Mysql memory limits
1 Reference Manual :: 13.6.3 InnoDB Startup Options and System Variables
Linux HugeTLBfs: Improve MySQL Database Application Performance Applications that perform a lot of memory accesses (several GBs) may obtain performance improvements by using large pages due to reduced Translation Lookaside Buffer (TLB) misses. HugeTLBfs is memory management feature offered in Linux kernel, which is valuable for applications that use a large virtual address space. It is especially useful for database applications such as MySQL, Oracle and others. Other server software that uses the prefork or similar (e.g. Apache web server) model will also benefit.
Michael Tokarev: Re: O_DIRECT question Linus Torvalds wrote:> > On Thu, 11 Jan 2007, Viktor wrote:>> OK, madvise() used with mmap'ed file allows to have reads from a file>> with zero-copy between kernel/user buffers and don't pollute cache>> memory unnecessarily. But how about writes? How is to do zero-copy>> writes to a file and don't pollute cache memory without using O_DIRECT?>> Do I miss the appropriate interface?> > mmap()+msync() can do that too. It can, somehow... until there's an I/O error.
Bugs: #40757: server crash after failed plugin/engine initialization
Heikki Tuuri answers to Innodb questions, Part II | MySQL Performance Blog I now got answers to the second portions of the questions you asked Heikki. If you have not seen the first part it can be found here. Same as during last time I will provide my comments for some of the answers under PZ and will use HT for original Heikkis answer. Q26: You also say on Unix/Linux only one read-ahead can happen at the same time.
Properties: Description: This variable changes the way InnoDB open files and flush data to disk and is should be considered as very important for InnoDB performance. Variable's Day Out #12: innodb_flush_method
Linux 64-bit, MySQL, Swap and Memory The VM for Linux prefers system cache over application memory. What does this mean? The best way I can explain is by example. Imagine you have 32 GB of RAMMySQL is set to take 20 GB of RAM for a process based buffer and up to 6M for the various thread buffers. Over a period of time the box swaps.
November 3, 2007 by Peter Zaitsev39 Comments My last post about Innodb Performance Optimization got a lot of comments choosing proper innodb_buffer_pool_size and indeed I oversimplified things a bit too much, so let me write a bit better description. Innodb Buffer Pool is by far the most important option for Innodb Performance and it must be set correctly. I’ve seen a lot of clients which came through extreme sufferings leaving it at default value (8M).
I’m often asked how one can evaluate IO subsystem (Hard drive RAID or SAN) performance for MySQL needs so I’ve decided to write some simple steps you can take to get a good feeling about it, it is not perfect but usually can tell you quite a lot of what you should expect from the system. What I usually look for MySQL is performance in random reads and random writes. Sequential reads and writes are rarely the problem for OLTP workloads, so we will not look at them. I also prefer to look at performance with O_DIRECT flag set to bypass OS cache. This may execute separate code path in kernel and so has a bit different performance pattern compared to buffered IO (even followed by fsync regularly) , but it allows to easily bypass OS cache both for reads and for writes and so does not require creating large working sets for boxes with significant amounts of memory (or reducing amount of usable memory). Evaluating IO subsystem performance for MySQL Needs | MySQL Performance Blog
Percona MySQL Consulting can often recover lost or corrupted data from MyISAM and InnoDB tables or from corrupted MySQL binary logs and general query logs. We have created special data recovery software that can recover data from InnoDB tables to assist with your MySQL restore. If you want to try InnoDB data recovery yourself, see the Percona Data Recovery Tool for InnoDB. These scenarios are often recoverable: Accidentally deleted data in MySQLDropped InnoDB tablesTruncated or recreated MySQL tablesInnoDB tablespace corruption that innodb_force_recovery will not repairMySQL database with a filesystem corruption We always encrypt your sensitive data and we destroy our copy of it after we are done. Data Recovery - Percona
Compiling sysbench 0.4.12 for Debian | Random Bugs Home » Bugs, Debian, Featured, How-to, Linux, Shell 9 July 200919 Comments On the Linux market are a lot of distributions and every distribution is unique in his way. Is normal to have different compilers and tools from distribution to distribution so is almost normal to have programs what doesn’t compile on all distributions. sysbench 0.4.12 is one of them.
A thread on the lkml began with a query about using O_DIRECT when opening a file. An early white paper written by Andrea Arcangeli [ interview ] to describe the O_DIRECT patch before it was merged into the 2.4 kernel explains, " with O_DIRECT the kernel will do DMA directly from/to the physical memory pointed [to] by the userspace buffer passed as [a] parameter to the read/write syscalls. So there will be no CPU and memory bandwidth spent in the copies between userspace memory and kernel cache, and there will be no CPU time spent in kernel in the management of the cache (like cache lookups, per-page locks etc..). " Linux creator Linus Torvalds was quick to reply that despite all the claims there is no good reason for mounting files with O_DIRECT, suggesting that interfaces like madvise() and posix_fadvise() should be used instead, " there really is no valid reason for EVER using O_DIRECT. You need a buffer whatever IO you do, and it might as well be the page cache. Accessing Files With O_DIRECT
In mid 2006, YouTube served approximately 100 million videos in a single day. To maintain a website of that scale, one would imagine YouTube has hundreds of DBAs. But in fact, there are just three people that make it all work. Paul Tuckfield, the MySQL DBA at YouTube shares horror stories about scalability at YouTube and how he coped with them to keep the show going everyday, while learning important lessons along the way. YouTube uses MySQL as the back-end. IT Conversations | MySQL Conference from O'Reilly Media | Paul Tuckfield
7.9.8 Enabling Large Page Support
Although most Linux users are familiar with the role of process schedulers, such as the new O(1) scheduler, many users are not so familiar with the role of I/O schedulers. I/O schedulers are similar in some aspects to process schedulers; for instance, both schedule some resource among multiple users. A process scheduler virtualizes the resource of processor time among multiple executing processes on the system. So, what does an I/O scheduler schedule? A naïve system would not even include an I/O scheduler. Kernel Korner - I/O Schedulers
Linux: How To Clear The Cache From Memory
Dans cet article, je vais tenter d'expliquer les différentes informations que le noyau Linux nous donne au travers du fichier /proc/meminfo. Comme support, je vais afficher les données qui concernent mon système. Il s'agit d'un noyau 2.6.24-1 dans une Debian unstable. Ma machine repose sur une architecure x86 en 32 bits et contient une barrette de 1 Go de mémoire RAM. La mémoire sous Linux : analyse du fichier /proc/meminfo - Sygus.net
drop_caches | LinuxInsight Writing to this will cause the kernel to drop clean caches, dentries and inodes from memory, causing that memory to become free. To free pagecache: echo 1 > /proc/sys/vm/drop_caches To free dentries and inodes: echo 2 > /proc/sys/vm/drop_caches To free pagecache, dentries and inodes:
/proc/sys/vm | LinuxInsight
Linux System Administrators Guide: Prev Chapter 6. Memory Management Next 6.6. The buffer cache Reading from a disk is very slow compared to accessing (real) memory. Linux System Administrator's Guide - The buffer cache
The Linux Page Cache and pdflush
MySQL Swapping to Disk
5.1.5 Server Status Variables
7.4.8 Quand MySQL ouvre et ferme les tables
7.9.3 Tuning Server Parameters
7.9.5 How MySQL Uses Memory
16.1.1 How to Set Up Replication
188.8.131.52 Creating a User for Replication