大きなテーブルのクエリが非常に遅い（左結合テーブルが2つある）

Question

このクエリを以下のように最適化する方法をもっと早くすることができますか。とにかく、それは非常に多くの行のために遅く動作します。同じ3つのテーブルのインデックスでは、非常に大きなテーブルを高速に検索することはできません。どうかアドバイスや改善をいただければ幸いです。ありがとうございました。

SET @timeset := 0; 
SET @timeset2 := 0; 
SET @previousDay := 0; 
SET @previousDay2 := 0; 
SET @datefrom = cast('2017-05-01 00:00:00' as datetime); 
SET @dateto = cast('2017-05-15 00:00:00' as datetime); 

SET @rownumFirstTable := 0; 
SET @rownumSecondTable = 0; 

SELECT 

    `hour_time_local`, 
    DAY(`hour_time_local`) AS `day`, 
    IF(DAY(`hour_time_local`) != @previousDay, @timeset:=0, @timeset:=1) AS ``, 
    @rownumFirstTable := IF(@timeset != 0, @rownumFirstTable :=@rownumFirstTable +1, @rownumFirstTable :=1) AS `row_first_table`, 
    @previousDay := DAY(`hour_time_local`), 

    `low_speed` AS `LOW_SPEED_15_PERCENTILE`, 
    `day_second_table`, 
    `LOW_SPEED_15_PERCENTILE_INDEX`, 

    `row_second_table`, 
    `high_speed`, 
    `hour_time_second_table`, 
    `day_second_table`, 
    `HIGH_SPEED_15_PERCENTILE_INDEX` 

FROM 
    t.table_speed AS `first_table` 

LEFT JOIN 
(
    SELECT 
     COUNT(low_speed) AS `count_low_speed`, 
     CEIL((15/100) * COUNT(low_speed)) AS `LOW_SPEED_15_PERCENTILE_INDEX`, 
     CEIL((15/100) * COUNT(high_speed)) AS `HIGH_SPEED_15_PERCENTILE_INDEX`, 
     DAY(`hour_time_local`) AS `day_second_table` 

    FROM t.table_speed 
    WHERE (`hour_time_local` >= @datefrom) AND (`hour_time_local` < @dateto) AND (`traffic_id` = 'XXXXXXXX') 
    GROUP BY DAY(`hour_time_local`), MONTH(`hour_time_local`), YEAR(`hour_time_local`) 
) AS `second_table` ON `id` = `first_table`.`id` 

LEFT JOIN 
(
    SELECT 
     DAY(`hour_time_local`) AS `day_second_table`, 
     @timeset2 AS `timeset`, 
     IF(DAY(`hour_time_local`) != @previousDay2, @timeset2:=0, @timeset2:=1) AS ``, 
     @previousDay2 := DAY(`hour_time_local`), 
     IF(@timeset2 != 0, @rownumSecondTable:=@rownumSecondTable+1, @rownumSecondTable:=1), 
     @rownumSecondTableAS `row_second_table`, 
     `hour_time_local` AS `hour_time_second_table`, 
     `ht_high_speed` AS `high_speed` 

    FROM t.table_speed, (SELECT @rownumSecondTableAS :=0) AS `third_table` 
    WHERE (`hour_time_local` >= @datefrom) AND (`hour_time_local` < @dateto) AND (`traffic_id` = '703170016-1') AND (`ht_high_speed` > 0) 
) AS `third_table` ON `id` = `first_table`.`id` 

WHERE (`hour_time_local` >= @datefrom) AND (`hour_time_local` < @dateto) AND (`traffic_id` = '703170016-1') AND (`low_speed` > 0) 

HAVING 
(
    ( 
     (`day` = `day_first_table`) AND (`day` = `day_second_table`) AND ((`row_first_table` = `LOW_SPEED_15_PERCENTILE_INDEX`) AND (`row_second_table` = `HIGH_SPEED_15_PERCENTILE_INDEX`)) 
    ) 
) 

ORDER BY `hour_time_local` ASC; 

Answer 1

最初に、上記の問題の解決策を見つけました。改善されたクエリは、以下で説明するクエリよりもはるかに高速です。 2番目に私は最後のヘルプに感謝していますが、改善、助けはここで歓迎されるでしょう。

SET @timeset := 0; 
SET @timeset2 := 0; 
SET @previousDay := 0; 
SET @previousDay2 := 0; 
SET @datefrom = cast('2017-05-01 00:00:00' as datetime); 
SET @dateto = cast('2017-05-15 00:00:00' as datetime); 
SET @rownum_lt := 0; 
SET @rownum_ht := 0; 

SELECT 

    IF(DAY(`hour_time_local`) != @previousDay, @timeset:=0, @timeset:=1) AS ``, 
    @rownum_lt := IF(@timeset != 0, @rownum_lt:=@rownum_lt+1, @rownum_lt:=1) AS `row_low_speed`, 
    @previousDay := DAY(`hour_time_local`) AS ``, 

    `hour_time_local` AS `lt_hour_time_local`, 
    `hour_time_local_b`, 

    `LOW_SPEED_15_PERCENTILE_INDEX`, 
    `low_speed` AS `low_speed_a`, 

    `row_high_speed`, 
    `ht_hour_time_local`, 
    `HIGH_SPEED_15_PERCENTILE_INDEX`, 
    `high_speed` 

FROM unicam_stats.traffic_id_hour_stats_measured AS `hs` 

CROSS JOIN 
(
    SELECT 
     `hour_time_local` AS `ht_hour_time_local`, 
     `high_speed` AS `high_speed_ref`, 
     IF(DAY(`hour_time_local`) != @previousDay2, @timeset2:=0, @timeset2:=1) AS `b`, 
     @rownum_ht := IF(@timeset2 != 0, @rownum_ht:=@rownum_ht+1, @rownum_ht:=1) AS `row_high_speed`, 
     @previousDay2 := DAY(`hour_time_local`) AS `a`, 
     `hour_time_local_a`, 
     `HIGH_SPEED_15_PERCENTILE_INDEX` 

    FROM unicam_stats.traffic_id_hour_stats_measured AS `ht_hs` 

    LEFT JOIN 
    (
     SELECT 
      `hour_time_local` AS `hour_time_local_a`, 
      CEIL((15/100) * COUNT(high_speed)) AS `HIGH_SPEED_15_PERCENTILE_INDEX` 

     FROM unicam_stats.traffic_id_hour_stats_measured AS `ht_a` 
     WHERE (`hour_time_local` >= @datefrom) AND (`hour_time_local` < @dateto) AND (`traffic_id` = '703170016-1') 
     GROUP BY DAY(`hour_time_local`), MONTH(`hour_time_local`), YEAR(`hour_time_local`) 
    ) AS `ht_a` ON `id` = `ht_hs`.`id` 

    WHERE (`hour_time_local` >= @datefrom) AND (`hour_time_local` < @dateto) AND (`traffic_id` = '703170016-1') AND (`high_speed` > 0) 
    GROUP BY `hour_time_local`, `hour_time_local_a` 
    HAVING (`row_high_speed` = `HIGH_SPEED_15_PERCENTILE_INDEX` AND DAY(`ht_hour_time_local`) = DAY(`hour_time_local_a`)) 

) AS `ht` 

LEFT JOIN 
(
    SELECT 
     `hour_time_local` AS `hour_time_local_b`, 
     CEIL((15/100) * COUNT(low_speed)) AS `LOW_SPEED_15_PERCENTILE_INDEX` 

    FROM unicam_stats.traffic_id_hour_stats_measured AS `lt_a` 
    WHERE (`hour_time_local` >= @datefrom) AND (`hour_time_local` < @dateto) AND (`traffic_id` = '703170016-1') 
    GROUP BY DAY(`hour_time_local`), MONTH(`hour_time_local`), YEAR(`hour_time_local`) 

) AS `lt_a` ON `id` = `hs`.`id` AND `traffic_id` = `hs`.`traffic_id` 


WHERE (`hour_time_local` >= @datefrom) AND (`hour_time_local` < @dateto) AND (`traffic_id` = '703170016-1') AND (`low_speed` > 0) 
HAVING (`row_low_speed` = `LOW_SPEED_15_PERCENTILE_INDEX` AND DAY(`lt_hour_time_local`) = DAY(`hour_time_local_b`) AND DAY(`ht_hour_time_local`) = DAY(`hour_time_local_b`)) 
ORDER BY `hour_time_local`, `hour_time_local_b`, `ht_hour_time_local`