MySQL weird float and decimal behaviour [duplicate] - mysql

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Difference between float and decimal data type
(12 answers)
Closed 9 years ago.
I have a table contain column float(10,5) and decimal(10,5)
I update the table to be:
update table1
set decimaltesting = 12311123123123123.456789,
floattesting = 12311123123123123.456789;
The result become:
decimal = 99999.99999
float = 100000.00000
but if I change column to float(6,3) and decimal(6,3) and update it with the same value as above
The result become:
float = 999.999
decimal = 999.999
Why for the first scenario, float value will be 100000.00000?

Garbage in - garbage out
Remember this simple rule. Your statement will not be correct in common case - since, for example, with strict sql mode it will fail with error. But since you're getting results as you've described, I assume you have allowed such behavior. The correct point is - that your application is aware about it's models data types - and so such things are under control - and you're not passing garbage to your DBMS, resulting with garbage as well.
Always about precision
Your sample is a good demonstration about - what's the difference between fixed-point and floating-point data types. First thing - according to manual page:
When a floating-point or fixed-point column is assigned a value that
exceeds the range implied by the specified (or default) precision and
scale, MySQL stores the value representing the corresponding endpoint
of that range.
-that is why you're seeing that 999.999 and so on. But - what about strange 100000.00000? The hint is - that you can see this only with floating point field. Why? Because MySQL will convert your out-of-range value to maximum allowed by your field, but, since floating point values are stored approximately, there's no guarantee that final value will hold precision - and, therefore, it may result in your 100000.00000 value. Note, that such thing will never happen with fixed-point data type.

Related

problems handling significant digits in mysql converting float to double

I am inserting data from one table into another in a MariaDB database, where the column in the first table is FLOAT, and in the second it's DOUBLE. The data can have values of any size, precision and decimal places.
Here is what happens to the values when I do a straight-forward copy:
INSERT INTO data2 (value) SELECT value FROM data1
The values are given random extra significant figures:
FLOAT in data1 DOUBLE in data2
-0.000000000000454747 -0.0000000000004547473508864641
-122.319 -122.31932830810547
14864199700 14864220160
CAST(value AS DECIMAL(65,30)) generates exactly the same values as col 2 above, except I see trailing zeroes.
Yet when I just do
UPDATE data2 SET value = 14867199700 WHERE id = 133025046;
the DOUBLE value is accepted.
Do I have to export all the value to an SQL script and re-import them? Isn't there a better way?
Despite hours trying to experimenting with the issue, I'm not much closer to a solution, despite its limited nature. I can see this is problem that besets all technologies, not just MariaDB or databases, so I have probably just missed the answer somewhere. Stackoverflow is desperately trying to guide to a solution with new suggestion features I hadn't seen before, but unfortunately they are no help, like the other suggested answers.
Your test case is flawed. You are feeding in decimal digits, and not testing just the transfer of FLOAT to DOUBLE.
UPDATE tbl SET double_col = float_col will always copy exactly the same value. This because the DOUBLE representation is a superset of the FLOAT representation (53 vs 24 bits of precision; etc).
Literal, with decimal places: UPDATE tbl SET double_col = 123.456 will mangle the number because of rounding from decimal to DOUBLE. Ditto for float_col. Furthermore, the mangled results will be different!
Hole number literal: UPDATE tbl SET double_col = 14867199700 will be stored exactly. But if you put that same literal into a FLOAT, it will be rounded to 24 bits, so it cannot be stored exactly. You lose exactness at about 7 significant digits for FLOAT and about 16 for DOUBLE. The literal in this example has 9 significant digits (after ignoring trailing zeros).
That's just a sampling of the nightmares you can get into.
You must consider FLOAT and DOUBLE to be approximate. You should never compare for equality; you don't know what might have messed with the last bit of the value.
Also, you should not try to guess when MySQL will perform expressions in DECIMAL instead of DOUBLE.
And, keep in mind that division is usually imprecise due to rounding to some number of bits or decimals.
The "mantissa" of 14864199700 is
1.10111010111111001101100 (binary of FLOAT : 24 bits including 'hidden' leading bit)
1.1011101011111100110110000000101000000000000000000000 (binary of DOUBLE)
^ ^ (lost in FLOAT)
Each of those is multiplied by the same power of 2. The DOUBLE gets exactly 14864199700. The FLOAT lost the bits pointed to.
You can play around with such at https://gregstoll.dyndns.org/~gregstoll/floattohex/
Believe it or not, things used to be worse. People would be billed for $0.00 -- due to rounding errors. Or results of what should have been 1+1 showed as 1.99999999.

how can I stop mysql from rounding float values?

I'm storing monetary values in a mysql table as floats.
problem being, mysql is rounding the numbers up or down.
ex. 12345.68 gets rounded to 12345.7
How can I stop this or is there a better data type I should be using?
I would like to retain the original values within the 2 decimal places.
Do not use FLOAT type. Use DECIMAL instead. Float converts decimal numbers to binary which results in rounding (loss of precision). Decimal stores the numbers as decimals - no conversion.
In your case defining the column as DECIMAL(12,2) should be ok. Chose the width (first number) based on the expected size of the numbers. In the example, the expected size is 12 digits (including the digits after the decimal point).
Change the definition of the applicable column from its current setting to:
FLOAT(9,2)
The 2 in the previous snippet instructs MySQL to maintain values up to 2 decimal places. It's likely set to 1 at the moment; thus the observed behavior. Feel free to change the 9 to a more applicable value.
More on floats and precision.
Related answer, which advises on not using floats, but instead decimal.

roundings with Access

With Microsoft Access 2010, I have two Single fields:
A = 1.1
B = 2.1
I create a query where I have defined C=A*B
Microsoft Access says that C = 2.30999994277954
but, in reality, C =2.31
How can I get the right result (2.31)?
Slightly off results from operations performed on decimal values can happen if your numeric field size is single or double rather than decimal. Single and double (or floating point) numbers are very close approximations of the "true" numbers, but should not be relied upon if accuracy in operations is required. A related stackoverflow question has more information about this issue: Access comparing floating-point numbers "incorrectly"
If it's possible to modify the underlying table's design, you should change the field size property for the "A" and "B" fields from single to decimal. After changing the field size BUT BEFORE saving the table, you will also need to adjust the Scale property for "A" and "B" from 0 to whatever number of places to the right of the decimal point you might require. You will likely still have a notice about losing data, but if you adjust the field properties correctly before saving the table, this shouldn't be a problem. You should probably make a copy of the table before doing this so that you can verify that there was no data loss. After saving your table and verifying the changes did not result in data loss, your query should represent A * B accurately.

Storing statistical data, do I need DECIMAL, FLOAT or DOUBLE?

I am creating for fun, but I still want to approach it seriously, a site which hosts various tests. With these tests I hope to collect statistical data.
Some of the data will include the percentage of the completeness of the tests as they are timed. I can easily compute the percentage of the tests but I would like true data to be returned as I store the various different values concerning the tests on completion.
Most of the values are, in PHP floats, so my question is, if I want true statistical data should I store them in MYSQL as FLOAT, DOUBLE or DECIMAL.
I would like to utilize MYSQL'S functions such as AVG() and LOG10() as well as TRUNCATE(). For MYSQL to return true data based off of my values that I insert, what should I use as the database column choice.
I ask because some numbers may or may not be floats such as, 10, 10.89, 99.09, or simply 0.
But I would like true and valid statistical data to be returned.
Can I rely on floating point math for this?
EDIT
I know this is a generic question, and I apologise extensively, but for non mathematicians like myself, also I am not a MYSQL expert, I would like an opinion of an expert in this field.
I have done my research but I still feel I have a clouded judgement on the matter. Again I apologise if my question is off topic or not suitable for this site.
This link does a good job of explaining what you are looking for. Here is what is says:
All these three Types, can be specified by the following Parameters (size, d). Where size is the total size of the String, and d represents precision. E.g To store a Number like 1234.567, you will set the Datatype to DOUBLE(7, 3) where 7 is the total number of digits and 3 is the number of digits to follow the decimal point.
FLOAT and DOUBLE, both represent floating point numbers. A FLOAT is for single-precision, while a DOUBLE is for double-precision numbers. A precision from 0 to 23 results in a 4-byte single-precision FLOAT column. A precision from 24 to 53 results in an 8-byte double-precision DOUBLE column. FLOAT is accurate to approximately 7 decimal places, and DOUBLE upto 14.
Decimal’s declaration and functioning is similar to Double. But there is one big difference between floating point values and decimal (numeric) values. We use DECIMAL data type to store exact numeric values, where we do not want precision but exact and accurate values. A Decimal type can store a Maximum of 65 Digits, with 30 digits after decimal point.
So, for the most accurate and precise value, Decimal would be the best option.
Unless you are storing decimal data (i.e. currency), you should use a standard floating point type (FLOAT or DOUBLE). DECIMAL is a fixed point type, so can overflow when computing things like SUM, and will be ridiculously inaccurate for LOG10.
There is nothing "less precise" about binary floating point types, in fact, they will be much more accurate (and faster) for your needs. Go with DOUBLE.
Decimal : Fixed-Point Types (Exact Value). Use it when you care about exact precision like money.
Example: salary DECIMAL(8,2), 8 is the total number of digits, 2 is the number of decimal places. salary will be in the range of -999999.99 to 999999.99
Float, Double : Floating-Point Types (Approximate Value). Float uses 4 bytes to represent value, Double uses 8 bytes to represent value.
Example: percentage FLOAT(5,2), same as the type decimal, 5 is total digits and 2 is the decimal places. percentage will store values between -999.99 to 999.99.
Note that they are approximate value, in this case:
Value like 1 / 3.0 = 0.3333333... will be stored as 0.33 (2 decimal place)
Value like 33.009 will be stored as 33.01 (rounding to 2 decimal place)
Put it simply, Float and double are not as precise as decimal. decimal is recommended for money related number input.(currency and salary).
Another point need to point out is: Do NOT compare float number using "=","<>", because float numbers are not precise.
Linger: The website you mention and quote has IMO some imprecise info that made me confused. In the docs I read that when you declare a float or a double, the decimal point is in fact NOT included in the number. So it is not the number of chars in a string but all digits used.
Compare the docs:
"DOUBLE PRECISION(M,D).. Here, “(M,D)” means than values can be stored with up to M digits in total, of which D digits may be after the decimal point. For example, a column defined as FLOAT(7,4) will look like -999.9999 when displayed"
http://dev.mysql.com/doc/refman/5.1/en/floating-point-types.html
Also the nomenclature in misleading - acc to docs: M is 'precision' and D is 'scale', whereas the website takes 'scale' for 'precision'.
Thought it would be useful in case sb like me was trying to get a picture.
Correct me if I'm wrong, hope I haven't read some outdated docs:)
Float and Double are Floating point data types, which means that the numbers they store can be precise up to a certain number of digits only.
For example for a table with a column of float type if you store 7.6543219 it will be stored as 7.65432.
Similarly the Double data type approximates values but it has more precision than Float.
When creating a table with a column of Decimal data type, you specify the total number of digits and number of digits after decimal to store, and if the number you store is within the range you specified it will be stored exactly.
When you want to store exact values, Decimal is the way to go, it is what is known as a fixed data type.
Simply use FLOAT. And do not tack on '(m,n)'. Do display numbers to a suitable precision with formatting options. Do not expect to get correct answers with "="; for example, float_col = 0.12 will always return FALSE.
For display purposes, use formatting to round the results as needed.
Percentages, averages, etc are all rounded (at least in some cases). That any choice you make will sometimes have issues.
Use DECIMAL(m,n) for currency; use ...INT for whole numbers; use DOUBLE for scientific stuff that needs more than 7 digits of precision; use FLOAT` for everything else.
Transcendentals (such as the LOG10 that you mentioned) will do their work in DOUBLE; they will essentially never be exact. It is OK to feed it a FLOAT arg and store the result in FLOAT.
This Answer applies not just to MySQL, but to essentially any database or programming language. (The details may vary.)
PS: (m,n) has been removed from FLOAT and DOUBLE. It only added extra rounding and other things that were essentially no benefit.

Float value conversion in the database

In my database some fields (amount, balance) are assigned as floating value, but now i have a problem with that .if the amount is 1.56 it will take 1.6
then i alter the table using Round(amount,2)
still it shows the same problem.
if anybody know please help me.
The float fields must be declared as float(some_integer, 1) to show the behaviour you described. The first integer in such a declaration tells MySQL how much digits should be visible alltogether, the ones left to the decimal point + the ones right to it. To have 3 digits to the left and 2 to the right of the decimal point you would declare it as float(5,2).
Like Doan Cuong already mentioned it would be better if you would choose decimal data type.
See the different behaviour of it live here.
To quote the manual:
The DECIMAL and NUMERIC types store exact numeric data values. These types are used when it is important to preserve exact precision, for example with monetary data.
The FLOAT and DOUBLE types represent approximate numeric data values.
For additional info about the data types read more here.