So why do you need a search engine, is database not enough? If you create a small website it might not matter. With medium or big size applications it's often wiser to go for a search engine. Saying that, even a small websites can benefit from Solr if you desire a high level of relevance in search results.

Their example involves an ecommerce website and a search for a term (iPhones) and how difficult it could be to match against the possible multiple variations on the models. Solr makes this kind of searching easier. He shows you how to get a Solr instance all set up and configured as well as the PHP PECL extension from here. A sample PHP script is also included showing connecting to Solr, inserting a new document and searching for a simple query of "hello".

Solarium is a library I often use at Enrise for querying Solr. For one of the projects I work on, AutoTrack.nl a second hand car site, I was having issues on advanced faceting with Solr which I could easily solve using Solarium. [...] Faceting is a technique for guided navigation where search results are separated into categories, often including counts on those categories. The user can then select from those categories to restrict their search step by step.

He includes an example of what kind of results this sort of searching could return and how you can use the "facet.mincount" to restrict the results to an even finer set. There's a bit of code included showing how to use this filtering method with a combination of "addFilterQuery" and "createFacetField" calls before executing the select through Solarium.

The main aim of this application is to go familiar with the Google Plus API usage. Google Plus provides an extremely easy to use API to access the public contents on it. Here we will create a simple search application to search user profiles on Google Plus.

Complete code is provided in the post (PHP) and instructions on setting up an "application" on G+ so you can get the keys needed to connect to the API. You can see it in action in the live demo or just download the source to get started.

Most of my co-workers never really heard of bloom filters, and I'm continuously need to explain what they are, what their purpose is and why it's a better solution than other ones. So let's do an introduction on bloom filters. [...] Bloom filters have the property of being exceptionally fast AND exceptionally small compared to other structures but it comes with a price: it MIGHT be possible that our bloom filter thinks that an element is inside our set, when it really isn't. Luckily, the reverse is not possible: when a bloom filter says something is NOT in the set, you are 100% sure that it isn't part of the set.

He explains how the filter works, noting how it's better for memory consumption and how it's possible for it to give a "maybe" response instead of ab absolute "yes" or "no". He also points out a PHP extension, bloomy that takes the hard work out of it for you.

Cake Php Search Component is used to implement search in your cake php projects.The component provide highly reusability. component is meant to use across all the controllers. you just include this search component in your Controller and call a component function to fetch your conditions types in search form and refine the data .

The component (available for download here) is simple to install and full instructions for implementing it are included in the post - including it in the controller, creating search and pagination elements, making a controller action and finally making a view to tie it all together.

For those that are not yet aware of this probably because they only arrived to the PHPClasses site recently, PHP Zeitgeist is an initiative that aims to study what were the last year trends regarding what PHP developers have been searching for.

According to their results, some of the trends ramping up (or still going strong) for 2012 include:

• Social media sites
• Sites like Groupon, Foursquare and Bitcoin
• jQuery plugins
• Doctrine
• MODX
• SugarCRM

So how can you practice using regex if you are limited to just using them in your code? The answer is to use a utility, of which there are many, that uses regex for performing search and replace. I'm sure everyone is familiar with the standard "find x and replace it with y" type of search and replace. Most IDEs and text editors have built in regex engines to handle search and replace. In this article I'd like to walk through a series of exercises to help you practice using regex.

His examples are based on Netbeans but can be used in just about any IDE that supports regex (or even just your code). He shows how to match word boundaries, do some grouping, work with back references and doing some search/replace based on multiple groupings.

Full-text search with SQLite is so ridiculously easy to implement, there are only two valid reasons you haven't done it yet. The first is you don't need the full-text capability, and the second is you didn't know it could be done.

In his method he creates a full-text search table (using fts4) and populating it with your data. You can use the "MATCH" keyword in your SQL to find the closest matches and even handy modifiers like "NEARBY", wildcards and token/prefixes in queries. For more detailed information, check out the SQLite documentation for a full guide.

Fresh from Adam Khoury's massive library of instructional videos comes a four-part, full-fledged tutorial on searching a MySQL database using PHP. The tutorials use the 'worked example' format (like Khan Academy), which makes learning relatively painless for newbies and not completely useless for more experienced developers.

The four videos require you to have at least a decent working knowledge of putting PHP and MySQL together and show you how to:

• create/populate an example table
• build the frontend search form
• use UNION and LIKEs to search the data
• using the FULLTEXT searching in MySQL to find more accurate results

A couple of weeks back I had to write a solution for a client to track the referrer search engine from where the user came to his sites contact page, without using Google Analytics. If a user was to fill the contact form on the website, the referring search engine name and the keyword for which it was refereed was to be emailed along with the contact information. The following is a solution for the same.

The code itself is pretty simple - it checks the $_SERVER['HTTP_REFERER'] and, based on an array of search engine types, looks for a certain "query" keyname in the URL and matches what follows (with a regular expression). This can be useful for not only determining what sort of audience is visiting your site, but could also be used to present a custom message to visitors from certain search engines (or, more complicated, to show different content based on search terms).