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  • SQLAuthority News – Reliving TechEd with Vinod Kumar at Bangalore User Groups

    - by pinaldave
    TechEd India 2012 was held in Bangalore last March 21 to 23, 2012. Just like every year, this event is bigger, grander and inspiring. Here is my blog post reviewing the event SQLAuthority News – #TechEdIn – TechEd India 2012 Memories and Photos. For me this is family event – I get to meet my friends who are dear as my family. I like to call User Groups as family too. Family shares life’s personal happiness and experience – the same way User Group shares professional experiences and quite often UG members become just like family member. When I learned that follower user group together building up a unique event I was pretty excited to learn who is going to be speaker for the event. BDotNet.in – Bangalore .NET Usergroup BITPro.in – Bangalore ITPro Usergroup It was indeed joy when I learned that presenter will be Vinod Kumar, who is integral part of user groups and hardcore SQL Server enthusiast. Vinod Kumar is going to present on following two sessions which are both focused on internals of the Windows and SQL Server. Understanding Windows with SysInternals Tools – This session will cover various tools from usage of Memory, x86 architecture, x64, WOW mode, Page faults, Virtual Memory mapping, OOM scenario, Perf Tool, PAL tool, Logman and more. Peeling the Onion: SQL Server Internals Demystified – This session will cover advanced disk formats, SQL Server 2012 security changes, memory changes, indirect checkPoint and more. I am very excited as this time I will get opportunity to sit in front rows (as I will be reaching there to get best possible position) and learn. I am looking forward to the event and I hope you will join us as well. Event Details: Date: Saturday, April 7, 2012 (10:30am until 1:30pm) Venue: Microsoft, Domlur, Bangalore. Event Details: https://www.facebook.com/events/139444029517882/ This session is FREE for all and everybody and anybody can walk in. Community Blog Posts Here are few of the blog post written by the community on this subject. Vinod Kumar on Reliving #TechEdIn at Blr UG Manas Dash on Reliving TechEd India 2012 with Vinod Kumar Sudeepta Ganguly on SysInternals n SQLInternals with Vinod Kumar Lohith Re Live TechEd India 2012 with Vinod Kumar  Reference: Pinal Dave (http://blog.sqlauthority.com) http://www.youtube.com/watch?v=oRw-p4mahLU Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority Author Visit, T SQL, Technology, Video

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  • SQL Server – Learning SQL Server Performance: Indexing Basics – Interview of Vinod Kumar by Pinal Dave

    - by pinaldave
    Recently I just wrote a blog post on about Learning SQL Server Performance: Indexing Basics and I received lots of request that if we can share some insight into the course. Every single time when Performance is discussed, Indexes are mentioned along with it. In recent times, data and application complexity is continuously growing.  The demand for faster query response, performance, and scalability by organizations is increasing and developers and DBAs need to now write efficient code to achieve this. When we developed the course – we made sure that this course remains practical and demo heavy instead of just theories on this subject. Vinod Kumar and myself we often thought about this and realized that practical understanding of the indexes is very important. One can not master every single aspects of the index. However there are some minimum expertise one should gain if performance is one of the concern. Here is 200 seconds interview of Vinod Kumar I took right after completing the course. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Index, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology, Video

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  • SQL SERVER – Concurrency Basics – Guest Post by Vinod Kumar

    - by pinaldave
    This guest post is by Vinod Kumar. Vinod Kumar has worked with SQL Server extensively since joining the industry over a decade ago. Working on various versions from SQL Server 7.0, Oracle 7.3 and other database technologies – he now works with the Microsoft Technology Center (MTC) as a Technology Architect. Let us read the blog post in Vinod’s own voice. Learning is always fun when it comes to SQL Server and learning the basics again can be more fun. I did write about Transaction Logs and recovery over my blogs and the concept of simplifying the basics is a challenge. In the real world we always see checks and queues for a process – say railway reservation, banks, customer supports etc there is a process of line and queue to facilitate everyone. Shorter the queue higher is the efficiency of system (a.k.a higher is the concurrency). Every database does implement this using checks like locking, blocking mechanisms and they implement the standards in a way to facilitate higher concurrency. In this post, let us talk about the topic of Concurrency and what are the various aspects that one needs to know about concurrency inside SQL Server. Let us learn the concepts as one-liners: Concurrency can be defined as the ability of multiple processes to access or change shared data at the same time. The greater the number of concurrent user processes that can be active without interfering with each other, the greater the concurrency of the database system. Concurrency is reduced when a process that is changing data prevents other processes from reading that data or when a process that is reading data prevents other processes from changing that data. Concurrency is also affected when multiple processes are attempting to change the same data simultaneously. Two approaches to managing concurrent data access: Optimistic Concurrency Model Pessimistic Concurrency Model Concurrency Models Pessimistic Concurrency Default behavior: acquire locks to block access to data that another process is using. Assumes that enough data modification operations are in the system that any given read operation is likely affected by a data modification made by another user (assumes conflicts will occur). Avoids conflicts by acquiring a lock on data being read so no other processes can modify that data. Also acquires locks on data being modified so no other processes can access the data for either reading or modifying. Readers block writer, writers block readers and writers. Optimistic Concurrency Assumes that there are sufficiently few conflicting data modification operations in the system that any single transaction is unlikely to modify data that another transaction is modifying. Default behavior of optimistic concurrency is to use row versioning to allow data readers to see the state of the data before the modification occurs. Older versions of the data are saved so a process reading data can see the data as it was when the process started reading and not affected by any changes being made to that data. Processes modifying the data is unaffected by processes reading the data because the reader is accessing a saved version of the data rows. Readers do not block writers and writers do not block readers, but, writers can and will block writers. Transaction Processing A transaction is the basic unit of work in SQL Server. Transaction consists of SQL commands that read and update the database but the update is not considered final until a COMMIT command is issued (at least for an explicit transaction: marked with a BEGIN TRAN and the end is marked by a COMMIT TRAN or ROLLBACK TRAN). Transactions must exhibit all the ACID properties of a transaction. ACID Properties Transaction processing must guarantee the consistency and recoverability of SQL Server databases. Ensures all transactions are performed as a single unit of work regardless of hardware or system failure. A – Atomicity C – Consistency I – Isolation D- Durability Atomicity: Each transaction is treated as all or nothing – it either commits or aborts. Consistency: ensures that a transaction won’t allow the system to arrive at an incorrect logical state – the data must always be logically correct.  Consistency is honored even in the event of a system failure. Isolation: separates concurrent transactions from the updates of other incomplete transactions. SQL Server accomplishes isolation among transactions by locking data or creating row versions. Durability: After a transaction commits, the durability property ensures that the effects of the transaction persist even if a system failure occurs. If a system failure occurs while a transaction is in progress, the transaction is completely undone, leaving no partial effects on data. Transaction Dependencies In addition to supporting all four ACID properties, a transaction might exhibit few other behaviors (known as dependency problems or consistency problems). Lost Updates: Occur when two processes read the same data and both manipulate the data, changing its value and then both try to update the original data to the new value. The second process might overwrite the first update completely. Dirty Reads: Occurs when a process reads uncommitted data. If one process has changed data but not yet committed the change, another process reading the data will read it in an inconsistent state. Non-repeatable Reads: A read is non-repeatable if a process might get different values when reading the same data in two reads within the same transaction. This can happen when another process changes the data in between the reads that the first process is doing. Phantoms: Occurs when membership in a set changes. It occurs if two SELECT operations using the same predicate in the same transaction return a different number of rows. Isolation Levels SQL Server supports 5 isolation levels that control the behavior of read operations. Read Uncommitted All behaviors except for lost updates are possible. Implemented by allowing the read operations to not take any locks, and because of this, it won’t be blocked by conflicting locks acquired by other processes. The process can read data that another process has modified but not yet committed. When using the read uncommitted isolation level and scanning an entire table, SQL Server can decide to do an allocation order scan (in page-number order) instead of a logical order scan (following page pointers). If another process doing concurrent operations changes data and move rows to a new location in the table, the allocation order scan can end up reading the same row twice. Also can happen if you have read a row before it is updated and then an update moves the row to a higher page number than your scan encounters later. Performing an allocation order scan under Read Uncommitted can cause you to miss a row completely – can happen when a row on a high page number that hasn’t been read yet is updated and moved to a lower page number that has already been read. Read Committed Two varieties of read committed isolation: optimistic and pessimistic (default). Ensures that a read never reads data that another application hasn’t committed. If another transaction is updating data and has exclusive locks on data, your transaction will have to wait for the locks to be released. Your transaction must put share locks on data that are visited, which means that data might be unavailable for others to use. A share lock doesn’t prevent others from reading but prevents them from updating. Read committed (snapshot) ensures that an operation never reads uncommitted data, but not by forcing other processes to wait. SQL Server generates a version of the changed row with its previous committed values. Data being changed is still locked but other processes can see the previous versions of the data as it was before the update operation began. Repeatable Read This is a Pessimistic isolation level. Ensures that if a transaction revisits data or a query is reissued the data doesn’t change. That is, issuing the same query twice within a transaction cannot pickup any changes to data values made by another user’s transaction because no changes can be made by other transactions. However, this does allow phantom rows to appear. Preventing non-repeatable read is a desirable safeguard but cost is that all shared locks in a transaction must be held until the completion of the transaction. Snapshot Snapshot Isolation (SI) is an optimistic isolation level. Allows for processes to read older versions of committed data if the current version is locked. Difference between snapshot and read committed has to do with how old the older versions have to be. It’s possible to have two transactions executing simultaneously that give us a result that is not possible in any serial execution. Serializable This is the strongest of the pessimistic isolation level. Adds to repeatable read isolation level by ensuring that if a query is reissued rows were not added in the interim, i.e, phantoms do not appear. Preventing phantoms is another desirable safeguard, but cost of this extra safeguard is similar to that of repeatable read – all shared locks in a transaction must be held until the transaction completes. In addition serializable isolation level requires that you lock data that has been read but also data that doesn’t exist. Ex: if a SELECT returned no rows, you want it to return no. rows when the query is reissued. This is implemented in SQL Server by a special kind of lock called the key-range lock. Key-range locks require that there be an index on the column that defines the range of values. If there is no index on the column, serializable isolation requires a table lock. Gets its name from the fact that running multiple serializable transactions at the same time is equivalent of running them one at a time. Now that we understand the basics of what concurrency is, the subsequent blog posts will try to bring out the basics around locking, blocking, deadlocks because they are the fundamental blocks that make concurrency possible. Now if you are with me – let us continue learning for SQL Server Locking Basics. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Concurrency

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  • Comparison of Architecture presentation patterns MVP(SC),MVP(PV),PM,MVVM and MVC

    This article will compare four important architecture presentation patterns i.e. MVP(SC),MVP(PV),PM,MVVM and MVC. Many developers are confused around what is the difference between these patterns and when should we use what. This article will first kick start with a background and explain different...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • Comparison of Architecture presentation patterns MVP(SC),MVP(PV),PM,MVVM and MVC

    This article will compare four important architecture presentation patterns i.e. MVP(SC),MVP(PV),PM,MVVM and MVC. Many developers are confused around what is the difference between these patterns and when should we use what. This article will first kick start with a background and explain different...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • HVM virtualization with PV drivers on XenServer

    - by Nathan
    Is it possible to create an HVM guest in XenServer 5.5 that uses PV drivers for disk and network without being fully paravirutalized? This should give me decent performance from the VM without having to jump through hoops to create a PV guest when a pre-built template doesn't exist. Since PV drivers exist for Windows, and XenServer provides templates for windows that use HVM virtualization this must be possible, I just don't see how to configure this myself.

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  • HVM virtualization with PV drivers on XenServer

    - by Nathan
    Is it possible to create an HVM guest in XenServer 5.5 that uses PV drivers for disk and network without being fully paravirutalized? This should give me decent performance from the VM without having to jump through hoops to create a PV guest when a pre-built template doesn't exist. Since PV drivers exist for Windows, and XenServer provides templates for windows that use HVM virtualization this must be possible, I just don't see how to configure this myself.

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  • Converting a PV vm back into an HVM vm

    - by wim.coekaerts
    I have been doing some Oracle VM benchmark stuff in the last week or 2 in my off hours and yesterday I wanted to convert one of my VMs that was based on a paravirt kernel into a vm that just boots as a regular hardware virt VM with a standard x86-64 kernel. It took me a little while to figure out the fastest way so now that I have it pretty much down I wanted to share the steps. A PV kernel uses pygrub and a paravirt kernel image that lives on the vm image virtual disk. since this disk image does not have to be bootable it doesn't contain a boot sector and if you just restart the VM in hvm mode the virtual bios will just not do much as it can't start the boot process from disk The first thing I do is make a backup of my vm.cfg file :-) and then edit it as follows : the original file contains : bootloader = '/usr/bin/pygrub' I replace that with : acpi = 1 apic = 1 builder = 'hvm' device_model = '/usr/lib/xen/bin/qemu-dm' kernel = '/usr/lib/xen/boot/hvmloader' then changing the disk files. I change my xvd disks to hd disks and I copy over the iso image of my instal lDVD. In the case of my VM template it was based on OL5U4 So I downloaded Enterprise-R5-U4-Server-x86_64-dvd.iso and added it as a cd device. disk = ['file:/ovs/OVM_EL5U4_X86_64_11202RAC_PVM/System.img,xvda,w', 'file:/ovs/OVM_EL5U4_X86_64_11202RAC_PVM/Oracle11202RAC_x86_64-xvdb.img,xvdb,w', ] to disk = ['file:/ovs/OVM_EL5U4_X86_64_11202RAC_PVM/System.img,hda,w', 'file:/ovs/OVM_EL5U4_X86_64_11202RAC_PVM/Oracle11202RAC_x86_64-xvdb.img,hdb,w', 'file:/ovs/OVM_EL5U4_X86_64_11202RAC_PVM/Enterprise-R5-U4-Server-x86_64-dvd.iso, hdc:cdrom,r', ] boot='d' for the network devices (vifs) I change : vif = ['bridge=xenbr2,type=netfront'] to vif = ['bridge=xenbr2,type=ioemu'] That should do it. Next, inside the VM, I copy over the regular kernel rpm that I want to end up running in hvm mode. In this example case it was : kernel-2.6.18-164.0.0.0.1.el5.x8664.rpm. I will use that later on in the process. I put this kernel simply in /root At this point I just start the vm with xm create vm.cfg and start my vnc console to the vm console. Oracle Linux will boot from the iso image, I just go through the install steps and click on UPgrade existing (not re-install). Because the VM is the same as the ISO the install won't actually do anything and it will run through instantly. When the "Reboot" button pops up, don't reboot. Switch to the command prompt console. hi alt-f2 to go to the shell prompt. Now it's easy : umount /mnt/sysimage/boot cd /mnt/sysimage chroot . mount /dev/hda1 (if that was your /boot partition) export PATH=/sbin:$PATH (just to clean that up) edit /etc/modprobe.conf and comment out the xen modules (just put a # in front) Install grub. if your /boot is hda1 then that is (hd0,0) $ grub root (hd0,0) setup (hd0) exit grub now you have a good bootsector, grub installed and you have your grub.conf file Install the new kernel cd root (this is your old /root in your pv image) rpm -ivh remove (or comment out) boot='d' in your vm.cfg restart the VM and you should be good to go, regular grub should start and load your environment. Caveats : this assumes you used labels for your filesystems. if /etc/fstab were to have devices listed then you would have to rename these device before rebooting as well. If you had a /dev/xvda disk then this would be /dev/hda or /dev/sda. All in all it is a relatively short and simple process.

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  • Converting a PV vm back into an HVM vm

    - by wim.coekaerts
    I have been doing some Oracle VM benchmark stuff in the last week or 2 in my off hours and yesterday I wanted to convert one of my VMs that was based on a paravirt kernel into a vm that just boots as a regular hardware virt VM with a standard x86-64 kernel. It took me a little while to figure out the fastest way so now that I have it pretty much down I wanted to share the steps. A PV kernel uses pygrub and a paravirt kernel image that lives on the vm image virtual disk. since this disk image does not have to be bootable it doesn't contain a boot sector and if you just restart the VM in hvm mode the virtual bios will just not do much as it can't start the boot process from disk The first thing I do is make a backup of my vm.cfg file :-) and then edit it as follows : the original file contains : bootloader = '/usr/bin/pygrub' I replace that with : acpi = 1 apic = 1 builder = 'hvm' device_model = '/usr/lib/xen/bin/qemu-dm' kernel = '/usr/lib/xen/boot/hvmloader' then changing the disk files. I change my xvd disks to hd disks and I copy over the iso image of my instal lDVD. In the case of my VM template it was based on OL5U4 So I downloaded Enterprise-R5-U4-Server-x86_64-dvd.iso and added it as a cd device. disk = ['file:/ovs/OVM_EL5U4_X86_64_11202RAC_PVM/System.img,xvda,w', 'file:/ovs/OVM_EL5U4_X86_64_11202RAC_PVM/Oracle11202RAC_x86_64-xvdb.img,xvdb,w', ] to disk = ['file:/ovs/OVM_EL5U4_X86_64_11202RAC_PVM/System.img,hda,w', 'file:/ovs/OVM_EL5U4_X86_64_11202RAC_PVM/Oracle11202RAC_x86_64-xvdb.img,hdb,w', 'file:/ovs/OVM_EL5U4_X86_64_11202RAC_PVM/Enterprise-R5-U4-Server-x86_64-dvd.iso, hdc:cdrom,r', ] boot='d' for the network devices (vifs) I change : vif = ['bridge=xenbr2,type=netfront'] to vif = ['bridge=xenbr2,type=ioemu'] That should do it. Next, inside the VM, I copy over the regular kernel rpm that I want to end up running in hvm mode. In this example case it was : kernel-2.6.18-164.0.0.0.1.el5.x8664.rpm. I will use that later on in the process. I put this kernel simply in /root At this point I just start the vm with xm create vm.cfg and start my vnc console to the vm console. Oracle Linux will boot from the iso image, I just go through the install steps and click on UPgrade existing (not re-install). Because the VM is the same as the ISO the install won't actually do anything and it will run through instantly. When the "Reboot" button pops up, don't reboot. Switch to the command prompt console. hi alt-f2 to go to the shell prompt. Now it's easy : umount /mnt/sysimage/boot cd /mnt/sysimage chroot . mount /dev/hda1 (if that was your /boot partition) export PATH=/sbin:$PATH (just to clean that up) edit /etc/modprobe.conf and comment out the xen modules (just put a # in front) Install grub. if your /boot is hda1 then that is (hd0,0) $ grub root (hd0,0) setup (hd0) exit grub now you have a good bootsector, grub installed and you have your grub.conf file Install the new kernel cd root (this is your old /root in your pv image) rpm -ivh remove (or comment out) boot='d' in your vm.cfg restart the VM and you should be good to go, regular grub should start and load your environment. Caveats : this assumes you used labels for your filesystems. if /etc/fstab were to have devices listed then you would have to rename these device before rebooting as well. If you had a /dev/xvda disk then this would be /dev/hda or /dev/sda. All in all it is a relatively short and simple process.

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  • How to extend a Linux PV partition online after virtual disk growth

    - by Yves Martin
    VMware allows to extend the size of a virtual disk online - when the VM is running. The next expected steps for Linux system are: extend the partition: delete and create a larger one with fdisk extend the PV size with pvresize use free extents for lvresize operations and then resize2fs for file system But I am stuck on the first step: fdisk and sfdisk still display the old size for the disk. My disk is a SCSI virtual disk connected thanks to the virtual LSI Logic controller. How to refresh the virtual disk size and partition table information available in Linux kernel without reboot ? As far as I know all that steps are possible for a running Windows, without reboot and even without any user actions thanks to VMWare tools. On Linux, I expects to do all steps online too and I already know steps 2, 3 and 4 work online. But the first one - change partition size declared in the partition table (still) seems to require a reboot. Update: My system is a Debian Lenny with kernel 2.6.26 and the disk I have extended is the main disk with a large PV containing the "root" LV for "/".

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  • Difference between Xen PV, Xen KVM and HVM?

    - by JP19
    Hi, I know that Xen is usually better than OpenVZ as the provider cannot oversell in Xen. However, what is the difference between Xen PV, Xen KVM and HVM (I was going through this provider's specs? Which one is better for what purposes and why? Edit: For an end-user who will just be hosting websites, which is better? From efficiency or other point of view, is there any advantage of one over the other?

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  • SOLVED:Bootloader isn't executable booting XEN PV Guest with virtual-manager

    - by user2284355
    I am going insane with an error I am encountering while trying to install a PV Guest of Debian Wheezy on a Ubuntu Server precise Xen default build with libvirt. The steps I take with virt-manager are the following: 1.Net install via: http://ftp.es.debian.org/debian/dists/stable/main/installer-amd64/ 2.Install process is flawless, installed via VNC over virt-manager 3.When the VM starts I get the following error: Error starting domain: POST operation failed: xend_post: error from xen daemon: (xend.err "Bootloader isn't executable") Most answers i have found on google say that I need to edit the VM's .cfg file and correct the path to pygrub but virt-manager does not seem to create this file (I have searched the entire drive with "find". Another detail is that virsh list --all shows no VMs (Not even dom0) while the command xm list shows all of them. Any help is much appreciated. EDIT: Connected remotely via virsh: virsh -c xen+ssh://user@ip dumpxml vmname Found line: /usr/bin/pygrub ln -s /usr/lib/xen-4.1/bin/pygrub /usr/bin/pygrub Now it works. If anyone can think of a better solution give me a shout. Cheers

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  • Resize PV on LVM

    - by Paul Tarjan
    I have this: Device Boot Start End Blocks Id System /dev/sda1 * 1 1217 9775552 83 Linux /dev/sda2 1218 60801 478608480 83 Linux And I'd like to shrink sda2 by about 10 Gigs to give some more space to sda1. sda2 is a PV on an LVM, but there is some free space in the VG so I don't have to worry about filesystem shrinking. How can I tell my LVM to move the data off of the first 10 gigs of sda2 and then redo my partition table to give it to sda1? (I don't have enough free space to just pvremove sda2, which would be the easy solution).

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  • Xen PV packet loss

    - by Delphinator
    I'm having some serious issues with packetloss with one of my servers. This server is a somewhat old (P4-era) machine running Debian Squeeze and Xen 4.0. There are two domUs running on it (both also Debian Squeeze), one gateway and a fileserver. Unfortunatly the processor has no virtualization extensions, therefore only PV can be used. While investigating why our network seems to be slower than it should I found some pretty bad packet loss (~25%). After further investigation and several experiments I did a measurment between the dom0 and one of the domUs: Server listening on UDP port 5001 Receiving 1470 byte datagrams UDP buffer size: 110 KByte (default) ------------------------------------------------------------ ------------------------------------------------------------ Client connecting to dom0, UDP port 5001 Sending 1470 byte datagrams UDP buffer size: 110 KByte (default) ------------------------------------------------------------ [ 3] local 192.168.1.2(domU) port 33817 connected with 192.168.1.100(dom0) port 5001 [ 4] local 192.168.1.2(domU) port 5001 connected with 192.168.1.100(dom0) port 48606 [ ID] Interval Transfer Bandwidth [ 3] 0.0-10.0 sec 46.3 MBytes 38.7 Mbits/sec [ 3] Sent 33020 datagrams [ 3] Server Report: [ 3] 0.0-10.0 sec 46.2 MBytes 38.6 Mbits/sec 0.030 ms 89/33019 (0.27%) [ 3] 0.0-10.0 sec 1 datagrams received out-of-order [ 4] 0.0-10.2 sec 43.0 MBytes 35.3 Mbits/sec 13.074 ms 11575/42256 (27%) tl;dr: 27% packet loss from dom0 to domU with 50Mbit UDP packets. Same thing happens from anywhere in the network. The problem gets better for smaller bandwidths (0.047% for 5Mbit) and worse for higher (59% for 200Mbit) ones. I did increase the CPU-weight of the dom0, there is no swapping going on, and actual networking-hardware is not involved. I never expected Xen (or anything related) to drop packets, and I'm completly clueless what to try next.

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  • Rapidly Deploy Oracle Applications with Oracle VM Templates

    - by monica.kumar
    Oracle today announced Oracle VM Templates for a number of Oracle Applications including Oracle E-Business Suite 12.1 Oracle's JD Edwards Enterprise One 9.0 Oracle's PeopleSoft 9.1 These Oracle VM Templates, based on Oracle Enterprise Linux, provide pre-installed and pre-configured enterprise software images that help eliminate the need to install new software from scratch, offering customers a time-saving approach to deploying a fully configured software stack. Learn more about Oracle VM Templates

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  • Linux.com: Q&A on Oracle's Unbreakable Enterprise Kernel

    - by monica.kumar
    Linux.com recently published a Q&A on Oracle's Unbreakable Enterprise Kernel for Linux. The interview highlights the key benefits of Oracle's new offering and also offers an insight into our long and ongoing commitment to advancing Linux. Here are some excerpts from the Q&A: All enhancements made in the Unbreakable Enterprise Kernel are open source and have been made available to the Linux community. Oracle Linux, including both the kernels, is free to download, use and distribute. You can download the Unbreakable Enterprise Kernel at http://public-yum.oracle.com Source code is available, including a public git repository with full changelog and individual patches and checkins for convenience. Read the entire interview. Visit the Oracle Linux Homepage.

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  • New Reference Configuration: Accelerate Deployment of Virtual Infrastructure

    - by monica.kumar
    Today, Oracle announced the availability of Oracle VM blade cluster reference configuration based on Sun servers, storage and Oracle VM software. Assembling and integrating software and hardware systems from different vendors can be a huge barrier to deploying virtualized infrastructures as it is often a complicated, time-consuming, risky and expensive process. Using this tested configuration can help reduce the time to configure and deploy a virtual infrastructure by up to 98% as compared to putting together multi-vendor configurations. Once ready, the infrastructure can be used to easily deploy enterprise applications in a matter of minutes to hours as opposed to days/weeks, by using Oracle VM Templates. Find out more: Press Release Business whitepaper Technical whitepaper

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  • SQL query mixing aggregated results and single values

    - by Paul Flowerdew
    I have a table with transactions. Each transaction has a transaction ID, and accounting period (AP), and a posting value (PV), as well as other fields. Some of the IDs are duplicated, usually because the transaction was done in error. To give an example, part of the table might look like: ID PV AP 123 100 2 123 -100 5 In this case the transaction was added in AP2 then removed in AP5. Another example would be: ID PV AP 456 100 2 456 -100 5 456 100 8 In the first example, the problem is that if I am analyzing what was spent in AP2, there is a transaction in there which actually shouldn't be taken into account because it was taken out again in AP5. In the second example, the second two transactions shouldn't be taken into account because they cancel each other out. I want to label as many transactions as possible which shouldn't be taken into account as erroneous. To identify these transactions, I want to find the ones with duplicate IDs whose PVs sum to zero (like ID 123 above) or transactions where the PV of the earliest one is equal to sum(PV), as in the second example. This second condition is what is causing me grief. So far I have SELECT * FROM table WHERE table.ID IN (SELECT table.ID FROM table GROUP BY table.ID HAVING COUNT(*) > 1 AND (SUM(table.PV) = 0 OR SUM(table.PV) = <PV of first transaction in each group>)) ORDER BY table.ID; The bit in chevrons is what I'm trying to do and I'm stuck. Can I do it like this or is there some other method I can use in SQL to do this? Edit 1: Btw I forgot to say that I'm using SQL Compact 3.5, in case it matters. Edit 2: I think the code snippet above is a bit misleading. I still want to mark out transactions with duplicate IDs where sum(PV) = 0, as in the first example. But where the PV of the earliest transaction = sum(PV), as in the second example, what I actually want is to keep the earliest transaction and mark out all the others with the same ID. Sorry if that caused confusion. Edit 3: I've been playing with Clodoaldo's solution and have made some progress, but still can't get quite what I want. I'm trying to get the transactions I know for certain to be erroneous. Suppose the following transactions are also in the table: ID PV AP 789 100 2 789 200 5 789 -100 8 In this example sum(PV) < 0 and the earliest PV < sum(PV) so I don't want to mark any of these out. If I modify Clodoaldo's query as follows: select t.* from t left join ( select id, min(ap) as ap, sum(pv) as sum_pv from t group by id having sum(pv) <> 0 ) s on t.id = s.id and t.ap = s.ap and t.pv = s.sum_pv where s.id is null This gives the result ID PV AP 123 100 2 123 -100 5 456 -100 5 456 100 8 789 100 3 789 200 5 789 -100 8 Whilst the first 4 transactions are ok (they would be marked out), the 789 transactions are also there, and I don't want them. But I can't figure out how to modify the query so that they're not included. Any ideas?

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  • how to group data in a list

    - by prince23
    I need to group data of a list in c# ex: i have a data like this in a list c# i have a class called information.cs with these properties name,school, parent ex data name school parent kumar fes All manju fes kumar anu frank kumar anitha jss All rohit frank manju anill vijaya manju vani jss kumar soumya jss kumar madhu jss rohit shiva jss rohit vanitha jss anitha anu jss anitha now taking this as an input i wanted the output to be formated with a Hierarchical data when parent is all means it is the topmost level kumar fes All. what i need to do here is i need to create an object[0] and then check in list whether kumar exists as a parent in the list if it exista then add those items as under the object[0] as a parent i need to create one more oject under **manju fes kumar anu frank kumar** what i wanted do here is iterate through the list anD then check the parent level based on name school parent kumar fes All -->obj[0] manju fes kumar -->obj1[0] anu frank kumar -->obj1[1] for obj1-- obj[0] will be parent like this i need to genarte a list or observation class anitha jss All-->obj[1] vanitha jss anitha -->obj1[0] anu jss vanitha -->obj2[0] here obj2[0]--obj1[0]--obj[1] will be an parent like this i need to create a list or an observationclass hope my Question is clear what i am trying ask you people. i wanted to know how i can create an observationclass. any help would be really great. hope my question is clear

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  • how to group data in a list c#

    - by prince23
    hi, i need to group data of a list in c# ex: i have a data like this in a list c# i have a class called information.cs with these properties name,school, parent ex data name school parent kumar fes All manju fes kumar anu frank kumar anitha jss All rohit frank manju anill vijaya manju vani jss kumar soumya jss kumar madhu jss rohit shiva jss rohit vanitha jss anitha anu jss anitha now taking this as an input i wanted the output to be formated with a Hierarchical data when parent is all means it is the topmost level kumar fes All. what i need to do here is i need to create an object[0] and then check in list whether kumar exists as a parent in the list if it exista then add those items as under the object[0] as a parent i need to create one more oject under **manju fes kumar anu frank kumar** what i wanted do here is iterate through the list anD then check the parent level based on name school parent kumar fes All -->obj[0] manju fes kumar -->obj1[0] anu frank kumar -->obj1[1] for obj1-- obj[0] will be parent like this i need to genarte a list or observation class anitha jss All-->obj[1] vanitha jss anitha -->obj1[0] anu jss vanitha -->obj2[0] here obj2[0]--obj1[0]--obj[1] will be an parent like this i need to create a list or an observationclass hope my Question is clear what i am trying ask you people. i wanted to know how i can create an observationclass any help would be really great thanks prince hope my question is clear

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  • Big Data – Is Big Data Relevant to me? – Big Data Questionnaires – Guest Post by Vinod Kumar

    - by Pinal Dave
    This guest post is by Vinod Kumar. Vinod Kumar has worked with SQL Server extensively since joining the industry over a decade ago. Working on various versions of SQL Server 7.0, Oracle 7.3 and other database technologies – he now works with the Microsoft Technology Center (MTC) as a Technology Architect. Let us read the blog post in Vinod’s own voice. I think the series from Pinal is a good one for anyone planning to start on Big Data journey from the basics. In my daily customer interactions this buzz of “Big Data” always comes up, I react generally saying – “Sir, do you really have a ‘Big Data’ problem or do you have a big Data problem?” Generally, there is a silence in the air when I ask this question. Data is everywhere in organizations – be it big data, small data, all data and for few it is bad data which is same as no data :). Wow, don’t discount me as someone who opposes “Big Data”, I am a big supporter as much as I am a critic of the abuse of this term by the people. In this post, I wanted to let my mind flow so that you can also think in the direction I want you to see these concepts. In any case, this is not an exhaustive dump of what is in my mind – but you will surely get the drift how I am going to question Big Data terms from customers!!! Is Big Data Relevant to me? Many of my customers talk to me like blank whiteboard with no idea – “why Big Data”. They want to jump into the bandwagon of technology and they want to decipher insights from their unexplored data a.k.a. unstructured data with structured data. So what are these industry scenario’s that come to mind? Here are some of them: Financials Fraud detection: Banks and Credit cards are monitoring your spending habits on real-time basis. Customer Segmentation: applies in every industry from Banking to Retail to Aviation to Utility and others where they deal with end customer who consume their products and services. Customer Sentiment Analysis: Responding to negative brand perception on social or amplify the positive perception. Sales and Marketing Campaign: Understand the impact and get closer to customer delight. Call Center Analysis: attempt to take unstructured voice recordings and analyze them for content and sentiment. Medical Reduce Re-admissions: How to build a proactive follow-up engagements with patients. Patient Monitoring: How to track Inpatient, Out-Patient, Emergency Visits, Intensive Care Units etc. Preventive Care: Disease identification and Risk stratification is a very crucial business function for medical. Claims fraud detection: There is no precise dollars that one can put here, but this is a big thing for the medical field. Retail Customer Sentiment Analysis, Customer Care Centers, Campaign Management. Supply Chain Analysis: Every sensors and RFID data can be tracked for warehouse space optimization. Location based marketing: Based on where a check-in happens retail stores can be optimize their marketing. Telecom Price optimization and Plans, Finding Customer churn, Customer loyalty programs Call Detail Record (CDR) Analysis, Network optimizations, User Location analysis Customer Behavior Analysis Insurance Fraud Detection & Analysis, Pricing based on customer Sentiment Analysis, Loyalty Management Agents Analysis, Customer Value Management This list can go on to other areas like Utility, Manufacturing, Travel, ITES etc. So as you can see, there are obviously interesting use cases for each of these industry verticals. These are just representative list. Where to start? A lot of times I try to quiz customers on a number of dimensions before starting a Big Data conversation. Are you getting the data you need the way you want it and in a timely manner? Can you get in and analyze the data you need? How quickly is IT to respond to your BI Requests? How easily can you get at the data that you need to run your business/department/project? How are you currently measuring your business? Can you get the data you need to react WITHIN THE QUARTER to impact behaviors to meet your numbers or is it always “rear-view mirror?” How are you measuring: The Brand Customer Sentiment Your Competition Your Pricing Your performance Supply Chain Efficiencies Predictive product / service positioning What are your key challenges of driving collaboration across your global business?  What the challenges in innovation? What challenges are you facing in getting more information out of your data? Note: Garbage-in is Garbage-out. Hold good for all reporting / analytics requirements Big Data POCs? A number of customers get into the realm of setting a small team to work on Big Data – well it is a great start from an understanding point of view, but I tend to ask a number of other questions to such customers. Some of these common questions are: To what degree is your advanced analytics (natural language processing, sentiment analysis, predictive analytics and classification) paired with your Big Data’s efforts? Do you have dedicated resources exploring the possibilities of advanced analytics in Big Data for your business line? Do you plan to employ machine learning technology while doing Advanced Analytics? How is Social Media being monitored in your organization? What is your ability to scale in terms of storage and processing power? Do you have a system in place to sort incoming data in near real time by potential value, data quality, and use frequency? Do you use event-driven architecture to manage incoming data? Do you have specialized data services that can accommodate different formats, security, and the management requirements of multiple data sources? Is your organization currently using or considering in-memory analytics? To what degree are you able to correlate data from your Big Data infrastructure with that from your enterprise data warehouse? Have you extended the role of Data Stewards to include ownership of big data components? Do you prioritize data quality based on the source system (that is Facebook/Twitter data has lower quality thresholds than radio frequency identification (RFID) for a tracking system)? Do your retention policies consider the different legal responsibilities for storing Big Data for a specific amount of time? Do Data Scientists work in close collaboration with Data Stewards to ensure data quality? How is access to attributes of Big Data being given out in the organization? Are roles related to Big Data (Advanced Analyst, Data Scientist) clearly defined? How involved is risk management in the Big Data governance process? Is there a set of documented policies regarding Big Data governance? Is there an enforcement mechanism or approach to ensure that policies are followed? Who is the key sponsor for your Big Data governance program? (The CIO is best) Do you have defined policies surrounding the use of social media data for potential employees and customers, as well as the use of customer Geo-location data? How accessible are complex analytic routines to your user base? What is the level of involvement with outside vendors and third parties in regard to the planning and execution of Big Data projects? What programming technologies are utilized by your data warehouse/BI staff when working with Big Data? These are some of the important questions I ask each customer who is actively evaluating Big Data trends for their organizations. These questions give you a sense of direction where to start, what to use, how to secure, how to analyze and more. Sign off Any Big data is analysis is incomplete without a compelling story. The best way to understand this is to watch Hans Rosling – Gapminder (2:17 to 6:06) videos about the third world myths. Don’t get overwhelmed with the Big Data buzz word, the destination to what your data speaks is important. In this blog post, we did not particularly look at any Big Data technologies. This is a set of questionnaire one needs to keep in mind as they embark their journey of Big Data. I did write some of the basics in my blog: Big Data – Big Hype yet Big Opportunity. Do let me know if these questions make sense?  Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • SQL SERVER – Transcript of Learning SQL Server Performance: Indexing Basics – Interview of Vinod Kumar by Pinal Dave

    - by pinaldave
    Recently I just wrote a blog post on about Learning SQL Server Performance: Indexing Basics and I received lots of request that if we can share some insight into the course. Here is 200 seconds interview of Vinod Kumar I took right after completing the course. We have few free codes to watch the course, please your comment at http://facebook.com/SQLAuth and we will few of first ones, we will send the code. There are many people who said they would like to read the transcript of the video. Here I have generated the same. Pinal: Vinod, we recently released this course, SQL Server Indexing. It is about performance tuning. So tell me – how do indexes help performance? Vinod: I think what happens in the industry when it comes to performance is that developers and DBAs look at indexes first.  So that’s the first step for any performance tuning exercise, indexing is one of the most critical aspects and it is important to learn it the right way. Pinal: Correct. So what you mean to say is that if you know indexing you can pretty much tune any server and query. Vinod: So I might contradict my false statement now. Indexing is usually a stepping stone but it does not lead you to the end. But it’s good to start with indexing and there are lots of nuances to indexing that you need to understand, like how SQL uses indexing and how performance can improve because of the strategies that you have made. Pinal: But now I’m confused. First you said indexes are good, and then you said that indexes can degrade your performance.  So what is this course about?  I mean how does this course really make an impact? Vinod: Ok -so from the course perspective, what we are trying to do is give you a capsule which gives you a good start. Every journey needs a beginning, you need that first step.  This course is that first step in understanding. This is the most basic, fundamental course that we have tried to attack. This is the fundamentals of indexing, some of the key things that you must know about indexing.   Some of the basics of indexing are lesser known and so I think this course is geared towards each and every one of you out there who wants to understand little bit more about indexing. Pinal: So what I understand is that if I enrolled in this course I will have a minimum understanding about indexing when dealing with performance tuning.  Right? Vinod: Exactly. In this course is we have tried to give you a nice summary. We are talking about clustered indexing, non clustered indexing, too many indexes, too few indexes, over indexing, under indexing, duplicate indexing, columns tune indexing, with SQL Server 2012. There’s lot’s to learn. Pinal: You can see the URL [http://bit.ly/sql-index] of the course on the screen. Go ahead, attend, and let us know what you think about it. Thank you. Vinod: Thank you. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Index, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology, Video

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  • SQL SERVER – #TechEdIn – Presenting Tomorrow on SQL Server Misconception and Resolution with Vinod Kumar at TechEd India 2012

    - by pinaldave
    I am excited AND nervous at the same time. I am going to present a very interesting topic tomorrow at an SQL Server track in India. This will be my fourth time presenting at TechEd India. So far, I have received so much feedback about this one session. It seems like every single person out there has their own wishes and requests. I am sure that it is going to very challenging experience to satisfy everyone who attends the event through my presentation. Surprise Element Here is the good news: I am going to co-present this session with Vinod Kumar, my long time friend and co-worker. We have known each other for almost four years now, but this is the very first time that we are going to present together on the big stage of TechEd.  When there are more than two presenters, the usual trick is to practice the session multiple times and know exactly what each other is going to present and talk about. However, there’s a catch – we decided to make it different this time and have shared nothing to each other regarding what exactly we are going to present. This makes everything extremely interesting as each of us will be as clueless as the audience when other person is going to talk. Action Item Here are a few of the action items for all of those who are going to attend this session. Vinod and I will be present at the venue 15 minutes before the session. Do come in early and talk with us. We would be glad to talk with you and see if either of us can accommodate your suggestion in our session. If we do, we will give a surprise gift for you. As discussed, this session is going to be a unique two-presenter session. You will have chance to take a side with one speaker and stump the other speaker. Come early to decide which speaker you want to cheer during the session. Quiz and Goodies By now, you must have figured out that this session is going to be an extremely interactive session. We need your support through your active participation. We will have some really brain-twisting quiz line up just for you. You will have to take part and win surprises from us! Trust me. If you get it right, we will give you something which can help you learn more! We will have a quiz on Twitter as well. We will ask a question in person and you will be able to participate on Twitter. 10 – Demos As I said, both of us do not know what each other is going to present, but there are few things which we know very well. We have 10 demos and 6 slides. I think this is going to be an exciting demo marathon. Trust me, you will love it and the taste of this session will be in your mouth till the next TechEd. Session Details Title: SQL Server Misconceptions and Resolution – A Practical Perspective (Add to Calendar) Abstract: “The earth is flat”! – An ancient common misconception, which has been proven incorrect as we progressed in modern times. In this session, we will see various database misconceptions prevailing and their resolutions with the aid of the demos. In this unique session, the audience will be a part of the conversation and resolution. Date and Time: March 21, 2012, 15:15 to 16:15 Location: Hotel Lalit Ashok - Kumara Krupa High Grounds, Bengaluru – 560001, Karnataka, India. Add to Calendar Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Interview Questions and Answers, SQL Query, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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