BACtaki commented on PR #1740:
URL: https://github.com/apache/systemds/pull/1740#issuecomment-1330084042
I have added the following API design notes to the JIRA:
1. Row aggregation: remove duplicate rows
* R: unique() removes duplicate rows, eg
```R
> df <- matrix(rep(1:6,length.out=9),nrow = 3,ncol=3,byrow = T)
> df
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 4 5 6
[3,] 1 2 3
> unique(df)
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 4 5 6
```
* SystemDS: the same can be achieved using the unique() sketch like so:
unique(X, dir="r")
2. Col aggregation: remove duplicate cols
* R: unique() removes duplicate rows, so we can obtain the desired
result using transpose, like so:
```R
> df <- matrix(rep(1:6,length.out=9),nrow = 3,ncol=3)
> df
[,1] [,2] [,3]
[1,] 1 4 1
[2,] 2 5 2
[3,] 3 6 3
> df_t
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 4 5 6
[3,] 1 2 3
> df_t_ = unique(df_t)
> df_t_
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 4 5 6
> df_t_t = t(df_t_)
> df_t_t
[,1] [,2]
[1,] 1 4
[2,] 2 5
[3,] 3 6
```
* SystemDS: the same can be achieved using the unique() sketch like so:
unique(X, dir="c")
3. RowCol aggregation: return only unique values in given matrix
* SystemDS
X = [[1, 1], [2, 2], [3, 3]]
unique(X) will return X' = [[1], [2], [3]]
* R
This is similar to how unique() operates on vectors in R:
```R
> df <- c(1, 1, 2, 2, 3, 3)
> df
[1] 1 1 2 2 3 3
> unique(df)
[1] 1 2 3
```
The difference is that SystemDS' unique() will support the same for not
only vectors, but also matrices.
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