@@ -49,32 +64,28 @@
The create function of RRDtool lets you set up new Round Robin Database (RRD) files. The file is created at its final, full size and filled with *UNKNOWN* data.
-+
+The name of the RRD you want to create. RRD files should end -with the extension .rrd. However, RRDtool will accept any +with the extension .rrd. However, RRDtool will accept any filename.
-+
+Specifies the time in seconds since 1970-01-01 UTC when the first value should be added to the RRD. RRDtool will not accept any data timed before or at the time specified.
See also AT-STYLE TIME SPECIFICATION section in the rrdfetch documentation for other ways to specify time.
-+
+Specifies the base interval in seconds with which data will be fed into the RRD.
-+
+A single RRD can accept input from several data sources (DS), for example incoming and outgoing traffic on a specific communication line. With the DS configuration option you must define some basic @@ -89,16 +100,16 @@ DERIVE, and ABSOLUTE the format for a data source entry is:
For COMPUTE data sources, the format is:
DS:ds-name:COMPUTE: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'' +definitions that follow. Also consult the section on "HOW TO MEASURE" for further insight.
is for things like temperatures or number of people in a room or the value of a RedHat share.
is for continuous incrementing counters like the ifInOctets counter in @@ -109,7 +120,7 @@ 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.
will store the derivative of the line going from the last to the @@ -118,13 +129,13 @@ example, to measure the rate of people entering or leaving a 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.
-NOTE on COUNTER vs DERIVE
+NOTE on COUNTER vs DERIVE
by Don Baarda <don.baarda@baesystems.com>
If you cannot tolerate ever mistaking the occasional counter reset for a -legitimate counter wrap, and would prefer ``Unknowns'' for all legitimate +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 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 @@ -134,7 +145,7 @@ 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.
is for counters which get reset upon reading. This is used for fast counters @@ -143,7 +154,7 @@ 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.
is for storing the result of a formula applied to other data sources @@ -153,7 +164,7 @@ 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.
+to as "virtual" or "computed" columns.heartbeat defines the maximum number of seconds that may pass @@ -178,10 +189,9 @@ 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 CDEFs must refer only to DEFs and CDEFs previously defined in the same graph command.
-+
+The purpose of an RRD is to store data in the round robin archives (RRA). An archive consists of a number of data values or statistics for each of the defined data-sources (DS) and is defined with an RRA line.
@@ -191,7 +201,34 @@ data point.The data is also processed with the consolidation function (CF) of the archive. There are several consolidation functions that consolidate primary data points via an aggregate function: AVERAGE, -MIN, MAX, LAST. The format of RRA line for these +MIN, MAX, LAST.
+the average of the data points is stored.
+the smallest of the data points is stored.
+the largest of the data points is stored.
+the last data points is used.
+Note that data aggregation inevitably leads to loss of precision and +information. The trick is to pick the aggregate function such that the +interesting properties of your data is kept across the aggregation +process.
+The format of RRA line for these consolidation functions is:
RRA:AVERAGE | MIN | MAX | LAST:xff:steps:rows
xff The xfiles factor defines what part of a consolidation interval may @@ -200,13 +237,12 @@ regarded as known. It is given as the ratio of allowed *UNKNOWN* PDPs to the number of PDPs in the interval. Thus, it ranges from 0 to 1 (exclusive).
steps defines how many of these primary data points are used to build a consolidated data point which then goes into the archive.
-rows defines how many generations of data values are kept in an RRA.
-rows defines how many generations of data values are kept in an RRA. +Obviously, this has to be greater than zero.
In addition to the aggregate functions, there are a set of specialized functions that enable RRDtool to provide data smoothing (via the Holt-Winters forecasting algorithm), confidence bands, and the @@ -216,10 +252,13 @@ flagging aberrant behavior in the data source time series:
RRA:HWPREDICT:rows:alpha:beta:seasonal period[:rra-num]
RRA:SEASONAL:seasonal period:gamma:rra-num
+RRA:MHWPREDICT:rows:alpha:beta:seasonal period[:rra-num]
+RRA:SEASONAL:seasonal period:gamma:rra-num[:smoothing-window=fraction]
RRA:DEVSEASONAL:seasonal period:gamma:rra-num
+RRA:DEVSEASONAL:seasonal period:gamma:rra-num[:smoothing-window=fraction]
RRA:DEVPREDICT:rows:rra-num
@@ -231,18 +270,30 @@ flagging aberrant behavior in the data source time series:These RRAs differ from the true consolidation functions in several ways. First, each of the RRAs is updated once for every primary data point. Second, these RRAs 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 RRA and SEASONAL RRA. Aberrant behavior -detection requires FAILURES, HWPREDICT, DEVSEASONAL, and SEASONAL.
-The actual predicted, or smoothed, values are stored in the HWPREDICT -RRA. The predicted deviations are stored in DEVPREDICT (think a standard -deviation which can be scaled to yield a confidence band). The FAILURES -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 RRAs to graph confidence bounds and failures -appears in the rrdgraph manpage.
+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 RRA and either an HWPREDICT or MHWPREDICT +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 +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 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 RRAs to graph +confidence bounds and failures appears in the rrdgraph manpage.
The SEASONAL and DEVSEASONAL RRAs 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 @@ -293,6 +344,12 @@ coefficient.
If SEASONAL and DEVSEASONAL RRAs are created explicitly, gamma need not be the same for both. Note that gamma can also be changed via the RRDtool tune command.
+smoothing-window specifies the fraction of a season that should be +averaged around each point. By default, the value of smoothing-window is +0.05, which means each value in SEASONAL and DEVSEASONAL will be occasionally +replaced by averaging it with its (seasonal period*0.05) nearest neighbors. +Setting smoothing-window to zero will disable the running-average smoother +altogether.
rra-num provides the links between related RRAs. If HWPREDICT is specified alone and the other RRAs are created implicitly, then there is no need to worry about this argument. If RRAs are created @@ -335,28 +392,28 @@ default value is 9.
It may help you to sort out why all this *UNKNOWN* data is popping up in your databases:RRDtool gets fed samples/updates at arbitrary times. From these it builds Primary -Data Points (PDPs) on every ``step'' interval. The PDPs are +Data Points (PDPs) on every "step" interval. The PDPs are then accumulated into the RRAs.
-The ``heartbeat'' defines the maximum acceptable interval between -samples/updates. If the interval between samples is less than ``heartbeat'', +
The "heartbeat" defines the maximum acceptable interval between +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 +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 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. If the total ``unknown'' time accounts for -more than half the ``step'', the entire PDP is marked -as ``unknown''. This means that a mixture of known and ``unknown'' sample -times in a single PDP ``step'' may or may not add up to enough ``known'' -time to warrent for a known PDP.
-The ``heartbeat'' can be short (unusual) or long (typical) relative to -the ``step'' interval between PDPs. A short ``heartbeat'' means you +
The known rates during a PDP's "step" interval are used to calculate +an average rate for that PDP. If the total "unknown" time accounts for +more than half the "step", the entire PDP is marked +as "unknown". This means that a mixture of known and "unknown" sample +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 +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 5 minutes and a -``heartbeat'' of one day, in which case a single sample every day will +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. -- Don Baarda <don.baarda@baesystems.com>
@@ -402,7 +459,7 @@ same average rate. -- Don Baarda <HOW TO MEASURE-Here are a few hints on how to measure:
-
- Temperature
+- Temperature
- -
Usually you have some type of meter you can read to get the temperature. @@ -411,11 +468,11 @@ that the temperature reading happened at a certain time. You can use the GAUGE data source type for this. RRDtool will then record your reading together with the time.
- Mail Messages
+- Mail Messages
- -
Assume you have a method to count the number of messages transported by -your mailserver in a certain amount of time, giving you data like '5 +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 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 @@ -425,7 +482,7 @@ from RRDtool for the day in question and multiply this number with the number of seconds in a day. Because all math is run with Doubles, the precision should be acceptable.
- It's always a Rate
+- It's always a Rate
RRDtool stores rates in amount/second for COUNTER, DERIVE and ABSOLUTE @@ -433,7 +490,7 @@ 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 +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 @@ -452,7 +509,7 @@ on the y axis, days on the x axis and one bar for each day).
RRA:MIN:0.5:12:2400 \ RRA:MAX:0.5:12:2400 \ RRA:AVERAGE:0.5:12:2400
This sets up an RRD called temperature.rrd which accepts one +
This sets up an RRD called temperature.rrd which accepts one temperature value every 300 seconds. If no new data is supplied for more than 600 seconds, the temperature becomes *UNKNOWN*. The minimum acceptable value is -273 and the maximum is 5'000.