rishvin commented on issue #1941:
URL:
https://github.com/apache/datafusion-comet/issues/1941#issuecomment-3111745019
> Some Updates: I have a simple test to start with, which will produce
`_groupingmapsort`.
>
> ```
> val data = Seq(
> | Map("a" -> 1, "b" -> 2),
> | Map("a" -> 3, "b" -> 4),
> | Map("b" -> 2, "a" -> 1)
> | )
>
> val df = data.toDF("map")
> df.groupBy("map").count().show(false)
> ```
>
> So far based on my understanding, it looks like - this will require some
plumbing at the Parquet reader utils in Scala, because currently we only
support primitive types but `MapType` is a complex type. I made some hack to
bypass some type-checking, however, the `Native.initColumnReader()` expects
`primitiveTypeId`. I have to understand how the `MapType` would translate to
`primitiveTypeId`. The closest one at the moment seems to be parquet's `BINARY`
physical type. So, thinking of passing `BINARY` type and annotating with
`MapKeyValueTypeAnnotation`. However, I'm still trying to understand this piece
of code, so I might be wrong. I will do some more experiments to have more
clarity on this.
I managed to scan the map-type by setting
`CometConf.COMET_NATIVE_SCAN_IMPL.key -> native_datafusion `. Added `map_sort`
UDF with return type as `Map`.
However, it looks like doing a group-by on the map-type is not possible at
the moment. Native code throws error message like - `Not yet implemented: not
yet implemented: Map(...)`.
This error seems to be coming from Arrow. So, presently, we cannot use
MapType for grouping, we might have to translate map more simple type. Will
explore more on this.
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