Posts Tagged ‘SOLR’
Here’s a quick roundup of search-related events coming soon:
Next week Lucene/Solr Revolution is to be held in San Diego, with a couple of days of training on April 29th & 30th and the main event on the 1st and 2nd May. This is probably the biggest event dedicated to Apache Lucene/Solr and features a huge array of presentations from Etsy, Wells Fargo, Lucidworks and even Microsoft who are increasingly supporting open source technologies.
Enterprise Search Europe is next on 15th and 16th May with a day of workshops on the 14th, including one from the Flax team. I’m looking forward to the various open source panels and presentations of course, and hearing from people from Ernst & Young, Neilsen Norman Group, Oracle and the University of Manchester. We’re also running a Meetup event on the first evening, open to all, with the usual informal mix of beer, snacks and search!
Some of the Flax team are hoping to attend Berlin Buzzwords on June 3rd & 4th – this conference promises to address “search”, “store” and “scale” – certainly sounds interesting! We know there will be lots of talks on elasticsearch and Lucene/Solr.
There’s more to come in the Autumn of course – more details when we know them. Hope to meet you at one of these great events!
One of the best things about the increased use of open source search technology is that features that were previously unattainable for clients with small budgets are now within reach. Our client Bride and Groom Direct, a UK-based business selling wedding gifts and stationery, asked us if we could help improve the search features on their website and in particular the auto-suggest – and they asked us to take a look at the website of US mega-retailer Sears.com for inspiration. They particularly liked the way that while you type, Sears’ website doesn’t just show you suggested words but also clickable picture previews of products you might be looking for.
Using Apache Solr and in under two days we built them a similar feature for their website: since we didn’t have direct access to their development servers we provided both Solr configuration files and a simple JQuery/Javascript demo of the features they needed (it’s about 170 lines of code). Their own developers then integrated these changes based on our notes. I think it’s safe to say that Bride and Groom Direct are a rather smaller business than Sears, but with open source they can have access to equally good search facilities. They’ve been kind enough to let us feature them on our Clients page and as you can see, they’re happy with the results.
The most well known open source search engine, Apache Lucene/Solr, has a rival in Elasticsearch, also based on Apache Lucene. Or maybe it doesn’t. I’m not convinced that there’s an actual battle going on here, above and beyond the fact that the commercial companies formed to support each technology (Lucidworks and Elasticsearch [the company]) are obviously competitors. Let’s look at the evidence:
- Elasticsearch contains (by some measures) 64 years of effort, Solr only 55 years….a point to Elasticsearch!
- Elasticsearch commits are 31% down on last year, Solr commits are 85% up…a point to Solr!
- There are more books about Solr than Elasticsearch…a point to Solr!
- Elasticsearch, sorry elasticsearch, has a cool lower case logo and fancy website…a point to Elasticsearch!
This is of course before we get to any actual technical differences in terms of performance, scalability, ease-of-use etc. which are probably a lot more important than the list above. There are vocal critics and supporters of each project on Twitter and other media, but the great thing in our view is that there is a choice of two such excellent search technologies, both open source, so for real world applications one can try both at little cost and choose whichever is most appropriate (there are even proven migration routes between the two – we’ve helped one client with this process).
It hasn’t taken long for some of Autonomy’s rivals to attempt to capitalise on the recent bad PR around HP’s acquisition – OpenText has offered a ’software trade-in’, Recommind has offered a ‘trade-up’ and Swiss company RSD has offered a free license for their governance software to Autonomy customers. No word yet from Exalead, Oracle (Endeca), Microsoft (FAST) or any of the other big commercial search companies but I’m sure their salespeople are making the most of the situation.
Migrating a search engine from one technology to another is rarely trouble-free: data must be re-indexed, query architectures rewritten, integration with external systems re-done, relevancy checked…however with sufficient forethought it can be done successfully. We’ve just helped one client migrate from a commercial engine to Apache Solr in a matter of weeks: although at first glance Solr didn’t seem to support all of the features the commercial engine provided, it proved possible to simulate them using multiple queries and with careful design for scalability, query performance is comparable.
Choosing one closed source engine to replace another doesn’t remove the risk that future corporate mergers & acquisitions will cause exactly the same lack of confidence that is no doubt affecting Autonomy customers – or huge increases in license fees, a drop in the quality of available support or the end of the product line altogether – and we’ve heard of all of these effects over the last few years. Moving to an open source search engine gives you freedom and control of the future of the technology your business is reliant upon, with a wealth of options for migration assistance, development and support.
So here’s our offer – we’d be happy to talk, for free (by phone or face-to-face for customers within reach of our Cambridge offices), to any Autonomy customers considering migration and to help them consider the open source options (some of these even have the Bayesian, probabilistic search features Autonomy IDOL provides) – and together with our partners we can also provide a level of ongoing support comparable to any closed source vendor. We don’t have salespeople, we don’t have a product to sell you and you’ll be talking directly to experts with decades of experience implementing search – and there’s no obligation to take things any further. We’d simply like to offer an alternative (and we believe, safer) route to effective search.
There’s an old saying that to find out what’s really going on, you have to “follow the money”. In the search industry two recent events have pointed the way: firstly, Attivio raised $34 million in new funding. Attivio produce a solution based on their own Active Intelligence Engine (yes, it’s still just a search engine) which itself is based on open source projects such as Apache Lucene. Secondly, this week the new(ish) company formed to offer support for the ElasticSearch open source search engine also raised funding to the tune of $10m.
From these two events we can conclude that the smart money has realised that the enterprise search market is heading in only one direction – towards open source software or solutions mainly based on it (another good example being our partner LucidWorks). News from this week’s ApacheCon in Germany of incredibly busy sessions around Lucene, Solr and ElasticSearch (as well as related and complimentary projects such as Stanbol) shows that the technical community agrees. I don’t think this will be the last time we hear of a significant investment by both the financial and technical communities in open source search.
There’s no doubt that the search market has been in turmoil for many months now: traditional, closed source vendors are either frantically repositioning to avoid the ‘juggernaut that is Apache’s Solr/Lucene project’ or attempting to bore customers to death with Powerpoint. Our sources tell us that in the UK at least, sales of most closed source search engines have flatlined – not at all surprising when freely available alternatives exist. Luckily there are some parts of the sector with some energy: Attivio (with $34m of new funding to spend) and Lucidworks are still working hard on their search products, but even these rely heavily on an open source core.
Enter a company without any history or experience in the search market, Huddle, with a tired message about the death of Enterprise Search. I’m not entirely sure what the point of this article is, but apparently the lack of contextual information is the problem - “You have to do research in 50 places — email, Web, C-drives, the cloud, even inside people’s heads.”. I look forward to a brain-compatible indexing tool! There’s also the misassumption that what works for the wider consumer-focused Web will work for the enterprise – Amazon.com, Google and the iPad/iPhone are all namechecked. Enterprise data simply isn’t like web or consumer data – it’s characterised by rarity and unconnectedness rather than popularity and context.
Unfortunately in most enterprises simply sprinkling on social or collaborative features will not fix the most common search problems: a mishmash of unconnected legacy systems, unreliable and inconsistent metadata, a complex and untested security model (at least within the context of being able to search for everything, for example your bosses’ salary) and usually the lack of a dedicated team responsible for search. Enterprise Search is hard and few projects get beyond basic indexing of filestores and databases, let along adding in more people-focused features.
I couldn’t find much about search on Huddle’s website, but what I did find implied that information must first be extracted from existing legacy systems and stored centrally. If you can manage this, preserving a consistent metadata model, coping with legacy formats, preserving full security and coping with updates then search should be relatively simple to implement on the resulting central store; however the devil is as ever in the detail.
After a short break the Cambridge Search Meetup returned last night with our usual mix of presentations, questions, networking, beer and snacks. We had a few issues with the projector and cables (one of these is on the shopping list for next time) so thanks to both presenters and audience for their patience!
First up was Liang Shen with a description of Journal Selector, a system for helping those publishing academic papers to find the correct journals to approach. The system allows one to copy and paste a chunk of a paper to a website and find which journals best match the subject matter, based on what they have published in the past. Running on the Amazon EC2 cloud the service indexes journals from feeds, HTML webpages and other sources, processes and stores this data in Amazon’s Hadoop-compatible database, indexes it with Apache Solr and then presents the results via the Drupal CMS. The results are impressive, allowing users to see exactly on what basis the system has recommended a journal to approach. You can see the presentation slides here.
Next was Rich Marr, who bravely offered to live-code a demonstration of his low-cost prototyping methodology for startups needing both NoSQL data storage and search across this data. In only 20 lines or so of code he showed us how to use Node.js to build a simple server that could accept messages (over Telnet, although HTTP or even IMAP would be as easy), store them in a CouchDB database and index them for searching (using a different message) with Elasticsearch. Rich’s demo prompted a lively discussion of how commoditized and componentized search technology is becoming, with open source components that allow one to build a prototype search engine in minutes.
Thanks to both our speakers – and the Meetups continue, with Rich Marr’s own London Open Source Search Social meeting on Tuesday 23rd October, and in Cambridge the Data Insights Meetup where I’ll be talking on November 1st.
This morning the largest open source search project, Apache Lucene/Solr, released a new version with a raft of new features. We’ve been advising clients to consider version 4.0 for several months now, as the alpha and beta versions have become available, and we know of several already running this version on live sites. Here’s a few highlights:
- Solr Cloud – a collection of new features for scalability and high availability (either on your own servers or on the Cloud), integrating Apache Zookeeper for distributed configuration management.
- More NoSQL features in case you’re planning to use Solr as a primary data store, including a transaction log
- A new web administration interface (including Solr Cloud features)
- New spatial search features including polygon support
- General performance improvements across the board (for example, fuzzy queries are 1-200 times faster!)
- Lucene now has pluggable codecs for storing index data on disk – a potentially powerful technique for performance optimisation, we’ve already been experimenting with storing updatable fields in a NoSQL database
- Lucene now has pluggable ranking models, so you can for example use BM25 Bayesian ranking, previously only available in search engines such as HP Autonomy and the open source Xapian.
The new release has been several years in the making and is a considerable improvement on the previous 3.x version – related projects such as elasticsearch will also benefit. There’s also a new book, Solr in Action, just out to coincide with this release. Exciting times ahead!
The exciting GOV.UK project is getting close to its first release date of October 17th and we were asked by them to help with some search tuning as they migrate from Apache Solr to elasticsearch. Although elasticsearch has some great features there are still some areas where it lags Solr, such as the lack of spelling suggestion and proximity boost features. Alan from Flax spent a couple of days working with the GDS team and has blogged about how proximity boosting in particular can be implemented – at least for terms that are relatively close to each other rather than being separated by a page or so.
If you’re interested in more details of how we fixed this and a few other elasticsearch issues, you may want to take a look at the code we worked on – one of the best things about working with the GOV.UK team is that it was already up as open source software within a day (yes, you read that right – code paid for by the taxpayer is open source, as it should be!). We’re looking forward to launch day!
Update: changed ‘proximity search’ to ‘proximity boost’ – thanks Alan!
It’s now eleven years since we started Flax (initially as Lemur Consulting Ltd) in late July 2001, deciding to specialise in search application development with a focus on open source software. At the time the fallout from the dotcom crash was still evident and like today the economic picture was far from rosy. Since few people even knew what a search engine was (Google was relatively new and had only started selling advertising a year before) it wasn’t always easy for us to find a market for our services.
When we visited clients they would list their requirements and we would then tell them how we believed open source search could help (often having to explain the open source movement first). Things are different these days: most of our enquiries come from those who have already chosen open source search software such as Apache Lucene/Solr but need our help in installing, integrating or supporting it. There’s also a rise in those clients considering applications and techniques outside the traditional site search or intranet search – web scraping and crawling for data aggregation, taxonomies and automatic classification, automatic media monitoring and of course massive scalability, distributed processing and Big Data. Even the UK government are using open source search.
So after all this time I’m tending to agree with Roger Magoulas of O’Reilly: open source won, and we made the right choice all those years ago.
