Also moved all the deprecated functions into one place for SQLContext and DataFrame, and updated tests to use the new API.
Author: Reynold Xin <rxin@databricks.com>
Closes#6210 from rxin/df-writer-reader-jdbc and squashes the following commits:
7465c2c [Reynold Xin] Fixed unit test.
118e609 [Reynold Xin] Updated tests.
3441b57 [Reynold Xin] Updated javadoc.
13cdd1c [Reynold Xin] [SPARK-7654][SQL] Move JDBC into DataFrame's reader/writer interface.
(cherry picked from commit 517eb37a85)
Signed-off-by: Reynold Xin <rxin@databricks.com>
Author: Reynold Xin <rxin@databricks.com>
Closes#6211 from rxin/mllib-reader and squashes the following commits:
79a2cb9 [Reynold Xin] [SPARK-7654][MLlib] Migrate MLlib to the DataFrame reader/writer API.
(cherry picked from commit 161d0b4a41)
Signed-off-by: Reynold Xin <rxin@databricks.com>
This patch introduces DataFrameWriter and DataFrameReader.
DataFrameReader interface, accessible through SQLContext.read, contains methods that create DataFrames. These methods used to reside in SQLContext. Example usage:
```scala
sqlContext.read.json("...")
sqlContext.read.parquet("...")
```
DataFrameWriter interface, accessible through DataFrame.write, implements a builder pattern to avoid the proliferation of options in writing DataFrame out. It currently implements:
- mode
- format (e.g. "parquet", "json")
- options (generic options passed down into data sources)
- partitionBy (partitioning columns)
Example usage:
```scala
df.write.mode("append").format("json").partitionBy("date").saveAsTable("myJsonTable")
```
TODO:
- [ ] Documentation update
- [ ] Move JDBC into reader / writer?
- [ ] Deprecate the old interfaces
- [ ] Move the generic load interface into reader.
- [ ] Update example code and documentation
Author: Reynold Xin <rxin@databricks.com>
Closes#6175 from rxin/reader-writer and squashes the following commits:
b146c95 [Reynold Xin] Deprecation of old APIs.
bd8abdf [Reynold Xin] Fixed merge conflict.
26abea2 [Reynold Xin] Added general load methods.
244fbec [Reynold Xin] Added equivalent to example.
4f15d92 [Reynold Xin] Added documentation for partitionBy.
7e91611 [Reynold Xin] [SPARK-7654][SQL] DataFrameReader and DataFrameWriter for input/output API.
(cherry picked from commit 578bfeeff5)
Signed-off-by: Reynold Xin <rxin@databricks.com>
Java and Scala examples for OneVsRest. Fixes the base classifier to be Logistic Regression and accepts the configuration parameters of the base classifier.
Author: Ram Sriharsha <rsriharsha@hw11853.local>
Closes#6115 from harsha2010/SPARK-7575 and squashes the following commits:
87ad3c7 [Ram Sriharsha] extra line
f5d9891 [Ram Sriharsha] Merge branch 'master' into SPARK-7575
7076084 [Ram Sriharsha] cleanup
dfd660c [Ram Sriharsha] cleanup
8703e4f [Ram Sriharsha] update doc
cb23995 [Ram Sriharsha] fix commandline options for JavaOneVsRestExample
69e91f8 [Ram Sriharsha] cleanup
7f4e127 [Ram Sriharsha] cleanup
d4c40d0 [Ram Sriharsha] Code Review fixes
461eb38 [Ram Sriharsha] cleanup
e0106d9 [Ram Sriharsha] Fix typo
935cf56 [Ram Sriharsha] Try to match Java and Scala Example Commandline options
5323ff9 [Ram Sriharsha] cleanup
196a59a [Ram Sriharsha] cleanup
6adfa0c [Ram Sriharsha] Style Fix
8cfc5d5 [Ram Sriharsha] [SPARK-7575] Example code for OneVsRest
(cherry picked from commit cc12a86fb0)
Signed-off-by: Joseph K. Bradley <joseph@databricks.com>
The difference is because we previously don't fit the intercept in Spark 1.3. Here, we change the input `String` so that the probability of instance 6 can be classified as `1.0` without any ambiguity.
with lambda = 0.001 in current LOR implementation, the prediction is
```
(4, spark i j k) --> prob=[0.1596407738787411,0.8403592261212589], prediction=1.0
(5, l m n) --> prob=[0.8378325685476612,0.16216743145233883], prediction=0.0
(6, spark hadoop spark) --> prob=[0.0692663313297627,0.9307336686702373], prediction=1.0
(7, apache hadoop) --> prob=[0.9821575333444208,0.01784246665557917], prediction=0.0
```
and the training accuracy is
```
(0, a b c d e spark) --> prob=[0.0021342419881406746,0.9978657580118594], prediction=1.0
(1, b d) --> prob=[0.9959176174854043,0.004082382514595685], prediction=0.0
(2, spark f g h) --> prob=[0.0014541569986711233,0.9985458430013289], prediction=1.0
(3, hadoop mapreduce) --> prob=[0.9982978367343561,0.0017021632656438518], prediction=0.0
```
Author: DB Tsai <dbt@netflix.com>
Closes#6109 from dbtsai/lor-example and squashes the following commits:
ac63ce4 [DB Tsai] first commit
(cherry picked from commit c1080b6fdd)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
A param instance is strongly attached to an parent in the current implementation. So if we make a copy of an estimator or a transformer in pipelines and other meta-algorithms, it becomes error-prone to copy the params to the copied instances. In this PR, a param is identified by its parent's UID and the param name. So it becomes loosely attached to its parent and all its derivatives. The UID is preserved during copying or fitting. All components now have a default constructor and a constructor that takes a UID as input. I keep the constructors for Param in this PR to reduce the amount of diff and moved `parent` as a mutable field.
This PR still needs some clean-ups, and there are several spark.ml PRs pending. I'll try to get them merged first and then update this PR.
jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes#6019 from mengxr/SPARK-7407 and squashes the following commits:
c4c8120 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7407
520f0a2 [Xiangrui Meng] address comments
2569168 [Xiangrui Meng] fix tests
873caca [Xiangrui Meng] fix tests in OneVsRest; fix a racing condition in shouldOwn
409ea08 [Xiangrui Meng] minor updates
83a163c [Xiangrui Meng] update JavaDeveloperApiExample
5db5325 [Xiangrui Meng] update OneVsRest
7bde7ae [Xiangrui Meng] merge master
697fdf9 [Xiangrui Meng] update Bucketizer
7b4f6c2 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7407
629d402 [Xiangrui Meng] fix LRSuite
154516f [Xiangrui Meng] merge master
aa4a611 [Xiangrui Meng] fix examples/compile
a4794dd [Xiangrui Meng] change Param to use to reduce the size of diff
fdbc415 [Xiangrui Meng] all tests passed
c255f17 [Xiangrui Meng] fix tests in ParamsSuite
818e1db [Xiangrui Meng] merge master
e1160cf [Xiangrui Meng] fix tests
fbc39f0 [Xiangrui Meng] pass test:compile
108937e [Xiangrui Meng] pass compile
8726d39 [Xiangrui Meng] use parent uid in Param
eaeed35 [Xiangrui Meng] update Identifiable
(cherry picked from commit 1b8625f425)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
As is, to specify this option on command line, you have to escape the angle brackets.
Author: Bryan Cutler <bjcutler@us.ibm.com>
Closes#6049 from BryanCutler/dataFormat-option-7522 and squashes the following commits:
b34afb4 [Bryan Cutler] [SPARK-7522] Removed angle brackets from dataFormat option
(cherry picked from commit 4f8a155192)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
jira: https://issues.apache.org/jira/browse/SPARK-7475
Add a new argument to specify the algorithm applied to LDA, to exhibit the basic usage of LDAOptimizer.
cc jkbradley
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes#6000 from hhbyyh/ldaExample and squashes the following commits:
0a7e2bc [Yuhao Yang] fix according to comments
5810b0f [Yuhao Yang] adjust ldaExample for online LDA
(cherry picked from commit b13162b364)
Signed-off-by: Joseph K. Bradley <joseph@databricks.com>
Otherwise it will throw exception:
```
Exception in thread "main" kafka.common.FailedToSendMessageException: Failed to send messages after 3 tries.
at kafka.producer.async.DefaultEventHandler.handle(DefaultEventHandler.scala:90)
at kafka.producer.Producer.send(Producer.scala:77)
at org.apache.spark.examples.streaming.KafkaWordCountProducer$.main(KafkaWordCount.scala:96)
at org.apache.spark.examples.streaming.KafkaWordCountProducer.main(KafkaWordCount.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:623)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:169)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:192)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:111)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
```
Author: jerryshao <saisai.shao@intel.com>
Closes#5936 from jerryshao/SPARK-7396 and squashes the following commits:
270bbe2 [jerryshao] Fix Kafka Produce throw Exception issue
(cherry picked from commit 316a5c0423)
Signed-off-by: Tathagata Das <tathagata.das1565@gmail.com>
This PR also makes some of the DataFrame to RDD methods private as the RDD class is private in 1.4
cc rxin pwendell
Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Closes#5949 from shivaram/sparkr-examples and squashes the following commits:
6c42fdc [Shivaram Venkataraman] Remove SparkR RDD examples, add dataframe examples
(cherry picked from commit 4e930420c1)
Signed-off-by: Reynold Xin <rxin@databricks.com>
The following items are added to Python kmeans:
kmeans - setEpsilon, setInitializationSteps
KMeansModel - computeCost, k
Author: Hrishikesh Subramonian <hrishikesh.subramonian@flytxt.com>
Closes#5647 from FlytxtRnD/newPyKmeansAPI and squashes the following commits:
b9e451b [Hrishikesh Subramonian] set seed to fixed value in doc test
5fd3ced [Hrishikesh Subramonian] doc test corrections
20b3c68 [Hrishikesh Subramonian] python 3 fixes
4d4e695 [Hrishikesh Subramonian] added arguments in python tests
21eb84c [Hrishikesh Subramonian] Python Kmeans - setEpsilon, setInitializationSteps, k and computeCost added.
(cherry picked from commit 5995ada96b)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
This PR added `copy(extra: ParamMap): Params` to `Params`, which makes a copy of the current instance with a randomly generated uid and some extra param values. With this change, we only need to implement `fit` and `transform` without extra param values given the default implementation of `fit(dataset, extra)`:
~~~scala
def fit(dataset: DataFrame, extra: ParamMap): Model = {
copy(extra).fit(dataset)
}
~~~
Inside `fit` and `transform`, since only the embedded values are used, I added `$` as an alias for `getOrDefault` to make the code easier to read. For example, in `LinearRegression.fit` we have:
~~~scala
val effectiveRegParam = $(regParam) / yStd
val effectiveL1RegParam = $(elasticNetParam) * effectiveRegParam
val effectiveL2RegParam = (1.0 - $(elasticNetParam)) * effectiveRegParam
~~~
Meta-algorithm like `Pipeline` implements its own `copy(extra)`. So the fitted pipeline model stored all copied stages (no matter whether it is a transformer or a model).
Other changes:
* `Params$.inheritValues` is moved to `Params!.copyValues` and returns the target instance.
* `fittingParamMap` was removed because the `parent` carries this information.
* `validate` was renamed to `validateParams` to be more precise.
TODOs:
* [x] add tests for newly added methods
* [ ] update documentation
jkbradley dbtsai
Author: Xiangrui Meng <meng@databricks.com>
Closes#5820 from mengxr/SPARK-5956 and squashes the following commits:
7bef88d [Xiangrui Meng] address comments
05229c3 [Xiangrui Meng] assert -> assertEquals
b2927b1 [Xiangrui Meng] organize imports
f14456b [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-5956
93e7924 [Xiangrui Meng] add tests for hasParam & copy
463ecae [Xiangrui Meng] merge master
2b954c3 [Xiangrui Meng] update Binarizer
465dd12 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-5956
282a1a8 [Xiangrui Meng] fix test
819dd2d [Xiangrui Meng] merge master
b642872 [Xiangrui Meng] example code runs
5a67779 [Xiangrui Meng] examples compile
c76b4d1 [Xiangrui Meng] fix all unit tests
0f4fd64 [Xiangrui Meng] fix some tests
9286a22 [Xiangrui Meng] copyValues to trained models
53e0973 [Xiangrui Meng] move inheritValues to Params and rename it to copyValues
9ee004e [Xiangrui Meng] merge copy and copyWith; rename validate to validateParams
d882afc [Xiangrui Meng] test compile
f082a31 [Xiangrui Meng] make Params copyable and simply handling of extra params in all spark.ml components
(cherry picked from commit e0833c5958)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
Main change: Added isValid field to Param. Modified all usages to use isValid when relevant. Added helper methods in ParamValidate.
Also overrode Params.validate() in:
* CrossValidator + model
* Pipeline + model
I made a few updates for the elastic net patch:
* I changed "tol" to "convergenceTol"
* I added some documentation
This PR is Scala + Java only. Python will be in a follow-up PR.
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#5740 from jkbradley/enforce-validate and squashes the following commits:
ad9c6c1 [Joseph K. Bradley] re-generated sharedParams after merging with current master
76415e8 [Joseph K. Bradley] reverted convergenceTol to tol
af62f4b [Joseph K. Bradley] Removed changes to SparkBuild, python linalg. Fixed test failures. Renamed ParamValidate to ParamValidators. Removed explicit type from ParamValidators calls where possible.
bb2665a [Joseph K. Bradley] merged with elastic net pr
ecda302 [Joseph K. Bradley] fix rat tests, plus add a little doc
6895dfc [Joseph K. Bradley] small cleanups
069ac6d [Joseph K. Bradley] many cleanups
928fb84 [Joseph K. Bradley] Maybe done
a910ac7 [Joseph K. Bradley] still workin
6d60e2e [Joseph K. Bradley] Still workin
b987319 [Joseph K. Bradley] Partly done with adding checks, but blocking on adding checking functionality to Param
dbc9fb2 [Joseph K. Bradley] merged with master. enforcing Params.validate
I've added an interface to JavaUtils to do byte conversion and added hooks within Utils.scala to handle conversion within Spark code (like for time strings). I've added matching tests for size conversion, and then updated all deprecated configs and documentation as per SPARK-5933.
Author: Ilya Ganelin <ilya.ganelin@capitalone.com>
Closes#5574 from ilganeli/SPARK-5932 and squashes the following commits:
11f6999 [Ilya Ganelin] Nit fixes
49a8720 [Ilya Ganelin] Whitespace fix
2ab886b [Ilya Ganelin] Scala style
fc85733 [Ilya Ganelin] Got rid of floating point math
852a407 [Ilya Ganelin] [SPARK-5932] Added much improved overflow handling. Can now handle sizes up to Long.MAX_VALUE Petabytes instead of being capped at Long.MAX_VALUE Bytes
9ee779c [Ilya Ganelin] Simplified fraction matches
22413b1 [Ilya Ganelin] Made MAX private
3dfae96 [Ilya Ganelin] Fixed some nits. Added automatic conversion of old paramter for kryoserializer.mb to new values.
e428049 [Ilya Ganelin] resolving merge conflict
8b43748 [Ilya Ganelin] Fixed error in pattern matching for doubles
84a2581 [Ilya Ganelin] Added smoother handling of fractional values for size parameters. This now throws an exception and added a warning for old spark.kryoserializer.buffer
d3d09b6 [Ilya Ganelin] [SPARK-5932] Fixing error in KryoSerializer
fe286b4 [Ilya Ganelin] Resolved merge conflict
c7803cd [Ilya Ganelin] Empty lines
54b78b4 [Ilya Ganelin] Simplified byteUnit class
69e2f20 [Ilya Ganelin] Updates to code
f32bc01 [Ilya Ganelin] [SPARK-5932] Fixed error in API in SparkConf.scala where Kb conversion wasn't being done properly (was Mb). Added test cases for both timeUnit and ByteUnit conversion
f15f209 [Ilya Ganelin] Fixed conversion of kryo buffer size
0f4443e [Ilya Ganelin] Merge remote-tracking branch 'upstream/master' into SPARK-5932
35a7fa7 [Ilya Ganelin] Minor formatting
928469e [Ilya Ganelin] [SPARK-5932] Converted some longs to ints
5d29f90 [Ilya Ganelin] [SPARK-5932] Finished documentation updates
7a6c847 [Ilya Ganelin] [SPARK-5932] Updated spark.shuffle.file.buffer
afc9a38 [Ilya Ganelin] [SPARK-5932] Updated spark.broadcast.blockSize and spark.storage.memoryMapThreshold
ae7e9f6 [Ilya Ganelin] [SPARK-5932] Updated spark.io.compression.snappy.block.size
2d15681 [Ilya Ganelin] [SPARK-5932] Updated spark.executor.logs.rolling.size.maxBytes
1fbd435 [Ilya Ganelin] [SPARK-5932] Updated spark.broadcast.blockSize
eba4de6 [Ilya Ganelin] [SPARK-5932] Updated spark.shuffle.file.buffer.kb
b809a78 [Ilya Ganelin] [SPARK-5932] Updated spark.kryoserializer.buffer.max
0cdff35 [Ilya Ganelin] [SPARK-5932] Updated to use bibibytes in method names. Updated spark.kryoserializer.buffer.mb and spark.reducer.maxMbInFlight
475370a [Ilya Ganelin] [SPARK-5932] Simplified ByteUnit code, switched to using longs. Updated docs to clarify that we use kibi, mebi etc instead of kilo, mega
851d691 [Ilya Ganelin] [SPARK-5932] Updated memoryStringToMb to use new interfaces
a9f4fcf [Ilya Ganelin] [SPARK-5932] Added unit tests for unit conversion
747393a [Ilya Ganelin] [SPARK-5932] Added unit tests for ByteString conversion
09ea450 [Ilya Ganelin] [SPARK-5932] Added byte string conversion to Jav utils
5390fd9 [Ilya Ganelin] Merge remote-tracking branch 'upstream/master' into SPARK-5932
db9a963 [Ilya Ganelin] Closing second spark context
1dc0444 [Ilya Ganelin] Added ref equality check
8c884fa [Ilya Ganelin] Made getOrCreate synchronized
cb0c6b7 [Ilya Ganelin] Doc updates and code cleanup
270cfe3 [Ilya Ganelin] [SPARK-6703] Documentation fixes
15e8dea [Ilya Ganelin] Updated comments and added MiMa Exclude
0e1567c [Ilya Ganelin] Got rid of unecessary option for AtomicReference
dfec4da [Ilya Ganelin] Changed activeContext to AtomicReference
733ec9f [Ilya Ganelin] Fixed some bugs in test code
8be2f83 [Ilya Ganelin] Replaced match with if
e92caf7 [Ilya Ganelin] [SPARK-6703] Added test to ensure that getOrCreate both allows creation, retrieval, and a second context if desired
a99032f [Ilya Ganelin] Spacing fix
d7a06b8 [Ilya Ganelin] Updated SparkConf class to add getOrCreate method. Started test suite implementation
Currently only added `createDirectStream` API, I'm not sure if `createRDD` is also needed, since some Java object needs to be wrapped in Python. Please help to review, thanks a lot.
Author: jerryshao <saisai.shao@intel.com>
Author: Saisai Shao <saisai.shao@intel.com>
Closes#4723 from jerryshao/direct-kafka-python-api and squashes the following commits:
a1fe97c [jerryshao] Fix rebase issue
eebf333 [jerryshao] Address the comments
da40f4e [jerryshao] Fix Python 2.6 Syntax error issue
5c0ee85 [jerryshao] Style fix
4aeac18 [jerryshao] Fix bug in example code
7146d86 [jerryshao] Add unit test
bf3bdd6 [jerryshao] Add more APIs and address the comments
f5b3801 [jerryshao] Small style fix
8641835 [Saisai Shao] Rebase and update the code
589c05b [Saisai Shao] Fix the style
d6fcb6a [Saisai Shao] Address the comments
dfda902 [Saisai Shao] Style fix
0f7d168 [Saisai Shao] Add the doc and fix some style issues
67e6880 [Saisai Shao] Fix test bug
917b0db [Saisai Shao] Add Python createRDD API for Kakfa direct stream
c3fc11d [jerryshao] Modify the docs
2c00936 [Saisai Shao] address the comments
3360f44 [jerryshao] Fix code style
e0e0f0d [jerryshao] Code clean and bug fix
338c41f [Saisai Shao] Add python API and example for direct kafka stream
jira: https://issues.apache.org/jira/browse/SPARK-7090
LDA was implemented with extensibility in mind. And with the development of OnlineLDA and Gibbs Sampling, we are collecting more detailed requirements from different algorithms.
As Joseph Bradley jkbradley proposed in https://github.com/apache/spark/pull/4807 and with some further discussion, we'd like to adjust the code structure a little to present the common interface and extension point clearly.
Basically class LDA would be a common entrance for LDA computing. And each LDA object will refer to a LDAOptimizer for the concrete algorithm implementation. Users can customize LDAOptimizer with specific parameters and assign it to LDA.
Concrete changes:
1. Add a trait `LDAOptimizer`, which defines the common iterface for concrete implementations. Each subClass is a wrapper for a specific LDA algorithm.
2. Move EMOptimizer to file LDAOptimizer and inherits from LDAOptimizer, rename to EMLDAOptimizer. (in case a more generic EMOptimizer comes in the future)
-adjust the constructor of EMOptimizer, since all the parameters should be passed in through initialState method. This can avoid unwanted confusion or overwrite.
-move the code from LDA.initalState to initalState of EMLDAOptimizer
3. Add property ldaOptimizer to LDA and its getter/setter, and EMLDAOptimizer is the default Optimizer.
4. Change the return type of LDA.run from DistributedLDAModel to LDAModel.
Further work:
add OnlineLDAOptimizer and other possible Optimizers once ready.
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes#5661 from hhbyyh/ldaRefactor and squashes the following commits:
0e2e006 [Yuhao Yang] respond to review comments
08a45da [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into ldaRefactor
e756ce4 [Yuhao Yang] solve mima exception
d74fd8f [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into ldaRefactor
0bb8400 [Yuhao Yang] refactor LDA with Optimizer
ec2f857 [Yuhao Yang] protoptype for discussion
....py
Author: tedyu <yuzhihong@gmail.com>
Closes#5673 from tedyu/master and squashes the following commits:
ab7c72b [tedyu] SPARK-7107 Adjust indentation to pass Python style tests
6e25939 [tedyu] Adjust line length to be shorter than 100 characters
18d172a [tedyu] SPARK-7107 Add parameter for zookeeper.znode.parent to hbase_inputformat.py
This is a continuation of [https://github.com/apache/spark/pull/5530] (which was for Decision Trees), but for ensembles: Random Forests and Gradient-Boosted Trees. Please refer to the JIRA [https://issues.apache.org/jira/browse/SPARK-6113], the design doc linked from the JIRA, and the previous PR linked above for design discussions.
This PR follows the example set by the previous PR for Decision Trees. It includes a few cleanups to Decision Trees.
Note: There is one issue which will be addressed in a separate PR: Ensembles' component Models have no parent or fittingParamMap. I plan to submit a separate PR which makes those values in Model be Options. It does not matter much which PR gets merged first.
CC: mengxr manishamde codedeft chouqin
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#5626 from jkbradley/dt-api-ensembles and squashes the following commits:
729167a [Joseph K. Bradley] small cleanups based on code review
bbae2a2 [Joseph K. Bradley] Updated per all comments in code review
855aa9a [Joseph K. Bradley] scala style fix
ea3d901 [Joseph K. Bradley] Added GBT to spark.ml, with tests and examples
c0f30c1 [Joseph K. Bradley] Added random forests and test suites to spark.ml. Not tested yet. Need to add example as well
d045ebd [Joseph K. Bradley] some more updates, but far from done
ee1a10b [Joseph K. Bradley] Added files from old PR and did some initial updates.
To run Spark, default will read file from HDFS if we don't set the schema.
Author: linweizhong <linweizhong@huawei.com>
Closes#5684 from Sephiroth-Lin/pyspark_example_minor and squashes the following commits:
19fe145 [linweizhong] Update example sql.py, so that can read file correctly
This is a reopening of #4867.
A short summary of the issues resolved from the previous PR:
1. HTTPClient version mismatch: Selenium (used for UI tests) requires version 4.3.x, and Tachyon included 4.2.5 through a transitive dependency of its shaded thrift jar. To address this, Tachyon 0.6.3 will promote the transitive dependencies of the shaded jar so they can be excluded in spark.
2. Jackson-Mapper-ASL version mismatch: In lower versions of hadoop-client (ie. 1.0.4), version 1.0.1 is included. The parquet library used in spark sql requires version 1.8+. Its unclear to me why upgrading tachyon-client would cause this dependency to break. The solution was to exclude jackson-mapper-asl from hadoop-client.
It seems that the dependency management in spark-parent will not work on transitive dependencies, one way to make sure jackson-mapper-asl is included with the correct version is to add it as a top level dependency. The best solution would be to exclude the dependency in the modules which require a higher version, but that did not fix the unit tests. Any suggestions on the best way to solve this would be appreciated!
Author: Calvin Jia <jia.calvin@gmail.com>
Closes#5354 from calvinjia/upgrade_tachyon_0.6.3 and squashes the following commits:
0eefe4d [Calvin Jia] Handle httpclient version in maven dependency management. Remove httpclient version setting from profiles.
7c00dfa [Calvin Jia] Set httpclient version to 4.3.2 for selenium. Specify version of httpclient for sql/hive (previously 4.2.5 transitive dependency of libthrift).
9263097 [Calvin Jia] Merge master to test latest changes
dbfc1bd [Calvin Jia] Use Tachyon 0.6.4 for cleaner dependencies.
e2ff80a [Calvin Jia] Exclude the jetty and curator promoted dependencies from tachyon-client.
a3a29da [Calvin Jia] Update tachyon-client exclusions.
0ae6c97 [Calvin Jia] Change tachyon version to 0.6.3
a204df9 [Calvin Jia] Update make distribution tachyon version.
a93c94f [Calvin Jia] Exclude jackson-mapper-asl from hadoop client since it has a lower version than spark's expected version.
a8a923c [Calvin Jia] Exclude httpcomponents from Tachyon
910fabd [Calvin Jia] Update to master
eed9230 [Calvin Jia] Update tachyon version to 0.6.1.
11907b3 [Calvin Jia] Use TachyonURI for tachyon paths instead of strings.
71bf441 [Calvin Jia] Upgrade Tachyon client version to 0.6.0.
Author: Prabeesh K <prabeesh.k@namshi.com>
Closes#5653 from prabeesh/fix and squashes the following commits:
9d7a9f5 [Prabeesh K] fixed scala string interpolation error
This does a few clean-ups. With this PR, all spark.ml tree components have ```private[ml]``` constructors.
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#5567 from jkbradley/dt-api-dt2 and squashes the following commits:
2263b5b [Joseph K. Bradley] Added note about tree example issue.
bb9f610 [Joseph K. Bradley] Small cleanups after original tree API PR
It should load from `testInput` instead of `input` for test data.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#5594 from viirya/use_testinput and squashes the following commits:
5e8b174 [Liang-Chi Hsieh] Fix style.
b60b475 [Liang-Chi Hsieh] Use testInput.
This is a PR for cleaning up and finalizing the DecisionTree API. PRs for ensembles will follow once this is merged.
### Goal
Here is the description copied from the JIRA (for both trees and ensembles):
> **Issue**: The APIs for DecisionTree and ensembles (RandomForests and GradientBoostedTrees) have been experimental for a long time. The API has become very convoluted because trees and ensembles have many, many variants, some of which we have added incrementally without a long-term design.
> **Proposal**: This JIRA is for discussing changes required to finalize the APIs. After we discuss, I will make a PR to update the APIs and make them non-Experimental. This will require making many breaking changes; see the design doc for details.
> **[Design doc](https://docs.google.com/document/d/1rJ_DZinyDG3PkYkAKSsQlY0QgCeefn4hUv7GsPkzBP4)** : This outlines current issues and the proposed API.
Overall code layout:
* The old API in mllib.tree.* will remain the same.
* The new API will reside in ml.classification.* and ml.regression.*
### Summary of changes
Old API
* Exactly the same, except I made 1 method in Loss private (but that is not a breaking change since that method was introduced after the Spark 1.3 release).
New APIs
* Under Pipeline API
* The new API preserves functionality, except:
* New API does NOT store prob (probability of label in classification). I want to have it store the full vector of probabilities but feel that should be in a later PR.
* Use abstractions for parameters, estimators, and models to avoid code duplication
* Limit parameters to relevant algorithms
* For enum-like types, only expose Strings
* We can make these pluggable later on by adding new parameters. That is a far-future item.
Test suites
* I organized DecisionTreeSuite, but I made absolutely no changes to the tests themselves.
* The test suites for the new API only test (a) similarity with the results of the old API and (b) elements of the new API.
* After code is moved to this new API, we should move the tests from the old suites which test the internals.
### Details
#### Changed names
Parameters
* useNodeIdCache -> cacheNodeIds
#### Other changes
* Split: Changed categories to set instead of list
#### Non-decision tree changes
* AttributeGroup
* Added parentheses to toMetadata, toStructField methods (These were removed in a previous PR, but I ran into 1 issue with the Scala compiler not being able to disambiguate between a toMetadata method with no parentheses and a toMetadata method which takes 1 argument.)
* Attributes
* Renamed: toMetadata -> toMetadataImpl
* Added toMetadata methods which return ML metadata (keyed with “ML_ATTR”)
* NominalAttribute: Added getNumValues method which examines both numValues and values.
* Params.inheritValues: Checks whether the parent param really belongs to the child (to allow Estimator-Model pairs with different sets of parameters)
### Questions for reviewers
* Is "DecisionTreeClassificationModel" too long a name?
* Is this OK in the docs?
```
class DecisionTreeRegressor extends TreeRegressor[DecisionTreeRegressionModel] with DecisionTreeParams[DecisionTreeRegressor] with TreeRegressorParams[DecisionTreeRegressor]
```
### Future
We should open up the abstractions at some point. E.g., it would be useful to be able to set tree-related parameters in 1 place and then pass those to multiple tree-based algorithms.
Follow-up JIRAs will be (in this order):
* Tree ensembles
* Deprecate old tree code
* Move DecisionTree implementation code to new API.
* Move tests from the old suites which test the internals.
* Update programming guide
* Python API
* Change RandomForest* to always use bootstrapping, even when numTrees = 1
* Provide the probability of the predicted label for classification. After we move code to the new API and update it to maintain probabilities for all labels, then we can add the probabilities to the new API.
CC: mengxr manishamde codedeft chouqin MechCoder
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#5530 from jkbradley/dt-api-dt and squashes the following commits:
6aae255 [Joseph K. Bradley] Changed tree abstractions not to take type parameters, and for setters to return this.type instead
ec17947 [Joseph K. Bradley] Updates based on code review. Main changes were: moving public types from ml.impl.tree to ml.tree, modifying CategoricalSplit to take an Array of categories but store a Set internally, making more types sealed or final
5626c81 [Joseph K. Bradley] style fixes
f8fbd24 [Joseph K. Bradley] imported reorg of DecisionTreeSuite from old PR. small cleanups
7ef63ed [Joseph K. Bradley] Added DecisionTreeRegressor, test suites, and example (for real this time)
e11673f [Joseph K. Bradley] Added DecisionTreeRegressor, test suites, and example
119f407 [Joseph K. Bradley] added DecisionTreeClassifier example
0bdc486 [Joseph K. Bradley] fixed issues after param PR was merged
f9fbb60 [Joseph K. Bradley] Done with DecisionTreeClassifier, but no save/load yet. Need to add example as well
2532c9a [Joseph K. Bradley] partial move to spark.ml API, not done yet
c72c1a0 [Joseph K. Bradley] Copied changes for common items, plus DecisionTreeClassifier from original PR
This PR update PySpark to support Python 3 (tested with 3.4).
Known issue: unpickle array from Pyrolite is broken in Python 3, those tests are skipped.
TODO: ec2/spark-ec2.py is not fully tested with python3.
Author: Davies Liu <davies@databricks.com>
Author: twneale <twneale@gmail.com>
Author: Josh Rosen <joshrosen@databricks.com>
Closes#5173 from davies/python3 and squashes the following commits:
d7d6323 [Davies Liu] fix tests
6c52a98 [Davies Liu] fix mllib test
99e334f [Davies Liu] update timeout
b716610 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
cafd5ec [Davies Liu] adddress comments from @mengxr
bf225d7 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
179fc8d [Davies Liu] tuning flaky tests
8c8b957 [Davies Liu] fix ResourceWarning in Python 3
5c57c95 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
4006829 [Davies Liu] fix test
2fc0066 [Davies Liu] add python3 path
71535e9 [Davies Liu] fix xrange and divide
5a55ab4 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
125f12c [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
ed498c8 [Davies Liu] fix compatibility with python 3
820e649 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
e8ce8c9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
ad7c374 [Davies Liu] fix mllib test and warning
ef1fc2f [Davies Liu] fix tests
4eee14a [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
20112ff [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
59bb492 [Davies Liu] fix tests
1da268c [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
ca0fdd3 [Davies Liu] fix code style
9563a15 [Davies Liu] add imap back for python 2
0b1ec04 [Davies Liu] make python examples work with Python 3
d2fd566 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
a716d34 [Davies Liu] test with python 3.4
f1700e8 [Davies Liu] fix test in python3
671b1db [Davies Liu] fix test in python3
692ff47 [Davies Liu] fix flaky test
7b9699f [Davies Liu] invalidate import cache for Python 3.3+
9c58497 [Davies Liu] fix kill worker
309bfbf [Davies Liu] keep compatibility
5707476 [Davies Liu] cleanup, fix hash of string in 3.3+
8662d5b [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
f53e1f0 [Davies Liu] fix tests
70b6b73 [Davies Liu] compile ec2/spark_ec2.py in python 3
a39167e [Davies Liu] support customize class in __main__
814c77b [Davies Liu] run unittests with python 3
7f4476e [Davies Liu] mllib tests passed
d737924 [Davies Liu] pass ml tests
375ea17 [Davies Liu] SQL tests pass
6cc42a9 [Davies Liu] rename
431a8de [Davies Liu] streaming tests pass
78901a7 [Davies Liu] fix hash of serializer in Python 3
24b2f2e [Davies Liu] pass all RDD tests
35f48fe [Davies Liu] run future again
1eebac2 [Davies Liu] fix conflict in ec2/spark_ec2.py
6e3c21d [Davies Liu] make cloudpickle work with Python3
2fb2db3 [Josh Rosen] Guard more changes behind sys.version; still doesn't run
1aa5e8f [twneale] Turned out `pickle.DictionaryType is dict` == True, so swapped it out
7354371 [twneale] buffer --> memoryview I'm not super sure if this a valid change, but the 2.7 docs recommend using memoryview over buffer where possible, so hoping it'll work.
b69ccdf [twneale] Uses the pure python pickle._Pickler instead of c-extension _pickle.Pickler. It appears pyspark 2.7 uses the pure python pickler as well, so this shouldn't degrade pickling performance (?).
f40d925 [twneale] xrange --> range
e104215 [twneale] Replaces 2.7 types.InstsanceType with 3.4 `object`....could be horribly wrong depending on how types.InstanceType is used elsewhere in the package--see http://bugs.python.org/issue8206
79de9d0 [twneale] Replaces python2.7 `file` with 3.4 _io.TextIOWrapper
2adb42d [Josh Rosen] Fix up some import differences between Python 2 and 3
854be27 [Josh Rosen] Run `futurize` on Python code:
7c5b4ce [Josh Rosen] Remove Python 3 check in shell.py.
Tiny bug in PowerIterationClusteringExample in which radius not accepted from command line
Author: sboeschhuawei <stephen.boesch@huawei.com>
Closes#5531 from javadba/picsub and squashes the following commits:
2aab8cf [sboeschhuawei] Fixed bug in PICExample in which the radius were not being accepted on command line
