Added a bunch of tags.
Also changed parquetFile to take varargs rather than a string followed by varargs.
Author: Reynold Xin <rxin@databricks.com>
Closes#4636 from rxin/df-doc and squashes the following commits:
651f80c [Reynold Xin] Fixed parquetFile in PySpark.
8dc3024 [Reynold Xin] [SQL] Various DataFrame doc changes.
I created a patch that disables the environment variables.
Thereby scala or python shell log a warning message to notify user about the deprecation
with the following message:
scala: "ADD_JARS environment variable is deprecated, use --jar spark submit argument instead"
python: "Warning: ADD_FILES environment variable is deprecated, use --py-files argument instead"
Is it what is expected or the code associated with the variables should be just completely removed?
Should it be somewhere documented?
Author: azagrebin <azagrebin@gmail.com>
Closes#4616 from azagrebin/master and squashes the following commits:
bab1aa9 [azagrebin] [SPARK-3340] Deprecate ADD_JARS and ADD_FILES: minor readability issue
0643895 [azagrebin] [SPARK-3340] Deprecate ADD_JARS and ADD_FILES: add warning messages
42f0107 [azagrebin] [SPARK-3340] Deprecate ADD_JARS and ADD_FILES
This patch changes PySpark so that the GatewayServer's port is communicated back to the Python process that launches it over a local socket instead of a pipe. The old pipe-based approach was brittle and could fail if `spark-submit` printed unexpected to stdout.
To accomplish this, I wrote a custom `PythonGatewayServer.main()` function to use in place of Py4J's `GatewayServer.main()`.
Closes#3424.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#4603 from JoshRosen/SPARK-2313 and squashes the following commits:
6a7740b [Josh Rosen] Remove EchoOutputThread since it's no longer needed
0db501f [Josh Rosen] Use select() so that we don't block if GatewayServer dies.
9bdb4b6 [Josh Rosen] Handle case where getListeningPort returns -1
3fb7ed1 [Josh Rosen] Remove stdout=PIPE
2458934 [Josh Rosen] Use underscore to mark env var. as private
d12c95d [Josh Rosen] Use Logging and Utils.tryOrExit()
e5f9730 [Josh Rosen] Wrap everything in a giant try-block
2f70689 [Josh Rosen] Use stdin PIPE to share fate with driver
8bf956e [Josh Rosen] Initial cut at passing Py4J gateway port back to driver via socket
This PR allow Python users to set params in constructors and in setParams, where we use decorator `keyword_only` to force keyword arguments. The trade-off is discussed in the design doc of SPARK-4586.
Generated doc:
CC: davies rxin
Author: Xiangrui Meng <meng@databricks.com>
Closes#4564 from mengxr/py-pipeline-kw and squashes the following commits:
fedf720 [Xiangrui Meng] use toDF
d565f2c [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into py-pipeline-kw
cbc15d3 [Xiangrui Meng] fix style
5032097 [Xiangrui Meng] update pipeline signature
950774e [Xiangrui Meng] simplify keyword_only and update constructor/setParams signatures
fdde5fc [Xiangrui Meng] fix style
c9384b8 [Xiangrui Meng] fix sphinx doc
8e59180 [Xiangrui Meng] add setParams and make constructors take params, where we force keyword args
Author: Yin Huai <yhuai@databricks.com>
Closes#4542 from yhuai/moveSaveMode and squashes the following commits:
65a4425 [Yin Huai] Move SaveMode to sql package.
There a bunch of logging coming from driver and worker, it's noisy and scaring, and a lots of exception in it, people are confusing about the tests are failing or not.
This PR will mute the logging during tests, only show them if any one failed.
Author: Davies Liu <davies@databricks.com>
Closes#4572 from davies/mute and squashes the following commits:
1e9069c [Davies Liu] mute the logging during python tests
1. DataFrame.renameColumn
2. DataFrame.show() and _repr_
3. Use simpleString() rather than jsonValue in DataFrame.dtypes
4. createDataFrame from local Python data, including pandas.DataFrame
Author: Davies Liu <davies@databricks.com>
Closes#4528 from davies/df3 and squashes the following commits:
014acea [Davies Liu] fix typo
6ba526e [Davies Liu] fix tests
46f5f95 [Davies Liu] address comments
6cbc154 [Davies Liu] dataframe.show() and improve dtypes
6f94f25 [Davies Liu] create DataFrame from local Python data
Deprecate inferSchema() and applySchema(), use createDataFrame() instead, which could take an optional `schema` to create an DataFrame from an RDD. The `schema` could be StructType or list of names of columns.
Author: Davies Liu <davies@databricks.com>
Closes#4498 from davies/create and squashes the following commits:
08469c1 [Davies Liu] remove Scala/Java API for now
c80a7a9 [Davies Liu] fix hive test
d1bd8f2 [Davies Liu] cleanup applySchema
9526e97 [Davies Liu] createDataFrame from RDD with columns
Author: Michael Armbrust <michael@databricks.com>
Closes#4436 from marmbrus/dfToString and squashes the following commits:
8a3c35f [Michael Armbrust] Merge remote-tracking branch 'origin/master' into dfToString
b72a81b [Michael Armbrust] add toString
```
pyspark.sql.DataFrame.to_pandas = to_pandas(self) unbound pyspark.sql.DataFrame method
Collect all the rows and return a `pandas.DataFrame`.
>>> df.to_pandas() # doctest: +SKIP
age name
0 2 Alice
1 5 Bob
pyspark.sql.Column.to_pandas = to_pandas(self) unbound pyspark.sql.Column method
Return a pandas.Series from the column
>>> df.age.to_pandas() # doctest: +SKIP
0 2
1 5
dtype: int64
```
Not tests by jenkins (they depends on pandas)
Author: Davies Liu <davies@databricks.com>
Closes#4476 from davies/to_pandas and squashes the following commits:
6276fb6 [Davies Liu] Convert DataFrame to pandas.DataFrame and Series
See https://issues.apache.org/jira/browse/SPARK-5633 for details
Author: Vladimir Vladimirov <vladimir.vladimirov@magnetic.com>
Closes#4403 from smartkiwi/master and squashes the following commits:
94c014e [Vladimir Vladimirov] SPARK-5633 pyspark saveAsTextFile support for compression codec
This PR adds three major improvements to Parquet data source:
1. Partition discovery
While reading Parquet files resides in Hive style partition directories, `ParquetRelation2` automatically discovers partitioning information and infers partition column types.
This is also a partial work for [SPARK-5182] [1], which aims to provide first class partitioning support for the data source API. Related code in this PR can be easily extracted to the data source API level in future versions.
1. Schema merging
When enabled, Parquet data source collects schema information from all Parquet part-files and tries to merge them. Exceptions are thrown when incompatible schemas are detected. This feature is controlled by data source option `parquet.mergeSchema`, and is enabled by default.
1. Metastore Parquet table conversion moved to analysis phase
This greatly simplifies the conversion logic. `ParquetConversion` strategy can be removed once the old Parquet implementation is removed in the future.
This version of Parquet data source aims to entirely replace the old Parquet implementation. However, the old version hasn't been removed yet. Users can fall back to the old version by turning off SQL configuration `spark.sql.parquet.useDataSourceApi`.
Other JIRA tickets fixed as side effects in this PR:
- [SPARK-5509] [3]: `EqualTo` now uses a proper `Ordering` to compare binary types.
- [SPARK-3575] [4]: Metastore schema is now preserved and passed to `ParquetRelation2` via data source option `parquet.metastoreSchema`.
TODO:
- [ ] More test cases for partition discovery
- [x] Fix write path after data source write support (#4294) is merged
It turned out to be non-trivial to fall back to old Parquet implementation on the write path when Parquet data source is enabled. Since we're planning to include data source write support in 1.3.0, I simply ignored two test cases involving Parquet insertion for now.
- [ ] Fix outdated comments and documentations
PS: This PR looks big, but more than a half of the changed lines in this PR are trivial changes to test cases. To test Parquet with and without the new data source, almost all Parquet test cases are moved into wrapper driver functions. This introduces hundreds of lines of changes.
[1]: https://issues.apache.org/jira/browse/SPARK-5182
[2]: https://issues.apache.org/jira/browse/SPARK-5528
[3]: https://issues.apache.org/jira/browse/SPARK-5509
[4]: https://issues.apache.org/jira/browse/SPARK-3575
<!-- Reviewable:start -->
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Author: Cheng Lian <lian@databricks.com>
Closes#4308 from liancheng/parquet-partition-discovery and squashes the following commits:
b6946e6 [Cheng Lian] Fixes MiMA issues, addresses comments
8232e17 [Cheng Lian] Write support for Parquet data source
a49bd28 [Cheng Lian] Fixes spelling typo in trait name "CreateableRelationProvider"
808380f [Cheng Lian] Fixes issues introduced while rebasing
50dd8d1 [Cheng Lian] Addresses @rxin's comment, fixes UDT schema merging
adf2aae [Cheng Lian] Fixes compilation error introduced while rebasing
4e0175f [Cheng Lian] Fixes Python Parquet API, we need Py4J array to call varargs method
0d8ec1d [Cheng Lian] Adds more test cases
b35c8c6 [Cheng Lian] Fixes some typos and outdated comments
dd704fd [Cheng Lian] Fixes Python Parquet API
596c312 [Cheng Lian] Uses switch to control whether use Parquet data source or not
7d0f7a2 [Cheng Lian] Fixes Metastore Parquet table conversion
a1896c7 [Cheng Lian] Fixes all existing Parquet test suites except for ParquetMetastoreSuite
5654c9d [Cheng Lian] Draft version of Parquet partition discovery and schema merging
1. Removed LocalHiveContext in Python.
2. Reduced DSL UDF support from 22 arguments to 10 arguments so JavaDoc/ScalaDoc look nicer.
Author: Reynold Xin <rxin@databricks.com>
Closes#4374 from rxin/df-style and squashes the following commits:
e493342 [Reynold Xin] [SQL][DataFrame] Minor cleanup.
Author: Reynold Xin <rxin@databricks.com>
Closes#4376 from rxin/SPARK-5605 and squashes the following commits:
c55f5fa [Reynold Xin] Added a Python test.
f4b8dbb [Reynold Xin] [SPARK-5605][SQL][DF] Allow using String to specify colum name in DSL aggregate functions.
Add a seed for tests.
Author: Davies Liu <davies@databricks.com>
Closes#4358 from davies/flaky_test and squashes the following commits:
02371c3 [Davies Liu] Merge branch 'master' of github.com:apache/spark into flaky_test
ced499b [Davies Liu] add seed for test
Added `awaitTerminationOrTimeout` to return if the waiting time elapsed:
* `true` if it's stopped.
* `false` if the waiting time elapsed before returning from the method.
* throw the reported error if it's thrown during the execution.
Also deprecated `awaitTermination(timeout: Long)`.
Author: zsxwing <zsxwing@gmail.com>
Closes#4171 from zsxwing/SPARK-5379 and squashes the following commits:
c9e660b [zsxwing] Add a unit test for awaitTerminationOrTimeout
8a89f92 [zsxwing] Add awaitTerminationOrTimeout to python
cdc820b [zsxwing] Add awaitTerminationOrTimeout
In Spark 1.2 we added a `binaryRecords` input method for loading flat binary data. This format is useful for numerical array data, e.g. in scientific computing applications. This PR adds support for the same format in Streaming applications, where it is similarly useful, especially for streaming time series or sensor data.
Summary of additions
- adding `binaryRecordsStream` to Spark Streaming
- exposing `binaryRecordsStream` in the new PySpark Streaming
- new unit tests in Scala and Python
This required adding an optional Hadoop configuration param to `fileStream` and `FileInputStream`, but was otherwise straightforward.
tdas davies
Author: freeman <the.freeman.lab@gmail.com>
Closes#3803 from freeman-lab/streaming-binary-records and squashes the following commits:
b676534 [freeman] Clarify note
5ff1b75 [freeman] Add note to java streaming context
eba925c [freeman] Simplify notes
c4237b8 [freeman] Add experimental tag
30eba67 [freeman] Add filter and newFilesOnly alongside conf
c2cfa6d [freeman] Expose new version of fileStream with conf in java
34d20ef [freeman] Add experimental tag
14bca9a [freeman] Add experimental tag
b85bffc [freeman] Formatting
47560f4 [freeman] Space formatting
9a3715a [freeman] Refactor to reflect changes to FileInputSuite
7373f73 [freeman] Add note and defensive assertion for byte length
3ceb684 [freeman] Merge remote-tracking branch 'upstream/master' into streaming-binary-records
317b6d1 [freeman] Make test inline
fcb915c [freeman] Formatting
becb344 [freeman] Formatting
d3e75b2 [freeman] Add tests in python
a4324a3 [freeman] Line length
029d49c [freeman] Formatting
1c739aa [freeman] Simpler default arg handling
94d90d0 [freeman] Spelling
2843e9d [freeman] Add params to docstring
8b70fbc [freeman] Reorganization
28bff9b [freeman] Fix missing arg
9398bcb [freeman] Expose optional hadoop configuration
23dd69f [freeman] Tests for binaryRecordsStream
36cb0fd [freeman] Add binaryRecordsStream to scala
fe4e803 [freeman] Add binaryRecordStream to Java API
ecef0eb [freeman] Add binaryRecordsStream to python
8550c26 [freeman] Expose additional argument combination
```scala
df.selectExpr("abs(colA)", "colB")
df.filter("age > 21")
```
Author: Reynold Xin <rxin@databricks.com>
Closes#4348 from rxin/SPARK-5579 and squashes the following commits:
2baeef2 [Reynold Xin] Fix Python.
b416372 [Reynold Xin] [SPARK-5579][SQL][DataFrame] Support for project/filter using SQL expressions.
The only issue is that `analyzeBlock` is removed, which was marked as a developer API. I didn't change other tests in the ALSSuite under `spark.mllib` to ensure that the implementation is correct.
CC: srowen coderxiang
Author: Xiangrui Meng <meng@databricks.com>
Closes#4321 from mengxr/SPARK-5536 and squashes the following commits:
5a3cee8 [Xiangrui Meng] update python tests that are too strict
e840acf [Xiangrui Meng] ignore scala style check for ALS.train
e9a721c [Xiangrui Meng] update mima excludes
9ee6a36 [Xiangrui Meng] merge master
9a8aeac [Xiangrui Meng] update tests
d8c3271 [Xiangrui Meng] remove analyzeBlocks
d68eee7 [Xiangrui Meng] add checkpoint to new ALS
22a56f8 [Xiangrui Meng] wrap old ALS
c387dff [Xiangrui Meng] support random seed
3bdf24b [Xiangrui Meng] make storage level configurable in the new ALS
This PR brings the Python API for Spark Streaming Kafka data source.
```
class KafkaUtils(__builtin__.object)
| Static methods defined here:
|
| createStream(ssc, zkQuorum, groupId, topics, storageLevel=StorageLevel(True, True, False, False,
2), keyDecoder=<function utf8_decoder>, valueDecoder=<function utf8_decoder>)
| Create an input stream that pulls messages from a Kafka Broker.
|
| :param ssc: StreamingContext object
| :param zkQuorum: Zookeeper quorum (hostname:port,hostname:port,..).
| :param groupId: The group id for this consumer.
| :param topics: Dict of (topic_name -> numPartitions) to consume.
| Each partition is consumed in its own thread.
| :param storageLevel: RDD storage level.
| :param keyDecoder: A function used to decode key
| :param valueDecoder: A function used to decode value
| :return: A DStream object
```
run the example:
```
bin/spark-submit --driver-class-path external/kafka-assembly/target/scala-*/spark-streaming-kafka-assembly-*.jar examples/src/main/python/streaming/kafka_wordcount.py localhost:2181 test
```
Author: Davies Liu <davies@databricks.com>
Author: Tathagata Das <tdas@databricks.com>
Closes#3715 from davies/kafka and squashes the following commits:
d93bfe0 [Davies Liu] Update make-distribution.sh
4280d04 [Davies Liu] address comments
e6d0427 [Davies Liu] Merge branch 'master' of github.com:apache/spark into kafka
f257071 [Davies Liu] add tests for null in RDD
23b039a [Davies Liu] address comments
9af51c4 [Davies Liu] Merge branch 'kafka' of github.com:davies/spark into kafka
a74da87 [Davies Liu] address comments
dc1eed0 [Davies Liu] Update kafka_wordcount.py
31e2317 [Davies Liu] Update kafka_wordcount.py
370ba61 [Davies Liu] Update kafka.py
97386b3 [Davies Liu] address comment
2c567a5 [Davies Liu] update logging and comment
33730d1 [Davies Liu] Merge branch 'master' of github.com:apache/spark into kafka
adeeb38 [Davies Liu] Merge pull request #3 from tdas/kafka-python-api
aea8953 [Tathagata Das] Kafka-assembly for Python API
eea16a7 [Davies Liu] refactor
f6ce899 [Davies Liu] add example and fix bugs
98c8d17 [Davies Liu] fix python style
5697a01 [Davies Liu] bypass decoder in scala
048dbe6 [Davies Liu] fix python style
75d485e [Davies Liu] add mqtt
07923c4 [Davies Liu] support kafka in Python
1. Throw UnsupportedOperationException if a Column is not computable.
2. Perform eager analysis on DataFrame so we can catch errors when they happen (not when an action is run).
Author: Reynold Xin <rxin@databricks.com>
Author: Davies Liu <davies@databricks.com>
Closes#4296 from rxin/col-computability and squashes the following commits:
6527b86 [Reynold Xin] Merge pull request #8 from davies/col-computability
fd92bc7 [Reynold Xin] Merge branch 'master' into col-computability
f79034c [Davies Liu] fix python tests
5afe1ff [Reynold Xin] Fix scala test.
17f6bae [Reynold Xin] Various fixes.
b932e86 [Reynold Xin] Added eager analysis for error reporting.
e6f00b8 [Reynold Xin] [SQL][API] ComputableColumn vs IncomputableColumn
Whenever a directory is created by the utility method, immediately restrict
its permissions so that only the owner has access to its contents.
Signed-off-by: Josh Rosen <joshrosen@databricks.com>
This PR is implementing the Gradient Boosted Trees for Python API.
Author: Kazuki Taniguchi <kazuki.t.1018@gmail.com>
Closes#3951 from kazk1018/gbt_for_py and squashes the following commits:
620d247 [Kazuki Taniguchi] [SPARK-5094][MLlib] Add Python API for Gradient Boosted Trees
This fixes an exception that prevented users from calling `help()` on Python DataFrame instances.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#4278 from JoshRosen/SPARK-5464-python-dataframe-help-command and squashes the following commits:
08f95f7 [Josh Rosen] Fix exception when calling help() on Python DataFrame instances
Turns out Scala does generate static methods for ones defined in a companion object. Finally no need to separate api.java.dsl and api.scala.dsl.
Author: Reynold Xin <rxin@databricks.com>
Closes#4276 from rxin/dsl and squashes the following commits:
30aa611 [Reynold Xin] Add all files.
1a9d215 [Reynold Xin] [SPARK-5445][SQL] Consolidate Java and Scala DSL static methods.
There is only a single `stat.py` file for the `mllib.stat` package. We recently added `MultivariateGaussian` under `mllib.stat.distribution` in Scala/Java. It would be nice to refactor `stat.py` and make it easy to expand. Note that `ChiSqTestResult` is moved from `mllib.stat` to `mllib.stat.test`. The latter is used in Scala/Java. It is only used in the return value of `Statistics.chiSqTest`, so this should be an okay change.
davies
Author: Xiangrui Meng <meng@databricks.com>
Closes#4266 from mengxr/py-stat-refactor and squashes the following commits:
1a5e1db [Xiangrui Meng] refactor stat.py
Also removed the literal implicit transformation since it is pretty scary for API design. Instead, created a new lit method for creating literals. This doesn't break anything from a compatibility perspective because Literal was added two days ago.
Author: Reynold Xin <rxin@databricks.com>
Closes#4241 from rxin/df-docupdate and squashes the following commits:
c0f4810 [Reynold Xin] Fix Python merge conflict.
094c7d7 [Reynold Xin] Minor style fix. Reset Python tests.
3c89f4a [Reynold Xin] Package.
dfe6962 [Reynold Xin] Updated Python aggregate.
5dd4265 [Reynold Xin] Made dsl Java callable.
14b3c27 [Reynold Xin] Fix literal expression for symbols.
68b31cb [Reynold Xin] Literal.
4cfeb78 [Reynold Xin] [SPARK-5097][SQL] Address DataFrame code review feedback.
We have seen many use cases of `treeAggregate`/`treeReduce` outside the ML domain. Maybe it is time to move them to Core. pwendell
Author: Xiangrui Meng <meng@databricks.com>
Closes#4228 from mengxr/SPARK-5430 and squashes the following commits:
20ad40d [Xiangrui Meng] exclude tree* from mima
e89a43e [Xiangrui Meng] fix compile and update java doc
3ae1a4b [Xiangrui Meng] add treeReduce/treeAggregate to Python
6f948c5 [Xiangrui Meng] add treeReduce/treeAggregate to JavaRDDLike
d600b6c [Xiangrui Meng] move treeReduce and treeAggregate to core
This PR adds Python API for ML pipeline and parameters. The design doc can be found on the JIRA page. It includes transformers and an estimator to demo the simple text classification example code.
TODO:
- [x] handle parameters in LRModel
- [x] unit tests
- [x] missing some docs
CC: davies jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Author: Davies Liu <davies@databricks.com>
Closes#4151 from mengxr/SPARK-4586 and squashes the following commits:
415268e [Xiangrui Meng] remove inherit_doc from __init__
edbd6fe [Xiangrui Meng] move Identifiable to ml.util
44c2405 [Xiangrui Meng] Merge pull request #2 from davies/ml
dd1256b [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-4586
14ae7e2 [Davies Liu] fix docs
54ca7df [Davies Liu] fix tests
78638df [Davies Liu] Merge branch 'SPARK-4586' of github.com:mengxr/spark into ml
fc59a02 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-4586
1dca16a [Davies Liu] refactor
090b3a3 [Davies Liu] Merge branch 'master' of github.com:apache/spark into ml
0882513 [Xiangrui Meng] update doc style
a4f4dbf [Xiangrui Meng] add unit test for LR
7521d1c [Xiangrui Meng] add unit tests to HashingTF and Tokenizer
ba0ba1e [Xiangrui Meng] add unit tests for pipeline
0586c7b [Xiangrui Meng] add more comments to the example
5153cff [Xiangrui Meng] simplify java models
036ca04 [Xiangrui Meng] gen numFeatures
46fa147 [Xiangrui Meng] update mllib/pom.xml to include python files in the assembly
1dcc17e [Xiangrui Meng] update code gen and make param appear in the doc
f66ba0c [Xiangrui Meng] make params a property
d5efd34 [Xiangrui Meng] update doc conf and move embedded param map to instance attribute
f4d0fe6 [Xiangrui Meng] use LabeledDocument and Document in example
05e3e40 [Xiangrui Meng] update example
d3e8dbe [Xiangrui Meng] more docs optimize pipeline.fit impl
56de571 [Xiangrui Meng] fix style
d0c5bb8 [Xiangrui Meng] a working copy
bce72f4 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-4586
17ecfb9 [Xiangrui Meng] code gen for shared params
d9ea77c [Xiangrui Meng] update doc
c18dca1 [Xiangrui Meng] make the example working
dadd84e [Xiangrui Meng] add base classes and docs
a3015cf [Xiangrui Meng] add Estimator and Transformer
46eea43 [Xiangrui Meng] a pipeline in python
33b68e0 [Xiangrui Meng] a working LR
This PR is based on #3255 , fix conflicts and code style.
Closes#3255.
Author: Yandu Oppacher <yandu.oppacher@jadedpixel.com>
Author: Davies Liu <davies@databricks.com>
Closes#3901 from davies/refactor-python-profile-code and squashes the following commits:
b4a9306 [Davies Liu] fix tests
4b79ce8 [Davies Liu] add docstring for profiler_cls
2700e47 [Davies Liu] use BasicProfiler as default
349e341 [Davies Liu] more refactor
6a5d4df [Davies Liu] refactor and fix tests
31bf6b6 [Davies Liu] fix code style
0864b5d [Yandu Oppacher] Remove unused method
76a6c37 [Yandu Oppacher] Added a profile collector to accumulate the profilers per stage
9eefc36 [Yandu Oppacher] Fix doc
9ace076 [Yandu Oppacher] Refactor of profiler, and moved tests around
8739aff [Yandu Oppacher] Code review fixes
9bda3ec [Yandu Oppacher] Refactor profiler code
Since Java and Scala both have access to iterate over partitions via the "toLocalIterator" function, python should also have that same ability.
Author: Michael Nazario <mnazario@palantir.com>
Closes#4237 from mnazario/feature/toLocalIterator and squashes the following commits:
1c58526 [Michael Nazario] Fix documentation off by one error
0cdc8f8 [Michael Nazario] Add toLocalIterator to PySpark
Author: Sandy Ryza <sandy@cloudera.com>
Closes#4251 from sryza/sandy-spark-5458 and squashes the following commits:
460827a [Sandy Ryza] Python too
d2dc160 [Sandy Ryza] SPARK-5458. Refer to aggregateByKey instead of combineByKey in docs
This is found through reading RDD from `sc.newAPIHadoopRDD` and writing it back using `rdd.saveAsNewAPIHadoopFile` in pyspark.
It turns out that whenever there are multiple RDD conversions from JavaRDD to PythonRDD then back to JavaRDD, the exception below happens:
```
15/01/16 10:28:31 ERROR Executor: Exception in task 0.0 in stage 3.0 (TID 7)
java.lang.ClassCastException: [Ljava.lang.Object; cannot be cast to java.util.ArrayList
at org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:157)
at org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:153)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:308)
```
The test case code below reproduces it:
```
from pyspark.rdd import RDD
dl = [
(u'2', {u'director': u'David Lean'}),
(u'7', {u'director': u'Andrew Dominik'})
]
dl_rdd = sc.parallelize(dl)
tmp = dl_rdd._to_java_object_rdd()
tmp2 = sc._jvm.SerDe.javaToPython(tmp)
t = RDD(tmp2, sc)
t.count()
tmp = t._to_java_object_rdd()
tmp2 = sc._jvm.SerDe.javaToPython(tmp)
t = RDD(tmp2, sc)
t.count() # it blows up here during the 2nd time of conversion
```
Author: Winston Chen <wchen@quid.com>
Closes#4146 from wingchen/master and squashes the following commits:
903df7d [Winston Chen] SPARK-5361, update to toSeq based on the PR
5d90a83 [Winston Chen] SPARK-5361, make python pretty, so to pass PEP 8 checks
126be6b [Winston Chen] SPARK-5361, add in test case
4cf1187 [Winston Chen] SPARK-5361, add in test case
9f1a097 [Winston Chen] add in tuple handling while converting form python RDD back to JavaRDD
This patch adds more helpful error messages for invalid programs that define nested RDDs, broadcast RDDs, perform actions inside of transformations (e.g. calling `count()` from inside of `map()`), and call certain methods on stopped SparkContexts. Currently, these invalid programs lead to confusing NullPointerExceptions at runtime and have been a major source of questions on the mailing list and StackOverflow.
In a few cases, I chose to log warnings instead of throwing exceptions in order to avoid any chance that this patch breaks programs that worked "by accident" in earlier Spark releases (e.g. programs that define nested RDDs but never run any jobs with them).
In SparkContext, the new `assertNotStopped()` method is used to check whether methods are being invoked on a stopped SparkContext. In some cases, user programs will not crash in spite of calling methods on stopped SparkContexts, so I've only added `assertNotStopped()` calls to methods that always throw exceptions when called on stopped contexts (e.g. by dereferencing a null `dagScheduler` pointer).
Author: Josh Rosen <joshrosen@databricks.com>
Closes#3884 from JoshRosen/SPARK-5063 and squashes the following commits:
a38774b [Josh Rosen] Fix spelling typo
a943e00 [Josh Rosen] Convert two exceptions into warnings in order to avoid breaking user programs in some edge-cases.
2d0d7f7 [Josh Rosen] Fix test to reflect 1.2.1 compatibility
3f0ea0c [Josh Rosen] Revert two unintentional formatting changes
8e5da69 [Josh Rosen] Remove assertNotStopped() calls for methods that were sometimes safe to call on stopped SC's in Spark 1.2
8cff41a [Josh Rosen] IllegalStateException fix
6ef68d0 [Josh Rosen] Fix Python line length issues.
9f6a0b8 [Josh Rosen] Add improved error messages to PySpark.
13afd0f [Josh Rosen] SparkException -> IllegalStateException
8d404f3 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-5063
b39e041 [Josh Rosen] Fix BroadcastSuite test which broadcasted an RDD
99cc09f [Josh Rosen] Guard against calling methods on stopped SparkContexts.
34833e8 [Josh Rosen] Add more descriptive error message.
57cc8a1 [Josh Rosen] Add error message when directly broadcasting RDD.
15b2e6b [Josh Rosen] [SPARK-5063] Useful error messages for nested RDDs and actions inside of transformations
This implements the functionality for SPARK-4749 and provides units tests in Scala and PySpark
Author: nate.crosswhite <nate.crosswhite@stresearch.com>
Author: nxwhite-str <nxwhite-str@users.noreply.github.com>
Author: Xiangrui Meng <meng@databricks.com>
Closes#3610 from nxwhite-str/master and squashes the following commits:
a2ebbd3 [nxwhite-str] Merge pull request #1 from mengxr/SPARK-4749-kmeans-seed
7668124 [Xiangrui Meng] minor updates
f8d5928 [nate.crosswhite] Addressing PR issues
277d367 [nate.crosswhite] Merge remote-tracking branch 'upstream/master'
9156a57 [nate.crosswhite] Merge remote-tracking branch 'upstream/master'
5d087b4 [nate.crosswhite] Adding KMeans train with seed and Scala unit test
616d111 [nate.crosswhite] Merge remote-tracking branch 'upstream/master'
35c1884 [nate.crosswhite] Add kmeans initial seed to pyspark API
Pretty minor, but submitted for consideration -- this would at least help people make this check in the most efficient way I know.
Author: Sean Owen <sowen@cloudera.com>
Closes#4074 from srowen/SPARK-5270 and squashes the following commits:
66885b8 [Sean Owen] Add note that JavaRDDLike should not be implemented by user code
2e9b490 [Sean Owen] More tests, and Mima-exclude the new isEmpty method in JavaRDDLike
28395ff [Sean Owen] Add isEmpty to Java, Python
7dd04b7 [Sean Owen] Add efficient RDD.isEmpty()
As part of SPARK-5193:
1. Removed UDFRegistration as a mixin in SQLContext and made it a field ("udf").
2. For Java UDFs, renamed dataType to returnType.
3. For Scala UDFs, added type tags.
4. Added all Java UDF registration methods to Scala's UDFRegistration.
5. Documentation
Author: Reynold Xin <rxin@databricks.com>
Closes#4056 from rxin/udf-registration and squashes the following commits:
ae9c556 [Reynold Xin] Updated example.
675a3c9 [Reynold Xin] Style fix
47c24ff [Reynold Xin] Python fix.
5f00c45 [Reynold Xin] Restore data type position in java udf and added typetags.
032f006 [Reynold Xin] [SPARK-5193][SQL] Reconcile Java and Scala UDFRegistration.
After the default batchSize changed to 0 (batched based on the size of object), but parallelize() still use BatchedSerializer with batchSize=1, this PR will use batchSize=1024 for parallelize by default.
Also, BatchedSerializer did not work well with list and numpy.ndarray, this improve BatchedSerializer by using __len__ and __getslice__.
Here is the benchmark for parallelize 1 millions int with list or ndarray:
| before | after | improvements
------- | ------------ | ------------- | -------
list | 11.7 s | 0.8 s | 14x
numpy.ndarray | 32 s | 0.7 s | 40x
Author: Davies Liu <davies@databricks.com>
Closes#4024 from davies/opt_numpy and squashes the following commits:
7618c7c [Davies Liu] improve performance of parallelize list/ndarray
Slightly different than the scala code which converts the sparsevector into a densevector and then checks the index.
I also hope I've added tests in the right place.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#4025 from MechCoder/spark-2909 and squashes the following commits:
07d0f26 [MechCoder] STY: Rename item to index
f02148b [MechCoder] [SPARK-2909] [Mlib] SparseVector in pyspark now supports indexing
