On Lucid Imaginations Blog Jay Hill published a great article on The seven deadly sins of solr. Basically it is a collection of his experiences “analyzing and evaluating a great many instances of Solr implementations, running in some of the largest Fortune 500 companies”. It is a collection of common mistakes, mis-configurations and pitfalls in Solr installations in production use.
I loved the article very much. However, many of the symptoms that Jay described in his article do not apply to Solr installations only. In the following I will try to come up with a more general classification of errors that occur when your average Java developer starts using a sufficiently large framework that is supposed to make his work easier. Happy about any input on your favourite production issues.
Remark: What is printed in italic is quoted as is.
Sin number 1: Sloth - I’ll do it later
Let’s define sloth as laziness or indifference. This one bites most of us at some time or another. We just can’t resist the impulse to take a shortcut, or we simply refuse to acknowledge the amount of effort required to do a task properly. Ultimately we wind up paying the price, usually with interest.
There is even a name for it in Scrum: Technical debt. It may be ok to take a shortcut, given this is done based on an informed decision. As with regular debt, you may get a big advantage like launching way earlier than your competitor. However as with real debt, it does come at a prize.
Lack of commitment
Jay describes the problems that are especially frequent when switching search applications: Humans in general do not like giving up their habits. A nice example described in more detail in a recent Zeit article is what happens each year in December/ January when the first snow falls: It is by no means irregular or not to be expected that it starts snowing in December in Germany. However there will be lots of people who are not prepared for that. They refuse to put on winter tiers in late autumn. They use their car instead of public transport despite warnings in public press. The conclusion of the article was simple: People are simply not willing to change habits they got used to. It does take longer and is a bit less flexible to get to work by public transport instead of your own car. It does require adjusting your daily routine, optimising your processes.
Something similar happens to a developer that is “forced” to switch technology, be it the search server, the database, the build system or simply the version control system: The old ways of doing stuff simply may not work as expected. New tools might be called for. New technologies to learn. However in not so seldom cases developers just blame the new tools: “But with the old setup this would always work.”
Developing software - probably more than anything else - means constant development, constant change. Technologies shift as tasks shift, tools are improved as workflows change. Developing software means to constantly watch closely what you are doing, reflecting on what works and what doesn’t and changing things that don’t work. Accepting change, seeing it as a chance rather than an obstacle is critical.
If however change is imposed on developers though good arguments in favour of the old approach exist, it may be worth the effort to at least take the technical view into account to make an informed decision.
Not reviewing, editing, or changing the default configuration files.
I have extended this one a bit: Developers not changing default configuration files are not that uncommon. Be it the default database configuration, default logging configuration for your modules or default configuration of your servlet container. Even if you are using software pre-packed by your distribution, it is still worth the effort to review configuration files for your services and adjust them to your needs. Usually they are to be used as examples that still need tweaking and customization after roll-out.
JVM settings and GC
If you are running Java application there is no way around to adjust GC settings as well as general JVM settings to your particular use case. There are great tutorials at sun.com that explain both the settings themselves as well as several rules-of-thumb of where to start. Still nothing should stop you from measuring your particular application and its specific needs - both, before and after tuning. Along with that goes the obvious recommendation to simply “know-your-tools” - learning load testing tools shortly before launch time is certainly no good choice. Trying to find out more on Java memory analysis late in the development cycle just because you need to find that stupid memory leak like *now* is no good idea neither.
There are several nice talks as well as several tutorials available online on the topic of JVM tuning, debugging memory as well as threading issues, one of them being the talk by Rainer Jung at Frocson 2008.
Sin number 2: Greed
Running a service on insufficient hardware (be it main memory, harddisks, bandwidth, …) is not only an issue with Solr installations. There are many cases where just adding hardware may help in the short run, but is a dead-end in the long run:
- Given a highly inefficient implementation, identifying bottlenecks, profiling, benchmarking and optimization go a long way.
- Given an inappropriate architecture, redesign, reimplementation and maybe even switching base technologies does help.
However as Jay pointed out, running production servers with less power than your average desktop Mac has does not help neither.
Sin number 3: Pride
Engineers love to code. Sometimes to the point of wanting to create custom work that may have a solution in place already, just because: a) They believe they can do it better. b) They believe they can learn by going through the process. c) It “would be fun”. This is not meant to discourage new work to help out with an open-source project, to contribute bug fixes, or certainly to improve existing functionality. But be careful not to rush off and start coding before you know what options already exist. Measure twice, cut once.
Don’t re-invent the wheel.
As described in Jay’s post, there are developers who seem to be actively searching for reasons to re-invent the wheel. Sure, this is far easier with open source software than with commercial software. Access to code here makes the difference: Understanding, learning from, sharing and improving the software is key to free software.
However there are so many cases where improve does not mean re-implement but submitting patches, fixing bugs, adding new features to the orignal project or just refactoring the original code and ironing out some well known bumbs to make life easier for others.
Every now and then a new query abstraction language for map reduce pops up. Some of those really solve distinct problem settings that cannot (and should not) be solved within one language. Especially if a technology is young, this is pretty usual as people try out different approaches to see what works and what does not work out so well. Good and stable things come from that - in general the fittest approach survives. However, too often I have heard developers excusing their re-invention by “having had too few time to do a throughough evaluation of existing frameworks and libraries”. The irony here really is that usually, coding up your own solution does take time as well. In other cases the excuse was missing support for some of the features needed. How about adding those features, submitting them upstream and benefitting from what is already there and an active community supporting the project, testing it, applying fixes and adding further improvements?
Make use of the mailing lists and the list archives.
Communication is key to success in software development. According to Conway’s law “Organizations
which design systems are constrained to produce systems which are copies of the communication structures of these organizations.” I guess it is pretty obvious that developing software today generally means designing complex systems.
In Open source, mailing lists (and bug trackers, the code itself, release notes etc.) are all ways for communication. (See also Bertrand’s brilliant talk on open source collaboration tools for that). With in-house development there is even added benefit as face-to-face communication or at least teleconferencing is possible.
However software developers in general seem to be reluctant to ask questions, to discuss their design, their implementation and their needs for changes. It just seems simpler to work-around a situation that disturbs you instead of propagating the problem to its source - or just asking for the information you need. A nice article on a related topic was published recently it-republik.
However asking these questions, taking part in these discussions is what makes software better. It is what happens regularly within open source projects in terms of design discussions on mailing lists, discussions on focussed issues in the bug tracker as well as in terms of code review.
There are several best practices that come with Agile Development that help starting discussions on code. Pair programming is one of these. Code reviews are another example. Having more than two eye balls look at a problem usually makes the solution more robust, gives confidence in what was implemented and as a nice side effect spreads knowledge on the code avoiding a single point of failure with just one developer being familiar with a particular piece of code.
Sin number 4: Lust
Must have more!You’ll have to grant me artistic license on this one, or else we won’t be able to keep this blog G-rated. So let’s define lust as “an unnatural craving for something to the point of self-indulgence or lunacy”. OK.
Setting the JVM Heap size too high, not leaving enough RAM for the OS.
Jay describes how setting the JVM RAM allocation too high can lead to Java eating up all memory and leaving nothing for the OS. The observation does not apply to Solr deployments only. Tomcat is just yet another application where this applies as well. Especially with IO-bound applications giving too much memory to the JVM is grave as the OS does not longer have enough space for disk caches.
The general take-away probably should be to measure and tune according to the real observed behaviour of your application. A second take-home message would be to understand your system - not only the Java part of it, but the whole machine from Java, the OS down to the hardware - to tune it effectively. However that should be a well known fact anyway. For Java developers, it sometimes helps to simply talk to your operations guys to get the bigger picture.
Too much attention on the JVM and garbage collection.
There are actually two aspects here: For one, as described by Jay it should not be necessary to try every arcane JVM or GC setting unless you are a JVM expert. More precisely, simply trying various options w/o understanding, what they mean, what side-effects they have and in which situations they help obviously isn’t a very good idea.
The second aspect would be developers starting with JVM optimization only to learn later on that the real problem is within their own application. Tuning JVM parameters really should be one of the last steps in your optimization pipeline. First should be benchmarking and profiling your own code. At the same stage you should review configuration parameters of your application (size of thread pools, connection pools etc.) as well your libraries and frameworks (here come solr’s configuration files, Tomcat’s configuration, RDBMs configuration parameters, cache configurations…). Last but not least should be JVM tuning - starting with adjusting memory to a reasonable amount, setting the GC configuration that makes most sense to your application.
Sin number 5: Envy
Bah!
Wanting features that other sites have, that you really don’t need.
It should be good engineering practice to start with your business needs and distill user stories from that and identify the technology that solves your problem. Don’t go from problem to solution without first having understood your problem. Or even worse: Don’t go from solution (that is from a technology you would love to use) to searching for a problem that this solution might solve: “But there must be a RDBMS somewhere in our architecture, right?”
Wanting to have a bigger index than the other guy.
The antithesis of the “greed” issue of not allocating enough resources. “Shooting for the moon” and trying to allow for possible growth over the next 20 years. Another scenario would be to never fix your system but leave every piece open and configurable, in the end leading to a system that is harder to configure than sendmail is. Yet another scenario would be to plan for billions of users before even launching: That may make sense for a new Google gadget, however for the “new kid on the block”? Probably unlikely, unless you have really good marketing guys. Plan for what is reasonable in your project, observe real traffic and identify real bottlenecks once you see them. Usually estimations of what bottlenecks could be are just plain wrong unless you have lot’s of experience with the type of application you are building. As Jeff Dean pointed out in his WSDM 2009 keynote, the right design for X users may still be right with 10x the amount of users. But do plan a rewrite at about the time you start having 100x and more the amount of users.
Sin number 6: Gluttony
“Staying fit and trim” is usually good practice when designing and running Solr applications. A lot of these issues cross over into the “Sloth” category, and are generally cases where the extra effort to keep your configuration and data efficiently managed is not considered important.
Lack of attention to field configuration in the schema.
Storing fields that will never be retrieved. Indexing fields that will never be searched. Storing term vectors, positions and offsets when they will never be used. Unnecessary bloat. Understand your data and your users and design your schema and fields accordingly.
On a more general scale that might be wrapped into the general advise of keeping only data that is really needed: Rotate logs on a schedule fit to your business, operations needs and based on available machines. Rotate data written into your database backend: It may make sense to keep users that did not interact with your application for 10 years. If you have a large datacenter for storage that may make even more sense. However usually keeping inactive users in your records simply eats up space.
Unexamined queries that are redundant or inefficient.
Queries that catch too much information, are redundant or multiple queries that could be folded into one are not only a problem for Solr users. Anyone using data sources that are expensive to query probably knows how to optimize those queries for reduced cost.
Sin number 7: Wrath
Now! While wrath is usually considered to be synonymous with anger, let’s use an older definition here: “a vehement denial of the truth, both to others and in the form of self-denial, impatience.”
Assuming you will never need to re-index your data.
Hmm - don’t only backup. Include recovery in your plans! Admittedly with search applications, this includes keeping the original documents - it is not unusual to add more fields or to want to parse data differently from the first indexing run. Same applies if you are post-processing data that has been entered by users or spidered from the web for tasks like information extraction, classifier training etc.
Rushing to production.
Of course we all have deadlines, but you only get one chance to make a first impression. Years ago I was part of a project where we released our search application prematurely (ahead of schedule) because the business decided it was better to have something in place rather than not have a search option. We developers felt that, with another four weeks of work we could deliver a fully-ready system that would be an excellent search application. But we rushed to production with some major flaws. Customers of ours were furious when they searched for their products and couldn’t find them. We developed a bad reputation, angered some business partners, and lost money just because it was deemed necessary to have a search application up and running four weeks early.
Leaving that as is - just adding, this does not apply to search applications only 
So keep it simple and separate, stay smart, stay up to date, and keep your application on the straight-and-narrow (YAGNI ). Seek (intelligently) and ye shall find.
Free Software, Hacking, Lucene, Scrum
anti-patterns, development, sin, Solr
