Subtraction of two equal values is not zero in mysql - mysql

Why Subtraction of two equal values in mysql does not equal zero?
both field type are double. See image below

That's known as a approximate precision . This isn't an error, floating point data types are intended to work such way. They can not store data precisely. So if that matters, you should use fixed-point data types, such as DECIMAL in MySQL.
On the other hand, you can always use precision delta for comparisons for floating point, like:
SELECT
`foo`,
`bar`,
IF(ABS(`foo`-`bar`)<1E-13, 0, `foo`-`bar`) AS zero_compared
FROM
t
as you can see, here delta is 1E-13 (normally, that will be enough)

This problem is due to floating point precision and calculations on them.
You can also refer this Issue for clarity on your problem:
MySQL floating point comparison issues

Related

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.

MySQL weird rounding off results

I spotted some rounding bug in MySQL. Here is my query:
SELECT /*debugz*/ ROUND((SUM(grade)/2),0) AS grade, SUM(grade) FROM entry.computed_grade a WHERE a.stud_id='7901159' AND a.sy='2014' AND a.term=01 AND a.terms=01 AND a.catalog_no='Christian Life Formation';
and the result is this:
grade sum(grade)
------ ------------
92 185
The grade result should be 93, not 92 because 185/2 = 92.5
Try this
SELECT CEIL((SUM(grade)/2),0) AS grade, SUM(grade) FROM entry.computed_grade a WHERE ((a.stud_id='7901159') AND (a.sy='2014') AND (a.term=01) AND (a.terms=01) AND (a.catalog_no='Christian Life Formation'));
Try to use ceil instead of round.
e.g ceil(1.45) = 2
You should check rounding behavior artickle for mysql. I believe here is the reason of your problem:
For approximate-value numbers, the result depends on the C library. On
many systems, this means that ROUND() uses the “round to nearest even”
rule: A value with any fractional part is rounded to the nearest even
integer.
By the way it's IEEE standard for float point rounding, so you might want stay with it
Do not "patch" this problem by tweaking the query. Actually fix your database. If you are not storing the "grade" column as the DECIMAL data type, and are instead using FLOAT or DOUBLE, your design is inherently broken.
Because floating-point values are approximate and not stored as exact values, attempts to treat them as exact in comparisons may lead to problems. 
http://dev.mysql.com/doc/refman/5.6/en/floating-point-types.html
This is not a bug in MySQL. It is an inherent limitation in industry-standard floating point number storage. Use DECIMAL columns to store meaningful, precise numbers, and the other two types only when low storage space or a wide range of allowable values are more important than precision.

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.

Intriguing sql query (not in select)

I have the following sql query in mysql:
SELECT *
FROM _t_test
WHERE pret NOT
IN ( 2.6700, 2.6560, 1.8200 )
I would expect the rows with the value 1.8200 not to be shown, yet I still get them.
Am I missing something?
The field "pret" is double(16,4).
This is a rounding error. A double is not an exact value, so 1.8200 isn't represented exactly, so the values are not exactly the same.
For MYSQL floating points, see http://dev.mysql.com/doc/refman/5.0/en/problems-with-float.html
The correct way to do floating-point number comparison is to first
decide on an acceptable tolerance for differences between the numbers
and then do the comparison against the tolerance value. For example,
if we agree that floating-point numbers should be regarded the same if
they are same within a precision of one in ten thousand (0.0001), the
comparison should be written to find differences larger than the
tolerance value
See http://en.wikipedia.org/wiki/Double_precision_floating-point_format