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conditions, filtering conditions, aggregate queries, and sorting fields as index candidate fields.
C. Combine frequently-used fields to form a composite index. The field order of the composite index is the same as that of the primary key. You also need to put the most commonly used fields in front, put the fields with low repetition rate in front.
D. Do not add too many indexes to a table because the index affects the insert and update speeds.
Indexing is not only a matter of consideration when
Hardware preparation environment:
Hard drive: 16 SAS 15 k raid 5 with 512 MCache
CPU: AMD 4-core two
Memory: 16 GB
Software environment:
Operating System: RedHat AS4.6 2.6.9-67. ELsmp
Mysql: 5.0.
Performance Tuning based on different scenarios is as follows:
Scenario:
Write operations (insert, query, and delete) are intensive, and the data capacity far exceeds the memory size (minimum is more than GB, or ev
Article Source: http://hi.baidu.com/top2top/blog/item/0bea951600a16050f2de322b.html apache2.0 prefork and worker module Performance Tuning
The performance improvement of Apache 2.0 is the most attractive. On UNIX systems that support POSIX Threads, Apache can use different MPM to run in a mix of multi-process and multi-thread modes to enhance the scalabi
This document is a translation of section 1.1 of the IBM Redbook Linux Performanceand Tuning guidelines.Original address:http://www.redbooks.ibm.com/redpapers/pdfs/redp4285.pdfOriginal Eduardo Ciliendo, Takechika Kunimasa, Byron BraswellThe translation is as follows:1.1 Linux Process ManagementProcess management is one of the most important functions of the operating system. Efficient process management can ensure a smooth and efficient operation of a
Translation: Brother Fei ( http://hi.baidu.com/imlidapeng )All rights reserved, respect other people's labor results, please indicate the author and original source and this statement when reproduced.The original name: "Linux Performance and Tuning guidelines"Original address: http://www.redbooks.ibm.com/abstracts/redp4285.html---------------------------------------------------------------------------------
our library to collect data: User events, DOM changes, network requests, exceptions, debug messages, and so on. Our players are highly optimized to render and use all the data collected in sequence, from both visual and technical aspects to provide you with a perfect pixel-level simulation of everything the user has done in the browser.If you want to try it, you can try Sessionstackfor free.Resources
Https://developers.google.com/web/fundamentals/p
Document directory
Preliminary steps
Using bind variables
There are several relatively easy steps you can take to improve performance. From the user's perspective, one of the most frequently used interfaces with a database involves SQL statements, so getting a handle on them is a good place to start, in terms of being able to see an immediate improvement. -->Oracle perfor
First, JVM performance tuning strategySecond, performance tuning1. Java thread Pool (java.util.concurrent.ThreadPoolExecutor)The thread pool used by most applications on JVM6 is the thread pool that comes with the JDK, and the thread pool of mature Java threads is verbose because the thread pool behaves a bit like we imagined. The Java thread pool has several imp
Original link: Spark Streaming performance tuning The Spark streaming provides an efficient and convenient streaming mode, but in some scenarios the default configuration is not optimal, and even the external data cannot be processed in real time, and we need to make relevant modifications to the default configuration. Because of the reality of the scene and the amount of data is not the same, so we can not
and optimized the performance of Hadoop clusters deployed in virtualization and Physical Mode on the same scale. The experiment shows that the virtualized Hadoop cluster can well support the production environment.Performance Comparison between a virtualized environment and a physical environment
Figure 1 shows the deployment style of the Performance Tuning Test
, you can copy the collection into an array.Pay attention to redraw and re-typesetting, batch modify style, operate DOM tree offline, cache and reduce access to layout information.Use absolute coordinates in animations, using drag-and-drop proxies.Minimize the number of event handles using event-managed technology.Algorithm and process optimizationThe performance characteristics of the for,while,do-while cycle are similar, and no one is faster or slow
default.Copying files between OSS, currently only supports copying object and does not support copying multipart.General recommendationsJobs * Parallel and CPU cores are 1:1,2:1, but not too bigToo many concurrent numbers will directly fill the network card, the CPU will be crowded. It is recommended to observe the environment CPU, network, process/thread condition while concurrencyReferenceOssutil Large File Breakpoint continuationPlease add a link to the original link descriptionThis article
1. JPS (Java Virtual machine Process Status Tool)JPS is primarily used to output process state information running in the JVM-Q does not output the class name, jar name, and parameters passed in the Main method-m output parameters that pass in the Main method-L OUTPUT The full name of the main class or Jar-V Output parameters for incoming JVM2. JstackJstack is used primarily to view thread stack information within a Java processThe command line parameter options are described below:-L long listi
Performance optimizations for CSS:
Related tuning of Style tags
How to use special CSS styles
CSS abbreviation (color, up or down merge, etc.)
CSS declarations (the class on the page should be unique globally, and locating a node with a unique class name is often quicker than combining positioning.) separation of styles from elements, both independently maintained )
CSS selectors (the ID select
AIX
Performance Tuning-Memory and CPU
Sar-P all CPU usage
Sar-A File AccessThe number of fast reads (B) by the Directory Access daemon when the dirblk/s locates the fileIget/s I node to find the number of times the system process is calledLookuppn/s Directory: the number of times the process finds the V node and obtains the path name.
Activity of SAR-B buffer, including transmission, access, and hit rateNu
for new TCP connections, which defaults to 0, which means shutdown; Net.ipv4.tcp_tw_recycle = 1 indicates a fast recovery of time-wait sockets in a TCP connection, and the default is 0, which means close; NET.IPV4.TCP_FIN_TIMEOUT=30 modifies the default timeout time for the system . If the above configuration tuning performance is not ideal, you can continue to modify the configuration:Vi/etc/sysctl.co
Linux system Performance Tuning related commands summary:1. PS: See which processes are currently running in the systemCommon commands are PS aux | Grep-i MySQLHttp://www.cnblogs.com/peida/archive/2012/12/19/2824418.html2. Top: Dynamic display of the CPU, memory usage, and load of each programHttp://www.cnblogs.com/ggjucheng/archive/2012/01/08/2316399.html3. Overall load of IO, process IO load, load from a
Tags: mysql, mariadbEvery day seems very busy, in fact, found themselves still very lazy, read a lot of books, not a good read. Recently, not so much work, decided to finish reading a few books, and continue to keep on updating. I hope I can persist in the end! The later content is all about MySQL management (performance tuning, high availability and monitoring), mariadb and MySQL, and your own experiments.
MySQL Management: Performance tuning, high availability and monitoring mini-bookmysql5.5.x Main Improvements1. Use InnoDB storage engine by default2. Make full use of CPU multi-core processing capability3, improve the number of brush write dirty pages and merge the number of inserts, improve I/O4, let Innodb_buffer_pool buffer pool of heat data to survive longer, pollution problems5, InnoDB Data recovery ti
so that you can mark the snapshot information set at important times. A baseline is defined between a pair of snapshots, and the snapshot is identified by their snapshot sequence number. eachThe baseline has only a couple of snapshots. A typical performance tuning practice starts with collecting baseline collections of metrics, making changes, and then capturing another set of baselines. You can compare th
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