clickhouse MATERIALIZED VIEW 问题答案

【问题标题】：clickhouse MATERIALIZED VIEW issuesclickhouse MATERIALIZED VIEW 问题
【发布时间】：2020-12-18 20:03:19
【问题描述】：

我这样创建了 MATERIALIZED VIEW：

创建目标表：

CREATE TABLE user_deatils_daily (
  day date,
  hour UInt8 ,
  appid UInt32,
  isp String,
  city String,
  country String,
  session_count UInt64,
  avg_score AggregateFunction(avg, Float32),
  min_revenue  AggregateFunction(min, Float32),
  max_load_time AggregateFunction(max, Int32)
)
ENGINE = SummingMergeTree()
PARTITION BY toRelativeWeekNum(day) 
ORDER BY (day,hour)

创建MV：

CREATE MATERIALIZED VIEW user_deatils_daily_mv
TO user_deatils_daily as 
select toDate(session_ts) as day, toHour(toDateTime(session_ts)) as hour,appid,isp,city,country,
count(session_uuid) as session_count,avgState() as avg_score,
minState(revenue) as min_revenue,
maxState(perf_page_load_time) as max_load_time 
from user_deatils where toDate(session_ts)>='2020-08-26' group by session_ts,appid,isp,city,country

目标表中的数据开始填充数据。一段时间后，目标表被新数据填充并且不保存旧数据。这是为什么呢？

【问题讨论】：

标签： clickhouse

【解决方案1】：

SummingMergeTree() PARTITION BY toRelativeWeekNum(day) ORDER BY (day,hour)

表示计算总和groupby toRelativeWeekNum(day), day,hour)

user_deatils_daily 对user_deatils_daily_mv 一无所知。它们不相关。

user_deatils_daily_mv 只是插入到user_deatils_daily

SummingMergeTree 对group by session_ts,appid,isp,city,country一无所知

我希望看到ORDER BY (ts,appid,isp,city,country);

我愿意：

CREATE TABLE user_details_daily 
( ts DateTime, 
  appid UInt32, 
  isp String, 
  city String, 
  country String, 
  session_count SimpleAggregateFunction(sum,UInt64), 
  avg_score AggregateFunction(avg, Float32), 
  min_revenue SimpleAggregateFunction(min, Float32), 
  max_load_time SimpleAggregateFunction(max, Int32) ) 
ENGINE = AggregatingMergeTree() 
PARTITION BY toStartOfWeek(ts) 
ORDER BY (ts,appid,isp,city,country);

CREATE MATERIALIZED VIEW user_deatils_daily_mv TO user_details_daily 
as select 
   toStartOfHour(toDateTime(session_ts)) ts,
   appid,
   isp,
   city,
   country,
   count(session_uuid) as session_count ,
   avgState() as avg_score,
   min(revenue) as min_revenue,
   max(perf_page_load_time) as max_load_time 
   from user_details 
where toDate(session_ts)>='2020-08-26' group by ts,appid,isp,city,country;

【讨论】：