Movielogr

movie poster

Rating: 8 stars

Tags

KevinP

Seen 1 time

Seen on: 05/25/2002

View on: IMDb | TMDb

Memento (2000)

Directed by Christopher Nolan

Mystery | Drama | Thriller

Most recently watched by sleestakk

Overview

Leonard Shelby is tracking down the man who raped and murdered his wife. The difficulty of locating his wife’s killer, however, is compounded by the fact that he suffers from a rare, untreatable form of short-term memory loss. Although he can recall details of life before his accident, Leonard cannot remember what happened fifteen minutes ago, where he’s going, or why.

Rated R | Length 113 minutes

Actors

Guy Pearce | Carrie-Anne Moss | Joe Pantoliano | Mark Boone Junior | Russ Fega | Jorja Fox | Stephen Tobolowsky | Harriet Sansom Harris | Thomas Lennon | Callum Keith Rennie | Kimberly Campbell | Marianne Muellerleile | Larry Holden

Viewing Notes

Kevin and I rented this from his local Blockbuster since it was a new release and we’d heard good things. Excellent flick.

Comments

No comments yet. Log in and be the first!

  BENCHMARKS  
Loading Time: Base Classes  0.0015
Controller Execution Time ( Members / Movie Detail )  0.3233
Total Execution Time  0.3248
  GET DATA  
No GET data exists
  MEMORY USAGE  
531,520 bytes
  POST DATA  
No POST data exists
  URI STRING  
members/sleestakk/movie_detail/8274
  CLASS/METHOD  
members/movie_detail
  DATABASE:  movielogr_dev (Members:$db)   QUERIES: 17 (0.3036 seconds)  (Hide)
0.0003  
SELECT 1
FROM `ml_sessions`
WHERE `id` = '081f48ad32a2c68e5880327ed860a3bb509b9ff6'
AND `ip_address` = '216.73.216.6' ?>
0.2981  
SELECT GET_LOCK('8517240fcc9d68379d2bded637dac916', 300) AS ci_session_lock ?>
0.0004  
SELECT `data`
FROM `ml_sessions`
WHERE `id` = '081f48ad32a2c68e5880327ed860a3bb509b9ff6'
AND `ip_address` = '216.73.216.6' ?>
0.0003  
SELECT `username`, `user_id`
FROM `ml_users`
WHERE `username` = 'sleestakk'
 LIMIT 1 ?>
0.0003  
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` = 8274
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 ?>
0.0019  
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` = 8274
AND `MV`.`user_id` = 9
ORDER BY `date_viewed` DESC ?>
0.0002  
SET SESSION group_concat_max_len = 1024 ?>
0.0002  
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` = 8274 ?>
0.0002  
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` = 8274 ?>
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` = 8274
 LIMIT 1 ?>
0.0001  
SELECT `star_rating`
FROM `ml_movie_ratings_ten_star` `MR`
WHERE `MR`.`rating_id` = '18'
 LIMIT 1 ?>
0.0002  
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` = 8274
GROUP BY `MV2`.`movie_id`
ORDER BY `MV2`.`date_viewed` DESC ?>
0.0002  
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` = 8274 ?>
0.0002  
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` = 4855
ORDER BY `date_viewed` DESC
 LIMIT 10 ?>
  HTTP HEADERS  (Show)
  SESSION DATA  (Show)
  CONFIG VARIABLES  (Show)