that creates 500-5000 new INSERTS of a database in a loop. The problem is that it is very slow! I am getting about 100 inserts per minute on Postgres 8.3. We have used MySQL on smaller hardware (smaller EC2 instance) and have never experienced such speed issues.
More details: Postgres 8.3 on Ubuntu 9.04 server. The server is a "big" Amazon EC2 with an EBS (ext3) database - 11GB / 20GB.
Here are some of my postgresql.conf - let me know if you need more
shared_buffers = 4000MB
effective_cache_size = 7128MB
My python:
for k in kw:
k = k.lower()
p = ProfileKeyword(profile=self)
logging.debug(k)
p.keyword, created = Keyword.objects.get_or_create(keyword=k, defaults={'keyword':k,})
if not created and ProfileKeyword.objects.filter(profile=self, keyword=p.keyword).count():
#checking created is just a small optimization to save some database hits on new keywords
pass #duplicate entry
else:
p.save()
Some output from above:
top - 16:56:22 up 21 days, 20:55, 4 users, load average: 0.99, 1.01, 0.94
Tasks: 68 total, 1 running, 67 sleeping, 0 stopped, 0 zombie
Cpu(s): 5.8%us, 0.2%sy, 0.0%ni, 90.5%id, 0.7%wa, 0.0%hi, 0.0%si, 2.8%st
Mem: 15736360k total, 12527788k used, 3208572k free, 332188k buffers
Swap: 0k total, 0k used, 0k free, 11322048k cached
PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND
14767 postgres 25 0 4164m 117m 114m S 22 0.8 2:52.00 postgres
1 root 20 0 4024 700 592 S 0 0.0 0:01.09 init
2 root RT 0 0 0 0 S 0 0.0 0:11.76 migration/0
3 root 34 19 0 0 0 S 0 0.0 0:00.00 ksoftirqd/0
4 root RT 0 0 0 0 S 0 0.0 0:00.00 watchdog/0
5 root 10 -5 0 0 0 S 0 0.0 0:00.08 events/0
6 root 11 -5 0 0 0 S 0 0.0 0:00.00 khelper
7 root 10 -5 0 0 0 S 0 0.0 0:00.00 kthread
9 root 10 -5 0 0 0 S 0 0.0 0:00.00 xenwatch
10 root 10 -5 0 0 0 S 0 0.0 0:00.00 xenbus
18 root RT -5 0 0 0 S 0 0.0 0:11.84 migration/1
19 root 34 19 0 0 0 S 0 0.0 0:00.01 ksoftirqd/1
Let me know if other details would be helpful.
source to share
First, ORM operations will always be slower than pure SQL. I once wrote an update for a large database in ORM code and installed it working, but left it after a few hours when it only finished a small fraction. After rewriting in SQL, it all lasted less than a minute.
Second, keep in mind that your code here executes up to four separate operations with the database for each row of your data set - get
in get_or_create, perhaps, also create
, count
in the filter, and finally save
. This is a large database access.
Bearing in mind that no more than 5000 objects are small, you should first read the entire dataset into memory. You can then do a single filter
to get all the existing keyword objects in one go, keeping a huge number of queries in the keyword get_or_create
, and also avoiding the need to duplicate keyword profiles in the first place.
source to share