大模型分析结果展示
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spllzh
309
src/main/resources/mapper/CpaBrandScoreStatisticsMapper.xml
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309
src/main/resources/mapper/CpaBrandScoreStatisticsMapper.xml
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<?xml version="1.0" encoding="UTF-8"?>
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<!DOCTYPE mapper PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN" "http://mybatis.org/dtd/mybatis-3-mapper.dtd">
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<mapper namespace="com.rj.mapper.CpaBrandScoreStatisticsMapper">
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<!-- 通用查询映射结果 -->
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<resultMap id="BaseResultMap" type="com.rj.entity.CpaBrandScoreStatistics">
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<id column="id" property="id" />
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<result column="dealer_code" property="dealerCode" />
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<result column="dealer_name" property="dealerName" />
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<result column="big_area" property="bigArea" />
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<result column="statistics_date" property="statisticsDate" />
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<result column="statistics_type" property="statisticsType" />
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<result column="total_records" property="totalRecords" />
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<result column="total_score" property="totalScore" />
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<result column="average_score_percentage" property="averageScorePercentage" />
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<result column="positive_count" property="positiveCount" />
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<result column="neutral_count" property="neutralCount" />
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<result column="negative_count" property="negativeCount" />
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<result column="positive_rate" property="positiveRate" />
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<result column="neutral_rate" property="neutralRate" />
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<result column="negative_rate" property="negativeRate" />
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<result column="earliest_interaction" property="earliestInteraction" />
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<result column="latest_interaction" property="latestInteraction" />
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<result column="created_at" property="createdAt" />
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<result column="created_by" property="createdBy" />
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<result column="updated_at" property="updatedAt" />
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<result column="updated_by" property="updatedBy" />
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<result column="is_deleted" property="isDeleted" />
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</resultMap>
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<!-- 通用查询结果列 -->
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<sql id="Base_Column_List">
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id, dealer_code, dealer_name, big_area, statistics_date, statistics_type,
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total_records, total_score, average_score_percentage,
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positive_count, neutral_count, negative_count,
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positive_rate, neutral_rate, negative_rate,
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earliest_interaction, latest_interaction,
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created_at, created_by, updated_at, updated_by, is_deleted
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</sql>
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<!-- 根据经销商编码和统计类型查询统计数据 -->
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<select id="selectByDealerCodeAndType" resultMap="BaseResultMap">
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SELECT <include refid="Base_Column_List" />
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FROM cpa_brandcore_statistics
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WHERE is_deleted = 0
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<if test="dealerCode != null and dealerCode != ''">
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AND dealer_code = #{dealerCode}
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</if>
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<if test="statisticsType != null and statisticsType != ''">
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AND statistics_type = #{statisticsType}
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</if>
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ORDER BY statistics_date DESC, average_score_percentage DESC
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</select>
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<!-- 根据大区和统计类型查询统计数据 -->
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<select id="selectByBigAreaAndType" resultMap="BaseResultMap">
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SELECT <include refid="Base_Column_List" />
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FROM cpa_brandcore_statistics
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WHERE is_deleted = 0
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<if test="bigArea != null and bigArea != ''">
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AND big_area = #{bigArea}
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</if>
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<if test="statisticsType != null and statisticsType != ''">
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AND statistics_type = #{statisticsType}
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</if>
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ORDER BY statistics_date DESC, average_score_percentage DESC
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</select>
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<!-- 根据日期范围查询统计数据 -->
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<select id="selectByDateRange" resultMap="BaseResultMap">
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SELECT <include refid="Base_Column_List" />
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FROM cpa_brandcore_statistics
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WHERE is_deleted = 0
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<if test="startDate != null">
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AND statistics_date >= #{startDate}
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</if>
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<if test="endDate != null">
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AND statistics_date <= #{endDate}
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</if>
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<if test="statisticsType != null and statisticsType != ''">
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AND statistics_type = #{statisticsType}
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</if>
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ORDER BY statistics_date DESC, average_score_percentage DESC
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</select>
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<!-- 获取经销商排名统计 -->
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<select id="selectDealerRanking" resultType="java.util.Map">
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SELECT
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dealer_code,
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dealer_name,
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big_area,
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SUM(total_records) as total_records,
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SUM(total_score) as total_score,
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ROUND(AVG(average_score_percentage), 2) as avg_score_percentage,
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SUM(positive_count) as total_positive_count,
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SUM(neutral_count) as total_neutral_count,
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SUM(negative_count) as total_negative_count,
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ROUND(SUM(positive_count) / SUM(total_records) * 100, 2) as avg_positive_rate
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FROM cpa_brandcore_statistics
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WHERE is_deleted = 0
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<if test="statisticsType != null and statisticsType != ''">
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AND statistics_type = #{statisticsType}
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</if>
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GROUP BY dealer_code, dealer_name, big_area
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ORDER BY avg_score_percentage DESC, total_score DESC
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<if test="limit != null and limit > 0">
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LIMIT #{limit}
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</if>
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</select>
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<!-- 获取大区排名统计 -->
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<select id="selectBigAreaRanking" resultType="java.util.Map">
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SELECT
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big_area,
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COUNT(DISTINCT dealer_code) as dealer_count,
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SUM(total_records) as total_records,
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SUM(total_score) as total_score,
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ROUND(AVG(average_score_percentage), 2) as avg_score_percentage,
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SUM(positive_count) as total_positive_count,
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SUM(neutral_count) as total_neutral_count,
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SUM(negative_count) as total_negative_count,
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ROUND(SUM(positive_count) / SUM(total_records) * 100, 2) as avg_positive_rate
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FROM cpa_brandcore_statistics
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WHERE is_deleted = 0
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<if test="statisticsType != null and statisticsType != ''">
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AND statistics_type = #{statisticsType}
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</if>
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GROUP BY big_area
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ORDER BY avg_score_percentage DESC, total_score DESC
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</select>
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<!-- 批量插入统计数据 -->
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<insert id="batchInsert" parameterType="java.util.List">
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INSERT INTO cpa_brandcore_statistics (
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id, dealer_code, dealer_name, big_area, statistics_date, statistics_type,
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total_records, total_score, average_score_percentage,
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positive_count, neutral_count, negative_count,
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positive_rate, neutral_rate, negative_rate,
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earliest_interaction, latest_interaction,
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created_at, created_by, updated_at, updated_by, is_deleted
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) VALUES
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<foreach collection="statisticsList" item="item" separator=",">
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(
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#{item.id}, #{item.dealerCode}, #{item.dealerName}, #{item.bigArea},
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#{item.statisticsDate}, #{item.statisticsType},
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#{item.totalRecords}, #{item.totalScore}, #{item.averageScorePercentage},
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#{item.positiveCount}, #{item.neutralCount}, #{item.negativeCount},
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#{item.positiveRate}, #{item.neutralRate}, #{item.negativeRate},
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#{item.earliestInteraction}, #{item.latestInteraction},
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#{item.createdAt}, #{item.createdBy}, #{item.updatedAt}, #{item.updatedBy}, #{item.isDeleted}
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)
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</foreach>
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ON DUPLICATE KEY UPDATE
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total_records = VALUES(total_records),
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total_score = VALUES(total_score),
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average_score_percentage = VALUES(average_score_percentage),
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positive_count = VALUES(positive_count),
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neutral_count = VALUES(neutral_count),
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negative_count = VALUES(negative_count),
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positive_rate = VALUES(positive_rate),
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neutral_rate = VALUES(neutral_rate),
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negative_rate = VALUES(negative_rate),
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earliest_interaction = VALUES(earliest_interaction),
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latest_interaction = VALUES(latest_interaction),
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updated_at = VALUES(updated_at),
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updated_by = VALUES(updated_by)
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</insert>
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<!-- 根据条件删除统计数据 -->
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<delete id="deleteByCondition">
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DELETE FROM cpa_brandcore_statistics
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WHERE is_deleted = 0
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<if test="dealerCode != null and dealerCode != ''">
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AND dealer_code = #{dealerCode}
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</if>
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<if test="statisticsType != null and statisticsType != ''">
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AND statistics_type = #{statisticsType}
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</if>
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<if test="startDate != null">
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AND statistics_date >= #{startDate}
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</if>
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<if test="endDate != null">
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AND statistics_date <= #{endDate}
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</if>
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</delete>
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<!-- 执行日统计SQL（方案1：按经销商和日期双重分组统计） -->
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<select id="executeDailyStatistics" resultType="java.util.Map">
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SELECT
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dealer_code,
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dealer_name,
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big_area,
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DATE(interaction_date) as statistics_date,
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COUNT(*) as daily_records,
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-- 得分统计
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SUM(CASE
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WHEN entity_brand = '积极' THEN 2
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WHEN entity_brand = '中性' THEN 1
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WHEN entity_brand = '消极' THEN 0
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ELSE 0
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END) as daily_total_score,
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ROUND(SUM(CASE
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WHEN entity_brand = '积极' THEN 2
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WHEN entity_brand = '中性' THEN 1
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WHEN entity_brand = '消极' THEN 0
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ELSE 0
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END) / COUNT(*) * 100, 2) as daily_average_score_percentage,
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-- 情感分布统计
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SUM(CASE WHEN entity_brand = '积极' THEN 1 ELSE 0 END) as daily_positive_count,
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SUM(CASE WHEN entity_brand = '中性' THEN 1 ELSE 0 END) as daily_neutral_count,
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SUM(CASE WHEN entity_brand = '消极' THEN 1 ELSE 0 END) as daily_negative_count,
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-- 百分比统计
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ROUND(SUM(CASE WHEN entity_brand = '积极' THEN 1 ELSE 0 END) / COUNT(*) * 100, 2) as daily_positive_rate,
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ROUND(SUM(CASE WHEN entity_brand = '中性' THEN 1 ELSE 0 END) / COUNT(*) * 100, 2) as daily_neutral_rate,
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ROUND(SUM(CASE WHEN entity_brand = '消极' THEN 1 ELSE 0 END) / COUNT(*) * 100, 2) as daily_negative_rate,
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-- 时间范围信息
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MIN(interaction_date) as daily_earliest_time,
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MAX(interaction_date) as daily_latest_time
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FROM customer_profile_analysis
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WHERE is_deleted = 0
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AND entity_brand IS NOT NULL
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AND entity_brand != ''
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AND interaction_date >= #{startDateTime}
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AND interaction_date <= #{endDateTime}
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GROUP BY dealer_code, dealer_name, big_area, DATE(interaction_date)
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ORDER BY statistics_date DESC, daily_total_score DESC, daily_average_score_percentage DESC
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</select>
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<!-- 执行日期范围统计SQL -->
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<select id="executeDateRangeStatistics" resultType="java.util.Map">
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SELECT
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dealer_code,
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dealer_name,
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big_area,
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COUNT(*) as daily_records,
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-- 得分统计
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SUM(CASE
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WHEN entity_brand = '积极' THEN 2
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WHEN entity_brand = '中性' THEN 1
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WHEN entity_brand = '消极' THEN 0
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ELSE 0
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END) as daily_total_score,
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ROUND(SUM(CASE
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WHEN entity_brand = '积极' THEN 2
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WHEN entity_brand = '中性' THEN 1
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WHEN entity_brand = '消极' THEN 0
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ELSE 0
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END) / COUNT(*) * 100, 2) as daily_average_score_percentage,
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-- 情感分布统计
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SUM(CASE WHEN entity_brand = '积极' THEN 1 ELSE 0 END) as daily_positive_count,
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SUM(CASE WHEN entity_brand = '中性' THEN 1 ELSE 0 END) as daily_neutral_count,
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SUM(CASE WHEN entity_brand = '消极' THEN 1 ELSE 0 END) as daily_negative_count,
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-- 百分比统计
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ROUND(SUM(CASE WHEN entity_brand = '积极' THEN 1 ELSE 0 END) / COUNT(*) * 100, 2) as daily_positive_rate,
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ROUND(SUM(CASE WHEN entity_brand = '中性' THEN 1 ELSE 0 END) / COUNT(*) * 100, 2) as daily_neutral_rate,
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ROUND(SUM(CASE WHEN entity_brand = '消极' THEN 1 ELSE 0 END) / COUNT(*) * 100, 2) as daily_negative_rate,
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-- 时间范围信息
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MIN(interaction_date) as daily_earliest_time,
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MAX(interaction_date) as daily_latest_time
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FROM customer_profile_analysis
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WHERE is_deleted = 0
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AND entity_brand IS NOT NULL
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AND entity_brand != ''
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AND interaction_date >= #{startDateTime}
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AND interaction_date <= #{endDateTime}
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GROUP BY dealer_code, dealer_name, big_area
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ORDER BY daily_total_score DESC, daily_average_score_percentage DESC
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</select>
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<!-- 执行总计统计SQL -->
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<select id="executeTotalStatistics" resultType="java.util.Map">
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SELECT
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dealer_code,
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dealer_name,
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big_area,
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COUNT(*) as daily_records,
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-- 得分统计
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SUM(CASE
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WHEN entity_brand = '积极' THEN 2
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WHEN entity_brand = '中性' THEN 1
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WHEN entity_brand = '消极' THEN 0
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ELSE 0
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END) as daily_total_score,
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ROUND(SUM(CASE
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WHEN entity_brand = '积极' THEN 2
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WHEN entity_brand = '中性' THEN 1
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WHEN entity_brand = '消极' THEN 0
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ELSE 0
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END) / COUNT(*) * 100, 2) as daily_average_score_percentage,
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-- 情感分布统计
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SUM(CASE WHEN entity_brand = '积极' THEN 1 ELSE 0 END) as daily_positive_count,
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SUM(CASE WHEN entity_brand = '中性' THEN 1 ELSE 0 END) as daily_neutral_count,
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SUM(CASE WHEN entity_brand = '消极' THEN 1 ELSE 0 END) as daily_negative_count,
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-- 百分比统计
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ROUND(SUM(CASE WHEN entity_brand = '积极' THEN 1 ELSE 0 END) / COUNT(*) * 100, 2) as daily_positive_rate,
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ROUND(SUM(CASE WHEN entity_brand = '中性' THEN 1 ELSE 0 END) / COUNT(*) * 100, 2) as daily_neutral_rate,
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ROUND(SUM(CASE WHEN entity_brand = '消极' THEN 1 ELSE 0 END) / COUNT(*) * 100, 2) as daily_negative_rate,
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-- 时间范围信息
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MIN(interaction_date) as daily_earliest_time,
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MAX(interaction_date) as daily_latest_time
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FROM customer_profile_analysis
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WHERE is_deleted = 0
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AND entity_brand IS NOT NULL
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AND entity_brand != ''
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GROUP BY dealer_code, dealer_name, big_area
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ORDER BY daily_total_score DESC, daily_average_score_percentage DESC
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</select>
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</mapper>
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