[
https://issues.apache.org/jira/browse/ARROW-9029?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Wes McKinney updated ARROW-9029:
--------------------------------
Description:
In analytics, it is common for data to be all not-null or mostly not-null. Data
with > 50% nulls tends to be more exceptional. In this light, our
{{BitmapReader}} class which allows iteration of each bit in a bitmap can be
computationally suboptimal for mostly set validity bitmaps.
I propose instead a new interface for use in kernel implementations, for lack
of a better term {{BitmapScanner}}. This works as follows:
* Uses hardware popcount to compute the number of set values in 256 bits at a
time (or whatever is the right window size).
* Code can use the returned "run" (length + # of set bits) to switch between
nullable/non-nullable code paths
For data with a lot of nulls, this may degrade performance somewhat but
probably not that much empirically. However, data that is mostly-not-null
should benefit from this.
This BitmapScanner utility can probably also be used to accelerate the
implementation of Filter for mostly-not-null data
I tried some other things that were slower (like trying to find the largest
consecutive run of all-set words) before doing the simple 256-bit popcount
solution.
was:
In analytics, it is common for data to be all not-null or mostly not-null. Data
with > 50% nulls tends to be more exceptional. In this light, our
{{BitmapReader}} class which allows iteration of each bit in a bitmap can be
computationally suboptimal for mostly set validity bitmaps.
I propose instead a new interface for use in kernel implementations, for lack
of a better term {{BitmapScanner}}. This works as follows:
* Uses popcount to accumulate consecutive 64-bit words from a bitmap where all
values are set, up to some limit (e.g. anywhere from 8 to 128 words or more --
we can use benchmarks to determine what is a good limit). The length of this
"all-on" run is returned to the caller in a single function call, so that this
"run" of data can be processed without any bit-by-bit bitmap checking
* If words containing unset bits is encountered, the scanner will similarly
accumulate non-full words until the next full word is encountered or a limit is
hit. The length of this "has nulls" run is returned to the caller, which then
proceeds bit-by-bit to process the data
For data with a lot of nulls, this may degrade performance somewhat but
probably not that much empirically. However, data that is mostly-not-null
should benefit from this.
This BitmapScanner utility can probably also be used to accelerate the
implementation of Filter for mostly-not-null data
> [C++] Implement BitmapScanner interface to accelerate processing of
> mostly-not-null data
> ----------------------------------------------------------------------------------------
>
> Key: ARROW-9029
> URL: https://issues.apache.org/jira/browse/ARROW-9029
> Project: Apache Arrow
> Issue Type: Improvement
> Components: C++
> Reporter: Wes McKinney
> Assignee: Wes McKinney
> Priority: Major
> Labels: pull-request-available
> Fix For: 1.0.0
>
> Time Spent: 1h 20m
> Remaining Estimate: 0h
>
> In analytics, it is common for data to be all not-null or mostly not-null.
> Data with > 50% nulls tends to be more exceptional. In this light, our
> {{BitmapReader}} class which allows iteration of each bit in a bitmap can be
> computationally suboptimal for mostly set validity bitmaps.
> I propose instead a new interface for use in kernel implementations, for lack
> of a better term {{BitmapScanner}}. This works as follows:
> * Uses hardware popcount to compute the number of set values in 256 bits at a
> time (or whatever is the right window size).
> * Code can use the returned "run" (length + # of set bits) to switch between
> nullable/non-nullable code paths
> For data with a lot of nulls, this may degrade performance somewhat but
> probably not that much empirically. However, data that is mostly-not-null
> should benefit from this.
> This BitmapScanner utility can probably also be used to accelerate the
> implementation of Filter for mostly-not-null data
> I tried some other things that were slower (like trying to find the largest
> consecutive run of all-set words) before doing the simple 256-bit popcount
> solution.
--
This message was sent by Atlassian Jira
(v8.3.4#803005)