feat: Query11 implementation

execute/q11.py

@@ -0,0 +1,38 @@
+from pathlib import Path
+
+import pandas as pd
+import polars as pl
+
+from queries import q11
+
+pd.options.mode.copy_on_write = True
+pd.options.future.infer_string = True
+
+nation = Path("data") / "nation.parquet"
+partsupp = Path("data") / "partsupp.parquet"
+supplier = Path("data") / "supplier.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(q11.query(fn(nation), fn(partsupp), fn(supplier)))
+
+tool = "pandas[pyarrow]"
+fn = IO_FUNCS[tool]
+print(q11.query(fn(nation), fn(partsupp), fn(supplier)))
+
+tool = "polars[eager]"
+fn = IO_FUNCS[tool]
+print(q11.query(fn(nation), fn(partsupp), fn(supplier)))
+
+tool = "polars[lazy]"
+fn = IO_FUNCS[tool]
+print(q11.query(fn(nation), fn(partsupp), fn(supplier)).collect())

queries/q11.py

@@ -0,0 +1,45 @@
+from datetime import datetime
+
+import narwhals as nw
+from narwhals.typing import FrameT
+
+
+@nw.narwhalify
+def query(
+    nation_ds_raw: FrameT,
+    partsupp_ds_raw: FrameT,
+    supplier_ds_raw: FrameT,
+) -> FrameT:
+    var1 = datetime(1993, 10, 1)
+    var2 = datetime(1994, 1, 1)
+
+    nation_ds = nw.from_native(nation_ds_raw)
+    partsupp_ds = nw.from_native(partsupp_ds_raw)
+    supplier_ds = nw.from_native(supplier_ds_raw)
+
+    var1 = "GERMANY"
+    var2 = 0.0001
+
+    q1 = (
+        partsupp_ds.join(supplier_ds, left_on="ps_suppkey", right_on="s_suppkey")
+        .join(nation_ds, left_on="s_nationkey", right_on="n_nationkey")
+        .filter(nw.col("n_name") == var1)
+    )
+    q2 = q1.select(
+        (nw.col("ps_supplycost") * nw.col("ps_availqty")).sum().round(2).alias("tmp")
+        * var2
+    )
+
+    q_final = (
+        q1.with_columns(
+            (nw.col("ps_supplycost") * nw.col("ps_availqty")).alias("value")
+        )
+        .group_by("ps_partkey")
+        .agg(nw.sum("value"))
+        .join(q2, how="cross")
+        .filter(nw.col("value") > nw.col("tmp"))
+        .select("ps_partkey", "value")
+        .sort("value", descending=True)
+    )
+
+    return nw.to_native(q_final)