当前位置：首页 > article >正文

二百七十五、Kettle——ClickHouse增量导入数据补全以及数据修复记录表数据（实时）

article 2024/11/1 8:50:48

一、目的

在完成数据修复后，需要生成修复记录

二、Hive中原有代码

2.1 表结构

--52、数据补全以及数据修复记录表 dwd_data_correction_record
create  table  if not exists  hurys_db.dwd_data_correction_record(
    data_type      int        comment '数据类型 1:转向比,2:统计,3:评价,4:区域,6:静态排队,7:动态排队',
    device_no      string     comment '设备编号',
    id             string     comment '唯一ID',
    create_time    timestamp  comment '创建时间',
    record_type    int        comment '记录类型 0:补全,1:修复'
)
comment '数据补全以及数据修复记录表'
partitioned by (day string)
stored as orc
;

2.2 SQL代码

--6 静态排队数据修复记录
insert into table  hurys_db.dwd_data_correction_record partition(day)
select
       '6' data_type,
       t1.device_no,
       t1.id,
       t1.create_time,
       '1' record_type,
       t1.day
from hurys_db.dwd_queue_error as t1
right join hurys_db.dwd_queue as t2
on t1.id=t2.id and t1.device_no=t2.device_no
where t1.id is not null and t1.day='2024-09-04'
;

三、ClickHouse中现有代码

3.1 表结构

--52、数据补全以及数据修复记录表 dwd_data_correction_record
create  table  if not exists  hurys_jw.dwd_data_correction_record(
    data_type      Int32      comment '数据类型 1:转向比,2:统计,3:评价,4:区域,6:静态排队,7:动态排队',
    device_no      String     comment '设备编号',
    id             String     comment '唯一ID',
    create_time    DateTime   comment '创建时间',
    record_type    Int32      comment '记录类型 0:补全,1:修复',
    day            Date       comment '日期'
)
ENGINE = MergeTree
PARTITION BY day
PRIMARY KEY (day,id)
ORDER BY (day,id)
SETTINGS index_granularity = 8192;

3.2 SQL代码

--6 静态排队数据修复记录
select
       '6' data_type,
       t1.device_no,
       t1.id,
       t1.create_time,
       '1' record_type,
       cast(t1.day as String) day
from hurys_jw.dwd_queue_error as t1
inner join  hurys_jw.dwd_queue as t2
on t1.id=t2.id and t1.device_no=t2.device_no
where t1.id is not null --and t1.create_time > ?
group by t1.device_no,  t1.id, t1.create_time,  t1.day
;

四、Kettle任务

由于修复记录必须是数据完成修复后执行，但是又不能每天执行一次，因为数据修复任务最后会删除错误数据表当天分区数据

4.1 newtime 2

4.2 替换NULL值 2

4.3 clickhouse输入 2

select
'6' data_type,
t1.device_no,
t1.id,
t1.create_time,
'1' record_type,
cast(t1.day as String) day
from hurys_jw.dwd_queue_error as t1
inner join hurys_jw.dwd_queue as t2
on t1.id=t2.id and t1.device_no=t2.device_no
where t1.id is not null and t1.create_time > ?
group by t1.device_no, t1.id, t1.create_time, t1.day
;