Movielogr

movie poster

Rating: stars

Tags

hbo

Seen 1 time

Seen on: 01/09/2011

View on: IMDb | TMDb

Deadly Impact (2010)

Directed by Robert Kurtzman

Action

Most recently watched by jenerator

Overview

Deadly Impact follows hard-nosed cop Thomas Armstrong (Flanery) whose life was shattered when he became the helpless target of a mastermind murderer. Returning home after a much-needed break, Armstrong joins the FBI to seek revenge and help track down the same killer that threatened his existence, however this time the assassin is back to terrorize not just a single person, but the entire city.

Length 96 minutes

Actors

Joe Pantoliano | Amanda Wyss | Fredrick Lopez | Luce Rains | Sean Patrick Flanery | David House | John Koyama | Greg Serano | Carmen Serano | Mike Miller | Mike Seal | Kevin Wiggins | Kieran Sequoia | James Tarwater | Julianne Flores | Michelle Greathouse

Comments

No comments yet. Log in and be the first!

  BENCHMARKS  
Loading Time: Base Classes  0.0016
Controller Execution Time ( Members / Movie Detail )  0.0280
Total Execution Time  0.0296
  GET DATA  
No GET data exists
  MEMORY USAGE  
537,944 bytes
  POST DATA  
No POST data exists
  URI STRING  
members/jenerator/movie_detail/6470
  CLASS/METHOD  
members/movie_detail
  DATABASE:  movielogr_dev (Members:$db)   QUERIES: 17 (0.0073 seconds)  (Hide)
0.0004   SELECT 1
FROM 
`ml_sessions`
WHERE `id` = '52317da4e39c51b387519414712094fbfb172ec1'
AND `ip_address` = '216.73.216.111' 
0.0002   SELECT GET_LOCK('b453d8f8e4d8a091b32aca6826ee28fb'300) AS ci_session_lock 
0.0002   SELECT `data`
FROM `ml_sessions`
WHERE `id` = '52317da4e39c51b387519414712094fbfb172ec1'
AND `ip_address` = '216.73.216.111' 
0.0004   SELECT `username`, `user_id`
FROM `ml_users`
WHERE `username` = 'jenerator'
 
LIMIT 1 
0.0004   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` = 6470
AND `MV`.`user_id` = 61
 LIMIT 1 
0.0005   SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 61
 LIMIT 1 
0.0002   SET SESSION group_concat_max_len 12288 
0.0027   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_five_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` = 6470
AND `MV`.`user_id` = 61
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` = 6470 
0.0003   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` = 6470 
0.0002   SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 61
 LIMIT 1 
0.0002   SELECT `rating_id`
FROM `ml_movies` `MV`
WHERE `MV`.`user_id` = 61
AND `MV`.`movie_id` = 6470
 LIMIT 1 
0.0002   SELECT `star_rating`
FROM `ml_movie_ratings_five_star` `MR`
WHERE `MR`.`rating_idIS NULL
 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` = 61
AND `MV`.`movie_id` = 6470
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` = 6470 
0.0003   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` = 3795
ORDER BY 
`date_viewedDESC
 LIMIT 10 
  HTTP HEADERS  (Show)
  SESSION DATA  (Show)
  CONFIG VARIABLES  (Show)