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Implement VectorUdf and use it in Queries 1 and 8 of TPCH benchmarks. #127
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stephentoub
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src/csharp/Microsoft.Spark.Experimental/Sql/ExperimentalFunctions.cs
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Nice. |
imback82
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- Remove Vector<T> usage, instead have simple price calculation methods. - Formatting fix ups - Change generic type names A1 => T1
I've responded to all feedback and updated the PR. Please take a look. |
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LGTM |
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LGTM. Thanks @eerhardt!
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As requested in #45, this brings Vector UDF support to .NET for Apache Spark.
See https://databricks.com/blog/2017/10/30/introducing-vectorized-udfs-for-pyspark.html for the equivalent Python capabilities. This first round of implementation supports
PandasUDFType.SCALAR
type of UDFs, but grouped UDFs can be implemented in the future.On an Azure DS5 Ubuntu 18 box, I'm seeing the following results in these two TPCH queries using the
1 GB
dataset and a single core--master local
:Notes
DataFrame
type in .NET that can be created from an Arrow RecordBatch, with usable APIs. VectorUdf will be considered an "experimental" API until we have a stable long-term plan for how to pass columnar data to a .NET method.Vector<T>
, which still uses vectorization under the covers and works on the current targeted frameworks.