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How to make Safari accept Google search strings in the Location bar quickly

A few months ago, I switched to Safari after having used Google Chrome exclusively for the past four years (before that it was a mix of Safari and FireFox). Safari is lean and fast, but the one thing that really bothered me was the fact that I would often try searching for something by entering keywords in the location/address bar, then hit enter, and nothing would happen.

I quickly realized that if I did this and nothing happened, I could jump back into the location bar (⌘-L), press the left arrow key to get my cursor in the beginning of the string, then hit space and enter to perform the search.

Until today, I've begrudgingly used that workaround. But then I was checking Safari's preferences to see if I might be missing something obvious, when I decided to uncheck some options and see if it made a difference. And it did!

Safari Search Preferences

Setting up Faceted Apache Solr search in Drupal 8

Note: Extra special thanks to Doug Vann for providing motivation to finally post this blog post!

Early in 2016, when the Search API and Solr-related modules for Drupal 8 were in early alpha status, I wrote the blog post Set up a faceted Apache Solr search page on Drupal 8 with Search API Solr and Facets.

Set up faceted Apache Solr search on Drupal 8 (2016 - deprecated)

Note: A lot has changed in Drupal 8 and the Search API module ecosystem since this post was written in May 2016... I wrote a new blog post for Faceted Solr Search in Drupal 8, so please read that if you're just getting started. I'm leaving this up as a historical reference, as the general process and architecture are the same, but many details are different.

In Drupal 8, Search API Solr is the consolidated successor to both the Apache Solr Search and Search API Solr modules in Drupal 7. I thought I'd document the process of setting up the module on a Drupal 8 site, connecting to an Apache Solr search server, and configuring a search index and search results page with search facets, since the process has changed slightly from Drupal 7.

Solr for Drupal Developers, Part 3: Testing Solr locally

In earlier Solr for Drupal Developers posts, you learned about Apache Solr and it's history in and integration with Drupal. In this post, I'm going to walk you through a quick guide to getting Apache Solr running on your local workstation so you can test it out with a Drupal site you're working on.

The guide below is for those using Mac or Linux workstations, but if you're using Windows (or even if you run Mac or Linux), you can use Drupal VM instead, which optionally installs Apache Solr alongside Drupal.

As an aside, I am writing this series of blog posts from the perspective of a Drupal developer who has worked with large-scale, highly customized Solr search for Mercy (example), and with a variety of small-to-medium sites who are using Hosted Apache Solr, a service I've been running as part of Midwestern Mac since early 2011.

Installing Apache Solr in a Virtual Machine

Apache Solr can be run directly from any computer that has Java 1.7 or later, so technically you could run it on any modern Mac, Windows, or Linux workstation natively. But to keep your local workstation cleaner, and to save time and hassle (especially if you don't want to kludge your computer with a Java runtime!), this guide will show you how to set up an Apache Solr virtual machine using Vagrant, VirtualBox, and Ansible.

Let's get started:

Solr for Drupal Developers, Part 2: Solr and Drupal, A History

Drupal has included basic site search functionality since its first public release. Search administration was added in Drupal 2.0.0 in 2001, and search quality, relevance, and customization was improved dramatically throughout the Drupal 4.x series, especially in Drupal 4.7.0. Drupal's built-in search provides decent database-backed search, but offers a minimal set of features, and slows down dramatically as the size of a Drupal site grows beyond thousands of nodes.

In the mid-2000s, when most custom search solutions were relatively niche products, and the Google Search Appliance dominated the field of large-scale custom search, Yonik Seeley started working on Solr for CNet Networks. Solr was designed to work with Lucene, and offered fast indexing, extremely fast search, and as time went on, other helpful features like distributed search and geospatial search. Once the project was open-sourced and released under the Apache Software Foundation's umbrella in 2006, the search engine became one of the most popular engines for customized and more performant site search.

As an aside, I am writing this series of blog posts from the perspective of a Drupal developer who has worked with large-scale, highly customized Solr search for Mercy (example), and with a variety of small-to-medium sites who are using Hosted Apache Solr, a service I've been running as part of Midwestern Mac since early 2011.

Timeline of Apache Solr and Drupal Solr Integration

If you can't view the timeline, please click through and read this article on Midwestern Mac's website directly.

A brief history of Apache Solr Search and Search API Solr

Only two years after Apache Solr was released, the first module that integrated Solr with Drupal, Apache Solr Search, was created. Originally, the module was written for Drupal 5.x, but it has been actively maintained for many years and was ported to Drupal 6 and 7, with some relatively major rewrites and modifications to keep the module up to date, easy to use, and integrated with all of Apache Solr's new features over time. As Solr gained popularity, many Drupal sites started switching from using core search or the Views module to using Apache Solr.

Solr for Drupal Developers, Part 1: Intro to Apache Solr

It's common knowledge in the Drupal community that Apache Solr (and other text-optimized search engines like Elasticsearch) blow database-backed search out of the water in terms of speed, relevance, and functionality. But most developers don't really know why, or just how much an engine like Solr can help them.

I'm going to be writing a series of blog posts on Apache Solr and Drupal, and while some parts of the series will be very Drupal-centric, I hope I'll be able to illuminate why Solr itself (and other search engines like it) are so effective, and why you should be using them instead of simple database-backed search (like Drupal core's Search module uses by default), even for small sites where search isn't a primary feature.

As an aside, I am writing this series of blog posts from the perspective of a Drupal developer who has worked with large-scale, highly customized Solr search for Mercy (example), and with a variety of small-to-medium sites who are using Hosted Apache Solr, a service I've been running as part of Midwestern Mac since early 2011.

Why not Database?

Apache Solr's wiki leads off it's Why Use Solr page with the following:

If your use case requires a person to type words into a search box, you want a text search engine like Solr.

At a basic level, databases are optimized for storing and retrieiving bits of data, usually either a record at a time, or in batches. And relational databases like MySQL, MariaDB, PostgreSQL, and SQLite are set up in such a way that data is stored in various tables and fields, rather than in one large bucket per record.

In Drupal, a typical node entity will have a title in the node table, a body in the field_data_body table, maybe an image with a description in another table, an author whose name is in the users table, etc. Usually, you want to allow users of your site to enter a keyword in a search box and search through all the data stored across all those fields.

Drupal's Search module avoids making ugly and slow search queries by building an index of all the search terms on the site, and storing that index inside a separate database table, which is then used to map keywords to entities that match those keywords. Drupal's venerable Views module will even enable you to bypass the search indexing and search directly in multiple tables for a certain keyword. So what's the downside?

Mainly, performance. Databases are built to be efficient query engines—provide a specific set of parameters, and the database returns a specific set of data. Most databases are not optimized for arbitrary string-based search. Queries where you use LIKE '%keyword%' are not that well optimized, and will be slow—especially if the query is being used across multiple JOINed tables! And even if you use the Search module or some other method of pre-indexing all the keyword data, relational databases will still be less efficient (and require much more work on a developer's part) for arbitrary text searches.

If you're simply building lists of data based on very specific parameters (especially where the conditions for your query all utilize speedy indexes in the database), a relational database like MySQL will be highly effective. But usually, for search, you don't just have a couple options and maybe a custom sort—you have a keyword field (primarily), and end users have high expectations that they'll find what they're looking for by simply entering a few keywords and clicking 'Search'.

Filter/Search on multiple fields with Views 3.x

[Update: As of Views 7.x-3.4, you can now use the new "Global: Combine fields filter" to combine fields for an exposed search. Just add the fields you want to search to the view's Fields section, then add a 'Global: Combine fields filter' and select all the fields you want to search. Simple as that!]


A common need I run into with a ton of Drupal sites and Views is searching/filtering content based on multiple fields. For example, a lot of people would like to search for content using either the Title or the Body for a particular content type.

There are two primary solutions offered for this situation, but they both have downsides or are overly complex, in my opinion:

  • Use the Computed Field module to create yet another field stored in the database, combining the two (or more) fields you want to search, then expose a filter for that field instead of both of the individual fields. (I don't like this because it duplicates content/storage, and involves an extra module to do so).
  • Use the Views Filters Populate to invisibly populate a second field that you've added to a views OR group (using Views OR in Views 2.x, or the built-in AND/OR functionality in Views 3.x). (This module is slightly limited in that you can only work with strings, and again, it involves an extra module).

Instead of using an extra module, I simply do the following to achieve a multi-field search:

Microsoft Xbox 360 2011 December Update Apes iOS slide-to-search

In yet another example of Microsoft copying Apple's user interface concepts, the latest update to the Xbox 360's dashboard/Xbox LIVE integration now uses the same 'slide-to-left-to-search' user interface paradigm that started with Apple's iOS 3.0. Watch for yourself in the video below:

With Windows Phone 7, Microsoft's been taking some great steps in a new and innovative direction in UX/interaction design... but it seems their design teams still copy off Apple when they need to. Of course, there are worse companies to copy from—at least they're not copying Android!

Adding Images to Search Results (Drupal Search)

For a while (earlier in my Drupal career), I was avoiding adding imagefield-attached images to nodes that appeared in my search results, because I remember the first time I tried doing so, I was still quite confused by the way drupal handled search results theming.

Well, after another crack at it, I finally have a nice, performant way of displaying images from nodes added via imagefields (or in drupal 7, image fields) inline with search results, and it didn't require much work at all!

Images in Search Results

The image above shows inline images for LOLSaints.com, a site which uses Midwestern Mac's Hosted Apache Solr search service to return results quickly and allows faceting, etc. using the excellent Apache Solr Search Integration module. But the technique I'm using works equally well with built-in (but slower) Drupal core search module's results.

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