[CalendarServer-changes] [9552] CalendarServer/trunk/contrib/performance/loadtest

[source_changes at macosforge.org]

Revision: 9552
          http://trac.macosforge.org/projects/calendarserver/changeset/9552
Author:   cdaboo at apple.com
Date:     2012-08-10 11:28:21 -0700 (Fri, 10 Aug 2012)
Log Message:
-----------
Minor tweak to the LogNormal distribution description for attendee distribution.

Modified Paths:
--------------
    CalendarServer/trunk/contrib/performance/loadtest/config.dist.plist
    CalendarServer/trunk/contrib/performance/loadtest/config.plist

Modified: CalendarServer/trunk/contrib/performance/loadtest/config.dist.plist
===================================================================
--- CalendarServer/trunk/contrib/performance/loadtest/config.dist.plist	2012-08-10 00:43:06 UTC (rev 9551)
+++ CalendarServer/trunk/contrib/performance/loadtest/config.dist.plist	2012-08-10 18:28:21 UTC (rev 9552)
@@ -355,17 +355,32 @@
 							</dict>
 
 							<!-- Define the distribution of how many attendees will be invited to an event.
-							    Experience shows that sigma should equal sqrt(mu) to give a peak at around 1.
-							    mu = 0.5  sigma = 0.71 gives an average of 1.6 attendees
-							    mu = 0.75 sigma = 0.87 gives an average of 2.6 attendees
-							    mu = 1.0  sigma = 1.0 gives an average of 4 attendees
-							    mu = 1.1  sigma = 1.05 gives an average of 4.7 attendees
-							    mu = 1.2  sigma = 1.1 gives an average of 5.5 attendees
-							    mu = 1.3  sigma = 1.14 gives an average of 6.5 attendees
-							    mu = 1.4  sigma = 1.18 gives an average of 7.6 attendees
-							    mu = 1.5  sigma = 1.22 gives an average of 8.8 attendees
-							    mu = 1.75  sigma = 1.32 gives an average of 12.5 attendees
-							    mu = 2.0  sigma = 1.41 gives an average of 17.4 attendees
+							
+								LogNormal is the best fit to observed data.
+							    
+							    Here is a formula for calculating mu and sigma based on average number
+							    of attendees A, with the peak at 1:
+							    
+							    mu = 2/3 * ln(A)
+							    sigma = sqrt(mu)
+							    
+							    Some useful values:
+							    
+							    Attendees		mu		sigma
+							    
+							     1.5			0.25	0.50
+							     2.0			0.46	0.68
+								 3.0			0.73	0.86
+							     4.0			0.92	0.96
+							     5.0			1.07	1.04
+							     6.0			1.19	1.09
+							     7.0			1.30	1.14
+							     8.0			1.39	1.18
+							     9.0			1.46	1.21
+							    10.0			1.54	1.24
+							    15.0			1.81	1.34
+							    20.0			2.00	1.41
+
 							     -->
 							<key>inviteeCountDistribution</key>
 							<dict>
@@ -375,10 +390,10 @@
 								<dict>
 									<!-- mean -->
 									<key>mu</key>
-									<real>1.3</real>
+									<real>1.19</real>
 									<!-- standard deviation -->
 									<key>sigma</key>
-									<real>1.14</real>
+									<real>1.09</real>
 									<!-- maximum -->
 									<key>maximum</key>
 									<real>100</real>

Modified: CalendarServer/trunk/contrib/performance/loadtest/config.plist
===================================================================
--- CalendarServer/trunk/contrib/performance/loadtest/config.plist	2012-08-10 00:43:06 UTC (rev 9551)
+++ CalendarServer/trunk/contrib/performance/loadtest/config.plist	2012-08-10 18:28:21 UTC (rev 9552)
@@ -349,17 +349,32 @@
 							</dict>
 
 							<!-- Define the distribution of how many attendees will be invited to an event.
-							    Experience shows that sigma should equal sqrt(mu) to give a peak at around 1.
-							    mu = 0.5  sigma = 0.71 gives an average of 1.6 attendees
-							    mu = 0.75 sigma = 0.87 gives an average of 2.6 attendees
-							    mu = 1.0  sigma = 1.0 gives an average of 4 attendees
-							    mu = 1.1  sigma = 1.05 gives an average of 4.7 attendees
-							    mu = 1.2  sigma = 1.1 gives an average of 5.5 attendees
-							    mu = 1.3  sigma = 1.14 gives an average of 6.5 attendees
-							    mu = 1.4  sigma = 1.18 gives an average of 7.6 attendees
-							    mu = 1.5  sigma = 1.22 gives an average of 8.8 attendees
-							    mu = 1.75  sigma = 1.32 gives an average of 12.5 attendees
-							    mu = 2.0  sigma = 1.41 gives an average of 17.4 attendees
+							
+								LogNormal is the best fit to observed data.
+							    
+							    Here is a formula for calculating mu and sigma based on average number
+							    of attendees A, with the peak at 1:
+							    
+							    mu = 2/3 * ln(A)
+							    sigma = sqrt(mu)
+							    
+							    Some useful values:
+							    
+							    Attendees		mu		sigma
+							    
+							     1.5			0.25	0.50
+							     2.0			0.46	0.68
+								 3.0			0.73	0.86
+							     4.0			0.92	0.96
+							     5.0			1.07	1.04
+							     6.0			1.19	1.09
+							     7.0			1.30	1.14
+							     8.0			1.39	1.18
+							     9.0			1.46	1.21
+							    10.0			1.54	1.24
+							    15.0			1.81	1.34
+							    20.0			2.00	1.41
+
 							     -->
 							<key>inviteeCountDistribution</key>
 							<dict>
@@ -369,10 +384,10 @@
 								<dict>
 									<!-- mean -->
 									<key>mu</key>
-									<real>1.3</real>
+									<real>1.19</real>
 									<!-- standard deviation -->
 									<key>sigma</key>
-									<real>1.14</real>
+									<real>1.09</real>
 									<!-- maximum -->
 									<key>maximum</key>
 									<real>100</real>
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