[SPARK-3140] Clarify confusing PySpark exception message

We read the py4j port from the stdout of the `bin/spark-submit` subprocess. If there is interference in stdout (e.g. a random echo in `spark-submit`), we throw an exception with a warning message. We do not, however, distinguish between this case from the case where no stdout is produced at all.

I wasted a non-trivial amount of time being baffled by this exception in search of places where I print random whitespace (in vain, of course). A clearer exception message that distinguishes between these cases will prevent similar headaches that I have gone through.

Author: Andrew Or <andrewor14@gmail.com>

Closes #2067 from andrewor14/python-exception and squashes the following commits:

742f823 [Andrew Or] Further clarify warning messages
e96a7a0 [Andrew Or] Distinguish between unexpected output and no output at all
[SPARK-3143][MLLIB] add tf-idf user guide

Moved TF-IDF before Word2Vec because the former is more basic. I also added a link for Word2Vec. atalwalkar

Author: Xiangrui Meng <meng@databricks.com>

Closes #2061 from mengxr/tfidf-doc and squashes the following commits:

ca04c70 [Xiangrui Meng] address comments
a5ea4b4 [Xiangrui Meng] add tf-idf user guide
[SPARK-2843][MLLIB] add a section about regularization parameter in ALS

atalwalkar srowen

Author: Xiangrui Meng <meng@databricks.com>

Closes #2064 from mengxr/als-doc and squashes the following commits:

b2e20ab [Xiangrui Meng] introduced -> discussed
98abdd7 [Xiangrui Meng] add reference
339bd08 [Xiangrui Meng] add a section about regularization parameter in ALS
[SPARK-2840] [mllib] DecisionTree doc update (Java, Python examples)

Updated DecisionTree documentation, with examples for Java, Python.
Added same Java example to code as well.
CC: @mengxr  @manishamde @atalwalkar

Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com>

Closes #2063 from jkbradley/dt-docs and squashes the following commits:

2dd2c19 [Joseph K. Bradley] Last updates based on github review.
9dd1b6b [Joseph K. Bradley] Updated decision tree doc.
d802369 [Joseph K. Bradley] Updates based on comments: cache data, corrected doc text.
b9bee04 [Joseph K. Bradley] Updated DT examples
57eee9f [Joseph K. Bradley] Created JavaDecisionTree example from example in docs, and corrected doc example as needed.
d939a92 [Joseph K. Bradley] Updated DecisionTree documentation.  Added Java, Python examples.
[SPARK-2742][yarn] delete useless variables

Author: XuTingjun <1039320815@qq.com>

Closes #1614 from XuTingjun/yarn-bug and squashes the following commits:

f07096e [XuTingjun] Update ClientArguments.scala
Link to Contributing to Spark wiki page on README.md.
[SPARK-3169] Removed dependency on spark streaming test from spark flume sink

Due to maven bug https://jira.codehaus.org/browse/MNG-1378, maven could not resolve spark streaming classes required by the spark-streaming test-jar dependency of external/flume-sink. There is no particular reason that the external/flume-sink has to depend on Spark Streaming at all, so I am eliminating this dependency. Also I have removed the exclusions present in the Flume dependencies, as there is no reason to exclude them (they were excluded in the external/flume module to prevent dependency collisions with Spark).

Since Jenkins will test the sbt build and the unit test, I only tested maven compilation locally.

Author: Tathagata Das <tathagata.das1565@gmail.com>

Closes #2101 from tdas/spark-sink-pom-fix and squashes the following commits:

8f42621 [Tathagata Das] Added Flume sink exclusions back, and added netty to test dependencies
93b559f [Tathagata Das] Removed dependency on spark streaming test from spark flume sink
[SPARK-2963] REGRESSION - The description about how to build for using CLI and Thrift JDBC server is absent in proper document  -

The most important things I mentioned in #1885 is as follows.

* People who build Spark is not always programmer.
* If a person who build Spark is not a programmer, he/she won't read programmer's guide before building.

So, how to build for using CLI and JDBC server is not only in programmer's guide.

Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>

Closes #2080 from sarutak/SPARK-2963 and squashes the following commits:

ee07c76 [Kousuke Saruta] Modified regression of the description about building for using Thrift JDBC server and CLI
ed53329 [Kousuke Saruta] Modified description and notaton of proper noun
07c59fc [Kousuke Saruta] Added a description about how to build to use HiveServer and CLI for SparkSQL to building-with-maven.md
6e6645a [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-2963
c88fa93 [Kousuke Saruta] Added a description about building to use HiveServer and CLI for SparkSQL
[SPARK-3068]remove MaxPermSize option for jvm 1.8

In JVM 1.8.0, MaxPermSize is no longer supported.
In spark `stderr` output, there would be a line of

    Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=128m; support was removed in 8.0

Author: Daoyuan Wang <daoyuan.wang@intel.com>

Closes #2011 from adrian-wang/maxpermsize and squashes the following commits:

ef1d660 [Daoyuan Wang] direct get java version in runtime
37db9c1 [Daoyuan Wang] code refine
3c1d554 [Daoyuan Wang] remove MaxPermSize option for jvm 1.8
[Minor] fix typo

Fix a typo in comment.

Author: Liang-Chi Hsieh <viirya@gmail.com>

Closes #2105 from viirya/fix_typo and squashes the following commits:

6596a80 [Liang-Chi Hsieh] fix typo.
[SQL] Make functionRegistry in HiveContext transient.

Seems we missed `transient` for the `functionRegistry` in `HiveContext`.

cc: marmbrus

Author: Yin Huai <huaiyin.thu@gmail.com>

Closes #2074 from yhuai/makeFunctionRegistryTransient and squashes the following commits:

6534e7d [Yin Huai] Make functionRegistry transient.
[SPARK-2554][SQL] CountDistinct partial aggregation and object allocation improvements

Author: Michael Armbrust <michael@databricks.com>
Author: Gregory Owen <greowen@gmail.com>

Closes #1935 from marmbrus/countDistinctPartial and squashes the following commits:

5c7848d [Michael Armbrust] turn off caching in the constructor
8074a80 [Michael Armbrust] fix tests
32d216f [Michael Armbrust] reynolds comments
c122cca [Michael Armbrust] Address comments, add tests
b2e8ef3 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into countDistinctPartial
fae38f4 [Michael Armbrust] Fix style
fdca896 [Michael Armbrust] cleanup
93d0f64 [Michael Armbrust] metastore concurrency fix.
db44a30 [Michael Armbrust] JIT hax.
3868f6c [Michael Armbrust] Merge pull request #9 from GregOwen/countDistinctPartial
c9e67de [Gregory Owen] Made SpecificRow and types serializable by Kryo
2b46c4b [Michael Armbrust] Merge remote-tracking branch 'origin/master' into countDistinctPartial
8ff6402 [Michael Armbrust] Add specific row.
58d15f1 [Michael Armbrust] disable codegen logging
87d101d [Michael Armbrust] Fix isNullAt bug
abee26d [Michael Armbrust] WIP
27984d0 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into countDistinctPartial
57ae3b1 [Michael Armbrust] Fix order dependent test
b3d0f64 [Michael Armbrust] Add golden files.
c1f7114 [Michael Armbrust] Improve tests / fix serialization.
f31b8ad [Michael Armbrust] more fixes
38c7449 [Michael Armbrust] comments and style
9153652 [Michael Armbrust] better toString
d494598 [Michael Armbrust] Fix tests now that the planner is better
41fbd1d [Michael Armbrust] Never try and create an empty hash set.
050bb97 [Michael Armbrust] Skip no-arg constructors for kryo,
bd08239 [Michael Armbrust] WIP
213ada8 [Michael Armbrust] First draft of partially aggregated and code generated count distinct / max
[SPARK-2967][SQL]  Follow-up: Also copy hash expressions in sort based shuffle fix.

Follow-up to #2066

Author: Michael Armbrust <michael@databricks.com>

Closes #2072 from marmbrus/sortShuffle and squashes the following commits:

2ff8114 [Michael Armbrust] Fix bug
[SPARK-2871] [PySpark] add `key` argument for max(), min() and top(n)

RDD.max(key=None)

        param key: A function used to generate key for comparing

        >>> rdd = sc.parallelize([1.0, 5.0, 43.0, 10.0])
        >>> rdd.max()
        43.0
        >>> rdd.max(key=str)
        5.0

RDD.min(key=None)

        Find the minimum item in this RDD.

        param key: A function used to generate key for comparing

        >>> rdd = sc.parallelize([2.0, 5.0, 43.0, 10.0])
        >>> rdd.min()
        2.0
        >>> rdd.min(key=str)
        10.0

RDD.top(num, key=None)

        Get the top N elements from a RDD.

        Note: It returns the list sorted in descending order.
        >>> sc.parallelize([10, 4, 2, 12, 3]).top(1)
        [12]
        >>> sc.parallelize([2, 3, 4, 5, 6], 2).top(2)
        [6, 5]
        >>> sc.parallelize([10, 4, 2, 12, 3]).top(3, key=str)
        [4, 3, 2]

Author: Davies Liu <davies.liu@gmail.com>

Closes #2094 from davies/cmp and squashes the following commits:

ccbaf25 [Davies Liu] add `key` to top()
ad7e374 [Davies Liu] fix tests
2f63512 [Davies Liu] change `comp` to `key` in min/max
dd91e08 [Davies Liu] add `comp` argument for RDD.max() and RDD.min()
[SPARK-2871] [PySpark] add approx API for RDD

RDD.countApprox(self, timeout, confidence=0.95)

        :: Experimental ::
        Approximate version of count() that returns a potentially incomplete
        result within a timeout, even if not all tasks have finished.

        >>> rdd = sc.parallelize(range(1000), 10)
        >>> rdd.countApprox(1000, 1.0)
        1000

RDD.sumApprox(self, timeout, confidence=0.95)

        Approximate operation to return the sum within a timeout
        or meet the confidence.

        >>> rdd = sc.parallelize(range(1000), 10)
        >>> r = sum(xrange(1000))
        >>> (rdd.sumApprox(1000) - r) / r < 0.05

RDD.meanApprox(self, timeout, confidence=0.95)

        :: Experimental ::
        Approximate operation to return the mean within a timeout
        or meet the confidence.

        >>> rdd = sc.parallelize(range(1000), 10)
        >>> r = sum(xrange(1000)) / 1000.0
        >>> (rdd.meanApprox(1000) - r) / r < 0.05
        True

Author: Davies Liu <davies.liu@gmail.com>

Closes #2095 from davies/approx and squashes the following commits:

e8c252b [Davies Liu] add approx API for RDD
Clean unused code in SortShuffleWriter

Just clean unused code which have been moved into ExternalSorter.

Author: Raymond Liu <raymond.liu@intel.com>

Closes #1882 from colorant/sortShuffleWriter and squashes the following commits:

e6337be [Raymond Liu] Clean unused code in SortShuffleWriter
[SPARK-3192] Some scripts have 2 space indentation but other scripts have 4 space indentation.

Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>

Closes #2104 from sarutak/SPARK-3192 and squashes the following commits:

db78419 [Kousuke Saruta] Modified indentation of spark-shell
[SPARK-2841][MLlib] Documentation for feature transformations

Documentation for newly added feature transformations:
1. TF-IDF
2. StandardScaler
3. Normalizer

Author: DB Tsai <dbtsai@alpinenow.com>

Closes #2068 from dbtsai/transformer-documentation and squashes the following commits:

109f324 [DB Tsai] address feedback
[MLlib][SPARK-2997] Update SVD documentation to reflect roughly square

Update the documentation to reflect the fact we can handle roughly square matrices.

Author: Reza Zadeh <rizlar@gmail.com>

Closes #2070 from rezazadeh/svddocs and squashes the following commits:

826b8fe [Reza Zadeh] left singular vectors
3f34fc6 [Reza Zadeh] PCA is still TS
7ffa2aa [Reza Zadeh] better title
aeaf39d [Reza Zadeh] More docs
788ed13 [Reza Zadeh] add computational cost explanation
6429c59 [Reza Zadeh] Add link to rowmatrix docs
1eeab8b [Reza Zadeh] Update SVD documentation to reflect roughly square
[SPARK-2871] [PySpark] add zipWithIndex() and zipWithUniqueId()

RDD.zipWithIndex()

        Zips this RDD with its element indices.

        The ordering is first based on the partition index and then the
        ordering of items within each partition. So the first item in
        the first partition gets index 0, and the last item in the last
        partition receives the largest index.

        This method needs to trigger a spark job when this RDD contains
        more than one partitions.

        >>> sc.parallelize(range(4), 2).zipWithIndex().collect()
        [(0, 0), (1, 1), (2, 2), (3, 3)]

RDD.zipWithUniqueId()

        Zips this RDD with generated unique Long ids.

        Items in the kth partition will get ids k, n+k, 2*n+k, ..., where
        n is the number of partitions. So there may exist gaps, but this
        method won't trigger a spark job, which is different from
        L{zipWithIndex}

        >>> sc.parallelize(range(4), 2).zipWithUniqueId().collect()
        [(0, 0), (2, 1), (1, 2), (3, 3)]

Author: Davies Liu <davies.liu@gmail.com>

Closes #2092 from davies/zipWith and squashes the following commits:

cebe5bf [Davies Liu] improve test cases, reverse the order of index
0d2a128 [Davies Liu] add zipWithIndex() and zipWithUniqueId()