我的腳本存放目錄 /user/local/bin/
注意：有些腳本涉及到用戶和密碼記得要改成自己的！路徑有的也需要留意。
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目錄
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1.xsync集羣分發腳本
參考這篇博客安裝
https://blog.csdn.net/yhblog/article/details/84066218
#!/bin/bash
#獲取輸入參數的個數.沒有參數直接退出
pcount=$#
if((pcount==0));then
echo no args;
exit;
fi
#2.獲取文件名稱
p1=$1
fname=`basename $p1`
echo fname=$fname
#3.獲取上級目錄到絕對路徑
pdir=`cd -P $(dirname $p1); pwd`
echo pdir=$pdir
#4.獲取當前用戶名稱
user=`whoami`
#5.循環
for ((host=102; host<105;host++));do
echo ----------------hadoop$host------------------
rsync -av $pdir/$fname $user@hadoop$host:$pdir
done
2.zookeeper集羣起動關閉腳本
#!/bin/bash
case $1 in
"start"){
for i in hadoop102 hadoop103 hadoop104
do
ssh $i "/opt/module/zookeeper-3.4.10/bin/zkServer.sh start"
done
};;
"stop"){
for i in hadoop102 hadoop103 hadoop104
do
ssh $i "/opt/module/zookeeper-3.4.10/bin/zkServer.sh stop"
done
};;
"status"){
for i in hadoop102 hadoop103 hadoop104
do
ssh $i "/opt/module/zookeeper-3.4.10/bin/zkServer.sh status"
done
};;
esac
3.日誌啓動腳本
#!/bin/bash
for i in hadoop102 hadoop103
do
echo ---------$i 生成日誌----------
ssh $i "java -jar /opt/module/log-collector-1.0-SNAPSHOT-jar-with-dependencies.jar $1 $2 >/dev/null 2>&1 &"
done
4.時間同步腳本（用於造假數據）
#!/bin/bash
for i in hadoop102 hadoop103 hadoop104
do
echo ---------$i 同步時間----------
ssh -t $i "sudo data -s $1"
done
5.集羣各個節點查看狀態腳本
#!/bin/bash
for i in hadoop102 hadoop103 hadoop104
do
echo ---------$i ----------
ssh $i "$*"
done
6.日誌採集 Flume 啓動停止腳本
#!/bin/bash
case $1 in
"start"){
for i in hadoop102 hadoop103
do
echo " --------啓動 $i 採集 flume-------"
ssh $i "nohup /opt/module/flume/bin/flume-ng agent --conf-file /opt/module/flume/conf/file-flume-kafka.conf --name a1 -Dflume.root.logger=INFO,LOGFILE >/opt/module/flume/test1 2>&1 &"
done
};;
"stop"){
for i in hadoop102 hadoop103
do
echo " --------停止 $i 採集 flume-------"
ssh $i "ps -ef | grep file-flume-kafka | grep -v grep |awk '{print \$2}' | xargs kill"
done
};;
esac
7.Kafka 集羣啓動停止腳本
#! /bin/bash
case $1 in
"start"){
for i in hadoop102 hadoop103 hadoop104
do
echo " --------啓動 $i Kafka-------"
ssh $i "/opt/module/kafka/bin/kafka-server-start.sh -daemon /opt/module/kafka/config/server.properties "
done
};;
"stop"){
for i in hadoop102 hadoop103 hadoop104
do
echo " --------停止 $i Kafka-------"
ssh $i "/opt/module/kafka/bin/kafka-server-stop.sh stop"
done
};;
esac
8.日誌消費 Flume 啓動停止腳本
#! /bin/bash
case $1 in
"start"){
for i in hadoop104
do
echo " --------啓動 $i 消費 flume-------"
ssh $i "nohup /opt/module/flume/bin/flume-ng agent --conf-file /opt/module/flume/conf/kafka-flume-hdfs.conf --name a1 -Dflume.root.logger=INFO,LOGFILE >/opt/module/flume/log.txt 2>&1 &"
done
};;
"stop"){
for i in hadoop104
do
echo " --------停止 $i 消費 flume-------"
ssh $i "ps -ef | grep kafka-flume-hdfs | grep -v grep |awk '{print \$2}' | xargs kill"
done
};;
esac
9.採集通道啓動/停止腳本
#! /bin/bash
case $1 in
"start"){
echo " -------- 啓動 集羣 -------"
echo " -------- 啓動 hadoop 集羣 -------"
/opt/module/hadoop-2.7.2/sbin/start-dfs.sh
ssh hadoop103 "/opt/module/hadoop-2.7.2/sbin/start-yarn.sh"
#啓動 Zookeeper 集羣
zk.sh start
sleep 4s;
#啓動 Flume 採集集羣
f1.sh start
#啓動 Kafka 採集集羣
kf.sh start
sleep 6s;
#啓動 Flume 消費集羣
f2.sh start
};;
"stop"){
echo " -------- 停止 集羣 -------"
#停止 Flume 消費集羣
f2.sh stop
#停止 Kafka 採集集羣
kf.sh stop
sleep 6s;
#停止 Flume 採集集羣
f1.sh stop
#停止 Zookeeper 集羣
zk.sh stop
echo " -------- 停止 hadoop 集羣 -------"
ssh hadoop103 "/opt/module/hadoop-2.7.2/sbin/stop-yarn.sh"
/opt/module/hadoop-2.7.2/sbin/stop-dfs.sh
};;
esac
10.mysql業務數據通過sqoop導入hdfs腳本
#! /bin/bash
sqoop=/opt/module/sqoop/bin/sqoop
do_date=`date -d '-1 day' +%F`
if [[ -n "$2" ]]; then
do_date=$2
fi
import_data(){
$sqoop import --connect jdbc:mysql://hadoop102:3306/gmall --username root --password 123456 --target-dir /origin_data/gmall/db/$1/$do_date --delete-target-dir --query "$2 and \$CONDITIONS" --num-mappers 1 --fields-terminated-by '\t' --compress --compression-codec lzop --null-string '\\N' --null-non-string '\\N'
hadoop jar /opt/module/hadoop-2.7.2/share/hadoop/common/hadoop-lzo-0.4.20.jar com.hadoop.compression.lzo.DistributedLzoIndexer /origin_data/gmall/db/$1/$do_date
}
import_order_info(){
import_data order_info "select
id,
final_total_amount,
order_status,
user_id,
out_trade_no,
create_time,
operate_time,
province_id,
benefit_reduce_amount,
original_total_amount,
feight_fee
from order_info
where (date_format(create_time,'%Y-%m-%d')='$do_date'
or date_format(operate_time,'%Y-%m-%d')='$do_date')"
}
import_coupon_use(){
import_data coupon_use "select
id,
coupon_id,
user_id,
order_id,
coupon_status,
get_time,
using_time,
used_time
from coupon_use
where (date_format(get_time,'%Y-%m-%d')='$do_date'
or date_format(using_time,'%Y-%m-%d')='$do_date'
or date_format(used_time,'%Y-%m-%d')='$do_date')"
}
import_order_status_log(){
import_data order_status_log "select
id,
order_id,
order_status,
operate_time
from order_status_log
where
date_format(operate_time,'%Y-%m-%d')='$do_date'"
}
import_activity_order(){
import_data activity_order "select
id, activity_id,
order_id,
create_time
from activity_order
where
date_format(create_time,'%Y-%m-%d')='$do_date'"
}
import_user_info(){
import_data "user_info" "select
id,
name,
birthday,
gender,
email,
user_level,
create_time,
operate_time
from user_info
where (DATE_FORMAT(create_time,'%Y-%m-%d')='$do_date'
or DATE_FORMAT(operate_time,'%Y-%m-%d')='$do_date')"
}
import_order_detail(){
import_data order_detail "select
od.id,
order_id,
user_id,
sku_id,
sku_name,
order_price,
sku_num,
od.create_time
from order_detail od
join order_info oi
on od.order_id=oi.id
where
DATE_FORMAT(od.create_time,'%Y-%m-%d')='$do_date'"
}
import_payment_info(){
import_data "payment_info" "select
id,
out_trade_no,
order_id,
user_id,
alipay_trade_no,
total_amount,
subject,
payment_type,
payment_time
from payment_info
where
DATE_FORMAT(payment_time,'%Y-%m-%d')='$do_date'"
}
import_comment_info(){
import_data comment_info "select
id,
user_id,
sku_id,
spu_id,
order_id,
appraise,
comment_txt,
create_time
from comment_info
where date_format(create_time,'%Y-%m-%d')='$do_date'"
}
import_order_refund_info(){
import_data order_refund_info "select
id,
user_id,
order_id,
sku_id,
refund_type,
refund_num,
refund_amount,
refund_reason_type,
create_time
from order_refund_info
where
date_format(create_time,'%Y-%m-%d')='$do_date'"
}
import_sku_info(){
import_data sku_info "select
id,
spu_id,
price,
sku_name,
sku_desc,
weight,
tm_id,
category3_id,
create_time
from sku_info
where 1=1"
}
import_base_category1(){
import_data "base_category1" "select
id,
name
from base_category1
where 1=1"
}
import_base_category2(){
import_data "base_category2" "select
id,
name,
category1_id
from base_category2
where 1=1"
}
import_base_category3(){
import_data "base_category3" "select
id,
name,
category2_id
from base_category3
where 1=1"
}
import_base_province(){
import_data base_province "select
id,
name,
region_id,
area_code,
iso_code
from base_province
where 1=1"
}
import_base_region(){
import_data base_region "select
id,
region_name
from base_region
where 1=1"
}
import_base_trademark(){
import_data base_trademark "select
tm_id,
tm_name
from base_trademark
where 1=1"
}
import_spu_info(){
import_data spu_info "select
id,
spu_name,
category3_id,
tm_id
from spu_info
where 1=1"
}
import_favor_info(){
import_data favor_info "select
id,
user_id,
sku_id,
spu_id,
is_cancel,
create_time,
cancel_time
from favor_info
where 1=1"
}
import_cart_info(){
import_data cart_info "select
id,
user_id,
sku_id,
cart_price,
sku_num,
sku_name,
create_time,
operate_time,
is_ordered,
order_time
from cart_info
where 1=1"
}
import_coupon_info(){
import_data coupon_info "select
id,
coupon_name,
coupon_type,
condition_amount,
condition_num,
activity_id,
benefit_amount,
benefit_discount,
create_time,
range_type,
spu_id,
tm_id,
category3_id,
limit_num,
operate_time,
expire_time
from coupon_info
where 1=1"
}
import_activity_info(){
import_data activity_info "select
id,
activity_name,
activity_type,
start_time,
end_time,
create_time
from activity_info
where 1=1"
}
import_activity_rule(){
import_data activity_rule "select
id,
activity_id,
condition_amount,
condition_num,
benefit_amount,
benefit_discount,
benefit_level
from activity_rule
where 1=1"
}
import_base_dic(){
import_data base_dic "select
dic_code,
dic_name,
parent_code,
create_time,
operate_time
from base_dic
where 1=1"
}
case $1 in
"order_info")
import_order_info
;;
"base_category1")
import_base_category1
;;
"base_category2")
import_base_category2
;;
"base_category3")
import_base_category3
;;
"order_detail")
import_order_detail
;;
"sku_info")
import_sku_info
;;
"user_info")
import_user_info
;;
"payment_info")
import_payment_info
;;
"base_province")
import_base_province
;;
"base_region")
import_base_region
;;
"base_trademark")
import_base_trademark
;;
"activity_info")
import_activity_info
;;
"activity_order")
import_activity_order
;;
"cart_info")
import_cart_info
;;
"comment_info")
import_comment_info
;;
"coupon_info")
import_coupon_info
;;
"coupon_use")
import_coupon_use
;;
"favor_info")
import_favor_info
;;
"order_refund_info")
import_order_refund_info
;;
"order_status_log")
import_order_status_log
;;
"spu_info")
import_spu_info
;;
"activity_rule")
import_activity_rule
;;
"base_dic")
import_base_dic
;;
"first")
import_base_category1
import_base_category2
import_base_category3
import_order_info
import_order_detail
import_sku_info
import_user_info
import_payment_info
import_base_province
import_base_region
import_base_trademark
import_activity_info
import_activity_order
import_cart_info
import_comment_info
import_coupon_use
import_coupon_info
import_favor_info
import_order_refund_info
import_order_status_log
import_spu_info
import_activity_rule
import_base_dic
;;
"all")
import_base_category1
import_base_category2
import_base_category3
import_order_info
import_order_detail
import_sku_info
import_user_info
import_payment_info
import_base_trademark
import_activity_info
import_activity_order
import_cart_info
import_comment_info
import_coupon_use
import_coupon_info
import_favor_info
import_order_refund_info
import_order_status_log
import_spu_info
import_activity_rule
import_base_dic
;;
esac
11.數倉搭建-ODS 層（用戶行爲數據）加載數據腳本
#!/bin/bash
# 定義變量方便修改
APP=gmall
hive=/opt/module/hive/bin/hive
# 如果是輸入的日期按照取輸入日期；如果沒輸入日期取當前時間的前一天
if [ -n "$1" ] ;then
do_date=$1
else
do_date=`date -d "-1 day" +%F`
fi
echo "===日誌日期爲 $do_date==="
sql="
load data inpath '/origin_data/gmall/log/topic_start/$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
12.數倉搭建-ODS 層（業務數據）加載數據腳本
#!/bin/bash
APP=gmall
hive=/opt/module/hive/bin/hive
# 如果是輸入的日期按照取輸入日期；如果沒輸入日期取當前時間的前一天
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
13.數倉搭建-DWD 層啓動表加載數據腳本
#!/bin/bash
# 定義變量方便修改
APP=gmall
hive=/opt/module/hive/bin/hive
# 如果是輸入的日期按照取輸入日期；如果沒輸入日期取當前時間的前一天
if [ -n "$1" ] ;then
do_date=$1
else
do_date=`date -d "-1 day" +%F`
fi
sql="
set hive.exec.dynamic.partition.mode=nonstrict;
insert overwrite table "$APP".dwd_start_log
PARTITION (dt='$do_date')
select
get_json_object(line,'$.mid') mid_id,
get_json_object(line,'$.uid') user_id,
get_json_object(line,'$.vc') version_code,
get_json_object(line,'$.vn') version_name,
get_json_object(line,'$.l') lang,
get_json_object(line,'$.sr') source,
get_json_object(line,'$.os') os,
get_json_object(line,'$.ar') area,
get_json_object(line,'$.md') model,
get_json_object(line,'$.ba') brand,
get_json_object(line,'$.sv') sdk_version,
get_json_object(line,'$.g') gmail,
get_json_object(line,'$.hw') height_width,
get_json_object(line,'$.t') app_time,
get_json_object(line,'$.nw') network,
get_json_object(line,'$.ln') lng,
get_json_object(line,'$.la') lat,
get_json_object(line,'$.entry') entry,
get_json_object(line,'$.open_ad_type') open_ad_type,
get_json_object(line,'$.action') action,
get_json_object(line,'$.loading_time') loading_time,
get_json_object(line,'$.detail') detail,
get_json_object(line,'$.extend1') extend1
from "$APP".ods_start_log
where dt='$do_date';
"
$hive -e "$sql"
14.數倉搭建-DWD 層數據解析腳本
#!/bin/bash
# 定義變量方便修改
APP=gmall
hive=/opt/module/hive/bin/hive
# 如果是輸入的日期按照取輸入日期；如果沒輸入日期取當前時間的前一天
if [ -n "$1" ] ;then
do_date=$1
else
do_date=`date -d "-1 day" +%F`
fi
sql="
use gmall;
insert overwrite table "$APP".dwd_base_event_log partition(dt='$do_date') select base_analizer(line,'mid') as mid_id, base_analizer(line,'uid') as user_id, base_analizer(line,'vc') as version_code, base_analizer(line,'vn') as version_name, base_analizer(line,'l') as lang, base_analizer(line,'sr') as source, base_analizer(line,'os') as os, base_analizer(line,'ar') as area,base_analizer(line,'md') as model, base_analizer(line,'ba') as brand, base_analizer(line,'sv') as sdk_version, base_analizer(line,'g') as gmail, base_analizer(line,'hw') as height_width, base_analizer(line,'t') as app_time, base_analizer(line,'nw') as network, base_analizer(line,'ln') as lng, base_analizer(line,'la') as lat, event_name, event_json, base_analizer(line,'st') as server_time from "$APP".ods_event_log lateral view flat_analizer(base_analizer(line,'et')) tem_flat as event_name,event_json where dt='$do_date' and base_analizer(line,'et')<>'';
"
$hive -e "$sql"
15.數倉搭建-DWD 層事件表加載數據腳本
#!/bin/bash
# 定義變量方便修改
APP=gmall
hive=/opt/module/hive/bin/hive
# 如果是輸入的日期按照取輸入日期；如果沒輸入日期取當前時間的前一天
if [ -n "$1" ] ;then
do_date=$1
else
do_date=`date -d "-1 day" +%F`
fi
sql="
insert overwrite table "$APP".dwd_display_log PARTITION (dt='$do_date') select mid_id, user_id, version_code, version_name, lang, source, os, area, model, brand, sdk_version, gmail, height_width, app_time, network, lng, lat, get_json_object(event_json,'$.kv.action') action, get_json_object(event_json,'$.kv.goodsid') goodsid, get_json_object(event_json,'$.kv.place') place, get_json_object(event_json,'$.kv.extend1') extend1, get_json_object(event_json,'$.kv.category') category, server_time from "$APP".dwd_base_event_log where dt='$do_date' and event_name='display';
insert overwrite table "$APP".dwd_newsdetail_log PARTITION (dt='$do_date') select mid_id, user_id, version_code, version_name, lang, source, os, area, model, brand, sdk_version, gmail, height_width, app_time, network, lng, lat, get_json_object(event_json,'$.kv.entry') entry, get_json_object(event_json,'$.kv.action') action, get_json_object(event_json,'$.kv.goodsid') goodsid, get_json_object(event_json,'$.kv.showtype') showtype, get_json_object(event_json,'$.kv.news_staytime') news_staytime, get_json_object(event_json,'$.kv.loading_time') loading_time, get_json_object(event_json,'$.kv.type1') type1, get_json_object(event_json,'$.kv.category') category, server_time from "$APP".dwd_base_event_log where dt='$do_date' and event_name='newsdetail';
insert overwrite table "$APP".dwd_loading_log PARTITION (dt='$do_date') select mid_id, user_id, version_code, version_name, lang, source, os, area, model, brand, sdk_version, gmail, height_width, app_time, network, lng, lat, get_json_object(event_json,'$.kv.action') action, get_json_object(event_json,'$.kv.loading_time') loading_time, get_json_object(event_json,'$.kv.loading_way') loading_way, get_json_object(event_json,'$.kv.extend1') extend1, get_json_object(event_json,'$.kv.extend2') extend2, get_json_object(event_json,'$.kv.type') type, get_json_object(event_json,'$.kv.type1') type1, server_time from "$APP".dwd_base_event_log where dt='$do_date' and event_name='loading';
insert overwrite table "$APP".dwd_ad_log PARTITION (dt='$do_date') select mid_id, user_id, version_code, version_name, lang, source, os, area, model, brand, sdk_version, gmail, height_width, app_time, network, lng, lat, get_json_object(event_json,'$.kv.entry') entry, get_json_object(event_json,'$.kv.action') action, get_json_object(event_json,'$.kv.contentType') contentType, get_json_object(event_json,'$.kv.displayMills') displayMills, get_json_object(event_json,'$.kv.itemId') itemId, get_json_object(event_json,'$.kv.activityId') activityId, server_time from "$APP".dwd_base_event_log where dt='$do_date' and event_name='ad';
insert overwrite table "$APP".dwd_notification_log PARTITION (dt='$do_date') select mid_id, user_id, version_code, version_name, lang, source, os, area, model, brand, sdk_version, gmail, height_width, app_time, network, lng, lat, get_json_object(event_json,'$.kv.action') action, get_json_object(event_json,'$.kv.noti_type') noti_type, get_json_object(event_json,'$.kv.ap_time') ap_time, get_json_object(event_json,'$.kv.content') content, server_time from "$APP".dwd_base_event_log where dt='$do_date' and event_name='notification';
insert overwrite table "$APP".dwd_active_background_log PARTITION (dt='$do_date') select mid_id, user_id, version_code, version_name, lang, source, os, area, model, brand, sdk_version, gmail, height_width, app_time, network, lng, lat, get_json_object(event_json,'$.kv.active_source') active_source, server_time from "$APP".dwd_base_event_log where dt='$do_date' and event_name='active_background';
insert overwrite table "$APP".dwd_comment_log PARTITION (dt='$do_date') select mid_id, user_id, version_code, version_name, lang, source, os, area, model, brand, sdk_version, gmail, height_width, app_time, network, lng, lat, get_json_object(event_json,'$.kv.comment_id') comment_id, get_json_object(event_json,'$.kv.userid') userid, get_json_object(event_json,'$.kv.p_comment_id') p_comment_id, get_json_object(event_json,'$.kv.content') content, get_json_object(event_json,'$.kv.addtime') addtime, get_json_object(event_json,'$.kv.other_id') other_id, get_json_object(event_json,'$.kv.praise_count') praise_count, get_json_object(event_json,'$.kv.reply_count') reply_count, server_time from "$APP".dwd_base_event_log where dt='$do_date' and event_name='comment';
insert overwrite table "$APP".dwd_favorites_log PARTITION (dt='$do_date') select mid_id, user_id, version_code, version_name, lang, source, os, area, model, brand, sdk_version, gmail, height_width, app_time, network, lng, lat, get_json_object(event_json,'$.kv.id') id, get_json_object(event_json,'$.kv.course_id') course_id, get_json_object(event_json,'$.kv.userid') userid, get_json_object(event_json,'$.kv.add_time') add_time, server_time from "$APP".dwd_base_event_log where dt='$do_date' and event_name='favorites';
insert overwrite table "$APP".dwd_praise_log PARTITION (dt='$do_date') select mid_id, user_id, version_code, version_name, lang, source, os, area, model, brand, sdk_version, gmail, height_width, app_time, network, lng, lat, get_json_object(event_json,'$.kv.id') id, get_json_object(event_json,'$.kv.userid') userid, get_json_object(event_json,'$.kv.target_id') target_id, get_json_object(event_json,'$.kv.type') type, get_json_object(event_json,'$.kv.add_time') add_time, server_time from "$APP".dwd_base_event_log where dt='$do_date' and event_name='praise';
insert overwrite table "$APP".dwd_error_log PARTITION (dt='$do_date') select mid_id, user_id, version_code, version_name, lang, source, os, area, model, brand, sdk_version, gmail, height_width, app_time, network, lng, lat, get_json_object(event_json,'$.kv.errorBrief') errorBrief, get_json_object(event_json,'$.kv.errorDetail') errorDetail, server_time from "$APP".dwd_base_event_log where dt='$do_date' and event_name='error';
"
$hive -e "$sql"
16.數倉搭建-DWD 層數據導入腳本
#!/bin/bash
APP=gmall
hive=/opt/module/hive/bin/hive
# 如果是輸入的日期按照取輸入日期；如果沒輸入日期取當前時間的前一天
if [ -n "$2" ] ;then
do_date=$2
else
do_date=`date -d "-1 day" +%F`
fi
sql1="
set hive.exec.dynamic.partition.mode=nonstrict;
insert overwrite table ${APP}.dwd_dim_sku_info partition(dt='$do_date') select sku.id, sku.spu_id, sku.price, sku.sku_name, sku.sku_desc, sku.weight, sku.tm_id, ob.tm_name, sku.category3_id, c2.id category2_id, c1.id category1_id, c3.name category3_name, c2.name category2_name, c1.name category1_name, spu.spu_name, sku.create_time from ( select * from ${APP}.ods_sku_info where dt='$do_date' )sku join ( select * from ${APP}.ods_base_trademark where dt='$do_date' )ob on sku.tm_id=ob.tm_id join ( select * from ${APP}.ods_spu_info where dt='$do_date' )spu on spu.id = sku.spu_id join ( select * from ${APP}.ods_base_category3 where dt='$do_date' )c3 on sku.category3_id=c3.id join ( select * from ${APP}.ods_base_category2 where dt='$do_date' )c2 on c3.category2_id=c2.id join ( select * from ${APP}.ods_base_category1 where dt='$do_date' )c1 on c2.category1_id=c1.id;
insert overwrite table ${APP}.dwd_dim_coupon_info partition(dt='$do_date') select id, coupon_name, coupon_type, condition_amount, condition_num, activity_id, benefit_amount, benefit_discount, create_time, range_type, spu_id, tm_id, category3_id, limit_num, operate_time, expire_time from ${APP}.ods_coupon_info where dt='$do_date';
insert overwrite table ${APP}.dwd_dim_activity_info partition(dt='$do_date') select info.id, info.activity_name, info.activity_type, rule.condition_amount, rule.condition_num, rule.benefit_amount, rule.benefit_discount, rule.benefit_level, info.start_time, info.end_time, info.create_time from ( select * from ${APP}.ods_activity_info where dt='$do_date' )info left join ( select * from ${APP}.ods_activity_rule where dt='$do_date' )rule on info.id = rule.activity_id; insert overwrite table ${APP}.dwd_fact_order_detail partition(dt='$do_date') select od.id, od.order_id, od.user_id, od.sku_id, od.sku_name, od.order_price, od.sku_num, od.create_time, oi.province_id, od.order_price*od.sku_num from ( select * from ${APP}.ods_order_detail where dt='$do_date' ) od join ( select * from ${APP}.ods_order_info where dt='$do_date' ) oi on od.order_id=oi.id; insert overwrite table ${APP}.dwd_fact_payment_info partition(dt='$do_date') select pi.id, pi.out_trade_no, pi.order_id, pi.user_id, pi.alipay_trade_no, pi.total_amount, pi.subject, pi.payment_type, pi.payment_time, oi.province_id from ( select * from ${APP}.ods_payment_info where dt='$do_date' )pi join ( select id, province_id from ${APP}.ods_order_info where dt='$do_date' )oi on pi.order_id = oi.id; insert overwrite table ${APP}.dwd_fact_order_refund_info partition(dt='$do_date') select id, user_id, order_id, sku_id, refund_type, refund_num, refund_amount, refund_reason_type, create_time from ${APP}.ods_order_refund_info where dt='$do_date';
insert overwrite table ${APP}.dwd_fact_comment_info partition(dt='$do_date') select id, user_id, sku_id, spu_id, order_id, appraise, create_time from ${APP}.ods_comment_info where dt='$do_date';
insert overwrite table ${APP}.dwd_fact_cart_info partition(dt='$do_date') select id, user_id, sku_id, cart_price, sku_num, sku_name, create_time, operate_time, is_ordered, order_time from ${APP}.ods_cart_info where dt='$do_date';
insert overwrite table ${APP}.dwd_fact_favor_info partition(dt='$do_date') select id, user_id, sku_id, spu_id, is_cancel, create_time, cancel_time from ${APP}.ods_favor_info where dt='$do_date';
insert overwrite table ${APP}.dwd_fact_coupon_use partition(dt) select if(new.id is null,old.id,new.id), if(new.coupon_id is null,old.coupon_id,new.coupon_id), if(new.user_id is null,old.user_id,new.user_id), if(new.order_id is null,old.order_id,new.order_id), if(new.coupon_status is null,old.coupon_status,new.coupon_status), if(new.get_time is null,old.get_time,new.get_time), if(new.using_time is null,old.using_time,new.using_time), if(new.used_time is null,old.used_time,new.used_time), date_format(if(new.get_time is null,old.get_time,new.get_time),'yyyy-MM-dd') from ( select id, coupon_id, user_id, order_id, coupon_status, get_time, using_time, used_time from ${APP}.dwd_fact_coupon_use where dt in ( select date_format(get_time,'yyyy-MM-dd') from ${APP}.ods_coupon_use where dt='$do_date' ) )old full outer join ( select id, coupon_id, user_id, order_id, coupon_status, get_time, using_time, used_time from ${APP}.ods_coupon_use where dt='$do_date' )new on old.id=new.id;
insert overwrite table ${APP}.dwd_fact_order_info partition(dt) select if(new.id is null,old.id,new.id), if(new.order_status is null,old.order_status,new.order_status), if(new.user_id is null,old.user_id,new.user_id), if(new.out_trade_no is null,old.out_trade_no,new.out_trade_no), if(new.tms['1001'] is null,old.create_time,new.tms['1001']), if(new.tms['1002'] is null,old.payment_time,new.tms['1002']), if(new.tms['1003'] is null,old.cancel_time,new.tms['1003']), if(new.tms['1004'] is null,old.finish_time,new.tms['1004']), if(new.tms['1005'] is null,old.refund_time,new.tms['1005']), if(new.tms['1006'] is null,old.refund_finish_time,new.tms['1006']), if(new.province_id is null,old.province_id,new.province_id), if(new.activity_id is null,old.activity_id,new.activity_id), if(new.original_total_amount is null,old.original_total_amount,new.original_total_amount), if(new.benefit_reduce_amount is null,old.benefit_reduce_amount,new.benefit_reduce_amount), if(new.feight_fee is null,old.feight_fee,new.feight_fee), if(new.final_total_amount is null,old.final_total_amount,new.final_total_amount), date_format(if(new.tms['1001'] is null,old.create_time,new.tms['1001']),'yyyy-MM-dd') from ( select id, order_status, user_id, out_trade_no, create_time, payment_time, cancel_time, finish_time, refund_time, refund_finish_time, province_id, activity_id, original_total_amount, benefit_reduce_amount, feight_fee, final_total_amount from ${APP}.dwd_fact_order_info where dt in( select date_format(create_time,'yyyy-MM-dd') from ${APP}.ods_order_info where dt='$do_date' ) )old full outer join ( select info.id, info.order_status, info.user_id, info.out_trade_no, info.province_id, act.activity_id, log.tms, info.original_total_amount, info.benefit_reduce_amount, info.feight_fee, info.final_total_amount from ( select order_id, str_to_map(concat_ws(',',collect_set(concat(order_status,'=',operate_time))),',',' =') tms from ${APP}.ods_order_status_log where dt='$do_date' group by order_id )log join ( select * from ${APP}.ods_order_info where dt='$do_date' )info on log.order_id=info.id left join ( select * from ${APP}.ods_activity_order where dt='$do_date' )act on log.order_id=act.order_id )new on old.id=new.id; insert overwrite table ${APP}.dwd_dim_user_info_his_tmp select * from ( select id, name, birthday, gender, email, user_level, create_time, operate_time, '$do_date' start_date, '9999-99-99' end_date from ${APP}.ods_user_info where dt='$do_date' union all select uh.id, uh.name, uh.birthday, uh.gender, uh.email, uh.user_level, uh.create_time, uh.operate_time, uh.start_date, if(ui.id is not null and uh.end_date='9999-99-99', date_add(ui.dt,-1), uh.end_date) end_date from ${APP}.dwd_dim_user_info_his uh left join ( select * from ${APP}.ods_user_info where dt='$do_date' ) ui on uh.id=ui.id )his order by his.id, start_date;
insert overwrite table ${APP}.dwd_dim_user_info_his select * from ${APP}.dwd_dim_user_info_his_tmp;
"
sql2="
insert overwrite table ${APP}.dwd_dim_base_province select bp.id, bp.name, bp.area_code, bp.iso_code, bp.region_id, br.region_name from ${APP}.ods_base_province bp join ${APP}.ods_base_region br on bp.region_id=br.id;
"
case $1 in
"first"){
$hive -e "$sql1"
$hive -e "$sql2"
};;
"all"){
$hive -e "$sql1"
};;
esac
17.數倉搭建-DWS 層數據導入腳本
#!/bin/bash
APP=gmall
hive=/opt/module/hive/bin/hive
# 如果是輸入的日期按照取輸入日期；如果沒輸入日期取當前時間的前一天
if [ -n "$1" ] ;then
do_date=$1
else
do_date=`date -d "-1 day" +%F`
fi
sql="
insert overwrite table ${APP}.dws_uv_detail_daycount partition(dt='$do_date')
select
mid_id,
concat_ws('|', collect_set(user_id)) user_id,
concat_ws('|', collect_set(version_code)) version_code,
concat_ws('|', collect_set(version_name)) version_name,
concat_ws('|', collect_set(lang))lang,
concat_ws('|', collect_set(source)) source,
concat_ws('|', collect_set(os)) os,
concat_ws('|', collect_set(area)) area,
concat_ws('|', collect_set(model)) model,
concat_ws('|', collect_set(brand)) brand,
concat_ws('|', collect_set(sdk_version)) sdk_version,
concat_ws('|', collect_set(gmail)) gmail,
concat_ws('|', collect_set(height_width)) height_width,
concat_ws('|', collect_set(app_time)) app_time,
concat_ws('|', collect_set(network)) network,
concat_ws('|', collect_set(lng)) lng,
concat_ws('|', collect_set(lat)) lat,
count(*) login_count
from ${APP}.dwd_start_log
where dt='$do_date'
group by mid_id;
with
tmp_login as
(
select
user_id,
count(*) login_count
from ${APP}.dwd_start_log
where dt='$do_date'
and user_id is not null
group by user_id
),
tmp_cart as
(
select
user_id,
count(*) cart_count,
sum(cart_price*sku_num) cart_amount
from ${APP}.dwd_fact_cart_info
where dt='$do_date'
and user_id is not null
and date_format(create_time,'yyyy-MM-dd')='$do_date'
group by user_id
),
tmp_order as
(
select
user_id,
count(*) order_count,
sum(final_total_amount) order_amount
from ${APP}.dwd_fact_order_info
where dt='$do_date'
group by user_id
) ,
tmp_payment as
(
select
user_id,
count(*) payment_count,
sum(payment_amount) payment_amount
from ${APP}.dwd_fact_payment_info
where dt='$do_date'
group by user_id
)
insert overwrite table ${APP}.dws_user_action_daycount partition(dt='$do_date')
select
user_actions.user_id,
sum(user_actions.login_count),
sum(user_actions.cart_count),
sum(user_actions.cart_amount),
sum(user_actions.order_count),
sum(user_actions.order_amount),
sum(user_actions.payment_count),
sum(user_actions.payment_amount)
from
(
select
user_id,
login_count,
0 cart_count,
0 cart_amount,
0 order_count,
0 order_amount,
0 payment_count,
0 payment_amount
from
tmp_login
union all
select
user_id,
0 login_count,
cart_count,
cart_amount,
0 order_count,
0 order_amount,
0 payment_count,
0 payment_amount
from
tmp_cart
union all
select
user_id,
0 login_count,
0 cart_count,
0 cart_amount,
order_count,
order_amount,
0 payment_count,
0 payment_amount
from tmp_order
union all
select
user_id,
0 login_count,
0 cart_count,
0 cart_amount,
0 order_count,
0 order_amount,
payment_count,
payment_amount
from tmp_payment
) user_actions
group by user_id;
with
tmp_order as
(
select
sku_id,
count(*) order_count,
sum(sku_num) order_num,
sum(total_amount) order_amount
from ${APP}.dwd_fact_order_detail
where dt='$do_date'
group by sku_id
),
tmp_payment as
(
select
sku_id,
count(*) payment_count,
sum(sku_num) payment_num,
sum(total_amount) payment_amount
from ${APP}.dwd_fact_order_detail
where dt='$do_date'
and order_id in
(
select
id
from ${APP}.dwd_fact_order_info
where (dt='$do_date' or dt=date_add('$do_date',-1))
and date_format(payment_time,'yyyy-MM-dd')='$do_date'
)
group by sku_id
),
tmp_refund as
(
select
sku_id,
count(*) refund_count,
sum(refund_num) refund_num,
sum(refund_amount) refund_amount
from ${APP}.dwd_fact_order_refund_info
where dt='$do_date'
group by sku_id
),
tmp_cart as
(
select
sku_id,
count(*) cart_count,
sum(sku_num) cart_num
from ${APP}.dwd_fact_cart_info
where dt='$do_date'
and date_format(create_time,'yyyy-MM-dd')='$do_date'
group by sku_id
),
tmp_favor as
(
select
sku_id,
count(*) favor_count
from ${APP}.dwd_fact_favor_info
where dt='$do_date'
and date_format(create_time,'yyyy-MM-dd')='$do_date'
group by sku_id
),
tmp_appraise as
(
select
sku_id,
sum(if(appraise='1201',1,0)) appraise_good_count,
sum(if(appraise='1202',1,0)) appraise_mid_count,
sum(if(appraise='1203',1,0)) appraise_bad_count,
sum(if(appraise='1204',1,0)) appraise_default_count
from ${APP}.dwd_fact_comment_info
where dt='$do_date'
group by sku_id
)
insert overwrite table ${APP}.dws_sku_action_daycount partition(dt='$do_date')
select
sku_id,
sum(order_count),
sum(order_num),
sum(order_amount),
sum(payment_count),
sum(payment_num),
sum(payment_amount),
sum(refund_count),
sum(refund_num),
sum(refund_amount),
sum(cart_count),
sum(cart_num),
sum(favor_count),
sum(appraise_good_count),
sum(appraise_mid_count),
sum(appraise_bad_count),
sum(appraise_default_count)
from
(
select
sku_id,
order_count,
order_num,
order_amount,
0 payment_count,
0 payment_num,
0 payment_amount,
0 refund_count,
0 refund_num,
0 refund_amount,
0 cart_count,
0 cart_num,
0 favor_count,
0 appraise_good_count,
0 appraise_mid_count,
0 appraise_bad_count,
0 appraise_default_count
from tmp_order
union all
select
sku_id,
0 order_count,
0 order_num,
0 order_amount,
payment_count,
payment_num,
payment_amount,
0 refund_count,
0 refund_num,
0 refund_amount,
0 cart_count,
0 cart_num,
0 favor_count,
0 appraise_good_count,
0 appraise_mid_count,
0 appraise_bad_count,
0 appraise_default_count
from tmp_payment
union all
select
sku_id,
0 order_count,
0 order_num,
0 order_amount,
0 payment_count,
0 payment_num,
0 payment_amount,
refund_count,
refund_num,
refund_amount,
0 cart_count,
0 cart_num,
0 favor_count,
0 appraise_good_count,
0 appraise_mid_count,
0 appraise_bad_count,
0 appraise_default_count
from tmp_refund
union all
select
sku_id,
0 order_count,
0 order_num,
0 order_amount,
0 payment_count,
0 payment_num,
0 payment_amount,
0 refund_count,
0 refund_num,
0 refund_amount,
cart_count,
cart_num,
0 favor_count,
0 appraise_good_count,
0 appraise_mid_count,
0 appraise_bad_count,
0 appraise_default_count
from tmp_cart
union all
select
sku_id,
0 order_count,
0 order_num,
0 order_amount,
0 payment_count,
0 payment_num,
0 payment_amount,
0 refund_count,
0 refund_num,
0 refund_amount,
0 cart_count,
0 cart_num,
favor_count,
0 appraise_good_count,
0 appraise_mid_count,
0 appraise_bad_count,
0 appraise_default_count
from tmp_favor
union all
select
sku_id,
0 order_count,
0 order_num,
0 order_amount,
0 payment_count,
0 payment_num,
0 payment_amount,
0 refund_count,
0 refund_num,
0 refund_amount,
0 cart_count,
0 cart_num,
0 favor_count,
appraise_good_count,
appraise_mid_count,
appraise_bad_count,
appraise_default_count
from tmp_appraise
)tmp
group by sku_id;
insert overwrite table ${APP}.dws_coupon_use_daycount partition(dt='$do_date')
select
cu.coupon_id,
ci.coupon_name,
ci.coupon_type,
ci.condition_amount,
ci.condition_num,
ci.activity_id,
ci.benefit_amount,
ci.benefit_discount,
ci.create_time,
ci.range_type,
ci.spu_id,
ci.tm_id,
ci.category3_id,
ci.limit_num,
cu.get_count,
cu.using_count,
cu.used_count
from
(
select
coupon_id,
sum(if(date_format(get_time,'yyyy-MM-dd')='$do_date',1,0)) get_count,
sum(if(date_format(using_time,'yyyy-MM-dd')='$do_date',1,0)) using_count,
sum(if(date_format(used_time,'yyyy-MM-dd')='$do_date',1,0)) used_count
from ${APP}.dwd_fact_coupon_use
where dt='$do_date'
group by coupon_id
)cu
left join
(
select
*
from ${APP}.dwd_dim_coupon_info
where dt='$do_date'
)ci on cu.coupon_id=ci.id;
insert overwrite table ${APP}.dws_activity_info_daycount partition(dt='$do_date')
select
oi.activity_id,
ai.activity_name,
ai.activity_type,
ai.start_time,
ai.end_time,
ai.create_time,
oi.order_count,
oi.payment_count
from
(
select
activity_id,
sum(if(date_format(create_time,'yyyy-MM-dd')='$do_date',1,0)) order_count,
sum(if(date_format(payment_time,'yyyy-MM-dd')='$do_date',1,0)) payment_count
from ${APP}.dwd_fact_order_info
where (dt='$do_date' or dt=date_add('$do_date',-1))
and activity_id is not null
group by activity_id
)oi
join
(
select
*
from ${APP}.dwd_dim_activity_info
where dt='$do_date'
)ai
on oi.activity_id=ai.id;
insert overwrite table ${APP}.dws_sale_detail_daycount partition(dt='$do_date')
select
op.user_id,
op.sku_id,
ui.gender,
months_between('$do_date', ui.birthday)/12 age,
ui.user_level,
si.price,
si.sku_name,
si.tm_id,
si.category3_id,
si.category2_id,
si.category1_id,
si.category3_name,
si.category2_name,
si.category1_name,
si.spu_id,
op.sku_num,
op.order_count,
op.order_amount
from
(
select
user_id,
sku_id,
sum(sku_num) sku_num,
count(*) order_count,
sum(total_amount) order_amount
from ${APP}.dwd_fact_order_detail
where dt='$do_date'
group by user_id, sku_id
)op
join
(
select
*
from ${APP}.dwd_dim_user_info_his
where end_date='9999-99-99'
)ui on op.user_id = ui.id
join
(
select
*
from ${APP}.dwd_dim_sku_info
where dt='$do_date'
)si on op.sku_id = si.id;
"
$hive -e "$sql"
18.數倉搭建-DWT 層數據導入腳本
#!/bin/bash
APP=gmall
hive=/opt/module/hive/bin/hive
# 如果是輸入的日期按照取輸入日期；如果沒輸入日期取當前時間的前一天
if [ -n "$1" ] ;then
do_date=$1
else
do_date=`date -d "-1 day" +%F`
fi
sql="
insert overwrite table ${APP}.dwt_uv_topic
select
nvl(new.mid_id,old.mid_id),
nvl(new.user_id,old.user_id),
nvl(new.version_code,old.version_code),
nvl(new.version_name,old.version_name),
nvl(new.lang,old.lang),
nvl(new.source,old.source),
nvl(new.os,old.os),
nvl(new.area,old.area),
nvl(new.model,old.model),
nvl(new.brand,old.brand),
nvl(new.sdk_version,old.sdk_version),
nvl(new.gmail,old.gmail),
nvl(new.height_width,old.height_width),
nvl(new.app_time,old.app_time),
nvl(new.network,old.network),
nvl(new.lng,old.lng),
nvl(new.lat,old.lat),
nvl(old.login_date_first,'$do_date'),
if(new.login_count>0,'$do_date',old.login_date_last),
nvl(new.login_count,0),
nvl(new.login_count,0)+nvl(old.login_count,0)
from
(
select
*
from ${APP}.dwt_uv_topic
)old
full outer join
(
select
*
from ${APP}.dws_uv_detail_daycount
where dt='$do_date'
)new
on old.mid_id=new.mid_id;
insert overwrite table ${APP}.dwt_user_topic
select
nvl(new.user_id,old.user_id),
if(old.login_date_first is null and new.login_count>0,'$do_date',old.login_date_first),
if(new.login_count>0,'$do_date',old.login_date_last),
nvl(old.login_count,0)+if(new.login_count>0,1,0),
nvl(new.login_last_30d_count,0),
if(old.order_date_first is null and new.order_count>0,'$do_date',old.order_date_first),
if(new.order_count>0,'$do_date',old.order_date_last),
nvl(old.order_count,0)+nvl(new.order_count,0),
nvl(old.order_amount,0)+nvl(new.order_amount,0),
nvl(new.order_last_30d_count,0),
nvl(new.order_last_30d_amount,0),
if(old.payment_date_first is null and new.payment_count>0,'$do_date',old.payment_date_first),
if(new.payment_count>0,'$do_date',old.payment_date_last),
nvl(old.payment_count,0)+nvl(new.payment_count,0),
nvl(old.payment_amount,0)+nvl(new.payment_amount,0),
nvl(new.payment_last_30d_count,0),
nvl(new.payment_last_30d_amount,0)
from
(
select
*
from ${APP}.dwt_user_topic
)old
full outer join
(
select
user_id,
sum(if(dt='$do_date',login_count,0)) login_count,
sum(if(dt='$do_date',order_count,0)) order_count,
sum(if(dt='$do_date',order_amount,0)) order_amount,
sum(if(dt='$do_date',payment_count,0)) payment_count,
sum(if(dt='$do_date',payment_amount,0)) payment_amount,
sum(if(order_count>0,1,0)) login_last_30d_count,
sum(order_count) order_last_30d_count,
sum(order_amount) order_last_30d_amount,
sum(payment_count) payment_last_30d_count,
sum(payment_amount) payment_last_30d_amount
from ${APP}.dws_user_action_daycount
where dt>=date_add( '$do_date',-30)
group by user_id
)new
on old.user_id=new.user_id;
with
sku_act as
(
select
sku_id,
sum(if(dt='$do_date', order_count,0 )) order_count,
sum(if(dt='$do_date',order_num ,0 )) order_num,
sum(if(dt='$do_date',order_amount,0 )) order_amount ,
sum(if(dt='$do_date',payment_count,0 )) payment_count,
sum(if(dt='$do_date',payment_num,0 )) payment_num,
sum(if(dt='$do_date',payment_amount,0 )) payment_amount,
sum(if(dt='$do_date',refund_count,0 )) refund_count,
sum(if(dt='$do_date',refund_num,0 )) refund_num,
sum(if(dt='$do_date',refund_amount,0 )) refund_amount,
sum(if(dt='$do_date',cart_count,0 )) cart_count,
sum(if(dt='$do_date',cart_num,0 )) cart_num,
sum(if(dt='$do_date',favor_count,0 )) favor_count,
sum(if(dt='$do_date',appraise_good_count,0 )) appraise_good_count,
sum(if(dt='$do_date',appraise_mid_count,0 ) ) appraise_mid_count ,
sum(if(dt='$do_date',appraise_bad_count,0 )) appraise_bad_count,
sum(if(dt='$do_date',appraise_default_count,0 )) appraise_default_count,
sum( order_count ) order_count30 ,
sum( order_num ) order_num30,
sum(order_amount ) order_amount30,
sum(payment_count ) payment_count30,
sum(payment_num ) payment_num30,
sum(payment_amount ) payment_amount30,
sum(refund_count ) refund_count30,
sum(refund_num ) refund_num30,
sum(refund_amount ) refund_amount30,
sum(cart_count ) cart_count30,
sum(cart_num ) cart_num30,
sum(favor_count ) favor_count30,
sum(appraise_good_count ) appraise_good_count30,
sum(appraise_mid_count ) appraise_mid_count30,
sum(appraise_bad_count ) appraise_bad_count30,
sum(appraise_default_count ) appraise_default_count30
from ${APP}.dws_sku_action_daycount
where dt>=date_add ( '$do_date',-30)
group by sku_id
),
sku_topic
as
(
select
sku_id,
spu_id,
order_last_30d_count,
order_last_30d_num,
order_last_30d_amount,
order_count,
order_num,
order_amount ,
payment_last_30d_count,
payment_last_30d_num,
payment_last_30d_amount,
payment_count,
payment_num,
payment_amount,
refund_last_30d_count,
refund_last_30d_num,
refund_last_30d_amount,
refund_count,
refund_num,
refund_amount,
cart_last_30d_count,
cart_last_30d_num,
cart_count,
cart_num ,
favor_last_30d_count ,
favor_count ,
appraise_last_30d_good_count ,
appraise_last_30d_mid_count ,
appraise_last_30d_bad_count ,
appraise_last_30d_default_count ,
appraise_good_count ,
appraise_mid_count ,
appraise_bad_count ,
appraise_default_count
from ${APP}.dwt_sku_topic
)
insert overwrite table ${APP}.dwt_sku_topic
select
nvl(sku_act.sku_id,sku_topic.sku_id) ,
sku_info.spu_id,
nvl (sku_act.order_count30,0) ,
nvl (sku_act.order_num30,0) ,
nvl (sku_act.order_amount30,0) ,
nvl(sku_topic.order_count,0)+ nvl (sku_act.order_count,0) ,
nvl(sku_topic.order_num,0)+ nvl (sku_act.order_num,0) ,
nvl(sku_topic.order_amount,0)+ nvl (sku_act.order_amount,0),
nvl (sku_act.payment_count30,0),
nvl (sku_act.payment_num30,0),
nvl (sku_act.payment_amount30,0),
nvl(sku_topic.payment_count,0)+ nvl (sku_act.payment_count,0) ,
nvl(sku_topic.payment_num,0)+ nvl (sku_act.payment_count,0) ,
nvl(sku_topic.payment_amount,0)+ nvl (sku_act.payment_count,0) ,
nvl (refund_count30,0), nvl (sku_act.refund_num30,0),
nvl (sku_act.refund_amount30,0),
nvl(sku_topic.refund_count,0)+ nvl (sku_act.refund_count,0),
nvl(sku_topic.refund_num,0)+ nvl (sku_act.refund_num,0),
nvl(sku_topic.refund_amount,0)+ nvl (sku_act.refund_amount,0),
nvl(sku_act.cart_count30,0) ,
nvl(sku_act.cart_num30,0) ,
nvl(sku_topic.cart_count ,0)+ nvl (sku_act.cart_count,0),
nvl( sku_topic.cart_num ,0)+ nvl (sku_act.cart_num,0),
nvl(sku_act.favor_count30 ,0) ,
nvl (sku_topic.favor_count ,0)+ nvl (sku_act.favor_count,0),
nvl (sku_act.appraise_good_count30 ,0) ,
nvl (sku_act.appraise_mid_count30 ,0) ,
nvl (sku_act.appraise_bad_count30 ,0) ,
nvl (sku_act.appraise_default_count30 ,0) ,
nvl (sku_topic.appraise_good_count ,0)+ nvl (sku_act.appraise_good_count,0) ,
nvl (sku_topic.appraise_mid_count ,0)+ nvl (sku_act.appraise_mid_count,0) ,
nvl (sku_topic.appraise_bad_count ,0)+ nvl (sku_act.appraise_bad_count,0) ,
nvl (sku_topic.appraise_default_count ,0)+ nvl (sku_act.appraise_default_count,0)
from sku_act
full outer join sku_topic
on sku_act.sku_id =sku_topic.sku_id
left join
(select * from ${APP}.dwd_dim_sku_info where dt='$do_date') sku_info
on nvl(sku_topic.sku_id,sku_act.sku_id)= sku_info.id;
insert overwrite table ${APP}.dwt_coupon_topic
select
nvl(new.coupon_id,old.coupon_id),
nvl(new.get_count,0),
nvl(new.using_count,0),
nvl(new.used_count,0),
nvl(old.get_count,0)+nvl(new.get_count,0),
nvl(old.using_count,0)+nvl(new.using_count,0),
nvl(old.used_count,0)+nvl(new.used_count,0)
from
(
select
*
from ${APP}.dwt_coupon_topic
)old
full outer join
(
select
coupon_id,
get_count,
using_count,
used_count
from ${APP}.dws_coupon_use_daycount
where dt='$do_date'
)new
on old.coupon_id=new.coupon_id;
insert overwrite table ${APP}.dwt_activity_topic
select
nvl(new.id,old.id),
nvl(new.activity_name,old.activity_name),
nvl(new.order_count,0),
nvl(new.payment_count,0),
nvl(old.order_count,0)+nvl(new.order_count,0),
nvl(old.payment_count,0)+nvl(new.payment_count,0)
from
(
select
*
from ${APP}.dwt_activity_topic
)old
full outer join
(
select
id,
activity_name,
order_count,
payment_count
from ${APP}.dws_activity_info_daycount
where dt='$do_date'
)new
on old.id=new.id;
"
$hive -e "$sql"
19.數倉搭建-ADS 層會員主題信息導入腳本
#!/bin/bash
APP=gmall
hive=/opt/module/hive/bin/hive
# 如果是輸入的日期按照取輸入日期；如果沒輸入日期取當前時間的前一天
if [ -n "$1" ] ;then
do_date=$1
else
do_date=`date -d "-1 day" +%F`
fi
sql="
with
tmp_day_users as
(
select
'$do_date' dt,
count(*) day_users
from
${APP}.dwt_user_topic
where
login_date_last='$do_date'
),
tmp_day_new_users as
(
select
'$do_date' dt,
count(*) day_new_users
from
${APP}.dwt_user_topic
where
login_date_last='$do_date' and login_date_first='$do_date'
),
tmp_day_new_payment_users as
(
select
'$do_date' dt,
count(*) day_new_payment_users
from
${APP}.dwt_user_topic
where
payment_date_first='$do_date'
),
tmp_payment_users as
(
select
'$do_date' dt,
count(*) payment_users
from
${APP}.dwt_user_topic
where
payment_date_first is not null
),
tmp_users as
(
select
'$do_date' dt,
count(*) users
from
${APP}.dwt_user_topic
tmp_users
)
insert into table ${APP}.ads_user_topic
select
'$do_date' dt,
day_users,
day_new_users,
day_new_payment_users,
payment_users,
users,
day_users/users,
payment_users/users,
day_new_users/users
from
tmp_day_users
join
tmp_day_new_users
on
tmp_day_users.dt=tmp_day_new_users.dt
join
tmp_day_new_payment_users
on
tmp_day_users.dt=tmp_day_new_payment_users.dt
join
tmp_payment_users
on
tmp_day_users.dt=tmp_payment_users.dt
join
tmp_users
on
tmp_day_users.dt=tmp_users.dt;
"
$hive -e "$sql"
20.數倉搭建-ADS 層導入腳本
#!/bin/bash
hive=/opt/module/hive/bin/hive
# 如果是輸入的日期按照取輸入日期；如果沒輸入日期取當前時間的前一天
if [ -n "$1" ] ;then
do_date=$1
else
do_date=`date -d "-1 day" +%F`
fi
sql="use gmall;
insert into table ads_uv_count
select
'$do_date',
sum(if(login_date_last='$do_date',1,0)),
sum(if(login_date_last>=date_add(next_day('$do_date','monday'),-7) and login_date_last<=date_add(next_day('$do_date','monday'),-1) ,1,0)),
sum(if(date_format(login_date_last,'yyyy-MM')=date_format('$do_date','yyyy-M M'),1,0)),
if('$do_date'=date_add(next_day('$do_date','monday'),-1),'Y','N'),
if('$do_date'=last_day('$do_date'),'Y','N')
from dwt_uv_topic;
insert into table ads_new_mid_count
select
'$do_date',
count(*)
from dwt_uv_topic
where login_date_first='$do_date';
insert into table ads_silent_count
select
'$do_date',
count(*)
from dwt_uv_topic
where login_date_first=login_date_last and login_date_last<=date_add('$do_date',-7);
insert into table ads_back_count
select
'$do_date',
concat(date_add(next_day('2020-03-10','MO'),-7),'_',date_add(next_day('2020- 03-10','MO'),-1)),
count(*)
from
(
select
mid_id
from dwt_uv_topic
where login_date_last>=date_add(next_day('$do_date','MO'),-7)
and login_date_last<= date_add(next_day('$do_date','MO'),-1)
and login_date_first<date_add(next_day('$do_date','MO'),-7) )current_wk
left join
(
select
mid_id
from dws_uv_detail_daycount
where dt>=date_add(next_day('$do_date','MO'),-7*2)
and dt<= date_add(next_day('$do_date','MO'),-7-1)
group by mid_id
)last_wk
on current_wk.mid_id=last_wk.mid_id
where last_wk.mid_id is null;
insert into table ads_wastage_count
select
'$do_date',
count(*)
from dwt_uv_topic
where login_date_last<=date_add('$do_date',-7);
insert into table ads_user_retention_day_rate
select
'$do_date',
date_add('$do_date',-3),
3,
sum(if(login_date_first=date_add('$do_date',-3) and login_date_last='$do_date',1,0)),
sum(if(login_date_first=date_add('$do_date',-3),1,0)),
sum(if(login_date_first=date_add('$do_date',-3) and login_date_last='$do_date',1,0))/sum(if(login_date_first=date_add('$do_date', -3),1,0))*100
from dwt_uv_topic
union all
select
'$do_date',
date_add('$do_date',-2),
2,
sum(if(login_date_first=date_add('$do_date',-2) and login_date_last='$do_date',1,0)),
sum(if(login_date_first=date_add('$do_date',-2),1,0)),
sum(if(login_date_first=date_add('$do_date',-2) and login_date_last='$do_date',1,0))/sum(if(login_date_first=date_add('$do_date', -2),1,0))*100
from dwt_uv_topic
union all
select
'$do_date',
date_add('$do_date',-1),
1,
sum(if(login_date_first=date_add('$do_date',-1) and login_date_last='$do_date',1,0)),
sum(if(login_date_first=date_add('$do_date',-1),1,0)),
sum(if(login_date_first=date_add('$do_date',-1) and login_date_last='$do_date',1,0))/sum(if(login_date_first=date_add('$do_date', -1),1,0))*100
from dwt_uv_topic;
insert into table ads_continuity_wk_count
select
'$do_date',
concat(date_add(next_day('$do_date','MO'),-7*3),'_',date_add(next_day('$do_d ate','MO'),-1)),
count(*)
from
(
select
mid_id
from
(
select
mid_id
from dws_uv_detail_daycount
where dt>=date_add(next_day('$do_date','monday'),-7)
and dt<=date_add(next_day('$do_date','monday'),-1)
group by mid_id
union all
select
mid_id
from dws_uv_detail_daycount
where dt>=date_add(next_day('$do_date','monday'),-7*2)
and dt<=date_add(next_day('$do_date','monday'),-7-1)
group by mid_id
union all
select
mid_id
from dws_uv_detail_daycount
where dt>=date_add(next_day('$do_date','monday'),-7*3)
and dt<=date_add(next_day('$do_date','monday'),-7*2-1)
group by mid_id
)t1
group by mid_id having count(*)=3
)t2;
insert into table ads_continuity_uv_count
select
'$do_date',
concat(date_add('$do_date',-6),'_','$do_date'),
count(*)
from
(
select mid_id
from
(
select mid_id
from
(
select
mid_id,
date_sub(dt,rank) date_dif
from
(
select
mid_id,
dt,
rank() over(partition by mid_id order by dt) rank
from dws_uv_detail_daycount
where dt>=date_add('$do_date',-6) and dt<='$do_date'
)t1
)t2
group by mid_id,date_dif
having count(*)>=3
)t3
group by mid_id
)t4;
insert into table ads_user_topic
select
'$do_date',
sum(if(login_date_last='$do_date',1,0)),
sum(if(login_date_first='$do_date',1,0)),
sum(if(payment_date_first='$do_date',1,0)),
sum(if(payment_count>0,1,0)), count(*),
sum(if(login_date_last='$do_date',1,0))/count(*),
sum(if(payment_count>0,1,0))/count(*),
sum(if(login_date_first='$do_date',1,0))/sum(if(login_date_last='$do_date',1, 0))
from dwt_user_topic;
insert into table ads_user_action_convert_day
select
'$do_date',
uv.day_count,
ua.cart_count,
ua.cart_count/uv.day_count*100 visitor2cart_convert_ratio,
ua.order_count,
ua.order_count/ua.cart_count*100 visitor2order_convert_ratio,
ua.payment_count,
ua.payment_count/ua.order_count*100 order2payment_convert_ratio
from
(
select
'$do_date' dt,
sum(if(cart_count>0,1,0)) cart_count,
sum(if(order_count>0,1,0)) order_count,
sum(if(payment_count>0,1,0)) payment_count
from dws_user_action_daycount
where dt='$do_date'
)ua join ads_uv_count uv on uv.dt=ua.dt;
insert into table ads_product_info
select
'$do_date' dt,
sku_num,
spu_num
from
(
select
'$do_date' dt,
count(*) sku_num
from
dwt_sku_topic
) tmp_sku_num
join
(
select
'$do_date' dt,
count(*) spu_num
from
(
select
spu_id
from
dwt_sku_topic
group by
spu_id
) tmp_spu_id
) tmp_spu_num
on tmp_sku_num.dt=tmp_spu_num.dt;
insert into table ads_product_sale_topN
select
'$do_date',
sku_id,
payment_amount
from dws_sku_action_daycount
where dt='$do_date'
order by payment_amount desc
limit 10;
insert into table ads_product_favor_topN
select
'$do_date',
sku_id,
favor_count
from dws_sku_action_daycount
where dt='$do_date'
order by favor_count
limit 10;
insert into table ads_product_cart_topN
select
'$do_date' dt,
sku_id,
cart_num
from dws_sku_action_daycount
where dt='$do_date'
order by cart_num
limit 10;
insert into table ads_product_refund_topN
select
'$do_date',
sku_id,
refund_last_30d_count/payment_last_30d_count*100 refund_ratio
from dwt_sku_topic
order by refund_ratio desc
limit 10;
insert into table ads_appraise_bad_topN
select
'$do_date' dt,
sku_id,
appraise_bad_count/(appraise_bad_count+appraise_good_count+appraise_mid_count+appraise_default_count)*100 appraise_bad_ratio
from dws_sku_action_daycount
where dt='$do_date'
order by appraise_bad_ratio desc
limit 10;
insert into table ads_order_daycount
select
'$do_date',
sum(order_count),
sum(order_amount),
sum(if(order_count>0,1,0))
from dws_user_action_daycount
where dt='$do_date';
insert into table ads_payment_daycount
select
tmp_payment.dt,
tmp_payment.payment_count,
tmp_payment.payment_amount,
tmp_payment.payment_user_count,
tmp_skucount.payment_sku_count,
tmp_time.payment_avg_time
from
(
select
'$do_date' dt,
sum(payment_count) payment_count,
sum(payment_amount) payment_amount,
sum(if(payment_count>0,1,0)) payment_user_count
from dws_user_action_daycount
where dt='$do_date'
)tmp_payment
join
(
select
'$do_date' dt,
sum(if(payment_count>0,1,0)) payment_sku_count
from dws_sku_action_daycount
where dt='$do_date'
)tmp_skucount on tmp_payment.dt=tmp_skucount.dt
join
(
select
'$do_date' dt,
sum(unix_timestamp(payment_time)-unix_timestamp(create_time))/count(*)/60 payment_avg_time
from dwd_fact_order_info
where dt='$do_date'
and payment_time is not null
)tmp_time on tmp_payment.dt=tmp_time.dt;
insert into table ads_sale_tm_category1_stat_mn
select
mn.sku_tm_id,
mn.sku_category1_id,
mn.sku_category1_name,
sum(if(mn.order_count>=1,1,0)) buycount,
sum(if(mn.order_count>=2,1,0)) buyTwiceLast,
sum(if(mn.order_count>=2,1,0))/sum( if(mn.order_count>=1,1,0)) buyTwiceLastRatio,
sum(if(mn.order_count>=3,1,0)) buy3timeLast ,
sum(if(mn.order_count>=3,1,0))/sum( if(mn.order_count>=1,1,0)) buy3timeLastRatio ,
date_format('$do_date' ,'yyyy-MM') stat_mn,
'$do_date' stat_date
from
(
select
user_id,
sd.sku_tm_id,
sd.sku_category1_id,
sd.sku_category1_name,
sum(order_count) order_count
from dws_sale_detail_daycount sd
where date_format(dt,'yyyy-MM')=date_format('$do_date' ,'yyyy-MM')
group by user_id, sd.sku_tm_id, sd.sku_category1_id, sd.sku_category1_name
) mn
group by mn.sku_tm_id, mn.sku_category1_id, mn.sku_category1_name;
"
$hive -e "$sql"
21.hdfs_to_mysql傳輸腳本
#!/bin/bash
hive_db_name=gmall
mysql_db_name=gmall_report
export_data() {
/opt/module/sqoop/bin/sqoop export --connect "jdbc:mysql://hadoop102:3306/${mysql_db_name}?useUnicode=true& characterEncoding=utf-8" --username root --password 123456 --table $1 --num-mappers 1 --export-dir /warehouse/$hive_db_name/ads/$1 --input-fields-terminated-by "\t" --update-mode allowinsert --update-key $2 --input-null-string '\\N' --input-null-non-string '\\N'
}
case $1 in
"ads_uv_count")
export_data "ads_uv_count" "dt"
;;
"ads_user_action_convert_day")
export_data "ads_user_action_convert_day" "dt"
;;
"ads_user_topic")
export_data "ads_user_topic" "dt"
;;
"all")
export_data "ads_uv_count" "dt"
export_data "ads_user_action_convert_day" "dt"
export_data "ads_user_topic" "dt"
;;
esac