feat: add q4 implementation

tpch/execute/q4.py

@@ -0,0 +1,36 @@
+from pathlib import Path
+
+import pandas as pd
+import polars as pl
+from queries import q4
+
+pd.options.mode.copy_on_write = True
+pd.options.future.infer_string = True
+
+line_item = Path("data") / "lineitem.parquet"
+orders = Path("data") / "orders.parquet"
+
+IO_FUNCS = {
+    "pandas": lambda x: pd.read_parquet(x, engine="pyarrow"),
+    "pandas[pyarrow]": lambda x: pd.read_parquet(
+        x, engine="pyarrow", dtype_backend="pyarrow"
+    ),
+    "polars[eager]": lambda x: pl.read_parquet(x),
+    "polars[lazy]": lambda x: pl.scan_parquet(x),
+}
+
+tool = "pandas"
+fn = IO_FUNCS[tool]
+print(q4.query(fn(line_item), fn(orders)))
+
+tool = "pandas[pyarrow]"
+fn = IO_FUNCS[tool]
+print(q4.query(fn(line_item), fn(orders)))
+
+tool = "polars[eager]"
+fn = IO_FUNCS[tool]
+print(q4.query(fn(line_item), fn(orders)))
+
+tool = "polars[lazy]"
+fn = IO_FUNCS[tool]
+print(q4.query(fn(line_item), fn(orders)).collect())

tpch/queries/q4.py

@@ -0,0 +1,31 @@
+from datetime import datetime
+
+import narwhals as nw
+from narwhals.typing import FrameT
+
+
+@nw.narwhalify
+def query(
+    line_item_ds_raw: FrameT,
+    orders_ds_raw: FrameT,
+) -> FrameT:
+    var_1 = datetime(1993, 7, 1)
+    var_2 = datetime(1993, 10, 1)
+
+    line_item_ds = nw.from_native(line_item_ds_raw)
+    orders_ds = nw.from_native(orders_ds_raw)
+
+    result = (
+        line_item_ds.join(orders_ds, left_on="l_orderkey", right_on="o_orderkey")
+        .filter(
+            nw.col("o_orderdate").is_between(var_1, var_2, closed="left"),
+            nw.col("l_commitdate") < nw.col("l_receiptdate"),
+        )
+        .unique(subset=["o_orderpriority", "l_orderkey"])
+        .group_by("o_orderpriority")
+        .agg(nw.len().alias("order_count"))
+        .sort(by="o_orderpriority")
+        .with_columns(nw.col("order_count").cast(nw.Int64))
+    )
+
+    return nw.to_native(result)