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10 commits

Author SHA1 Message Date
HyukjinKwon 7c05f61514 [SPARK-28130][PYTHON] Print pretty messages for skipped tests when xmlrunner is available in PySpark
## What changes were proposed in this pull request?

Currently, pretty skipped message added by f7435bec6a mechanism seems not working when xmlrunner is installed apparently.

This PR fixes two things:

1. When `xmlrunner` is installed, seems `xmlrunner` does not respect `vervosity` level in unittests (default is level 1).

    So the output looks as below

    ```
    Running tests...
     ----------------------------------------------------------------------
    SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS
    ----------------------------------------------------------------------
    ```

    So it is not caught by our message detection mechanism.

2. If we manually set the `vervocity` level to `xmlrunner`, it prints messages as below:

    ```
    test_mixed_udf (pyspark.sql.tests.test_pandas_udf_scalar.ScalarPandasUDFTests) ... SKIP (0.000s)
    test_mixed_udf_and_sql (pyspark.sql.tests.test_pandas_udf_scalar.ScalarPandasUDFTests) ... SKIP (0.000s)
    ...
    ```

    This is different in our Jenkins machine:

    ```
    test_createDataFrame_column_name_encoding (pyspark.sql.tests.test_arrow.ArrowTests) ... skipped 'Pandas >= 0.23.2 must be installed; however, it was not found.'
    test_createDataFrame_does_not_modify_input (pyspark.sql.tests.test_arrow.ArrowTests) ... skipped 'Pandas >= 0.23.2 must be installed; however, it was not found.'
    ...
    ```

    Note that last `SKIP` is different. This PR fixes the regular expression to catch `SKIP` case as well.

## How was this patch tested?

Manually tested.

**Before:**

```
Starting test(python2.7): pyspark....
Finished test(python2.7): pyspark.... (0s)
...
Tests passed in 562 seconds

========================================================================
...
```

**After:**

```
Starting test(python2.7): pyspark....
Finished test(python2.7): pyspark.... (48s) ... 93 tests were skipped
...
Tests passed in 560 seconds

Skipped tests pyspark.... with python2.7:
      pyspark...(...) ... SKIP (0.000s)
...

========================================================================
...
```

Closes #24927 from HyukjinKwon/SPARK-28130.

Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2019-06-24 09:58:17 +09:00
Giovanni Lanzani 92530c7db1 [SPARK-9792] Make DenseMatrix equality semantical
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>
2019-04-01 09:30:33 -07:00
Maxim Gekk 027ed2d11b [SPARK-23643][CORE][SQL][ML] Shrinking the buffer in hashSeed up to size of the seed parameter
## What changes were proposed in this pull request?

The hashSeed method allocates 64 bytes instead of 8. Other bytes are always zeros (thanks to default behavior of ByteBuffer). And they could be excluded from hash calculation because they don't differentiate inputs.

## How was this patch tested?

By running the existing tests - XORShiftRandomSuite

Closes #20793 from MaxGekk/hash-buff-size.

Lead-authored-by: Maxim Gekk <maxim.gekk@databricks.com>
Co-authored-by: Maxim Gekk <max.gekk@gmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
2019-03-23 11:26:09 -05:00
Huaxin Gao be5d95adc6 [SPARK-27007][PYTHON] add rawPrediction to OneVsRest in PySpark
## What changes were proposed in this pull request?

Add RawPrediction to OneVsRest in PySpark to make it consistent with scala implementation

## How was this patch tested?

Add doctest

Closes #23910 from huaxingao/spark-27007.

Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
2019-03-02 09:09:28 -06:00
Huaxin Gao 74e9e1c192 [SPARK-22798][PYTHON][ML] Add multiple column support to PySpark StringIndexer
## What changes were proposed in this pull request?

Add multiple column support to PySpark StringIndexer

## How was this patch tested?

Add doctest

Closes #23741 from huaxingao/spark-22798.

Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
2019-02-20 08:52:46 -06:00
Huaxin Gao 06792afd4c [SPARK-16838][PYTHON] Add PMML export for ML KMeans in PySpark
## What changes were proposed in this pull request?

Add PMML export support for ML KMeans to PySpark.

## How was this patch tested?

Add tests in ml.tests.PersistenceTest.

Closes #23592 from huaxingao/spark-16838.

Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
2019-01-22 09:34:59 -06:00
Jatin Puri d2e86cb3cd [SPARK-26616][MLLIB] Expose document frequency in IDFModel
## What changes were proposed in this pull request?

This change exposes the `df` (document frequency) as a public val along with the number of documents (`m`) as part of the IDF model.

* The document frequency is returned as an `Array[Long]`
* If the minimum  document frequency is set, this is considered in the df calculation. If the count is less than minDocFreq, the df is 0 for such terms
* numDocs is not very required. But it can be useful, if we plan to provide a provision in future for user to give their own idf function, instead of using a default (log((1+m)/(1+df))). In such cases, the user can provide a function taking input of `m` and `df` and returning the idf value
* Pyspark changes

## How was this patch tested?

The existing test case was edited to also check for the document frequency values.

I  am not very good with python or pyspark. I have committed and run tests based on my understanding. Kindly let me know if I have missed anything

Reviewer request: mengxr  zjffdu yinxusen

Closes #23549 from purijatin/master.

Authored-by: Jatin Puri <purijatin@gmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
2019-01-22 07:41:54 -06:00
Hyukjin Kwon 518a3d10c8 [SPARK-26033][SPARK-26034][PYTHON][FOLLOW-UP] Small cleanup and deduplication in ml/mllib tests
## What changes were proposed in this pull request?

This PR is a small follow up that puts some logic and functions into smaller scope and make it localized, and deduplicate.

## How was this patch tested?

Manually tested. Jenkins tests as well.

Closes #23200 from HyukjinKwon/followup-SPARK-26034-SPARK-26033.

Authored-by: Hyukjin Kwon <gurwls223@apache.org>
Signed-off-by: Bryan Cutler <cutlerb@gmail.com>
2018-12-03 14:03:10 -08:00
hyukjinkwon bbbdaa82a4 [SPARK-26105][PYTHON] Clean unittest2 imports up that were added for Python 2.6 before
## What changes were proposed in this pull request?

Currently, some of PySpark tests sill assume the tests could be ran in Python 2.6 by importing `unittest2`. For instance:

```python
if sys.version_info[:2] <= (2, 6):
    try:
        import unittest2 as unittest
    except ImportError:
        sys.stderr.write('Please install unittest2 to test with Python 2.6 or earlier')
        sys.exit(1)
else:
    import unittest
```

While I am here, I removed some of unused imports and reordered imports per PEP 8.

We officially dropped Python 2.6 support a while ago and started to discuss about Python 2 drop. It's better to remove them out.

## How was this patch tested?

Manually tests, and existing tests via Jenkins.

Closes #23077 from HyukjinKwon/SPARK-26105.

Lead-authored-by: hyukjinkwon <gurwls223@apache.org>
Co-authored-by: Bryan Cutler <cutlerb@gmail.com>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>
2018-11-19 09:22:32 +08:00
Bryan Cutler 034ae305c3 [SPARK-26033][PYTHON][TESTS] Break large ml/tests.py file into smaller files
## What changes were proposed in this pull request?

This PR breaks down the large ml/tests.py file that contains all Python ML unit tests into several smaller test files to be easier to read and maintain.

The tests are broken down as follows:
```
pyspark
├── __init__.py
...
├── ml
│   ├── __init__.py
...
│   ├── tests
│   │   ├── __init__.py
│   │   ├── test_algorithms.py
│   │   ├── test_base.py
│   │   ├── test_evaluation.py
│   │   ├── test_feature.py
│   │   ├── test_image.py
│   │   ├── test_linalg.py
│   │   ├── test_param.py
│   │   ├── test_persistence.py
│   │   ├── test_pipeline.py
│   │   ├── test_stat.py
│   │   ├── test_training_summary.py
│   │   ├── test_tuning.py
│   │   └── test_wrapper.py
...
├── testing
...
│   ├── mlutils.py
...
```

## How was this patch tested?

Ran tests manually by module to ensure test count was the same, and ran `python/run-tests --modules=pyspark-ml` to verify all passing with Python 2.7 and Python 3.6.

Closes #23063 from BryanCutler/python-test-breakup-ml-SPARK-26033.

Authored-by: Bryan Cutler <cutlerb@gmail.com>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>
2018-11-18 16:02:15 +08:00