Movielogr

movie poster

Rating: 8.5 stars

Seen 1 time

Seen on: 12/13/2011

View on: IMDb | TMDb

Enter the Void (2009)

Directed by Gaspar Noé

Drama

Most recently watched by noahphex, sensoria, noahphex

Overview

This psychedelic tour of life after death is seen entirely from the point of view of Oscar, a young American drug dealer and addict living in Tokyo with his prostitute sister, Linda. When Oscar is killed by police during a bust gone bad, his spirit journeys from the past—where he sees his parents before their deaths—to the present—where he witnesses his own autopsy—and then to the future, where he looks out for his sister from beyond the grave.

Rated NR | Length 161 minutes

Actors

Sara Stockbridge | Paz de la Huerta | Olly Alexander | Nathaniel Brown | Emily Alyn Lind | Jesse Kuhn | Ed Spear | Cyril Roy | Masato Tanno | Nobuko Imai | Emiko Takeuchi | Sakiko Fukuhara | Janice Béliveau-Sicotte | Stuart Miller | Rumiko Kimishima

Viewing Notes

About a year ago you couldn’t throw a rock without hitting someone’s opinion on this movie; it was all the rage. I planned on watching it early this year when it showed up on Netflix Instant, but held off as I was told it was an edited version.

My friend Jay loaned me his Bluray which I then sat on for nearly 10 months, awaiting the right opportunity to watch this. I finally pulled the trigger and I am both sad and glad that I waited so long. Sad, because I think I was influenced too much by other people’s remarks on Twitter about the film; glad because I was able to watch it long after anyone stopped caring about what my opinion on it might be.

I thought it was technically brilliant. The opening credits alone, which felt like a Scraping Foetus off the Wheel album come to life, were fantastic and worth some sort of an award.

The film itself is brilliantly shot and edited with an exceptional soundtrack. It also lacks any sort of emotional depth; I never really made a connection with any of the characters, nor cared much about what happened to them. I think the reason for that is the same thing that makes the film technically brilliant: the kind of first person camera work. You are constantly aware of the plane that exists between you and the movie; constantly reminded that you are a spectator, not an involved participant, physically or emotionally.

Well worth a watch, but ultimately I felt like it fell short of its goal.

Comments

No comments yet. Log in and be the first!

  BENCHMARKS  
Loading Time: Base Classes  0.0015
Controller Execution Time ( Members / Movie Detail )  0.0257
Total Execution Time  0.0273
  GET DATA  
No GET data exists
  MEMORY USAGE  
538,712 bytes
  POST DATA  
No POST data exists
  URI STRING  
members/sensoria/movie_detail/7341
  CLASS/METHOD  
members/movie_detail
  DATABASE:  movielogr_dev (Members:$db)   QUERIES: 17 (0.0066 seconds)  (Hide)
0.0005   SELECT 1
FROM 
`ml_sessions`
WHERE `id` = '69f0807bf0058dfc0da224447554ee406e35c857'
AND `ip_address` = '216.73.216.111' 
0.0003   SELECT GET_LOCK('2b036dadad10baee50c3b78271e1a767'300) AS ci_session_lock 
0.0003   SELECT `data`
FROM `ml_sessions`
WHERE `id` = '69f0807bf0058dfc0da224447554ee406e35c857'
AND `ip_address` = '216.73.216.111' 
0.0004   SELECT `username`, `user_id`
FROM `ml_users`
WHERE `username` = 'sensoria'
 
LIMIT 1 
0.0003   SELECT `MV`.`title_id`, `MT`.`tmdb_id`
FROM `ml_movie_titles` `MT`
LEFT JOIN `ml_movies` `MVON `MV`.`title_id` = `MT`.`title_id`
WHERE `MV`.`movie_id` = 7341
AND `MV`.`user_id` = 1
 LIMIT 1 
0.0004   SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 1
 LIMIT 1 
0.0002   SET SESSION group_concat_max_len 12288 
0.0015   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_nameAS `genre_name_01`, `G2`.`genre_nameAS `genre_name_02`, `G3`.`genre_nameAS `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 directorsGROUP_CONCAT(DISTINCT(DR.tmdb_director_id) ORDER BY DR.tmdb_director_id ASC SEPARATOR "|") AS director_idsGROUP_CONCAT(DISTINCT(ACT.actor_name) ORDER BY ACT.tmdb_actor_id ASC SEPARATOR "|") AS actorsGROUP_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` `MVON `MV`.`title_id` = `MT`.`title_id`
LEFT JOIN `ml_movie_posters` `MPON `MV`.`title_id` = `MP`.`title_id`
LEFT JOIN `ml_lookup_genres` `G1ON `MV`.`genre_id_01` = `G1`.`genre_id`
LEFT JOIN `ml_lookup_genres` `G2ON `MV`.`genre_id_02` = `G2`.`genre_id`
LEFT JOIN `ml_lookup_genres` `G3ON `MV`.`genre_id_03` = `G3`.`genre_id`
LEFT JOIN `ml_lookup_formats` `FMTON `MV`.`format_id` = `FMT`.`format_id`
LEFT JOIN `ml_lookup_sources` `SRCON `MV`.`source_id` = `SRC`.`source_id`
LEFT JOIN `ml_lookup_devices` `DVCON `MV`.`device_id` = `DVC`.`device_id`
LEFT JOIN `ml_movie_ratings_ten_star` `STRON `MV`.`rating_id` = `STR`.`rating_id`
LEFT JOIN `ml_junction_movies_directors` `JMDON `MT`.`title_id` = `JMD`.`title_id`
LEFT JOIN `ml_directors_new` `DRON `JMD`.`tmdb_director_id` = `DR`.`tmdb_director_id`
LEFT JOIN `ml_junction_movies_actors` `JMAON `MT`.`title_id` = `JMA`.`title_id`
LEFT JOIN `ml_actors_new` `ACTON `JMA`.`tmdb_actor_id` = `ACT`.`tmdb_actor_id`
WHERE `MV`.`movie_id` = 7341
AND `MV`.`user_id` = 1
ORDER BY 
`date_viewedDESC 
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` `EVON `JME`.`event_id` = `EV`.`event_id`
WHERE `JME`.`movie_id` = 7341 
0.0004   SELECT `tag`, `JMT`.`tag_id`
FROM `ml_junction_movies_tags` `JMT`
LEFT JOIN `ml_tags` `MTON `JMT`.`tag_id` = `MT`.`tag_id`
WHERE `JMT`.`movie_id` = 7341 
0.0002   SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 1
 LIMIT 1 
0.0002   SELECT `rating_id`
FROM `ml_movies` `MV`
WHERE `MV`.`user_id` = 1
AND `MV`.`movie_id` = 7341
 LIMIT 1 
0.0002   SELECT `star_rating`
FROM `ml_movie_ratings_ten_star` `MR`
WHERE `MR`.`rating_id` = '19'
 
LIMIT 1 
0.0004   SELECT `MV2`.`date_viewed`, `MV2`.`movie_id`
FROM `ml_movies` `MV`
LEFT JOIN `ml_movies` `MV2ON `MV`.`title_id` = `MV2`.`title_idAND `MV`.`user_id` = `MV2`.`user_id`
WHERE `MV`.`user_id` = 1
AND `MV`.`movie_id` = 7341
GROUP BY 
`MV2`.`movie_id`
ORDER BY `MV2`.`date_viewedDESC 
0.0003   SELECT `comment_id`, `comment`, `commenter_id`, `timestamp`, `username`, `email_address`
FROM `ml_comments` `MC`
JOIN `ml_users` `MUON `MU`.`user_id` = `MC`.`commenter_id`
WHERE `movie_id` = 7341 
0.0004   SELECT `username`, `date_viewed`, `MV`.`movie_id`
FROM `ml_users` `MU`
JOIN `ml_movies` `MVON `MV`.`user_id` = `MU`.`user_id`
JOIN `ml_movie_titles` `MTON `MT`.`title_id` = `MV`.`title_id`
WHERE `MT`.`title_id` = 2820
ORDER BY 
`date_viewedDESC
 LIMIT 10 
  HTTP HEADERS  (Show)
  SESSION DATA  (Show)
  CONFIG VARIABLES  (Show)