Using SQL Server 2008 R2 when I enter the following query:
SELECT CAST(POWER(2.0, 63.0) AS BIGINT);
Which yields the result:
9223372036854775800
However, using the Windows desktop calculator and raising 2 to the 63 yields:
9223372036854775807
Can someone please explain the difference -- or is there some internal conversion that SQL Server is doing? ... or am I missing something else?
The range of BIGINTin MS Sql Server is:
-2^63 (-9,223,372,036,854,775,808) to 2^63-1 (9,223,372,036,854,775,807)
And your calculator is giving you the wrong number, because 2^63 can't have an odd number for its right-most digit.
The POWER function in SQL Server (http://technet.microsoft.com/en-us/library/ms174276.aspx), returns the same type as its first argument.
The correct way to write this query is:
DECLARE #foo REAL = 2.0
SELECT CAST(POWER( #foo, 63.0 ) AS BIGINT)
By which, you will get Arithmetic overflow error converting expression to data type bigint. error message.
And about the reason that's
http://www.extremeoptimization.com/resources/Articles/FPDotNetConceptsAndFormats.aspx
And regarding the question of why POWER function is returning a wrong number? As #simonatrcl mentioned in his answer, there is arithmetic problems with floating-point numbers which sometimes result in invalid result. You can read about floating-point numbers and the problems with them here:
http://www.extremeoptimization.com/resources/Articles/FPDotNetConceptsAndFormats.aspx
You can also check the boundaries for integer types in MS Sql Server here:
http://technet.microsoft.com/en-us/library/ms187745.aspx
Power will be returning a FLOAT. Floating point numbers are not accurate beyond certain limits, and will drop a bit of accuracy (if you've ever has a negative 0 problem you'll know what I mean!).
That's what you're getting here...
As far as the calculator goes and tested on XP, Win7 and Win8.1:
2^63 = 9223372036854775808 (obviously)
As far as MSSQL goes:
The upper limit of a BIGINT is defined as 2^63-1, meaning 1 less than 2^63
Now if you would like MSSQL to calculate that for you one would be tempted to write something like:
SELECT POWER(CAST(2 AS BIGINT), 63) - 1
The result would be a bigint because you've cast the first argument of the power to a bigint. MSSQL will first calculate the power and then subtract 1. However, since the result of the power would exceed the range of a bigint, this statement will fail: Arithmetic overflow error converting expression to data type bigint.
So let us invoke some math to solve this. I assume everyone agrees with
2^4 = 2 * 2 * 2 * 2 = 2 * (2^3) = 2^3 + 2^3
and thus
2^4-1 = 2 * 2 * 2 * 2 - 1 = 2 * (2^3) - 1 = 2^3 + 2^3 - 1
That's what we're going to make use of...
SELECT POWER(CAST(2 AS BIGINT), 62) + (POWER(CAST(2 AS BIGINT), 62) - 1)
This results in 9223372036854775807 which is indeed the upper limit of a bigint.
Note that the () around the subtraction is really needed. Otherwise the addition of the result of the two powers would be done first, again resulting in an overflow.
Related
I've narrowed down a data issue on a legacy SQL Server 2008 database.
The column is a 'float'. SSMS shows four of the records as '0.04445' but when i query for all records that match the first value, only 3 of the four are returned. The last record is somehow different, i suspect it is off by 0.0000000001 or something and the SMSS GUI is rounding it for display(?). Using the '<' operator has similar results ('where my_column < 0.04445' returns three of the four) This is causing some catastrophic calculation errors in the calling app.
I tried casting it to a decimal ('SELECT CAST(my_column as DECIMAL(38,20)) FROM...') but all four records just come back 0.044450000000000000000000000000
I suspect that there are many other similar errors in this same column, as the data has been entered in various ways over the years.
Is there any way to see this column in its full value/precision/mantissa, rather than the rounded value?
I can't change the schema or the app.
Update - using the 'Edit Top 200 Rows' feature, I can see that about three quarters of them are 0.044449999999999996 and the other quarter are ecxactly 0.04445. But I can't get it to display that level of accuracy in a regular query result
You can use CONVERT(VARBINARY(8), my_column) to the number in its original form. What you get should be 0x3FA6C226809D4952 or 0x3FA6C226809D4951. And what number that really is? 3FA6C226809D4951 is binary
0 01111111010 0110110000100010011010000000100111010100100101010001
0 => number is positive
01111111010 => 1018-1023 = -5 is exponent (so we get 2^-5)
1.0110110000100010011010000000100111010100100101010001 => 6405920109971793*2^-52
so the 0x3FA6C226809D4951 is exactly 6405920109971793*2^-57, which is 0.044449999999999996458388551445750636048614978790283203125
and 0x3FA6C226809D4952 is exactly 6405920109971794*2^-57, which is 0.04445000000000000339728245535297901369631290435791015625
So, your question is really about SSMS, not about your application or SQL Server itself, right? You want to see the actual float values in SSMS without rounding, right?
By design SSMS rounds float during display. For example, see this answer.
But, you can see the actual value that is stored in the column if you convert it to a string explicitly using CONVERT function.
float and real styles
For a float or real expression, style can have
one of the values shown in the following table. Other values are
processed as 0.
0 (default) A maximum of 6 digits. Use in scientific notation, when appropriate.
1 Always 8 digits. Always use in scientific notation.
2 Always 16 digits. Always use in scientific notation.
3 Always 17 digits. Use for lossless conversion.
With this style, every distinct float or real value is guaranteed to
convert to a distinct character string.
It looks like style 3 is just what you need:
convert(varchar(30), my_column, 3)
Here is my test:
DECLARE #v1 float = 0.044449999999999996e0;
DECLARE #v2 float = 0.044445e0;
SELECT #v1, #v2, convert(varchar(30), #v1, 3), convert(varchar(30), #v2, 3)
Result that I see in SSMS:
+------------------+------------------+-------------------------+-------------------------+
| (No column name) | (No column name) | (No column name) | (No column name) |
+------------------+------------------+-------------------------+-------------------------+
| 0.04445 | 0.044445 | 4.4449999999999996e-002 | 4.4444999999999998e-002 |
+------------------+------------------+-------------------------+-------------------------+
Attached is a code sample to run in SQL. This seems like unexpected behavior for SQL Server. What should happen is to remove the negative from the number but when using the same function under the update command it does the absolute value and also rounds the number. Why is this?
DECLARE #TEST TABLE (TEST varchar(2048));
INSERT INTO #TEST VALUES (' -29972.95');
SELECT TEST FROM #TEST;
SELECT ABS(TEST) FROM #TEST;
UPDATE #TEST SET TEST = ABS(TEST);
SELECT TEST FROM #TEST;
Below are the results of that code.
-29972.95
29972.95
29973
This seems more a "feature" of the CONVERT function than anything to do with SELECT or UPDATE (only reason it is different is because the UPDATE implicitly converts the FLOAT(8) returned by ABS(...) back into VARCHAR).
The compute scalar in the update plan contains the expression
[Expr1003] = Scalar Operator(CONVERT_IMPLICIT(varchar(2048),
abs(CONVERT_IMPLICIT(float(53),[TEST],0))
,0) /*<-- style used for convert from float*/
)
Value - Output
0 (default) - A maximum of 6 digits. Use in scientific notation, when appropriate.
1 - Always 8 digits. Always use in scientific notation.
2 - Always 16 digits. Always use in scientific notation.
From MSDN: https://learn.microsoft.com/en-us/sql/t-sql/functions/cast-and-convert-transact-sql?view=sql-server-2017
This can be seen in the example below:
SELECT
[# Digits],
CONVERT(FLOAT(8), CONVERT(VARCHAR(20), N)) AS [FLOAT(VARCHAR(N))],
CONVERT(FLOAT(8), CONVERT(VARCHAR(20), N, 0)) AS [FLOAT(VARCHAR(N, 0))],
CONVERT(FLOAT(8), CONVERT(VARCHAR(20), N, 1)) AS [FLOAT(VARCHAR(N, 1))]
FROM (SELECT '6 digits', ABS('9972.95') UNION ALL SELECT '7 digits', ABS('29972.95')) T ([# Digits], N)
This returns the following results:
# Digits FLOAT(VARCHAR(N)) FLOAT(VARCHAR(N, 0)) FLOAT(VARCHAR(N, 1))
-------- ----------------- -------------------- --------------------
6 digits 9972.95 9972.95 9972.95
7 digits 29973 29973 29972.95
This proves the UPDATE was using CONVERT(VARCHAR, ABS(...)) effectively with the default style of "0". This limited the FLOAT from the ABS to 6 digits. Taking 1 character away so it does not overflow the implicit conversion, you retain the actual values in this scenario.
Taking this back to the OP:
The ABS function in this case is returning a FLOAT(8) in the example.
The UPDATE then caused an implicit conversion that was effectively `CONVERT(VARCHAR(2048), ABS(...), 0), which then overflowed the max digits of the default style.
To get around this behavior (if this is related to a practical issue), you need to specify the style of 1 or 2 (or even 3 to get 17 digits) to avoid this truncation (but be sure to handle the scientific notation used since it is now always returned in this case)
(some preliminary testing deleted for brevity)
It definitely has to do with silent truncating during INSERT/UPDATEs.
If you change the value insertion to this:
INSERT INTO #TEST SELECT ABS(' -29972.95')
You immediately get the same rounding/truncation without doing an UPDATE.
Meanwhile, SELECT ABS(' -29972.95') produces expected results.
Further testing supports the theory of an implicit float conversion, and indicates that the culprit lies with the conversion back to varchar:
DECLARE #Flt float = ' -29972.95'
SELECT #Flt;
SELECT CAST(#Flt AS varchar(2048))
Produces:
-29972.95
-29972
Probably final edit:
I was sniffing up the same tree as Martin. I found this.
Which made me try this:
DECLARE #Flt float = ' -29972.95'
SELECT #Flt;
SELECT CONVERT(varchar(2048),#Flt,128)
Which produced this:
-29972.95
-29972.95
So I'm gonna call this kinda documented since the 128 style is a legacy style that is deprecated and may go away in a future release. But none of the currently documented styles produce the same result. Very interesting.
ABS() is supposed to operate on numeric values and varchar input is converted to float. Most likely explanation for this behavior is that float has highest precedence among all numeric data types such as decimal, int, bit.
Your SELECT statement simply returns the float result. However the UPDATE statement implicitly converts the float back to varchar producing unexpected results:
SELECT
test,
ABS(test) AS test_abs,
CAST(ABS(test) AS VARCHAR(100)) AS test_abs_str
FROM (VALUES
('-29972.95'),
('-29972.94'),
('-29972.9')
) AS test(test)
test | test_abs | test_abs_str
----------|----------|-------------
-29972.95 | 29972.95 | 29973
-29972.94 | 29972.94 | 29972.9
-29972.9 | 29972.9 | 29972.9
I would suggest that you use explicit conversion and exact numeric datatype to avoid this and other potential problems with implicit conversions / floats:
SELECT
test,
ABS(CAST(test AS DECIMAL(18, 2))) AS test_abs,
CAST(ABS(CAST(test AS DECIMAL(18, 2))) AS VARCHAR(100)) AS test_abs_str
FROM (VALUES
('-29972.95'),
('-29972.94'),
('-29972.9')
) AS test(test)
test | test_abs | test_abs_str
----------|----------|-------------
-29972.95 | 29972.95 | 29972.95
-29972.94 | 29972.94 | 29972.94
-29972.9 | 29972.90 | 29972.90
ABS is a mathematical function, that means is designed to work with numeric values, you cannot expect a proper behavior of the function when using other data types like in this case VARCHAR, I suggest first to do the required CAST to a numeric data type before applying the ABS function as follows:
UPDATE #TEST SET TEST = ABS(CAST(TEST AS DECIMAL(18,2)))
After this your query will output
29972.95
This does not solve how it is posible that ABS works fine when selecting and not when updating a value, maybe it is a bug on sqlserver but also it is a really bad practice to avoid casting to proper data types required by functions. Maybe an implicit cast occurs when a SELECT clause is performed but ignored on UPDATE because microsoft is expecting you to do the right thing.
Four simple SELECT statements:
SELECT 33883.50 * -1;
SELECT 33883.50 / -1.05;
SELECT 33883.50 * -1 / 1.05;
SELECT (33883.50 * -1) / 1.05;
But the results are not as I would expect:
-33883.50
-32270.000000
-32269.96773000
-32270.000000
That third result is the one that seems questionable. I can see what is happening, first SQL Server evaluates this:
SELECT -1 / 1.05;
Getting an answer of:
-0.952380
Then it takes that answer and uses it to perform this calculation:
SELECT 33883.50 * -0.952380;
To get the (wrong) answer of:
-32269.96773000
But why is it doing this?
In your example
33883.50 * -1 / 1.05
is evaluated as
33883.50 * (-1 / 1.05)
instead of
(33883.50 * -1) / 1.05
which results in a loss in precision.
I played a bit with it. I used SQL Sentry Plan Explorer to see the details of how SQL Server evaluates expressions. For example,
2 * 3 * -4 * 5 * 6
is evaluated as
((2)*(3)) * ( -((4)*(5))*(6))
I'd explain it like this. In T-SQL unary minus is made to be the same priority as subtraction, which is lower than multiplication. Yes,
When two operators in an expression have the same operator precedence
level, they are evaluated left to right based on their position in the
expression.
, but here we have an expression that mixes operators with different priorities and parser follows these priorities to the letter. Multiplication has to go first, so it evaluates 4 * 5 * 6 at first and then applies unary minus to the result.
Normally (say in C++) unary minus has higher priority (like bitwise NOT) and such expressions are parsed and evaluated as expected. They should have made unary minus/plus same highest priority as bitwise NOT in T-SQL, but they didn't and this is the result. So, it is not a bug, but a bad design decision. It is even documented, though quite obscurely.
When you refer to Oracle - that the same example works differently in Oracle than in SQL Server:
Oracle may have different rules for operator precedence than SQL Server. All it takes is to make unary minus highest priority as it should.
Oracle may have different rules for determining result precision and scale when evaluating expressions with decimal type.
Oracle may have different rules for rounding intermediate results. SQL Server "uses rounding when converting a number to a decimal or numeric value with a lower precision and scale".
Oracle may be using completely different types for these kind of expressions, not decimal. In SQL Server "a constant with a decimal point is automatically converted into a numeric data value, using the minimum precision and scale necessary. For example, the constant 12.345 is converted into a numeric value with a precision of 5 and a scale of 3."
Even definition of decimal may be different in Oracle. Even in SQL Server "the default maximum precision of numeric and decimal data types is 38. In earlier versions of SQL Server, the default maximum is 28."
Do you know BODMAS rule. The answer is correct its not because of Sql Server, Its a basic mathematics.
First comes Division then comes the Subtraction, So always Division will happen before Subtraction
If you want to get correct answer then use proper parenthesis
SELECT (33883.50 * -1) / 1.05;
T-SQL has an rule for operator precedence which it follows. You can read about it on the link https://msdn.microsoft.com/en-us/library/ms190276.aspx.
It seems to be a precedence rule concerning unary operators. I have tried the following queries
SELECT 33883.50 * cast(-1 as int) / 1.05;
SELECT 33883.50 * (-1 * 1) / 1.05;
and it returns the right answer. The best thing to do is to use parentheses on expressions you want to occur first, and test thoroughly.
At some point I have a numeric(28,10) and I cast it in money (I know its bad but for legacy reason I have to return money) in the same time I also have to set the sign (multiplying by +1/-1).
In a first attempt I had cast the +/-1 to match the numeric type.
For the value 133.3481497944 we encounter a strange behavior (I have simplified the actual code in order to keep only the elements needed to demonstrate the problem):
SELECT CAST(CAST(133.3481497944 AS numeric(28,10))*cast(1 AS numeric(28,10)) AS money)
133.3482
which is not correctly rounded...
Removing the cast solve the problem
SELECT CAST(CAST(133.3481497944 AS numeric(28,10)) * 1 AS money)
133.3481
Did someone know what is happening in SQL? How can a multiplication by 1 and cast(1 AS numeric(28,10)) affect the result of the rounding?
When multiplying numerics, SQL uses the following rules to determine the precision and scale of the output:
p = p1 + p2 + 1
s = s1 + s2
which makes sense - you wouldn't want 1.5 * 2.5 to be truncated to one digit past the decimal. Nor would you want 101 * 201 to be limited to 3 digits of precision, giving you 20300 instead of 20301.
In your case that would result in a precision of 57 and a scale of 20, which isn't possible - the maximum precision and scale is 38.
If the resulting type is too big, decimal digits are sacrificed in order to preserve the integral (most significant) part of the result.
From the SQL Programmability & API Development Team Blog:
In SQL Server 2005 RTM (and previous versions), we decided preserve a minimum scale of 6 in both multiplication and division.
So your answer depands on how big and precise you need the multiplier to be. In order to preserve 10 digits of decimal precision. If the multiplier needs a scale bigger than 9, then decimal digits may be truncated. If you use a smaller precision and scale, you should be fine:
SELECT CAST(CAST(133.3481497944 AS numeric(28,10))*cast(1 AS numeric(9,7)) AS money)
yields 133.3481.
I don't see any ROUNDing here. I only see casting. Don't assume that it will round, when you CAST. Historically, when we cast the environment truncates (SQL server or not) or behaves not as we expect - especially when we're talking about FLOATs.
SELECT
CAST(CAST(133.3481497944 AS numeric(28,10))*cast(1 AS numeric(28,10)) AS money) --Your original,
CAST(1 AS numeric(28,10)) --Just the 1 casted,
CAST(133.3481497944 AS numeric(28,10)) --Your expected calculation,
CAST(133.3481497944 AS numeric(28,10))*cast(1 AS numeric(28,10)) -- The actual calculation
SELECT
CAST(133.3481497944 AS numeric(28,10))*cast(1.5 AS numeric(28,10)),
CAST(133.3481497944 AS numeric(28,10))*1.5,
CAST((133.3481497944*1) AS money),
133.3481497944*1
Returns
133.3482
1.0000000000
133.3481497944
133.348150
200.022225
200.02222469160
133.3481
133.3481497944
So as mentioned above, there really isn't any true rounding, but a loss of precision during the cast. As to exactly why, I don't know. Most likely during the calculation(multiplication) while using the Numeric(28,10) it cuts off some precision.
I added the second lines to show that really you may not need your numeric casting.
I have a column X which is full of floats with decimals places ranging from 0 (no decimals) to 6 (maximum). I can count on the fact that there are no floats with greater than 6 decimal places. Given that, how do I make a new column such that it tells me how many digits come after the decimal?
I have seen some threads suggesting that I use CAST to convert the float to a string, then parse the string to count the length of the string that comes after the decimal. Is this the best way to go?
You can use something like this:
declare #v sql_variant
set #v=0.1242311
select SQL_VARIANT_PROPERTY(#v, 'Scale') as Scale
This will return 7.
I tried to make the above query work with a float column but couldn't get it working as expected. It only works with a sql_variant column as you can see here: http://sqlfiddle.com/#!6/5c62c/2
So, I proceeded to find another way and building upon this answer, I got this:
SELECT value,
LEN(
CAST(
CAST(
REVERSE(
CONVERT(VARCHAR(50), value, 128)
) AS float
) AS bigint
)
) as Decimals
FROM Numbers
Here's a SQL Fiddle to test this out: http://sqlfiddle.com/#!6/23d4f/29
To account for that little quirk, here's a modified version that will handle the case when the float value has no decimal part:
SELECT value,
Decimals = CASE Charindex('.', value)
WHEN 0 THEN 0
ELSE
Len (
Cast(
Cast(
Reverse(CONVERT(VARCHAR(50), value, 128)) AS FLOAT
) AS BIGINT
)
)
END
FROM numbers
Here's the accompanying SQL Fiddle: http://sqlfiddle.com/#!6/10d54/11
This thread is also using CAST, but I found the answer interesting:
http://www.sqlservercentral.com/Forums/Topic314390-8-1.aspx
DECLARE #Places INT
SELECT TOP 1000000 #Places = FLOOR(LOG10(REVERSE(ABS(SomeNumber)+1)))+1
FROM dbo.BigTest
and in ORACLE:
SELECT FLOOR(LOG(10,REVERSE(CAST(ABS(.56544)+1 as varchar(50))))) + 1 from DUAL
A float is just representing a real number. There is no meaning to the number of decimal places of a real number. In particular the real number 3 can have six decimal places, 3.000000, it's just that all the decimal places are zero.
You may have a display conversion which is not showing the right most zero values in the decimal.
Note also that the reason there is a maximum of 6 decimal places is that the seventh is imprecise, so the display conversion will not commit to a seventh decimal place value.
Also note that floats are stored in binary, and they actually have binary places to the right of a binary point. The decimal display is an approximation of the binary rational in the float storage which is in turn an approximation of a real number.
So the point is, there really is no sense of how many decimal places a float value has. If you do the conversion to a string (say using the CAST) you could count the decimal places. That really would be the best approach for what you are trying to do.
I answered this before, but I can tell from the comments that it's a little unclear. Over time I found a better way to express this.
Consider pi as
(a) 3.141592653590
This shows pi as 11 decimal places. However this was rounded to 12 decimal places, as pi, to 14 digits is
(b) 3.1415926535897932
A computer or database stores values in binary. For a single precision float, pi would be stored as
(c) 3.141592739105224609375
This is actually rounded up to the closest value that a single precision can store, just as we rounded in (a). The next lowest number a single precision can store is
(d) 3.141592502593994140625
So, when you are trying to count the number of decimal places, you are trying to find how many decimal places, after which all remaining decimals would be zero. However, since the number may need to be rounded to store it, it does not represent the correct value.
Numbers also introduce rounding error as mathematical operations are done, including converting from decimal to binary when inputting the number, and converting from binary to decimal when displaying the value.
You cannot reliably find the number of decimal places a number in a database has, because it is approximated to round it to store in a limited amount of storage. The difference between the real value, or even the exact binary value in the database will be rounded to represent it in decimal. There could always be more decimal digits which are missing from rounding, so you don't know when the zeros would have no more non-zero digits following it.
Solution for Oracle but you got the idea. trunc() removes decimal part in Oracle.
select *
from your_table
where (your_field*1000000 - trunc(your_field*1000000)) <> 0;
The idea of the query: Will there be any decimals left after you multiply by 1 000 000.
Another way I found is
SELECT 1.110000 , LEN(PARSENAME(Cast(1.110000 as float),1)) AS Count_AFTER_DECIMAL
I've noticed that Kshitij Manvelikar's answer has a bug. If there are no decimal places, instead of returning 0, it returns the total number of characters in the number.
So improving upon it:
Case When (SomeNumber = Cast(SomeNumber As Integer)) Then 0 Else LEN(PARSENAME(Cast(SomeNumber as float),1)) End
Here's another Oracle example. As I always warn non-Oracle users before they start screaming at me and downvoting etc... the SUBSTRING and INSTRING are ANSI SQL standard functions and can be used in any SQL. The Dual table can be replaced with any other table or created. Here's the link to SQL SERVER blog whre i copied dual table code from: http://blog.sqlauthority.com/2010/07/20/sql-server-select-from-dual-dual-equivalent/
CREATE TABLE DUAL
(
DUMMY VARCHAR(1)
)
GO
INSERT INTO DUAL (DUMMY)
VALUES ('X')
GO
The length after dot or decimal place is returned by this query.
The str can be converted to_number(str) if required. You can also get the length of the string before dot-decimal place - change code to LENGTH(SUBSTR(str, 1, dot_pos))-1 and remove +1 in INSTR part:
SELECT str, LENGTH(SUBSTR(str, dot_pos)) str_length_after_dot FROM
(
SELECT '000.000789' as str
, INSTR('000.000789', '.')+1 dot_pos
FROM dual
)
/
SQL>
STR STR_LENGTH_AFTER_DOT
----------------------------------
000.000789 6
You already have answers and examples about casting etc...
This question asks of regular SQL, but I needed a solution for SQLite. SQLite has neither a log10 function, nor a reverse string function builtin, so most of the answers here don't work. My solution is similar to Art's answer, and as a matter of fact, similar to what phan describes in the question body. It works by converting the floating point value (in SQLite, a "REAL" value) to text, and then counting the caracters after a decimal point.
For a column named "Column" from a table named "Table", the following query will produce a the count of each row's decimal places:
select
length(
substr(
cast(Column as text),
instr(cast(Column as text), '.')+1
)
) as "Column-precision" from "Table";
The code will cast the column as text, then get the index of a period (.) in the text, and fetch the substring from that point on to the end of the text. Then, it calculates the length of the result.
Remember to limit 100 if you don't want it to run for the entire table!
It's not a perfect solution; for example, it considers "10.0" as having 1 decimal place, even if it's only a 0. However, this is actually what I needed, so it wasn't a concern to me.
Hopefully this is useful to someone :)
Probably doesn't work well for floats, but I used this approach as a quick and dirty way to find number of significant decimal places in a decimal type in SQL Server. Last parameter of round function if not 0 indicates to truncate rather than round.
CASE
WHEN col = round(col, 1, 1) THEN 1
WHEN col = round(col, 2, 1) THEN 2
WHEN col = round(col, 3, 1) THEN 3
...
ELSE null END