Partial Searching Two Text Fields on SQL Azure - Best Practice - sql-server

I am trying to ascertain the best way of implementing a partial search on two columns within a table. The aim is to have this search perform as quickly as possible.
Our issue is that our database is hosted on SQL Azure; which does not support FullTextIndexing. This means the only native commands available to us in SQL are CHARINDEX() and LIKE '% %'.
The structure of the query if we were to do it in pure T-SQL would be:
DECLARE #SearchTerm VarChar(255) = 'Luke'
SELECT AU.UserID,
AU.FirstName,
AU.Surname
FROM dbo.Users AU
WHERE AU.FirstName LIKE '%'+#SearchTerm+'%'
OR AU.Surname LIKE '%'+#SearchTerm+'%'
Also available to us is the ability to use Lucene; we already have it set up on a Worker Role on Windows Azure however we would have to maintain the integrity of the data both inside the database and within Lucene.
What I want to find out is:
Is there a better way of performing a LIKE search in T-SQL than what I am using above
If I added a Calculated Column to the table containing both the first and last names would this improve the performance of the query?
Alternatively; if we move to Lucene; would the read performance be that much greater than the above query? (In regards to this; there is under 10,000 rows currently in the dbo.Users table)
Throwing the doors open; is there some method we haven't considered that would make this a whole load easier?

Adding a calculated column containing both first and last names will force the results to contain both the first and the last name, but your SQL above is for matching either the first OR the last name.
If you want to match first AND last name, a calculated column may be faster as there are tricks the database programmer can apply for you (example: Boyer-Moore fast string searching, which gets faster as the pattern size increases).
My experience with Lucene is that it is significantly faster than any database search -- I've seen nothing faster on everyday hardware. But as you say, you will have to keep the Lucene index in sync with the database.

Related

Optimization problems with View using Clustered Index Insert on tempdb on SQL Server 2008

I am creating a Java function that needs to use a SQL query with a lot of joins before doing a full scan of its result. Instead of hard-coding a lot of joins I decided to create a view with this complex query. Then the Java function just uses the following query to get this result:
SELECT * FROM VW_####
So the program is working fine but I want to make it faster since this SELECT command is taking a lot of time. After taking a look on its plan execution plan I created some indexes and made it +-30% faster but I want to make it faster.
The problem is that every operation in the execution plan have cost between 0% and 4% except one operation, a clustered-index insert that has +-50% of the execution cost. I think that the system is using a temporary table to store the view's data, but an index in this view isn't useful for me because I need all rows from it.
So what can I do to optimize that insert in the CWT_PrimaryKey? I think that I can't turn off that index because it seems to be part of the SQL Server's internals. I read somewhere that this operation could appear when you use cursors but I think that I am not using (or does the view use it?).
The command to create the view is something simple (no T-SQL, no OPTION, etc) like:
create view VW_#### as SELECTS AND JOINS HERE
And here is a picture of the problematic part from the execution plan: http://imgur.com/PO0ZnBU
EDIT: More details:
Well the query to create the problematic view is a big query that join a lot of tables. Based on a single parameter the Java-Client modifies the query string before creating it. This view represents a "data unit" from a legacy Database migrated to the SQLServer that didn't had any Foreign or Primary Key, so our team choose to follow this strategy. Because of that the view have more than 50 columns and it is made from the join of other seven views.
Main view's query (with a lot of Portuguese words): http://pastebin.com/Jh5vQxzA
The other views (from VW_Sintese1 until VW_Sintese7) are created like this one but without using extra views, they just use joins with the tables that contain the data requested by the main view.
Then the Java Client create a prepared Statement with the query "Select * from VW_Sintese####" and execute it using the function "ExecuteQuery", something like:
String query = "Select * from VW_Sintese####";
PreparedStatement ps = myConn.prepareStatement(query,ResultSet.TYPE_SCROLL_INSENSITIVE, ResultSet.CONCUR_READ_ONLY);
ResultSet rs = ps.executeQuery();
And then the program goes on until the end.
Thanks for the attention.
First: you should post the code of the view along with whatever is using the views because of the rest of this answer.
Second: the definition of a view in SQL Server is later used to substitute in querying. In other words, you created a view, but since (I'm assuming) it isn't an indexed view, it is the same as writing the original, long SELECT statement. SQL Server kind of just swaps it out in the DML statement.
From Microsoft's 'Querying Microsoft SQL Server 2012': T-SQL supports the following table expressions: derived tables, common table expressions (CTEs), views, inline table-valued functions.
And a direct quote:
It’s important to note that, from a performance standpoint, when SQL Server optimizes
queries involving table expressions, it first unnests the table expression’s logic, and therefore interacts with the underlying tables directly. It does not somehow persist the table expression’s result in an internal work table and then interact with that work table. This means that table expressions don’t have a performance side to them—neither good nor
bad—just no side.
This is a long way of reinforcing the first statement: please include the SQL code in the view and what you're actually using as the SELECT statement. Otherwise, we can't help much :) Cheers!
Edit: Okay, so you've created a view (no performance gain there) that does 4-5 LEFT JOIN on to the main view (again, you're not helping yourself out much here by eliminating rows, etc.). If there are search arguments you can use to filter down the resultset to fewer rows, you should have those in here. And lastly, you're ordering all of this at the top, so your query engine will have to get those views, join them up to a massive SELECT statement, figure out the correct order, and (I'm guessing here) the result count is HUGE and SQL's db engine is ordering it in some kind of temporary table.
The short answer: get less data (fewer columns and only the rows you need); don't order the results if the resultset is very large, just get the data to the client and then sort it there.
Again, if you want more help, you'll need to post table schemas and index strategies for all tables that are in the query (including the views that are joined) and you'll need to include all view definitions (including the views that are joined).

MSSQL/Oracle Query Tuning 500,000+ records Coldfusion - does lower() reduce performance

I'm not trying to start a debate on which is better in general, I'm asking specifically to this question. :)
I need to write a query to pull back a list of userid (uid) from a database containing 500k+ records. I'm returning just the one field, uid. I can query either our Oracle box or our MSSQL 2000 box. The query looks like this (this has not been simplied)
select uid
from employeeRec
where uid = 'abc123'
Yes, it really is that simply of a query. Where I need the tuninig help is that the uid is indexed and some uid could be (not many but some) 'ABC123' or 'abc123'. MSSQL doesn't care of the case-sensitivity whereas Oracle does. So for Oracle, my query would look like this:
select uid
from employeeRec
where lower(uid) = 'abc123'
I've learned that if you use lower on an index field in MSSQL, you render the index useless (there are ways around it but that is beyond the scope of my question here - since if I choose MSSQL, I don't need to use lower at all). I wanted to know if I choose Oracle, and use the lower() function, will that also hurt performance of the query?
I'm looping over this query about 200 times in addition to some other queries that are being run and to process the entire loop takes 1 second per iteration and I've narrowed down the slowness to this particular query. For a web page, 200 seconds seems like eternity. For you CF readers, timeout value has been increased so the page doesn't error out and there are no page errors, I'm just trying to speed up this query.
Another item to note: This database is in a different city than the other queries being run so I do expect some lag time there.
As TomTom put, your index will simply not be used by Oracle. But, you can create a function based index, and this new index will be used when you issue your query.
create index my_new_ix on employeeRec(lower(uid));
Wrapping an indexed column in a function call would have the potential to cause performance problems in Oracle. Oracle couldn't use a plain index on UID to process your query. On the other hand, you could create a function-based index on lower(uid) that would be used by the query, i.e.
CREATE INDEX case_insensitive_idx
ON employeeRec( lower( uid ) );
Note that if you want to do case-insensitive queries in general, you may be better served setting NLS parameters to force case-insensitivity. You'd still need function-based indexes on the columns you're searching on, but it can simplify your queries a bit.
I wanted to know if I choose Oracle,
and use the lower() function, will
that also hurt performance of the
query?
Yes. The perforamnce reduction is because the index is on the original value and the collation i case sensitive, so all possible values must be run through the function to filter out the ones matching.

Creating an index on a view with OpenQuery

SQL Server doesn't allow creating an view with schema binding where the view query uses OpenQuery as shown below.
Is there a way or a work-around to create an index on such a view?
The best you could do would be to schedule a periodic export of the AD data you are interested in to a table.
The table could of course then have all the indexes you like. If you ran the export every 10 minutes and the possibility of getting data that is 9 minutes and 59 seconds out of date is not a problem, then your queries will be lightning fast.
The only part of concern would be managing locking and concurrency during the export time. One strategy might be to export the data into a new table and then through renames swap it into place. Another might be to use SYNONYMs (SQL 2005 and up) to do something similar where you just point the SYNONYM to two alternating tables.
The data that supplies the query you're performing comes from a completely different system outside of SQL Server. There's no way that SQL Server can create an indexed view on data it does not own. For starters, how would it be notified when something had been changed so it could update its indexes? There would have to be some notification and update mechanism, which is implausible because SQL Server could not reasonably maintain ACID for such a distributed, slow, non-SQL server transaction to an outside system.
Thus my suggestion for mimicking such a thing through your own scheduled jobs that refresh the data every X minutes.
--Responding to your comment--
You can't tell whether a new user has been added without querying. If Active Directory supports some API that generates events, I've never heard of it.
But, each time you query, you could store the greatest creation time of all the users in a table, then through dynamic SQL, query only for new users with a creation date after that. This query should theoretically be very fast as it would pull very little data across the wire. You would just have to look into what the exact AD field would be for the creation date of the user and the syntax for conditions on that field.
If managing the dynamic SQL was too tough, a very simple vbscript, VB, or .Net application could also query active directory for you on a schedule and update the database.
Here are the basics for Indexed views and thier requirements. Note what you are trying to do would probably fall in the category of a Derived Table, therefore it is not possible to create an indexed view using "OpenQuery"
This list is from http://www.sqlteam.com/article/indexed-views-in-sql-server-2000
1.View definition must always return the same results from the same underlying data.
2.Views cannot use non-deterministic functions.
3.The first index on a View must be a clustered, UNIQUE index.
4.If you use Group By, you must include the new COUNT_BIG(*) in the select list.
5.View definition cannot contain the following
a.TOP
b.Text, ntext or image columns
c.DISTINCT
d.MIN, MAX, COUNT, STDEV, VARIANCE, AVG
e.SUM on a nullable expression
f.A derived table
g.Rowset function
h.Another view
i.UNION
j.Subqueries, outer joins, self joins
k.Full-text predicates like CONTAIN or FREETEXT
l.COMPUTE or COMPUTE BY
m.Cannot include order by in view definition
In this case, there is no way for SQL Server to know of any changes (data, schema, whatever) in the remote data source. For a local table, it can use SCHEMABINDING etc to ensure the underlying tables(s) stay the same and it can track datachanges.
If you need to query the view often, then I'd use a local table that is refreshed periodically. In fact, I'd use a table anyway. AD queries are't the quickest at the best of times...

What is a maintainable way to store large text fields without sacrificing performance?

I have been dancing around this issue for awhile but it keeps coming up. We have a system and our may of our tables start with a description that is originally stored as an NVARCHAR(150) and I then we get a ticket asking to expand the field size to 250, then 1000 etc, etc...
This cycle is repeated on ever "note" field and/or "description" field we add to most tables. Of course the concern for me is performance and breaking the 8k limit of the page. However, my other concern is making the system less maintainable by breaking these fields out of EVERY table in the system into a lazy loaded reference.
So here I am faced with these same to 2 options that have been staring me in the face. (others are welcome) please lend me your opinions.
Change all may notes and/or descriptions to NVARCHAR(MAX) and make sure we do exclude these fields in all listings. Basically never do a: SELECT * FROM [TableName] unless is it only retrieving one record.
Remove all notes and/or description fields and replace them with a forign key reference to a [Notes] table.
CREATE TABLE [dbo].[Notes] (
[NoteId] [int] NOT NULL,
[NoteText] [NVARCHAR](MAX)NOT NULL )
Obviously I would prefer use option 1 because it will change so much in our system if we go with 2. However if option 2 is really the only good way to proceed, then at least I can say these changes are necessary and I have done the homework.
UPDATE:
I ran several test on a sample database with 100,000 records in it. What I find is that the because of cluster index scans the IO required for option 1 is "roughly" twice that of option 2. If I select a large number of records (1000 or more) option 1 is twice as slow even if I do not include the large text field in the select. As I request less rows the lines blur more. I a web app where page sizes of 50 or so are the norm, so option 1 will work, but I will be converting all instances to option 2 in the (very) near future for scalability.
Option 2 is better for several reasons:
When querying your tables, the large
text fields fill up pages quickly,
forcing the database to scan more
pages to retrieve data. This is
especially taxing when you don't
actually need to return the text
data.
As you mentioned, it gives you
a clean break to change the data
type in one swoop. Microsoft has
deprecated TEXT in SQL Server 2008,
so you should stick with
VARCHAR/VARBINARY.
Separate filegroups. Having
all your text data in a slower,
cheaper storage location might be
something you decide to pursue in
the future. If not, no harm, no
foul.
While Option 1 is easier for now, Option 2 will give you more flexibility in the long-term. My suggestion would be to implement a simple proof-of-concept with the "notes" information separated from the main table and perform some of your queries on both examples. Compare the execution plans, client statistics and logical I/O reads (SET STATISTICS IO ON) for some of your queries against these tables.
A quick note to those suggesting the use of a TEXT/NTEXT from MSDN:
This feature will be removed in a
future version of Microsoft SQL
Server. Avoid using this feature in
new development work, and plan to
modify applications that currently use
this feature. Use varchar(max),
nvarchar(max) and varbinary(max) data
types instead. For more information,
see Using Large-Value Data Types.
I'd go with Option 2.
You can create a view that joins the two tables to make the transition easier on everyone, and then go through a clean-up process that removes the view and uses the single table wherever possible.
You want to use a TEXT field. TEXT fields aren't stored directly in the row; instead, it stores a pointer to the text data. This is transparent to queries, though - if you ask for a TEXT field, it will return the actual text, not the pointer.
Essentially, using a TEXT field is somewhat between your two solutions. It keeps your table rows much smaller than using a varchar, but you'll still want to avoid asking for them in your queries if possible.
The TEXT/NTEXT data type has practically unlimited length while taking up next to nothing in your record.
It comes with a few strings attached, like special behavior with string functions, but for a secondary "notes/description" type of field these may be less of a problem.
Just to expand on Option 2
You could:
Rename existing MyTable to MyTable_V2
Move the Notes column into a joined Notes table (with 1:1 joining ID)
Create a VIEW called MyTable that joins MyTable_V2 and Notes tables
Create an INSTEAD OF trigger on MyTable view which saves the Notes column into the Notes table (IF NULL then delete any existing Notes row, if NOT NULL then Insert if not found, otherwise Update). Perform appropriate action on MyTable_V2 table
Note: We've had trouble doing this where there is a Computed column in MyTable_V2 (I think that was the problem, either way we've hit snags when doing this with "unusual" tables)
All new Insert/Update/Delete code should be written to operate directly on MyTable_V2 and Notes tables
Optionally: Have the INSERT OF trigger on MyTable log the fact that it was called (it can do this minimally, UPDATE a pre-existing log table row with GetDate() only if existing row's date is > 24 hours old - so will only do an update once a day).
When you are no longer getting any log records you can drop the INSTEAD OF trigger on MyTable view and you are now fully MyTable_V2 compliant!
Huge amount of hassle to implement, as you surmised.
Alternatively trawl the code for all references to MyTable and change them to MyTable_V2, put a VIEW in place of MyTable for SELECT only, and not create the INSTEAD OF trigger.
My plan would be to fix all Insert/Update/Delete statements referencing the now deprecated MyTable. For me this would be made somewhat easier because we use unique names for all tables and columns in the database, and we use the same names in all application code, so making sure I had found all instances by a simple FIND would be high.
P.S. Option 2 is also preferable if you have any SELECT * lying around. We have had clients whos application performance has gone downhill fast when they added large Text/Blob columns to existing tables - because of "lazy" SELECT * statements. Hopefully that isn;t the case in your shop though!

TSQL "LIKE" or Regular Expressions?

I have a bunch (750K) of records in one table that I have to see they're in another table. The second table has millions of records, and the data is something like this:
Source table
9999-A1B-1234X, with the middle part potentially being longer than three digits
Target table
DescriptionPhrase9999-A1B-1234X(9 pages) - yes, the parens and the words are in the field.
Currently I'm running a .net app that loads the source records, then runs through and searches on a like (using a tsql function) to determine if there are any records. If yes, the source table is updated with a positive. If not, the record is left alone.
the app processes about 1000 records an hour. When I did this as a cursor sproc on sql server, I pretty much got the same speed.
Any ideas if regular expressions or any other methodology would make it go faster?
What about doing it all in the DB, rather than pulling records into your .Net app:
UPDATE source_table s SET some_field = true WHERE EXISTS
(
SELECT target_join_field FROM target_table t
WHERE t.target_join_field LIKE '%' + s.source_join_field + '%'
)
This will reduce the total number of queries from 750k update queries down to 1 update.
First I would redesign if at all possible. Better to add a column that contains the correct value and be able to join on it. If you still need the long one. you can use a trigger to extract the data into the column at the time it is inserted.
If you have data you can match on you need neither like '%somestuff%' which can't use indexes or a cursor both of which are performance killers. This should bea set-based task if you have designed properly. If the design is bad and can't be changed to a good design, I see no good way to get good performance using t-SQl and I would attempt the regular expression route. Not knowing how many different prharses and the structure of each, I cannot say if the regular expression route would be easy or even possible. But short of a redesign (which I strongly suggest you do), I don't see another possibility.
BTW if you are working with tables that large, I would resolve to never write another cursor. They are extremely bad for performance especially when you start taking about that size of record. Learn to think in sets not record by record processing.
One thing to be aware of with using a single update (mbeckish's answer) is that the transaction log (enabling a rollback if the query becomes cancelled) will be huge. This will drastically slow down your query. As such it is probably better to proces them in blocks of 1,000 rows or such like.
Also, the condition (b.field like '%' + a.field + '%') will need to check every single record in b (millions) for every record in a (750,000). That equates to more than 750 billion string comparisons. Not great.
The gut feel "index stuff" won't help here either. An index keeps things in order, so the first character(s) dictate the position in the index, not the ones you're interested in.
First Idea
For this reason I would actually consider creating another table, and parsing the long/messy value into something nicer. An example would be just to strip off any text from the last '(' onwards. (This assumes all the values follow that pattern) This would simplify the query condition to (b.field like '%' + a.field)
Still, an index wouldn't help here either though as the important characters are at the end. So, bizarrely, it could well be worth while storing the characters of both tables in reverse order. The index on you temporary table would then come in to use.
It may seem very wastefull to spent that much time, but in this case a small benefit would yield a greate reward. (A few hours work to halve the comparisons from 750billion to 375billion, for example. And if you can get the index in to play you could reduce this a thousand fold thanks to index being tree searches, not just ordered tables...)
Second Idea
Assuming you do copy the target table into a temp table, you may benefit extra from processing them in blocks of 1000 by also deleting the matching records from the target table. (This would only be worthwhile where you delete a meaningful amount from the target table. Such that after all 750,000 records have been checked, the target table is now [for example] half the size that it started at.)
EDIT:
Modified Second Idea
Put the whole target table in to a temp table.
Pre-process the values as much as possible to make the string comparison faster, or even bring indexes in to play.
Loop through each record from the source table one at a time. Use the following logic in your loop...
DELETE target WHERE field LIKE '%' + #source_field + '%'
IF (##row_count = 0)
[no matches]
ELSE
[matches]
The continuous deleting makes the query faster on each loop, and you're only using one query on the data (instead of one to find matches, and a second to delete the matches)
Try this --
update SourceTable
set ContainsBit = 1
from SourceTable t1
join (select TargetField from dbo.TargetTable t2) t2
on charindex(t1.SourceField, t2.TargetField) > 0
First thing is to make sure you have an index for that column on the searched table. Second is to do the LIKE without a % sign on the left side. Check the execution plan to see if you are not doing a table scan on every row.
As le dorfier correctly pointed out, there is little hope if you are using a UDF.
There are lots of ways to skin the cat - I would think that first it would be important to know if this is a one-time operation, or a regular task that needs to be completed regularly.
Not knowing all the details of you problem, if it was me, at this was a one-time (or infrequent operation, which it sounds like it is), I'd probably extract out just the pertinent fields from the two tables including the primary key from the source table and export them down to a local machine as text files. The files sizes will likely be significantly smaller than the full tables in your database.
I'd run it locally on a fast machine using a routine written in something like 'C'/C++ or another "lightweight" language that has raw processing power, and write out a table of primary keys that "match", which I would then load back into the sql server and use it as a basis of an update query (i.e. update source table where id in select id from temp table).
You might spend a few hours writing the routine, but it would run in a fraction of the time you are seeing in sql.
By the sounds of you sql, you may be trying to do 750,000 table scans against a multi-million records table.
Tell us more about the problem.
Holy smoke, what great responses!
system is on disconnected network, so I can't copy paste, but here's the retype
Current UDF:
Create function CountInTrim
(#caseno varchar255)
returns int
as
Begin
declare #reccount int
select #reccount = count(recId) from targettable where title like '%' + #caseNo +'%'
return #reccount
end
Basically, if there's a record count, then there's a match, and the .net app updates the record. The cursor based sproc had the same logic.
Also, this is a one time process, determining which entries in a legacy record/case management system migrated successfully into the new system, so I can't redesign anything. Of course, developers of either system are no longer available, and while I have some sql experience, I am by no means an expert.
I parsed the case numbers from the crazy way the old system had to make the source table, and that's the only thing in common with the new system, the case number format. I COULD attempt to parse out the case number in the new system, then run matches against the two sets, but with a possible set of data like:
DescriptionPhrase1999-A1C-12345(5 pages)
Phrase/Two2000-A1C2F-5432S(27 Pages)
DescPhraseThree2002-B2B-2345R(8 pages)
Parsing that became a bit more complex so I thought I'd keep it simpler.
I'm going to try the single update statement, then fall back to regex in the clr if needed.
I'll update the results. And, since I've already processed more than half the records, that should help.
Try either Dan R's update query from above:
update SourceTable
set ContainsBit = 1
from SourceTable t1
join (select TargetField
from dbo.TargetTable t2) t2
on charindex(t1.SourceField, t2.TargetField) > 0
Alternatively, if the timeliness of this is important and this is sql 2005 or later, then this would be a classic use for a calculated column using SQL CLR code with Regular Expressions - no need for a standalone app.

Resources