SQL statement to get all customers with no orders TODAY(current date) - sql

The question is, how do I write a statement that would return all customers with NO Orders TODAY using sql join?
Tables : tbl_member ,tbl_order
tbl_member consist of id,name,
tbl_order consist of id, date, foodOrdered


If you left join, the select where the table on the right is nulkl, it limits to the rows that DO NOT meet the join condition:
select t1.*
from tbl_member t1
left join tbl_member t2
on t1.id = t2.id -- assuming that t2.id relates to t1.id
and t2.date = current_date() -- today's date in mysql
where t2.id is null


Assuming tbl_order date is a datetime (it probably should be) for sql server you could use something like:
declare #tbl_member table
(
id int,
fullname varchar(50)
)
declare #tbl_order table
(
id int,
orderdate datetime,
foodOrdered varchar(50)
)
INSERT INTO #tbl_member VALUES (1, 'George Washington')
INSERT INTO #tbl_member VALUES (2, 'Abraham Lincoln')
INSERT INTO #tbl_member VALUES (3, 'Mickey Mouse')
INSERT INTO #tbl_member VALUES (3, 'Donald Duck')
INSERT INTO #tbl_order VALUES (1, '2017-07-01 13:00:00', 'Fish and Chips')
INSERT INTO #tbl_order VALUES (2, '2017-07-03 08:00:00', 'Full English')
INSERT INTO #tbl_order VALUES (3, '2017-07-25 08:00:00', 'Veggie Burger')
INSERT INTO #tbl_order VALUES (3, '2017-07-25 12:00:00', 'Bangers and Mash')
SELECT id, fullname FROM #tbl_member WHERE id NOT IN
(SELECT id FROM #tbl_order
WHERE CAST(orderDate as date) = CAST(GETDATE() as Date))
It helps if you specify what flavour database you are using as the syntax is often subtly different.

Related

Spark SQL Query to assign join date by next closest once

`CREATE TABLE TABLE_1(
CALL_ID INT,
CALL_DATE DATE);
INSERT INTO TABLE_1(CALL_ID, CALL_DATE)
VALUES (1, '2022-10-22'),
(2, '2022-10-31'),
(3, '2022-11-04');
CREATE TABLE TABLE_2(
PROD_ID INT,
PROD_DATE DATE);
INSERT INTO TABLE_2(PROD_ID, PROD_DATE)
VALUES (1, '2022-10-25'),
(2, '2022-11-17');
CREATE TABLE TABLE_RESULT(
CALL_ID INT,
CALL_DATE DATE,
PROD_ID INT,
PROD_DATE DATE);
INSERT INTO TABLE_RESULT(CALL_ID, CALL_DATE, PROD_ID, PROD_DATE)
VALUES (1, '2022-10-22', 1, '2022-10-25'),
(2, '2022-10-31', NULL, NULL),
(3, '2022-11-04', 2, '2022-11-17');`
Can you help me to create the TABLE_RESULT with a join in a elegant way? This is a very small example.
Thanks

I solved it. Thanks anyway.
SELECT * FROM (SELECT *, COALESCE(LEAD(CALL_DATE) OVER (PARTITION BY 1 ORDER BY CALL_DATE), CURRENT_DATE) AS CALL_DATE_NEXT FROM TABLE_1) AS A LEFT JOIN TABLE_2 AS B ON (A.CALL_DATE<=B.PROD_DATE AND A.CALL_DATE_NEXT>B.PROD_DATE)

How to calculate the average value of following n rows based on another column - SQL (Oracle)

I am trying to calculate average monthly value of premiums for each POLICY_ID in monthly basis as shown below. When a customer updates his/her yearly payment frequency to a value different than 12, I need to manually calculate the average monthly value for the PREMIUM. How can I achieve the values shown in MONTHLY _PREMIUM_DESIRED?
Thanks in advance.
Note: Oracle version 12c
What I've tried:
SELECT
T.*,
SUM(PREMIUM) OVER(PARTITION BY T.POLICY_ID ORDER BY T.POLICY_ID, T.PAYMENT_DATE ROWS BETWEEN CURRENT ROW AND 12/T.YEARLY_PAYMENT_FREQ-1 FOLLOWING ) / (12/T.YEARLY_PAYMENT_FREQ) MONTLY_PREMIUM_CALCULATED
FROM MYTABLE T
;
Code for data:
DROP TABLE MYTABLE;
CREATE TABLE MYTABLE (POLICY_ID NUMBER(11), PAYMENT_DATE DATE, PREMIUM NUMBER(5), YEARLY_PAYMENT_FREQ NUMBER(2),MONTHLY_PREMIUM_DESIRED NUMBER(5));
INSERT INTO MYTABLE VALUES (1, DATE '2014-10-01',120,12,120);
INSERT INTO MYTABLE VALUES (1, DATE '2014-11-01',360,4,120);
INSERT INTO MYTABLE VALUES (1, DATE '2014-12-01',0,4,120);
INSERT INTO MYTABLE VALUES (1, DATE '2015-01-01',0,4,120);
INSERT INTO MYTABLE VALUES (1, DATE '2015-02-01',360,4,120);
INSERT INTO MYTABLE VALUES (1, DATE '2015-03-01',0,4,120);
INSERT INTO MYTABLE VALUES (1, DATE '2015-04-01',0,4,120);
INSERT INTO MYTABLE VALUES (1, DATE '2015-05-01',720,2,120);
INSERT INTO MYTABLE VALUES (1, DATE '2015-06-01',0,2,120);
INSERT INTO MYTABLE VALUES (1, DATE '2015-07-01',0,2,120);
INSERT INTO MYTABLE VALUES (1, DATE '2015-08-01',0,2,120);
INSERT INTO MYTABLE VALUES (1, DATE '2015-09-01',0,2,120);
INSERT INTO MYTABLE VALUES (1, DATE '2015-10-01',0,2,120);
INSERT INTO MYTABLE VALUES (1, DATE '2015-11-01',120,12,120);
INSERT INTO MYTABLE VALUES (2, DATE '2015-01-01',60,3,15);
INSERT INTO MYTABLE VALUES (2, DATE '2015-02-01',0,3,15);
INSERT INTO MYTABLE VALUES (2, DATE '2015-03-01',0,3,15);
INSERT INTO MYTABLE VALUES (2, DATE '2015-04-01',0,3,15);
INSERT INTO MYTABLE VALUES (2, DATE '2015-05-01',180,1,15);
INSERT INTO MYTABLE VALUES (2, DATE '2015-06-01',0,1,15);
INSERT INTO MYTABLE VALUES (2, DATE '2015-07-01',0,1,15);
INSERT INTO MYTABLE VALUES (2, DATE '2015-08-01',0,1,15);
INSERT INTO MYTABLE VALUES (2, DATE '2015-09-01',0,1,15);
INSERT INTO MYTABLE VALUES (2, DATE '2015-10-01',0,1,15);
INSERT INTO MYTABLE VALUES (2, DATE '2015-11-01',0,1,15);
INSERT INTO MYTABLE VALUES (2, DATE '2015-12-01',0,1,15);
INSERT INTO MYTABLE VALUES (2, DATE '2016-01-01',0,1,15);
INSERT INTO MYTABLE VALUES (2, DATE '2016-02-01',0,1,15);
INSERT INTO MYTABLE VALUES (2, DATE '2016-03-01',0,1,15);
INSERT INTO MYTABLE VALUES (2, DATE '2016-04-01',0,1,15);
INSERT INTO MYTABLE VALUES (2, DATE '2016-05-01',15,12,15);
INSERT INTO MYTABLE VALUES (2, DATE '2016-06-01',15,12,15);
SELECT * FROM MYTABLE;
EDIT:
Regardless from payment frequency PREMIUM amount can also be changed by customer. Below, for the POLICY_ID = 1, I have added new records starting from "2015/11/01" to demonstrate this situation. In this case, average monthly premium increased from 120 to 240.
Also removed the screenshot to make the question more readable.
DROP TABLE MYTABLE2;
CREATE TABLE MYTABLE2 (POLICY_ID NUMBER(11), PAYMENT_DATE DATE, PREMIUM NUMBER(5), YEARLY_PAYMENT_FREQ NUMBER(2),MONTHLY_PREMIUM_DESIRED NUMBER(5));
INSERT INTO MYTABLE2 VALUES (1, DATE '2014-10-01',120,12,120);
INSERT INTO MYTABLE2 VALUES (1, DATE '2014-11-01',360,4,120);
INSERT INTO MYTABLE2 VALUES (1, DATE '2014-12-01',0,4,120);
INSERT INTO MYTABLE2 VALUES (1, DATE '2015-01-01',0,4,120);
INSERT INTO MYTABLE2 VALUES (1, DATE '2015-02-01',360,4,120);
INSERT INTO MYTABLE2 VALUES (1, DATE '2015-03-01',0,4,120);
INSERT INTO MYTABLE2 VALUES (1, DATE '2015-04-01',0,4,120);
INSERT INTO MYTABLE2 VALUES (1, DATE '2015-05-01',720,2,120);
INSERT INTO MYTABLE2 VALUES (1, DATE '2015-06-01',0,2,120);
INSERT INTO MYTABLE2 VALUES (1, DATE '2015-07-01',0,2,120);
INSERT INTO MYTABLE2 VALUES (1, DATE '2015-08-01',0,2,120);
INSERT INTO MYTABLE2 VALUES (1, DATE '2015-09-01',0,2,120);
INSERT INTO MYTABLE2 VALUES (1, DATE '2015-10-01',0,2,120);
INSERT INTO MYTABLE2 VALUES (1, DATE '2015-11-01',240,12,240);
INSERT INTO MYTABLE2 VALUES (1, DATE '2016-12-01',240,12,240); --newly added records
INSERT INTO MYTABLE2 VALUES (1, DATE '2016-01-01',960,4,240); --newly added records
INSERT INTO MYTABLE2 VALUES (1, DATE '2016-02-01',0,4,240); --newly added records
INSERT INTO MYTABLE2 VALUES (1, DATE '2016-03-01',0,4,240); --newly added records
INSERT INTO MYTABLE2 VALUES (1, DATE '2016-04-01',0,4,240); --newly added records
INSERT INTO MYTABLE2 VALUES (1, DATE '2016-05-01',960,4,240); --newly added records
INSERT INTO MYTABLE2 VALUES (1, DATE '2016-06-01',0,4,240); --newly added records
INSERT INTO MYTABLE2 VALUES (1, DATE '2016-07-01',0,4,240); --newly added records
INSERT INTO MYTABLE2 VALUES (1, DATE '2016-08-01',0,4,240); --newly added records
INSERT INTO MYTABLE2 VALUES (2, DATE '2015-01-01',60,3,15);
INSERT INTO MYTABLE2 VALUES (2, DATE '2015-02-01',0,3,15);
INSERT INTO MYTABLE2 VALUES (2, DATE '2015-03-01',0,3,15);
INSERT INTO MYTABLE2 VALUES (2, DATE '2015-04-01',0,3,15);
INSERT INTO MYTABLE2 VALUES (2, DATE '2015-05-01',180,1,15);
INSERT INTO MYTABLE2 VALUES (2, DATE '2015-06-01',0,1,15);
INSERT INTO MYTABLE2 VALUES (2, DATE '2015-07-01',0,1,15);
INSERT INTO MYTABLE2 VALUES (2, DATE '2015-08-01',0,1,15);
INSERT INTO MYTABLE2 VALUES (2, DATE '2015-09-01',0,1,15);
INSERT INTO MYTABLE2 VALUES (2, DATE '2015-10-01',0,1,15);
INSERT INTO MYTABLE2 VALUES (2, DATE '2015-11-01',0,1,15);
INSERT INTO MYTABLE2 VALUES (2, DATE '2015-12-01',0,1,15);
INSERT INTO MYTABLE2 VALUES (2, DATE '2016-01-01',0,1,15);
INSERT INTO MYTABLE2 VALUES (2, DATE '2016-02-01',0,1,15);
INSERT INTO MYTABLE2 VALUES (2, DATE '2016-03-01',0,1,15);
INSERT INTO MYTABLE2 VALUES (2, DATE '2016-04-01',0,1,15);
INSERT INTO MYTABLE2 VALUES (2, DATE '2016-05-01',15,12,15);
INSERT INTO MYTABLE2 VALUES (2, DATE '2016-06-01',15,12,15);
SELECT * FROM MYTABLE2;

I think the calculation is:
select t.*,
premium / (12 / yearly_payment_freq)) as monthly_premium_calculated
from mytable t;
EDIT:
I see, you also need this spread over the intermediate months. So you can assign the groups by counting the number of non-zero payments. Then:
select t.*,
( max(premium) over (partition by policy_id, grp) /
(12 / yearly_payment_freq)
) as monthly_premium_calculated
from (select t.*,
sum(case when premium > 0 then 1 else 0 end) over (partition by policy_id order by payment_date) as grp
from mytable t
) t;
Here is a db<>fiddle (it uses Postgres because that is easier to set up than Oracle).

How to use DateDiff into only one SELECT statement?

I want to make a short version on my DATEDIFF function on my SQL Query. In my code, I created two temporary tables then there, I select and use the DATEDIFF funtion.
I would want this code to be simplified and only use ONE SELECT statement that will provide the same results. Is it possible?
Here is my result:
This is my SQL Query
DECLARE #Temp TABLE (ID int, Stamp datetime)
INSERT INTO #Temp (ID, Stamp) VALUES (1, '2016-08-17')
INSERT INTO #Temp (ID, Stamp) VALUES (1, GETDATE())
INSERT INTO #Temp (ID, Stamp) VALUES (1, GETDATE()+0.5)
INSERT INTO #Temp (ID, Stamp) VALUES (2, '2016-08-16')
INSERT INTO #Temp (ID, Stamp) VALUES (2, GETDATE())
INSERT INTO #Temp (ID, Stamp) VALUES (2, GETDATE()+3)
SELECT ROW_NUMBER() OVER (ORDER BY ID) as c, ID, Stamp INTO #Temp2
FROM #Temp
SELECT ROW_NUMBER() OVER (ORDER BY ID) as d, ID, Stamp INTO #Temp3
FROM #Temp
SELECT temp2.ID, temp2.Stamp, ISNULL(DATEDIFF(day, temp3.Stamp, temp2.Stamp),0) as DateDiff
FROM #Temp2 as temp2
LEFT JOIN #Temp3 as temp3 on temp2.ID = temp3.ID and temp2.c = temp3.d + 1
Thanks!

If you are using SQL Server 2012:
select * ,isnull(datediff(day,lag(stamp) over(partition by id order by stamp),stamp) ,0)
from #temp t1
Else use this..
;with cte
as
(select * ,row_number() over (partition by id order by stamp ) as rownum
from #temp t1
)
select c1.id,c1.stamp,isnull(datediff(day,c2.stamp,c1.stamp),0) as datee
from cte c1
left join
cte c2
on c1.id=c2.id and c1.rownum=c2.rownum+1

You could remove insert into the temp-tables and use subselects within the final query:
DECLARE #Temp TABLE (ID int, Stamp datetime)
INSERT INTO #Temp (ID, Stamp) VALUES (1, '2016-08-17')
INSERT INTO #Temp (ID, Stamp) VALUES (1, GETDATE())
INSERT INTO #Temp (ID, Stamp) VALUES (1, GETDATE()+0.5)
INSERT INTO #Temp (ID, Stamp) VALUES (2, '2016-08-16')
INSERT INTO #Temp (ID, Stamp) VALUES (2, GETDATE())
INSERT INTO #Temp (ID, Stamp) VALUES (2, GETDATE()+3)
SELECT temp2.ID, temp2.Stamp, ISNULL(DATEDIFF(day, temp3.Stamp, temp2.Stamp),0) as DateDiff
FROM (SELECT ROW_NUMBER() OVER (ORDER BY ID) as c, ID, Stamp FROM #Temp) as temp2
LEFT JOIN (SELECT ROW_NUMBER() OVER (ORDER BY ID) as d, ID, Stamp FROM #Temp) as temp3
on temp2.ID = temp3.ID and temp2.c = temp3.d + 1

In SQL Server 2012+, you would just use lag():
select t.*
isnull(datediff(day, lag(stamp) over (partition by id order by stamp), stamp), 0)
from #temp t;
In earlier versions, I would use outer apply:
select t.*,
isnull(datediff(day, t2.stamp, t.stamp), 0)
from #temp t outer apply
(select top 1 t2.*
from #temp t2
where t2.id = t.id and t2.stamp < t.stamp
order by t2.stamp desc
) t2;

try a cte,
DECLARE #Temp TABLE (ID int, Stamp datetime)
INSERT INTO #Temp (ID, Stamp) VALUES (1, '2016-08-17')
INSERT INTO #Temp (ID, Stamp) VALUES (1, GETDATE())
INSERT INTO #Temp (ID, Stamp) VALUES (1, GETDATE()+0.5)
INSERT INTO #Temp (ID, Stamp) VALUES (2, '2016-08-16')
INSERT INTO #Temp (ID, Stamp) VALUES (2, GETDATE())
INSERT INTO #Temp (ID, Stamp) VALUES (2, GETDATE()+3)
;WITH CTE AS
(
SELECT ROW_NUMBER() OVER (ORDER BY ID) as RowNo, ID, Stamp
FROM #Temp
)
SELECT temp2.ID, temp2.Stamp, ISNULL(DATEDIFF(day, temp3.Stamp, temp2.Stamp),0) as DateDiff
FROM CTE as temp2
LEFT JOIN CTE as temp3 on temp2.ID = temp3.ID
AND temp2.RowNo = temp3.RowNo + 1

Copying data from one table to another

I'm updating data by selecting data from table and inserting into another. However there are some constraints on the other table and I get this :
DETAIL: Key (entry_id)=(391) is duplicated.
I basically do this :
insert into table_tmp
select * from table_one
How can I skip insert when this key entry duplicate occurs?
Update I can't save this schema info on SQL fiddle but here it is :
CREATE TABLE table1
("entry_id" int, "text" varchar(255))
;
INSERT INTO table1
("entry_id", "text")
VALUES
(1, 'one'),
(2, 'two'),
(3, 'test'),
(3, 'test'),
(12, 'three'),
(13, 'four')
;
CREATE TABLE table2
("entry_id" int, "text" varchar(255))
;
Create unique index entry_id_idxs
on table2 (entry_id)
where text='test';
INSERT INTO table2
("entry_id", "text")
VALUES
(1, 'one'),
(2, 'two'),
(3, 'test'),
(3, 'test'),
(12, 'three'),
(13, 'four')
;
Error that I get if I try to build the schema

Insert using join that returns unmatched rows:
INSERT INTO table2
SELECT DISTINCT t1.*
FROM table1 t1
LEFT JOIN table2 t2 ON t2.entry_id = t1.entry_id
WHERE t2.entry_id IS NULL

Use this query - SQLFiddle Demo:
INSERT INTO table2
SELECT t1.* FROM table1 t1
WHERE NOT EXISTS (
SELECT entry_id
FROM table2 t2
WHERE t2.entry_id = t1.entry_id
)

Merging records based on a time difference?

I have the following table:
CREATE TABLE #TEMP (id int, name varchar(255), startdate datetime, enddate datetime)
INSERT INTO #TEMP VALUES(1, 'John', '2011-01-11 00:00:00.000','2011-01-11 00:01:10.000')
INSERT INTO #TEMP VALUES(2, 'John', '2011-01-11 00:00:20.000','2011-01-11 00:01:50.000')
INSERT INTO #TEMP VALUES(3, 'John', '2011-01-11 00:01:40.000','2011-01-11 00:01:50.000')
INSERT INTO #TEMP VALUES(4, 'Adam', '2011-01-11 00:00:40.000','2011-01-11 00:01:20.000')
INSERT INTO #TEMP VALUES(5, 'Adam', '2011-01-11 00:00:10.000','2011-01-11 00:01:30.000')
SELECT * FROM #TEMP
DROP TABLE #TEMP
I am trying to merge all records with the same name within a range of 60 seconds to each other to get the following:
John 2011-01-11 00:00:00.000 2011-01-11 00:01:10.000
John 2011-01-11 00:01:40.000 2011-01-11 00:01:50.000
Adam 2011-01-11 00:00:10.000 2011-01-11 00:01:20.000
Any suggestions on how to do this on a table with about 50K records? Currently, I managed to get to this:
SELECT * FROM #TEMP
CREATE TABLE #Merge(id1 int, id2 int)
INSERT INTO #Merge
SELECT id, uuid
FROM
(
SELECT t.id, u.uuid, t.name, t.startdate, t.enddate, u.ustartdate, u.uenddate,
(CASE WHEN (DATEDIFF(second, t.startdate, u.ustartdate) <= 60 AND DATEDIFF(second, t.startdate, u.ustartdate) >= 0) then 1 else 0 END) Flag
FROM #Temp t
INNER JOIN
(SELECT id AS uuid, name, startdate AS ustartdate, enddate AS uenddate
FROM #Temp) u
ON t.name = u.name AND t.startdate != u.ustartdate AND t.id != u.uuid
) w
WHERE Flag = 1
SELECT * FROM #Merge
-- Insert non-mergable records
CREATE TABLE #TEMP2 (id int, name varchar(255), membergroup varchar(255), startdate datetime, enddate datetime)
INSERT INTO #TEMP2
SELECT * FROM #TEMP
WHERE id NOT IN (SELECT id1 FROM #Merge UNION SELECT id2 FROM #Merge)
SELECT * FROM #TEMP2
Of course, I am not sure how to proceed from here. The #Merge table gives me rows that are to be merged. What I did was to insert non-mergable rows first into #Temp2 first.
EDIT:
Updated set of rows, just in case:
INSERT INTO #TEMP VALUES(1, 'John', 'A', '2011-01-11 00:00:00.000','2011-01-11 00:01:10.000')
INSERT INTO #TEMP VALUES(2, 'John', 'A', '2011-01-11 00:00:01.000','2011-01-11 00:01:10.000')
INSERT INTO #TEMP VALUES(3, 'John', 'B', '2011-01-11 00:00:20.000','2011-01-11 00:01:50.000')
INSERT INTO #TEMP VALUES(4, 'John', 'C', '2011-01-11 00:01:40.000','2011-01-11 00:01:50.000')
INSERT INTO #TEMP VALUES(5, 'John', 'C', '2011-01-11 00:01:50.000','2011-01-11 00:02:20.000')
INSERT INTO #TEMP VALUES(6, 'Adam', 'A', '2011-01-11 00:00:40.000','2011-01-11 00:01:20.000')
INSERT INTO #TEMP VALUES(7, 'Adam', 'B', '2011-01-11 00:00:10.000','2011-01-11 00:01:30.000')
INSERT INTO #TEMP VALUES(8, 'Adam', 'B', '2011-01-11 00:03:10.000','2011-01-11 00:04:30.000')

The code below manage's to show both merged rows (rows 1-2,4-5) and unique rows (row 3)
SELECT DISTINCT a.id,a.name,a.startdate,a.enddate
FROM temp a
LEFT JOIN temp b ON a.name = b.name AND a.id < b.id AND DATEDIFF(s,a.startdate,b.startdate)<=60
LEFT JOIN temp c ON c.name = a.name AND c.id < a.id AND DATEDIFF(s,c.startdate,a.startdate)<=60
WHERE (b.id IS NOT NULL OR c.id IS NULL) AND a.id <= COALESCE(c.id,a.id)

Given you haven't said how to use the 60 second interval and your sample code showed only a startdate comparison, here you go
SELECT
*
FROM
#Temp t1
CROSS APPLY
(SELECT TOP 1*
FROM #Temp t2
WHERE t1.name = t2.name AND DATEDIFF(second, t1.startdate, t2.startdate) < 60 AND t1.id < t2.id
ORDER BY id DESC
) t2x
Based on startdate only, row pairs 1/2 and 4/5 make it into the output. Row 3 doesn't so you'll have to explain why you added it.
That is, row id = 3 is not within 60 seconds of row 1 or 2 based on startdate. So it shouldn't be in the output.
This assumes that id and startdate are both increasing.
Edit, after chat:
SELECT
*
FROM
#Temp t1
CROSS APPLY
(SELECT TOP 1 *
FROM #Temp t2
WHERE t1.name = t2.name AND DATEDIFF(second, t1.startdate, t2.startdate) < 60 AND t1.id < t2.id
ORDER BY t2.id DESC
) t2x
UNION ALL
SELECT
t1.*, t1.*
FROM
#Temp t1
WHERE NOT EXISTS
(
SELECT
t1ZZ.id, t2xZZ.id
FROM
#Temp t1ZZ
CROSS APPLY
(SELECT TOP 1 *
FROM #Temp t2ZZ
WHERE t1ZZ.name = t2ZZ.name AND DATEDIFF(second, t1ZZ.startdate, t2ZZ.startdate) < 60 AND t1ZZ.id < t2ZZ.id
ORDER BY t2ZZ.id DESC
) t2xZZ
WHERE
t1.id IN (t1ZZ.id, t2xZZ.id)
)