Adding missing day rows

Hi, 

I am trying to get data for everyday in a particular date range even if there is no data for that day.

For example,

Desired O/P:

I came up with this SQL Procedure:

CREATE PROCEDURE add_missing_days()
BEGIN

DECLARE DONE INT DEFAULT 0;
DECLARE ITEMID INTEGER;
DECLARE LOCID integer;

DECLARE FND INTEGER;
DECLARE DT DATE;
DECLARE END_DT DATE;
DECLARE PREV_RATE VARCHAR(255);

DECLARE item_ids CURSOR FOR SELECT DISTINCT `ITEM_ID`,`LOCATION_ID` FROM `transform_data_1` ORDER BY `ITEM_ID`,`LOCATION_ID`, `Transaction Date` ASC;
DECLARE CONTINUE HANDLER FOR NOT FOUND SET DONE = 1;

OPEN item_ids;
item_ids_loop : LOOP
    FETCH item_ids INTO ITEMID, LOCID;

    IF DONE = 1 
    THEN CLOSE item_ids;
    LEAVE item_ids_loop; 
    END IF;


        SET DT = str_to_date('2018-01-01', '%Y-%m-%d');
    	SET END_DT = CURRENT_DATE;

    	WHILE DT < END_DT DO
        	SET PREV_RATE = 0;
        	SET FND = ( SELECT COUNT(*) FROM `transform_data_1`
                    WHERE `ITEM_ID` = ITEMID AND `LOCATION_ID` = LOCID and `Transaction Date` = DT );
        	IF ( FND = 0 ) THEN
            	INSERT INTO `transform_data_1`( `ITEM_ID`, `LOCATION_ID`, `Transaction Date`, `Inventory Count` )
            	VALUES( ITEMID, LOCID, DT, PREV_RATE );
        	ELSE
            	SET PREV_RATE = ( SELECT `Inventory Count` FROM `transform_data_1`
                              WHERE `ITEM_ID` = ITEMID AND `LOCATION_ID` = LOCID AND `Transaction Date` = DT );
        	END IF;

        	SET DT = DATE_ADD( DT, INTERVAL 1 DAY );
    	END WHILE;
END LOOP item_ids_loop;
END

This code works for just 1 month Date range . But if I try running it for the entire date range , it times-out and fails. Considering I am working on a big dataset and adding a row for each day for each Item and Location it takes a lot of processing time. For now I have broken the dataflow into different months and eventually combining all the dataflows into one.

However this is not dynamic and I will have to keep adding new dataflows for each month over time. I just want to achieve this in a single dataflow.

So  I was wondering if there was a more efficient way to achieve this.

Thanks,

Prajwal