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Queries, Patterns, and Search – food for thought

Sunday, April 28th, 2013.

fishWith all the talk of CQRS, the area that doesn’t get enough treatment (in my opinion) is that of queries. Many are already beginning to understand the importance of task-based UIs and how that aligns to the underlying commands being sent, validated, and processed in the system as well as the benefits of messaging-centric infrastructure (like NServiceBus) for handling those commands reliably. When it comes to queries, though, it isn’t nearly as well understood what it means for a query to be “task based”.

Starting with CRUD

Let’s start with a traditional CRUD application and work our way out from there.

In these environments, we often see users asking us to build “excel-like” screens that allow them to view a set of data as well as sort, filter, and group that data along various axes. While we might not get this requirement right away, after some time users begin to ask us to allow them to “save” a certain “query” that they have set up, providing it some kind of name.

That, right there, is a task-based query and it is the beginning of deeper domain insight.

Pattern matching

Any time a user is repeatedly running the same query (this can be once a day or some other unit of time) there is some scenario that the business is trying to identify and is using that user as a pattern-matching engine to see if the data indicates that that scenario has occurred.

It’s quite common for us to get a requirement to add some field (often a boolean or enum) to an entity which defaults to some value and then see that same field used in filtering other queries. These measures are sometimes instituted as a temporary stop-gap while a larger feature is being implemented, though (as the saying goes) there is nothing more permanent than a temporary solution.

Where we developers go wrong

The thing is, many developers don’t notice these sorts of things happening because we don’t actually look at the kinds of queries users are running.

One excellent technique to better understand a domain is to sit down with your users while they’re working and ask them, “what made you run that query just now?”, “why that specific set of filters?”.

What I’ve noticed over the years is that our users find very creative ways to achieve their business objectives despite the limitations of the system that they’re working with. We developers ultimately see these as requirements, but they are better interpreted as workarounds.

I’ll talk some more about how a software development organization should deal with these workarounds in a future post, but I want to focus back in on the queries for now.

Oh, and don’t get me started on caching or NoSQL, not that I think that those tools don’t provide value – they do, but they’re only relevant once you know which business problem you’re solving and why.

Not all queries are created equal

Even before bringing up the questions I described in the previous section, any time you get query-centric requirements the first question to ask is “how often will the user be running this specific query?”.

If the answer is that the specific query will be run periodically (every day, week, etc), then drill deeper to see what pattern the user will be looking for in the data. If the person you’re talking to doesn’t know to answer that question, then go find someone who does. Every periodic query I’ve seen has some pattern behind it – and in my conversations with thousands of other developers over the years, I’ve seen that this is not just my personal experience.

But there is a case where a query does get run repeatedly without there being a pattern behind it.

I know this sounds like I’m contradicting myself, but the distinction is the word “specific” that I emphasized above.

There are certain users who behave very differently from other users – these users are often doing what I call research, i.e. the “I don’t know what I’m looking for but I’ll know it when I see it” people.

These researchers tend to repeatedly query the data in the system however they tend to run different queries all the time. This is the reason why traditional data warehouse type solutions don’t tend to work well for them. Data warehouses are optimized for running specific queries repeatedly.

Keeping the Single-Responsibility Principle in mind – we should not try to create a single query mechanism that will address these two very different and independently evolving needs.

And now on to Search

Search is a feature that is needed in many systems and whose complexity is greatly underestimated.

While the developer community has taken some decent strides in understanding that search needs to be treated differently from other queries, the common Lucene/Solr solutions that are applied are often overwhelmed by the size of the data set on which the business operates.

The problem is compounded by our user population being spoiled by Google – that simple little text box and voila, exactly what you’re looking for magically appears instantaneously. They don’t understand (or care) how much engineering effort went into making that “just work”.

Lucene and Solr work well when your data set isn’t too large, and then they become pretty useless as the quality of their results degrades. The thing is that many of us in IT tend to work on projects where we have an unrealistically small data set that we use to test the system and, at these volumes, it looks like our solutions work great. But if you have 20 million customers, do you think a full text search on “Smith” is going to find just the right one?

Larger data sets require a relevance engine – something that feeds off of what users do AFTER the query to influence the results of future queries. Did the user page to the next screen? That needs to be fed back in. Did they click on one of the results? That needs to be fed back in too. Did they go back to the search and do another similar search right after looking at a result – that should possibly undo the previous feedback.

And that’s just relevance for beginners.

You know what makes Google, you know, Google? It’s that they have this absolutely massive data set of what users do after the query that informs which results they return when. You probably don’t have that. That and search is/was their main business for many years – I’m betting that it’s not your main business.

You should discuss this with your stakeholders the next time they ask for search functionality in your system.

In closing

I know that the common CQRS talking points tell you to keep your queries simple, but that doesn’t mean that simple is easy.

It takes a fair bit of domain understanding to figure out what the queries in the system are supposed to be – what tasks users are trying to achieve through these queries. And even when you do reach this understanding, convincing various business stakeholders to change the design of the UI to reflect these insights is far from easy.

It often seems like the reasonable solution to give our users everything, to not limit them in any way, and then they’ll be able to do anything. What ends up happening is that our users end up drowning in a sea of data, unable to see the forest for the trees, ultimately resulting in the company not noticing important trends quickly enough (or at all) and therefore making poor business decisions.

Even if your company doesn’t believe itself to be in “Big Data” territory, I’d suggest talking with the people on the “front lines” just in case. Many of them will report feeling overwhelmed by the quantity of stuff (to use the correct scientific term) they need to deal with.

It’s not about Lucene, Solr, OData, SSRS, or any other technology.

It’s on you. Go get ‘em.

  
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8 Comments

  1. Geert Depickere Says:

    The technique you describe maps perfectly with the principles and practices of user centered design:

    [Users] have (business) [goals]. They execute [tasks] to achieve these goals. These tasks are performed in a certain [environment].

    To make the solution really user-friendly and practical you need to take into account all of these [aspects].

    One technique is to go and observe users as they execute their tasks currently and to ask lots of “why” questions to really discover what they want to achieve (their goals), and then try to find the best way for them to achieve this. This could be completely different from how they do it today (running the same query repeatedly and searching for the answers they are after vs. having the system do the searching for them and present them the answers in an email).

    So don’t rush in and give the users what they ASK for, but take a step back and try to give them what they NEED.


  2. Lev Gorodinski Says:

    Insightful post about query usage patterns. From my experience, CQRS has raised awareness of queries by making their implementation more explicit. Furthermore, the notion of task-based UI also calls for domain -based analysis of queries as it does for commands.

    Do you have any specific examples of relevance engines that you’ve seen?

    I disagree with Lucene/Solr not being able to scale. Even a single node installation is quite adept at searching large data sets sufficient for many enterprises. The Lucene-based ElasticSearch can take you far beyond that as it powers GitHub, Foursquare, SoundCloud, Sumtbleupon. As far as I remember, it event powers the search engine DuckDuckGo hosted on AWS. I do agree however that implementing search even with a single node installation is no trivial task requiring a great deal of plumbing to be in place to integrate with existing data sources.


  3. udidahan Says:

    Geert – yes, I draw heavily on that background.


  4. udidahan Says:

    Lev,

    When I say they don’t scale – I don’t mean technically. I mean that the quality of their results degrades. Will update the post to reflect that.


  5. Lev Gorodinski Says:

    OK that makes more sense!

    Do you think the relevance engine for enterprise search is best driven by signals such as clicks after the search or other signals used by Google, or is it worthwhile to first consider domain-specific signals?

    For example, the search for “Smith” will usually have some context which can be associated with the query. If this contextual information is indexed then Lucene’s relevance engine can suffice.

    I think incorporating generic signals, such as one’s used by Google, can be helpful, but may require a large amount of data on user searches. Google certainly has it, but an enterprise may not.


  6. udidahan Says:

    Lev,

    I think the best thing to do is to step AWAY from search and look at usage patterns like “last N [entity] viewed” and make those explicit to users.

    I’d also say that having a view for “hot” entities that other users are operating on can also reduce how much people lean on search. The reason for this is that multiple users often end up collaborating on the same related set of entities.

    Once all that’s been filtered out, then you start with other domain-specific filtering for search (phone numbers, addresses, user “friendly” IDs).

    In short, avoid “generic” search as much as possible – it’s too hard.


  7. Joey Guerra Says:

    I have to say, I’m really impressed as to how you can articulate this phenomenon. I strive to get better at that. I worked at true.com (dating site) and was always irritated with the term “search” because I’ve always felt that as a single guy, I want to find a date so I can get a girlfriend. I didn’t want to spend my time “searching”. Needless to say I couldn’t convince the president of the company to follow the thought process implied by this simple idea. It really blows my mind how hard it is to convince people that most of the search software that we build should really by finding. Not searching. My team just built a subscription management system (using nservicebus by the way) that contains a CRM web app used by customer care to find subscribers when they call in. The mindset is still about searching for subscribers instead of finding them. And I realize its a difficult distinction to comprehend. I really think its about the initial perspective when defining the problem. Unfortunately, a third party vendor was contracted to build the system and it was too late for me to influence the finding part of the business but this is an area where if the software assisted the customer care rep to “find” a subscriber, it would make them more efficient. More effective. Anyways, this article rings true to me.


  8. Arturo Hernandez Says:

    On the decision to store aggregates themselves or store data on a normalized database. It is true that we don’t need to store it in a normalized table. But If I understood correctly you suggest for responsiveness and optimization sake to often times store only the aggregates. In my experience it is simpler to think on normalized data terms, than it is to think in terms of aggregates. And actually, I rather the system itself compile away the tables into aggregates. This last thing is impossible now. But when we are looking at DDD, shouldn’t we look at the simplest way of writing an app? Maybe there is a mental switch that just has not tripped in my head. I while it has not tripped I still think it is easier to think first about data when it is normalized.


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He started out with sketching a naive traditional n-tier application (big ball of mud), and based on suggestions from the audience we explored different solutions which might improve the solution. Whatever suggestions we threw at him, he always had a thoroughly considered answer describing pros and cons with the suggested solution. He obviously has a lot of experience with real world enterprise SOA applications.”

Raphaël Wouters Raphaël Wouters, Owner/Managing Partner at Medinternals
“I attended Udi's excellent course 'Advanced Distributed System Design with SOA and DDD' at Skillsmatter. Few people can truly claim such a high skill and expertise level, present it using a pragmatic, concrete no-nonsense approach and still stay reachable.”

Nimrod Peleg Nimrod Peleg, Lab Engineer at Technion IIT
“One of the best programmers and software engineer I've ever met, creative, knows how to design and implemet, very collaborative and finally - the applications he designed implemeted work for many years without any problems!

Jose Manuel Beas
“When I attended Udi's SOA Workshop, then it suddenly changed my view of what Service Oriented Architectures were all about. Udi explained complex concepts very clearly and created a very productive discussion environment where all the attendees could learn a lot. I strongly recommend hiring Udi.”

Daniel Jin Daniel Jin, Senior Lead Developer at PJM Interconnection
“Udi is one of the top SOA guru in the .NET space. He is always eager to help others by sharing his knowledge and experiences. His blog articles often offer deep insights and is a invaluable resource. I highly recommend him.”

Pasi Taive Pasi Taive, Chief Architect at Tieto
“I attended both of Udi's "UI Composition Key to SOA Success" and "DDD in Enterprise Apps" sessions and they were exceptionally good. I will definitely participate in his sessions again. Udi is a great presenter and has the ability to explain complex issues in a manner that everyone understands.”

Eran Sagi, Software Architect at HP
“So far, I heard about Service Oriented architecture all over. Everyone mentions it – the big buzz word. But, when I actually asked someone for what does it really mean, no one managed to give me a complete satisfied answer. Finally in his excellent course “Advanced Distributed Systems”, I got the answers I was looking for. Udi went over the different motivations (principles) of Services Oriented, explained them well one by one, and showed how each one could be technically addressed using NService bus. In his course, Udi also explain the way of thinking when coming to design a Service Oriented system. What are the questions you need to ask yourself in order to shape your system, place the logic in the right places for best Service Oriented system.

I would recommend this course for any architect or developer who deals with distributed system, but not only. In my work we do not have a real distributed system, but one PC which host both the UI application and the different services inside, all communicating via WCF. I found that many of the architecture principles and motivations of SOA apply for our system as well. Enough that you have SW partitioned into components and most of the principles becomes relevant to you as well. Bottom line – an excellent course recommended to any SW Architect, or any developer dealing with distributed system.”

Consult with Udi

Guest Authored Books
Chapter: Introduction to SOA    Article: The Enterprise Service Bus and Your SOA

97 Things Every Software Architect Should Know



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