[SPARK-3006] Failed to execute spark-shell in Windows OS

Modified the order of the options and arguments in spark-shell.cmd

Author: Masayoshi TSUZUKI <tsudukim@oss.nttdata.co.jp>

Closes #1918 from tsudukim/feature/SPARK-3006 and squashes the following commits:

8bba494 [Masayoshi TSUZUKI] [SPARK-3006] Failed to execute spark-shell in Windows OS
1a32410 [Masayoshi TSUZUKI] [SPARK-3006] Failed to execute spark-shell in Windows OS

(cherry picked from commit 9497b12d429cf9d075807896637e40e205175203)
Signed-off-by: Andrew Or <andrewor14@gmail.com>
[Docs] Add missing <code> tags (minor)

These configs looked inconsistent from the rest.

Author: Andrew Or <andrewor14@gmail.com>

Closes #1936 from andrewor14/docs-code and squashes the following commits:

15f578a [Andrew Or] Add <code> tag

(cherry picked from commit e4245656438d00714ebd59e89c4de3fdaae83494)
Signed-off-by: Reynold Xin <rxin@apache.org>
[SPARK-2995][MLLIB] add ALS.setIntermediateRDDStorageLevel

As mentioned in SPARK-2465, using `MEMORY_AND_DISK_SER` for user/product in/out links together with `spark.rdd.compress=true` can help reduce the space requirement by a lot, at the cost of speed. It might be useful to add this option so people can run ALS on much bigger datasets.

Another option for the method name is `setIntermediateRDDStorageLevel`.

Author: Xiangrui Meng <meng@databricks.com>

Closes #1913 from mengxr/als-storagelevel and squashes the following commits:

d942017 [Xiangrui Meng] rename to setIntermediateRDDStorageLevel
7550029 [Xiangrui Meng] add ALS.setIntermediateDataStorageLevel

(cherry picked from commit 69a57a18ee35af1cc5a00b67a80837ea317cd330)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
[SPARK-3029] Disable local execution of Spark jobs by default

Currently, local execution of Spark jobs is only used by take(), and it can be problematic as it can load a significant amount of data onto the driver. The worst case scenarios occur if the RDD is cached (guaranteed to load whole partition), has very large elements, or the partition is just large and we apply a filter with high selectivity or computational overhead.

Additionally, jobs that run locally in this manner do not show up in the web UI, and are thus harder to track or understand what is occurring.

This PR adds a flag to disable local execution, which is turned OFF by default, with the intention of perhaps eventually removing this functionality altogether. Removing it now is a tougher proposition since it is part of the public runJob API. An alternative solution would be to limit the flag to take()/first() to avoid impacting any external users of this API, but such usage (or, at least, reliance upon the feature) is hopefully minimal.

Author: Aaron Davidson <aaron@databricks.com>

Closes #1321 from aarondav/allowlocal and squashes the following commits:

136b253 [Aaron Davidson] Fix DAGSchedulerSuite
5599d55 [Aaron Davidson] [RFC] Disable local execution of Spark jobs by default

(cherry picked from commit d069c5d9d2f6ce06389ca2ddf0b3ae4db72c5797)
Signed-off-by: Reynold Xin <rxin@apache.org>
SPARK-2893: Do not swallow Exceptions when running a custom kryo registrator

The previous behaviour of swallowing ClassNotFound exceptions when running a custom Kryo registrator could lead to difficult to debug problems later on at serialisation / deserialisation time, see SPARK-2878.  Instead it is better to fail fast.

Added test case.

Author: Graham Dennis <graham.dennis@gmail.com>

Closes #1827 from GrahamDennis/feature/spark-2893 and squashes the following commits:

fbe4cb6 [Graham Dennis] [SPARK-2878]: Update the test case to match the updated exception message
65e53c5 [Graham Dennis] [SPARK-2893]: Improve message when a spark.kryo.registrator fails.
f480d85 [Graham Dennis] [SPARK-2893] Fix typo.
b59d2c2 [Graham Dennis] SPARK-2893: Do not swallow Exceptions when running a custom spark.kryo.registrator

(cherry picked from commit 6b8de0e36c7548046c3b8a57f2c8e7e788dde8cc)
Signed-off-by: Reynold Xin <rxin@apache.org>