There are some missing API docs in pyspark.mllib.linalg.Vector (including DenseVector and SparseVector). We should add them based on their Scala counterparts.
Author: vinodkc <vinod.kc.in@gmail.com>
Closes#8834 from vinodkc/fix_SPARK-10631.
It does not make much sense to set `spark.shuffle.spill` or `spark.sql.planner.externalSort` to false: I believe that these configurations were initially added as "escape hatches" to guard against bugs in the external operators, but these operators are now mature and well-tested. In addition, these configurations are not handled in a consistent way anymore: SQL's Tungsten codepath ignores these configurations and will continue to use spilling operators. Similarly, Spark Core's `tungsten-sort` shuffle manager does not respect `spark.shuffle.spill=false`.
This pull request removes these configurations, adds warnings at the appropriate places, and deletes a large amount of code which was only used in code paths that did not support spilling.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#8831 from JoshRosen/remove-ability-to-disable-spilling.
As ```assertEquals``` is deprecated, so we need to change ```assertEquals``` to ```assertEqual``` for existing python unit tests.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#8814 from yanboliang/spark-10615.
JIRA: https://issues.apache.org/jira/browse/SPARK-10642
When calling `rdd.lookup()` on a RDD with tuple keys, `portable_hash` will return a long. That causes `DAGScheduler.submitJob` to throw `java.lang.ClassCastException: java.lang.Long cannot be cast to java.lang.Integer`.
Author: Liang-Chi Hsieh <viirya@appier.com>
Closes#8796 from viirya/fix-pyrdd-lookup.
Missed this when reviewing `pyspark.mllib.random` for SPARK-10275.
Author: noelsmith <mail@noelsmith.com>
Closes#8773 from noel-smith/mllib-random-versionadded-fix.
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#8633 from noel-smith/SPARK-10273-since-mllib-feature.
PySpark DenseVector, SparseVector ```__eq__``` method should use semantics equality, and DenseVector can compared with SparseVector.
Implement PySpark DenseVector, SparseVector ```__hash__``` method based on the first 16 entries. That will make PySpark Vector objects can be used in collections.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#8166 from yanboliang/spark-9793.
[SPARK-3382](https://issues.apache.org/jira/browse/SPARK-3382) added a ```convergenceTol``` parameter for GradientDescent-based methods in Scala. We need that parameter in Python; otherwise, Python users will not be able to adjust that behavior (or even reproduce behavior from previous releases since the default changed).
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#8457 from yanboliang/spark-10194.
Adding STDDEV support for DataFrame using 1-pass online /parallel algorithm to compute variance. Please review the code change.
Author: JihongMa <linlin200605@gmail.com>
Author: Jihong MA <linlin200605@gmail.com>
Author: Jihong MA <jihongma@jihongs-mbp.usca.ibm.com>
Author: Jihong MA <jihongma@Jihongs-MacBook-Pro.local>
Closes#6297 from JihongMA/SPARK-SQL.
Just fixing a typo in exception message, raised when attempting to pickle SparkContext.
Author: Icaro Medeiros <icaro.medeiros@gmail.com>
Closes#8724 from icaromedeiros/master.
Changes:
* Make Scala doc for StringIndexerInverse clearer. Also remove Scala doc from transformSchema, so that the doc is inherited.
* MetadataUtils.scala: “ Helper utilities for tree-based algorithms” —> not just trees anymore
CC: holdenk mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#8679 from jkbradley/doc-fixes-1.5.
LinearRegression and LogisticRegression lack of some Params for Python, and some Params are not shared classes which lead we need to write them for each class. These kinds of Params are list here:
```scala
HasElasticNetParam
HasFitIntercept
HasStandardization
HasThresholds
```
Here we implement them in shared params at Python side and make LinearRegression/LogisticRegression parameters peer with Scala one.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#8508 from yanboliang/spark-10026.
Missing method of ml.feature are listed here:
```StringIndexer``` lacks of parameter ```handleInvalid```.
```StringIndexerModel``` lacks of method ```labels```.
```VectorIndexerModel``` lacks of methods ```numFeatures``` and ```categoryMaps```.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#8313 from yanboliang/spark-10027.
Modified class-level docstrings to mark all feature transformers in pyspark.ml as experimental.
Author: noelsmith <mail@noelsmith.com>
Closes#8623 from noel-smith/SPARK-10094-mark-pyspark-ml-trans-exp.
`pyspark.sql.column.Column` object has `__getitem__` method, which makes it iterable for Python. In fact it has `__getitem__` to address the case when the column might be a list or dict, for you to be able to access certain element of it in DF API. The ability to iterate over it is just a side effect that might cause confusion for the people getting familiar with Spark DF (as you might iterate this way on Pandas DF for instance)
Issue reproduction:
```
df = sqlContext.jsonRDD(sc.parallelize(['{"name": "El Magnifico"}']))
for i in df["name"]: print i
```
Author: 0x0FFF <programmerag@gmail.com>
Closes#8574 from 0x0FFF/SPARK-10417.
This PR addresses issue [SPARK-10392](https://issues.apache.org/jira/browse/SPARK-10392)
The problem is that for "start of epoch" date (01 Jan 1970) PySpark class DateType returns 0 instead of the `datetime.date` due to implementation of its return statement
Issue reproduction on master:
```
>>> from pyspark.sql.types import *
>>> a = DateType()
>>> a.fromInternal(0)
0
>>> a.fromInternal(1)
datetime.date(1970, 1, 2)
```
Author: 0x0FFF <programmerag@gmail.com>
Closes#8556 from 0x0FFF/SPARK-10392.
This PR addresses [SPARK-10162](https://issues.apache.org/jira/browse/SPARK-10162)
The issue is with DataFrame filter() function, if datetime.datetime is passed to it:
* Timezone information of this datetime is ignored
* This datetime is assumed to be in local timezone, which depends on the OS timezone setting
Fix includes both code change and regression test. Problem reproduction code on master:
```python
import pytz
from datetime import datetime
from pyspark.sql import *
from pyspark.sql.types import *
sqc = SQLContext(sc)
df = sqc.createDataFrame([], StructType([StructField("dt", TimestampType())]))
m1 = pytz.timezone('UTC')
m2 = pytz.timezone('Etc/GMT+3')
df.filter(df.dt > datetime(2000, 01, 01, tzinfo=m1)).explain()
df.filter(df.dt > datetime(2000, 01, 01, tzinfo=m2)).explain()
```
It gives the same timestamp ignoring time zone:
```
>>> df.filter(df.dt > datetime(2000, 01, 01, tzinfo=m1)).explain()
Filter (dt#0 > 946713600000000)
Scan PhysicalRDD[dt#0]
>>> df.filter(df.dt > datetime(2000, 01, 01, tzinfo=m2)).explain()
Filter (dt#0 > 946713600000000)
Scan PhysicalRDD[dt#0]
```
After the fix:
```
>>> df.filter(df.dt > datetime(2000, 01, 01, tzinfo=m1)).explain()
Filter (dt#0 > 946684800000000)
Scan PhysicalRDD[dt#0]
>>> df.filter(df.dt > datetime(2000, 01, 01, tzinfo=m2)).explain()
Filter (dt#0 > 946695600000000)
Scan PhysicalRDD[dt#0]
```
PR [8536](https://github.com/apache/spark/pull/8536) was occasionally closed by me dropping the repo
Author: 0x0FFF <programmerag@gmail.com>
Closes#8555 from 0x0FFF/SPARK-10162.
* Added isLargerBetter() method to Pyspark Evaluator to match the Scala version.
* JavaEvaluator delegates isLargerBetter() to underlying Scala object.
* Added check for isLargerBetter() in CrossValidator to determine whether to use argmin or argmax.
* Added test cases for where smaller is better (RMSE) and larger is better (R-Squared).
(This contribution is my original work and that I license the work to the project under Sparks' open source license)
Author: noelsmith <mail@noelsmith.com>
Closes#8399 from noel-smith/pyspark-rmse-xval-fix.
PySpark DataFrameReader should could accept an RDD of Strings (like the Scala version does) for JSON, rather than only taking a path.
If this PR is merged, it should be duplicated to cover the other input types (not just JSON).
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#8444 from yanboliang/spark-9964.
Replace `JavaConversions` implicits with `JavaConverters`
Most occurrences I've seen so far are necessary conversions; a few have been avoidable. None are in critical code as far as I see, yet.
Author: Sean Owen <sowen@cloudera.com>
Closes#8033 from srowen/SPARK-9613.
This PR removed the `outputFile` configuration from pom.xml and updated `tests.py` to search jars for both sbt build and maven build.
I ran ` mvn -Pkinesis-asl -DskipTests clean install` locally, and verified the jars in my local repository were correct. I also checked Python tests for maven build, and it passed all tests.
Author: zsxwing <zsxwing@gmail.com>
Closes#8373 from zsxwing/SPARK-10168 and squashes the following commits:
e0b5818 [zsxwing] Fix the sbt build
c697627 [zsxwing] Add the jar pathes to the exception message
be1d8a5 [zsxwing] Fix the issue that maven publishes wrong artifact jars
The current code only checks checkpoint files in local filesystem, and always tries to create a new Python SparkContext (even if one already exists). The solution is to do the following:
1. Use the same code path as Java to check whether a valid checkpoint exists
2. Create a new Python SparkContext only if there no active one.
There is not test for the path as its hard to test with distributed filesystem paths in a local unit test. I am going to test it with a distributed file system manually to verify that this patch works.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#8366 from tdas/SPARK-10142 and squashes the following commits:
3afa666 [Tathagata Das] Added tests
2dd4ae5 [Tathagata Das] Added the check to not create a context if one already exists
9bf151b [Tathagata Das] Made python checkpoint recovery use java to find the checkpoint files
Details of the bug and explanations can be seen in [SPARK-10122](https://issues.apache.org/jira/browse/SPARK-10122).
tdas , please help to review.
Author: jerryshao <sshao@hortonworks.com>
Closes#8347 from jerryshao/SPARK-10122 and squashes the following commits:
4039b16 [jerryshao] Fix getOffsetRanges in transform() bug
This PR includes the following fixes:
1. Use `range` instead of `xrange` in `queue_stream.py` to support Python 3.
2. Fix the issue that `utf8_decoder` will return `bytes` rather than `str` when receiving an empty `bytes` in Python 3.
3. Fix the commands in docs so that the user can copy them directly to the command line. The previous commands was broken in the middle of a path, so when copying to the command line, the path would be split to two parts by the extra spaces, which forces the user to fix it manually.
Author: zsxwing <zsxwing@gmail.com>
Closes#8315 from zsxwing/SPARK-9812.
DataFrame.withColumn in Python should be consistent with the Scala one (replacing the existing column that has the same name).
cc marmbrus
Author: Davies Liu <davies@databricks.com>
Closes#8300 from davies/with_column.
Previously, users of evaluator (`CrossValidator` and `TrainValidationSplit`) would only maximize the metric in evaluator, leading to a hacky solution which negated metrics to be minimized and caused erroneous negative values to be reported to the user.
This PR adds a `isLargerBetter` attribute to the `Evaluator` base class, instructing users of `Evaluator` on whether the chosen metric should be maximized or minimized.
CC jkbradley
Author: Feynman Liang <fliang@databricks.com>
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#8290 from feynmanliang/SPARK-10097.
Add Python API, user guide and example for ml.feature.ElementwiseProduct.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#8061 from yanboliang/SPARK-9768.
Recently, PySpark ML streaming tests have been flaky, most likely because of the batches not being processed in time. Proposal: Replace the use of _ssc_wait (which waits for a fixed amount of time) with a method which waits for a fixed amount of time but can terminate early based on a termination condition method. With this, we can extend the waiting period (to make tests less flaky) but also stop early when possible (making tests faster on average, which I verified locally).
CC: mengxr tdas freeman-lab
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#8087 from jkbradley/streaming-ml-tests.
This bug is caused by a wrong column-exist-check in `__getitem__` of pyspark dataframe. `DataFrame.apply` accepts not only top level column names, but also nested column name like `a.b`, so we should remove that check from `__getitem__`.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#8202 from cloud-fan/nested.
This bug only happen on Python 3 and Windows.
I tested this manually with python 3 and disable python daemon, no unit test yet.
Author: Davies Liu <davies@databricks.com>
Closes#8181 from davies/open_mode.
If pandas is broken (can't be imported, raise other exceptions other than ImportError), pyspark can't be imported, we should ignore all the exceptions.
Author: Davies Liu <davies@databricks.com>
Closes#8173 from davies/fix_pandas.
This requires some discussion. I'm not sure whether `runs` is a useful parameter. It certainly complicates the implementation. We might want to optimize the k-means implementation with block matrix operations. In this case, having `runs` may not be worth the trade-off. Also it increases the communication cost in a single job, which might cause other issues.
This PR also renames `epsilon` to `tol` to have consistent naming among algorithms. The Python constructor is updated to include all parameters.
jkbradley yu-iskw
Author: Xiangrui Meng <meng@databricks.com>
Closes#8148 from mengxr/SPARK-9918 and squashes the following commits:
149b9e5 [Xiangrui Meng] fix constructor in Python and rename epsilon to tol
3cc15b3 [Xiangrui Meng] fix test and change initStep to initSteps in python
a0a0274 [Xiangrui Meng] remove runs from k-means in the pipeline API
Reinstated LogisticRegression.threshold Param for binary compatibility. Param thresholds overrides threshold, if set.
CC: mengxr dbtsai feynmanliang
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#8079 from jkbradley/logreg-reinstate-threshold.
Check and add miss docs for PySpark ML (this issue only check miss docs for o.a.s.ml not o.a.s.mllib).
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#8059 from yanboliang/SPARK-9766.
rxin
First pull request for Spark so let me know if I am missing anything
The contribution is my original work and I license the work to the project under the project's open source license.
Author: Brennan Ashton <bashton@brennanashton.com>
Closes#8016 from btashton/patch-1.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#7961 from tdas/SPARK-9640 and squashes the following commits:
974ce19 [Tathagata Das] Undo changes related to SPARK-9727
004ae26 [Tathagata Das] style fixes
9bbb97d [Tathagata Das] Minor style fies
e6a677e [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into SPARK-9640
ca90719 [Tathagata Das] Removed extra line
ba9cfc7 [Tathagata Das] Improved kinesis test selection logic
88d59bd [Tathagata Das] updated test modules
871fcc8 [Tathagata Das] Fixed SparkBuild
94be631 [Tathagata Das] Fixed style
b858196 [Tathagata Das] Fixed conditions and few other things based on PR comments.
e292e64 [Tathagata Das] Added filters for Kinesis python tests
This PR is based on #4229, thanks prabeesh.
Closes#4229
Author: Prabeesh K <prabsmails@gmail.com>
Author: zsxwing <zsxwing@gmail.com>
Author: prabs <prabsmails@gmail.com>
Author: Prabeesh K <prabeesh.k@namshi.com>
Closes#7833 from zsxwing/pr4229 and squashes the following commits:
9570bec [zsxwing] Fix the variable name and check null in finally
4a9c79e [zsxwing] Fix pom.xml indentation
abf5f18 [zsxwing] Merge branch 'master' into pr4229
935615c [zsxwing] Fix the flaky MQTT tests
47278c5 [zsxwing] Include the project class files
478f844 [zsxwing] Add unpack
5f8a1d4 [zsxwing] Make the maven build generate the test jar for Python MQTT tests
734db99 [zsxwing] Merge branch 'master' into pr4229
126608a [Prabeesh K] address the comments
b90b709 [Prabeesh K] Merge pull request #1 from zsxwing/pr4229
d07f454 [zsxwing] Register StreamingListerner before starting StreamingContext; Revert unncessary changes; fix the python unit test
a6747cb [Prabeesh K] wait for starting the receiver before publishing data
87fc677 [Prabeesh K] address the comments:
97244ec [zsxwing] Make sbt build the assembly test jar for streaming mqtt
80474d1 [Prabeesh K] fix
1f0cfe9 [Prabeesh K] python style fix
e1ee016 [Prabeesh K] scala style fix
a5a8f9f [Prabeesh K] added Python test
9767d82 [Prabeesh K] implemented Python-friendly class
a11968b [Prabeesh K] fixed python style
795ec27 [Prabeesh K] address comments
ee387ae [Prabeesh K] Fix assembly jar location of mqtt-assembly
3f4df12 [Prabeesh K] updated version
b34c3c1 [prabs] adress comments
3aa7fff [prabs] Added Python streaming mqtt word count example
b7d42ff [prabs] Mqtt streaming support in Python
Raise an read-only exception when user try to mutable a Row.
Author: Davies Liu <davies@databricks.com>
Closes#8009 from davies/readonly_row and squashes the following commits:
8722f3f [Davies Liu] add tests
05a3d36 [Davies Liu] Row should be read-only
Add an option `recursive` to `Row.asDict()`, when True (default is False), it will convert the nested Row into dict.
Author: Davies Liu <davies@databricks.com>
Closes#8006 from davies/as_dict and squashes the following commits:
922cc5a [Davies Liu] turn Row into dict recursively
All data sources show up as "PhysicalRDD" in physical plan explain. It'd be better if we can show the name of the data source.
Without this patch:
```
== Physical Plan ==
NewAggregate with UnsafeHybridAggregationIterator ArrayBuffer(date#0, cat#1) ArrayBuffer((sum(CAST((CAST(count#2, IntegerType) + 1), LongType))2,mode=Final,isDistinct=false))
Exchange hashpartitioning(date#0,cat#1)
NewAggregate with UnsafeHybridAggregationIterator ArrayBuffer(date#0, cat#1) ArrayBuffer((sum(CAST((CAST(count#2, IntegerType) + 1), LongType))2,mode=Partial,isDistinct=false))
PhysicalRDD [date#0,cat#1,count#2], MapPartitionsRDD[3] at
```
With this patch:
```
== Physical Plan ==
TungstenAggregate(key=[date#0,cat#1], value=[(sum(CAST((CAST(count#2, IntegerType) + 1), LongType)),mode=Final,isDistinct=false)]
Exchange hashpartitioning(date#0,cat#1)
TungstenAggregate(key=[date#0,cat#1], value=[(sum(CAST((CAST(count#2, IntegerType) + 1), LongType)),mode=Partial,isDistinct=false)]
ConvertToUnsafe
Scan ParquetRelation[file:/scratch/rxin/spark/sales4][date#0,cat#1,count#2]
```
Author: Reynold Xin <rxin@databricks.com>
Closes#8024 from rxin/SPARK-9733 and squashes the following commits:
811b90e [Reynold Xin] Fixed Python test case.
52cab77 [Reynold Xin] Cast.
eea9ccc [Reynold Xin] Fix test case.
fcecb22 [Reynold Xin] [SPARK-9733][SQL] Improve explain message for data source scan node.
Previously, we use 64MB as the default page size, which was way too big for a lot of Spark applications (especially for single node).
This patch changes it so that the default page size, if unset by the user, is determined by the number of cores available and the total execution memory available.
Author: Reynold Xin <rxin@databricks.com>
Closes#8012 from rxin/pagesize and squashes the following commits:
16f4756 [Reynold Xin] Fixed failing test.
5afd570 [Reynold Xin] private...
0d5fb98 [Reynold Xin] Update default value.
674a6cd [Reynold Xin] Address review feedback.
dc00e05 [Reynold Xin] Merge with master.
73ebdb6 [Reynold Xin] [SPARK-9700] Pick default page size more intelligently.
https://issues.apache.org/jira/browse/SPARK-9691
jkbradley rxin
Author: Yin Huai <yhuai@databricks.com>
Closes#7999 from yhuai/pythonRand and squashes the following commits:
4187e0c [Yin Huai] Regression test.
a985ef9 [Yin Huai] Use "if seed is not None" instead "if seed" because "if seed" returns false when seed is 0.
Inspiration drawn from this blog post: https://lab.getbase.com/pandarize-spark-dataframes/
Author: Reynold Xin <rxin@databricks.com>
Closes#7977 from rxin/isin and squashes the following commits:
9b1d3d6 [Reynold Xin] Added return.
2197d37 [Reynold Xin] Fixed test case.
7c1b6cf [Reynold Xin] Import warnings.
4f4a35d [Reynold Xin] [SPARK-9659][SQL] Rename inSet to isin to match Pandas function.
After https://github.com/apache/spark/pull/7263 it is pretty straightforward to Python wrappers.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#7930 from MechCoder/spark-9533 and squashes the following commits:
1bea394 [MechCoder] make getVectors a lazy val
5522756 [MechCoder] [SPARK-9533] [PySpark] [ML] Add missing methods in Word2Vec ML
Author: zhichao.li <zhichao.li@intel.com>
Closes#7709 from zhichao-li/translate and squashes the following commits:
9418088 [zhichao.li] refine checking condition
f2ab77a [zhichao.li] clone string
9d88f2d [zhichao.li] fix indent
6aa2962 [zhichao.li] style
e575ead [zhichao.li] add python api
9d4bab0 [zhichao.li] add special case for fodable and refactor unittest
eda7ad6 [zhichao.li] update to use TernaryExpression
cdfd4be [zhichao.li] add function translate
mengxr This adds the `BlockMatrix` to PySpark. I have the conversions to `IndexedRowMatrix` and `CoordinateMatrix` ready as well, so once PR #7554 is completed (which relies on PR #7746), this PR can be finished.
Author: Mike Dusenberry <mwdusenb@us.ibm.com>
Closes#7761 from dusenberrymw/SPARK-6486_Add_BlockMatrix_to_PySpark and squashes the following commits:
27195c2 [Mike Dusenberry] Adding one more check to _convert_to_matrix_block_tuple, and a few minor documentation changes.
ae50883 [Mike Dusenberry] Minor update: BlockMatrix should inherit from DistributedMatrix.
b8acc1c [Mike Dusenberry] Moving BlockMatrix to pyspark.mllib.linalg.distributed, updating the logic to match that of the other distributed matrices, adding conversions, and adding documentation.
c014002 [Mike Dusenberry] Using properties for better documentation.
3bda6ab [Mike Dusenberry] Adding documentation.
8fb3095 [Mike Dusenberry] Small cleanup.
e17af2e [Mike Dusenberry] Adding BlockMatrix to PySpark.
This PR is based on #7580 , thanks to EntilZha
PR for work on https://issues.apache.org/jira/browse/SPARK-8231
Currently, I have an initial implementation for contains. Based on discussion on JIRA, it should behave same as Hive: https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDFArrayContains.java#L102-L128
Main points are:
1. If the array is empty, null, or the value is null, return false
2. If there is a type mismatch, throw error
3. If comparison is not supported, throw error
Closes#7580
Author: Pedro Rodriguez <prodriguez@trulia.com>
Author: Pedro Rodriguez <ski.rodriguez@gmail.com>
Author: Davies Liu <davies@databricks.com>
Closes#7949 from davies/array_contains and squashes the following commits:
d3c08bc [Davies Liu] use foreach() to avoid copy
bc3d1fe [Davies Liu] fix array_contains
719e37d [Davies Liu] Merge branch 'master' of github.com:apache/spark into array_contains
e352cf9 [Pedro Rodriguez] fixed diff from master
4d5b0ff [Pedro Rodriguez] added docs and another type check
ffc0591 [Pedro Rodriguez] fixed unit test
7a22deb [Pedro Rodriguez] Changed test to use strings instead of long/ints which are different between python 2 an 3
b5ffae8 [Pedro Rodriguez] fixed pyspark test
4e7dce3 [Pedro Rodriguez] added more docs
3082399 [Pedro Rodriguez] fixed unit test
46f9789 [Pedro Rodriguez] reverted change
d3ca013 [Pedro Rodriguez] Fixed type checking to match hive behavior, then added tests to insure this
8528027 [Pedro Rodriguez] added more tests
686e029 [Pedro Rodriguez] fix scala style
d262e9d [Pedro Rodriguez] reworked type checking code and added more tests
2517a58 [Pedro Rodriguez] removed unused import
28b4f71 [Pedro Rodriguez] fixed bug with type conversions and re-added tests
12f8795 [Pedro Rodriguez] fix scala style checks
e8a20a9 [Pedro Rodriguez] added python df (broken atm)
65b562c [Pedro Rodriguez] made array_contains nullable false
33b45aa [Pedro Rodriguez] reordered test
9623c64 [Pedro Rodriguez] fixed test
4b4425b [Pedro Rodriguez] changed Arrays in tests to Seqs
72cb4b1 [Pedro Rodriguez] added checkInputTypes and docs
69c46fb [Pedro Rodriguez] added tests and codegen
9e0bfc4 [Pedro Rodriguez] initial attempt at implementation
This adds Python API for those DataFrame functions that is introduced in 1.5.
There is issue with serialize byte_array in Python 3, so some of functions (for BinaryType) does not have tests.
cc rxin
Author: Davies Liu <davies@databricks.com>
Closes#7922 from davies/python_functions and squashes the following commits:
8ad942f [Davies Liu] fix test
5fb6ec3 [Davies Liu] fix bugs
3495ed3 [Davies Liu] fix issues
ea5f7bb [Davies Liu] Add python API for DataFrame functions
This PR adds the RowMatrix, IndexedRowMatrix, and CoordinateMatrix distributed matrices to PySpark. Each distributed matrix class acts as a wrapper around the Scala/Java counterpart by maintaining a reference to the Java object. New distributed matrices can be created using factory methods added to DistributedMatrices, which creates the Java distributed matrix and then wraps it with the corresponding PySpark class. This design allows for simple conversion between the various distributed matrices, and lets us re-use the Scala code. Serialization between Python and Java is implemented using DataFrames as needed for IndexedRowMatrix and CoordinateMatrix for simplicity. Associated documentation and unit-tests have also been added. To facilitate code review, this PR implements access to the rows/entries as RDDs, the number of rows & columns, and conversions between the various distributed matrices (not including BlockMatrix), and does not implement the other linear algebra functions of the matrices, although this will be very simple to add now.
Author: Mike Dusenberry <mwdusenb@us.ibm.com>
Closes#7554 from dusenberrymw/SPARK-6485_Add_CoordinateMatrix_RowMatrix_IndexedMatrix_to_PySpark and squashes the following commits:
bb039cb [Mike Dusenberry] Minor documentation update.
b887c18 [Mike Dusenberry] Updating the matrix conversion logic again to make it even cleaner. Now, we allow the 'rows' parameter in the constructors to be either an RDD or the Java matrix object. If 'rows' is an RDD, we create a Java matrix object, wrap it, and then store that. If 'rows' is a Java matrix object of the correct type, we just wrap and store that directly. This is only for internal usage, and publicly, we still require 'rows' to be an RDD. We no longer store the 'rows' RDD, and instead just compute it from the Java object when needed. The point of this is that when we do matrix conversions, we do the conversion on the Scala/Java side, which returns a Java object, so we should use that directly, but exposing 'java_matrix' parameter in the public API is not ideal. This non-public feature of allowing 'rows' to be a Java matrix object is documented in the '__init__' constructor docstrings, which are not part of the generated public API, and doctests are also included.
7f0dcb6 [Mike Dusenberry] Updating module docstring.
cfc1be5 [Mike Dusenberry] Use 'new SQLContext(matrix.rows.sparkContext)' rather than 'SQLContext.getOrCreate', as the later doesn't guarantee that the SparkContext will be the same as for the matrix.rows data.
687e345 [Mike Dusenberry] Improving conversion performance. This adds an optional 'java_matrix' parameter to the constructors, and pulls the conversion logic out into a '_create_from_java' function. Now, if the constructors are given a valid Java distributed matrix object as 'java_matrix', they will store those internally, rather than create a new one on the Scala/Java side.
3e50b6e [Mike Dusenberry] Moving the distributed matrices to pyspark.mllib.linalg.distributed.
308f197 [Mike Dusenberry] Using properties for better documentation.
1633f86 [Mike Dusenberry] Minor documentation cleanup.
f0c13a7 [Mike Dusenberry] CoordinateMatrix should inherit from DistributedMatrix.
ffdd724 [Mike Dusenberry] Updating doctests to make documentation cleaner.
3fd4016 [Mike Dusenberry] Updating docstrings.
27cd5f6 [Mike Dusenberry] Simplifying input conversions in the constructors for each distributed matrix.
a409cf5 [Mike Dusenberry] Updating doctests to be less verbose by using lists instead of DenseVectors explicitly.
d19b0ba [Mike Dusenberry] Updating code and documentation to note that a vector-like object (numpy array, list, etc.) can be used in place of explicit Vector object, and adding conversions when necessary to RowMatrix construction.
4bd756d [Mike Dusenberry] Adding param documentation to IndexedRow and MatrixEntry.
c6bded5 [Mike Dusenberry] Move conversion logic from tuples to IndexedRow or MatrixEntry types from within the IndexedRowMatrix and CoordinateMatrix constructors to separate _convert_to_indexed_row and _convert_to_matrix_entry functions.
329638b [Mike Dusenberry] Moving the Experimental tag to the top of each docstring.
0be6826 [Mike Dusenberry] Simplifying doctests by removing duplicated rows/entries RDDs within the various tests.
c0900df [Mike Dusenberry] Adding the colons that were accidentally not inserted.
4ad6819 [Mike Dusenberry] Documenting the and parameters.
3b854b9 [Mike Dusenberry] Minor updates to documentation.
10046e8 [Mike Dusenberry] Updating documentation to use class constructors instead of the removed DistributedMatrices factory methods.
119018d [Mike Dusenberry] Adding static methods to each of the distributed matrix classes to consolidate conversion logic.
4d7af86 [Mike Dusenberry] Adding type checks to the constructors. Although it is slightly verbose, it is better for the user to have a good error message than a cryptic stacktrace.
93b6a3d [Mike Dusenberry] Pulling the DistributedMatrices Python class out of this pull request.
f6f3c68 [Mike Dusenberry] Pulling the DistributedMatrices Scala class out of this pull request.
6a3ecb7 [Mike Dusenberry] Updating pattern matching.
08f287b [Mike Dusenberry] Slight reformatting of the documentation.
a245dc0 [Mike Dusenberry] Updating Python doctests for compatability between Python 2 & 3. Since Python 3 removed the idea of a separate 'long' type, all values that would have been outputted as a 'long' (ex: '4L') will now be treated as an 'int' and outputed as one (ex: '4'). The doctests now explicitly convert to ints so that both Python 2 and 3 will have the same output. This is fine since the values are all small, and thus can be easily represented as ints.
4d3a37e [Mike Dusenberry] Reformatting a few long Python doctest lines.
7e3ca16 [Mike Dusenberry] Fixing long lines.
f721ead [Mike Dusenberry] Updating documentation for each of the distributed matrices.
ab0e8b6 [Mike Dusenberry] Updating unit test to be more useful.
dda2f89 [Mike Dusenberry] Added wrappers for the conversions between the various distributed matrices. Added logic to be able to access the rows/entries of the distributed matrices, which requires serialization through DataFrames for IndexedRowMatrix and CoordinateMatrix types. Added unit tests.
0cd7166 [Mike Dusenberry] Implemented the CoordinateMatrix API in PySpark, following the idea of the IndexedRowMatrix API, including using DataFrames for serialization.
3c369cb [Mike Dusenberry] Updating the architecture a bit to make conversions between the various distributed matrix types easier. The different distributed matrix classes are now only wrappers around the Java objects, and take the Java object as an argument during construction. This way, we can call for example on an , which returns a reference to a Java RowMatrix object, and then construct a PySpark RowMatrix object wrapped around the Java object. This is analogous to the behavior of PySpark RDDs and DataFrames. We now delegate creation of the various distributed matrices from scratch in PySpark to the factory methods on .
4bdd09b [Mike Dusenberry] Implemented the IndexedRowMatrix API in PySpark, following the idea of the RowMatrix API. Note that for the IndexedRowMatrix, we use DataFrames to serialize the data between Python and Scala/Java, so we accept PySpark RDDs, then convert to a DataFrame, then convert back to RDDs on the Scala/Java side before constructing the IndexedRowMatrix.
23bf1ec [Mike Dusenberry] Updating documentation to add PySpark RowMatrix. Inserting newline above doctest so that it renders properly in API docs.
b194623 [Mike Dusenberry] Updating design to have a PySpark RowMatrix simply create and keep a reference to a wrapper over a Java RowMatrix. Updating DistributedMatrices factory methods to accept numRows and numCols with default values. Updating PySpark DistributedMatrices factory method to simply create a PySpark RowMatrix. Adding additional doctests for numRows and numCols parameters.
bc2d220 [Mike Dusenberry] Adding unit tests for RowMatrix methods.
d7e316f [Mike Dusenberry] Implemented the RowMatrix API in PySpark by doing the following: Added a DistributedMatrices class to contain factory methods for creating the various distributed matrices. Added a factory method for creating a RowMatrix from an RDD of Vectors. Added a createRowMatrix function to the PythonMLlibAPI to interface with the factory method. Added DistributedMatrix, DistributedMatrices, and RowMatrix classes to the pyspark.mllib.linalg api.
Added HasRawPredictionCol, HasProbabilityCol to RandomForestClassifier, plus doc tests for those columns.
CC: holdenk yanboliang
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#7903 from jkbradley/rf-prob-python and squashes the following commits:
c62a83f [Joseph K. Bradley] made unit test more robust
14eeba2 [Joseph K. Bradley] added HasRawPredictionCol, HasProbabilityCol to RandomForestClassifier in PySpark
This PR replaces the old "threshold" with a generalized "thresholds" Param. We keep getThreshold,setThreshold for backwards compatibility for binary classification.
Note that the primary author of this PR is holdenk
Author: Holden Karau <holden@pigscanfly.ca>
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#7909 from jkbradley/holdenk-SPARK-8069-add-cutoff-aka-threshold-to-random-forest and squashes the following commits:
3952977 [Joseph K. Bradley] fixed pyspark doc test
85febc8 [Joseph K. Bradley] made python unit tests a little more robust
7eb1d86 [Joseph K. Bradley] small cleanups
6cc2ed8 [Joseph K. Bradley] Fixed remaining merge issues.
0255e44 [Joseph K. Bradley] Many cleanups for thresholds, some more tests
7565a60 [Holden Karau] fix pep8 style checks, add a getThreshold method similar to our LogisticRegression.scala one for API compat
be87f26 [Holden Karau] Convert threshold to thresholds in the python code, add specialized support for Array[Double] to shared parems codegen, etc.
6747dad [Holden Karau] Override raw2prediction for ProbabilisticClassifier, fix some tests
25df168 [Holden Karau] Fix handling of thresholds in LogisticRegression
c02d6c0 [Holden Karau] No default for thresholds
5e43628 [Holden Karau] CR feedback and fixed the renamed test
f3fbbd1 [Holden Karau] revert the changes to random forest :(
51f581c [Holden Karau] Add explicit types to public methods, fix long line
f7032eb [Holden Karau] Fix a java test bug, remove some unecessary changes
adf15b4 [Holden Karau] rename the classifier suite test to ProbabilisticClassifierSuite now that we only have it in Probabilistic
398078a [Holden Karau] move the thresholding around a bunch based on the design doc
4893bdc [Holden Karau] Use numtrees of 3 since previous result was tied (one tree for each) and the switch from different max methods picked a different element (since they were equal I think this is ok)
638854c [Holden Karau] Add a scala RandomForestClassifierSuite test based on corresponding python test
e09919c [Holden Karau] Fix return type, I need more coffee....
8d92cac [Holden Karau] Use ClassifierParams as the head
3456ed3 [Holden Karau] Add explicit return types even though just test
a0f3b0c [Holden Karau] scala style fixes
6f14314 [Holden Karau] Since hasthreshold/hasthresholds is in root classifier now
ffc8dab [Holden Karau] Update the sharedParams
0420290 [Holden Karau] Allow us to override the get methods selectively
978e77a [Holden Karau] Move HasThreshold into classifier params and start defining the overloaded getThreshold/getThresholds functions
1433e52 [Holden Karau] Revert "try and hide threshold but chainges the API so no dice there"
1f09a2e [Holden Karau] try and hide threshold but chainges the API so no dice there
efb9084 [Holden Karau] move setThresholds only to where its used
6b34809 [Holden Karau] Add a test with thresholding for the RFCS
74f54c3 [Holden Karau] Fix creation of vote array
1986fa8 [Holden Karau] Setting the thresholds only makes sense if the underlying class hasn't overridden predict, so lets push it down.
2f44b18 [Holden Karau] Add a global default of null for thresholds param
f338cfc [Holden Karau] Wait that wasn't a good idea, Revert "Some progress towards unifying threshold and thresholds"
634b06f [Holden Karau] Some progress towards unifying threshold and thresholds
85c9e01 [Holden Karau] Test passes again... little fnur
099c0f3 [Holden Karau] Move thresholds around some more (set on model not trainer)
0f46836 [Holden Karau] Start adding a classifiersuite
f70eb5e [Holden Karau] Fix test compile issues
a7d59c8 [Holden Karau] Move thresholding into Classifier trait
5d999d2 [Holden Karau] Some more progress, start adding a test (maybe try and see if we can find a better thing to use for the base of the test)
1fed644 [Holden Karau] Use thresholds to scale scores in random forest classifcation
31d6bf2 [Holden Karau] Start threading the threshold info through
0ef228c [Holden Karau] Add hasthresholds
Add Python API for RFormula. Similar to other feature transformers in Python. This is just a thin wrapper over the Scala implementation. ericl MechCoder
Author: Xiangrui Meng <meng@databricks.com>
Closes#7879 from mengxr/SPARK-9544 and squashes the following commits:
3d5ff03 [Xiangrui Meng] add an doctest for . and -
5e969a5 [Xiangrui Meng] fix pydoc
1cd41f8 [Xiangrui Meng] organize imports
3c18b10 [Xiangrui Meng] add Python API for RFormula
Make the following ml.classification class support raw and probability prediction for PySpark:
```scala
NaiveBayesModel
DecisionTreeClassifierModel
LogisticRegressionModel
```
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#7866 from yanboliang/spark-9536-9537 and squashes the following commits:
2934dab [Yanbo Liang] ml.NaiveBayes, ml.DecisionTreeClassifier and ml.LogisticRegression support probability prediction
This PR is based on #7208 , thanks to HuJiayin
Closes#7208
Author: HuJiayin <jiayin.hu@intel.com>
Author: Davies Liu <davies@databricks.com>
Closes#7850 from davies/initcap and squashes the following commits:
54472e9 [Davies Liu] fix python test
17ffe51 [Davies Liu] Merge branch 'master' of github.com:apache/spark into initcap
ca46390 [Davies Liu] Merge branch 'master' of github.com:apache/spark into initcap
3a906e4 [Davies Liu] implement title case in UTF8String
8b2506a [HuJiayin] Update functions.py
2cd43e5 [HuJiayin] fix python style check
b616c0e [HuJiayin] add python api
1f5a0ef [HuJiayin] add codegen
7e0c604 [HuJiayin] Merge branch 'master' of https://github.com/apache/spark into initcap
6a0b958 [HuJiayin] add column
c79482d [HuJiayin] support soundex
7ce416b [HuJiayin] support initcap rebase code
This is based on #7641, thanks to zhichao-li
Closes#7641
Author: zhichao.li <zhichao.li@intel.com>
Author: Davies Liu <davies@databricks.com>
Closes#7848 from davies/substr and squashes the following commits:
461b709 [Davies Liu] remove bytearry from tests
b45377a [Davies Liu] Merge branch 'master' of github.com:apache/spark into substr
01d795e [zhichao.li] scala style
99aa130 [zhichao.li] add substring to dataframe
4f68bfe [zhichao.li] add binary type support for substring
This PR is based on #7581 , just fix the conflict.
Author: Cheng Hao <hao.cheng@intel.com>
Author: Davies Liu <davies@databricks.com>
Closes#7851 from davies/sort_array and squashes the following commits:
a80ef66 [Davies Liu] fix conflict
7cfda65 [Davies Liu] Merge branch 'master' of github.com:apache/spark into sort_array
664c960 [Cheng Hao] update the sort_array by using the ArrayData
276d2d5 [Cheng Hao] add empty line
0edab9c [Cheng Hao] Add asending/descending support for sort_array
80fc0f8 [Cheng Hao] Add type checking
a42b678 [Cheng Hao] Add sort_array support
Add expression `sort_array` support.
Author: Cheng Hao <hao.cheng@intel.com>
This patch had conflicts when merged, resolved by
Committer: Davies Liu <davies.liu@gmail.com>
Closes#7581 from chenghao-intel/sort_array and squashes the following commits:
664c960 [Cheng Hao] update the sort_array by using the ArrayData
276d2d5 [Cheng Hao] add empty line
0edab9c [Cheng Hao] Add asending/descending support for sort_array
80fc0f8 [Cheng Hao] Add type checking
a42b678 [Cheng Hao] Add sort_array support
This PR is based on #7533 , thanks to zhichao-li
Closes#7533
Author: zhichao.li <zhichao.li@intel.com>
Author: Davies Liu <davies@databricks.com>
Closes#7843 from davies/str_index and squashes the following commits:
391347b [Davies Liu] add python api
3ce7802 [Davies Liu] fix substringIndex
f2d29a1 [Davies Liu] Merge branch 'master' of github.com:apache/spark into str_index
515519b [zhichao.li] add foldable and remove null checking
9546991 [zhichao.li] scala style
67c253a [zhichao.li] hide some apis and clean code
b19b013 [zhichao.li] add codegen and clean code
ac863e9 [zhichao.li] reduce the calling of numChars
12e108f [zhichao.li] refine unittest
d92951b [zhichao.li] add lastIndexOf
52d7b03 [zhichao.li] add substring_index function
This PR brings SQL function soundex(), see https://issues.apache.org/jira/browse/HIVE-9738
It's based on #7115 , thanks to HuJiayin
Author: HuJiayin <jiayin.hu@intel.com>
Author: Davies Liu <davies@databricks.com>
Closes#7812 from davies/soundex and squashes the following commits:
fa75941 [Davies Liu] Merge branch 'master' of github.com:apache/spark into soundex
a4bd6d8 [Davies Liu] fix soundex
2538908 [HuJiayin] add codegen soundex
d15d329 [HuJiayin] add back ut
ded1a14 [HuJiayin] Merge branch 'master' of https://github.com/apache/spark
e2dec2c [HuJiayin] support soundex rebase code
This PR adds the Python API for Kinesis, including a Python example and a simple unit test.
Author: zsxwing <zsxwing@gmail.com>
Closes#6955 from zsxwing/kinesis-python and squashes the following commits:
e42e471 [zsxwing] Merge branch 'master' into kinesis-python
455f7ea [zsxwing] Remove streaming_kinesis_asl_assembly module and simply add the source folder to streaming_kinesis_asl module
32e6451 [zsxwing] Merge remote-tracking branch 'origin/master' into kinesis-python
5082d28 [zsxwing] Fix the syntax error for Python 2.6
fca416b [zsxwing] Fix wrong comparison
96670ff [zsxwing] Fix the compilation error after merging master
756a128 [zsxwing] Merge branch 'master' into kinesis-python
6c37395 [zsxwing] Print stack trace for debug
7c5cfb0 [zsxwing] RUN_KINESIS_TESTS -> ENABLE_KINESIS_TESTS
cc9d071 [zsxwing] Fix the python test errors
466b425 [zsxwing] Add python tests for Kinesis
e33d505 [zsxwing] Merge remote-tracking branch 'origin/master' into kinesis-python
3da2601 [zsxwing] Fix the kinesis folder
687446b [zsxwing] Fix the error message and the maven output path
add2beb [zsxwing] Merge branch 'master' into kinesis-python
4957c0b [zsxwing] Add the Python API for Kinesis
support ml.NaiveBayes for Python
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#7568 from yanboliang/spark-9214 and squashes the following commits:
5ee3fd6 [Yanbo Liang] fix typos
3ecd046 [Yanbo Liang] fix typos
f9c94d1 [Yanbo Liang] change lambda_ to smoothing and fix other issues
180452a [Yanbo Liang] fix typos
7dda1f4 [Yanbo Liang] support ml.NaiveBayes for Python
This PR is based on #6988 , thanks to adrian-wang .
This brings two SQL functions: to_date() and trunc().
Closes#6988
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Author: Davies Liu <davies@databricks.com>
Closes#7805 from davies/to_date and squashes the following commits:
2c7beba [Davies Liu] Merge branch 'master' of github.com:apache/spark into to_date
310dd55 [Daoyuan Wang] remove dup test in rebase
980b092 [Daoyuan Wang] resolve rebase conflict
a476c5a [Daoyuan Wang] address comments from davies
d44ea5f [Daoyuan Wang] function to_date, trunc
This was previously committed but then reverted due to test failures (see #6769).
Author: Xiangrui Meng <meng@databricks.com>
Closes#7755 from rxin/SPARK-7157 and squashes the following commits:
fbf9044 [Xiangrui Meng] fix python test
542bd37 [Xiangrui Meng] update test
604fe6d [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7157
f051afd [Xiangrui Meng] use udf instead of building expression
f4e9425 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7157
8fb990b [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7157
103beb3 [Xiangrui Meng] add Java-friendly sampleBy
991f26f [Xiangrui Meng] fix seed
4a14834 [Xiangrui Meng] move sampleBy to stat
832f7cc [Xiangrui Meng] add sampleBy to DataFrame
This is based on MechCoder 's PR https://github.com/apache/spark/pull/7731. Hopefully it could pass tests. MechCoder I tried to make minimal changes. If this passes Jenkins, we can merge this one first and then try to move `__init__.py` to `local.py` in a separate PR.
Closes#7731
Author: Xiangrui Meng <meng@databricks.com>
Closes#7746 from mengxr/SPARK-9408 and squashes the following commits:
0e05a3b [Xiangrui Meng] merge master
1135551 [Xiangrui Meng] add a comment for str(...)
c48cae0 [Xiangrui Meng] update tests
173a805 [Xiangrui Meng] move linalg.py to linalg/__init__.py
This PR is based on #7589 , thanks to adrian-wang
Added SQL function date_add, date_sub, add_months, month_between, also add a rule for
add/subtract of date/timestamp and interval.
Closes#7589
cc rxin
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Author: Davies Liu <davies@databricks.com>
Closes#7754 from davies/date_add and squashes the following commits:
e8c633a [Davies Liu] Merge branch 'master' of github.com:apache/spark into date_add
9e8e085 [Davies Liu] Merge branch 'master' of github.com:apache/spark into date_add
6224ce4 [Davies Liu] fix conclict
bd18cd4 [Davies Liu] Merge branch 'master' of github.com:apache/spark into date_add
e47ff2c [Davies Liu] add python api, fix date functions
01943d0 [Davies Liu] Merge branch 'master' into date_add
522e91a [Daoyuan Wang] fix
e8a639a [Daoyuan Wang] fix
42df486 [Daoyuan Wang] fix style
87c4b77 [Daoyuan Wang] function add_months, months_between and some fixes
1a68e03 [Daoyuan Wang] poc of time interval calculation
c506661 [Daoyuan Wang] function date_add , date_sub
This pull request enables Unsafe mode by default in Spark SQL. In order to do this, we had to fix a number of small issues:
**List of fixed blockers**:
- [x] Make some default buffer sizes configurable so that HiveCompatibilitySuite can run properly (#7741).
- [x] Memory leak on grouped aggregation of empty input (fixed by #7560 to fix this)
- [x] Update planner to also check whether codegen is enabled before planning unsafe operators.
- [x] Investigate failing HiveThriftBinaryServerSuite test. This turns out to be caused by a ClassCastException that occurs when Exchange tries to apply an interpreted RowOrdering to an UnsafeRow when range partitioning an RDD. This could be fixed by #7408, but a shorter-term fix is to just skip the Unsafe exchange path when RangePartitioner is used.
- [x] Memory leak exceptions masking exceptions that actually caused tasks to fail (will be fixed by #7603).
- [x] ~~https://issues.apache.org/jira/browse/SPARK-9162, to implement code generation for ScalaUDF. This is necessary for `UDFSuite` to pass. For now, I've just ignored this test in order to try to find other problems while we wait for a fix.~~ This is no longer necessary as of #7682.
- [x] Memory leaks from Limit after UnsafeExternalSort cause the memory leak detector to fail tests. This is a huge problem in the HiveCompatibilitySuite (fixed by f4ac642a4e5b2a7931c5e04e086bb10e263b1db6).
- [x] Tests in `AggregationQuerySuite` are failing due to NaN-handling issues in UnsafeRow, which were fixed in #7736.
- [x] `org.apache.spark.sql.ColumnExpressionSuite.rand` needs to be updated so that the planner check also matches `TungstenProject`.
- [x] After having lowered the buffer sizes to 4MB so that most of HiveCompatibilitySuite runs:
- [x] Wrong answer in `join_1to1` (fixed by #7680)
- [x] Wrong answer in `join_nulls` (fixed by #7680)
- [x] Managed memory OOM / leak in `lateral_view`
- [x] Seems to hang indefinitely in `partcols1`. This might be a deadlock in script transformation or a bug in error-handling code? The hang was fixed by #7710.
- [x] Error while freeing memory in `partcols1`: will be fixed by #7734.
- [x] After fixing the `partcols1` hang, it appears that a number of later tests have issues as well.
- [x] Fix thread-safety bug in codegen fallback expression evaluation (#7759).
Author: Josh Rosen <joshrosen@databricks.com>
Closes#7564 from JoshRosen/unsafe-by-default and squashes the following commits:
83c0c56 [Josh Rosen] Merge remote-tracking branch 'origin/master' into unsafe-by-default
f4cc859 [Josh Rosen] Merge remote-tracking branch 'origin/master' into unsafe-by-default
963f567 [Josh Rosen] Reduce buffer size for R tests
d6986de [Josh Rosen] Lower page size in PySpark tests
013b9da [Josh Rosen] Also match TungstenProject in checkNumProjects
5d0b2d3 [Josh Rosen] Add task completion callback to avoid leak in limit after sort
ea250da [Josh Rosen] Disable unsafe Exchange path when RangePartitioning is used
715517b [Josh Rosen] Enable Unsafe by default
This is #7791 for Python. hhbyyh
Author: Xiangrui Meng <meng@databricks.com>
Closes#7798 from mengxr/regex-tok-py and squashes the following commits:
baa2dcd [Xiangrui Meng] fix doc for RegexTokenizer
Also we could create a Python UDT without having a Scala one, it's important for Python users.
cc mengxr JoshRosen
Author: Davies Liu <davies@databricks.com>
Closes#7453 from davies/class_in_main and squashes the following commits:
4dfd5e1 [Davies Liu] add tests for Python and Scala UDT
793d9b2 [Davies Liu] Merge branch 'master' of github.com:apache/spark into class_in_main
dc65f19 [Davies Liu] address comment
a9a3c40 [Davies Liu] Merge branch 'master' of github.com:apache/spark into class_in_main
a86e1fc [Davies Liu] fix serialization
ad528ba [Davies Liu] Merge branch 'master' of github.com:apache/spark into class_in_main
63f52ef [Davies Liu] fix pylint check
655b8a9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into class_in_main
316a394 [Davies Liu] support Python UDT with UTF
0bcb3ef [Davies Liu] fix bug in mllib
de986d6 [Davies Liu] fix test
83d65ac [Davies Liu] fix bug in StructType
55bb86e [Davies Liu] support Python UDT in __main__ (without Scala one)
`names` is not defined in this context, I think you meant `self.names`.
davies
Author: Alex Angelini <alex.louis.angelini@gmail.com>
Closes#7766 from angelini/fix_struct_type_names and squashes the following commits:
01543a1 [Alex Angelini] Fix reference to self.names in StructType
Implement the classification trait for RandomForestClassifiers. The plan is to use this in the future to providing thresholding for RandomForestClassifiers (as well as other classifiers that implement that trait).
Author: Holden Karau <holden@pigscanfly.ca>
Closes#7432 from holdenk/SPARK-9016-make-random-forest-classifiers-implement-classification-trait and squashes the following commits:
bf22fa6 [Holden Karau] Add missing imports for testing suite
e948f0d [Holden Karau] Check the prediction generation from rawprediciton
25320c3 [Holden Karau] Don't supply numClasses when not needed, assert model classes are as expected
1a67e04 [Holden Karau] Use old decission tree stuff instead
673e0c3 [Holden Karau] Merge branch 'master' into SPARK-9016-make-random-forest-classifiers-implement-classification-trait
0d15b96 [Holden Karau] FIx typo
5eafad4 [Holden Karau] add a constructor for rootnode + num classes
fc6156f [Holden Karau] scala style fix
2597915 [Holden Karau] take num classes in constructor
3ccfe4a [Holden Karau] Merge in master, make pass numClasses through randomforest for training
222a10b [Holden Karau] Increase numtrees to 3 in the python test since before the two were equal and the argmax was selecting the last one
16aea1c [Holden Karau] Make tests match the new models
b454a02 [Holden Karau] Make the Tree classifiers extends the Classifier base class
77b4114 [Holden Karau] Import vectors lib
This PR introduces save / load for GMM's in python API.
Also I refactored `GaussianMixtureModel` and inherited it from `JavaModelWrapper` with model being `GaussianMixtureModelWrapper`, a wrapper which provides convenience methods to `GaussianMixtureModel` (due to serialization and deserialization issues) and I moved the creation of gaussians to the scala backend.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#7617 from MechCoder/python_gmm_save_load and squashes the following commits:
9c305aa [MechCoder] [SPARK-7105] [PySpark] [MLlib] Support model save/load in GMM
Author: JD <jd@csh.rit.edu>
Author: Joseph Batchik <josephbatchik@gmail.com>
Closes#7606 from JDrit/expr and squashes the following commits:
ad7f607 [Joseph Batchik] fixing python linter error
9d6daea [Joseph Batchik] removed order by per @rxin's comment
707d5c6 [Joseph Batchik] Added expr to fuctions.py
79df83c [JD] added example to the docs
b89eec8 [JD] moved function up as per @rxin's comment
4960909 [JD] updated per @JoshRosen's comment
2cb329c [JD] updated per @rxin's comment
9a9ad0c [JD] removing unused import
6dc26d0 [JD] removed split
7f2222c [JD] Adding expr function as per SPARK-8668
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
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 257236c3e1. 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 257236c3e1.
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.
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 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
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
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)
Follow up for https://github.com/apache/spark/pull/5946
Currently we iterate over indices and values in SparseVector and can be vectorized.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#7222 from MechCoder/sparse_optim and squashes the following commits:
dcb51d3 [MechCoder] [SPARK-8823] [MLlib] [PySpark] Optimizations for SparseVector dot product
Add numNodes and depth to treeModels, add treeWeights to ensemble Models.
Add __repr__ to all models.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#7095 from MechCoder/missing_methods_tree and squashes the following commits:
23b08be [MechCoder] private [spark]
38a0860 [MechCoder] rename pyTreeWeights to javaTreeWeights
6d16ad8 [MechCoder] Fix Python 3 Error
47d7023 [MechCoder] Use np.allclose and treeEnsembleModel -> TreeEnsembleMethods
819098c [MechCoder] [SPARK-8711] [ML] Add additional methods ot PySpark ML tree models
PySpark PowerIterationClustering test failure due to bad demo data.
If the data is small, PowerIterationClustering will behavior indeterministic.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#7177 from yanboliang/spark-8765 and squashes the following commits:
392ae54 [Yanbo Liang] fix model.assignments output
5ec3f1e [Yanbo Liang] fix PySpark PowerIterationClustering test issue
This reverts commit 25f574eb9a. After speaking to some users and developers, we realized that FP-growth doesn't meet the requirement for frequent sequence mining. PrefixSpan (SPARK-6487) would be the correct algorithm for it. feynmanliang
Author: Xiangrui Meng <meng@databricks.com>
Closes#7240 from mengxr/SPARK-7212.revert and squashes the following commits:
2b3d66b [Xiangrui Meng] Revert "[SPARK-7212] [MLLIB] Add sequence learning flag"
Add Python API for hex/unhex, also cleanup Hex/Unhex
Author: Davies Liu <davies@databricks.com>
Closes#7223 from davies/hex and squashes the following commits:
6f1249d [Davies Liu] no explicit rule to cast string into binary
711a6ed [Davies Liu] fix test
f9fe5a3 [Davies Liu] Merge branch 'master' of github.com:apache/spark into hex
f032fbb [Davies Liu] Merge branch 'hex' of github.com:davies/spark into hex
49e325f [Davies Liu] Merge branch 'master' of github.com:apache/spark into hex
b31fc9a [Davies Liu] Update math.scala
25156b7 [Davies Liu] address comments and fix test
c3af78c [Davies Liu] address commments
1a24082 [Davies Liu] Add Python API for hex and unhex
Jira: https://issues.apache.org/jira/browse/SPARK-8270
Info: I can not build the latest master, it stucks during the build process: `[INFO] Dependency-reduced POM written at: /Users/tarek/test/spark/bagel/dependency-reduced-pom.xml`
Author: Tarek Auel <tarek.auel@googlemail.com>
Closes#7214 from tarekauel/SPARK-8270 and squashes the following commits:
ab348b9 [Tarek Auel] Merge branch 'master' into SPARK-8270
a2ad318 [Tarek Auel] [SPARK-8270] changed order of fields
d91b12c [Tarek Auel] [SPARK-8270] python fix
adbd075 [Tarek Auel] [SPARK-8270] fixed typo
23185c9 [Tarek Auel] [SPARK-8270] levenshtein distance
