=head1 NAME
-rrdtool create - Set up a new Round Robin Database
-
-=for html <div align="right"><a href="rrdcreate.pdf">PDF</a> version.</div>
+rrdcreate - Set up a new Round Robin Database
=head1 SYNOPSIS
-B<rrdtool> B<create> I<filename>
-S<[B<--start>|B<-b> I<start time>]>
-S<[B<--step>|B<-s> I<step>]>
-S<[B<DS:>I<ds-name>B<:>I<DST>B<:>I<heartbeat>B<:>I<min>B<:>I<max>]>
+B<rrdtool> B<create> I<filename>
+S<[B<--start>|B<-b> I<start time>]>
+S<[B<--step>|B<-s> I<step>]>
+S<[B<--no-overwrite>]>
+S<[B<DS:>I<ds-name>B<:>I<DST>B<:>I<dst arguments>]>
S<[B<RRA:>I<CF>B<:>I<cf arguments>]>
=head1 DESCRIPTION
-The create function of the RRDtool lets you set up new
-Round Robin Database (B<RRD>) files.
-The file is created at its final, full size and filled
-with I<*UNKNOWN*> data.
-
-=over 8
+The create function of RRDtool lets you set up new Round Robin
+Database (B<RRD>) files. The file is created at its final, full size
+and filled with I<*UNKNOWN*> data.
-=item I<filename>
+=head2 I<filename>
The name of the B<RRD> you want to create. B<RRD> files should end
-with the extension F<.rrd>. However, B<rrdtool> will accept any
+with the extension F<.rrd>. However, B<RRDtool> will accept any
filename.
-=item B<--start>|B<-b> I<start time> (default: now - 10s)
+=head2 B<--start>|B<-b> I<start time> (default: now - 10s)
Specifies the time in seconds since 1970-01-01 UTC when the first
-value should be added to the B<RRD>. B<rrdtool> will not accept
+value should be added to the B<RRD>. B<RRDtool> will not accept
any data timed before or at the time specified.
See also AT-STYLE TIME SPECIFICATION section in the
-I<rrdfetch> documentation for more ways to specify time.
+I<rrdfetch> documentation for other ways to specify time.
-=item B<--step>|B<-s> I<step> (default: 300 seconds)
+=head2 B<--step>|B<-s> I<step> (default: 300 seconds)
Specifies the base interval in seconds with which data will be fed
into the B<RRD>.
-=item B<DS:>I<ds-name>B<:>I<DST>B<:>I<heartbeat>B<:>I<min>B<:>I<max>
+=head2 B<--no-overwrite>
+
+Do not clobber an existing file of the same name.
+
+=head2 B<DS:>I<ds-name>B<:>I<DST>B<:>I<dst arguments>
-A single B<RRD> can accept input from several data sources (B<DS>).
-(e.g. Incoming and Outgoing traffic on a specific communication
-line). With the B<DS> configuration option you must define some basic
-properties of each data source you want to use to feed the B<RRD>.
+A single B<RRD> can accept input from several data sources (B<DS>),
+for example incoming and outgoing traffic on a specific communication
+line. With the B<DS> configuration option you must define some basic
+properties of each data source you want to store in the B<RRD>.
I<ds-name> is the name you will use to reference this particular data
source from an B<RRD>. A I<ds-name> must be 1 to 19 characters long in
the characters [a-zA-Z0-9_].
-I<DST> defines the Data Source Type. See the section on "How to Measure" below for further insight.
-The Datasource Type must be onw of the following:
+I<DST> defines the Data Source Type. The remaining arguments of a
+data source entry depend on the data source type. For GAUGE, COUNTER,
+DERIVE, and ABSOLUTE the format for a data source entry is:
-=over 4
+B<DS:>I<ds-name>B<:>I<GAUGE | COUNTER | DERIVE | ABSOLUTE>B<:>I<heartbeat>B<:>I<min>B<:>I<max>
-=item B<GAUGE>
+For COMPUTE data sources, the format is:
+
+B<DS:>I<ds-name>B<:>I<COMPUTE>B<:>I<rpn-expression>
+
+In order to decide which data source type to use, review the
+definitions that follow. Also consult the section on "HOW TO MEASURE"
+for further insight.
+
+=over
-is for things like temperatures or number of people in a
-room or value of a RedHat share.
+=item B<GAUGE>
+
+is for things like temperatures or number of people in a room or the
+value of a RedHat share.
=item B<COUNTER>
-is for continuous incrementing counters like the
-InOctets counter in a router. The B<COUNTER> data source assumes that
-the counter never decreases, except when a counter overflows. The update
-function takes the overflow into account. The counter is stored as a
-per-second rate. When the counter overflows, RRDtool checks if the overflow happened at
-the 32bit or 64bit border and acts accordingly by adding an appropriate value to the result.
+is for continuous incrementing counters like the ifInOctets counter in
+a router. The B<COUNTER> data source assumes that the counter never
+decreases, except when a counter overflows. The update function takes
+the overflow into account. The counter is stored as a per-second
+rate. When the counter overflows, RRDtool checks if the overflow
+happened at the 32bit or 64bit border and acts accordingly by adding
+an appropriate value to the result.
=item B<DERIVE>
will store the derivative of the line going from the last to the
current value of the data source. This can be useful for gauges, for
example, to measure the rate of people entering or leaving a
-room. Internally, derive works exaclty like COUNTER but without
+room. Internally, derive works exactly like COUNTER but without
overflow checks. So if your counter does not reset at 32 or 64 bit you
might want to use DERIVE and combine it with a MIN value of 0.
-=item B<ABSOLUTE>
+B<NOTE on COUNTER vs DERIVE>
+
+by Don Baarda E<lt>don.baarda@baesystems.comE<gt>
+
+If you cannot tolerate ever mistaking the occasional counter reset for a
+legitimate counter wrap, and would prefer "Unknowns" for all legitimate
+counter wraps and resets, always use DERIVE with min=0. Otherwise, using
+COUNTER with a suitable max will return correct values for all legitimate
+counter wraps, mark some counter resets as "Unknown", but can mistake some
+counter resets for a legitimate counter wrap.
+
+For a 5 minute step and 32-bit counter, the probability of mistaking a
+counter reset for a legitimate wrap is arguably about 0.8% per 1Mbps of
+maximum bandwidth. Note that this equates to 80% for 100Mbps interfaces, so
+for high bandwidth interfaces and a 32bit counter, DERIVE with min=0 is
+probably preferable. If you are using a 64bit counter, just about any max
+setting will eliminate the possibility of mistaking a reset for a counter
+wrap.
+
+=item B<ABSOLUTE>
is for counters which get reset upon reading. This is used for fast counters
which tend to overflow. So instead of reading them normally you reset them
-after every read to make sure you have a maximal time available before the
+after every read to make sure you have a maximum time available before the
next overflow. Another usage is for things you count like number of messages
since the last update.
+=item B<COMPUTE>
+
+is for storing the result of a formula applied to other data sources
+in the B<RRD>. This data source is not supplied a value on update, but
+rather its Primary Data Points (PDPs) are computed from the PDPs of
+the data sources according to the rpn-expression that defines the
+formula. Consolidation functions are then applied normally to the PDPs
+of the COMPUTE data source (that is the rpn-expression is only applied
+to generate PDPs). In database software, such data sets are referred
+to as "virtual" or "computed" columns.
+
=back
I<heartbeat> defines the maximum number of seconds that may pass
-between two updates of this data source before the value of the
+between two updates of this data source before the value of the
data source is assumed to be I<*UNKNOWN*>.
-I<min> and I<max> are optional entries defining the expected range of
-the data supplied by this data source. If I<min> and/or I<max> are
-defined, any value outside the defined range will be regarded as
-I<*UNKNOWN*>. If you do not know or care about min and max, set them
-to U for unknown. Note that min and max always refer to the processed values
-of the DS. For a traffic-B<COUNTER> type DS this would be the max and min
-data-rate expected from the device.
+I<min> and I<max> define the expected range values for data supplied by a
+data source. If I<min> and/or I<max> any value outside the defined range
+will be regarded as I<*UNKNOWN*>. If you do not know or care about min and
+max, set them to U for unknown. Note that min and max always refer to the
+processed values of the DS. For a traffic-B<COUNTER> type DS this would be
+the maximum and minimum data-rate expected from the device.
I<If information on minimal/maximal expected values is available,
always set the min and/or max properties. This will help RRDtool in
doing a simple sanity check on the data supplied when running update.>
-=item B<RRA:>I<CF>B<:>I<cf arguments>
-
+I<rpn-expression> defines the formula used to compute the PDPs of a
+COMPUTE data source from other data sources in the same <RRD>. It is
+similar to defining a B<CDEF> argument for the graph command. Please
+refer to that manual page for a list and description of RPN operations
+supported. For COMPUTE data sources, the following RPN operations are
+not supported: COUNT, PREV, TIME, and LTIME. In addition, in defining
+the RPN expression, the COMPUTE data source may only refer to the
+names of data source listed previously in the create command. This is
+similar to the restriction that B<CDEF>s must refer only to B<DEF>s
+and B<CDEF>s previously defined in the same graph command.
+
+=head2 B<RRA:>I<CF>B<:>I<cf arguments>
+
The purpose of an B<RRD> is to store data in the round robin archives
-(B<RRA>). An archive consists of a number of data values or statistics for
+(B<RRA>). An archive consists of a number of data values or statistics for
each of the defined data-sources (B<DS>) and is defined with an B<RRA> line.
-When data is entered into an B<RRD>, it is first fit into time slots of
-the length defined with the B<-s> option becoming a I<primary data point>.
+When data is entered into an B<RRD>, it is first fit into time slots
+of the length defined with the B<-s> option, thus becoming a I<primary
+data point>.
+
+The data is also processed with the consolidation function (I<CF>) of
+the archive. There are several consolidation functions that
+consolidate primary data points via an aggregate function: B<AVERAGE>,
+B<MIN>, B<MAX>, B<LAST>.
+
+=over
+
+=item AVERAGE
+
+the average of the data points is stored.
+
+=item MIN
+
+the smallest of the data points is stored.
+
+=item MAX
+
+the largest of the data points is stored.
+
+=item LAST
+
+the last data points is used.
+
+=back
+
+Note that data aggregation inevitably leads to loss of precision and
+information. The trick is to pick the aggregate function such that the
+I<interesting> properties of your data is kept across the aggregation
+process.
-The data is also processed with the consolidation function (I<CF>)
-of the archive. There are several consolidation functions that consolidate
-primary data points via an aggregate function: B<AVERAGE>, B<MIN>, B<MAX>, B<LAST>.
-The format of B<RRA> line for these consolidation function is:
+
+The format of B<RRA> line for these
+consolidation functions is:
B<RRA:>I<AVERAGE | MIN | MAX | LAST>B<:>I<xff>B<:>I<steps>B<:>I<rows>
I<xff> The xfiles factor defines what part of a consolidation interval may
be made up from I<*UNKNOWN*> data while the consolidated value is still
-regarded as known.
+regarded as known. It is given as the ratio of allowed I<*UNKNOWN*> PDPs
+to the number of PDPs in the interval. Thus, it ranges from 0 to 1 (exclusive).
+
I<steps> defines how many of these I<primary data points> are used to build
a I<consolidated data point> which then goes into the archive.
I<rows> defines how many generations of data values are kept in an B<RRA>.
+Obviously, this has to be greater than zero.
-=back
-
-=head1 Aberrant Behaviour detection with Holt-Winters forecasting
-
-by Jake Brutlag E<lt>jakeb@corp.webtv.netE<gt>
+=head1 Aberrant Behavior Detection with Holt-Winters Forecasting
In addition to the aggregate functions, there are a set of specialized
functions that enable B<RRDtool> to provide data smoothing (via the
-Holt-Winters forecasting algorithm), confidence bands, and the flagging
-aberrant behavior in the data source time series:
+Holt-Winters forecasting algorithm), confidence bands, and the
+flagging aberrant behavior in the data source time series:
-=over 4
+=over
-=item B<RRA:>I<HWPREDICT>B<:>I<rows>B<:>I<alpha>B<:>I<beta>B<:>I<seasonal period>B<:>I<rra num>
+=item *
+
+B<RRA:>I<HWPREDICT>B<:>I<rows>B<:>I<alpha>B<:>I<beta>B<:>I<seasonal period>[B<:>I<rra-num>]
-=item B<RRA:>I<SEASONAL>B<:>I<seasonal period>B<:>I<gamma>B<:>I<rra num>
+=item *
-=item B<RRA:>I<DEVSEASONAL>B<:>I<seasonal period>B<:>I<gamma>B<:>I<rra num>
+B<RRA:>I<MHWPREDICT>B<:>I<rows>B<:>I<alpha>B<:>I<beta>B<:>I<seasonal period>[B<:>I<rra-num>]
-=item B<RRA:>I<DEVPREDICT>B<:>I<rows>B<:>I<rra num>
+=item *
+
+B<RRA:>I<SEASONAL>B<:>I<seasonal period>B<:>I<gamma>B<:>I<rra-num>[B<:smoothing-window=>I<fraction>]
+
+=item *
-=item B<RRA:>I<FAILURES>B<:>I<rows>B<:>I<threshold>B<:>I<window length>B<:>I<rra num>
+B<RRA:>I<DEVSEASONAL>B<:>I<seasonal period>B<:>I<gamma>B<:>I<rra-num>[B<:smoothing-window=>I<fraction>]
+
+=item *
+
+B<RRA:>I<DEVPREDICT>B<:>I<rows>B<:>I<rra-num>
+
+=item *
+
+B<RRA:>I<FAILURES>B<:>I<rows>B<:>I<threshold>B<:>I<window length>B<:>I<rra-num>
=back
These B<RRAs> differ from the true consolidation functions in several ways.
First, each of the B<RRA>s is updated once for every primary data point.
Second, these B<RRAs> are interdependent. To generate real-time confidence
-bounds, then a matched set of HWPREDICT, SEASONAL, DEVSEASONAL, and
-DEVPREDICT must exist. Generating smoothed values of the primary data points
-requires both a HWPREDICT B<RRA> and SEASONAL B<RRA>. Aberrant behavior
-detection requires FAILURES, HWPREDICT, DEVSEASONAL, and SEASONAL.
-
-The actual predicted, or smoothed, values are stored in the HWPREDICT
-B<RRA>. The predicted deviations are store in DEVPREDICT (think a standard
-deviation which can be scaled to yield a confidence band). The FAILURES
-B<RRA> stores binary indicators. A 1 marks the indexed observation a
-failure; that is, the number of confidence bounds violations in the
-preceding window of observations met or exceeded a specified threshold. An
-example of using these B<RRAs> to graph confidence bounds and failures
-appears in L<rrdgraph>.
+bounds, a matched set of SEASONAL, DEVSEASONAL, DEVPREDICT, and either
+HWPREDICT or MHWPREDICT must exist. Generating smoothed values of the primary
+data points requires a SEASONAL B<RRA> and either an HWPREDICT or MHWPREDICT
+B<RRA>. Aberrant behavior detection requires FAILURES, DEVSEASONAL, SEASONAL,
+and either HWPREDICT or MHWPREDICT.
+
+The predicted, or smoothed, values are stored in the HWPREDICT or MHWPREDICT
+B<RRA>. HWPREDICT and MHWPREDICT are actually two variations on the
+Holt-Winters method. They are interchangeable. Both attempt to decompose data
+into three components: a baseline, a trend, and a seasonal coefficient.
+HWPREDICT adds its seasonal coefficient to the baseline to form a prediction, whereas
+MHWPREDICT multiplies its seasonal coefficient by the baseline to form a
+prediction. The difference is noticeable when the baseline changes
+significantly in the course of a season; HWPREDICT will predict the seasonality
+to stay constant as the baseline changes, but MHWPREDICT will predict the
+seasonality to grow or shrink in proportion to the baseline. The proper choice
+of method depends on the thing being modeled. For simplicity, the rest of this
+discussion will refer to HWPREDICT, but MHWPREDICT may be substituted in its
+place.
+
+The predicted deviations are stored in DEVPREDICT (think a standard deviation
+which can be scaled to yield a confidence band). The FAILURES B<RRA> stores
+binary indicators. A 1 marks the indexed observation as failure; that is, the
+number of confidence bounds violations in the preceding window of observations
+met or exceeded a specified threshold. An example of using these B<RRAs> to graph
+confidence bounds and failures appears in L<rrdgraph>.
The SEASONAL and DEVSEASONAL B<RRAs> store the seasonal coefficients for the
-Holt-Winters Forecasting algorithm and the seasonal deviations respectively.
+Holt-Winters forecasting algorithm and the seasonal deviations, respectively.
There is one entry per observation time point in the seasonal cycle. For
-example, if primary data points are generated every five minutes, and the
-seasonal cycle is 1 day, both SEASONAL and DEVSEASONAL with have 288 rows.
+example, if primary data points are generated every five minutes and the
+seasonal cycle is 1 day, both SEASONAL and DEVSEASONAL will have 288 rows.
In order to simplify the creation for the novice user, in addition to
-supporting explicit creation the HWPREDICT, SEASONAL, DEVPREDICT,
-DEVSEASONAL, and FAILURES B<RRAs>, the B<rrdtool> create command supports
+supporting explicit creation of the HWPREDICT, SEASONAL, DEVPREDICT,
+DEVSEASONAL, and FAILURES B<RRAs>, the B<RRDtool> create command supports
implicit creation of the other four when HWPREDICT is specified alone and
-the final argument I<rra num> is omitted.
+the final argument I<rra-num> is omitted.
I<rows> specifies the length of the B<RRA> prior to wrap around. Remember
that there is a one-to-one correspondence between primary data points and
entries in these RRAs. For the HWPREDICT CF, I<rows> should be larger than
-the I<seasonal period>. If the DEVPREDICT B<RRA> is implicity created, the
+the I<seasonal period>. If the DEVPREDICT B<RRA> is implicitly created, the
default number of rows is the same as the HWPREDICT I<rows> argument. If the
FAILURES B<RRA> is implicitly created, I<rows> will be set to the I<seasonal
-period> argument of the HWPREDICT B<RRA>. Of course, the B<rrdtool>
+period> argument of the HWPREDICT B<RRA>. Of course, the B<RRDtool>
I<resize> command is available if these defaults are not sufficient and the
-create wishes to avoid explicit creations of the other specialized function
+creator wishes to avoid explicit creations of the other specialized function
B<RRAs>.
I<seasonal period> specifies the number of primary data points in a seasonal
cycle. If SEASONAL and DEVSEASONAL are implicitly created, this argument for
those B<RRAs> is set automatically to the value specified by HWPREDICT. If
-they are explicity created, the creator should verify that all three
+they are explicitly created, the creator should verify that all three
I<seasonal period> arguments agree.
-I<alpha> is the adaptation parameter of the intercept (or baseline)
-coefficient in the Holt-Winters Forecasting algorithm. See L<rrdtool> for a
+I<alpha> is the adaption parameter of the intercept (or baseline)
+coefficient in the Holt-Winters forecasting algorithm. See L<rrdtool> for a
description of this algorithm. I<alpha> must lie between 0 and 1. A value
closer to 1 means that more recent observations carry greater weight in
-predicting the baseline component of the forecast. A value closer to 0 mean
-that past history carries greater weight in predicted the baseline
+predicting the baseline component of the forecast. A value closer to 0 means
+that past history carries greater weight in predicting the baseline
component.
I<beta> is the adaption parameter of the slope (or linear trend) coefficient
-in the Holt-Winters Forecating algorihtm. I<beta> must lie between 0 and 1
+in the Holt-Winters forecasting algorithm. I<beta> must lie between 0 and 1
and plays the same role as I<alpha> with respect to the predicted linear
trend.
I<gamma> is the adaption parameter of the seasonal coefficients in the
-Holt-Winters Forecasting algorithm (HWPREDICT) or the adaption parameter in
+Holt-Winters forecasting algorithm (HWPREDICT) or the adaption parameter in
the exponential smoothing update of the seasonal deviations. It must lie
between 0 and 1. If the SEASONAL and DEVSEASONAL B<RRAs> are created
implicitly, they will both have the same value for I<gamma>: the value
specified for the HWPREDICT I<alpha> argument. Note that because there is
one seasonal coefficient (or deviation) for each time point during the
-seasonal cycle, the adaption rate is much slower than the baseline. Each
+seasonal cycle, the adaptation rate is much slower than the baseline. Each
seasonal coefficient is only updated (or adapts) when the observed value
occurs at the offset in the seasonal cycle corresponding to that
coefficient.
-If SEASONAL and DEVSEASONAL B<RRAs> are created explicity, I<gamma> need not
+If SEASONAL and DEVSEASONAL B<RRAs> are created explicitly, I<gamma> need not
be the same for both. Note that I<gamma> can also be changed via the
-B<rrdtool> I<tune> command.
-
-I<rra num> provides the links between related B<RRAs>. If HWPREDICT is
-specified alone and the other B<RRAs> created implicitly, then there is no
-need to worry about this argument. If B<RRAs> are created explicitly, then
-pay careful attention to this argument. For each B<RRA> which includes this
-argument, there is a dependency between that B<RRA> and another B<RRA>. The
-I<rra num> argument is the 1-based index in the order of B<RRA> creation
-(that is, the order they appear in the I<create> command). The dependent
-B<RRA> for each B<RRA> requiring the I<rra num> argument is listed here:
+B<RRDtool> I<tune> command.
+
+I<smoothing-window> specifies the fraction of a season that should be
+averaged around each point. By default, the value of I<smoothing-window> is
+0.05, which means each value in SEASONAL and DEVSEASONAL will be occasionally
+replaced by averaging it with its (I<seasonal period>*0.05) nearest neighbors.
+Setting I<smoothing-window> to zero will disable the running-average smoother
+altogether.
+
+I<rra-num> provides the links between related B<RRAs>. If HWPREDICT is
+specified alone and the other B<RRAs> are created implicitly, then
+there is no need to worry about this argument. If B<RRAs> are created
+explicitly, then carefully pay attention to this argument. For each
+B<RRA> which includes this argument, there is a dependency between
+that B<RRA> and another B<RRA>. The I<rra-num> argument is the 1-based
+index in the order of B<RRA> creation (that is, the order they appear
+in the I<create> command). The dependent B<RRA> for each B<RRA>
+requiring the I<rra-num> argument is listed here:
-=over 4
+=over
=item *
-HWPREDICT I<rra num> is the index of the SEASONAL B<RRA>.
+HWPREDICT I<rra-num> is the index of the SEASONAL B<RRA>.
-=item *
+=item *
-SEASONAL I<rra num> is the index of the HWPREDICT B<RRA>.
+SEASONAL I<rra-num> is the index of the HWPREDICT B<RRA>.
-=item *
+=item *
-DEVPREDICT I<rra num> is the index of the DEVSEASONAL B<RRA>.
+DEVPREDICT I<rra-num> is the index of the DEVSEASONAL B<RRA>.
=item *
-DEVSEASONAL I<rra num> is the index of the HWPREDICT B<RRA>.
+DEVSEASONAL I<rra-num> is the index of the HWPREDICT B<RRA>.
-=item *
+=item *
-FAILURES I<rra num> is the index of the DEVSEASONAL B<RRA>.
+FAILURES I<rra-num> is the index of the DEVSEASONAL B<RRA>.
=back
I<window length> is the number of time points in the window. Specify an
integer greater than or equal to the threshold and less than or equal to 28.
The time interval this window represents depends on the interval between
-primary data points. If the FAILURES B<RRA> is implicity created, the
+primary data points. If the FAILURES B<RRA> is implicitly created, the
default value is 9.
=head1 The HEARTBEAT and the STEP
-Here is an explanation by Don Baarda on the inner workings of rrdtool.
+Here is an explanation by Don Baarda on the inner workings of RRDtool.
It may help you to sort out why all this *UNKNOWN* data is popping
up in your databases:
-RRD gets fed samples at arbitrary times. From these it builds Primary
-Data Points (PDPs) at exact times every "step" interval. The PDPs are
-then accumulated into RRAs.
+RRDtool gets fed samples/updates at arbitrary times. From these it builds Primary
+Data Points (PDPs) on every "step" interval. The PDPs are
+then accumulated into the RRAs.
The "heartbeat" defines the maximum acceptable interval between
-samples. If the interval between samples is less than "heartbeat",
+samples/updates. If the interval between samples is less than "heartbeat",
then an average rate is calculated and applied for that interval. If
the interval between samples is longer than "heartbeat", then that
entire interval is considered "unknown". Note that there are other
things that can make a sample interval "unknown", such as the rate
-exceeding limits, or even an "unknown" input sample.
+exceeding limits, or a sample that was explicitly marked as unknown.
The known rates during a PDP's "step" interval are used to calculate
-an average rate for that PDP. Also, if the total "unknown" time during
-the "step" interval exceeds the "heartbeat", the entire PDP is marked
+an average rate for that PDP. If the total "unknown" time accounts for
+more than B<half> the "step", the entire PDP is marked
as "unknown". This means that a mixture of known and "unknown" sample
-time in a single PDP "step" may or may not add up to enough "unknown"
-time to exceed "heartbeat" and hence mark the whole PDP "unknown". So
-"heartbeat" is not only the maximum acceptable interval between
-samples, but also the maximum acceptable amount of "unknown" time per
-PDP (obviously this is only significant if you have "heartbeat" less
-than "step").
+times in a single PDP "step" may or may not add up to enough "known"
+time to warrant a known PDP.
The "heartbeat" can be short (unusual) or long (typical) relative to
the "step" interval between PDPs. A short "heartbeat" means you
require multiple samples per PDP, and if you don't get them mark the
PDP unknown. A long heartbeat can span multiple "steps", which means
it is acceptable to have multiple PDPs calculated from a single
-sample. An extreme example of this might be a "step" of 5mins and a
+sample. An extreme example of this might be a "step" of 5 minutes and a
"heartbeat" of one day, in which case a single sample every day will
result in all the PDPs for that entire day period being set to the
same average rate. I<-- Don Baarda E<lt>don.baarda@baesystems.comE<gt>>
+ time|
+ axis|
+ begin__|00|
+ |01|
+ u|02|----* sample1, restart "hb"-timer
+ u|03| /
+ u|04| /
+ u|05| /
+ u|06|/ "hbt" expired
+ u|07|
+ |08|----* sample2, restart "hb"
+ |09| /
+ |10| /
+ u|11|----* sample3, restart "hb"
+ u|12| /
+ u|13| /
+ step1_u|14| /
+ u|15|/ "swt" expired
+ u|16|
+ |17|----* sample4, restart "hb", create "pdp" for step1 =
+ |18| / = unknown due to 10 "u" labled secs > 0.5 * step
+ |19| /
+ |20| /
+ |21|----* sample5, restart "hb"
+ |22| /
+ |23| /
+ |24|----* sample6, restart "hb"
+ |25| /
+ |26| /
+ |27|----* sample7, restart "hb"
+ step2__|28| /
+ |22| /
+ |23|----* sample8, restart "hb", create "pdp" for step1, create "cdp"
+ |24| /
+ |25| /
+
+graphics by I<vladimir.lavrov@desy.de>.
+
=head1 HOW TO MEASURE
=item Temperature
-Normally you have some type of meter you can read to get the temperature.
-The temperature is not realy connected with a time. The only connection is
+Usually you have some type of meter you can read to get the temperature.
+The temperature is not really connected with a time. The only connection is
that the temperature reading happened at a certain time. You can use the
-B<GAUGE> data source type for this. RRRtool will the record your reading
+B<GAUGE> data source type for this. RRDtool will then record your reading
together with the time.
=item Mail Messages
-Assume you have a methode to count the number of messages transported by
-your mailserver in a certain amount of time, this give you data like '5
-messages in the last 65 seconds'. If you look at the count of 5 like and
-B<ABSOLUTE> datatype you can simply update the rrd with the number 5 and the
+Assume you have a method to count the number of messages transported by
+your mail server in a certain amount of time, giving you data like '5
+messages in the last 65 seconds'. If you look at the count of 5 like an
+B<ABSOLUTE> data type you can simply update the RRD with the number 5 and the
end time of your monitoring period. RRDtool will then record the number of
messages per second. If at some later stage you want to know the number of
messages transported in a day, you can get the average messages per second
=item It's always a Rate
-RRDtool stores rates in amount/second for COUNTER, DERIVE and ABSOLUTE data.
-When you plot the data, you will get on the y axis amount/second which you
-might be tempted to convert to absolute amount volume by multiplying by the
-delta-time between the points. RRDtool plots continuous data, and as such is
-not appropriate for plotting absolute volumes as for example "total bytes"
-sent and received in a router. What you probably want is plot rates that you
-can scale to for example bytes/hour or plot volumes with another tool that
-draws bar-plots, where the delta-time is clear on the plot for each point
-(such that when you read the graph you see for example GB on the y axis,
-days on the x axis and one bar for each day).
+RRDtool stores rates in amount/second for COUNTER, DERIVE and ABSOLUTE
+data. When you plot the data, you will get on the y axis
+amount/second which you might be tempted to convert to an absolute
+amount by multiplying by the delta-time between the points. RRDtool
+plots continuous data, and as such is not appropriate for plotting
+absolute amounts as for example "total bytes" sent and received in a
+router. What you probably want is plot rates that you can scale to
+bytes/hour, for example, or plot absolute amounts with another tool
+that draws bar-plots, where the delta-time is clear on the plot for
+each point (such that when you read the graph you see for example GB
+on the y axis, days on the x axis and one bar for each day).
=back
=head1 EXAMPLE
-C<rrdtool create temperature.rrd --step 300 DS:temp:GAUGE:600:-273:5000
-RRA:AVERAGE:0.5:1:1200 RRA:MIN:0.5:12:2400 RRA:MAX:0.5:12:2400
-RRA:AVERAGE:0.5:12:2400>
+ rrdtool create temperature.rrd --step 300 \
+ DS:temp:GAUGE:600:-273:5000 \
+ RRA:AVERAGE:0.5:1:1200 \
+ RRA:MIN:0.5:12:2400 \
+ RRA:MAX:0.5:12:2400 \
+ RRA:AVERAGE:0.5:12:2400
This sets up an B<RRD> called F<temperature.rrd> which accepts one
temperature value every 300 seconds. If no new data is supplied for
more than 600 seconds, the temperature becomes I<*UNKNOWN*>. The
-minimum acceptable value is -273 and the maximum is 5000.
+minimum acceptable value is -273 and the maximum is 5'000.
-A few archives areas are also defined. The first stores the
-temperatures supplied for 100 hours (1200 * 300 seconds = 100
+A few archive areas are also defined. The first stores the
+temperatures supplied for 100 hours (1'200 * 300 seconds = 100
hours). The second RRA stores the minimum temperature recorded over
-every hour (12 * 300 seconds = 1 hour), for 100 days (2400 hours). The
-third and the fourth RRA's do the same with the for the maximum and
+every hour (12 * 300 seconds = 1 hour), for 100 days (2'400 hours). The
+third and the fourth RRA's do the same for the maximum and
average temperature, respectively.
=head1 EXAMPLE 2
-C<rrdtool create monitor.rrd --step 300
-DS:ifOutOctets:COUNTER:1800:0:4294967295
-RRA:AVERAGE:0.5:1:2016
-RRA:HWPREDICT:1440:0.1:0.0035:288>
+ rrdtool create monitor.rrd --step 300 \
+ DS:ifOutOctets:COUNTER:1800:0:4294967295 \
+ RRA:AVERAGE:0.5:1:2016 \
+ RRA:HWPREDICT:1440:0.1:0.0035:288
This example is a monitor of a router interface. The first B<RRA> tracks the
-traffic flow in octects; the second B<RRA> generates the specialized
-functions B<RRAs> for aberrant behavior detection. Note that the I<rra num>
-argument of HWPREDICT is missing, so the other B<RRAs> will be implicitly be
+traffic flow in octets; the second B<RRA> generates the specialized
+functions B<RRAs> for aberrant behavior detection. Note that the I<rra-num>
+argument of HWPREDICT is missing, so the other B<RRAs> will implicitly be
created with default parameter values. In this example, the forecasting
algorithm baseline adapts quickly; in fact the most recent one hour of
-observations (each at 5 minute intervals) account for 75% of the baseline
+observations (each at 5 minute intervals) accounts for 75% of the baseline
prediction. The linear trend forecast adapts much more slowly. Observations
-made in during the last day (at 288 observations per day) account for only
+made during the last day (at 288 observations per day) account for only
65% of the predicted linear trend. Note: these computations rely on an
-exponential smoothing formula described in a forthcoming LISA 2000 paper.
+exponential smoothing formula described in the LISA 2000 paper.
The seasonal cycle is one day (288 data points at 300 second intervals), and
-the seasonal adaption paramter will be set to 0.1. The RRD file will store 5
-days (1440 data points) of forecasts and deviation predictions before wrap
+the seasonal adaption parameter will be set to 0.1. The RRD file will store 5
+days (1'440 data points) of forecasts and deviation predictions before wrap
around. The file will store 1 day (a seasonal cycle) of 0-1 indicators in
the FAILURES B<RRA>.
-The same RRD file and B<RRAs> are created with the following command, which explicitly
-creates all specialized function B<RRAs>.
-
-C<rrdtool create monitor.rrd --step 300
-DS:ifOutOctets:COUNTER:1800:0:4294967295
-RRA:AVERAGE:0.5:1:2016
-RRA:HWPREDICT:1440:0.1:0.0035:288:3
-RRA:SEASONAL:288:0.1:2
-RRA:DEVPREDICT:1440:5
-RRA:DEVSEASONAL:288:0.1:2
-RRA:FAILURES:288:7:9:5>
-
-Of course, explicit creation need not replicate implicit create, a number of arguments
-could be changed.
+The same RRD file and B<RRAs> are created with the following command,
+which explicitly creates all specialized function B<RRAs>.
+
+ rrdtool create monitor.rrd --step 300 \
+ DS:ifOutOctets:COUNTER:1800:0:4294967295 \
+ RRA:AVERAGE:0.5:1:2016 \
+ RRA:HWPREDICT:1440:0.1:0.0035:288:3 \
+ RRA:SEASONAL:288:0.1:2 \
+ RRA:DEVPREDICT:1440:5 \
+ RRA:DEVSEASONAL:288:0.1:2 \
+ RRA:FAILURES:288:7:9:5
+
+Of course, explicit creation need not replicate implicit create, a
+number of arguments could be changed.
+
+=head1 EXAMPLE 3
+
+ rrdtool create proxy.rrd --step 300 \
+ DS:Total:DERIVE:1800:0:U \
+ DS:Duration:DERIVE:1800:0:U \
+ DS:AvgReqDur:COMPUTE:Duration,Requests,0,EQ,1,Requests,IF,/ \
+ RRA:AVERAGE:0.5:1:2016
+
+This example is monitoring the average request duration during each 300 sec
+interval for requests processed by a web proxy during the interval.
+In this case, the proxy exposes two counters, the number of requests
+processed since boot and the total cumulative duration of all processed
+requests. Clearly these counters both have some rollover point, but using the
+DERIVE data source also handles the reset that occurs when the web proxy is
+stopped and restarted.
+
+In the B<RRD>, the first data source stores the requests per second rate
+during the interval. The second data source stores the total duration of all
+requests processed during the interval divided by 300. The COMPUTE data source
+divides each PDP of the AccumDuration by the corresponding PDP of
+TotalRequests and stores the average request duration. The remainder of the
+RPN expression handles the divide by zero case.
=head1 AUTHOR
-Tobias Oetiker E<lt>oetiker@ee.ethz.chE<gt>
+Tobias Oetiker E<lt>tobi@oetiker.chE<gt>
projects / rrdtool.git / blobdiff