Before, you could have this code
```
A = SparseMatrix(2, 2, [0, 2, 3], [0], [2])
B = DenseMatrix(2, 2, [2, 0, 0, 0])
B == A # False
A == B # True
```
The second would be `True` as `SparseMatrix` already checks for semantic
equality. This commit changes `DenseMatrix` so that equality is
semantical as well.
## What changes were proposed in this pull request?
Better semantic equality for DenseMatrix
## How was this patch tested?
Unit tests were added, plus manual testing. Note that the code falls back to the old behavior when `other` is not a SparseMatrix.
Closes#17968 from gglanzani/SPARK-9792.
Authored-by: Giovanni Lanzani <giovanni@lanzani.nl>
Signed-off-by: Holden Karau <holden@pigscanfly.ca>
## What changes were proposed in this pull request?
Fix implementation of unary negation (`__neg__`) in Pyspark DenseVectors
## How was this patch tested?
Existing tests, plus new doctest
Closes#23570 from srowen/SPARK-26638.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
The exit() builtin is only for interactive use. applications should use sys.exit().
## What changes were proposed in this pull request?
All usage of the builtin `exit()` function is replaced by `sys.exit()`.
## How was this patch tested?
I ran `python/run-tests`.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Benjamin Peterson <benjamin@python.org>
Closes#20682 from benjaminp/sys-exit.
## What changes were proposed in this pull request?
`_convert_to_vector` converts a scipy sparse matrix to csc matrix for initializing `SparseVector`. However, it doesn't guarantee the converted csc matrix has sorted indices and so a failure happens when you do something like that:
from scipy.sparse import lil_matrix
lil = lil_matrix((4, 1))
lil[1, 0] = 1
lil[3, 0] = 2
_convert_to_vector(lil.todok())
File "/home/jenkins/workspace/python/pyspark/mllib/linalg/__init__.py", line 78, in _convert_to_vector
return SparseVector(l.shape[0], csc.indices, csc.data)
File "/home/jenkins/workspace/python/pyspark/mllib/linalg/__init__.py", line 556, in __init__
% (self.indices[i], self.indices[i + 1]))
TypeError: Indices 3 and 1 are not strictly increasing
A simple test can confirm that `dok_matrix.tocsc()` won't guarantee sorted indices:
>>> from scipy.sparse import lil_matrix
>>> lil = lil_matrix((4, 1))
>>> lil[1, 0] = 1
>>> lil[3, 0] = 2
>>> dok = lil.todok()
>>> csc = dok.tocsc()
>>> csc.has_sorted_indices
0
>>> csc.indices
array([3, 1], dtype=int32)
I checked the source codes of scipy. The only way to guarantee it is `csc_matrix.tocsr()` and `csr_matrix.tocsc()`.
## How was this patch tested?
Existing tests.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#17532 from viirya/make-sure-sorted-indices.
## What changes were proposed in this pull request?
There are many locations in the Spark repo where the same word occurs consecutively. Sometimes they are appropriately placed, but many times they are not. This PR removes the inappropriately duplicated words.
## How was this patch tested?
N/A since only docs or comments were updated.
Author: Niranjan Padmanabhan <niranjan.padmanabhan@gmail.com>
Closes#16455 from neurons/np.structure_streaming_doc.
## What changes were proposed in this pull request?
Replaces` ValueError` with `IndexError` when index passed to `ml` / `mllib` `SparseVector.__getitem__` is out of range. This ensures correct iteration behavior.
Replaces `ValueError` with `IndexError` for `DenseMatrix` and `SparkMatrix` in `ml` / `mllib`.
## How was this patch tested?
PySpark `ml` / `mllib` unit tests. Additional unit tests to prove that the problem has been resolved.
Author: zero323 <zero323@users.noreply.github.com>
Closes#15144 from zero323/SPARK-17587.
## What changes were proposed in this pull request?
1. In scala, add negative low bound checking and put all the low/upper bound checking in one place
2. In python, add low/upper bound checking of indices.
## How was this patch tested?
unit test added
Author: Jeff Zhang <zjffdu@apache.org>
Closes#14555 from zjffdu/SPARK-16965.
## What changes were proposed in this pull request?
Copy the linalg (Vector/Matrix and VectorUDT/MatrixUDT) in PySpark to new ML package.
## How was this patch tested?
Existing tests.
Author: Xiangrui Meng <meng@databricks.com>
Author: Liang-Chi Hsieh <simonh@tw.ibm.com>
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#13099 from viirya/move-pyspark-vector-matrix-udt4.
