数仓搭建-DIM层

1 商品维度表（全量）

建表语句

DROP TABLE IF EXISTS dim_sku_info;
CREATE EXTERNAL TABLE dim_sku_info (
    `id` STRING COMMENT '商品id',
    `price` DECIMAL(16,2) COMMENT '商品价格',
    `sku_name` STRING COMMENT '商品名称',
    `sku_desc` STRING COMMENT '商品描述',
    `weight` DECIMAL(16,2) COMMENT '重量',
    `is_sale` BOOLEAN COMMENT '是否在售',
    `spu_id` STRING COMMENT 'spu编号',
    `spu_name` STRING COMMENT 'spu名称',
    `category3_id` STRING COMMENT '三级分类id',
    `category3_name` STRING COMMENT '三级分类名称',
    `category2_id` STRING COMMENT '二级分类id',
    `category2_name` STRING COMMENT '二级分类名称',
    `category1_id` STRING COMMENT '一级分类id',
    `category1_name` STRING COMMENT '一级分类名称',
    `tm_id` STRING COMMENT '品牌id',
    `tm_name` STRING COMMENT '品牌名称',
    `sku_attr_values` ARRAY<STRUCT<attr_id:STRING,value_id:STRING,attr_name:STRING,value_name:STRING>> COMMENT '平台属性',
    `sku_sale_attr_values` ARRAY<STRUCT<sale_attr_id:STRING,sale_attr_value_id:STRING,sale_attr_name:STRING,sale_attr_value_name:STRING>> COMMENT '销售属性',
    `create_time` STRING COMMENT '创建时间'
) COMMENT '商品维度表'
PARTITIONED BY (`dt` STRING)
STORED AS PARQUET
LOCATION '/warehouse/gmall/dim/dim_sku_info/'
TBLPROPERTIES ("parquet.compression"="lzo");

 数据装载思路

 

 装载语句：

首日装载

with
sku as
(
    select
        id,
        price,
        sku_name,
        sku_desc,
        weight,
        is_sale,
        spu_id,
        category3_id,
        tm_id,
        create_time
    from ods_sku_info
    where dt='2020-06-14'
),
spu as
(
    select
        id,
        spu_name
    from ods_spu_info
    where dt='2020-06-14'
),
c3 as
(
    select
        id,
        name,
        category2_id
    from ods_base_category3
    where dt='2020-06-14'
),
c2 as
(
    select
        id,
        name,
        category1_id
    from ods_base_category2
    where dt='2020-06-14'
),
c1 as
(
    select
        id,
        name
    from ods_base_category1
    where dt='2020-06-14'
),
tm as
(
    select
        id,
        tm_name
    from ods_base_trademark
    where dt='2020-06-14'
),
attr as
(
    select
        sku_id,
        collect_set(named_struct('attr_id',attr_id,'value_id',value_id,'attr_name',attr_name,'value_name',value_name)) attrs
    from ods_sku_attr_value
    where dt='2020-06-14'
    group by sku_id
),
sale_attr as
(
    select
        sku_id,
        collect_set(named_struct('sale_attr_id',sale_attr_id,'sale_attr_value_id',sale_attr_value_id,'sale_attr_name',sale_attr_name,'sale_attr_value_name',sale_attr_value_name)) sale_attrs
    from ods_sku_sale_attr_value
    where dt='2020-06-14'
    group by sku_id
)
insert overwrite table dim_sku_info partition(dt='2020-06-14')
select
    sku.id,
    sku.price,
    sku.sku_name,
    sku.sku_desc,
    sku.weight,
    sku.is_sale,
    sku.spu_id,
    spu.spu_name,
    sku.category3_id,
    c3.name,
    c3.category2_id,
    c2.name,
    c2.category1_id,
    c1.name,
    sku.tm_id,
    tm.tm_name,
    attr.attrs,
    sale_attr.sale_attrs,
    sku.create_time
from sku
left join spu on sku.spu_id=spu.id
left join c3 on sku.category3_id=c3.id
left join c2 on c3.category2_id=c2.id
left join c1 on c2.category1_id=c1.id
left join tm on sku.tm_id=tm.id
left join attr on sku.id=attr.sku_id
left join sale_attr on sku.id=sale_attr.sku_id;

先创建商品维度表，再执行装载语句：

 查看商品维度表中的结果

 出现异常的原因：会先将索引文件当成小文件合并，将其当做普通文件处理。更严重的是，这会导致LZO文件无法切片。

 解决索引文件被误合并的问题：（关闭hive的mat端的小文件合并）

解决办法：修改CombineHiveInputFormat为HiveInputFormat

hive (gmall)>

set hive.input.format=org.apache.hadoop.hive.ql.io.HiveInputFormat;

 再来执行一下装载语句

（insert overwrite会把原来的数据覆盖掉，所以可以多次执行装载语句）

 2 优惠券维度表（全量）

建表语句

DROP TABLE IF EXISTS dim_coupon_info;
CREATE EXTERNAL TABLE dim_coupon_info(
    `id` STRING COMMENT '购物券编号',
    `coupon_name` STRING COMMENT '购物券名称',
    `coupon_type` STRING COMMENT '购物券类型 1 现金券 2 折扣券 3 满减券 4 满件打折券',
    `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 '减金额',
    `benefit_discount` DECIMAL(16,2) COMMENT '折扣',
    `create_time` STRING COMMENT '创建时间',
    `range_type` STRING COMMENT '范围类型 1、商品 2、品类 3、品牌',
    `limit_num` BIGINT COMMENT '最多领取次数',
    `taken_count` BIGINT COMMENT '已领取次数',
    `start_time` STRING COMMENT '可以领取的开始日期',
    `end_time` STRING COMMENT '可以领取的结束日期',
    `operate_time` STRING COMMENT '