Movielogr

Home

movie poster

Average Rating: 8/10

View on: IMDb | TMDb

The Perks of Being a Wallflower (2012)

Directed by Stephen Chbosky

Most recently watched by sleestakk, zombiefreak

Overview

Pittsburgh, Pennsylvania, 1991. High school freshman Charlie is a wallflower, always watching life from the sidelines, until two senior students, Sam and her stepbrother Patrick, become his mentors, helping him discover the joys of friendship, music and love.

Rated PG-13 | Length 103 minutes

Actors

Joan Cusack | Emma Watson | Tom Savini | Melanie Lynskey | Nina Dobrev | Paul Rudd | Johnny Simmons | Dylan McDermott | Logan Lerman | Reece Thompson | Mae Whitman | Kate Walsh | Nicholas Braun | Stacy Chbosky | Ezra Miller | Dihlon McManne | Brian Balzerini | Julia Garner | Zane Holtz | Erin Wilhelmi | Patrick de Ledebur | Atticus Cain | Morgan Wolk | Landon Pigg | Mark McClain Wilson | Chelsea Zhang | Adam Hagenbuch | Laurie Klatscher | Joe Fishel | Jennifer Enskat | William L. Thomas | Jeffrey Jones | Jordan Paley | Tom Kruszewski | Emily Marie Callaway | Jesse Scheirer | Justine Nicole Schaefer | Julie Marie Schaefer | Leo Miles Farmerie | Isabel Muschweck | Timothy Breslin

  BENCHMARKS  
Loading Time: Base Classes  0.0016
Controller Execution Time ( Overview / Movie Detail )  0.0253
Total Execution Time  0.0269
  GET DATA  
No GET data exists
  MEMORY USAGE  
520,224 bytes
  POST DATA  
No POST data exists
  URI STRING  
overview/movie_detail/5595
  CLASS/METHOD  
overview/movie_detail
  DATABASE:  movielogr_dev (Overview:$db)   QUERIES: 10 (0.0041 seconds)  (Hide)
0.0004   SELECT 1
FROM `ml_sessions`
WHERE `id` = 'd1e0e9768e2b13f50738d14771d0af01dde0a4ec'
AND `ip_address` = '216.73.216.111' 
0.0002   SELECT GET_LOCK('01ca37e9d2f753d88b3e751725b82248', 300) AS ci_session_lock 
0.0003   SELECT `data`
FROM `ml_sessions`
WHERE `id` = 'd1e0e9768e2b13f50738d14771d0af01dde0a4ec'
AND `ip_address` = '216.73.216.111' 
0.0004   SELECT `MT`.`title_id`, `MT`.`tmdb_id`
FROM `ml_movie_titles` `MT`
WHERE `MT`.`title_id` = 5595
 LIMIT 1 
0.0003   SET SESSION group_concat_max_len = 12288 
0.0015   SELECT `MT`.`title_id`, `title`, `prefix`, `year`, `imdb_link`, `imdb_id`, `MT`.`tmdb_id`, `overview`, `certification`, `runtime`, MAX(MP.filename) AS filename, GROUP_CONCAT(DISTINCT(DR.director_name) ORDER BY DR.tmdb_director_id ASC SEPARATOR "|") AS directors, GROUP_CONCAT(DISTINCT(DR.tmdb_director_id) ORDER BY DR.tmdb_director_id ASC SEPARATOR "|") AS director_ids, GROUP_CONCAT(DISTINCT(ACT.actor_name) ORDER BY ACT.tmdb_actor_id ASC SEPARATOR "|") AS actors, GROUP_CONCAT(DISTINCT(ACT.tmdb_actor_id) ORDER BY ACT.tmdb_actor_id ASC SEPARATOR "|") AS actor_ids
FROM `ml_movie_titles` `MT`
LEFT JOIN `ml_movie_posters` `MP` ON `MT`.`title_id` = `MP`.`title_id`
LEFT JOIN `ml_junction_movies_directors` `JMD` ON `MT`.`title_id` = `JMD`.`title_id`
LEFT JOIN `ml_directors_new` `DR` ON `JMD`.`tmdb_director_id` = `DR`.`tmdb_director_id`
LEFT JOIN `ml_junction_movies_actors` `JMA` ON `MT`.`title_id` = `JMA`.`title_id`
LEFT JOIN `ml_actors_new` `ACT` ON `JMA`.`tmdb_actor_id` = `ACT`.`tmdb_actor_id`
WHERE `MT`.`title_id` = 5595
GROUP BY `title_id` 
0.0002   SET SESSION group_concat_max_len = 1024 
0.0004   SELECT `username`, `date_viewed`, `MV`.`movie_id`
FROM `ml_users` `MU`
JOIN `ml_movies` `MV` ON `MV`.`user_id` = `MU`.`user_id`
JOIN `ml_movie_titles` `MT` ON `MT`.`title_id` = `MV`.`title_id`
WHERE `MT`.`title_id` = 5595
ORDER BY `date_viewed` DESC
 LIMIT 10 
0.0003   SELECT AVG(NULLIF(rating_id, 2)) AS `avg_rating`
FROM `ml_movies`
WHERE `title_id` = 5595 
0.0002   SELECT `star_rating`
FROM `ml_movie_ratings_ten_star`
WHERE `rating_id` = 18 
  HTTP HEADERS  (Show)
  SESSION DATA  (Show)
  CONFIG VARIABLES  (Show)