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• Database Trends & Applications column: Database Benchmarking from A to Z

  - by KKline

  Have you heard of the monthly print and web magazine Database Trends & Applications (DBTA)? Did you know I'm the regular columnist covering SQL Server ? For the past six months, I've been writing a series of articles about database benchmarking culminating in the latest article discussing my three favorite database benchmarking tools: the free, open-source HammerDB, the native SQL Server Distributed Replay Utility, and the commercial Benchmark Factory from Dell / Quest Software. Wondering what...(read more)

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• Benchmarking CPU processing power

  - by Federico Zancan

  Provided that many tools for computers benchmarking are available already, I'd like to write my own, starting with processing power measurement. I'd like to write it in C under Linux, but other language alternatives are welcome. I thought starting from floating point operations per second, but it is just a hint. I also thought it'd be correct to keep track of CPU number of cores, RAM amount and the like, to more consistently associate results with CPU architecture. How would you proceed to the task of measuring CPU computing power? And on top of that: I would worry about a properly minimum workload induced by concurrently running services; is it correct to run benchmarking as a standalone (and possibly avulsed from the OS environment) process?

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• Benchmarking ORM associations

  - by barerd

  I am trying to benchmark two cases of self referential many to many as described in datamapper associations. Both cases consist of an Item clss, which may require many other items. In both cases, I required the ruby benchmark library and source file, created two items and benchmarked require/unrequie functions as below: Benchmark.bmbm do |x| x.report("require:") { item_1.require_item item_2, 10 } x.report("unrequire:") { item_1.unrequire_item item_2 } end To be clear, both functions are datamapper add/modify functions like: componentMaps.create :component_id => item.id, :quantity => quantity componentMaps.all(:component_id => item.id).destroy! and links_to_components.create :component_id => item.id, :quantity => quantity links_to_components.all(:component_id => item.id).destroy! The results are variable and in the range of 0.018001 to 0.022001 for require function in both cases, and 0.006 to 0.01 for unrequire function in both cases. This made me suspicious about the correctness of my test method. Edit I went ahead and compared a "get by primary key case" to a "finding first matching record case" by: (1..10000).each do |i| Item.create :name => "item_#{i}" end Benchmark.bmbm do |x| x.report("Get") { item = Item.get 9712 } x.report("First") { item = Item.first :name => "item_9712" } end where the results were very different like 0 sec compared to 0.0312, as expected. This suggests that the benchmarking works. I wonder whether I benchmarked the two types of associations correctly, and whether a difference between 0.018 and 0.022 sec significant?

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• How to invalidate cache when benchmarking?

  - by Michael Buen

  I have this code, that when swapping the order of UsingAs and UsingCast, their performance also swaps. using System; using System.Diagnostics; using System.Linq; using System.IO; class Test { const int Size = 30000000; static void Main() { object[] values = new MemoryStream[Size]; UsingAs(values); UsingCast(values); Console.ReadLine(); } static void UsingCast(object[] values) { Stopwatch sw = Stopwatch.StartNew(); int sum = 0; foreach (object o in values) { if (o is MemoryStream) { var m = (MemoryStream)o; sum += (int)m.Length; } } sw.Stop(); Console.WriteLine("Cast: {0} : {1}", sum, (long)sw.ElapsedMilliseconds); } static void UsingAs(object[] values) { Stopwatch sw = Stopwatch.StartNew(); int sum = 0; foreach (object o in values) { if (o is MemoryStream) { var m = o as MemoryStream; sum += (int)m.Length; } } sw.Stop(); Console.WriteLine("As: {0} : {1}", sum, (long)sw.ElapsedMilliseconds); } } Outputs: As: 0 : 322 Cast: 0 : 281 When doing this... UsingCast(values); UsingAs(values); ...Results to this: Cast: 0 : 322 As: 0 : 281 When doing just this... UsingAs(values); ...Results to this: As: 0 : 322 When doing just this: UsingCast(values); ...Results to this: Cast: 0 : 322 Aside from running them independently, how to invalidate the cache so the second code being benchmarked won't receive the cached memory of first code? Benchmarking aside, just loved the fact that modern processors do this caching magic :-)

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• How to run benchmarking on MySQL?

  - by HexaHow

  My server has installed MySQL Server 5.1. I would like to run benchmarking on the MySQL, but I couldn't found sql-bench, which is Benchmark Suite provided by MySQL. The MySQL Benchmark Suite seem like complicated to be install or setup into my server. I need one can be direct setup to test the benchmark without using Perl script liked the benchmark suite from MySQL. Do anyone knows how to get the most popular benchmarking tool to measure MySQL performance? I need to measure the performance of my SQL written in ASP.Net that connecting to MySQL. I need to optimize the SQL script. It's better has a benchmarking tool where can be read my SQL in many times and return me the query result's time for comparison, etc. I just need to know the time consuming and performance for the each SQL runs in many times.

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• Benchmarking MySQL on win7

  - by Patrick

  I've setup a nginx server running php 5.3.6 and mysql 5.5.1.3. My computer is an AMD quadcore 9650, 4gb ram, 500gb 7200rpm HD. I ran the PHP MySQL Benchmark Tool v. 0.1, and got the following results: Testing a(n) MYISAM table using 100000 rows. Successfully created database speedtestdb Sucessfully created table speedtesttable Table Type Verified: MYISAM .. Done. 100000 inserts in 19.73628 seconds or 5067 inserts per second. Done. 100000 row reads in 0.2801 seconds or 357015 row reads per second. Done. 100000 updates in 4.03876 seconds or 24760 updates per second. I'm wondering where this stands as far as performance goes, and what are some steps I can take if any to improve on this. I'm not trying to make anything fantastic, just getting a feel for how to best optimize a web server in this configuration.

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• Benchmarking hosting providers IO with Bonnie

  - by Derek Organ

  Ok, because of a bunch of projects I'm working on I've access to dedicated Servers on a 3 hosting providers. As an experiment and for educational purposes I decided to see if I could benchmark how good the IO is with each. Bit of research lead me to Bonnie++ So I installed it on the server and ran this simple command /usr/sbin/bonnie -d /tmp/foo The 3 machines in different hosting providers are all dedicated machines, one is a VPS, other two are on some cloud platform e.g. VMWare / Xen using some kind of clustered SAN for storage This might be a naive thing to do but here are the results I found. HOST A Version 1.03c ------Sequential Output------ --Sequential Input- --Random- -Per Chr- --Block-- -Rewrite- -Per Chr- --Block-- --Seeks-- Machine Size K/sec %CP K/sec %CP K/sec %CP K/sec %CP K/sec %CP /sec %CP xxxxxxxxxxxxxxxx 1G 45081 88 56244 14 19167 4 20965 40 67110 6 67.2 0 ------Sequential Create------ --------Random Create-------- -Create-- --Read--- -Delete-- -Create-- --Read--- -Delete-- files /sec %CP /sec %CP /sec %CP /sec %CP /sec %CP /sec %CP 16 15264 28 +++++ +++ +++++ +++ +++++ +++ +++++ +++ +++++ +++ xxxxxxxx,1G,45081,88,56244,14,19167,4,20965,40,67110,6,67.2,0,16,15264,28,+++++,+++,+++++,+++,+++++,+++,+++++,+++,+++++,+++ HOST B Version 1.03d ------Sequential Output------ --Sequential Input- --Random- -Per Chr- --Block-- -Rewrite- -Per Chr- --Block-- --Seeks-- Machine Size K/sec %CP K/sec %CP K/sec %CP K/sec %CP K/sec %CP /sec %CP xxxxxxxxxxxx 4G 43070 91 64510 15 19092 0 29276 47 39169 0 448.2 0 ------Sequential Create------ --------Random Create-------- -Create-- --Read--- -Delete-- -Create-- --Read--- -Delete-- files /sec %CP /sec %CP /sec %CP /sec %CP /sec %CP /sec %CP 16 24799 52 +++++ +++ +++++ +++ 25443 54 +++++ +++ +++++ +++ xxxxxxx,4G,43070,91,64510,15,19092,0,29276,47,39169,0,448.2,0,16,24799,52,+++++,+++,+++++,+++,25443,54,+++++,+++,+++++,+++ HOST C Version 1.03c ------Sequential Output------ --Sequential Input- --Random- -Per Chr- --Block-- -Rewrite- -Per Chr- --Block-- --Seeks-- Machine Size K/sec %CP K/sec %CP K/sec %CP K/sec %CP K/sec %CP /sec %CP xxxxxxxxxxxxx 1536M 15598 22 85698 13 258969 20 16194 22 723655 21 +++++ +++ ------Sequential Create------ --------Random Create-------- -Create-- --Read--- -Delete-- -Create-- --Read--- -Delete-- files /sec %CP /sec %CP /sec %CP /sec %CP /sec %CP /sec %CP 16 14142 22 +++++ +++ 18621 22 13544 22 +++++ +++ 17363 21 xxxxxxxx,1536M,15598,22,85698,13,258969,20,16194,22,723655,21,+++++,+++,16,14142,22,+++++,+++,18621,22,13544,22,+++++,+++,17363,21 Ok, so first off what is the best way to read the figures and are there any issues with really comparing these numbers? Is this in any way a true representation of IO Speed? If not is there any way for me to test that? Note: these 3 machines are using either Ubuntu or Debian (I presume that doesn't really matter)

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• Codeigniter benchmarking, where are these ms coming from?

  - by ropstah

  I'm in the process of benchmarking my website. class Home extends Controller { function Home() { parent::Controller(); $this->benchmark->mark('Constructor_start'); $this->output->enable_profiler(TRUE); $this->load->library ('MasterPage'); $this->benchmark->mark('Constructor_end'); } function index() { $this->benchmark->mark('Index_start'); $this->masterpage->setMasterPage('master/home'); $this->masterpage->addContent('home/index', 'page'); $this->masterpage->show(); $this->benchmark->mark('Index_start'); } } These are the results: Loading Time Base Classes: 0.0076 Constructor: 0.0007 Index: 0.0440 Controller Execution Time ( Home/ Index ): 0.4467 Total Execution Time: 0.4545` I understand the following: Loading Time Base Classes (0.0076) Constructor (0.0007) Index (0.0440) But where is the rest of the time coming from?

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• Benchmarking PHP page load times

  - by Anant

  How could I measure the time taken to load a page (with various different PHP statements)? Somewhat like the stats available here - http://talks.php.net/show/drupal08/24

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• Graph representation benchmarking

  - by Carlucho

  Currently am developing a program that solves (if possible) any given labyrinth of dimensions from 3X4 to 26x30. I represent the graph using both adj matrix (sparse) and adj list. I would like to know how to output the total time taken by the DFS to find the solution using one and then the other method. Programatically, how could i produce such benchmark?

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• Benchmarking a UDP server

  - by Nicolas

  I am refactoring a UDP listener from Java to C. It needs to handle between 1000 and 10000 UDP messages per second, with an average data length of around 60 bytes. There is no reply necessary. Data cannot be lost (Don't ask why UDP was decided). I fork off a process to deal with the incoming data so that I can recvfrom as quickly as possible - without filling up my kernel buffers. The child then handles the data received. In short, my algo is: Listen for data. When data is received, check for errors. Fork off a child. If I'm a child, do what I with the data and exit. If I'm a parent, reap any zombie children waitpid(-1, NULL, WNOHANG). Repeat. Firstly, any comments about the above? I'm creating the socket with socket(AF_INET, SOCK_DGRAM, IPPROTO_UDP), binding with AF_INET and INADDR_ANY and recvfrom with no flags. Secondly, can anyone suggest something that I can use to test that this application (or at least the listener) can handle more messages than what I am expecting? Or, would I need to hack something together to do this. I'd guess the latter would be better, so that I can compare data that is generated versus data that is received. But, comments would be appreciated.

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• Benchmarking a particular method in Objective-C

  - by Jasconius

  I have a critical method in an Objective-C application that I need to optimize as much as possible. I first need to take some easy benchmarks on this one single method so I can compare my progress as I optimize. What is the easiest way to track the execution time of a given method in, say, milliseconds, and print that to console.

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• Server Benchmarking: What tools to use with my real-world test data

  - by mdemmitt

  I want to benchmark a new server using historical HTTP-request data. I have a textfile that contains one day's worth of real historical requests to a production server. What is the best tool for sending that list of requests on the server I'm testing? The tool I use should be able to configure the following: Number of threads making the requests Number of requests/second sent A list of request URLs to use when making the requests. Apache Bench seems like a close fit. However, Bench does not seem to be able to take in a list of request URLs as a parameter. What would you recommend?

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• Benchmarking Java programs

  - by stefan-ock

  For university, I perform bytecode modifications and analyze their influence on performance of Java programs. Therefore, I need Java programs---in best case used in production---and appropriate benchmarks. For instance, I already got HyperSQL and measure its performance by the benchmark program PolePosition. The Java programs running on a JVM without JIT compiler. Thanks for your help! P.S.: I cannot use programs to benchmark the performance of the JVM or of the Java language itself (such as Wide Finder).

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• Visual Studio add-in for performance benchmarking

  - by chiccodoro

  I'd like to measure the performance of some code blocks in my c# winforms application. In particular I want to measure performance regression/improvement after some restructuring of the code. So long I've seen the System.Diagnostics.Stopwatch. However, I want to avoid writing measuring code into my classes, I would rather prefer to separate measuring from actual code. As for debugging, you can set breakpoints on several code lines and "jump" from one to the next by "Continue Execution", I imagine something similar for measuring: Mark to lines of code and make Visual Studio display the time elapsing from one to the next. Is there any feature/add-in in that direction?

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• C-states and P-states : confounding factors for benchmarking

  - by Dave

  I was recently looking into a performance issue in the java.util.concurrent (JUC) fork-join pool framework related to particularly long latencies when trying to wake (unpark) threads in the pool. Eventually I tracked the issue down to the power & scaling governor and idle-state policies on x86. Briefly, P-states refer to the set of clock rates (speeds) at which a processor can run. C-states reflect the possible idle states. The deeper the C-state (higher numerical values) the less power the processor will draw, but the longer it takes the processor to respond and exit that sleep state on the next idle to non-idle transition. In some cases the latency can be worse than 100 microseconds. C0 is normal execution state, and P0 is "full speed" with higher Pn values reflecting reduced clock rates. C-states are P-states are orthogonal, although P-states only have meaning at C0. You could also think of the states as occupying a spectrum as follows : P0, P1, P2, Pn, C1, C2, ... Cn, where all the P-states are at C0. Our fork-join framework was calling unpark() to wake a thread from the pool, and that thread was being dispatched onto a processor at deep C-state, so we were observing rather impressive latencies between the time of the unpark and the time the thread actually resumed and was able to accept work. (I originally thought we were seeing situations where the wakee was preempting the waker, but that wasn't the case. I'll save that topic for a future blog entry). It's also worth pointing out that higher P-state values draw less power and there's usually some latency in ramping up the clock (P-states) in response to offered load. The issue of C-states and P-states isn't new and has been described at length elsewhere, but it may be new to Java programmers, adding a new confounding factor to benchmarking methodologies and procedures. To get stable results I'd recommend running at C0 and P0, particularly for server-side applications. As appropriate, disabling "turbo" mode may also be prudent. But it also makes sense to run with the system defaults to understand if your application exhibits any performance sensitivity to power management policies. The operating system power management sub-system typically control the P-state and C-states based on current and recent load. The scaling governor manages P-states. Operating systems often use adaptive policies that try to avoid deep C-states for some period if recent deep idle episodes proved to be very short and futile. This helps make the system more responsive under bursty or otherwise irregular load. But it also means the system is stateful and exhibits a memory effect, which can further complicate benchmarking. Forcing C0 + P0 should avoid this issue.

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• Benchmarking Linux flash player and google chrome built in flash player

  - by Fischer

  I use xubuntu 14.04 64 bit, I installed flash player from software center and xubuntu-restricted-extras too Are there any benchmarks on Linux flash player and google chrome built in flash player? I just want to see their performance because in theory google's flash player should be more updated and have better performance than the one we use in Firefox. (that's what I read everywhere) I have chrome latest version installed and Firefox next, and I found that flash videos in Chrome are laggy and they take long time to load. While the same flash videos load much faster in Firefox and I tend to prefer watching flash videos in firefox, especially the long ones because it loads them so much faster. I can't believe these results on my PC, so is there any way to benchmark flash players performance on both browsers? I want to know if it's because of the flash player or the browsers or something else

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• Looking for WAMP Benchmarking (my current WAMP is very slow, so are other solutions)

  - by therobyouknow

  I'm running ZWAMP WAMP stack on my local development machine. However I have found it to be very slow at serving pages from a Drupal site I have setup. By contrast, my live production site on shared hosting is reasonably quick. For me the goal with a local WAMP stack was to develop offline and send completed work to the live production site. I liked ZWAMP because it didn't require adjustments to User Access Control or other permissions. I've looked at Drupal Acquia Development Stack but found this too restrictive: only one site instance/doc root can be installed. I've looked at other DAMP stacks and heard reports of them being slow. My local development machine that I am running the WAMP stack on is a Dual Core 2.6Ghz hyperthreaded Intel i7, 4Gb RAM, 7200rpm hard disk, running Windows 64bit professional. Surely this is fast enough. So I'm looking for: Causes of the slowness of the WAMP and how to improve the speed Benchmark data of various WAMP stacks

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• Benchmarking MySQL Replication with Multi-Threaded Slaves

  - by Mat Keep

  0 0 1 1145 6530 Homework 54 15 7660 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} The objective of this benchmark is to measure the performance improvement achieved when enabling the Multi-Threaded Slave enhancement delivered as a part MySQL 5.6. As the results demonstrate, Multi-Threaded Slaves delivers 5x higher replication performance based on a configuration with 10 databases/schemas. For real-world deployments, higher replication performance directly translates to: · Improved consistency of reads from slaves (i.e. reduced risk of reading "stale" data) · Reduced risk of data loss should the master fail before replicating all events in its binary log (binlog) The multi-threaded slave splits processing between worker threads based on schema, allowing updates to be applied in parallel, rather than sequentially. This delivers benefits to those workloads that isolate application data using databases - e.g. multi-tenant systems deployed in cloud environments. Multi-Threaded Slaves are just one of many enhancements to replication previewed as part of the MySQL 5.6 Development Release, which include: · Global Transaction Identifiers coupled with MySQL utilities for automatic failover / switchover and slave promotion · Crash Safe Slaves and Binlog · Optimized Row Based Replication · Replication Event Checksums · Time Delayed Replication These and many more are discussed in the “MySQL 5.6 Replication: Enabling the Next Generation of Web & Cloud Services” Developer Zone article  Back to the benchmark - details are as follows. Environment The test environment consisted of two Linux servers: · one running the replication master · one running the replication slave. Only the slave was involved in the actual measurements, and was based on the following configuration: - Hardware: Oracle Sun Fire X4170 M2 Server - CPU: 2 sockets, 6 cores with hyper-threading, 2930 MHz. - OS: 64-bit Oracle Enterprise Linux 6.1 - Memory: 48 GB Test Procedure Initial Setup: Two MySQL servers were started on two different hosts, configured as replication master and slave. 10 sysbench schemas were created, each with a single table: CREATE TABLE `sbtest` (    `id` int(10) unsigned NOT NULL AUTO_INCREMENT,    `k` int(10) unsigned NOT NULL DEFAULT '0',    `c` char(120) NOT NULL DEFAULT '',    `pad` char(60) NOT NULL DEFAULT '',    PRIMARY KEY (`id`),    KEY `k` (`k`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1 10,000 rows were inserted in each of the 10 tables, for a total of 100,000 rows. When the inserts had replicated to the slave, the slave threads were stopped. The slave data directory was copied to a backup location and the slave threads position in the master binlog noted. 10 sysbench clients, each configured with 10 threads, were spawned at the same time to generate a random schema load against each of the 10 schemas on the master. Each sysbench client executed 10,000 "update key" statements: UPDATE sbtest set k=k+1 WHERE id = <random row> In total, this generated 100,000 update statements to later replicate during the test itself. Test Methodology: The number of slave workers to test with was configured using: SET GLOBAL slave_parallel_workers=<workers> Then the slave IO thread was started and the test waited for all the update queries to be copied over to the relay log on the slave. The benchmark clock was started and then the slave SQL thread was started. The test waited for the slave SQL thread to finish executing the 100k update queries, doing "select master_pos_wait()". When master_pos_wait() returned, the benchmark clock was stopped and the duration calculated. The calculated duration from the benchmark clock should be close to the time it took for the SQL thread to execute the 100,000 update queries. The 100k queries divided by this duration gave the benchmark metric, reported as Queries Per Second (QPS). Test Reset: The test-reset cycle was implemented as follows: · the slave was stopped · the slave data directory replaced with the previous backup · the slave restarted with the slave threads replication pointer repositioned to the point before the update queries in the binlog. The test could then be repeated with identical set of queries but a different number of slave worker threads, enabling a fair comparison. The Test-Reset cycle was repeated 3 times for 0-24 number of workers and the QPS metric calculated and averaged for each worker count. MySQL Configuration The relevant configuration settings used for MySQL are as follows: binlog-format=STATEMENT relay-log-info-repository=TABLE master-info-repository=TABLE As described in the test procedure, the slave_parallel_workers setting was modified as part of the test logic. The consequence of changing this setting is: 0 worker threads:    - current (i.e. single threaded) sequential mode    - 1 x IO thread and 1 x SQL thread    - SQL thread both reads and executes the events 1 worker thread:    - sequential mode    - 1 x IO thread, 1 x Coordinator SQL thread and 1 x Worker thread    - coordinator reads the event and hands it to the worker who executes 2+ worker threads:    - parallel execution    - 1 x IO thread, 1 x Coordinator SQL thread and 2+ Worker threads    - coordinator reads events and hands them to the workers who execute them Results Figure 1 below shows that Multi-Threaded Slaves deliver ~5x higher replication performance when configured with 10 worker threads, with the load evenly distributed across our 10 x schemas. This result is compared to the current replication implementation which is based on a single SQL thread only (i.e. zero worker threads). Figure 1: 5x Higher Performance with Multi-Threaded Slaves The following figure shows more detailed results, with QPS sampled and reported as the worker threads are incremented. The raw numbers behind this graph are reported in the Appendix section of this post. Figure 2: Detailed Results As the results above show, the configuration does not scale noticably from 5 to 9 worker threads. When configured with 10 worker threads however, scalability increases significantly. The conclusion therefore is that it is desirable to configure the same number of worker threads as schemas. Other conclusions from the results: · Running with 1 worker compared to zero workers just introduces overhead without the benefit of parallel execution. · As expected, having more workers than schemas adds no visible benefit. Aside from what is shown in the results above, testing also demonstrated that the following settings had a very positive effect on slave performance: relay-log-info-repository=TABLE master-info-repository=TABLE For 5+ workers, it was up to 2.3 times as fast to run with TABLE compared to FILE. Conclusion As the results demonstrate, Multi-Threaded Slaves deliver significant performance increases to MySQL replication when handling multiple schemas. This, and the other replication enhancements introduced in MySQL 5.6 are fully available for you to download and evaluate now from the MySQL Developer site (select Development Release tab). You can learn more about MySQL 5.6 from the documentation  Please don’t hesitate to comment on this or other replication blogs with feedback and questions. Appendix – Detailed Results

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• Website Benchmarking - How Does Your Website Compare?

  With over 14 billion websites, the internet is fast becoming the first place people look for information. As the number of websites swells it becomes increasingly difficult to set your own website apart from the rest. Being able to quantify the friendliness of your website is essential if you want to know what changes can be made for the better and how you can expect those changes to effect traffic and ranking.

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• Benchmarking and Comparing Encog, Neuroph and JOONE Neural Networks

  I compare the performance of Encog, Neuroph and JOONE.

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• How to identify web development benchmarking questions? [closed]

  - by GenericJam

  I am in my final year of college and I have to put forward some sort of thesis for my final year project. The project is a web based attendance system that I am building for the college. I have it about 70% complete in Java. After completing it in Java, the plan is for me to rewrite the server bit in Erlang and then release the bitter rivals in a head to head cage match. The idea being that there is some sort of grounds for comparison. There are a few hurdles along the way, such as me learning Erlang. I understand that a performance comparison like this isn't strictly scientific as there are many factors such as the programmer (myself); the hardware it runs on; etc... but it is meant to be a reasonable comparison of the merits of using Java vs. Erlang for web development. I need help in identifying what the relevant questions are that my project could address. Even though the project scope is fixed, I am trying to shoehorn in some worthwhile scientific inquiries.

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• ab benchmarking testing

  - by Tennyson

  I have a question about ab benchmarking test, if i need to measure the time the server takes to serve IO.php with persistent connection. does the persistent connection mean i need to input "./ab -k ........." or "./ab -n 1000 -c 100 ........." Thanks a lot

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• http benchmarking?

  - by Sam Williams

  im running varnish-nginx(php-fpm) and im using ab but it keeps messing up. [root@localhost src]# ab -k -n 100000 -c 750 http://192.168.135.12/index.php This is ApacheBench, Version 2.0.40-dev <$Revision: 1.146 $> apache-2.0 Copyright 1996 Adam Twiss, Zeus Technology Ltd, http://www.zeustech.net/ Copyright 2006 The Apache Software Foundation, http://www.apache.org/ Benchmarking 192.168.135.12 (be patient) apr_socket_recv: Connection reset by peer (104) is there anything else i can use? or am i doing it wrong?

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• can benchmarking burn computer components

  - by user23950

  I only have the ordinary cooling mechanism of a computer. 1 fan for the power supply and two fans that share the same cable. Can benchmarking my computer lead to burning of the processor or the ram or the hdd? Can you give me some applications that can lead to this

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