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<li><a href="#name">NAME</a></li>
<li><a href="#synopsis">SYNOPSIS</a></li>
<li><a href="#description">DESCRIPTION</a></li>
+ <ul>
+
+ <li><a href="#filename"><em>filename</em></a></li>
+ <li><a href="#start_b_start_time__default__now__10s_"><strong>-start</strong>|<strong>-b</strong> <em>start time</em> (default: now - 10s)</a></li>
+ <li><a href="#step_s_step__default__300_seconds_"><strong>-step</strong>|<strong>-s</strong> <em>step</em> (default: 300 seconds)</a></li>
+ <li><a href="#ds_dsname_dst_dst_arguments"><strong>DS:</strong><em>ds-name</em><strong>:</strong><em>DST</em><strong>:</strong><em>dst arguments</em></a></li>
+ <li><a href="#rra_cf_cf_arguments"><strong>RRA:</strong><em>CF</em><strong>:</strong><em>cf arguments</em></a></li>
+ </ul>
+
<li><a href="#aberrant_behavior_detection_with_holtwinters_forecasting">Aberrant Behavior Detection with Holt-Winters Forecasting</a></li>
<li><a href="#the_heartbeat_and_the_step">The HEARTBEAT and the STEP</a></li>
<li><a href="#how_to_measure">HOW TO MEASURE</a></li>
<p>The create function of RRDtool lets you set up new Round Robin
Database (<strong>RRD</strong>) files. The file is created at its final, full size
and filled with <em>*UNKNOWN*</em> data.</p>
-<dl>
-<dt><strong><a name="item_filename"><em>filename</em></a></strong></dt>
-
-<dd>
+<p>
+</p>
+<h2><a name="filename"><em>filename</em></a></h2>
<p>The name of the <strong>RRD</strong> you want to create. <strong>RRD</strong> files should end
with the extension <em>.rrd</em>. However, <strong>RRDtool</strong> will accept any
filename.</p>
-</dd>
-<dt><strong><a name="item_time"><strong>--start</strong>|<strong>-b</strong> <em>start time</em> (default: now - 10s)</a></strong></dt>
-
-<dd>
+<p>
+</p>
+<h2><a name="start_b_start_time__default__now__10s_"><strong>--start</strong>|<strong>-b</strong> <em>start time</em> (default: now - 10s)</a></h2>
<p>Specifies the time in seconds since 1970-01-01 UTC when the first
value should be added to the <strong>RRD</strong>. <strong>RRDtool</strong> will not accept
any data timed before or at the time specified.</p>
<p>See also AT-STYLE TIME SPECIFICATION section in the
<em>rrdfetch</em> documentation for other ways to specify time.</p>
-</dd>
-<dt><strong><a name="item_step"><strong>--step</strong>|<strong>-s</strong> <em>step</em> (default: 300 seconds)</a></strong></dt>
-
-<dd>
+<p>
+</p>
+<h2><a name="step_s_step__default__300_seconds_"><strong>--step</strong>|<strong>-s</strong> <em>step</em> (default: 300 seconds)</a></h2>
<p>Specifies the base interval in seconds with which data will be fed
into the <strong>RRD</strong>.</p>
-</dd>
-<dt><strong><a name="item_ds_3ads_2dname_3adst_3adst_arguments"><strong>DS:</strong><em>ds-name</em><strong>:</strong><em>DST</em><strong>:</strong><em>dst arguments</em></a></strong></dt>
-
-<dd>
+<p>
+</p>
+<h2><a name="ds_dsname_dst_dst_arguments"><strong>DS:</strong><em>ds-name</em><strong>:</strong><em>DST</em><strong>:</strong><em>dst arguments</em></a></h2>
<p>A single <strong>RRD</strong> can accept input from several data sources (<strong>DS</strong>),
for example incoming and outgoing traffic on a specific communication
line. With the <strong>DS</strong> configuration option you must define some basic
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.</p>
-<p>NOTE on COUNTER vs DERIVE</p>
+<p><strong>NOTE on COUNTER vs DERIVE</strong></p>
<p>by Don Baarda <<a href="mailto:don.baarda@baesystems.com">don.baarda@baesystems.com</a>></p>
<p>If you cannot tolerate ever mistaking the occasional counter reset for a
legitimate counter wrap, and would prefer ``Unknowns'' for all legitimate
names of data source listed previously in the create command. This is
similar to the restriction that <strong>CDEF</strong>s must refer only to <strong>DEF</strong>s
and <strong>CDEF</strong>s previously defined in the same graph command.</p>
-</dd>
-<dt><strong><a name="item_rra_3acf_3acf_arguments"><strong>RRA:</strong><em>CF</em><strong>:</strong><em>cf arguments</em></a></strong></dt>
-
-<dd>
+<p>
+</p>
+<h2><a name="rra_cf_cf_arguments"><strong>RRA:</strong><em>CF</em><strong>:</strong><em>cf arguments</em></a></h2>
<p>The purpose of an <strong>RRD</strong> is to store data in the round robin archives
(<strong>RRA</strong>). An archive consists of a number of data values or statistics for
each of the defined data-sources (<strong>DS</strong>) and is defined with an <strong>RRA</strong> line.</p>
<p>The data is also processed with the consolidation function (<em>CF</em>) of
the archive. There are several consolidation functions that
consolidate primary data points via an aggregate function: <strong>AVERAGE</strong>,
-<strong>MIN</strong>, <strong>MAX</strong>, <strong>LAST</strong>. The format of <strong>RRA</strong> line for these
+<strong>MIN</strong>, <strong>MAX</strong>, <strong>LAST</strong>.</p>
+<dl>
+<dt><strong><a name="item_average">AVERAGE</a></strong></dt>
+
+<dd>
+<p>the average of the data points is stored.</p>
+</dd>
+<dt><strong><a name="item_min">MIN</a></strong></dt>
+
+<dd>
+<p>the smallest of the data points is stored.</p>
+</dd>
+<dt><strong><a name="item_max">MAX</a></strong></dt>
+
+<dd>
+<p>the largest of the data points is stored.</p>
+</dd>
+<dt><strong><a name="item_last">LAST</a></strong></dt>
+
+<dd>
+<p>the last data points is used.</p>
+</dd>
+</dl>
+<p>Note that data aggregation inevitably leads to loss of precision and
+information. The trick is to pick the aggregate function such that the
+<em>interesting</em> properties of your data is kept across the aggregation
+process.</p>
+<p>The format of <strong>RRA</strong> line for these
consolidation functions is:</p>
<p><strong>RRA:</strong><em>AVERAGE | MIN | MAX | LAST</em><strong>:</strong><em>xff</em><strong>:</strong><em>steps</em><strong>:</strong><em>rows</em></p>
<p><em>xff</em> The xfiles factor defines what part of a consolidation interval may
to the number of PDPs in the interval. Thus, it ranges from 0 to 1 (exclusive).</p>
<p><em>steps</em> defines how many of these <em>primary data points</em> are used to build
a <em>consolidated data point</em> which then goes into the archive.</p>
-<p><em>rows</em> defines how many generations of data values are kept in an <strong>RRA</strong>.</p>
-</dd>
-</dl>
+<p><em>rows</em> defines how many generations of data values are kept in an <strong>RRA</strong>.
+Obviously, this has to be greater than zero.</p>
<p>
</p>
<hr />
<p><strong>RRA:</strong><em>HWPREDICT</em><strong>:</strong><em>rows</em><strong>:</strong><em>alpha</em><strong>:</strong><em>beta</em><strong>:</strong><em>seasonal period</em>[<strong>:</strong><em>rra-num</em>]</p>
</li>
<li>
-<p><strong>RRA:</strong><em>SEASONAL</em><strong>:</strong><em>seasonal period</em><strong>:</strong><em>gamma</em><strong>:</strong><em>rra-num</em></p>
+<p><strong>RRA:</strong><em>MHWPREDICT</em><strong>:</strong><em>rows</em><strong>:</strong><em>alpha</em><strong>:</strong><em>beta</em><strong>:</strong><em>seasonal period</em>[<strong>:</strong><em>rra-num</em>]</p>
+</li>
+<li>
+<p><strong>RRA:</strong><em>SEASONAL</em><strong>:</strong><em>seasonal period</em><strong>:</strong><em>gamma</em><strong>:</strong><em>rra-num</em>[<strong>:smoothing-window=</strong><em>fraction</em>]</p>
</li>
<li>
-<p><strong>RRA:</strong><em>DEVSEASONAL</em><strong>:</strong><em>seasonal period</em><strong>:</strong><em>gamma</em><strong>:</strong><em>rra-num</em></p>
+<p><strong>RRA:</strong><em>DEVSEASONAL</em><strong>:</strong><em>seasonal period</em><strong>:</strong><em>gamma</em><strong>:</strong><em>rra-num</em>[<strong>:smoothing-window=</strong><em>fraction</em>]</p>
</li>
<li>
<p><strong>RRA:</strong><em>DEVPREDICT</em><strong>:</strong><em>rows</em><strong>:</strong><em>rra-num</em></p>
<p>These <strong>RRAs</strong> differ from the true consolidation functions in several ways.
First, each of the <strong>RRA</strong>s is updated once for every primary data point.
Second, these <strong>RRAs</strong> are interdependent. To generate real-time confidence
-bounds, a matched set of HWPREDICT, SEASONAL, DEVSEASONAL, and
-DEVPREDICT must exist. Generating smoothed values of the primary data points
-requires both a HWPREDICT <strong>RRA</strong> and SEASONAL <strong>RRA</strong>. Aberrant behavior
-detection requires FAILURES, HWPREDICT, DEVSEASONAL, and SEASONAL.</p>
-<p>The actual predicted, or smoothed, values are stored in the HWPREDICT
-<strong>RRA</strong>. The predicted deviations are stored in DEVPREDICT (think a standard
-deviation which can be scaled to yield a confidence band). The FAILURES
-<strong>RRA</strong> 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 <strong>RRAs</strong> to graph confidence bounds and failures
-appears in <a href="././rrdgraph.html">the rrdgraph manpage</a>.</p>
+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 <strong>RRA</strong> and either an HWPREDICT or MHWPREDICT
+<strong>RRA</strong>. Aberrant behavior detection requires FAILURES, DEVSEASONAL, SEASONAL,
+and either HWPREDICT or MHWPREDICT.</p>
+<p>The predicted, or smoothed, values are stored in the HWPREDICT or MHWPREDICT
+<strong>RRA</strong>. 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.</p>
+<p>The predicted deviations are stored in DEVPREDICT (think a standard deviation
+which can be scaled to yield a confidence band). The FAILURES <strong>RRA</strong> 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 <strong>RRAs</strong> to graph
+confidence bounds and failures appears in <a href="././rrdgraph.html">the rrdgraph manpage</a>.</p>
<p>The SEASONAL and DEVSEASONAL <strong>RRAs</strong> store the seasonal coefficients for the
Holt-Winters forecasting algorithm and the seasonal deviations, respectively.
There is one entry per observation time point in the seasonal cycle. For
<p>If SEASONAL and DEVSEASONAL <strong>RRAs</strong> are created explicitly, <em>gamma</em> need not
be the same for both. Note that <em>gamma</em> can also be changed via the
<strong>RRDtool</strong> <em>tune</em> command.</p>
+<p><em>smoothing-window</em> specifies the fraction of a season that should be
+averaged around each point. By default, the value of <em>smoothing-window</em> is
+0.05, which means each value in SEASONAL and DEVSEASONAL will be occasionally
+replaced by averaging it with its (<em>seasonal period</em>*0.05) nearest neighbors.
+Setting <em>smoothing-window</em> to zero will disable the running-average smoother
+altogether.</p>
<p><em>rra-num</em> provides the links between related <strong>RRAs</strong>. If HWPREDICT is
specified alone and the other <strong>RRAs</strong> are created implicitly, then
there is no need to worry about this argument. If <strong>RRAs</strong> are created