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Using the interactive Ray Cluster for Modin

  • This example demonstrates how to connect to the Practicus AI Ray cluster we created, and execute modin + Ray operations.
  • Please run this example on the Ray Coordinator (master).
import practicuscore as prt 

# Let's get a Ray session.
# this is similar to running `import ray` and then `ray.init()`
ray = prt.distributed.get_client()

# Modin aims to be a drop-in replacement for pandas
# import pandas as pd
import modin.pandas as pd

df = pd.read_csv("/home/ubuntu/samples/airline.csv")

print("DataFrame type is:", type(df))

df["passengers"] = df["passengers"] * 2

df

Ray Dashboard

Practicus AI Ray offers an interactive dashboard where you can view execution details. Let's open the dashboard.

dashboard_url = prt.distributed.open_dashboard()

print("Page did not open? You can open this url manually:", dashboard_url)

df["passengers"] = df["passengers"] * 2

df

# Let's close the session
ray.shutdown()

Terminating the cluster

  • You can go back to the other worker where you created the cluster to run:

coordinator_worker.terminate()
- Or, terminate "self" and children workers with the below:

prt.get_local_worker().terminate()

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