电商数仓（四）：电商数据仓库实战

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本文为学习笔记，对应视频教程来自【尚硅谷】电商数仓V5.0

数据仓库环境准备

数据仓库运行环境

Hive环境搭建
Hive引擎简介

Hive引擎包括：默认MR、tez、spark

Hive on Spark：Hive既作为存储元数据又负责SQL的解析优化，语法是HQL语法，执行引擎变成了Spark，Spark负责采用RDD执行。

Spark on Hive : Hive只作为存储元数据，Spark负责SQL解析优化，语法是Spark SQL语法，Spark负责采用RDD执行。

Hive on Spark配置

官网下载的Hive3.1.2和Spark3.0.0默认是不兼容的。因为Hive3.1.2支持的Spark版本是2.4.5，所以需要我们重新编译Hive3.1.2版本。

编译步骤：官网下载Hive3.1.2源码，修改pom文件中引用的Spark版本为3.0.0，如果编译通过，直接打包获取jar包。如果报错，就根据提示，修改相关方法，直到不报错，打包获取jar包。

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# 1.在Hive所在节点部署Spark
[eitan@hadoop102 ~]$ tar -zxf /opt/software/spark-3.0.0-bin-hadoop3.2.tgz -C /opt/module/
[eitan@hadoop102 ~]$ mv /opt/module/spark-3.0.0-bin-hadoop3.2/ /opt/module/spark

# 2.配置SPARK_HOME环境变量
[eitan@hadoop102 ~]$ sudo vim /etc/profile.d/my_env.sh 
# SPARK_HOME
export SPARK_HOME=/opt/module/spark
export PATH=$PATH:$SPARK_HOME/bin

# 3.在hive中创建spark配置文件
[eitan@hadoop102 ~]$ vim /opt/module/hive/conf/spark-defaults.conf
spark.master                             yarn
spark.eventLog.enabled                   true
spark.eventLog.dir                       hdfs://hadoop102:8020/spark-history
spark.executor.memory                    1g
spark.driver.memory                      1g

[eitan@hadoop102 ~]$ hadoop fs -mkdir /spark-history

# 4.向HDFS上传Spark纯净版jar包
[eitan@hadoop102 ~]$ tar -zxf /opt/software/spark-3.0.0-bin-without-hadoop.tgz
[eitan@hadoop102 ~]$ hadoop fs -mkdir /spark-jars
[eitan@hadoop102 ~]$ hadoop fs -put ./spark-3.0.0-bin-without-hadoop/jars/* /spark-jars

# 5.修改hive-site.xml文件
[eitan@hadoop102 ~]$ vim /opt/module/hive/conf/hive-site.xml 
    <!-- Spark依赖位置（注意：端口号8020必须和namenode的端口号一致）-->
    <property>
        <name>spark.yarn.jars</name>
        <value>hdfs://hadoop102:8020/spark-jars/*</value>
    </property>

    <!-- Hive执行引擎 -->
    <property>
        <name>hive.execution.engine</name>
        <value>spark</value>
    </property>
    
# 6.Hive on Spark测试
hive (default)> create table student(id int, name string);
hive (default)> insert into table student values(1,'abc');
--------------------------------------------------------------------------------------
          STAGES   ATTEMPT        STATUS  TOTAL  COMPLETED  RUNNING  PENDING  FAILED  
--------------------------------------------------------------------------------------
Stage-0 ........         0      FINISHED      1          1        0        0       0  
Stage-1 ........         0      FINISHED      1          1        0        0       0  
--------------------------------------------------------------------------------------
STAGES: 02/02    [==========================>>] 100%  ELAPSED TIME: 21.24 s    
--------------------------------------------------------------------------------------

hive (default)> insert into table student values(2,'def');
--------------------------------------------------------------------------------------
          STAGES   ATTEMPT        STATUS  TOTAL  COMPLETED  RUNNING  PENDING  FAILED  
--------------------------------------------------------------------------------------
Stage-2 ........         0      FINISHED      1          1        0        0       0  
Stage-3 ........         0      FINISHED      1          1        0        0       0  
--------------------------------------------------------------------------------------
STAGES: 02/02    [==========================>>] 100%  ELAPSED TIME: 12.07 s    
--------------------------------------------------------------------------------------
Yarn环境配置
增加ApplicationMaster资源比例

容量调度器对每个资源队列中同时运行的Application Master占用的资源进行了限制，该限制通过yarn.scheduler.capacity.maximum-am-resource-percent参数实现，其默认值是0.1，表示每个资源队列上Application Master最多可使用的资源为该队列总资源的10%，目的是防止大部分资源都被Application Master占用，而导致Map/Reduce Task无法执行。

生产环境该参数可使用默认值。但学习环境，集群资源总数很少，如果只分配10%的资源给Application Master，则可能出现，同一时刻只能运行一个Job的情况，因为一个Application Master使用的资源就可能已经达到10%的上限了。故此处可将该值适当调大。

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# 1.在hadoop102的/opt/module/hadoop-3.1.3/etc/hadoop/capacity-scheduler.xml文件中修改如下参数值
[eitan@hadoop102 ~]$ vim /opt/module/hadoop-3.1.3/etc/hadoop/capacity-scheduler.xml
  <property>
    <name>yarn.scheduler.capacity.maximum-am-resource-percent</name>
    <value>0.8</value>
    <description>
      Maximum percent of resources in the cluster which can be used to run
      application masters i.e. controls number of concurrent running
      applications.
    </description>
  </property>

# 2.分发capacity-scheduler.xml配置文件
[eitan@hadoop102 ~]$ xsync /opt/module/hadoop-3.1.3/etc/hadoop/capacity-scheduler.xml

# 3.关闭正在运行的任务，重新启动yarn集群
[eitan@hadoop103 ~]$ /opt/module/hadoop-3.1.3/sbin/stop-yarn.sh
[eitan@hadoop103 ~]$ /opt/module/hadoop-3.1.3/sbin/start-yarn.sh

数据仓库开发环境

启动HiveServer2
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[eitan@hadoop102 ~]$ /opt/module/hive/bin/hiveserver2
配置DataGrip连接

image-20220608110007888

模拟数据准备

通常企业在开始搭建数仓时，业务系统中会存在历史数据，一般是业务数据库存在历史数据，而用户行为日志无历史数据。假定数仓上线的日期为2020-06-14，为模拟真实场景，需准备以下数据。注：在执行以下操作之前，先将HDFS上/origin_data路径下之前的数据删除。

用户行为日志

用户行为日志，一般是没有历史数据的，故日志只需要准备2020-06-14一天的数据。

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# 1.启动日志采集通道，包括Flume、Kafak等
[eitan@hadoop102 ~]$ myhadoop.sh start
[eitan@hadoop102 ~]$ zk.sh start

[eitan@hadoop102 ~]$ kf.sh start
[eitan@hadoop102 ~]$ f1.sh start
[eitan@hadoop102 ~]$ f2.sh start


# 2.修改两个日志服务器（hadoop102、hadoop103）中的 /opt/module/applog/application.yml配置文件，将mock.date参数改为2020-06-14
[eitan@hadoop102 ~]$ vim /opt/module/applog/application.yml
#业务日期
mock.date: "2020-06-14"

[eitan@hadoop102 ~]$ xsync /opt/module/applog/application.yml
# 3.执行日志生成脚本lg.sh
[eitan@hadoop102 ~]$ lg.sh
业务数据
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# 1.业务数据一般存在历史数据，此处需准备2020-06-10至2020-06-14的数据
[eitan@hadoop102 ~]$ cd /opt/module/db_log/

[eitan@hadoop102 db_log]$ vim application.properties
#业务日期
mock.date=2020-06-10
#是否重置，首日须置为1，之后置为0
mock.clear=1
#是否重置用户，首日须置为1，之后置为0
mock.clear.user=1

[eitan@hadoop102 db_log]$ java -jar gmall2020-mock-db-2021-11-14.jar

[eitan@hadoop102 db_log]$ vim application.properties
#业务日期
mock.date=2020-06-11
#是否重置，首日须置为1，之后置为0
mock.clear=0
#是否重置用户，首日须置为1，之后置为0
mock.clear.user=0

[eitan@hadoop102 db_log]$ java -jar gmall2020-mock-db-2021-11-14.jar 

# 2.全量表同步
[eitan@hadoop102 ~]$ mysql_to_hdfs_full.sh all 2020-06-14

# 3.增量同步，先清空maxwell数据库里的表
[eitan@hadoop102 ~]$ vim /opt/module/maxwell/config.properties
mock_date=2020-06-14

[eitan@hadoop102 ~]$ mxw.sh start
[eitan@hadoop102 ~]$ f3.sh start

[eitan@hadoop102 ~]$ mysql_to_kafka_inc_init.sh all

数仓开发之ODS层

ODS层的设计要点如下：

  1. ODS层的表结构设计依托于从业务系统同步过来的数据结构。
  2. ODS层要保存全部历史数据，故其压缩格式应选择压缩比较高的，此处选择gzip。
  3. ODS层表名的命名规范为：ods_表名_单分区增量全量标识（inc/full）。

日志表

建表数据
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-- 创建静态分区外部表
DROP TABLE IF EXISTS ods_log_inc;

CREATE EXTERNAL TABLE ods_log_inc
(
    `common`   STRUCT<ar :STRING,ba :STRING,ch :STRING,is_new :STRING,md :STRING,mid :STRING,os :STRING,uid :STRING,vc
                      :STRING> COMMENT '公共信息',
    `page`     STRUCT<during_time :STRING,item :STRING,item_type :STRING,last_page_id :STRING,page_id
                      :STRING,source_type :STRING> COMMENT '页面信息',
    `actions`  ARRAY<STRUCT<action_id:STRING,item:STRING,item_type:STRING,ts:BIGINT>> COMMENT '动作信息',
    `displays` ARRAY<STRUCT<display_type :STRING,item :STRING,item_type :STRING,`order` :STRING,pos_id
                            :STRING>> COMMENT '曝光信息',
    `start`    STRUCT<entry :STRING,loading_time :BIGINT,open_ad_id :BIGINT,open_ad_ms :BIGINT,open_ad_skip_ms
                      :BIGINT> COMMENT '启动信息',
    `err`      STRUCT<error_code:BIGINT,msg:STRING> COMMENT '错误信息',
    `ts`       BIGINT COMMENT '时间戳'
) COMMENT '活动信息表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.JsonSerDe'
    LOCATION '/warehouse/gmall/ods/ods_log_inc/';
解决DataGrip元数据显示问题
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[eitan@hadoop102 ~]$ vim /opt/module/hive/conf/hive-site.xml
    <!-- 解决DataGrip元数据显示问题 -->
    <property>
        <name>metastore.storage.schema.reader.impl</name>
        <value>org.apache.hadoop.hive.metastore.SerDeStorageSchemaReader</value>
    </property>

每日数据装载脚本
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[eitan@hadoop102 ~]$ vim ~/bin/hdfs_to_ods_log.sh
#!/bin/bash

# 定义变量方便修改
APP=gmall

# 如果是输入的日期按照取输入日期；如果没输入日期取当前时间的前一天
if [ -n "$1" ] ;then
   do_date=$1
else
   do_date=`date -d "-1 day" +%F`
fi

echo ================== 日志日期为 $do_date ==================
sql="
load data inpath '/origin_data/$APP/log/topic_log/$do_date' into table ${APP}.ods_log_inc partition(dt='$do_date');
"
hive -e "$sql"

[eitan@hadoop102 ~]$ chmod u+x ~/bin/hdfs_to_ods_log.sh

[eitan@hadoop102 ~]$ hdfs_to_ods_log.sh 2020-06-14

业务表

活动信息表（全量表）
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DROP TABLE IF EXISTS ods_activity_info_full;
CREATE EXTERNAL TABLE ods_activity_info_full
(
    `id`            STRING COMMENT '活动id',
    `activity_name` STRING COMMENT '活动名称',
    `activity_type` STRING COMMENT '活动类型',
    `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'
) COMMENT '活动信息表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
        NULL DEFINED AS ''
    LOCATION '/warehouse/gmall/ods/ods_activity_info_full/';
活动规则表（全量表）
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DROP TABLE IF EXISTS ods_activity_rule_full;
CREATE EXTERNAL TABLE ods_activity_rule_full
(
    `id`               STRING COMMENT '编号',
    `activity_id`      STRING COMMENT '类型',
    `activity_type`    STRING COMMENT '活动类型',
    `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_level`    STRING COMMENT '优惠级别'
) COMMENT '活动规则表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
        NULL DEFINED AS ''
    LOCATION '/warehouse/gmall/ods/ods_activity_rule_full/';
一级品类表（全量表）
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DROP TABLE IF EXISTS ods_base_category1_full;
CREATE EXTERNAL TABLE ods_base_category1_full
(
    `id`   STRING COMMENT '编号',
    `name` STRING COMMENT '分类名称'
) COMMENT '一级品类表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
        NULL DEFINED AS ''
    LOCATION '/warehouse/gmall/ods/ods_base_category1_full/';
二级品类表（全量表）
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DROP TABLE IF EXISTS ods_base_category2_full;
CREATE EXTERNAL TABLE ods_base_category2_full
(
    `id`           STRING COMMENT '编号',
    `name`         STRING COMMENT '二级分类名称',
    `category1_id` STRING COMMENT '一级分类编号'
) COMMENT '二级品类表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
        NULL DEFINED AS ''
    LOCATION '/warehouse/gmall/ods/ods_base_category2_full/';
三级品类表（全量表）
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DROP TABLE IF EXISTS ods_base_category3_full;
CREATE EXTERNAL TABLE ods_base_category3_full
(
    `id`           STRING COMMENT '编号',
    `name`         STRING COMMENT '三级分类名称',
    `category2_id` STRING COMMENT '二级分类编号'
) COMMENT '三级品类表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
        NULL DEFINED AS ''
    LOCATION '/warehouse/gmall/ods/ods_base_category3_full/';
编码字典表（全量表）
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DROP TABLE IF EXISTS ods_base_dic_full;
CREATE EXTERNAL TABLE ods_base_dic_full
(
    `dic_code`     STRING COMMENT '编号',
    `dic_name`     STRING COMMENT '编码名称',
    `parent_code`  STRING COMMENT '父编号',
    `create_time`  STRING COMMENT '创建日期',
    `operate_time` STRING COMMENT '修改日期'
) COMMENT '编码字典表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
        NULL DEFINED AS ''
    LOCATION '/warehouse/gmall/ods/ods_base_dic_full/';
省份表（全量表）
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DROP TABLE IF EXISTS ods_base_province_full;
CREATE EXTERNAL TABLE ods_base_province_full
(
    `id`         STRING COMMENT '编号',
    `name`       STRING COMMENT '省份名称',
    `region_id`  STRING COMMENT '地区ID',
    `area_code`  STRING COMMENT '地区编码',
    `iso_code`   STRING COMMENT '旧版ISO-3166-2编码，供可视化使用',
    `iso_3166_2` STRING COMMENT '新版IOS-3166-2编码，供可视化使用'
) COMMENT '省份表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
        NULL DEFINED AS ''
    LOCATION '/warehouse/gmall/ods/ods_base_province_full/';
地区表（全量表）
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DROP TABLE IF EXISTS ods_base_region_full;
CREATE EXTERNAL TABLE ods_base_region_full
(
    `id`          STRING COMMENT '编号',
    `region_name` STRING COMMENT '地区名称'
) COMMENT '地区表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
        NULL DEFINED AS ''
    LOCATION '/warehouse/gmall/ods/ods_base_region_full/';
品牌表（全量表）
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DROP TABLE IF EXISTS ods_base_trademark_full;
CREATE EXTERNAL TABLE ods_base_trademark_full
(
    `id`       STRING COMMENT '编号',
    `tm_name`  STRING COMMENT '品牌名称',
    `logo_url` STRING COMMENT '品牌logo的图片路径'
) COMMENT '品牌表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
        NULL DEFINED AS ''
    LOCATION '/warehouse/gmall/ods/ods_base_trademark_full/';
购物车表（全量表）
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DROP TABLE IF EXISTS ods_cart_info_full;
CREATE EXTERNAL TABLE ods_cart_info_full
(
    `id`           STRING COMMENT '编号',
    `user_id`      STRING COMMENT '用户id',
    `sku_id`       STRING COMMENT 'sku_id',
    `cart_price`   DECIMAL(16, 2) COMMENT '放入购物车时价格',
    `sku_num`      BIGINT COMMENT '数量',
    `img_url`      BIGINT COMMENT '商品图片地址',
    `sku_name`     STRING COMMENT 'sku名称 (冗余)',
    `is_checked`   STRING COMMENT '是否被选中',
    `create_time`  STRING COMMENT '创建时间',
    `operate_time` STRING COMMENT '修改时间',
    `is_ordered`   STRING COMMENT '是否已经下单',
    `order_time`   STRING COMMENT '下单时间',
    `source_type`  STRING COMMENT '来源类型',
    `source_id`    STRING COMMENT '来源编号'
) COMMENT '购物车全量表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
        NULL DEFINED AS ''
    LOCATION '/warehouse/gmall/ods/ods_cart_info_full/';
优惠券信息表（全量表）
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DROP TABLE IF EXISTS ods_coupon_info_full;
CREATE EXTERNAL TABLE ods_coupon_info_full
(
    `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 '最多领用次数',
    `taken_count`      BIGINT COMMENT '已领用次数',
    `start_time`       STRING COMMENT '开始领取时间',
    `end_time`         STRING COMMENT '结束领取时间',
    `operate_time`     STRING COMMENT '修改时间',
    `expire_time`      STRING COMMENT '过期时间'
) COMMENT '优惠券信息表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
        NULL DEFINED AS ''
    LOCATION '/warehouse/gmall/ods/ods_coupon_info_full/';
商品平台属性表（全量表）
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DROP TABLE IF EXISTS ods_sku_attr_value_full;
CREATE EXTERNAL TABLE ods_sku_attr_value_full
(
    `id`         STRING COMMENT '编号',
    `attr_id`    STRING COMMENT '平台属性ID',
    `value_id`   STRING COMMENT '平台属性值ID',
    `sku_id`     STRING COMMENT '商品ID',
    `attr_name`  STRING COMMENT '平台属性名称',
    `value_name` STRING COMMENT '平台属性值名称'
) COMMENT 'sku平台属性表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
        NULL DEFINED AS ''
    LOCATION '/warehouse/gmall/ods/ods_sku_attr_value_full/';
商品表（全量表）
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DROP TABLE IF EXISTS ods_sku_info_full;
CREATE EXTERNAL TABLE ods_sku_info_full
(
    `id`              STRING COMMENT 'skuId',
    `spu_id`          STRING COMMENT 'spuid',
    `price`           DECIMAL(16, 2) COMMENT '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',
    `tm_id`           STRING COMMENT '品牌id',
    `category3_id`    STRING COMMENT '品类id',
    `sku_default_igm` STRING COMMENT '商品图片地址',
    `is_sale`         STRING COMMENT '是否在售',
    `create_time`     STRING COMMENT '创建时间'
) COMMENT 'SKU商品表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
        NULL DEFINED AS ''
    LOCATION '/warehouse/gmall/ods/ods_sku_info_full/';
商品销售属性值表（全量表）
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DROP TABLE IF EXISTS ods_sku_sale_attr_value_full;
CREATE EXTERNAL TABLE ods_sku_sale_attr_value_full
(
    `id`                   STRING COMMENT '编号',
    `sku_id`               STRING COMMENT 'sku_id',
    `spu_id`               STRING COMMENT 'spu_id',
    `sale_attr_value_id`   STRING COMMENT '销售属性值id',
    `sale_attr_id`         STRING COMMENT '销售属性id',
    `sale_attr_name`       STRING COMMENT '销售属性名称',
    `sale_attr_value_name` STRING COMMENT '销售属性值名称'
) COMMENT 'sku销售属性名称'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
        NULL DEFINED AS ''
    LOCATION '/warehouse/gmall/ods/ods_sku_sale_attr_value_full/';
SPU表（全量表）
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DROP TABLE IF EXISTS ods_spu_info_full;
CREATE EXTERNAL TABLE ods_spu_info_full
(
    `id`           STRING COMMENT 'spu_id',
    `spu_name`     STRING COMMENT 'spu名称',
    `description`  STRING COMMENT '描述信息',
    `category3_id` STRING COMMENT '品类id',
    `tm_id`        STRING COMMENT '品牌id'
) COMMENT 'SPU商品表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
        NULL DEFINED AS ''
    LOCATION '/warehouse/gmall/ods/ods_spu_info_full/';
购物车表（增量表）
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DROP TABLE IF EXISTS ods_cart_info_inc;
CREATE EXTERNAL TABLE ods_cart_info_inc
(
    `type` STRING COMMENT '变动类型',
    `ts`   BIGINT COMMENT '变动时间',
    `data` STRUCT<id :STRING,user_id :STRING,sku_id :STRING,cart_price :DECIMAL(16, 2),sku_num :BIGINT,img_url :STRING,sku_name
                  :STRING,is_checked :STRING,create_time :STRING,operate_time :STRING,is_ordered :STRING,order_time
                  :STRING,source_type :STRING,source_id :STRING> COMMENT '数据',
    `old`  MAP<STRING,STRING> COMMENT '旧值'
) COMMENT '购物车增量表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.JsonSerDe'
    LOCATION '/warehouse/gmall/ods/ods_cart_info_inc/';
评论表（增量表）
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DROP TABLE IF EXISTS ods_comment_info_inc;
CREATE EXTERNAL TABLE ods_comment_info_inc
(
    `type` STRING COMMENT '变动类型',
    `ts`   BIGINT COMMENT '变动时间',
    `data` STRUCT<id :STRING,user_id :STRING,nick_name :STRING,head_img :STRING,sku_id :STRING,spu_id :STRING,order_id
                  :STRING,appraise :STRING,comment_txt :STRING,create_time :STRING,operate_time :STRING> COMMENT '数据',
    `old`  MAP<STRING,STRING> COMMENT '旧值'
) COMMENT '评价表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.JsonSerDe'
    LOCATION '/warehouse/gmall/ods/ods_comment_info_inc/';
优惠券领用表（增量表）
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DROP TABLE IF EXISTS ods_coupon_use_inc;
CREATE EXTERNAL TABLE ods_coupon_use_inc
(
    `type` STRING COMMENT '变动类型',
    `ts`   BIGINT COMMENT '变动时间',
    `data` STRUCT<id :STRING,coupon_id :STRING,user_id :STRING,order_id :STRING,coupon_status :STRING,get_time :STRING,using_time
                  :STRING,used_time :STRING,expire_time :STRING> COMMENT '数据',
    `old`  MAP<STRING,STRING> COMMENT '旧值'
) COMMENT '优惠券领用表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.JsonSerDe'
    LOCATION '/warehouse/gmall/ods/ods_coupon_use_inc/';
收藏表（增量表）
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DROP TABLE IF EXISTS ods_favor_info_inc;
CREATE EXTERNAL TABLE ods_favor_info_inc
(
    `type` STRING COMMENT '变动类型',
    `ts`   BIGINT COMMENT '变动时间',
    `data` STRUCT<id :STRING,user_id :STRING,sku_id :STRING,spu_id :STRING,is_cancel :STRING,create_time :STRING,cancel_time
                  :STRING> COMMENT '数据',
    `old`  MAP<STRING,STRING> COMMENT '旧值'
) COMMENT '收藏表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.JsonSerDe'
    LOCATION '/warehouse/gmall/ods/ods_favor_info_inc/';
订单明细表（增量表）
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DROP TABLE IF EXISTS ods_order_detail_inc;
CREATE EXTERNAL TABLE ods_order_detail_inc
(
    `type` STRING COMMENT '变动类型',
    `ts`   BIGINT COMMENT '变动时间',
    `data` STRUCT<id :STRING,order_id :STRING,sku_id :STRING,sku_name :STRING,img_url :STRING,order_price
                  :DECIMAL(16, 2),sku_num :BIGINT,create_time :STRING,source_type :STRING,source_id :STRING,split_total_amount
                  :DECIMAL(16, 2),split_activity_amount :DECIMAL(16, 2),split_coupon_amount
                  :DECIMAL(16, 2)> COMMENT '数据',
    `old`  MAP<STRING,STRING> COMMENT '旧值'
) COMMENT '订单明细表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.JsonSerDe'
    LOCATION '/warehouse/gmall/ods/ods_order_detail_inc/';
订单明细活动关联表（增量表）
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DROP TABLE IF EXISTS ods_order_detail_activity_inc;
CREATE EXTERNAL TABLE ods_order_detail_activity_inc
(
    `type` STRING COMMENT '变动类型',
    `ts`   BIGINT COMMENT '变动时间',
    `data` STRUCT<id :STRING,order_id :STRING,order_detail_id :STRING,activity_id :STRING,activity_rule_id :STRING,sku_id
                  :STRING,create_time :STRING> COMMENT '数据',
    `old`  MAP<STRING,STRING> COMMENT '旧值'
) COMMENT '订单明细活动关联表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.JsonSerDe'
    LOCATION '/warehouse/gmall/ods/ods_order_detail_activity_inc/';
订单明细优惠券关联表（增量表）
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DROP TABLE IF EXISTS ods_order_detail_coupon_inc;
CREATE EXTERNAL TABLE ods_order_detail_coupon_inc
(
    `type` STRING COMMENT '变动类型',
    `ts`   BIGINT COMMENT '变动时间',
    `data` STRUCT<id :STRING,order_id :STRING,order_detail_id :STRING,coupon_id :STRING,coupon_use_id :STRING,sku_id
                  :STRING,create_time :STRING> COMMENT '数据',
    `old`  MAP<STRING,STRING> COMMENT '旧值'
) COMMENT '订单明细优惠券关联表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.JsonSerDe'
    LOCATION '/warehouse/gmall/ods/ods_order_detail_coupon_inc/';
订单表（增量表）
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DROP TABLE IF EXISTS ods_order_info_inc;
CREATE EXTERNAL TABLE ods_order_info_inc
(
    `type` STRING COMMENT '变动类型',
    `ts`   BIGINT COMMENT '变动时间',
    `data` STRUCT<id :STRING,consignee :STRING,consignee_tel :STRING,total_amount :DECIMAL(16, 2),order_status :STRING,user_id
                  :STRING,payment_way :STRING,delivery_address :STRING,order_comment :STRING,out_trade_no :STRING,trade_body
                  :STRING,create_time :STRING,operate_time :STRING,expire_time :STRING,process_status :STRING,tracking_no
                  :STRING,parent_order_id :STRING,img_url :STRING,province_id :STRING,activity_reduce_amount
                  :DECIMAL(16, 2),coupon_reduce_amount :DECIMAL(16, 2),original_total_amount :DECIMAL(16, 2),freight_fee
                  :DECIMAL(16, 2),freight_fee_reduce :DECIMAL(16, 2),refundable_time :DECIMAL(16, 2)> COMMENT '数据',
    `old`  MAP<STRING,STRING> COMMENT '旧值'
) COMMENT '订单表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.JsonSerDe'
    LOCATION '/warehouse/gmall/ods/ods_order_info_inc/';
退单表（增量表）
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DROP TABLE IF EXISTS ods_order_refund_info_inc;
CREATE EXTERNAL TABLE ods_order_refund_info_inc
(
    `type` STRING COMMENT '变动类型',
    `ts`   BIGINT COMMENT '变动时间',
    `data` STRUCT<id :STRING,user_id :STRING,order_id :STRING,sku_id :STRING,refund_type :STRING,refund_num :BIGINT,refund_amount
                  :DECIMAL(16, 2),refund_reason_type :STRING,refund_reason_txt :STRING,refund_status :STRING,create_time
                  :STRING> COMMENT '数据',
    `old`  MAP<STRING,STRING> COMMENT '旧值'
) COMMENT '退单表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.JsonSerDe'
    LOCATION '/warehouse/gmall/ods/ods_order_refund_info_inc/';
订单状态流水表（增量表）
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DROP TABLE IF EXISTS ods_order_status_log_inc;
CREATE EXTERNAL TABLE ods_order_status_log_inc
(
    `type` STRING COMMENT '变动类型',
    `ts`   BIGINT COMMENT '变动时间',
    `data` STRUCT<id :STRING,order_id :STRING,order_status :STRING,operate_time :STRING> COMMENT '数据',
    `old`  MAP<STRING,STRING> COMMENT '旧值'
) COMMENT '退单表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.JsonSerDe'
    LOCATION '/warehouse/gmall/ods/ods_order_status_log_inc/';
支付表（增量表）
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DROP TABLE IF EXISTS ods_payment_info_inc;
CREATE EXTERNAL TABLE ods_payment_info_inc
(
    `type` STRING COMMENT '变动类型',
    `ts`   BIGINT COMMENT '变动时间',
    `data` STRUCT<id :STRING,out_trade_no :STRING,order_id :STRING,user_id :STRING,payment_type :STRING,trade_no
                  :STRING,total_amount :DECIMAL(16, 2),subject :STRING,payment_status :STRING,create_time :STRING,callback_time
                  :STRING,callback_content :STRING> COMMENT '数据',
    `old`  MAP<STRING,STRING> COMMENT '旧值'
) COMMENT '支付表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.JsonSerDe'
    LOCATION '/warehouse/gmall/ods/ods_payment_info_inc/';
退款表（增量表）
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DROP TABLE IF EXISTS ods_refund_payment_inc;
CREATE EXTERNAL TABLE ods_refund_payment_inc
(
    `type` STRING COMMENT '变动类型',
    `ts`   BIGINT COMMENT '变动时间',
    `data` STRUCT<id :STRING,out_trade_no :STRING,order_id :STRING,sku_id :STRING,payment_type :STRING,trade_no :STRING,total_amount
                  :DECIMAL(16, 2),subject :STRING,refund_status :STRING,create_time :STRING,callback_time :STRING,callback_content
                  :STRING> COMMENT '数据',
    `old`  MAP<STRING,STRING> COMMENT '旧值'
) COMMENT '退款表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.JsonSerDe'
    LOCATION '/warehouse/gmall/ods/ods_refund_payment_inc/';
用户表（增量表）
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DROP TABLE IF EXISTS ods_user_info_inc;
CREATE EXTERNAL TABLE ods_user_info_inc
(
    `type` STRING COMMENT '变动类型',
    `ts`   BIGINT COMMENT '变动时间',
    `data` STRUCT<id :STRING,login_name :STRING,nick_name :STRING,passwd :STRING,name :STRING,phone_num :STRING,email
                  :STRING,head_img :STRING,user_level :STRING,birthday :STRING,gender :STRING,create_time :STRING,operate_time
                  :STRING,status :STRING> COMMENT '数据',
    `old`  MAP<STRING,STRING> COMMENT '旧值'
) COMMENT '用户表'
    PARTITIONED BY (`dt` STRING)
    ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.JsonSerDe'
    LOCATION '/warehouse/gmall/ods/ods_user_info_inc/';
数据装载脚本
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[eitan@hadoop102 ~]$ vim ~/bin/hdfs_to_ods_db.sh
#!/bin/bash

APP=gmall

if [ -n "$2" ] ;then
   do_date=$2
else 
   do_date=`date -d '-1 day' +%F`
fi

load_data(){
    sql=""
    for i in $*; do
        #判断路径是否存在
        hadoop fs -test -e /origin_data/$APP/db/${i:4}/$do_date
        #路径存在方可装载数据
        if [[ $? = 0 ]]; then
            sql=$sql"load data inpath '/origin_data/$APP/db/${i:4}/$do_date' OVERWRITE into table ${APP}.$i partition(dt='$do_date');"
        fi
    done
    hive -e "$sql"
}

case $1 in
    "ods_activity_info_full")
        load_data "ods_activity_info_full"
    ;;
    "ods_activity_rule_full")
        load_data "ods_activity_rule_full"
    ;;
    "ods_base_category1_full")
        load_data "ods_base_category1_full"
    ;;
    "ods_base_category2_full")
        load_data "ods_base_category2_full"
    ;;
    "ods_base_category3_full")
        load_data "ods_base_category3_full"
    ;;
    "ods_base_dic_full")
        load_data "ods_base_dic_full"
    ;;
    "ods_base_province_full")
        load_data "ods_base_province_full"
    ;;
    "ods_base_region_full")
        load_data "ods_base_region_full"
    ;;
    "ods_base_trademark_full")
        load_data "ods_base_trademark_full"
    ;;
    "ods_cart_info_full")
        load_data "ods_cart_info_full"
    ;;
    "ods_coupon_info_full")
        load_data "ods_coupon_info_full"
    ;;
    "ods_sku_attr_value_full")
        load_data "ods_sku_attr_value_full"
    ;;
    "ods_sku_info_full")
        load_data "ods_sku_info_full"
    ;;
    "ods_sku_sale_attr_value_full")
        load_data "ods_sku_sale_attr_value_full"
    ;;
    "ods_spu_info_full")
        load_data "ods_spu_info_full"
    ;;

    "ods_cart_info_inc")
        load_data "ods_cart_info_inc"
    ;;
    "ods_comment_info_inc")
        load_data "ods_comment_info_inc"
    ;;
    "ods_coupon_use_inc")
        load_data "ods_coupon_use_inc"
    ;;
    "ods_favor_info_inc")
        load_data "ods_favor_info_inc"
    ;;
    "ods_order_detail_inc")
        load_data "ods_order_detail_inc"
    ;;
    "ods_order_detail_activity_inc")
        load_data "ods_order_detail_activity_inc"
    ;;
    "ods_order_detail_coupon_inc")
        load_data "ods_order_detail_coupon_inc"
    ;;
    "ods_order_info_inc")
        load_data "ods_order_info_inc"
    ;;
    "ods_order_refund_info_inc")
        load_data "ods_order_refund_info_inc"
    ;;
    "ods_order_status_log_inc")
        load_data "ods_order_status_log_inc"
    ;;
    "ods_payment_info_inc")
        load_data "ods_payment_info_inc"
    ;;
    "ods_refund_payment_inc")
        load_data "ods_refund_payment_inc"
    ;;
    "ods_user_info_inc")
        load_data "ods_user_info_inc"
    ;;
    "all")
        load_data "ods_activity_info_full" "ods_activity_rule_full" "ods_base_category1_full" "ods_base_category2_full" "ods_base_category3_full" "ods_base_dic_full" "ods_base_province_full" "ods_base_region_full" "ods_base_trademark_full" "ods_cart_info_full" "ods_coupon_info_full" "ods_sku_attr_value_full" "ods_sku_info_full" "ods_sku_sale_attr_value_full" "ods_spu_info_full" "ods_cart_info_inc" "ods_comment_info_inc" "ods_coupon_use_inc" "ods_favor_info_inc" "ods_order_detail_inc" "ods_order_detail_activity_inc" "ods_order_detail_coupon_inc" "ods_order_info_inc" "ods_order_refund_info_inc" "ods_order_status_log_inc" "ods_payment_info_inc" "ods_refund_payment_inc" "ods_user_info_inc"
    ;;
esac

[eitan@hadoop102 ~]$ chmod u+x ~/bin/hdfs_to_ods_db.sh 

[eitan@hadoop102 ~]$ hdfs_to_ods_db.sh all 2020-06-14

数仓开发之DIM层

DIM层设计要点：

  1. DIM层的设计依据是维度建模理论，该层存储维度模型的维度表。

  2. DIM层的数据存储格式为orc列式存储+snappy压缩。

  3. DIM层表名的命名规范为dim_表名_全量表或者拉链表标识（full/zip）

商品维度表

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DROP TABLE IF EXISTS dim_sku_full;
CREATE EXTERNAL TABLE dim_sku_full
(
    `id`                   STRING COMMENT 'sku_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 ORC
    LOCATION '/warehouse/gmall/dim/dim_sku_full/'
    TBLPROPERTIES ('orc.compress' = 'snappy');