| Commit message (Collapse) | Author | Age | Files | Lines |
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Only install signal in main thread, or it will fail to create context in not-main thread.
Author: Davies Liu <davies@databricks.com>
Closes #9574 from davies/python_signal.
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Python
cc jkbradley
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes #9534 from yu-iskw/SPARK-11566.
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like `df.agg(corr("col1", "col2")`
davies
Author: felixcheung <felixcheung_m@hotmail.com>
Closes #9536 from felixcheung/pyfunc.
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evaluate AggregateExpression1s
https://issues.apache.org/jira/browse/SPARK-9830
This PR contains the following main changes.
* Removing `AggregateExpression1`.
* Removing `Aggregate` operator, which is used to evaluate `AggregateExpression1`.
* Removing planner rule used to plan `Aggregate`.
* Linking `MultipleDistinctRewriter` to analyzer.
* Renaming `AggregateExpression2` to `AggregateExpression` and `AggregateFunction2` to `AggregateFunction`.
* Updating places where we create aggregate expression. The way to create aggregate expressions is `AggregateExpression(aggregateFunction, mode, isDistinct)`.
* Changing `val`s in `DeclarativeAggregate`s that touch children of this function to `lazy val`s (when we create aggregate expression in DataFrame API, children of an aggregate function can be unresolved).
Author: Yin Huai <yhuai@databricks.com>
Closes #9556 from yhuai/removeAgg1.
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in Python more specific
cc jkbradley
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes #9577 from yu-iskw/SPARK-11610.
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For now they are thin wrappers around the corresponding Hive UDAFs.
One limitation with these in Hive 0.13.0 is they only support aggregating primitive types.
I chose snake_case here instead of camelCase because it seems to be used in the majority of the multi-word fns.
Do we also want to add these to `functions.py`?
This approach was recommended here: https://github.com/apache/spark/pull/8592#issuecomment-154247089
marmbrus rxin
Author: Nick Buroojy <nick.buroojy@civitaslearning.com>
Closes #9526 from nburoojy/nick/udaf-alias.
(cherry picked from commit a6ee4f989d020420dd08b97abb24802200ff23b2)
Signed-off-by: Michael Armbrust <michael@databricks.com>
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pyspark.ml.classification
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes #8690 from yu-iskw/SPARK-10280.
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Could jkbradley and davies review it?
- Create a wrapper class: `LDAModelWrapper` for `LDAModel`. Because we can't deal with the return value of`describeTopics` in Scala from pyspark directly. `Array[(Array[Int], Array[Double])]` is too complicated to convert it.
- Add `loadLDAModel` in `PythonMLlibAPI`. Since `LDAModel` in Scala is an abstract class and we need to call `load` of `DistributedLDAModel`.
[[SPARK-8467] Add LDAModel.describeTopics() in Python - ASF JIRA](https://issues.apache.org/jira/browse/SPARK-8467)
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes #8643 from yu-iskw/SPARK-8467-2.
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#9527 missed updating the python tests.
Author: Michael Armbrust <michael@databricks.com>
Closes #9533 from marmbrus/hotfixTextValue.
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…ithinPartitions.
Author: Nong Li <nong@databricks.com>
Closes #9504 from nongli/spark-11410.
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https://issues.apache.org/jira/browse/SPARK-10116
This is really trivial, just happened to notice it -- if `XORShiftRandom.hashSeed` is really supposed to have random bits throughout (as the comment implies), it needs to do something for the conversion to `long`.
mengxr mkolod
Author: Imran Rashid <irashid@cloudera.com>
Closes #8314 from squito/SPARK-10116.
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normal equation solver
Follow up [SPARK-9836](https://issues.apache.org/jira/browse/SPARK-9836), we should also support summary statistics for ```intercept```.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #9485 from yanboliang/spark-11473.
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coefficients/intercept/scale
PySpark ```AFTSurvivalRegressionModel``` should expose coefficients/intercept/scale. mengxr vectorijk
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #9492 from yanboliang/spark-11527.
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return properly
This adds a failing test checking that `awaitTerminationOrTimeout` returns the expected value, and then fixes that failing test with the addition of a `return`.
tdas zsxwing
Author: Nick Evans <me@nicolasevans.org>
Closes #9336 from manygrams/fix_await_termination_or_timeout.
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Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes #9469 from yu-iskw/SPARK-10028.
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We added a bunch of higher order statistics such as skewness and kurtosis to GroupedData. I don't think they are common enough to justify being listed, since users can always use the normal statistics aggregate functions.
That is to say, after this change, we won't support
```scala
df.groupBy("key").kurtosis("colA", "colB")
```
However, we will still support
```scala
df.groupBy("key").agg(kurtosis(col("colA")), kurtosis(col("colB")))
```
Author: Reynold Xin <rxin@databricks.com>
Closes #9446 from rxin/SPARK-11489.
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Add Python API for stddev/stddev_pop/stddev_samp/variance/var_pop/var_samp/skewness/kurtosis
Author: Davies Liu <davies@databricks.com>
Closes #9424 from davies/py_var.
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in ML models
Deprecated in `LogisticRegression` and `LinearRegression`
Author: vectorijk <jiangkai@gmail.com>
Closes #9311 from vectorijk/spark-10592.
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and pyspark.ml.*
Author: lihao <lihaowhu@gmail.com>
Closes #9275 from lidinghao/SPARK-10286.
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This PR deprecates `runs` in k-means. `runs` introduces extra complexity and overhead in MLlib's k-means implementation. I haven't seen much usage with `runs` not equal to `1`. We don't have a unit test for it either. We can deprecate this method in 1.6, and void it in 1.7. It helps us simplify the implementation.
cc: srowen
Author: Xiangrui Meng <meng@databricks.com>
Closes #9322 from mengxr/SPARK-11358.
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provided schema
When creating a DataFrame from an RDD in PySpark, `createDataFrame` calls `.take(10)` to verify the first 10 rows of the RDD match the provided schema. Similar to https://issues.apache.org/jira/browse/SPARK-8070, but that issue affected cases where a schema was not provided.
Verifying the first 10 rows is of limited utility and causes the DAG to be executed non-lazily. If necessary, I believe this verification should be done lazily on all rows. However, since the caller is providing a schema to follow, I think it's acceptable to simply fail if the schema is incorrect.
marmbrus We chatted about this at SparkSummitEU. davies you made a similar change for the infer-schema path in https://github.com/apache/spark/pull/6606
Author: Jason White <jason.white@shopify.com>
Closes #9392 from JasonMWhite/createDataFrame_without_take.
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JIRA: https://issues.apache.org/jira/browse/SPARK-11322
As reported by JoshRosen in [databricks/spark-redshift/issues/89](https://github.com/databricks/spark-redshift/issues/89#issuecomment-149828308), the exception-masking behavior sometimes makes debugging harder. To deal with this issue, we should keep full stack trace in the captured exception.
Author: Liang-Chi Hsieh <viirya@appier.com>
Closes #9283 from viirya/py-exception-stacktrace.
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Adds DataFrameReader.text and DataFrameWriter.text.
Author: Reynold Xin <rxin@databricks.com>
Closes #9259 from rxin/SPARK-11292.
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[SPARK-10668](https://issues.apache.org/jira/browse/SPARK-10668) has provided ```WeightedLeastSquares``` solver("normal") in ```LinearRegression``` with L2 regularization in Scala and R, Python ML ```LinearRegression``` should also support setting solver("auto", "normal", "l-bfgs")
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #9328 from yanboliang/spark-11367.
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returns incorrect answer in some cases
Fix computation of root-sigma-inverse in multivariate Gaussian; add a test and fix related Python mixture model test.
Supersedes https://github.com/apache/spark/pull/9293
Author: Sean Owen <sowen@cloudera.com>
Closes #9309 from srowen/SPARK-11302.2.
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implement {RandomForest, GBT, TreeEnsemble, TreeClassifier, TreeRegressor}Params for Python API
in pyspark/ml/{classification, regression}.py
Author: vectorijk <jiangkai@gmail.com>
Closes #9233 from vectorijk/spark-10024.
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BlockMatrix
This PR adds addition and multiplication to PySpark's `BlockMatrix` class via `add` and `multiply` functions.
Author: Mike Dusenberry <mwdusenb@us.ibm.com>
Closes #9139 from dusenberrymw/SPARK-6488_Add_Addition_and_Multiplication_to_PySpark_BlockMatrix.
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from the Kafka Streaming API
jerryshao tdas
I know this is kind of minor, and I know you all are busy, but this brings this class in line with the `OffsetRange` class, and makes tests a little more concise.
Instead of doing something like:
```
assert topic_and_partition_instance._topic == "foo"
assert topic_and_partition_instance._partition == 0
```
You can do something like:
```
assert topic_and_partition_instance == TopicAndPartition("foo", 0)
```
Before:
```
>>> from pyspark.streaming.kafka import TopicAndPartition
>>> TopicAndPartition("foo", 0) == TopicAndPartition("foo", 0)
False
```
After:
```
>>> from pyspark.streaming.kafka import TopicAndPartition
>>> TopicAndPartition("foo", 0) == TopicAndPartition("foo", 0)
True
```
I couldn't find any tests - am I missing something?
Author: Nick Evans <me@nicolasevans.org>
Closes #9236 from manygrams/topic_and_partition_equality.
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Duplicated the since decorator from pyspark.sql into pyspark (also tweaked to handle functions without docstrings).
Added since to methods + "versionadded::" to classes (derived from the git file history in pyspark).
Author: noelsmith <mail@noelsmith.com>
Closes #8627 from noel-smith/SPARK-10271-since-mllib-clustering.
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Author: Jeff Zhang <zjffdu@apache.org>
Closes #9248 from zjffdu/SPARK-11279.
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pyspark.mllib.regression
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes #8684 from yu-iskw/SPARK-10277.
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WIP
Author: Gábor Lipták <gliptak@gmail.com>
Closes #8323 from gliptak/SPARK-7021.
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…rint in python
No test needed. Verify it manually in pyspark shell
Author: Jeff Zhang <zjffdu@apache.org>
Closes #9177 from zjffdu/SPARK-11205.
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Without an empty line, sphinx will treat doctest as docstring. holdenk
~~~
/Users/meng/src/spark/python/pyspark/ml/feature.py:docstring of pyspark.ml.feature.CountVectorizer:3: ERROR: Undefined substitution referenced: "label|raw |vectors | +-----+---------------+-------------------------+ |0 |[a, b, c] |(3,[0,1,2],[1.0,1.0,1.0])".
/Users/meng/src/spark/python/pyspark/ml/feature.py:docstring of pyspark.ml.feature.CountVectorizer:3: ERROR: Undefined substitution referenced: "1 |[a, b, b, c, a]|(3,[0,1,2],[2.0,2.0,1.0])".
~~~
Author: Xiangrui Meng <meng@databricks.com>
Closes #9188 from mengxr/py-count-vec-doc-fix.
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Namely "." shows up in some places in the template when using the param docstring and not in others
Author: Holden Karau <holden@pigscanfly.ca>
Closes #9017 from holdenk/SPARK-10767-Make-pyspark-shared-params-codegen-more-consistent.
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pyspark.mllib.classification
Duplicated the since decorator from pyspark.sql into pyspark (also tweaked to handle functions without docstrings).
Added since to methods + "versionadded::" to classes derived from the file history.
Note - some methods are inherited from the regression module (i.e. LinearModel.intercept) so these won't have version numbers in the API docs until that model is updated.
Author: noelsmith <mail@noelsmith.com>
Closes #8626 from noel-smith/SPARK-10269-since-mlib-classification.
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Duplicated the since decorator from pyspark.sql into pyspark (also tweaked to handle functions without docstrings).
Added since to public methods + "versionadded::" to classes (derived from the git file history in pyspark).
Note - I added also the tags to MultilabelMetrics even though it isn't declared as public in the __all__ statement... if that's incorrect - I'll remove.
Author: noelsmith <mail@noelsmith.com>
Closes #8628 from noel-smith/SPARK-10272-since-mllib-evalutation.
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Upgrade to Py4j0.9
Author: Holden Karau <holden@pigscanfly.ca>
Author: Holden Karau <holden@us.ibm.com>
Closes #8615 from holdenk/SPARK-10447-upgrade-pyspark-to-py4j0.9.
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Also added SQLContext.newSession()
Author: Davies Liu <davies@databricks.com>
Closes #9122 from davies/py_create.
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This commit refactors the `run-tests-jenkins` script into Python. This refactoring was done by brennonyork in #7401; this PR contains a few minor edits from joshrosen in order to bring it up to date with other recent changes.
From the original PR description (by brennonyork):
Currently a few things are left out that, could and I think should, be smaller JIRA's after this.
1. There are still a few areas where we use environment variables where we don't need to (like `CURRENT_BLOCK`). I might get around to fixing this one in lieu of everything else, but wanted to point that out.
2. The PR tests are still written in bash. I opted to not change those and just rewrite the runner into Python. This is a great follow-on JIRA IMO.
3. All of the linting scripts are still in bash as well and would likely do to just add those in as follow-on JIRA's as well.
Closes #7401.
Author: Brennon York <brennon.york@capitalone.com>
Closes #9161 from JoshRosen/run-tests-jenkins-refactoring.
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by presenting the Object
The _verify_type() function had Errors that were raised when there were Type conversion issues but left out the Object in question. The Object is now added in the Error to reduce the strain on the user to debug through to figure out the Object that failed the Type conversion.
The use case for me was a Pandas DataFrame that contained 'nan' as values for columns of Strings.
Author: Mahmoud Lababidi <mahmoud@thehumangeo.com>
Author: Mahmoud Lababidi <lababidi@gmail.com>
Closes #9149 from lababidi/master.
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Make sure comma-separated paths get processed correcly in ResolvedDataSource for a HadoopFsRelationProvider
Author: Koert Kuipers <koert@tresata.com>
Closes #8416 from koertkuipers/feat-sql-comma-separated-paths.
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binary search
At this moment `SparseVector.__getitem__` executes `np.searchsorted` first and checks if result is in an expected range after that. It is possible to check if index can contain non-zero value before executing `np.searchsorted`.
Author: zero323 <matthew.szymkiewicz@gmail.com>
Closes #9098 from zero323/sparse_vector_getitem_improved.
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…rror message
For negative indices in the SparseVector, we update the index value. If we have an incorrect index
at this point, the error message has the incorrect *updated* index instead of the original one. This
change contains the fix for the same.
Author: Bhargav Mangipudi <bhargav.mangipudi@gmail.com>
Closes #9069 from bhargav/spark-10759.
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Output list of supported modules for python tests in error message when given bad module name.
CC: davies
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #9088 from jkbradley/python-tests-modules.
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cancel all running jobs
This patch adds a signal handler to trap Ctrl-C and cancels running job.
Author: Ashwin Shankar <ashankar@netflix.com>
Closes #9033 from ashwinshankar77/master.
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PySpark
Support for recommendUsersForProducts and recommendProductsForUsers in matrix factorization model for PySpark
Author: Vladimir Vladimirov <vladimir.vladimirov@magnetic.com>
Closes #8700 from smartkiwi/SPARK-10535_.
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with given regParam and convergenceTol parameters
These params were being passed into the StreamingLogisticRegressionWithSGD constructor, but not transferred to the call for model training. Same with StreamingLinearRegressionWithSGD. I added the params as named arguments to the call and also fixed the intercept parameter, which was being passed as regularization value.
Author: Bryan Cutler <bjcutler@us.ibm.com>
Closes #9002 from BryanCutler/StreamingSGD-convergenceTol-bug-10959.
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when we…
__gettitem__ method throws IndexError exception when we try to access index after the last non-zero entry
from pyspark.mllib.linalg import Vectors
sv = Vectors.sparse(5, {1: 3})
sv[0]
## 0.0
sv[1]
## 3.0
sv[2]
## Traceback (most recent call last):
## File "<stdin>", line 1, in <module>
## File "/python/pyspark/mllib/linalg/__init__.py", line 734, in __getitem__
## row_ind = inds[insert_index]
## IndexError: index out of bounds
Author: zero323 <matthew.szymkiewicz@gmail.com>
Closes #9009 from zero323/sparse_vector_index_error.
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Add the Python API for isotonicregression.
Author: Holden Karau <holden@pigscanfly.ca>
Closes #8214 from holdenk/SPARK-9774-add-python-api-for-ml-regression-isotonicregression.
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