X-Git-Url: https://git.tokkee.org/?p=pkg-rrdtool.git;a=blobdiff_plain;f=doc%2Frrdcreate.txt;h=64d1633d675ef91b5dd4324d8466d828b2c061e7;hp=18647ec9b4c7a110b12840e20aff2bd8dbf7a8e7;hb=645054bac6187b0e83fd4125fd59e4feda216b64;hpb=ffa00ac697dccce18dca8880ca7a14066521ac5c diff --git a/doc/rrdcreate.txt b/doc/rrdcreate.txt index 18647ec..64d1633 100644 --- a/doc/rrdcreate.txt +++ b/doc/rrdcreate.txt @@ -14,29 +14,25 @@ DDEESSCCRRIIPPTTIIOONN (RRRRDD) 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 - + _f_i_l_e_n_a_m_e The name of the RRRRDD you want to create. RRRRDD files should end with the extension _._r_r_d. However, RRRRDDttooooll will accept any filename. - ----ssttaarrtt||--bb _s_t_a_r_t _t_i_m_e ((ddeeffaauulltt:: nnooww -- 1100ss)) - + ----ssttaarrtt||--bb _s_t_a_r_t _t_i_m_e ((ddeeffaauulltt:: nnooww -- 1100ss)) Specifies the time in seconds since 1970-01-01 UTC when the first value should be added to the RRRRDD. RRRRDDttooooll 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 documenta- - tion for other ways to specify time. - - ----sstteepp||--ss _s_t_e_p ((ddeeffaauulltt:: 330000 sseeccoonnddss)) + See also AT-STYLE TIME SPECIFICATION section in the _r_r_d_f_e_t_c_h + documentation for other ways to specify time. + ----sstteepp||--ss _s_t_e_p ((ddeeffaauulltt:: 330000 sseeccoonnddss)) Specifies the base interval in seconds with which data will be fed into the RRRRDD. - DDSS::_d_s_-_n_a_m_e::_D_S_T::_d_s_t _a_r_g_u_m_e_n_t_s - - A single RRRRDD can accept input from several data sources (DDSS), for exam- - ple incoming and outgoing traffic on a specific communication line. + DDSS::_d_s_-_n_a_m_e::_D_S_T::_d_s_t _a_r_g_u_m_e_n_t_s + A single RRRRDD can accept input from several data sources (DDSS), for + example incoming and outgoing traffic on a specific communication line. With the DDSS configuration option you must define some basic properties of each data source you want to store in the RRRRDD. @@ -54,9 +50,9 @@ DDEESSCCRRIIPPTTIIOONN DDSS::_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 defini- - tions that follow. Also consult the section on "HOW TO MEASURE" for - further insight. + 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. GGAAUUGGEE is for things like temperatures or number of people in a room or @@ -91,28 +87,28 @@ DDEESSCCRRIIPPTTIIOONN 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 mistak- - ing 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 pos- - sibility of mistaking a reset for a 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. AABBSSOOLLUUTTEE is for counters which get reset upon reading. This is used for fast - counters which tend to overflow. So instead of reading them nor- - mally you reset them after every read to make sure you have a maxi- - mum time available before the next overflow. Another usage is for - things you count like number of messages since the last update. + 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. CCOOMMPPUUTTEE is for storing the result of a formula applied to other data sources in the RRRRDD. 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 nor- - mally to the PDPs of the COMPUTE data source (that is the rpn- + 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. @@ -134,16 +130,15 @@ DDEESSCCRRIIPPTTIIOONN _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 . It is similar to defining a CCDDEEFF argument for the graph command. Please refer - to that manual page for a list and description of RPN operations sup- - ported. 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 CCDDEEFFs must refer only to DDEEFFs and CCDDEEFFs previously - defined in the same graph command. - - RRRRAA::_C_F::_c_f _a_r_g_u_m_e_n_t_s - + 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 CCDDEEFFs must refer only to DDEEFFs and CCDDEEFFs + previously defined in the same graph command. + + RRRRAA::_C_F::_c_f _a_r_g_u_m_e_n_t_s The purpose of an RRRRDD is to store data in the round robin archives (RRRRAA). An archive consists of a number of data values or statistics for each of the defined data-sources (DDSS) and is defined with an RRRRAA line. @@ -168,8 +163,8 @@ DDEESSCCRRIIPPTTIIOONN Note that data aggregation inevitably leads to loss of precision and information. The trick is to pick the aggregate function such that the - _i_n_t_e_r_e_s_t_i_n_g properties of your data is kept across the aggregation pro- - cess. + _i_n_t_e_r_e_s_t_i_n_g properties of your data is kept across the aggregation + process. The format of RRRRAA line for these consolidation functions is: @@ -193,43 +188,43 @@ AAbbeerrrraanntt BBeehhaavviioorr DDeetteeccttiioonn w Winters forecasting algorithm), confidence bands, and the flagging aberrant behavior in the data source time series: - · RRRRAA::_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] + · RRRRAA::_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] - · RRRRAA::_M_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] + · RRRRAA::_M_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] - · RRRRAA::_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[::ssmmooootthhiinngg--wwiinnddooww==_f_r_a_c_- - _t_i_o_n] + · RRRRAA::_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[::ssmmooootthhiinngg--wwiinnddooww==_f_r_a_c_t_i_o_n] - · RRRRAA::_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[::ssmmooootthhiinngg--wwiinn-- - ddooww==_f_r_a_c_t_i_o_n] + · RRRRAA::_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[::ssmmooootthhiinngg--wwiinnddooww==_f_r_a_c_t_i_o_n] - · RRRRAA::_D_E_V_P_R_E_D_I_C_T::_r_o_w_s::_r_r_a_-_n_u_m + · RRRRAA::_D_E_V_P_R_E_D_I_C_T::_r_o_w_s::_r_r_a_-_n_u_m - · RRRRAA::_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 + · RRRRAA::_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 RRRRAAss differ from the true consolidation functions in several ways. First, each of the RRRRAAs is updated once for every primary data point. Second, these RRRRAAss are interdependent. To generate real-time confidence bounds, a matched set of SEASONAL, DEVSEASONAL, DEVPREDICT, - and either HWPREDICT or MHWPREDICT must exist. Generating smoothed val- - ues of the primary data points requires a SEASONAL RRRRAA and either an - HWPREDICT or MHWPREDICT RRRRAA. Aberrant behavior detection requires FAIL- - URES, DEVSEASONAL, SEASONAL, and either HWPREDICT or MHWPREDICT. + and either HWPREDICT or MHWPREDICT must exist. Generating smoothed + values of the primary data points requires a SEASONAL RRRRAA and either an + HWPREDICT or MHWPREDICT RRRRAA. Aberrant behavior detection requires + FAILURES, DEVSEASONAL, SEASONAL, and either HWPREDICT or MHWPREDICT. - The predicted, or smoothed, values are stored in the HWPREDICT or MHW- - PREDICT RRRRAA. HWPREDICT and MHWPREDICT are actually two variations on + The predicted, or smoothed, values are stored in the HWPREDICT or + MHWPREDICT RRRRAA. 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 sea- - sonal coefficient. HWPREDICT adds its seasonal coefficient to the - baseline to form a prediction, whereas MHWPREDICT multiplies its sea- - sonal 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 substi- - tuted in its place. + 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 @@ -243,8 +238,8 @@ AAbbeerrrraanntt BBeehhaavviioorr DDeetteeccttiioonn w 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 DEVSEA- - SONAL will have 288 rows. + 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, @@ -257,46 +252,46 @@ AAbbeerrrraanntt BBeehhaavviioorr DDeetteeccttiioonn w 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 RRRRAA is implicitly created, the default number of rows is the same as the HWPREDICT _r_o_w_s argument. - If the FAILURES RRRRAA 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 HWPREDICT RRRRAA. Of course, the RRRRDDttooooll + If the FAILURES RRRRAA 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 HWPREDICT RRRRAA. Of course, the RRRRDDttooooll _r_e_s_i_z_e command is available if these defaults are not sufficient and the creator wishes to avoid explicit creations of the other specialized function RRRRAAss. - _s_e_a_s_o_n_a_l _p_e_r_i_o_d specifies the number of primary data points in a sea- - sonal cycle. If SEASONAL and DEVSEASONAL are implicitly created, this - argument for those RRRRAAss 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 baseline) coeffi- - cient in the Holt-Winters forecasting algorithm. 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 - predicting the baseline component of the forecast. A value closer to 0 - means that past history carries greater weight in predicting the base- - line component. - - _b_e_t_a is the adaption parameter of the slope (or linear trend) coeffi- - cient in the Holt-Winters forecasting algorithm. _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. + _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 RRRRAAss 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 baseline) + coefficient in the Holt-Winters forecasting algorithm. 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 predicting 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 algorithm. _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 coefficients in the - Holt-Winters forecasting algorithm (HWPREDICT) or the adaption parame- - ter in the exponential smoothing update of the seasonal deviations. It - must lie between 0 and 1. If the SEASONAL and DEVSEASONAL RRRRAAss are cre- - ated 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 deviation) 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 corre- - sponding to that coefficient. + 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 RRRRAAss 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 deviation) 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 RRRRAAss 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 RRRRDD-- - ttooooll _t_u_n_e command. + be the same for both. Note that _g_a_m_m_a can also be changed via the + RRRRDDttooooll _t_u_n_e command. _s_m_o_o_t_h_i_n_g_-_w_i_n_d_o_w specifies the fraction of a season that should be averaged around each point. By default, the value of _s_m_o_o_t_h_i_n_g_-_w_i_n_d_o_w @@ -305,24 +300,25 @@ AAbbeerrrraanntt BBeehhaavviioorr DDeetteeccttiioonn w nearest neighbors. Setting _s_m_o_o_t_h_i_n_g_-_w_i_n_d_o_w to zero will disable the running-average smoother altogether. - _r_r_a_-_n_u_m provides the links between related RRRRAAss. If HWPREDICT is speci- - fied alone and the other RRRRAAss are created implicitly, then there is no - need to worry about this argument. If RRRRAAss are created explicitly, then - carefully pay attention to this argument. For each RRRRAA which includes - this argument, there is a dependency between that RRRRAA and another RRRRAA. - The _r_r_a_-_n_u_m argument is the 1-based index in the order of RRRRAA creation - (that is, the order they appear in the _c_r_e_a_t_e command). The dependent - RRRRAA for each RRRRAA requiring the _r_r_a_-_n_u_m argument is listed here: + _r_r_a_-_n_u_m provides the links between related RRRRAAss. If HWPREDICT is + specified alone and the other RRRRAAss are created implicitly, then there + is no need to worry about this argument. If RRRRAAss are created + explicitly, then carefully pay attention to this argument. For each RRRRAA + which includes this argument, there is a dependency between that RRRRAA + and another RRRRAA. The _r_r_a_-_n_u_m argument is the 1-based index in the order + of RRRRAA creation (that is, the order they appear in the _c_r_e_a_t_e command). + The dependent RRRRAA for each RRRRAA requiring the _r_r_a_-_n_u_m argument is listed + here: - · HWPREDICT _r_r_a_-_n_u_m is the index of the SEASONAL RRRRAA. + · HWPREDICT _r_r_a_-_n_u_m is the index of the SEASONAL RRRRAA. - · SEASONAL _r_r_a_-_n_u_m is the index of the HWPREDICT RRRRAA. + · SEASONAL _r_r_a_-_n_u_m is the index of the HWPREDICT RRRRAA. - · DEVPREDICT _r_r_a_-_n_u_m is the index of the DEVSEASONAL RRRRAA. + · DEVPREDICT _r_r_a_-_n_u_m is the index of the DEVSEASONAL RRRRAA. - · DEVSEASONAL _r_r_a_-_n_u_m is the index of the HWPREDICT RRRRAA. + · DEVSEASONAL _r_r_a_-_n_u_m is the index of the HWPREDICT RRRRAA. - · FAILURES _r_r_a_-_n_u_m is the index of the DEVSEASONAL RRRRAA. + · FAILURES _r_r_a_-_n_u_m is the index of the DEVSEASONAL RRRRAA. _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 @@ -330,9 +326,9 @@ AAbbeerrrraanntt BBeehhaavviioorr DDeetteeccttiioonn w _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 window represents depends on the inter- - val between primary data points. If the FAILURES RRRRAA is implicitly cre- - ated, the default value is 9. + to 28. The time interval this window represents depends on the + interval between primary data points. If the FAILURES RRRRAA is implicitly + created, the default value is 9. TThhee HHEEAARRTTBBEEAATT aanndd tthhee SSTTEEPP Here is an explanation by Don Baarda on the inner workings of RRDtool. @@ -343,13 +339,14 @@ TThhee HHEEAARRTTBBEEAATT aanndd tthhee SSTTEEPP 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 sam- - ples/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 a sample that was explicitly marked as unknown. + 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 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 @@ -363,10 +360,10 @@ TThhee HHEEAARRTTBBEEAATT aanndd tthhee SSTTEEPP 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 "heart- - beat" 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 aver- - age 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_> + 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. _-_- _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| @@ -410,28 +407,28 @@ HHOOWW TTOO MMEEAASSUURREE Here are a few hints on how to measure: Temperature - Usually you have some type of meter you can read to get the temper- - ature. The temperature is not really connected with a time. The - only connection is that the temperature reading happened at a cer- - tain time. You can use the GGAAUUGGEE data source type for this. RRDtool - will then record your reading together with the time. + 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 GGAAUUGGEE 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 messages trans- - ported 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 AABBSSOOLLUUTTEE data type you can simply update the RRD - with the number 5 and the end time of your monitoring period. RRD- - tool 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 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 preci- - sion should be acceptable. + 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 messages in the last 65 seconds'. If you look at + the count of 5 like an AABBSSOOLLUUTTEE 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 + 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 - RRDtool stores rates in amount/second for COUNTER, DERIVE and ABSO- - LUTE data. When you plot the data, you will get on the y axis + 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 @@ -451,17 +448,17 @@ EEXXAAMMPPLLEE RRA:MAX:0.5:12:2400 \ RRA:AVERAGE:0.5:12:2400 - This sets up an RRRRDD called _t_e_m_p_e_r_a_t_u_r_e_._r_r_d which accepts one tempera- - ture 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. + This sets up an RRRRDD 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. + RRA's do the same for the maximum and average temperature, + respectively. EEXXAAMMPPLLEE 22 rrdtool create monitor.rrd --step 300 \ @@ -475,18 +472,18 @@ EEXXAAMMPPLLEE 22 argument of HWPREDICT is missing, so the other RRRRAAss 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) accounts for 75% of the base- - line prediction. The linear trend forecast adapts much more slowly. + observations (each at 5 minute intervals) accounts for 75% of the + baseline prediction. The linear trend forecast adapts much more slowly. Observations made during the last day (at 288 observations per day) - account for only 65% of the predicted linear trend. Note: these compu- - tations rely on an exponential smoothing formula described in the LISA - 2000 paper. + 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 second inter- - vals), 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 RRRRAA. + The seasonal cycle is one day (288 data points at 300 second + 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 RRRRAA. The same RRD file and RRRRAAss are created with the following command, which explicitly creates all specialized function RRRRAAss. @@ -500,8 +497,8 @@ EEXXAAMMPPLLEE 22 RRA:DEVSEASONAL:288:0.1:2 \ RRA:FAILURES:288:7:9:5 - Of course, explicit creation need not replicate implicit create, a num- - ber of arguments could be changed. + Of course, explicit creation need not replicate implicit create, a + number of arguments could be changed. EEXXAAMMPPLLEE 33 rrdtool create proxy.rrd --step 300 \ @@ -520,14 +517,15 @@ EEXXAAMMPPLLEE 33 In the RRRRDD, 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 COM- - PUTE data source divides each PDP of the AccumDuration by the corre- - sponding PDP of TotalRequests and stores the average request duration. - The remainder of the RPN expression handles the divide by zero case. + 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. AAUUTTHHOORR Tobias Oetiker -1.3.99909060808 2008-06-11 RRDCREATE(1) +1.3.999 2009-04-19 RRDCREATE(1)