rec_example.module in Recommender API 7.3

File

rec_example/rec_example.module

<?php

/**
 * This module has three purposes:
 * 1. Test the performance of Recommender API over 100K, 1M and 10M ratings.
 * 2. Evaluate different settings of RecAPI for development purposes.
 * 3. Demonstrate how to use RecAPI to generate recommendations.
 *
 * To use this example module, please download GroupLens movies recommendations dataset at:
 * http://grouplens.org/node/73
 *
 * Save the 100K dataset to /tmp/100k, 1M dataset to /tmp/1m, 10M dataset to /tmp/10m.
 *
 * @author danithaca (http://drupal.org/user/112233)
 *
 */

/**
 * Implements hook_menu();
 */
function rec_example_menu() {
  $items = array();
  $items['admin/config/recommender/rec_example'] = array(
    'title' => 'Recommender API Example',
    'description' => 'Configuration and trigger rec_example module.',
    'page callback' => 'drupal_get_form',
    'page arguments' => array(
      'rec_example_settings_form',
    ),
    'access arguments' => array(
      'administer recommender',
    ),
  );
  return $items;
}
function rec_example_settings_form() {
  $form = array();
  $form['rebuild'] = array(
    '#type' => 'submit',
    '#value' => t('Rebuild'),
    '#name' => 'rebuild',
    '#disabled' => FALSE,
  );
  $form['refresh'] = array(
    '#type' => 'submit',
    '#value' => t('Refresh'),
    '#name' => 'refresh',
    '#disabled' => FALSE,
  );
  $form['load_file'] = array(
    '#type' => 'submit',
    '#value' => t('Load data'),
    '#name' => 'load_file',
    '#disabled' => FALSE,
  );
  return $form;
}
function rec_example_settings_form_submit($form, &$form_state) {
  switch ($form_state['clicked_button']['#name']) {
    case 'rebuild':
      $new_params = array(
        'algorithm' => 'svd',
      );

      //recommender_app_update('rec_example', $new_params);
      recommender_create_command('rec_example');
      break;
    case 'refresh':
      recommender_create_command('rec_example_update');
      break;
    case 'load_file':
      $batch = array(
        'title' => t('Importing Data'),
        'operations' => array(
          array(
            'rec_example_load_file_small_ram',
            array(
              '/tmp/100k/u1.base',
            ),
          ),
        ),
        'finished' => 'rec_example_batch_finish',
      );
      batch_set($batch);

      // only needed if not inside a form _submit handler :
      batch_process();
      break;
  }
}
function rec_example_batch_finish($success, $results, $operations) {
  if ($success) {
    drupal_set_message(t('Successfully loaded file.'));
  }

  //drupal_goto('admin/config/rec_example');
}
function rec_example_batch_insert($values) {
  if (empty($values)) {
    return;
  }
  $query = db_insert('recommender_preference_staging')
    ->fields(array(
    'source_eid',
    'target_eid',
    'score',
    'updated',
  ));
  foreach ($values as $row) {
    $query
      ->values($row);
  }
  $query
    ->execute();
}
function rec_example_load_file_small_ram($file_name) {
  db_delete('recommender_preference_staging')
    ->execute();
  $ratings_file = fopen($file_name, 'r');
  $count = 0;
  $values = array();
  if ($ratings_file) {
    while (!feof($ratings_file)) {
      $line = fgets($ratings_file);
      $values[] = explode("\t", $line);
      $count++;
      if ($count % 500 == 0) {
        rec_example_batch_insert($values);
        $values = array();
      }

      //db_query("INSERT INTO {recommender_preference_staging}(source_eid, target_eid, score, updated) VALUE (:e1, :e2, :score, :updated)",

      //    array(':e1' => $fields[0], ':e2' => $fields[1], ':score' => $fields[2], ':updated' => $fields[3]));
    }

    //rec_example_batch_insert($values);
    fclose($ratings_file);
  }
  else {
    drupal_set_message('Cannot load file: ' . $file_name);
  }
}
function rec_example_load_file_high_performance($file_name = '/tmp/100k/u1.base') {
  db_delete('recommender_preference_staging')
    ->execute();
  $ratings_str = file_get_contents($file_name, 'r');
  if ($ratings_str) {
    $ratings = explode("\n", $ratings_str);
    $query = db_insert('recommender_preference_staging')
      ->fields(array(
      'source_eid',
      'target_eid',
      'score',
      'updated',
    ));
    foreach ($ratings as $line) {
      $fields = explode("\t", $line);
      assert(count($fields) == 4);
      $query
        ->values(array(
        'source_eid' => $fields[0],
        'target_eid' => $fields[1],
        'score' => $fields[2],
        'updated' => $fields[3],
      ));
    }
    $query
      ->execute();
  }
  else {
    drupal_set_message('Cannot load file: ' . $file_name);
  }
}

// $simpred: 0 - similarity table, 1 - prediction table
// $un1: 0 - first field is user, 1 - first field is node
// $un2: 0 - second field is user, 1 - second field is node

/*function rec_example_debug_table($app_name, $simpred, $un1, $un2) {
  $app_id = recommender_get_app_id($app_name);

  // load data
  if ($simpred == 0) {
    $sql = "SELECT mouse1_id un1, mouse2_id un2, similarity score FROM {recommender_similarity} WHERE app_id=%s ORDER BY mouse1_id, mouse2_id";
  }
  else if ($simpred == 1) {
    $sql = "SELECT mouse_id un1, cheese_id un2, prediction score FROM {recommender_prediction} WHERE app_id=%s ORDER BY mouse_id, cheese_id";
  }
  $result = db_query($sql, $app_id);

  // load users
  $users = array();
  $u_result = db_query("SELECT uid, name FROM {users}");
  while ($u = db_fetch_array($u_result)) {
    $users[$u['uid']] = $u['name'];
  }

  // load nodes
  $nodes = array();
  $n_result = db_query("SELECT nid, title FROM {node}");
  while ($n = db_fetch_array($n_result)) {
    $nodes[$n['nid']] = $n['title'];
  }

  $un1_content = $un1 ? $nodes : $users;
  $un2_content = $un2 ? $nodes : $users;

  $un1_header = $un1 ? 'node' : 'user';
  $un2_header = $un2 ? 'node' : 'user';
  $header = array($un1_header, $un2_header, 'score');
  $rows = array();

  while($record = db_fetch_array($result)) {
    $r = array();
    $r[] = l($un1_content[$record['un1']], "{$un1_header}/{$record['un1']}");
    $r[] = l($un2_content[$record['un2']], "{$un2_header}/{$record['un2']}");
    $r[] = $record['score'];
    $rows[] = $r;
  }

  return theme('table', $header, $rows);
}*/

Functions

Name	Description
rec_example_batch_finish
rec_example_batch_insert
rec_example_load_file_high_performance
rec_example_load_file_small_ram
rec_example_menu	Implements hook_menu();
rec_example_settings_form
rec_example_settings_form_submit