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  • ubuntu hardrive repartition without uninstalling ubuntu or windows 7 and losing data of hardrive

    - by user141692
    I have and asus r500v with 750 gb gpt system uefi motherboard core i7 3610qm, nvidia geforce gt, with ubuntu and w7 dual boot, I had problems installing ubuntu because of the grub but I fix it with https://bugs.launchpad.net/ubuntu/+source/grub2/+bug/807801, but I still have the problem of "warning: the partition is misaligned by 3072 bytes. this may result iin very poor performance. Repartitioning is suggested" in every linux partitioin I made and my 750 gb is not being used at the maximun capacity it only uses 698 gb. I want to make partitions so that the warning doesnt show up and I can use the maximum capacity of the HDD, as I did with another dual boot laptop (compaq presario cq40). I have the following partitions: unknown 1.0Mb: partition type: lynux Basic DAta partition, device: /dev/sda2 Usage: --, Partition flags: --, partition label:-- warning: the partition is misaligned by 3072 bytes. this may result in very poor performance. repartitioning is suggested. -system 210 Mb FAt, usage: Filesystem, partition type: EFI system Partition, Partition Flags:--, Label: system, Device: /dev/sda1, partition label: EFI system partition, Capacity 210MB, avilable:--, Mount Point: mounted at /boot/efi -134 Mb NTFS, usage: filesystem, partition type: linux basic data partition, partition flags:.--, device: /dev/sda7, partition label: --, capacity: 134MB,available:--, mount point: not mounted -OS 250 GB NTFS, usage: file system, partititon type: linux basic data partition, partition flags: --, type: NTFS, label: OS, device: /dev/sda3, partition label: basic data partition, capacity: 250 GB, available:-, mount point: not mounted -10GB FAT 32, usage: filesystem, partition type: EFI system partition, partition flags:--, type: FAT 32, label: --, device: /dev/sda4, partition label: --, capacity: 10GB, available:--, mount point: not mounted warning: the partition is misaligned by 3072 bytes. this may result in very poor performance. repartitioning is suggested. -10gb ext 4, usage: file system, partition type: linux basic data partition, partition flags:--, type: EXT4(version1) label:--, device: /dev/sda9, partition label:--, capacity: 10 GB, available:--, mount point at / warning: the partition is misaligned by 1536 bytes. this may result in very poor performance. repartitioning is suggested. -478GB ext4, usage: filesystem, partition type: linux basic data partition, partition flags:--, type: EXT4, label:--, device: /dev/sda5, partition label:--, capacity: 478gb, available:--, mount point: mounted at /home warning: the partition is misaligned by 512 bytes. this may result in very poor performance. repartitioning is suggested. -2.0gb Swap 2.0Gb, usage: swap space, partition type: linux swap partitioin, partition flags:-, device: /dev/sda6, partition label: capacity: 2.0gb warning: the partition is misaligned by 512 bytes. this may result in very poor performance. repartitioning is suggested. and as you can see it is not well organized so please help me to organize the partitions witahout uninstalling the w7, and if possible the grub2

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  • Implications of using many USB web cameras

    - by Martin
    I'm looking into connecting multiple low resolution USB webcams to a single computer. What implications might this have on performance? How does, for example, four 320x240 cameras fare against a single 640x480 camera? I'm not well versed in the architecture of the USB interface, what are the performance caveats? By performance I mean how would it affect the time to read the image data from multiple cameras compared to a single one.

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  • How to get Windows Server 2008 VM to use multiple cores

    - by David Fraser
    I have a Windows Server 2008 machine running in VirtualBox. On initial installation, only one processor was made available, but now I want to run it as a multiprocessor machine. I have made all four cores available in the VirtualBox settings (as well as enabling VT-x/AMD-V and Nested Paging), but Task Manager still only shows one CPU. However, the four CPU cores are visible in Device Manager under Processors. In the event log on startup, I can see the following relevant events: EventLog.6009 Microsoft (R) Windows (R) 6.00.6002 Service Pack 2 Multiprocessor Free Kernel-Processor-Power.4 Processor 0 exposes the following: 1 idle state(s), 0 performance state(s), 0 throttle state(s) Kernel-Processor-Power.4 Processor 255 exposes the following: 0 idle state(s), 0 performance state(s), 0 throttle state(s) Kernel-Processor-Power.4 Processor 255 exposes the following: 0 idle state(s), 0 performance state(s), 0 throttle state(s) Kernel-Processor-Power.4 Processor 255 exposes the following: 0 idle state(s), 0 performance state(s), 0 throttle state(s) How can I make this system actually boot up as a multiprocessor machine?

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  • How to get Windows Server 2008 VM to use multiple cores

    - by David Fraser
    I have a Windows Server 2008 machine running in VirtualBox. On initial installation, only one processor was made available, but now I want to run it as a multiprocessor machine. I have made all four cores available in the VirtualBox settings (as well as enabling VT-x/AMD-V and Nested Paging), but Task Manager still only shows one CPU. However, the four CPU cores are visible in Device Manager under Processors. In the event log on startup, I can see the following relevant events: EventLog.6009 Microsoft (R) Windows (R) 6.00.6002 Service Pack 2 Multiprocessor Free Kernel-Processor-Power.4 Processor 0 exposes the following: 1 idle state(s), 0 performance state(s), 0 throttle state(s) Kernel-Processor-Power.4 Processor 255 exposes the following: 0 idle state(s), 0 performance state(s), 0 throttle state(s) Kernel-Processor-Power.4 Processor 255 exposes the following: 0 idle state(s), 0 performance state(s), 0 throttle state(s) Kernel-Processor-Power.4 Processor 255 exposes the following: 0 idle state(s), 0 performance state(s), 0 throttle state(s) How can I make this system actually boot up as a multiprocessor machine?

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  • Network speed between a VM and another machine which is not residing on the same host, is 11MB/s at most

    - by Henno
    Problem Network speed between a VM and another machine which is not residing on the same host, is 11MB/s at most. Topology Facts ESXi5 version is 5.0.0.504890 VM has the latest Vmware Tools installed VM is using E1000 network driver Physical box has Win Srv 2008 R2 as the OS CrystalDiskMark says the drive on physical box can read/write 100MB/s vCenter is another vm on esx both vm and physical box are showing 1Gbps link speed Configuration Networking shows vmnic0 as 1000 Full NTttcp is a client/server tool from Microsoft for measuring pure network throughput Here's what I've done so far: Test1: VM is running Filezilla FTP Server (default settings, one user account made) Physical box is running Filezilla FTP Client (default settings) Physical box is uploading a big file to FTP server Transfer speed (as observed by Windows Task Manager on both machines): ~11MB/s (bad) Physical box is downloading that file from FTP server Transfer speed (as observed by Windows Task Manager on both machines): still ~11MB/s (bad) Could it be disk performance issue? Test2: Physical box is running ntttcpr.exe -a 6 -m 6,0,VM_IP_ADDRESS VM is running ntttcps.exe -a 6 -m 6,0,PHY_BOX_IP_ADDRESS Transfer speed (as observed by Windows Task Manager on both machines): ~11MB/s (bad) Could it be switch performance issue? Test3: physical box is running vSphere Client I open Summary Storage datastore Browse Datastore... from physical box and upload a file to datastore Transfer speed (as observed by Windows Task Manager on physical box): ~26-36MB/s (good) Could it be a vm specific issue? Test4: Installed ntttcp to another vm on the same esx server Measured network performance between vms on the same esx server with NTttcp Transfer speed (as observed by Windows Task Manager on physical box): ~90-120MB/s (excellent :) Test5: I have another esx server on the same site, connecting to the same datastore and same switch. Those two ESX servers have both 2 NICs. One NIC goes to switch while the other goes directly to the other ESX server. vMotioned one of the testing vms off to the other ESX host Measured network performance between vms on different esx servers with NTttcp Transfer speed (as observed by Windows Task Manager on physical box): ~11MB/s (bad) While I'm aware of these: ESXi 4.1 slow file transfer ESXi 5 network performance is slow Debian Etch and ESXi slow network speeds VMWare ESXi slow file copy to guest they did not help (or I must have been missed something)

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  • Using MRTG's threshold feature to execute a php script

    - by Dan Fried
    I've set up mrtg using the online manual and the only online tutorial I found on the subject of thresholds, and the threshold just isn't firing. In my mrtg.cfg file, the relevant lines are ThreshDir: /path/to/mrtg/thresh ThreshMaxI[performance]: 1 ThreshMaxO[performance]: 1 ThreshProgI[performance]: /path/to/mrtg/scripts/alert.php ThreshProgO[performance]: /path/to/mrtg/scripts/alert.php The paths are right, because if I enter the paths wrong I get an error on executing mrtg. websitePerformance checks how long it takes to download the homepage, in milliseconds, so it should be exceeding the max every time. Alert.php is working fine when invoked directly from the shell, and when I point to a nonexistent script it tells me the script is not executable. No error messages are being generated, that I can find. The thresh directory is always empty. Why isn't the threshold being triggered by results that are greater than 1? Anyone have any suggestions?

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  • glusterfs mounts get unmounted when 1 of the 2 bricks goes offline

    - by Shiquemano
    I have an odd case where 1 of the 2 replicated glusterfs bricks will go offline and take all of the client mounts down with it. As I understand it, this should not be happening. It should fail over to the brick that is still online, but this hasn't been the case. I suspect that this is due to configuration issue. Here is a description of the system: 2 gluster servers on dedicated hardware (gfs0, gfs1) 8 client servers on vms (client1, client2, client3, ... , client8) Half of the client servers are mounted with gfs0 as the primary, and the other half are pointed at gfs1. Each of the clients are mounted with the following entry in /etc/fstab: /etc/glusterfs/datavol.vol /data glusterfs defaults 0 0 Here is the content of /etc/glusterfs/datavol.vol: volume datavol-client-0 type protocol/client option transport-type tcp option remote-subvolume /data/datavol option remote-host gfs0 end-volume volume datavol-client-1 type protocol/client option transport-type tcp option remote-subvolume /data/datavol option remote-host gfs1 end-volume volume datavol-replicate-0 type cluster/replicate subvolumes datavol-client-0 datavol-client-1 end-volume volume datavol-dht type cluster/distribute subvolumes datavol-replicate-0 end-volume volume datavol-write-behind type performance/write-behind subvolumes datavol-dht end-volume volume datavol-read-ahead type performance/read-ahead subvolumes datavol-write-behind end-volume volume datavol-io-cache type performance/io-cache subvolumes datavol-read-ahead end-volume volume datavol-quick-read type performance/quick-read subvolumes datavol-io-cache end-volume volume datavol-md-cache type performance/md-cache subvolumes datavol-quick-read end-volume volume datavol type debug/io-stats option count-fop-hits on option latency-measurement on subvolumes datavol-md-cache end-volume The config above is the latest attempt at making this behave properly. I have also tried the following entry in /etc/fstab: gfs0:/datavol /data glusterfs defaults,backupvolfile-server=gfs1 0 0 This was the entry for half of the clients, while the other half had: gfs1:/datavol /data glusterfs defaults,backupvolfile-server=gfs0 0 0 The results were exactly the same as the above configuration. Both configs connect everything just fine, they just don't fail over. Any help would be appreciated.

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  • Option Trading: Getting the most out of the event session options

    - by extended_events
    You can control different aspects of how an event session behaves by setting the event session options as part of the CREATE EVENT SESSION DDL. The default settings for the event session options are designed to handle most of the common event collection situations so I generally recommend that you just use the defaults. Like everything in the real world though, there are going to be a handful of “special cases” that require something different. This post focuses on identifying the special cases and the correct use of the options to accommodate those cases. There is a reason it’s called Default The default session options specify a total event buffer size of 4 MB with a 30 second latency. Translating this into human terms; this means that our default behavior is that the system will start processing events from the event buffer when we reach about 1.3 MB of events or after 30 seconds, which ever comes first. Aside: What’s up with the 1.3 MB, I thought you said the buffer was 4 MB?The Extended Events engine takes the total buffer size specified by MAX_MEMORY (4MB by default) and divides it into 3 equally sized buffers. This is done so that a session can be publishing events to one buffer while other buffers are being processed. There are always at least three buffers; how to get more than three is covered later. Using this configuration, the Extended Events engine can “keep up” with most event sessions on standard workloads. Why is this? The fact is that most events are small, really small; on the order of a couple hundred bytes. Even when you start considering events that carry dynamically sized data (eg. binary, text, etc.) or adding actions that collect additional data, the total size of the event is still likely to be pretty small. This means that each buffer can likely hold thousands of events before it has to be processed. When the event buffers are finally processed there is an economy of scale achieved since most targets support bulk processing of the events so they are processed at the buffer level rather than the individual event level. When all this is working together it’s more likely that a full buffer will be processed and put back into the ready queue before the remaining buffers (remember, there are at least three) are full. I know what you’re going to say: “My server is exceptional! My workload is so massive it defies categorization!” OK, maybe you weren’t going to say that exactly, but you were probably thinking it. The point is that there are situations that won’t be covered by the Default, but that’s a good place to start and this post assumes you’ve started there so that you have something to look at in order to determine if you do have a special case that needs different settings. So let’s get to the special cases… What event just fired?! How about now?! Now?! If you believe the commercial adage from Heinz Ketchup (Heinz Slow Good Ketchup ad on You Tube), some things are worth the wait. This is not a belief held by most DBAs, particularly DBAs who are looking for an answer to a troubleshooting question fast. If you’re one of these anxious DBAs, or maybe just a Program Manager doing a demo, then 30 seconds might be longer than you’re comfortable waiting. If you find yourself in this situation then consider changing the MAX_DISPATCH_LATENCY option for your event session. This option will force the event buffers to be processed based on your time schedule. This option only makes sense for the asynchronous targets since those are the ones where we allow events to build up in the event buffer – if you’re using one of the synchronous targets this option isn’t relevant. Avoid forgotten events by increasing your memory Have you ever had one of those days where you keep forgetting things? That can happen in Extended Events too; we call it dropped events. In order to optimizes for server performance and help ensure that the Extended Events doesn’t block the server if to drop events that can’t be published to a buffer because the buffer is full. You can determine if events are being dropped from a session by querying the dm_xe_sessions DMV and looking at the dropped_event_count field. Aside: Should you care if you’re dropping events?Maybe not – think about why you’re collecting data in the first place and whether you’re really going to miss a few dropped events. For example, if you’re collecting query duration stats over thousands of executions of a query it won’t make a huge difference to miss a couple executions. Use your best judgment. If you find that your session is dropping events it means that the event buffer is not large enough to handle the volume of events that are being published. There are two ways to address this problem. First, you could collect fewer events – examine you session to see if you are over collecting. Do you need all the actions you’ve specified? Could you apply a predicate to be more specific about when you fire the event? Assuming the session is defined correctly, the next option is to change the MAX_MEMORY option to a larger number. Picking the right event buffer size might take some trial and error, but a good place to start is with the number of dropped events compared to the number you’ve collected. Aside: There are three different behaviors for dropping events that you specify using the EVENT_RETENTION_MODE option. The default is to allow single event loss and you should stick with this setting since it is the best choice for keeping the impact on server performance low.You’ll be tempted to use the setting to not lose any events (NO_EVENT_LOSS) – resist this urge since it can result in blocking on the server. If you’re worried that you’re losing events you should be increasing your event buffer memory as described in this section. Some events are too big to fail A less common reason for dropping an event is when an event is so large that it can’t fit into the event buffer. Even though most events are going to be small, you might find a condition that occasionally generates a very large event. You can determine if your session is dropping large events by looking at the dm_xe_sessions DMV once again, this time check the largest_event_dropped_size. If this value is larger than the size of your event buffer [remember, the size of your event buffer, by default, is max_memory / 3] then you need a large event buffer. To specify a large event buffer you set the MAX_EVENT_SIZE option to a value large enough to fit the largest event dropped based on data from the DMV. When you set this option the Extended Events engine will create two buffers of this size to accommodate these large events. As an added bonus (no extra charge) the large event buffer will also be used to store normal events in the cases where the normal event buffers are all full and waiting to be processed. (Note: This is just a side-effect, not the intended use. If you’re dropping many normal events then you should increase your normal event buffer size.) Partitioning: moving your events to a sub-division Earlier I alluded to the fact that you can configure your event session to use more than the standard three event buffers – this is called partitioning and is controlled by the MEMORY_PARTITION_MODE option. The result of setting this option is fairly easy to explain, but knowing when to use it is a bit more art than science. First the science… You can configure partitioning in three ways: None, Per NUMA Node & Per CPU. This specifies the location where sets of event buffers are created with fairly obvious implication. There are rules we follow for sub-dividing the total memory (specified by MAX_MEMORY) between all the event buffers that are specific to the mode used: None: 3 buffers (fixed)Node: 3 * number_of_nodesCPU: 2.5 * number_of_cpus Here are some examples of what this means for different Node/CPU counts: Configuration None Node CPU 2 CPUs, 1 Node 3 buffers 3 buffers 5 buffers 6 CPUs, 2 Node 3 buffers 6 buffers 15 buffers 40 CPUs, 5 Nodes 3 buffers 15 buffers 100 buffers   Aside: Buffer size on multi-processor computersAs the number of Nodes or CPUs increases, the size of the event buffer gets smaller because the total memory is sub-divided into more pieces. The defaults will hold up to this for a while since each buffer set is holding events only from the Node or CPU that it is associated with, but at some point the buffers will get too small and you’ll either see events being dropped or you’ll get an error when you create your session because you’re below the minimum buffer size. Increase the MAX_MEMORY setting to an appropriate number for the configuration. The most likely reason to start partitioning is going to be related to performance. If you notice that running an event session is impacting the performance of your server beyond a reasonably expected level [Yes, there is a reasonably expected level of work required to collect events.] then partitioning might be an answer. Before you partition you might want to check a few other things: Is your event retention set to NO_EVENT_LOSS and causing blocking? (I told you not to do this.) Consider changing your event loss mode or increasing memory. Are you over collecting and causing more work than necessary? Consider adding predicates to events or removing unnecessary events and actions from your session. Are you writing the file target to the same slow disk that you use for TempDB and your other high activity databases? <kidding> <not really> It’s always worth considering the end to end picture – if you’re writing events to a file you can be impacted by I/O, network; all the usual stuff. Assuming you’ve ruled out the obvious (and not so obvious) issues, there are performance conditions that will be addressed by partitioning. For example, it’s possible to have a successful event session (eg. no dropped events) but still see a performance impact because you have many CPUs all attempting to write to the same free buffer and having to wait in line to finish their work. This is a case where partitioning would relieve the contention between the different CPUs and likely reduce the performance impact cause by the event session. There is no DMV you can check to find these conditions – sorry – that’s where the art comes in. This is  largely a matter of experimentation. On the bright side you probably won’t need to to worry about this level of detail all that often. The performance impact of Extended Events is significantly lower than what you may be used to with SQL Trace. You will likely only care about the impact if you are trying to set up a long running event session that will be part of your everyday workload – sessions used for short term troubleshooting will likely fall into the “reasonably expected impact” category. Hey buddy – I think you forgot something OK, there are two options I didn’t cover: STARTUP_STATE & TRACK_CAUSALITY. If you want your event sessions to start automatically when the server starts, set the STARTUP_STATE option to ON. (Now there is only one option I didn’t cover.) I’m going to leave causality for another post since it’s not really related to session behavior, it’s more about event analysis. - Mike Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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  • Consolidating and Virtualizing with Oracle&rsquo;s Network Fabric

    - by Ferhat Hatay
    Server, storage and operating system virtualization technologies are already widely  deployed within datacenters, and are considered an integral component to drive cost  savings and agility. These technologies are now being combined with network  virtualization to usher in a new era of cloud computing. Oracle provides a networking fabric that delivers cloud-ready network services based on  Ethernet or InfiniBand fabrics that are tightly integrated with application infrastructure. Oracle’s network fabric provides the performance and manageability required for any  Oracle application environment or private cloud infrastructure. Logical architecture of Oracle’s network fabric. Oracle’s unique ability to deliver extreme performance and scale by tightly integrating  network services across application infrastructure is demonstrated in the Oracle Exalogic  Elastic Cloud and the Oracle Exadata Database Machine. These engineered solutions  offer up to 5X and 10X performance gains respectively compared to traditional multivendor architectures where the offerings are not engineered to work together. By integrating advanced networking capabilities across the entire hardware and software  stack, Oracle’s network fabric can help maximize application performance and scale,  reduce the number of network components, and simplify datacenter operations through  integrated network management and orchestration. The resulting business benefits are: Reduced acquisition costs Lower power and cooling costs Reduced management costs Faster deployment Greater agility in meeting changing business needs For more information see the whitepaper: Consolidating and Virtualizing Datacenter Networks with Oracle's Network Fabric.

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  • Webfarm and IIS configuration tips/tricks

    - by steve schofield
    I was recently talking with some good friends about tips for performance and what an IIS Administrator could do on the server side.  I also see this question from time to time in the forums @ http://forums.iis.net.    Of course, you should test individual settings in a controlled environment while performing load testing before just implementing on your production farm.  IIS Compression enabled (both static and dynamic if possible, set it to 9)  If you are running IIS 6, check this article out by Scott Forsyth. Run FRT for long running pages (Failed Request Tracing) Sql Connection pooling in code Look at using PAL with performance counters ( http://blogs.iis.net/ganekar/archive/2009/08/12/pal-performance-analyzer-with-iis.aspx )  Look at load testing using visual studio load testing tools Log parser finding long running pages.  Here is a couple examples Look at CPU, Memory and disk counters.  Make sure the server has enough resources. Same machineKey account across all same nodes Localize content vs. using UNC based content on a single server (My UNC tag with great posts) Content expiration ETAG’s the same across all web-farms Disable Scalable Networking Pack Use YSlow or Developer tools in Chrome to help measure the client experience improvements. Additionally, some basic counters in for measuring applications is: I would recommend checking out the Chapter 17 in IIS 7 Resource kit. it was one of the chapters I authored. :) Concurrent Connections,  Request Per / Sec, Request Queued.  I strongly suggest testing one change at a time to see how it helps improve your performance.  Hopefully this post provides a few options to review in your environment.   Cheers, Steve SchofieldMicrosoft MVP - IIS

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  • Option Trading: Getting the most out of the event session options

    - by extended_events
    You can control different aspects of how an event session behaves by setting the event session options as part of the CREATE EVENT SESSION DDL. The default settings for the event session options are designed to handle most of the common event collection situations so I generally recommend that you just use the defaults. Like everything in the real world though, there are going to be a handful of “special cases” that require something different. This post focuses on identifying the special cases and the correct use of the options to accommodate those cases. There is a reason it’s called Default The default session options specify a total event buffer size of 4 MB with a 30 second latency. Translating this into human terms; this means that our default behavior is that the system will start processing events from the event buffer when we reach about 1.3 MB of events or after 30 seconds, which ever comes first. Aside: What’s up with the 1.3 MB, I thought you said the buffer was 4 MB?The Extended Events engine takes the total buffer size specified by MAX_MEMORY (4MB by default) and divides it into 3 equally sized buffers. This is done so that a session can be publishing events to one buffer while other buffers are being processed. There are always at least three buffers; how to get more than three is covered later. Using this configuration, the Extended Events engine can “keep up” with most event sessions on standard workloads. Why is this? The fact is that most events are small, really small; on the order of a couple hundred bytes. Even when you start considering events that carry dynamically sized data (eg. binary, text, etc.) or adding actions that collect additional data, the total size of the event is still likely to be pretty small. This means that each buffer can likely hold thousands of events before it has to be processed. When the event buffers are finally processed there is an economy of scale achieved since most targets support bulk processing of the events so they are processed at the buffer level rather than the individual event level. When all this is working together it’s more likely that a full buffer will be processed and put back into the ready queue before the remaining buffers (remember, there are at least three) are full. I know what you’re going to say: “My server is exceptional! My workload is so massive it defies categorization!” OK, maybe you weren’t going to say that exactly, but you were probably thinking it. The point is that there are situations that won’t be covered by the Default, but that’s a good place to start and this post assumes you’ve started there so that you have something to look at in order to determine if you do have a special case that needs different settings. So let’s get to the special cases… What event just fired?! How about now?! Now?! If you believe the commercial adage from Heinz Ketchup (Heinz Slow Good Ketchup ad on You Tube), some things are worth the wait. This is not a belief held by most DBAs, particularly DBAs who are looking for an answer to a troubleshooting question fast. If you’re one of these anxious DBAs, or maybe just a Program Manager doing a demo, then 30 seconds might be longer than you’re comfortable waiting. If you find yourself in this situation then consider changing the MAX_DISPATCH_LATENCY option for your event session. This option will force the event buffers to be processed based on your time schedule. This option only makes sense for the asynchronous targets since those are the ones where we allow events to build up in the event buffer – if you’re using one of the synchronous targets this option isn’t relevant. Avoid forgotten events by increasing your memory Have you ever had one of those days where you keep forgetting things? That can happen in Extended Events too; we call it dropped events. In order to optimizes for server performance and help ensure that the Extended Events doesn’t block the server if to drop events that can’t be published to a buffer because the buffer is full. You can determine if events are being dropped from a session by querying the dm_xe_sessions DMV and looking at the dropped_event_count field. Aside: Should you care if you’re dropping events?Maybe not – think about why you’re collecting data in the first place and whether you’re really going to miss a few dropped events. For example, if you’re collecting query duration stats over thousands of executions of a query it won’t make a huge difference to miss a couple executions. Use your best judgment. If you find that your session is dropping events it means that the event buffer is not large enough to handle the volume of events that are being published. There are two ways to address this problem. First, you could collect fewer events – examine you session to see if you are over collecting. Do you need all the actions you’ve specified? Could you apply a predicate to be more specific about when you fire the event? Assuming the session is defined correctly, the next option is to change the MAX_MEMORY option to a larger number. Picking the right event buffer size might take some trial and error, but a good place to start is with the number of dropped events compared to the number you’ve collected. Aside: There are three different behaviors for dropping events that you specify using the EVENT_RETENTION_MODE option. The default is to allow single event loss and you should stick with this setting since it is the best choice for keeping the impact on server performance low.You’ll be tempted to use the setting to not lose any events (NO_EVENT_LOSS) – resist this urge since it can result in blocking on the server. If you’re worried that you’re losing events you should be increasing your event buffer memory as described in this section. Some events are too big to fail A less common reason for dropping an event is when an event is so large that it can’t fit into the event buffer. Even though most events are going to be small, you might find a condition that occasionally generates a very large event. You can determine if your session is dropping large events by looking at the dm_xe_sessions DMV once again, this time check the largest_event_dropped_size. If this value is larger than the size of your event buffer [remember, the size of your event buffer, by default, is max_memory / 3] then you need a large event buffer. To specify a large event buffer you set the MAX_EVENT_SIZE option to a value large enough to fit the largest event dropped based on data from the DMV. When you set this option the Extended Events engine will create two buffers of this size to accommodate these large events. As an added bonus (no extra charge) the large event buffer will also be used to store normal events in the cases where the normal event buffers are all full and waiting to be processed. (Note: This is just a side-effect, not the intended use. If you’re dropping many normal events then you should increase your normal event buffer size.) Partitioning: moving your events to a sub-division Earlier I alluded to the fact that you can configure your event session to use more than the standard three event buffers – this is called partitioning and is controlled by the MEMORY_PARTITION_MODE option. The result of setting this option is fairly easy to explain, but knowing when to use it is a bit more art than science. First the science… You can configure partitioning in three ways: None, Per NUMA Node & Per CPU. This specifies the location where sets of event buffers are created with fairly obvious implication. There are rules we follow for sub-dividing the total memory (specified by MAX_MEMORY) between all the event buffers that are specific to the mode used: None: 3 buffers (fixed)Node: 3 * number_of_nodesCPU: 2.5 * number_of_cpus Here are some examples of what this means for different Node/CPU counts: Configuration None Node CPU 2 CPUs, 1 Node 3 buffers 3 buffers 5 buffers 6 CPUs, 2 Node 3 buffers 6 buffers 15 buffers 40 CPUs, 5 Nodes 3 buffers 15 buffers 100 buffers   Aside: Buffer size on multi-processor computersAs the number of Nodes or CPUs increases, the size of the event buffer gets smaller because the total memory is sub-divided into more pieces. The defaults will hold up to this for a while since each buffer set is holding events only from the Node or CPU that it is associated with, but at some point the buffers will get too small and you’ll either see events being dropped or you’ll get an error when you create your session because you’re below the minimum buffer size. Increase the MAX_MEMORY setting to an appropriate number for the configuration. The most likely reason to start partitioning is going to be related to performance. If you notice that running an event session is impacting the performance of your server beyond a reasonably expected level [Yes, there is a reasonably expected level of work required to collect events.] then partitioning might be an answer. Before you partition you might want to check a few other things: Is your event retention set to NO_EVENT_LOSS and causing blocking? (I told you not to do this.) Consider changing your event loss mode or increasing memory. Are you over collecting and causing more work than necessary? Consider adding predicates to events or removing unnecessary events and actions from your session. Are you writing the file target to the same slow disk that you use for TempDB and your other high activity databases? <kidding> <not really> It’s always worth considering the end to end picture – if you’re writing events to a file you can be impacted by I/O, network; all the usual stuff. Assuming you’ve ruled out the obvious (and not so obvious) issues, there are performance conditions that will be addressed by partitioning. For example, it’s possible to have a successful event session (eg. no dropped events) but still see a performance impact because you have many CPUs all attempting to write to the same free buffer and having to wait in line to finish their work. This is a case where partitioning would relieve the contention between the different CPUs and likely reduce the performance impact cause by the event session. There is no DMV you can check to find these conditions – sorry – that’s where the art comes in. This is  largely a matter of experimentation. On the bright side you probably won’t need to to worry about this level of detail all that often. The performance impact of Extended Events is significantly lower than what you may be used to with SQL Trace. You will likely only care about the impact if you are trying to set up a long running event session that will be part of your everyday workload – sessions used for short term troubleshooting will likely fall into the “reasonably expected impact” category. Hey buddy – I think you forgot something OK, there are two options I didn’t cover: STARTUP_STATE & TRACK_CAUSALITY. If you want your event sessions to start automatically when the server starts, set the STARTUP_STATE option to ON. (Now there is only one option I didn’t cover.) I’m going to leave causality for another post since it’s not really related to session behavior, it’s more about event analysis. - Mike Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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  • The Social Business Thought Leaders - John Hagel

    - by kellsey.ruppel
    While many European economies are on the brink of a recession between increasing taxation and mounting loss of jobs and bankruptcy filing rates, there's an understandable risk of losing sight of the deeper forces at play. Yet instead of surrendering to uncertainty and trying to survive in the short term, many organizations are feeling the urge to be better prepared to thrive in these complex times by developing a more articulated long term understanding of both the opportunities / challenges ahead. For example: What long-term economic, technological and societal changes are rolling out? Which foundational dynamics will affect our companies' performance, productivity, competition, and innovative potential in the upcoming decades? How will digital infrastructure change our business landscape? What kind of capabilities will be key to compete in a market shaped by growing turbulence, unpredictability and volatility? Breaking out from a strictly cyclical thinking, studies such as the Shift Index by John Hagel, Co-Chairman of the Center for the Edge at Deloitte & Touche (See Measuring the forces of long-term change - The 2009 Shift Index), depict a worrying performance challenge that affected every industry in the entire US economy over the last 45 years. Amidst a more than doubled competitive intensity of the market, and even with an improved labor productivity, the actual performance of US firms has consistently fallen to 25% of what it was in 1965. Most of this reported value is shifting from institutions and organizations to individuals, whether they are customers or young creative talent. To thrive in the digital economy and reverse declining performance trends, companies will have to fundamentally rethink their management approach by moving from knowledge stocks to knowledge flows, from scalable efficiency to scalable learning, from push organizations to pull organizations. Based on the outcomes of the Shift Index and on the book The Power of Pull, the first episode of the Social Business Thought-Leaders features John Hagel to provide strategic insights on how companies will succeed in the 21st century.

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  • Flash Technology Can Revolutionize your IT Infrastructure

    - by kimberly.billings
    A recent article in the Data Center Journal written by Mark Teter outlines how flash is becoming a disruptive technology in the data center and how it will soon replace HDDs in the storage hierarchy. As Teter explains, the drivers behind this trend are lower cost/performance and power savings; flash is over 100x faster for reads than the fastest HDD, and while it is expensive, it can produce dramatic reductions in the cost of performance as measured in Input/Outputs per second (IOPS). What's more, flash consumes 1/5th the power of HDD, so it's faster AND greener. Teter writes, "when appropriately used, flash turns the current economics of IT performance on its head. That's disruptive." Exadata Smart Flash Cache in the Sun Oracle Database Machine makes intelligent use of flash storage to deliver extreme performance for OLTP and mixed workloads. It intelligently caches data from the Oracle Database replacing slow mechanical I/O operations to disk with very rapid flash memory operations. Exadata Smart Flash Cache is the fundamental technology of the Sun Oracle Database Machine that enables the processing of up to 1 million random I/O operations per second (IOPS), and the scanning of data within Exadata storage at up to 50 GB/second. Are you incorporating flash into your storage strategy? Let us know! Read more: "Flash technology can revolutionize your IT infrastructure", The Data Center Journal, March 30, 2010. Exadata Smart Flash Cache and the Sun Oracle Database Machine white paper var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www."); document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E")); try { var pageTracker = _gat._getTracker("UA-13185312-1"); pageTracker._trackPageview(); } catch(err) {}

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  • New Whitepaper: Best Practices for Gathering EBS Database Statistics

    - by Elke Phelps (Oracle Development)
    Most Oracle Applications DBAs and E-Business Suite users understand the importance of accurate database statistics.  Missing, stale or skewed statistics can adversely affect performance.  Oracle E-Business Suite statistics should only be gathered using FND_STATS or the Gather Statistics concurrent request. Gathering statistics with DBMS_STATS or the desupported ANALYZE command may result in suboptimal executions plans for E-Business Suite. Our E-Business Suite Performance Team has been busy implementing and testing new features for gathering statistics using FND_STATS in Oracle E-Business Suite databases.  The new features and guidelines for when and how to gather statistics are published in the following whitepaper: Best Practices for Gathering Statistics with Oracle E-Business Suite (Note 1586374.1) The new white paper details the following options for gathering statistics using FND_STATS and the Gather Statistics concurrent request:: History Mode - backup existing statistics prior to gather new statistics GATHER_AUTO Option - gather statistics for tables based upon % change Histograms - collect statistics for histograms AUTO Sampling - use the new FND_STATS feature that supports the AUTO option for using AUTO sample size Extended Statistics - use the new FND_STATS feature that supports the creation of column groups and automatic statistics collection on the column groups when table statistics are gathered Incremental Statistics - gather incremental statistics for partitioned tables The new white paper also includes examples and performance test cases for the following: Extended Optimizer Statistics Incremental Statistics Gathering Concurrent Statistics Gathering This white paper includes details about the standalone Oracle E-Business Suite Release 11i and 12 patches that are required to take advantage of this new functionality. Your feedback is welcome We would be very interested in hearing about your experiences with these new options for gathering statistics.  Please feel free to post your comments here or drop us a line privately.Related Oracle OpenWorld 2013 Session Getting Optimal Performance from Oracle E-Business Suite (CON8485) Related My Oracle Support Notes Collecting Statistics with Oracle EBS 11i and R12 (Note 368252.1) Non-EBS Related Blogs, White Papers and My Oracle Support Notes  Oracle Optimizer Blog Understanding Optimizer Statistic (white paper) Fixed Objects Statistics(GATHER_FIXED_OBJECTS_STATS) Considerations (Note 798257.1)

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  • Discover the MySQL Connect Content Catalog!

    - by Bertrand Matthelié
    The MySQL Connect content catalog is now live! MySQL Connect offers you a unique opportunity to attend:Keynotes including: "The State of the Dolphin", by Oracle's Chief Corporate Architect Edward Screven and VP of MySQL Engineering Tomas Ulin. An exciting panel on "Current MySQL Usage Models and Future Developments" with Davi Arnaud from LinkedIn, Daniel Austin from PayPal, Mark Callaghan from Facebook and Calvin Sun from Twitter. Over 65 Conference sessions enabling you to hear from: Oracle MySQL engineers on MySQL 5.6, InnoDB, replication, performance tuning, security, NoSQL, MySQL Cluster, Big Data...and more. MySQL customers including the US Census Bureau, Big Fish Games, Booking.com, Ticketmaster, and Tumblr. Internationally recognized MySQL community members and partners on topics such as performance, MySQL 5.6, backup, MySQL in the Cloud, OpenStack and Hadoop. 6 Birds-of-a-feather sessions about sharding, replication, backup, and other subjects.8 Hands-On Labs designed to give you hands-on experience about MySQL replication, the MySQL Performance Schema, MySQL Cluster...and more.6 Tutorials providing you in-depth knowledge about MySQL Performance Tuning best practices, enhancing productivity with MySQL 5.6 new features or the essentials to get started with MySQL (tutorials are available as an add-on package to MySQL Connect registrants).Demo pods and exhibitors, to learn more about Partner’s and Oracle’s offerings.Receptions on both Saturday and Sunday nights, enabling you to ask all your questions to Oracle's MySQL engineers and to network with some of the world’s best MySQL professionals.Check out the MySQL Connect content catalog and find out about the amazing sessions you have the opportunity to attend.Reminder: The early bird discount is running until July 19, Register Now to save US$500! Plan to Attend Oracle OpenWorld or JavaOne? Add the MySQL Connect event to your Oracle OpenWorld or JavaOne registration for only US$100. Exhibit/Sponsorship opportunities are also available. We look forward to seeing you at MySQL Connect!

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  • C#/.NET &ndash; Finding an Item&rsquo;s Index in IEnumerable&lt;T&gt;

    - by James Michael Hare
    Sorry for the long blogging hiatus.  First it was, of course, the holidays hustle and bustle, then my brother and his wife gave birth to their son, so I’ve been away from my blogging for two weeks. Background: Finding an item’s index in List<T> is easy… Many times in our day to day programming activities, we want to find the index of an item in a collection.  Now, if we have a List<T> and we’re looking for the item itself this is trivial: 1: // assume have a list of ints: 2: var list = new List<int> { 1, 13, 42, 64, 121, 77, 5, 99, 132 }; 3:  4: // can find the exact item using IndexOf() 5: var pos = list.IndexOf(64); This will return the position of the item if it’s found, or –1 if not.  It’s easy to see how this works for primitive types where equality is well defined.  For complex types, however, it will attempt to compare them using EqualityComparer<T>.Default which, in a nutshell, relies on the object’s Equals() method. So what if we want to search for a condition instead of equality?  That’s also easy in a List<T> with the FindIndex() method: 1: // assume have a list of ints: 2: var list = new List<int> { 1, 13, 42, 64, 121, 77, 5, 99, 132 }; 3:  4: // finds index of first even number or -1 if not found. 5: var pos = list.FindIndex(i => i % 2 == 0);   Problem: Finding an item’s index in IEnumerable<T> is not so easy... This is all well and good for lists, but what if we want to do the same thing for IEnumerable<T>?  A collection of IEnumerable<T> has no indexing, so there’s no direct method to find an item’s index.  LINQ, as powerful as it is, gives us many tools to get us this information, but not in one step.  As with almost any problem involving collections, there are several ways to accomplish the same goal.  And once again as with almost any problem involving collections, the choice of the solution somewhat depends on the situation. So let’s look at a few possible alternatives.  I’m going to express each of these as extension methods for simplicity and consistency. Solution: The TakeWhile() and Count() combo One of the things you can do is to perform a TakeWhile() on the list as long as your find condition is not true, and then do a Count() of the items it took.  The only downside to this method is that if the item is not in the list, the index will be the full Count() of items, and not –1.  So if you don’t know the size of the list beforehand, this can be confusing. 1: // a collection of extra extension methods off IEnumerable<T> 2: public static class EnumerableExtensions 3: { 4: // Finds an item in the collection, similar to List<T>.FindIndex() 5: public static int FindIndex<T>(this IEnumerable<T> list, Predicate<T> finder) 6: { 7: // note if item not found, result is length and not -1! 8: return list.TakeWhile(i => !finder(i)).Count(); 9: } 10: } Personally, I don’t like switching the paradigm of not found away from –1, so this is one of my least favorites.  Solution: Select with index Many people don’t realize that there is an alternative form of the LINQ Select() method that will provide you an index of the item being selected: 1: list.Select( (item,index) => do something here with the item and/or index... ) This can come in handy, but must be treated with care.  This is because the index provided is only as pertains to the result of previous operations (if any).  For example: 1: // assume have a list of ints: 2: var list = new List<int> { 1, 13, 42, 64, 121, 77, 5, 99, 132 }; 3:  4: // you'd hope this would give you the indexes of the even numbers 5: // which would be 2, 3, 8, but in reality it gives you 0, 1, 2 6: list.Where(item => item % 2 == 0).Select((item,index) => index); The reason the example gives you the collection { 0, 1, 2 } is because the where clause passes over any items that are odd, and therefore only the even items are given to the select and only they are given indexes. Conversely, we can’t select the index and then test the item in a Where() clause, because then the Where() clause would be operating on the index and not the item! So, what we have to do is to select the item and index and put them together in an anonymous type.  It looks ugly, but it works: 1: // extensions defined on IEnumerable<T> 2: public static class EnumerableExtensions 3: { 4: // finds an item in a collection, similar to List<T>.FindIndex() 5: public static int FindIndex<T>(this IEnumerable<T> list, Predicate<T> finder) 6: { 7: // if you don't name the anonymous properties they are the variable names 8: return list.Select((item, index) => new { item, index }) 9: .Where(p => finder(p.item)) 10: .Select(p => p.index + 1) 11: .FirstOrDefault() - 1; 12: } 13: }     So let’s look at this, because i know it’s convoluted: First Select() joins the items and their indexes into an anonymous type. Where() filters that list to only the ones matching the predicate. Second Select() picks the index of the matches and adds 1 – this is to distinguish between not found and first item. FirstOrDefault() returns the first item found from the previous clauses or default (zero) if not found. Subtract one so that not found (zero) will be –1, and first item (one) will be zero. The bad thing is, this is ugly as hell and creates anonymous objects for each item tested until it finds the match.  This concerns me a bit but we’ll defer judgment until compare the relative performances below. Solution: Convert ToList() and use FindIndex() This solution is easy enough.  We know any IEnumerable<T> can be converted to List<T> using the LINQ extension method ToList(), so we can easily convert the collection to a list and then just use the FindIndex() method baked into List<T>. 1: // a collection of extension methods for IEnumerable<T> 2: public static class EnumerableExtensions 3: { 4: // find the index of an item in the collection similar to List<T>.FindIndex() 5: public static int FindIndex<T>(this IEnumerable<T> list, Predicate<T> finder) 6: { 7: return list.ToList().FindIndex(finder); 8: } 9: } This solution is simplicity itself!  It is very concise and elegant and you need not worry about anyone misinterpreting what it’s trying to do (as opposed to the more convoluted LINQ methods above). But the main thing I’m concerned about here is the performance hit to allocate the List<T> in the ToList() call, but once again we’ll explore that in a second. Solution: Roll your own FindIndex() for IEnumerable<T> Of course, you can always roll your own FindIndex() method for IEnumerable<T>.  It would be a very simple for loop which scans for the item and counts as it goes.  There’s many ways to do this, but one such way might look like: 1: // extension methods for IEnumerable<T> 2: public static class EnumerableExtensions 3: { 4: // Finds an item matching a predicate in the enumeration, much like List<T>.FindIndex() 5: public static int FindIndex<T>(this IEnumerable<T> list, Predicate<T> finder) 6: { 7: int index = 0; 8: foreach (var item in list) 9: { 10: if (finder(item)) 11: { 12: return index; 13: } 14:  15: index++; 16: } 17:  18: return -1; 19: } 20: } Well, it’s not quite simplicity, and those less familiar with LINQ may prefer it since it doesn’t include all of the lambdas and behind the scenes iterators that come with deferred execution.  But does having this long, blown out method really gain us much in performance? Comparison of Proposed Solutions So we’ve now seen four solutions, let’s analyze their collective performance.  I took each of the four methods described above and run them over 100,000 iterations of lists of size 10, 100, 1000, and 10000 and here’s the performance results.  Then I looked for targets at the begining of the list (best case), middle of the list (the average case) and not in the list (worst case as must scan all of the list). Each of the times below is the average time in milliseconds for one execution as computer over the 100,000 iterations: Searches Matching First Item (Best Case)   10 100 1000 10000 TakeWhile 0.0003 0.0003 0.0003 0.0003 Select 0.0005 0.0005 0.0005 0.0005 ToList 0.0002 0.0003 0.0013 0.0121 Manual 0.0001 0.0001 0.0001 0.0001   Searches Matching Middle Item (Average Case)   10 100 1000 10000 TakeWhile 0.0004 0.0020 0.0191 0.1889 Select 0.0008 0.0042 0.0387 0.3802 ToList 0.0002 0.0007 0.0057 0.0562 Manual 0.0002 0.0013 0.0129 0.1255   Searches Where Not Found (Worst Case)   10 100 1000 10000 TakeWhile 0.0006 0.0039 0.0381 0.3770 Select 0.0012 0.0081 0.0758 0.7583 ToList 0.0002 0.0012 0.0100 0.0996 Manual 0.0003 0.0026 0.0253 0.2514   Notice something interesting here, you’d think the “roll your own” loop would be the most efficient, but it only wins when the item is first (or very close to it) regardless of list size.  In almost all other cases though and in particular the average case and worst case, the ToList()/FindIndex() combo wins for performance, even though it is creating some temporary memory to hold the List<T>.  If you examine the algorithm, the reason why is most likely because once it’s in a ToList() form, internally FindIndex() scans the internal array which is much more efficient to iterate over.  Thus, it takes a one time performance hit (not including any GC impact) to create the List<T> but after that the performance is much better. Summary If you’re concerned about too many throw-away objects, you can always roll your own FindIndex() method, but for sheer simplicity and overall performance, using the ToList()/FindIndex() combo performs best on nearly all list sizes in the average and worst cases.    Technorati Tags: C#,.NET,Litte Wonders,BlackRabbitCoder,Software,LINQ,List

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  • Partner Webcast - Is your Application Ready? Prove it with the Oracle Exastack Program

    - by Thanos
    At Oracle we design Engineered Systems that are pre-integrated to reduce the cost and complexity of IT infrastructures while increasing productivity and performance. Oracle innovates and optimizes performance at every IT layer to simplify business operations, drive down costs and accelerate business innovation.As the Engineered System foundation platform, Oracle Exadata and Oracle Exalogic, run all of Oracle Cloud's services across a range of global data centers, delivering extreme performance, massive scalability, and fault tolerance that has no single point of failure.The Oracle Exastack Program enables you as an ISV to leverage Oracle's scalable, integrated infrastructure to test, tune and optimize your applications for high performance. By getting Exastack Ready and Exastack Optimized, your applications get formal recognition from Oracle and additional visibility, while you as an ISV receive additional set of OPN benefits. Don't miss this opportunity to learn more about how you can optimize your applications to run faster and more reliably leveraging Oracle Exastack, but also become more competitive letting everybody know you are ready. Agenda: Oracle Engineered Systems Strategy OPN Exastack Program Benefits & Objectives Value for You Oracle is resourced for your success How to Apply –Demo Next Steps & Useful contacts Delivery FormatThis FREE online LIVE eSeminar will be delivered over the Web. Registrations received less than 24hours prior to start time may not receive confirmation to attend. Thursday 06 December 2012, 10.00 CET (GMT+1) Duration: 1 hour Register Now! " height="6"> For any questions please contact us at [email protected] our ISV Migration Center blog Or Follow us @oracleimc to learn more on Oracle Technologies, upcoming partner webcasts and events. Existing content available YouTube - SlideShare - Oracle Mix

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  • Large invoice database structure and rendering

    - by user132624
    Our client has a MS SQL database that has 1 million customer invoice records in it. Using the database, our client wants its customers to be able to log into a frontend web site and then be able to view, modify and download their company’s invoices. Given the size of the database and the large number of customers who may log into the web site at any time, we are concerned about data base engine performance and web page invoice rendering performance. The 1 million invoice database is for just 90 days sales, so we will remove invoices over 90 days old from the database. Most of the invoices have multiple line items. We can easily convert our invoices into various data formats so for example it is easy for us to convert to and from SQL to XML with related schema and XSLT. Any data conversion would be done on another server so as not to burden the web interface server. We have tentatively decided to run the web site on a .NET Framework IIS web server using MS SQL on MS Azure. How would you suggest we structure our database for best performance? For example, should we put all the invoices of all customers located within the same 5 digit or 6 digit zip codes into the same table? Or could we set up a separate home directory for each customer on IIS and place each customer’s invoices in each customer’s home directory in XML format? And secondly what would you suggest would be the best method to render customer invoices on a web page and allow customers to modify for best performance? The ADO.net XML Data Set looks intriguing to us as a method, but we have never used it.

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  • Oracle Linux Partner Pavilion Spotlight

    - by Ted Davis
    With the first day of Oracle OpenWorld starting in less than a week, we wanted to showcase some of our premier partners exhibiting in the Oracle Linux Partner Pavilion ( Booth #1033) this year. We have Independent Hardware Vendors, Independent Software Vendors and Systems Integrators that show the breadth of support in the Oracle Linux and Oracle VM ecosystem. We'll be highlighting partners all week so feel free to come back check us out. Centrify delivers integrated software and cloud-based solutions that centrally control, secure and audit access to cross-platform systems, mobile devices and applications by leveraging the infrastructure organizations already own. From the data center and into the cloud, more than 4,500 organizations, including 40 percent of the Fortune 50 and more than 60 Federal agencies, rely on Centrify's identity consolidation and privilege management solutions to reduce IT expenses, strengthen security and meet compliance requirements. Visit Centrify at Oracle OpenWorld 2102 for a look at Centrify Suite and see how you can streamline security management on Oracle Linux.  Unify identities across the enterprise and remove the pain and security issues associated with managing local user accounts by leveraging Active Directory Implement a least-privilege security model with flexible, role-based controls that protect privileged operations while still granting users the privileges they need to perform their job Get a central, global view of audited user sessions across your Oracle Linux environment  "Data Intensity's cloud infrastructure leverages Oracle VM and Oracle Linux to provide highly available enterprise application management solutions.  Engineers will be available to answer questions about and demonstrate the technology, including management tools, configuration do's and don'ts, high availability, live migration, integrating the technology with Oracle software, and how the integrated support process works."    Mellanox’s end-to-end InfiniBand and Ethernet server and storage interconnect solutions deliver the highest performance, efficiency and scalability for enterprise, high-performance cloud and web 2.0 applications. Mellanox’s interconnect solutions accelerate Oracle RAC query throughput performance to reach 50Gb/s compared to TCP/IP based competing solutions that cap off at less than 12Gb/s. Mellanox solutions help Oracle’s Exadata to deliver 10X performance boost at 50% Hardware cost making it the world’s leading database appliance. Thanks for reviewing today's Partner spotlight. We will highlight new partners each day this week leading up to Oracle OpenWorld.

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  • SQLAuthority News – Scaling Up Your Data Warehouse with SQL Server 2008 R2

    - by pinaldave
    Data Warehouses are suppose to be containing huge amount of the data from the beginning. However, there are cases when too big is not enough. Every Data Warehouse Admin will agree that they have faced situation where they will need to scale up their data warehouse. Microsoft has released white paper discussing the same. Here is the abstract from the Microsoft Official site: SQL Server 2008 introduced many new functional and performance improvements for data warehousing, and SQL Server 2008 R2 includes all these and more. This paper discusses how to use SQL Server 2008 R2 to get great performance as your data warehouse scales up. We present lessons learned during extensive internal data warehouse testing on a 64-core HP Integrity Superdome during the development of the SQL Server 2008 release, and via production experience with large-scale SQL Server customers. Our testing indicates that many customers can expect their performance to nearly double on the same hardware they are currently using, merely by upgrading to SQL Server 2008 R2 from SQL Server 2005 or earlier, and compressing their fact tables. We cover techniques to improve manageability and performance at high-scale, encompassing data loading (extract, transform, load), query processing, partitioning, index maintenance, indexed view (aggregate) management, and backup and restore. Scaling Up Your Data Warehouse with SQL Server 2008 R2 Reference: Pinal Dave (http://blog.SQLAuthority.com)   Filed under: PostADay, SQL, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Oracle's SPARC T4, 007 Style

    - by Kristin Rose
    The names 4, T4, and this power house travels hand in hand with its good friend SPARC. About 6 years ago on-chip encryption acceleration was first shipped in a commercial system, the SPARC T1. Today, thanks to Oracle SPARC innovative leadership in on-chip encryption acceleration, complex cryptographic computations was born and has since rapidly evolved. Customers can now have security with performance because we my friend, are in the Age of Big Data.If you need some high speed action in your life, listen here. The SPARC T4 systems offer customers much more value for applications than just increased performance through its cross sell opportunity. This is done by enabling partners to integrate your own applications to Oracle’s SPARC T4 Servers for Cloud deployments, and providing direct business benefits that supersedes the commodity approach to data center computing such as security, performance and optimization.As companies continue down this complex path of big data, eCommerce, and mobility, the need to provide better and more in-depth security is more prominent than ever. Oracle’s SPARC T4 processor allows customers to deliver the highest levels of application security, as well as deliver the necessary level performance without added cost, and complexity.To learn more behind the value of SPARC T4, check out a more in-depth blog here. For more on the SPARC T4 family of products, click here.Encryption Lives Another Day,The OPN Communications Team 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:10.0pt; font-family:"Times New Roman","serif";}

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  • Business Analyst role in development process

    - by Ryan
    I work as a business analyst and I currently oversee much of the development efforts of an internal project. I'm responsible for the requirements, specs, and overall testing. I work closely with the developers (onshore and offshore). The offshore team produces all of the reports. Version 1.0 had a 9 month development cycle and I had about 4-5 months to test all the reports. There was the usual back and forth to get the implementation right. Version 2.0 had a much shorter development cycle (3 months). I received the first version of the reports about 3 weeks ago and noticed a lot of things wrong with it. Many of the requirements were wrong and the performance of the queries was horrendous at 5x - 6x longer than it should have been. The onshore lead developer was out and did not supervise the offshore development team in generating the reports. Without consulting management, I took a look at the SQL in the reports and was able to improve performance greatly (by a factor of 6x) which is acceptable for this version. I sent the updated queries as guidelines to the offshore team and told them they should look at doing X instead of Y to improve performance and also to fix some specific logic issues. I then spoke to my managers about this because it doesn't feel right that I was developing SQL queries, but given our time crunch I saw no other way. We were able to fix the issue quite fast which I'm happy with. Current situation: the onshore managers aren't too pleased that the offshore team did not code for performance. I know there are some things I could have done better throughout this process and I do not in any way consider myself a programmer. My question is, if an offshore team that works apart from the onshore project resources fails to deliver an acceptable release, is it appropriate to clean up their work to meet a deadline? What kind of problems could this create in the future?

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  • What's New in Business Analytics at Oracle?

    - by jmorourke
    Business Analytics, which includes Business intelligence and Enterprise Performance Management, are top priorities for IT and Finance executives in 2012.  Some of the hot market trends and topics include managing big data, mobile information access, in-memory computing, advanced analytics, predictive modeling, leveraging unstructured data, as well as risk and performance management.  Find out what Oracle is doing about all of this, and what’s new from the market leader in Business Analytics by attending our live webcast event on April 4th titled “Introducing Oracle’s Business Analytics Strategy”.  At this event, you’ll hear about Oracle’s strategy for Business Analytics from Mark Hurd, Oracle President and you can learn about the latest advancements in Oracle’s Business Analytics solutions from Balaji Yelamanchili, SVP of Analytics and Performance Management. The keynote session from Mark and Balaji will be followed by breakout sessions that provide a more in-depth look at what’s new in specific product areas including the latest release of Oracle’s Hyperion Enterprise Performance Management suite, Oracle Business Intelligence Applications and Exalytics In-Memory Machine, Oracle Endeca Information Discovery, Big Data and Advanced Analytics solutions. This event will provide a great opportunity to hear about what’s new in Business Analytics at Oracle, and for attendees to pose questions to Oracle experts during live chat sessions.  Here’s a link to the registration page, and more details about the April 4th event.  We hope to see you (virtually) there! http://www.oracle.com/us/corporate/events/business-analytics/index.html Also, use the following hashtag to follow along on Twitter and share comments during the webcast and Q&A sessions:  #oracleanalytics

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  • Introducing the Industry's First Analytics Machine, Oracle Exalytics

    - by Manan Goel
    Analytics is all about gaining insights from the data for better decision making. The business press is abuzz with examples of leading organizations across the world using data-driven insights for strategic, financial and operational excellence. A recent study on “data-driven decision making” conducted by researchers at MIT and Wharton provides empirical evidence that “firms that adopt data-driven decision making have output and productivity that is 5-6% higher than the competition”. The potential payoff for firms can range from higher shareholder value to a market leadership position. However, the vision of delivering fast, interactive, insightful analytics has remained elusive for most organizations. Most enterprise IT organizations continue to struggle to deliver actionable analytics due to time-sensitive, sprawling requirements and ever tightening budgets. The issue is further exasperated by the fact that most enterprise analytics solutions require dealing with a number of hardware, software, storage and networking vendors and precious resources are wasted integrating the hardware and software components to deliver a complete analytical solution. Oracle Exalytics In-Memory Machine is the world’s first engineered system specifically designed to deliver high performance analysis, modeling and planning. Built using industry-standard hardware, market-leading business intelligence software and in-memory database technology, Oracle Exalytics is an optimized system that delivers answers to all your business questions with unmatched speed, intelligence, simplicity and manageability. Oracle Exalytics’s unmatched speed, visualizations and scalability delivers extreme performance for existing analytical and enterprise performance management applications and enables a new class of intelligent applications like Yield Management, Revenue Management, Demand Forecasting, Inventory Management, Pricing Optimization, Profitability Management, Rolling Forecast and Virtual Close etc. Requiring no application redesign, Oracle Exalytics can be deployed in existing IT environments by itself or in conjunction with Oracle Exadata and/or Oracle Exalogic to enable extreme performance and best in class user experience. Based on proven hardware, software and in-memory technology, Oracle Exalytics lowers the total cost of ownership, reduces operational risk and provides unprecedented analytical capability for workgroup, departmental and enterprise wide deployments. Click here to learn more about Oracle Exalytics.  

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