[SPARK-1460] Returning SchemaRDD instead of normal RDD on Set operations...

... 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
SPARK-1579: Clean up PythonRDD and avoid swallowing IOExceptions

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
[SQL] Fix Performance Issue in data type casting

Using lazy val object instead of function in the class Cast, which improved the performance nearly by 2X in my local micro-benchmark.

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

Closes #679 from chenghao-intel/fix_type_casting and squashes the following commits:

71b0902 [Cheng Hao] using lazy val object instead of function for data type casting
Nicer logging for SecurityManager startup

Happy to open a jira ticket if you'd like to track one there.

Author: Andrew Ash <andrew@andrewash.com>

Closes #678 from ash211/SecurityManagerLogging and squashes the following commits:

2aa0b7a [Andrew Ash] Nicer logging for SecurityManager startup
Typo fix: fetchting -> fetching

Author: Andrew Ash <andrew@andrewash.com>

Closes #680 from ash211/patch-3 and squashes the following commits:

9ce3746 [Andrew Ash] Typo fix: fetchting -> fetching
[SPARK-1688] Propagate PySpark worker stderr to driver

When at least one of the following conditions is true, PySpark cannot be loaded:

1. PYTHONPATH is not set
2. PYTHONPATH does not contain the python directory (or jar, in the case of YARN)
3. The jar does not contain pyspark files (YARN)
4. The jar does not contain py4j files (YARN)

However, we currently throw the same random `java.io.EOFException` for all of the above cases, when trying to read from the python daemon's output. This message is super unhelpful.

This PR includes the python stderr and the PYTHONPATH in the exception propagated to the driver. Now, the exception message looks something like:

```
Error from python worker:
  : No module named pyspark
PYTHONPATH was:
  /path/to/spark/python:/path/to/some/jar
java.io.EOFException
  <stack trace>
```

whereas before it was just

```
java.io.EOFException
  <stack trace>
```

Author: Andrew Or <andrewor14@gmail.com>

Closes #603 from andrewor14/pyspark-exception and squashes the following commits:

10d65d3 [Andrew Or] Throwable -> Exception, worker -> daemon
862d1d7 [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-exception
a5ed798 [Andrew Or] Use block string and interpolation instead of var (minor)
cc09c45 [Andrew Or] Account for the fact that the python daemon may not have terminated yet
444f019 [Andrew Or] Use the new RedirectThread + include system PYTHONPATH
aab00ae [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-exception
0cc2402 [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-exception
783efe2 [Andrew Or] Make python daemon stderr indentation consistent
9524172 [Andrew Or] Avoid potential NPE / error stream contention + Move things around
29f9688 [Andrew Or] Add back original exception type
e92d36b [Andrew Or] Include python worker stderr in the exception propagated to the driver
7c69360 [Andrew Or] Merge branch 'master' of github.com:apache/spark into pyspark-exception
cdbc185 [Andrew Or] Fix python attribute not found exception when PYTHONPATH is not set
dcc0353 [Andrew Or] Check both python and system environment variables for PYTHONPATH
6c09c21 [Andrew Or] Validate PYTHONPATH and PySpark modules before starting python workers
SPARK-1569 Spark on Yarn, authentication broken by pr299

Pass the configs as java options since the executor needs to know before it registers whether to create the connection using authentication or not.    We could see about passing only the authentication configs but for now I just had it pass them all.

I also updating it to use a list to construct the command to make it the same as ClientBase and avoid any issues with spaces.

Author: Thomas Graves <tgraves@apache.org>

Closes #649 from tgravescs/SPARK-1569 and squashes the following commits:

0178ab8 [Thomas Graves] add akka settings
22a8735 [Thomas Graves] Change to only path spark.auth* configs
8ccc1d4 [Thomas Graves] SPARK-1569 Spark on Yarn, authentication broken
[SPARK-1743][MLLIB] add loadLibSVMFile and saveAsLibSVMFile to pyspark

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
Update GradientDescentSuite.scala

use more faster way to construct an array

Author: baishuo(白硕) <vc_java@hotmail.com>

Closes #588 from baishuo/master and squashes the following commits:

45b95fb [baishuo(白硕)] Update GradientDescentSuite.scala
c03b61c [baishuo(白硕)] Update GradientDescentSuite.scala
b666d27 [baishuo(白硕)] Update GradientDescentSuite.scala
SPARK-1544 Add support for deep decision trees.

@etrain and I came with a PR for arbitrarily deep decision trees at the cost of multiple passes over the data at deep tree levels.

To summarize:
1) We take a parameter that indicates the amount of memory users want to reserve for computation on each worker (and 2x that at the driver).
2) Using that information, we calculate two things - the maximum depth to which we train as usual (which is, implicitly, the maximum number of nodes we want to train in parallel), and the size of the groups we should use in the case where we exceed this depth.

cc: @atalwalkar, @hirakendu, @mengxr

Author: Manish Amde <manish9ue@gmail.com>
Author: manishamde <manish9ue@gmail.com>
Author: Evan Sparks <sparks@cs.berkeley.edu>

Closes #475 from manishamde/deep_tree and squashes the following commits:

968ca9d [Manish Amde] merged master
7fc9545 [Manish Amde] added docs
ce004a1 [Manish Amde] minor formatting
b27ad2c [Manish Amde] formatting
426bb28 [Manish Amde] programming guide blurb
8053fed [Manish Amde] more formatting
5eca9e4 [Manish Amde] grammar
4731cda [Manish Amde] formatting
5e82202 [Manish Amde] added documentation, fixed off by 1 error in max level calculation
cbd9f14 [Manish Amde] modified scala.math to math
dad9652 [Manish Amde] removed unused imports
e0426ee [Manish Amde] renamed parameter
718506b [Manish Amde] added unit test
1517155 [Manish Amde] updated documentation
9dbdabe [Manish Amde] merge from master
719d009 [Manish Amde] updating user documentation
fecf89a [manishamde] Merge pull request #6 from etrain/deep_tree
0287772 [Evan Sparks] Fixing scalastyle issue.
2f1e093 [Manish Amde] minor: added doc for maxMemory parameter
2f6072c [manishamde] Merge pull request #5 from etrain/deep_tree
abc5a23 [Evan Sparks] Parameterizing max memory.
50b143a [Manish Amde] adding support for very deep trees
SPARK-1668: Add implicit preference as an option to examples/MovieLensALS

Add --implicitPrefs as an command-line option to the example app MovieLensALS under examples/

Author: Sandeep <sandeep@techaddict.me>

Closes #597 from techaddict/SPARK-1668 and squashes the following commits:

8b371dc [Sandeep] Second Pass on reviews by mengxr
eca9d37 [Sandeep] based on mengxr's suggestions
937e54c [Sandeep] Changes
5149d40 [Sandeep] Changes based on review
1dd7657 [Sandeep] use mean()
42444d7 [Sandeep] Based on Suggestions by mengxr
e3082fa [Sandeep] SPARK-1668: Add implicit preference as an option to examples/MovieLensALS Add --implicitPrefs as an command-line option to the example app MovieLensALS under examples/
Use numpy directly for matrix multiply.

Using matrix multiply to compute XtX and XtY yields a 5-20x speedup depending on problem size.

For example - the following takes 19s locally after this change vs. 5m21s before the change. (16x speedup).
bin/pyspark examples/src/main/python/als.py local[8] 1000 1000 50 10 10

Author: Evan Sparks <evan.sparks@gmail.com>

Closes #687 from etrain/patch-1 and squashes the following commits:

e094dbc [Evan Sparks] Touching only diaganols on update.
d1ab9b6 [Evan Sparks] Use numpy directly for matrix multiply.
[SQL] Improve SparkSQL Aggregates

* Add native min/max (was using hive before).
* Handle nulls correctly in Avg and Sum.

Author: Michael Armbrust <michael@databricks.com>

Closes #683 from marmbrus/aggFixes and squashes the following commits:

64fe30b [Michael Armbrust] Improve SparkSQL Aggregates * Add native min/max (was using hive before). * Handle nulls correctly in Avg and Sum.