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Optimize create_cumulative_bydate() function
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Until today, the function was executing simple SQL queries returning
atomic data, and PHP code had to loop over each row to compute the total
number of reported and resolved Issues.

This reports the effort to aggregate the data on the database server,
greatly simplifying the PHP code

It also fixes a bug where the last resolved issue was sometimes not
computed, resulting in an incorrect result set.

Fixes #34041,#34042
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@dregad
dregad committed Mar 19, 2024
1 parent a6c90df commit f109d15
Showing 1 changed file with 52 additions and 63 deletions.
115 changes: 52 additions & 63 deletions plugins/MantisGraph/core/graph_api.php
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Expand Up @@ -447,13 +447,15 @@ function create_category_summary( array $p_filter = null ) {
}

/**
* Create cumulative graph by date
* @param array $p_filter Filter array.
* @return array | null
* Generate cumulative graph data by date.
*
* @param array|null $p_filter Filter array.
*
* @return array|null
*/
function create_cumulative_bydate( array $p_filter = null ) {
$t_clo_val = config_get( 'bug_closed_status_threshold' );
$t_res_val = config_get( 'bug_resolved_status_threshold' );
$t_seconds_per_day = SECONDS_PER_DAY;

$t_project_id = helper_get_current_project();
$t_user_id = auth_get_current_user_id();
Expand All @@ -467,98 +469,85 @@ function create_cumulative_bydate( array $p_filter = null ) {

# Get all the submitted dates
$t_query = new DBQuery();
$t_sql = 'SELECT date_submitted FROM {bug} WHERE ' . $t_specific_where;
$t_sql = <<< SQL
SELECT
FLOOR(date_submitted / $t_seconds_per_day) date_index,
COUNT(*) num
FROM {bug}
WHERE $t_specific_where
SQL;
if( $p_filter ) {
$t_subquery = filter_cache_subquery( $p_filter );
$t_sql .= ' AND {bug}.id IN :filter';
$t_query->bind( 'filter', $t_subquery );
}
$t_sql .= ' ORDER BY date_submitted';
$t_sql .= ' GROUP BY date_index';
$t_query->sql( $t_sql );

$t_calc_metrics = array();
while( $t_row = $t_query->fetch() ) {
# rationalise the timestamp to a day to reduce the amount of data
$t_date = $t_row['date_submitted'];
$t_date = (int)( $t_date / SECONDS_PER_DAY );

if( isset( $t_calc_metrics[$t_date] ) ) {
$t_calc_metrics[$t_date][0]++;
} else {
$t_calc_metrics[$t_date] = array( 1, 0, 0, );
}
extract( $t_row, EXTR_PREFIX_ALL, 'v' );
$t_calc_metrics[$v_date_index] = [ $v_num, 0, 0 ];
}

# ## Get all the dates where a transition from not resolved to resolved may have happened
# also, get the last updated date for the bug as this may be all the information we have
# Get a count of resolved issues.
# Query explanation:
# - Use a sub-query against the history table, to retrieve the most recent
# date_modified for a transition to a status higher than resolved.
# - If there are no history records (i.e. with pre 0.18 data), date_modified
# will be NULL, so we fall back to the bug's last_updated date
# - Group by day to reduce the amount of data
$t_query = new DBQuery();
$t_sql = 'SELECT {bug}.id, last_updated, date_modified, new_value, old_value'
. ' FROM {bug} LEFT JOIN {bug_history} ON {bug}.id = {bug_history}.bug_id'
. ' WHERE ' . $t_specific_where
. ' AND {bug}.status >= :int_resolved'
. ' AND ( ( {bug_history}.new_value >= :str_resolved AND {bug_history}.old_value < :str_resolved AND {bug_history}.field_name = :field_name )'
. ' OR {bug_history}.id is NULL )';
$t_sql = <<< SQL
SELECT
FLOOR(COALESCE(max_date_modified, last_updated) / $t_seconds_per_day ) date_index,
COUNT(*) num
FROM {bug}
LEFT JOIN(
SELECT bug_id, MAX(date_modified) max_date_modified
FROM {bug_history}
WHERE field_name = :field_name AND new_value >= :str_resolved AND old_value < :str_resolved
GROUP BY bug_id
) hist ON hist.bug_id ={bug}.id
WHERE $t_specific_where
AND {bug}.status >= :int_resolved
SQL;
if( $p_filter ) {
$t_subquery = filter_cache_subquery( $p_filter );
$t_sql .= ' AND {bug}.id IN :filter';
$t_query->bind( 'filter', $t_subquery );
}
$t_sql .= ' ORDER BY {bug}.id, date_modified ASC';
$t_sql .= ' GROUP BY date_index';
$t_query->sql( $t_sql );
$t_query->bind( array(
'int_resolved' => (int)$t_res_val,
'str_resolved' => (string)$t_res_val,
'field_name' => 'status'
) );

$t_last_id = 0;
$t_last_date = 0;
'field_name' => 'status',
) );

while( $t_row = $t_query->fetch() ) {
$t_id = $t_row['id'];

# if h_last_updated is NULL, there were no appropriate history records
# (i.e. pre 0.18 data), use last_updated from bug table instead
if( null == $t_row['date_modified'] ) {
$t_date = $t_row['last_updated'];
extract( $t_row, EXTR_PREFIX_ALL, 'v' );
if( isset( $t_calc_metrics[$v_date_index] ) ) {
$t_calc_metrics[$v_date_index][1] = $v_num;
} else {
if( $t_res_val > $t_row['old_value'] ) {
$t_date = $t_row['date_modified'];
}
}
if( $t_id <> $t_last_id ) {
if( 0 <> $t_last_id ) {

# rationalise the timestamp to a day to reduce the amount of data
$t_date_index = (int)( $t_last_date / SECONDS_PER_DAY );

if( isset( $t_calc_metrics[$t_date_index] ) ) {
$t_calc_metrics[$t_date_index][1]++;
} else {
$t_calc_metrics[$t_date_index] = array(
0,
1,
0,
);
}
}
$t_last_id = $t_id;
$t_calc_metrics[$v_date_index] = [ 0, $v_num, 0 ];
}
$t_last_date = $t_date;
}

if ( $t_last_id == 0 ) {
if( !$t_calc_metrics ) {
return null;
}
ksort( $t_calc_metrics );

# Consolidate metrics data
$t_metrics = [];
$t_last_opened = 0;
$t_last_resolved = 0;
foreach( $t_calc_metrics as $i => $t_values ) {
$t_date = $i * SECONDS_PER_DAY;
$t_metrics[0][$t_date] = $t_last_opened = $t_last_opened + $t_calc_metrics[$i][0];
$t_metrics[1][$t_date] = $t_last_resolved = $t_last_resolved + $t_calc_metrics[$i][1];
$t_metrics[2][$t_date] = $t_metrics[0][$t_date] - $t_metrics[1][$t_date];
foreach( $t_calc_metrics as $t_date_index => $t_values ) {
$t_date = $t_date_index * SECONDS_PER_DAY;
$t_metrics[0][$t_date] = $t_last_opened = $t_last_opened + $t_values[0];
$t_metrics[1][$t_date] = $t_last_resolved = $t_last_resolved + $t_values[1];
$t_metrics[2][$t_date] = $t_last_opened - $t_last_resolved;
}
return $t_metrics;
}
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