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@@ -24,6 +24,8 @@
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<result column="demand_content_topic" jdbcType="VARCHAR" property="demandContentTopic" />
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<result column="point_type" jdbcType="VARCHAR" property="pointType" />
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<result column="standard_element" jdbcType="VARCHAR" property="standardElement" />
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+ <result column="match_generalized_element" jdbcType="VARCHAR" property="matchGeneralizedElement" />
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+ <result column="match_generalized_point_type" jdbcType="VARCHAR" property="matchGeneralizedPointType" />
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<result column="element_dimension" jdbcType="VARCHAR" property="elementDimension" />
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<result column="category_name" jdbcType="VARCHAR" property="categoryName" />
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<result column="crowd_count" jdbcType="INTEGER" property="crowdCount" />
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@@ -116,11 +118,12 @@
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id, dt, online_action, channel_name, crowd_segment, channel_level3, demand_id, crowd_package,
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conversion_target, partner, account, scene_value, demand_strategy, drive_dimension_time,
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dimension, demand_filter_sort_strategy, demand_type, demand_content_id, demand_content_title,
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- demand_content_topic, point_type, standard_element, element_dimension, category_name,
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- crowd_count, video_count, visit_uv, uv_ratio, total_rov, match_experiment_id, match_method,
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- match_video_filter, match_sort, video_id, config_code, score, sim, rov, match_text,
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- title, cover, video, experiment_id, scene_sum_rov, `status`, create_timestamp, update_timestamp,
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- category, match_exposure_pv, match_head_single_return_rate, match_head_distribution_single_return_rate
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+ demand_content_topic, point_type, standard_element, match_generalized_element, match_generalized_point_type,
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+ element_dimension, category_name, crowd_count, video_count, visit_uv, uv_ratio, total_rov,
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+ match_experiment_id, match_method, match_video_filter, match_sort, video_id, config_code,
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+ score, sim, rov, match_text, title, cover, video, experiment_id, scene_sum_rov, `status`,
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+ create_timestamp, update_timestamp, category, match_exposure_pv, match_head_single_return_rate,
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+ match_head_distribution_single_return_rate
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</sql>
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<select id="selectByExample" parameterType="com.tzld.piaoquan.api.model.po.contentplatform.ContentPlatformDemandVideoExample" resultMap="BaseResultMap">
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select
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@@ -163,7 +166,8 @@
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demand_strategy, drive_dimension_time, dimension,
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demand_filter_sort_strategy, demand_type, demand_content_id,
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demand_content_title, demand_content_topic,
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- point_type, standard_element, element_dimension,
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+ point_type, standard_element, match_generalized_element,
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+ match_generalized_point_type, element_dimension,
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category_name, crowd_count, video_count,
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visit_uv, uv_ratio, total_rov,
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match_experiment_id, match_method, match_video_filter,
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@@ -181,7 +185,8 @@
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#{demandStrategy,jdbcType=VARCHAR}, #{driveDimensionTime,jdbcType=VARCHAR}, #{dimension,jdbcType=VARCHAR},
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#{demandFilterSortStrategy,jdbcType=VARCHAR}, #{demandType,jdbcType=VARCHAR}, #{demandContentId,jdbcType=VARCHAR},
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#{demandContentTitle,jdbcType=VARCHAR}, #{demandContentTopic,jdbcType=VARCHAR},
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- #{pointType,jdbcType=VARCHAR}, #{standardElement,jdbcType=VARCHAR}, #{elementDimension,jdbcType=VARCHAR},
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+ #{pointType,jdbcType=VARCHAR}, #{standardElement,jdbcType=VARCHAR}, #{matchGeneralizedElement,jdbcType=VARCHAR},
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+ #{matchGeneralizedPointType,jdbcType=VARCHAR}, #{elementDimension,jdbcType=VARCHAR},
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#{categoryName,jdbcType=VARCHAR}, #{crowdCount,jdbcType=INTEGER}, #{videoCount,jdbcType=INTEGER},
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#{visitUv,jdbcType=BIGINT}, #{uvRatio,jdbcType=DOUBLE}, #{totalRov,jdbcType=DOUBLE},
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#{matchExperimentId,jdbcType=VARCHAR}, #{matchMethod,jdbcType=VARCHAR}, #{matchVideoFilter,jdbcType=VARCHAR},
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@@ -262,6 +267,12 @@
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<if test="standardElement != null">
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standard_element,
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</if>
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+ <if test="matchGeneralizedElement != null">
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+ match_generalized_element,
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+ </if>
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+ <if test="matchGeneralizedPointType != null">
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+ match_generalized_point_type,
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+ </if>
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<if test="elementDimension != null">
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element_dimension,
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</if>
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@@ -417,6 +428,12 @@
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<if test="standardElement != null">
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#{standardElement,jdbcType=VARCHAR},
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</if>
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+ <if test="matchGeneralizedElement != null">
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+ #{matchGeneralizedElement,jdbcType=VARCHAR},
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+ </if>
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+ <if test="matchGeneralizedPointType != null">
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+ #{matchGeneralizedPointType,jdbcType=VARCHAR},
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+ </if>
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<if test="elementDimension != null">
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#{elementDimension,jdbcType=VARCHAR},
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</if>
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@@ -581,6 +598,12 @@
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<if test="record.standardElement != null">
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standard_element = #{record.standardElement,jdbcType=VARCHAR},
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</if>
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+ <if test="record.matchGeneralizedElement != null">
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+ match_generalized_element = #{record.matchGeneralizedElement,jdbcType=VARCHAR},
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+ </if>
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+ <if test="record.matchGeneralizedPointType != null">
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+ match_generalized_point_type = #{record.matchGeneralizedPointType,jdbcType=VARCHAR},
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+ </if>
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<if test="record.elementDimension != null">
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element_dimension = #{record.elementDimension,jdbcType=VARCHAR},
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</if>
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@@ -697,6 +720,8 @@
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demand_content_topic = #{record.demandContentTopic,jdbcType=VARCHAR},
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point_type = #{record.pointType,jdbcType=VARCHAR},
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standard_element = #{record.standardElement,jdbcType=VARCHAR},
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+ match_generalized_element = #{record.matchGeneralizedElement,jdbcType=VARCHAR},
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+ match_generalized_point_type = #{record.matchGeneralizedPointType,jdbcType=VARCHAR},
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element_dimension = #{record.elementDimension,jdbcType=VARCHAR},
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category_name = #{record.categoryName,jdbcType=VARCHAR},
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crowd_count = #{record.crowdCount,jdbcType=INTEGER},
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@@ -796,6 +821,12 @@
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<if test="standardElement != null">
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standard_element = #{standardElement,jdbcType=VARCHAR},
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</if>
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+ <if test="matchGeneralizedElement != null">
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+ match_generalized_element = #{matchGeneralizedElement,jdbcType=VARCHAR},
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+ </if>
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+ <if test="matchGeneralizedPointType != null">
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+ match_generalized_point_type = #{matchGeneralizedPointType,jdbcType=VARCHAR},
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+ </if>
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<if test="elementDimension != null">
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element_dimension = #{elementDimension,jdbcType=VARCHAR},
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</if>
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@@ -909,6 +940,8 @@
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demand_content_topic = #{demandContentTopic,jdbcType=VARCHAR},
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point_type = #{pointType,jdbcType=VARCHAR},
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standard_element = #{standardElement,jdbcType=VARCHAR},
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+ match_generalized_element = #{matchGeneralizedElement,jdbcType=VARCHAR},
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+ match_generalized_point_type = #{matchGeneralizedPointType,jdbcType=VARCHAR},
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element_dimension = #{elementDimension,jdbcType=VARCHAR},
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category_name = #{categoryName,jdbcType=VARCHAR},
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crowd_count = #{crowdCount,jdbcType=INTEGER},
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