Calling the process of storage nodes

Whether we can achieve such a node, and its function is called with parameters of the storage process
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Grf:
DB_INPUT_TABLE → DB_CALL_PROCEDURE
Or
DELIMITED_DATA_READER → DB_CALL_PROCEDURE
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table structure:
create table hwtest1 (c1 numeric(10,2),c2 varchar2(30),c3 date);
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procedure content:
create or replace procedure p_hw1(args1 in number, args2 in varchar2,args3 in date,re1 out varchar2) is
c_1 numeric(10,2);
c_2 varchar2(30);
c_3 date;
begin
c_1 := args1;
c_2 := args2;
c_3 := args3;
begin
insert into hwtest1 (c1,c2,c3) values(c_1,c_2,c_3);
commit;
re1:=‘Success’;
Exception WHEN OTHERS Then
rollback;
re1 := ‘Failed’;
end;
end p_hw1;

I contrast etl some similar products, these products are in the process of storage support, I would like to cloverEtl open-source organizations achieve this demand should not be very difficult?

You think that the demand is not necessary?
I sincerely hope that the functions of cloverETL can be more powerful.

Hi,
could you please explain more what you think? Something like you wrote in first post can do DBInputTable: when you set maxErrors>0 then correct records will be sent to database and incorrect you can log.

Thank you for your response, I think, this node will be responsible only for the importation of the record sent to the database server storage process, and can return to the stored procedure in the definition of parameters.
Each node can be set up through the corresponding record of success and the failure of the information recorded information output to a designated location, this should belong to log module functions.
Successful track record is based on the number of users in the storage process is set up transactions, and if the settings and the affairs of the rollback transactions, the records of the number of so successful is 0.
(MaxErrors attributes) in the process of storage services with high-level should be as DB_OUTPUT_TABLE nodes in the errorAction attribute priority.
Output port storage output value of the return process.

Example: