Пример #1
0
 public function __construct(\alojaweb\inc\DBUtils $dbConnection)
 {
     $this->dbConnection = $dbConnection;
     /* In this array there are the filter names with its default options
      * that will be overwritten by the given custom defaults and options if given
      * Array with filter => filter specific settings
      *
      * Specific settings is an array with
      * types: inputText, inputNumber[{le,ge}], inputDate[{le,ge}], selectOne, selectMultiple, checkbox[Negated]
      * default: null (any), array(values)
      * table: associated DB table name
      * parseFunction: function to parse special filter, for filters that need a lot of customization
      *
      * Very custom filters such as advanced filters not in this array
      *
      */
     $this->filters = array('bench' => array('table' => 'execs', 'default' => array('terasort', 'wordcount'), 'type' => 'selectMultiple', 'label' => 'Benchmarks:'), 'datasize' => array('database' => 'aloja2', 'table' => 'execs', 'default' => null, 'type' => 'selectMultiple', 'label' => 'Datasize: ', 'beautifier' => function ($value) {
         return Utils::beautifyDatasize($value);
     }, 'parseFunction' => 'parseDatasize'), 'scale_factor' => array('table' => 'execs', 'default' => null, 'type' => 'selectMultiple', 'label' => 'Scale factor: '), 'bench_type' => array('table' => 'execs', 'default' => array('HiBench'), 'type' => 'selectOne', 'label' => 'Bench suite:'), 'net' => array('table' => 'execs', 'default' => null, 'type' => 'selectMultiple', 'label' => 'Network:', 'beautifier' => function ($value) {
         return Utils::getNetworkName($value);
     }), 'disk' => array('table' => 'execs', 'default' => null, 'type' => 'selectMultiple', 'label' => 'Disk:'), 'blk_size' => array('table' => 'execs', 'default' => null, 'type' => 'selectMultiple', 'label' => 'Block size (b):', 'beautifier' => function ($value) {
         return $value . ' MB';
     }), 'comp' => array('table' => 'execs', 'default' => null, 'type' => 'selectMultiple', 'label' => 'Compression (c):', 'beautifier' => function ($value) {
         return Utils::getCompressionName($value);
     }), 'id_cluster' => array('table' => 'execs', 'default' => null, 'type' => 'selectMultiple', 'label' => 'Clusters (CL):', 'beautifier' => function ($value) {
         return $this->filters['id_cluster']['namesClusters'][$value];
     }, 'generateChoices' => function () {
         $choices = $this->dbConnection->get_rows("select distinct id_cluster,CONCAT_WS('/',LPAD(id_cluster,2,0),c.vm_size,CONCAT(c.datanodes,'Dn')) as name  from aloja2.execs e join aloja2.clusters c using (id_cluster) WHERE 1 " . DBUtils::getFilterExecs(' ') . " ORDER BY c.name ASC");
         $returnChoices = array();
         foreach ($choices as $choice) {
             $returnChoices[] = $choice['id_cluster'];
             //Not nice, but saves multiple queries to DB in the beautifier
             $this->filters['id_cluster']['namesClusters'][$choice['id_cluster']] = $choice['name'];
         }
         return $returnChoices;
     }), 'maps' => array('table' => 'execs', 'default' => null, 'type' => 'selectMultiple', 'label' => 'Maps:', 'beautifier' => function ($value) {
         if ($value == 0) {
             return 'N/A';
         } else {
             return $value;
         }
     }), 'replication' => array('table' => 'execs', 'default' => null, 'type' => 'selectMultiple', 'label' => 'Replication (r):'), 'iosf' => array('table' => 'execs', 'default' => null, 'type' => 'selectMultiple', 'label' => 'I/O sort factor (I):'), 'iofilebuf' => array('table' => 'execs', 'default' => null, 'type' => 'selectMultiple', 'label' => 'I/O file buffer:', 'beautifier' => function ($value) {
         $suffix = ' KB';
         if ($value >= 1024) {
             $value /= 1024;
             $suffix = ' MB';
         }
         return $value . $suffix;
     }), 'provider' => array('table' => 'clusters', 'default' => null, 'type' => 'selectMultiple', 'label' => 'Provider:'), 'vm_OS' => array('table' => 'clusters', 'default' => null, 'type' => 'selectMultiple', 'label' => 'VM OS:'), 'datanodes' => array('table' => 'clusters', 'default' => null, 'type' => 'selectMultiple', 'label' => 'Cluster datanodes:'), 'vm_size' => array('table' => 'clusters', 'default' => null, 'type' => 'selectMultiple', 'label' => 'VM Size:'), 'vm_cores' => array('table' => 'clusters', 'default' => null, 'type' => 'selectMultiple', 'label' => 'VM cores:'), 'vm_RAM' => array('table' => 'clusters', 'default' => null, 'type' => 'selectMultiple', 'label' => 'VM RAM:', 'beautifier' => function ($value) {
         if ($value * 10 % 10 != 0) {
             return number_format($value, 1) . ' GB';
         } else {
             return number_format($value, 0) . ' GB';
         }
     }), 'type' => array('table' => 'clusters', 'default' => null, 'type' => 'selectMultiple', 'label' => 'Cluster type:'), 'hadoop_version' => array('table' => 'execs', 'default' => null, 'type' => 'selectMultiple', 'label' => 'Hadoop version:'), 'minexetime' => array('table' => 'execs', 'field' => 'exe_time', 'default' => Utils::in_dev() ? 1 : 50, 'type' => 'inputNumberge', 'label' => 'Min exec time:'), 'maxexetime' => array('table' => 'execs', 'field' => 'exe_time', 'default' => null, 'type' => 'inputNumberle', 'label' => 'Max exec time:'), 'datefrom' => array('table' => 'execs', 'field' => 'start_time', 'default' => null, 'type' => 'inputDatege', 'label' => 'Date from:'), 'dateto' => array('table' => 'execs', 'field' => 'end_time', 'default' => null, 'type' => 'inputDatele', 'label' => 'Date to:'), 'money' => array('table' => 'mixed', 'field' => '(clustersAlias.cost_hour/3600)*execsAlias.exe_time', 'default' => null, 'type' => 'inputNumberle', 'label' => 'Max cost (US$):'), 'valid' => array('table' => 'execs', 'field' => 'valid', 'type' => 'checkbox', 'default' => 1, 'label' => 'Only valid execs'), 'filter' => array('table' => 'execs', 'field' => 'filter', 'type' => 'checkbox', 'default' => 1, 'label' => 'Filter', 'parseFunction' => function () {
         $whereClause = "";
         if (isset($_GET['filter'])) {
             $values = 1;
         } else {
             if (!$this->formisSubmitted()) {
                 $values = $this->filters['filter']['default'];
             } else {
                 $values = 0;
             }
         }
         if ($values) {
             $whereClause = " AND execsAlias.filter = 0 ";
         }
         return array('currentChoice' => $values, 'whereClause' => $whereClause);
     }), 'prepares' => array('table' => 'execs', 'type' => 'checkbox', 'default' => Utils::in_dev() ? 1 : 0, 'label' => 'Include prepares', 'parseFunction' => function () {
         $whereClause = "";
         $values = 0;
         if (isset($_GET['prepares'])) {
             $values = 1;
         } else {
             $values = $this->filters['prepares']['default'];
             if (!$values) {
                 $whereClause = " AND execsAlias.bench NOT LIKE 'prep_%' ";
             }
         }
         return array('currentChoice' => $values, 'whereClause' => $whereClause);
     }), 'perf_details' => array('table' => 'execs', 'type' => 'checkbox', 'default' => 0, 'label' => 'Only execs with perf details'), 'prediction_model' => array('type' => 'selectOne', 'default' => null, 'label' => 'Reference Model: ', 'generateChoices' => function () {
         $query = "SELECT DISTINCT id_learner FROM aloja_ml.predictions";
         $retval = $this->dbConnection->get_rows($query);
         return array_column($retval, "id_learner");
     }, 'parseFunction' => function () {
         $choice = isset($_GET['prediction_model']) ? Utils::get_GET_stringArray('prediction_model') : array("");
         if ($choice = array("")) {
             $query = "SELECT DISTINCT id_learner FROM aloja_ml.predictions LIMIT 1";
             $choice = $this->dbConnection->get_rows($query)[0]['id_learner'];
         }
         return array('whereClause' => '', 'currentChoice' => $choice);
     }, 'filterGroup' => 'MLearning'), 'upred' => array('type' => 'checkbox', 'default' => 0, 'label' => 'Use predictions', 'parseFunction' => function () {
         $choice = !isset($_GET['upred']) ? 0 : 1;
         return array('whereClause' => '', 'currentChoice' => $choice);
     }, 'filterGroup' => 'MLearning'), 'uobsr' => array('type' => 'checkbox', 'default' => 1, 'label' => 'Use observations', 'parseFunction' => function () {
         $choice = !isset($_GET['uobsr']) && $this->formIssubmitted() ? 0 : 1;
         return array('whereClause' => '', 'currentChoice' => $choice);
     }, 'filterGroup' => 'MLearning'), 'warning' => array('field' => 'outlier', 'table' => 'ml_predictions', 'type' => 'checkbox', 'default' => 0, 'label' => 'Show warnings', 'parseFunction' => function () {
         $learner = $this->filters['prediction_model']['currentChoice'];
         $whereClause = "";
         $values = isset($_GET['warning']) ? 1 : 0;
         if ($values && !empty($learner)) {
             $whereClause = " AND (ml_predictionsAlias.outlier <= {$values} OR ml_predictionsAlias.outlier IS NULL) " . "AND (ml_predictionsAlias.id_learner = '{$learner[0]}' OR ml_predictionsAlias.id_learner IS NULL)";
         }
         return array('currentChoice' => $values, 'whereClause' => $whereClause);
     }, 'filterGroup' => 'MLearning'), 'outlier' => array('table' => 'ml_predictions', 'type' => 'checkbox', 'default' => 0, 'label' => 'Show outliers', 'parseFunction' => function () {
         $learner = $this->filters['prediction_model']['currentChoice'];
         $whereClause = "";
         $values = isset($_GET['outlier']) ? 2 : 0;
         if ($values && !empty($learner)) {
             $whereClause = " AND (ml_predictionsAlias.outlier <= 2 OR ml_predictionsAlias.outlier IS NULL) " . "AND (ml_predictionsAlias.id_learner = '{$learner}' OR ml_predictionsAlias.id_learner IS NULL)";
             $values = 1;
         } else {
             if (!empty($learner) && !isset($_GET['warning'])) {
                 $whereClause = " AND (ml_predictionsAlias.outlier = 0 OR ml_predictionsAlias.outlier IS NULL) " . "AND (ml_predictionsAlias.id_learner = '{$learner}' OR ml_predictionsAlias.id_learner IS NULL)";
             }
         }
         return array('currentChoice' => $values, 'whereClause' => $whereClause);
     }, 'filterGroup' => 'MLearning'));
     $this->aliasesTables = array('execs' => 'e', 'clusters' => 'c', 'ml_predictions' => 'p');
     //To render groups on template. Rows are of 2 columns each. emptySpace puts an empty element on the rendered row
     $this->filterGroups = array('basic' => array('label' => 'Basic filters', 'filters' => array('money', 'bench', 'bench_type', 'datasize', 'scale_factor', 'id_cluster', 'net', 'disk'), 'tabOpenDefault' => true), 'hardware' => array('label' => 'Hardware', 'filters' => array('datanodes', 'vm_size', 'vm_cores', 'vm_RAM', 'type', 'provider', 'vm_OS'), 'tabOpenDefault' => false), 'hadoop' => array('label' => 'Hadoop', 'filters' => array('maps', 'comp', 'replication', 'blk_size', 'iosf', 'iofilebuf', 'hadoop_version'), 'tabOpenDefault' => false), 'advanced' => array('label' => 'Advanced filters', 'filters' => array('valid', 'filter', 'prepares', 'perf_details', 'datefrom', 'dateto', 'minexetime', 'maxexetime'), 'tabOpenDefault' => false), 'MLearning' => array('label' => 'Machine Learning', 'filters' => array('prediction_model', 'upred', 'uobsr', 'warning', 'outlier'), 'tabOpenDefault' => true));
 }
Пример #2
0
 public function mlparamEvaluationAction()
 {
     $rows = $categories = $series = '';
     $must_wait = 'NO';
     try {
         $dbml = new \PDO($this->container->get('config')['db_conn_chain_ml'], $this->container->get('config')['mysql_user'], $this->container->get('config')['mysql_pwd']);
         $dbml->setAttribute(\PDO::ATTR_ERRMODE, \PDO::ERRMODE_EXCEPTION);
         $dbml->setAttribute(\PDO::ATTR_EMULATE_PREPARES, false);
         $db = $this->container->getDBUtils();
         $where_configs = '';
         $preset = null;
         if (count($_GET) <= 1 || count($_GET) == 2 && array_key_exists('parameval', $_GET) || count($_GET) == 2 && array_key_exists('current_model', $_GET)) {
             $preset = Utils::setDefaultPreset($db, 'mlparameval');
         }
         $selPreset = isset($_GET['presets']) ? $_GET['presets'] : "none";
         $params = array();
         $param_names = array('benchs', 'nets', 'disks', 'mapss', 'iosfs', 'replications', 'iofilebufs', 'comps', 'blk_sizes', 'id_clusters', 'datanodess', 'bench_types', 'vm_sizes', 'vm_coress', 'vm_RAMs', 'types');
         // Order is important
         foreach ($param_names as $p) {
             $params[$p] = Utils::read_params($p, $where_configs, FALSE);
             sort($params[$p]);
         }
         $money = Utils::read_params('money', $where_configs);
         $paramEval = isset($_GET['parameval']) && $_GET['parameval'] != '' ? $_GET['parameval'] : 'maps';
         $minExecs = isset($_GET['minexecs']) ? $_GET['minexecs'] : -1;
         $minExecsFilter = "";
         // FIXME PATCH FOR PARAM LIBRARIES WITHOUT LEGACY
         $where_configs = str_replace("AND .", "AND ", $where_configs);
         $where_configs = str_replace("`id_cluster`", "e.`id_cluster`", $where_configs);
         if ($minExecs > 0) {
             $minExecsFilter = "HAVING COUNT(*) > {$minExecs}";
         }
         $filter_execs = DBUtils::getFilterExecs();
         $options = Utils::getFilterOptions($db);
         $paramOptions = array();
         foreach ($options[$paramEval] as $option) {
             if ($paramEval == 'id_cluster') {
                 $paramOptions[] = $option['name'];
             } else {
                 if ($paramEval == 'comp') {
                     $paramOptions[] = Utils::getCompressionName($option[$paramEval]);
                 } else {
                     if ($paramEval == 'net') {
                         $paramOptions[] = Utils::getNetworkName($option[$paramEval]);
                     } else {
                         if ($paramEval == 'disk') {
                             $paramOptions[] = Utils::getDisksName($option[$paramEval]);
                         } else {
                             $paramOptions[] = $option[$paramEval];
                         }
                     }
                 }
             }
         }
         $benchOptions = $db->get_rows("SELECT DISTINCT bench FROM execs e LEFT JOIN clusters c ON e.id_cluster = c.id_cluster WHERE 1 {$filter_execs} {$where_configs} GROUP BY {$paramEval}, bench order by {$paramEval}");
         // get the result rows
         $query = "SELECT count(*) as count, {$paramEval}, e.id_exec, exec as conf, bench, " . "exe_time, avg(exe_time) avg_exe_time, min(exe_time) min_exe_time " . "from execs e LEFT JOIN clusters c ON e.id_cluster = c.id_cluster WHERE 1 {$filter_execs} {$where_configs}" . "GROUP BY {$paramEval}, bench {$minExecsFilter} order by bench,{$paramEval}";
         $rows = $db->get_rows($query);
         if (!$rows) {
             throw new \Exception("No results for query!");
         }
         $arrayBenchs = array();
         foreach ($paramOptions as $param) {
             foreach ($benchOptions as $bench) {
                 $arrayBenchs[$bench['bench']][$param] = null;
                 $arrayBenchs[$bench['bench']][$param]['y'] = 0;
                 $arrayBenchs[$bench['bench']][$param]['count'] = 0;
             }
         }
         $series = array();
         $bench = '';
         foreach ($rows as $row) {
             if ($paramEval == 'comp') {
                 $row[$paramEval] = Utils::getCompressionName($row['comp']);
             } else {
                 if ($paramEval == 'id_cluster') {
                     $row[$paramEval] = Utils::getClusterName($row[$paramEval], $db);
                 } else {
                     if ($paramEval == 'net') {
                         $row[$paramEval] = Utils::getNetworkName($row['net']);
                     } else {
                         if ($paramEval == 'disk') {
                             $row[$paramEval] = Utils::getDisksName($row['disk']);
                         } else {
                             if ($paramEval == 'iofilebuf') {
                                 $row[$paramEval] /= 1024;
                             }
                         }
                     }
                 }
             }
             $arrayBenchs[$row['bench']][$row[$paramEval]]['y'] = round((int) $row['avg_exe_time'], 2);
             $arrayBenchs[$row['bench']][$row[$paramEval]]['count'] = (int) $row['count'];
         }
         // ----------------------------------------------------
         // Add predictions to the series
         // ----------------------------------------------------
         $jsonData = $jsonHeader = "[]";
         $instance = "";
         $arrayBenchs_pred = array();
         // FIXME PATCH FOR PARAM LIBRARIES WITHOUT LEGACY
         $where_configs = str_replace("AND .", "AND ", $where_configs);
         // compose instance
         $instance = MLUtils::generateSimpleInstance($param_names, $params, true, $db);
         $model_info = MLUtils::generateModelInfo($param_names, $params, true, $db);
         $instances = MLUtils::generateInstances($param_names, $params, true, $db);
         // model for filling
         $possible_models = $possible_models_id = array();
         MLUtils::findMatchingModels($model_info, $possible_models, $possible_models_id, $dbml);
         $current_model = "";
         if (array_key_exists('current_model', $_GET) && in_array($_GET['current_model'], $possible_models_id)) {
             $current_model = $_GET['current_model'];
         }
         if (!empty($possible_models_id)) {
             if ($current_model == "") {
                 $query = "SELECT AVG(ABS(exe_time - pred_time)) AS MAE, AVG(ABS(exe_time - pred_time)/exe_time) AS RAE, p.id_learner FROM predictions p, learners l WHERE l.id_learner = p.id_learner AND p.id_learner IN ('" . implode("','", $possible_models_id) . "') AND predict_code > 0 ORDER BY MAE LIMIT 1";
                 $result = $dbml->query($query);
                 $row = $result->fetch();
                 $current_model = $row['id_learner'];
             }
             $config = $instance . '-' . $current_model . "-parameval";
             $query_cache = "SELECT count(*) as total FROM trees WHERE id_learner = '" . $current_model . "' AND model = '" . $model_info . "'";
             $is_cached_mysql = $dbml->query($query_cache);
             $tmp_result = $is_cached_mysql->fetch();
             $is_cached = $tmp_result['total'] > 0;
             $ret_data = null;
             if (!$is_cached) {
                 // Call to MLFindAttributes, to fetch data
                 $_GET['pass'] = 2;
                 $_GET['unseen'] = 1;
                 $_GET['current_model'] = $current_model;
                 $mlfa1 = new MLFindAttributesController();
                 $mlfa1->container = $this->container;
                 $ret_data = $mlfa1->mlfindattributesAction();
                 if ($ret_data == 1) {
                     $must_wait = "YES";
                     $jsonData = $jsonHeader = '[]';
                 } else {
                     $is_cached_mysql = $dbml->query($query_cache);
                     $tmp_result = $is_cached_mysql->fetch();
                     $is_cached = $tmp_result['total'] > 0;
                 }
             }
             if ($is_cached) {
                 $must_wait = 'NO';
                 $query = "SELECT count(*) as count, {$paramEval}, bench, exe_time, avg(pred_time) avg_pred_time, min(pred_time) min_pred_time " . "FROM predictions e WHERE e.id_learner = '" . $current_model . "' {$filter_execs} {$where_configs}" . "GROUP BY {$paramEval}, bench {$minExecsFilter} order by bench, {$paramEval}";
                 $result = $dbml->query($query);
                 // Initialize array
                 foreach ($paramOptions as $param) {
                     foreach ($benchOptions as $bench) {
                         $arrayBenchs_pred[$bench['bench'] . '_pred'][$param] = null;
                         $arrayBenchs_pred[$bench['bench'] . '_pred'][$param]['y'] = 0;
                         $arrayBenchs_pred[$bench['bench'] . '_pred'][$param]['count'] = 0;
                     }
                 }
                 foreach ($result as $row) {
                     $bench_n = $row['bench'] . '_pred';
                     $class = $row[$paramEval];
                     if ($paramEval == 'comp') {
                         $value = Utils::getCompressionName($class);
                     } else {
                         if ($paramEval == 'id_cluster') {
                             $value = Utils::getClusterName($class, $db);
                         } else {
                             if ($paramEval == 'net') {
                                 $value = Utils::getNetworkName($class);
                             } else {
                                 if ($paramEval == 'disk') {
                                     $value = Utils::getDisksName($class);
                                 } else {
                                     if ($paramEval == 'iofilebuf') {
                                         $value = $class / 1024;
                                     } else {
                                         $value = $class;
                                     }
                                 }
                             }
                         }
                     }
                     if (!in_array($value, $paramOptions)) {
                         $paramOptions[] = $value;
                         foreach ($benchOptions as $bench) {
                             $arrayBenchs_pred[$bench['bench'] . '_pred'][$value] = null;
                             $arrayBenchs_pred[$bench['bench'] . '_pred'][$value]['y'] = 0;
                             $arrayBenchs_pred[$bench['bench'] . '_pred'][$value]['count'] = 0;
                             $arrayBenchs[$bench['bench']][$value] = null;
                             $arrayBenchs[$bench['bench']][$value]['y'] = 0;
                             $arrayBenchs[$bench['bench']][$value]['count'] = 0;
                         }
                     }
                     $arrayBenchs_pred[$bench_n][$value]['y'] = (int) $row['avg_pred_time'];
                     $arrayBenchs_pred[$bench_n][$value]['count'] = (int) $row['count'];
                 }
             }
         }
         // ----------------------------------------------------
         // END - Add predictions to the series
         // ----------------------------------------------------
         asort($paramOptions);
         foreach ($arrayBenchs as $key => $arrayBench) {
             $caregories = '';
             $data_a = null;
             $data_p = null;
             foreach ($paramOptions as $param) {
                 if ($arrayBenchs[$key][$param]['count'] > 0 && empty($arrayBenchs_pred) || !empty($arrayBenchs_pred) && ($arrayBenchs_pred[$key . '_pred'][$param]['count'] > 0 || $arrayBenchs[$key][$param]['count'] > 0)) {
                     $data_a[] = $arrayBenchs[$key][$param];
                     if (!empty($arrayBenchs_pred)) {
                         $data_p[] = $arrayBenchs_pred[$key . '_pred'][$param];
                     }
                     $categories = $categories . "'{$param} " . Utils::getParamevalUnit($paramEval) . "',";
                     // FIXME - Redundant n times performed... don't care now
                 }
             }
             $series[] = array('name' => $key, 'data' => $data_a);
             if (!empty($arrayBenchs_pred)) {
                 $series[] = array('name' => $key . '_pred', 'data' => $data_p);
             }
         }
         $series = json_encode($series);
         if (!empty($arrayBenchs_pred)) {
             $colors = "['#7cb5ec','#9cd5fc','#434348','#636368','#90ed7d','#b0fd9d','#f7a35c','#f7c37c','#8085e9','#a0a5f9','#f15c80','#f17ca0','#e4d354','#f4f374','#8085e8','#a0a5f8','#8d4653','#ad6673','#91e8e1','#b1f8f1']";
         } else {
             $colors = "['#7cb5ec','#434348','#90ed7d','#f7a35c','#8085e9','#f15c80','#e4d354','#8085e8','#8d4653','#91e8e1']";
         }
     } catch (\Exception $e) {
         $this->container->getTwig()->addGlobal('message', $e->getMessage() . "\n");
         $series = $jsonHeader = $colors = '[]';
         $instance = $current_model = '';
         $possible_models = $possible_models_id = array();
         $must_wait = 'NO';
     }
     echo $this->container->getTwig()->render('mltemplate/mlconfigperf.html.twig', array('selected' => 'mlparameval', 'title' => 'Improvement of Hadoop Execution by SW and HW Configurations', 'categories' => $categories, 'series' => $series, 'benchs' => $params['benchs'], 'nets' => $params['nets'], 'disks' => $params['disks'], 'blk_sizes' => $params['blk_sizes'], 'comps' => $params['comps'], 'id_clusters' => $params['id_clusters'], 'mapss' => $params['mapss'], 'replications' => $params['replications'], 'iosfs' => $params['iosfs'], 'iofilebufs' => $params['iofilebufs'], 'datanodess' => $params['datanodess'], 'bench_types' => $params['bench_types'], 'vm_sizes' => $params['vm_sizes'], 'vm_coress' => $params['vm_coress'], 'vm_RAMs' => $params['vm_RAMs'], 'types' => $params['types'], 'money' => $money, 'paramEval' => $paramEval, 'instance' => $instance, 'models' => '<li>' . implode('</li><li>', $possible_models) . '</li>', 'models_id' => $possible_models_id, 'current_model' => $current_model, 'gammacolors' => $colors, 'must_wait' => $must_wait, 'preset' => $preset, 'selPreset' => $selPreset, 'options' => Utils::getFilterOptions($db)));
 }
Пример #3
0
 public function paramEvaluationAction()
 {
     $db = $this->container->getDBUtils();
     $this->buildFilters(array('minexecs' => array('default' => null, 'type' => 'inputNumber', 'label' => 'Minimum executions:', 'parseFunction' => function () {
         return 0;
     }, 'filterGroup' => 'basic')));
     $whereClause = $this->filters->getWhereClause();
     $model_html = '';
     $model_info = $db->get_rows("SELECT id_learner, model, algorithm, dataslice FROM aloja_ml.learners");
     foreach ($model_info as $row) {
         $model_html = $model_html . "<li><b>" . $row['id_learner'] . "</b> => " . $row['algorithm'] . " : " . $row['model'] . " : " . $row['dataslice'] . "</li>";
     }
     $categories = '';
     $series = '';
     try {
         $paramEval = isset($_GET['parameval']) && Utils::get_GET_string('parameval') != '' ? Utils::get_GET_string('parameval') : 'maps';
         $minExecs = isset($_GET['minexecs']) ? Utils::get_GET_int('minexecs') : -1;
         $this->filters->changeCurrentChoice('minexecs', $minExecs == -1 ? null : $minExecs);
         $shortAliasParamEval = array('maps' => 'e', 'comp' => 'e', 'id_cluster' => 'c', 'net' => 'e', 'disk' => 'e', 'replication' => 'e', 'iofilebuf' => 'e', 'blk_size' => 'e', 'iosf' => 'e', 'vm_size' => 'c', 'vm_cores' => 'c', 'vm_ram' => 'c', 'datanodes' => 'c', 'hadoop_version' => 'e', 'type' => 'c');
         $minExecsFilter = "";
         if ($minExecs > 0) {
             $minExecsFilter = "HAVING COUNT(*) > {$minExecs}";
         }
         $filter_execs = DBUtils::getFilterExecs();
         $options = $this->filters->getFiltersArray()[$paramEval]['choices'];
         $benchOptions = "SELECT DISTINCT e.bench FROM aloja2.execs e JOIN aloja2.clusters c USING (id_cluster) LEFT JOIN aloja_ml.predictions p USING (id_exec) WHERE 1 {$filter_execs} {$whereClause} GROUP BY {$shortAliasParamEval[$paramEval]}.{$paramEval}, e.bench order by {$shortAliasParamEval[$paramEval]}.{$paramEval}";
         $params = $this->filters->getFiltersSelectedChoices(array('prediction_model', 'upred', 'uobsr'));
         $whereClauseML = str_replace("exe_time", "pred_time", $whereClause);
         $whereClauseML = str_replace("start_time", "creation_time", $whereClauseML);
         $query = "SELECT COUNT(*) AS count, {$shortAliasParamEval[$paramEval]}.{$paramEval}, e.bench, avg(e.exe_time) avg_exe_time, min(e.exe_time) min_exe_time\n\t\t\t\t\t  FROM aloja2.execs AS e JOIN aloja2.clusters AS c USING (id_cluster)\n\t\t\t\t\t  LEFT JOIN aloja_ml.predictions AS p USING (id_exec)\n\t\t\t\t\t  WHERE 1 {$filter_execs} {$whereClause}\n\t\t\t\t\t  GROUP BY {$shortAliasParamEval[$paramEval]}.{$paramEval}, e.bench {$minExecsFilter} ORDER BY e.bench, {$shortAliasParamEval[$paramEval]}.{$paramEval}";
         $queryPredictions = "\n\t\t\t\t\tSELECT COUNT(*) AS count, {$shortAliasParamEval[$paramEval]}.{$paramEval}, CONCAT('pred_',e.bench) as bench,\n\t\t\t\t\t\tavg(e.pred_time) as avg_exe_time, min(e.pred_time) as min_exe_time\n\t\t\t\t\t\tFROM aloja_ml.predictions AS e\n\t\t\t\t\t\tJOIN clusters c USING (id_cluster)\n\t\t\t\t\t\tWHERE 1 {$filter_execs} " . str_replace("p.", "e.", $whereClauseML) . " AND e.id_learner = '" . $params['prediction_model'] . "'\n\t\t\t\t\t\tGROUP BY {$shortAliasParamEval[$paramEval]}.{$paramEval}, e.bench {$minExecsFilter} ORDER BY e.bench, {$shortAliasParamEval[$paramEval]}.{$paramEval}";
         // get the result rows
         if ($params['uobsr'] == 1 && $params['upred'] == 1) {
             $query = "({$query}) UNION ({$queryPredictions})";
             $benchOptions = "SELECT DISTINCT e.bench FROM aloja2.execs e JOIN aloja2.clusters c USING (id_cluster) LEFT JOIN aloja_ml.predictions p USING (id_exec) WHERE 1 {$filter_execs} {$whereClause} GROUP BY {$shortAliasParamEval[$paramEval]}.{$paramEval}, e.bench\n\t\t\t\t\t\t\t\t UNION\n\t\t\t\t\t\t\t\t (SELECT DISTINCT CONCAT('pred_', e.bench) as bench FROM aloja_ml.predictions AS e\n\t\t\t\t\t\t\t\t  JOIN clusters c USING (id_cluster)\n\t\t\t\t\t\t\t\t WHERE 1 {$filter_execs} " . str_replace("p.", "e.", $whereClauseML) . " AND e.id_learner = '" . $params['prediction_model'] . "'\n\t\t\t\t\t\t\t\t GROUP BY {$shortAliasParamEval[$paramEval]}.{$paramEval}, e.bench {$minExecsFilter})\n\t\t\t\t\t\t\t\t ORDER BY bench";
             $optionsPredictions = "SELECT DISTINCT {$shortAliasParamEval[$paramEval]}.{$paramEval} FROM aloja_ml.predictions AS e JOIN clusters c USING (id_cluster) WHERE 1 {$filter_execs} " . str_replace("p.", "e.", $whereClauseML) . " AND e.id_learner = '" . $params['prediction_model'] . "' ORDER BY {$shortAliasParamEval[$paramEval]}.{$paramEval}";
             $optionsPredictions = $db->get_rows($optionsPredictions);
             foreach ($optionsPredictions as $predOption) {
                 $options[] = $predOption[$paramEval];
             }
         } else {
             if ($params['uobsr'] == 0 && $params['upred'] == 1) {
                 $query = $queryPredictions;
                 $benchOptions = "SELECT DISTINCT CONCAT('pred_', e.bench) as bench FROM aloja_ml.predictions AS e\n \t\t\t\t\t\t\t\t JOIN clusters c USING (id_cluster)\n\t\t\t\t\t\t\t\t WHERE 1 {$filter_execs} " . str_replace("p.", "e.", $whereClauseML) . " AND e.id_learner = '" . $params['prediction_model'] . "'\n\t\t\t\t\t\t\t\t GROUP BY {$shortAliasParamEval[$paramEval]}.{$paramEval}, e.bench {$minExecsFilter} ORDER BY e.bench, {$shortAliasParamEval[$paramEval]}.{$paramEval}";
                 $options = array();
                 $optionsPredictions = "SELECT DISTINCT {$shortAliasParamEval[$paramEval]}.{$paramEval} FROM aloja_ml.predictions AS e JOIN clusters c USING (id_cluster) WHERE 1 {$filter_execs} " . str_replace("p.", "e.", $whereClauseML) . " AND e.id_learner = '" . $params['prediction_model'] . "' ORDER BY {$shortAliasParamEval[$paramEval]}.{$paramEval}";
                 $optionsPredictions = $db->get_rows($optionsPredictions);
                 foreach ($optionsPredictions as $predOption) {
                     $options[] = $predOption[$paramEval];
                 }
             } else {
                 if ($params['uobsr'] == 0 && $params['upred'] == 0) {
                     $this->container->getTwig()->addGlobal('message', "Warning: No data selected (Predictions|Observations) from the ML Filters. Adding the Observed executions to the figure by default.\n");
                 }
             }
         }
         $rows = $db->get_rows($query);
         $benchOptions = $db->get_rows($benchOptions);
         if (!$rows) {
             throw new \Exception("No results for query!");
         }
         $paramOptions = array();
         foreach ($options as $option) {
             if ($paramEval == 'id_cluster') {
                 $paramOptions[] = Utils::getClusterName($option, $db);
             } else {
                 if ($paramEval == 'comp') {
                     $paramOptions[] = Utils::getCompressionName($option);
                 } else {
                     if ($paramEval == 'net') {
                         $paramOptions[] = Utils::getNetworkName($option);
                     } else {
                         if ($paramEval == 'disk') {
                             $paramOptions[] = Utils::getDisksName($option);
                         } else {
                             if ($paramEval == 'vm_ram') {
                                 $paramOptions[] = Utils::getBeautyRam($option);
                             } else {
                                 $paramOptions[] = $option;
                             }
                         }
                     }
                 }
             }
         }
         $categories = '';
         $arrayBenchs = array();
         foreach ($paramOptions as $param) {
             $categories .= "'{$param}" . Utils::getParamevalUnit($paramEval) . "',";
             foreach ($benchOptions as $bench) {
                 $arrayBenchs[$bench['bench']][$param] = null;
             }
         }
         $series = array();
         foreach ($rows as $row) {
             if ($paramEval == 'comp') {
                 $row[$paramEval] = Utils::getCompressionName($row['comp']);
             } else {
                 if ($paramEval == 'id_cluster') {
                     $row[$paramEval] = Utils::getClusterName($row[$paramEval], $db);
                 } else {
                     if ($paramEval == 'net') {
                         $row[$paramEval] = Utils::getNetworkName($row['net']);
                     } else {
                         if ($paramEval == 'disk') {
                             $row[$paramEval] = Utils::getDisksName($row['disk']);
                         } else {
                             if ($paramEval == 'vm_ram') {
                                 $row[$paramEval] = Utils::getBeautyRam($row['vm_ram']);
                             }
                         }
                     }
                 }
             }
             $arrayBenchs[strtolower($row['bench'])][$row[$paramEval]]['y'] = round((int) $row['avg_exe_time'], 2);
             $arrayBenchs[strtolower($row['bench'])][$row[$paramEval]]['count'] = (int) $row['count'];
         }
         foreach ($arrayBenchs as $key => $arrayBench) {
             $series[] = array('name' => $key, 'data' => array_values($arrayBench));
         }
         $series = json_encode($series);
     } catch (\Exception $e) {
         $this->container->getTwig()->addGlobal('message', $e->getMessage() . "\n");
     }
     return $this->render('configEvaluationViews/parameval.html.twig', array('title' => 'Improvement of Hadoop Execution by SW and HW Configurations', 'minexecs' => $minExecs, 'categories' => $categories, 'series' => $series, 'paramEval' => $paramEval, 'models' => $model_html));
 }
Пример #4
0
 public function mlparamEvaluationAction()
 {
     $rows = $categories = $series = $instance = $model_info = $config = $current_model = $slice_info = '';
     $arrayBenchs_pred = $possible_models = $possible_models_id = $other_models = array();
     $jsonData = $jsonHeader = "[]";
     $must_wait = 'NO';
     try {
         $dbml = new \PDO($this->container->get('config')['db_conn_chain'], $this->container->get('config')['mysql_user'], $this->container->get('config')['mysql_pwd']);
         $dbml->setAttribute(\PDO::ATTR_ERRMODE, \PDO::ERRMODE_EXCEPTION);
         $dbml->setAttribute(\PDO::ATTR_EMULATE_PREPARES, false);
         $db = $this->container->getDBUtils();
         if (array_key_exists('parameval', $_GET)) {
             $paramEval = isset($_GET['parameval']) && Utils::get_GET_string('parameval') != '' ? Utils::get_GET_string('parameval') : 'maps';
             unset($_GET["parameval"]);
         }
         $this->buildFilters(array('current_model' => array('type' => 'selectOne', 'default' => null, 'label' => 'Model to use: ', 'generateChoices' => function () {
             return array();
         }, 'parseFunction' => function () {
             $choice = isset($_GET['current_model']) ? $_GET['current_model'] : array("");
             return array('whereClause' => '', 'currentChoice' => $choice);
         }, 'filterGroup' => 'MLearning'), 'minExecs' => array('default' => 0, 'type' => 'inputNumber', 'label' => 'Minimum executions:', 'parseFunction' => function () {
             return 0;
         }, 'filterGroup' => 'basic'), 'minexetime' => array('default' => 0), 'valid' => array('default' => 0), 'filter' => array('default' => 0), 'prepares' => array('default' => 0)));
         $this->buildFilterGroups(array('MLearning' => array('label' => 'Machine Learning', 'tabOpenDefault' => true, 'filters' => array('current_model'))));
         $where_configs = $this->filters->getWhereClause();
         $params = array();
         $param_names = array('bench', 'net', 'disk', 'maps', 'iosf', 'replication', 'iofilebuf', 'comp', 'blk_size', 'id_cluster', 'datanodes', 'vm_OS', 'vm_cores', 'vm_RAM', 'provider', 'vm_size', 'type', 'bench_type', 'hadoop_version');
         // Order is important
         $params = $this->filters->getFiltersSelectedChoices($param_names);
         foreach ($param_names as $p) {
             if (!is_null($params[$p]) && is_array($params[$p])) {
                 sort($params[$p]);
             }
         }
         $params_additional = array();
         $param_names_additional = array('datefrom', 'dateto', 'minexetime', 'maxexetime', 'valid', 'filter');
         // Order is important
         $params_additional = $this->filters->getFiltersSelectedChoices($param_names_additional);
         $param_variables = $this->filters->getFiltersSelectedChoices(array('current_model', 'minExecs'));
         $param_current_model = $param_variables['current_model'];
         $minExecs = $param_variables['minExecs'];
         $where_configs = str_replace("AND .", "AND ", $where_configs);
         $where_configs = str_replace("id_cluster", "e.id_cluster", $where_configs);
         $minExecsFilter = "";
         if ($minExecs > 0) {
             $minExecsFilter = "HAVING COUNT(*) > {$minExecs}";
         }
         $filter_execs = DBUtils::getFilterExecs();
         $options = $this->filters->getFilterChoices();
         $paramOptions = array();
         foreach ($options[$paramEval] as $option) {
             if ($paramEval == 'comp') {
                 $paramOptions[] = Utils::getCompressionName($option);
             } else {
                 if ($paramEval == 'net') {
                     $paramOptions[] = Utils::getNetworkName($option);
                 } else {
                     if ($paramEval == 'disk') {
                         $paramOptions[] = Utils::getDisksName($option);
                     } else {
                         $paramOptions[] = $option;
                     }
                 }
             }
         }
         $param_eval_query = $paramEval == 'id_cluster' ? 'e.id_cluster' : $paramEval;
         $benchOptions = $db->get_rows("SELECT DISTINCT bench FROM aloja2.execs e LEFT JOIN aloja2.clusters c ON e.id_cluster = c.id_cluster WHERE 1 {$filter_execs} {$where_configs} GROUP BY {$param_eval_query}, bench order by {$param_eval_query}");
         // get the result rows
         $query = "SELECT count(*) as count, {$param_eval_query}, e.id_exec, exec as conf, bench, " . "exe_time, avg(exe_time) avg_exe_time, min(exe_time) min_exe_time " . "from aloja2.execs e LEFT JOIN aloja2.clusters c ON e.id_cluster = c.id_cluster WHERE 1 {$filter_execs} {$where_configs}" . "GROUP BY {$param_eval_query},bench {$minExecsFilter} order by bench,{$param_eval_query}";
         $rows = $db->get_rows($query);
         if (!$rows) {
             throw new \Exception("No results for query!");
         }
         $arrayBenchs = array();
         foreach ($paramOptions as $param) {
             foreach ($benchOptions as $bench) {
                 $arrayBenchs[$bench['bench']][$param] = null;
                 $arrayBenchs[$bench['bench']][$param]['y'] = 0;
                 $arrayBenchs[$bench['bench']][$param]['count'] = 0;
             }
         }
         $series = array();
         $bench = '';
         foreach ($rows as $row) {
             if ($paramEval == 'comp') {
                 $row[$paramEval] = Utils::getCompressionName($row['comp']);
             } else {
                 if ($paramEval == 'net') {
                     $row[$paramEval] = Utils::getNetworkName($row['net']);
                 } else {
                     if ($paramEval == 'disk') {
                         $row[$paramEval] = Utils::getDisksName($row['disk']);
                     } else {
                         if ($paramEval == 'iofilebuf') {
                             $row[$paramEval] /= 1024;
                         }
                     }
                 }
             }
             $arrayBenchs[$row['bench']][$row[$paramEval]]['y'] = round((int) $row['avg_exe_time'], 2);
             $arrayBenchs[$row['bench']][$row[$paramEval]]['count'] = (int) $row['count'];
         }
         // ----------------------------------------------------
         // Add predictions to the series
         // ----------------------------------------------------
         $param_variables = $this->filters->getFiltersSelectedChoices(array('current_model'));
         $param_current_model = $param_variables['current_model'];
         $where_configs = str_replace("AND .", "AND ", $where_configs);
         // compose instance
         $instance = MLUtils::generateSimpleInstance($this->filters, $param_names, $params, true);
         $model_info = MLUtils::generateModelInfo($this->filters, $param_names, $params, true);
         $slice_info = MLUtils::generateDatasliceInfo($this->filters, $param_names_additional, $params_additional);
         // model for filling
         MLUtils::findMatchingModels($model_info, $possible_models, $possible_models_id, $dbml);
         $current_model = '';
         if (!is_null($possible_models_id) && in_array($param_current_model, $possible_models_id)) {
             $current_model = $param_current_model;
         }
         // Other models for filling
         $where_models = '';
         if (!empty($possible_models_id)) {
             $where_models = " WHERE id_learner NOT IN ('" . implode("','", $possible_models_id) . "')";
         }
         $result = $dbml->query("SELECT id_learner FROM aloja_ml.learners" . $where_models);
         foreach ($result as $row) {
             $other_models[] = $row['id_learner'];
         }
         if (!empty($possible_models_id)) {
             if ($current_model == "") {
                 $query = "SELECT AVG(ABS(exe_time - pred_time)) AS MAE, AVG(ABS(exe_time - pred_time)/exe_time) AS RAE, p.id_learner FROM aloja_ml.predictions p, aloja_ml.learners l WHERE l.id_learner = p.id_learner AND p.id_learner IN ('" . implode("','", $possible_models_id) . "') AND predict_code > 0 ORDER BY MAE LIMIT 1";
                 $result = $dbml->query($query);
                 $row = $result->fetch();
                 $current_model = $row['id_learner'];
             }
             $config = $instance . '-' . $current_model . ' ' . $slice_info . "-parameval";
             $query_cache = "SELECT count(*) as total FROM aloja_ml.trees WHERE id_learner = '" . $current_model . "' AND model = '" . $model_info . "'";
             $is_cached_mysql = $dbml->query($query_cache);
             $tmp_result = $is_cached_mysql->fetch();
             $is_cached = $tmp_result['total'] > 0;
             $ret_data = null;
             if (!$is_cached) {
                 // Call to MLFindAttributes, to fetch data
                 $_GET['pass'] = 2;
                 $_GET['unseen'] = 1;
                 $_GET['current_model'] = $current_model;
                 $mlfa1 = new MLFindAttributesController();
                 $mlfa1->container = $this->container;
                 $ret_data = $mlfa1->mlfindattributesAction();
                 if ($ret_data == 1) {
                     $must_wait = "YES";
                     $jsonData = $jsonHeader = '[]';
                 } else {
                     $is_cached_mysql = $dbml->query($query_cache);
                     $tmp_result = $is_cached_mysql->fetch();
                     $is_cached = $tmp_result['total'] > 0;
                 }
             }
             if ($is_cached) {
                 $must_wait = 'NO';
                 $query = "SELECT count(*) as count, {$param_eval_query}, bench, exe_time, avg(pred_time) avg_pred_time, min(pred_time) min_pred_time " . "FROM aloja_ml.predictions e WHERE e.id_learner = '" . $current_model . "' {$filter_execs} {$where_configs}" . "GROUP BY {$param_eval_query}, bench {$minExecsFilter} order by bench,{$param_eval_query}";
                 $result = $dbml->query($query);
                 // Initialize array
                 foreach ($paramOptions as $param) {
                     foreach ($benchOptions as $bench) {
                         $arrayBenchs_pred[$bench['bench'] . '_pred'][$param] = null;
                         $arrayBenchs_pred[$bench['bench'] . '_pred'][$param]['y'] = 0;
                         $arrayBenchs_pred[$bench['bench'] . '_pred'][$param]['count'] = 0;
                     }
                 }
                 foreach ($result as $row) {
                     $bench_n = $row['bench'] . '_pred';
                     $class = $row[$paramEval];
                     if ($paramEval == 'comp') {
                         $value = Utils::getCompressionName($class);
                     } else {
                         if ($paramEval == 'id_cluster') {
                             $value = Utils::getClusterName($class, $db);
                         } else {
                             if ($paramEval == 'net') {
                                 $value = Utils::getNetworkName($class);
                             } else {
                                 if ($paramEval == 'disk') {
                                     $value = Utils::getDisksName($class);
                                 } else {
                                     if ($paramEval == 'iofilebuf') {
                                         $value = $class / 1024;
                                     } else {
                                         $value = $class;
                                     }
                                 }
                             }
                         }
                     }
                     if (!in_array($value, $paramOptions)) {
                         $paramOptions[] = $value;
                         foreach ($benchOptions as $bench) {
                             $arrayBenchs_pred[$bench['bench'] . '_pred'][$value] = null;
                             $arrayBenchs_pred[$bench['bench'] . '_pred'][$value]['y'] = 0;
                             $arrayBenchs_pred[$bench['bench'] . '_pred'][$value]['count'] = 0;
                             $arrayBenchs[$bench['bench']][$value] = null;
                             $arrayBenchs[$bench['bench']][$value]['y'] = 0;
                             $arrayBenchs[$bench['bench']][$value]['count'] = 0;
                         }
                     }
                     $arrayBenchs_pred[$bench_n][$value]['y'] = (int) $row['avg_pred_time'];
                     $arrayBenchs_pred[$bench_n][$value]['count'] = (int) $row['count'];
                 }
             }
         }
         // ----------------------------------------------------
         // END - Add predictions to the series
         // ----------------------------------------------------
         asort($paramOptions);
         foreach ($arrayBenchs as $key => $arrayBench) {
             $caregories = '';
             $data_a = null;
             $data_p = null;
             foreach ($paramOptions as $param) {
                 if ($arrayBenchs[$key][$param]['count'] > 0 && empty($arrayBenchs_pred) || !empty($arrayBenchs_pred) && ($arrayBenchs_pred[$key . '_pred'][$param]['count'] > 0 || $arrayBenchs[$key][$param]['count'] > 0)) {
                     $data_a[] = $arrayBenchs[$key][$param];
                     if (!empty($arrayBenchs_pred)) {
                         $data_p[] = $arrayBenchs_pred[$key . '_pred'][$param];
                     }
                     $categories = $categories . "'{$param} " . Utils::getParamevalUnit($paramEval) . "',";
                     // FIXME - Redundant n times performed... don't care now
                 }
             }
             $series[] = array('name' => $key, 'data' => $data_a);
             if (!empty($arrayBenchs_pred)) {
                 $series[] = array('name' => $key . '_pred', 'data' => $data_p);
             }
         }
         $series = json_encode($series);
         if (!empty($arrayBenchs_pred)) {
             $colors = "['#7cb5ec','#9cd5fc','#434348','#636368','#90ed7d','#b0fd9d','#f7a35c','#f7c37c','#8085e9','#a0a5f9','#f15c80','#f17ca0','#e4d354','#f4f374','#8085e8','#a0a5f8','#8d4653','#ad6673','#91e8e1','#b1f8f1']";
         } else {
             $colors = "['#7cb5ec','#434348','#90ed7d','#f7a35c','#8085e9','#f15c80','#e4d354','#8085e8','#8d4653','#91e8e1']";
         }
     } catch (\Exception $e) {
         $this->container->getTwig()->addGlobal('message', $e->getMessage() . "\n");
         $series = $jsonHeader = $colors = '[]';
         $must_wait = 'NO';
     }
     $return_params = array('title' => 'Improvement of Hadoop Execution by SW and HW Configurations', 'categories' => $categories, 'series' => $series, 'paramEval' => $paramEval, 'instance' => $instance, 'models' => '<li>' . implode('</li><li>', $possible_models) . '</li>', 'models_id' => $possible_models_id, 'current_model' => $current_model, 'gammacolors' => $colors, 'model_info' => $model_info, 'slice_info' => $slice_info, 'must_wait' => $must_wait);
     $this->filters->setCurrentChoices('current_model', array_merge($possible_models_id, array('---Other models---'), $other_models));
     return $this->render('mltemplate/mlparameval.html.twig', $return_params);
 }
Пример #5
0
 public function paramEvaluationAction()
 {
     $db = $this->container->getDBUtils();
     $preset = null;
     if (sizeof($_GET) <= 1) {
         $preset = Utils::setDefaultPreset($db, 'Parameter Evaluation');
     }
     $selPreset = isset($_GET['presets']) ? $_GET['presets'] : "none";
     $rows = '';
     $categories = '';
     $series = '';
     try {
         $where_configs = '';
         $concat_config = "";
         if (!isset($_GET['benchs'])) {
             $_GET['benchs'] = array('wordcount', 'terasort', 'sort');
         }
         $datefrom = Utils::read_params('datefrom', $where_configs);
         $dateto = Utils::read_params('dateto', $where_configs);
         $benchs = Utils::read_params('benchs', $where_configs);
         $nets = Utils::read_params('nets', $where_configs);
         $disks = Utils::read_params('disks', $where_configs);
         $blk_sizes = Utils::read_params('blk_sizes', $where_configs);
         $comps = Utils::read_params('comps', $where_configs);
         $id_clusters = Utils::read_params('id_clusters', $where_configs);
         $mapss = Utils::read_params('mapss', $where_configs);
         $replications = Utils::read_params('replications', $where_configs);
         $iosfs = Utils::read_params('iosfs', $where_configs);
         $iofilebufs = Utils::read_params('iofilebufs', $where_configs);
         $money = Utils::read_params('money', $where_configs);
         $datanodes = Utils::read_params('datanodess', $where_configs, false);
         $benchtype = Utils::read_params('bench_types', $where_configs);
         $vm_sizes = Utils::read_params('vm_sizes', $where_configs, false);
         $vm_coress = Utils::read_params('vm_coress', $where_configs, false);
         $vm_RAMs = Utils::read_params('vm_RAMs', $where_configs, false);
         $hadoop_versions = Utils::read_params('hadoop_versions', $where_configs, false);
         $types = Utils::read_params('types', $where_configs, false);
         $valid = Utils::read_params('valids', $where_configs);
         $filters = Utils::read_params('filters', $where_configs, false);
         $allunchecked = isset($_GET['allunchecked']) ? $_GET['allunchecked'] : '';
         $minexetime = Utils::read_params('minexetime', $where_configs, false);
         $maxexetime = Utils::read_params('maxexetime', $where_configs, false);
         $provider = Utils::read_params('providers', $where_configs, false);
         $vm_OS = Utils::read_params('vm_OSs', $where_configs, false);
         $paramEval = isset($_GET['parameval']) && $_GET['parameval'] != '' ? $_GET['parameval'] : 'maps';
         $minExecs = isset($_GET['minexecs']) ? $_GET['minexecs'] : -1;
         $minExecsFilter = "";
         if ($minExecs > 0) {
             $minExecsFilter = "HAVING COUNT(*) > {$minExecs}";
         }
         $filter_execs = DBUtils::getFilterExecs();
         $options = Utils::getFilterOptions($db);
         $paramOptions = array();
         foreach ($options[$paramEval] as $option) {
             if ($paramEval == 'id_cluster') {
                 $paramOptions[] = $option['name'];
             } else {
                 if ($paramEval == 'comp') {
                     $paramOptions[] = Utils::getCompressionName($option[$paramEval]);
                 } else {
                     if ($paramEval == 'net') {
                         $paramOptions[] = Utils::getNetworkName($option[$paramEval]);
                     } else {
                         if ($paramEval == 'disk') {
                             $paramOptions[] = Utils::getDisksName($option[$paramEval]);
                         } else {
                             if ($paramEval == 'vm_ram') {
                                 $paramOptions[] = Utils::getBeautyRam($option['vm_RAM']);
                             } else {
                                 $paramOptions[] = $option[$paramEval];
                             }
                         }
                     }
                 }
             }
         }
         // 			if($paramEval == 'maps')
         // 				$paramOptions = array(4,6,8,10,12,16,24,32);
         // 			else if($paramEval == 'comp')
         // 				$paramOptions = array('None','ZLIB','BZIP2','Snappy');
         // 		    else if($paramEval == 'id_cluster')
         // 				$paramOptions = array('rl-06');
         // 			else if($paramEval == 'net')
         // 				$paramOptions = array('Ethernet','Infiniband');
         // 			else if($paramEval == 'disk')
         // 				$paramOptions = array('Hard-disk drive','1 HDFS remote(s)/tmp local','2 HDFS remote(s)/tmp local','3 HDFS remote(s)/tmp local','1 HDFS remote(s)', '2 HDFS remote(s)', '3 HDFS remote(s)', 'SSD');
         // 			else if($paramEval == 'replication')
         // 				$paramOptions = array(1,2,3);
         // 			else if($paramEval == 'iofilebuf')
         // 				$paramOptions = array(1,4,16,32,64,128,256);
         // 			else if($paramEval == 'blk_size')
         // 				$paramOptions = array(32,64,128,256);
         // 			else if($paramEval == 'iosf')
         // 				$paramOptions = array(5,10,20,50);
         $benchOptions = $db->get_rows("SELECT DISTINCT bench FROM execs e JOIN clusters c USING (id_cluster) WHERE 1 {$filter_execs} {$where_configs} GROUP BY {$paramEval}, bench order by {$paramEval}");
         // get the result rows
         $query = "SELECT count(*) as count, {$paramEval}, e.id_exec, exec as conf, bench, " . "exe_time, avg(exe_time) avg_exe_time, min(exe_time) min_exe_time " . "from execs e JOIN clusters c USING (id_cluster) WHERE 1 {$filter_execs} {$where_configs}" . "GROUP BY {$paramEval}, bench {$minExecsFilter} order by bench,{$paramEval}";
         $rows = $db->get_rows($query);
         if (!$rows) {
             throw new \Exception("No results for query!");
         }
         $categories = '';
         $arrayBenchs = array();
         foreach ($paramOptions as $param) {
             $categories .= "'{$param}" . Utils::getParamevalUnit($paramEval) . "',";
             foreach ($benchOptions as $bench) {
                 $arrayBenchs[$bench['bench']][$param] = null;
             }
         }
         $series = array();
         $bench = '';
         foreach ($rows as $row) {
             if ($paramEval == 'comp') {
                 $row[$paramEval] = Utils::getCompressionName($row['comp']);
             } else {
                 if ($paramEval == 'id_cluster') {
                     $row[$paramEval] = Utils::getClusterName($row[$paramEval], $db);
                 } else {
                     if ($paramEval == 'net') {
                         $row[$paramEval] = Utils::getNetworkName($row['net']);
                     } else {
                         if ($paramEval == 'disk') {
                             $row[$paramEval] = Utils::getDisksName($row['disk']);
                         } else {
                             if ($paramEval == 'vm_ram') {
                                 $row[$paramEval] = Utils::getBeautyRam($row['vm_ram']);
                             }
                         }
                     }
                 }
             }
             $arrayBenchs[strtolower($row['bench'])][$row[$paramEval]]['y'] = round((int) $row['avg_exe_time'], 2);
             $arrayBenchs[strtolower($row['bench'])][$row[$paramEval]]['count'] = (int) $row['count'];
         }
         foreach ($arrayBenchs as $key => $arrayBench) {
             $series[] = array('name' => $key, 'data' => array_values($arrayBench));
         }
         $series = json_encode($series);
     } catch (\Exception $e) {
         $this->container->getTwig()->addGlobal('message', $e->getMessage() . "\n");
     }
     echo $this->container->getTwig()->render('parameval/parameval.html.twig', array('selected' => 'Parameter Evaluation', 'title' => 'Improvement of Hadoop Execution by SW and HW Configurations', 'categories' => $categories, 'series' => $series, 'datefrom' => $datefrom, 'dateto' => $dateto, 'benchs' => $benchs, 'nets' => $nets, 'disks' => $disks, 'blk_sizes' => $blk_sizes, 'comps' => $comps, 'id_clusters' => $id_clusters, 'mapss' => $mapss, 'replications' => $replications, 'iosfs' => $iosfs, 'iofilebufs' => $iofilebufs, 'money' => $money, 'datanodess' => $datanodes, 'bench_types' => $benchtype, 'vm_sizes' => $vm_sizes, 'vm_coress' => $vm_coress, 'vm_RAMs' => $vm_RAMs, 'vm_OS' => $vm_OS, 'hadoop_versions' => $hadoop_versions, 'types' => $types, 'providers' => $provider, 'filters' => $filters, 'allunchecked' => $allunchecked, 'minexetime' => $minexetime, 'maxexetime' => $maxexetime, 'preset' => $preset, 'selPreset' => $selPreset, 'paramEval' => $paramEval, 'options' => $options));
 }