I have a table Books in my MySQL database which has the columns Title (varchar(255)) and Edition (varchar(20)). Example values for these are "Introduction to Microeconomics" and "4".
I want to let users search for Books based on Title and Edition. So, for example they could enter "Microeconomics 4" and it would get the proper result. My question is how I should set this up on the database side.
I've been told that FULLTEXT search is generally a good way to do things like this. However, because the edition is sometimes just a single character ("4"), full text search would have to be setup to look at individual characters (ft_min_word_len = 1).. This, I've heard, is very inefficient.
So, how should I setup searches of this database?
UPDATE: I'm aware the CONCAT/LIKE could be used here.. My question is whether it would be too slow. My Books database has hundreds of thousands of books and a lot of users are going to be searching it..
here are the steps for solution
1) read the search string from user.
2) make the string in to parts according to space(" ") between the words.
3) use following query for getting the result
SELECT * FROM books WHERE Title LIKE '%part[0]%' AND Edition LIKE '%part[1]%';
here part[0] and part[1] are separated words from the given word
the PHP code for the above could be
<?php
$string_array=explode(" ",$string); //$string is the value we are searching
$select_query="SELECT * FROM books WHERE Title LIKE '%".$string_array[0]."%' AND Edition LIKE '%".$string_array[1]."%';";
$result=mysql_fetch_array(mysql_query($select_query));
?>
for $string_array[0] it could be extended to get all the parts except last one which can be applied for the case "Introduction to Microeconomics 4"
For your application, where you're interested in just title and edition, I suspect that using a FULLTEXT index with MATCH/AGAINST and reducing the ft_min_word_len to 1 would not have that much impact performance-wise (if you were data was more verbose or user written content, then I might hesitate).
The easiest way to check is to change the value, REPAIR the table to account for the new ft_min_word_len and rebuild the index, and do some simple benchmarking.
Having said that, for your application, I might consider looking into Sphinx. It's definitely going to be magnitudes faster, and your content is relatively static, so a delay between re-indexing (Sphinx's main drawback IMO) isn't an issue. Plus, with careful usage of the wordforms and exceptions, you could map things like 4/four/fourth/IV all to the same token for improved searching.
Related
In Sql Server, I have a table containing 46 million rows.
In "Title" column of table, I want make search. The word may be at any index of field value.
For example:
Value in table: BROTHERS COMPANY
Search string: ROTHER
I want this search to match the given record. This is exactly what LIKE '%ROTHER%' do. However, LIKE '%%' usage should not be used on large tables because of performance issues. How can I achieve it?
Though I don't know your requirements, your best approach may be to challenge them. Middle-of-the-string searches are usually not very practical. If you can get your users to perform prefix searches (broth%) then you can easily use Full Text's wildcard search (CONTAINS(*, '"broth*"')). Full Text can also handle suffix searches (%rothers) with a little extra work.
But when it comes to middle-of-the-string searches with SQL Server, you're stuck using LIKE. However you may be able to improve performance of LIKE by using a binary collation as explained in this article. (I hate to post a link without including its content but it is way too long of an article to post here and I don't understand the approach enough to sum it up.)
If that doesn't help and if middle-of-the-string searches are that important of a requirement then you should consider using a different search solution like Lucene.
Add Full-Text index if you want.
You can search the table using CONTAINS:
SELECT *
FROM YourTable
WHERE CONTAINS(TableColumnName, 'SearchItem')
I'm searching against a table of news articles. The 2 relevant columns are ArticleTitle and ArticleText. When I want to search an article for a particular term, i started out with
column LIKE '%term%'.
However that gave me a lot of articles with the term inside anchor links, for example <a href="example.com/*term*> which would potentially return an irrelevant article.
So then I switched to
column LIKE '% term %'.
The problem with this query is it didn't find articles who's title or text began/ended with the term. Also it didn't match against things like term- or term's, which I do want.
It seems like the query i want should be able to do something like this
'%[^a-z]term[^a-z]%
This should exclude terms within anchor links, but everything else. I think this query still excludes strings that begin/end with the term. Is there a better solution? Does SQL-Server's FULL TEXT INDEXING solve this problem?
Additionally, would it be a good idea to store ArticleTitle and ArticleText as HTML-free columns? Then i could use '%term%' without getting anchor links. These would be 2 extra columns though, because eventually i will need the original HTML for formatting purposes.
Thanks.
SQL Server's LIKE allows you to define Regex-like patterns like you described.
A better option is to use fulltext search:
WHERE CONTAINS(ArticleTitle, 'term')
exploits the index properly (the LIKE '%term%' query is slow), and provides other benefit in the search algorithm.
Additionally, you might benefit from storing a plaintext version of the article alongside the HTML version, and run your search queries on it.
SQL is not designed to interpret HTML strings. As such, you'd only be able to postpone the problem till a more difficult issue arrives (for example, a comment node that contains your search terms as part of a plain sentence).
You can still utilize FULL TEXT as a prefilter and then run an HTML analysis on the application layer to further filter your result set.
Still pretty new to Rails and hoping to develop a function on a site enabling a search to be performed of the manner detailed below:
User inputs a search term / phrase (string of words but unlikely to be more than 5 or 6)
String is chopped into its constituent words
Entries in a single model with a description (a single field in the model) are output
Having looked at previous questions on this site, I am aware that there are a number of add-ons which are commonly used for search queries, however, are these needed in such a simple situation?
I was thinking that I could use an SQL command with a number of ANDs to perform this task?
Currently the model is stored within sqlite3, but it is probably going to grow to about 100,000 lines (just 10 fields though) in the near future if this is likely to cause problems?
Finally, is there an easy way to pull out the words of a string automatically for any length of string / up to a certain limit that is unlikely to be exceeded?
Thanks in advance for your time and patience
You can easily pull the words from a string with ruby: 'alice bob charlie'.split(/\s+/) will give you an array with the words.
Then, you can string those words together into an SQL query to find the appropriate records. It don't know about the performance of this solution though... You should definitely test it out to see if there are any performance issues.
Given your data stored somewhere in a database:
Hello my name is Tom I like dinosaurs to talk about SQL.
SQL is amazing. I really like SQL.
We want to implement a site search, allowing visitors to enter terms and return relating records. A user might search for:
Dinosaurs
And the SQL:
WHERE articleBody LIKE '%Dinosaurs%'
Copes fine with returning the correct set of records.
How would we cope however, if a user mispells dinosaurs? IE:
Dinosores
(Poor sore dino). How can we search allowing for error in spelling? We can associate common misspellings we see in search with the correct spelling, and then search on the original terms + corrected term, but this is time consuming to maintain.
Any way programatically?
Edit
Appears SOUNDEX could help, but can anyone give me an example using soundex where entering the search term:
Dinosores wrocks
returns records instead of doing:
WHERE articleBody LIKE '%Dinosaurs%' OR articleBody LIKE '%Wrocks%'
which would return squadoosh?
If you're using SQL Server, have a look at SOUNDEX.
For your example:
select SOUNDEX('Dinosaurs'), SOUNDEX('Dinosores')
Returns identical values (D526) .
You can also use DIFFERENCE function (on same link as soundex) that will compare levels of similarity (4 being the most similar, 0 being the least).
SELECT DIFFERENCE('Dinosaurs', 'Dinosores'); --returns 4
Edit:
After hunting around a bit for a multi-text option, it seems that this isn't all that easy. I would refer you to the link on the Fuzzt Logic answer provided by #Neil Knight (+1 to that, for me!).
This stackoverflow article also details possible sources for implentations for Fuzzy Logic in TSQL. Once respondant also outlined Full text Indexing as a potential that you might want to investigate.
Perhaps your RDBMS has a SOUNDEX function? You didn't mention which one was involved here.
SQL Server's SOUNDEX
Just to throw an alternative out there. If SSIS is an option, then you can use Fuzzy Lookup.
SSIS Fuzzy Lookup
I'm not sure if introducing a separate "search engine" is possible, but if you look at products like the Google search appliance or Autonomy, these products can index a SQL database and provide more searching options - for example, handling misspellings as well as synonyms, search results weighting, alternative search recommendations, etc.
Also, SQL Server's full-text search feature can be configured to use a thesaurus, which might help:
http://msdn.microsoft.com/en-us/library/ms142491.aspx
Here is another SO question from someone setting up a thesaurus to handle common misspellings:
FORMSOF Thesaurus in SQL Server
Short answer, there is nothing built in to most SQL engines that can do dictionary-based correction of "fat fingers". SoundEx does work as a tool to find words that would sound alike and thus correct for phonetic misspellings, but if the user typed in "Dinosars" missing the final U, or truly "fat-fingered" it and entered "Dinosayrs", SoundEx would not return an exact match.
Sounds like you want something on the level of Google Search's "Did you mean __?" feature. I can tell you that is not as simple as it looks. At a 10,000-foot level, the search engine would look at each of those keywords and see if it's in a "dictionary" of known "good" search terms. If it isn't, it uses an algorithm much like a spell-checker suggestion to find the dictionary word that is the closest match (requires the fewest letter substitutions, additions, deletions and transpositions to turn the given word into the dictionary word). This will require some heavy procedural code, either in a stored proc or CLR Db function in your database, or in your business logic layer.
You can also try the SubString(), to eliminate the first 3 or so characters . Below is an example of how that can be achieved
SELECT Fname, Lname
FROM Table1 ,Table2
WHERE substr(Table1.Fname, 1,3) || substr(Table1.Lname,1 ,3) = substr(Table2.Fname, 1,3) || substr(Table2.Lname, 1 , 3))
ORDER BY Table1.Fname;
I am trying to determine what the best way is to find variations of a first name in a database. For example, I search for Bill Smith. I would like it return "Bill Smith", obviously, but I would also like it to return "William Smith", or "Billy Smith", or even "Willy Smith". My initial thought was to build a first name hierarchy, but I do not know where I could obtain such data, if it even exists.
Since users can search the directory, I thought this would be a key feature. For example, people I went to school with called me Joe, but I always go by Joseph now. So, I was looking at doing a phonetic search on the last name, either with NYSIIS or Double Metaphone and then searching on the first name using this name heirarchy. Is there a better way to do this - maybe some sort of graded relevance using a full text search on the full name instead of a two part search on the first and last name? Part of me thinks that if I stored a name as a single value instead of multiple values, it might facilitate more search options at the expense of being able to address a user by the first name.
As far as platform, I am using SQL Server 2005 - however, I don't have a problem shifting some of the matching into the code; for example, pre-seeding the phonetic keys for a user, since they wouldn't change.
Any thoughts or guidance would be appreciated. Countless searches have pretty much turned up empty. Thanks!
Edit: It seems that there are two very distinct camps on the functionality and I am definitely sitting in the middle right now. I could see the argument of a full-text search - most likely done with a lack of data normalization, and a multi-part approach that uses different criteria for different parts of the name.
The problem ultimately comes down to user intent. The Bill / William example is a good one, because it shows the mutation of a first name based upon the formality of the usage. I think that building a name hierarchy is the more accurate (and extensible) solution, but is going to be far more complex. The fuzzy search approach is easier to implement at the expense of accuracy. Is this a fair comparison?
Resolution: Upon doing some tests, I have determined to go with an approach where the initial registration will take a full name and I will split it out into multiple fields (forename, surname, middle, suffix, etc.). Since I am sure that it won't be perfect, I will allow the user to edit the "parts", including adding a maiden or alternate name. As far as searching goes, with either solution I am going to need to maintain what variations exists, either in a database table, or as a thesaurus. Neither have an advantage over the other in this case. I think it is going to come down to performance, and I will have to actually run some benchmarks to determine which is best. Thank you, everyone, for your input!
In my opinion you should either do a feature right and make it complete, or you should leave it off to avoid building a half-assed intelligence into a computer program that still gets it wrong most of the time ("Looks like you're writing a letter", anyone?).
In case of human names, a computer will get it wrong most of the time, doing it right and complete is impossible, IMHO. Maybe you can hack something that does the most common English names. But actually, the intelligence to look for both "Bill" and "William" is built into almost any English speaking person - I would leave it to them to connect the dots.
The term you are looking for is Hypocorism:
http://en.wikipedia.org/wiki/Hypocorism
And Wikipedia lists many of them. You could bang out some Python or Perl to scrape that page and put it in a db.
I would go with a structure like this:
create table given_names (
id int primary key,
name text not null unique
);
create table hypocorisms (
id int references given_names(id),
name text not null,
primary key (id, name)
);
insert into given_names values (1, 'William');
insert into hypocorisms values (1, 'Bill');
insert into hypocorisms values (1, 'Billy');
Then you could write a function/sproc to normalize a name:
normalize_given_name('Bill'); --returns William
One issue you will face is that different names can have the same hypocorism (Albert -> Al, Alan -> Al)
I think your basic approach is solid. I don't think fulltext is going to help you. For seeding, behindthename.com seems to have large amount of the data you want.
Are you using SQl Server 2005 Express with Advanced Services as to me it sounds you would benefit from the Full Text indexing and more specifically Contains and Containstable which you can use with specific instructions here is a link for the uses of Containstable:
http://msdn.microsoft.com/en-us/library/ms189760.aspx
and here is the download link for SQL Server 2005 With Advanced Services:
http://www.microsoft.com/downloads/details.aspx?familyid=4C6BA9FD-319A-4887-BC75-3B02B5E48A40&displaylang=en
Hope this helps,
Andrew
You can use the SQL Server Full Text Search and do an inflectional search.
Basically like:
SELECT ProductId, ProductName
FROM ProductModel
WHERE CONTAINS(CatalogDescription, ' FORMSOF(THESAURUS, metal) ')
Check out:
http://en.wikipedia.org/wiki/SQL_Server_Full_Text_Search#Inflectional_Searches
http://msdn.microsoft.com/en-us/library/ms345119.aspx
http://www.mssqltips.com/tip.asp?tip=1491
Not sure what your application is, but if your users know at the time of sign up that people from their past might be searching the database for them, you could offer them the chance in the user profile to define other names they might be known as (including last names, women change these all the time and makes finding them much harder!) and that they want people to be able to search on. Store these in a separate related table. Then search on that. Just make the structure such that you can define one name as the main name (the one you use for everything except the search.)
You'll find that you're dabbling in an area known as "Natural Language Processing" and you'll need to do several things, most of which can be found under the topic of stemming.
Simplistic stemming simply breaks the word apart, but more advanced algorithms associate words that mean the same thing - for instance Google might use stemming to convert "cat" and "kitten" to "feline" and search for all three, weighing the actual word provided by the user as slightly heavier so exact matches return before stemmed matches.
It's a known problem, and there are open source stemmers available.
-Adam
No, Full Text searches will not help to solve your problem.
I think you might want to take a look at some of the following links: (Funny, no one mentioned SoundEx till now)
SoundEx - MSDN
SoundEx - Google results
InformIT - Tolerant Search algorithms
Basically SoundEx allows you to evaluate the level of similarity in similar sounding words. The function is also available on SQL 2005.
As a side issue, instead of returning similar results, it might prove more intuitive to the user to use a AJAX based script to deliver similar sounding names before the user initiates his/her search. That way you can show the user "similar names" or "did you mean..." kind of data.
Here's an idea for automatically finding "name synonyms" like Bill/William. That problem has been studied in the broader context of synonyms in general: inducing them from statistics of which words commonly appear in the same contexts in a large text corpus like the Web. You could try combining that approach with a list of names like Moby Names; I don't know if it's been done before.
Here are some pointers.