Contents of this patch:

[rrdtool.git] / doc / rrdtune.pod

diff --git a/doc/rrdtune.pod b/doc/rrdtune.pod
index 18f478d..d4fa076 100644 (file)
--- a/doc/rrdtune.pod
+++ b/doc/rrdtune.pod
@@ -13,20 +13,19 @@ S<[B<--maximum>|B<-a> I<ds-name>:I<max>]>
 S<[B<--data-source-type>|B<-d> I<ds-name>:I<DST>]>
 S<[B<--data-source-rename>|B<-r> I<old-name>:I<new-name>]>
 S<[B<--deltapos> I<scale-value>]>
-S<[B<--deltaneg> I<scale value>]>
+S<[B<--deltaneg> I<scale-value>]>
 S<[B<--failure-threshold> I<failure-threshold>]>
 S<[B<--window-length> I<window-length>]>
 S<[B<--alpha> I<adaption-parameter>]>
 S<[B<--beta> I<adaption-parameter>]>
 S<[B<--gamma> I<adaption-parameter>]>
+S<[B<--gamma-deviation> I<adaption-parameter>]>
+S<[B<--aberrant-reset> I<ds-name>]>
 
 =head1 DESCRIPTION
 
 The tune option allows you to alter some of the basic configuration
 values stored in the header area of a Round Robin Database (B<RRD>).
-All these tunable parameters together decide when data fed into an 
-B<RRD> is to be regarded as invalid. Invalid data is entered into the 
-database as *UNKNOWN*.
 
 One application of the B<tune> function is to relax the 
 validation rules on an B<RRD>. This allows to fill a new B<RRD> with
@@ -74,8 +73,8 @@ Alter the deviation scaling factor for the upper bound of the confidence band
 used internally to calculate violations for the FAILURES B<RRA>. The default
 value is 2. Note that this parameter is not related to graphing confidence
 bounds, that scale factor must be specified as a CDEF argument to generate 
-a graph with confidence bounds. It need not agree with the value used internally 
-by the FAILURES B<RRA> (although common sense dictates it should).
+a graph with confidence bounds. The graph scale factor need not agree with the 
+value used internally by the FAILURES B<RRA>.
 
 =item S<B<--deltaneg> I<scale-value>>
 
@@ -111,8 +110,40 @@ Must be between 0 and 1.
 
 =item S<B<--gamma> I<adaption-parameter>>
 
-Alter the seasonal coefficient and deviation adaptation parameters the SEASONAL and
-DEVSEAONAL B<RRAs>. Must be between 0 and 1.
+Alter the seasonal coefficient adaptation parameter for the SEASONAL
+B<RRA>. Must be between 0 and 1.
+
+=item S<B<--gamma-deviation> I<adaption-parameter>>
+
+Alter the seasonal deviation adaptation parameter for the DEVSEASONAL
+B<RRA>. Must be between 0 and 1.
+
+=item S<B<--aberrant-reset> I<ds-name>>
+
+This option causes the aberrant behavior detection algorithm to reset
+for the specified data source; that is, forget all it is has learn.
+Specifically, for the HWPREDICT B<RRA>, it sets the intercept and slope
+coefficients to unknown. For the SEASONAL B<RRA>, it sets all seasonal
+coefficients to unknown. For the DEVSEASONL B<RRA>, it sets all seasonal
+deviation coefficients to unknown. For the FAILURES B<RRA>, it erases
+the violation history. Note that reset does not erase past predictions
+(the values of the HWPREDICT B<RRA>), predicted deviations (the values of the
+DEVPREDICT B<RRA>), or failure history (the values of the FAILURES B<RRA>).
+This option will function even if not all the listed B<RRAs> are present.
+
+Due to the implementation of this option, there is an indirect impact on
+other data sources in the RRD. A smoothing algorithm is applied to
+SEASONAL and DEVSEASONAL values on a periodic basis. During bootstrap
+initialization this smoothing is deferred. For efficiency, the implementation
+of smoothing is not data source specific. This means that utilizing
+reset for one data source will delay running the smoothing algorithm
+for all data sources in the file. This is unlikely to have serious
+consequences, unless the data being collected for the non-reset data soures 
+is unusually volatile during the reinitialization period of the reset 
+data source.
+
+Use of this tuning option is advised when the behavior of the data source 
+time series changes in a drastic and permanent manner.
 
 =back