首頁經營效果中,增加按發布產品拆分指標選項
出自 qingwei personal wiki
目錄
描述
https://aone.alibaba-inc.com/req/17665713
新表
- dwp_en_dm_vip_comp_term_region_catelv3_cube_d (dwp_en_dm_vip_comp_term_region_cube_d)
- dwp_en_dm_vip_catelv3_term_cube_d (dwp_en_dm_vip_cate_term_cube_d)
- 獲取具體類目的指標在行業平均效果 (老表不分類目,是店鋪的所有類目匯總)
- 指標包括 'comp_fb_uv' , 'comp_ord_amt' , 'shop_pv' , 'comp_ord_cnt' , 'comp_clk_cnt' , 'comp_atm_uv' , 'shop_uv' , 'comp_imps_cnt' , 'comp_fb_cnt'
- dwp_en_dm_vip_comp_cate_term_eff_d (dwp_en_dm_vip_comp_term_eff_d)
oneness
vip.home.getShopSummary
select
${returnFields}
from
<if test='statisticsType == "day" and seperateByCate == "false"'>
dwp_en_dm_vip_comp_term_eff_d
</if>
<if test='statisticsType == "week" and seperateByCate == "false"'>
dwp_en_dm_vip_comp_term_eff_w
</if>
<if test='statisticsType == "month" and seperateByCate == "false"'>
dwp_en_dm_vip_comp_term_eff_m
</if>
<if test='statisticsType == "day" and seperateByCate == "true"'>
dwp_en_dm_vip_comp_cate_term_eff_d
</if>
<if test='statisticsType == "week" and seperateByCate == "true"'>
dwp_en_dm_vip_comp_cate_term_eff_w
</if>
<if test='statisticsType == "month" and seperateByCate == "true"'>
dwp_en_dm_vip_comp_cate_term_eff_m
</if>
where
admin_mbr_seq = #{adminMemberSeq}
and terminal_type = #{terminalType}
<if test='seperateByCate == "true"'>
and cate_lv3_id = #{cateId}
</if>
<if test="statDateList != null">
and stat_date in
<foreach collection="statDateList" item="item" open="(" separator="," close=")">
#{item}
</foreach>
</if>
<if test="region!= null">
and statistic_type = #{region}
</if>
hsf 測試
vip/home/getShopSummary
[
"vip/home/getShopSummary-new",
{
"adminMemberSeq": "14",
"statDate": "2018-12-04",
"statisticsType": "day",
"prevDate": "2018-12-03",
"cateId": "330",
"seperateByCate": "true"
}
]
- 比較老版少了4個字段 (dwp_en_dm_vip_comp_cate_term_eff_d)
- statDate {1} fbUv {4} orderAmount {4} shopPv {4} orderCount {4} searchClicks {4} shopUv {4} tmUv {4} searchImps {4} fbPv
- statDate {1} fbUv {4} searchClicks {4} tmUv {4} searchImps {4} fbPv {4}
- 少的字段: orderAmount shopPv orderCount shopUv
vip/home/getShopTrends
[
"vip/home/getShopTrends-new",
{
"adminMemberSeq": "14",
"beginDate": "2018-12-03",
"endDate": "2018-12-04",
"statisticsType": "day",
"cateId": "145",
"seperateByCate": "true"
}
]
vip/home/getShopRegionAnalysis
[
"vip/home/getShopRegionAnalysis-new",
{
"adminMemberSeq": "14",
"statDate": "2018-12-04",
"statisticsType": "day",
"cateId": "1521",
"seperateByCate": "true"
}
]
[
"vip/home/getShopRegionAnalysis-new",
{
"adminMemberSeq": "14",
"statDate": "2018-12-08",
"statisticsType": "week",
"cateId": "1521",
"seperateByCate": "true"
}
]
oneness查詢
行業平均(數據有問題!!!)
select
stat_date as statDate,
round(cate_lv3_top10_avg,
1) as cateAvg,
target_type as indicatorType,
round(cate_lv3_top10_avg) as cateTop10Avg
from
dwp_en_dm_vip_catelv3_term_cube_m
where
cate_lv3_id = '127726013'
and stat_date >= '2018-11-01'
and '2018-12-01' >= stat_date
and terminal_type = 'TOTAL'
and statistic_type = 'all'
and target_type in (
'comp_fb_uv' , 'adm_click_cnt' , 'comp_clk_cnt' , 'comp_atm_uv' , 'comp_imps_cnt' , 'comp_fb_cnt' , 'adm_imps_cnt'
)
卡片數據與趨勢數據最後一天對應不上(添加選擇框後)
# 为 空
select
stat_date as statDate,
fb_uv_1d_013 as fbUv,
clk_cnt_1d_092 as searchClicks,
fb_uv_1d_014 as tmUv,
imps_cnt_1d_027 as searchImps,
fb_cnt_1d_013 as fbPv
from
dwp_en_dm_vip_comp_cate_term_eff_d
where
admin_mbr_seq = '200042360'
and terminal_type = 'TOTAL'
and cate_lv3_id = '127820002'
and stat_date = '2018-12-23'
and statistic_type = 'all'
線上問題
類目數據
SELECT
cate_lv2_id, cate_lv2_desc, cate_lv3_id, cate_lv3_desc
FROM
dwp_en_dm_vip_comp_cate_filter_d
WHERE
stat_date='2019-01-07'
AND admin_mbr_seq=230098990
卡片數據
# 用户supeall 两个3级类目:127726081, 5904002 数据一样
select
stat_date as statDate,
fb_uv_1d_013 as fbUv,
adm_click_cnt_1d_003 as p4pClickCnt,
clk_cnt_1d_092 as searchClicks,
fb_uv_1d_014 as tmUv,
imps_cnt_1d_027 as searchImps,
fb_cnt_1d_013 as fbPv,
adm_imps_cnt_1d_001 as p4pExposureCnt
from
dwp_en_dm_vip_comp_cate_term_eff_d
where
admin_mbr_seq = '230098990'
and terminal_type = 'TOTAL'
and cate_lv3_id = '5904002'
and stat_date in (
'2019-01-07' , '2018-12-31'
)
and statistic_type = 'os'