SPARK-3574. Shuffle finish time always reported as -1

The included test waits 100 ms after job completion for task completion events to come in so it can verify they have reasonable finish times.  Does anyone know a better way to wait on listener events that are expected to come in?

Author: Sandy Ryza <sandy@cloudera.com>

Closes #2440 from sryza/sandy-spark-3574 and squashes the following commits:

c81439b [Sandy Ryza] Fix test failure
b340956 [Sandy Ryza] SPARK-3574. Remove shuffleFinishTime metric
[SPARK-3609][SQL] Adds sizeInBytes statistics for Limit operator when all output attributes are of native data types

This helps to replace shuffled hash joins with broadcast hash joins in some cases.

Author: Cheng Lian <lian.cs.zju@gmail.com>

Closes #2468 from liancheng/more-stats and squashes the following commits:

32687dc [Cheng Lian] Moved the test case to PlannerSuite
5595a91 [Cheng Lian] Removes debugging code
73faf69 [Cheng Lian] Test case for auto choosing broadcast hash join
f30fe1d [Cheng Lian] Adds sizeInBytes estimation for Limit when all output types are native types
[SPARK-3414][SQL] Replace LowerCaseSchema with Resolver

**This PR introduces a subtle change in semantics for HiveContext when using the results in Python or Scala.  Specifically, while resolution remains case insensitive, it is now case preserving.**

_This PR is a follow up to #2293 (and to a lesser extent #2262 #2334)._

In #2293 the catalog was changed to store analyzed logical plans instead of unresolved ones.  While this change fixed the reported bug (which was caused by yet another instance of us forgetting to put in a `LowerCaseSchema` operator) it had the consequence of breaking assumptions made by `MultiInstanceRelation`.  Specifically, we can't replace swap out leaf operators in a tree without rewriting changed expression ids (which happens when you self join the same RDD that has been registered as a temp table).

In this PR, I instead remove the need to insert `LowerCaseSchema` operators at all, by moving the concern of matching up identifiers completely into analysis.  Doing so allows the test cases from both #2293 and #2262 to pass at the same time (and likely fixes a slew of other "unknown unknown" bugs).

While it is rolled back in this PR, storing the analyzed plan might actually be a good idea.  For instance, it is kind of confusing if you register a temporary table, change the case sensitivity of resolution and now you can't query that table anymore.  This can be addressed in a follow up PR.

Follow-ups:
 - Configurable case sensitivity
 - Consider storing analyzed plans for temp tables

Author: Michael Armbrust <michael@databricks.com>

Closes #2382 from marmbrus/lowercase and squashes the following commits:

c21171e [Michael Armbrust] Ensure the resolver is used for field lookups and ensure that case insensitive resolution is still case preserving.
d4320f1 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into lowercase
2de881e [Michael Armbrust] Address comments.
219805a [Michael Armbrust] style
5b93711 [Michael Armbrust] Replace LowerCaseSchema with Resolver.
[SPARK-3599]Avoid loading properties file frequently

https://issues.apache.org/jira/browse/SPARK-3599

Author: WangTao <barneystinson@aliyun.com>
Author: WangTaoTheTonic <barneystinson@aliyun.com>

Closes #2454 from WangTaoTheTonic/avoidLoadingFrequently and squashes the following commits:

3681182 [WangTao] do not use clone
7dca036 [WangTao] use lazy val instead
2a79f26 [WangTaoTheTonic] Avoid loaing properties file frequently
MAINTENANCE: Automated closing of pull requests.

This commit exists to close the following pull requests on Github:

Closes #1328 (close requested by 'pwendell')
Closes #2314 (close requested by 'pwendell')
Closes #997 (close requested by 'pwendell')
Closes #550 (close requested by 'pwendell')
Closes #1506 (close requested by 'pwendell')
Closes #2423 (close requested by 'mengxr')
Closes #554 (close requested by 'joshrosen')
[SPARK-3595] Respect configured OutputCommitters when calling saveAsHadoopFile

Addresses the issue in https://issues.apache.org/jira/browse/SPARK-3595, namely saveAsHadoopFile hardcoding the OutputCommitter.  This is not ideal when running Spark jobs that write to S3, especially when running them from an EMR cluster where the default OutputCommitter is a DirectOutputCommitter.

Author: Ian Hummel <ian@themodernlife.net>

Closes #2450 from themodernlife/spark-3595 and squashes the following commits:

f37a0e5 [Ian Hummel] Update based on comments from pwendell
a11d9f3 [Ian Hummel] Fix formatting
4359664 [Ian Hummel] Add an example showing usage
8b6be94 [Ian Hummel] Add ability to specify OutputCommitter, espcially useful when writing to an S3 bucket from an EMR cluster
[Minor]ignore .idea_modules

ignore .idea_modules ,  ```sbt/sbt gen-idea``` generate this dir.

Author: wangfei <wangfei1@huawei.com>

Closes #2476 from scwf/patch-4 and squashes the following commits:

e6ab88a [wangfei] ignore .idea_modules
[MLLib] Fix example code variable name misspelling in MLLib Feature Extraction guide

Author: RJ Nowling <rnowling@gmail.com>

Closes #2459 from rnowling/tfidf-fix and squashes the following commits:

b370a91 [RJ Nowling] Fix variable name misspelling in MLLib Feature Extraction guide
Update docs to use jsonRDD instead of wrong jsonRdd.

Author: Grega Kespret <grega.kespret@gmail.com>

Closes #2479 from gregakespret/patch-1 and squashes the following commits:

dd6b90a [Grega Kespret] Update docs to use jsonRDD instead of wrong jsonRdd.
[SPARK-3578] Fix upper bound in GraphGenerators.sampleLogNormal

GraphGenerators.sampleLogNormal is supposed to return an integer strictly less than maxVal. However, it violates this guarantee. It generates its return value as follows:

```scala
var X: Double = maxVal

while (X >= maxVal) {
  val Z = rand.nextGaussian()
  X = math.exp(mu + sigma*Z)
}
math.round(X.toFloat)
```

When X is sampled to be close to (but less than) maxVal, then it will pass the while loop condition, but the rounded result will be equal to maxVal, which will violate the guarantee. For example, if maxVal is 5 and X is 4.9, then X < maxVal, but `math.round(X.toFloat)` is 5.

This PR instead rounds X before checking the loop condition, guaranteeing that the condition will hold for the return value.

Author: Ankur Dave <ankurdave@gmail.com>

Closes #2439 from ankurdave/SPARK-3578 and squashes the following commits:

f6655e5 [Ankur Dave] Go back to math.floor
5900c22 [Ankur Dave] Round X in loop condition
6fd5fb1 [Ankur Dave] Run sampleLogNormal bounds check 1000 times
1638598 [Ankur Dave] Round down in sampleLogNormal to guarantee upper bound
[YARN] SPARK-2668: Add variable of yarn log directory for reference from the log4j configuration

Assign value of yarn container log directory to java opts "spark.yarn.app.container.log.dir", So user defined log4j.properties can reference this value and write log to YARN container's log directory.
Otherwise, user defined file appender will only write to container's CWD, and log files in CWD will not be displayed on YARN UI，and either cannot be aggregated to HDFS log directory after job finished.

User defined log4j.properties reference example:
log4j.appender.rolling_file.File = ${spark.yarn.app.container.log.dir}/spark.log

Author: peng.zhang <peng.zhang@xiaomi.com>

Closes #1573 from renozhang/yarn-log-dir and squashes the following commits:

16c5cb8 [peng.zhang] Update doc
f2b5e2a [peng.zhang] Change variable's name, and update running-on-yarn.md
503ea2d [peng.zhang] Support log4j log to yarn container dir
[SPARK-3477] Clean up code in Yarn Client / ClientBase

This is part of a broader effort to clean up the Yarn integration code after #2020.

The high-level changes in this PR include:
- Removing duplicate code, especially across the alpha and stable APIs
- Simplify unnecessarily complex method signatures and hierarchies
- Rename unclear variable and method names
- Organize logging output produced when the user runs Spark on Yarn
- Extensively add documentation
- Privatize classes where possible

I have tested the stable API on a Hadoop 2.4 cluster. I tested submitting a jar that references classes in other jars in both client and cluster mode. I also made changes in the alpha API, though I do not have access to an alpha cluster. I have verified that it compiles, but it would be ideal if others can help test it.

For those interested in some examples in detail, please read on.

--------------------------------------------------------------------------------------------------------

***Appendix***

- The loop to `getApplicationReport` from the RM is duplicated in 4 places: in the stable `Client`, alpha `Client`, and twice in `YarnClientSchedulerBackend`. We should not have different loops for client and cluster deploy modes.
- There are many fragmented small helper methods that are only used once and should just be inlined. For instance, `ClientBase#getLocalPath` returns `null` on certain conditions, and its only caller `ClientBase#addFileToClasspath` checks whether the value returned is `null`. We could just have the caller check on that same condition to avoid passing `null`s around.
- In `YarnSparkHadoopUtil#addToEnvironment`, we take in an argument `classpathSeparator` that always has the same value upstream (i.e. `File.pathSeparator`). This argument is now removed from the signature and all callers of this method upstream.
- `ClientBase#copyRemoteFile` is now renamed to `copyFileToRemote`. It was unclear whether we are copying a remote file to our local file system, or copying a locally visible file to a remote file system. Also, even the content of the method has inaccurately named variables. We use `val remoteFs` to signify the file system of the locally visible file and `val fs` to signify the remote, destination file system. These are now renamed `srcFs` and `destFs` respectively.
- We currently log the AM container's environment and resource mappings directly as Scala collections. This is incredibly hard to read and probably too verbose for the average Spark user. In other modes (e.g. standalone), we also don't log the launch commands by default, so the logging level of these information is now set to `DEBUG`.
- None of these classes (`Client`, `ClientBase`, `YarnSparkHadoopUtil` etc.) is intended to be used by a Spark application (the user should go through Spark submit instead). At the very least they should be `private[spark]`.

Author: Andrew Or <andrewor14@gmail.com>

Closes #2350 from andrewor14/yarn-cleanup and squashes the following commits:

39e8c7b [Andrew Or] Address review comments
6619f9b [Andrew Or] Merge branch 'master' of github.com:apache/spark into yarn-cleanup
2ca6d64 [Andrew Or] Improve logging in application monitor
a3b9693 [Andrew Or] Minor changes
7dd6298 [Andrew Or] Simplify ClientBase#monitorApplication
547487c [Andrew Or] Provide default values for null application report entries
a0ad1e9 [Andrew Or] Fix class not found error
1590141 [Andrew Or] Address review comments
45ccdea [Andrew Or] Remove usages of getAMMemory
d8e33b6 [Andrew Or] Merge branch 'master' of github.com:apache/spark into yarn-cleanup
ed0b42d [Andrew Or] Fix alpha compilation error
c0587b4 [Andrew Or] Merge branch 'master' of github.com:apache/spark into yarn-cleanup
6d74888 [Andrew Or] Minor comment changes
6573c1d [Andrew Or] Clean up, simplify and document code for setting classpaths
e4779b6 [Andrew Or] Clean up log messages + variable naming in ClientBase
8766d37 [Andrew Or] Heavily add documentation to Client* classes + various clean-ups
6c94d79 [Andrew Or] Various cleanups in ClientBase and ClientArguments
ef7069a [Andrew Or] Clean up YarnClientSchedulerBackend more
6de9072 [Andrew Or] Guard against potential NPE in debug logging mode
fabe4c4 [Andrew Or] Reuse more code in YarnClientSchedulerBackend
3f941dc [Andrew Or] First cut at simplifying the Client (stable and alpha)
[SPARK-3304] [YARN] ApplicationMaster's Finish status is wrong when uncaught exception is thrown from ReporterThread

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

Closes #2198 from sarutak/SPARK-3304 and squashes the following commits:

2696237 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-3304
5b80363 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-3304
4eb0a3e [Kousuke Saruta] Remoed the description about spark.yarn.scheduler.reporterThread.maxFailure
9741597 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-3304
f7538d4 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-3304
358ef8d [Kousuke Saruta] Merge branch 'SPARK-3304' of github.com:sarutak/spark into SPARK-3304
0d138c6 [Kousuke Saruta] Revert "tmp"
f8da10a [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-3304
b6e9879 [Kousuke Saruta] tmp
8d256ed [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-3304
13b2652 [Kousuke Saruta] Merge branch 'SPARK-3304' of github.com:sarutak/spark into SPARK-3304
2711e15 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-3304
c081f8e [Kousuke Saruta] Modified ApplicationMaster to handle exception in ReporterThread itself
0bbd3a6 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-3304
a6982ad [Kousuke Saruta] Added ability handling uncaught exception thrown from Reporter thread
[SPARK-3598][SQL]cast to timestamp should be the same as hive

this patch fixes timestamp smaller than 0 and cast int as timestamp

select cast(1000 as timestamp) from src limit 1;

should return 1970-01-01 00:00:01, but we now take it as 1000 seconds.
also, current implementation has bug when the time is before 1970-01-01 00:00:00.
rxin marmbrus chenghao-intel

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

Closes #2458 from adrian-wang/timestamp and squashes the following commits:

4274b1d [Daoyuan Wang] set test not related to timezone
1234f66 [Daoyuan Wang] fix timestamp smaller than 0 and cast int as timestamp
[SPARK-3582][SQL] not limit argument type for hive simple udf

Since we have moved to `ConventionHelper`, it is quite easy to avoid call `javaClassToDataType` in hive simple udf. This will solve SPARK-3582.

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

Closes #2506 from adrian-wang/spark3582 and squashes the following commits:

450c28e [Daoyuan Wang] not limit argument type for hive simple udf
[SPARK-3536][SQL] SELECT on empty parquet table throws exception

It returns null metadata from parquet if querying on empty parquet file while calculating splits.So added null check and returns the empty splits.

Author : ravipesala ravindra.pesalahuawei.com

Author: ravipesala <ravindra.pesala@huawei.com>

Closes #2456 from ravipesala/SPARK-3536 and squashes the following commits:

1e81a50 [ravipesala] Fixed the issue when querying on empty parquet file.
SPARK-2745 [STREAMING] Add Java friendly methods to Duration class

tdas is this what you had in mind for this JIRA? I saw this one and thought it would be easy to take care of, and helpful as I use streaming from Java.

I could do the same for `Time`? Happy to do so.

Author: Sean Owen <sowen@cloudera.com>

Closes #2403 from srowen/SPARK-2745 and squashes the following commits:

5a9e706 [Sean Owen] Change "Duration" to "Durations" to avoid changing Duration case class API
bda301c [Sean Owen] Just delegate to Scala binary operator syntax to avoid scalastyle warning
7dde949 [Sean Owen] Disable scalastyle for false positives. Add Java static factory methods seconds(), minutes() to Duration. Add Java-friendly methods to Time too, and unit tests. Remove unnecessary math.floor from Time.floor()
4dee32e [Sean Owen] Add named methods to Duration in parallel to symbolic methods for Java-friendliness. Also add unit tests for Duration, in Scala and Java.
[SPARK-3481][SQL] removes the evil MINOR HACK

 a follow up of https://github.com/apache/spark/pull/2377 and https://github.com/apache/spark/pull/2352, see detail there.

Author: wangfei <wangfei1@huawei.com>

Closes #2505 from scwf/patch-6 and squashes the following commits:

4874ec8 [wangfei] removes the evil MINOR HACK
[SPARK-3268][SQL] DoubleType, FloatType and DecimalType modulus support

Supported modulus operation using % operator on fractional datatypes FloatType, DoubleType and DecimalType
Example:
SELECT 1388632775.0 % 60 from tablename LIMIT 1

Author : Venkata Ramana Gollamudi ramana.gollamudihuawei.com

Author: Venkata Ramana Gollamudi <ramana.gollamudi@huawei.com>

Closes #2457 from gvramana/double_modulus_support and squashes the following commits:

79172a8 [Venkata Ramana Gollamudi] Add hive cache to testcase
c09bd5b [Venkata Ramana Gollamudi] Added a HiveQuerySuite testcase
193fa81 [Venkata Ramana Gollamudi] corrected testcase
3624471 [Venkata Ramana Gollamudi] modified testcase
e112c09 [Venkata Ramana Gollamudi] corrected the testcase
513d0e0 [Venkata Ramana Gollamudi] modified to add modulus support to fractional types float,double,decimal
296d253 [Venkata Ramana Gollamudi] modified to add modulus support to fractional types float,double,decimal
[SPARK-3646][SQL] Copy SQL configuration from SparkConf when a SQLContext is created.

This will allow us to take advantage of things like the spark.defaults file.

Author: Michael Armbrust <michael@databricks.com>

Closes #2493 from marmbrus/copySparkConf and squashes the following commits:

0bd1377 [Michael Armbrust] Copy SQL configuration from SparkConf when a SQLContext is created.