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| author | freeman <the.freeman.lab@gmail.com> | 2015-01-05 13:10:59 -0800 |
|---|---|---|
| committer | Xiangrui Meng <meng@databricks.com> | 2015-01-05 13:10:59 -0800 |
| commit | 6c6f32574023b8e43a24f2081ff17e6e446de2f3 (patch) | |
| tree | 01940cc05e61712eb4e3e383f6a4ae12c8209c28 /python/pyspark/mllib/linalg.py | |
| parent | 1c0e7ce056c79e1db96f85b8c56a479b8b043970 (diff) | |
| download | spark-6c6f32574023b8e43a24f2081ff17e6e446de2f3.tar.gz spark-6c6f32574023b8e43a24f2081ff17e6e446de2f3.tar.bz2 spark-6c6f32574023b8e43a24f2081ff17e6e446de2f3.zip | |
[SPARK-5089][PYSPARK][MLLIB] Fix vector convert
This is a small change addressing a potentially significant bug in how PySpark + MLlib handles non-float64 numpy arrays. The automatic conversion to `DenseVector` that occurs when passing RDDs to MLlib algorithms in PySpark should automatically upcast to float64s, but currently this wasn't actually happening. As a result, non-float64 would be silently parsed inappropriately during SerDe, yielding erroneous results when running, for example, KMeans.
The PR includes the fix, as well as a new test for the correct conversion behavior.
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Author: freeman <the.freeman.lab@gmail.com>
Closes #3902 from freeman-lab/fix-vector-convert and squashes the following commits:
764db47 [freeman] Add a test for proper conversion behavior
704f97e [freeman] Return array after changing type
Diffstat (limited to 'python/pyspark/mllib/linalg.py')
| -rw-r--r-- | python/pyspark/mllib/linalg.py | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/python/pyspark/mllib/linalg.py b/python/pyspark/mllib/linalg.py index f7aa2b0cb0..4f8491f43e 100644 --- a/python/pyspark/mllib/linalg.py +++ b/python/pyspark/mllib/linalg.py @@ -178,7 +178,7 @@ class DenseVector(Vector): elif not isinstance(ar, np.ndarray): ar = np.array(ar, dtype=np.float64) if ar.dtype != np.float64: - ar.astype(np.float64) + ar = ar.astype(np.float64) self.array = ar def __reduce__(self): |