_R_R_D_-_B_E_G_I_N_N_E_R_S(1)                    rrdtool                   _R_R_D_-_B_E_G_I_N_N_E_R_S(1)

NNAAMMEE
       rrd-beginners - RRDtool Beginners' Guide

SSYYNNOOPPSSIISS
       Helping new RRDtool users to understand the basics of RRDtool

DDEESSCCRRIIPPTTIIOONN
       This manual is an attempt to assist beginners in understanding the
       concepts of RRDtool. It sheds a light on differences between RRDtool
       and other databases. With help of an example, it explains the structure
       of RRDtool database. This is followed by an overview of the "graph"
       feature of RRDtool.  At the end, it has sample scripts that illustrate
       the usage/wrapping of RRDtool within Shell or Perl scripts.

   WWhhaatt mmaakkeess RRRRDDttooooll ssoo ssppeecciiaall??
       RRDtool is GNU licensed software developed by Tobias Oetiker, a system
       manager at the Swiss Federal Institute of Technology. Though it is a
       database, there are distinct differences between RRDtool databases and
       other databases as listed below:

       •   RRDtool  stores  data;  that  makes it a back-end tool. The RRDtool
           command set allows one to create graphs; that makes it a  front-end
           tool  as  well.  Other databases just store data and can not create
           graphs.

       •   In case of linear databases, new data gets appended at  the  bottom
           of  the  database table. Thus its size keeps on increasing, whereas
           the size of an RRDtool database is  determined  at  creation  time.
           Imagine  an  RRDtool database as the perimeter of a circle. Data is
           added along the perimeter.  When  new  data  reaches  the  starting
           point,  it  overwrites  existing  data.  This  way,  the size of an
           RRDtool database always remains constant. The  name  "Round  Robin"
           stems from this behavior.

       •   Other  databases  store  the  values  as  supplied.  RRDtool can be
           configured to calculate the rate of change from the previous to the
           current value and store this information instead.

       •   Other databases get updated when values are supplied.  The  RRDtool
           database  is  structured  in  such  a  way  that  it  needs data at
           predefined time intervals. If it does not get a  new  value  during
           the  interval,  it  stores  an UNKNOWN value for that interval. So,
           when using the RRDtool database, it is imperative  to  use  scripts
           that  run  at  regular  intervals to ensure a constant data flow to
           update the RRDtool database.

       RRDtool is designed to store time  series  of  data.  With  every  data
       update, an associated time stamp is stored. Time is always expressed in
       seconds  passed  since  epoch (01-01-1970). RRDtool can be installed on
       Unix as well as Windows. It comes with  a  command  set  to  carry  out
       various  operations  on RRD databases. This command set can be accessed
       from the command line, as well as  from  Shell  or  Perl  scripts.  The
       scripts act as wrappers for accessing data stored in RRDtool databases.

   UUnnddeerrssttaannddiinngg bbyy aann eexxaammppllee
       The  structure  of  an  RRD  database  is  different  than other linear
       databases.  Other databases define tables with columns, and many  other
       parameters. These definitions sometimes are very complex, especially in
       large  databases.   RRDtool databases are primarily used for monitoring
       purposes and hence are very simple in structure.  The  parameters  that
       need to be defined are variables that hold values and archives of those
       values.  Being  time sensitive, a couple of time related parameters are
       also defined. Because of its structure, the definition  of  an  RRDtool
       database  also includes a provision to specify specific actions to take
       in the absence of update values.  Data  Source  (DS),  heartbeat,  Date
       Source  Type  (DST),  Round  Robin  Archive  (RRA),  and  Consolidation
       Function  (CF)  are  some  of  the  terminologies  related  to  RRDtool
       databases.

       The  structure of a database and the terminology associated with it can
       be best explained with an example.

        rrdtool create target.rrd \
                --start 1023654125 \
                --step 300 \
                DS:mem:GAUGE:600:0:671744 \
                RRA:AVERAGE:0.5:12:24 \
                RRA:AVERAGE:0.5:288:31

       This  example  creates  a  database  named   _t_a_r_g_e_t_._r_r_d.   Start   time
       (1'023'654'125)  is  specified  in  total number of seconds since epoch
       (time in seconds since 01-01-1970). While updating  the  database,  the
       update time is also specified.  This update time MUST be larger (later)
       than start time and MUST be in seconds since epoch.

       The  step of 300 seconds indicates that the database expects new values
       every 300 seconds. The wrapper script should be scheduled to run  every
       sstteepp seconds so that it updates the database every sstteepp seconds.

       DS  (Data Source) is the actual variable which relates to the parameter
       on the device that is monitored. Its syntax is

        DS:variable_name:DST:heartbeat:min:max

       DDSS is a key word. "variable_name" is a name under which  the  parameter
       is  saved  in  the  database. There can be as many DSs in a database as
       needed. After every step interval, a new value of  DS  is  supplied  to
       update  the  database.   This  value  is also called Primary Data Point
       ((PPDDPP)). In our example mentioned above, a new PDP is generated every 300
       seconds.

       Note, that if you do NOT supply  new  data  points  exactly  every  300
       seconds,  this  is  not  a  problem,  RRDtool will interpolate the data
       accordingly.

       DDSSTT (Data Source Type) defines the type of the DS. It can  be  COUNTER,
       DERIVE, ABSOLUTE, GAUGE. A DS declared as COUNTER will save the rate of
       change  of the value over a step period. This assumes that the value is
       always increasing (the difference between the current and the  previous
       value  is  greater  than  0). Traffic counters on a router are an ideal
       candidate for using COUNTER as DST. DERIVE is the same as COUNTER,  but
       it  allows  negative  values  as  well.  If you want to see the rate of
       _c_h_a_n_g_e in free disk space on your server, then you might  want  to  use
       the  DERIVE  data  type. ABSOLUTE also saves the rate of change, but it
       assumes that the previous value is set to 0. The difference between the
       current and the previous value is always equal to  the  current  value.
       Thus it just stores the current value divided by the step interval (300
       seconds  in  our  example).  GAUGE does not save the rate of change. It
       saves the actual value itself. There are no divisions or  calculations.
       Memory  consumption  in  a  server  is  a typical example of gauge. The
       difference between the different types DSTs  can  be  explained  better
       with the following example:

        Values       = 300, 600, 900, 1200
        Step         = 300 seconds
        COUNTER DS   =    1,  1,   1,    1
        DERIVE DS    =    1,  1,   1,    1
        ABSOLUTE DS  =    1,  2,   3,    4
        GAUGE DS     = 300, 600, 900, 1200

       The  next  parameter  is  hheeaarrttbbeeaatt.  In  our example, heartbeat is 600
       seconds. If the database does not get a new PDP within 300 seconds,  it
       will  wait  for another 300 seconds (total 600 seconds).  If it doesn't
       receive any PDP within 600 seconds, it will save an UNKNOWN value  into
       the  database.  This UNKNOWN value is a special feature of RRDtool - it
       is much better than to assume a missing value was 0 (zero) or any other
       number which might also be  a  valid  data  value.   For  example,  the
       traffic flow counter on a router keeps increasing. Lets say, a value is
       missed for an interval and 0 is stored instead of UNKNOWN. Now when the
       next  value becomes available, it will calculate the difference between
       the current value and the previous value (0) which is not correct.  So,
       inserting the value UNKNOWN makes much more sense here.

       The   next   two   parameters   are  the  minimum  and  maximum  value,
       respectively. If the variable to be stored has predictable maximum  and
       minimum values, this should be specified here. Any update value falling
       out of this range will be stored as UNKNOWN.

       The  next  line  declares  a  round robin archive (RRA). The syntax for
       declaring an RRA is

        RRA:CF:xff:step:rows

       RRA is the keyword to declare RRAs. The consolidation function (CF) can
       be AVERAGE, MINIMUM, MAXIMUM, and LAST. The concept of the consolidated
       data point (CDP) comes into the picture here. A CDP is CFed  (averaged,
       maximum/minimum value or last value) from _s_t_e_p number of PDPs. This RRA
       will hold _r_o_w_s CDPs.

       Lets  have  a  look at the example above. For the first RRA, 12 (steps)
       PDPs (DS variables) are AVERAGEed (CF) to form one CDP.  24  (rows)  of
       these  CDPs  are  archived.  Each  PDP  occurs  at 300 seconds. 12 PDPs
       represent 12 times 300 seconds which is 1 hour. It means 1  CDP  (which
       is  equal  to  12  PDPs)  represents  data  worth  1 hour. 24 such CDPs
       represent 1 day (1 hour times 24 CDPs). This  means,  this  RRA  is  an
       archive  for one day. After 24 CDPs, CDP number 25 will replace the 1st
       CDP. The second RRA saves 31 CDPs; each CPD represents an AVERAGE value
       for a day (288 PDPs, each covering 300 seconds = 24  hours).  Therefore
       this  RRA  is an archive for one month. A single database can have many
       RRAs. If there are multiple DSs, each individual RRA will save data for
       all the DSs in the database. For example, if a database has 3  DSs  and
       daily,  weekly,  monthly,  and  yearly RRAs are declared, then each RRA
       will hold data from all 3 data sources.

   GGrraapphhiiccaall MMaaggiicc
       Another important feature of RRDtool is its ability to  create  graphs.
       The  "graph"  command  uses  the "fetch" command internally to retrieve
       values from the database. With the retrieved values it draws graphs  as
       defined  by the parameters supplied on the command line. A single graph
       can show different DS (Data  Sources)  from  a  database.  It  is  also
       possible  to  show  the  values from more than one database in a single
       graph. Often, it is necessary  to  perform  some  math  on  the  values
       retrieved  from the database before plotting them. For example, in SNMP
       replies, memory consumption values are usually specified in KBytes  and
       traffic  flow  on  interfaces  is  specified in Bytes. Graphs for these
       values will be more meaningful if values are represented in MBytes  and
       mbps.  The RRDtool graph command allows one to define such conversions.
       Apart from mathematical calculations, it is also  possible  to  perform
       logical  operations  such as greater than, less than, and if/then/else.
       If a database contains more than one RRA archive, then a  question  may
       arise - how does RRDtool decide which RRA archive to use for retrieving
       the  values?  RRDtool  looks  at several things when making its choice.
       First it makes sure that the RRA covers as much of  the  graphing  time
       frame  as  possible.  Second  it  looks  at  the  resolution of the RRA
       compared to the resolution of the graph. It tries to find one which has
       the same or higher better resolution. With  the  "-r"  option  you  can
       force  RRDtool to assume a different resolution than the one calculated
       from the pixel width of the graph.

       Values of different variables can be presented in 5 different shapes in
       a graph - AREA, LINE1, LINE2, LINE3, and STACK. AREA is represented  by
       a  solid  colored  area  with  values  as  the  boundary  of this area.
       LINE1/2/3 (increasing width) are  just  plain  lines  representing  the
       values.  STACK  is  also  an  area  but  it is "stack"ed on top AREA or
       LINE1/2/3. Another important  thing  to  note  is  that  variables  are
       plotted  in  the order they are defined in the graph command. Therefore
       care must be taken to define STACK only after defining AREA/LINE. It is
       also possible to put formatted comments  within  the  graph.   Detailed
       instructions can be found in the graph manual.

   WWrraappppiinngg RRRRDDttooooll wwiitthhiinn SShheellll//PPeerrll ssccrriipptt
       After understanding RRDtool it is now a time to actually use RRDtool in
       scripts. Tasks involved in network management are data collection, data
       storage,  and  data retrieval. In the following example, the previously
       created target.rrd database is used. Data collection and  data  storage
       is  done  using  Shell scripts. Data retrieval and report generation is
       done using Perl scripts. These scripts are shown below:

       _S_h_e_l_l _s_c_r_i_p_t _(_c_o_l_l_e_c_t_s _d_a_t_a_, _u_p_d_a_t_e_s _d_a_t_a_b_a_s_e_)

        #!/bin/sh
        a=0
        while [ "$a" == 0 ]; do
        snmpwalk -c public 192.168.1.250 hrSWRunPerfMem > snmp_reply
            total_mem=`awk 'BEGIN {tot_mem=0}
                                  { if ($NF == "KBytes")
                                    {tot_mem=tot_mem+$(NF-1)}
                                  }
                            END {print tot_mem}' snmp_reply`
            # I can use N as a replacement for the current time
            rrdtool update target.rrd N:$total_mem
            # sleep until the next 300 seconds are full
            perl -e 'sleep 300 - time % 300'
        done # end of while loop

       _P_e_r_l _s_c_r_i_p_t _(_r_e_t_r_i_e_v_e_s _d_a_t_a _f_r_o_m  _d_a_t_a_b_a_s_e  _a_n_d  _g_e_n_e_r_a_t_e_s  _g_r_a_p_h_s  _a_n_d
       _s_t_a_t_i_s_t_i_c_s_)

        #!/usr/bin/perl -w
        # This script fetches data from target.rrd, creates a graph of memory
        # consumption on the target (Dual P3 Processor 1 GHz, 656 MB RAM)

        # call the RRD perl module
        use lib qw( /usr/local/rrdtool-1.0.41/lib/perl ../lib/perl );
        use RRDs;
        my $cur_time = time();                # set current time
        my $end_time = $cur_time - 86400;     # set end time to 24 hours ago
        my $start_time = $end_time - 2592000; # set start 30 days in the past

        # fetch average values from the RRD database between start and end time
        my ($start,$step,$ds_names,$data) =
            RRDs::fetch("target.rrd", "AVERAGE",
                        "-r", "600", "-s", "$start_time", "-e", "$end_time");
        # save fetched values in a 2-dimensional array
        my $rows = 0;
        my $columns = 0;
        my $time_variable = $start;
        foreach $line (@$data) {
          $vals[$rows][$columns] = $time_variable;
          $time_variable = $time_variable + $step;
          foreach $val (@$line) {
                  $vals[$rows][++$columns] = $val;}
          $rows++;
          $columns = 0;
        }
        my $tot_time = 0;
        my $count = 0;
        # save the values from the 2-dimensional into a 1-dimensional array
        for $i ( 0 .. $#vals ) {
            $tot_mem[$count] = $vals[$i][1];
            $count++;
        }
        my $tot_mem_sum = 0;
        # calculate the total of all values
        for $i ( 0 .. ($count-1) ) {
            $tot_mem_sum = $tot_mem_sum + $tot_mem[$i];
        }
        # calculate the average of the array
        my $tot_mem_ave = $tot_mem_sum/($count);
        # create the graph
        RRDs::graph ("/images/mem_$count.png",
                    "--title= Memory Usage",
                    "--vertical-label=Memory Consumption (MB)",
                    "--start=$start_time",
                    "--end=$end_time",
                    "--color=BACK#CCCCCC",
                    "--color=CANVAS#CCFFFF",
                    "--color=SHADEB#9999CC",
                    "--height=125",
                    "--upper-limit=656",
                    "--lower-limit=0",
                    "--rigid",
                    "--base=1024",
                    "DEF:tot_mem=target.rrd:mem:AVERAGE",
                    "CDEF:tot_mem_cor=tot_mem,0,671744,LIMIT,UN,0,tot_mem,IF,1024,/",
                    "CDEF:machine_mem=tot_mem,656,+,tot_mem,-",
                    "COMMENT:Memory Consumption between $start_time",
                    "COMMENT:    and $end_time                     ",
                    "HRULE:656#000000:Maximum Available Memory - 656 MB",
                    "AREA:machine_mem#CCFFFF:Memory Unused",
                    "AREA:tot_mem_cor#6699CC:Total memory consumed in MB");
        my $err=RRDs::error;
        if ($err) {print "problem generating the graph: $err\n";}
        # print the output
        print "Average memory consumption is ";
        printf "%5.2f",$tot_mem_ave/1024;
        print " MB. Graphical representation can be found at /images/mem_$count.png.";

AAUUTTHHOORR
       Ketan Patel <k2pattu@yahoo.com>

1.10.0                            2026-05-19                  _R_R_D_-_B_E_G_I_N_N_E_R_S(1)
