Update increasing-memory-of-fire-server.rst

docs/installation-upgrading/configuration/increasing-memory-of-fire-server.rst

@@ -1,16 +1,16 @@
 Increasing Memory of Fire Server
 ================================
 
-By default, when the Sparkflows web server is started with run-fire-server.sh, it is given 1.5 GB of memory.
+By default, when the Sparkflows web server is started with ``run-fire-server.sh``, it is given ``1.5 GB of memory``.
 
-Below is from run-fire-server.sh.
+Below is from run-fire-server.sh::
 
-**nohup ${JAVA} -server -Djava.ext.dirs=./user-lib/ -Xmx1548m -Xms1356m -XX:+CMSClassUnloadingEnabled -XX:PermSize=512m -XX:MaxPermSize=512m -jar ./app/fire-ui-1.3.0.war --spring.config.name=application,db,log4j --spring.config.location=file:./conf/ &**
+    nohup ${JAVA} -server -Djava.ext.dirs=./user-lib/ -Xmx1548m -Xms1356m -XX:+CMSClassUnloadingEnabled -XX:PermSize=512m -XX:MaxPermSize=512m -jar ./app/fire-ui-1.3.0.war --spring.config.name=application,db,log4j --spring.config.location=file:./conf/ &
 
-In order to increase the amount of memory for the Sparkflows web server, increase the value of -Xmx based on the amount of memory available on your server.
+* In order to increase the amount of memory for the Sparkflows web server, ``increase the value of -Xmx`` based on the amount of memory available on your server.
 
-For example, you could raise it to 5 GB or 10 GB or more up to 25 GB.
+* For example, you could raise it to 5 GB or 10 GB or more up to 25 GB.
 
-The increased memory size, if available, allows Sparkflows to handle more requests and return results faster. Of course, when connected to a Spark cluster, the full jobs are submitted to the Spark cluster through spark-submit, allowing it to be very scalable and not dependent on the Sparkflows web server.
+* The increased memory size, if available, allows Sparkflows to handle more requests and return results faster. Of course, when connected to a Spark cluster, the full jobs are submitted to the Spark cluster through spark-submit, allowing it to be very scalable and not dependent on the Sparkflows web server.
 
-The interactive execution of the workflows in the workflow editor, is run within Sparkflows on a small subset of the data. These interactive executions would benefit from increased memory.
+* The interactive execution of the workflows in the workflow editor, is run within Sparkflows on a small subset of the data. These interactive executions would benefit from increased memory.