This patch adds the ability to register lambda functions written in Python, Java or Scala as UDFs for use in SQL or HiveQL.
Scala:
```scala
registerFunction("strLenScala", (_: String).length)
sql("SELECT strLenScala('test')")
```
Python:
```python
sqlCtx.registerFunction("strLenPython", lambda x: len(x), IntegerType())
sqlCtx.sql("SELECT strLenPython('test')")
```
Java:
```java
sqlContext.registerFunction("stringLengthJava", new UDF1<String, Integer>() {
Override
public Integer call(String str) throws Exception {
return str.length();
}
}, DataType.IntegerType);
sqlContext.sql("SELECT stringLengthJava('test')");
```
Author: Michael Armbrust <michael@databricks.com>
Closes#1063 from marmbrus/udfs and squashes the following commits:
9eda0fe [Michael Armbrust] newline
747c05e [Michael Armbrust] Add some scala UDF tests.
d92727d [Michael Armbrust] Merge remote-tracking branch 'apache/master' into udfs
005d684 [Michael Armbrust] Fix naming and formatting.
d14dac8 [Michael Armbrust] Fix last line of autogened java files.
8135c48 [Michael Armbrust] Move UDF unit tests to pyspark.
40b0ffd [Michael Armbrust] Merge remote-tracking branch 'apache/master' into udfs
6a36890 [Michael Armbrust] Switch logging so that SQLContext can be serializable.
7a83101 [Michael Armbrust] Drop toString
795fd15 [Michael Armbrust] Try to avoid capturing SQLContext.
e54fb45 [Michael Armbrust] Docs and tests.
437cbe3 [Michael Armbrust] Update use of dataTypes, fix some python tests, address review comments.
01517d6 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into udfs
8e6c932 [Michael Armbrust] WIP
3f96a52 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into udfs
6237c8d [Michael Armbrust] WIP
2766f0b [Michael Armbrust] Move udfs support to SQL from hive. Add support for Java UDFs.
0f7d50c [Michael Armbrust] Draft of native Spark SQL UDFs for Scala and Python.
Added experimental Python API for Decision Trees.
API:
* class DecisionTreeModel
** predict() for single examples and RDDs, taking both feature vectors and LabeledPoints
** numNodes()
** depth()
** __str__()
* class DecisionTree
** trainClassifier()
** trainRegressor()
** train()
Examples and testing:
* Added example testing classification and regression with batch prediction: examples/src/main/python/mllib/tree.py
* Have also tested example usage in doc of python/pyspark/mllib/tree.py which tests single-example prediction with dense and sparse vectors
Also: Small bug fix in python/pyspark/mllib/_common.py: In _linear_predictor_typecheck, changed check for RDD to use isinstance() instead of type() in order to catch RDD subclasses.
CC mengxr manishamde
Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com>
Closes#1727 from jkbradley/decisiontree-python-new and squashes the following commits:
3744488 [Joseph K. Bradley] Renamed test tree.py to decision_tree_runner.py Small updates based on github review.
6b86a9d [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into decisiontree-python-new
affceb9 [Joseph K. Bradley] * Fixed bug in doc tests in pyspark/mllib/util.py caused by change in loadLibSVMFile behavior. (It used to threshold labels at 0 to make them 0/1, but it now leaves them as they are.) * Fixed small bug in loadLibSVMFile: If a data file had no features, then loadLibSVMFile would create a single all-zero feature.
67a29bc [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into decisiontree-python-new
cf46ad7 [Joseph K. Bradley] Python DecisionTreeModel * predict(empty RDD) returns an empty RDD instead of an error. * Removed support for calling predict() on LabeledPoint and RDD[LabeledPoint] * predict() does not cache serialized RDD any more.
aa29873 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into decisiontree-python-new
bf21be4 [Joseph K. Bradley] removed old run() func from DecisionTree
fa10ea7 [Joseph K. Bradley] Small style update
7968692 [Joseph K. Bradley] small braces typo fix
e34c263 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into decisiontree-python-new
4801b40 [Joseph K. Bradley] Small style update to DecisionTreeSuite
db0eab2 [Joseph K. Bradley] Merge branch 'decisiontree-bugfix2' into decisiontree-python-new
6873fa9 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into decisiontree-python-new
225822f [Joseph K. Bradley] Bug: In DecisionTree, the method sequentialBinSearchForOrderedCategoricalFeatureInClassification() indexed bins from 0 to (math.pow(2, featureCategories.toInt - 1) - 1). This upper bound is the bound for unordered categorical features, not ordered ones. The upper bound should be the arity (i.e., max value) of the feature.
93953f1 [Joseph K. Bradley] Likely done with Python API.
6df89a9 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into decisiontree-python-new
4562c08 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into decisiontree-python-new
665ba78 [Joseph K. Bradley] Small updates towards Python DecisionTree API
188cb0d [Joseph K. Bradley] Merge branch 'decisiontree-bugfix' into decisiontree-python-new
6622247 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into decisiontree-python-new
b8fac57 [Joseph K. Bradley] Finished Python DecisionTree API and example but need to test a bit more.
2b20c61 [Joseph K. Bradley] Small doc and style updates
1b29c13 [Joseph K. Bradley] Merge branch 'decisiontree-bugfix' into decisiontree-python-new
584449a [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into decisiontree-python-new
dab0b67 [Joseph K. Bradley] Added documentation for DecisionTree internals
8bb8aa0 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into decisiontree-bugfix
978cfcf [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into decisiontree-bugfix
6eed482 [Joseph K. Bradley] In DecisionTree: Changed from using procedural syntax for functions returning Unit to explicitly writing Unit return type.
376dca2 [Joseph K. Bradley] Updated meaning of maxDepth by 1 to fit scikit-learn and rpart. * In code, replaced usages of maxDepth <-- maxDepth + 1 * In params, replace settings of maxDepth <-- maxDepth - 1
e06e423 [Joseph K. Bradley] Merge branch 'decisiontree-bugfix' into decisiontree-python-new
bab3f19 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into decisiontree-python-new
59750f8 [Joseph K. Bradley] * Updated Strategy to check numClassesForClassification only if algo=Classification. * Updates based on comments: ** DecisionTreeRunner *** Made dataFormat arg default to libsvm ** Small cleanups ** tree.Node: Made recursive helper methods private, and renamed them.
52e17c5 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into decisiontree-bugfix
f5a036c [Joseph K. Bradley] Merge branch 'decisiontree-bugfix' into decisiontree-python-new
da50db7 [Joseph K. Bradley] Added one more test to DecisionTreeSuite: stump with 2 continuous variables for binary classification. Caused problems in past, but fixed now.
8e227ea [Joseph K. Bradley] Changed Strategy so it only requires numClassesForClassification >= 2 for classification
cd1d933 [Joseph K. Bradley] Merge branch 'decisiontree-bugfix' into decisiontree-python-new
8ea8750 [Joseph K. Bradley] Bug fix: Off-by-1 when finding thresholds for splits for continuous features.
8a758db [Joseph K. Bradley] Merge branch 'decisiontree-bugfix' into decisiontree-python-new
5fe44ed [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into decisiontree-python-new
2283df8 [Joseph K. Bradley] 2 bug fixes.
73fbea2 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into decisiontree-bugfix
5f920a1 [Joseph K. Bradley] Demonstration of bug before submitting fix: Updated DecisionTreeSuite so that 3 tests fail. Will describe bug in next commit.
f825352 [Joseph K. Bradley] Wrote Python API and example for DecisionTree. Also added toString, depth, and numNodes methods to DecisionTreeModel.
When standalone Workers launch executors, they inherit the Spark home set by the driver. This means if the worker machines do not share the same directory structure as the driver node, the Workers will attempt to run scripts (e.g. bin/compute-classpath.sh) that do not exist locally and fail. This is a common scenario if the driver is launched from outside of the cluster.
The solution is to simply not pass the driver's Spark home to the Workers. This PR further makes an attempt to avoid overloading the usages of `spark.home`, which is now only used for setting executor Spark home on Mesos and in python.
This is based on top of #1392 and originally reported by YanTangZhai. Tested on standalone cluster.
Author: Andrew Or <andrewor14@gmail.com>
Closes#1734 from andrewor14/spark-home-reprise and squashes the following commits:
f71f391 [Andrew Or] Revert changes in python
1c2532c [Andrew Or] Merge branch 'master' of github.com:apache/spark into spark-home-reprise
188fc5d [Andrew Or] Avoid using spark.home where possible
09272b7 [Andrew Or] Always use Worker's working directory as spark home
These changes allow StatCounters to work properly on NumPy arrays, to fix the issue reported here (https://issues.apache.org/jira/browse/SPARK-2012).
If NumPy is installed, the NumPy functions ``maximum``, ``minimum``, and ``sqrt``, which work on arrays, are used to merge statistics. If not, we fall back on scalar operators, so it will work on arrays with NumPy, but will also work without NumPy.
New unit tests added, along with a check for NumPy in the tests.
Author: Jeremy Freeman <the.freeman.lab@gmail.com>
Closes#1725 from freeman-lab/numpy-max-statcounter and squashes the following commits:
fe973b1 [Jeremy Freeman] Avoid duplicate array import in tests
7f0e397 [Jeremy Freeman] Refactored check for numpy
8e764dd [Jeremy Freeman] Explicit numpy imports
875414c [Jeremy Freeman] Fixed indents
1c8a832 [Jeremy Freeman] Unit tests for StatCounter with NumPy arrays
176a127 [Jeremy Freeman] Use numpy arrays in StatCounter
Related to issue: [SPARK-2550](https://issues.apache.org/jira/browse/SPARK-2550?jql=project%20%3D%20SPARK%20AND%20resolution%20%3D%20Unresolved%20AND%20priority%20%3D%20Major%20ORDER%20BY%20key%20DESC).
Author: Michael Giannakopoulos <miccagiann@gmail.com>
Closes#1624 from miccagiann/new-branch and squashes the following commits:
c02e5f5 [Michael Giannakopoulos] Merge cleanly with upstream/master.
8dcb888 [Michael Giannakopoulos] Putting the if/else if statements in brackets.
fed8eaa [Michael Giannakopoulos] Adding a space in the message related to the IllegalArgumentException.
44e6ff0 [Michael Giannakopoulos] Adding a blank line before python class LinearRegressionWithSGD.
8eba9c5 [Michael Giannakopoulos] Change function signatures. Exception is thrown from the scala component and not from the python one.
638be47 [Michael Giannakopoulos] Modified code to comply with code standards.
ec50ee9 [Michael Giannakopoulos] Shorten the if-elif-else statement in regression.py file
b962744 [Michael Giannakopoulos] Replaced the enum classes, with strings-keywords for defining the values of 'regType' parameter.
78853ec [Michael Giannakopoulos] Providing intercept and regualizer functionallity for linear methods in only one function.
3ac8874 [Michael Giannakopoulos] Added support for regularizer and intercection parameters for linear regression method.
Curently, daemon.py forks a pool of numProcessors subprocesses, and those processes fork themselves again to create the actual Python worker processes that handle data.
I think that this extra layer of indirection is unnecessary and adds a lot of complexity. This commit attempts to remove this middle layer of subprocesses by launching the workers directly from daemon.py.
See https://github.com/mesos/spark/pull/563 for the original PR that added daemon.py, where I raise some issues with the current design.
Author: Josh Rosen <joshrosen@apache.org>
Closes#1680 from JoshRosen/pyspark-daemon and squashes the following commits:
5abbcb9 [Josh Rosen] Replace magic number: 4 -> EINTR
5495dff [Josh Rosen] Throw IllegalStateException if worker launch fails.
b79254d [Josh Rosen] Detect failed fork() calls; improve error logging.
282c2c4 [Josh Rosen] Remove daemon.py exit logging, since it caused problems:
8554536 [Josh Rosen] Fix daemon’s shutdown(); log shutdown reason.
4e0fab8 [Josh Rosen] Remove shared-memory exit_flag; don't die on worker death.
e9892b4 [Josh Rosen] [WIP] [SPARK-2764] Simplify daemon.py process structure.
Convert Row in JavaSchemaRDD into Array[Any] and unpickle them as tuple in Python, then convert them into namedtuple, so use can access fields just like attributes.
This will let nested structure can be accessed as object, also it will reduce the size of serialized data and better performance.
root
|-- field1: integer (nullable = true)
|-- field2: string (nullable = true)
|-- field3: struct (nullable = true)
| |-- field4: integer (nullable = true)
| |-- field5: array (nullable = true)
| | |-- element: integer (containsNull = false)
|-- field6: array (nullable = true)
| |-- element: struct (containsNull = false)
| | |-- field7: string (nullable = true)
Then we can access them by row.field3.field5[0] or row.field6[5].field7
It also will infer the schema in Python, convert Row/dict/namedtuple/objects into tuple before serialization, then call applySchema in JVM. During inferSchema(), the top level of dict in row will be StructType, but any nested dictionary will be MapType.
You can use pyspark.sql.Row to convert unnamed structure into Row object, make the RDD can be inferable. Such as:
ctx.inferSchema(rdd.map(lambda x: Row(a=x[0], b=x[1]))
Or you could use Row to create a class just like namedtuple, for example:
Person = Row("name", "age")
ctx.inferSchema(rdd.map(lambda x: Person(*x)))
Also, you can call applySchema to apply an schema to a RDD of tuple/list and turn it into a SchemaRDD. The `schema` should be StructType, see the API docs for details.
schema = StructType([StructField("name, StringType, True),
StructType("age", IntegerType, True)])
ctx.applySchema(rdd, schema)
PS: In order to use namedtuple to inferSchema, you should make namedtuple picklable.
Author: Davies Liu <davies.liu@gmail.com>
Closes#1598 from davies/nested and squashes the following commits:
f1d15b6 [Davies Liu] verify schema with the first few rows
8852aaf [Davies Liu] check type of schema
abe9e6e [Davies Liu] address comments
61b2292 [Davies Liu] add @deprecated to pythonToJavaMap
1e5b801 [Davies Liu] improve cache of classes
51aa135 [Davies Liu] use Row to infer schema
e9c0d5c [Davies Liu] remove string typed schema
353a3f2 [Davies Liu] fix code style
63de8f8 [Davies Liu] fix typo
c79ca67 [Davies Liu] fix serialization of nested data
6b258b5 [Davies Liu] fix pep8
9d8447c [Davies Liu] apply schema provided by string of names
f5df97f [Davies Liu] refactor, address comments
9d9af55 [Davies Liu] use arrry to applySchema and infer schema in Python
84679b3 [Davies Liu] Merge branch 'master' of github.com:apache/spark into nested
0eaaf56 [Davies Liu] fix doc tests
b3559b4 [Davies Liu] use generated Row instead of namedtuple
c4ddc30 [Davies Liu] fix conflict between name of fields and variables
7f6f251 [Davies Liu] address all comments
d69d397 [Davies Liu] refactor
2cc2d45 [Davies Liu] refactor
182fb46 [Davies Liu] refactor
bc6e9e1 [Davies Liu] switch to new Schema API
547bf3e [Davies Liu] Merge branch 'master' into nested
a435b5a [Davies Liu] add docs and code refactor
2c8debc [Davies Liu] Merge branch 'master' into nested
644665a [Davies Liu] use tuple and namedtuple for schemardd
RandomRDDGenerators but without support for randomRDD and randomVectorRDD, which take in arbitrary DistributionGenerator.
`randomRDD.py` is named to avoid collision with the built-in Python `random` package.
Author: Doris Xin <doris.s.xin@gmail.com>
Closes#1628 from dorx/pythonRDD and squashes the following commits:
55c6de8 [Doris Xin] review comments. all python units passed.
f831d9b [Doris Xin] moved default args logic into PythonMLLibAPI
2d73917 [Doris Xin] fix for linalg.py
8663e6a [Doris Xin] reverting back to a single python file for random
f47c481 [Doris Xin] docs update
687aac0 [Doris Xin] add RandomRDDGenerators.py to run-tests
4338f40 [Doris Xin] renamed randomRDD to rand and import as random
29d205e [Doris Xin] created mllib.random package
bd2df13 [Doris Xin] typos
07ddff2 [Doris Xin] units passed.
23b2ecd [Doris Xin] WIP
Prior to this change, every PySpark task completion opened a new socket to the accumulator server, passed its updates through, and then quit. I'm not entirely sure why PySpark always sends accumulator updates, but regardless this causes a very rapid buildup of ephemeral TCP connections that remain in the TCP_WAIT state for around a minute before being cleaned up.
Rather than trying to allow these sockets to be cleaned up faster, this patch simply reuses the connection between tasks completions (since they're fed updates in a single-threaded manner by the DAGScheduler anyway).
The only tricky part here was making sure that the AccumulatorServer was able to shutdown in a timely manner (i.e., stop polling for new data), and this was accomplished via minor feats of magic.
I have confirmed that this patch eliminates the buildup of ephemeral sockets due to the accumulator updates. However, I did note that there were still significant sockets being created against the PySpark daemon port, but my machine was not able to create enough sockets fast enough to fail. This may not be the last time we've seen this issue, though.
Author: Aaron Davidson <aaron@databricks.com>
Closes#1503 from aarondav/accum and squashes the following commits:
b3e12f7 [Aaron Davidson] SPARK-2282: Reuse Socket for sending accumulator updates to Pyspark
LocalHiveContext is redundant with HiveContext. The only difference is it creates `./metastore` instead of `./metastore_db`.
Author: Michael Armbrust <michael@databricks.com>
Closes#1641 from marmbrus/localHiveContext and squashes the following commits:
e5ec497 [Michael Armbrust] Add deprecation version
626e056 [Michael Armbrust] Don't remove from imports yet
905cc5f [Michael Armbrust] Merge remote-tracking branch 'apache/master' into localHiveContext
1c2727e [Michael Armbrust] Deprecate LocalHiveContext
Per discussion at https://issues.apache.org/jira/browse/SPARK-2341 , this is a look at deprecating the multiclass parameter. Thoughts welcome of course.
Author: Sean Owen <srowen@gmail.com>
Closes#1663 from srowen/SPARK-2341 and squashes the following commits:
8a3abd7 [Sean Owen] Suppress MIMA error for removed package private classes
18a8c8e [Sean Owen] Updates from review
83d0092 [Sean Owen] Deprecated methods with multiclass, and instead always parse target as a double (ie. multiclass = true)
JIRA issue: https://issues.apache.org/jira/browse/SPARK-2024
This PR is a followup to #455 and adds capabilities for saving PySpark RDDs using SequenceFile or any Hadoop OutputFormats.
* Added RDD methods ```saveAsSequenceFile```, ```saveAsHadoopFile``` and ```saveAsHadoopDataset```, for both old and new MapReduce APIs.
* Default converter for converting common data types to Writables. Users may specify custom converters to convert to desired data types.
* No out-of-box support for reading/writing arrays, since ArrayWritable itself doesn't have a no-arg constructor for creating an empty instance upon reading. Users need to provide ArrayWritable subtypes. Custom converters for converting arrays to suitable ArrayWritable subtypes are also needed when writing. When reading, the default converter will convert any custom ArrayWritable subtypes to ```Object[]``` and they get pickled to Python tuples.
* Added HBase and Cassandra output examples to show how custom output formats and converters can be used.
cc MLnick mateiz ahirreddy pwendell
Author: Kan Zhang <kzhang@apache.org>
Closes#1338 from kanzhang/SPARK-2024 and squashes the following commits:
c01e3ef [Kan Zhang] [SPARK-2024] code formatting
6591e37 [Kan Zhang] [SPARK-2024] renaming pickled -> pickledRDD
d998ad6 [Kan Zhang] [SPARK-2024] refectoring to get method params below 10
57a7a5e [Kan Zhang] [SPARK-2024] correcting typo
75ca5bd [Kan Zhang] [SPARK-2024] Better type checking for batch serialized RDD
0bdec55 [Kan Zhang] [SPARK-2024] Refactoring newly added tests
9f39ff4 [Kan Zhang] [SPARK-2024] Adding 2 saveAsHadoopDataset tests
0c134f3 [Kan Zhang] [SPARK-2024] Test refactoring and adding couple unbatched cases
7a176df [Kan Zhang] [SPARK-2024] Add saveAsSequenceFile to PySpark
The current PR contains the following changes:
* Expose `DataType`s in the sql package (internal details are private to sql).
* Users can create Rows.
* Introduce `applySchema` to create a `SchemaRDD` by applying a `schema: StructType` to an `RDD[Row]`.
* Add a function `simpleString` to every `DataType`. Also, the schema represented by a `StructType` can be visualized by `printSchema`.
* `ScalaReflection.typeOfObject` provides a way to infer the Catalyst data type based on an object. Also, we can compose `typeOfObject` with some custom logics to form a new function to infer the data type (for different use cases).
* `JsonRDD` has been refactored to use changes introduced by this PR.
* Add a field `containsNull` to `ArrayType`. So, we can explicitly mark if an `ArrayType` can contain null values. The default value of `containsNull` is `false`.
New APIs are introduced in the sql package object and SQLContext. You can find the scaladoc at
[sql package object](http://yhuai.github.io/site/api/scala/index.html#org.apache.spark.sql.package) and [SQLContext](http://yhuai.github.io/site/api/scala/index.html#org.apache.spark.sql.SQLContext).
An example of using `applySchema` is shown below.
```scala
import org.apache.spark.sql._
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
val schema =
StructType(
StructField("name", StringType, false) ::
StructField("age", IntegerType, true) :: Nil)
val people = sc.textFile("examples/src/main/resources/people.txt").map(_.split(",")).map(p => Row(p(0), p(1).trim.toInt))
val peopleSchemaRDD = sqlContext. applySchema(people, schema)
peopleSchemaRDD.printSchema
// root
// |-- name: string (nullable = false)
// |-- age: integer (nullable = true)
peopleSchemaRDD.registerAsTable("people")
sqlContext.sql("select name from people").collect.foreach(println)
```
I will add new contents to the SQL programming guide later.
JIRA: https://issues.apache.org/jira/browse/SPARK-2179
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#1346 from yhuai/dataTypeAndSchema and squashes the following commits:
1d45977 [Yin Huai] Clean up.
a6e08b4 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
c712fbf [Yin Huai] Converts types of values based on defined schema.
4ceeb66 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
e5f8df5 [Yin Huai] Scaladoc.
122d1e7 [Yin Huai] Address comments.
03bfd95 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
2476ed0 [Yin Huai] Minor updates.
ab71f21 [Yin Huai] Format.
fc2bed1 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
bd40a33 [Yin Huai] Address comments.
991f860 [Yin Huai] Move "asJavaDataType" and "asScalaDataType" to DataTypeConversions.scala.
1cb35fe [Yin Huai] Add "valueContainsNull" to MapType.
3edb3ae [Yin Huai] Python doc.
692c0b9 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
1d93395 [Yin Huai] Python APIs.
246da96 [Yin Huai] Add java data type APIs to javadoc index.
1db9531 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
d48fc7b [Yin Huai] Minor updates.
33c4fec [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
b9f3071 [Yin Huai] Java API for applySchema.
1c9f33c [Yin Huai] Java APIs for DataTypes and Row.
624765c [Yin Huai] Tests for applySchema.
aa92e84 [Yin Huai] Update data type tests.
8da1a17 [Yin Huai] Add Row.fromSeq.
9c99bc0 [Yin Huai] Several minor updates.
1d9c13a [Yin Huai] Update applySchema API.
85e9b51 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
e495e4e [Yin Huai] More comments.
42d47a3 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
c3f4a02 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
2e58dbd [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
b8b7db4 [Yin Huai] 1. Move sql package object and package-info to sql-core. 2. Minor updates on APIs. 3. Update scala doc.
68525a2 [Yin Huai] Update JSON unit test.
3209108 [Yin Huai] Add unit tests.
dcaf22f [Yin Huai] Add a field containsNull to ArrayType to indicate if an array can contain null values or not. If an ArrayType is constructed by "ArrayType(elementType)" (the existing constructor), the value of containsNull is false.
9168b83 [Yin Huai] Update comments.
fc649d7 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
eca7d04 [Yin Huai] Add two apply methods which will be used to extract StructField(s) from a StructType.
949d6bb [Yin Huai] When creating a SchemaRDD for a JSON dataset, users can apply an existing schema.
7a6a7e5 [Yin Huai] Fix bug introduced by the change made on SQLContext.inferSchema.
43a45e1 [Yin Huai] Remove sql.util.package introduced in a previous commit.
0266761 [Yin Huai] Format
03eec4c [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeAndSchema
90460ac [Yin Huai] Infer the Catalyst data type from an object and cast a data value to the expected type.
3fa0df5 [Yin Huai] Provide easier ways to construct a StructType.
16be3e5 [Yin Huai] This commit contains three changes: * Expose `DataType`s in the sql package (internal details are private to sql). * Introduce `createSchemaRDD` to create a `SchemaRDD` from an `RDD` with a provided schema (represented by a `StructType`) and a provided function to construct `Row`, * Add a function `simpleString` to every `DataType`. Also, the schema represented by a `StructType` can be visualized by `printSchema`.
Author: Josh Rosen <joshrosen@apache.org>
Closes#1626 from JoshRosen/SPARK-2305 and squashes the following commits:
03fb283 [Josh Rosen] Update Py4J to version 0.8.2.1.
Datetime and time in Python will be converted into java.util.Calendar after serialization, it will be converted into java.sql.Timestamp during inferSchema().
In javaToPython(), Timestamp will be converted into Calendar, then be converted into datetime in Python after pickling.
Author: Davies Liu <davies.liu@gmail.com>
Closes#1601 from davies/date and squashes the following commits:
f0599b0 [Davies Liu] remove tests for sets and tuple in sql, fix list of list
c9d607a [Davies Liu] convert datetype for runtime
709d40d [Davies Liu] remove brackets
96db384 [Davies Liu] support datetime type for SchemaRDD
fix the problem with pickle operator.itemgetter with multiple index.
Author: Davies Liu <davies.liu@gmail.com>
Closes#1627 from davies/itemgetter and squashes the following commits:
aabd7fa [Davies Liu] fix pickle itemgetter with cloudpickle
During rdd.take(n), JVM will close the socket if it had got enough data, the Python worker should keep silent in this case.
In the same time, the worker should not print the trackback into stderr if it send the traceback to JVM successfully.
Author: Davies Liu <davies.liu@gmail.com>
Closes#1625 from davies/error and squashes the following commits:
4fbcc6d [Davies Liu] disable log4j during testing when exception is expected.
cc14202 [Davies Liu] keep silent in worker if JVM close the socket
This addresses a PySpark issue where a failed attempt to construct SparkContext would prevent any future SparkContext creation.
Author: Josh Rosen <joshrosen@apache.org>
Closes#1606 from JoshRosen/SPARK-1550 and squashes the following commits:
ec7fadc [Josh Rosen] [SPARK-1550] [PySpark] Allow SparkContext creation after failed attempts
Added a set of serializer/deserializer for Double in _common.py and PythonMLLibAPI in MLLib.
Author: Doris Xin <doris.s.xin@gmail.com>
Closes#1581 from dorx/doubleSerDe and squashes the following commits:
86a85b3 [Doris Xin] Merge branch 'master' into doubleSerDe
2bfe7a4 [Doris Xin] Removed magic byte
ad4d0d9 [Doris Xin] removed a space in unit
a9020bc [Doris Xin] units passed
7dad9af [Doris Xin] WIP
Similar to SPARK-1034, the problem was that Py4J didn’t cope well with the fake ClassTags used in the Java API. It doesn’t look like there’s any reason why PythonRDD needs to take a ClassTag, since it just ignores the type of the previous RDD, so I removed the type parameter and we no longer pass ClassTags from Python.
Author: Josh Rosen <joshrosen@apache.org>
Closes#1605 from JoshRosen/spark-2601 and squashes the following commits:
b68e118 [Josh Rosen] Fix Py4J error when transforming pickleFiles [SPARK-2601]
Add several default configs for PySpark, related to serialization in JVM.
spark.serializer = org.apache.spark.serializer.KryoSerializer
spark.serializer.objectStreamReset = 100
spark.rdd.compress = True
This will help to reduce the memory usage during RDD.partitionBy()
Author: Davies Liu <davies.liu@gmail.com>
Closes#1568 from davies/conf and squashes the following commits:
cd316f1 [Davies Liu] remove duplicated line
f71a355 [Davies Liu] rebase to master, add spark.rdd.compress = True
8f63f45 [Davies Liu] Merge branch 'master' into conf
8bc9f08 [Davies Liu] fix unittest
c04a83d [Davies Liu] some default configs for PySpark
Author: Josh Rosen <joshrosen@apache.org>
Closes#1596 from JoshRosen/spark-1458 and squashes the following commits:
fdbb0bf [Josh Rosen] Add SparkContext.version to Python & Java [SPARK-1458]
exact sample size not supported for now.
Author: Doris Xin <doris.s.xin@gmail.com>
Closes#1554 from dorx/pystratified and squashes the following commits:
4ba927a [Doris Xin] use rel diff (+- 50%) instead of abs diff (+- 50)
bdc3f8b [Doris Xin] updated unit to check sample holistically
7713c7b [Doris Xin] Python version of stratified sampling
During aggregation in Python worker, if the memory usage is above spark.executor.memory, it will do disk spilling aggregation.
It will split the aggregation into multiple stage, in each stage, it will partition the aggregated data by hash and dump them into disks. After all the data are aggregated, it will merge all the stages together (partition by partition).
Author: Davies Liu <davies.liu@gmail.com>
Closes#1460 from davies/spill and squashes the following commits:
cad91bf [Davies Liu] call gc.collect() after data.clear() to release memory as much as possible.
37d71f7 [Davies Liu] balance the partitions
902f036 [Davies Liu] add shuffle.py into run-tests
dcf03a9 [Davies Liu] fix memory_info() of psutil
67e6eba [Davies Liu] comment for MAX_TOTAL_PARTITIONS
f6bd5d6 [Davies Liu] rollback next_limit() again, the performance difference is huge:
e74b785 [Davies Liu] fix code style and change next_limit to memory_limit
400be01 [Davies Liu] address all the comments
6178844 [Davies Liu] refactor and improve docs
fdd0a49 [Davies Liu] add long doc string for ExternalMerger
1a97ce4 [Davies Liu] limit used memory and size of objects in partitionBy()
e6cc7f9 [Davies Liu] Merge branch 'master' into spill
3652583 [Davies Liu] address comments
e78a0a0 [Davies Liu] fix style
24cec6a [Davies Liu] get local directory by SPARK_LOCAL_DIR
57ee7ef [Davies Liu] update docs
286aaff [Davies Liu] let spilled aggregation in Python configurable
e9a40f6 [Davies Liu] recursive merger
6edbd1f [Davies Liu] Hash based disk spilling aggregation
Author: Prashant Sharma <prashant.s@imaginea.com>
Closes#1051 from ScrapCodes/SPARK-2014/pyspark-cache and squashes the following commits:
f192df7 [Prashant Sharma] Code Review
2a2f43f [Prashant Sharma] [SPARK-2014] Make PySpark store RDDs in MEMORY_ONLY_SER with compression by default
In CPython, hash of None is different cross machines, it will cause wrong result during shuffle. This PR will fix this.
Author: Davies Liu <davies.liu@gmail.com>
Closes#1371 from davies/hash_of_none and squashes the following commits:
d01745f [Davies Liu] add comments, remove outdated unit tests
5467141 [Davies Liu] disable hijack of hash, use it only for partitionBy()
b7118aa [Davies Liu] use __builtin__ instead of __builtins__
839e417 [Davies Liu] hijack hash to make hash of None consistant cross machines
to avoid overflow in `exp(x)` if `x` is large.
Author: Xiangrui Meng <meng@databricks.com>
Closes#1493 from mengxr/py-logistic and squashes the following commits:
259e863 [Xiangrui Meng] stabilize logistic function in pyspark
http://legacy.python.org/dev/peps/pep-0008/
## Programming Recommendations
- Comparisons to singletons like None should always be done with is or is not, never the equality operators.
Author: Ken Takagiwa <ken@Kens-MacBook-Pro.local>
Closes#1422 from giwa/apache_master and squashes the following commits:
7b361f3 [Ken Takagiwa] follow pep8 None should be checked using is or is not
Author: Prashant Sharma <prashant.s@imaginea.com>
Closes#1354 from ScrapCodes/pep8-comp-1 and squashes the following commits:
9858ea8 [Prashant Sharma] Code Review
d8851b7 [Prashant Sharma] Found # noqa works even inside comment blocks. Not sure if it works with all versions of python.
10c0cef [Prashant Sharma] Made rdd.py pep8 complaint by using Autopep8 and a little manual tweaking.
Author: Andrew Or <andrewor14@gmail.com>
Closes#1365 from andrewor14/master-fs and squashes the following commits:
497f100 [Andrew Or] Sneak in a space and hope no one will notice
05ba6da [Andrew Or] Remove unused val
It should not be the responsibility of the worker subprocess, which
does not intentionally fork, to try and cleanup child processes. Doing
so is complex and interferes with operations such as
platform.system().
If it is desirable to have tighter control over subprocesses, then
namespaces should be used and it should be the manager's resposibility
to handle cleanup.
Author: Matthew Farrellee <matt@redhat.com>
Closes#1247 from mattf/SPARK-1394 and squashes the following commits:
c36f308 [Matthew Farrellee] [SPARK-1394] Remove SIGCHLD handler in worker subprocess
This reverts a change introduced in 3870248740, which redirected all stderr to the OS pipe instead of directly to the `bin/pyspark` shell output. This causes a simple job to hang in two ways:
1. If the cluster is not configured correctly or does not have enough resources, the job hangs without producing any output, because the relevant warning messages are masked.
2. If the stderr volume is large, this could lead to a deadlock if we redirect everything to the OS pipe. From the [python docs](https://docs.python.org/2/library/subprocess.html):
```
Note Do not use stdout=PIPE or stderr=PIPE with this function as that can deadlock
based on the child process output volume. Use Popen with the communicate() method
when you need pipes.
```
Note that we cannot remove `stdout=PIPE` in a similar way, because we currently use it to communicate the py4j port. However, it should be fine (as it has been for a long time) because we do not produce a ton of traffic through `stdout`.
That commit was not merged in branch-1.0, so this fix is for master only.
Author: Andrew Or <andrewor14@gmail.com>
Closes#1178 from andrewor14/fix-python and squashes the following commits:
e68e870 [Andrew Or] Merge branch 'master' of github.com:apache/spark into fix-python
20849a8 [Andrew Or] Tone down stdout interference message
a09805b [Andrew Or] Return more than 1 line of error message to user
6dfbd1e [Andrew Or] Don't swallow original exception
0d1861f [Andrew Or] Provide more helpful output if stdout is garbled
21c9d7c [Andrew Or] Do not mask stderr from output
The jira for the issue can be found at: https://issues.apache.org/jira/browse/SPARK-2061
Most of spark has used over to consistently using `partitions` instead of `splits`. We should do likewise and add a `partitions` method to JavaRDDLike and have `splits` just call that. We should also go through all cases where other API's (e.g. Python) call `splits` and we should change those to use the newer API.
Author: Anant <anant.asty@gmail.com>
Closes#1062 from anantasty/SPARK-2061 and squashes the following commits:
b83ce6b [Anant] Fixed syntax issue
21f9210 [Anant] Fixed version number in deprecation string
9315b76 [Anant] made related changes to use partitions in python api
8c62dd1 [Anant] Made splits deprecated in JavaRDDLike
Adds cogroup for 4 RDDs.
Author: Allan Douglas R. de Oliveira <allandouglas@gmail.com>
Closes#813 from douglaz/more_cogroups and squashes the following commits:
f8d6273 [Allan Douglas R. de Oliveira] Test python groupWith for one more case
0e9009c [Allan Douglas R. de Oliveira] Added scala tests
c3ffcdd [Allan Douglas R. de Oliveira] Added java tests
517a67f [Allan Douglas R. de Oliveira] Added tests for python groupWith
2f402d5 [Allan Douglas R. de Oliveira] Removed TODO
17474f4 [Allan Douglas R. de Oliveira] Use new cogroup function
7877a2a [Allan Douglas R. de Oliveira] Fixed code
ba02414 [Allan Douglas R. de Oliveira] Added varargs cogroup to pyspark
c4a8a51 [Allan Douglas R. de Oliveira] Added java cogroup 4
e94963c [Allan Douglas R. de Oliveira] Fixed spacing
f1ee57b [Allan Douglas R. de Oliveira] Fixed scala style issues
d7196f1 [Allan Douglas R. de Oliveira] Allow the cogroup of 4 RDDs
For shuffle-based operators, such as rdd.groupBy() or rdd.sortByKey(), PySpark will always assume that the default parallelism to use for the reduce side is ctx.defaultParallelism, which is a constant typically determined by the number of cores in cluster.
In contrast, Spark's Partitioner#defaultPartitioner will use the same number of reduce partitions as map partitions unless the defaultParallelism config is explicitly set. This tends to be a better default in order to avoid OOMs, and should also be the behavior of PySpark.
JIRA: https://issues.apache.org/jira/browse/SPARK-2203
Author: Aaron Davidson <aaron@databricks.com>
Closes#1138 from aarondav/pyfix and squashes the following commits:
1bd5751 [Aaron Davidson] SPARK-2203: PySpark defaults to use same num reduce partitions as map partitions
If the gateway process fails to start correctly (e.g., because JAVA_HOME isn't set correctly, there's no Spark jar, etc.), right now pyspark fails because of a very difficult-to-understand error, where we try to parse stdout to get the port where Spark started and there's nothing there. This commit properly catches the error and throws an exception that includes the stderr output for much easier debugging.
Thanks to @shivaram and @stogers for helping to fix this issue!
Author: Kay Ousterhout <kayousterhout@gmail.com>
Closes#383 from kayousterhout/pyspark and squashes the following commits:
36dd54b [Kay Ousterhout] [SPARK-1466] Raise exception if Gateway process doesn't start.
JIRA: https://issues.apache.org/jira/browse/SPARK-2060
Programming guide: http://yhuai.github.io/site/sql-programming-guide.html
Scala doc of SQLContext: http://yhuai.github.io/site/api/scala/index.html#org.apache.spark.sql.SQLContext
Author: Yin Huai <huai@cse.ohio-state.edu>
Closes#999 from yhuai/newJson and squashes the following commits:
227e89e [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
ce8eedd [Yin Huai] rxin's comments.
bc9ac51 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
94ffdaa [Yin Huai] Remove "get" from method names.
ce31c81 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
e2773a6 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
79ea9ba [Yin Huai] Fix typos.
5428451 [Yin Huai] Newline
1f908ce [Yin Huai] Remove extra line.
d7a005c [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
7ea750e [Yin Huai] marmbrus's comments.
6a5f5ef [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
83013fb [Yin Huai] Update Java Example.
e7a6c19 [Yin Huai] SchemaRDD.javaToPython should convert a field with the StructType to a Map.
6d20b85 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
4fbddf0 [Yin Huai] Programming guide.
9df8c5a [Yin Huai] Python API.
7027634 [Yin Huai] Java API.
cff84cc [Yin Huai] Use a SchemaRDD for a JSON dataset.
d0bd412 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
ab810b0 [Yin Huai] Make JsonRDD private.
6df0891 [Yin Huai] Apache header.
8347f2e [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
66f9e76 [Yin Huai] Update docs and use the entire dataset to infer the schema.
8ffed79 [Yin Huai] Update the example.
a5a4b52 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
4325475 [Yin Huai] If a sampled dataset is used for schema inferring, update the schema of the JsonTable after first execution.
65b87f0 [Yin Huai] Fix sampling...
8846af5 [Yin Huai] API doc.
52a2275 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
0387523 [Yin Huai] Address PR comments.
666b957 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
a2313a6 [Yin Huai] Address PR comments.
f3ce176 [Yin Huai] After type conflict resolution, if a NullType is found, StringType is used.
0576406 [Yin Huai] Add Apache license header.
af91b23 [Yin Huai] Merge remote-tracking branch 'upstream/master' into newJson
f45583b [Yin Huai] Infer the schema of a JSON dataset (a text file with one JSON object per line or a RDD[String] with one JSON object per string) and returns a SchemaRDD.
f31065f [Yin Huai] A query plan or a SchemaRDD can print out its schema.
Removes Python syntax in Scaladoc, corrects result in Scaladoc, and removes irrelevant cache() call in Python doc.
Author: Sandy Ryza <sandy@cloudera.com>
Closes#1086 from sryza/sandy-spark-2146 and squashes the following commits:
185ff18 [Sandy Ryza] Use Seq instead of Array
c996120 [Sandy Ryza] SPARK-2146. Fix takeOrdered doc
This never got merged from the apache/incubator-spark repo (which is now deleted) but there had been several rounds of code review on this PR there.
I think this is ready for merging.
Author: Andrew Ash <andrew@andrewash.com>
This patch had conflicts when merged, resolved by
Committer: Reynold Xin <rxin@apache.org>
Closes#369 from ash211/sortby and squashes the following commits:
d09147a [Andrew Ash] Fix Ordering import
43d0a53 [Andrew Ash] Fix missing .collect()
29a54ed [Andrew Ash] Re-enable test by converting to a closure
5a95348 [Andrew Ash] Add license for RDDSuiteUtils
64ed6e3 [Andrew Ash] Remove leaked diff
d4de69a [Andrew Ash] Remove scar tissue
63638b5 [Andrew Ash] Add Python version of .sortBy()
45e0fde [Andrew Ash] Add Java version of .sortBy()
adf84c5 [Andrew Ash] Re-indent to keep line lengths under 100 chars
9d9b9d8 [Andrew Ash] Use parentheses on .collect() calls
0457b69 [Andrew Ash] Ignore failing test
99f0baf [Andrew Ash] Merge branch 'master' into sortby
222ae97 [Andrew Ash] Try moving Ordering objects out to a different class
3fd0dd3 [Andrew Ash] Add (failing) test for sortByKey with explicit Ordering
b8b5bbc [Andrew Ash] Align remove extra spaces that were used to align ='s in test code
8c53298 [Andrew Ash] Actually use ascending and numPartitions parameters
381eef2 [Andrew Ash] Correct silly typo
7db3e84 [Andrew Ash] Support ascending and numPartitions params in sortBy()
0f685fd [Andrew Ash] Merge remote-tracking branch 'origin/master' into sortby
ca4490d [Andrew Ash] Add .sortBy(f) method on RDD
Added batching with default batch size 10 in SchemaRDD.javaToPython
Author: Kan Zhang <kzhang@apache.org>
Closes#1023 from kanzhang/SPARK-2079 and squashes the following commits:
2d1915e [Kan Zhang] [SPARK-2079] Add batching in SchemaRDD.javaToPython
19b0c09 [Kan Zhang] [SPARK-2079] Removing unnecessary wrapping in SchemaRDD.javaToPython
Modified the takeSample method in RDD to use the ScaSRS sampling technique to improve performance. Added a private method that computes sampling rate > sample_size/total to ensure sufficient sample size with success rate >= 0.9999. Added a unit test for the private method to validate choice of sampling rate.
Author: Doris Xin <doris.s.xin@gmail.com>
Author: dorx <doris.s.xin@gmail.com>
Author: Xiangrui Meng <meng@databricks.com>
Closes#916 from dorx/takeSample and squashes the following commits:
5b061ae [Doris Xin] merge master
444e750 [Doris Xin] edge cases
3de882b [dorx] Merge pull request #2 from mengxr/SPARK-1939
82dde31 [Xiangrui Meng] update pyspark's takeSample
48d954d [Doris Xin] remove unused imports from RDDSuite
fb1452f [Doris Xin] allowing num to be greater than count in all cases
1481b01 [Doris Xin] washing test tubes and making coffee
dc699f3 [Doris Xin] give back imports removed by accident in rdd.py
64e445b [Doris Xin] logwarnning as soon as it enters the while loop
55518ed [Doris Xin] added TODO for logging in rdd.py
eff89e2 [Doris Xin] addressed reviewer comments.
ecab508 [Doris Xin] "fixed checkstyle violation
0a9b3e3 [Doris Xin] "reviewer comment addressed"
f80f270 [Doris Xin] Merge branch 'master' into takeSample
ae3ad04 [Doris Xin] fixed edge cases to prevent overflow
065ebcd [Doris Xin] Merge branch 'master' into takeSample
9bdd36e [Doris Xin] Check sample size and move computeFraction
e3fd6a6 [Doris Xin] Merge branch 'master' into takeSample
7cab53a [Doris Xin] fixed import bug in rdd.py
ffea61a [Doris Xin] SPARK-1939: Refactor takeSample method in RDD
1441977 [Doris Xin] SPARK-1939 Refactor takeSample method in RDD to use ScaSRS
Hi, I found this typo while learning spark and thought I'd do a pull request.
Author: Jeff Thompson <jeffreykeatingthompson@gmail.com>
Closes#1065 from jkthompson/docstring-typo-minmax and squashes the following commits:
29b6a26 [Jeff Thompson] fixed typo in docstring for min()
This has been messing up the SQL PySpark tests on Jenkins.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#1054 from pwendell/pyspark and squashes the following commits:
1eb5487 [Patrick Wendell] False change
06f062d [Patrick Wendell] HOTFIX: PySpark tests should be order insensitive
This is a hot fix for the hot fix in fb499be1ac. The changes in that commit did not actually cause the `doctest` module in python to be loaded for the following tests:
- pyspark/broadcast.py
- pyspark/accumulators.py
- pyspark/serializers.py
(@pwendell I might have told you the wrong thing)
Author: Andrew Or <andrewor14@gmail.com>
Closes#1053 from andrewor14/python-test-fix and squashes the following commits:
d2e5401 [Andrew Or] Explain why these tests are handled differently
0bd6fdd [Andrew Or] Fix 3 pyspark tests not being invoked
`ndarray.dot` is not available in numpy 1.4. This PR makes pyspark/mllib compatible with numpy 1.4.
Author: Xiangrui Meng <meng@databricks.com>
Closes#1035 from mengxr/numpy-1.4 and squashes the following commits:
7ad2f0c [Xiangrui Meng] use numpy.dot instead of ndarray.dot
Author: Patrick Wendell <pwendell@gmail.com>
Closes#1036 from pwendell/jenkins-test and squashes the following commits:
9c99856 [Patrick Wendell] Better output during tests
71e7b74 [Patrick Wendell] Removing incorrect python path
74984db [Patrick Wendell] HOTFIX: Allow PySpark tests to run on Jenkins.
So I finally resurrected this PR. It seems the old one against the incubator mirror is no longer available, so I cannot reference it.
This adds initial support for reading Hadoop ```SequenceFile```s, as well as arbitrary Hadoop ```InputFormat```s, in PySpark.
# Overview
The basics are as follows:
1. ```PythonRDD``` object contains the relevant methods, that are in turn invoked by ```SparkContext``` in PySpark
2. The SequenceFile or InputFormat is read on the Scala side and converted from ```Writable``` instances to the relevant Scala classes (in the case of primitives)
3. Pyrolite is used to serialize Java objects. If this fails, the fallback is ```toString```
4. ```PickleSerializer``` on the Python side deserializes.
This works "out the box" for simple ```Writable```s:
* ```Text```
* ```IntWritable```, ```DoubleWritable```, ```FloatWritable```
* ```NullWritable```
* ```BooleanWritable```
* ```BytesWritable```
* ```MapWritable```
It also works for simple, "struct-like" classes. Due to the way Pyrolite works, this requires that the classes satisfy the JavaBeans convenstions (i.e. with fields and a no-arg constructor and getters/setters). (Perhaps in future some sugar for case classes and reflection could be added).
I've tested it out with ```ESInputFormat``` as an example and it works very nicely:
```python
conf = {"es.resource" : "index/type" }
rdd = sc.newAPIHadoopRDD("org.elasticsearch.hadoop.mr.EsInputFormat", "org.apache.hadoop.io.NullWritable", "org.elasticsearch.hadoop.mr.LinkedMapWritable", conf=conf)
rdd.first()
```
I suspect for things like HBase/Cassandra it will be a bit trickier to get it to work out the box.
# Some things still outstanding:
1. ~~Requires ```msgpack-python``` and will fail without it. As originally discussed with Josh, add a ```as_strings``` argument that defaults to ```False```, that can be used if ```msgpack-python``` is not available~~
2. ~~I see from https://github.com/apache/spark/pull/363 that Pyrolite is being used there for SerDe between Scala and Python. @ahirreddy @mateiz what is the plan behind this - is Pyrolite preferred? It seems from a cursory glance that adapting the ```msgpack```-based SerDe here to use Pyrolite wouldn't be too hard~~
3. ~~Support the key and value "wrapper" that would allow a Scala/Java function to be plugged in that would transform whatever the key/value Writable class is into something that can be serialized (e.g. convert some custom Writable to a JavaBean or ```java.util.Map``` that can be easily serialized)~~
4. Support ```saveAsSequenceFile``` and ```saveAsHadoopFile``` etc. This would require SerDe in the reverse direction, that can be handled by Pyrolite. Will work on this as a separate PR
Author: Nick Pentreath <nick.pentreath@gmail.com>
Closes#455 from MLnick/pyspark-inputformats and squashes the following commits:
268df7e [Nick Pentreath] Documentation changes mer @pwendell comments
761269b [Nick Pentreath] Address @pwendell comments, simplify default writable conversions and remove registry.
4c972d8 [Nick Pentreath] Add license headers
d150431 [Nick Pentreath] Merge remote-tracking branch 'upstream/master' into pyspark-inputformats
cde6af9 [Nick Pentreath] Parameterize converter trait
5ebacfa [Nick Pentreath] Update docs for PySpark input formats
a985492 [Nick Pentreath] Move Converter examples to own package
365d0be [Nick Pentreath] Make classes private[python]. Add docs and @Experimental annotation to Converter interface.
eeb8205 [Nick Pentreath] Fix path relative to SPARK_HOME in tests
1eaa08b [Nick Pentreath] HBase -> Cassandra app name oversight
3f90c3e [Nick Pentreath] Merge remote-tracking branch 'upstream/master' into pyspark-inputformats
2c18513 [Nick Pentreath] Add examples for reading HBase and Cassandra InputFormats from Python
b65606f [Nick Pentreath] Add converter interface
5757f6e [Nick Pentreath] Default key/value classes for sequenceFile asre None
085b55f [Nick Pentreath] Move input format tests to tests.py and clean up docs
43eb728 [Nick Pentreath] PySpark InputFormats docs into programming guide
94beedc [Nick Pentreath] Clean up args in PythonRDD. Set key/value converter defaults to None for PySpark context.py methods
1a4a1d6 [Nick Pentreath] Address @mateiz style comments
01e0813 [Nick Pentreath] Merge remote-tracking branch 'upstream/master' into pyspark-inputformats
15a7d07 [Nick Pentreath] Remove default args for key/value classes. Arg names to camelCase
9fe6bd5 [Nick Pentreath] Merge remote-tracking branch 'upstream/master' into pyspark-inputformats
84fe8e3 [Nick Pentreath] Python programming guide space formatting
d0f52b6 [Nick Pentreath] Python programming guide
7caa73a [Nick Pentreath] Merge remote-tracking branch 'upstream/master' into pyspark-inputformats
93ef995 [Nick Pentreath] Add back context.py changes
9ef1896 [Nick Pentreath] Recover earlier changes lost in previous merge for serializers.py
077ecb2 [Nick Pentreath] Recover earlier changes lost in previous merge for context.py
5af4770 [Nick Pentreath] Merge branch 'master' into pyspark-inputformats
35b8e3a [Nick Pentreath] Another fix for test ordering
bef3afb [Nick Pentreath] Merge remote-tracking branch 'upstream/master' into pyspark-inputformats
e001b94 [Nick Pentreath] Fix test failures due to ordering
78978d9 [Nick Pentreath] Add doc for SequenceFile and InputFormat support to Python programming guide
64eb051 [Nick Pentreath] Scalastyle fix
e7552fa [Nick Pentreath] Merge branch 'master' into pyspark-inputformats
44f2857 [Nick Pentreath] Remove msgpack dependency and switch serialization to Pyrolite, plus some clean up and refactoring
c0ebfb6 [Nick Pentreath] Change sequencefile test data generator to easily be called from PySpark tests
1d7c17c [Nick Pentreath] Amend tests to auto-generate sequencefile data in temp dir
17a656b [Nick Pentreath] remove binary sequencefile for tests
f60959e [Nick Pentreath] Remove msgpack dependency and serializer from PySpark
450e0a2 [Nick Pentreath] Merge branch 'master' into pyspark-inputformats
31a2fff [Nick Pentreath] Scalastyle fixes
fc5099e [Nick Pentreath] Add Apache license headers
4e08983 [Nick Pentreath] Clean up docs for PySpark context methods
b20ec7e [Nick Pentreath] Clean up merge duplicate dependencies
951c117 [Nick Pentreath] Merge branch 'master' into pyspark-inputformats
f6aac55 [Nick Pentreath] Bring back msgpack
9d2256e [Nick Pentreath] Merge branch 'master' into pyspark-inputformats
1bbbfb0 [Nick Pentreath] Clean up SparkBuild from merge
a67dfad [Nick Pentreath] Clean up Msgpack serialization and registering
7237263 [Nick Pentreath] Add back msgpack serializer and hadoop file code lost during merging
25da1ca [Nick Pentreath] Add generator for nulls, bools, bytes and maps
65360d5 [Nick Pentreath] Adding test SequenceFiles
0c612e5 [Nick Pentreath] Merge branch 'master' into pyspark-inputformats
d72bf18 [Nick Pentreath] msgpack
dd57922 [Nick Pentreath] Merge remote-tracking branch 'upstream/master' into pyspark-inputformats
e67212a [Nick Pentreath] Add back msgpack dependency
f2d76a0 [Nick Pentreath] Merge branch 'master' into pyspark-inputformats
41856a5 [Nick Pentreath] Merge branch 'master' into pyspark-inputformats
97ef708 [Nick Pentreath] Remove old writeToStream
2beeedb [Nick Pentreath] Merge remote-tracking branch 'upstream/master' into pyspark-inputformats
795a763 [Nick Pentreath] Change name to WriteInputFormatTestDataGenerator. Cleanup some var names. Use SPARK_HOME in path for writing test sequencefile data.
174f520 [Nick Pentreath] Add back graphx settings
703ee65 [Nick Pentreath] Add back msgpack
619c0fa [Nick Pentreath] Merge remote-tracking branch 'upstream/master' into pyspark-inputformats
1c8efbc [Nick Pentreath] Merge remote-tracking branch 'upstream/master' into pyspark-inputformats
eb40036 [Nick Pentreath] Remove unused comment lines
4d7ef2e [Nick Pentreath] Fix indentation
f1d73e3 [Nick Pentreath] mergeConfs returns a copy rather than mutating one of the input arguments
0f5cd84 [Nick Pentreath] Remove unused pair UTF8 class. Add comments to msgpack deserializer
4294cbb [Nick Pentreath] Add old Hadoop api methods. Clean up and expand comments. Clean up argument names
818a1e6 [Nick Pentreath] Add seqencefile and Hadoop InputFormat support to PythonRDD
4e7c9e3 [Nick Pentreath] Merge remote-tracking branch 'upstream/master' into pyspark-inputformats
c304cc8 [Nick Pentreath] Adding supporting sequncefiles for tests. Cleaning up
4b0a43f [Nick Pentreath] Refactoring utils into own objects. Cleaning up old commented-out code
d86325f [Nick Pentreath] Initial WIP of PySpark support for SequenceFile and arbitrary Hadoop InputFormat
Add getNumPartitions to pyspark RDD to provide an intuitive way to get number of partitions in RDD like we can do in scala today.
Author: Syed Hashmi <shashmi@cloudera.com>
Closes#995 from syedhashmi/master and squashes the following commits:
de0ed5e [Syed Hashmi] [SPARK-1308] Add getNumPartitions to pyspark RDD
We should standardize the text format used to represent vectors and labeled points. The proposed formats are the following:
1. dense vector: `[v0,v1,..]`
2. sparse vector: `(size,[i0,i1],[v0,v1])`
3. labeled point: `(label,vector)`
where "(..)" indicates a tuple and "[...]" indicate an array. `loadLabeledPoints` is added to pyspark's `MLUtils`. I didn't add `loadVectors` to pyspark because `RDD.saveAsTextFile` cannot stringify dense vectors in the proposed format automatically.
`MLUtils#saveLabeledData` and `MLUtils#loadLabeledData` are deprecated. Users should use `RDD#saveAsTextFile` and `MLUtils#loadLabeledPoints` instead. In Scala, `MLUtils#loadLabeledPoints` is compatible with the format used by `MLUtils#loadLabeledData`.
CC: @mateiz, @srowen
Author: Xiangrui Meng <meng@databricks.com>
Closes#685 from mengxr/labeled-io and squashes the following commits:
2d1116a [Xiangrui Meng] make loadLabeledData/saveLabeledData deprecated since 1.0.1
297be75 [Xiangrui Meng] change LabeledPoint.parse to LabeledPointParser.parse to maintain binary compatibility
d6b1473 [Xiangrui Meng] Merge branch 'master' into labeled-io
56746ea [Xiangrui Meng] replace # by .
623a5f0 [Xiangrui Meng] merge master
f06d5ba [Xiangrui Meng] add docs and minor updates
640fe0c [Xiangrui Meng] throw SparkException
5bcfbc4 [Xiangrui Meng] update test to add scientific notations
e86bf38 [Xiangrui Meng] remove NumericTokenizer
050fca4 [Xiangrui Meng] use StringTokenizer
6155b75 [Xiangrui Meng] merge master
f644438 [Xiangrui Meng] remove parse methods based on eval from pyspark
a41675a [Xiangrui Meng] python loadLabeledPoint uses Scala's implementation
ce9a475 [Xiangrui Meng] add deserialize_labeled_point to pyspark with tests
e9fcd49 [Xiangrui Meng] add serializeLabeledPoint and tests
aea4ae3 [Xiangrui Meng] minor updates
810d6df [Xiangrui Meng] update tokenizer/parser implementation
7aac03a [Xiangrui Meng] remove Scala parsers
c1885c1 [Xiangrui Meng] add headers and minor changes
b0c50cb [Xiangrui Meng] add customized parser
d731817 [Xiangrui Meng] style update
63dc396 [Xiangrui Meng] add loadLabeledPoints to pyspark
ea122b5 [Xiangrui Meng] Merge branch 'master' into labeled-io
cd6c78f [Xiangrui Meng] add __str__ and parse to LabeledPoint
a7a178e [Xiangrui Meng] add stringify to pyspark's Vectors
5c2dbfa [Xiangrui Meng] add parse to pyspark's Vectors
7853f88 [Xiangrui Meng] update pyspark's SparseVector.__str__
e761d32 [Xiangrui Meng] make LabelPoint.parse compatible with the dense format used before v1.0 and deprecate loadLabeledData and saveLabeledData
9e63a02 [Xiangrui Meng] add loadVectors and loadLabeledPoints
19aa523 [Xiangrui Meng] update toString and add parsers for Vectors and LabeledPoint
Author: Kan Zhang <kzhang@apache.org>
Closes#755 from kanzhang/SPARK-1161 and squashes the following commits:
24ed8a2 [Kan Zhang] [SPARK-1161] Fixing doc tests
44e0615 [Kan Zhang] [SPARK-1161] Adding an optional batchSize with default value 10
d929429 [Kan Zhang] [SPARK-1161] Add saveAsObjectFile and SparkContext.objectFile in Python
Make partitionBy use a tweaked version of hash as its default partition function
since the python hash function does not consistently assign the same value
to None across python processes.
Associated JIRA at https://issues.apache.org/jira/browse/SPARK-1468
Author: Erik Selin <erik.selin@jadedpixel.com>
Closes#371 from tyro89/consistent_hashing and squashes the following commits:
201c301 [Erik Selin] Make partitionBy use a tweaked version of hash as its default partition function since the python hash function does not consistently assign the same value to None across python processes.
stop resetting spark.driver.port in unit tests (scala, java and python).
Author: Syed Hashmi <shashmi@cloudera.com>
Author: CodingCat <zhunansjtu@gmail.com>
Closes#943 from syedhashmi/master and squashes the following commits:
885f210 [Syed Hashmi] Removing unnecessary file (created by mergetool)
b8bd4b5 [Syed Hashmi] Merge remote-tracking branch 'upstream/master'
b895e59 [Syed Hashmi] Revert "[SPARK-1784] Add a new partitioner"
57b6587 [Syed Hashmi] Revert "[SPARK-1784] Add a balanced partitioner"
1574769 [Syed Hashmi] [SPARK-1942] Stop clearing spark.driver.port in unit tests
4354836 [Syed Hashmi] Revert "SPARK-1686: keep schedule() calling in the main thread"
fd36542 [Syed Hashmi] [SPARK-1784] Add a balanced partitioner
6668015 [CodingCat] SPARK-1686: keep schedule() calling in the main thread
4ca94cc [Syed Hashmi] [SPARK-1784] Add a new partitioner
https://issues.apache.org/jira/browse/SPARK-1917
Author: Uri Laserson <laserson@cloudera.com>
Closes#866 from laserson/SPARK-1917 and squashes the following commits:
d947e8c [Uri Laserson] Added test for scipy.special importing
1798bbd [Uri Laserson] SPARK-1917: fix PySpark import of scipy.special
This patch simply ports over the Scala implementation of RDD#take(), which reads the first partition at the driver, then decides how many more partitions it needs to read and will possibly start a real job if it's more than 1. (Note that SparkContext#runJob(allowLocal=true) only runs the job locally if there's 1 partition selected and no parent stages.)
Author: Aaron Davidson <aaron@databricks.com>
Closes#922 from aarondav/take and squashes the following commits:
fa06df9 [Aaron Davidson] SPARK-1839: PySpark RDD#take() shouldn't always read from driver
Added doctest for method textFile and description for methods _initialize_context and _ensure_initialized in context.py
Author: Jyotiska NK <jyotiska123@gmail.com>
Closes#187 from jyotiska/pyspark_context and squashes the following commits:
356f945 [Jyotiska NK] Added doctest for textFile method in context.py
5b23686 [Jyotiska NK] Updated context.py with method descriptions
Author: Reynold Xin <rxin@apache.org>
Closes#871 from rxin/mllib-pep8 and squashes the following commits:
848416f [Reynold Xin] Fixed a typo in the previous cleanup (c -> sc).
a8db4cd [Reynold Xin] Fix PEP8 violations in Python mllib.
Mostly related to the following two rules in PEP8 and PEP257:
- Line length < 72 chars.
- First line should be a concise description of the function/class.
Author: Reynold Xin <rxin@apache.org>
Closes#869 from rxin/docstring-schemardd and squashes the following commits:
7cf0cbc [Reynold Xin] Updated sql.py for pep8 docstring.
0a4aef9 [Reynold Xin] Merge branch 'master' into docstring-schemardd
6678937 [Reynold Xin] Python docstring update for sql.py.
Minor cleanup following #841.
Author: Reynold Xin <rxin@apache.org>
Closes#868 from rxin/schema-count and squashes the following commits:
5442651 [Reynold Xin] SPARK-1822: Some minor cleanup work on SchemaRDD.count()
Author: Kan Zhang <kzhang@apache.org>
Closes#841 from kanzhang/SPARK-1822 and squashes the following commits:
2f8072a [Kan Zhang] [SPARK-1822] Minor style update
cf4baa4 [Kan Zhang] [SPARK-1822] Adding Scaladoc
e67c910 [Kan Zhang] [SPARK-1822] SchemaRDD.count() should use optimizer
If I run the following on a YARN cluster
```
bin/spark-submit sheep.py --master yarn-client
```
it fails because of a mismatch in paths: `spark-submit` thinks that `sheep.py` resides on HDFS, and balks when it can't find the file there. A natural workaround is to add the `file:` prefix to the file:
```
bin/spark-submit file:/path/to/sheep.py --master yarn-client
```
However, this also fails. This time it is because python does not understand URI schemes.
This PR fixes this by automatically resolving all paths passed as command line argument to `spark-submit` properly. This has the added benefit of keeping file and jar paths consistent across different cluster modes. For python, we strip the URI scheme before we actually try to run it.
Much of the code is originally written by @mengxr. Tested on YARN cluster. More tests pending.
Author: Andrew Or <andrewor14@gmail.com>
Closes#853 from andrewor14/submit-paths and squashes the following commits:
0bb097a [Andrew Or] Format path correctly before adding it to PYTHONPATH
323b45c [Andrew Or] Include --py-files on PYTHONPATH for pyspark shell
3c36587 [Andrew Or] Improve error messages (minor)
854aa6a [Andrew Or] Guard against NPE if user gives pathological paths
6638a6b [Andrew Or] Fix spark-shell jar paths after #849 went in
3bb0359 [Andrew Or] Update more comments (minor)
2a1f8a0 [Andrew Or] Update comments (minor)
6af2c77 [Andrew Or] Merge branch 'master' of github.com:apache/spark into submit-paths
a68c4d1 [Andrew Or] Handle Windows python file path correctly
427a250 [Andrew Or] Resolve paths properly for Windows
a591a4a [Andrew Or] Update tests for resolving URIs
6c8621c [Andrew Or] Move resolveURIs to Utils
db8255e [Andrew Or] Merge branch 'master' of github.com:apache/spark into submit-paths
f542dce [Andrew Or] Fix outdated tests
691c4ce [Andrew Or] Ignore special primary resource names
5342ac7 [Andrew Or] Add missing space in error message
02f77f3 [Andrew Or] Resolve command line arguments to spark-submit properly
Author: Kan Zhang <kzhang@apache.org>
Closes#697 from kanzhang/SPARK-1519 and squashes the following commits:
4f8d1ed [Kan Zhang] [SPARK-1519] Support minPartitions param of wholeTextFiles() in PySpark
**Problem.** For `bin/pyspark`, there is currently no other way to specify Spark configuration properties other than through `SPARK_JAVA_OPTS` in `conf/spark-env.sh`. However, this mechanism is supposedly deprecated. Instead, it needs to pick up configurations explicitly specified in `conf/spark-defaults.conf`.
**Solution.** Have `bin/pyspark` invoke `bin/spark-submit`, like all of its counterparts in Scala land (i.e. `bin/spark-shell`, `bin/run-example`). This has the additional benefit of making the invocation of all the user facing Spark scripts consistent.
**Details.** `bin/pyspark` inherently handles two cases: (1) running python applications and (2) running the python shell. For (1), Spark submit already handles running python applications. For cases in which `bin/pyspark` is given a python file, we can simply call pass the file directly to Spark submit and let it handle the rest.
For case (2), `bin/pyspark` starts a python process as before, which launches the JVM as a sub-process. The existing code already provides a code path to do this. All we needed to change is to use `bin/spark-submit` instead of `spark-class` to launch the JVM. This requires modifications to Spark submit to handle the pyspark shell as a special case.
This has been tested locally (OSX and Windows 7), on a standalone cluster, and on a YARN cluster. Running IPython also works as before, except now it takes in Spark submit arguments too.
Author: Andrew Or <andrewor14@gmail.com>
Closes#799 from andrewor14/pyspark-submit and squashes the following commits:
bf37e36 [Andrew Or] Minor changes
01066fa [Andrew Or] bin/pyspark for Windows
c8cb3bf [Andrew Or] Handle perverse app names (with escaped quotes)
1866f85 [Andrew Or] Windows is not cooperating
456d844 [Andrew Or] Guard against shlex hanging if PYSPARK_SUBMIT_ARGS is not set
7eebda8 [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-submit
b7ba0d8 [Andrew Or] Address a few comments (minor)
06eb138 [Andrew Or] Use shlex instead of writing our own parser
05879fa [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-submit
a823661 [Andrew Or] Fix --die-on-broken-pipe not propagated properly
6fba412 [Andrew Or] Deal with quotes + address various comments
fe4c8a7 [Andrew Or] Update --help for bin/pyspark
afe47bf [Andrew Or] Fix spark shell
f04aaa4 [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-submit
a371d26 [Andrew Or] Route bin/pyspark through Spark submit
Author: Patrick Wendell <pwendell@gmail.com>
Closes#784 from pwendell/group-by-key and squashes the following commits:
9b4505f [Patrick Wendell] Small fix
6347924 [Patrick Wendell] Documentation: Encourage use of reduceByKey instead of groupByKey.
The default constructor loads default properties, which can fail the test.
Author: Xiangrui Meng <meng@databricks.com>
Closes#775 from mengxr/pyspark-conf-fix and squashes the following commits:
83ef6c4 [Xiangrui Meng] do not load defaults when testing SparkConf in pyspark
Author: Michael Armbrust <michael@databricks.com>
Closes#761 from marmbrus/existingContext and squashes the following commits:
4651051 [Michael Armbrust] Make it possible to create Java/Python SQLContexts from an existing Scala SQLContext.
Tolerate empty strings in PythonRDD
Author: Kan Zhang <kzhang@apache.org>
Closes#644 from kanzhang/SPARK-1690 and squashes the following commits:
c62ad33 [Kan Zhang] Adding Python doctest
473ec4b [Kan Zhang] [SPARK-1690] Tolerating empty elements when saving Python RDD to text files
This fixes https://issues.apache.org/jira/browse/SPARK-1731 by adding the Python includes to the PYTHONPATH before depickling the broadcast values
@airhorns
Author: Bouke van der Bijl <boukevanderbijl@gmail.com>
Closes#656 from bouk/python-includes-before-broadcast and squashes the following commits:
7b0dfe4 [Bouke van der Bijl] Add Python includes to path before depickling broadcast values
Make loading/saving labeled data easier for pyspark users.
Also changed type check in `SparseVector` to allow numpy integers.
Author: Xiangrui Meng <meng@databricks.com>
Closes#672 from mengxr/pyspark-mllib-util and squashes the following commits:
2943fa7 [Xiangrui Meng] format docs
d61668d [Xiangrui Meng] add loadLibSVMFile and saveAsLibSVMFile to pyspark
This patch includes several cleanups to PythonRDD, focused around fixing [SPARK-1579](https://issues.apache.org/jira/browse/SPARK-1579) cleanly. Listed in order of approximate importance:
- The Python daemon waits for Spark to close the socket before exiting,
in order to avoid causing spurious IOExceptions in Spark's
`PythonRDD::WriterThread`.
- Removes the Python Monitor Thread, which polled for task cancellations
in order to kill the Python worker. Instead, we do this in the
onCompleteCallback, since this is guaranteed to be called during
cancellation.
- Adds a "completed" variable to TaskContext to avoid the issue noted in
[SPARK-1019](https://issues.apache.org/jira/browse/SPARK-1019), where onCompleteCallbacks may be execution-order dependent.
Along with this, I removed the "context.interrupted = true" flag in
the onCompleteCallback.
- Extracts PythonRDD::WriterThread to its own class.
Since this patch provides an alternative solution to [SPARK-1019](https://issues.apache.org/jira/browse/SPARK-1019), I did test it with
```
sc.textFile("latlon.tsv").take(5)
```
many times without error.
Additionally, in order to test the unswallowed exceptions, I performed
```
sc.textFile("s3n://<big file>").count()
```
and cut my internet during execution. Prior to this patch, we got the "stdin writer exited early" message, which was unhelpful. Now, we get the SocketExceptions propagated through Spark to the user and get proper (though unsuccessful) task retries.
Author: Aaron Davidson <aaron@databricks.com>
Closes#640 from aarondav/pyspark-io and squashes the following commits:
b391ff8 [Aaron Davidson] Detect "clean socket shutdowns" and stop waiting on the socket
c0c49da [Aaron Davidson] SPARK-1579: Clean up PythonRDD and avoid swallowing IOExceptions
... that do not change schema
Author: Kan Zhang <kzhang@apache.org>
Closes#448 from kanzhang/SPARK-1460 and squashes the following commits:
111e388 [Kan Zhang] silence MiMa errors in EdgeRDD and VertexRDD
91dc787 [Kan Zhang] Taking into account newly added Ordering param
79ed52a [Kan Zhang] [SPARK-1460] Returning SchemaRDD on Set operations that do not change schema
- [x] Move all of them into subpackages of org.apache.spark.examples (right now some are in org.apache.spark.streaming.examples, for instance, and others are in org.apache.spark.examples.mllib)
- [x] Move Python examples into examples/src/main/python
- [x] Update docs to reflect these changes
Author: Sandeep <sandeep@techaddict.me>
This patch had conflicts when merged, resolved by
Committer: Matei Zaharia <matei@databricks.com>
Closes#571 from techaddict/SPARK-1637 and squashes the following commits:
47ef86c [Sandeep] Changes based on Discussions on PR, removing use of RawTextHelper from examples
8ed2d3f [Sandeep] Docs Updated for changes, Change for java examples
5f96121 [Sandeep] Move Python examples into examples/src/main/python
0a8dd77 [Sandeep] Move all Scala Examples to org.apache.spark.examples (some are in org.apache.spark.streaming.examples, for instance, and others are in org.apache.spark.examples.mllib)
This PR updates spark-submit to allow submitting Python scripts (currently only with deploy-mode=client, but that's all that was supported before) and updates the PySpark code to properly find various paths, etc. One significant change is that we assume we can always find the Python files either from the Spark assembly JAR (which will happen with the Maven assembly build in make-distribution.sh) or from SPARK_HOME (which will exist in local mode even if you use sbt assembly, and should be enough for testing). This means we no longer need a weird hack to modify the environment for YARN.
This patch also updates the Python worker manager to run python with -u, which means unbuffered output (send it to our logs right away instead of waiting a while after stuff was written); this should simplify debugging.
In addition, it fixes https://issues.apache.org/jira/browse/SPARK-1709, setting the main class from a JAR's Main-Class attribute if not specified by the user, and fixes a few help strings and style issues in spark-submit.
In the future we may want to make the `pyspark` shell use spark-submit as well, but it seems unnecessary for 1.0.
Author: Matei Zaharia <matei@databricks.com>
Closes#664 from mateiz/py-submit and squashes the following commits:
15e9669 [Matei Zaharia] Fix some uses of path.separator property
051278c [Matei Zaharia] Small style fixes
0afe886 [Matei Zaharia] Add license headers
4650412 [Matei Zaharia] Add pyFiles to PYTHONPATH in executors, remove old YARN stuff, add tests
15f8e1e [Matei Zaharia] Set PYTHONPATH in PythonWorkerFactory in case it wasn't set from outside
47c0655 [Matei Zaharia] More work to make spark-submit work with Python:
d4375bd [Matei Zaharia] Clean up description of spark-submit args a bit and add Python ones
Final pass before the v1.0 release.
* Remove `VectorRDDs`
* Move `BinaryClassificationMetrics` from `evaluation.binary` to `evaluation`
* Change default value of `addIntercept` to false and allow to add intercept in Ridge and Lasso.
* Clean `DecisionTree` package doc and test suite.
* Mark model constructors `private[spark]`
* Rename `loadLibSVMData` to `loadLibSVMFile` and hide `LabelParser` from users.
* Add `saveAsLibSVMFile`.
* Add `appendBias` to `MLUtils`.
Author: Xiangrui Meng <meng@databricks.com>
Closes#524 from mengxr/mllib-cleaning and squashes the following commits:
295dc8b [Xiangrui Meng] update loadLibSVMFile doc
1977ac1 [Xiangrui Meng] fix doc of appendBias
649fcf0 [Xiangrui Meng] rename loadLibSVMData to loadLibSVMFile; hide LabelParser from user APIs
54b812c [Xiangrui Meng] add appendBias
a71e7d0 [Xiangrui Meng] add saveAsLibSVMFile
d976295 [Xiangrui Meng] Merge branch 'master' into mllib-cleaning
b7e5cec [Xiangrui Meng] remove some experimental annotations and make model constructors private[mllib]
9b02b93 [Xiangrui Meng] minor code style update
a593ddc [Xiangrui Meng] fix python tests
fc28c18 [Xiangrui Meng] mark more classes experimental
f6cbbff [Xiangrui Meng] fix Java tests
0af70b0 [Xiangrui Meng] minor
6e139ef [Xiangrui Meng] Merge branch 'master' into mllib-cleaning
94e6dce [Xiangrui Meng] move BinaryLabelCounter and BinaryConfusionMatrixImpl to evaluation.binary
df34907 [Xiangrui Meng] clean DecisionTreeSuite to use LocalSparkContext
c81807f [Xiangrui Meng] set the default value of AddIntercept to false
03389c0 [Xiangrui Meng] allow to add intercept in Ridge and Lasso
c66c56f [Xiangrui Meng] move tree md to package object doc
a2695df [Xiangrui Meng] update guide for BinaryClassificationMetrics
9194f4c [Xiangrui Meng] move BinaryClassificationMetrics one level up
1c1a0e3 [Xiangrui Meng] remove VectorRDDs because it only contains one function that is not necessary for us to maintain
This reopens https://github.com/apache/incubator-spark/pull/640 against the new repo
Author: Sandy Ryza <sandy@cloudera.com>
Closes#30 from sryza/sandy-spark-1004 and squashes the following commits:
89889d4 [Sandy Ryza] Move unzipping py4j to the generate-resources phase so that it gets included in the jar the first time
5165a02 [Sandy Ryza] Fix docs
fd0df79 [Sandy Ryza] PySpark on YARN
`RDD.pipe`'s doctest throws interrupted system call exception on Mac. It can be fixed by wrapping `pipe.stdout.readline` in an iterator.
Author: Xiangrui Meng <meng@databricks.com>
Closes#594 from mengxr/pyspark-pipe and squashes the following commits:
cc32ac9 [Xiangrui Meng] fix interrupted system call error in pyspark's RDD.pipe
Author: Michael Armbrust <michael@databricks.com>
Closes#585 from marmbrus/pythonCacheTable and squashes the following commits:
7ec1f91 [Michael Armbrust] Minor fix to python table caching API.
* Additions to the PySpark API to cancel jobs
* Monitor Thread in PythonRDD to kill Python workers if a task is interrupted
Author: Ahir Reddy <ahirreddy@gmail.com>
Closes#541 from ahirreddy/python-cancel and squashes the following commits:
dfdf447 [Ahir Reddy] Changed success -> completed and made logging message clearer
6c860ab [Ahir Reddy] PR Comments
4b4100a [Ahir Reddy] Success flag
adba6ed [Ahir Reddy] Destroy python workers
27a2f8f [Ahir Reddy] Start the writer thread...
d422f7b [Ahir Reddy] Remove unnecesssary vals
adda337 [Ahir Reddy] Busy wait on the ocntext.interrupted flag, and then kill the python worker
d9e472f [Ahir Reddy] Revert "removed unnecessary vals"
5b9cae5 [Ahir Reddy] removed unnecessary vals
07b54d9 [Ahir Reddy] Fix canceling unit test
8ae9681 [Ahir Reddy] Don't interrupt worker
7722342 [Ahir Reddy] Monitor Thread for python workers
db04e16 [Ahir Reddy] Added canceling api to PySpark
copying form previous pull request https://github.com/apache/spark/pull/462
Its probably better to let the underlying language implementation take care of the default . This was easier to do with python as the default value for seed in random and numpy random is None.
In Scala/Java side it might mean propagating an Option or null(oh no!) down the chain until where the Random is constructed. But, looks like the convention in some other methods was to use System.nanoTime. So, followed that convention.
Conflict with overloaded method in sql.SchemaRDD.sample which also defines default params.
sample(fraction, withReplacement=false, seed=math.random)
Scala does not allow more than one overloaded to have default params. I believe the author intended to override the RDD.sample method and not overload it. So, changed it.
If backward compatible is important, 3 new method can be introduced (without default params) like this
sample(fraction)
sample(fraction, withReplacement)
sample(fraction, withReplacement, seed)
Added some tests for the scala RDD takeSample method.
Author: Arun Ramakrishnan <smartnut007@gmail.com>
This patch had conflicts when merged, resolved by
Committer: Matei Zaharia <matei@databricks.com>
Closes#477 from smartnut007/master and squashes the following commits:
07bb06e [Arun Ramakrishnan] SPARK-1438 fixing more space formatting issues
b9ebfe2 [Arun Ramakrishnan] SPARK-1438 removing redundant import of random in python rddsampler
8d05b1a [Arun Ramakrishnan] SPARK-1438 RDD . Replace System.nanoTime with a Random generated number. python: use a separate instance of Random instead of seeding language api global Random instance.
69619c6 [Arun Ramakrishnan] SPARK-1438 fix spacing issue
0c247db [Arun Ramakrishnan] SPARK-1438 RDD language apis to support optional seed in RDD methods sample/takeSample
If there are no `transpose()` in `self.theta`, a
*ValueError: matrices are not aligned*
is occurring. The former test case just ignore this situation.
Author: Xusen Yin <yinxusen@gmail.com>
Closes#463 from yinxusen/python-naive-bayes and squashes the following commits:
fcbe3bc [Xusen Yin] fix bugs of dot in python
I used the sbt-unidoc plugin (https://github.com/sbt/sbt-unidoc) to create a unified Scaladoc of our public packages, and generate Javadocs as well. One limitation is that I haven't found an easy way to exclude packages in the Javadoc; there is a SBT task that identifies Java sources to run javadoc on, but it's been very difficult to modify it from outside to change what is set in the unidoc package. Some SBT-savvy people should help with this. The Javadoc site also lacks package-level descriptions and things like that, so we may want to look into that. We may decide not to post these right now if it's too limited compared to the Scala one.
Example of the built doc site: http://people.csail.mit.edu/matei/spark-unified-docs/
Author: Matei Zaharia <matei@databricks.com>
This patch had conflicts when merged, resolved by
Committer: Patrick Wendell <pwendell@gmail.com>
Closes#457 from mateiz/better-docs and squashes the following commits:
a63d4a3 [Matei Zaharia] Skip Java/Scala API docs for Python package
5ea1f43 [Matei Zaharia] Fix links to Java classes in Java guide, fix some JS for scrolling to anchors on page load
f05abc0 [Matei Zaharia] Don't include java.lang package names
995e992 [Matei Zaharia] Skip internal packages and class names with $ in JavaDoc
a14a93c [Matei Zaharia] typo
76ce64d [Matei Zaharia] Add groups to Javadoc index page, and a first package-info.java
ed6f994 [Matei Zaharia] Generate JavaDoc as well, add titles, update doc site to use unified docs
acb993d [Matei Zaharia] Add Unidoc plugin for the projects we want Unidoced
Author: Michael Armbrust <michael@databricks.com>
Closes#447 from marmbrus/pythonInsert and squashes the following commits:
c7ab692 [Michael Armbrust] Keep docstrings < 72 chars.
ff62870 [Michael Armbrust] Add insertInto and saveAsTable to Python API.
Author: Reynold Xin <rxin@apache.org>
Closes#444 from rxin/pyspark and squashes the following commits:
fc11356 [Reynold Xin] Made the PySpark shell version checking compatible with Python 2.6.
571830b [Reynold Xin] Fixed broken pyspark shell.
https://issues.apache.org/jira/browse/SPARK-1483
From the original JIRA: " The parameter name is part of the public API in Scala and Python, since you can pass named parameters to a method, so we should name it to this more descriptive term. Everywhere else we refer to "splits" as partitions." - @mateiz
Author: CodingCat <zhunansjtu@gmail.com>
Closes#430 from CodingCat/SPARK-1483 and squashes the following commits:
4b60541 [CodingCat] deprecate defaultMinSplits
ba2c663 [CodingCat] Rename minSplits to minPartitions in public APIs
This will make the tests more stable when not running SQL tests.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#439 from pwendell/hive-tests and squashes the following commits:
88a6032 [Patrick Wendell] FIX: Don't build Hive in assembly unless running Hive tests.
Python alternative for https://github.com/apache/spark/pull/392; managed from shell.py
Author: AbhishekKr <abhikumar163@gmail.com>
Closes#399 from abhishekkr/pyspark_shell and squashes the following commits:
134bdc9 [AbhishekKr] pyspark require Python2, failing if system default is Py3 from shell.py
This makes it possible to create tables and insert into them using the DSL and SQL for the scala and java apis.
Author: Michael Armbrust <michael@databricks.com>
Closes#354 from marmbrus/insertIntoTable and squashes the following commits:
6c6f227 [Michael Armbrust] Create random temporary files in python parquet unit tests.
f5e6d5c [Michael Armbrust] Merge remote-tracking branch 'origin/master' into insertIntoTable
765c506 [Michael Armbrust] Add to JavaAPI.
77b512c [Michael Armbrust] typos.
5c3ef95 [Michael Armbrust] use names for boolean args.
882afdf [Michael Armbrust] Change createTableAs to saveAsTable. Clean up api annotations.
d07d94b [Michael Armbrust] Add tests, support for creating parquet files and hive tables.
fa3fe81 [Michael Armbrust] Make insertInto available on JavaSchemaRDD as well. Add createTableAs function.
This PR adds a SparseVector class in PySpark and updates all the regression, classification and clustering algorithms and models to support sparse data, similar to MLlib. I chose to add this class because SciPy is quite difficult to install in many environments (more so than NumPy), but I plan to add support for SciPy sparse vectors later too, and make the methods work transparently on objects of either type.
On the Scala side, we keep Python sparse vectors sparse and pass them to MLlib. We always return dense vectors from our models.
Some to-do items left:
- [x] Support SciPy's scipy.sparse matrix objects when SciPy is available. We can easily add a function to convert these to our own SparseVector.
- [x] MLlib currently uses a vector with one extra column on the left to represent what we call LabeledPoint in Scala. Do we really want this? It may get annoying once you deal with sparse data since you must add/subtract 1 to each feature index when training. We can remove this API in 1.0 and use tuples for labeling.
- [x] Explain how to use these in the Python MLlib docs.
CC @mengxr, @joshrosen
Author: Matei Zaharia <matei@databricks.com>
Closes#341 from mateiz/py-ml-update and squashes the following commits:
d52e763 [Matei Zaharia] Remove no-longer-needed slice code and handle review comments
ea5a25a [Matei Zaharia] Fix remaining uses of copyto() after merge
b9f97a3 [Matei Zaharia] Fix test
1e1bd0f [Matei Zaharia] Add MLlib logistic regression example in Python
88bc01f [Matei Zaharia] Clean up inheritance of LinearModel in Python, and expose its parametrs
37ab747 [Matei Zaharia] Fix some examples and docs due to changes in MLlib API
da0f27e [Matei Zaharia] Added a MLlib K-means example and updated docs to discuss sparse data
c48e85a [Matei Zaharia] Added some tests for passing lists as input, and added mllib/tests.py to run-tests script.
a07ba10 [Matei Zaharia] Fix some typos and calculation of initial weights
74eefe7 [Matei Zaharia] Added LabeledPoint class in Python
889dde8 [Matei Zaharia] Support scipy.sparse matrices in all our algorithms and models
ab244d1 [Matei Zaharia] Allow SparseVectors to be initialized using a dict
a5d6426 [Matei Zaharia] Add linalg.py to run-tests script
0e7a3d8 [Matei Zaharia] Keep vectors sparse in Java when reading LabeledPoints
eaee759 [Matei Zaharia] Update regression, classification and clustering models for sparse data
2abbb44 [Matei Zaharia] Further work to get linear models working with sparse data
154f45d [Matei Zaharia] Update docs, name some magic values
881fef7 [Matei Zaharia] Added a sparse vector in Python and made Java-Python format more compact
Currently it requires NumPy 1.7 due to using the copyto method (http://docs.scipy.org/doc/numpy/reference/generated/numpy.copyto.html) for extracting data out of an array.
Replace it with a fallback
Author: Sandeep <sandeep@techaddict.me>
Closes#391 from techaddict/1426 and squashes the following commits:
d365962 [Sandeep] SPARK-1426: Make MLlib work with NumPy versions older than 1.7 Currently it requires NumPy 1.7 due to using the copyto method (http://docs.scipy.org/doc/numpy/reference/generated/numpy.copyto.html) for extracting data out of an array. Replace it with a fallback
An initial API that exposes SparkSQL functionality in PySpark. A PythonRDD composed of dictionaries, with string keys and primitive values (boolean, float, int, long, string) can be converted into a SchemaRDD that supports sql queries.
```
from pyspark.context import SQLContext
sqlCtx = SQLContext(sc)
rdd = sc.parallelize([{"field1" : 1, "field2" : "row1"}, {"field1" : 2, "field2": "row2"}, {"field1" : 3, "field2": "row3"}])
srdd = sqlCtx.applySchema(rdd)
sqlCtx.registerRDDAsTable(srdd, "table1")
srdd2 = sqlCtx.sql("SELECT field1 AS f1, field2 as f2 from table1")
srdd2.collect()
```
The last line yields ```[{"f1" : 1, "f2" : "row1"}, {"f1" : 2, "f2": "row2"}, {"f1" : 3, "f2": "row3"}]```
Author: Ahir Reddy <ahirreddy@gmail.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#363 from ahirreddy/pysql and squashes the following commits:
0294497 [Ahir Reddy] Updated log4j properties to supress Hive Warns
307d6e0 [Ahir Reddy] Style fix
6f7b8f6 [Ahir Reddy] Temporary fix MIMA checker. Since we now assemble Spark jar with Hive, we don't want to check the interfaces of all of our hive dependencies
3ef074a [Ahir Reddy] Updated documentation because classes moved to sql.py
29245bf [Ahir Reddy] Cache underlying SchemaRDD instead of generating and caching PythonRDD
f2312c7 [Ahir Reddy] Moved everything into sql.py
a19afe4 [Ahir Reddy] Doc fixes
6d658ba [Ahir Reddy] Remove the metastore directory created by the HiveContext tests in SparkSQL
521ff6d [Ahir Reddy] Trying to get spark to build with hive
ab95eba [Ahir Reddy] Set SPARK_HIVE=true on jenkins
ded03e7 [Ahir Reddy] Added doc test for HiveContext
22de1d4 [Ahir Reddy] Fixed maven pyrolite dependency
e4da06c [Ahir Reddy] Display message if hive is not built into spark
227a0be [Michael Armbrust] Update API links. Fix Hive example.
58e2aa9 [Michael Armbrust] Build Docs for pyspark SQL Api. Minor fixes.
4285340 [Michael Armbrust] Fix building of Hive API Docs.
38a92b0 [Michael Armbrust] Add note to future non-python developers about python docs.
337b201 [Ahir Reddy] Changed com.clearspring.analytics stream version from 2.4.0 to 2.5.1 to match SBT build, and added pyrolite to maven build
40491c9 [Ahir Reddy] PR Changes + Method Visibility
1836944 [Michael Armbrust] Fix comments.
e00980f [Michael Armbrust] First draft of python sql programming guide.
b0192d3 [Ahir Reddy] Added Long, Double and Boolean as usable types + unit test
f98a422 [Ahir Reddy] HiveContexts
79621cf [Ahir Reddy] cleaning up cruft
b406ba0 [Ahir Reddy] doctest formatting
20936a5 [Ahir Reddy] Added tests and documentation
e4d21b4 [Ahir Reddy] Added pyrolite dependency
79f739d [Ahir Reddy] added more tests
7515ba0 [Ahir Reddy] added more tests :)
d26ec5e [Ahir Reddy] added test
e9f5b8d [Ahir Reddy] adding tests
906d180 [Ahir Reddy] added todo explaining cost of creating Row object in python
251f99d [Ahir Reddy] for now only allow dictionaries as input
09b9980 [Ahir Reddy] made jrdd explicitly lazy
c608947 [Ahir Reddy] SchemaRDD now has all RDD operations
725c91e [Ahir Reddy] awesome row objects
55d1c76 [Ahir Reddy] return row objects
4fe1319 [Ahir Reddy] output dictionaries correctly
be079de [Ahir Reddy] returning dictionaries works
cd5f79f [Ahir Reddy] Switched to using Scala SQLContext
e948bd9 [Ahir Reddy] yippie
4886052 [Ahir Reddy] even better
c0fb1c6 [Ahir Reddy] more working
043ca85 [Ahir Reddy] working
5496f9f [Ahir Reddy] doesn't crash
b8b904b [Ahir Reddy] Added schema rdd class
67ba875 [Ahir Reddy] java to python, and python to java
bcc0f23 [Ahir Reddy] Java to python
ab6025d [Ahir Reddy] compiling
The Mesos backend uses this property when setting up a slave process. It is similarly set in the Scala repl (org.apache.spark.repl.SparkILoop), but I couldn't find any analogous for pyspark.
Author: Ivan Wick <ivanwick+github@gmail.com>
This patch had conflicts when merged, resolved by
Committer: Matei Zaharia <matei@databricks.com>
Closes#311 from ivanwick/master and squashes the following commits:
da0c3e4 [Ivan Wick] Set spark.executor.uri from environment variable (needed by Mesos)
Author: Sandeep <sandeep@techaddict.me>
Closes#356 from techaddict/1428 and squashes the following commits:
3bdf5f6 [Sandeep] SPARK-1428: MLlib should convert non-float64 NumPy arrays to float64 instead of complaining
Author: Holden Karau <holden@pigscanfly.ca>
Closes#242 from holdenk/spark-1320-cogroupandgroupshouldpassiterator and squashes the following commits:
f289536 [Holden Karau] Fix bad merge, should have been Iterable rather than Iterator
77048f8 [Holden Karau] Fix merge up to master
d3fe909 [Holden Karau] use toSeq instead
7a092a3 [Holden Karau] switch resultitr to resultiterable
eb06216 [Holden Karau] maybe I should have had a coffee first. use correct import for guava iterables
c5075aa [Holden Karau] If guava 14 had iterables
2d06e10 [Holden Karau] Fix Java 8 cogroup tests for the new API
11e730c [Holden Karau] Fix streaming tests
66b583d [Holden Karau] Fix the core test suite to compile
4ed579b [Holden Karau] Refactor from iterator to iterable
d052c07 [Holden Karau] Python tests now pass with iterator pandas
3bcd81d [Holden Karau] Revert "Try and make pickling list iterators work"
cd1e81c [Holden Karau] Try and make pickling list iterators work
c60233a [Holden Karau] Start investigating moving to iterators for python API like the Java/Scala one. tl;dr: We will have to write our own iterator since the default one doesn't pickle well
88a5cef [Holden Karau] Fix cogroup test in JavaAPISuite for streaming
a5ee714 [Holden Karau] oops, was checking wrong iterator
e687f21 [Holden Karau] Fix groupbykey test in JavaAPISuite of streaming
ec8cc3e [Holden Karau] Fix test issues\!
4b0eeb9 [Holden Karau] Switch cast in PairDStreamFunctions
fa395c9 [Holden Karau] Revert "Add a join based on the problem in SVD"
ec99e32 [Holden Karau] Revert "Revert this but for now put things in list pandas"
b692868 [Holden Karau] Revert
7e533f7 [Holden Karau] Fix the bug
8a5153a [Holden Karau] Revert me, but we have some stuff to debug
b4e86a9 [Holden Karau] Add a join based on the problem in SVD
c4510e2 [Holden Karau] Revert this but for now put things in list pandas
b4e0b1d [Holden Karau] Fix style issues
71e8b9f [Holden Karau] I really need to stop calling size on iterators, it is the path of sadness.
b1ae51a [Holden Karau] Fix some of the types in the streaming JavaAPI suite. Probably still needs more work
37888ec [Holden Karau] core/tests now pass
249abde [Holden Karau] org.apache.spark.rdd.PairRDDFunctionsSuite passes
6698186 [Holden Karau] Revert "I think this might be a bad rabbit hole. Started work to make CoGroupedRDD use iterator and then went crazy"
fe992fe [Holden Karau] hmmm try and fix up basic operation suite
172705c [Holden Karau] Fix Java API suite
caafa63 [Holden Karau] I think this might be a bad rabbit hole. Started work to make CoGroupedRDD use iterator and then went crazy
88b3329 [Holden Karau] Fix groupbykey to actually give back an iterator
4991af6 [Holden Karau] Fix some tests
be50246 [Holden Karau] Calling size on an iterator is not so good if we want to use it after
687ffbc [Holden Karau] This is the it compiles point of replacing Seq with Iterator and JList with JIterator in the groupby and cogroup signatures
This is the default mode for running spark-shell and pyspark, intended to allow users running spark for the first time to see the performance benefits of using multiple cores, while not breaking backwards compatibility for users who use "local" mode and expect exactly 1 core.
Author: Aaron Davidson <aaron@databricks.com>
Closes#182 from aarondav/110 and squashes the following commits:
a88294c [Aaron Davidson] Rebased changes for new spark-shell
a9f393e [Aaron Davidson] SPARK-1099: Introduce local[*] mode to infer number of cores
The reason it wasn't working was passing a bytearray to stream.write(), which is not supported in Python 2.6 but is in 2.7. (This array came from NumPy when we converted data to send it over to Java). Now we just convert those bytearrays to strings of bytes, which preserves nonprintable characters as well.
Author: Matei Zaharia <matei@databricks.com>
Closes#335 from mateiz/mllib-python-2.6 and squashes the following commits:
f26c59f [Matei Zaharia] Update docs to no longer say we need Python 2.7
a84d6af [Matei Zaharia] SPARK-1421. Make MLlib work on Python 2.6
Move the PR#468 of apache-incubator-spark to the apache-spark
"Adding an option to persist Spark RDD blocks into Tachyon."
Author: Haoyuan Li <haoyuan@cs.berkeley.edu>
Author: RongGu <gurongwalker@gmail.com>
Closes#158 from RongGu/master and squashes the following commits:
72b7768 [Haoyuan Li] merge master
9f7fa1b [Haoyuan Li] fix code style
ae7834b [Haoyuan Li] minor cleanup
a8b3ec6 [Haoyuan Li] merge master branch
e0f4891 [Haoyuan Li] better check offheap.
55b5918 [RongGu] address matei's comment on the replication of offHeap storagelevel
7cd4600 [RongGu] remove some logic code for tachyonstore's replication
51149e7 [RongGu] address aaron's comment on returning value of the remove() function in tachyonstore
8adfcfa [RongGu] address arron's comment on inTachyonSize
120e48a [RongGu] changed the root-level dir name in Tachyon
5cc041c [Haoyuan Li] address aaron's comments
9b97935 [Haoyuan Li] address aaron's comments
d9a6438 [Haoyuan Li] fix for pspark
77d2703 [Haoyuan Li] change python api.git status
3dcace4 [Haoyuan Li] address matei's comments
91fa09d [Haoyuan Li] address patrick's comments
589eafe [Haoyuan Li] use TRY_CACHE instead of MUST_CACHE
64348b2 [Haoyuan Li] update conf docs.
ed73e19 [Haoyuan Li] Merge branch 'master' of github.com:RongGu/spark-1
619a9a8 [RongGu] set number of directories in TachyonStore back to 64; added a TODO tag for duplicated code from the DiskStore
be79d77 [RongGu] find a way to clean up some unnecessay metods and classed to make the code simpler
49cc724 [Haoyuan Li] update docs with off_headp option
4572f9f [RongGu] reserving the old apply function API of StorageLevel
04301d3 [RongGu] rename StorageLevel.TACHYON to Storage.OFF_HEAP
c9aeabf [RongGu] rename the StorgeLevel.TACHYON as StorageLevel.OFF_HEAP
76805aa [RongGu] unifies the config properties name prefix; add the configs into docs/configuration.md
e700d9c [RongGu] add the SparkTachyonHdfsLR example and some comments
fd84156 [RongGu] use randomUUID to generate sparkapp directory name on tachyon;minor code style fix
939e467 [Haoyuan Li] 0.4.1-thrift from maven central
86a2eab [Haoyuan Li] tachyon 0.4.1-thrift is in the staging repo. but jenkins failed to download it. temporarily revert it back to 0.4.1
16c5798 [RongGu] make the dependency on tachyon as tachyon-0.4.1-thrift
eacb2e8 [RongGu] Merge branch 'master' of https://github.com/RongGu/spark-1
bbeb4de [RongGu] fix the JsonProtocolSuite test failure problem
6adb58f [RongGu] Merge branch 'master' of https://github.com/RongGu/spark-1
d827250 [RongGu] fix JsonProtocolSuie test failure
716e93b [Haoyuan Li] revert the version
ca14469 [Haoyuan Li] bump tachyon version to 0.4.1-thrift
2825a13 [RongGu] up-merging to the current master branch of the apache spark
6a22c1a [Haoyuan Li] fix scalastyle
8968b67 [Haoyuan Li] exclude more libraries from tachyon dependency to be the same as referencing tachyon-client.
77be7e8 [RongGu] address mateiz's comment about the temp folder name problem. The implementation followed mateiz's advice.
1dcadf9 [Haoyuan Li] typo
bf278fa [Haoyuan Li] fix python tests
e82909c [Haoyuan Li] minor cleanup
776a56c [Haoyuan Li] address patrick's and ali's comments from the previous PR
8859371 [Haoyuan Li] various minor fixes and clean up
e3ddbba [Haoyuan Li] add doc to use Tachyon cache mode.
fcaeab2 [Haoyuan Li] address Aaron's comment
e554b1e [Haoyuan Li] add python code
47304b3 [Haoyuan Li] make tachyonStore in BlockMananger lazy val; add more comments StorageLevels.
dc8ef24 [Haoyuan Li] add old storelevel constructor
e01a271 [Haoyuan Li] update tachyon 0.4.1
8011a96 [RongGu] fix a brought-in mistake in StorageLevel
70ca182 [RongGu] a bit change in comment
556978b [RongGu] fix the scalastyle errors
791189b [RongGu] "Adding an option to persist Spark RDD blocks into Tachyon." move the PR#468 of apache-incubator-spark to the apache-spark
Also clarified comment on each file having to fit in memory
Author: Matei Zaharia <matei@databricks.com>
Closes#327 from mateiz/py-whole-files and squashes the following commits:
9ad64a5 [Matei Zaharia] SPARK-1414. Python API for SparkContext.wholeTextFiles
Since python does not have a library for max heap and usual tricks like inverting values etc.. does not work for all cases.
We have our own implementation of max heap.
Author: Prashant Sharma <prashant.s@imaginea.com>
Closes#97 from ScrapCodes/SPARK-1162/pyspark-top-takeOrdered2 and squashes the following commits:
35f86ba [Prashant Sharma] code review
2b1124d [Prashant Sharma] fixed tests
e8a08e2 [Prashant Sharma] Code review comments.
49e6ba7 [Prashant Sharma] SPARK-1162 added takeOrdered to pyspark
In PR https://github.com/apache/spark/pull/117, we added dense/sparse vector data model and updated KMeans to support sparse input. This PR is to replace all other `Array[Double]` usage by `Vector` in generalized linear models (GLMs) and Naive Bayes. Major changes:
1. `LabeledPoint` becomes `LabeledPoint(Double, Vector)`.
2. Methods that accept `RDD[Array[Double]]` now accept `RDD[Vector]`. We cannot support both in an elegant way because of type erasure.
3. Mark 'createModel' and 'predictPoint' protected because they are not for end users.
4. Add libSVMFile to MLContext.
5. NaiveBayes can accept arbitrary labels (introducing a breaking change to Python's `NaiveBayesModel`).
6. Gradient computation no longer creates temp vectors.
7. Column normalization and centering are removed from Lasso and Ridge because the operation will densify the data. Simple feature transformation can be done before training.
TODO:
1. ~~Use axpy when possible.~~
2. ~~Optimize Naive Bayes.~~
Author: Xiangrui Meng <meng@databricks.com>
Closes#245 from mengxr/vector and squashes the following commits:
eb6e793 [Xiangrui Meng] move libSVMFile to MLUtils and rename to loadLibSVMData
c26c4fc [Xiangrui Meng] update DecisionTree to use RDD[Vector]
11999c7 [Xiangrui Meng] Merge branch 'master' into vector
f7da54b [Xiangrui Meng] add minSplits to libSVMFile
da25e24 [Xiangrui Meng] revert the change to default addIntercept because it might change the behavior of existing code without warning
493f26f [Xiangrui Meng] Merge branch 'master' into vector
7c1bc01 [Xiangrui Meng] add a TODO to NB
b9b7ef7 [Xiangrui Meng] change default value of addIntercept to false
b01df54 [Xiangrui Meng] allow to change or clear threshold in LR and SVM
4addc50 [Xiangrui Meng] merge master
4ca5b1b [Xiangrui Meng] remove normalization from Lasso and update tests
f04fe8a [Xiangrui Meng] remove normalization from RidgeRegression and update tests
d088552 [Xiangrui Meng] use static constructor for MLContext
6f59eed [Xiangrui Meng] update libSVMFile to determine number of features automatically
3432e84 [Xiangrui Meng] update NaiveBayes to support sparse data
0f8759b [Xiangrui Meng] minor updates to NB
b11659c [Xiangrui Meng] style update
78c4671 [Xiangrui Meng] add libSVMFile to MLContext
f0fe616 [Xiangrui Meng] add a test for sparse linear regression
44733e1 [Xiangrui Meng] use in-place gradient computation
e981396 [Xiangrui Meng] use axpy in Updater
db808a1 [Xiangrui Meng] update JavaLR example
befa592 [Xiangrui Meng] passed scala/java tests
75c83a4 [Xiangrui Meng] passed test compile
1859701 [Xiangrui Meng] passed compile
834ada2 [Xiangrui Meng] optimized MLUtils.computeStats update some ml algorithms to use Vector (cont.)
135ab72 [Xiangrui Meng] merge glm
0e57aa4 [Xiangrui Meng] update Lasso and RidgeRegression to parse the weights correctly from GLM mark createModel protected mark predictPoint protected
d7f629f [Xiangrui Meng] fix a bug in GLM when intercept is not used
3f346ba [Xiangrui Meng] update some ml algorithms to use Vector
Author: Prashant Sharma <prashant.s@imaginea.com>
Author: Prashant Sharma <scrapcodes@gmail.com>
Closes#262 from ScrapCodes/SPARK-1336/ReduceVerbosity and squashes the following commits:
87dfa54 [Prashant Sharma] Further reduction in noise and made pyspark tests to fail fast.
811170f [Prashant Sharma] Reducing the ouput of run-tests script.
Author: Prashant Sharma <prashant.s@imaginea.com>
Closes#235 from ScrapCodes/SPARK-1322/top-rev-sort and squashes the following commits:
f316266 [Prashant Sharma] Minor change in comment.
58e58c6 [Prashant Sharma] SPARK-1322, top in pyspark should sort result in descending order.
Doctest added for map in rdd.py
Author: Jyotiska NK <jyotiska123@gmail.com>
Closes#177 from jyotiska/pyspark_rdd_map_doctest and squashes the following commits:
a38527f [Jyotiska NK] Added doctest for map function in rdd.py
Here's the addition of min and max to statscounter.py and min and max methods to rdd.py.
Author: Dan McClary <dan.mcclary@gmail.com>
Closes#144 from dwmclary/SPARK-1246-add-min-max-to-stat-counter and squashes the following commits:
fd3fd4b [Dan McClary] fixed error, updated test
82cde0e [Dan McClary] flipped incorrectly assigned inf values in StatCounter
5d96799 [Dan McClary] added max and min to StatCounter repr for pyspark
21dd366 [Dan McClary] added max and min to StatCounter output, updated doc
1a97558 [Dan McClary] added max and min to StatCounter output, updated doc
a5c13b0 [Dan McClary] Added min and max to Scala and Java RDD, added min and max to StatCounter
ed67136 [Dan McClary] broke min/max out into separate transaction, added to rdd.py
1e7056d [Dan McClary] added underscore to getBucket
37a7dea [Dan McClary] cleaned up boundaries for histogram -- uses real min/max when buckets are derived
29981f2 [Dan McClary] fixed indentation on doctest comment
eaf89d9 [Dan McClary] added correct doctest for histogram
4916016 [Dan McClary] added histogram method, added max and min to statscounter
https://spark-project.atlassian.net/browse/SPARK-1240
It seems that the current implementation does not handle the empty RDD case when run takeSample
In this patch, before calling sample() inside takeSample API, I add a checker for this case and returns an empty Array when it's a empty RDD; also in sample(), I add a checker for the invalid fraction value
In the test case, I also add several lines for this case
Author: CodingCat <zhunansjtu@gmail.com>
Closes#135 from CodingCat/SPARK-1240 and squashes the following commits:
fef57d4 [CodingCat] fix the same problem in PySpark
36db06b [CodingCat] create new test cases for takeSample from an empty red
810948d [CodingCat] further fix
a40e8fb [CodingCat] replace if with require
ad483fd [CodingCat] handle the case with empty RDD when take sample
Author: Prashant Sharma <prashant.s@imaginea.com>
Closes#93 from ScrapCodes/SPARK-1162/pyspark-top-takeOrdered and squashes the following commits:
ece1fa4 [Prashant Sharma] Added top in python.
Author: prabinb <prabin.banka@imaginea.com>
Closes#92 from prabinb/python-api-rdd and squashes the following commits:
51129ca [prabinb] Added missing Python RDD functions Added __repr__ function to StorageLevel class. Added doctest for RDD.getStorageLevel().
Author: Prashant Sharma <prashant.s@imaginea.com>
Closes#115 from ScrapCodes/SPARK-1168/pyspark-foldByKey and squashes the following commits:
db6f67e [Prashant Sharma] SPARK-1168, Added foldByKey to pyspark.
Author: jyotiska <jyotiska123@gmail.com>
Closes#34 from jyotiska/pyspark_code and squashes the following commits:
c9439be [jyotiska] replaced dict with namedtuple
a6bf4cd [jyotiska] added callsite info for context.py
was raised earlier as a part of apache/incubator-spark#486
Author: Prabin Banka <prabin.banka@imaginea.com>
Closes#76 from prabinb/python-api-zip and squashes the following commits:
b1a31a0 [Prabin Banka] Added Python RDD.zip function
(Continued from old repo, prior discussion at https://github.com/apache/incubator-spark/pull/615)
This patch cements our deprecation of the SPARK_MEM environment variable by replacing it with three more specialized variables:
SPARK_DAEMON_MEMORY, SPARK_EXECUTOR_MEMORY, and SPARK_DRIVER_MEMORY
The creation of the latter two variables means that we can safely set driver/job memory without accidentally setting the executor memory. Neither is public.
SPARK_EXECUTOR_MEMORY is only used by the Mesos scheduler (and set within SparkContext). The proper way of configuring executor memory is through the "spark.executor.memory" property.
SPARK_DRIVER_MEMORY is the new way of specifying the amount of memory run by jobs launched by spark-class, without possibly affecting executor memory.
Other memory considerations:
- The repl's memory can be set through the "--drivermem" command-line option, which really just sets SPARK_DRIVER_MEMORY.
- run-example doesn't use spark-class, so the only way to modify examples' memory is actually an unusual use of SPARK_JAVA_OPTS (which is normally overriden in all cases by spark-class).
This patch also fixes a lurking bug where spark-shell misused spark-class (the first argument is supposed to be the main class name, not java options), as well as a bug in the Windows spark-class2.cmd. I have not yet tested this patch on either Windows or Mesos, however.
Author: Aaron Davidson <aaron@databricks.com>
Closes#99 from aarondav/sparkmem and squashes the following commits:
9df4c68 [Aaron Davidson] SPARK-929: Fully deprecate usage of SPARK_MEM
Author: Prashant Sharma <prashant.s@imaginea.com>
Author: Prashant Sharma <scrapcodes@gmail.com>
Closes#80 from ScrapCodes/SPARK-1165/RDD.intersection and squashes the following commits:
9b015e9 [Prashant Sharma] Added a note, shuffle is required for intersection.
1fea813 [Prashant Sharma] correct the lines wrapping
d0c71f3 [Prashant Sharma] SPARK-1165 RDD.intersection in java
d6effee [Prashant Sharma] SPARK-1165 Implemented RDD.intersection in python.
The following Python APIs are added,
RDD.id()
SparkContext.setJobGroup()
SparkContext.setLocalProperty()
SparkContext.getLocalProperty()
SparkContext.sparkUser()
was raised earlier as a part of apache/incubator-spark#486
Author: Prabin Banka <prabin.banka@imaginea.com>
Closes#75 from prabinb/python-api-backup and squashes the following commits:
cc3c6cd [Prabin Banka] Added missing Python APIs
Author: Prashant Sharma <prashant.s@imaginea.com>
Closes#73 from ScrapCodes/SPARK-1109/wrong-API-docs and squashes the following commits:
1a55b58 [Prashant Sharma] SPARK-1109 wrong API docs for pyspark map function
This surroungs the complete worker code in a try/except block so we catch any error that arrives. An example would be the depickling failing for some reason
@JoshRosen
Author: Bouke van der Bijl <boukevanderbijl@gmail.com>
Closes#644 from bouk/catch-depickling-errors and squashes the following commits:
f0f67cc [Bouke van der Bijl] Lol indentation
0e4d504 [Bouke van der Bijl] Surround the complete python worker with the try block
Updated doctests for mapValues and flatMapValues in rdd.py
Author: jyotiska <jyotiska123@gmail.com>
Closes#621 from jyotiska/python_spark and squashes the following commits:
716f7cd [jyotiska] doctest updated for mapValues, flatMapValues in rdd.py
Fixed minor typo in worker.py
Author: jyotiska <jyotiska123@gmail.com>
Closes#630 from jyotiska/pyspark_code and squashes the following commits:
ee44201 [jyotiska] typo fixed in worker.py
Patch to allow PySpark to use existing JVM and Gateway. Changes to PySpark implementation of SparkConf to take existing SparkConf JVM handle. Change to PySpark SparkContext to allow subclass specific context initialization.
Author: Ahir Reddy <ahirreddy@gmail.com>
Closes#622 from ahirreddy/pyspark-existing-jvm and squashes the following commits:
a86f457 [Ahir Reddy] Patch to allow PySpark to use existing JVM and Gateway. Changes to PySpark implementation of SparkConf to take existing SparkConf JVM handle. Change to PySpark SparkContext to allow subclass specific context initialization.
Added example Python code for sort
I added an example Python code for sort. Right now, PySpark has limited examples for new people willing to use the project. This example code sorts integers stored in a file. I was able to sort 5 million, 10 million and 25 million integers with this code.
Author: jyotiska <jyotiska123@gmail.com>
== Merge branch commits ==
commit 8ad8faf6c8e02ae1cd68565d98524edf165f54df
Author: jyotiska <jyotiska123@gmail.com>
Date: Sun Feb 9 11:00:41 2014 +0530
Added comments in code on collect() method
commit 6f98f1e313f4472a7c2207d36c4f0fbcebc95a8c
Author: jyotiska <jyotiska123@gmail.com>
Date: Sat Feb 8 13:12:37 2014 +0530
Updated python example code sort.py
commit 945e39a5d68daa7e5bab0d96cbd35d7c4b04eafb
Author: jyotiska <jyotiska123@gmail.com>
Date: Sat Feb 8 12:59:09 2014 +0530
Added example python code for sort
Version number to 1.0.0-SNAPSHOT
Since 0.9.0-incubating is done and out the door, we shouldn't be building 0.9.0-incubating-SNAPSHOT anymore.
@pwendell
Author: Mark Hamstra <markhamstra@gmail.com>
== Merge branch commits ==
commit 1b00a8a7c1a7f251b4bb3774b84b9e64758eaa71
Author: Mark Hamstra <markhamstra@gmail.com>
Date: Wed Feb 5 09:30:32 2014 -0800
Version number to 1.0.0-SNAPSHOT
This fixes SPARK-1043, a bug introduced in 0.9.0
where PySpark couldn't serialize strings > 64kB.
This fix was written by @tyro89 and @bouk in #512.
This commit squashes and rebases their pull request
in order to fix some merge conflicts.
Fix PySpark hang when input files are deleted (SPARK-1025)
This pull request addresses [SPARK-1025](https://spark-project.atlassian.net/browse/SPARK-1025), an issue where PySpark could hang if its input files were deleted.
Remove Typesafe Config usage and conf files to fix nested property names
With Typesafe Config we had the subtle problem of no longer allowing
nested property names, which are used for a few of our properties:
http://apache-spark-developers-list.1001551.n3.nabble.com/Config-properties-broken-in-master-td208.html
This PR is for branch 0.9 but should be added into master too.
(cherry picked from commit 34e911ce9a)
Signed-off-by: Patrick Wendell <pwendell@gmail.com>
This helps in case the exception happened while serializing a record to
be sent to Java, leaving the stream to Java in an inconsistent state
where PythonRDD won't be able to read the error.
We've used camel case in other Spark methods so it felt reasonable to
keep using it here and make the code match Scala/Java as much as
possible. Note that parameter names matter in Python because it allows
passing optional parameters by name.
- Added a Python wrapper for Naive Bayes
- Updated the Scala Naive Bayes to match the style of our other
algorithms better and in particular make it easier to call from Java
(added builder pattern, removed default value in train method)
- Updated Python MLlib functions to not require a SparkContext; we can
get that from the RDD the user gives
- Added a toString method in LabeledPoint
- Made the Python MLlib tests run as part of run-tests as well (before
they could only be run individually through each file)
SPARK-991: Report information gleaned from a Python stacktrace in the UI
Scala:
- Added setCallSite/clearCallSite to SparkContext and JavaSparkContext.
These functions mutate a LocalProperty called "externalCallSite."
- Add a wrapper, getCallSite, that checks for an externalCallSite and, if
none is found, calls the usual Utils.formatSparkCallSite.
- Change everything that calls Utils.formatSparkCallSite to call
getCallSite instead. Except getCallSite.
- Add wrappers to setCallSite/clearCallSite wrappers to JavaSparkContext.
Python:
- Add a gruesome hack to rdd.py that inspects the traceback and guesses
what you want to see in the UI.
- Add a RAII wrapper around said gruesome hack that calls
setCallSite/clearCallSite as appropriate.
- Wire said RAII wrapper up around three calls into the Scala code.
I'm not sure that I hit all the spots with the RAII wrapper. I'm also
not sure that my gruesome hack does exactly what we want.
One could also approach this change by refactoring
runJob/submitJob/runApproximateJob to take a call site, then threading
that parameter through everything that needs to know it.
One might object to the pointless-looking wrappers in JavaSparkContext.
Unfortunately, I can't directly access the SparkContext from
Python---or, if I can, I don't know how---so I need to wrap everything
that matters in JavaSparkContext.
Conflicts:
core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala
Also replaced SparkConf.getOrElse with just a "get" that takes a default
value, and added getInt, getLong, etc to make code that uses this
simpler later on.
Bug fixes for file input stream and checkpointing
- Fixed bugs in the file input stream that led the stream to fail due to transient HDFS errors (listing files when a background thread it deleting fails caused errors, etc.)
- Updated Spark's CheckpointRDD and Streaming's CheckpointWriter to use SparkContext.hadoopConfiguration, to allow checkpoints to be written to any HDFS compatible store requiring special configuration.
- Changed the API of SparkContext.setCheckpointDir() - eliminated the unnecessary 'useExisting' parameter. Now SparkContext will always create a unique subdirectory within the user specified checkpoint directory. This is to ensure that previous checkpoint files are not accidentally overwritten.
- Fixed bug where setting checkpoint directory as a relative local path caused the checkpointing to fail.
The test in context.py created two different instances of the
SparkContext class by copying "globals", so that some tests can have a
global "sc" object and others can try initializing their own contexts.
This led to two JVM gateways being created since SparkConf also looked
at pyspark.context.SparkContext to get the JVM.
Python bindings for mllib
This pull request contains Python bindings for the regression, clustering, classification, and recommendation tools in mllib.
For each 'train' frontend exposed, there is a Scala stub in PythonMLLibAPI.scala and a Python stub in mllib.py. The Python stub serialises the input RDD and any vector/matrix arguments into a mutually-understood format and calls the Scala stub. The Scala stub deserialises the RDD and the vector/matrix arguments, calls the appropriate 'train' function, serialises the resulting model, and returns the serialised model.
ALSModel is slightly different since a MatrixFactorizationModel has RDDs inside. The Scala stub returns a handle to a Scala MatrixFactorizationModel; prediction is done by calling the Scala predict method.
I have tested these bindings on an x86_64 machine running Linux. There is a risk that these bindings may fail on some choose-your-own-endian platform if Python's endian differs from java.nio.ByteBuffer's idea of the native byte order.
Add collectPartition to JavaRDD interface.
This interface is useful for implementing `take` from other language frontends where the data is serialized. Also remove `takePartition` from PythonRDD and use `collectPartition` in rdd.py.
Thanks @concretevitamin for the original change and tests.
Change the implementation to use runJob instead of PartitionPruningRDD.
Also update the unit tests and the python take implementation
to use the new interface.
