简介
在今年2月初,SLS 已经发布针对新冠病毒肺炎疫情国内动态展示分析 APP,目前该能力全面开放给政府、社区、第三方平台和开放者进行广泛应用,完全免费开放。
简介
SLS
SLS


亮点
亮点
1. 提供规整的疫情数据,并每天定时同步更新
SLS 已经将疫情相关数据进行收集和规整,每天定时更新,并形成可视化平台覆盖全球各个国家/地区、省份/州的疫情信息。你只需要专注在数据的分析和展示,其它繁琐的细节 SLS 都已经处理好。



3. 数据平台开放,互联互通

数据
数据
数据样例
type: Country/Region Cases
version: v2020-04-17T11:55:36
Last Update: 2020-04-09 01:12:20
Country/Region: China
Country/Region (ch): 中国
LatLng: 35.000074,104.999927
Confirmed: 83798
Confirmed Hist: [644, 923, 1409, 2079, 2882]
Confirmed Trend: {"2020-01-23": 644, "2020-01-24": 923, "2020-01-25": 1409, "2020-01-26": 2079, "2020-01-27": 2882}
New Confirmed Hist: [95, 279, 486, 670, 803]
New Confirmed Trend: {"2020-01-23": 95, "2020-01-24": 279, "2020-01-25": 486, "2020-01-26": 670, "2020-01-27": 803}
Deaths: 3352
Deaths Hist: [18, 26, 42, 56, 82]
Deaths Trend: {"2020-01-23": 18, "2020-01-24": 26, "2020-01-25": 42, "2020-01-26": 56, "2020-01-27": 82}
Recovered: 78556
Recovered Hist: [30, 36, 39, 49, 58]
Recovered Trend: {"2020-01-23": 30, "2020-01-24": 36, "2020-01-25": 39, "2020-01-26": 49, "2020-01-27": 58}
数据格式

实时:写入后可以立即被分析。
快速:一秒内,查询(5个条件)可处理10亿级数据,分析(5个维度聚合+GroupBy)可聚合亿级别数据。
灵活:可以改变任意查询和分析条件,实时获取结果。
生态丰富:除控制台提供的报表、仪表盘、快速分析等功能外,还可以与Grafana、DataV、Jaeger等产品无缝对接,并支持Restful API,JDBC等协议。
type : "Province/State Cases" | select .... from log l right join (select max(version) as version from log) r on l.version = r.version
type : "Global Cases" | select date_format(date_parse(l.a, '%Y-%m-%d'), '%b %e') as "Date", l.b as "Confirmed", l.b - r2.b - r6.b as "Active Confirmed", r2.b as "Deaths", r6.b as "Recovered" from (select a,b from log l right join (select max(version) as version from log) r on l.version = r.version, unnest( cast( json_parse("Confirmed Trend") as map(varchar, bigint) ) ) as t(a,b)) l left join (select a,b from log l right join (select max(version) as version from log) r on l.version = r.version, unnest( cast( json_parse("New Confirmed Trend") as map(varchar, bigint) ) ) as t(a,b)) r on l.a = r.a left join (select a, b from log l right join (select max(version) as version from log) r on l.version = r.version, unnest( cast( json_parse("Deaths Trend") as map(varchar, bigint) ) ) as t(a, b)) r2 on l.a = r2.a left join (select a, b from log l right join (select max(version) as version from log) r on l.version = r.version, unnest( cast( json_parse("Recovered Trend") as map(varchar, bigint) ) ) as t(a, b)) r6 on l.a = r6.a order by l.a

