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一、ods 层介绍
1、保持数据原貌不做任何修改,起到备份数据的作用。
2、数据采用 LZO 压缩,减少磁盘存储空间。100G 数据可以压缩到 10G 以内。
3、创建分区表,防止后续的全表扫描,在企业开发中大量使用分区表。
4、创建外部表,在企业开发中,除了自己用的临时表,创建内部表外,绝大多数场景都是创建外部表。
二、用户行为数据
1、启动日志表 ods_start_log
// 创建启动日志表 ods_start_log
// 创建输入数据是 lzo,输出是 text,支持 json 解析的分区表
DROP table if exists ods_start_log;
CREATE EXTERNAL TABLE ods_start_log (`line` string)
PARTITIONED BY (`dt` string)
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
LOCATION '/warehouse/gmall/ods/ods_start_log';
// 加载数据
load data inpath '/origin_data/gmall/log/topic_start/2020-03-10' into table gmall.ods_start_log partition(dt='2020-03-10');
// 为 lzo 压缩文件创建索引
hadoop jar /opt/module/hadoop-2.7.2/share/hadoop/common/hadoop-lzo-0.4.20.jar com.hadoop.compression.lzo.DistributedLzoIndexer /warehouse/gmall/ods/ods_start_log/dt=2020-03-10
2、事件日志表 ods_event_log
// 创建事件日志表 ods_event_log
// 创建输入数据是 lzo,输出是 text,支持 json 解析的分区表
drop table if exists ods_event_log;
CREATE EXTERNAL TABLE ods_event_log(`line` string)
PARTITIONED BY (`dt` string)
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
LOCATION '/warehouse/gmall/ods/ods_event_log';
// 加载数据
load data inpath '/origin_data/gmall/log/topic_event/2020-03-10' into table gmall.ods_event_log partition(dt='2020-03-10');
// 为 lzo 压缩文件创建索引
hadoop jar /opt/module/hadoop-2.7.2/share/hadoop/common/hadoop-lzo-0.4.20.jar com.hadoop.compression.lzo.DistributedLzoIndexer /warehouse/gmall/ods/ods_event_log/dt=2020-03-10
3、ods层 用户行为数据加载脚本 hdfs_to_ods_log.sh
#!/bin/bash
# 定义变量方便修改
APP=gmall
hive=/opt/module/hive/bin/hive
# 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 $do_date==="
sql=" load data inpath '/origin_data/gmall/log/topic_start/$do_date' overwrite into table ${APP}.ods_start_log partition(dt='$do_date'); load data inpath '/origin_data/gmall/log/topic_event/$do_date' overwrite into table ${APP}.ods_event_log partition(dt='$do_date'); "
$hive -e "$sql"
hadoop jar /opt/module/hadoop-2.7.2/share/hadoop/common/hadoop-lzo-0.4.20.jar com.hadoop.compression.lzo.DistributedLzoIndexer /warehouse/gmall/ods/ods_start_log/dt=$do_date
hadoop jar /opt/module/hadoop-2.7.2/share/hadoop/common/hadoop-lzo-0.4.20.jar com.hadoop.compression.lzo.DistributedLzoIndexer /warehouse/gmall/ods/ods_event_log/dt=$do_date
4、为什么要对 lzo 数据创建索引?
lzo 文件默认不支持 split,创建索引后支持 split,这样作为 map 输入时就可以将文件分割成多个 map,否则只能有一个 map。
三、业务数据
1、订单表 ods_order_info (增量及更新)
drop table if exists ods_order_info;
create external table ods_order_info (
`id` string COMMENT '订单号',
`final_total_amount` decimal(10,2) COMMENT '订单金额',
`order_status` string COMMENT '订单状态',
`user_id` string COMMENT '用户id',
`out_trade_no` string COMMENT '支付流水号',
`create_time` string COMMENT '创建时间',
`operate_time` string COMMENT '操作时间',
`province_id` string COMMENT '省份ID',
`benefit_reduce_amount` decimal(10,2) COMMENT '优惠金额',
`original_total_amount` decimal(10,2) COMMENT '原价金额',
`feight_fee` decimal(10,2) COMMENT '运费'
) COMMENT '订单表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_order_info/';
2、订单详情表 ods_order_detail (增量)
drop table if exists ods_order_detail;
create external table ods_order_detail(
`id` string COMMENT '订单编号',
`order_id` string COMMENT '订单号',
`user_id` string COMMENT '用户id',
`sku_id` string COMMENT '商品id',
`sku_name` string COMMENT '商品名称',
`order_price` decimal(10,2) COMMENT '商品价格',
`sku_num` bigint COMMENT '商品数量',
`create_time` string COMMENT '创建时间'
) COMMENT '订单详情表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_order_detail/';
3、sku 商品表 ods_sku_info (全量)
drop table if exists ods_sku_info;
create external table ods_sku_info(
`id` string COMMENT 'skuId',
`spu_id` string COMMENT 'spuid',
`price` decimal(10,2) COMMENT '价格',
`sku_name` string COMMENT '商品名称',
`sku_desc` string COMMENT '商品描述',
`weight` string COMMENT '重量',
`tm_id` string COMMENT '品牌id',
`category3_id` string COMMENT '品类id',
`create_time` string COMMENT '创建时间'
) COMMENT 'SKU商品表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_sku_info/';
4、用户表 ods_user_info (增量及更新)
drop table if exists ods_user_info;
create external table ods_user_info(
`id` string COMMENT '用户id',
`name` string COMMENT '姓名',
`birthday` string COMMENT '生日',
`gender` string COMMENT '性别',
`email` string COMMENT '邮箱',
`user_level` string COMMENT '用户等级',
`create_time` string COMMENT '创建时间',
`operate_time` string COMMENT '操作时间'
) COMMENT '用户表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_user_info/';
5、商品一级分类表 ods_base_category1 (全量)
drop table if exists ods_base_category1;
create external table ods_base_category1(
`id` string COMMENT 'id',
`name` string COMMENT '名称'
) COMMENT '商品一级分类表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_base_category1/';
6、商品二级分类表 ods_base_category2 (全量)
drop table if exists ods_base_category2;
create external table ods_base_category2(
`id` string COMMENT ' id',
`name` string COMMENT '名称',
category1_id string COMMENT '一级品类id'
) COMMENT '商品二级分类表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_base_category2/';
7、商品三级分类表 ods_base_category3 (全量)
drop table if exists ods_base_category3;
create external table ods_base_category3(
`id` string COMMENT ' id',
`name` string COMMENT '名称',
category2_id string COMMENT '二级品类id'
) COMMENT '商品三级分类表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_base_category3/';
8、支付流水表 ods_payment_info (增量)
drop table if exists ods_payment_info;
create external table ods_payment_info(
`id` bigint COMMENT '编号',
`out_trade_no` string COMMENT '对外业务编号',
`order_id` string COMMENT '订单编号',
`user_id` string COMMENT '用户编号',
`alipay_trade_no` string COMMENT '支付宝交易流水编号',
`total_amount` decimal(16,2) COMMENT '支付金额',
`subject` string COMMENT '交易内容',
`payment_type` string COMMENT '支付类型',
`payment_time` string COMMENT '支付时间'
) COMMENT '支付流水表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_payment_info/';
9、省份表 ods_base_province (特殊)
drop table if exists ods_base_province;
create external table ods_base_province (
`id` bigint 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 'iso编码'
) COMMENT '省份表'
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_base_province/';
10、地区表 ods_base_region (特殊)
drop table if exists ods_base_region;
create external table ods_base_region (
`id` bigint COMMENT '编号',
`region_name` string COMMENT '地区名称'
) COMMENT '地区表'
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_base_region/';
11、品牌表 ods_base_trademark (全量)
drop table if exists ods_base_trademark;
create external table ods_base_trademark (
`tm_id` bigint COMMENT '编号',
`tm_name` string COMMENT '品牌名称'
) COMMENT '品牌表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_base_trademark/';
12、订单状态表 ods_order_status_log (增量)
drop table if exists ods_order_status_log;
create external table ods_order_status_log (
`id` bigint COMMENT '编号',
`order_id` string COMMENT '订单ID',
`order_status` string COMMENT '订单状态',
`operate_time` string COMMENT '修改时间'
) COMMENT '订单状态表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_order_status_log/';
13、spu 商品表 ods_spu_info (全量)
drop table if exists ods_spu_info;
create external table ods_spu_info(
`id` string COMMENT 'spuid',
`spu_name` string COMMENT 'spu名称',
`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'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_spu_info/';
14、商品评论表 ods_comment_info (增量)
drop table if exists ods_comment_info;
create external table ods_comment_info(
`id` string COMMENT '编号',
`user_id` string COMMENT '用户ID',
`sku_id` string COMMENT '商品sku',
`spu_id` string COMMENT '商品spu',
`order_id` string COMMENT '订单ID',
`appraise` string COMMENT '评价',
`create_time` string COMMENT '评价时间'
) COMMENT '商品评论表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_comment_info/';
15、退单表 ods_order_refund_info (增量)
drop table if exists ods_order_refund_info;
create external table ods_order_refund_info(
`id` string COMMENT '编号',
`user_id` string COMMENT '用户ID',
`order_id` string COMMENT '订单ID',
`sku_id` string COMMENT '商品ID',
`refund_type` string COMMENT '退款类型',
`refund_num` bigint COMMENT '退款件数',
`refund_amount` decimal(16,2) COMMENT '退款金额',
`refund_reason_type` string COMMENT '退款原因类型',
`create_time` string COMMENT '退款时间'
) COMMENT '退单表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_order_refund_info/';
16、加购表 ods_cart_info (全量)
drop table if exists ods_cart_info;
create external table ods_cart_info(
`id` string COMMENT '编号',
`user_id` string COMMENT '用户id',
`sku_id` string COMMENT 'skuid',
`cart_price` string COMMENT '放入购物车时价格',
`sku_num` string COMMENT '数量',
`sku_name` string COMMENT 'sku名称 (冗余)',
`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'
) COMMENT '加购表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_cart_info/';
17、商品收藏表 ods_favor_info (全量)
drop table if exists ods_favor_info;
create external table ods_favor_info(
`id` string COMMENT '编号',
`user_id` string COMMENT '用户id',
`sku_id` string COMMENT 'skuid',
`spu_id` string COMMENT 'spuid',
`is_cancel` string COMMENT '是否取消',
`create_time` string COMMENT '收藏时间',
`cancel_time` string COMMENT '取消时间'
) COMMENT '商品收藏表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_favor_info/';
18、优惠券领用表 ods_coupon_use (新增及变化)
drop table if exists ods_coupon_use;
create external table ods_coupon_use(
`id` string COMMENT '编号',
`coupon_id` string COMMENT '优惠券ID',
`user_id` string COMMENT 'skuid',
`order_id` string COMMENT 'spuid',
`coupon_status` string COMMENT '优惠券状态',
`get_time` string COMMENT '领取时间',
`using_time` string COMMENT '使用时间(下单)',
`used_time` string COMMENT '使用时间(支付)'
) COMMENT '优惠券领用表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_coupon_use/';
19、优惠券表 ods_coupon_info (全量)
drop table if exists ods_coupon_info;
create external table ods_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` string COMMENT '满额数',
`condition_num` string COMMENT '满件数',
`activity_id` string COMMENT '活动编号',
`benefit_amount` string COMMENT '减金额',
`benefit_discount` string 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',
`spu_id` string COMMENT '商品id',
`tm_id` string COMMENT '品牌id',
`category3_id` string COMMENT '品类id',
`limit_num` string COMMENT '最多领用次数',
`operate_time` string COMMENT '修改时间',
`expire_time` string COMMENT '过期时间'
) COMMENT '优惠券表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_coupon_info/';
20、活动表 ods_activity_info (全量)
drop table if exists ods_activity_info;
create external table ods_activity_info(
`id` string COMMENT '编号',
`activity_name` string COMMENT '活动名称',
`activity_type` string COMMENT '活动类型',
`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 '活动表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_activity_info/';
21、活动订单关联表 ods_activity_order (增量)
drop table if exists ods_activity_order;
create external table ods_activity_order(
`id` string COMMENT '编号',
`activity_id` string COMMENT '优惠券ID',
`order_id` string COMMENT 'skuid',
`create_time` string COMMENT '领取时间'
) COMMENT '活动订单关联表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_activity_order/';
22、优惠规则表 ods_activity_rule (全量)
drop table if exists ods_activity_rule;
create external table ods_activity_rule(
`id` string COMMENT '编号',
`activity_id` string COMMENT '活动ID',
`condition_amount` string COMMENT '满减金额',
`condition_num` string COMMENT '满减件数',
`benefit_amount` string COMMENT '优惠金额',
`benefit_discount` string COMMENT '优惠折扣',
`benefit_level` string COMMENT '优惠级别'
) COMMENT '优惠规则表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_activity_rule/';
23、编码字典表 ods_base_dic (全量)
drop table if exists ods_base_dic;
create external table ods_base_dic(
`dic_code` string COMMENT '编号',
`dic_name` string COMMENT '编码名称',
`parent_code` string COMMENT '父编码',
`create_time` string COMMENT '创建日期',
`operate_time` string COMMENT '操作日期'
) COMMENT '编码字典表'
PARTITIONED BY (`dt` string)
row format delimited fields terminated by '\t'
STORED AS
INPUTFORMAT 'com.hadoop.mapred.DeprecatedLzoTextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
location '/warehouse/gmall/ods/ods_base_dic/';
24、ods 层业务数据加载脚本 hdfs_to_ods_db.sh
#!/bin/bash
APP=gmall
hive=/opt/module/hive/bin/hive
# 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 "$2" ] ;then
do_date=$2
else
do_date=`date -d "-1 day" +%F`
fi
sql1=" load data inpath '/origin_data/$APP/db/order_info/$do_date' OVERWRITE into table ${APP}.ods_order_info partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/order_detail/$do_date' OVERWRITE into table ${APP}.ods_order_detail partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/sku_info/$do_date' OVERWRITE into table ${APP}.ods_sku_info partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/user_info/$do_date' OVERWRITE into table ${APP}.ods_user_info partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/payment_info/$do_date' OVERWRITE into table ${APP}.ods_payment_info partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/base_category1/$do_date' OVERWRITE into table ${APP}.ods_base_category1 partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/base_category2/$do_date' OVERWRITE into table ${APP}.ods_base_category2 partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/base_category3/$do_date' OVERWRITE into table ${APP}.ods_base_category3 partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/base_trademark/$do_date' OVERWRITE into table ${APP}.ods_base_trademark partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/activity_info/$do_date' OVERWRITE into table ${APP}.ods_activity_info partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/activity_order/$do_date' OVERWRITE into table ${APP}.ods_activity_order partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/cart_info/$do_date' OVERWRITE into table ${APP}.ods_cart_info partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/comment_info/$do_date' OVERWRITE into table ${APP}.ods_comment_info partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/coupon_info/$do_date' OVERWRITE into table ${APP}.ods_coupon_info partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/coupon_use/$do_date' OVERWRITE into table ${APP}.ods_coupon_use partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/favor_info/$do_date' OVERWRITE into table ${APP}.ods_favor_info partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/order_refund_info/$do_date' OVERWRITE into table ${APP}.ods_order_refund_info partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/order_status_log/$do_date' OVERWRITE into table ${APP}.ods_order_status_log partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/spu_info/$do_date' OVERWRITE into table ${APP}.ods_spu_info partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/activity_rule/$do_date' OVERWRITE into table ${APP}.ods_activity_rule partition(dt='$do_date'); load data inpath '/origin_data/$APP/db/base_dic/$do_date' OVERWRITE into table ${APP}.ods_base_dic partition(dt='$do_date'); "
sql2=" load data inpath '/origin_data/$APP/db/base_province/$do_date' OVERWRITE into table ${APP}.ods_base_province; load data inpath '/origin_data/$APP/db/base_region/$do_date' OVERWRITE into table ${APP}.ods_base_region; "
case $1 in
"first"){
$hive -e "$sql1"
$hive -e "$sql2"
};;
"all"){
$hive -e "$sql1"
};;
esac
四、ods 层总结
1、注意用 lzo 压缩、可以大幅度减少磁盘存储空间。
2、要保持数据原貌不做更改,字段要和原数据符合,起到备份数据的作用。
3、创建分区表,方便扫描。
4、注意表的类型,是全量表、增量表、新增及变化表还是特殊表。
5、要注意为 lzo 文件创建索引,使得 lzo 数据支持切片。
6、ods 层用户行为表 2 张,业务数据表 23 张,ods 层共计 25 张表。
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