Movielogr

movie poster

Rating: 7 stars

Seen 1 time

Seen on: 12/31/2003

View on: IMDb | TMDb

Paycheck (2003)

Directed by John Woo

Action | Science Fiction | Thriller

Most recently watched by sleestakk

Overview

Michael Jennings is a genius who’s hired – and paid handsomely – by high-tech firms to work on highly sensitive projects, after which his short-term memory is erased so he’s incapable of breaching security. But at the end of a three-year job, he’s told he isn’t getting a paycheck and instead receives a mysterious envelope. In it are clues he must piece together to find out why he wasn’t paid – and why he’s now in hot water.

Rated PG-13 | Length 119 minutes

Actors

Uma Thurman | Callum Keith Rennie | Ben Affleck | Kathryn Morris | Joe Morton | David Lewis | Aaron Eckhart | Colm Feore | John Cassini | Paul Giamatti | Krista Allen | Ivana Miličević | Emily Holmes | Serge Houde | Barclay Hope | Michael C. Hall | Peter Friedman | Kendall Cross | Michelle Harrison | Craig March | Claudette Mink | Fulvio Cecere | Chelah Horsdal | Benita Ha | Ryan Robbins | Catherine Lough Haggquist | Darryl Scheelar | Mark Brandon | Brad Kelly | Christopher Kennedy | Jason Calder | Peter Shinkoda | Roger Haskett | Dee Jay Jackson | Mike Godenir | Brent Connolly | Craig Hosking | Michelle Anderson | Lori Berlanga | Ryan Zwick | Calvin Finlayson | Steve Wright | Robert Clark | Andrea Siradze | Isabelle Roland | Peter Caton

Viewing Notes

Not one of John Woo’s better films for sure but enjoyable for what it tries to do. Full of holes when you try to break it down but whatever. Despite the silly ending it’s a decent thriller once you accept the rules they attempt to establish.  And it looks good. I’d revisit someday.

Comments

No comments yet. Log in and be the first!

  BENCHMARKS  
Loading Time: Base Classes  0.0014
Controller Execution Time ( Members / Movie Detail )  0.0333
Total Execution Time  0.0348
  GET DATA  
No GET data exists
  MEMORY USAGE  
540,112 bytes
  POST DATA  
No POST data exists
  URI STRING  
members/sleestakk/movie_detail/7815
  CLASS/METHOD  
members/movie_detail
  DATABASE:  movielogr_dev (Members:$db)   QUERIES: 17 (0.0082 seconds)  (Hide)
0.0003  
SELECT 1
FROM `ml_sessions`
WHERE `id` = '52afb5fdfec7f97d44c5f7c1a20226e894898425'
AND `ip_address` = '216.73.216.6' ?>
0.0002  
SELECT GET_LOCK('9b97b09e7de1277c39b98e338a62100f', 300) AS ci_session_lock ?>
0.0002  
SELECT `data`
FROM `ml_sessions`
WHERE `id` = '52afb5fdfec7f97d44c5f7c1a20226e894898425'
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` = 7815
AND `MV`.`user_id` = 9
 LIMIT 1 ?>
0.0004  
SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 9
 LIMIT 1 ?>
0.0002  
SET SESSION group_concat_max_len = 12288 ?>
0.0024  
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` = 7815
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` = 7815 ?>
0.0021  
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` = 7815 ?>
0.0002  
SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 9
 LIMIT 1 ?>
0.0001  
SELECT `rating_id`
FROM `ml_movies` `MV`
WHERE `MV`.`user_id` = 9
AND `MV`.`movie_id` = 7815
 LIMIT 1 ?>
0.0002  
SELECT `star_rating`
FROM `ml_movie_ratings_ten_star` `MR`
WHERE `MR`.`rating_id` = '16'
 LIMIT 1 ?>
0.0003  
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` = 7815
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` = 7815 ?>
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` = 4542
ORDER BY `date_viewed` DESC
 LIMIT 10 ?>
  HTTP HEADERS  (Show)
  SESSION DATA  (Show)
  CONFIG VARIABLES  (Show)