I have developed some mysql queries for my application, and created indexes and used EXPLAIN statements as well.
What types of testing methods we can use to check queries (performance testing, load testing, concurrency testing and others)
How to use those testing methods in your system, anything related to query testing is helpful to me.
Thanks in advance.
Test with sysbench , it is a great tool for simulating database traffic. Furthermore I would suggest getting familiar with the MySQL EXPLAIN statement as it helps to dissect a query and improve on slow areas.
There are quite a few articles on the internet that explain how to properly benchmark, here is just one of them http://20bits.com/articles/10-tips-for-optimizing-mysql-queries-that-dont-suck/ .
Last but not least there is no substitute for testing with real data. Theoretically speaking certain queries should handle better than others, but the only sure way to know this is by testing your schema with actual data. There is a handly tool named generatedata that creates a lot of dummy data so that you can perform said tests.
In order to properly benchmark your queries you must ensure any cached queries and database information is wiped so that the result times are accurate and independent of one-another; you can do this by performing a RESET QUERY CACHE and FLUSH TABLES before running each query.
Additional information as requested:
From experience the best way to handle concurrency is by using the MySQL SET TRANSACTION statement to properly isolate your queries. By using the InnoDB engine the database will perform row locking which is often sufficient for most applications. You can test this by performing equivalent tasks on the database but with separate transactions. Concurrency is a very broad topic in the database world and I would highly recommend further researching this topic.
Related
We are in the process of designing a new system that will either use MySQL or Postgres depending upon the performance.But there are several problems in doing a realistic comparison.I have summed up some of them,it would be helpful if some experts threw some wisdom in here.
Using a neutral performance testing tool
There is something for postgres called explain analyze which basically gives all the details necessary to optimize on the database side.But MySQL does not have something which is as detailed as this one.
Of course these commands give info about a single query, real time performance involves bigger workloads on how the application is going to receive.
How much of this is true ? If a query is slower in postgres and faster in MySQL will it be faster in postgres over heavier workloads, of course only real time tests can tell,but is it worth going in this direction?
I am familiar with Jmeter, but are there any other better tools to do such tasks.
Optimization of both the databases
Postgres is said to be slower for simple reads, but scales well as the data grows and for more complex workloads.Taken from here and here.
With that said,how much optimisation is necessary so that the tests are fair to both database systems.
Any additional points are also welcome.
size of data will have more significance than workload, resource (memory) tuning can have a big effect too.
"With that said,how much optimisation is necessary so that the tests are fair to both database systems."
Is seems to me that the only way to be fair is to do real-world optimisation. Optimise your test systems to as close to production as you can justify. if you're not going to be writing SQL both are going to perform about the same. (+/- $1000 worth of server hardware)
if you're writing SQL you want to keep the programmers happy. ($10000 of programmers won't get you much more performance)
The only realistic performance comparison is with the system that you are designing. Why don't you make your system to be configurable to use either MySql or PostgreSQL then run load tests against it with both databases and compare the performance results? That is what I did in comparing MySql vs PostgreSQL vs Docker in this open source news feed micro-service.
I want to set up a teamspeak 3 server. I can choose between SQLite and MySQL as database. Well I usually tend to "do not use SQLite in production". But on the other hand, it's a teamspeak server. Well okay, just let me google this... I found this:
Speed
SQLite3 is much faster than MySQL database. It's because file database is always faster than unix socket. When I requested edit of channel it took about 0.5-1 sec on MySQL database (127.0.0.1) and almost instantly (0.1 sec) on SQLite 3. [...]
http://forum.teamspeak.com/showthread.php/77126-SQLite-vs-MySQL-Answer-is-here
I don't want to start a SQLite vs MySQL debate. I just want to ask: Is his argument even valid? I can't imagine it's true what he says. But unfortunately I'm not expert enough to answer this question myself.
Maybe TeamSpeak dev's have some major differences in their db architecture between SQLite and MySQL which explains a huge difference in speed (I can't imagine this).
At First Access Time will Appear Faster in SQLite
The access time for SQLite will appear faster at first instance, but this is with a small number of users online. SQLite uses a very simplistic access algorithm, its fast but does not handle concurrency.
As the database starts to grow, and the amount of simultaneous access it will start to suffer. The way servers handle multiple requests is completely different and way more complex and optimized for high concurrency. For example, SQLite will lock the whole table if an update is going on, and queue the orders.
RDBMS's Makes a lot of extra work that make them more Scalable
MySQL for example, even with a single user will create an access QUEUE, lock tables partially instead of allowing only single user-per time executions, and other pretty complex tasks in order to make sure the database is still accessible for any other simultaneous access.
This will make a single user connection slower, but pays off in the future, when 100's of users are online, and in this case, the simple
"LOCK THE WHOLE TABLE AND EXECUTE A SINGLE QUERY EACH TIME"
procedure of SQLite will hog the server.
SQLite is made for simplicity and Self Contained Database Applications.
If you are expecting to have 10 simultaneous access writing at the database at a time SQLite may perform well, but you won't want an 100 user application that constant writes and reads data to the database using SQLite. It wasn't designed for such scenario, and it will trash resources.
Considering your TeamSpeak scenario you are likely to be ok with SQLite, even for some business it is OK, some websites need databases that will be read only unless when adding new content.
For this kind of uses SQLite is a cheap, easy to implement, self contained, perfect solution that will get the job done.
The relevant difference is that SQLite uses a much simpler locking algorithm (a simple global database lock).
Using fine-grained locking (as MySQL and most other DB servers do) is much more complex, and slower if there is only a single database user, but required if you want to allow more concurrency.
I have not personally tested SQLite vs MySQL, but it is easy to find examples on the web that say the opposite (for instance). You do ask a question that is not quite so religious: is that argument valid?
First, the essence of the argument is somewhat specious. A Unix socket would be used to communicate to a database server. A "file database" seems to refer to the fact that communication is through a compiled-in interface. In the terminology of SQLite, it is server-less. Most databases store data in files, so the terminology "file database" is a little misleading.
Performance of a database involves multiple factors, such as:
Communication of query to the database.
Speed of compilation (ability to store pre-compiled queries is a plus here).
Speed of processing.
Ability to handle complex processing.
Compiler optimizations and execution engine algorithms.
Communication of results back to the application.
Having the interface be compiled-in affects the first and last of these. There is nothing that prevents a server-less database from excelling at the rest. However, database servers are typically millions of lines of code -- much larger than SQLite. A lot of this supports extra functionality. Some of it supports improved optimizations and better algorithms.
As with most performance questions, the answer is to test the systems yourself on your data in your environment. Being server-less is not an automatic performance gain. Having a server doesn't make a database "better". They are different applications designed for different optimization points.
In short:
For Local application databses, single user applications, and little simple projects keeping small data SQLite is winner.
For Network database applications, multiuser and concurrency, load balancing and growing data managements, security and roll based authentications, big projects and widely used services you should choose MySql.
In your question I do not know much about teamspeak servers and what kind of data it actually needs to keep in its database but if it just needs a local DBMS and not needs to proccess lots of concurrency and managements SQLite will be my choice.
I'm thinking about moving our production env from a self hosted solution to amazon aws. I took a look at the different services and thought about using RDS as replacement for our mysql instances. The hardware we're using for our master seems to be better than the best hardware we can get when using rds (Quadruple Extra Large DB Instance). Since I can't simply move our production env to aws and see if the performance is still good enough I'd love to make some tests in advance.
I thought about creating a full query log from our current master, configure the rds instance and start to replay the full query log against it. Actually I don't even know if this kind of testing is a good idea but I guess you'll tell me if there are better ways to make sure the performance of mysql won't drop dramatically when making the move to rds.
Is there a preferred tool to replay the full query log?
at what metrics should I take a look while running the test
cpu usage?
memory usage?
disk usage?
query time?
anything else?
Thanks in advance
I'd recommend against replaying the query log - it's almost certainly not going to give you the information you want, and will take a significant amount of effort.
Firstly, you'd need to prepare your database so that replaying the query log won't break constraints when inserting, updating or deleting data, and that subsequent "select" queries will find the records they should find. This is distinctly non-trivial on anything other than a toy database - just taking a back-up and replaying the log doesn't necessarily guarantee the ordering of DML statements will match what happened on production. This may well give you a false sense of comfort - all your select statements return in a few milliseconds, because the data they're looking for doesn't exist!
Secondly, load and performance testing rarely works by replaying what happened on production - that doesn't (usually) reflect the peak conditions that will bring your system to its knees. For instance, most production systems run happily most of the time at <50% capacity, but go through spikes during the day, when they might reach 80% or more of capacity - that's what you care about, can your new environment handle the peaks.
My recommendation would be to use a tool like JMeter to write performance scripts (either directly to the database using the JDBC driver, or through the front end if you've got a web appilcation). Your performance scripts should reflect the behaviour you see from users, and be parameterized so they're not dependent on the order in which records are created.
Set yourself some performance targets (ideally based on current production levels, with a multiplier to cover you against spikes), e.g. "100 concurrent users, with no query taking more than 1 second"), and use JMeter to simulate that load. If you reach it first time, congratulations - go home! If not, look at the performance counters to see where the bottleneck is; see if you can alleviate that bottleneck (or tune your queries, your awesome on-premise hardware may be hiding some performance issues). Typical bottlenecks are CPU, RAM, and disk I/O.
Experiment with different test scenarios - "lots of writes", "lots of reads", "lots of reporting queries", and mix them up.
The idea is to understand the bottlenecks on the system, and see how far you are from those bottleneck, and understand what you can do to alleviate them. Once you know that, your decision to migrate will be far more robust.
the question is about the best practice.
How to perform a reliable SQL query test?
That is the question is about optimization of DB structure and SQL query itself not the system and DB performance, buffers, caches.
When you have a complicated query with a lot of joins etc, one day you need to understand how to optimize it and you come to EXPLAIN command (mysql::explain, postresql::explain) to study the execution plan.
After tuning the DB structure you execute the query to see any performance changes but here you're on the pan of multiple level of optimization/buffering/caching. How to avoid this? I need the pure time for the query execution and be sure it is not affected.
If you know different practise for different servers please specify explicitly: mysql, postgresql, mssql etc.
Thank you.
For Microsoft SQL Server you can use DBCC FREEPROCCACHE (to drop compiled query plans) and DBCC DROPCLEANBUFFERS (to purge the data cache) to ensure that you are starting from a completely uncached state. Then you can profile both uncached and cached performance, and determine your performance accurately in both cases.
Even so, a lot of the time you'll get different results at different times depending on how complex your query is and what else is happening on the server. It's usually wise to test performance multiple times in different operating scenarios to be sure you understand what the full performance profile of the query is.
I'm sure many of these general principles apply to other database platforms as well.
In the PostgreSQL world you need to flush the database cache as well as the OS cache as PostgreSQL leverages the OS caching system.
See this link for some discussions.
http://archives.postgresql.org/pgsql-performance/2010-08/msg00295.php
Why do you need pure execution time? It depends on so many factors and almost meaningless on live server. I would recommend to collect some statistic from live server and analyze queries execution time using pgfouine tool (it's for postgresql) and make decisions based on it. You will see exactly what do you need to tune and how effective was your changes on a report.
As I've been looking into the differences between Postgres and MySQL, it has struck me that, if what I read is to be believed, MySQL should be (disclaimer: by reading the rest of this sentence, you agree to read the next paragraph as well) the laughingstock of the RMDB world: it doesn't enforce ACID by default, the net is rife with stories of MySQL-related data loss and by all accounts and the query optimizer is a joke.
But none of this seems to matter. It's not hard to tell that MySQL has about a million times* as much hype as Postgres (it's LAMP, not LAPP), big installations of MySQL are not unheard of (LJ? Digg?) and I haven't noticed a drop in MySQL's popularity.
This makes me wonder: are these "problems" with MySQL really that bad?
So, if you have used MySQL for a reasonably large project**, what was your experience like? Did you use Postgres as well? How was it worse? How was it better?
*: [citation needed]
**: I'm well aware that, for "small things" (blogs, what have you), MySQL (along with practically every other RDB) is just fine.
Since it's tagged [subjective], I'll be subjective. For me it's about the little things. PostgreSQL is more developer friendly and makes it easy to do the right thing regarding data integrity by default.
If you give MySQL an incorrect type, it will implicitly convert it even if the conversion is incorrect. PostgreSQL will complain.
EXPLAIN in PostgeSQL is way more useful than in MySQL. It gives you the exact structured query plan. What kind of algorithm will it use, what cost does does each step have, etc. This means that if the query optimizer in MySQL doesn't do what you think it does, you will have hard time to debug it.
If you ever wrote anything more complex in the MySQL stored procedure language, you will know how painful it is. PL/pgSQL is actually a nice language + you can use many other languages.
MySQL doesn't have sequences, so if you need them you have to roll your own. Most people will do it wrong and have race conditions in their code.
PostgreSQL exposes most of it's internal lock types to the developer. If you need to lock your table in a special way, you can do that.
Everything is programmable in PostgreSQL. For example, if you need your own data type for some specific data, you can add it. You can add casts and operators for the data types. Probably not worth the effort for small projects, but it's better than storing things as strings.
PostgreSQL adds every action including DDL changes to a transaction, unlike MySQL. If you have a conversion script that creates/drops tables, BEGIN/END won't help you in MySQL to keep it in consistent state.
That doesn't mean it's impossible to write good database applications with MySQL, it just requires more effort.
MySQL can be used for reasonably large applications, provided you really know what you do and don't trust the defaults.
MySQL defaults are optimized to be easy-to-use and to get started quickly and to provide best performance (usually). Other databases choose defaults that are at the very least ACID and are scalable (i.e. choose defaults that are not necessarily the best/fastest for small data sets)
Another item is that MySQL only learned to be a "real database" relatively recent, while almost all competing products started life with full ACID in mind.
MySQL had problems with almost all aspects of ACID at one time or another. Most of them are gone or can be configured away, but you will have to check each one. The problem with troubles in atomicity for example is that you will not notice them until you place your system under heavy load (which often coincides with it being a production system, unfortunately).
So my summary would be: MySQL is capable of working in this environments, but it takes work. And the path it took to get to that point cost it quite a few points in the confidence area.
Provided you know what its capabilities are, then it may fit your use case.
If used correctly, then it is ACID compliant. If used incorrectly, it is not. The trouble is, that people seem to assume that it's a good thing to have ACID compliance.
In reality ACID is often the enemy of performance (Particularly the D for durability). By relaxing durability very slightly, we can typically get a very large performance boost.
Likewise, even using the MyISAM engine (which doesn't have much by way of durability, and not a lot of the others either) is still appropriate to some problem domains.
We are using MySQL in some applications - and it is doing a pretty good job.
In the newer projects we are using the InnoDB engine - and albeit it may be slower than the default engine it is working well.
Right now we are using an ORM mapper - and so most of the complexity is hidden behind the ORM mapper (and working nice).
I think the infrastructure (Tools and information) is one of MySQL's big plusses: we are using really nice tools: Toad for MySQL and MySQL Administrator.
Altough I have to admit that I had a shocking experience last week when helping a friend with a SQL statement and the correleated subquery nearly stopped his MySQL server - but with the trick of enclosing it in another query - it worked really well.
This is nothing which REALLY shocks me - because I've used other DB systems which cost big bucks (I'm looking at you - DB2) - and they had other things to work around. (maybe not as drastic - but still you had to optimize for them).
I haven't used both for a single large project, but having used both I have some idea of how they compare.
In general almost all MySQL's problems can be worked around with good discipline. The issue is more that developer has to know all the gotchas and work around them. After working with PostgreSQL or Oracle this feels a bit like death by a thousand papercuts. You get that used to stuff just working.
This is a pretty significant issue in the types of stuff that I have worked on. Complex schemas with complex queries and lots of data. tight schedules with little time for performance engineering meaning that getting consistently reasonable performance without having to manually optimize queries is important. A good cost based optimizer is almost a requirement. Combine that with quite a lot of outsourcing with development teams that don't have the experience to catch all the gotchas in time and the little issues escalate to large QA problems. Hitting any of MySQL silent data corruption gotchas in production is something that really scares me. I'll take any declarative constraints at the database level that I can get to have atleast some safety net, MySQL unfortunately falls short on that.
PostgreSQL has the added benefit that it can run significantly more algorithms using more advanced data-structures in the database. Most of our large projects have a few cases where MySQL will hit its limits. Moving the algorithms outside the database requires considerably more effort with pretty tricky code involving correct locking and synchronization. In particular I have at one time or another hit the need for partial indexes, indexes on expressions, custom aggregate functions, set returning stored procedures, array and hash datatypes, inverted indexes on array values, update/delete-returning, deferrable foreign key constraints.
On the other hand MySQL has at least for now a better story for scale out. If I had to support a huge number users on a reasonably simple application, and had the team to build a heavily partitioned and replicated database with eventual consistency, I'd pick MySQL over PostgreSQL for the low level data storage building block. On the other the competitors in that space are the key-value databases.
are these "problems" with MySQL really that bad?
Actually, the pain MySQL will inflict on you can range from moderate to insane, and much of it depends on MyISAM.
I find a good rule of thumb is this :
are you backing up some MyISAM tables ?
MyISAM is great for data you don't really care about, like traffic logs and the like, or for data that you can easily restore in case of a problem since it's read-only and hence never changed since the time you loaded that 10GB dump. In those cases the compact row format of MyISAM brings great space savings (that however do not translate into faster seq scan speed, for some reason).
If the data you put in MyISAM tables is worth backing up, you are going to enter in a world of hurt when you realize some day that it is all inconsistent because of the lack of FK and constraint checks, and incidentally all your backups will contain inconsistent data too.
If you make lots of concurrent updates to MyISAM tables, then you are gonna go way past the world of hurt stage : when the load reaches a certain threshold, you are doomed. Of course the readers block writers which block readers which block queued writers, etc, so the performance is bad, load avg goes to 200, and your box is nuked, but also I could consistently crasy MyISAM tables in a benchmark I wrote 2 years ago just by hitting them with too much load. Random data ensued, sometimes crashing the mysql on selects or spewing random errors.
So, if you avoid MyISAM like the plague it is, the problems with MySQL aren't really that bad. InnoDB is robust. However, generally I find it inferior to Postgres, which is faster and has so many less gotchas, and Gets The Job Done easier and faster.
No, the issues you mention are NOT a big deal. See Google and Facebook as two examples of companies that are using MySQL to accomplish Herculean tasks you'll only ever dream of encountering.
I use the following rules when running a MySQL to prevent headaches down the line:
Take daily, weekly, monthly snapshots of database. More often than not the problems you'll run in to have nothing to do with MySQL, instead it's a boneheaded developer running:
DELETE FROM mytable; # Where is the WHERE?
Use InnoDB by default, the only reason to use MyISAM is for full text search.
Get your database schema under source control.