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  • How do I change the location of DivX cache files?

    - by andygrunt
    I recently installed to the latest version of DivX and suddenly found my C drive filling up with the cache files. I tracked it down to: C:\Files\My Videos\DivX Movies\Temporary Downloaded Files My old laptop (running WinXP) only has a small hard drive and any DivX cache files fills it up so I want it to use my D drive where I have a little more room. The trouble is I can't see anywhere in the DivX preferences where I can change the cache location. Can anyone tell me how I can change the location of the DivX cache files?

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  • Can I reduce the CPU speed of my MacBook when on battery?

    - by Greg Hewgill
    I've got a MacBook with a Core 2 Duo CPU. I've got CoreDuoTemp installed which can show the current speed of the CPU. It appears to always show: Mini : 1.0 GHz Maxi : 2.0 GHz Current : 2.0 GHz I believe my laptop would run longer on battery if it were to run at a maximum of 1 GHz. Is there a way to configure this, or is the CPU speed adjustment completely automatic?

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  • How to see if turbo boost is working on I7 860 CPU?

    - by Jan Derk
    I just build myself a new system with a Intel I7 860 CPU. When loading it using a single threaded application like Super PI, CPU-Z shows 2.933Ghz as speed. Now I understood that the I7 goes into turbo boost mode up to 3.46GHz for a single core. How can I check that? Is there a utility to monitor CPU speed per core?

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  • Sudden and frequent hangs on desktop computer: mobo or CPU fault?

    - by djechelon
    I have a desktop computer equipped with an ASUS Crosshair 2 Formula and a Phenom x6 3.2GHz CPU. My problem is that often the computer will hang all of a sudden, completely stopping responding. When that occurs, reset key is inoperative and power button turns the computer off but is unable to turn it back on. I have to physically disconnect power cable. The problem can occur anytime, when I'm booting Windows, when I'm logging in, when I'm listening to a song, when I'm browsing Internet, etc. It always occurs after very few minutes of 3D gameplay I thought it was a video card fault. I had 3 8800GTX so I could try all combinations of them: didn't fix I thought it was a RAM problem: I tried running with only a subset of my DDR2 banks but didn't fix. Almost every time I have to reset and reconfigure BIOS (without AHCI, Win7 won't boot, so I need to restore a few things). If I enable AMD Live, Cool&Quiet or other things from CPU configuration menu I'll be sure that the computer won't reach Windows desktop in 99% of cases (it randomly hangs somewhere in the boot process or even in the BIOS POST). Another interesting thing is that during the POST process the computer always takes unusually long time detecting USB devices (LCD POSTer shows USB INIT), and I've also tried disconnecting all USB devices but didn't take less time to POST BIOS revision is 2702, the latest. Today I found a different behaviour once: during boot screen I got a BSOD with error Stop 0x00000101 A clock interrupt was not received on a secondary processor within the allocated time interval, and this is usually related to overclocking, but I never overclocked my CPU. Judging from the description of my problem, hoping someone had the same and fixed, and since I don't have a spare CPU or motherboard for replacement, I'd like to ask if you think this is a problem with faulty CPU or faulty motherboard, and if I can perform additional tests (I mean software tests because of my lack of spare components) to identify the component to replace.

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  • Nginx Reverse Proxy : post_action if proxy cache hit - Possbile?

    - by anonymous-one
    We have recently found out about nginxes post_action. We were wondering it there was a way to use this directive if a proxy cache hit is made? The flow we were hoping on is as follows: 1) User request comes in 2) If cache HIT goto A / If cache MISS goto B A) 1) Serve Cached Result A) 2) post_action to another url on the backend B) 1) Server request from backend B) 2) Store result from backend Any ideas if this is possible via post_action? Thanks!

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  • How to limit my CPU power programmatically on Windows 7?

    - by Ivan
    Whenever I run a CPU-heavy activity (like compressing a big set of files into an archive for example) my CPU switches to its full throttle (maximum frequency) and shuts down of overheat in less than a minute. Instead, I would like it to keep slowed-down slightly to do the task a bit slower but be able to reach the finish. At the same time I don't want to dim my screen brightness or adjust anything else what standard Windows power-saving system does. So how do I actually set a cap to limit my CPU power? The CPU is Core 2 Duo T7250, the OS is Windows 7 32-bit, there seem to be no BIOS settings or jumpers available to configure the frequencies.

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  • Why does my iTunes use so much CPU time?

    - by bikesandcode
    I have a roughly 2 year old Macbook (10.5). I have iTunes 10. When iTunes is playing MP3s, I see CPU usage of the iTunes process in the system monitor ranging from 65%-75%. When I pause the music, I see CPU usage of about 65%-75%. I do not have any visualisations going, to my knowledge I have not turned on any CPU destroying features, my music library isn't tiny, but it's hardly huge (3GB). This is mildly annoying when I'm plugged into the wall as I only have slightly longer compile times, but if I am out and about, this is a major drain on the battery. Using VLC I see CPU loads of ~= 10% at the most when listening to music and generally lower. What the heck is iTunes doing?

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  • How to diagnose issue between mobo, RAID, and SSD cache drive? [migrated]

    - by goober
    Background This issue is happening on my custom-built desktop. Relevant specs: Motherboard: ASUS P8Z68-V PRO Utilizing Intel RST technology (application that uses unused SSD as cache) Processor: Intel core i7-2600k (not overclocked) HDDs: RAID1 of 2x Seagate Barracuda 1TB (ST31000524AS) (RAID performed via z68 chipset) Machine has run fine for ~1 year with no issues, and has been well-maintained (dust, etc.) What Happened Random Freezing issues -- intermittent Looked at the RST application screen to see that the acceleration cache was listed as "unavailable" -- recommended that I power down and reconnect the drive. Reconnected the drive to no avail. Attempted to move the drive to another SATA port. Acceleration option disappeared from RST software. Now, the freeze happens whenever loading something particularly data-driven (a video, a game, etc.) Steps Attempted Reconnected the drive to no avail. Updated Intel RST software to v. 11.6.0.1030 to see if that made a difference. Attempted to move the drive to another SATA port. Acceleration option disappeared from RST software. Connected the drive as its own volume. Formatted it, ran disk check errors -- all seems fine. Reconnected the drive and selected it again as the cache drive. Now, what happens when there is a freeze: Machine freezes I am unable to perform any command Screen then goes black I hit the reset button During boot, all drives show as "Disabled" and I am told no volume can be found I then hit the reset button (or power off/on) again. Either the next time (or sometimes after repeating this once more), the metadata cache is reconstructed and the system boots fine, showing the SSD as a cache. Question I believe this is an issue with the SSD itself, but how can I be sure since connecting it separately appeared to show no problems? I want to make sure it's not an issue with the motherboard, SATA ports, etc.

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  • Can an ESX server under heavy load cause cpu spikes on guest VM's?

    - by ReferentiallySeethru
    So we have a number of vm's running on an ESX 4.1 server for product testing. The ESX Server is at times under heavy load. We've been experiencing high CPU levels during some use cases, but we can't always duplicate this. If the ESX server as a whole is under heavy load could this cause guest machines to show high CPU usage? To ask it a different way, if the guest machines require more cpu resources than the server has, how does this affect CPU usage as indicated by the OS and process?

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  • 100% CPU in QuickTime H.264 decoder on Windows on Win7, except when using XP compat. mode

    - by user858518
    I have a Windows program that uses the Apple QuickTime API to play video. On Windows 7, CPU usage is 100% on one core, which I believe is why the playback is choppy. If I turn on XP compatibility mode for this program, the CPU usage is around 20% of one core, and playback is normal. Using a profiling tool called Very Sleepy (http://www.codersnotes.com/sleepy), I was able to narrow down the high CPU usage to a function in the QuickTime H.264 decoder called JVTCompComponentDispatch. I can't imagine why there would be a difference in CPU usage when XP compatibility mode is turned off or on. Any ideas?

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  • How to kill/restart automatically a specific Windows application if it begins taking 100% CPU?

    - by Esko Luontola
    I have one program running in the background (so I can use a remote controller with my PC) but every now and then the program crashes and begins using 100% CPU (I have quad-core, so it's 25% CPU usage). When that happens, the program needs to be killed and restarted. Is there a program for Windows, which can be used to detect automatically that a specific application hogs all the CPU, and would then automatically kill and restart that application?

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  • Boost your infrastructure with Coherence into the Cloud

    - by Nino Guarnacci
    Authors: Nino Guarnacci & Francesco Scarano,  at this URL could be found the original article:  http://blogs.oracle.com/slc/coherence_into_the_cloud_boost. Thinking about the enterprise cloud, come to mind many possible configurations and new opportunities in enterprise environments. Various customers needs that serve as guides to this new trend are often very different, but almost always united by two main objectives: Elasticity of infrastructure both Hardware and Software Investments related to the progressive needs of the current infrastructure Characteristics of innovation and economy. A concrete use case that I worked on recently demanded the fulfillment of two basic requirements of economy and innovation.The client had the need to manage a variety of data cache, which can process complex queries and parallel computational operations, maintaining the caches in a consistent state on different server instances, on which the application was installed.In addition, the customer was looking for a solution that would allow him to manage the likely situations in load peak during certain times of the year.For this reason, the customer requires a replication site, on which convey part of the requests during periods of peak; the desire was, however, to prevent the immobilization of investments in owned hardware-software architectures; so, to respond to this need, it was requested to seek a solution based on Cloud technologies and architectures already offered by the market. Coherence can already now address the requirements of large cache between different nodes in the cluster, providing further technology to search and parallel computing, with the simultaneous use of all hardware infrastructure resources. Moreover, thanks to the functionality of "Push Replication", which can replicate and update the information contained in the cache, even to a site hosted in the cloud, it is satisfied the need to make resilient infrastructure that can be based also on nodes temporarily housed in the Cloud architectures. There are different types of configurations that can be realized using the functionality "Push-Replication" of Coherence. Configurations can be either: Active - Passive  Hub and Spoke Active - Active Multi Master Centralized Replication Whereas the architecture of this particular project consists of two sites (Site 1 and Site Cloud), between which only Site 1 is enabled to write into the cache, it was decided to adopt an Active-Passive Configuration type (Hub and Spoke). If, however, the requirement should change over time, it will be particularly easy to change this configuration in an Active-Active configuration type. Although very simple, the small sample in this post, inspired by the specific project is effective, to better understand the features and capabilities of Coherence and its configurations. Let's create two distinct coherence cluster, located at miles apart, on two different domain contexts, one of them "hosted" at home (on-premise) and the other one hosted by any cloud provider on the network (or just the same laptop to test it :)). These two clusters, which we call Site 1 and Site Cloud, will contain the necessary information, so a simple client can insert data only into the Site 1. On both sites will be subscribed a listener, who listens to the variations of specific objects within the various caches. To implement these features, you need 4 simple classes: CachedResponse.java Represents the POJO class that will be inserted into the cache, and fulfills the task of containing useful information about the hypothetical links navigation ResponseSimulatorHelper.java Represents a link simulator, which has the task of randomly creating objects of type CachedResponse that will be added into the caches CacheCommands.java Represents the model of our example, because it is responsible for receiving instructions from the controller and performing basic operations against the cache, such as insert, delete, update, listening, objects within the cache Shell.java It is our controller, which give commands to be executed within the cache of the two Sites So, summarily, we execute the java class "Shell", asking it to put into the cache 100 objects of type "CachedResponse" through the java class "CacheCommands", then the simulator "ResponseSimulatorHelper" will randomly create new instances of objects "CachedResponse ". Finally, the Shell class will listen to for events occurring within the cache on the Site Cloud, while insertions and deletions are performed on Site 1. Now, we realize the two configurations of two respective sites / cluster: Site 1 and Site Cloud.For the Site 1 we define a cache of type "distributed" with features of "read and write", using the cache class store for the "push replication", a functionality offered by the project "incubator" of Oracle Coherence.For the "Site Cloud" we expect even the definition of “distributed” cache type with tcp proxy feature enabled, so it can receive updates from Site 1.  Coherence Cache Config XML file for "storage node" on "Site 1" site1-prod-cache-config.xml Coherence Cache Config XML file for "storage node" on "Site Cloud" site2-prod-cache-config.xml For two clients "Shell" which will connect respectively to the two clusters we have provided two easy access configurations.  Coherence Cache Config XML file for Shell on "Site 1" site1-shell-prod-cache-config.xml Coherence Cache Config XML file for Shell on "Site Cloud" site2-shell-prod-cache-config.xml Now, we just have to get everything and run our tests. To start at least one "storage" node (which holds the data) for the "Cloud Site", we can run the standard class  provided OOTB by Oracle Coherence com.tangosol.net.DefaultCacheServer with the following parameters and values:-Xmx128m-Xms64m-Dcom.sun.management.jmxremote -Dtangosol.coherence.management=all -Dtangosol.coherence.management.remote=true -Dtangosol.coherence.distributed.localstorage=true -Dtangosol.coherence.cacheconfig=config/site2-prod-cache-config.xml-Dtangosol.coherence.clusterport=9002-Dtangosol.coherence.site=SiteCloud To start at least one "storage" node (which holds the data) for the "Site 1", we can perform again the standard class provided by Coherence  com.tangosol.net.DefaultCacheServer with the following parameters and values:-Xmx128m-Xms64m-Dcom.sun.management.jmxremote -Dtangosol.coherence.management=all -Dtangosol.coherence.management.remote=true -Dtangosol.coherence.distributed.localstorage=true -Dtangosol.coherence.cacheconfig=config/site1-prod-cache-config.xml-Dtangosol.coherence.clusterport=9001-Dtangosol.coherence.site=Site1 Then, we start the first client "Shell" for the "Cloud Site", launching the java class it.javac.Shell  using these parameters and values: -Xmx64m-Xms64m-Dcom.sun.management.jmxremote -Dtangosol.coherence.management=all -Dtangosol.coherence.management.remote=true -Dtangosol.coherence.distributed.localstorage=false -Dtangosol.coherence.cacheconfig=config/site2-shell-prod-cache-config.xml-Dtangosol.coherence.clusterport=9002-Dtangosol.coherence.site=SiteCloud Finally, we start the second client "Shell" for the "Site 1", re-launching a new instance of class  it.javac.Shell  using  the following parameters and values: -Xmx64m-Xms64m-Dcom.sun.management.jmxremote -Dtangosol.coherence.management=all -Dtangosol.coherence.management.remote=true -Dtangosol.coherence.distributed.localstorage=false -Dtangosol.coherence.cacheconfig=config/site1-shell-prod-cache-config.xml-Dtangosol.coherence.clusterport=9001-Dtangosol.coherence.site=Site1  And now, let’s execute some tests to validate and better understand our configuration. TEST 1The purpose of this test is to load the objects into the "Site 1" cache and seeing how many objects are cached on the "Site Cloud". Within the "Shell" launched with parameters to access the "Site 1", let’s write and run the command: load test/100 Within the "Shell" launched with parameters to access the "Site Cloud" let’s write and run the command: size passive-cache Expected result If all is OK, the first "Shell" has uploaded 100 objects into a cache named "test"; consequently the "push-replication" functionality has updated the "Site Cloud" by sending the 100 objects to the second cluster where they will have been posted into a respective cache, which we named "passive-cache". TEST 2The purpose of this test is to listen to deleting and adding events happening on the "Site 1" and that are replicated within the cache on "Cloud Site". In the "Shell" launched with parameters to access the "Site Cloud" let’s write and run the command: listen passive-cache/name like '%' or a "cohql" query, with your preferred parameters In the "Shell" launched with parameters to access the "Site 1" let’s write and run the following commands: load test/10 load test2/20 delete test/50 Expected result If all is OK, the "Shell" to Site Cloud let us to listen to all the add and delete events within the cache "cache-passive", whose objects satisfy the query condition "name like '%' " (ie, every objects in the cache; you could change the tests and create different queries).Through the Shell to "Site 1" we launched the commands to add and to delete objects on different caches (test and test2). With the "Shell" running on "Site Cloud" we got the evidence (displayed or printed, or in a log file) that its cache has been filled with events and related objects generated by commands executed from the" Shell "on" Site 1 ", thanks to "push-replication" feature.  Other tests can be performed, such as, for example, the subscription to the events on the "Site 1" too, using different "cohql" queries, changing the cache configuration,  to effectively demonstrate both the potentiality and  the versatility produced by these different configurations, even in the cloud, as in our case. More information on how to configure Coherence "Push Replication" can be found in the Oracle Coherence Incubator project documentation at the following link: http://coherence.oracle.com/display/INC10/Home More information on Oracle Coherence "In Memory Data Grid" can be found at the following link: http://www.oracle.com/technetwork/middleware/coherence/overview/index.html To download and execute the whole sources and configurations of the example explained in the above post,  click here to download them; After download the last available version of the Push-Replication Pattern library implementation from the Oracle Coherence Incubator site, and download also the related and required version of Oracle Coherence. For simplicity the required .jarS to execute the example (that can be found into the Push-Replication-Pattern  download and Coherence Distribution download) are: activemq-core-5.3.1.jar activemq-protobuf-1.0.jar aopalliance-1.0.jar coherence-commandpattern-2.8.4.32329.jar coherence-common-2.2.0.32329.jar coherence-eventdistributionpattern-1.2.0.32329.jar coherence-functorpattern-1.5.4.32329.jar coherence-messagingpattern-2.8.4.32329.jar coherence-processingpattern-1.4.4.32329.jar coherence-pushreplicationpattern-4.0.4.32329.jar coherence-rest.jar coherence.jar commons-logging-1.1.jar commons-logging-api-1.1.jar commons-net-2.0.jar geronimo-j2ee-management_1.0_spec-1.0.jar geronimo-jms_1.1_spec-1.1.1.jar http.jar jackson-all-1.8.1.jar je.jar jersey-core-1.8.jar jersey-json-1.8.jar jersey-server-1.8.jar jl1.0.jar kahadb-5.3.1.jar miglayout-3.6.3.jar org.osgi.core-4.1.0.jar spring-beans-2.5.6.jar spring-context-2.5.6.jar spring-core-2.5.6.jar spring-osgi-core-1.2.1.jar spring-osgi-io-1.2.1.jar At this URL could be found the original article: http://blogs.oracle.com/slc/coherence_into_the_cloud_boost Authors: Nino Guarnacci & Francesco Scarano

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  • CPU Usage in Very Large Coherence Clusters

    - by jpurdy
    When sizing Coherence installations, one of the complicating factors is that these installations (by their very nature) tend to be application-specific, with some being large, memory-intensive caches, with others acting as I/O-intensive transaction-processing platforms, and still others performing CPU-intensive calculations across the data grid. Regardless of the primary resource requirements, Coherence sizing calculations are inherently empirical, in that there are so many permutations that a simple spreadsheet approach to sizing is rarely optimal (though it can provide a good starting estimate). So we typically recommend measuring actual resource usage (primarily CPU cycles, network bandwidth and memory) at a given load, and then extrapolating from those measurements. Of course there may be multiple types of load, and these may have varying degrees of correlation -- for example, an increased request rate may drive up the number of objects "pinned" in memory at any point, but the increase may be less than linear if those objects are naturally shared by concurrent requests. But for most reasonably-designed applications, a linear resource model will be reasonably accurate for most levels of scale. However, at extreme scale, sizing becomes a bit more complicated as certain cluster management operations -- while very infrequent -- become increasingly critical. This is because certain operations do not naturally tend to scale out. In a small cluster, sizing is primarily driven by the request rate, required cache size, or other application-driven metrics. In larger clusters (e.g. those with hundreds of cluster members), certain infrastructure tasks become intensive, in particular those related to members joining and leaving the cluster, such as introducing new cluster members to the rest of the cluster, or publishing the location of partitions during rebalancing. These tasks have a strong tendency to require all updates to be routed via a single member for the sake of cluster stability and data integrity. Fortunately that member is dynamically assigned in Coherence, so it is not a single point of failure, but it may still become a single point of bottleneck (until the cluster finishes its reconfiguration, at which point this member will have a similar load to the rest of the members). The most common cause of scaling issues in large clusters is disabling multicast (by configuring well-known addresses, aka WKA). This obviously impacts network usage, but it also has a large impact on CPU usage, primarily since the senior member must directly communicate certain messages with every other cluster member, and this communication requires significant CPU time. In particular, the need to notify the rest of the cluster about membership changes and corresponding partition reassignments adds stress to the senior member. Given that portions of the network stack may tend to be single-threaded (both in Coherence and the underlying OS), this may be even more problematic on servers with poor single-threaded performance. As a result of this, some extremely large clusters may be configured with a smaller number of partitions than ideal. This results in the size of each partition being increased. When a cache server fails, the other servers will use their fractional backups to recover the state of that server (and take over responsibility for their backed-up portion of that state). The finest granularity of this recovery is a single partition, and the single service thread can not accept new requests during this recovery. Ordinarily, recovery is practically instantaneous (it is roughly equivalent to the time required to iterate over a set of backup backing map entries and move them to the primary backing map in the same JVM). But certain factors can increase this duration drastically (to several seconds): large partitions, sufficiently slow single-threaded CPU performance, many or expensive indexes to rebuild, etc. The solution of course is to mitigate each of those factors but in many cases this may be challenging. Larger clusters also lead to the temptation to place more load on the available hardware resources, spreading CPU resources thin. As an example, while we've long been aware of how garbage collection can cause significant pauses, it usually isn't viewed as a major consumer of CPU (in terms of overall system throughput). Typically, the use of a concurrent collector allows greater responsiveness by minimizing pause times, at the cost of reducing system throughput. However, at a recent engagement, we were forced to turn off the concurrent collector and use a traditional parallel "stop the world" collector to reduce CPU usage to an acceptable level. In summary, there are some less obvious factors that may result in excessive CPU consumption in a larger cluster, so it is even more critical to test at full scale, even though allocating sufficient hardware may often be much more difficult for these large clusters.

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  • Implementing Custom CacheDependency to invalidate ASP.Net cache item

    - by Ajay
    Hi, I want to implement my own customCacheDependency class by deriving base CacheDependency, as provided SqlCacheDependency is not suitable for my case. (thousands of cache items, and there will so many subscriptions in SQL as well as issues with registration in ASP.Net) I want to use this in ASP.Net VirtualPathProvider's our custom implementation, so I can pass this CustomCacheDependecy to notify the asp.net that file content in the DB has changed. Can some one point me to any custom implementation of CacheDependency (preferably using MessageQueue)? Thanks & Regards, Ajay

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  • How to cache method results in .Net

    - by SP
    Using webmethods, caching the results is pretty straight forward using "CacheDuration" attribute. Is there a similar "easy" way to cache non-webmethod outputs (or static methods) based on the parameters? I would appreciate any help. Thanks in advance!

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  • html cache history back

    - by msaif
    if i use history.back() for button press then what will happen? html content will be displayed from local history of browser or cache and browser dont request to server? or browser request to server based on url resides in history of browser??

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  • debugging JBoss 100% CPU usage

    - by NateS
    Originally posted on Server Fault, where it was suggested this question might better asked here. We are using JBoss to run two of our WARs. One is our web app, the other is our web service. The web app accesses a database on another machine and makes requests to the web service. The web service makes JMS requests to other machines, aggregates the data, and returns it. At our biggest client, about once a month the JBoss Java process takes 100% of all CPUs. The machine running JBoss has 8 CPUs. Our web app is still accessible during this time, however pages take about 3 minutes to load. Restarting JBoss restores everything to normal. The database machine and all the other machines are fine, only the machine running JBoss is affected. Memory usage is normal. Network utilization is normal. There are no suspect error messages in the JBoss logs. I have set up a test environment as close as possible to the client's production environment and I've done load testing with as much as 2x the number of concurrent users. I have not gotten my test environment to replicate the problem. Where do we go from here? How can we narrow down the problem? Currently the only plan we have is to wait until the problem occurs in production on its own, then do some debugging to determine the cause. So far people have just restarted JBoss when the problem occurred to minimize down time. Next time it happens they will get a developer to take a look. The question is, next time it happens, what can be done to determine the cause? We could setup a separate JBoss instance on the same box and install the web app separately from the web service. This way when the problem next occurs we will know which WAR has the problem (assuming it is our code). This doesn't narrow it down much though. Should I enable JMX remote? This way the next time the problem occurs I can connect with VisualVM and see which threads are taking the CPU and what the hell they are doing. However, is there a significant down side to enabling JMX remote in a production environment? Is there another way to see what threads are eating the CPU and to get a stacktrace to see what they are doing? Any other ideas? Thanks!

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  • Clear cache with greasemonkey

    - by Paul
    I have a web application running in a kiosk, which is set up with greasemonkey so that we can customize little things about the application and ensure the customizations only occur at the kiosk. I have been digging through the GM api hoping that it would have some functionality to affect browser settings, but alas it looks like it only affects pages running in the browser. Is there a way for me to tell the browser to clear it's cache when a certain event happens in the application?

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  • Write-Through Cache

    - by Mubashar Ahmad
    Dear All I am trying to do an C# implementation of Write-through Cache to minimize the read hits on db i need your suggestions, articles or sample codes to fulfill this assignment. Initially this would be use only on one server but will be updated to work in clustered environment. I only able to get a worth reading article on Oracle Site. Please share your views Regards Mubashar

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