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I have a web site that's been progressivelly expanding in both traffic and complexity of database design. I've always worked as a developer first & foremost, and never really been much of a DB administrator beyond what I need to do to get my code running. This needs to change - I need to improve efficiency on the database side of things.
To give a vague example, I'm looking for how to go about learning:
Optimising complex tables/relationships for performance/scaling
How to index efficiently. (At the moment I throw indexes on foreign keys, and that's about it)
General design principles for complex databases
Most of the resources I've found are either directed more towards the basics of SQL ("this is a SELECT query, a JOIN, etc") or focus primarily on performance issues outside the DB.
So, I know this is a little vague - but where should I look to ensure my database is designed in the most most efficient & integral manner possible?
Learn about data modeling. Choosing the right data structure is always a crucial first step, for programming in general and databases in particular. Performance cannot be "bolted" on top of a bad data structure! The ERwin Methods Guide is probably not a bad way to start learning about data modeling.
Learn how DBMSes organize data at the physical level. This will help you immensely in understanding how to "shape" your data for performance and how to effectively leverage many of the performance mechanisms modern DBMSes put at your disposal. Use The Index, Luke! is an excellent tutorial on the topic.
Learn how to efficiently access the database and make sure you really understand the client API that will be called from your code. Different APIs have their own idiosyncrasies, but they all share some common themes, such as parameter binding, query preparation and fetching. Even if you are "shielded" by an ORM from ever having to, say, bind parameters manually, this is still taking place "under the covers" and understanding it raises your ability to write performant code.
Measure, measure, measure. Modern information systems are immensely complex and even experts find themselves making incorrect assumptions, so don't rely on assumptions!
I would suggest some reading in performance tuning. It is very specialized depending on the database backend you use. BUt here are some books to consider:
SQl Server
http://www.amazon.com/Server-Query-Performance-Tuning-Distilled/dp/1590594215/ref=sr_1_2?s=books&ie=UTF8&qid=1334154710&sr=1-2
http://www.amazon.com/Performance-Tuning-Server-Dynamic-Management/dp/1906434476/ref=sr_1_12?s=books&ie=UTF8&qid=1334154710&sr=1-12
MySQL
http://www.amazon.com/High-Performance-MySQL-Optimization-ebook/dp/B0028N4W7Y/ref=sr_1_3?ie=UTF8&qid=1334154504&sr=8-3
Oracle
http://www.amazon.com/Oracle-Database-Release-Performance-Techniques/dp/0071780262/ref=sr_1_2?s=books&ie=UTF8&qid=1334154909&sr=1-2
General performance Tuning
http://www.amazon.com/SQL-Performance-Tuning-Peter-Gulutzan/dp/0201791692/ref=sr_1_18?s=books&ie=UTF8&qid=1334154964&sr=1-18
First and foremost, I'd recommend learning how to use EXPLAIN and what its output means. Run it on your most common queries and study the output. Are the queries using sensible indexes? Are they using indexes at all? Queries that look very simple at a glance might end up being quite costly.
Next, I'd suggest finding your slowest queries. Postgres (for example) has a feature that allows you to log the SQL source for all queries that take longer than N seconds to run. Are they slow because they're unindexed, very complex, or operating on a huge amount of data?
Third, I'd look at the number of times a particular query is run. Are you using the database to store static data, and hitting a table over and over again to grab a record that never changes? You could probably cache the result somewhere.
Let's assume you've got a nosql database - redis, cassandra, mongodb. And you need to check the overall performance for this database - various platforms, operation systems, even programming languages which are used for test. It's not tied to a specific application or schema.
What tests you want to see? Can you please help me to form requirements?
How database operates in cluster?
In broken cluster?
In cloud env?
How it can perform queries when 10k connections opened?
What tools you will use?
Is it something like JMeter->http server->database?
Jmeter->tcp app->database?
Other?
All material I've found about database performance testing is like testing database as a part of some product (specific scheme, specific env).
Have you thought about database performance testing when database is product itself?
Looking forward for you help.
-vova
In NoSQL benchmarks and performance evaluations I've put together a list of the benchmarks that are correct in the sense that they clearly define the purpose of the benchmark and compare similar features (apples-to-apples comparisons); there are way too many benchmarks out there that are failing at at least one of these fundamental requirements of a benchmark. Going through those you'll be able to extract the bits that are interesting for your own benchmark plus learn what tools have been used and get some benchmarking code too.
So far the most generic NoSQL benchmark is YCSB (Yahoo Cloud Servicing Benchmark). Recently the Cubrid blog posted the results of running this benchmark against some of the most popular NoSQL solutions and that might give you an idea of how to interpret results.
check the overall performance for this database
Unless you need to do it for fun, or you just want to get a benchmark for the sake of getting a benchmark, I would recommend to tailor a performance benchmark to the actual problem/requirements.
For example do you really need crazy fast writes? Are you ok with losing data? Do you mind spending time on configuring fail over? Do you plan to scale up or out? Are you planning for TBs of data? etc..
From the examples you gave => Redis, Cassandra and MongoDB are quite different:
Redis is mostly cache, and it is really fast, but being just a cache it would not help you much in doing medium complexity aggregation. However it is currently the best cache (my opinion) out there. "Redis + a killer DB" is an ideal combination. It also has a built in benchmark tool you can try.
Cassandra is a solid product modelled after Google Big Table (but I am sure you already know that). It scale writes well if you have lots of nodes, but if you reach TBs of data for example, it can take days to add nodes. It is also not a simplest one to get. But if you are ok to pay, there are excellent guys from Datastax who can take all the complexity away. I have a very simple Cassandra Bombardier that may help you to start off.
MongoDB is a great DB for multiple reasons: very sexy and simple query language, good documentation, huge community, etc.. Not so great in other aspects: need to spend time sharding it correctly, and then resharding it again [compare to e.g. Riak, where it is done automatically]. It is very fast (writes) if the data [not just the index] fits in RAM, it starts slow down very quickly if it does not. There is a ongoing speculation that you may lose data (from one of the Basho engineers: "I had personally spent some time finding out ways to demonstrate that MongoDB will lose writes in the face of failure"), aggregation queries may take a while given a not so large dataset. I have a Mongo Performance Playground that you may find useful.
I need to present performance test tool to management team of my company. Some of them think performance testing is not necessary for us because our customer never request or give requirement about performance to us.
However one of our current big project found performance problem, responding time is very long, server down when it handle many concurrent user.
I think I need to prepare myself to present about it benefit both concrete and non-concrete. Anyone have experience with performance testing tool? How it can empower your productivity?
Management cares about money. Show them how your tool will save them money and you will get their approval. Everything else is usually trivial to them.
Expanding on what #LWoodyiii had to say. When presenting a case for anything, whether that be hiring more people, or investing in a performance testing tool (or outsourcing your performance testing for that matter), it needs to be presented in terms of money saved. By doing a little leg work, you should be able to back into the $ saved amount.
If you had never had any performance problems, then it would be more difficult to quantify $ saved. But in your case, it should be a little easier to figure this out, as you have already had some significant performance issues. You should be able to put a $ amount to your existing performance problem. You should be able to quantify the revenue lost (lost transactions, lost customers, decreased transaction throughput, etc...) due to the degradation of service. You can also factor in costs associated with fixing and resolving the performance issue. Then it is a matter of comparing the costs of having performance problems vs implementing a performance testing program (tool, training and resource costs).
It also probably would not hurt to spice up the presentation with some anecdotal performance horror stories that were well publicized in the news and how much those outages cost those firms.
It sounds like you haven't used profilers yourself. That would be a good start. You didn't mention your environment but red-gate makes a wonderful profile for .NET.
http://www.red-gate.com/products/ants_performance_profiler/index.htm
Whatever environment you're in, you can probably find a decent profiler with a trial period. Use the trial period to profile your app and get to know how profilers work and how they can help make your app better.
One thing to demonstrate about productivity is how they can let you focus on the biggest bottlenecks and have the most impact on improving performance with the least effort. With a good profiler you won't bother optimizing code that is already performant.
Of course, if your company really don't care about performance they won't want you doing any optimization anyways. There are lots of companies like this and it stinks.
I think performance is one of the trivial cases that is really difficult to present to someone else especially the management. You should have some "Clear" plus "simple" way to show the use of it.
I have the experience with profilers like JBuilder and YourKit but no other performance tools. But I think the "Numbers" shown on them are not sufficient to show the use for them.
If you can build a nice practical example it would be great. Show same case for both scenarios. If you can show that the old one's response time is large and after performance improving the same operation takes much less time then it is a good way to prove your claim.
Since I am a Lone Developer, I have to think about every aspect of the systems I am working on. Lately I've been thinking about performance of my two websites, and ways to improve it. Sites like StackOverflow proclaim, "performance is a feature." However, "premature optimization is the root of all evil," and none of my customers have complained yet about the sites' performance.
My question is, is performance always important? Should performance always be a feature?
Note: I don't think this question is the same as this one, as that poster is asking when to consider performance and I am asking if the answer to that question is always, and if so, why. I also don't think this question should be CW, as I believe there is an answer and reasoning for that answer.
Adequate performance is always important.
Absolute fastest possible performance is almost never important.
It's always worth keeping an eye on performance and being aware of anything outrageously non-optimal that you're doing (particularly at a design/architecture level) but that's not the same as micro-optimising every line of code.
Performance != Optimization.
Performance is a feature indeed, but premature optimization will cost you time and will not yield the same result as when you optimize the parts that need optimization. And you can't really know which parts need optimization until you can actually profile something.
Performance is the feature that your clients will not tell you about if it's missing, unless it's really painfully slow and they're forced to use your product. Existing customers may report it in the end, but new customers will simply not bother if the performance is required.
You need to know what performance you need, and formulate it as a requirement. Then, you have to meet your own requirement.
That 'root of all evil' quote is almost always misused and misunderstood.
Designing your application to perform well can be mostly be done with just good design. Good design != premature optimization, and it's utterly ridiculous to go off writing crap code and blowing off doing a better job on the design as an 'evil' waste. Now, I'm not specifically talking about you here... but I see people do this a lot.
It usually saves you time to do a good job on the design. If you emphasize that, you'll get better at it... and get faster and faster at writing systems that perform well from the start.
Understanding what kinds of structures and access methods work best in certain situations is key here.
Sure, if you're app becomes truly massive or has insane speed requirements you may find yourself doing tricked out optimizations that make your code uglier or harder to maintain... and it would be wrong to do those things before you need to.
But that is absolutely NOT the same thing as making an effort to understand and use the right algorithms or data patterns or whatever in the first place.
Your users are probably not going to complain about bad performance if it's bearable. They possibly wouldn't even know it could be faster. Reacting to complaints as a primary driver is a bad way to operate. Sure, you need to address complaints you receive... but a lack of them does not mean there isn't a problem. The fact that you are considering improving performance is a bit of an indicator right there. Was it just a whim, or is some part of you telling you it should be better? Why did you consider improving it?
Just don't go crazy doing unnecessary stuff.
Keep performance in mind but given your situation it would be unwise to spend too much time up front on it.
Performance is important but it's often hard to know where your bottleneck will be. Therefore I'd suggest planning to dedicate some time to this feature once you've got something to work with.
Thus you need to set up metrics that are important to your clients and you. Keep and analyse these measurements. Then estimate how long and how much each would take to implement. Now you can aim on getting as much bang for you buck/time.
If it's web it would be wise to note your page size and performance using Firebug + yslow and/or google page speed. Again, know what applies to a small site like yours and things that only apply to yahoo and google.
Jackson’s Rules of Optimization:
Rule 1. Don’t do it.
Rule 2 (for experts only). Don’t do it
yet— that is, not until you have a
perfectly clear and unoptimized
solution.
—M. A. Jackson
Extracted from Code Complete 2nd edition.
To give a generalized answer to a general question:
First make it work, then make it right, then make it fast.
http://c2.com/cgi/wiki?MakeItWorkMakeItRightMakeItFast
This puts a more constructive perspective on "premature optimization is the root of all evil".
So to parallel Jon Skeet's answer, adequate performance (as part of making something work, and making it right) is always important. Even then it can often be addressed after other functionality.
Jon Skeets 'adequate' nails it, with the additional provision that for a library you don't know yet what's adequate, so it's better to err on the safe side.
It is one of the many stakes you must not get wrong, but the quality of your app is largely determined by the weakest link.
Performance is definitely always important in a certain sense - maybe not the one you mean: namely in all phases of development.
In Big O notation, what's inside the parantheses is largely decided by design - both components isolation and data storage. Choice of algorithm will usually only best/worst case behavior (unless you start with decidedly substandard algorithms). Code optimizations will mostly affect the constant factor - which shouldn't be neglected, either.
But that's true for all aspects of code: in any stage, you have a good chance to fail any aspect - stability, maintainability, compatibility etc. Performance needs to be balanced, so that no aspect is left behind.
In most applications 90% or more of execution time is spend in 10% or less of the code. Usually there is little use in optimizing other code than these 10%.
performance is only important to the extent that developing the performance improvement takes less time than the total amount of time that will be saved for the user(s).
the result is that if you're developing something for millions... yeah it's important to save them time. if you're coding up a tool for your own use... it might be more trouble than it's worth to save a minute or even an hour or more.
(this is clearly not a rule set in stone... there are times when performance is truly critical no matter how much development time it takes)
There should be a balance to everything. Cost (or time to develop) vs Performance for instance. More performance = more cost. If a requirement of the system being built is high performance then the cost should not matter, but if cost is a factor then you optimize within reason. After a while, your return on investment suffers in that more performance does not bring in more returns.
The importance of performance is IMHO highly correlated to your problem set. If you are creating a site with an expectation of a heavy load and lot of server side processing, then you might want to put some more time into performance (otherwise your site might end up being unusable). However, for most applications the the time put into optimizing your perfomance on a website is not going to pay off - users won't notice the difference.
So I guess it breaks down to this:
Will users notice the improvements?
How does this improvement compare to competing sites?
If users will notice AND the improvement would be enough to differentiate you from the competition - performance is an important feature - otherwise not so much. (To a point - I don't recommend ignoring it entirely - you don't want your site to turtle along after all).
No. Fast enough is generally good enough.
It's not necessarily true, however, that your client's ideas about "fast enough" should trump your own. If you think it's fast enough and your client doesn't then yes, you need to accommodate your ideas to theirs. But if you're client thinks it's fast enough and you don't you should seriously consider going with your opinion, no theirs (since you may be more knowledgeable about performance standards in the wider world).
How important performance is depends largely and foremost on what you do.
For example, if you write a library that can be used in any environment, this can hardly ever have too much performance. In some environments, a 10% performance advantage can be a major feature for a library.
If you, OTOH, write an application, there's always a point where it is fast enough. Users won't neither realize nor care whether a button pressed reacts within 0.05 or 0.2 seconds - even though that's a factor of 4.
However, it is always easier to get working code faster, than it is to get fast code working.
No. Performance is not important.
Lack of performance is important.
Performance is something to be designed in from the outset, not tacked on at the end. For the past 15 years I have been working in the performance engineering space and the cause of most project failures that I work on is a lack of requirements on performance. A couple of posts have noted "fast enough" as an observation and whether your expectation matches that of your clients, but what about when you have a situation of your client, your architectural team, your platform engineering team, your functional test team, your performance test team and your operations team all have different expectations on performance, none of which have been committed to stone and measured against. Bad Magic to be certain.
Capture those expectations on the part of your clients. Commit them to a specific, objective, measurable requirement that you can evaluate at each stage of production of your software. Expectations may not be uniform, with one section of your app/code needing to be faster than others, nor will each customer have the same expectations on what is considered acceptable. Having this information will force you to confront decisions in the design and implementation that you may have overlooked in the past and it will result in a product which is a better match to your clients expectations.
Are there any good scripts that I could run against my Oracle database to test for SQL defects or maybe common performance issues?
Edit: Everything in an Oracle database can be queried. From the PL/SQL packages, indexes and sql running stats. The performance books say look in this place and it will show some absolute values that need the developer to be able to interpret. Has anyone combined their knowledge to include this interpretation within the scripts?
Are you asking for the information in this book?
http://www.amazon.com/Oracle-Database-Performance-Techniques-Osborne/dp/0072263059/ref=sr_1_1?ie=UTF8&s=books&qid=1264619796&sr=1-1
Are you asking about this wiki?
http://wiki.oracle.com/page/Performance+Tuning
Or are you asking for this vendor information?
http://www.oracle.com/technology/deploy/performance/index.html
Edit. There is no magical set of queries that you simply run and set the various tuning options.
Oracle is very complicated. Changing a parameter to make one thing fast can make several other things faster or slower. Or makes makes the instance consume more real memory than you have installed. It's hard to generalize this into magical queries. You have tools, but even then, the tools give you tuning options and you may need to run different experiments.
Performance is a balance. You have to strike a balance between physical I/O time and CPU time. It's not possible to generalize this into a magical query. Your system may need faster physical I/O (data warehouses, for instance, often need this) because it can't effectively work from cache. My system may need faster processor time and will have to work in cache to achieve this.
Performance is a function of your application. No magical query of Oracle will reveal a single thing about how your application is designed to work.
Enterprise Manager and it's associated performance tools are a good place to start looking for queries that are consuming the most resources. Here you can see the plans generated for your SQL, view traces of long running queries, etc.
If you have a budget, there is Spotlight by Quest. I've only used the trial version, but I found it useful.
I would recommend checking out the book Optimizing Oracle Performance and any of Cary Millsap's other writings. It is a waste of time to think about optimizing every query. You really need an approach to finding out where your performance bottlenecks are. His Method R approach is a very good one to read up on. Also most of Tom Kyte's books go into detail about performance issues.