RRDCREATE(1)                 rrdtool                 RRDCREATE(1)



NNAAMMEE
       rrdcreate - Set up a new Round Robin Database

SSYYNNOOPPSSIISS
       rrrrddttooooll ccrreeaattee _f_i_l_e_n_a_m_e [----ssttaarrtt|--bb _s_t_a_r_t _t_i_m_e]
       [----sstteepp|--ss _s_t_e_p] [DDSS::_d_s_-_n_a_m_e::_D_S_T::_d_s_t _a_r_g_u_m_e_n_t_s]
       [RRRRAA::_C_F::_c_f _a_r_g_u_m_e_n_t_s]

DDEESSCCRRIIPPTTIIOONN
       The create function of RRDtool lets you set up new Round
       Robin Database (RRRRDD) files.  The file is created at its
       final, full size and filled with _*_U_N_K_N_O_W_N_* data.

       _f_i_l_e_n_a_m_e
               The name of the RRRRDD you want to create. RRRRDD files
               should end with the extension _._r_r_d. However, RRRRDD--
               ttooooll will accept any filename.

       ----ssttaarrtt|--bb _s_t_a_r_t _t_i_m_e (default: now - 10s)
               Specifies the time in seconds since 1970-01-01 UTC
               when the first value should be added to the RRRRDD.
               RRRRDDttooooll will not accept any data timed before or
               at the time specified.

               See also AT-STYLE TIME SPECIFICATION section in
               the _r_r_d_f_e_t_c_h documentation for other ways to spec-
               ify time.

       ----sstteepp|--ss _s_t_e_p (default: 300 seconds)
               Specifies the base interval in seconds with which
               data will be fed into the RRRRDD.

       DDSS::_d_s_-_n_a_m_e::_D_S_T::_d_s_t _a_r_g_u_m_e_n_t_s
               A single RRRRDD can accept input from several data
               sources (DDSS), for example incoming and outgoing
               traffic on a specific communication line. With the
               DDSS configuration option you must define some basic
               properties of each data source you want to store
               in the RRRRDD.

               _d_s_-_n_a_m_e is the name you will use to reference this
               particular data source from an RRRRDD. A _d_s_-_n_a_m_e must
               be 1 to 19 characters long in the characters
               [a-zA-Z0-9_].

               _D_S_T 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:

               DDSS::_d_s_-_n_a_m_e::_G_A_U_G_E _| _C_O_U_N_T_E_R _| _D_E_R_I_V_E _| _A_B_S_O_-
               _L_U_T_E::_h_e_a_r_t_b_e_a_t::_m_i_n::_m_a_x

               For COMPUTE data sources, the format is:

               DDSS::_d_s_-_n_a_m_e::_C_O_M_P_U_T_E::_r_p_n_-_e_x_p_r_e_s_s_i_o_n

               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.

               GGAAUUGGEE
                   is for things like temperatures or number of
                   people in a room or the value of a RedHat
                   share.

               CCOOUUNNTTEERR
                   is for continuous incrementing counters like
                   the ifInOctets counter in a router. The
                   CCOOUUNNTTEERR data source assumes that the counter
                   never decreases, except when a counter over-
                   flows.  The update function takes the overflow
                   into account.  The counter is stored as a per-
                   second rate. When the counter overflows, RRD-
                   tool checks if the overflow happened at the
                   32bit or 64bit border and acts accordingly by
                   adding an appropriate value to the result.

               DDEERRIIVVEE
                   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 enter-
                   ing or leaving a room. Internally, derive
                   works exactly like COUNTER but without over-
                   flow 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
                       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 counter wraps and
                       resets, always use DERIVE with min=0. Oth-
                       erwise, using COUNTER with a suitable max
                       will return correct values for all legiti-
                       mate 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 inter-
                       faces 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.

               AABBSSOOLLUUTTEE
                   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 maximum time available before the
                   next overflow. Another usage is for things you
                   count like number of messages since the last
                   update.

               CCOOMMPPUUTTEE
                   is for storing the result of a formula applied
                   to other data sources in the RRRRDD. This data
                   source is not supplied a value on update, but
                   rather its Primary Data Points (PDPs) are com-
                   puted 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.

               _h_e_a_r_t_b_e_a_t defines the maximum number of seconds
               that may pass between two updates of this data
               source before the value of the data source is
               assumed to be _*_U_N_K_N_O_W_N_*.

               _m_i_n and _m_a_x define the expected range values for
               data supplied by a data source. If _m_i_n and/or _m_a_x
               any value outside the defined range will be
               regarded as _*_U_N_K_N_O_W_N_*. 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-CCOOUUNNTTEERR type DS
               this would be the maximum and minimum data-rate
               expected from the device.

               _I_f _i_n_f_o_r_m_a_t_i_o_n _o_n _m_i_n_i_m_a_l_/_m_a_x_i_m_a_l _e_x_p_e_c_t_e_d _v_a_l_u_e_s
               _i_s _a_v_a_i_l_a_b_l_e_, _a_l_w_a_y_s _s_e_t _t_h_e _m_i_n _a_n_d_/_o_r _m_a_x _p_r_o_p_-
               _e_r_t_i_e_s_. _T_h_i_s _w_i_l_l _h_e_l_p _R_R_D_t_o_o_l _i_n _d_o_i_n_g _a _s_i_m_p_l_e
               _s_a_n_i_t_y _c_h_e_c_k _o_n _t_h_e _d_a_t_a _s_u_p_p_l_i_e_d _w_h_e_n _r_u_n_n_i_n_g
               _u_p_d_a_t_e_.

               _r_p_n_-_e_x_p_r_e_s_s_i_o_n 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 defin-
               ing a CCDDEEFF argument for the graph command. Please
               refer to that manual page for a list and descrip-
               tion of RPN operations supported. For COMPUTE data
               sources, the following RPN operations are not sup-
               ported: 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 CCDDEEFFs must refer
               only to DDEEFFs and CCDDEEFFs previously defined in the
               same graph command.

       RRRRAA::_C_F::_c_f _a_r_g_u_m_e_n_t_s
               The purpose of an RRRRDD is to store data in the
               round robin archives (RRRRAA). An archive consists of
               a number of data values or statistics for each of
               the defined data-sources (DDSS) and is defined with
               an RRRRAA line.

               When data is entered into an RRRRDD, it is first fit
               into time slots of the length defined with the --ss
               option, thus becoming a _p_r_i_m_a_r_y _d_a_t_a _p_o_i_n_t.

               The data is also processed with the consolidation
               function (_C_F) of the archive. There are several
               consolidation functions that consolidate primary
               data points via an aggregate function: AAVVEERRAAGGEE,
               MMIINN, MMAAXX, LLAASSTT. The format of RRRRAA line for these
               consolidation functions is:

               RRRRAA::_A_V_E_R_A_G_E _| _M_I_N _| _M_A_X _| _L_A_S_T::_x_f_f::_s_t_e_p_s::_r_o_w_s

               _x_f_f The xfiles factor defines what part of a con-
               solidation interval may be made up from _*_U_N_K_N_O_W_N_*
               data while the consolidated value is still
               regarded as known. It is given as the ratio of
               allowed _*_U_N_K_N_O_W_N_* PDPs to the number of PDPs in
               the interval. Thus, it ranges from 0 to 1 (exclu-
               sive).

               _s_t_e_p_s defines how many of these _p_r_i_m_a_r_y _d_a_t_a
               _p_o_i_n_t_s are used to build a _c_o_n_s_o_l_i_d_a_t_e_d _d_a_t_a _p_o_i_n_t
               which then goes into the archive.

               _r_o_w_s defines how many generations of data values
               are kept in an RRRRAA.

AAbbeerrrraanntt BBeehhaavviioorr DDeetteeccttiioonn wwiitthh HHoolltt--WWiinntteerrss FFoorreeccaassttiinngg
       In addition to the aggregate functions, there are a set of
       specialized functions that enable RRRRDDttooooll to provide data
       smoothing (via the Holt-Winters forecasting algorithm),
       confidence bands, and the flagging aberrant behavior in
       the data source time series:

       +o   RRRRAA::_H_W_P_R_E_D_I_C_T::_r_o_w_s::_a_l_p_h_a::_b_e_t_a::_s_e_a_s_o_n_a_l _p_e_r_i_o_d[::_r_r_a_-
           _n_u_m]

       +o   RRRRAA::_S_E_A_S_O_N_A_L::_s_e_a_s_o_n_a_l _p_e_r_i_o_d::_g_a_m_m_a::_r_r_a_-_n_u_m

       +o   RRRRAA::_D_E_V_S_E_A_S_O_N_A_L::_s_e_a_s_o_n_a_l _p_e_r_i_o_d::_g_a_m_m_a::_r_r_a_-_n_u_m

       +o   RRRRAA::_D_E_V_P_R_E_D_I_C_T::_r_o_w_s::_r_r_a_-_n_u_m

       +o   RRRRAA::_F_A_I_L_U_R_E_S::_r_o_w_s::_t_h_r_e_s_h_o_l_d::_w_i_n_d_o_w _l_e_n_g_t_h::_r_r_a_-_n_u_m

       These RRRRAAss differ from the true consolidation functions in
       several ways.  First, each of the RRRRAAs is updated once for
       every primary data point.  Second, these RRRRAAss are interde-
       pendent. 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 RRRRAA and SEA-
       SONAL RRRRAA. Aberrant behavior detection requires FAILURES,
       HWPREDICT, DEVSEASONAL, and SEASONAL.

       The actual predicted, or smoothed, values are stored in
       the HWPREDICT RRRRAA. The predicted deviations are stored in
       DEVPREDICT (think a standard deviation which can be scaled
       to yield a confidence band). The FAILURES RRRRAA stores
       binary indicators. A 1 marks the indexed observation as
       failure; that is, the number of confidence bounds viola-
       tions in the preceding window of observations met or
       exceeded a specified threshold. An example of using these
       RRRRAAss to graph confidence bounds and failures appears in
       rrdgraph.

       The SEASONAL and DEVSEASONAL RRRRAAss store the seasonal coef-
       ficients for the 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 will have 288 rows.

       In order to simplify the creation for the novice user, in
       addition to supporting explicit creation of the HWPREDICT,
       SEASONAL, DEVPREDICT, DEVSEASONAL, and FAILURES RRRRAAss, the
       RRRRDDttooooll create command supports implicit creation of the
       other four when HWPREDICT is specified alone and the final
       argument _r_r_a_-_n_u_m is omitted.

       _r_o_w_s specifies the length of the RRRRAA 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, _r_o_w_s should be larger than the _s_e_a_s_o_n_a_l
       _p_e_r_i_o_d. If the DEVPREDICT RRRRAA is implicitly created, the
       default number of rows is the same as the HWPREDICT _r_o_w_s
       argument. If the FAILURES RRRRAA is implicitly created, _r_o_w_s
       will be set to the _s_e_a_s_o_n_a_l _p_e_r_i_o_d argument of the HWPRE-
       DICT RRRRAA. Of course, the RRRRDDttooooll _r_e_s_i_z_e command is avail-
       able if these defaults are not sufficient and the creator
       wishes to avoid explicit creations of the other special-
       ized function RRRRAAss.

       _s_e_a_s_o_n_a_l _p_e_r_i_o_d specifies the number of primary data
       points in a seasonal cycle. If SEASONAL and DEVSEASONAL
       are implicitly created, this argument for those RRRRAAss is
       set automatically to the value specified by HWPREDICT. If
       they are explicitly created, the creator should verify
       that all three _s_e_a_s_o_n_a_l _p_e_r_i_o_d arguments agree.

       _a_l_p_h_a is the adaption parameter of the intercept (or base-
       line) coefficient in the Holt-Winters forecasting algo-
       rithm. See rrdtool for a description of this algorithm.
       _a_l_p_h_a must lie between 0 and 1. A value closer to 1 means
       that more recent observations carry greater weight in pre-
       dicting the baseline component of the forecast. A value
       closer to 0 means that past history carries greater weight
       in predicting the baseline component.

       _b_e_t_a is the adaption parameter of the slope (or linear
       trend) coefficient in the Holt-Winters forecasting algo-
       rithm. _b_e_t_a must lie between 0 and 1 and plays the same
       role as _a_l_p_h_a with respect to the predicted linear trend.

       _g_a_m_m_a is the adaption parameter of the seasonal coeffi-
       cients in the Holt-Winters forecasting algorithm (HWPRE-
       DICT) or the adaption parameter in the exponential smooth-
       ing update of the seasonal deviations. It must lie between
       0 and 1. If the SEASONAL and DEVSEASONAL RRRRAAss are created
       implicitly, they will both have the same value for _g_a_m_m_a:
       the value specified for the HWPREDICT _a_l_p_h_a argument. Note
       that because there is one seasonal coefficient (or devia-
       tion) for each time point during the 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 RRRRAAss are created explicitly,
       _g_a_m_m_a need not be the same for both. Note that _g_a_m_m_a can
       also be changed via the RRRRDDttooooll _t_u_n_e command.

       _r_r_a_-_n_u_m provides the links between related RRRRAAss. If HWPRE-
       DICT is specified alone and the other RRRRAAss are created
       implicitly, then there is no need to worry about this
       argument. If RRRRAAss are created explicitly, then carefully
       pay attention to this argument. For each RRRRAA which
       includes this argument, there is a dependency between that
       RRRRAA and another RRRRAA. The _r_r_a_-_n_u_m argument is the 1-based
       index in the order of RRRRAA creation (that is, the order
       they appear in the _c_r_e_a_t_e command). The dependent RRRRAA for
       each RRRRAA requiring the _r_r_a_-_n_u_m argument is listed here:

       +o   HWPREDICT _r_r_a_-_n_u_m is the index of the SEASONAL RRRRAA.

       +o   SEASONAL _r_r_a_-_n_u_m is the index of the HWPREDICT RRRRAA.

       +o   DEVPREDICT _r_r_a_-_n_u_m is the index of the DEVSEASONAL
           RRRRAA.

       +o   DEVSEASONAL _r_r_a_-_n_u_m is the index of the HWPREDICT RRRRAA.

       +o   FAILURES _r_r_a_-_n_u_m is the index of the DEVSEASONAL RRRRAA.

       _t_h_r_e_s_h_o_l_d is the minimum number of violations (observed
       values outside the confidence bounds) within a window that
       constitutes a failure. If the FAILURES RRRRAA is implicitly
       created, the default value is 7.

       _w_i_n_d_o_w _l_e_n_g_t_h 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 win-
       dow represents depends on the interval between primary
       data points. If the FAILURES RRRRAA is implicitly created,
       the default value is 9.

TThhee HHEEAARRTTBBEEAATT aanndd tthhee SSTTEEPP
       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:

       RRDtool gets fed samples at arbitrary times. From these it
       builds Primary Data Points (PDPs) at exact times on every
       "step" interval. The PDPs are then accumulated into RRAs.

       The "heartbeat" defines the maximum acceptable interval
       between samples. 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.

       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 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
       "unknown" time to exceed "heartbeat" and hence mark the
       whole PDP "unknown". So "heartbeat" is not only the maxi-
       mum acceptable interval between samples, but also the max-
       imum acceptable amount of "unknown" time per PDP (obvi-
       ously this is only significant if you have "heartbeat"
       less than "step").

       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 5
       minutes and a "heartbeat" of one day, in which case a sin-
       gle sample every day will result in all the PDPs for that
       entire day period being set to the same average rate. _-_-
       _D_o_n _B_a_a_r_d_a _<_d_o_n_._b_a_a_r_d_a_@_b_a_e_s_y_s_t_e_m_s_._c_o_m_>

              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 > "hb"
               |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 _v_l_a_d_i_m_i_r_._l_a_v_r_o_v_@_d_e_s_y_._d_e.

HHOOWW TTOO MMEEAASSUURREE
       Here are a few hints on how to measure:

       Temperature
           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 GGAAUUGGEE data source type for this. RRDtool
           will then record your reading together with the time.

       Mail Messages
           Assume you have a method to count the number of mes-
           sages transported by your mailserver 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 AABBSSOOLLUUTTEE data type you can simply update the
           RRD with the number 5 and the end time of your moni-
           toring 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 from RRD-
           tool 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
           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 multi-
           plying 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 proba-
           bly 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).

EEXXAAMMPPLLEE
        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 RRRRDD called _t_e_m_p_e_r_a_t_u_r_e_._r_r_d which accepts
       one temperature value every 300 seconds. If no new data is
       supplied for more than 600 seconds, the temperature
       becomes _*_U_N_K_N_O_W_N_*.  The minimum acceptable value is -273
       and the maximum is 5'000.

       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 (2'400 hours). The third and the fourth RRA's do
       the same for the maximum and average temperature, respec-
       tively.

EEXXAAMMPPLLEE 22
        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
       RRRRAA tracks the traffic flow in octets; the second RRRRAA gen-
       erates the specialized functions RRRRAAss for aberrant behav-
       ior detection. Note that the _r_r_a_-_n_u_m argument of HWPREDICT
       is missing, so the other RRRRAAss will implicitly be created
       with default parameter values. In this example, the fore-
       casting algorithm baseline adapts quickly; in fact the
       most recent one hour of observations (each at 5 minute
       intervals) accounts for 75% of the baseline prediction.
       The linear trend forecast adapts much more slowly. Obser-
       vations 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 the LISA 2000 paper.

       The seasonal cycle is one day (288 data points at 300 sec-
       ond intervals), and 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 RRRRAA.

       The same RRD file and RRRRAAss are created with the following
       command, which explicitly creates all specialized function
       RRRRAAss.

        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.

EEXXAAMMPPLLEE 3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 pro-
       cessed requests. Clearly these counters both have some
       rollover point, but using the DERIVE data source also han-
       dles the reset that occurs when the web proxy is stopped
       and restarted.

       In the RRRRDD, 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 dura-
       tion. The remainder of the RPN expression handles the
       divide by zero case.

AAUUTTHHOORR
       Tobias Oetiker <tobi@oetiker.ch>



1.2.15                      2006-07-14               RRDCREATE(1)
