How to get this kind of data? - sql

I have data some thing like this:
+---------+---------+---------+-------+
| MAXIMUM | MINIMUM | SENSORS | TIME |
+---------+---------+---------+-------+
| 10 | 12 | 14 | 13:12 |
| 80 | 70 | 100 | 14:54 |
+---------+---------+---------+-------+
But I need something like this:
+---------+-------+
| X | Y |
+---------+-------+
| MAXIMUM | 10 |
| MINIMUM | 12 |
| SENSORS | 14 |
| TIME | 13:12 |
| MAXIMUM | 80 |
| MINIMUM | 70 |
| SENSORS | 100 |
| TIME | 14:54 |
+---------+-------+
How to get this kind of data is there any possibility to get data?


Just another option
Example
Select B.*
From YourTable
Cross Apply (values ('MAXIMUM',convert(nvarchar(50),MAXIMUM))
,('MINIMUM',convert(nvarchar(50),MINIMUM))
,('SENSORS',SENSORS)
,('TIME' ,convert(nvarchar(50),[TIME],108))
) B(x,y)
Returns
x y
MAXIMUM 10
MINIMUM 12
SENSORS 14
TIME 13:12:00
MAXIMUM 80
MINIMUM 70
SENSORS 100
TIME 14:54:00


You can use UNPIVOT:
declare #tmp table (MAXIMUM nvarchar(10), MINIMUM nvarchar(10), SENSORS nvarchar(10), [TIME] nvarchar(10))
insert into #tmp select 10,12,14 ,'13:12'
insert into #tmp select 80,70,100,'14:54'
select u.x,u.y
from #tmp s
unpivot
(
[y]
for [x] in ([MAXIMUM],[MINIMUM],[SENSORS],[TIME])
) u;
Results:

Related

Select only record until timestamp from another table

I have three tables.
The first one is Device table
+----------+------+
| DeviceId | Type |
+----------+------+
| 1 | 10 |
| 2 | 20 |
| 3 | 30 |
+----------+------+
The second one is History table - data received by different devices.
+----------+-------------+--------------------+
| DeviceId | Temperature | TimeStamp |
+----------+-------------+--------------------+
| 1 | 31 | 15.08.2020 1:42:00 |
| 2 | 100 | 15.08.2020 1:42:01 |
| 2 | 40 | 15.08.2020 1:43:00 |
| 1 | 32 | 15.08.2020 1:44:00 |
| 1 | 34 | 15.08.2020 1:45:00 |
| 3 | 20 | 15.08.2020 1:46:00 |
| 2 | 45 | 15.08.2020 1:47:00 |
+----------+-------------+--------------------+
The third one is DeviceStatusHistory table
+----------+---------+--------------------+
| DeviceId | State | TimeStamp |
+----------+---------+--------------------+
| 1 | 1(OK) | 15.08.2020 1:42:00 |
| 2 | 1(OK) | 15.08.2020 1:43:00 |
| 1 | 1(OK) | 15.08.2020 1:44:00 |
| 1 | 0(FAIL) | 15.08.2020 1:44:30 |
| 1 | 0(FAIL) | 15.08.2020 1:46:00 |
| 2 | 0(FAIL) | 15.08.2020 1:46:10 |
+----------+---------+--------------------+
I want to select the last temperature of devices, but take into account only those history records that occurs until the first device failure.
Since device1 starts failing from 15.08.2020 1:44:30, I don't want its records that go after that timestamp.
The same for the device2.
So as a final result, I want to have only data of all devices until they get first FAIL status:
+----------+-------------+--------------------+
| DeviceId | Temperature | TimeStamp |
+----------+-------------+--------------------+
| 2 | 40 | 15.08.2020 1:43:00 |
| 1 | 32 | 15.08.2020 1:44:00 |
| 3 | 20 | 15.08.2020 1:46:00 |
+----------+-------------+--------------------+
I can select an appropriate history only if device failed at least once:
SELECT * FROM Device D
CROSS APPLY
(SELECT TOP 1 * FROM History H
WHERE D.Id = H.DeviceId
and H.DeviceTimeStamp <
(select MIN(UpdatedOn) from DeviceStatusHistory Y where [State]=0 and DeviceId=D.Id)
ORDER BY H.DeviceTimeStamp desc) X
ORDER BY D.Id;
The problems is, if a device never fails, I don't get its history at all.
Update:
My idea is to use something like this
SELECT * FROM DeviceHardwarePart HP
CROSS APPLY
(SELECT TOP 1 * FROM History H
WHERE HP.Id = H.DeviceId
and H.DeviceTimeStamp <
(select ISNULL((select MIN(UpdatedOn) from DeviceMetadataPart where [State]=0 and DeviceId=HP.Id),
cast('12/31/9999 23:59:59.997' as datetime)))
ORDER BY H.DeviceTimeStamp desc) X
ORDER BY HP.Id;
I'm not sure whether it is a good solution

You can use COALESCE: coalesce(min(UpdateOn), cast('9999-12-31 23:59:59' as datetime)). This ensures you always have an upperbound for your select instead of NULL.

I will treat this as two parts problem
I will try to find the time at which device has failed and if it hasn't failed I will keep it as a large value like some timestamp in 2099
Once I have the above I can simply join with histories table and take the latest value before the failed timestamp.
In order to get one, I guess there can be several approaches. From top of my mind something like below should work
select device_id, coalesce(min(failed_timestamps), cast('01-01-2099 01:01:01' as timestamp)) as failed_at
(select device_id, case when state = 0 then timestamp else null end as failed_timestamps from History) as X
group by device_id
This gives us the minimum of failed timestamp for a particular device, and an arbitrary large value for the devices which have never failed.
I guess after this the solution is straight forward.

Find the period of occurence of a value in table

I have a table with the following data.
+------------+---------+
| Date | Version |
+------------+---------+
| 1/10/2019 | 1 |
| .... | |
| 15/10/2019 | 1 |
| 16/10/2019 | 2 |
| .... | |
| 26/10/2019 | 2 |
| 27/10/2019 | 1 |
| .... | |
| 30/10/2019 | 1 |
+------------+---------+
I need to find the period of occurrence for version in the table.
Eg:Suppose I need to get Version 1 occurence details which is present from 1/10/2019 to 15/10/2019 and from 27/10/2019 to 30/10/2019. How can i query the database for such a result?
I have tried many ways but not able to produce the desired result .I even doubt this is possible using a query!
Any inputs are highly appreciated.
Expected output:
+---------+-------------+-------------+
| Version | Period from | Period To |
+---------+-------------+-------------+
| 1 | 1/10/2019 | 15/10/2019 |
| 2 | 16/10/2019 | 26/10/2019 |
| 1 | 27/10/2019 | 30/10/2019 |
+---------+-------------+-------------+

This is gaps and Islands question.
Try this
DECLARE #SampleData TABLE ( [Date] DATE, [Version] INT)
INSERT INTO #SampleData ([Date], [Version])
VALUES
('01-10-2019', 1), ('02-10-2019', 1), ('15-10-2019', 1),
('16-10-2019', 2), ('17-10-2019', 2),('26-10-2019', 2),
('27-10-2019', 1), ('28-10-2019', 1), ('30-10-2019', 1)
SELECT
Y.[Version]
,PeriodFrom = MIN(Y.[Date])
,PeriodTo = MAX(Y.[Date])
FROM(
SELECT
X.[Version]
,X.[Date]
,ISLAND = RN-ROW_NUMBER()OVER( PARTITION BY X.[Version] ORDER BY X.[Date])
FROM(
SELECT
RN=ROW_NUMBER()OVER( ORDER BY S.[Date])
,S.[Date]
,S.[Version]
FROM
#SampleData S
) X
) Y
GROUP BY
Y.[Version], Y.ISLAND
ORDER BY
PeriodFrom
Output
Version PeriodFrom PeriodTo
1 2019-10-01 2019-10-15
2 2019-10-16 2019-10-26
1 2019-10-27 2019-10-30

Convert decimals into whole numbers and finding the difference between two columns

I have two columns like below:
A | B
0.33 | 0.55
0.44 | 0.65
10 | 20
10.1 | 10.234
11.236 | 12.8963
12 | 30
30.5698| 35.6893
Here in the above columns, the values with the decimals should be multiplied by 100 to convert them into whole numbers and the whole numbers should not be disturbed as they are in a correct format.
Using the converted whole numbers, the difference of the columns is calculated.
So I tried the mathematical function in hive say MOD function.
But using this function, the difference of the whole numbers is correct. But the difference of the decimals is wrong.
I don't know where i'm going wrong.
I tried the following code:
select mod(B,100)-mod(A,100) from sample
The actual result is:
A | B | C
0.33 | 0.55 | 22
0.44 | 0.65 | 21
10 | 20 | 10
10.1 | 10.234 | 13
11.236 | 12.8963| 166
12 | 30 | 18
30.5698| 35.6893| 512

What data type are A and B?
If you define them as decimals, all the values will have the same presicion:
create table temp.table_name (
A decimal(10,5)
,B decimal(10,5)
)
stored as parquet location '../temp.db/table_name'
;
INSERT INTO TABLE temp.table_name
VALUES (0.33 ,0.55)
,(0.44 ,0.65)
,(10 ,20)
,(10.1 ,10.234)
,(11.236 ,12.8963)
,(12 ,30)
,(30.5698,35.6893);
Result of the select (All the data with the same precision):
+---------------+---------------+--+
| table_name.a | table_name.b |
+---------------+---------------+--+
| 0.33000 | 0.55000 |
| 0.44000 | 0.65000 |
| 10.00000 | 20.00000 |
| 10.10000 | 10.23400 |
| 11.23600 | 12.89630 |
| 12.00000 | 30.00000 |
| 30.56980 | 35.68930 |
+---------------+---------------+--+
Select to get the difference in decimals:
select a ,b ,( cast(round((b*100),0) as int) -
cast(round((a*100),0) as int)) as res
from temp.table_name;
Result - difference of the decimals:
+-----------+-----------+-------+--+
| a | b | res |
+-----------+-----------+-------+--+
| 0.33000 | 0.55000 | 22 |
| 0.44000 | 0.65000 | 21 |
| 10.00000 | 20.00000 | 1000 |
| 10.10000 | 10.23400 | 13 |
| 11.23600 | 12.89630 | 166 |
| 12.00000 | 30.00000 | 1800 |
| 30.56980 | 35.68930 | 512 |
+-----------+-----------+-------+--+
Hope that can help you.

T-SQL return individual values instead of cumulative value

I have a 1 table in a db that stored Incoming, Outgoing and Net values for various Account Codes over time. Although there is a date field the sequence of events per Account Code is based on the "Version" number where 0 = original record for each Account Code and it increments by 1 after each change to that Account Code.
The Outgoing and Incoming values are stored in the db as cumulative values rather than the individual transaction value but I am looking for a way to Select * From this table and return the individual amounts as opposed to the cumulative.
Below are test scripts of table and data, and also 2 examples.
If i Select where code = '123' in the test table I currently get this (values are cumulative);
+------+------------+---------+---------+---------+-----+
| Code | Date | Version | Incoming| Outgoing| Net |
+------+------------+---------+---------+---------+-----+
| 123 | 01/01/2018 | 0 | 100 | 0 | 100 |
| 123 | 07/01/2018 | 1 | 150 | 0 | 150 |
| 123 | 09/01/2018 | 2 | 150 | 100 | 50 |
| 123 | 14/01/2018 | 3 | 200 | 100 | 100 |
| 123 | 18/01/2018 | 4 | 200 | 175 | 25 |
| 123 | 23/01/2018 | 5 | 225 | 175 | 50 |
| 123 | 30/01/2018 | 6 | 225 | 225 | 0 |
+------+------------+---------+---------+---------+-----+
This is what I would like to see (each individual transaction);
+------+------------+---------+----------+----------+------+
| Code | Date | Version | Incoming | Outgoing | Net |
+------+------------+---------+----------+----------+------+
| 123 | 01/01/2018 | 0 | 100 | 0 | 100 |
| 123 | 07/01/2018 | 1 | 50 | 0 | 50 |
| 123 | 09/01/2018 | 2 | 0 | 100 | -100 |
| 123 | 14/01/2018 | 3 | 50 | 0 | 50 |
| 123 | 18/01/2018 | 4 | 0 | 75 | -75 |
| 123 | 23/01/2018 | 5 | 25 | 0 | 25 |
| 123 | 30/01/2018 | 6 | 0 | 50 | -50 |
+------+------------+---------+----------+----------+------+
If I had the individual transaction values and wanted to report on the cumulative, I would use an OVER PARTITION BY, but is there an opposite to that?
I am not looking to redesign the create table or the process in which it is stored, I am just looking for a way to report on this from our MI environment.
Note: I've added other random Account Codes into this to emphasis how the data is not ordered by Code or Version, but by Date.
thanks in advance for any help.
USE [tempdb];
IF EXISTS ( SELECT *
FROM INFORMATION_SCHEMA.TABLES
WHERE TABLE_NAME = 'Table1'
AND TABLE_SCHEMA = 'dbo')
DROP TABLE [dbo].[Table1];
GO
CREATE TABLE [dbo].[Table1]
(
[Code] CHAR(3)
,[Date] DATE
,[Version] CHAR(3)
,[Incoming] DECIMAL(20,2)
,[Outgoing] DECIMAL(20,2)
,[Net] DECIMAL(20,2)
);
GO
INSERT INTO [dbo].[Table1] VALUES
('123','2018-01-01','0','100','0','100'),
('456','2018-01-02','0','50','0','50'),
('789','2018-01-03','0','0','0','0'),
('456','2018-01-04','1','100','0','100'),
('456','2018-01-05','2','150','0','150'),
('789','2018-01-06','1','50','50','0'),
('123','2018-01-07','1','150','0','150'),
('456','2018-01-08','3','200','0','200'),
('123','2018-01-09','2','150','100','50'),
('789','2018-01-10','2','0','0','0'),
('456','2018-01-11','4','225','0','225'),
('789','2018-01-12','3','75','25','50'),
('987','2018-01-13','0','0','50','-50'),
('123','2018-01-14','3','200','100','100'),
('654','2018-01-15','0','100','0','100'),
('456','2018-01-16','5','250','0','250'),
('987','2018-01-17','1','50','50','0'),
('123','2018-01-18','4','200','175','25'),
('789','2018-01-19','4','100','25','75'),
('987','2018-01-20','2','150','125','25'),
('321','2018-01-21','0','100','0','100'),
('654','2018-01-22','1','0','0','0'),
('123','2018-01-23','5','225','175','50'),
('321','2018-01-24','1','100','50','50'),
('789','2018-01-25','5','100','50','50'),
('987','2018-01-26','3','150','150','0'),
('456','2018-01-27','6','250','250','0'),
('456','2018-01-28','7','270','250','20'),
('321','2018-01-29','2','100','100','0'),
('123','2018-01-30','6','225','225','0'),
('987','2018-01-31','4','175','150','25')
;
GO
SELECT *
FROM [dbo].[Table1]
WHERE [Code] = '123'
GO;
USE [tempdb];
IF EXISTS ( SELECT *
FROM INFORMATION_SCHEMA.TABLES
WHERE TABLE_NAME = 'Table1'
AND TABLE_SCHEMA = 'dbo')
DROP TABLE [dbo].[Table1];
GO;
}

Just use lag():
select Evt, Date, Version,
(Loss - lag(Loss, 1, 0) over (partition by evt order by date)) as incoming,
(Rec - lag(Rec, 1, 0) over (partition by evt order by date)) as outgoing,
(Net - lag(Net, 1, 0) over (partition by evt order by date)) as net
from [dbo].[Table1];

Add extra column in sql to show ratio with previous row

I have a SQL table with a format like this:
SELECT period_id, amount FROM table;
+--------------------+
| period_id | amount |
+-----------+--------+
| 1 | 12 |
| 2 | 11 |
| 3 | 15 |
| 4 | 20 |
| .. | .. |
+-----------+--------+
I'd like to add an extra column (just in my select statement) that calculates the growth ratio with the previous amount, like so:
SELECT period_id, amount, [insert formula here] AS growth FROM table;
+-----------------------------+
| period_id | amount | growth |
+-----------+-----------------+
| 1 | 12 | |
| 2 | 11 | 0.91 | <-- 11/12
| 3 | 15 | 1.36 | <-- 15/11
| 4 | 20 | 1.33 | <-- 20/15
| .. | .. | .. |
+-----------+-----------------+
Just need to work out how to perform the operation with the line before. Not interested in adding to the table. Any help appreciated :)
** also want to point out that period_id is in order but not necessarily increasing incrementally

The window function Lag() would be a good fit here.
You may notice that we use (amount+0.0). This is done just in case AMOUNT is an INT, and NullIf() to avoid the dreaded divide by zero
Declare #YourTable table (period_id int,amount int)
Insert Into #YourTable values
( 1,12),
( 2,11),
( 3,15),
( 4,20)
Select period_id
,amount
,growth = cast((amount+0.0) / NullIf(lag(amount,1) over (Order By Period_ID),0) as decimal(10,2))
From #YourTable
Returns
period_id amount growth
1 12 NULL
2 11 0.92
3 15 1.36
4 20 1.33

If you are using SQL Server 2012+ then go for John Cappelletti answer.
And If you are also less blessed like me then this below code work for you in the 2008 version too.
Declare #YourTable table (period_id int,amount int)
Insert Into #YourTable values
( 1,12),
( 2,11),
( 3,15),
( 4,20)
;WITH CTE AS (
SELECT ROW_NUMBER() OVER (
ORDER BY period_id
) SNO
,period_id
,amount
FROM #YourTable
)
SELECT C1.period_id
,C1.amount
,CASE
WHEN C2.amount IS NOT NULL AND C2.amount<>0
THEN CAST(C1.amount / CAST(C2.amount AS FLOAT) AS DECIMAL(18, 2))
END AS growth
FROM CTE C1
LEFT JOIN CTE C2 ON C1.SNO = C2.SNO + 1
Which works same as LAG.
+-----------+--------+--------+
| period_id | amount | growth |
+-----------+--------+--------+
| 1 | 12 | NULL |
| 2 | 11 | 0.92 |
| 3 | 15 | 1.36 |
| 4 | 20 | 1.33 |
+-----------+--------+--------+