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from __future__ import annotations | ||
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from datetime import date | ||
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import narwhals.stable.v1 as nw | ||
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def q1(lineitem: nw.LazyFrame) -> nw.DataFrame: | ||
var_1 = date(1998, 9, 2) | ||
query_result = ( | ||
lineitem.filter(nw.col("l_shipdate") <= var_1) | ||
.with_columns( | ||
disc_price=nw.col("l_extendedprice") * (1 - nw.col("l_discount")), | ||
charge=( | ||
nw.col("l_extendedprice") | ||
* (1.0 - nw.col("l_discount")) | ||
* (1.0 + nw.col("l_tax")) | ||
), | ||
) | ||
.group_by(["l_returnflag", "l_linestatus"]) | ||
.agg( | ||
[ | ||
nw.col("l_quantity").sum().alias("sum_qty"), | ||
nw.col("l_extendedprice").sum().alias("sum_base_price"), | ||
nw.col("disc_price").sum().alias("sum_disc_price"), | ||
nw.col("charge").sum().alias("sum_charge"), | ||
nw.col("l_quantity").mean().alias("avg_qty"), | ||
nw.col("l_extendedprice").mean().alias("avg_price"), | ||
nw.col("l_discount").mean().alias("avg_disc"), | ||
nw.len().alias("count_order"), | ||
], | ||
) | ||
.sort(["l_returnflag", "l_linestatus"]) | ||
) | ||
return query_result.collect() | ||
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def q2( | ||
region: nw.LazyFrame, | ||
nation: nw.LazyFrame, | ||
supplier: nw.LazyFrame, | ||
part: nw.LazyFrame, | ||
part_supp: nw.LazyFrame, | ||
) -> nw.DataFrame: | ||
var_1 = 15 | ||
var_2 = "BRASS" | ||
var_3 = "EUROPE" | ||
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tmp = ( | ||
part.join(part_supp, left_on="p_partkey", right_on="ps_partkey") | ||
.join(supplier, left_on="ps_suppkey", right_on="s_suppkey") | ||
.join(nation, left_on="s_nationkey", right_on="n_nationkey") | ||
.join(region, left_on="n_regionkey", right_on="r_regionkey") | ||
.filter( | ||
nw.col("p_size") == var_1, | ||
nw.col("p_type").str.ends_with(var_2), | ||
nw.col("r_name") == var_3, | ||
) | ||
) | ||
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final_cols = [ | ||
"s_acctbal", | ||
"s_name", | ||
"n_name", | ||
"p_partkey", | ||
"p_mfgr", | ||
"s_address", | ||
"s_phone", | ||
"s_comment", | ||
] | ||
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return ( | ||
tmp.group_by("p_partkey") | ||
.agg(nw.col("ps_supplycost").min().alias("ps_supplycost")) | ||
.join( | ||
tmp, | ||
left_on=["p_partkey", "ps_supplycost"], | ||
right_on=["p_partkey", "ps_supplycost"], | ||
) | ||
.select(final_cols) | ||
.sort( | ||
["s_acctbal", "n_name", "s_name", "p_partkey"], | ||
descending=[True, False, False, False], | ||
) | ||
.head(100) | ||
.collect() | ||
) | ||
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def q3( | ||
customer: nw.LazyFrame, line_item: nw.LazyFrame, orders: nw.LazyFrame | ||
) -> nw.DataFrame: | ||
var_1 = var_2 = date(1995, 3, 15) | ||
var_3 = "BUILDING" | ||
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return ( | ||
customer.filter(nw.col("c_mktsegment") == var_3) | ||
.join(orders, left_on="c_custkey", right_on="o_custkey") | ||
.join(line_item, left_on="o_orderkey", right_on="l_orderkey") | ||
.filter( | ||
nw.col("o_orderdate") < var_2, | ||
nw.col("l_shipdate") > var_1, | ||
) | ||
.with_columns( | ||
(nw.col("l_extendedprice") * (1 - nw.col("l_discount"))).alias("revenue") | ||
) | ||
.group_by(["o_orderkey", "o_orderdate", "o_shippriority"]) | ||
.agg([nw.sum("revenue")]) | ||
.select( | ||
[ | ||
nw.col("o_orderkey").alias("l_orderkey"), | ||
"revenue", | ||
"o_orderdate", | ||
"o_shippriority", | ||
] | ||
) | ||
.sort(by=["revenue", "o_orderdate"], descending=[True, False]) | ||
.head(10) | ||
.collect() | ||
) |
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from __future__ import annotations | ||
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from pathlib import Path | ||
from typing import TYPE_CHECKING | ||
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import pytest | ||
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import narwhals.stable.v1 as nw | ||
from tpch.benchmarks.queries import q1 | ||
from tpch.benchmarks.queries import q2 | ||
from tpch.benchmarks.queries import q3 | ||
from tpch.benchmarks.utils import lib_to_reader | ||
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if TYPE_CHECKING: | ||
from pytest_codspeed.plugin import BenchmarkFixture | ||
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DATA_FOLDER = Path("tests/data") | ||
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@pytest.mark.parametrize("library", ["pandas", "polars", "pyarrow", "dask"]) | ||
def test_queries(benchmark: BenchmarkFixture, library: str) -> None: | ||
read_fn = lib_to_reader[library] | ||
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customer = nw.from_native(read_fn(DATA_FOLDER / "customer.parquet")).lazy() | ||
lineitem = nw.from_native(read_fn(DATA_FOLDER / "lineitem.parquet")).lazy() | ||
nation = nw.from_native(read_fn(DATA_FOLDER / "nation.parquet")).lazy() | ||
orders = nw.from_native(read_fn(DATA_FOLDER / "orders.parquet")).lazy() | ||
part = nw.from_native(read_fn(DATA_FOLDER / "part.parquet")).lazy() | ||
partsupp = nw.from_native(read_fn(DATA_FOLDER / "partsupp.parquet")).lazy() | ||
region = nw.from_native(read_fn(DATA_FOLDER / "region.parquet")).lazy() | ||
supplier = nw.from_native(read_fn(DATA_FOLDER / "supplier.parquet")).lazy() | ||
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_ = benchmark(q1, lineitem) | ||
_ = benchmark(q2, region, nation, supplier, part, partsupp) | ||
_ = benchmark(q3, customer, lineitem, orders) |
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import dask.dataframe as dd | ||
import pandas as pd | ||
import polars as pl | ||
import pyarrow.parquet as pq | ||
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lib_to_reader = { | ||
"dask": lambda path: dd.read_parquet(path, dtype_backend="pyarrow"), | ||
"pandas": pd.read_parquet, | ||
"polars": pl.scan_parquet, | ||
"pyarrow": pq.read_table, | ||
} |
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