[SPARK-21305][ML][MLLIB] Add options to disable multi-threading of native BLAS

## What changes were proposed in this pull request?

Many ML/MLLIB algorithms use native BLAS (like Intel MKL, ATLAS, OpenBLAS) to improvement the performance.
Many popular Native BLAS, like Intel MKL, OpenBLAS, use multi-threading technology, which will conflict with Spark.  Spark should provide options to disable multi-threading of Native BLAS.

https://github.com/xianyi/OpenBLAS/wiki/faq#multi-threaded
https://software.intel.com/en-us/articles/recommended-settings-for-calling-intel-mkl-routines-from-multi-threaded-applications

## How was this patch tested?
The existing UT.

Author: Peng Meng <[email protected]>

Closes apache#18551 from mpjlu/optimzeBLAS.

Author: Peng Meng

conf/spark-env.sh.template

@@ -61,3 +61,7 @@
 # - SPARK_IDENT_STRING  A string representing this instance of spark. (Default: $USER)
 # - SPARK_NICENESS      The scheduling priority for daemons. (Default: 0)
 # - SPARK_NO_DAEMONIZE  Run the proposed command in the foreground. It will not output a PID file.
+# Options for native BLAS, like Intel MKL, OpenBLAS, and so on.
+# You might get better performance to enable these options if using native BLAS (see SPARK-21305).
+# - MKL_NUM_THREADS=1        Disable multi-threading of Intel MKL
+# - OPENBLAS_NUM_THREADS=1   Disable multi-threading of OpenBLAS

docs/ml-guide.md

@@ -61,6 +61,12 @@ To configure `netlib-java` / Breeze to use system optimised binaries, include
 project and read the [netlib-java](https://github.com/fommil/netlib-java) documentation for your
 platform's additional installation instructions.
 
+The most popular native BLAS such as [Intel MKL](https://software.intel.com/en-us/mkl), [OpenBLAS](http://www.openblas.net), can use multiple threads in a single operation, which can conflict with Spark's execution model.
+
+Configuring these BLAS implementations to use a single thread for operations may actually improve performance (see [SPARK-21305](https://issues.apache.org/jira/browse/SPARK-21305)). It is usually optimal to match this to the number of cores each Spark task is configured to use, which is 1 by default and typically left at 1.
+
+Please refer to resources like the following to understand how to configure the number of threads these BLAS implementations use: [Intel MKL](https://software.intel.com/en-us/articles/recommended-settings-for-calling-intel-mkl-routines-from-multi-threaded-applications) and [OpenBLAS](https://github.com/xianyi/OpenBLAS/wiki/faq#multi-threaded).
+
 To use MLlib in Python, you will need [NumPy](http://www.numpy.org) version 1.4 or newer.
 
 [^1]: To learn more about the benefits and background of system optimised natives, you may wish to