Backend services for Ufora - fast, scalable, automatically parallel Python for data-science
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Ufora is a compiled, automatically parallel subset of python for data science and numerical computing.
Any code you run with Ufora will work unmodified in python. But with Ufora, it can run hundreds or thousands of times faster, and can operate on datasets many times larger than the RAM of a single machine.
Client installation is through pip. Workers can be booted in the cloud, or locally using docker.
#install the pyfora front-end and boto.
pip install pyfora boto
#link to your AWS account
export AWS_ACCESS_KEY_ID=<your aws access key id>
export AWS_SECRET_ACCESS_KEY=<your aws secret key>
#boot some workers in aws. This can take a couple of minutes.
pyfora_aws start --ec2-region us-west-2 --num-instances 4
Now we're ready to run some code:
import pyfora
#stick the ip address from pyfora_aws here
ufora = pyfora.connect('http://<ip_address>:30000')
def isPrime(p):
if p < 2: return 0
x = 2
while x*x <= p:
if p%x == 0: return 0
x = x + 1
return 1
with ufora.remotely.downloadAll():
result = sum(isPrime(x) for x in xrange(100 * 1000 * 1000))
print "found ", result, " primes between 0 and 100 million"
The ufora.remotely.downloadAll() block invokes Ufora. Without it, python
takes about an hour to do this on a fast machine. With 4 c3.8xlarge boxes on
amazon, pyfora takes about 10 seconds. It's the same exact code, hundreds of times
faster.
The current release, 0.1, is an early release of the Ufora python functionality.
The core Ufora VM has been under development for years, but the python front-end
is new.
As of the 0.1 release, most core python language features and primitives are
implemented, as are a few builtins (sum, xrange, range, etc.).
In the upcoming 0.2 release, we're planning on filling out some more of the
python builtins, implementing the basic functionality present in numpy and
pandas, and enabling a pathway to load data from amazon S3.
After that, we're considering some of the following:
scikit data science algorithms (gbm, regressions, etc.)Please let us know what you'd like to see next, or if you'd like to get involved.
Users of the Ufora platform should visit ufora-users. Developers should visit ufora-dev.
The development of Ufora is ongoing, and led by Ufora Inc.. Drop us a line if you'd like to get involved or need enterprise support.
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Last updated
almost 10 years ago
docker pull ufora/service