PROBLEM:
I need to write an advanced search functionality for a website. All the data is stored in MySQL and I'm using Zend Framework on top. I know that I can write a script that takes the search page and builds an SQL query out of it, but this becomes extremely slow if there's a lot of hits. Then I would have to get down to the gritty details of optimizing the database tables/fields/etc. which I'm trying to avoid if possible.
Lucene: I gave Lucene a try, but since it's a full-text search engine, it does not allow any mathematical operators!! So if I wanted to get all the records where field_x > 5, there is no way to do it (correct?)
General Practice? I would like to know how large sites deal with this dilemma. Is there a standard way of doing this that I don't know about, or does everyone have to deal with the nasty details of optimizing the database at some point? I was hoping that some fast indexing/searching technology existed (e.g. Lucene) that would address this problem.
ANY OTHER COMMENTS OR SUGGESTION ARE MOST WELCOME!!
Thanks a lot guys!
Ali
You can use Zend Lucene for textual search, and combine it with MySQL for joins.
Please see Mark Krellenstein's Search Engine vs DBMS paper about the choice; Basically, search engines are better for ranked text search; Databases are better for more complex data manipulations, such as joins, using different record structures.
For a simple x>5 type query, you can use a range query inside Lucene.
Use Lucene for your text-based searches, and use SQL for field_x > 5 searches. I say this because text-based search is hard to get right, and you're probably better off leaving that to an expert.
If you need your users to have the capability of building mathematical expression searches, consider writing an expression builder dialog like this example to collect the search phrase. Then use a parameterized SQL query to execute the search.
SqlWhereBuilder ASP.NET Server Control
http://www.codeproject.com/KB/custom-controls/SqlWhereBuilder.aspx
You can use filters in Lucene to carry out a text search of a reduced set of records. So if you query the database first to get all records where field_x > 5, build a filter (a list of lucene document IDs) and pass this into the lucene search method along with the text query. I'm just learning about this, here's a link to a question I asked (it uses Lucene.Net and C# but it may help) - ignore my question, just check out the accepted answer:
How do you implement a custom filter with Lucene.net?
Related
I'm trying to create a search feature in Meteor 1.8.1 that does the following:
returns partial matches, e.g. "fish" will find "fish", "fishcake" and "dogfish"
has server-side control of which documents are returned, so search results don't include documents that are not published to the user
is reasonably efficient
returns a limited number of results
This seems like it should be a common requirement, but I'm failing to find any solution.
MongoDB full text search will only return on whole words, so will only find "fish".
Easy search doesn't support server-side permissions, as far as I can tell.
I could try a regex solution but I think it would be expensive?
Thank you for any solutions!
Edit: From discussion it seems that Easy Search does support server-side filtering using a selector, and this would be the best solution. However, I can't get a selector working from the examples and documentation. For clarity, I've created a new question for that issue
The documentation explicitly states that for advanced use cases you may want to use elastic search and offers you a pluggable extension to ease the burden of integration.
https://matteodem.github.io/meteor-easy-search/docs/recipes/#advanced-search
You might wish that a search for cafe returns documents with the text café in them (special character). Or that your search string is split up by whitespace and those terms used to search across multiple fields.
You should consider using a search engine like ElasticSearch for your search if you have these usecases. ElasticSearch allows you to configure precisely how your fields are being searched. One way you can do that is by analyzing your data, so that searching itself is as fast as possible.
What is the best practice methododology of implementing site-wide search in Yii2?
This question is not about how to implement search specifically, but rather about what kind of approach to use. Should we use Sphinx? Elasticsearch? Or do we use UNION selects to get the data into a DataProvider?
Assume the application is using a relational database to store data. We want to search and display multiple different models. For example, our database contains tables of Books, Authors and Stores. When we search for a keyword we want to display results from all 3 tables (matching Books by title or content, Authors by full name and Stores by name etc).
There are tutorials which show how to use Elasticsearch but assume that our data is stored in the Elasticsearch database, which does not make sense. Our data is already stored in MySQL or PostgreSQL. Does this mean
we need to maintain a duplicate of our data in the Elasticsearch database?
What is the best practice methododology of implementing site-wide search in Yii2?
That depends on many factors, so I cant give you a specific recommendation for your case. Some of the factors to think about are:
What would you like to achieve with this search? Is every little bit in your database a significant search term?
Do you need only full-text-search or a wide range of analytics?
Have you any limits in time or costs?
Can your (tech-)infrastructure handle your ideas?
Is it worth to bring in another extensive technology in the project?
Can you handle additional maintenance tasks to run such a search engine?
And many more ...
In my internal Yii2 Project with a PostgreSQL RDBMS, I decided to use a PostgreSQL Text Search Type called tsvector. Thats good enough for my needs. Why?
You can use Stemming.
Supports Fuzzy search.
Supports basic ranking.
Supports multiple languages.
I highly recommend this blog post Postgres full-text search is Good Enough.
I am trying to implement a search engine for my recipes-website using mongo db.
I am trying to display the search suggestions in type-ahead widget box to the users.
I am even trying to support mis-spelled queries(levenshtein distance).
For example: whenever users type 'pza', type-ahead should display 'pizza' as one of the suggestion.
How can I implement such functionality using mongodb?
Please note, the search should be instantaneous, since the search result will be fetched by type-ahead widget. The collections over which I would run search queries have at-most 1 million entries.
I thought of implementing levenshtein distance algorithm, but this would slow down performance, as collection is huge.
I read FTS(Full Text Search) in mongo 2.6 is quite stable now, but my requirement is Approximate match, not FTS. FTS won't return 'pza' for 'pizza'.
Please recommend me the efficient way.
I am using node js mongodb native driver.
The text search feature in MongoDB (as at 2.6) does not have any built-in features for fuzzy/partial string matching. As you've noted, the use case currently focuses on language & stemming support with basic boolean operators and word/phrase matching.
There are several possible approaches to consider for fuzzy matching depending on your requirements and how you want to qualify "efficient" (speed, storage, developer time, infrastructure required, etc):
Implement support for fuzzy/partial matching in your application logic using some of the readily available soundalike and similarity algorithms. Benefits of this approach include not having to add any extra infrastructure and being able to closely tune matching to your requirements.
For some more detailed examples, see: Efficient Techniques for Fuzzy and Partial matching in MongoDB.
Integrate with an external search tool that provides more advanced search features. This adds some complexity to your deployment and is likely overkill just for typeahead, but you may find other search features you would like to incorporate elsewhere in your application (e.g. "like this", word proximity, faceted search, ..).
For example see: How to Perform Fuzzy-Matching with Mongo Connector and Elastic Search. Note: ElasticSearch's fuzzy query is based on Levenshtein distance.
Use an autocomplete library like Twitter's open source typeahead.js, which includes a suggestion engine and query/caching API. Typeahead is actually complementary to any of the other backend approaches, and its (optional) suggestion engine Bloodhound supports prefetching as well as caching data in local storage.
The best case for it would be using elasticsearch fuzzy query:
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-fuzzy-query.html
It supports levenshtein distance algorithm out of the box and has additional features which can be useful for your requirements i.e.:
- more like this
- powerful facets / aggregations
- autocomplete
I am just wondering if we could achieve some RDBMS capabilities in lucene.
Example:
1) I have 10,000 project documents (pdf files) which have to be indexed with their content to make them available for search.
2) Every document is related to a SINGLE PROJECT. The project can contain details like project name, number, start date, end date, location, type etc.
I have to search in the contents of the pdf files for a given keyword, but while displaying the results I want to display the project meta data as mentioned in point (2).
My idea is to associate a field called projectId with each pdf file while indexing. Once we get that, we will fire search again for getting project meta data.
This way we could avoid duplicated data. Also, if we want to update the project meta data we will end up updating at a SINGLE PLACE only. Otherwise if we store this meta data with all the pdf doument indexes, we will end up updating all of the documents, which is not the way I am looking for.
please advise.
If I understand you correctly, you have two questions:
Can I store a project id in Lucene and use it for further searches? Yes, you can. This is a common practice.
Can I use this project id to search Lucene for project meta data? Yes, you can. I do not know if this is a good idea. It depends on the frequency of your meta data updates and your access pattern. If the meta data is relatively static, and you only access it by id, Lucene may be a good place to store it. Otherwise, you can use the project id as a primary key to a database table, which could be a better fit.
Sounds like a perfectly good thing to do. The only limitation you'll have (by storing a reference to the project in Lucene rather than the project data itself) is that you won't be able to query both the document text and project metadata at the same time. For example, "documentText:foo OR projectName:bar" . If you have no such requirement, then seems like storing the ID in Lucene which refers to a database row is a fine thing to do.
I am not sure on your overall setup, but maybe Hibernate Search is for you. It would allow you to combine the benefits of a relational database with the power of a fulltext search engine like Lucene. The meta data could live in the database, maybe together with the original pdf documents, while the Lucene documents just contain the searchable data.
This is definitely possible. But always be aware of the fact that you're using Lucene for something that it was not intended for. In general, Lucene is designed for full-text search, not for mapping relational content. So the more complex your system your relational content becomes, the more you'll see a decrease in performance.
In particular, there are a few areas to keep a close eye on:
Storing the value of each field in your index will decrease performance. If you are not overly concerned with sub-second search results, or if your index is relatively small, then this may not be a problem.
Also, be aware that if you are not using the default ranking algorithm, and your custom algorithm requires information about the project in order to calculate the score for each document, this will have a dramatic impact on search performance, as well.
If you need a more powerful index that was designed for relational content, there are hierarchical indexing tools out there (one developed by Apache, called Jackrabbit) that are worth looking into.
As your project continues to grow, you might also check out Solr, also developed by Apache, which provides some added functionality, such as multi-faceted search.
You can use Lucene that way;
Pros:
Full-text search is easy to implement, which is not the case in an RDBMS.
Cons:
Referential integrity: you get it for free in an RDBMS, but in Lucene, you must implement it yourself.
I'm using lucene in my project.
Here is my question:
should I use lucene to replace the whole search module which has been implemented with sql using a large number of like statement and accurate search by id or sth,
or should I just use lucene in fuzzy search(i mean full text search)?
Probably you should use lucene, unless the SQL search is very performant.
We are right now moving to Solr (based on Lucene) because our search queries are inherently slow, and cannot be sped up with our database.... If you have reasonably large tables, your search queries will start to get really slow unless the DB has some kind of highly optimized free text search mechanisms.
Thus, let Lucene do what it does best....
I don't think using like statement abusively is a good idea.
And I believe the performance of lucene will be better than database.
I'm actually very impressed by Solr, at work we were looking for a replacement for our Google Mini (it's woefully inadequate for any serious site search) and were expecting something that would take a while to implement. Within 30 minutes of installing Solr we had done what we had expected to take at least a few days and provided us with a far more powerful search interface than we had before.
You could probably use Solr to do quite a lot of clever things beyond a simple site search.