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[GitHub] [arrow-datafusion] comphead opened a new pull request, #4560: Write faster kernel for is_distinct
comphead opened a new pull request, #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560
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Closes #4482.
# Rationale for this change
See #4482
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[GitHub] [arrow-datafusion] alamb commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
alamb commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1344215044
@tustvold do you have any additional suggestions for speeding up this kernel?
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[GitHub] [arrow-datafusion] Dandandan commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
Dandandan commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1344860319
Ah on further look - I think it might not be correct for when the left and/or right side doesn't contain a null bitmap.
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[GitHub] [arrow-datafusion] alamb commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
alamb commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1344643540
> Yes, I believe there is a ticket already to add it
https://github.com/apache/arrow-rs/issues/960
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[GitHub] [arrow-datafusion] tustvold commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
tustvold commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1345182817
Agreed, I got the boolean expression wrong, I think the corrected form I posted is correct, and would require handling the single buffer case?
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[GitHub] [arrow-datafusion] alamb commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
alamb commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1353533903
> Do we need to move the is distinct and is not distinct to arrow-rs?
I agree -- we should move the kernel to arrow and that work is tracked by https://github.com/apache/arrow-rs/issues/960 (which is also referenced in the code) https://github.com/apache/arrow-datafusion/pull/4560/files#diff-133624520f20c20b33c2c54ec6ae565f09b058ef317ede0e768bd23bae30941dR26
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[GitHub] [arrow-datafusion] tustvold commented on a diff in pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
tustvold commented on code in PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#discussion_r1047821803
##########
datafusion/physical-expr/src/expressions/binary/kernels_arrow.rs:
##########
@@ -515,4 +513,40 @@ mod tests {
let err = modulus_decimal_scalar(&left_decimal_array, 0).unwrap_err();
assert_eq!("Arrow error: Divide by zero error", err.to_string());
}
+
+ #[test]
+ fn is_distinct_from_nulls() -> Result<()> {
Review Comment:
:+1:
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[GitHub] [arrow-datafusion] alamb commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
alamb commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1346615315
Thank you @comphead
Here is what I recommend:
1. Add tests to this PR (or point at other pre-existing tests) that show it works correctly with `NULL` values
2. Merge this PR and we can file a ticket to switch to the arrow-rs kernel if/when that is available.
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[GitHub] [arrow-datafusion] comphead commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
comphead commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1349906330
Avg time now **70s**
@alamb added tests for nulls
@tustvold iterating through `.values()` is significantly faster than accessing `value_unchecked(i)`
@Dandandan you mentioned null bitmap is optional, is it for some specific primitiveArray types?
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[GitHub] [arrow-datafusion] comphead commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
comphead commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1352554241
@liukun4515 thats a great question and the ticket still exists https://github.com/apache/arrow-rs/issues/960
But it requires a bit more work on arrow side, planning to take care on this ticket
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[GitHub] [arrow-datafusion] liukun4515 commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
liukun4515 commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1352487618
Do we need to move the `is distinct` and `is not distinct` to arrow-rs?
cc @alamb @alamb
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[GitHub] [arrow-datafusion] tustvold commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
tustvold commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1344873446
> please correct me if I'm wrong but current implementation in datafusion also lacks null bitmap?
The iterators consult the bitmap and return `Option<T>` and so the `x == y` is actually comparing `Option` and not the bare values.
> I think it might not be correct for when the left or right side doesn't contain a null bitmap.
Assuming `*out & (left | right)` is correct (which I _think_ it is) if either side is missing a null bitmap it simplifies to `*out & (left | TRUE)` i.e. `*out`.
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[GitHub] [arrow-datafusion] Dandandan commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
Dandandan commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1352121111
Nice, thank you @comphead !
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[GitHub] [arrow-datafusion] alamb merged pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
alamb merged PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560
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[GitHub] [arrow-datafusion] comphead commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
comphead commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1345348792
@Dandandan when you say null bitmap, do you mean this structure
https://github.com/apache/arrow-datafusion/blob/master/datafusion/common/src/from_slice.rs#L105?
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[GitHub] [arrow-datafusion] Dandandan commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
Dandandan commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1344855803
Looks correct to me and a really clever implementation!
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[GitHub] [arrow-datafusion] tustvold commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
tustvold commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1344393843
It needs proper testing but the following I think is correct
```
pub(crate) fn is_distinct_from<A>(left: A, right: A) -> Result<BooleanArray>
where
A: ArrayAccessor,
A::Item: PartialEq,
{
let ld = left.data();
let rd = right.data();
assert_eq!(ld.len(), rd.len());
let mut distinct = MutableBuffer::collect_bool(left.len(), |i| unsafe {
// SAFETY: i in range 0..len
left.value_unchecked(i) != right.value_unchecked(i)
});
if let (Some(l), Some(r)) = (ld.null_buffer(), rd.null_buffer()) {
let left = BitChunks::new(l.as_slice(), ld.offset(), ld.len());
let right = BitChunks::new(r.as_slice(), rd.offset(), rd.len());
// Pad to multiple of u64
distinct.resize(bit_util::ceil(ld.len(), 8), 0);
// Distinct so long as one or both are valid
distinct
.typed_data_mut::<u64>()
.iter_mut()
.zip(left)
.zip(right)
.for_each(|((out, left), right)| *out = *out & (left | right))
}
let builder = ArrayDataBuilder::new(DataType::Boolean)
.len(left.len())
.add_buffer(distinct.into());
Ok(BooleanArray::from(unsafe { builder.build_unchecked() }))
}
```
I'll work on getting it added to arrow-rs
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[GitHub] [arrow-datafusion] comphead commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
comphead commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1344643258
> Yes, I believe there is a ticket already to add it
Thanks, please ping the arrow-rs ticket for tracking and we close this issue once adopt arrow-rs new implementation
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[GitHub] [arrow-datafusion] comphead commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
comphead commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1351741474
Thanks @alamb Added 1 more test to cover ```
Arrow arrays will only contain a null bitmap if they have a non-zero null count, otherwise it will be empty. No null buffer means all positions are valid, i.e. non-null.```
For bench I'll create a separate PR
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[GitHub] [arrow-datafusion] Dandandan commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
Dandandan commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1345182062
> > please correct me if I'm wrong but current implementation in datafusion also lacks null bitmap?
>
> The iterators consult the bitmap and return `Option<T>` and so the `x == y` is actually comparing `Option` and not the bare values.
>
> > I think it might not be correct for when the left or right side doesn't contain a null bitmap.
>
> Assuming `*out & (left | right)` is correct (which I _think_ it is) if either side is missing a null bitmap it simplifies to `*out & (left | TRUE)` i.e. `*out`.
>
> Edit: I think it might need to be `(*out & left & right) | (left ^ right)` 🤔
The main thing I think is wrong is that `left.value_unchecked(i) != right.value_unchecked(I)` might return true or false regardless of validity for each `i`. If only the left side contains a bitmap, it should also consider this left bitmap for the results (always distinct if left side is null value regardless of values or distinct if valid and having different values)`.
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[GitHub] [arrow-datafusion] Dandandan commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
Dandandan commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1345371014
>
I mean the validity/null data structure that can optionally be present in arrow arrays. This uses a bitmap to encode false/true values (not valid / valid).
You can see it is accessed as `.null_buffer()` from the code from @tustvold .
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[GitHub] [arrow-datafusion] Dandandan commented on a diff in pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
Dandandan commented on code in PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#discussion_r1044424248
##########
datafusion/physical-expr/src/expressions/binary/kernels_arrow.rs:
##########
@@ -55,11 +55,58 @@ pub(crate) fn is_distinct_from<T>(
where
T: ArrowNumericType,
{
- Ok(left
- .iter()
- .zip(right.iter())
- .map(|(x, y)| Some(x != y))
- .collect())
+ let array_len = left.data().len().min(right.data().len());
+ let mut arr = vec![false; array_len].into_boxed_slice();
+
+ let left_values = left.values();
Review Comment:
It should also look at the null bitmap (if available).
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[GitHub] [arrow-datafusion] comphead commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
comphead commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1344620606
Thanks @tustvold @Dandandan for the feedback. The same 1B perf test for the code above is **90s**.
Will `is_distinct_from<A>/is_not_distinct_from<A>` be a part of arrow-rs and datafusion adopts it with new arrow-rs version?
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[GitHub] [arrow-datafusion] tustvold commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
tustvold commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1344624268
Yes, I believe there is a ticket already to add it
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[GitHub] [arrow-datafusion] comphead commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
comphead commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1344862892
> Ah on further look - I think it might not be correct for when the left or right side doesn't contain a null bitmap.
@Dandandan please correct me if I'm wrong but current implementation in datafusion also lacks null bitmap?
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[GitHub] [arrow-datafusion] ursabot commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
ursabot commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1352123362
Benchmark runs are scheduled for baseline = 40e6a67604514124332bf132020a026bbe5b5903 and contender = 454203174a49ac8f36fc64da59f43d20c1400348. 454203174a49ac8f36fc64da59f43d20c1400348 is a master commit associated with this PR. Results will be available as each benchmark for each run completes.
Conbench compare runs links:
[Skipped :warning: Benchmarking of arrow-datafusion-commits is not supported on ec2-t3-xlarge-us-east-2] [ec2-t3-xlarge-us-east-2](https://conbench.ursa.dev/compare/runs/cd60e9f4966d42199acc32987c515dc3...358b1912cf88474ba545bab17b551b8e/)
[Skipped :warning: Benchmarking of arrow-datafusion-commits is not supported on test-mac-arm] [test-mac-arm](https://conbench.ursa.dev/compare/runs/bb7edd0c83fd46ba8bde76e5eb8cbd55...9c80207f9a104b1cb749445553a85af1/)
[Skipped :warning: Benchmarking of arrow-datafusion-commits is not supported on ursa-i9-9960x] [ursa-i9-9960x](https://conbench.ursa.dev/compare/runs/169e796ec820431d91cbb9c02a86bbf1...387162958c664b43a78a0377ac613f38/)
[Skipped :warning: Benchmarking of arrow-datafusion-commits is not supported on ursa-thinkcentre-m75q] [ursa-thinkcentre-m75q](https://conbench.ursa.dev/compare/runs/df1c189de11b47a2952623dd8ef2d3d1...a8329820b7a242df92adf394943b4d90/)
Buildkite builds:
Supported benchmarks:
ec2-t3-xlarge-us-east-2: Supported benchmark langs: Python, R. Runs only benchmarks with cloud = True
test-mac-arm: Supported benchmark langs: C++, Python, R
ursa-i9-9960x: Supported benchmark langs: Python, R, JavaScript
ursa-thinkcentre-m75q: Supported benchmark langs: C++, Java
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[GitHub] [arrow-datafusion] alamb commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
alamb commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1352118183
Thanks @comphead
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[GitHub] [arrow-datafusion] comphead commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
comphead commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1343632676
Hi @Dandandan
This change includes optimization for `is_distinct/is_not_distinct`.
1B array processed with avg **170s** before, and **80s** now.
Also using our own conversion to `BooleanArray` instead of `BooleanArray::from_slice`, as their implementation likely loses ticks on derefencing in loop. This part allowed to save 20s. Perhaps we can fix it in arrow-rs as well.
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[GitHub] [arrow-datafusion] tustvold commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
tustvold commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1346622521
Some example cases to try out might be:
* NULL is distinct from the 0 value
* NULL is not distinct from NULL even if the value in the corresponding null slots are distinct
* NULL is distinct from an array containing no nulls
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[GitHub] [arrow-datafusion] alamb commented on a diff in pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
alamb commented on code in PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#discussion_r1048318618
##########
datafusion/physical-expr/src/expressions/binary/kernels_arrow.rs:
##########
@@ -482,4 +513,40 @@ mod tests {
let err = modulus_decimal_scalar(&left_decimal_array, 0).unwrap_err();
assert_eq!("Arrow error: Divide by zero error", err.to_string());
}
+
+ #[test]
+ fn is_distinct_from_nulls() -> Result<()> {
+ let left_int_array =
+ create_int_array(&[Some(0), Some(0), None, Some(3), Some(0), Some(0)]);
+ let right_int_array =
+ create_int_array(&[Some(0), None, None, None, Some(0), None]);
+
+ // is_distinct: left distinct right
+ let result = is_distinct_from(&left_int_array, &right_int_array)?;
+ assert_eq!(
+ BooleanArray::from(vec![
+ Some(false),
+ Some(true),
+ Some(false),
+ Some(true),
+ Some(false),
+ Some(true)
+ ]),
+ result
+ );
+ // is_distinct: left distinct right
Review Comment:
```suggestion
// is_not_distinct: left distinct right
```
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[GitHub] [arrow-datafusion] alamb commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
alamb commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1350915531
I think this PR is ready to merge. Please let me know if there any concerns with doing so otherwise I will do so tomorrow
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[GitHub] [arrow-datafusion] tustvold commented on pull request #4560: Write faster kernel for is_distinct
Posted by GitBox <gi...@apache.org>.
tustvold commented on PR #4560:
URL: https://github.com/apache/arrow-datafusion/pull/4560#issuecomment-1349929493
> iterating through .values() is significantly faster than accessing value_unchecked(i)
Yeah, I've seen this before. Last time it required some hackery with `inline(never)` to make it do the right thing. It is frustrating playing LLVM bingo :laughing:
> Avg time now 70s
Very cool, perhaps you could add the benchmark code so that we can catch regressions in this? I'm also curious if this benchmark contains any null values?
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