I have a table that currently contains 10 million records.
One of the columns is SourceText of type nvarchar(4000).
I need a very efficient way to search the SourceText to see if it contains another string.
I have extreme flexibility will the table structures--I can modify the insert procedure and use other, better indexed tables to track things. One thought was to tokenize the SourceText by word and store the words in an indexed table, then use a mapping table to map to the main table. The problem is that the SourceText column can be any language, and there are always rules re:parantheses, etc. For example, in english if I tokenize using ' ' as the delimiter, I will still get things like (Where instead of Where, which is problematic.
Any ideas?
It would be a quite interesting and challenging project (and I think it's possible) to implement a fast full text search without the optional and very powerful full text search component of SQL Server ;-)
I have a problem where there is a huge list of strings or phrases it might scale from 100,000 to 100Million. when i search for a phrase if found it gives me the Id or index to database for further operation. I know hash table can be used for this, but i am looking for other algorithm which could serve me to generate index based on strings and can also be useful in some other features like autocomplete etc.
I read suffix tree/array based on some SO threads they serve the purpose but consumes alot memory than i can afford. Any alternatives to this?
Since my search is only in a huge list of millions of strings. No docs no webpages not interested in search engine like lucene etc.
Also read about inverted index sounds helpful but which algorithm i need to study for it?.
If this Database index is within MS SQL Server you may get good results with SQL Full Text Indexing. Other SQL providers may have a similar function but I would not be able to help with those.
Check out: http://www.simple-talk.com/sql/learn-sql-server/understanding-full-text-indexing-in-sql-server/
and
http://msdn.microsoft.com/en-us/library/ms142571.aspx
I am creating a new database, which I am basically designing for the logging/history purpose. So, I'll make around 8-10 tables in this database. Which will keep the data and I'll retrieve it for showing history information to the user.
I am creating database from the SQL Server 2005 and I can see that there is a check box of " Use full Indexing". I am not sure whether I make it check or unchecked. As I am not familiar with the database too much, suggest me that by checking it, will it increase the performance of my database in retrieval?
I think that is the check box for FULLTEXT indexing.
You turn it on only if you plan to do some natural language queries or a lot of text-based queries.
See here for a description of what it is used to support.
http://msdn.microsoft.com/en-us/library/ms142571.aspx
From that base link, you can follow through to http://msdn.microsoft.com/en-us/library/ms142547.aspx (amongst others). Interesting is this quote
Comparison of LIKE to Full-Text Search
In contrast to full-text search, the LIKE Transact-SQL predicate works
on character patterns only. Also, you cannot use the LIKE predicate to
query formatted binary data. Furthermore, a LIKE query against a large
amount of unstructured text data is much slower than an equivalent
full-text query against the same data. A LIKE query against millions
of rows of text data can take minutes to return; whereas a full-text
query can take only seconds or less against the same data, depending
on the number of rows that are returned.
There is a cost for this of course which is in the storage of the patterns and relationships between words in the same record. It is really useful if you are storing articles for example, where you want to enable searching by "contains a, b and c". A LIKE pattern would be complicated and extremely slow to process like %A%B%C% OR LIKE '%B%A%C' Or ... and all the permutations for the order of appearance of A, B and C.
I am trying to visualize how to create a search for an application that we are building. I would like a suggestion on how to approach 'searching' through large sets of data.
For instance, this particular search would be on a 750k record minimum table, of product sku's, sizing, material type, create date, etc;
Is anyone aware of a 'plugin' solution for Coldfusion to do this? I envision a google like single entry search where a customer can type in the part number, or the sizing, etc, and get hits on any or all relevant results.
Currently if I run a 'LIKE' comparison query, it seems to take ages (ok a few seconds, but still), and it is too long. At times making a user sit there and wait up to 10 seconds for queries & page loads.
Or are there any SQL formulas to help accomplish this? I want to use a proven method to search the data, not just a simple SQL like or = comparison operation.
So this is a multi-approach question, should I attack this at the SQL level (as it ultimately looks to be) or is there a plug in/module for ColdFusion that I can grab that will give me speedy, advanced search capability.
You could try indexing your db records with a Verity (or Solr, if CF9) search.
I'm not sure it would be faster, and whether even trying it would be worthwhile would depend a lot on how often you update the records you need to search. If you update them rarely, you could do an Verity Index update whenever you update them. If you update the records constantly, that's going to be a drag on the webserver, and certainly mitigate any possible gains in search speed.
I've never indexed a database via Verity, but I've indexed large collections of PDFs, Word Docs, etc, and I recall the search being pretty fast. I don't know if it will help your current situation, but it might be worth further research.
If your slowdown is specifically the search of textual fields (as I surmise from your mentioning of LIKE), the best solution is building an index table (not to be confiused with DB table indexes that are also part of the answer).
Build an index table mapping the unique ID of your records from main table to a set of words (1 word per row) of the textual field. If it matters, add the field of origin as a 3rd column in the index table, and if you want "relevance" features you may want to consider word count.
Populate the index table with either a trigger (using splitting) or from your app - the latter might be better, simply call a stored proc with both the actual data to insert/update and the list of words already split up.
This will immediately drastically speed up textual search as it will no longer do "LIKE", AND will be able to use indexes on index table (no pun intended) without interfering with indexing on SKU and the like on the main table.
Also, ensure that all the relevant fields are indexed fully - not necessarily in the same compund index (SKU, sizing etc...), and any field that is searched as a range field (sizing or date) is a good candidate for a clustered index (as long as the records are inserted in approximate order of that field's increase or you don't care about insert/update speed as much).
For anything mode detailed, you will need to post your table structure, existing indexes, the queries that are slow and the query plans you have now for those slow queries.
Another item is to enure that as little of the fields are textual as possible, especially ones that are "decodable" - your comment mentioned "is it boxed" in the text fields set. If so, I assume the values are "yes"/"no" or some other very limited data set. If so, simply store a numeric code for valid values and do en/de-coding in your app, and search by the numeric code. Not a tremendous speed improvement but still an improvement.
I've done this using SQL's full text indexes. This will require very application changes and no changes to the database schema except for the addition of the full text index.
First, add the Full Text index to the table. Include in the full text index all of the columns the search should perform against. I'd also recommend having the index auto update; this shouldn't be a problem unless your SQL Server is already being highly taxed.
Second, to do the actual search, you need to convert your query to use a full text search. The first step is to convert the search string into a full text search string. I do this by splitting the search string into words (using the Split method) and then building a search string formatted as:
"Word1*" AND "Word2*" AND "Word3*"
The double-quotes are critical; they tell the full text index where the words begin and end.
Next, to actually execute the full text search, use the ContainsTable command in your query:
SELECT *
from containstable(Bugs, *, '"Word1*" AND "Word2*" AND "Word3*"')
This will return two columns:
Key - The column identified as the primary key of the full text search
Rank - A relative rank of the match (1 - 1000 with a higher ranking meaning a better match).
I've used approaches similar to this many times and I've had good luck with it.
If you want a truly plug-in solution then you should just go with Google itself. It sounds like your doing some kind of e-commerce or commercial site (given the use of the term 'SKU'), So you probably have a catalog of some kind with product pages. If you have consistent markup then you can configure a google appliance or service to do exactly what you want. It will send a bot in to index your pages and find your fields. No SQl, little coding, it will not be dependent on your database, or even coldfusion. It will also be quite fast and familiar to customers.
I was able to do this with a coldfusion site in about 6 hours, done! The only thing to watch out for is that google's index is limited to what the bot can see, so if you have a situation where you want to limit access based on a users role or permissions or group, then it may not be the solution for you (although you can configure a permission service for Google to check with)
Because SQL Server is where your data is that is where your search performance is going to be a possible issue. Make sure you have indexes on the columns you are searching on and if using a like you can't use and index if you do this SELECT * FROM TABLEX WHERE last_name LIKE '%FR%'
But it can use an index if you do it like this SELECT * FROM TABLEX WHERE last_name LIKE 'FR%'. The key here is to allow as many of the first characters to not be wild cards.
Here is a link to a site with some general tips. https://web.archive.org/web/1/http://blogs.techrepublic%2ecom%2ecom/datacenter/?p=173
SSIS 2005/2008 does fuzzy lookups and groupings. Is there a feature that does the same in T-SQL?
Fuzzy lookup uses a q-gram approach, by breaking strings up into tiny sub-strings and indexing them. You can then then search input by breaking it up into equally sized strings. You can inspect the format of their index and write a CLR function to use the same style of index but you might be talking about a fair chunk of work.
It is actually quite interesting how they did it, very simple yet provides very robust matching and is very configurable.
From that I recall of the index when I last looked at it, each q-gram or substring is stored in a row in an table (the index). That row contains an nvarchar column (among other values) that is used as binary data and contains references to the rows that match.
There is also an open feedback suggestion on Microsoft Connect for this feature.
SQL Server has a SOUNDEX() function:
SELECT *
FROM Customers
WHERE SOUNDEX(Lastname) = SOUNDEX('Stonehouse')
AND SOUNDEX(Firstname) = SOUNDEX('Scott')
Full Text Search is a great fuzzy tool. Brief primer here
On March 5 2009 I will have an article posted on www.sqlservercentral.com with a sample of Jaro-Winkler TSQL