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cmdlineluser avatar cmdlineluser commented on September 21, 2024

Can reproduce.

It seems the _right is completely ignored for whatever reason.

(df1.join(df2, on="a")
    .select(pl.col("b").filter(pl.col("b") == pl.col("foo_right")))
    .collect()
)
# ComputeError: column 'foo' not available in 'DataFrame' with Schema:
# name: a, data type: Int64
# name: b, data type: Int64

It appears to be projection_pushdown related:

(df1.join(df2, on="a")
    .select(pl.col("b").filter(pl.col("b") == pl.col("foo_right")))
    .collect(projection_pushdown=False)
)
# ColumnNotFoundError: foo_right

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ritchie46 avatar ritchie46 commented on September 21, 2024

The raising of eager seems to be correct. The join doesn't produce b_right:

df1 = pl.DataFrame({"a": [1,2,3]}).lazy()
df2 = pl.DataFrame({"a": [1,2,3], "b": [4,5,6]}).lazy()
df1.join(df2, on="a").collect()
run JoinExec
shape: (3, 2)
┌─────┬─────┐
│ a   ┆ b   │
│ --- ┆ --- │
│ i64 ┆ i64 │
╞═════╪═════╡
│ 1   ┆ 4   │
│ 2   ┆ 5   │
│ 3   ┆ 6   │
└─────┴─────┘

So it is a bug in your query and the lazy version should raise as well.

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