Is there any difference between DECIMAL and NUMERIC in BigQuery? - google-bigquery

Official Documentation just tells us that "DECIMAL is an alias for NUMERIC". Is there any differences?

There is no difference semantically. If we have to name one difference, it could be that if you check the table schema (through UI or INFORMATION_SCHEMA), only NUMERIC will ever appear, which is why DECIMAL is only a alias not a real type.

Related

Checking SQLite value type - numeric vs. textual

Is it possible to filter SQLite column values in SQL based on whether the value is numeric or textual? I have seen references to using CAST for this purpose. However, it appears to be useless as SELECT CAST('1a' AS NUMERIC) passes the check for a numeric type.
The typeof() SQL function is designated for type checking. However, its result depends on both column type definition (according to the official docs) and the format used during insertion. For example, when a number is inserted as a text literal into a NUMERIC column, it is converted into a number if possible, and typeof() will return an appropriate numeric type or text, if conversion did not occur. The TEXT column, on the other hand, stores all numeric literals as text. BLOB column stores textual and numeric literals without interpretation. Therefore, a mixed-type column should be probably declared as BLOB or NUMERIC (depending on whether textual literals needs to be converted to numbers, if possible). With this behavior in mind, typeof() is well suitable for type checking.
Thats just an idea:
SELECT [FilterColumn] FROM [Table] WHERE [FilterColumn]='0' OR (ceiling(log([FilterColumn],10)) =LENGTH([FilterColumn]) AND CAST([FilterColumn] AS INTEGER)>0)
This works for integer numbers where number of digits=log([FilterColumn],10). To distinguish a single letter from casting to 0, [FilterColumn]='0' OR [FilterColumn]>0 included.
I suppose there are more elegant solutions

Implicit casting when joining fields of different types

I am joining a field that has single digit numbers formatted with a leading 0 to another that does not have leading 0's. When I realized this I tested my query out only to find that it was actually working perfectly. Then I realized what I'd done... I had joined an nvarchar field to an int field. I would have thought sql would have given me an error for this but apparently it converts the character field to an int field for me.
I realize this is probably not a good practice and I plan to explicitly cast it myself now, but I'm just curious if there are rules for how SQL decides which field to cast in these situations. What's to keep it from casting the int field to a character type instead (in which case my query would no longer work properly)?
There are rules indeed.
CAST and CONVERT (Transact-SQL) to learn what can be converted to what ("Implicit Conversions" section).
Data Type Precedence (Transact-SQL) to learn what will be converted to what unless specifically asked.

SQL - Numeric data type with leading zeros

I need to store Medicare APC codes. I believe the format requires 4 numbers. Leading zeros are relevant. Is there any way to store this data type with verification? How should I store this data (varchar(4), int)?
This kind of issue, storing zero leading numbers that need to be treated as Numeric values on some scenarios (i.e. sorting) and as textual values in others (i.e. addresses) is always a pain and there is no one answer that is best for all users. At my company we have a database that stores numbers as text for codes (not Medicare APC codes) and we must pad them with zero’s so they will sort properly when used in an order operation.
Do not use a numeric data type for this because the item is not a true number but textual data that uses numeric characters. You will not be performing any calculations or aggregates on the codes and so the only benefit to storing them as a number would be to ensure proper sorting of the codes and that can be done with the code stored as text by padding it with zeros where needed. If you sue a numeric data type then any time the code is combined with other textual values you will have to explicitly convert it to CHAR/VARCHAR or let SQL Server do it since implicit conversions should always be avoided that means a lot of extra work for you and the query processor any time the code is used.
Assuming you decide to go with a textual data type the question then is should you use VARCHAR or CHAR and while many who have posted say VARCHAR I would suggest you go with CHAR set to a length of 4. WHY?
The VARCHAR data type is for textual data in which the size (the length or number of characters) is unknown in advance. For this Medicare code we know the length will always be at least 4 and possibly no more than 4 for the foreseeable future. SQL Server handles the storage of the data differently between CHAR and VARCHAR. SQL Server’s BOL (Books On Line) says :
Use CHAR when the size of the column data entries are consistent
Use VARCHAR when the size of the column data varies considerably.
I can’t say for certain this is true for SQL Server 2008 and up but for earlier versions, the use of a VARCHAR data type carries an extra overhead of 1 byte per row of data per column in a table that has a VARCHAR data type. If the data stored is always the same size and in your scenario it sounds like it is then this extra byte is a waste.
In the end it’s up to you as to whether you like CHAR or VARCHAR better but definitely don’t use a numeric data type to store a fixed length code.
That's not numeric data; it's textual data that happens to contain digits.
Use a VARCHAR.
I agree, using
CHAR(4)
for the check constraint use
check( APC_ODE LIKE '[0-9][0-9][0-9][0-9]' )
This will force a 4 digit number only to be accepted...
varchar(4)
optionally, you can still add a check constraint to ensure the data is numeric with leading zeros. This example will throw exceptions in Oracle. In other RDBMS, you could use regular expression checks:
alter table X add constraint C
check (cast(APC_CODE as int) = cast(APC_CODE as int))
If you are certain that the APC codes will always be numeric (that is if it wouldn't change in the near future), a better way would be to leave the database column as is, and handle the formatting (to include leading zeros) at places where you use this field values.
If you need leading 0s, then you must use a varchar or other string data type.
There are ways to format the output for leading 0s without compromising your actual data.
See this blog entry for an easy method.
CHAR(4) seems more appropriate to me (if I understood you right, and the code is always 4 digits).
What you want to use is a VARCHAR data type with a CHECK constraint, using LIKE with a pattern to check for numeric values.
in TSQL
check( isnumeric(APC_ODE) = 1)

SQL Server join question

This is on Microsoft SQL Server. We have a query where we are trying to join two tables on fields containing numeric data.
One table has the field defined as numeric(18,2) and the other table has the field defined as decimal(24,4). When joining with the native data types, the query hangs and we run out of patience before it will finish (left it running 6 min…). So we tried casting the two fields to be both numeric(18,2) and the query finished in under 10 seconds. So we tried casting the two fields to be both decimal(18,2) and again the query hangs. Does anyone know the difference between the decimal and numeric data types that would make them perform so differently?
DECIMAL and NUMERIC datatypes are the one and the same thing in SQL Server.
Quote from BOL:
Numeric data types that have fixed
precision and scale.
decimal[ (p[ ,s] )] and numeric[ (p[
,s] )] Fixed precision and scale
numbers. When maximum precision is
used, valid values are from - 10^38 +1
through 10^38 - 1. The ISO synonyms
for decimal are dec and dec(p, s).
numeric is functionally equivalent to
decimal.
From that, I'm surprised to hear of a difference. I'd expect the execution plans to be the same between the 2 routes, can you check?
Why are you using two datatypes to begin with? If they contain the same type of data (and joining on them implies they do), they should be the same datatype. Fix this and all your problems go away. Why waste server resources continually casting to match two fields that should be defined the same?
You of course may need to adjust the input variables for any insert or update queries to match waht you chose as the datatype.
My guess is that it's not a matter of a specific difference between the two data types, but simply the fact that SQL Server needs to implicitly convert them to match for the join operation.
I don't know why there would be a difference from your first query and the second, where you explicitly convert, but I can see why there might be a problem when you convert to a datatype that doesn't match and then SQL Server has to implicitly convert them anyway (as in your third case). Maybe in the first case, SQL Server is implicitly converting both to decimal(24,4) so as not to lose data and that operation takes longer than converting the other way. Have you tried explicitly converting the numeric(18,2) to a decimal(24,4)?

Difference between DECIMAL and NUMERIC

What's the difference between the SQL datatype NUMERIC and DECIMAL ?
If databases treat these differently, I'd like to know how for at least:
SQL Server
Oracle
Db/2
MySQL
PostgreSQL
Furthermore, are there any differences in how database drivers interpret these types?
They are the same for almost all purposes.
At one time different vendors used different names (NUMERIC/DECIMAL) for almost the same thing. SQL-92 made them the same with one minor difference which can be vendor specific:
NUMERIC must be exactly as precise as it is defined — so if you define 4 decimal places to the left of the decimal point and 4 decimal places to the right of it, the DB must always store 4 + 4 decimal places, no more, no less.
DECIMAL is free to allow higher numbers if that's easier to implement. This means that the database can actually store more digits than specified (due to the behind-the-scenes storage having space for extra digits). This means the database might allow storing 12345.0000 in the above example of 4 + 4 decimal places, but storing 1.00005 is still not allowed if doing so could affect any future calculations.
Most current database systems treat DECIMAL and NUMERIC either as perfect synonyms, or as two distinct types with exactly the same behavior. If the types are considered distinct at all, you might not be able to define a foreign key constrain on a DECIMAL column referencing a NUMERIC column or vice versa.
They are synonyms, no difference at all.
At least on SQL Server in the ANSI SQL standards.
This SO answer shows some difference in ANSI but I suspect in implementation they are the same
Postgres: No difference
in documentation description in table 8.1 looks same, yet it is not explained why it is mentioned separately, so
according to Tom Lane post
There isn't any difference, in
Postgres. There are two type names because the SQL standard requires
us to accept both names. In a quick look in the standard it appears
that the only difference is this:
17)NUMERIC specifies the data type exact numeric, with the decimal
precision and scale specified by the <precision> and <scale>.
18)DECIMAL specifies the data type exact numeric, with the decimal
scale specified by the <scale> and the implementation-defined
decimal precision equal to or greater than the value of the
specified <precision>.
ie, for DECIMAL the implementation is allowed to allow more digits
than requested to the left of the decimal point. Postgres doesn't
exercise that freedom so there's no difference between these types for
us.
regards, tom lane
also a page lower docs state clearly, that
The types decimal and numeric are equivalent. Both types are part of
the SQL standard.
and also at aliases table decimal [ (p, s) ] is mentioned as alias for numeric [ (p, s) ]
They are actually equivalent, but they are independent types, and not technically synonyms, like ROWVERSION and TIMESTAMP - though they may have been referred to as synonyms in the documentation at one time. That is a slightly different meaning of synonym (e.g. they are indistinguishable except in name, not one is an alias for the other). Ironic, right?
What I interpret from the wording in MSDN is actually:
These types are identical, they just have different names.
Other than the type_id values, everything here is identical:
SELECT * FROM sys.types WHERE name IN (N'numeric', N'decimal');
I have absolutely no knowledge of any behavioral differences between the two, and going back to SQL Server 6.5, have always treated them as 100% interchangeable.
for DECIMAL(18,2) and NUMERIC(18,2)? Assigning one to the other is technically a "conversion"?
Only if you do so explicitly. You can prove this easily by creating a table and then inspecting the query plan for queries that perform explicit or - you might expect - implicit conversions. Here's a simple table:
CREATE TABLE [dbo].[NumDec]
(
[num] [numeric](18, 0) NULL,
[dec] [decimal](18, 0) NULL
);
Now run these queries and capture the plan:
DECLARE #num NUMERIC(18,0);
DECLARE #dec DECIMAL(18,0);
SELECT
CONVERT(DECIMAL(18,0), [num]), -- conversion
CONVERT(NUMERIC(18,0), [dec]) -- conversion
FROM dbo.NumDec
UNION ALL SELECT [num],[dec]
FROM dbo.NumDec WHERE [num] = #dec -- no conversion
UNION ALL SELECT [num],[dec]
FROM dbo.NumDec WHERE [dec] = #num; -- no conversion
we have explicit conversions where we asked for them, but no explicit conversions where we might have expected them. Seems the optimizer is treating them as interchangeable, too.
Personally, I prefer to use the term DECIMAL just because it's much more accurate and descriptive. BIT is "numeric" too.