This is continuation of #7512 which added `--name` option to spark-shell. This PR adds the same option to pyspark.

Note that `--conf spark.app.name` in command-line has no effect in spark-shell and pyspark. Instead, `--name` must be used. This is in fact inconsistency with spark-sql which doesn't accept `--name` option while it accepts `--conf spark.app.name`. I am not fixing this inconsistency in this PR. IMO, one of `--name` and `--conf spark.app.name` is needed not both. But since I cannot decide which to choose, I am not making any change here.

Author: Cheolsoo Park <cheolsoop@netflix.com>

Closes #7610 from piaozhexiu/SPARK-9270 and squashes the following commits:

763e86d [Cheolsoo Park] Update windows script
400b7f9 [Cheolsoo Park] Allow --name option to pyspark

spark.mllib support batch predict for LinearRegressionModel, RidgeRegressionModel and LassoModel.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #7614 from yanboliang/spark-9122 and squashes the following commits:

4e610c0 [Yanbo Liang] spark.mllib regression support batch predict

Romove Decimal.Unlimited (change to support precision up to 38, to match with Hive and other databases).

In order to keep backward source compatibility, Decimal.Unlimited is still there, but change to Decimal(38, 18).

If no precision and scale is provide, it's Decimal(10, 0) as before.

Author: Davies Liu <davies@databricks.com>

Closes #7605 from davies/decimal_unlimited and squashes the following commits:

aa3f115 [Davies Liu] fix tests and style
fb0d20d [Davies Liu] address comments
bfaae35 [Davies Liu] fix style
df93657 [Davies Liu] address comments and clean up
06727fd [Davies Liu] Merge branch 'master' of github.com:apache/spark into decimal_unlimited
4c28969 [Davies Liu] fix tests
8d783cc [Davies Liu] fix tests
788631c [Davies Liu] fix double with decimal in Union/except
1779bde [Davies Liu] fix scala style
c9c7c78 [Davies Liu] remove Decimal.Unlimited

We forgot to update doc. brkyvz

Author: Xiangrui Meng <meng@databricks.com>

Closes #7608 from mengxr/SPARK-9243 and squashes the following commits:

0ea3236 [Xiangrui Meng] null -> zero in crosstab doc

Spark has an option called spark.localExecution.enabled; according to the docs:

> Enables Spark to run certain jobs, such as first() or take() on the driver, without sending tasks to the cluster. This can make certain jobs execute very quickly, but may require shipping a whole partition of data to the driver.

This feature ends up adding quite a bit of complexity to DAGScheduler, especially in the runLocallyWithinThread method, but as far as I know nobody uses this feature (I searched the mailing list and haven't seen any recent mentions of the configuration nor stacktraces including the runLocally method). As a step towards scheduler complexity reduction, I propose that we remove this feature and all code related to it for Spark 1.5.

This pull request simply brings #7484 up to date.

Author: Josh Rosen <joshrosen@databricks.com>
Author: Reynold Xin <rxin@databricks.com>

Closes #7585 from rxin/remove-local-exec and squashes the following commits:

84bd10e [Reynold Xin] Python fix.
1d9739a [Reynold Xin] Merge pull request #7484 from JoshRosen/remove-localexecution
eec39fa [Josh Rosen] Remove allowLocal(); deprecate user-facing uses of it.
b0835dc [Josh Rosen] Remove local execution code in DAGScheduler
8975d96 [Josh Rosen] Remove local execution tests.
ffa8c9b [Josh Rosen] Remove documentation for configuration

Since save / load has been merged in LDA, it takes no time to write the wrappers in Python as well.

Author: MechCoder <manojkumarsivaraj334@gmail.com>

Closes #7587 from MechCoder/python_lda_save_load and squashes the following commits:

c8e4ea7 [MechCoder] [SPARK-9223] [PySpark] Support model save/load in LDA

There are a few memory limits that people hit often and that we could
make higher, especially now that memory sizes have grown.

- spark.akka.frameSize: This defaults at 10 but is often hit for map
  output statuses in large shuffles. This memory is not fully allocated
  up-front, so we can just make this larger and still not affect jobs
  that never sent a status that large. We increase it to 128.

- spark.executor.memory: Defaults at 512m, which is really small. We
  increase it to 1g.

Author: Matei Zaharia <matei@databricks.com>

Closes #7586 from mateiz/configs and squashes the following commits:

ce0038a [Matei Zaharia] [SPARK-9244] Increase some memory defaults

Pull Request for: https://issues.apache.org/jira/browse/SPARK-8230

Primary issue resolved is to implement array/map size for Spark SQL. Code is ready for review by a committer. Chen Hao is on the JIRA ticket, but I don't know his username on github, rxin is also on JIRA ticket.

Things to review:
1. Where to put added functions namespace wise, they seem to be part of a few operations on collections which includes `sort_array` and `array_contains`. Hence the name given `collectionOperations.scala` and `_collection_functions` in python.
2. In Python code, should it be in a `1.5.0` function array or in a collections array?
3. Are there any missing methods on the `Size` case class? Looks like many of these functions have generated Java code, is that also needed in this case?
4. Something else?

Author: Pedro Rodriguez <ski.rodriguez@gmail.com>
Author: Pedro Rodriguez <prodriguez@trulia.com>

Closes #7462 from EntilZha/SPARK-8230 and squashes the following commits:

9a442ae [Pedro Rodriguez] fixed functions and sorted __all__
9aea3bb [Pedro Rodriguez] removed imports from python docs
15d4bf1 [Pedro Rodriguez] Added null test case and changed to nullSafeCodeGen
d88247c [Pedro Rodriguez] removed python code
bd5f0e4 [Pedro Rodriguez] removed duplicate function from rebase/merge
59931b4 [Pedro Rodriguez] fixed compile bug instroduced when merging
c187175 [Pedro Rodriguez] updated code to add size to __all__ directly and removed redundent pretty print
130839f [Pedro Rodriguez] fixed failing test
aa9bade [Pedro Rodriguez] fix style
e093473 [Pedro Rodriguez] updated python code with docs, switched classes/traits implemented, added (failing) expression tests
0449377 [Pedro Rodriguez] refactored code to use better abstract classes/traits and implementations
9a1a2ff [Pedro Rodriguez] added unit tests for map size
2bfbcb6 [Pedro Rodriguez] added unit test for size
20df2b4 [Pedro Rodriguez] Finished working version of size function and added it to python
b503e75 [Pedro Rodriguez] First attempt at implementing size for maps and arrays
99a6a5c [Pedro Rodriguez] fixed failing test
cac75ac [Pedro Rodriguez] fix style
933d843 [Pedro Rodriguez] updated python code with docs, switched classes/traits implemented, added (failing) expression tests
42bb7d4 [Pedro Rodriguez] refactored code to use better abstract classes/traits and implementations
f9c3b8a [Pedro Rodriguez] added unit tests for map size
2515d9f [Pedro Rodriguez] added documentation
0e60541 [Pedro Rodriguez] added unit test for size
acf9853 [Pedro Rodriguez] Finished working version of size function and added it to python
84a5d38 [Pedro Rodriguez] First attempt at implementing size for maps and arrays

Add expressions `regex_extract` & `regex_replace`

Author: Cheng Hao <hao.cheng@intel.com>

Closes #7468 from chenghao-intel/regexp and squashes the following commits:

e5ea476 [Cheng Hao] minor update for documentation
ef96fd6 [Cheng Hao] update the code gen
72cf28f [Cheng Hao] Add more log for compilation error
4e11381 [Cheng Hao] Add regexp_replace / regexp_extract support

This PR adds DataFrame reader/writer shortcut methods for ORC in both Scala and Python.

Author: Cheng Lian <lian@databricks.com>

Closes #7444 from liancheng/spark-9100 and squashes the following commits:

284d043 [Cheng Lian] Fixes PySpark test cases and addresses PR comments
e0b09fb [Cheng Lian] Adds DataFrame reader/writer shortcut methods for ORC

Several places in the PySpark SparseVector docs have one defined as:
```
SparseVector(4, [2, 4], [1.0, 2.0])
```
The index 4 goes out of bounds (but this is not checked).

CC: mengxr

Author: Joseph K. Bradley <joseph@databricks.com>

Closes #7541 from jkbradley/sparsevec-doc-typo-fix and squashes the following commits:

c806a65 [Joseph K. Bradley] fixed doc test
e2dcb23 [Joseph K. Bradley] Fixed typo in pyspark sparsevector doc tests

This PR also remove the duplicated code between registerFunction and UserDefinedFunction.

cc JoshRosen

Author: Davies Liu <davies@databricks.com>

Closes #7450 from davies/fix_return_type and squashes the following commits:

e80bf9f [Davies Liu] remove debugging code
f94b1f6 [Davies Liu] fix mima
8f9c58b [Davies Liu] convert returned object from UDF into internal type

JIRA: https://issues.apache.org/jira/browse/SPARK-9101

Author: Mateusz Buśkiewicz <mateusz.buskiewicz@getbase.com>

Closes #7499 from sixers/spark-9101 and squashes the following commits:

dd75aa6 [Mateusz Buśkiewicz] [SPARK-9101] [PySpark] Test for selecting null literal
97e3f2f [Mateusz Buśkiewicz] [SPARK-9101] [PySpark] Add missing NullType to _atomic_types in pyspark.sql.types

Python API for the KS-test

Statistics.kolmogorovSmirnovTest(data, distName, *params)
I'm not quite sure how to support the callable function since it is not serializable.

Author: MechCoder <manojkumarsivaraj334@gmail.com>

Closes #7430 from MechCoder/spark-8996 and squashes the following commits:

2dd009d [MechCoder] minor
021d233 [MechCoder] Remove one wrapper and other minor stuff
49d07ab [MechCoder] [SPARK-8996] [MLlib] Python API for Kolmogorov-Smirnov Test

[SPARK-9021] [PYSPARK] Change RDD.aggregate() to do reduce(mapPartitions()) instead of mapPartitions.fold()

I'm relatively new to Spark and functional programming, so forgive me if this pull request is just a result of my misunderstanding of how Spark should be used.

Currently, if one happens to use a mutable object as `zeroValue` for `RDD.aggregate()`, possibly unexpected behavior can occur.

This is because pyspark's current implementation of `RDD.aggregate()` does not serialize or make a copy of `zeroValue` before handing it off to `RDD.mapPartitions(...).fold(...)`. This results in a single reference to `zeroValue` being used for both `RDD.mapPartitions()` and `RDD.fold()` on each partition. This can result in strange accumulator values being fed into each partition's call to `RDD.fold()`, as the `zeroValue` may have been changed in-place during the `RDD.mapPartitions()` call.

As an illustrative example, submit the following to `spark-submit`:
```
from pyspark import SparkConf, SparkContext
import collections

def updateCounter(acc, val):
    print 'update acc:', acc
    print 'update val:', val
    acc[val] += 1
    return acc

def comboCounter(acc1, acc2):
    print 'combo acc1:', acc1
    print 'combo acc2:', acc2
    acc1.update(acc2)
    return acc1

def main():
    conf = SparkConf().setMaster("local").setAppName("Aggregate with Counter")
    sc = SparkContext(conf = conf)

    print '======= AGGREGATING with ONE PARTITION ======='
    print sc.parallelize(range(1,10), 1).aggregate(collections.Counter(), updateCounter, comboCounter)

    print '======= AGGREGATING with TWO PARTITIONS ======='
    print sc.parallelize(range(1,10), 2).aggregate(collections.Counter(), updateCounter, comboCounter)

if __name__ == "__main__":
    main()
```

One probably expects this to output the following:
```
Counter({1: 1, 2: 1, 3: 1, 4: 1, 5: 1, 6: 1, 7: 1, 8: 1, 9: 1})
```

But it instead outputs this (regardless of the number of partitions):
```
Counter({1: 2, 2: 2, 3: 2, 4: 2, 5: 2, 6: 2, 7: 2, 8: 2, 9: 2})
```

This is because (I believe) `zeroValue` gets passed correctly to each partition, but after `RDD.mapPartitions()` completes, the `zeroValue` object has been updated and is then passed to `RDD.fold()`, which results in all items being double-counted within each partition before being finally reduced at the calling node.

I realize that this type of calculation is typically done by `RDD.mapPartitions(...).reduceByKey(...)`, but hopefully this illustrates some potentially confusing behavior. I also noticed that other `RDD` methods use this `deepcopy` approach to creating unique copies of `zeroValue` (i.e., `RDD.aggregateByKey()` and `RDD.foldByKey()`), and that the Scala implementations do seem to serialize the `zeroValue` object appropriately to prevent this type of behavior.

Author: Nicholas Hwang <moogling@gmail.com>

Closes #7378 from njhwang/master and squashes the following commits:

659bb27 [Nicholas Hwang] Fixed RDD.aggregate() to perform a reduce operation on collected mapPartitions results, similar to how fold currently is implemented. This prevents an initial combOp being performed on each partition with zeroValue (which leads to unexpected behavior if zeroValue is a mutable object) before being combOp'ed with other partition results.
8d8d694 [Nicholas Hwang] Changed dict construction to be compatible with Python 2.6 (cannot use list comprehensions to make dicts)
56eb2ab [Nicholas Hwang] Fixed whitespace after colon to conform with PEP8
391de4a [Nicholas Hwang] Removed used of collections.Counter from RDD tests for Python 2.6 compatibility; used defaultdict(int) instead. Merged treeAggregate test with mutable zero value into aggregate test to reduce code duplication.
2fa4e4b [Nicholas Hwang] Merge branch 'master' of https://github.com/njhwang/spark
ba528bd [Nicholas Hwang] Updated comments regarding protection of zeroValue from mutation in RDD.aggregate(). Added regression tests for aggregate(), fold(), aggregateByKey(), foldByKey(), and treeAggregate(), all with both 1 and 2 partition RDDs. Confirmed that aggregate() is the only problematic implementation as of commit 257236c3. Also replaced some parallelizations of ranges with xranges, per the documentation's recommendations of preferring xrange over range.
7820391 [Nicholas Hwang] Updated comments regarding protection of zeroValue from mutation in RDD.aggregate(). Added regression tests for aggregate(), fold(), aggregateByKey(), foldByKey(), and treeAggregate(), all with both 1 and 2 partition RDDs. Confirmed that aggregate() is the only problematic implementation as of commit 257236c3.
90d1544 [Nicholas Hwang] Made sure RDD.aggregate() makes a deepcopy of zeroValue for all partitions; this ensures that the mapPartitions call works with unique copies of zeroValue in each partition, and prevents a single reference to zeroValue being used for both map and fold calls on each partition (resulting in possibly unexpected behavior).

This pull request fixes some of the problems in #6981.

- Added date functions to `__all__` so they get exposed
- Rename day_of_month -> dayofmonth
- Rename day_in_year -> dayofyear
- Rename week_of_year -> weekofyear
- Removed "day" from Scala/Python API since it is ambiguous. Only leaving the alias in SQL.

Author: Reynold Xin <rxin@databricks.com>

This patch had conflicts when merged, resolved by
Committer: Reynold Xin <rxin@databricks.com>

Closes #7506 from rxin/datetime and squashes the following commits:

0cb24d9 [Reynold Xin] Export all functions in Python.
e44a4a0 [Reynold Xin] Removed day function from Scala and Python.
9c08fdc [Reynold Xin] [SQL] Make date/time functions more consistent with other database systems.

JIRA: https://issues.apache.org/jira/browse/SPARK-9166

Simply capture and hide `IllegalArgumentException` in Python API.

Author: Liang-Chi Hsieh <viirya@appier.com>

Closes #7497 from viirya/hide_illegalargument and squashes the following commits:

8324dce [Liang-Chi Hsieh] Fix python style.
9ace67d [Liang-Chi Hsieh] Also check exception message.
8b2ce5c [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into hide_illegalargument
7be016a [Liang-Chi Hsieh] Capture and hide IllegalArgumentException in Python.

[SPARK-8199][SPARK-8184][SPARK-8183][SPARK-8182][SPARK-8181][SPARK-8180][SPARK-8179][SPARK-8177][SPARK-8178][SPARK-9115][SQL] date functions

Jira:
https://issues.apache.org/jira/browse/SPARK-8199
https://issues.apache.org/jira/browse/SPARK-8184
https://issues.apache.org/jira/browse/SPARK-8183
https://issues.apache.org/jira/browse/SPARK-8182
https://issues.apache.org/jira/browse/SPARK-8181
https://issues.apache.org/jira/browse/SPARK-8180
https://issues.apache.org/jira/browse/SPARK-8179
https://issues.apache.org/jira/browse/SPARK-8177
https://issues.apache.org/jira/browse/SPARK-8179
https://issues.apache.org/jira/browse/SPARK-9115

Regarding `day`and `dayofmonth` are both necessary?

~~I am going to add `Quarter` to this PR as well.~~ Done.

~~As soon as the Scala coding is reviewed and discussed, I'll add the python api.~~ Done

Author: Tarek Auel <tarek.auel@googlemail.com>
Author: Tarek Auel <tarek.auel@gmail.com>

Closes #6981 from tarekauel/SPARK-8199 and squashes the following commits:

f7b4c8c [Tarek Auel] [SPARK-8199] fixed bug in tests
bb567b6 [Tarek Auel] [SPARK-8199] fixed test
3e095ba [Tarek Auel] [SPARK-8199] style and timezone fix
256c357 [Tarek Auel] [SPARK-8199] code cleanup
5983dcc [Tarek Auel] [SPARK-8199] whitespace fix
6e0c78f [Tarek Auel] [SPARK-8199] removed setTimeZone in tests, according to cloud-fans comment in #7488
4afc09c [Tarek Auel] [SPARK-8199] concise leap year handling
ea6c110 [Tarek Auel] [SPARK-8199] fix after merging master
70238e0 [Tarek Auel] Merge branch 'master' into SPARK-8199
3c6ae2e [Tarek Auel] [SPARK-8199] removed binary search
fb98ba0 [Tarek Auel] [SPARK-8199] python docstring fix
cdfae27 [Tarek Auel] [SPARK-8199] cleanup & python docstring fix
746b80a [Tarek Auel] [SPARK-8199] build fix
0ad6db8 [Tarek Auel] [SPARK-8199] minor fix
523542d [Tarek Auel] [SPARK-8199] address comments
2259299 [Tarek Auel] [SPARK-8199] day_of_month alias
d01b977 [Tarek Auel] [SPARK-8199] python underscore
56c4a92 [Tarek Auel] [SPARK-8199] update python docu
e223bc0 [Tarek Auel] [SPARK-8199] refactoring
d6aa14e [Tarek Auel] [SPARK-8199] fixed Hive compatibility
b382267 [Tarek Auel] [SPARK-8199] fixed bug in day calculation; removed set TimeZone in HiveCompatibilitySuite for test purposes; removed Hive tests for second and minute, because we can cast '2015-03-18' to a timestamp and extract a minute/second from it
1b2e540 [Tarek Auel] [SPARK-8119] style fix
0852655 [Tarek Auel] [SPARK-8119] changed from ExpectsInputTypes to implicit casts
ec87c69 [Tarek Auel] [SPARK-8119] bug fixing and refactoring
1358cdc [Tarek Auel] Merge remote-tracking branch 'origin/master' into SPARK-8199
740af0e [Tarek Auel] implement date function using a calculation based on days
4fb66da [Tarek Auel] WIP: date functions on calculation only
1a436c9 [Tarek Auel] wip
f775f39 [Tarek Auel] fixed return type
ad17e96 [Tarek Auel] improved implementation
c42b444 [Tarek Auel] Removed merge conflict file
ccb723c [Tarek Auel] [SPARK-8199] style and fixed merge issues
10e4ad1 [Tarek Auel] Merge branch 'master' into date-functions-fast
7d9f0eb [Tarek Auel] [SPARK-8199] git renaming issue
f3e7a9f [Tarek Auel] [SPARK-8199] revert change in DataFrameFunctionsSuite
6f5d95c [Tarek Auel] [SPARK-8199] fixed year interval
d9f8ac3 [Tarek Auel] [SPARK-8199] implement fast track
7bc9d93 [Tarek Auel] Merge branch 'master' into SPARK-8199
5a105d9 [Tarek Auel] [SPARK-8199] rebase after #6985 got merged
eb6760d [Tarek Auel] Merge branch 'master' into SPARK-8199
f120415 [Tarek Auel] improved runtime
a8edebd [Tarek Auel] use Calendar instead of SimpleDateFormat
5fe74e1 [Tarek Auel] fixed python style
3bfac90 [Tarek Auel] fixed style
356df78 [Tarek Auel] rely on cast mechanism of Spark. Simplified implementation
02efc5d [Tarek Auel] removed doubled code
a5ea120 [Tarek Auel] added python api; changed test to be more meaningful
b680db6 [Tarek Auel] added codegeneration to all functions
c739788 [Tarek Auel] added support for quarter SPARK-8178
849fb41 [Tarek Auel] fixed stupid test
638596f [Tarek Auel] improved codegen
4d8049b [Tarek Auel] fixed tests and added type check
5ebb235 [Tarek Auel] resolved naming conflict
d0e2f99 [Tarek Auel] date functions

I Implemented the KMeans API for spark.ml Pipelines. But it doesn't include clustering abstractions for spark.ml (SPARK-7610). It would fit for another issues. And I'll try it later, since we are trying to add the hierarchical clustering algorithms in another issue. Thanks.

[SPARK-7879] KMeans API for spark.ml Pipelines - ASF JIRA https://issues.apache.org/jira/browse/SPARK-7879

Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>

Closes #6756 from yu-iskw/SPARK-7879 and squashes the following commits:

be752de [Yu ISHIKAWA] Add assertions
a14939b [Yu ISHIKAWA] Fix the dashed line's length in pyspark.ml.rst
4c61693 [Yu ISHIKAWA] Remove the test about whether "features" and "prediction" columns exist or not in Python
fb2417c [Yu ISHIKAWA] Use getInt, instead of get
f397be4 [Yu ISHIKAWA] Switch the comparisons.
ca78b7d [Yu ISHIKAWA] Add the Scala docs about the constraints of each parameter.
effc650 [Yu ISHIKAWA] Using expertSetParam and expertGetParam
c8dc6e6 [Yu ISHIKAWA] Remove an unnecessary test
19a9d63 [Yu ISHIKAWA] Include spark.ml.clustering to python tests
1abb19c [Yu ISHIKAWA] Add the statements about spark.ml.clustering into pyspark.ml.rst
f8338bc [Yu ISHIKAWA] Add the placeholders in Python
4a03003 [Yu ISHIKAWA] Test for contains in Python
6566c8b [Yu ISHIKAWA] Use `get`, instead of `apply`
288e8d5 [Yu ISHIKAWA] Using `contains` to check the column names
5a7d574 [Yu ISHIKAWA] Renamce `validateInitializationMode` to `validateInitMode` and remove throwing exception
97cfae3 [Yu ISHIKAWA] Fix the type of return value of `KMeans.copy`
e933723 [Yu ISHIKAWA] Remove the default value of seed from the Model class
978ee2c [Yu ISHIKAWA] Modify the docs of KMeans, according to mllib's KMeans
2ec80bc [Yu ISHIKAWA] Fit on 1 line
e186be1 [Yu ISHIKAWA] Make a few variables, setters and getters be expert ones
b2c205c [Yu ISHIKAWA] Rename the method `getInitializationSteps` to `getInitSteps` and `setInitializationSteps` to `setInitSteps` in Scala and Python
f43f5b4 [Yu ISHIKAWA] Rename the method `getInitializationMode` to `getInitMode` and `setInitializationMode` to `setInitMode` in Scala and Python
3cb5ba4 [Yu ISHIKAWA] Modify the description about epsilon and the validation
4fa409b [Yu ISHIKAWA] Add a comment about the default value of epsilon
2f392e1 [Yu ISHIKAWA] Make some variables `final` and Use `IntParam` and `DoubleParam`
19326f8 [Yu ISHIKAWA] Use `udf`, instead of callUDF
4d2ad1e [Yu ISHIKAWA] Modify the indentations
0ae422f [Yu ISHIKAWA] Add a test for `setParams`
4ff7913 [Yu ISHIKAWA] Add "ml.clustering" to `javacOptions` in SparkBuild.scala
11ffdf1 [Yu ISHIKAWA] Use `===` and the variable
220a176 [Yu ISHIKAWA] Set a random seed in the unit testing
92c3efc [Yu ISHIKAWA] Make the points for a test be fewer
c758692 [Yu ISHIKAWA] Modify the parameters of KMeans in Python
6aca147 [Yu ISHIKAWA] Add some unit testings to validate the setter methods
687cacc [Yu ISHIKAWA] Alias mllib.KMeans as MLlibKMeans in KMeansSuite.scala
a4dfbef [Yu ISHIKAWA] Modify the last brace and indentations
5bedc51 [Yu ISHIKAWA] Remve an extra new line
444c289 [Yu ISHIKAWA] Add the validation for `runs`
e41989c [Yu ISHIKAWA] Modify how to validate `initStep`
7ea133a [Yu ISHIKAWA] Change how to validate `initMode`
7991e15 [Yu ISHIKAWA] Add a validation for `k`
c2df35d [Yu ISHIKAWA] Make `predict` private
93aa2ff [Yu ISHIKAWA] Use `withColumn` in `transform`
d3a79f7 [Yu ISHIKAWA] Remove the inhefited docs
e9532e1 [Yu ISHIKAWA] make `parentModel` of KMeansModel private
8559772 [Yu ISHIKAWA] Remove the `paramMap` parameter of KMeans
6684850 [Yu ISHIKAWA] Rename `initializationSteps` to `initSteps`
99b1b96 [Yu ISHIKAWA] Rename `initializationMode` to `initMode`
79ea82b [Yu ISHIKAWA] Modify the parameters of KMeans docs
6569bcd [Yu ISHIKAWA] Change how to set the default values with `setDefault`
20a795a [Yu ISHIKAWA] Change how to set the default values with `setDefault`
11c2a12 [Yu ISHIKAWA] Limit the imports
badb481 [Yu ISHIKAWA] Alias spark.mllib.{KMeans, KMeansModel}
f80319a [Yu ISHIKAWA] Rebase mater branch and add copy methods
85d92b1 [Yu ISHIKAWA] Add `KMeans.setPredictionCol`
aa9469d [Yu ISHIKAWA] Fix a python test suite error caused by python 3.x
c2d6bcb [Yu ISHIKAWA] ADD Java test suites of the KMeans API for spark.ml Pipeline
598ed2e [Yu ISHIKAWA] Implement the KMeans API for spark.ml Pipelines in Python
63ad785 [Yu ISHIKAWA] Implement the KMeans API for spark.ml Pipelines in Scala

Add Python API for PCA transformer

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #7190 from yanboliang/spark-8792 and squashes the following commits:

8f4ac31 [Yanbo Liang] address comments
8a79cc0 [Yanbo Liang] Add Python API for PCA transformer

Vectors.dense() should accept numbers directly, like the one in Scala. We already use it in doctests, it worked by luck.

cc mengxr jkbradley

Author: Davies Liu <davies@databricks.com>

Closes #7476 from davies/fix_vectors_dense and squashes the following commits:

e0fd292 [Davies Liu] fix Vectors.dense

andrewor14 davies vanzin can you take a look at this? thanks

Author: Lianhui Wang <lianhuiwang09@gmail.com>

Closes #7438 from lianhuiwang/SPARK-8646 and squashes the following commits:

cb3f12d [Lianhui Wang] add whitespace
6d874a6 [Lianhui Wang] support pyspark for yarn-client

- `BinaryType` for `Length`
- `FormatNumber`

Author: Cheng Hao <hao.cheng@intel.com>

Closes #7034 from chenghao-intel/expression and squashes the following commits:

e534b87 [Cheng Hao] python api style issue
601bbf5 [Cheng Hao] add python API support
3ebe288 [Cheng Hao] update as feedback
52274f7 [Cheng Hao] add support for udf_format_number and length for binary

Fixes implementation of `explainedVariance` and `r2` to be consistent with their definitions as described in [SPARK-9005](https://issues.apache.org/jira/browse/SPARK-9005).

Author: Feynman Liang <fliang@databricks.com>

Closes #7361 from feynmanliang/SPARK-9005-RegressionMetrics-bugs and squashes the following commits:

f1112fc [Feynman Liang] Add explainedVariance formula
1a3d098 [Feynman Liang] SROwen code review comments
08a0e1b [Feynman Liang] Fix pyspark tests
db8605a [Feynman Liang] Style fix
bde9761 [Feynman Liang] Fix RegressionMetrics tests, relax assumption predictor is unbiased
c235de0 [Feynman Liang] Fix RegressionMetrics tests
4c4e56f [Feynman Liang] Fix RegressionMetrics computation of explainedVariance and r2

This adds Pylint checks to PySpark.

For now this lazy installs using easy_install to /dev/pylint (similar to the pep8 script).
We still need to figure out what rules to be allowed.

Author: MechCoder <manojkumarsivaraj334@gmail.com>

Closes #7241 from MechCoder/pylint and squashes the following commits:

2fc7291 [MechCoder] Remove pylint test fail
6d883a2 [MechCoder] Silence warnings and make pylint tests fail to check if it works in jenkins
f3a5e17 [MechCoder] undefined-variable
ca8b749 [MechCoder] Minor changes
71629f8 [MechCoder] remove trailing whitespace
8498ff9 [MechCoder] Remove blacklisted arguments and pointless statements check
1dbd094 [MechCoder] Disable all checks for now
8b8aa8a [MechCoder] Add pylint configuration file
7871bb1 [MechCoder] [SPARK-8706] [PySpark] [Project infra] Add pylint checks to PySpark

I implemented the Python API for LDA. But I didn't implemented a method for `LDAModel.describeTopics()`, beause it's a little hard to implement it now. And adding document about that and an example code would fit for another issue.

TODO: LDAModel.describeTopics() in Python must be also implemented. But it would be nice to fit for another issue. Implementing it is a little hard, since the return value of `describeTopics` in Scala consists of Tuple classes.

Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>

Closes #6791 from yu-iskw/SPARK-6259 and squashes the following commits:

6855f59 [Yu ISHIKAWA] LDA inherits object
28bd165 [Yu ISHIKAWA] Change the place of testing code
d7a332a [Yu ISHIKAWA] Remove the doc comment about the optimizer's default value
083e226 [Yu ISHIKAWA] Add the comment about the supported values and the default value of `optimizer`
9f8bed8 [Yu ISHIKAWA] Simplify casting
faa9764 [Yu ISHIKAWA] Add some comments for the LDA paramters
98f645a [Yu ISHIKAWA] Remove the interface for `describeTopics`. Because it is not implemented.
57ac03d [Yu ISHIKAWA] Remove the unnecessary import in Python unit testing
73412c3 [Yu ISHIKAWA] Fix the typo
2278829 [Yu ISHIKAWA] Fix the indentation
39514ec [Yu ISHIKAWA] Modify how to cast the input data
8117e18 [Yu ISHIKAWA] Fix the validation problems by `lint-scala`
77fd1b7 [Yu ISHIKAWA] Not use LabeledPoint
68f0653 [Yu ISHIKAWA] Support some parameters for `ALS.train()` in Python
25ef2ac [Yu ISHIKAWA] Resolve conflicts with rebasing

This reverts commit 9b62e937.

This adds Pylint checks to PySpark.

For now this lazy installs using easy_install to /dev/pylint (similar to the pep8 script).
We still need to figure out what rules to be allowed.

Author: MechCoder <manojkumarsivaraj334@gmail.com>

Closes #7241 from MechCoder/pylint and squashes the following commits:

8496834 [MechCoder] Silence warnings and make pylint tests fail to check if it works in jenkins
57393a3 [MechCoder] undefined-variable
a8e2547 [MechCoder] Minor changes
7753810 [MechCoder] remove trailing whitespace
75c5d2b [MechCoder] Remove blacklisted arguments and pointless statements check
6bde250 [MechCoder] Disable all checks for now
3464666 [MechCoder] Add pylint configuration file
d28109f [MechCoder] [SPARK-8706] [PySpark] [Project infra] Add pylint checks to PySpark

It may loss a microsecond if using timestamp as float, should be `int` instead.

Author: Davies Liu <davies@databricks.com>

Closes #7363 from davies/fix_microsecond and squashes the following commits:

36f6007 [Davies Liu] fix microsecond loss in Python 3

This will allow problems with piped commands to be detected.
This will also allow tasks to be retried where errors are rare (such as network problems in piped commands).

Author: Scott Taylor <github@megatron.me.uk>

Closes #6262 from megatron-me-uk/patch-2 and squashes the following commits:

04ae1d5 [Scott Taylor] Remove spurious empty line
98fa101 [Scott Taylor] fix blank line style error
574b564 [Scott Taylor] Merge pull request #2 from megatron-me-uk/patch-4
0c1e762 [Scott Taylor] Update rdd pipe method for checkCode
ab9a2e1 [Scott Taylor] Update rdd pipe tests for checkCode
eb4801c [Scott Taylor] fix fail_condition
b0ac3a4 [Scott Taylor] Merge pull request #1 from megatron-me-uk/megatron-me-uk-patch-1
a307d13 [Scott Taylor] update rdd tests to test pipe modes
34fcdc3 [Scott Taylor] add optional argument 'mode' for rdd.pipe
a0c0161 [Scott Taylor] fix generator issue
8a9ef9c [Scott Taylor] make check_return_code an iterator
0486ae3 [Scott Taylor] style fixes
8ed89a6 [Scott Taylor] Chain generators to prevent potential deadlock
4153b02 [Scott Taylor] fix list.sort returns None
491d3fc [Scott Taylor] Pass a function handle to assertRaises
3344a21 [Scott Taylor] wrap assertRaises with QuietTest
3ab8c7a [Scott Taylor] remove whitespace for style
cc1a73d [Scott Taylor] fix style issues in pipe test
8db4073 [Scott Taylor] Add a test for rdd pipe functions
1b3dc4e [Scott Taylor] fix missing space around operator style
0974f98 [Scott Taylor] add space between words in multiline string
45f4977 [Scott Taylor] fix line too long style error
5745d85 [Scott Taylor] Remove space to fix style
f552d49 [Scott Taylor] Catch non-zero exit from pipe commands

It may loss precision in microseconds when using float for it.

Author: Davies Liu <davies@databricks.com>

Closes #7344 from davies/fix_date_test and squashes the following commits:

249ec61 [Davies Liu] fix flaky test

[SPARK-7902] [SPARK-6289] [SPARK-8685] [SQL] [PYSPARK] Refactor of serialization for Python DataFrame

This PR fix the long standing issue of serialization between Python RDD and DataFrame, it change to using a customized Pickler for InternalRow to enable customized unpickling (type conversion, especially for UDT), now we can support UDT for UDF, cc mengxr .

There is no generated `Row` anymore.

Author: Davies Liu <davies@databricks.com>

Closes #7301 from davies/sql_ser and squashes the following commits:

81bef71 [Davies Liu] address comments
e9217bd [Davies Liu] add regression tests
db34167 [Davies Liu] Refactor of serialization for Python DataFrame

This PR propose a simple way to expose OffsetRange in Python code, also the usage of offsetRanges is similar to Scala/Java way, here in Python we could get OffsetRange like:

```
dstream.foreachRDD(lambda r: KafkaUtils.offsetRanges(r))
```

Reason I didn't follow the way what SPARK-8389 suggested is that: Python Kafka API has one more step to decode the message compared to Scala/Java, Which makes Python API return a transformed RDD/DStream, not directly wrapped so-called JavaKafkaRDD, so it is hard to backtrack to the original RDD to get the offsetRange.

Author: jerryshao <saisai.shao@intel.com>

Closes #7185 from jerryshao/SPARK-8389 and squashes the following commits:

4c6d320 [jerryshao] Another way to fix subclass deserialization issue
e6a8011 [jerryshao] Address the comments
fd13937 [jerryshao] Fix serialization bug
7debf1c [jerryshao] bug fix
cff3893 [jerryshao] refactor the code according to the comments
2aabf9e [jerryshao] Style fix
848c708 [jerryshao] Add HasOffsetRanges for Python

Write missing pydocs in `SparseVector` attributes.

Author: lewuathe <lewuathe@me.com>

Closes #7290 from Lewuathe/SPARK-6266 and squashes the following commits:

51d9895 [lewuathe] Update docs
0480d35 [lewuathe] Merge branch 'master' into SPARK-6266
ba42cf3 [lewuathe] [SPARK-6266] PySpark SparseVector missing doc for size, indices, values

JIRA: https://issues.apache.org/jira/browse/SPARK-8866

Author: Yijie Shen <henry.yijieshen@gmail.com>

Closes #7283 from yijieshen/micro_timestamp and squashes the following commits:

dc735df [Yijie Shen] update CastSuite to avoid round error
714eaea [Yijie Shen] add timestamp_udf into blacklist due to precision lose
c3ca2f4 [Yijie Shen] fix unhandled case in CurrentTimestamp
8d4aa6b [Yijie Shen] use 1us precision for timestamp type

This PR fixes the converter for Python DataFrame, especially for DecimalType

Closes #7106

Author: Davies Liu <davies@databricks.com>

Closes #7131 from davies/decimal_python and squashes the following commits:

4d3c234 [Davies Liu] Merge branch 'master' of github.com:apache/spark into decimal_python
20531d6 [Davies Liu] Merge branch 'master' of github.com:apache/spark into decimal_python
7d73168 [Davies Liu] fix conflit
6cdd86a [Davies Liu] Merge branch 'master' of github.com:apache/spark into decimal_python
7104e97 [Davies Liu] improve type infer
9cd5a21 [Davies Liu] run python tests with SPARK_PREPEND_CLASSES
829a05b [Davies Liu] fix UDT in python
c99e8c5 [Davies Liu] fix mima
c46814a [Davies Liu] convert decimal for Python DataFrames

Add confusionMatrix method at class MulticlassMetrics in pyspark/mllib

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #7286 from yanboliang/spark-8068 and squashes the following commits:

6109fe1 [Yanbo Liang] Add confusionMatrix method at class MulticlassMetrics in pyspark/mllib

Adding __str__ and  __repr__ to DenseMatrix and SparseMatrix

Author: MechCoder <manojkumarsivaraj334@gmail.com>

Closes #6342 from MechCoder/spark-7785 and squashes the following commits:

7b9a82c [MechCoder] Add tests for greater than 16 elements
b88e9dd [MechCoder] Increment limit to 16
1425a01 [MechCoder] Change tests
36bd166 [MechCoder] Change str and repr representation
97f0da9 [MechCoder] zip is same as izip in python3
94ca4b2 [MechCoder] Added doctests and iterate over values instead of colPtrs
b26fa89 [MechCoder] minor
394dde9 [MechCoder] [SPARK-7785] Add __str__ and __repr__ to Matrices

Add std, mean to StandardScalerModel
getVectors, findSynonyms to Word2Vec Model
setFeatures and getFeatures to hashingTF

Author: MechCoder <manojkumarsivaraj334@gmail.com>

Closes #7086 from MechCoder/missing_model_methods and squashes the following commits:

9fbae90 [MechCoder] Add type
6e3d6b2 [MechCoder] [SPARK-8704] Add missing methods in StandardScaler (ML and PySpark)