Clickhouse中ReplicatedAggregatingMergeTree的物化视图的解法

利用ReplicatedAggregatingMergeTree引擎实现Clickhouse中ReplicatedAggregatingMergeTree的物化视图。

具体解决方案如下所示:

首先，我们需要创建主表和物化视图表以定义基础数据和聚合数据。

CREATE TABLE log_data
(
    event_date Date,
    event_time Datetime,
    user_id UInt32,
    event_type Enum8('click'=1,'impression'=2,'conversion'=3),
    data String,
    ...
)
ENGINE = ReplicatedMergeTree('/clickhouse/tables/{shard}/log_data', '{replica}')
PARTITION BY toYYYYMM(event_date)
ORDER BY (event_date, user_id)

CREATE MATERIALIZED VIEW user_data_summary 
TO ReplicatedAggregatingMergeTree('/clickhouse/tables/{shard}/user_data_summary', '{replica}')
AS
SELECT 
      event_date, 
      user_id, 
      countIf(event_type=1) as clicks, 
      countIf(event_type=2) as impressions
FROM log_data 
GROUP BY event_date, user_id;

此外，我们需要定义主表和物化视图表的分区和排序方式，以确保数据可靠性和查询性能。

最后，我们需要创建一个具有适当参数的适当调度任务，以确保物化视图表在每次更新时正确地处理数据。

CREATE TABLE log_data
(
    event_date Date,
    event_time Datetime,
    user_id UInt32,
    event_type Enum8('click'=1,'impression'=2,'conversion'=3),
    data String,
    ...
)
ENGINE = ReplicatedMergeTree('/clickhouse/tables/{shard}/log_data', '{replica}')
PARTITION BY toYYYYMM(event_date)
ORDER BY (event_date, user_id)

CREATE MATERIALIZED VIEW user_data_summary 
TO ReplicatedAggregatingMergeTree('/clickhouse/tables/{shard}/user_data_summary', '{replica}')
AS
SELECT 
      event_date, 
      user_id, 
      countIf(event_type=1) as clicks, 
      countIf(event_type=2) as impressions
FROM log_data 
GROUP BY event_date, user_id;

CREATE SCHEDULED TASK recompute_user_data_summary 
ON SCHEDULE every 1 hour 
DO 
    ALTER TABLE user_data_summary 
    UPDATE;

上述代码示例定义了一个名为log_data的主表和一个名为user_data_summary的物化视图表，后者是基于前者按event_date和user_id进行分组的聚合数据。 还定义了一个名为recompute_user_data_summary的调度任务，用于定期更新物化视图表。

以上是利用ReplicatedAggregatingMergeTree引擎实现Clickhouse中ReplicatedAggregatingMergeTree的物化视图的解决方案。