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性能优化之mybatis实现接口的批量查询,减少数据库的查询消耗

时间:2019-06-11 11:01:24      阅读:681      评论:0      收藏:0      [点我收藏+]
    <select id="selectByTime" resultType="com.neo.xnol.api.activity.dto.ActivityMqmsgDTO">
        SELECT
            id,
            eventType,
            eventId,
            userId,
            userName,
            content,
            msgStatus,
            retryCount,
            errorDetails,
            createTime,
            updateTime,
            msgVersion,
            sysVersion
        FROM
            t_activity_mqmsg
        WHERE
            userId= #{userId}
        AND
            eventType IN
            <foreach collection="eventTypeList" index="index" item="item" open="(" separator="," close=")">
                  #{item}
            </foreach>
        AND
            createTime &gt;= #{beginTime}
        AND
            createTime &lt;= #{endTime}
        ORDER BY
            createTime
    </select>

 

    <select id="findActivityInfoListByCategoryId" resultMap="BaseResultMap" >
        SELECT
            a.*
        FROM  t_activity_info a
        WHERE
        a.categoryId in
        <foreach collection="list" item="categoryId" open="(" close=")"
            separator=",">
            #{categoryId}
        </foreach>
        and a.isDelete = 0
        and a.`endTime` > now()
        <if test="organizationId != null and organizationId != 3">
            AND a.organizationId = #{organizationId,jdbcType=INTEGER}
        </if>
        ORDER BY a.createTime DESC
    </select>

 

  <select id="selectOneByRewardType" resultMap="BaseResultMap">
    select w.* 
      from t_lucky_winning w 
     inner join t_lucky_activity a 
        on w.luckyId = a.luckyId and a.activityId = #{activityId,jdbcType=INTEGER}
     inner join t_lucky_reward r on w.rewardId = r.id
     where r.rewardId in(
     <foreach collection="rewardIds" item="rewardId" separator=",">
         #{rewardId,jdbcType=INTEGER}
     </foreach>)
     order by w.luckytime desc
     limit 1
  </select>

 

性能优化之mybatis实现接口的批量查询,减少数据库的查询消耗

原文:https://www.cnblogs.com/qmfsun/p/11002258.html

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