Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

refactor: Don't run streaming group-by in partitionable gb #15611

Merged
merged 2 commits into from
Apr 12, 2024
Merged

refactor: Don't run streaming group-by in partitionable gb #15611

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
785e52f
refactor: Don't run streaming group-by in partitionable gb
ritchie46 Apr 12, 2024
406b68e
update test
ritchie46 Apr 12, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
57 changes: 0 additions & 57 deletions crates/polars-lazy/src/physical_plan/executors/group_by_partitioned.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3,8 +3,6 @@ use polars_core::utils::{accumulate_dataframes_vertical, split_df};
use rayon::prelude::*;

use super::*;
#[cfg(feature = "streaming")]
use crate::physical_plan::planner::create_physical_plan;

/// Take an input Executor and a multiple expressions
pub struct PartitionGroupByExec {
Expand Down Expand Up @@ -249,54 +247,6 @@ fn can_run_partitioned(
}

impl PartitionGroupByExec {
#[cfg(feature = "streaming")]
fn run_streaming(
&mut self,
state: &mut ExecutionState,
original_df: DataFrame,
) -> Option<PolarsResult<DataFrame>> {
#[allow(clippy::needless_update)]
let group_by_options = GroupbyOptions {
slice: self.slice,
..Default::default()
}
.into();
let lp = LogicalPlan::GroupBy {
input: Arc::new(original_df.lazy().logical_plan),
keys: Arc::new(std::mem::take(&mut self.keys)),
aggs: std::mem::take(&mut self.aggs),
schema: self.output_schema.clone(),
apply: None,
maintain_order: false,
options: group_by_options,
};
let mut expr_arena = Default::default();
let mut lp_arena = Default::default();
let node = to_alp(lp, &mut expr_arena, &mut lp_arena).unwrap();

let inserted = streaming::insert_streaming_nodes(
node,
&mut lp_arena,
&mut expr_arena,
&mut vec![],
false,
false,
true,
)
.unwrap();

if inserted {
let mut phys_plan = create_physical_plan(node, &mut lp_arena, &mut expr_arena).unwrap();

if state.verbose() {
eprintln!("run STREAMING HASH AGGREGATION")
}
Some(phys_plan.execute(state))
} else {
None
}
}

fn execute_impl(
&mut self,
state: &mut ExecutionState,
Expand All @@ -321,13 +271,6 @@ impl PartitionGroupByExec {
);
}

#[cfg(feature = "streaming")]
if !self.maintain_order && std::env::var("POLARS_NO_STREAMING_GROUPBY").is_err() {
if let Some(out) = self.run_streaming(state, original_df.clone()) {
return out;
}
}

if state.verbose() {
eprintln!("run PARTITIONED HASH AGGREGATION")
}
Expand Down
5 changes: 1 addition & 4 deletions py-polars/tests/unit/test_queries.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,7 +1,6 @@
from __future__ import annotations

from datetime import date, datetime, time, timedelta
from typing import Any

import numpy as np
import pandas as pd
Expand Down Expand Up @@ -115,9 +114,7 @@ def test_maintain_order_after_sampling() -> None:
assert result.to_dict(as_series=False) == expected


def test_sorted_group_by_optimization(monkeypatch: Any) -> None:
monkeypatch.setenv("POLARS_NO_STREAMING_GROUPBY", "1")

def test_sorted_group_by_optimization() -> None:
df = pl.DataFrame({"a": np.random.randint(0, 5, 20)})

# the sorted optimization should not randomize the
Expand Down
Loading