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  • What's the most efficient way to manage large datasets with Javascript/jQuery in IE?

    - by RenderIn
    I have a search that returns JSON, which I then transform into a HTML table in Javascript. It repeatedly calls the jQuery.append() method, once for each row. I have a modern machine, and the Firefox response time is acceptable. But in IE 8 it is unbearably slow. I decided to move the transformation from data to HTML into the server-side PHP, changing the return type from JSON to HTML. Now, rather than calling the jQuery.append() time repeatedly, I call the jQuery.html() method once with the entire table. I noticed Firefox got faster, but IE got slower. These results are anecdotal and I have not done any benchmarking, but the IE performance is very disappointing. Is there something I can do to speed up the manipulation of large amounts of data in IE or is it simply a bad idea to process very much data at once with AJAX/Javascript?

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  • Survey Probes the Project Management Concerns of Financial Services Executives

    - by Melissa Centurio Lopes
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* 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-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Do you wonder what are the top reasons why large projects in the financial industry fail to meet budgets, schedules, and other key performance criteria? Being able to answer this question can provide important insight and value of good project management practices for your organization. According to 400 senior executives who participated in a new survey conducted by the Economist Intelligence Unit and sponsored by Oracle, unrealistic project goals is the main reason for roadblocks to success Other common stumbling blocks are poor alignment between project and organizational goals, inadequate human resources, lack of strong leadership, and unwillingness among team members to point out problems. This survey sample also had a lot to say about the impact of regulatory compliance on the overall portfolio management process. Thirty-nine percent acknowledged that regulations enabled efficient functioning of their businesses. But a similar number said that regulations often require more financial resources than were originally allocated to bring projects in on time. Regulations were seen by 35 percent of the executives as roadblocks to their ability to invest in the organization’s growth and success. These revelations among others are discussed in depth in a new on-demand Webcast titled “Too Good to Fail: Developing Project Management Expertise in Financial Services” now available from Oracle. The Webcast features Brian Gardner, editor of the Economist Intelligence Unit, who presents these findings from this survey along with Guy Barlow, director of industry strategy for Oracle Primavera. Together, they analyze what the numbers mean for project and program managers and the financial services industry. Register today to watch the on-demand Webcast and get a full rundown and analysis of the survey results. Take the Economist Intelligence Unit benchmarking survey and see how your views compare with those of other financial services industry executives in ensuring project success.  Read more in the October Edition of the quarterly Information InDepth EPPM Newsletter

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  • WPF Control Toolkits Comparison for LOB Apps

    In preparation for a new WPF project Ive been researching options for WPF Control toolkits.  While we want a lot of the benefits of WPF, the application is a fairly typical line of business application (LOB).  So were not focused on things like media and animations, but instead a simple, solid, intuitive, and modern user interface that allows for well architected separation of business logic and presentation layers. While WPF is mature, it hasnt lived the long life that Winforms has yet, so there is still a lot of room for third party and community control toolkits to fill the gaps between the controls that ship with the Framework.  There are two such gaps I was concerned about.  As this is an LOB app, we have needs for presenting lots of data and not surprisingly much of it is in grid format with the need for high performance, grouping, inline editing, aggregation, printing and exporting and things that weve been doing with LOB apps for a long time.  In addition we want a dashboard style for the UI in which the user can rearrange and shrink and grow tiles that house the content and functionality.  From a cost perspective, building these types of well performing controls from scratch doesnt make sense.  So I evaluated what you get from the .NET Framework along with a few different options for control toolkits.  I tried to be fairly thorough, but know that this isnt a detailed benchmarking comparison or intense evaluation.  Its just meant to be a feature set comparison to be used when thinking about building an LOB app in WPF.  I tried to list important feature differences and notes based on my experience with the trial versions and what I found in documentation and reference materials and samples.  Ive also listed the importance of the controls based on how I think they are needed in LOB apps.  There are several toolkits available, but given I dont have unlimited time, I picked just a few.  Maybe Ill add on more later.  The toolkits I compared are: Teleriks RadControls for WPF since I had heard some good things about Telerik Infragistics NetAdvantage WPF since both I and the customer have some experience with the vendors tools WPF Toolkit on codeplex since many of my colleagues have used it Blacklight codeplex project which had WPF support for the Tile View control  (with Release 4.3 WPF is not going to be supported in favor of focusing only on SilverLight controls, so I dropped that from the comparison) Click Here to Download the WPF Control Toolkits Comparison Hopefully this helps someone out there.  Feel free to post a comment on your experiences or if you think something I listed is incorrect or missing.  Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • Proven Approach to Financial Progress Using Modern Best Practice

    - by Oracle Accelerate for Midsize Companies
    Normal 0 false false false EN-US X-NONE X-NONE by Larry Simcox, Sr. Director, Oracle Midsize Programs Top performing organizations generate 25 percent higher profit margins and grow at twice the rate of their competitors. How do they do it? Recently, Dr. Stephen G. Timme, President of FinListics Solutions and Adjunct Professor at the Georgia Institute of Technology, joined me on a webcast to answer that question. I've know Dr. Timme since my days at G-log when we worked together to help customers determine the ROI of transportation management solutions. We were also joined by Steve Cox, Vice President of Oracle Midsize Programs, who recently published an Oracle E-book, "Modern Best Practice Explained". In this webcast, Cox provides his perspective on how best performing companies are moving from best practice to modern best practice.  Watch the webcast replay and you'll learn about the easy to follow, top down approach to: Identify processes that should be targeted for improvement Leverage a modern best practice maturity model to start a path to progress Link financial performance gaps to operational KPIs Improve cash flow by benchmarking key financial metrics Develop intelligent estimates of achievable cash flow benefits Click HERE to watch a replay of the webcast. You might also be interested in the following: Video: Modern Best Practices Defined  AppCast: Modern Best Practices for Growing Companies Looking for more news and information about Oracle Solutions for Midsize Companies? Read the latest Oracle for Midsize Companies Newsletter Sign-up to receive the latest communications from Oracle’s industry leaders and experts Larry Simcox Senior Director, Oracle Midsize Programs responsible for supporting and creating marketing content ,communications, sales and partner program support for Oracle's go to market activities for midsize companies. I have over 17 years experience helping customers identify the value and ROI from their IT investment. I live in Charlotte NC with my family and my dog Dingo. The views expressed here are my own, and not necessarily those of Oracle. /* 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-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;}

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  • Overheating computer

    - by Samurai Waffle
    My computer overheats somewhat frequently, usually during intense use. And by intense use I mean browsing the internet while downloading, or gaming. It even overheats on extremely old games though, Master of Orion 2, which was developed for Windows 95. My computer has a Pentium 4 Ghz processor, 2 GB of ram, and is running Windows XP. One of the symptoms it has after overheating, is that it'll turn on immediately afterwards, but won't show any video on my monitor. I usually have to wait at least 5 minutes (mostly at least 10) before I can get it to turn on and show video on my monitor. I also usually have to wiggle around the graphics card a little bit, which is the ASUS A9550 Series with 256 MB. I'm not sure exactly what is causing the computer to overheat. At first I thought it was the video card, but after I noticed it was doing it while playing Master of Orion 2, I'm not so sure, because that game can't be making the video card work all that hard. So how exactly can I pinpoint the problem? Thanks for any help provided. Edit: Okay I downloaded the programs that you specified, and will start benchmarking my system to try and pinpoint what's overheating. What is the temperature range for when it's getting to hot? Also I have an abundant amount of software experience with computers, but unfortunately not to much hardware experience.

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  • Can compressing Program Files save space *and* give a significant boost to SSD performance?

    - by Christopher Galpin
    Considering solid-state disk space is still an expensive resource, compressing large folders has appeal. Thanks to VirtualStore, could Program Files be a case where it might even improve performance? Discovery In particular I have been reading: SSD and NTFS Compression Speed Increase? Does NTFS compression slow SSD/flash performance? Will somebody benchmark whole disk compression (HD,SSD) please? (may have to scroll up) The first link is particularly dreamy, but maybe head a little too far in the clouds. The third link has this sexy semi-log graph (logarithmic scale!). Quote (with notes): Using highly compressable data (IOmeter), you get at most a 30x performance increase [for reads], and at least a 49x performance DECREASE [for writes]. Assuming I interpreted and clarified that sentence correctly, this single user's benchmark has me incredibly interested. Although write performance tanks wretchedly, read performance still soars. It gave me an idea. Idea: VirtualStore It so happens that thanks to sanity saving security features introduced in Windows Vista, write access to certain folders such as Program Files is virtualized for non-administrator processes. Which means, in normal (non-elevated) usage, a program or game's attempt to write data to its install location in Program Files (which is perhaps a poor location) is redirected to %UserProfile%\AppData\Local\VirtualStore, somewhere entirely different. Thus, to my understanding, writes to Program Files should primarily only occur when installing an application. This makes compressing it not only a huge source of space gain, but also a potential candidate for performance gain. Testing The beginning of this post has me a bit timid, it suggests benchmarking NTFS compression on a whole drive is difficult because turning it off "doesn't decompress the objects". However it seems to me the compact command is perfectly capable of doing so for both drives and individual folders. Could it be only marking them for decompression the next time the OS reads from them? I need to find the answer before I begin my own testing.

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  • 3d Studio Max and 2+CPUs - Core limit ?

    - by FreekOne
    Hi guys, I am scouting for parts to put in a new machine, and in the process, while looking at different benchmarks I stumbled upon this benchmark and it got me a bit worried. Quote form it: Noticably absent from this review is an old-time favorite, 3ds Max. I did attempt to run our custom 3ds Max benchmark on both the 2009 and 2010 versions of the software, but the application would simply not load on the Westmere box with hyper-threading enabled. Evidently Autodesk didn't plan far enough ahead to write their software for more than 16 threads. Once there is an update that addresses this issue, I will happily add 3ds Max back into the benchmarking mix. Since I was looking at dual hexa-core Xeons (x5650), that would put my future machine at 24 logical cores which (duh) is well over 16 cores and since I'm mostly building this for 3DS Max work, you can see how this would seriously spoil my plans. I tried looking for additional information on this potential issue, but the above article seems to be the only one who mentions it. Could anyone who has access to a 16 core machine or an in-depth knowledge about 3DS Max please confirm this ? Any help would be much appreciated !

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  • Hard Drive benchmark values show write very very slow

    - by John
    I recently started to have issues with my laptop being very slow. I ran a hard drive benchmarking tool (by ATTO) that showed that the write speed was very very slow on my boot drive. I ran the same benchmark on my usb drive and it was 650 times faster than my boot drive when it came to writing. Reading is very fast/normal on both. I swapped out an identical drive and ran the same benchmark. This time the drive showed proper write speed. Thinking that I had a hard drive going bad I cloned the old one onto the new one. I managed to clone the problem too. Anyone have any ideas on what in WinXP SP3 might be causing the write issues? I am on a corporate network and we have commercial anti-virus software installed. (AVG I think) I regularly run defraggler and have about 40 gig free on a 100 gig drive. The machine has 4 gigs of memory. Any ideas? TIA J

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  • dd oflag=direct 5x fast

    - by César
    I have Centos 6.2 in server with this specs: 2xCPU 16 Core AMD Opteron 6282 SE 64GB RAM Raid controller H700 1GB cache NV - 2HD 74GB SAS 15Krpm RAID1 stripe 16k (OS Centos 6.2) sda - 4HD 146GB SAS 15Krpm RAID10 stripe 16k (ext4 bs 4096, no barriers) sdb -> /vol01 Raid controller H800 1GB cache nv - MD1200 12HD 300GB SAS 15Krpm RAID10 stripe 256k (For DB Postgres 8.3.18) (ext4 bs 4096, stride 64, stripe-width 384, no barriers) sdc -> /vol02 I'm benchmarking IO speed with dd, and view thah if in RAID10 12 disk exec: dd if=/dev/zero of=DD bs=8M count=10000 oflag=direct 10000+0 records in 10000+0 records out 83886080000 bytes (84 GB) copied, 126,03 s, 666 MB/s but if I remove "oflag=direct" option obtain about 80 MB/s. In read benchmark, results are similar: dd of=/dev/null if=DD bs=8M count=10000 iflag=direct 10000+0 records in 10000+0 records out 83886080000 bytes (84 GB) copied, 79,5918 s, 1,1 GB/s If remove iflag=direct obtain 150MB/s... I don't understand this huge differences, on other machines y don't have this behavior. Can I have some kernel parameter misconfigured? Thanks!

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  • Macbook Pro - 15" with i7 processor - Any problems with heat?

    - by webworm
    You may have already heard about the review done by the folks at PC Authority in Australia, where they had an i7 MacBook Pro that got up to 100 degrees Celsius during benchmarking. Here is the URL in case you have not read it. http://www.pcauthority.com.au/News/172791,macbook-pro-helps-core-i7-hit-100-degrees.aspx In any case, I was considering purchasing a 15" Macbook Pro with the i7 processor and the NVIDIA GeForce GT330M with 512 video memory. Having read how hot the computer got I started to become hesitant about purchasing. My main concern is long term damage to the computer due to excessive heat. I plan to use the MacBook Pro as a development machine where I will be running Windows 7 within VMWare Fusion or Virtual Box. Within the VM I will be running IIS, SQL Server, Visual Studio and SharePoint Server. Hence why I would like to have the power of the i7 processor. That is why I wanted to check with actually owners of the MacBooks with the i7 processor and see what their experiences have been. Have you noticed excessive heat? How does your Macbook handle process intensive apps over long periods of time? Thank you!

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  • Performance: Nginx SSL slowness or just SSL slowness in general?

    - by Mauvis Ledford
    I have an Amazon Web Services setup with an Apache instance behind Nginx with Nginx handling SSL and serving everything but the .php pages. In my ApacheBench tests I'm seeing this for my most expensive API call (which cache via Memcached): 100 concurrent calls to API call (http): 115ms (median) 260ms (max) 100 concurrent calls to API call (https): 6.1s (median) 11.9s (max) I've done a bit of research, disabled the most expensive SSL ciphers and enabled SSL caching (I know it doesn't help in this particular test.) Can you tell me why my SSL is taking so long? I've set up a massive EC2 server with 8CPUs and even applying consistent load to it only brings it up to 50% total CPU. I have 8 Nginx workers set and a bunch of Apache. Currently this whole setup is on one EC2 box but I plan to split it up and load balance it. There have been a few questions on this topic but none of those answers (disable expensive ciphers, cache ssl, seem to do anything.) Sample results below: $ ab -k -n 100 -c 100 https://URL This is ApacheBench, Version 2.3 <$Revision: 655654 $> Copyright 1996 Adam Twiss, Zeus Technology Ltd, http://www.zeustech.net/ Licensed to The Apache Software Foundation, http://www.apache.org/ Benchmarking URL.com (be patient).....done Server Software: nginx/1.0.15 Server Hostname: URL.com Server Port: 443 SSL/TLS Protocol: TLSv1/SSLv3,AES256-SHA,2048,256 Document Path: /PATH Document Length: 73142 bytes Concurrency Level: 100 Time taken for tests: 12.204 seconds Complete requests: 100 Failed requests: 0 Write errors: 0 Keep-Alive requests: 0 Total transferred: 7351097 bytes HTML transferred: 7314200 bytes Requests per second: 8.19 [#/sec] (mean) Time per request: 12203.589 [ms] (mean) Time per request: 122.036 [ms] (mean, across all concurrent requests) Transfer rate: 588.25 [Kbytes/sec] received Connection Times (ms) min mean[+/-sd] median max Connect: 65 168 64.1 162 268 Processing: 385 6096 3438.6 6199 11928 Waiting: 379 6091 3438.5 6194 11923 Total: 449 6264 3476.4 6323 12196 Percentage of the requests served within a certain time (ms) 50% 6323 66% 8244 75% 9321 80% 9919 90% 11119 95% 11720 98% 12076 99% 12196 100% 12196 (longest request)

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  • Website has become slower on a VPS, was much fast on a shared host. What's wrong?

    - by Arpit Tambi
    My shared host suspended my website stating system overload, so I moved my website to a VPS which has 4GB RAM. But for some reason the website has become very slow. This is the vmstat output - procs -----------memory---------- ---swap-- -----io---- --system-- -----cpu------ r b swpd free buff cache si so bi bo in cs us sy id wa st 1 0 0 3050500 0 0 0 0 0 1 0 0 0 0 100 0 0 Here's the Apache Benchmark output for a STATIC html page I ran on the server itself - Benchmarking www.ask-oracle.com (be patient)...apr_poll: The timeout specified has expired (70007) Total of 20 requests completed Update: Server Config: List item Centos 5.6 4 cores cpu 4 GB RAM LAMP stack with APC Wordpress Only one website It takes almost double time to load now, same website was much fast on shared hosting. I know I need to tweak some settings but have no clue where to start from? I have already tried to optimize apache, mysql etc. Update 2: CPU usage is low, see uptime output: 11:09:02 up 7 days, 21:26, 1 user, load average: 0.09, 0.11, 0.09 Update 3: When I load any webpage, browser shows "Waiting" for a long time and then page loads quickly. So I suspect server can accept only limited connections and holds extra connections in a waiting state. How to check this? Update 4: Following is the output on executing netperf TCP STREAM TEST from 0.0.0.0 (0.0.0.0) port 0 AF_INET to localhost.localdomain (127.0.0.1) port 0 AF_INET Recv Send Send Socket Socket Message Elapsed Size Size Size Time Throughput bytes bytes bytes secs. 10^6bits/sec 87380 16384 16384 10.00 9615.40 [root@ip-118-139-177-244 j3ngn5ri6r01t3]# Here are the Apache MPM settings from httpd.conf, do they look okay? <IfModule worker.c> StartServers 5 MaxClients 100 MinSpareThreads 50 MaxSpareThreads 250 ThreadsPerChild 125 MaxRequestsPerChild 10000 ServerLimit 100 </IfModule>

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  • Why is writing to my external hard drive slow, while benchmarks show fast writing?

    - by matix2267
    I have an iOmega eGo 320GB portable drive connected through USB2.0 to my laptop running Windows Vista. It's been working fine for quite some time until recently it became very slow when writing e.g. when copying ~300MB movie over to the drive at first it is extremely fast but it actually doesn't write it only puts in cache and then hangs on last 10-20MBs for about a minute. When copying larger files it's the same story: starts fast but then slows down to ~5MB/s (sometimes even slower down to 2MB/s). Strange thing is that I have always had caching disabled for this drive (it was disabled by default and I never bothered changing it). At first I thought that the disk is dying so I checked S.M.A.R.T. values and everything is fine there. I also run chkdsk and it seemed to fix the problem - it worked fast for a few minutes but then it slowed down again. I also tried plugging it into another USB port - no difference. Additionally I noticed that reading under certain circumstances is sometimes slower e.g. loading times for some games are ~10 times longer, whereas simple copying files from this drive to my internal HDD is fast. I ran a speed benchmark using CrystalDiskMark with a 5x100MB run and strangely got these results: read write (MB/s) Seq 33.05 28.25 512k 17.30 15.27 4k 0.267 0.372 4kQD32 0.510 0.260 This is different from what most other people have (I've found many threads about slow disk write while googling but all of them were slow on benchmarks too) which is why I decided to post this problem here. BTW most of the time when writing (or sometimes reading) the activity led is mostly idle (blinks a while and then stops for longer, sometimes has slower blinks ~1 sek, sometimes goes off for a few seconds - extremely long blink :) ) but when benchmarking, defragmenting or just reading (copying from this drive, installing apps from installers there, watching HD videos) it is blinking really fast (like it should) and there are no slowdowns. It shouldn't be driver issue unless stock Windows drivers have some issues I'm not aware of.

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  • IBM BladeCenter S: Disk Configuration

    - by gravyface
    Have just the one storage bay right now (SAS 15K 600GB x 6) and have configured one storage pool in RAID 10 with 4 disks (and two global spares). For each blade, I've created a volume and mapped accordingly: Blade #1 400 GB Blade #2 200 GB Blade #3 100 GB Blade #4 100 GB When I boot up Blade 1 and enter into the UEFI Setup (F1) followed by the Adapters and UEFI Drivers LSI Logic Fusion MPT SAS Driver Utility, I see 4 disks: two are the on-board 73GB drives, the other two are 200GB each and assume I'm being presented with two logical disks from the volume I created and mapped to this blade. I was a bit surprised by this: I figured I would've been presented with one logical drive per volume, not two. I'm assuming I can just configure whatever RAID level I wish that supports two disks, but not really sure what the benefits/trade-offs here. Should I go with RAID 10 on top of RAID 10? RAID 0? Software RAID 0/1/10? Does it even matter? If this is "normal" to see two disks, then I'm going to likely just do some benchmarking and see if it makes a difference changing the RAID levels (my guess is no); if this is not normal, well, please let me know. :)

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  • Tuning Linux + HAProxy

    - by react
    I'm currently rolling out HAProxy on Centos 6 which will send requests to some Apache HTTPD servers and I'm having issues with performance. I've spent the last couple of days googling and still can't seem to get past 10k/sec connections consistently when benchmarking (sometimes I do get 30k/sec though). I've pinned the IRQ's of the TX/RX queues for both the internal and external NICS to separate CPU cores and made sure HAProxy is pinned to it's own core. I've also made the following adjustments to sysctl.conf: # Max open file descriptors fs.file-max = 331287 # TCP Tuning net.ipv4.tcp_tw_reuse = 1 net.ipv4.ip_local_port_range = 1024 65023 net.ipv4.tcp_max_syn_backlog = 10240 net.ipv4.tcp_max_tw_buckets = 400000 net.ipv4.tcp_max_orphans = 60000 net.ipv4.tcp_synack_retries = 3 net.core.somaxconn = 40000 net.ipv4.tcp_rmem = 4096 8192 16384 net.ipv4.tcp_wmem = 4096 8192 16384 net.ipv4.tcp_mem = 65536 98304 131072 net.core.netdev_max_backlog = 40000 net.ipv4.tcp_tw_reuse = 1 If I use AB to hit the a webserver directly I easily get 30k/s connections. If I stop the webservers and use AB to hit HAProxy then I get 30k/s connections but obviously it's useless. I've also disabled iptables for now since I read that nf_conntrack can slow everything down, no change. I've also disabled the irqbalance service. The fact that I can hit each individual device with 30k/s makes me believe the tuning of the servers is OK and that it must be some HAProxy config? Here's the config which I've built from reading tuning articles, etc http://pastebin.com/zsCyAtgU The server is a dual Xeon CPU E5-2620 (6 cores) with 32GB of RAM. Running Centos 6.2 x64. The private and public interfaces are on separate NICS. Anyone have any ideas? Thanks.

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  • When using software RAID and LVM on Linux, which IO scheduler and readahead settings are honored?

    - by andrew311
    In the case of multiple layers (physical drives - md - dm - lvm), how do the schedulers, readahead settings, and other disk settings interact? Imagine you have several disks (/dev/sda - /dev/sdd) all part of a software RAID device (/dev/md0) created with mdadm. Each device (including physical disks and /dev/md0) has its own setting for IO scheduler (changed like so) and readahead (changed using blockdev). When you throw in things like dm (crypto) and LVM you add even more layers with their own settings. For example, if the physical device has a read ahead of 128 blocks and the RAID has a readahead of 64 blocks, which is honored when I do a read from /dev/md0? Does the md driver attempt a 64 block read which the physical device driver then translates to a read of 128 blocks? Or does the RAID readahead "pass-through" to the underlying device, resulting in a 64 block read? The same kind of question holds for schedulers? Do I have to worry about multiple layers of IO schedulers and how they interact, or does the /dev/md0 effectively override underlying schedulers? In my attempts to answer this question, I've dug up some interesting data on schedulers and tools which might help figure this out: Linux Disk Scheduler Benchmarking from Google blktrace - generate traces of the i/o traffic on block devices Relevant Linux kernel mailing list thread

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  • amazon ec2-medium apache requests per second terrible

    - by TheDayIsDone
    EDITED -- test running from localhost now to rule out network... i have a c1.medium using EBS. when i do an apache benchmark and i'm just printing a "hello" for the test from localhost - no database hits, it's very slow. i can repeat this test many times with the same results. any thoughts? thanks in advance. ab -n 1000 -c 100 http://localhost/home/test/ Benchmarking localhost (be patient) Completed 100 requests Completed 200 requests Completed 300 requests Completed 400 requests Completed 500 requests Completed 600 requests Completed 700 requests Completed 800 requests Completed 900 requests Completed 1000 requests Finished 1000 requests Server Software: Apache/2.2.23 Server Hostname: localhost Server Port: 80 Document Path: /home/test/ Document Length: 5 bytes Concurrency Level: 100 Time taken for tests: 25.300 seconds Complete requests: 1000 Failed requests: 0 Write errors: 0 Total transferred: 816000 bytes HTML transferred: 5000 bytes Requests per second: 39.53 [#/sec] (mean) Time per request: 2530.037 [ms] (mean) Time per request: 25.300 [ms] (mean, across all concurrent requests) Transfer rate: 31.50 [Kbytes/sec] received Connection Times (ms) min mean[+/-sd] median max Connect: 0 7 21.0 0 73 Processing: 81 2489 665.7 2500 4057 Waiting: 80 2443 654.0 2445 4057 Total: 85 2496 653.5 2500 4057 Percentage of the requests served within a certain time (ms) 50% 2500 66% 2651 75% 2842 80% 2932 90% 3301 95% 3506 98% 3762 99% 3838 100% 4057 (longest request)

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  • Exception with RubyAMF and Ruby 1.9 although code works

    - by Tam
    I'm getting an exception with RubyAMF using Ruby 1.9 and Rails 2.3.5. Although code afterward executes normally I'm not very comfortable with seeing such exception in the log file. Do you know what is causing it: >>>>>>>> RubyAMF >>>>>>>>> #<RubyAMF::Actions::PrepareAction:0x0000010139ff48> took: 0.00020 secs >>>>>>>> RubyAMF >>>>>>>>> #<RubyAMF::Actions::RailsInvokeAction:0x0000010139ff10> took: 0.29973 secs You have a nil object when you didn't expect it! You might have expected an instance of Array. The error occurred while evaluating nil.include? /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/activerecord-2.3.5/lib/active_record/attribute_methods.rb:142:in `create_time_zone_conversion_attribute?' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/activerecord-2.3.5/lib/active_record/attribute_methods.rb:75:in `block in define_attribute_methods' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/activerecord-2.3.5/lib/active_record/attribute_methods.rb:71:in `each' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/activerecord-2.3.5/lib/active_record/attribute_methods.rb:71:in `define_attribute_methods' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/activerecord-2.3.5/lib/active_record/attribute_methods.rb:242:in `method_missing' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/activerecord-2.3.5/lib/active_record/base.rb:2832:in `hash' /Users/tammam56/lal/vendor/plugins/ruby_amf/io/amf_serializer.rb:366:in `hash' /Users/tammam56/lal/vendor/plugins/ruby_amf/io/amf_serializer.rb:366:in `hash' /Users/tammam56/lal/vendor/plugins/ruby_amf/io/amf_serializer.rb:366:in `[]=' /Users/tammam56/lal/vendor/plugins/ruby_amf/io/amf_serializer.rb:366:in `store_object' /Users/tammam56/lal/vendor/plugins/ruby_amf/io/amf_serializer.rb:234:in `write_amf3_object' /Users/tammam56/lal/vendor/plugins/ruby_amf/io/amf_serializer.rb:154:in `write_amf3' /Users/tammam56/lal/vendor/plugins/ruby_amf/io/amf_serializer.rb:78:in `write' /Users/tammam56/lal/vendor/plugins/ruby_amf/io/amf_serializer.rb:70:in `block in run' /Users/tammam56/lal/vendor/plugins/ruby_amf/io/amf_serializer.rb:56:in `upto' /Users/tammam56/lal/vendor/plugins/ruby_amf/io/amf_serializer.rb:56:in `run' /Users/tammam56/lal/vendor/plugins/ruby_amf/app/filters.rb:91:in `block in run' /Users/tammam56/.rvm/rubies/ruby-1.9.1-p378/lib/ruby/1.9.1/benchmark.rb:309:in `realtime' /Users/tammam56/lal/vendor/plugins/ruby_amf/app/filters.rb:91:in `run' /Users/tammam56/lal/vendor/plugins/ruby_amf/app/filters.rb:12:in `block in run' /Users/tammam56/lal/vendor/plugins/ruby_amf/app/filters.rb:11:in `each' /Users/tammam56/lal/vendor/plugins/ruby_amf/app/filters.rb:11:in `run' /Users/tammam56/lal/vendor/plugins/ruby_amf/app/rails_gateway.rb:28:in `service' /Users/tammam56/lal/app/controllers/rubyamf_controller.rb:19:in `gateway' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/base.rb:1331:in `perform_action' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/filters.rb:617:in `call_filters' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/filters.rb:610:in `perform_action_with_filters' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/benchmarking.rb:68:in `block in perform_action_with_benchmark' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/activesupport-2.3.5/lib/active_support/core_ext/benchmark.rb:17:in `block in ms' /Users/tammam56/.rvm/rubies/ruby-1.9.1-p378/lib/ruby/1.9.1/benchmark.rb:309:in `realtime' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/activesupport-2.3.5/lib/active_support/core_ext/benchmark.rb:17:in `ms' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/benchmarking.rb:68:in `perform_action_with_benchmark' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/rescue.rb:160:in `perform_action_with_rescue' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/flash.rb:146:in `perform_action_with_flash' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/base.rb:532:in `process' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/filters.rb:606:in `process_with_filters' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/base.rb:391:in `process' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/base.rb:386:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/routing/route_set.rb:437:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/dispatcher.rb:87:in `dispatch' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/dispatcher.rb:121:in `_call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/dispatcher.rb:130:in `block in build_middleware_stack' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/activerecord-2.3.5/lib/active_record/query_cache.rb:29:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/activerecord-2.3.5/lib/active_record/query_cache.rb:29:in `block in call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/activerecord-2.3.5/lib/active_record/connection_adapters/abstract/query_cache.rb:34:in `cache' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/activerecord-2.3.5/lib/active_record/query_cache.rb:9:in `cache' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/activerecord-2.3.5/lib/active_record/query_cache.rb:28:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/activerecord-2.3.5/lib/active_record/connection_adapters/abstract/connection_pool.rb:361:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/string_coercion.rb:25:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/rack-1.0.1/lib/rack/head.rb:9:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/rack-1.0.1/lib/rack/methodoverride.rb:24:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/params_parser.rb:15:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/session/cookie_store.rb:93:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/failsafe.rb:26:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/rack-1.0.1/lib/rack/lock.rb:11:in `block in call' <internal:prelude>:8:in `synchronize' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/rack-1.0.1/lib/rack/lock.rb:11:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/dispatcher.rb:114:in `block in call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/reloader.rb:34:in `run' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/actionpack-2.3.5/lib/action_controller/dispatcher.rb:108:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/rails-2.3.5/lib/rails/rack/static.rb:31:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/rack-1.0.1/lib/rack/urlmap.rb:46:in `block in call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/rack-1.0.1/lib/rack/urlmap.rb:40:in `each' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/rack-1.0.1/lib/rack/urlmap.rb:40:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/rails-2.3.5/lib/rails/rack/log_tailer.rb:17:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/rack-1.0.1/lib/rack/content_length.rb:13:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/rack-1.0.1/lib/rack/chunked.rb:15:in `call' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/rack-1.0.1/lib/rack/handler/mongrel.rb:64:in `process' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/mongrel-1.1.5/lib/mongrel.rb:159:in `block in process_client' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/mongrel-1.1.5/lib/mongrel.rb:158:in `each' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/mongrel-1.1.5/lib/mongrel.rb:158:in `process_client' /Users/tammam56/.rvm/gems/ruby-1.9.1-p378/gems/mongrel-1.1.5/lib/mongrel.rb:285:in `block (2 levels) in run '

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  • BizTalk 2009 - BizTalk Benchmark Wizard: Running a Test

    - by StuartBrierley
    The BizTalk Benchmark Wizard is a ultility that can be used to gain some validation of a BizTalk installation, giving a level of guidance on whether it is performing as might be expected.  It should be used after BizTalk Server has been installed and before any solutions are deployed to the environment.  This will ensure that you are getting consistent and clean results from the BizTalk Benchmark Wizard. The BizTalk Benchmark Wizard applies load to the BizTalk Server environment under a choice of specific scenarios. During these scenarios performance counter information is collected and assessed against statistics that are appropriate to the BizTalk Server environment. For details on installing the Benchmark Wizard see my previous post. The BizTalk Benchmarking Wizard provides two simple test scenarios, one for messaging and one for Orchestrations, which can be used to test your BizTalk implementation. Messaging Loadgen generates a new XML message and sends it over NetTCP A WCF-NetTCP Receive Location receives a the xml document from Loadgen. The PassThruReceive pipeline performs no processing and the message is published by the EPM to the MessageBox. The WCF One-Way Send Port, which is the only subscriber to the message, retrieves the message from the MessageBox The PassThruTransmit pipeline provides no additional processing The message is delivered to the back end WCF service by the WCF NetTCP adapter Orchestrations Loadgen generates a new XML message and sends it over NetTCP A WCF-NetTCP Receive Location receives a the xml document from Loadgen. The XMLReceive pipeline performs no processing and the message is published by the EPM to the MessageBox. The message is delivered to a simple Orchestration which consists of a receive location and a send port The WCF One-Way Send Port, which is the only subscriber to the Orchestration message, retrieves the message from the MessageBox The PassThruTransmit pipeline provides no additional processing The message is delivered to the back end WCF service by the WCF NetTCP adapter Below is a quick outline of how to run the BizTalk Benchmark Wizard on a single server, although it should be noted that this is not ideal as this server is then both generating and processing the load.  In order to separate this load out you should run the "Indigo" service on a seperate server. To start the BizTalk Benchmark Wizard click Start > All Programs > BizTalk Benchmark Wizard > BizTalk Benchmark Wizard. On this screen click next, you will then get the following pop up window. Check the server and database names and check the "check prerequsites" check-box before pressing ok.  The wizard will then check that the appropriate test scenarios are installed. You should then choose the test scenario that wish to run (messaging or orchestration) and the architecture that most closely matches your environment. You will then be asked to confirm the host server for each of the host instances. Next you will be presented with the prepare screen.  You will need to start the indigo service before pressing the Test Indigo Service Button. If you are running the indigo service on a separate server you can enter the server name here.  To start the indigo service click Start > All Programs > BizTalk Benchmark Wizard > Start Indigo Service.   While the test is running you will be presented with two speed dial type displays - one for the received messages per second and one for the processed messages per second. The green dial shows the current rate and the red dial shows the overall average rate.  Optionally you can view the CPU usage of the various servers involved in processing the tests. For my development environment I expected low results and this is what I got.  Although looking at the online high scores table and comparing to the quad core system listed, the results are perhaps not really that bad. At some time I may look at what improvements I can make to this score, but if you are interested in that now take a look at Benchmark your BizTalk Server (Part 3).

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  • Which key:value store to use with Python?

    - by Kurt
    So I'm looking at various key:value (where value is either strictly a single value or possibly an object) stores for use with Python, and have found a few promising ones. I have no specific requirement as of yet because I am in the evaluation phase. I'm looking for what's good, what's bad, what are the corner cases these things handle well or don't, etc. I'm sure some of you have already tried them out so I'd love to hear your findings/problems/etc. on the various key:value stores with Python. I'm looking primarily at: memcached - http://www.danga.com/memcached/ python clients: http://pypi.python.org/pypi/python-memcached/1.40 http://www.tummy.com/Community/software/python-memcached/ CouchDB - http://couchdb.apache.org/ python clients: http://code.google.com/p/couchdb-python/ Tokyo Tyrant - http://1978th.net/tokyotyrant/ python clients: http://code.google.com/p/pytyrant/ Lightcloud - http://opensource.plurk.com/LightCloud/ Based on Tokyo Tyrant, written in Python Redis - http://code.google.com/p/redis/ python clients: http://pypi.python.org/pypi/txredis/0.1.1 MemcacheDB - http://memcachedb.org/ So I started benchmarking (simply inserting keys and reading them) using a simple count to generate numeric keys and a value of "A short string of text": memcached: CentOS 5.3/python-2.4.3-24.el5_3.6, libevent 1.4.12-stable, memcached 1.4.2 with default settings, 1 gig memory, 14,000 inserts per second, 16,000 seconds to read. No real optimization, nice. memcachedb claims on the order of 17,000 to 23,000 inserts per second, 44,000 to 64,000 reads per second. I'm also wondering how the others stack up speed wise.

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  • EPIPE blocks server

    - by timn
    I have written a single-threaded asynchronous server in C running on Linux: The socket is non-blocking and as for polling, I am using epoll. Benchmarks show that the server performs fine and according to Valgrind, there are no memory leaks or other problems. The only problem is that when a write() command is interrupted (because the client closed the connection), the server will encounter a SIGPIPE. I am doing the interrupted artifically by running the benchmarking utility "siege" with the parameter -b. It does lots of requests in a row which all work perfectly. Now I press CTRL-C and restart the "siege". Sometimes I am lucky and the server does not manage to send the full response because the client's fd is invalid. As expected errno is set to EPIPE. I handle this situation, execute close() on the fd and then free the memory related to the connection. Now the problem is that the server blocks and does not answer properly anymore. Here is the strace output: accept(3, {sa_family=AF_INET, sin_port=htons(50611), sin_addr=inet_addr("127.0.0.1")}, [16]) = 5 fcntl64(5, F_GETFD) = 0 fcntl64(5, F_SETFL, O_RDONLY|O_NONBLOCK) = 0 epoll_ctl(4, EPOLL_CTL_ADD, 5, {EPOLLIN|EPOLLERR|EPOLLHUP|EPOLLET, {u32=158310248, u64=158310248}}) = 0 epoll_wait(4, {{EPOLLIN, {u32=158310248, u64=158310248}}}, 128, -1) = 1 read(5, "GET /user/register HTTP/1.1\r\nHos"..., 4096) = 161 write(5, "HTTP/1.1 200 OK\r\nContent-Type: t"..., 106) = 106 <<<<< write(5, "00001000\r\n", 10) = -1 EPIPE (Broken pipe) <<<<< Why did the previous write() work fine but not this one? --- SIGPIPE (Broken pipe) @ 0 (0) --- As you can see, the client establishes a new connection which consequently is accepted. Then, it's added to the EPOLL queue. epoll_wait() signalises that the client sent data (EPOLLIN). The request is parsed and and a response is composed. Sending the headers works fine but when it comes to the body, write() results in an EPIPE. It is not a bug in "siege" because it blocks any incoming connections, no matter from which client.

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  • Python Socket Getting Connection Reset

    - by Ian
    I created a threaded socket listener that stores newly accepted connections in a queue. The socket threads then read from the queue and respond. For some reason, when doing benchmarking with 'ab' (apache benchmark) using a concurrency of 2 or more, I always get a connection reset before it's able to complete the benchmark (this is taking place locally, so there's no external connection issue). class server: _ip = '' _port = 8888 def __init__(self, ip=None, port=None): if ip is not None: self._ip = ip if port is not None: self._port = port self.server_listener(self._ip, self._port) def now(self): return time.ctime(time.time()) def http_responder(self, conn, addr): httpobj = http_builder() httpobj.header('HTTP/1.1 200 OK') httpobj.header('Content-Type: text/html; charset=UTF-8') httpobj.header('Connection: close') httpobj.body("Everything looks good") data = httpobj.generate() sent = conn.sendall(data) def http_thread(self, id): self.log("THREAD %d: Starting Up..." % id) while True: conn, addr = self.q.get() ip, port = addr self.log("THREAD %d: responding to request: %s:%s - %s" % (id, ip, port, self.now())) self.http_responder(conn, addr) self.q.task_done() conn.close() def server_listener(self, host, port): self.q = Queue.Queue(0) sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) sock.bind( (host, port) ) sock.listen(5) for i in xrange(4): #thread count thread.start_new(self.http_thread, (i+1, )) while True: self.q.put(sock.accept()) sock.close() server('', 9999) When running the benchmark, I get totally random numbers of good requests before it errors out, usually between 4 and 500. Edit: Took me a while to figure it out, but the problem was in sock.listen(5). Because I was using apache benchmark with a higher concurrency (5 and up) it was causing the backlog of connections to pile up, at which point the connections started getting dropped by the socket.

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  • Why do my CouchDB databases grow so fast?

    - by konrad
    I was wondering why my CouchDB database was growing to fast so I wrote a little test script. This script changes an attributed of a CouchDB document 1200 times and takes the size of the database after each change. After performing these 1200 writing steps the database is doing a compaction step and the db size is measured again. In the end the script plots the databases size against the revision numbers. The benchmarking is run twice: The first time the default number of document revision (=1000) is used (_revs_limit). The second time the number of document revisions is set to 1. The first run produces the following plot The second run produces this plot For me this is quite an unexpected behavior. In the first run I would have expected a linear growth as every change produces a new revision. When the 1000 revisions are reached the size value should be constant as the older revisions are discarded. After the compaction the size should fall significantly. In the second run the first revision should result in certain database size that is then keeps during the following writing steps as every new revision leads to the deletion of the previous one. I could understand if there is a little bit of overhead needed to manage the changes but this growth behavior seems weird to me. Can anybody explain this phenomenon or correct my assumptions that lead to the wrong expectations?

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  • Why is my code slower using #import "progid:typelib" than using "MFC Class From TypeLib"?

    - by Pakman
    I am writing an automation client in Visual C++ with MFC. If I right-click on my solution » Add » Class, I have the option to select MFC Class From TypeLib. Selecting this option generates source/header files for all interfaces. This allows me to write code such as: #include "CApplication.h" #include "CDocument.h" // ... connect to automation server ... CApplication *myApp = new CApplication(pDisp); CDocument myDoc = myApp->get_ActiveDocument(); Using this method, my benchmarking function that makes about 12000 automation calls takes 1 second. Meanwhile, the following code: #import "progid:Library.Application" Library::IApplicationPtr myApp; // ... connect to automation server ... Library::IDocumentPtr myDoc = myApp->GetActiveDocument(); takes about 2.4 seconds for the same benchmark. I assume the smart-pointer implementation is slowing me down, but I don't know why. Even worse, I'm not sure how to use #import construct to achieve the speeds that the first method yields. Is this possible? How or why not? Thanks for your time!

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  • Using EhCache for session.createCriteria(...).list()

    - by James Smith
    I'm benchmarking the performance gains from using a 2nd level cache in Hibernate (enabling EhCache), but it doesn't seem to improve performance. In fact, the time to perform the query slightly increases. The query is: session.createCriteria(MyEntity.class).list(); The entity is: @Entity @Cache(usage = CacheConcurrencyStrategy.NONSTRICT_READ_WRITE) public class MyEntity { @Id @GeneratedValue private long id; @Column(length=5000) private String data; //---SNIP getters and setters--- } My hibernate.cfg.xml is: <!-- all the normal stuff to get it to connect & map the entities plus:--> <property name="hibernate.cache.region.factory_class"> net.sf.ehcache.hibernate.EhCacheRegionFactory </property> The MyEntity table contains about 2000 rows. The problem is that before adding in the cache, the query above to list all entities took an average of 65 ms. After the cache, they take an average of 74 ms. Is there something I'm missing? Is there something extra that needs to be done that will increase performance?

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