pandorafms/pandora_server/lib/PandoraFMS/PredictionServer.pm

package PandoraFMS::PredictionServer;
##########################################################################
# Pandora FMS Prediction Server.
# Pandora FMS. the Flexible Monitoring System. http://www.pandorafms.org
##########################################################################
# Copyright (c) 2005-2009 Artica Soluciones Tecnologicas S.L
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public License
# as published by the Free Software Foundation; version 2
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.
##########################################################################

use strict;
use warnings;

use threads;
use threads::shared;
use Thread::Semaphore;

use IO::Socket::INET;
use Net::Ping;
use POSIX qw(strftime);

use PandoraFMS::Tools;
use PandoraFMS::DB;
use PandoraFMS::Core;
use PandoraFMS::ProducerConsumerServer;

# Inherits from PandoraFMS::ProducerConsumerServer
our @ISA = qw(PandoraFMS::ProducerConsumerServer);

# Global variables
my @TaskQueue :shared;
my %PendingTasks :shared;
my $Sem :shared = Thread::Semaphore->new;
my $TaskSem :shared = Thread::Semaphore->new (0);

########################################################################################
# Prediction Server class constructor.
########################################################################################
sub new ($$;$) {
	my ($class, $config, $dbh) = @_;

	return undef unless $config->{'predictionserver'} == 1;

	# Call the constructor of the parent class
	my $self = $class->SUPER::new($config, 5, \&PandoraFMS::PredictionServer::data_producer, \&PandoraFMS::PredictionServer::data_consumer, $dbh);

    bless $self, $class;
    return $self;
}

###############################################################################
# Run.
###############################################################################
sub run ($) {
	my $self = shift;
	my $pa_config = $self->getConfig ();

	print_message ($pa_config, " [*] Starting Pandora FMS Prediction Server.", 1);
	$self->setNumThreads ($pa_config->{'prediction_threads'});
	$self->SUPER::run (\@TaskQueue, \%PendingTasks, $Sem, $TaskSem);
}

###############################################################################
# Data producer.
###############################################################################
sub data_producer ($) {
	my $self = shift;
	my ($pa_config, $dbh) = ($self->getConfig (), $self->getDBH ());

	my @tasks;
	my @rows;

	if ($pa_config->{'pandora_master'} != 1) {
		@rows = get_db_rows ($dbh, 'SELECT tagente_modulo.id_agente_modulo, tagente_modulo.flag
			FROM tagente, tagente_modulo, tagente_estado
			WHERE server_name = ?
			AND tagente_modulo.id_agente = tagente.id_agente
			AND tagente.disabled = 0
			AND tagente_modulo.prediction_module != 0
			AND tagente_modulo.disabled = 0
			AND tagente_estado.id_agente_modulo = tagente_modulo.id_agente_modulo
			AND (tagente_modulo.flag = 1
			  OR (tagente_estado.last_execution_try + tagente_estado.current_interval) < UNIX_TIMESTAMP())
			ORDER BY last_execution_try ASC ', $pa_config->{'servername'});
    } else {
		@rows = get_db_rows ($dbh, 'SELECT DISTINCT(tagente_modulo.id_agente_modulo), tagente_modulo.flag
                                FROM tagente, tagente_modulo, tagente_estado
								WHERE ((server_name = ?) OR (server_name = ANY(SELECT name FROM tserver WHERE status = 0)))
                                AND tagente_modulo.id_agente = tagente.id_agente
                                AND tagente.disabled = 0
                                AND tagente_modulo.disabled = 0
                                AND tagente_modulo.prediction_module != 0
                                AND tagente_estado.id_agente_modulo = tagente_modulo.id_agente_modulo
                                AND (tagente_modulo.flag = 1 OR (tagente_estado.last_execution_try + tagente_estado.current_interval) < UNIX_TIMESTAMP())
                                ORDER BY last_execution_try ASC', $pa_config->{'servername'});
	}

	foreach my $row (@rows) {
		
		# Reset forced execution flag
		if ($row->{'flag'} == 1) {
			db_do ($dbh, 'UPDATE tagente_modulo SET flag = 0 WHERE id_agente_modulo = ?', $row->{'id_agente_modulo'});
		}

		push (@tasks, $row->{'id_agente_modulo'});
	}

	return @tasks;
}

###############################################################################
# Data consumer.
###############################################################################
sub data_consumer ($$) {
	my ($self, $task) = @_;

	exec_prediction_module ($self->getConfig (), $task, $self->getServerID (), $self->getDBH ());
}

##########################################################################
# Execute prediction module.
##########################################################################
sub exec_prediction_module ($$$$) {
    my ($pa_config, $id_am, $server_id, $dbh) = @_;

    # Get a full hash for agent_module record reference ($agent_module)
	my $agent_module = get_db_single_row ($dbh, 'SELECT * FROM tagente_modulo WHERE id_agente_modulo = ?', $id_am);
	return unless defined $agent_module;

    # Get a full hash for target agent_module record reference ($target_module)
    my $target_module = get_db_single_row ($dbh, 'SELECT * FROM tagente_modulo WHERE id_agente_modulo = ?', $agent_module->{'prediction_module'});
	return unless defined $target_module;

    # Prediction mode explanation
    #
    # 0 is for target type of generic_proc. It compares latest data with current data. Needs to get
    # data on a "middle" interval, so if interval is 300, get data to compare with 150  before 
    # and 150 in the future. If current data is ABOVE or BELOW average +- typical_deviation 
    # this is a BAD value (0), if not is ok (1) and written in target module as is.
    # more interval configured for this module, more "margin" has to compare data.
    #
    # 1 is for target type of generic_data. It get's data in the future, using the interval given in
    # module. It gets average from current timestamp to INTERVAL in the future and gets average
    # value. Typical deviation is not used here. 

	# 0 proc, 1 data
    my $prediction_mode = ($agent_module->{'id_tipo_modulo'} == 2) ? 0 : 1;

    # Initialize another global sub variables.
	my $module_data = 0;    # 0 data for default

	# Get current timestamp
	my $utimestamp = time ();
	my $timestamp = strftime ("%Y-%m-%d %H:%M:%S", localtime($utimestamp));

    # Get different data from each week one month ago (4 values)
    # $agent_module->{'module_interval'} uses a margin of interval to get average data from the past
    my @week_data;
    my @week_utimestamp;

    for (my $i=0; $i<4; $i++){
        $week_utimestamp[$i] = $utimestamp - (84600*7*($i+1));
        # Adjust for proc prediction
        if ($prediction_mode == 0) {
            $week_utimestamp[$i] = $week_utimestamp[$i] - ($agent_module->{'module_interval'} / 2);
        }
    }

    # Let's calculate statistical average using past data
    # n = total of real data values
    my ($n, $average, $temp1) = (0, 0, 0);
    for (my $i=0; $i < 4; $i++){
        my ($first_data, $last_data, $average_interval);
        my $sum_data = 0;

        $temp1 = $week_utimestamp[$i] + $agent_module->{'module_interval'};
        # Get data for week $i in the past
        
        $average_interval = get_db_value ($dbh, 'SELECT AVG(datos) FROM tagente_datos WHERE id_agente_modulo = ? AND utimestamp > ? AND utimestamp < ?', $target_module->{'id_agente_modulo'}, $week_utimestamp[$i], $temp1);

        # Need to get data outside interval because no data.
        if (!(defined($average_interval)) || ($average_interval == 0)) {
            $last_data = get_db_value ($dbh, 'SELECT datos FROM tagente_datos WHERE id_agente_modulo = ? AND utimestamp > ? LIMIT 1', $target_module->{'id_agente_modulo'}, $week_utimestamp[$i]);
            next unless defined ($last_data);
            $first_data = get_db_value ($dbh, 'SELECT datos FROM tagente_datos WHERE id_agente_modulo = ? AND utimestamp < ? LIMIT 1', $target_module->{'id_agente_modulo'}, $temp1);
            next unless defined ($first_data);
            $sum_data++ if ($last_data != 0);
            $sum_data++ if ($first_data != 0);
            $week_data[$i] = (($last_data + $first_data) / $sum_data);
        } else {
            $week_data[$i] = $average_interval;
        }

        # It's possible that one of the week_data[i] values was not valid (NULL)
        # so recheck it and relay on n=0 for "no data" values set to 0 in result
        # Calculate total ammount of valida data for each data sample
        if ((is_numeric($week_data[$i])) && ($week_data[$i] > 0)){
            $n++;
            # Average SUM
            $average = $average + $week_data[$i];
        }
    }

    # Real average value
    $average = ($n > 0) ? ($average / $n) : 0;

    # (PROC) Compare with current data
    if ($prediction_mode == 0){
        # Calculate typical deviation
        my $typical_deviation = 0;
        for (my $i=0; $i< $n; $i++){
            if ((is_numeric($week_data[$i])) && ($week_data[$i] > 0)) {
                $typical_deviation = $typical_deviation + (($week_data[$i] - $average)**2);
            }
        }
        $typical_deviation = sqrt ($typical_deviation / ($n-1));

        my $current_value = get_db_value ($dbh, 'SELECT datos FROM tagente_estado WHERE id_agente_modulo = ?', $target_module->{'id_agente_modulo'});
        if ( ($current_value > ($average - $typical_deviation)) && ($current_value < ($average + $typical_deviation)) ){
            $module_data = 1; # OK !!
        } else {
            $module_data = 0; # Out of predictions
        }
    } else {
        # Prediction based on data
        $module_data = $average;
    }

	pandora_process_module ($pa_config, $module_data, undef, $agent_module, undef, $timestamp, $utimestamp, $server_id, $dbh);
	pandora_update_agent ($pa_config, $timestamp, $agent_module->{'id_agente'}, $pa_config->{'servername'}.'_Prediction', $pa_config->{'version'}, -1,  0,$dbh);
}

1;
__END__