examples/tips.py

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import os
import ray

from datafusion import SessionContext, col, lit, functions as F
from datafusion_ray import DatafusionRayContext

SCRIPT_DIR = os.path.dirname(os.path.realpath(__file__))

# Connect to a cluster
ray.init()

# Create a context and register a table
df_ctx = SessionContext()

ray_ctx = DatafusionRayContext(df_ctx)
# Register either a CSV or Parquet file
# ctx.register_csv("tips", f"{SCRIPT_DIR}/tips.csv", True)
df_ctx.register_parquet("tips", f"{SCRIPT_DIR}/tips.parquet")

result_set = ray_ctx.sql(
    "select sex, smoker, avg(tip/total_bill) as tip_pct from tips group by sex, smoker"
)
for record_batch in result_set:
    print(record_batch.to_pandas())

# Alternatively, to use the DataFrame API
df = df_ctx.read_parquet(f"{SCRIPT_DIR}/tips.parquet")
df = (
    df.aggregate(
        [col("sex"), col("smoker"), col("day"), col("time")],
        [F.avg(col("tip") / col("total_bill")).alias("tip_pct")],
    )
    .filter(col("day") != lit("Dinner"))
    .aggregate([col("sex"), col("smoker")], [F.avg(col("tip_pct")).alias("avg_pct")])
)

ray_results = ray_ctx.plan(df.execution_plan())
df_ctx.create_dataframe([ray_results]).show()