Movielogr

movie poster

Rating: 9.5 stars

Tags

Netflix Chicago Cease Fire gangs

Seen 1 time

Seen on: 05/15/2012

View on: IMDb | TMDb

The Interrupters (2011)

Directed by Steve James

Documentary

Most recently watched by sensoria, sleestakk, noahphex

Overview

The Interrupters tells the moving and surprising stories of three Violence Interrupters — former gang members who try to protect their Chicago communities from the violence they once caused.

Rated NR | Length 125 minutes

Actors

Ameena Matthews | Tio Hardiman | Cobe Williams | Gary Slutkin | Caprysha Anderson | Eddie Bocanegra | "Lil' Mikey" Davis

Viewing Notes

Easily one of the best documentaries I’ve seen in a long time, The Interrupters hits close to home as it’s about gang violence in Chicago, my adopted home (even though I live in the suburbs now, and even when I did live in Chicago, it was far from the areas in the film).

It’s pretty amazing to see people act so selflessly and put themselves in harm’s way to positively effect the lives of others and attempt to turn their communities around.

Comments

No comments yet. Log in and be the first!

  BENCHMARKS  
Loading Time: Base Classes  0.0017
Controller Execution Time ( Members / Movie Detail )  0.0500
Total Execution Time  0.0517
  GET DATA  
No GET data exists
  MEMORY USAGE  
531,560 bytes
  POST DATA  
No POST data exists
  URI STRING  
members/sensoria/movie_detail/7490
  CLASS/METHOD  
members/movie_detail
  DATABASE:  movielogr_dev (Members:$db)   QUERIES: 16 (0.0180 seconds)  (Hide)
0.0002  
SELECT GET_LOCK('5c3f544f3fdb281ecf027db0b3b86cad', 300) AS ci_session_lock ?>
0.0003  
SELECT `data`
FROM `ml_sessions`
WHERE `id` = '82af11c5197106a2847cf0fe7c33ff2a515c245f'
AND `ip_address` = '216.73.216.6' ?>
0.0126  
SELECT `username`, `user_id`
FROM `ml_users`
WHERE `username` = 'sensoria'
 LIMIT 1 ?>
0.0006  
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` = 7490
AND `MV`.`user_id` = 1
 LIMIT 1 ?>
0.0003  
SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 1
 LIMIT 1 ?>
0.0002  
SET SESSION group_concat_max_len = 12288 ?>
0.0020  
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` = 7490
AND `MV`.`user_id` = 1
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` = 7490 ?>
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` = 7490 ?>
0.0002  
SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 1
 LIMIT 1 ?>
0.0001  
SELECT `rating_id`
FROM `ml_movies` `MV`
WHERE `MV`.`user_id` = 1
AND `MV`.`movie_id` = 7490
 LIMIT 1 ?>
0.0001  
SELECT `star_rating`
FROM `ml_movie_ratings_ten_star` `MR`
WHERE `MR`.`rating_id` = '21'
 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` = 1
AND `MV`.`movie_id` = 7490
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` = 7490 ?>
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` = 3088
ORDER BY `date_viewed` DESC
 LIMIT 10 ?>
  HTTP HEADERS  (Show)
  SESSION DATA  (Show)
  CONFIG VARIABLES  (Show)