DPark 0.2

Python clone of Spark, MapReduce like computing framework supporting iterative algorithms.

DPark is a Python clone of Spark, MapReduce(R) alike computing framework supporting iterative computation.

Example for word counting (wc.py):

import dpark
file = dpark.textFile("/tmp/words.txt")
words = file.flatMap(lambda x:x.split()).map(lambda x:(x,1))
wc = words.reduceByKey(lambda x,y:x+y).collectAsMap()
print wc

This script can run locally or on a Mesos cluster without any modification, just using different command-line arguments:

$ python wc.py
$ python wc.py -m process
$ python wc.py -m host[:port]

See examples/ for more use cases.

Some more docs (in Chinese): https://github.com/jackfengji/test_pro/wiki

DPark can run with Mesos 0.9 or higher.

If a $MESOS_MASTER environment variable is set, you can use a shortcut and run DPark with Mesos just by typing

$ python wc.py -m mesos

$MESOS_MASTER can be any scheme of Mesos master, such as

$ export MESOS_MASTER=zk://zk1:2181,zk2:2181,zk3:2181/mesos_master

In order to speed up shuffling, you should deploy Nginx at port 5055 for accessing data in DPARK_WORK_DIR (default is /tmp/dpark), such as:

server {
        listen 5055;
        server_name localhost;
        root /tmp/dpark/;
}

Mailing list: [e-mail] (http://groups.google.com/group/dpark-users)