Movielogr

movie poster

Rating: 8 stars

Tags

KevinP

Seen 1 time

Seen on: 03/01/2002

View on: IMDb | TMDb

Office Space (1999)

Directed by Mike Judge

Comedy | Crime

Most recently watched by ericjgruber, sleestakk

Overview

A depressed white-collar worker tries hypnotherapy, only to find himself in a perpetual state of devil-may-care bliss that prompts him to start living by his own rules, and hatch a hapless attempt to embezzle money from his soul-killing employers.

Rated R | Length 90 minutes

Actors

Ajay Naidu | Jennifer Aniston | Diedrich Bader | Michael McShane | John C. McGinley | Paul Willson | Stephen Root | Ron Livingston | Mike Judge | Richard Riehle | Orlando Jones | Jack Betts | Gary Cole | David Herman | Greg Pitts | Kinna McInroe | Alexandra Wentworth | Joe Bays | Todd Duffey | Gabriel Folse | Rupert Reyes | Jesse De Luna | Tom Schuster | Jackie Belvin | Linda Wakeman | Jennifer Jane Emerson | Kyle Scott Jackson | Barbara George-Reiss | Justin Possenti | Charissa Allen

Viewing Notes

Rented this from Video Mania having not seen it. Kevin came over and we watched… and laughed. Really good movie. Can see why so many people reference it.

Comments

No comments yet. Log in and be the first!

  BENCHMARKS  
Loading Time: Base Classes  0.0015
Controller Execution Time ( Members / Movie Detail )  0.0274
Total Execution Time  0.0289
  GET DATA  
No GET data exists
  MEMORY USAGE  
532,272 bytes
  POST DATA  
No POST data exists
  URI STRING  
members/sleestakk/movie_detail/7820
  CLASS/METHOD  
members/movie_detail
  DATABASE:  movielogr_dev (Members:$db)   QUERIES: 17 (0.0062 seconds)  (Hide)
0.0004  
SELECT 1
FROM `ml_sessions`
WHERE `id` = '54501fb77a9c844a96e49694fb70667278400bdc'
AND `ip_address` = '216.73.216.6' ?>
0.0002  
SELECT GET_LOCK('5b584dd57005c1eb828815281dbcc8fd', 300) AS ci_session_lock ?>
0.0002  
SELECT `data`
FROM `ml_sessions`
WHERE `id` = '54501fb77a9c844a96e49694fb70667278400bdc'
AND `ip_address` = '216.73.216.6' ?>
0.0004  
SELECT `username`, `user_id`
FROM `ml_users`
WHERE `username` = 'sleestakk'
 LIMIT 1 ?>
0.0004  
SELECT `MV`.`title_id`, `MT`.`tmdb_id`
FROM `ml_movie_titles` `MT`
LEFT JOIN `ml_movies` `MV` ON `MV`.`title_id` = `MT`.`title_id`
WHERE `MV`.`movie_id` = 7820
AND `MV`.`user_id` = 9
 LIMIT 1 ?>
0.0003  
SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 9
 LIMIT 1 ?>
0.0002  
SET SESSION group_concat_max_len = 12288 ?>
0.0016  
SELECT `MV`.`title_id`, `MV`.`movie_id`, COUNT(DISTINCT MV.title_id) AS mv_count, `title`, `prefix`, `year`, `imdb_link`, `MT`.`imdb_id`, `MT`.`tmdb_id`, `overview`, `certification`, `runtime`, `genre_id_01`, `genre_id_02`, `genre_id_03`, MAX(MP.filename) AS filename, `G1`.`genre_name` AS `genre_name_01`, `G2`.`genre_name` AS `genre_name_02`, `G3`.`genre_name` AS `genre_name_03`, `date_viewed`, `notes`, `MV`.`format_id`, `FMT`.`format_name`, `MV`.`source_id`, `SRC`.`source_name`, `MV`.`device_id`, `DVC`.`device_name`, `MV`.`rating_id`, `STR`.`star_rating`, `rewatch`, 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_movies` `MV` ON `MV`.`title_id` = `MT`.`title_id`
LEFT JOIN `ml_movie_posters` `MP` ON `MV`.`title_id` = `MP`.`title_id`
LEFT JOIN `ml_lookup_genres` `G1` ON `MV`.`genre_id_01` = `G1`.`genre_id`
LEFT JOIN `ml_lookup_genres` `G2` ON `MV`.`genre_id_02` = `G2`.`genre_id`
LEFT JOIN `ml_lookup_genres` `G3` ON `MV`.`genre_id_03` = `G3`.`genre_id`
LEFT JOIN `ml_lookup_formats` `FMT` ON `MV`.`format_id` = `FMT`.`format_id`
LEFT JOIN `ml_lookup_sources` `SRC` ON `MV`.`source_id` = `SRC`.`source_id`
LEFT JOIN `ml_lookup_devices` `DVC` ON `MV`.`device_id` = `DVC`.`device_id`
LEFT JOIN `ml_movie_ratings_ten_star` `STR` ON `MV`.`rating_id` = `STR`.`rating_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 `MV`.`movie_id` = 7820
AND `MV`.`user_id` = 9
ORDER BY `date_viewed` DESC ?>
0.0002  
SET SESSION group_concat_max_len = 1024 ?>
0.0003  
SELECT `event_title`, `JME`.`event_id`
FROM `ml_junction_movies_events` `JME`
LEFT JOIN `ml_movie_events` `EV` ON `JME`.`event_id` = `EV`.`event_id`
WHERE `JME`.`movie_id` = 7820 ?>
0.0003  
SELECT `tag`, `JMT`.`tag_id`
FROM `ml_junction_movies_tags` `JMT`
LEFT JOIN `ml_tags` `MT` ON `JMT`.`tag_id` = `MT`.`tag_id`
WHERE `JMT`.`movie_id` = 7820 ?>
0.0002  
SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 9
 LIMIT 1 ?>
0.0002  
SELECT `rating_id`
FROM `ml_movies` `MV`
WHERE `MV`.`user_id` = 9
AND `MV`.`movie_id` = 7820
 LIMIT 1 ?>
0.0002  
SELECT `star_rating`
FROM `ml_movie_ratings_ten_star` `MR`
WHERE `MR`.`rating_id` = '18'
 LIMIT 1 ?>
0.0005  
SELECT `MV2`.`date_viewed`, `MV2`.`movie_id`
FROM `ml_movies` `MV`
LEFT JOIN `ml_movies` `MV2` ON `MV`.`title_id` = `MV2`.`title_id` AND `MV`.`user_id` = `MV2`.`user_id`
WHERE `MV`.`user_id` = 9
AND `MV`.`movie_id` = 7820
GROUP BY `MV2`.`movie_id`
ORDER BY `MV2`.`date_viewed` DESC ?>
0.0003  
SELECT `comment_id`, `comment`, `commenter_id`, `timestamp`, `username`, `email_address`
FROM `ml_comments` `MC`
JOIN `ml_users` `MU` ON `MU`.`user_id` = `MC`.`commenter_id`
WHERE `movie_id` = 7820 ?>
0.0003  
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` = 2324
ORDER BY `date_viewed` DESC
 LIMIT 10 ?>
  HTTP HEADERS  (Show)
  SESSION DATA  (Show)
  CONFIG VARIABLES  (Show)