yordan-pavlov opened a new pull request #7261:
URL: https://github.com/apache/arrow/pull/7261


   Currently comparing an array to a scalar / literal value using the 
comparison operations defined in the comparison kernel here 
   
https://github.com/apache/arrow/blob/master/rust/arrow/src/compute/kernels/comparison.rs
   is very inefficient because:
   (1) an array with the scalar value repeated has to be created, taking time 
and wasting memory
   (2) time is spent during comparison to load the same literal values over and 
over
   
   This pull request implements scalar comparison functions and benchmarks 
indicate good performance gains:
   
   eq Float32 time: [938.54 us 950.28 us 962.65 us]
   eq scalar Float32 time: [836.47 us 838.47 us 840.78 us]
   eq Float32 simd time: [75.836 us 76.389 us 77.185 us]
   eq scalar Float32 simd time: [61.551 us 61.605 us 61.671 us]
   
   The benchmark results above show that the scalar comparison function is 
about 12% faster for non-SIMD and about 20% faster for SIMD comparison 
operations.
   And this is before accounting for creating the literal array. 
   In a more complex benchmark, the scalar comparison version is about 40% 
faster overall when we account for not having to create arrays of scalar / 
literal values.
   Here are the benchmark results:
   
   filter/filter with arrow SIMD (array) time: [647.77 us 675.12 us 706.69 us]
   filter/filter with arrow SIMD (scalar) time: [402.19 us 404.23 us 407.22 us]
   
   And here is the code for the benchmark:
   
https://github.com/yordan-pavlov/arrow-benchmark/blob/master/rust/arrow_benchmark/src/main.rs#L230
   
   In future these scalar comparison operations could be used to improve the 
performance of DataFusion with expressions comparing arrays to scalar / literal 
values which happens often in real world queries.
   
   @paddyhoran  @andygrove  let me know what you think


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