Cette requête obtient une liste des publications créées par les personnes que vous suivez. Vous pouvez suivre un nombre illimité de personnes, mais la plupart des personnes suivent <1000 autres.
Avec ce style de requête, l'optimisation évidente serait de mettre en cache les "Post"
identifiants, mais malheureusement, je n'ai pas le temps pour le moment.
EXPLAIN ANALYZE SELECT
"Post"."id",
"Post"."actionId",
"Post"."commentCount",
...
FROM
"Posts" AS "Post"
INNER JOIN "Users" AS "user" ON "Post"."userId" = "user"."id"
LEFT OUTER JOIN "ActivityLogs" AS "activityLog" ON "Post"."activityLogId" = "activityLog"."id"
LEFT OUTER JOIN "WeightLogs" AS "weightLog" ON "Post"."weightLogId" = "weightLog"."id"
LEFT OUTER JOIN "Workouts" AS "workout" ON "Post"."workoutId" = "workout"."id"
LEFT OUTER JOIN "WorkoutLogs" AS "workoutLog" ON "Post"."workoutLogId" = "workoutLog"."id"
LEFT OUTER JOIN "Workouts" AS "workoutLog.workout" ON "workoutLog"."workoutId" = "workoutLog.workout"."id"
WHERE
"Post"."userId" IN (
201486,
1825186,
998608,
340844,
271909,
308218,
341986,
216893,
1917226,
... -- many more
)
AND "Post"."private" IS NULL
ORDER BY
"Post"."createdAt" DESC
LIMIT 10;
Rendements:
Limit (cost=3.01..4555.20 rows=10 width=2601) (actual time=7923.011..7973.138 rows=10 loops=1)
-> Nested Loop Left Join (cost=3.01..9019264.02 rows=19813 width=2601) (actual time=7923.010..7973.133 rows=10 loops=1)
-> Nested Loop Left Join (cost=2.58..8935617.96 rows=19813 width=2376) (actual time=7922.995..7973.063 rows=10 loops=1)
-> Nested Loop Left Join (cost=2.15..8821537.89 rows=19813 width=2315) (actual time=7922.984..7961.868 rows=10 loops=1)
-> Nested Loop Left Join (cost=1.71..8700662.11 rows=19813 width=2090) (actual time=7922.981..7961.846 rows=10 loops=1)
-> Nested Loop Left Join (cost=1.29..8610743.68 rows=19813 width=2021) (actual time=7922.977..7961.816 rows=10 loops=1)
-> Nested Loop (cost=0.86..8498351.81 rows=19813 width=1964) (actual time=7922.972..7960.723 rows=10 loops=1)
-> Index Scan using posts_createdat_public_index on "Posts" "Post" (cost=0.43..8366309.39 rows=20327 width=261) (actual time=7922.869..7960.509 rows=10 loops=1)
Filter: ("userId" = ANY ('{201486,1825186,998608,340844,271909,308218,341986,216893,1917226, ... many more ...}'::integer[]))
Rows Removed by Filter: 218360
-> Index Scan using "Users_pkey" on "Users" "user" (cost=0.43..6.49 rows=1 width=1703) (actual time=0.005..0.006 rows=1 loops=10)
Index Cond: (id = "Post"."userId")
-> Index Scan using "ActivityLogs_pkey" on "ActivityLogs" "activityLog" (cost=0.43..5.66 rows=1 width=57) (actual time=0.107..0.107 rows=0 loops=10)
Index Cond: ("Post"."activityLogId" = id)
-> Index Scan using "WeightLogs_pkey" on "WeightLogs" "weightLog" (cost=0.42..4.53 rows=1 width=69) (actual time=0.001..0.001 rows=0 loops=10)
Index Cond: ("Post"."weightLogId" = id)
-> Index Scan using "Workouts_pkey" on "Workouts" workout (cost=0.43..6.09 rows=1 width=225) (actual time=0.001..0.001 rows=0 loops=10)
Index Cond: ("Post"."workoutId" = id)
-> Index Scan using "WorkoutLogs_pkey" on "WorkoutLogs" "workoutLog" (cost=0.43..5.75 rows=1 width=61) (actual time=1.118..1.118 rows=0 loops=10)
Index Cond: ("Post"."workoutLogId" = id)
-> Index Scan using "Workouts_pkey" on "Workouts" "workoutLog.workout" (cost=0.43..4.21 rows=1 width=225) (actual time=0.004..0.004 rows=0 loops=10)
Index Cond: ("workoutLog"."workoutId" = id)
Total runtime: 7974.524 ms
Comment cela peut-il être optimisé pour le moment?
J'ai les index pertinents suivants:
-- Gets used
CREATE INDEX "posts_createdat_public_index" ON "public"."Posts" USING btree("createdAt" DESC) WHERE "private" IS null;
-- Don't get used
CREATE INDEX "posts_userid_fk_index" ON "public"."Posts" USING btree("userId");
CREATE INDEX "posts_following_index" ON "public"."Posts" USING btree("userId", "createdAt" DESC) WHERE "private" IS null;
Cela nécessite peut-être un grand indice composite partiel avec createdAt
et userId
où private IS NULL
?