You can simply install Mars via pip:
pip install pymars
To run Mars on a single machine, there are two ways.
Threaded: a thread-based scheduling which is by default.
Local cluster: a process-based scheduling which owns the entire distributed runtime.
After installation, you can simply open a Python console and run
import mars.tensor as mt from mars.session import new_session a = mt.ones((5, 5), chunk_size=3) b = a * 4 # if there isn't a local session, # execute will create a default one first b.execute() # or create a session explicitly sess = new_session() b.execute(session=sess) # run b
Users can start the distributed runtime of Mars on a single machine. First, install Mars distributed by run
pip install 'pymars[distributed]'
For now, local cluster mode can only run on Linux and Mac OS.
Then start a local cluster by run
import mars.tensor as mt from mars.deploy.local import new_cluster from mars.session import new_session cluster = new_cluster() # new cluster will start a session and set it as default one # execute will then run in the local cluster a = mt.random.rand(10, 10) a.dot(a.T).execute() # cluster.session is the session created (a + 1).execute(session=cluster.session) # users can also create a session explicitly # cluster.endpoint needs to be passed to new_session session2 = new_session(cluster.endpoint) (a * 2).execute(session=session2)