Beispiele für kontinuierliche Datenpipelines¶

-- Create a landing table to store raw JSON data.
-- Snowpipe could load data into this table.
create or replace table raw (var variant);

-- Create a stream to capture inserts to the landing table.
-- A task will consume a set of columns from this stream.
create or replace stream rawstream1 on table raw;

-- Create a second stream to capture inserts to the landing table.
-- A second task will consume another set of columns from this stream.
create or replace stream rawstream2 on table raw;

-- Create a table that stores the names of office visitors identified in the raw data.
create or replace table names (id int, first_name string, last_name string);

-- Create a table that stores the visitation dates of office visitors identified in the raw data.
create or replace table visits (id int, dt date);

-- Create a task that inserts new name records from the rawstream1 stream into the names table
-- every minute when the stream contains records.
-- Replace the 'mywh' warehouse with a warehouse that your role has USAGE privilege on.
create or replace task raw_to_names
warehouse = mywh
schedule = '1 minute'
when
system$stream_has_data('rawstream1')
as
merge into names n
  using (select var:id id, var:fname fname, var:lname lname from rawstream1) r1 on n.id = to_number(r1.id)
  when matched then update set n.first_name = r1.fname, n.last_name = r1.lname
  when not matched then insert (id, first_name, last_name) values (r1.id, r1.fname, r1.lname)
;

-- Create another task that merges visitation records from the rawstream1 stream into the visits table
-- every minute when the stream contains records.
-- Records with new IDs are inserted into the visits table;
-- Records with IDs that exist in the visits table update the DT column in the table.
-- Replace the 'mywh' warehouse with a warehouse that your role has USAGE privilege on.
create or replace task raw_to_visits
warehouse = mywh
schedule = '1 minute'
when
system$stream_has_data('rawstream2')
as
merge into visits v
  using (select var:id id, var:visit_dt visit_dt from rawstream2) r2 on v.id = to_number(r2.id)
  when matched then update set v.dt = r2.visit_dt
  when not matched then insert (id, dt) values (r2.id, r2.visit_dt)
;

-- Resume both tasks.
alter task raw_to_names resume;
alter task raw_to_visits resume;

-- Insert a set of records into the landing table.
insert into raw
  select parse_json(column1)
  from values
  ('{"id": "123","fname": "Jane","lname": "Smith","visit_dt": "2019-09-17"}'),
  ('{"id": "456","fname": "Peter","lname": "Williams","visit_dt": "2019-09-17"}');

-- Query the change data capture record in the table streams
select * from rawstream1;
select * from rawstream2;

-- Wait for the tasks to run.
-- A tiny buffer is added to the wait time
-- because absolute precision in task scheduling is not guaranteed.
call system$wait(70);

-- Query the table streams again.
-- Records should be consumed and no longer visible in streams.

-- Verify the records were inserted into the target tables.
select * from names;
select * from visits;

-- Insert another set of records into the landing table.
-- The records include both new and existing IDs in the target tables.
insert into raw
  select parse_json(column1)
  from values
  ('{"id": "456","fname": "Peter","lname": "Williams","visit_dt": "2019-09-25"}'),
  ('{"id": "789","fname": "Ana","lname": "Glass","visit_dt": "2019-09-25"}');

-- Wait for the tasks to run.
call system$wait(70);

-- Records should be consumed and no longer visible in streams.
select * from rawstream1;
select * from rawstream2;

-- Verify the records were inserted into the target tables.
select * from names;
select * from visits;

-- Use the landing table from the previous example.
-- Alternatively, create a landing table.
-- Snowpipe could load data into this table.
create or replace table raw (id int, type string);

-- Create a stream on the table.  We will use this stream to feed the unload command.
create or replace stream rawstream on table raw;

-- Create a task that executes the COPY statement every minute.
-- The COPY statement reads from the stream and loads into the table stage for the landing table.
-- Replace the 'mywh' warehouse with a warehouse that your role has USAGE privilege on.
create or replace task unloadtask
warehouse = mywh
schedule = '1 minute'
when
  system$stream_has_data('RAWSTREAM')
as
copy into @%raw/rawstream from rawstream overwrite=true;
;

-- Resume the task.
alter task unloadtask resume;

-- Insert raw data into the landing table.
insert into raw values (3,'processed');

-- Query the change data capture record in the table stream
select * from rawstream;

-- Wait for the tasks to run.
-- A tiny buffer is added to the wait time
-- because absolute precision in task scheduling is not guaranteed.
call system$wait(70);

-- Records should be consumed and no longer visible in the stream.
select * from rawstream;

-- Verify the COPY statement unloaded a data file into the table stage.
ls @%raw;

-- Create a task that executes an ALTER EXTERNAL TABLE ... REFRESH statement every 5 minutes.
-- Replace the 'mywh' warehouse with a warehouse that your role has USAGE privilege on.
CREATE TASK exttable_refresh_task
WAREHOUSE=mywh
SCHEDULE='5 minutes'
  AS
ALTER EXTERNAL TABLE mydb.myschema.exttable REFRESH;