=head1 NAME

rrd-beginners - RRDtool Beginners' Guide

=head1 SYNOPSIS

Helping new RRDtool users to understand the basics of RRDtool

=head1 DESCRIPTION

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.

=head2 What makes RRDtool so special?

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:

=over

=item *

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

=item *

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.

=item *

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.

=item *

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.

=back

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.

=head2 Understanding by an example

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 F<target.rrd>. 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 large (later)
then start time and MUST be in seconds since epoch.

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

B<DS> is a key word. C<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 B<(PDP)>. In our example
mentioned above, a new PDP is generated every 300 seconds.

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

B<DST> (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 I<change> in free diskspace 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 B<heartbeat>. 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 I<step>
number of PDPs. This RRA will hold I<rows> 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
theses 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.

=head2 Graphical Magic

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 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.

=head2 Wrapping RRDtool within Shell/Perl script

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:

=head3 Shell script (collects data, updates database)

 #!/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

=head3 Perl script (retrieves data from database and generates graphs and statistics)

 #!/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.";

=head1 AUTHOR

Ketan Patel E<lt>k2pattu@yahoo.comE<gt>

