I am new to SQLite. When I use MySQL, it's reasonable to use count(*)/5. However, in SQLite, I try to calculate count(Name)/5 but the result shows zero.
I don't know why this won't work. Is there any way to calculate this?
Because COUNT returns an integer, and 5 is an integer. As seen here: You will have to either cast it, or simply add a decimal to /5.0. Now it will no longer be limited to integers.
Cheers!
If the operands are both integers, SQLite does integer division. So, just make one operand a float:
SELECT COUNT(name)/5. FROM demo
Related
How do I remove the ".000000" part of the "2386.000000" field? I want to leave only the numerical part before the dot in databricks
You can use cast
select cast(2386.000000 as int) i
There are many ways to convert a float to an int. The cast() function is just one.
Please see the following link for all supported Spark SQL functions.
https://spark.apache.org/docs/2.3.0/api/sql/index.html#round
In my solution, I use the round() function. As long as you get the correct answer, the path you take may differ.
In my Metabase, I wrote a query SELECT 10/5 It showing a result 2.000000000 which is correct.
But When I wrote SELECT 5/10 It showing a result 0.000000000. The result should show 0.500000000.
Can you explain it? Why divide function is not working?
Metabase can parse SQL different ways. It depends on connector type.
But in most cases, the result depends on the data type.
Your example uses integer division, because both of operands are integer.
You can just try to change the data type
It is rounding off the value,
Like for select 7/5 it will print 1.
With this code I keep on getting 3.500000. How do I make it 3.5 with one decimal point? I can get it higher but not lower.
(Select AVG(CONVERT(DECIMAL(12,2),Cats)) from #Catsnumber)
This will work
Select CONVERT(DECIMAL(12,2),AVG(Cats))from #Catsnumber
Use either ROUND or CAST to a precise numeric data type with the precision you want
Currently I have a working To_Char in Oracle:
To_Char($Num,'FM' || RPAD(RPAD(LPAD(LPAD('.',least($intmaxlength,$intminlength)+1,'0'),$intmaxlength+1,'9'),$intmaxlength+1+$decminlength,'0'),$intmaxlength+1+$decmaxlength,'9'))
My goal is to convert a number to a string, fitting into four parameters for integers and decimals.
I would like to add minimum and maximum precision. For example, the integers to the left of the decimal point in 1234567.89 should have a minimum of 1 but a maximum of five (so the extra integers would be trimmed). In addition, I'd like to do the same for scale - the decimals to the right, by setting a minimum of two decimal places and a maximum of four. These numbers are just examples, the numbers will be updated dynamically.
I have minimal experience in MSSQL, but from what I can see some equivalent functions like Least are missing in it versus Oracle.
Here are string functions for MSQL
https://msdn.microsoft.com/en-us/library/ms181984.aspx
for least i dont think there is any equivalent.
But i found this getting-the-minimum-of-two-values-in-sql
I'm dividing some integers x & y in MS SQL, and I wan the result to be in a floating-point form. 5/2 should equal 2.5. When I simply do
SELECT 5/2
I get 2, which doesn't suprise me, since it's creating an int from two ints. I know I can force it to a float by doing:
SELECT CAST(5 AS FLOAT)/CAST(2 AS FLOAT);
but that seems like overkill. I find that I can just as easily (and much more readably) get the same result by using
SELECT (0.0+5)/2;
I'm guessing that this is just some sort of implicit type-casting? Is there some reason either method is better/worse?
Under the covers there's no difference in implementation. The implicit casts accomplish the same thing as your explicit casts.
Since you write 0.0, TSQL interprets this as float value. All following ints are implicitly cast to float.
See also the implicit data type conversion matrix in the section Implicit Conversions
Not sure something being shorter is more readable since true reading involves comprehension.
SELECT CAST(5 AS FLOAT)/CAST(2 AS FLOAT);
There really is no doubt what the intention is here and will be understood when you come back to the code 6 months from now or when another developer looks at it for the first time.