shahidki31 opened a new pull request #32734:
URL: https://github.com/apache/spark/pull/32734
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### What changes were proposed in this pull request?
If the dataset contains mix of sparse and dense vectors output of PCA seems
different. The issue here is we check only the first row's Vector type. If the
first row is dense and rest all the row's are sparse, we compute PCA based on
dense path. Similarly, if only first row in Sparse and rest all the rows are
dense, we compute based on Sparse computation path.
Following datasets will produce different results with PCA, even though the
data is same, except first row type is sparse.
```
val data1 = Array(
Vectors.sparse(5, Seq((1, 1.0), (3, 7.0))),
Vectors.dense(2.0, 0.0, 3.0, 4.0, 5.0),
Vectors.dense(4.0, 0.0, 0.0, 6.0, 7.0)
)
```
```
+-----------------------------------------------------------+
|pcaFeatures |
+-----------------------------------------------------------+
|[1.6485728230883807,-4.013282700516296,-5.524543751369388] |
|[-4.645104331781534,-1.1167972663619026,-5.524543751369387]|
|[-6.428880535676489,-5.337951427775355,-5.524543751369389] |
+-----------------------------------------------------------+
```
```
val data1 = Array(
Vectors.dense(0.0, 1.0, 0.0, 7.0, 0.0 ),
Vectors.dense(2.0, 0.0, 3.0, 4.0, 5.0),
Vectors.dense(4.0, 0.0, 0.0, 6.0, 7.0)
)
```
```
+------------------------------------------------------------+
|pcaFeatures |
+------------------------------------------------------------+
|[1.6485728230883814,-4.0132827005162985,-1.0091435193998504]|
|[-4.645104331781533,-1.1167972663619048,-1.0091435193998501]|
|[-6.428880535676488,-5.337951427775359,-1.009143519399851] |
+------------------------------------------------------------+
```
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### Why are the changes needed?
To fix inconsistent result if dataset contains both sparse and dense
vectors. We need to treat the entire metrics as Sparse if all the rows are
sparse. Otherwise we need to consider the matrix as dense.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Added UTs
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