From eb25dfd82c66fe41fe71010de85c2c7833ae2f0d Mon Sep 17 00:00:00 2001 From: "zhangruiquan@genew.com" Date: Wed, 30 Oct 2024 18:34:13 +0800 Subject: [PATCH] =?UTF-8?q?=E6=9B=B4=E6=96=B0?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- package.json | 2 +- ...3\345\272\223\347\263\273\347\273\2374.md" | 1441 +++++++---------- .../image-20241030100155584.png" | Bin 0 -> 12959 bytes .../image-20241030100516837.png" | Bin 0 -> 165222 bytes .../image-20241030100751026.png" | Bin 0 -> 164784 bytes .../image-20241030103708179.png" | Bin 0 -> 128815 bytes .../image-20241030160608259.png" | Bin 0 -> 7745 bytes .../image-20241030170441861.png" | Bin 0 -> 22792 bytes .../image-20241030170455732.png" | Bin 0 -> 38123 bytes .../image-20241030170530045.png" | Bin 0 -> 173888 bytes .../image-20241030170609366.png" | Bin 0 -> 236653 bytes .../image-20241030172016772.png" | Bin 0 -> 56478 bytes .../image-20241030180616089.png" | Bin 0 -> 77547 bytes 13 files changed, 573 insertions(+), 870 deletions(-) create mode 100644 "source/_posts/\347\224\265\345\225\206\346\225\260\344\273\223\351\241\271\347\233\256-\347\224\265\345\225\206\346\225\260\346\215\256\344\273\223\345\272\223\347\263\273\347\273\2374/image-20241030100155584.png" create mode 100644 "source/_posts/\347\224\265\345\225\206\346\225\260\344\273\223\351\241\271\347\233\256-\347\224\265\345\225\206\346\225\260\346\215\256\344\273\223\345\272\223\347\263\273\347\273\2374/image-20241030100516837.png" create mode 100644 "source/_posts/\347\224\265\345\225\206\346\225\260\344\273\223\351\241\271\347\233\256-\347\224\265\345\225\206\346\225\260\346\215\256\344\273\223\345\272\223\347\263\273\347\273\2374/image-20241030100751026.png" create mode 100644 "source/_posts/\347\224\265\345\225\206\346\225\260\344\273\223\351\241\271\347\233\256-\347\224\265\345\225\206\346\225\260\346\215\256\344\273\223\345\272\223\347\263\273\347\273\2374/image-20241030103708179.png" create mode 100644 "source/_posts/\347\224\265\345\225\206\346\225\260\344\273\223\351\241\271\347\233\256-\347\224\265\345\225\206\346\225\260\346\215\256\344\273\223\345\272\223\347\263\273\347\273\2374/image-20241030160608259.png" create mode 100644 "source/_posts/\347\224\265\345\225\206\346\225\260\344\273\223\351\241\271\347\233\256-\347\224\265\345\225\206\346\225\260\346\215\256\344\273\223\345\272\223\347\263\273\347\273\2374/image-20241030170441861.png" create mode 100644 "source/_posts/\347\224\265\345\225\206\346\225\260\344\273\223\351\241\271\347\233\256-\347\224\265\345\225\206\346\225\260\346\215\256\344\273\223\345\272\223\347\263\273\347\273\2374/image-20241030170455732.png" create mode 100644 "source/_posts/\347\224\265\345\225\206\346\225\260\344\273\223\351\241\271\347\233\256-\347\224\265\345\225\206\346\225\260\346\215\256\344\273\223\345\272\223\347\263\273\347\273\2374/image-20241030170530045.png" create mode 100644 "source/_posts/\347\224\265\345\225\206\346\225\260\344\273\223\351\241\271\347\233\256-\347\224\265\345\225\206\346\225\260\346\215\256\344\273\223\345\272\223\347\263\273\347\273\2374/image-20241030170609366.png" create mode 100644 "source/_posts/\347\224\265\345\225\206\346\225\260\344\273\223\351\241\271\347\233\256-\347\224\265\345\225\206\346\225\260\346\215\256\344\273\223\345\272\223\347\263\273\347\273\2374/image-20241030172016772.png" create mode 100644 "source/_posts/\347\224\265\345\225\206\346\225\260\344\273\223\351\241\271\347\233\256-\347\224\265\345\225\206\346\225\260\346\215\256\344\273\223\345\272\223\347\263\273\347\273\2374/image-20241030180616089.png" diff --git a/package.json b/package.json index db1de31c..16452a29 100644 --- a/package.json +++ b/package.json @@ -9,7 +9,7 @@ "server": "hexo server" }, "hexo": { - "version": "4.2.1" + "version": "4.2.0" }, "dependencies": { "hexo": "^4.0.0", diff --git "a/source/_posts/\347\224\265\345\225\206\346\225\260\344\273\223\351\241\271\347\233\256-\347\224\265\345\225\206\346\225\260\346\215\256\344\273\223\345\272\223\347\263\273\347\273\2374.md" "b/source/_posts/\347\224\265\345\225\206\346\225\260\344\273\223\351\241\271\347\233\256-\347\224\265\345\225\206\346\225\260\346\215\256\344\273\223\345\272\223\347\263\273\347\273\2374.md" index 377b9de9..69054537 100644 --- "a/source/_posts/\347\224\265\345\225\206\346\225\260\344\273\223\351\241\271\347\233\256-\347\224\265\345\225\206\346\225\260\346\215\256\344\273\223\345\272\223\347\263\273\347\273\2374.md" +++ "b/source/_posts/\347\224\265\345\225\206\346\225\260\344\273\223\351\241\271\347\233\256-\347\224\265\345\225\206\346\225\260\346\215\256\344\273\223\345\272\223\347\263\273\347\273\2374.md" @@ -502,17 +502,15 @@ ER模型 : Entity(实体) Relationship(关系),实体关系模型 (2)PDF版 - - 从上述指标体系中抽取出来的所有派生指标见如下表格。 ![image-20241027002609132](电商数仓项目-电商数据仓库系统4/image-20241027002609132.png) -### 5.2.4 维度模型设计 +### 5.2.5 维度模型设计 维度模型的设计参照上述得到的业务总线矩阵即可。事实表存储在DWD层,维度表存储在DIM层。 -### 5.2.5 汇总模型设计 +### 5.2.6 汇总模型设计 汇总模型的设计参考上述整理出的指标体系(主要是派生指标)即可。汇总表与派生指标的对应关系是,**一张汇总**表通常**包含**业务过程相同、统计周期相同、统计粒度相同的**多个派生指标**。请思考:汇总表与事实表的对应关系是? @@ -2307,701 +2305,477 @@ left join sale_attr on sku.id=sale_attr.sku_id; **1)建表语句** +```hive DROP TABLE IF EXISTS dim_coupon_full; - CREATE EXTERNAL TABLE dim_coupon_full - ( + `id` STRING COMMENT '优惠券编号', + `coupon_name` STRING COMMENT '优惠券名称', + `coupon_type_code` STRING COMMENT '优惠券类型编码', + `coupon_type_name` STRING COMMENT '优惠券类型名称', + `condition_amount` DECIMAL(16, 2) COMMENT '满额数', + `condition_num` BIGINT COMMENT '满件数', + `activity_id` STRING COMMENT '活动编号', + `benefit_amount` DECIMAL(16, 2) COMMENT '减免金额', + `benefit_discount` DECIMAL(16, 2) COMMENT '折扣', + `benefit_rule` STRING COMMENT '优惠规则:满元*减*元,满*件打*折', + `create_time` STRING COMMENT '创建时间', + `range_type_code` STRING COMMENT '优惠范围类型编码', + `range_type_name` STRING COMMENT '优惠范围类型名称', + `limit_num` BIGINT COMMENT '最多领取次数', + `taken_count` BIGINT COMMENT '已领取次数', + `start_time` STRING COMMENT '可以领取的开始时间', + `end_time` STRING COMMENT '可以领取的结束时间', + `operate_time` STRING COMMENT '修改时间', + `expire_time` STRING COMMENT '过期时间' +) COMMENT '优惠券维度表' + PARTITIONED BY (`dt` STRING) + STORED AS ORC + LOCATION '/warehouse/gmall/dim/dim_coupon_full/' + TBLPROPERTIES ('orc.compress' = 'snappy'); +``` -`id` STRING COMMENT '优惠券编号', +**2)数据装载** -`coupon_name` STRING COMMENT '优惠券名称', +(1)思路分析 -`coupon_type_code` STRING COMMENT '优惠券类型编码', +1. 分区规划 -`coupon_type_name` STRING COMMENT '优惠券类型名称', +同8.1。 -`condition_amount` DECIMAL(16, 2) COMMENT '满额数', +2. 数据流向 -`condition_num` BIGINT COMMENT '满件数', +同8.1。 -`activity_id` STRING COMMENT '活动编号', +3. 数据装载 -`benefit_amount` DECIMAL(16, 2) COMMENT '减免金额', +我们只会用到字典表的编码和名称两个字段,单独建表意义不大,应做维度退化。优惠券相关的原始业务表只有coupon_info,不需要确定主维表和相关维表。因此,只须关联ods_coupon_info_full与ods_base_dic_full。 -`benefit_discount` DECIMAL(16, 2) COMMENT '折扣', +(2)执行步骤 -`benefit_rule` STRING COMMENT '优惠规则:满元*减*元,满*件打*折', +1. 从ods_coupon_info_full表中筛选2022-06-08分区的数据,选取需要的字段,如优惠券名称、优惠券类型、使用条件等。 -`create_time` STRING COMMENT '创建时间', +2. 将①中获取的数据与ods_base_dic_full关联获取优惠券类型名称和优惠范围类型名称。关联字段分别为优惠券类型和优惠范围类型,这两种编码在字典表中一定有对应记录,而字典表中其它编码对应记录对我们是没有意义的,因此以ods_coupon_info_full作为主表,应使用内连接或左外连接。 -`range_type_code` STRING COMMENT '优惠范围类型编码', +3. 通过case when… then… end语法根据不同的优惠券类型,生成不同的优惠规则字符串,记为benefit_rule字段。 -`range_type_name` STRING COMMENT '优惠范围类型名称', +4. 最终,将查询结果覆盖写入dim_coupon_full的2022-06-08分区。 -`limit_num` BIGINT COMMENT '最多领取次数', +(3)图解 -`taken_count` BIGINT COMMENT '已领取次数', +1. 分区规划 -`start_time` STRING COMMENT '可以领取的开始时间', +同8.1。 -`end_time` STRING COMMENT '可以领取的结束时间', +2. 数据流向 -`operate_time` STRING COMMENT '修改时间', +同8.1。 -`expire_time` STRING COMMENT '过期时间' +3. 数据装载 -) COMMENT '优惠券维度表' + ![image-20241030100516837](电商数仓项目-电商数据仓库系统4/image-20241030100516837.png) -PARTITIONED BY (`dt` STRING) +(4)代码实现 -STORED AS ORC +```hive +insert overwrite table dim_coupon_full partition(dt='2022-06-08') +select + id, + coupon_name, + coupon_type, + coupon_dic.dic_name, + condition_amount, + condition_num, + activity_id, + benefit_amount, + benefit_discount, + case coupon_type + when '3201' then concat('满',condition_amount,'元减',benefit_amount,'元') + when '3202' then concat('满',condition_num,'件打', benefit_discount,' 折') + when '3203' then concat('减',benefit_amount,'元') + end benefit_rule, + create_time, + range_type, + range_dic.dic_name, + limit_num, + taken_count, + start_time, + end_time, + operate_time, + expire_time +from +( + select + id, + coupon_name, + coupon_type, + condition_amount, + condition_num, + activity_id, + benefit_amount, + benefit_discount, + create_time, + range_type, + limit_num, + taken_count, + start_time, + end_time, + operate_time, + expire_time + from ods_coupon_info_full + where dt='2022-06-08' +)ci +left join +( + select + dic_code, + dic_name + from ods_base_dic_full + where dt='2022-06-08' + and parent_code='32' +)coupon_dic +on ci.coupon_type=coupon_dic.dic_code +left join +( + select + dic_code, + dic_name + from ods_base_dic_full + where dt='2022-06-08' + and parent_code='33' +)range_dic +on ci.range_type=range_dic.dic_code; +``` + +## 8.3 活动维度表 -LOCATION '/warehouse/gmall/dim/dim_coupon_full/' +![image-20241030100155584](电商数仓项目-电商数据仓库系统4/image-20241030100155584.png) -TBLPROPERTIES ('orc.compress' = 'snappy'); +**1)建表语句** + +```hive +DROP TABLE IF EXISTS dim_activity_full; +CREATE EXTERNAL TABLE dim_activity_full +( + `activity_rule_id` STRING COMMENT '活动规则ID', + `activity_id` STRING COMMENT '活动ID', + `activity_name` STRING COMMENT '活动名称', + `activity_type_code` STRING COMMENT '活动类型编码', + `activity_type_name` STRING COMMENT '活动类型名称', + `activity_desc` STRING COMMENT '活动描述', + `start_time` STRING COMMENT '开始时间', + `end_time` STRING COMMENT '结束时间', + `create_time` STRING COMMENT '创建时间', + `condition_amount` DECIMAL(16, 2) COMMENT '满减金额', + `condition_num` BIGINT COMMENT '满减件数', + `benefit_amount` DECIMAL(16, 2) COMMENT '优惠金额', + `benefit_discount` DECIMAL(16, 2) COMMENT '优惠折扣', + `benefit_rule` STRING COMMENT '优惠规则', + `benefit_level` STRING COMMENT '优惠级别' +) COMMENT '活动维度表' + PARTITIONED BY (`dt` STRING) + STORED AS ORC + LOCATION '/warehouse/gmall/dim/dim_activity_full/' + TBLPROPERTIES ('orc.compress' = 'snappy'); +``` **2)数据装载** (1)思路分析 -① 分区规划 +1. 分区规划 同8.1。 -② 数据流向 +2. 数据流向 同8.1。 -③ 数据装载 +3. 数据装载 -我们只会用到字典表的编码和名称两个字段,单独建表意义不大,应做维度退化。优惠券相关的原始业务表只有coupon_info,不需要确定主维表和相关维表。因此,只须关联ods_coupon_info_full与ods_base_dic_full。 +活动相关的原始业务表有activity_rule、activity_info,此外,为了获取活动类型名称,还需要关联字典表。activity_rule中记录了活动的规则描述,activity_info记录了活动描述,用户下单时,每条明细记录都可能参与活动,order_detail_activity(订单活动关联表)记录了这些信息,该表中记录的是每个SKU具体参与了那次活动,满足了该活动的哪条规则,因此,要让事实表与活动维度进行关联,活动维度表的粒度应细化至活动规则粒度。综上,以activity_rule作为主表。 (2)执行步骤 -① 从ods_coupon_info_full表中筛选2022-06-08分区的数据,选取需要的字段,如优惠券名称、优惠券类型、使用条件等。 +1. 从ods_activity_rule_full表中筛选2022-06-08分区的数据,并选取需要的字段,子查询记为rule。 + +2. 从ods_activity_info_full 表中筛选2022-06-08分区的数据,并选取需要的字段,子查询记为info。 -② 将①中获取的数据与ods_base_dic_full关联获取优惠券类型名称和优惠范围类型名称。关联字段分别为优惠券类型和优惠范围类型,这两种编码在字典表中一定有对应记录,而字典表中其它编码对应记录对我们是没有意义的,因此以ods_coupon_info_full作为主表,应使用内连接或左外连接。 +3. 筛选字典表2022-06-08分区的数据。 -③ 通过case when… then… end语法根据不同的优惠券类型,生成不同的优惠规则字符串,记为benefit_rule字段。 +4. 以rule作为主表,通过activity_id关联info。活动规则和活动信息的每一条数据都可以在另一张表中找到对应记录,因此inner join、left join、right join、full outer join都是等价的,任选一种即可。此处选择left join。 -④ 最终,将查询结果覆盖写入dim_coupon_full的2022-06-08分区。 +5. 与8.2同理,关联字段表获取编码名称字段选择left join。 + +6. 筛选字段,写入dim_activity_full的2022-06-08分区。 (3)图解 -① 分区规划 +1. 分区规划 同8.1。 -② 数据流向 +2. 数据流向 同8.1。 -③ 数据装载 +3. 数据装载 -(4)代码实现 + ![image-20241030100751026](电商数仓项目-电商数据仓库系统4/image-20241030100751026.png) -insert overwrite table dim_coupon_full partition(dt='2022-06-08') +(4)代码实现 +```hive +insert overwrite table dim_activity_full partition(dt='2022-06-08') select + rule.id, + info.id, + activity_name, + rule.activity_type, + dic.dic_name, + activity_desc, + start_time, + end_time, + create_time, + condition_amount, + condition_num, + benefit_amount, + benefit_discount, + case rule.activity_type + when '3101' then concat('满',condition_amount,'元减',benefit_amount,'元') + when '3102' then concat('满',condition_num,'件打', benefit_discount,' 折') + when '3103' then concat('打', benefit_discount,'折') + end benefit_rule, + benefit_level +from +( + select + id, + activity_id, + activity_type, + condition_amount, + condition_num, + benefit_amount, + benefit_discount, + benefit_level + from ods_activity_rule_full + where dt='2022-06-08' +)rule +left join +( + select + id, + activity_name, + activity_type, + activity_desc, + start_time, + end_time, + create_time + from ods_activity_info_full + where dt='2022-06-08' +)info +on rule.activity_id=info.id +left join +( + select + dic_code, + dic_name + from ods_base_dic_full + where dt='2022-06-08' + and parent_code='31' +)dic +on rule.activity_type=dic.dic_code; +``` -id, - -coupon_name, +## 8.4 地区维度表 -coupon_type, +**1)建表语句** -coupon_dic.dic_name, +```hive +DROP TABLE IF EXISTS dim_province_full; +CREATE EXTERNAL TABLE dim_province_full +( + `id` STRING COMMENT '省份ID', + `province_name` STRING COMMENT '省份名称', + `area_code` STRING COMMENT '地区编码', + `iso_code` STRING COMMENT '旧版国际标准地区编码,供可视化使用', + `iso_3166_2` STRING COMMENT '新版国际标准地区编码,供可视化使用', + `region_id` STRING COMMENT '地区ID', + `region_name` STRING COMMENT '地区名称' +) COMMENT '地区维度表' + PARTITIONED BY (`dt` STRING) + STORED AS ORC + LOCATION '/warehouse/gmall/dim/dim_province_full/' + TBLPROPERTIES ('orc.compress' = 'snappy'); +``` -condition_amount, +**2)数据装载** -condition_num, +(1)思路分析 -activity_id, +1. 分区规划 -benefit_amount, +同8.1。 -benefit_discount, +2. 数据流向 -case coupon_type +同8.1。 -when '3201' then concat('满',condition_amount,'元减',benefit_amount,'元') +3. 数据装载 -when '3202' then concat('满',condition_num,'件打', benefit_discount,' 折') +原始业务数据库中与地区相关的表有base_province和base_region,二者通过region_id产生联系。下单等业务过程相关的表中都通过province_id字段与地区维度产生关联,显然base_province应为主维表。 -when '3203' then concat('减',benefit_amount,'元') +(2)执行步骤 -end benefit_rule, +1. 筛选ods_base_province_full表2022-06-08分区的数据,选取所须字段,子查询记为province。 -create_time, +2. 筛选ods_base_region_full表2022-06-08分区的数据,选取所须字段,子查询记为region。 -range_type, +3. 通过region_id将province和region关联起来。两张表不存在不满足关联条件的数据,inner join、left join、right join、full outer join都是一样的,此处选用left join。 -range_dic.dic_name, +4. 选取所须字段,写入dim_province_full表的2022-06-08分区。 -limit_num, +(3)图解 -taken_count, +1. 分区规划 -start_time, +同8.1。 -end_time, +2. 数据流向 -operate_time, +同8.1。 -expire_time +3. 数据装载 -from + ![image-20241030103708179](电商数仓项目-电商数据仓库系统4/image-20241030103708179.png) -( +(4)代码实现 +```hive +insert overwrite table dim_province_full partition(dt='2022-06-08') select + province.id, + province.name, + province.area_code, + province.iso_code, + province.iso_3166_2, + region_id, + region_name +from +( + select + id, + name, + region_id, + area_code, + iso_code, + iso_3166_2 + from ods_base_province_full + where dt='2022-06-08' +)province +left join +( + select + id, + region_name + from ods_base_region_full + where dt='2022-06-08' +)region +on province.region_id=region.id; +``` -id, - -coupon_name, +## 8.5 营销坑位维度表 -coupon_type, +**1)建表语句** -condition_amount, +```hive +DROP TABLE IF EXISTS dim_promotion_pos_full; +CREATE EXTERNAL TABLE dim_promotion_pos_full +( + `id` STRING COMMENT '营销坑位ID', + `pos_location` STRING COMMENT '营销坑位位置', + `pos_type` STRING COMMENT '营销坑位类型 ', + `promotion_type` STRING COMMENT '营销类型', + `create_time` STRING COMMENT '创建时间', + `operate_time` STRING COMMENT '修改时间' +) COMMENT '营销坑位维度表' + PARTITIONED BY (`dt` STRING) + STORED AS ORC + LOCATION '/warehouse/gmall/dim/dim_promotion_pos_full/' + TBLPROPERTIES ('orc.compress' = 'snappy'); +``` -condition_num, +**2)数据装载** -activity_id, +(1)思路分析 -benefit_amount, +1. 分区规划 -benefit_discount, +同8.1。 -create_time, +2. 数据流向 -range_type, +同8.1。 -limit_num, +3. 数据装载 -taken_count, +原始业务数据库中只有promotion_pos表与营销坑位维度相关,从ods_promotion_pos_full表中筛选2022-06-08分区的数据,选择所须字段写入dim_promotion_pos_full表的2022-06-08分区即可。 -start_time, +(2)执行步骤 -end_time, +略。 -operate_time, +(3)图解 -expire_time +略。 -from ods_coupon_info_full +(4)代码实现 -where dt='2022-06-08' +```hive +insert overwrite table dim_promotion_pos_full partition(dt='2022-06-08') +select + `id`, + `pos_location`, + `pos_type`, + `promotion_type`, + `create_time`, + `operate_time` +from ods_promotion_pos_full +where dt='2022-06-08'; +``` -)ci +## 8.6 营销渠道维度表 -left join +**1)建表语句** +```hive +DROP TABLE IF EXISTS dim_promotion_refer_full; +CREATE EXTERNAL TABLE dim_promotion_refer_full ( + `id` STRING COMMENT '营销渠道ID', + `refer_name` STRING COMMENT '营销渠道名称', + `create_time` STRING COMMENT '创建时间', + `operate_time` STRING COMMENT '修改时间' +) COMMENT '营销渠道维度表' + PARTITIONED BY (`dt` STRING) + STORED AS ORC + LOCATION '/warehouse/gmall/dim/dim_promotion_refer_full/' + TBLPROPERTIES ('orc.compress' = 'snappy'); +``` -select +**2)数据装载** -dic_code, +(1)思路分析 -dic_name +1. 分区规划 -from ods_base_dic_full +同8.1。 -where dt='2022-06-08' - -and parent_code='32' - -)coupon_dic - -on ci.coupon_type=coupon_dic.dic_code - -left join - -( - -select - -dic_code, - -dic_name - -from ods_base_dic_full - -where dt='2022-06-08' - -and parent_code='33' - -)range_dic - -on ci.range_type=range_dic.dic_code; - -## 8.3 活动维度表 - -**1)建表语句** - -DROP TABLE IF EXISTS dim_activity_full; - -CREATE EXTERNAL TABLE dim_activity_full - -( - -`activity_rule_id` STRING COMMENT '活动规则ID', - -`activity_id` STRING COMMENT '活动ID', - -`activity_name` STRING COMMENT '活动名称', - -`activity_type_code` STRING COMMENT '活动类型编码', - -`activity_type_name` STRING COMMENT '活动类型名称', - -`activity_desc` STRING COMMENT '活动描述', - -`start_time` STRING COMMENT '开始时间', - -`end_time` STRING COMMENT '结束时间', - -`create_time` STRING COMMENT '创建时间', - -`condition_amount` DECIMAL(16, 2) COMMENT '满减金额', - -`condition_num` BIGINT COMMENT '满减件数', - -`benefit_amount` DECIMAL(16, 2) COMMENT '优惠金额', - -`benefit_discount` DECIMAL(16, 2) COMMENT '优惠折扣', - -`benefit_rule` STRING COMMENT '优惠规则', - -`benefit_level` STRING COMMENT '优惠级别' - -) COMMENT '活动维度表' - -PARTITIONED BY (`dt` STRING) - -STORED AS ORC - -LOCATION '/warehouse/gmall/dim/dim_activity_full/' - -TBLPROPERTIES ('orc.compress' = 'snappy'); - -**2)数据装载** - -(1)思路分析 - -① 分区规划 - -同8.1。 - -② 数据流向 - -同8.1。 - -③ 数据装载 - -活动相关的原始业务表有activity_rule、activity_info,此外,为了获取活动类型名称,还需要关联字典表。activity_rule中记录了活动的规则描述,activity_info记录了活动描述,用户下单时,每条明细记录都可能参与活动,order_detail_activity(订单活动关联表)记录了这些信息,该表中记录的是每个SKU具体参与了那次活动,满足了该活动的哪条规则,因此,要让事实表与活动维度进行关联,活动维度表的粒度应细化至活动规则粒度。综上,以activity_rule作为主表。 - -(2)执行步骤 - -① 从ods_activity_rule_full表中筛选2022-06-08分区的数据,并选取需要的字段,子查询记为rule。 - -② 从ods_activity_info_full 表中筛选2022-06-08分区的数据,并选取需要的字段,子查询记为info。 - -③ 筛选字典表2022-06-08分区的数据。 - -④ 以rule作为主表,通过activity_id关联info。活动规则和活动信息的每一条数据都可以在另一张表中找到对应记录,因此inner join、left join、right join、full outer join都是等价的,任选一种即可。此处选择left join。 - -⑤ 与8.2同理,关联字段表获取编码名称字段选择left join。 - -⑥ 筛选字段,写入dim_activity_full的2022-06-08分区。 - -(3)图解 - -① 分区规划 - -同8.1。 - -② 数据流向 - -同8.1。 - -③ 数据装载 - -(4)代码实现 - -insert overwrite table dim_activity_full partition(dt='2022-06-08') - -select - -rule.id, - -info.id, - -activity_name, - -rule.activity_type, - -dic.dic_name, - -activity_desc, - -start_time, - -end_time, - -create_time, - -condition_amount, - -condition_num, - -benefit_amount, - -benefit_discount, - -case rule.activity_type - -when '3101' then concat('满',condition_amount,'元减',benefit_amount,'元') - -when '3102' then concat('满',condition_num,'件打', benefit_discount,' 折') - -when '3103' then concat('打', benefit_discount,'折') - -end benefit_rule, - -benefit_level - -from - -( - -select - -id, - -activity_id, - -activity_type, - -condition_amount, - -condition_num, - -benefit_amount, - -benefit_discount, - -benefit_level - -from ods_activity_rule_full - -where dt='2022-06-08' - -)rule - -left join - -( - -select - -id, - -activity_name, - -activity_type, - -activity_desc, - -start_time, - -end_time, - -create_time - -from ods_activity_info_full - -where dt='2022-06-08' - -)info - -on rule.activity_id=info.id - -left join - -( - -select - -dic_code, - -dic_name - -from ods_base_dic_full - -where dt='2022-06-08' - -and parent_code='31' - -)dic - -on rule.activity_type=dic.dic_code; - -## 8.4 地区维度表 - -**1)建表语句** - -DROP TABLE IF EXISTS dim_province_full; - -CREATE EXTERNAL TABLE dim_province_full - -( - -`id` STRING COMMENT '省份ID', - -`province_name` STRING COMMENT '省份名称', - -`area_code` STRING COMMENT '地区编码', - -`iso_code` STRING COMMENT '旧版国际标准地区编码,供可视化使用', - -`iso_3166_2` STRING COMMENT '新版国际标准地区编码,供可视化使用', - -`region_id` STRING COMMENT '地区ID', - -`region_name` STRING COMMENT '地区名称' - -) COMMENT '地区维度表' - -PARTITIONED BY (`dt` STRING) - -STORED AS ORC - -LOCATION '/warehouse/gmall/dim/dim_province_full/' - -TBLPROPERTIES ('orc.compress' = 'snappy'); - -**2)数据装载** - -(1)思路分析 - -① 分区规划 +2. 数据流向 同8.1。 -② 数据流向 - -同8.1。 - -③ 数据装载 - -原始业务数据库中与地区相关的表有base_province和base_region,二者通过region_id产生联系。下单等业务过程相关的表中都通过province_id字段与地区维度产生关联,显然base_province应为主维表。 - -(2)执行步骤 - -① 筛选ods_base_province_full表2022-06-08分区的数据,选取所须字段,子查询记为province。 - -② 筛选ods_base_region_full表2022-06-08分区的数据,选取所须字段,子查询记为region。 - -③ 通过region_id将province和region关联起来。两张表不存在不满足关联条件的数据,inner join、left join、right join、full outer join都是一样的,此处选用left join。 - -④ 选取所须字段,写入dim_province_full表的2022-06-08分区。 - -(3)图解 - -① 分区规划 - -同8.1。 - -② 数据流向 - -同8.1。 - -③ 数据装载 - -(4)代码实现 - -insert overwrite table dim_province_full partition(dt='2022-06-08') - -select - -province.id, - -province.name, - -province.area_code, - -province.iso_code, - -province.iso_3166_2, - -region_id, - -region_name - -from - -( - -select - -id, - -name, - -region_id, - -area_code, - -iso_code, - -iso_3166_2 - -from ods_base_province_full - -where dt='2022-06-08' - -)province - -left join - -( - -select - -id, - -region_name - -from ods_base_region_full - -where dt='2022-06-08' - -)region - -on province.region_id=region.id; - -## 8.5 营销坑位维度表 - -**1)建表语句** - -DROP TABLE IF EXISTS dim_promotion_pos_full; - -CREATE EXTERNAL TABLE dim_promotion_pos_full - -( - -`id` STRING COMMENT '营销坑位ID', - -`pos_location` STRING COMMENT '营销坑位位置', - -`pos_type` STRING COMMENT '营销坑位类型 ', - -`promotion_type` STRING COMMENT '营销类型', - -`create_time` STRING COMMENT '创建时间', - -`operate_time` STRING COMMENT '修改时间' - -) COMMENT '营销坑位维度表' - -PARTITIONED BY (`dt` STRING) - -STORED AS ORC - -LOCATION '/warehouse/gmall/dim/dim_promotion_pos_full/' - -TBLPROPERTIES ('orc.compress' = 'snappy'); - -**2)数据装载** - -(1)思路分析 - -① 分区规划 - -同8.1。 - -② 数据流向 - -同8.1。 - -③ 数据装载 - -原始业务数据库中只有promotion_pos表与营销坑位维度相关,从ods_promotion_pos_full表中筛选2022-06-08分区的数据,选择所须字段写入dim_promotion_pos_full表的2022-06-08分区即可。 - -(2)执行步骤 - -略。 - -(3)图解 - -略。 - -(4)代码实现 - -insert overwrite table dim_promotion_pos_full partition(dt='2022-06-08') - -select - -`id`, - -`pos_location`, - -`pos_type`, - -`promotion_type`, - -`create_time`, - -``` -operate_time -``` - -from ods_promotion_pos_full - -where dt='2022-06-08'; - -## 8.6 营销渠道维度表 - -**1)建表语句** - -DROP TABLE IF EXISTS dim_promotion_refer_full; - -CREATE EXTERNAL TABLE dim_promotion_refer_full - -( - -`id` STRING COMMENT '营销渠道ID', - -`refer_name` STRING COMMENT '营销渠道名称', - -`create_time` STRING COMMENT '创建时间', - -`operate_time` STRING COMMENT '修改时间' - -) COMMENT '营销渠道维度表' - -PARTITIONED BY (`dt` STRING) - -STORED AS ORC - -LOCATION '/warehouse/gmall/dim/dim_promotion_refer_full/' - -TBLPROPERTIES ('orc.compress' = 'snappy'); - -**2)数据装载** - -(1)思路分析 - -① 分区规划 - -同8.1。 - -② 数据流向 - -同8.1。 - -③ 数据装载 +3. 数据装载 原始业务数据库中只有promotion_refer表与营销渠道维度相关,从ods_promotion_refer_full表中筛选2022-06-08分区的数据,选取所须字段写入dim_promotion_refer_full表的2022-06-08分区即可。 @@ -3015,59 +2789,39 @@ TBLPROPERTIES ('orc.compress' = 'snappy'); (4)代码实现 +```hive insert overwrite table dim_promotion_refer_full partition(dt='2022-06-08') - select + `id`, + `refer_name`, + `create_time`, + `operate_time` +from ods_promotion_refer_full +where dt='2022-06-08'; +``` -`id`, - -`refer_name`, - -`create_time`, - -``` -operate_time -``` - -from ods_promotion_refer_full - -where dt='2022-06-08'; - -## 8.7 日期维度表 - -**1)建表语句** - -DROP TABLE IF EXISTS dim_date; - -CREATE EXTERNAL TABLE dim_date - -( - -`date_id` STRING COMMENT '日期ID', - -`week_id` STRING COMMENT '周ID,一年中的第几周', - -`week_day` STRING COMMENT '周几', - -`day` STRING COMMENT '每月的第几天', - -`month` STRING COMMENT '一年中的第几月', - -`quarter` STRING COMMENT '一年中的第几季度', - -`year` STRING COMMENT '年份', - -`is_workday` STRING COMMENT '是否是工作日', +## 8.7 日期维度表 -`holiday_id` STRING COMMENT '节假日' +**1)建表语句** +```hive +DROP TABLE IF EXISTS dim_date; +CREATE EXTERNAL TABLE dim_date +( + `date_id` STRING COMMENT '日期ID', + `week_id` STRING COMMENT '周ID,一年中的第几周', + `week_day` STRING COMMENT '周几', + `day` STRING COMMENT '每月的第几天', + `month` STRING COMMENT '一年中的第几月', + `quarter` STRING COMMENT '一年中的第几季度', + `year` STRING COMMENT '年份', + `is_workday` STRING COMMENT '是否是工作日', + `holiday_id` STRING COMMENT '节假日' ) COMMENT '日期维度表' - -STORED AS ORC - -LOCATION '/warehouse/gmall/dim/dim_date/' - -TBLPROPERTIES ('orc.compress' = 'snappy'); + STORED AS ORC + LOCATION '/warehouse/gmall/dim/dim_date/' + TBLPROPERTIES ('orc.compress' = 'snappy'); +``` **2)数据装载** @@ -3075,95 +2829,120 @@ TBLPROPERTIES ('orc.compress' = 'snappy'); (1)创建临时表 +```hive DROP TABLE IF EXISTS tmp_dim_date_info; - CREATE EXTERNAL TABLE tmp_dim_date_info ( - -`date_id` STRING COMMENT '日', - -`week_id` STRING COMMENT '周ID', - -`week_day` STRING COMMENT '周几', - -`day` STRING COMMENT '每月的第几天', - -`month` STRING COMMENT '第几月', - -`quarter` STRING COMMENT '第几季度', - -`year` STRING COMMENT '年', - -`is_workday` STRING COMMENT '是否是工作日', - -`holiday_id` STRING COMMENT '节假日' - + `date_id` STRING COMMENT '日', + `week_id` STRING COMMENT '周ID', + `week_day` STRING COMMENT '周几', + `day` STRING COMMENT '每月的第几天', + `month` STRING COMMENT '第几月', + `quarter` STRING COMMENT '第几季度', + `year` STRING COMMENT '年', + `is_workday` STRING COMMENT '是否是工作日', + `holiday_id` STRING COMMENT '节假日' ) COMMENT '时间维度表' - ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t' - LOCATION '/warehouse/gmall/tmp/tmp_dim_date_info/'; +``` (2)将数据文件上传到HFDS上临时表路径/warehouse/gmall/tmp/tmp_dim_date_info +data_info.txt + +```properties +2022-01-01 1 6 1 1 1 2022 0 元旦 +2022-01-02 1 7 2 1 1 2022 0 元旦 +2022-01-03 2 1 3 1 1 2022 0 元旦 +2022-01-04 2 2 4 1 1 2022 1 \N +2022-01-05 2 3 5 1 1 2022 1 \N +2022-01-06 2 4 6 1 1 2022 1 \N +2022-01-07 2 5 7 1 1 2022 1 \N +2022-01-08 2 6 8 1 1 2022 0 \N +2022-01-09 2 7 9 1 1 2022 0 \N +2022-01-10 3 1 10 1 1 2022 1 \N +2022-01-11 3 2 11 1 1 2022 1 \N +2022-01-12 3 3 12 1 1 2022 1 \N +2022-01-13 3 4 13 1 1 2022 1 \N +2022-01-14 3 5 14 1 1 2022 1 \N +2022-01-15 3 6 15 1 1 2022 0 \N +2022-01-16 3 7 16 1 1 2022 0 \N +2022-01-17 4 1 17 1 1 2022 1 \N +2022-01-18 4 2 18 1 1 2022 1 \N +2022-01-19 4 3 19 1 1 2022 1 \N +2022-01-20 4 4 20 1 1 2022 1 \N +2022-01-21 4 5 21 1 1 2022 1 \N +2022-01-22 4 6 22 1 1 2022 0 \N +2022-01-23 4 7 23 1 1 2022 0 \N +2022-01-24 5 1 24 1 1 2022 1 \N +2022-01-25 5 2 25 1 1 2022 1 \N +2022-01-26 5 3 26 1 1 2022 1 \N +2022-01-27 5 4 27 1 1 2022 1 \N +2022-01-28 5 5 28 1 1 2022 1 \N +2022-01-29 5 6 29 1 1 2022 1 \N +2022-01-30 5 7 30 1 1 2022 1 \N +2022-01-31 6 1 31 1 1 2022 0 春节 +2022-02-01 6 2 1 2 1 2022 0 春节 +2022-02-02 6 3 2 2 1 2022 0 春节 +2022-02-03 6 4 3 2 1 2022 0 春节 +2022-02-04 6 5 4 2 1 2022 0 春节 +2022-02-05 6 6 5 2 1 2022 0 春节 +2022-02-06 6 7 6 2 1 2022 0 春节 +2022-02-07 7 1 7 2 1 2022 1 \N +... ... +``` + (3)执行以下语句将其导入时间维度表 +```hive insert overwrite table dim_date select * from tmp_dim_date_info; +``` (4)检查数据是否导入成功 +```hive select * from dim_date; +``` ## 8.8 用户维度表 +![image-20241030160608259](电商数仓项目-电商数据仓库系统4/image-20241030160608259.png) + +![image-20241030180616089](电商数仓项目-电商数据仓库系统4/image-20241030180616089.png) + **1)建表语句** +```hive DROP TABLE IF EXISTS dim_user_zip; - CREATE EXTERNAL TABLE dim_user_zip - ( - -`id` STRING COMMENT '用户ID', - -`name` STRING COMMENT '用户姓名', - -`phone_num` STRING COMMENT '手机号码', - -`email` STRING COMMENT '邮箱', - -`user_level` STRING COMMENT '用户等级', - -`birthday` STRING COMMENT '生日', - -`gender` STRING COMMENT '性别', - -`create_time` STRING COMMENT '创建时间', - -`operate_time` STRING COMMENT '操作时间', - -`start_date` STRING COMMENT '开始日期', - -`end_date` STRING COMMENT '结束日期' - + `id` STRING COMMENT '用户ID', + `name` STRING COMMENT '用户姓名', + `phone_num` STRING COMMENT '手机号码', + `email` STRING COMMENT '邮箱', + `user_level` STRING COMMENT '用户等级', + `birthday` STRING COMMENT '生日', + `gender` STRING COMMENT '性别', + `create_time` STRING COMMENT '创建时间', + `operate_time` STRING COMMENT '操作时间', + `start_date` STRING COMMENT '开始日期', + `end_date` STRING COMMENT '结束日期' ) COMMENT '用户维度表' - -PARTITIONED BY (`dt` STRING) - -STORED AS ORC - -LOCATION '/warehouse/gmall/dim/dim_user_zip/' - -TBLPROPERTIES ('orc.compress' = 'snappy'); + PARTITIONED BY (`dt` STRING) + STORED AS ORC + LOCATION '/warehouse/gmall/dim/dim_user_zip/' + TBLPROPERTIES ('orc.compress' = 'snappy'); +``` **2)数据装载** (1)思路分析 -① 分区规划 +1. 分区规划 拉链表的分区有两类:9999-12-31分区和普通日期分区。前者保存最新的维度数据,后者保存有效期截至分区日期的数据。 -② 数据流向 +2. 数据流向 a)首日 @@ -3173,7 +2952,7 @@ b)每日 从数仓上线次日开始,采集user_info的变更数据,通常业务数据库的数据不会被删除,因而用户信息的变更只有新增和修改两类。新增的用户信息进入9999-12-31分区,修改的用户信息覆盖9999-12-31分区的记录,并将历史数据写入前一分区(如某用户信息在2022-06-09发生变化,当日的历史用户信息有效期截至2022-06-08,进入2022-06-08分区)。 -③ 数据装载 +3. 数据装载 首日数据装载:筛选所须字段,对敏感信息加密脱敏,写入9999-12-31分区即可。 @@ -3183,13 +2962,13 @@ b)每日 (2)知识储备 -① regexp:用法:A regexp B,AB均为字符串,A是待匹配的字符串,B是正则表达式。若A、B其中之一为null则返回false。若A中的任意子串可以匹配B则返回true,否则返回false。如果要让整个A串与B匹配才返回true,需要在B中通过^和$限定A开头和结尾的字符。 +1. regexp:用法:A regexp B,AB均为字符串,A是待匹配的字符串,B是正则表达式。若A、B其中之一为null则返回false。若A中的任意子串可以匹配B则返回true,否则返回false。如果要让整个A串与B匹配才返回true,需要在B中通过^和$限定A开头和结尾的字符。 -② rlike:等价于regexp。 +2. rlike:等价于regexp。 (3)执行步骤 -① 首日装载 +1. 首日装载 a)筛选ods_user_info_inc表当日分区的数据,对用户姓名、电话号码、邮箱地址做脱敏处理。其中电话号码、邮箱地址在加密前要校验格式是否合法,若不合法则返回null。用户的姓名可能被用于姓氏相关的统计,保留姓氏,手机号可能用于运营商相关统计,保留前三位,邮箱可能用于邮箱类型相关统计,保留@及之后的内容。 @@ -3200,7 +2979,7 @@ b)定义两个字段:start_date和end_date。 c)筛选统计所须的其它字段,写入9999-12-31分区。 -② 每日装载 +2. 每日装载 a)t1子查询 @@ -3237,197 +3016,121 @@ t2子查询包含了昨日和当日最新的用户数据,它们将进入两个 (4)图解 -① 分区规划 - -② 数据流向 - -③ 数据装载 - -(5)代码实现 - -① 首日装载 - -insert overwrite table dim_user_zip partition (dt = '9999-12-31') - -select data.id, - -concat(substr(data.name, 1, 1), '*') name, - -if(data.phone_num regexp '^(13[0-9]|14[01456879]|15[0-35-9]|16[2567]|17[0-8]|18[0-9]|19[0-35-9])\\d{8}$', - -concat(substr(data.phone_num, 1, 3), '*'), null) phone_num, - -if(data.email regexp '^[a-zA-Z0-9_-]+@[a-zA-Z0-9_-]+(\\.[a-zA-Z0-9_-]+)+$', +1. 分区规划 -concat('*@', split(data.email, '@')[1]), null) email, + ![image-20241030170441861](电商数仓项目-电商数据仓库系统4/image-20241030170441861.png) -data.user_level, +2. 数据流向 -data.birthday, + ![image-20241030170455732](电商数仓项目-电商数据仓库系统4/image-20241030170455732.png) -data.gender, +3. 数据装载 -data.create_time, + ![image-20241030170530045](电商数仓项目-电商数据仓库系统4/image-20241030170530045.png) -data.operate_time, + ![image-20241030170609366](电商数仓项目-电商数据仓库系统4/image-20241030170609366.png) -'2022-06-08' start_date, +(5)代码实现 -'9999-12-31' end_date +1. 首日装载 +```hive +insert overwrite table dim_user_zip partition (dt = '9999-12-31') +select data.id, + concat(substr(data.name, 1, 1), '*') name, + if(data.phone_num regexp '^(13[0-9]|14[01456879]|15[0-35-9]|16[2567]|17[0-8]|18[0-9]|19[0-35-9])\\d{8}$', + concat(substr(data.phone_num, 1, 3), '*'), null) phone_num, + if(data.email regexp '^[a-zA-Z0-9_-]+@[a-zA-Z0-9_-]+(\\.[a-zA-Z0-9_-]+)+$', + concat('*@', split(data.email, '@')[1]), null) email, + data.user_level, + data.birthday, + data.gender, + data.create_time, + data.operate_time, + '2022-06-08' start_date, + '9999-12-31' end_date from ods_user_info_inc - where dt = '2022-06-08' + and type = 'bootstrap-insert'; +``` -and type = 'bootstrap-insert'; - -② 每日装载 +2. 每日装载 +```hive set hive.exec.dynamic.partition.mode=nonstrict; - insert overwrite table dim_user_zip partition (dt) - -select id, - -name, - -phone_num, - -email, - -user_level, - -birthday, - -gender, - -create_time, - -operate_time, - -start_date, - -if(rn = 2, date_sub('2022-06-09', 1), end_date) end_date, - -if(rn = 1, '9999-12-31', date_sub('2022-06-09', 1)) dt - -from ( - -select id, - -name, - -phone_num, - -email, - -user_level, - -birthday, - -gender, - -create_time, - -operate_time, - -start_date, - -end_date, - -row_number() over (partition by id order by start_date desc) rn - -from ( - -select id, - -name, - -phone_num, - -email, - -user_level, - -birthday, - -gender, - -create_time, - -operate_time, - -start_date, - -end_date - -from dim_user_zip - -where dt = '9999-12-31' - -union - select id, - -concat(substr(name, 1, 1), '*') name, - -if(phone_num regexp - -'^(13[0-9]|14[01456879]|15[0-35-9]|16[2567]|17[0-8]|18[0-9]|19[0-35-9])\\d{8}$', - -concat(substr(phone_num, 1, 3), '*'), null) phone_num, - -if(email regexp '^[a-zA-Z0-9_-]+@[a-zA-Z0-9_-]+(\\.[a-zA-Z0-9_-]+)+$', - -concat('*@', split(email, '@')[1]), null) email, - -user_level, - -birthday, - -gender, - -create_time, - -operate_time, - -'2022-06-09' start_date, - -'9999-12-31' end_date - + name, + phone_num, + email, + user_level, + birthday, + gender, + create_time, + operate_time, + start_date, + if(rn = 2, date_sub('2022-06-09', 1), end_date) end_date, + if(rn = 1, '9999-12-31', date_sub('2022-06-09', 1)) dt from ( - -select data.id, - -data.name, - -data.phone_num, - -data.email, - -data.user_level, - -data.birthday, - -data.gender, - -data.create_time, - -data.operate_time, - -row_number() over (partition by data.id order by ts desc) rn - -from ods_user_info_inc - -where dt = '2022-06-09' - -) t1 - -where rn = 1 - -) t2 - -) t3; + select id, + name, + phone_num, + email, + user_level, + birthday, + gender, + create_time, + operate_time, + start_date, + end_date, + row_number() over (partition by id order by start_date desc) rn + from ( + select id, + name, + phone_num, + email, + user_level, + birthday, + gender, + create_time, + operate_time, + start_date, + end_date + from dim_user_zip + where dt = '9999-12-31' + union + select id, + concat(substr(name, 1, 1), '*') name, + if(phone_num regexp + '^(13[0-9]|14[01456879]|15[0-35-9]|16[2567]|17[0-8]|18[0-9]|19[0-35-9])\\d{8}$', + concat(substr(phone_num, 1, 3), '*'), null) phone_num, + if(email regexp '^[a-zA-Z0-9_-]+@[a-zA-Z0-9_-]+(\\.[a-zA-Z0-9_-]+)+$', + concat('*@', split(email, '@')[1]), null) email, + user_level, + birthday, + gender, + create_time, + operate_time, + '2022-06-09' start_date, + '9999-12-31' end_date + from ( + select data.id, + data.name, + data.phone_num, + data.email, + data.user_level, + data.birthday, + data.gender, + data.create_time, + data.operate_time, + row_number() over (partition by data.id order by ts desc) rn + from ods_user_info_inc + where dt = '2022-06-09' + ) t1 + where rn = 1 + ) t2 + ) t3; +``` ## 8.9 数据装载脚本 diff --git "a/source/_posts/\347\224\265\345\225\206\346\225\260\344\273\223\351\241\271\347\233\256-\347\224\265\345\225\206\346\225\260\346\215\256\344\273\223\345\272\223\347\263\273\347\273\2374/image-20241030100155584.png" "b/source/_posts/\347\224\265\345\225\206\346\225\260\344\273\223\351\241\271\347\233\256-\347\224\265\345\225\206\346\225\260\346\215\256\344\273\223\345\272\223\347\263\273\347\273\2374/image-20241030100155584.png" new file mode 100644 index 0000000000000000000000000000000000000000..47303c6be81a1ec8c6142c44d3b483425b0f1aa8 GIT binary patch literal 12959 zcmbumbyQnV)HZsM7MJ3sNDCCV;tmChyHniVo!~7{+zC$c;>8J0DMbUt9U9!-^$Wju zz2E)!-gUFGvSyu3W=@`&*?T|x*(X9pNg4~C6deEnELj;zH2^>|gtyI65#gV&>paf@ z;4L64`BB3=>tM;p3*Rb-?bs;g(!Y+yr|BdT%dl%UNEd%vOkn99){eOV%~D+!|CQpo zeDl^KXiI5SVdan}TZxw@4LQCCm6eP^;mL`Kx}4Sjeme@bBEzCi_`B5V#St!o 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