This was my Interview Question
there are two columns called Length and Breadth in Area table
Length Breadth Length*Breadth
20 NULL ?
30 ?
21.2 1 ?
I tried running the same question on MYSQL while inserting,To insert an empty value I tried the below query . Am I missing anything while inserting empty values in MYSQL.
insert into test.new_table values (30,);
Answers: With Null,Result is Null.
With float and int multiplication result is float
As per your question the expected results would be as below.
SELECT LENGTH,BREADTH,LENGTH*BREADTH AS CALC_AREA FROM AREA;
LENGTH BREADTH CALC_AREA
20
30 0 0
21.2 1 21.2
For any(first) record in SQL SERVER if you do computation with NULL the answer would be NULL.
For any(second) record in SQL SERVER, if you do product computation between a non-empty value and an empty value the result would be zero as empty value is treated as zero.
For any(third) record in SQL SERVER, if you do computation between two non-empty data type values the answer would be a NON-EMPTY value.
Check SQL Fiddle for reference - http://sqlfiddle.com/#!3/f250a/1
That blank Breath (second row) cannot happen unless Breath is VARCHAR. Assuming that, the answers will be:
NULL (since NULL times anything is NULL)
Throws error (since an empty string is not a number. In Sql Server, the error is "Error converting data type varchar to numeric.")
21.20 (since in Sql Server, for example, conversion to a numeric type is automatic, so SELECT 21.2 * '1' returns 21.20).
Assuming that Length and Breadth are numerical types of some kind the second record does not contain possible values — Breadth must be either 0 or NULL.
In any event, any mathematical operation in SQL involving a NULL value will return the value NULL, indicating that the expression cannot be evaluated. The answer are NULL, impossible, and 21.2.
The product of any value and NULL is NULL. This is called "NULL propagation" if you want to Google it. To score points in an interview, you might want to mention that NULL isn't a value; it's a special marker.
The fact that the column Breadth has one entry "NULL" and one entry that's blank (on the second row) is misleading. A numeric column that doesn't have a value in a particular row means that row is NULL. So the second column should also show "NULL".
The answer to the third row, 21.2 * 1, depends on the data type of the column "Length*Breadth". If it's a data type like float, double, or numberic(16,2), the answer is 21.2. If it's an integer column (integer, long, etc.), the answer is 21.
A more snarky answer might be "There's no answer. The string "Length*Breadth" isn't a legal SQL column name."
In standard SQL they would all generate errors because you are comparing values (or nulls) of different types:
CAST ( 20 AS FLOAT ) * CAST ( NULL AS INTEGER ) -- mismatched types error
CAST ( '' AS INTEGER ) -- type conversion error
CAST ( AS INTEGER ) -- type conversion error
CAST ( 21.2 AS FLOAT ) * CAST ( 2 AS INTEGER ) -- mismatched types error
On the other hand, most SQL product would implicitly cast values when comparing values (or nulls) of different types according to type precedence e.g. comparing float value to an integer value would in effect cast the integer to float and result in a float. At the product level, the most interesting question is what happens when you compare a null of type integer with a value (or even a null) of type float...
...but, frankly, not terribly interesting. In an interview you are presented with a framework (in the form of questions asked of you) on which to present your knowledge, skills and experience. The 'answer' here is to discuss nulls (e.g. point out that nulls are tricky to define and behave in unintuitive ways, which leads to frequent bugs and a desire to avoid nulls entirely, etc) and whether implicit casting is a good thing.
Related
Considering the following test code :
CREATE TABLE binary_test (bin_float BINARY_FLOAT, bin_double BINARY_DOUBLE, NUM NUMBER);
INSERT INTO binary_test VALUES (4356267548.32345E+100, 4356267548.32345E+2+300, 4356267548.32345E+100);
SELECT CASE WHEN bin_double>to_binary_double(num) THEN 'Greater'
WHEN bin_double=to_binary_double(num) THEN 'Equal'
WHEN bin_double<to_binary_double(num) THEN 'Lower'
ELSE 'Unknown' END comparison,
A.*
FROM binary_test A;
I've tried to see which one stores higher values. If I try to add E+300 for the number and binary_float columns, it returns numeric overflow error. So, I thought I could store a greater value with the binary_float.
However, when I tried to check it, it shows a lower value, and with the case comparison it says it is lower too. Could you please elaborate this situation?
You are inserting the value 4356267548.32345E+2+300 into the binary double column. That evaluates to 4356267548.32345E+2, which is 435626754832.345, plus 300 - which is 435626755132.345 (or 4.35626755132345E+011, which becomes 4.3562675513234497E+011 when converted to binary double). That is clearly lower than 4356267548.32345E+100 (or 4.35626754832345E+109, which becomes 4.3562675483234496E+109 when converted to binary double).
Not directly relevant, but you should also be aware that you're providing a decimal number literal, which will be implicitly converted to binary double during insert. So you can't use 4356267548.32345E+300, as that is too large for the number data type. If you want to specify a binary double literal then you need to append a d to it, i.e. 4356267548.32345E+300d; but that is still too large.
The highest you can go with that numeric part is 4356267548.32345E+298d, which evaluates to 4.3562675483234498E+307 - just below the data type limit of 1.79769313486231E+308; and note the loss of precision.
db<>fiddle
I am trying to understand the ARPU calculation in SQL from the following code, however I don't understand why the author has used NUMERIC with revenue in the 2nd query? Won't revenue (meal_price * order quantity) be numeric anyway?
The issue is probably the following. NUMERIC is a specific data type. However, it is not clear that meal_price and order_quantity are specifically NUMERIC -- and not some other type such as INT.
Many databases do integer division for INT, so 1 / 2 is 0 rather than 0.5.
The conversion to NUMERIC is a simple way to avoid integer division.
Of course if a and b are numeric types , a * b will be numeric type
But there are many different numeric types, see
https://www.postgresql.org/docs/13/datatype-numeric.html
NUMERIC is a KEYWORK to specify numeric type of arbitrary précision, see previous link, it's often used to do exact calculations (accouinting) that cannoy be done in foating type.
In your case the author choosed to define the type he wants to use and not let the system/db choose for him. (try to figure out if a and b are integer what shoult be the type of the result 2 * 4 / 3 ?). It's a good practice.
Can you comment on what approach shown below is preferable? I hope the question will not be blocked as "opinionated". I would like to believe there is an explanation that makes that clear.
Context: I have a code for mirroring 3rd party table contents to my own table (optimization). It worked some time flawlessly until the size/modification of the database reached some threshold.
The optimization is based on row version values of more tables, and remembering the maximum of the values from the source tables. This way I am able to update my local table incrementally, much faster than rebuilding it from time to time from scratch.
The problem started to appear when the row-version value exceeded the 4byte value. After some effort, I have spotted that the upper 4 bytes of the binary(8) value were set to 0. Later, the suspect was found to have a form COALESCE(MAX(row_version), 1).
The COALESCE was used to cover the case when the local table is fresh, containing now data -- for comparing the MAX(row_version) of source tables with something meaningful.
The examples to show the bug: To simulate the last mentioned situation, I want to convert the NULL value of the binary(8) column to 1. I am adding also the ISNULL usage that was added later. The original code contained the COALESCE only.
DECLARE #bin8null binary(8) = NULL
SELECT 'bin NULL' AS the_variable, #bin8null AS value
SELECT 'coalesce 1' AS op, COALESCE(#bin8null, 1) AS good_value
SELECT 'coalesce 1 + convert' AS op, CONVERT(binary(8), COALESCE(#bin8null, 1)) AS good_value
SELECT 'isnull 1' AS op, ISNULL(#bin8null, 1) AS good_value
SELECT 'isnull 0x1' AS op, ISNULL(#bin8null, 0x1) AS bad_value
(There is a bug in the image coalesce 0x1 + convert fixed later in the code to coalesce 1 + convert, but not fixed in the image.)
The application bug appeared when the binary value was bigger than the part that could be stored in 4 bytes. Here the 0xAAAAAAAA was used. (Actually, the 0x00000001 was the case, and it was difficult to spot that the single 1 was changed to 0.)
DECLARE #bin8 binary(8) = 0xAAAAAAAA01BB3A35
SELECT 'bin' AS the_variable, #bin8 AS value
SELECT 'coalesce 1' AS op, COALESCE(#bin8, 1) AS bad_value
SELECT 'coalesce 1 + convert' AS op, CONVERT(binary(8), COALESCE(#bin8, 1)) AS bad_value
SELECT 'coalesce 0x1 + convert ' AS op, CONVERT(binary(8), COALESCE(#bin8, 0x1)) AS good_value
SELECT 'isnull 1' AS op, ISNULL(#bin8, 1) AS good_value
SELECT 'isnull 0x1' AS op, ISNULL(#bin8, 0x1) AS good_value
When executed in Microsoft SQL Server Management Studio on MS-SQL Server 2014, the result looks like this:
Description -- my understanding: The COALESCE() seems to derive the type of the result from the type of the last processed argument. This way, the non-NULL binary(8) was converted to int, and that lead to the loss of upper 4 bytes. (See the 2nd and 3rd red bad_value on the picture. The difference between the two cases is only in decimal/hexadecimal form of display.)
On the other hand, the ISNULL() seems to preserve the type of the first argument, and converts the second value to that type. One should be careful to understand that binary(8) is more like a series of bytes. The interpretation as one large integer is only the interpretation. Hence, the 0x1 as the default value does not expand as 8bytes integer and produces bad value.
My solution: So, I have fixed the bug using ISNULL(MAX(row_version), 1). Is that correct?
This is not a bug. They're documented to handle data type precedence differently. COALESCE determines the data type of the output based on examining all of the arguments, while ISNULL has a more simplistic approach of inspecting only the first argument. (Both still need to contain values which are all compatible, meaning they are all possible to convert to the determined output type.)
From the COALESCE topic:
Returns the data type of expression with the highest data type precedence.
The ISNULL topic does not make this distinction in the same way, but implicitly states that the first expression determines the type:
replacement_value must be of a type that is implicitly convertible to the type of check_expression.
I have a similar example (and describe several other differences between COALESCE and ISNULL) here. Basically:
DECLARE #int int, #datetime datetime;
SELECT COALESCE(#int, CURRENT_TIMESTAMP);
-- works because datetime has a higher precedence than the chosen output type, int
2020-08-20 09:39:41.763
GO
DECLARE #int int, #datetime datetime;
SELECT ISNULL(#int, CURRENT_TIMESTAMP);
-- fails because int, the first (and chosen) output type, has a lower precedence than datetimeMsg 257, Level 16, State 3Implicit conversion from data type datetime to int is not allowed. Use the CONVERT function to run this query.
Let me start of by saying:
This is not a "bug".
ISNULL and COALESCE are not the same function, and operate quite differently.
ISNULL takes 2 parameters, and returns the second parameter if the first has a value NULL. If the 2 parameters are different datatypes, then the dataype of the first datatype is returned (implicitly casting the second value).
COALESCE takes 2+ parameters, and returns the first non-NULL parameter. COALESCE is a short hand CASE expression, and uses Data Type Precendence to determine the returned data type.
As a result, this is why ISNULL returns what you expect, there is no implicit conversion in your query for the non-NULL variable.
For the COALESCE there is implicit conversion. binary has the lowest precedence of all the data types, with a rank of 30 (at time of writing). The value 1 is an int, and has a precedence of 16; far higher than 30.
As a result COALESCE(#bin8, 1) will implicitly convert the value 0xAAAAAAAA01BB3A35 to an int and then return that value. You see this as SELECT CONVERT(int,0xAAAAAAAA01BB3A35) returns 29047349, which your first "bad" value; it's not "bad", it's correct for what you wrote.
Then for the latter "bad" value, we can convert that int value (29047349) back to a binary, which results in 0x0000000001BB3A35, which is, again the result you get.
TL;DR: checking return types of functions is important. ISNULL returns the data type of first parameter and will implicitly convert the second if needed. For COALESCE it uses Data Type Precedence, and will implicitly convert the returned value to the data type of with the highest precedence of all the possible return values.
This has been bothering me with my coding continuously and I can't seem to google a good workaround.
I have a number of columns which are data type nvarchar(255). Pretty standard I would assume.
Anyway, I want to run:
DELETE FROM Ranks WHERE ISNULL(INST,0) = 0
where INST is nvarchar(255). I am thrown the error:
Conversion failed when converting the nvarchar value 'Un' to data type int.
which is the first non null in the column. However, I don't care for this showing me the error means it's not null? - I just want to delete the nulls!
Is there something simple I'm missing.
Any help would be fab!
An expression may only be of one type.
Expression ISNULL(INST,0) involves two source types, nvarchar(255) and int. However, no type change happens at this point, because ISNULL is documented to return the type of its first argument (nvarchar), and will convert the second argument to that type if needed, so the entire original expression is equivalent to ISNULL(INST, '0').
Next step is the comparison expression, ISNULL(INST, '0') = 0. It again has nvarchar(255) and int as the source data types, but this time nothing can stop the conversion - in fact, it must happen for the comparison operator, =, to even work. According to the data type precedence list, the int wins, and is chosen as the resulting type of the comparison expression. Hence all values from column INST must be converted to int before the comparison = 0 is made.
If you
just want to delete the nulls
, then just delete the nulls:
DELETE FROM Ranks WHERE INST IS NULL
If for some reason you absolutely have to use isnull in this fashion, which there is no real reason for, then you should have stayed in the realm of strings:
DELETE FROM Ranks WHERE ISNULL(INST, '') = ''
That would have deleted null entries and entries with empty strings (''), just like the WHERE ISNULL(INST, 0) = 0 would have deleted null entries and entries with '0's if all values in INST could have been converted to int.
With ISNULL(INST,0) you are saying: If the string INST is null, replace it with the string 0. But 0 isn't a string, so this makes no sense.
With WHERE ISNULL(INST,0) = 0 you'd access all rows where INST is either NULL or 0 (but as mentioned a string is not an integer).
So what do you want to achieve? Delete all rows where INST is null? That would be
DELETE FROM ranks WHERE inst IS NULL;
SELECT logicalTime, traceValue, unitType, entName
FROM vwSimProjAgentTrace
WHERE valueType = 10
AND agentName ='AtisMesafesi'
AND ( entName = 'Hawk-1')
AND simName IN ('TipSenaryo1_0')
AND logicalTime IN (
SELECT logicalTime
FROM vwSimProjAgentTrace
WHERE valueType = 10 AND agentName ='AtisIrtifasi'
AND ( entName = 'Hawk-1')
AND simName IN ('TipSenaryo1_0')
AND CONVERT(FLOAT , traceValue) > 123
) ORDER BY simName, logicalTime
This is my sql command and table is a view table...
each time i put "convert(float...) part " i get
Msg 8114, Level 16, State 5, Line 1
Error converting data type nvarchar to float.
this error...
One (or more) of the rows has data in the traceValue field that cannot be converted to a float.
Make sure you've used the right combination of dots and commas to signal floating point values, as well as making sure you don't have pure invalid data (text for instance) in that field.
You can try this SQL to find the invalid rows, but there might be cases it won't handle:
SELECT * FROM vwSimProjAgentTrace WHERE NOT ISNUMERIC(traceValue)
You can find the documentation of ISNUMERIC here.
If you look in BoL (books online) at the convert command, you see that a nvarchar conversion to float is an implicit conversion. This means that only "float"-able values can be converted into a float. So, every numeric value (that is within the float range) can be converted. A non-numeric value can not be converted, which is quite logical.
Probably you have some non numeric values in your column. You might see them when you run your query without the convert. Look for something like comma vs dot. In a test scenario a comma instead of a dot gave me some problems.
For an example of isnumeric, look at this sqlfiddle