Using the interactive Spark Cluster Client

• This example demonstrates how to connect to the Practicus AI Spark cluster we created, and execute simple Spark operations.
• Please run this example on the Spark Coordinator (master).

import practicuscore as prt 

# Let's get a Spark session
spark = prt.distributed.get_client()

# And execute some code
data = [("Alice", 29), ("Bob", 34), ("Cathy", 23)]
columns = ["Name", "Age"]

# Create a DataFrame
df = spark.createDataFrame(data, columns)

# Perform a transformation
df_filtered = df.filter(df.Age > 30)

# Show results
df_filtered.show()

# Let's end the session
spark.stop()

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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