Assume mytable is an Oracle table and it has a field called id. The datatype of id is NUMBER(8). Compare the following queries:
select * from mytable where id like '715%'
and
select * from mytable where id between 71500000 and 71599999
I would think the second is more efficient since I think "number comparison" would require fewer number of assembly language instructions than "string comparison". I need a confirmation or correction. Please confirm/correct and throw any further comment related to either operator.
UPDATE: I forgot to mention 1 important piece of info. id in this case must be an 8-digit number.
If you only want values between 71500000 and 71599999 then yes the second one is much more efficient. The first one would also return values between 7150-7159, 71500-71599 etc. and so forth. You would either need to sift through unecessary results or write another couple lines of code to filter the rest of them out. The second option is definitely more efficient for what you seem to want to do.
It seems like the execution plan on the second query is more efficient.
The first query is doing a full table scan of the id's, whereas the second query is not.
My Test Data:
Execution Plan of first query:
Execution Plan of second query:
I don't like the idea of using LIKE with a numeric column.
Also, it may not give the results you are looking for.
If you have a value of 715000000, it will show up in the query result, even though it is larger than 71599999.
Also, I do not like between on principle.
If a thing is between two other things, it should not include those two other things. But this is just a personal annoyance.
I prefer to use >= and <= This avoids confusion when I read the query. In addition, sometimes I have to change the query to something like >= a and < c. If I started by using the between operator, I would have to rewrite it when I don't want to be inclusive.
Harv
In addition to the other points raised, using LIKE in the manner you suggest would cause Oracle to not use any indexes on the ID column due to the implicit conversion of the data from number to character, resulting in a full table scan when using LIKE versus and index range scan when using BETWEEN. Assuming, of course, you have an index on ID. Even if you don't, however, Oracle will have to do the type conversion on each value it scans in the LIKE case, which it won't have to do in the other.
You can use math function, otherwise you have to use to_char function to use like, but it will cause performance problems.
select * from mytable where floor(id /100000) = 715
or
select * from mytable where floor(id /100000) = TO_NUMBER('715') // this is parametric
Related
I have a problem where the fix is to exchange what gets filtered first, but I'm not sure if that is even possible and not knowledgeable enough how it works.
To give an example:
Here is a table
When you filter this using the ff query:
select * from pcparts where Parts = 'Monitor' and id = 255322 and Brand = 'Asus'
by logic this will be correct as the Asus component with a character in its ID will be filtered and will prevent an ORA-01722 error.
But to my experience this is inconsistent.
I tried using the same filtering in two different DB connections, the first one didn't get the error (as expected) but other one got an ORA-01722 error.
Checking the explain plan the difference in the two DB's is the ff:
I was thinking if its possible to make sure that the Parts got filtered first before the ID but I'm unable to find anything when i was searching, is this even possible, if not, what is a fix for this issue without relying on using TO_CHAR
I assume you want to (sort of) fix a buggy program without changing the source code.
According to your image, you are using "Filter Predicates", this normally means Oracle isn't using index (though I don't know what displays execution plans this way).
If you have an index on PARTS, Oracle will probably use this index.
create index myindex on mytable (parts);
If Oracle thinks this index is inefficient, it may still use full table scan. You may try to 'fake' Oracle into thinking this an efficient index by lying about the number of distinct values (the more distinct values, the more efficient)
exec dbms_stats.set_index_stats(ownname => 'myname', indname => 'myindex', numdist => 100000000)
Note: This WILL impact performance of other querys using this table
"Fix" is rather simple: take control over what you're doing.
It is evident that ID column's datatype is VARCHAR2. Therefore, don't make Oracle guess, instruct it what to do.
No : select * from pcparts where Parts = 'Monitor' and id = 255322 and Brand = 'Asus'
Yes: select * from pcparts where Parts = 'Monitor' and id = '255322' and Brand = 'Asus'
--------
VARCHAR2 column's value enclosed into single quotes
I have Users table contains about 500,000 rows of users data
The Full Name of the User is stored in 4 columns each have type nvarchar(50)
I have a computed column called UserFullName that's equal to the combination of the 4 columns
I have a Stored Procedure searching in Users table by name using like operatior as below
Select *
From Users
Where UserFullName like N'%'+#FullName+'%'
I have a performance issue while executing this SP .. it take long time :(
Is there any way to overcome the lack of performance of using Like operator ?
Not while still using the like operator in that fashion. The % at the start means your search needs to read every row and look for a match. If you really need that kind of search you should look into using a full text index.
Make sure your computed column is indexed, that way it won't have to compute the values each time you SELECT
Also, depending on your indexing, using PATINDEX might be quicker, but really you should use a fulltext index for this kind of thing:
http://msdn.microsoft.com/en-us/library/ms187317.aspx
If you are using index it will be good.
So you can give the column an id or something, like this:
Alter tablename add unique index(id)
Take a look at that article http://use-the-index-luke.com/sql/where-clause/searching-for-ranges/like-performance-tuning .
It easily describes how LIKE works in terms of performance.
Likely, you are facing such issues because your whole table shoould be traversed because of first % symbol.
You should try creating a list of substrings(in a separate table for example) representing k-mers and search for them without preceeding %. Also, an index for such column would help. Please read more about KMer here https://en.m.wikipedia.org/wiki/K-mer .
This will not break an index and will be more efficient to search.
I suppose I have always naively assumed that scalar functions in the select part of a SQL query will only get applied to the rows that meet all the criteria of the where clause.
Today I was debugging some code from a vendor and had that assumption challenged. The only reason I can think of for this code failing is that the Substring() function is getting called on data that should have been filtered out by the WHERE clause. But it appears that the substring call is being applied before the filtering happens, the query is failing.
Here is an example of what I mean. Let's say we have two tables, each with 2 columns and having 2 rows and 1 row respectively. The first column in each is just an id. NAME is just a string, and NAME_LENGTH tells us how many characters in the name with the same ID. Note that only names with more than one character have a corresponding row in the LONG_NAMES table.
NAMES: ID, NAME
1, "Peter"
2, "X"
LONG_NAMES: ID, NAME_LENGTH
1, 5
If I want a query to print each name with the last 3 letters cut off, I might first try something like this (assuming SQL Server syntax for now):
SELECT substring(NAME,1,len(NAME)-3)
FROM NAMES;
I would soon find out that this would give me an error, because when it reaches "X" it will try using a negative number for in the substring call, and it will fail.
The way my vendor decided to solve this was by filtering out rows where the strings were too short for the len - 3 query to work. He did it by joining to another table:
SELECT substring(NAMES.NAME,1,len(NAMES.NAME)-3)
FROM NAMES
INNER JOIN LONG_NAMES
ON NAMES.ID = LONG_NAMES.ID;
At first glance, this query looks like it might work. The join condition will eliminate any rows that have NAME fields short enough for the substring call to fail.
However, from what I can observe, SQL Server will sometimes try to calculate the the substring expression for everything in the table, and then apply the join to filter out rows. Is this supposed to happen this way? Is there a documented order of operations where I can find out when certain things will happen? Is it specific to a particular Database engine or part of the SQL standard? If I decided to include some predicate on my NAMES table to filter out short names, (like len(NAME) > 3), could SQL Server also choose to apply that after trying to apply the substring? If so then it seems the only safe way to do a substring would be to wrap it in a "case when" construct in the select?
Martin gave this link that pretty much explains what is going on - the query optimizer has free rein to reorder things however it likes. I am including this as an answer so I can accept something. Martin, if you create an answer with your link in it i will gladly accept that instead of this one.
I do want to leave my question here because I think it is a tricky one to search for, and my particular phrasing of the issue may be easier for someone else to find in the future.
TSQL divide by zero encountered despite no columns containing 0
EDIT: As more responses have come in, I am again confused. It does not seem clear yet when exactly the optimizer is allowed to evaluate things in the select clause. I guess I'll have to go find the SQL standard myself and see if i can make sense of it.
Joe Celko, who helped write early SQL standards, has posted something similar to this several times in various USENET newsfroups. (I'm skipping over the clauses that don't apply to your SELECT statement.) He usually said something like "This is how statements are supposed to act like they work". In other words, SQL implementations should behave exactly as if they did these steps, without actually being required to do each of these steps.
Build a working table from all of
the table constructors in the FROM
clause.
Remove from the working table those
rows that do not satisfy the WHERE
clause.
Construct the expressions in the
SELECT clause against the working table.
So, following this, no SQL dbms should act like it evaluates functions in the SELECT clause before it acts like it applies the WHERE clause.
In a recent posting, Joe expands the steps to include CTEs.
CJ Date and Hugh Darwen say essentially the same thing in chapter 11 ("Table Expressions") of their book A Guide to the SQL Standard. They also note that this chapter corresponds to the "Query Specification" section (sections?) in the SQL standards.
You are thinking about something called query execution plan. It's based on query optimization rules, indexes, temporaty buffers and execution time statistics. If you are using SQL Managment Studio you have toolbox over your query editor where you can look at estimated execution plan, it shows how your query will change to gain some speed. So if just used your Name table and it is in buffer, engine might first try to subquery your data, and then join it with other table.
I was curious since i read it in a doc. Does writing
select * from CONTACTS where id = ‘098’ and name like ‘Tom%’;
speed up the query as oppose to
select * from CONTACTS where name like ‘Tom%’ and id = ‘098’;
The first has an indexed column on the left side. Does it actually speed things up or is it superstition?
Using php and mysql
Check the query plans with explain. They should be exactly the same.
This is purely superstition. I see no reason that either query would differ in speed. If it was an OR query rather than an AND query however, then I could see that having it on the left may spped things up.
interesting question, i tried this once. query plans are the same (using EXPLAIN).
but considering short-circuit-evaluation i was wondering too why there is no difference (or does mysql fully evaluate boolean statements?)
You may be mis-remembering or mis-reading something else, regarding which side the wildcards are on a string literal in a Like predicate. Putting the wildcard on the right (as in yr example), allows the query engine to use any indices that might exist on the table column you are searching (in this case - name). But if you put the wildcard on the left,
select * from CONTACTS where name like ‘%Tom’ and id = ‘098’;
then the engine cannot use any existing index and must do a complete table scan.
Suppose that two tables exist: users and groups.
How does one provide "simple search" in which a user enters text and results contain both users and groups whose names contain the text?
The result of the search must distinguish between the two types.
The trick is to combine a UNION with a literal string to determine the type of 'object' returned. In most (?) cases, UNION ALL will be more efficient, and should be used unless duplicates are required in the sub-queries. The following pattern should suffice:
SELECT "group" type, name
FROM groups
WHERE name LIKE "%$text%"
UNION ALL
SELECT "user" type, name
FROM users
WHERE name LIKE "%$text%"
NOTE: I've added the answer myself, because I came across this problem yesterday, couldn't find a good solution, and used this method. If someone has a better approach, please feel free to add it.
If you use "UNION ALL" then the db doesn't try to remove duplicates - you won't have duplicates between the two queries anyway (since the first column is different), so UNION ALL will be faster.
(I assume that you don't have duplicates inside each query that you want to remove)
Using LIKE will cause a number of problems as it will require a table scan every single time when the LIKE comparator starts with a %. This forces SQL to check every single row and work it's way, byte by byte, through the string you are using for comparison. While this may be fine when you start, it quickly causes scaling issues.
A better way to handle this is using Full Text Search. While this would be a more complex option, it will provide you with better results for very large databases. Then you can use a functioning version of the example Bobby Jack gave you to UNION ALL your two result sets together and display the results.
I would suggest another addition
SELECT "group" type, name
FROM groups
WHERE UPPER(name) LIKE UPPER("%$text%")
UNION ALL
SELECT "user" type, name
FROM users
WHERE UPPER(name) LIKE UPPER("%$text%")
You could convert $text to upper case first or do just do it in the query. This way you get a case insensitive search.