[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

1 files changed, 2 insertions, 0 deletions

diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md
index 74bcc2eeb6..4b3a49eca7 100644
--- a/docs/running-on-yarn.md
+++ b/docs/running-on-yarn.md
@@ -205,6 +205,8 @@ Note that for the first option, both executors and the application master will s
 log4j configuration, which may cause issues when they run on the same node (e.g. trying to write
 to the same log file).
 
+If you need a reference to the proper location to put log files in the YARN so that YARN can properly display and aggregate them, use "${spark.yarn.app.container.log.dir}" in your log4j.properties. For example, log4j.appender.file_appender.File=${spark.yarn.app.container.log.dir}/spark.log. For streaming application, configuring RollingFileAppender and setting file location to YARN's log directory will avoid disk overflow caused by large log file, and logs can be accessed using YARN's log utility.
+
 # Important notes
 
 - Before Hadoop 2.2, YARN does not support cores in container resource requests. Thus, when running against an earlier version, the numbers of cores given via command line arguments cannot be passed to YARN.  Whether core requests are honored in scheduling decisions depends on which scheduler is in use and how it is configured.