我试图让这个查询运行得更快。似乎按质量字段排序才是真正让它慢下来的原因（该表大约有500万行）-也许有一个索引可以用来做这个？
查询：
SELECT "connectr_twitterpassage"."id", "connectr_twitterpassage"."third_party_id", "connectr_twitterpassage"."third_party_created", "connectr_twitterpassage"."source", "connectr_twitterpassage"."text", "connectr_twitterpassage"."author", "connectr_twitterpassage"."raw_data", "connectr_twitterpassage"."retweet_count", "connectr_twitterpassage"."favorited_count", "connectr_twitterpassage"."lang", "connectr_twitterpassage"."location", "connectr_twitterpassage"."author_followers_count", "connectr_twitterpassage"."is_retweet", "connectr_twitterpassage"."url", "connectr_twitterpassage"."author_fk_id", "connectr_twitterpassage"."quality", "connectr_twitterpassage"."is_top_tweet", "connectr_twitterpassage"."created", "connectr_twitterpassage"."modified"
FROM "connectr_twitterpassage"
INNER JOIN "connectr_twitterpassage_words" ON ("connectr_twitterpassage"."id" = "connectr_twitterpassage_words"."twitterpassage_id")
WHERE "connectr_twitterpassage_words"."word_id" = 18974807
ORDER BY "connectr_twitterpassage"."quality"
DESC LIMIT 100
下面是解释分析：http://explain.depesz.com/s/7zb
以及表定义：
\d connectr_twitterpassage
Column | Type | Modifiers
------------------------+--------------------------+----------------------------------------------------------------------
id
| integer | not null default nextval('connectr_twitterpassage_id_seq'::regclass)
third_party_id | character varying(10000) | not null
source | character varying(10000) | not null
text | character varying(10000) | not null
author | character varying(10000) | not null
raw_data | character varying(10000) | not null
created | timestamp with time zone | not null
modified | timestamp with time zone | not null
third_party_created | timestamp with time zone |
retweet_count | integer | not null
favorited_count | integer | not null
lang | character varying(10000) | not null
location | character varying(10000) | not null
author_followers_count | integer | not null
is_retweet | boolean | not null
url | character varying(10000) | not null
author_fk_id | integer |
quality | bigint |
is_top_tweet | boolean | not null
Indexes:
"connectr_passage_pkey" PRIMARY KEY, btree (id)
"connectr_twitterpassage_third_party_id_uniq" UNIQUE CONSTRAINT, btree (third_party_id)
"connectr_passage_author_followers_count" btree (author_followers_count)
"connectr_passage_favorited_count" btree (favorited_count)
"connectr_passage_retweet_count" btree (retweet_count)
"connectr_passage_source" btree (source)
"connectr_passage_source_like" btree (source varchar_pattern_ops)
"connectr_passage_third_party_id" btree (third_party_id)
"connectr_passage_third_party_id_like" btree (third_party_id varchar_pattern_ops)
"connectr_twitterpassage_author_fk_id" btree (author_fk_id)
"connectr_twitterpassage_created" btree (created)
"connectr_twitterpassage_is_top_tweet" btree (is_top_tweet)
"connectr_twitterpassage_quality" btree (quality)
"connectr_twitterpassage_third_party_created" btree (third_party_created)
"id_to_quality_sorted" btree (id, quality DESC NULLS LAST)
Foreign-key constraints:
"author_fk_id_refs_id_074720a5" FOREIGN KEY (author_fk_id) REFERENCES connectr_twitteruser(id) DEFERRABLE INITIALLY DEFERRED
Referenced by:
TABLE "connectr_passageviewevent" CONSTRAINT "passage_id_refs_id_892b36a6" FOREIGN KEY (passage_id) REFERENCES connectr_twitterpassage(id) DEFERRABLE INITIALLY DEFERRED
TABLE "connectr_connection" CONSTRAINT "twitter_from_id_refs_id_8adbab24" FOREIGN KEY (twitter_from_id) REFERENCES connectr_twitterpassage(id) DEFERRABLE INITIALLY DEFERRED
TABLE "connectr_connection" CONSTRAINT "twitter_to_id_refs_id_8adbab24" FOREIGN KEY (twitter_to_id) REFERENCES connectr_twitterpassage(id) DEFERRABLE INITIALLY DEFERRED
TABLE "connectr_twitterpassage_words" CONSTRAINT "twitterpassage_id_refs_id_720f772f" FOREIGN KEY (twitterpassage_id) REFERENCES connectr_twitterpassage(id) DEFERRABLE INITIALLY DEFERRED
connectr=# \d connectr_twitterpassage_words
Table "public.connectr_twitterpassage_words"
Column | Type | Modifiers
-------------------+---------+----------------------------------------------------------------------------
id | integer | not null default nextval('connectr_twitterpassage_words_id_seq'::regclass)
twitterpassage_id | integer | not null
word_id | integer | not null
Indexes:
"connectr_twitterpassage_words_pkey" PRIMARY KEY, btree (id)
"connectr_twitterpassage_twitterpassage_id_613c80271f09fba8_uniq" UNIQUE CONSTRAINT, btree (twitterpassage_id, word_id)
"connectr_twitterpassage_words_twitterpassage_id" btree (twitterpassage_id)
"connectr_twitterpassage_words_word_id" btree (word_id)
"word_to_twitterpassage_id" btree (word_id, twitterpassage_id)
Foreign-key constraints:
"twitterpassage_id_refs_id_720f772f" FOREIGN KEY (twitterpassage_id) REFERENCES connectr_twitterpassage(id) DEFERRABLE INITIALLY DEFERRED
"word_id_refs_id_64f49629" FOREIGN KEY (word_id) REFERENCES connectr_word(id) DEFERRABLE INITIALLY DEFERRED
connectr=# \d connectr_word
Table "public.connectr_word"
Column | Type | Modifiers
---------------------+--------------------------+------------------------------------------------------------
id | integer | not null default nextval('connectr_word_id_seq'::regclass)
word | character varying(10000) | not null
created | timestamp with time zone | not null
modified | timestamp with time zone | not null
frequency | double precision |
is_username | boolean | not null
is_hashtag | boolean | not null
cloud_eligible | boolean | not null
passage_count | integer |
avg_quality | double precision |
last_twitter_search | timestamp with time zone |
cloud_approved | boolean | not null
display_word | character varying(10000) | not null
is_trend | boolean | not null
Indexes:
"connectr_word_pkey" PRIMARY KEY, btree (id)
"connectr_word_word_uniq" UNIQUE CONSTRAINT, btree (word)
"connectr_word_avg_quality" btree (avg_quality)
"connectr_word_cloud_eligible" btree (cloud_eligible)
"connectr_word_last_twitter_search" btree (last_twitter_search)
"connectr_word_passage_count" btree (passage_count)
"connectr_word_word" btree (word)
Referenced by:
TABLE "connectr_passageviewevent" CONSTRAINT "source_word_id_refs_id_178d46eb" FOREIGN KEY (source_word_id) REFERENCES connectr_word(id) DEFERRABLE INITIALLY DEFERRED
TABLE "connectr_wordmatchrewardevent" CONSTRAINT "tapped_word_id_refs_id_c2ffb369" FOREIGN KEY (tapped_word_id) REFERENCES connectr_word(id) DEFERRABLE INITIALLY DEFERRED
TABLE "connectr_connection" CONSTRAINT "word_id_refs_id_00cccde2" FOREIGN KEY (word_id) REFERENCES connectr_word(id) DEFERRABLE INITIALLY DEFERRED
TABLE "connectr_twitterpassage_words" CONSTRAINT "word_id_refs_id_64f49629" FOREIGN KEY (word_id) REFERENCES connectr_word(id) DEFERRABLE INITIALLY DEFERRED
最佳答案
看一下explain输出，排序只需要很少的时间。它正在收集需要排序的数据，这需要时间。
你一定是花了点时间在磁盘上。如果可以更好地缓存数据，那么使用相同的查询可以大大加快速度。
否则，您最好的选择可能是通过将quality字段添加到connectr_twitterpassession_words表并在其上建立索引（word_id，quality，…）来取消数据的规格化