Why can't one use an output column in the having clause in postgresql? It doesn't change expressivity of the language anyhow, just forces people to rewrite output column definition in having clause. Is a way to avoid that, apart from putting the whole query as a subquery in SELECT * FROM (...) AS t WHERE condition ?
Bacause it's not implemented? And if you're asking why it wasn't implemented, I see 2 possible explanations:
standard doesn't require it
nobody had time to spent on it
if you'd like to have it - mail to -hackers, talk about, and then implement.
Frankly I don't see it as a big problem - it's not like you have 1000 characters to retype.
Related
I am writing dynamic sql code and it would be easier to use a generic where column in (<comma-seperated values>) clause, even when the clause might have 1 term (it will never have 0).
So, does this query:
select * from table where column in (value1)
have any different performance than
select * from table where column=value1
?
All my test result in the same execution plans, but if there is some knowledge/documentation that sets it to stone, it would be helpful.
This might not hold true for each and any RDBMS as well as for each an any query with its specific circumstances.
The engine will translate WHERE id IN(1,2,3) to WHERE id=1 OR id=2 OR id=3.
So your two ways to articulate the predicate will (probably) lead to exactly the same interpretation.
As always: We should not really bother about the way the engine "thinks". This was done pretty well by the developers :-) We tell - through a statement - what we want to get and not how we want to get this.
Some more details here, especially the first part.
I Think this will depend on platform you are using (optimizer of the given SQL engine).
I did a little test using MySQL Server and:
When I query select * from table where id = 1; i get 1 total, Query took 0.0043 seconds
When I query select * from table where id IN (1); i get 1 total, Query took 0.0039 seconds
I know this depends on Server and PC and what.. But The results are very close.
But you have to remember that IN is non-sargable (non search argument able), it will not use the index to resolve the query, = is sargable and support the index..
If you want the best one to use, You should test them in your environment because they both work so good!!
I'm creating result paging based on first letter of certain nvarchar column and not the usual one, that usually pages on number of results.
And I'm not faced with a challenge whether to filter results using LIKE operator or equality (=) operator.
select *
from table
where name like #firstletter + '%'
vs.
select *
from table
where left(name, 1) = #firstletter
I've tried searching the net for speed comparison between the two, but it's hard to find any results, since most search results are related to LEFT JOINs and not LEFT function.
"Left" vs "Like" -- one should always use "Like" when possible where indexes are implemented because "Like" is not a function and therefore can utilize any indexes you may have on the data.
"Left", on the other hand, is function, and therefore cannot make use of indexes. This web page describes the usage differences with some examples. What this means is SQL server has to evaluate the function for every record that's returned.
"Substring" and other similar functions are also culprits.
Your best bet would be to measure the performance on real production data rather than trying to guess (or ask us). That's because performance can sometimes depend on the data you're processing, although in this case it seems unlikely (but I don't know that, hence why you should check).
If this is a query you will be doing a lot, you should consider another (indexed) column which contains the lowercased first letter of name and have it set by an insert/update trigger.
This will, at the cost of a minimal storage increase, make this query blindingly fast:
select * from table where name_first_char_lower = #firstletter
That's because most database are read far more often than written, and this will amortise the cost of the calculation (done only for writes) across all reads.
It introduces redundant data but it's okay to do that for performance as long as you understand (and mitigate, as in this suggestion) the consequences and need the extra performance.
I had a similar question, and ran tests on both. Here is my code.
where (VOUCHER like 'PCNSF%'
or voucher like 'PCLTF%'
or VOUCHER like 'PCACH%'
or VOUCHER like 'PCWP%'
or voucher like 'PCINT%')
Returned 1434 rows in 1 min 51 seconds.
vs
where (LEFT(VOUCHER,5) = 'PCNSF'
or LEFT(VOUCHER,5)='PCLTF'
or LEFT(VOUCHER,5) = 'PCACH'
or LEFT(VOUCHER,4)='PCWP'
or LEFT (VOUCHER,5) ='PCINT')
Returned 1434 rows in 1 min 27 seconds
My data is faster with the left 5. As an aside my overall query does hit some indexes.
I would always suggest to use like operator when the search column contains index. I tested the above query in my production environment with select count(column_name) from table_name where left(column_name,3)='AAA' OR left(column_name,3)= 'ABA' OR ... up to 9 OR clauses. My count displays 7301477 records with 4 secs in left and 1 second in like i.e where column_name like 'AAA%' OR Column_Name like 'ABA%' or ... up to 9 like clauses.
Calling a function in where clause is not a best practice. Refer http://blog.sqlauthority.com/2013/03/12/sql-server-avoid-using-function-in-where-clause-scan-to-seek/
Entity Framework Core users
You can use EF.Functions.Like(columnName, searchString + "%") instead of columnName.startsWith(...) and you'll get just a LIKE function in the generated SQL instead of all this 'LEFT' craziness!
Depending upon your needs you will probably need to preprocess searchString.
See also https://github.com/aspnet/EntityFrameworkCore/issues/7429
This function isn't present in Entity Framework (non core) EntityFunctions so I'm not sure how to do it for EF6.
I designed a set of tables in pgAdmin. I gave names like Products and ProductRID. I was very surprised though when I went to query this table only to find a query like this yielded unknown relation:
select * from Products
Apparently the proper way to access this is
select * from "Products"
which is very ugly. I can rename the tables to all lower case to query without quotes, but then it looks ugly. Is there any kind of a setting so that it will retain the case, but behave without case sensitivity?
No there is no magic setting. The best way to deal with case sensitivity is to not quote your relations when you are creating them. If you are early on in schema design, go ahead and rename them (and column names) to lower case. The "looks ugly" problem will go away because in your queries you can still do
SELECT * FROM Products
and it will work fine.
You may check the relative wiki to get the precise answer
Why are my table and column names not recognized in my query? Why is capitalization not preserved?
Hope it clarifies.
I'm doing a bit of work which requires me to truncate DB2 character-based fields. Essentially, I need to discard all text which is found at or after the first alphabetic character.
e.g.
102048994BLAHBLAHBLAH
becomes:-
102048994
In SQL Server, this would be a doddle - PATINDEX would swoop in and save the day. Much celebration would ensue.
My problem is that I need to do this in DB2. Worse, the result needs to be used in a join query, also in DB2. I can't find an easy way to do this. Is there a PATINDEX equivalent in DB2?
Is there another way to solve this problem?
If need be, I'll hardcode 26 chained LOCATE functions to get my result, but if there is a better way, I am all ears.
SELECT TRANSLATE(lower(column), ' ', 'abcdefghijklmnopqrstuvwxyz')
FROM table
write a small UDF (user defined function) in C or JAVA, that does your task.
Peter
If you've got a very complicated SELECT statement and some records aren't included because of a join, what is the easiest way to debug this and find the reasons why?
Change the JOINS / INNER JOINS to OUTER JOINS and look for NULLs where they shouldn't be.
You could include your ON logic in the WHERE clause, phrase it like this:
WHERE 1=1
AND...
AND...
and just comment out as many of the terms until you isolate the unexpected behaviour.
I don't know if this will help you, but when I find myself with a complex Select that I'm having a hard time maintaining, or debugging, I'll break it up into separate common table expressions (CTE's). I've found this makes many of my queries much easier to understand and maintain.
Binary Search stylee:
If you have 10 joins, comment out the last 5.
Still have the problem? comment out the last 2/3 joins that are still uncommented
Still have the problem? comment out the last 1/2 joins that are still uncommented
Do this until you get down to it working, then the problem will lie in the last joins you commented out.
Yes you could do them one at a time but this is usually quicker.
Obviously you will have to comment out all the columns not used in the select statement, but I normally just put /* */ around all the columns, then put a * instead.
Just look at the number of results returned.