TNR Global Software Engineer Completes LucidWorks Solr Training

A Hands-On Workshop for Building Killer Search Apps–best practices to develop scalable, high availability and high performance search applications.

TNR Global announces the completion of LucidWorks “Solr Unleashed– A Hands-On Workshop for Building Killer Search Apps” training course.  The course was attended by senior software engineer Chaim “Jeff” Peck.

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From LucidWorks: A Hands-On Workshop for Building Killer Search Apps “This three-day class is designed to offer students in-depth information to implement Solr search engine technologies. Through a combination of lectures, hands-on lab exercises and tutorials, students will learn to apply best practices to develop scalable, high availability and high performance search applications. At the end of the course, students will understand how to set up and use Solr to index and search, how to analyze and solve common problems, and how to use optional Solr modules.”

“Jeff completed the course this summer with flying colors, and his attendance there rounds out our search team’s Solr skills wonderfully,”  said Karen Lynn, Director of Business Development.  “Our search team has been working with Solr for a couple of years now but Jeff’s focus was committed to a commercial search product that we also work with.  We like our team to be well balanced and cross trained in several search applications, so Jeff completing this course was really the final piece of the puzzle in our Solr background.”

TNR Global is an authorized integration partner for LucidWorks Enterprise search products.

The Future of Search Doesn’t Come in a Box: The Google Mini Says Goodbye

The future of search doesn’t come in a box.

Last week while many were on vacation, Google abandoned the smallest member of its’ Search Appliance family, the Google Mini. The small blue piece of external hardware was used for smaller data sets with a stable, some might say stagnant, data with slow and steady query rates. If you were a smaller business with search demands that weren’t, well–too demanding, then this piece of hardware could help you for a reasonable price tag.

Search evolves like all technologies do. Developers incorporate emerging technologies into their skill sets, and open source technologies like Lucene Solr have matured into a competitive option for companies of all sizes. IT managers are finally ready to move away from the confines of a Search Appliance in a box and move to a more agile solution that can offer room for growth, a lightweight application, and a healthy and growing community. Without the hefty annual licensing fees of a commercial product, Solr can save small to mid sized companies and startups valuable cash resources to invest in other areas of their respective businesses.

Open source technologies aside, many are speculating if Google will retire some of its other pieces of hardware like the well know GSA (Google Search Appliance). Although Google has a newly released version 6.14 with an updated website to easily explain features. Google continues evolving its enterprise search offerings to include a hosted search solution for e-tailers called Google Commerce Search, along with their standard Google Site Search. Neither of these products come in a physical blue or yellow box, and I wouldn’t expect Google’s next innovation to either.

There’s plenty lively discussion about this in the Enterprise Search Professionals discussion board on LinkedIn.

Fast to Lucene Solr: Choosing a Document Processing Pipeline for Solr

If we want to leverage the power that Solr offers, but we need support for a more robust document processing framework, what are our options?

One of the most powerful features of FAST ESP is its flexible document processing engine. The engine that ships with FAST ESP supports multiple document processing pipelines that comprise of multiple document processing stages. A document processing stage performs a document processing task and can add, modify or remove elements from a document before it is passed to the next stage in the pipeline. A simple example of processing stage would be one that processes a document’s URL element, ESP ships with many processing stages and several processing pipelines out of the box for handling both structured and unstructured documents. FAST ESP document processing engine also provides a Python plugin API to allow customers to create custom processing stages of their own, which is a feature we use heavily for our customer ESP installations.

Unfortunately, Solr does not offer the same robust support for document processing pipelines that ESP does. The ESP processing pipeline is document-centric while the Lucene Solr platform is field-centric. When a document is fed to ESP for processing, it is routed to processing stages in a processing pipeline that can access document elements generated by previous processing stages. This allows for complex and optimal operations that can leverage previous processing, such as reuse of a previously generated HTML DOM tree structures. When a document is passed to a Solr update handler, the document is broken up into a set of individual fields. Each field can have a set of processors known as Solr Analysis Filter that can be chained together for field processing before indexing occurs. While this is fine for content that has been heavily processed before being sent to Solr, individual filters lack the same level of access to other documents elements to easily support more complex processing behaviors.

Another difference between ESP and Solr platforms is that ESP’s document processing architecture allows it to be scaled independently from its indexing architecture. ESP’s document processing architecture is fully decoupled from its indexing architecture and is designed out-of-the-box to take advantage of multiple processor cores per machine and multiple document processor machines per cluster. Solr’s out-of-the-box document processing architecture is tightly coupled with its indexing architecture, making it difficult to independently scale Solr’s content processing capacity without adding the complexity and overhead of additional Solr services and Lucene indexes. When we work with multiple terabyte document sets, we find content processing tends to be the biggest bottleneck, so being able to scale content processing ability separately from indexing is mission critical.

If we want to leverage the power that Solr offers, but we need support for a more robust document processing framework, what are our options? There are quite a number of content processing frameworks we can chose from that we discovered during the course of our research. Some of the options currently available include, but are not limited to OpenPipeline OpenPipe, Pypes, UIMA, SMILA , Apache Commons Pipeline, Piped, Behemoth, and Cascading.

Most of these frameworks are written in Java which gives them access to an incredibly broad and diverse spectrum of Java libraries. Since Solr and Lucene are also written in Java, it might make a lot of sense to favor a Java processing framework from scratch, especially if you are more comfortable with Java as a programming language.

Since our clients tend to have highly customized document processing pipelines with many custom FAST ESP Python processing stages, we are heavily biased towards choosing a framework that minimizes the amount of code that would need to be migrated. Many of the available processing frameworks are written in Java, which would be fine if you prefer using Java and don’t have a large amount of currently working Python code to migrate. For our use cases, the decision of which framework to chose was incredibly simple given the option, so we chose Pypes for our migration solution.

For a full report on how we use Pypes for a Document Processing Engine including sample code, sign up for our free FAST to Lucene Solr White Paper here.

FAST ESP to Lucene Solr Presentation: Open Call for Questions

To pre-load the discussion on Michael’s Enterprise Search: FAST ESP to Lucene Solr talk, send your questions to: fast2solr@tnrglobal.com We want to hear from you!

TNR Global is excited to be participating in the Apache Lucene EuroCon conference in Barcelona.  Our own Michael McIntosh is scheduled to present:  “Enterprise Search: FAST ESP to Lucene Solr” Here is your chance to pre-load the discussion. Before Michael puts the final touches on his talk, he wants to know what issues or questions you may be have.  In the following video, he touches on some of the highlights of his upcoming talk, and asks for your input.

Enterprise Search: FAST ESP to Lucene Solr pre-conferece video - Click to Watch
Enterprise Search: FAST ESP to Lucene Solr pre-conf video

To participate in advance, send you questions or comments to:  fast2solr@tnrglobal.com.  While Michael cannot promise he will include your question or commentary in his actual talk, he will work to address them in an upcoming White Paper, to be released after the conference in November 2011. We look forward to hearing from you!

Migration Still Looms Large on the Horizon for FAST ESP Customers

“Designing a non-trivial search solution to fully meet your needs from scratch is hard enough on its own. If you are migrating an existing solution, it is very unlikely that you will find a one to one mapping of all of the features in a new search engine that you have come to depend upon with your existing implementation.” –Michael McIntosh, VP of Search Technologies, TNR Global, LLC

Microsoft acquired FAST all the way back in 2008 and then in early 2010 disclosed it’s plans to stop updating the FAST product on a Linux operating system after 2010, making FAST ESP 5.3 the latest and greatest, and very last update Linux users will see involving any improvements to the proprietary search platform. It was clear to anyone on Linux that a migration would need to occur, and as content grows, depending upon the size of your organization, that migration should probably happen sooner than later.

Buzz about migration ensued–an inevitable certainty for many companies, especially ones with huge amounts of data. But how many companies have jumped in with both feet? I had the opportunity to speak with an open source search engine expert who, along with the industry, believed that the move from Microsoft was a windfall for anyone in the business of enterprise search design and implementation. However, she admitted “we haven’t seen as large a response as we expected.”

This isn’t exactly surprising to everyone. “It’s coming” says our VP of Search Technologies, Michael McIntosh. “Corporations have an enormous investment in FAST ESP and it makes sense that they would be reluctant to move to something new until they absolutely have to.” That means, when their licenses expire.

“They will likely weigh the performance and support, or lack thereof, for the FAST ESP technical team with the timing of renewing a license and wait until they absolutely have to change to something else,” says McIntosh.

The purchase of Autonomy and the shift of HP from hardware to software could signal a recognition from Goliath HP the kind of growth opportunity enterprise search software offers, and that the “great shift” from FAST ESP to another search platform is very much on the horizon.

But as the clock continues to tick, companies using FAST ESP should be strategizing for migration now. “It’s an enormous undertaking to migrate an entire search solution from FAST to another platform. Designing a non-trivial search solution to fully meet your needs from scratch is hard enough on its own. If you are migrating an existing solution, it is very unlikely that you will find a one to one mapping of all of the features in a new search engine that you have come to depend upon with your existing implementation. Solving challenging issues like that requires both creativity and expertise to address your needs.” says McIntosh. If a need for migration is eminent, there will be a real need for expertise in the field of enterprise search on both proprietary and open source platforms, depending upon several factors like size, in house talent, and growth expectations.

How is your company preparing for the discontinuation of support of FAST ESP?  Need guidance?  Contact us for pointers, analysis, or architecture for a full migration.

Open Source Search Engines vs. Proprietary Search Engines

“If you are a cutting edge company, you will be severely limited by a proprietary search engine as a solution. The more open the technology, the more able we are to refine it to meet our client’s needs.” –Michael McIntosh, TNR Global

There are plenty of articles about the pros and cons of open source software vs. proprietary software. I sat down with our VP of Search Technologies Michael McIntosh to discuss the benefits of each in terms of search engines.

Karen: You’ve been working with proprietary search engines for some time now. Tell me your thoughts on that. What’s the upside of proprietary?

Michael: I’ve worked with proprietary search engines for several years, specifically with FAST ESP since 2003 back when it was known as FAST Data Search (FDS). Proprietary software products often have better documentation, better support; more thought out design and are more aggressively tested. Because the product supports an entire company—it must succeed. They have nicer tools, nicer interfaces.

Karen: And the downsides?

Michael: “Over the years, we’ve run into a number of difficulties with proprietary search engines. One thing that comes up is that if a problem isn’t outlined in user troubleshooting documentation, it can become incredibly difficult to diagnosis and correct, and doing that is a frustrating, time intensive problem. The black box nature of the product is very limiting. If it’s not in documentation, it might as well not exist at all.”

Karen: There are gaps in the user manual?

Michael: “Yes. But in defense of FAST ESP, the documentation has improved by leaps and bounds over the years. However, one anomaly we find is that the clean, easy to read PDF form of user documentation (the original) for ESP is often not as up-to-date or helpful as the searchable online documentation—which is harder to read, but usually more current and correct. Sometimes even the online documentation is wrong—which is also frustrating. But it has become something we cope with regard to FAST”

Karen: Give me an example of what kind of problems you run into when integrating the proprietary search engine into a client’s website.

Michael: “The enterprise search platform uses Service Oriented Architecture (SOA). That is a bunch of different components that are able communicate with each other as services. With this type of architecture, it doesn’t matter which language you write something in as long as it’s a service another language can communicate with via RESTful interfaces, SOAP or something like XML-RPC. These services can all work together, despite the fact you don’t have a unified api—and that’s actually awesome.

Karen: Why?

Michael: “Indexers for one—you generally don’t want them written in an interpreted language for performance reasons. Indexing can be a CPU intensive operation, which can be a weak spot for interpreted languages such as Python or Ruby compared to languages like C/C++ or Java. It is both CPU and disk intensive process so a scripting language can be great if you’re writing an application that’s not CPU intensive because code speed doesn’t matter so much. The true slow-down is something outside the script. You can optimize the speed of the script to make it run as fast as humanly possible but you’re limited because the disk can only rotate so fast. Your indexing service can be written in a low level language like C vs. some of the other services in languages like Python or Ruby or Java and get good performance. BUT if you don’t have documentation for compiled programs that make up the search engine product you’re going to have a terrible time trying to figure out how to fix issues when they arise.

Karen: “So basically, because you have so many different languages being used that you lack the source code for, and documentation is spotty, it becomes a needle in a haystack trying to figure out where the problem occurs.”

Michael: “Yes. And this is not such a problem for anyone using a search engine for really basic applications. The place where you run into problems is if you push the search engine technology to its limits or you are using it in ways outside its typical usage, which is almost everything we do. We are always trying to get the best possible performance out of the search engine. We’re trying to get the search engine to deal with features we need but it doesn’t natively support.

Karen: “What is it you’re pushing specifically for the search engine to do?”

Michael: “One thing we want is for FAST ESP to have is a feature to deal with creating a faceted search for arbitrary fields. The way ESP works is that it has an index profile which is a statically defined set of fields that it indexes. Inside its index profile you can mark certain fields to have navigators. One of our customers deals with product verticals. They have a whole bunch of products that aren’t unified—all with completely different attributes. We’ve managed to work around these roadblocks in ESP to create faceted navigation on arbitrary fields.

Karen: “So you get creative to make it better.”

Michael: “Yes we constantly get creative to make it better to use its strengths and find ways to work around its limitations.”

“Another issue we have with ESP is we have a number of websites we need crawled and each website has metadata associated with it. Unfortunately the way the ESP crawler works, there are not many straightforward ways to preserve metadata associated with the seed URL which we use to crawl a website and pass the meta information along to any associated links. We can’t do this easily inside the ESP crawler. Since its proprietary and black box, we can’t look at the source code to the crawler, and can’t modify the source code to the crawler. When it does something mysterious, we can have no idea why it might be behaving in an unwanted way. We had one instance when we had a number of websites the crawler was temporarily blacklisting for some reason. When the ESP crawler automatically blacklists a site, it stops crawling the site for 30 minutes and then begins again after 30 minutes. We learned one thing that triggers blacklisting is if a website has HTTP 503 errors. If a site has more than 20 or so of those errors, the crawler temporarily blacklists the site. The problem was that the documentation is too sparse on details for that topic. When we ran into that problem—it was really difficult to know what was going on so we could properly explain the issue to the client and address the problem. Conversely, if we had an open source search engine, I could have just searched the source code and speed up the diagnosis of the problem.”

Karen: So from a business prospective—using open source allows you to invest in a technology that gives you the power to modify the code to better meet your business needs.

Michael: “It certainly can. It can accelerate development time and speed of diagnosing problems when issues pop up. And issues always do pop up. If something is not working very well, we can look at the problem which a much higher degree of granularity.

If it’s a simple problem, we never contact support. We only contact support when we’re stumped. And we’re not easily stumped. Usually, they can’t answer they question immediately because if we’re asking for help, the problem is complex. Our ticket is escalated, and eventually we talk to someone who can help us. But it does take time. Even if a support staff is top notch, there is the time is costs to deal with that, and that costs us and our clients’ time. We have a highly customized ESP installation for one of our clients it always take an enormous amount of time to explain over and over how we have our systems set up, the different parts work, and it’s a big pain to go through that every time I run across a problem. If it were open source, I can simply look at the source code and solve the problem.”

Karen: Let’s talk in more detail about open source search engines. Upsides?

Michael: “If you choose a popular open source search engine solution like Lucene Solr, you have an active, passionate community behind that solution. There are several developers looking at that engine, working on it, and actively posting in publicly available forums. You can often get your questions answered there by top notch experts in search technology. You can potentially talk to the original coders and creators of the product—and they are often happy to help you. I’ve seen people post a Solr question on their twitter feed and within 7 seconds, the creator has responded with a link to a forum explaining the solution.

Karen: Wow, that’s amazing. Other advantages?

Michael: “It’s free. That’s attractive to most companies. The downside is the formal documentation isn’t usually as good as the proprietary, and there isn’t a dedicated support team for the product. But if you have some savvy software developers on your team, the open source community is robust and willing to share information about the product. And having access to the source code is extremely valuable.”

Karen: So in your opinion, what’s the bottom line on Open Source Search Engines vs. Proprietary Search Engines?

Michael: “If you are a cutting edge company, you will be severely limited by a proprietary search engine as a solution. The more open the technology, the more able we are to refine it to meet our client’s needs.”

If you’d like more information on the pros and cons of Open Source Search Engines vs. Proprietary Search Engines that are specific to your business or organization’s needs, feel free to contact us for a free consultation.

TNR Global to present at Apache Lucene Eurocon 2011 in Barcelona

We are happy to announce that TNR Global’s own Michael McIntosh will be presenting at the Apache Lucene Eurocon 2011 in Barcelona this October.  Michael’s talk is titled Enterprise Search:  FAST ESP to Lucene Solr.” His presentation will discuss migration from the FAST ESP platform to a Lucene Solr search platform. There are many reasons an IT department with a large scale search installation would want to move from a proprietary platform to Lucene Solr. In the case of FAST Search, the company’s purchase by Microsoft and discontinuation of the Linux platform has created an urgency for FAST users. Illustrated through actual case studies, the presentation will include challenges and concerns, present solutions and work-arounds to overcome migration issues.

Michael has more than 16 years of experience in large scale systems design and operation, online consumer product development, high volume transaction processing and engineering management. He has extensive experience developing, integrating and maintaining search technology solutions for companies such as FAST Search and Lycos.

We’re excited that Michael will be presenting in Barcelona this fall.  Please introduce yourself if you’re able to go!

Migration from FAST ESP to Lucene Solr

Download the presentation and see the video.

Michael McIntosh, Vice President of Enterprise Search Technologies at TNR, spoke at the Lucene Revolution conference in Boston, MA October 7-8, 2010. Michael reviewed the migration from Fast ESP to Lucene/Solr open source search. He discussed approaches to identifying core content areas of HTML documents such as Text-To-Tag Ratio Heuristics and Page Stereotype/Site Template Analysis, and reviewed specific use cases that we have encountered as search integration experts and discuss available tools.

TNR Global was a sponsor of Lucene Revolution. The conference gathered over 400 professionals from the enterprise search industry. We were happy to see so much interest in Lucene/Solr open source search, and get to know and learn from the folks who have done large scale implementations, including Twitter, LinkedIn, and eHarmony.  Not surprisingly, there was a lot of interest about migration from proprietory search systems to Solr, especially from FAST ESP due to Microsoft’s discontinuing FAST ESP support for Linux.  If you would like to learn more about how a migration from FAST ESP to Lucene Solr can benefit your company, contact us for a free consultation.

Migration from Microsoft FAST to Apache Lucene Solr

Is your company using Microsoft FAST ESP on a Linux platform?  Unfortunately, Microsoft announced in 2010 they will cease technical support for FAST ESP 5.3 after it’s 5 year life cycle for anyone using Linux as their operation system. Migration to another search platform will be a priority, and business leaders and technology professionals are looking closely at Lucene Solr as a solution.

We can assist your organization in any stage of a migration. We can perform an evaluation of your current architecture, draft a plan for migration, work with your internal team on the migration or just consult as needed. Whatever your specific needs are, we can help you achieve your goals. Read our White Paper released February 2012 that presents a Case Study on migration. The paper discusses:

  • Loading millions of documents into Solr indexes
  • Evaluation and recommendations for tools to bridge the features gap
  • Migrating custom pipeline code to Pypes with minimal changes
  • Proven ROI after a complete migration

Additionally, we have presented on the subject of FAST ESP to Lucene Solr migrations for the Lucene Revolution Conference in Boston, MA (2010 Slides: Migration from FAST ESP to Lucene Solr (PDF) (pdf:4,067,091)) and at the Apache Lucene Eurocon (web site dead) Barcelona (October 2011). Watch our VP of Search Technology Michael McIntosh’s presentation on FAST to Lucene Solr Migration below. If you like what you see, contact us to explore a Solr migration solution.


                                                                                                                     

Slide presentation 

Enterprise Search White Papers and Presentations

Below are links to our mini white papers, addressing questions about enterprise search and more.

Enterprise Search Basics (pdf:157,797) Enterprise Search and Government (pdf:112,083) Enterprise Search for Law Firms (pdf:110,350) Enterprise Search and E-Discovery (pdf:108,855)

Please contact us for additional information.

Migration from FAST ESP to Lucene Solr, by Michael McIntosh, VP, Enterprise Search Technologies, TNR Global

Video from the Lucene Revolution conference in Boston, MA.

from-fast-esp-to-solr

Migration from FAST ESP to Lucene Solr (PDF) (pdf:4,067,091)
presented by Michael McIntosh, VP, Enterprise Search Technologies, TNR Global at the Lucene Revolution Conference in Boston, MA.
There are many reasons that an IT department with a large scale search installation would want to move from a proprietary platform to Lucene Solr. In the case of FAST Search, the company’s purchase by Microsoft and discontinuation of the Linux platform has created an urgency for FAST users.
This presentation compares Lucene/Solr to FAST ESP on a feature basis, and as applied to an enterprise search installation. We explore how various advanced features of commercial enterprise search platforms can be implemented as added functions for Lucene/Solr. Actual cases are presented describing how to map the various functions between systems.