SELECT ems.vin AS vincode, count(*) AS `count` FROM autost_auction.epms_order ems WHERE ems.created_time >= DATE_SUB(NOW(), INTERVAL 90 DAY) and ems.created_time <= NOW() GROUP BY ems.vin；优化这条SQL，使created_time字段的索引生效

为了使 `created_time` 字段的索引生效，可以进行以下优化步骤：

1. 索引创建：首先，确保 `created_time` 字段已经创建了索引。如果没有创建索引，可以使用以下语句创建一个索引：

   CREATE INDEX idx_created_time ON autost_auction.epms_order (created_time);

2. 查询优化：优化查询语句以利用索引。以下是优化后的查询语句：

   SELECT
       ems.vin AS vincode,
       COUNT(*) AS `count` 
   FROM
       autost_auction.epms_order ems 
   WHERE
       ems.created_time >= DATE_SUB(NOW(), INTERVAL 90 DAY) AND ems.created_time <= NOW() 
   GROUP BY
       ems.vin;

注意，在 `WHERE` 子句中，将 `ems.created_time` 与常量进行比较，以使索引得到利用。同时，确保在 `GROUP BY` 子句中只包含需要分组的列。

以上是优化 SQL 查询的常见步骤。但请注意，优化效果可能因数据库的特定配置和数据量而有所不同。在进行任何更改之前，请确保在测试环境中进行彻底测试。

相关问题

帮我优化下这个sql ： SELECT t4.vin, t3.msg_id AS trip_id, t3.trip_start_time, t4.switch_value AS has_trip FROM ( SELECT * FROM dds.dwd_driving_calendar t1 WHERE t1.vin = 'LSJA24396MS179029' AND 1681745400001 > t1.trip_start_time AND 1681745400001 < t1.trip_end_time ) t3 LEFT JOIN ( SELECT * FROM dds.vehicle_journey_switch_history t2 WHERE t2.vin IN ( 'LSJA24396MS179029' ) ) t4 ON t3.vin = t4.vin AND t4.switch_key = 'vehicle_journey_data' AND '2023-04-17 23:30:00' > t4.create_time AND '2023-04-17 23:30:00' < t4.update_time

可以尝试优化以下几个方面：

1. 使用EXISTS替换LEFT JOIN

可以使用EXISTS来代替LEFT JOIN进行连接查询，因为EXISTS在查询到一条匹配的数据后就会停止，而LEFT JOIN需要查询完整个表再返回结果。

SELECT t3.vin, t3.msg_id AS trip_id, t3.trip_start_time, 
       t4.switch_value AS has_trip 
FROM dds.dwd_driving_calendar t3 
WHERE t3.vin = 'LSJA24396MS179029' 
  AND 1681745400001 > t3.trip_start_time 
  AND 1681745400001 < t3.trip_end_time
  AND EXISTS (
      SELECT 1 
      FROM dds.vehicle_journey_switch_history t4 
      WHERE t3.vin = t4.vin 
        AND t4.switch_key = 'vehicle_journey_data' 
        AND '2023-04-17 23:30:00' > t4.create_time 
        AND '2023-04-17 23:30:00' < t4.update_time
    )

2. 添加索引

在vin、trip_start_time、trip_end_time、switch_key、create_time和update_time列上添加索引，可以加速查询。

3. 不要使用SELECT *

在子查询中不要使用SELECT *，而是明确指定需要查询的列，可以减少不必要的数据读取和传输，提高查询效率。例如：

SELECT vin, msg_id AS trip_id, trip_start_time
FROM dds.dwd_driving_calendar 
WHERE vin = 'LSJA24396MS179029' 
  AND 1681745400001 > trip_start_time 
  AND 1681745400001 < trip_end_time

SELECT vin, switch_value
FROM dds.vehicle_journey_switch_history
WHERE vin IN ('LSJA24396MS179029') 
  AND switch_key = 'vehicle_journey_data' 
  AND '2023-04-17 23:30:00' > create_time 
  AND '2023-04-17 23:30:00' < update_time

WITH temp AS ( SELECT * FROM doris_fdbfault_QBMonitor_OA WHERE vin IN ( SELECT DISTINCT vin FROM vin_packID_pairing_v2 WHERE SUBSTR(packID, 6, 3) = 'VB6' ) ), result_detail AS ( SELECT day, vin, Flag_RositivetoGroundISOR, Counts_RositivetoGroundISOR, ST_RositivetoGroundISOR, ET_RositivetoGroundISOR, Flag_NegativetoGroundISOR, Counts_NegativetoGroundISOR, ST_NegativetoGroundISOR, ET_NegativetoGroundISOR FROM temp t1 WHERE day >= '2023-07-01' AND vin NOT IN ( SELECT DISTINCT vin FROM temp t2 WHERE t2.day < t1.day ) ) SELECT COUNT(*) FROM result_detail WHERE day = '2023-07-01'; 帮忙修改这段代码

根据你提供的代码，我注意到其中一个问题是在子查询中使用了相同的表别名 `t1`，这会导致语法错误。此外，你还可以进行一些代码优化来提高查询性能。

以下是修改后的代码：

WITH temp AS (
  SELECT *
  FROM doris_fdbfault_QBMonitor_OA
  WHERE vin IN (
    SELECT DISTINCT vin
    FROM vin_packID_pairing_v2
    WHERE SUBSTR(packID, 6, 3) = 'VB6'
  )
),
result_detail AS (
  SELECT t1.day, t1.vin, t1.Flag_RositivetoGroundISOR, t1.Counts_RositivetoGroundISOR, t1.ST_RositivetoGroundISOR, t1.ET_RositivetoGroundISOR,
         t1.Flag_NegativetoGroundISOR, t1.Counts_NegativetoGroundISOR, t1.ST_NegativetoGroundISOR, t1.ET_NegativetoGroundISOR
  FROM temp t1
  LEFT JOIN temp t2 ON t2.vin = t1.vin AND t2.day < t1.day
  WHERE t1.day >= '2023-07-01' AND t2.vin IS NULL
)
SELECT COUNT(*)
FROM result_detail
WHERE day = '2023-07-01';

在修改后的代码中，我将第一个子查询中的表别名 `t1` 修改为了 `t2`，以便与外部查询的别名区分开来。另外，我还将子查询中的 `NOT IN` 子句改为了使用左连接 `LEFT JOIN` 和 `IS NULL` 的方式来过滤出不满足条件的行，这样可以提高查询性能。

请注意，这只是根据你提供的代码进行的修改，如果还有其他问题，请提供更多详细信息，我将尽力帮助你。