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  • 4.8M wasn't enough so we went for 5.055M tpmc with Unbreakable Enterprise Kernel r2 :-)

    - by wcoekaer
    We released a new set of benchmarks today. One is an updated tpc-c from a few months ago where we had just over 4.8M tpmc at $0.98 and we just updated it to go to 5.05M and $0.89. The other one is related to Java Middleware performance. You can find the press release here. Now, I don't want to talk about the actual relevance of the benchmark numbers, as I am not in the benchmark team. I want to talk about why these numbers and these efforts, unrelated to what they mean to your workload, matter to customers. The actual benchmark effort is a very big, long, expensive undertaking where many groups work together as a big virtual team. Having the virtual team be within a single company of course helps tremendously... We already start with a very big server setup with tons of storage, many disks, lots of ram, lots of cpu's, cores, threads, large database setups. Getting the whole setup going to start tuning, by itself, is no easy task, but then the real fun starts with tuning the system for optimal performance -and- stability. A benchmark is not just revving an engine at high rpm, it's actually hitting the circuit. The tests require long runs, require surviving availability tests, such as surviving crashes -and- recovery under load. In the TPC-C example, the x4800 system had 4TB ram, 160 threads (8 sockets, hyperthreaded, 10 cores/socket), tons of storage attached, tons of luns visible to the OS. flash storage, non flash storage... many things at high scale that all have to be perfectly synchronized. During this process, we find bugs, we fix bugs, we find performance issues, we fix performance issues, we find interesting potential features to investigate for the future, we start new development projects for future releases and all this goes back into the products. As more and more customers, for Oracle Linux, are running larger and larger, faster and faster, more mission critical, higher available databases..., these things are just absolutely critical. Unrelated to what anyone's specific opinion is about tpc-c or tpc-h or specjenterprise etc, there is a ton of effort that the customer benefits from. All this work makes Oracle Linux and/or Oracle Solaris better platforms. Whether it's faster, more stable, more scalable, more resilient. It helps. Another point that I always like to re-iterate around UEK and UEK2 : we have our kernel source git repository online. Complete changelog of the mainline kernel, and our changes, easy to pull, easy to dissect, easy to know what went in when, why and where. No need to go log into a website and manually click through pages to hopefully discover changes or patches. No need to untar 2 tar balls and run a diff.

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  • Red Gate Software announces speaker line up for US SQL in the City tour

    SQL in the City is a free, full day training and networking event for database professionals. After the success of last year’s event, Red Gate has expanded the event to cover six cities from sea to shining sea, including: New York, Austin, San Francisco, Chicago, Boston, and Seattle. Compress live data by 73% Red Gate's SQL Storage Compress reduces the size of live SQL Server databases, saving you disk space and storage costs. Learn more.

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  • ZFS for Database Log Files

    - by user12620111
    I've been troubled by drop outs in CPU usage in my application server, characterized by the CPUs suddenly going from close to 90% CPU busy to almost completely CPU idle for a few seconds. Here is an example of a drop out as shown by a snippet of vmstat data taken while the application server is under a heavy workload. # vmstat 1  kthr      memory            page            disk          faults      cpu  r b w   swap  free  re  mf pi po fr de sr s3 s4 s5 s6   in   sy   cs us sy id  1 0 0 130160176 116381952 0 16 0 0 0 0  0  0  0  0  0 207377 117715 203884 70 21 9  12 0 0 130160160 116381936 0 25 0 0 0 0 0  0  0  0  0 200413 117162 197250 70 20 9  11 0 0 130160176 116381920 0 16 0 0 0 0 0  0  1  0  0 203150 119365 200249 72 21 7  8 0 0 130160176 116377808 0 19 0 0 0 0  0  0  0  0  0 169826 96144 165194 56 17 27  0 0 0 130160176 116377800 0 16 0 0 0 0  0  0  0  0  1 10245 9376 9164 2  1 97  0 0 0 130160176 116377792 0 16 0 0 0 0  0  0  0  0  2 15742 12401 14784 4 1 95  0 0 0 130160176 116377776 2 16 0 0 0 0  0  0  1  0  0 19972 17703 19612 6 2 92  14 0 0 130160176 116377696 0 16 0 0 0 0 0  0  0  0  0 202794 116793 199807 71 21 8  9 0 0 130160160 116373584 0 30 0 0 0 0  0  0 18  0  0 203123 117857 198825 69 20 11 This behavior occurred consistently while the application server was processing synthetic transactions: HTTP requests from JMeter running on an external machine. I explored many theories trying to explain the drop outs, including: Unexpected JMeter behavior Network contention Java Garbage Collection Application Server thread pool problems Connection pool problems Database transaction processing Database I/O contention Graphing the CPU %idle led to a breakthrough: Several of the drop outs were 30 seconds apart. With that insight, I went digging through the data again and looking for other outliers that were 30 seconds apart. In the database server statistics, I found spikes in the iostat "asvc_t" (average response time of disk transactions, in milliseconds) for the disk drive that was being used for the database log files. Here is an example:                     extended device statistics     r/s    w/s   kr/s   kw/s wait actv wsvc_t asvc_t  %w  %b device     0.0 2053.6    0.0 8234.3  0.0  0.2    0.0    0.1   0  24 c3t60080E5...F4F6d0s0     0.0 2162.2    0.0 8652.8  0.0  0.3    0.0    0.1   0  28 c3t60080E5...F4F6d0s0     0.0 1102.5    0.0 10012.8  0.0  4.5    0.0    4.1   0  69 c3t60080E5...F4F6d0s0     0.0   74.0    0.0 7920.6  0.0 10.0    0.0  135.1   0 100 c3t60080E5...F4F6d0s0     0.0  568.7    0.0 6674.0  0.0  6.4    0.0   11.2   0  90 c3t60080E5...F4F6d0s0     0.0 1358.0    0.0 5456.0  0.0  0.6    0.0    0.4   0  55 c3t60080E5...F4F6d0s0     0.0 1314.3    0.0 5285.2  0.0  0.7    0.0    0.5   0  70 c3t60080E5...F4F6d0s0 Here is a little more information about my database configuration: The database and application server were running on two different SPARC servers. Storage for the database was on a storage array connected via 8 gigabit Fibre Channel Data storage and log file were on different physical disk drives Reliable low latency I/O is provided by battery backed NVRAM Highly available: Two Fibre Channel links accessed via MPxIO Two Mirrored cache controllers The log file physical disks were mirrored in the storage device Database log files on a ZFS Filesystem with cutting-edge technologies, such as copy-on-write and end-to-end checksumming Why would I be getting service time spikes in my high-end storage? First, I wanted to verify that the database log disk service time spikes aligned with the application server CPU drop outs, and they did: At first, I guessed that the disk service time spikes might be related to flushing the write through cache on the storage device, but I was unable to validate that theory. After searching the WWW for a while, I decided to try using a separate log device: # zpool add ZFS-db-41 log c3t60080E500017D55C000015C150A9F8A7d0 The ZFS log device is configured in a similar manner as described above: two physical disks mirrored in the storage array. This change to the database storage configuration eliminated the application server CPU drop outs: Here is the zpool configuration: # zpool status ZFS-db-41   pool: ZFS-db-41  state: ONLINE  scan: none requested config:         NAME                                     STATE         ZFS-db-41                                ONLINE           c3t60080E5...F4F6d0  ONLINE         logs           c3t60080E5...F8A7d0  ONLINE Now, the I/O spikes look like this:                     extended device statistics                  r/s    w/s   kr/s   kw/s wait actv wsvc_t asvc_t  %w  %b device     0.0 1053.5    0.0 4234.1  0.0  0.8    0.0    0.7   0  75 c3t60080E5...F8A7d0s0                     extended device statistics                  r/s    w/s   kr/s   kw/s wait actv wsvc_t asvc_t  %w  %b device     0.0 1131.8    0.0 4555.3  0.0  0.8    0.0    0.7   0  76 c3t60080E5...F8A7d0s0                     extended device statistics                  r/s    w/s   kr/s   kw/s wait actv wsvc_t asvc_t  %w  %b device     0.0 1167.6    0.0 4682.2  0.0  0.7    0.0    0.6   0  74 c3t60080E5...F8A7d0s0     0.0  162.2    0.0 19153.9  0.0  0.7    0.0    4.2   0  12 c3t60080E5...F4F6d0s0                     extended device statistics                  r/s    w/s   kr/s   kw/s wait actv wsvc_t asvc_t  %w  %b device     0.0 1247.2    0.0 4992.6  0.0  0.7    0.0    0.6   0  71 c3t60080E5...F8A7d0s0     0.0   41.0    0.0   70.0  0.0  0.1    0.0    1.6   0   2 c3t60080E5...F4F6d0s0                     extended device statistics                  r/s    w/s   kr/s   kw/s wait actv wsvc_t asvc_t  %w  %b device     0.0 1241.3    0.0 4989.3  0.0  0.8    0.0    0.6   0  75 c3t60080E5...F8A7d0s0                     extended device statistics                  r/s    w/s   kr/s   kw/s wait actv wsvc_t asvc_t  %w  %b device     0.0 1193.2    0.0 4772.9  0.0  0.7    0.0    0.6   0  71 c3t60080E5...F8A7d0s0 We can see the steady flow of 4k writes to the ZIL device from O_SYNC database log file writes. The spikes are from flushing the transaction group. Like almost all problems that I run into, once I thoroughly understand the problem, I find that other people have documented similar experiences. Thanks to all of you who have documented alternative approaches. Saved for another day: now that the problem is obvious, I should try "zfs:zfs_immediate_write_sz" as recommended in the ZFS Evil Tuning Guide. References: The ZFS Intent Log Solaris ZFS, Synchronous Writes and the ZIL Explained ZFS Evil Tuning Guide: Cache Flushes ZFS Evil Tuning Guide: Tuning ZFS for Database Performance

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  • Disk Is Cheap! ORLY?

    People often conclude that the cheap price of storage is a license to use as much as possible, but there is a cost. Solomon Rutzky talks about the issues you may face if you are not careful with your storage decisions. Join SQL Backup’s 35,000+ customers to compress and strengthen your backups "SQL Backup will be a REAL boost to any DBA lucky enough to use it." Jonathan Allen. Download a free trial now.

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  • CTERA Adds Data Protection to Linux File Systems

    <b>Enterprise Storage Forum: </b>"CTERA Networks is giving the Linux Ext3 file system additional data protection in the form of new snapshot capabilities. The file system is also the basis of the company's Cloud-Attached Storage appliances, the C200 and CloudPlug."

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  • Oracle Magazine - Sep/Oct 2010

    Oracle Magazine Sep/Oct features articles on Oracle Exadata, Database Security, Oracle Enterprise Manager 11g, PL/Scope to analyze your PL/SQL, Using Oracle Essbase Release 11.1.2 Aggregate Storage Option Databases, Oracle Application Express 4.0 Websheets, Oracle Automatic Storage Management disk groups, Tom Kyte revisits a classic, recounts Cardinality Feedback, and remembers SQL*Plus and much more.

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  • Showing ZFS some LOVE

    - by Kristin Rose
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} L is for the way you look at us, and O because we’re Oracle, but V is very, very, extra ordinary, and E, well that’s obvious… E is because Oracle’s new Sun ZFS Storage Appliance is Excellent, and here at OPN, we like spell out the obvious!  If you haven’t already heard, the Sun ZFS Appliance has “A simple, GUI-driven setup and configuration, solid price-performance and world-class Oracle support behind it. The CRN Test Center recommends the Sun ZFS Storage”. Read more about what CRN said here. Oracle's Sun ZFS Appliance family delivers enterprise-class network attached storage (NAS) capabilities with leading Oracle integration, simplicity, efficiency, performance, and TCO.  The systems offer an easy way to manage and expand your storage environment at a lower cost, with more efficiency, better data integrity, and higher performance when compared with competitive NAS offerings. Did we mention that set up, including configuring, will take you less than an hour since it all comes in one box and is so darn simple to use? So if you L-O-V-E what you’re hearing about Oracle’s Sun Z-F-S, learn more by watching the video below, and visiting any of our available resources . It Had to Be You, The OPN Communications Team

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  • 13.10 upgrade dropping wifi [on hold]

    - by Daryl
    Almost a complete newb here. After my last upgrade from 12.04 to 13.10 my wifi now randomly drops. The only way I can get a signal back is a shutdown and restart otherwise it shows no network is even available to connect to. Had no problems until the upgrade. Any help would be appreciated. H/W path Device Class Description ==================================================== system h8-1534 (H2N64AA#ABA) /0 bus 2AC8 /0/0 memory 64KiB BIOS /0/4 processor AMD FX(tm)-6200 Six-Core Processor /0/4/5 memory 288KiB L1 cache /0/4/6 memory 6MiB L2 cache /0/4/7 memory 8MiB L3 cache /0/d memory 10GiB System Memory /0/d/0 memory DIMM Synchronous [empty] /0/d/1 memory 4GiB DIMM DDR3 Synchronous 1600 MHz (0.6 ns) /0/d/2 memory 2GiB DIMM DDR3 Synchronous 1600 MHz (0.6 ns) /0/d/3 memory 4GiB DIMM DDR3 Synchronous 1600 MHz (0.6 ns) /0/100 bridge RD890 PCI to PCI bridge (external gfx0 port B) /0/100/0.2 generic RD990 I/O Memory Management Unit (IOMMU) /0/100/2 bridge RD890 PCI to PCI bridge (PCI express gpp port B) /0/100/2/0 display Turks PRO [Radeon HD 7570] /0/100/2/0.1 multimedia Turks/Whistler HDMI Audio [Radeon HD 6000 Series] /0/100/5 bridge RD890 PCI to PCI bridge (PCI express gpp port E) /0/100/5/0 bus TUSB73x0 SuperSpeed USB 3.0 xHCI Host Controller /0/100/11 storage SB7x0/SB8x0/SB9x0 SATA Controller [RAID5 mode] /0/100/12 bus SB7x0/SB8x0/SB9x0 USB OHCI0 Controller /0/100/12.2 bus SB7x0/SB8x0/SB9x0 USB EHCI Controller /0/100/13 bus SB7x0/SB8x0/SB9x0 USB OHCI0 Controller /0/100/13.2 bus SB7x0/SB8x0/SB9x0 USB EHCI Controller /0/100/14 bus SBx00 SMBus Controller /0/100/14.2 multimedia SBx00 Azalia (Intel HDA) /0/100/14.3 bridge SB7x0/SB8x0/SB9x0 LPC host controller /0/100/14.4 bridge SBx00 PCI to PCI Bridge /0/100/14.5 bus SB7x0/SB8x0/SB9x0 USB OHCI2 Controller /0/100/15 bridge SB700/SB800/SB900 PCI to PCI bridge (PCIE port 0) /0/100/15.1 bridge SB700/SB800/SB900 PCI to PCI bridge (PCIE port 1) /0/100/15.2 bridge SB900 PCI to PCI bridge (PCIE port 2) /0/100/15.2/0 wlan0 network RT3290 Wireless 802.11n 1T/1R PCIe /0/100/15.2/0.1 generic RT3290 Bluetooth /0/100/15.3 bridge SB900 PCI to PCI bridge (PCIE port 3) /0/100/15.3/0 eth0 network RTL8111/8168/8411 PCI Express Gigabit Ethernet Controller /0/100/16 bus SB7x0/SB8x0/SB9x0 USB OHCI0 Controller /0/100/16.2 bus SB7x0/SB8x0/SB9x0 USB EHCI Controller /0/101 bridge Family 15h Processor Function 0 /0/102 bridge Family 15h Processor Function 1 /0/103 bridge Family 15h Processor Function 2 /0/104 bridge Family 15h Processor Function 3 /0/105 bridge Family 15h Processor Function 4 /0/106 bridge Family 15h Processor Function 5 /0/1 scsi0 storage /0/1/0.0.0 /dev/sda disk 1TB WDC WD1002FAEX-0 /0/1/0.0.0/1 volume 189MiB Windows FAT volume /0/1/0.0.0/2 /dev/sda2 volume 244MiB data partition /0/1/0.0.0/3 /dev/sda3 volume 931GiB LVM Physical Volume /0/2 scsi2 storage /0/2/0.0.0 /dev/cdrom disk DVD A DH16ACSHR /0/3 scsi6 storage /0/3/0.0.0 /dev/sdb disk SCSI Disk /0/3/0.0.1 /dev/sdc disk SCSI Disk /0/3/0.0.2 /dev/sdd disk SCSI Disk /0/3/0.0.3 /dev/sde disk MS/MS-Pro /0/3/0.0.3/0 /dev/sde disk /1 power Standard Efficiency I apologize for my newbness. I hope this is enough info for the hardware. Thanks Bruno for pointing out I needed to add more info. If I am lacking anything else please let me know and I'll post it.

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  • Restructuring a large Chrome Extension/WebApp

    - by A.M.K
    I have a very complex Chrome Extension that has gotten too large to maintain in its current format. I'd like to restructure it, but I'm 15 and this is the first webapp or extension of it's type I've built so I have no idea how to do it. TL;DR: I have a large/complex webapp I'd like to restructure and I don't know how to do it. Should I follow my current restructure plan (below)? Does that sound like a good starting point, or is there a different approach that I'm missing? Should I not do any of the things I listed? While it isn't relevant to the question, the actual code is on Github and the extension is on the webstore. The basic structure is as follows: index.html <html> <head> <link href="css/style.css" rel="stylesheet" /> <!-- This holds the main app styles --> <link href="css/widgets.css" rel="stylesheet" /> <!-- And this one holds widget styles --> </head> <body class="unloaded"> <!-- Low-level base elements are "hardcoded" here, the unloaded class is used for transitions and is removed on load. i.e: --> <div class="tab-container" tabindex="-1"> <!-- Tab nav --> </div> <!-- Templates for all parts of the application and widgets are stored as elements here. I plan on changing these to <script> elements during the restructure since <template>'s need valid HTML. --> <template id="template.toolbar"> <!-- Template content --> </template> <!-- Templates end --> <!-- Plugins --> <script type="text/javascript" src="js/plugins.js"></script> <!-- This contains the code for all widgets, I plan on moving this online and downloading as necessary soon. --> <script type="text/javascript" src="js/widgets.js"></script> <!-- This contains the main application JS. --> <script type="text/javascript" src="js/script.js"></script> </body> </html> widgets.js (initLog || (window.initLog = [])).push([new Date().getTime(), "A log is kept during page load so performance can be analyzed and errors pinpointed"]); // Widgets are stored in an object and extended (with jQuery, but I'll probably switch to underscore if using Backbone) as necessary var Widgets = { 1: { // Widget ID, this is set here so widgets can be retreived by ID id: 1, // Widget ID again, this is used after the widget object is duplicated and detached size: 3, // Default size, medium in this case order: 1, // Order shown in "store" name: "Weather", // Widget name interval: 300000, // Refresh interval nicename: "weather", // HTML and JS safe widget name sizes: ["tiny", "small", "medium"], // Available widget sizes desc: "Short widget description", settings: [ { // Widget setting specifications stored as an array of objects. These are used to dynamically generate widget setting popups. type: "list", nicename: "location", label: "Location(s)", placeholder: "Enter a location and press Enter" } ], config: { // Widget settings as stored in the tabs object (see script.js for storage information) size: "medium", location: ["San Francisco, CA"] }, data: {}, // Cached widget data stored locally, this lets it work offline customFunc: function(cb) {}, // Widgets can optionally define custom functions in any part of their object refresh: function() {}, // This fetches data from the web and caches it locally in data, then calls render. It gets called after the page is loaded for faster loads render: function() {} // This renders the widget only using information from data, it's called on page load. } }; script.js (initLog || (window.initLog = [])).push([new Date().getTime(), "These are also at the end of every file"]); // Plugins, extends and globals go here. i.e. Number.prototype.pad = .... var iChrome = function(refresh) { // The main iChrome init, called with refresh when refreshing to not re-run libs iChrome.Status.log("Starting page generation"); // From now on iChrome.Status.log is defined, it's used in place of the initLog iChrome.CSS(); // Dynamically generate CSS based on settings iChrome.Tabs(); // This takes the tabs stored in the storage (see fetching below) and renders all columns and widgets as necessary iChrome.Status.log("Tabs rendered"); // These will be omitted further along in this excerpt, but they're used everywhere // Checks for justInstalled => show getting started are run here /* The main init runs the bare minimum required to display the page, this sets all non-visible or instantly need things (such as widget dragging) on a timeout */ iChrome.deferredTimeout = setTimeout(function() { iChrome.deferred(refresh); // Pass refresh along, see above }, 200); }; iChrome.deferred = function(refresh) {}; // This calls modules one after the next in the appropriate order to finish rendering the page iChrome.Search = function() {}; // Modules have a base init function and are camel-cased and capitalized iChrome.Search.submit = function(val) {}; // Methods within modules are camel-cased and not capitalized /* Extension storage is async and fetched at the beginning of plugins.js, it's then stored in a variable that iChrome.Storage processes. The fetcher checks to see if processStorage is defined, if it is it gets called, otherwise settings are left in iChromeConfig */ var processStorage = function() { iChrome.Storage(function() { iChrome.Templates(); // Templates are read from their elements and held in a cache iChrome(); // Init is called }); }; if (typeof iChromeConfig == "object") { processStorage(); } Objectives of the restructure Memory usage: Chrome apparently has a memory leak in extensions, they're trying to fix it but memory still keeps on getting increased every time the page is loaded. The app also uses a lot on its own. Code readability: At this point I can't follow what's being called in the code. While rewriting the code I plan on properly commenting everything. Module interdependence: Right now modules call each other a lot, AFAIK that's not good at all since any change you make to one module could affect countless others. Fault tolerance: There's very little fault tolerance or error handling right now. If a widget is causing the rest of the page to stop rendering the user should at least be able to remove it. Speed is currently not an issue and I'd like to keep it that way. How I think I should do it The restructure should be done using Backbone.js and events that call modules (i.e. on storage.loaded = init). Modules should each go in their own file, I'm thinking there should be a set of core files that all modules can rely on and call directly and everything else should be event based. Widget structure should be kept largely the same, but maybe they should also be split into their own files. AFAIK you can't load all templates in a folder, therefore they need to stay inline. Grunt should be used to merge all modules, plugins and widgets into one file. Templates should also all be precompiled. Question: Should I follow my current restructure plan? Does that sound like a good starting point, or is there a different approach that I'm missing? Should I not do any of the things I listed? Do applications written with Backbone tend to be more intensive (memory and speed) than ones written in Vanilla JS? Also, can I expect to improve this with a proper restructure or is my current code about as good as can be expected?

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  • PROUHD: RAID for the end-user

    <b>Linuxconfig:</b> "Therefore, there is currently no storage solution that manages heterogeneous storage devices efficiently. In this article, we propose such a solution and we call it PROUHD (Pool of RAID Over User Heterogeneous Devices)."

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  • Practical PowerShell for SQL Server Developers and DBAs – Part 1

    There is a lot of confusion amongst DBAs about using PowerShell due to existence the deprecated SQLPS mini-shell of SSMS and the newer SQLPS module. In a two-part article and wallchart, Michael Sorens explains how to install it, what it is, and some of the excellent things it has to offer. Compress live data by 73% Red Gate's SQL Storage Compress reduces the size of live SQL Server databases, saving you disk space and storage costs. Learn more.

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  • The Seven Sins against T-SQL Performance

    There are seven common antipatterns in T-SQL coding that make code perform badly, and three good habits which will generally ensure that your code runs fast. If you learn nothing else from this list of great advice from Grant, just keep in mind that you should 'write for the optimizer'. Compress live data by 73% Red Gate's SQL Storage Compress reduces the size of live SQL Server databases, saving you disk space and storage costs. Learn more.

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  • Cleaning Up SQL Server Deployment Scripts

    Although, generally speaking, source control is the truth, a database doesn't quite conform to the ideal because the target schema can, for valid reasons, contain other conflicting truths that can't easily be captured in source control. Dave Ballantyne explains the problems and suggests a solution. Compress live data by 73% Red Gate's SQL Storage Compress reduces the size of live SQL Server databases, saving you disk space and storage costs. Learn more.

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  • Announcement: ZFS Backup Appliance

    - by uwes
    Announcing Product Software Changes for Sun ZFS Backup Appliance Effective December 4th, 2012, Replication and Cloning software licenses are no longer mandatory purchases with Sun ZFS Backup Appliance.   Replication and Cloning are still available as optional additions on new Sun ZFS Backup Appliance quotes, or as additions to existing systems. For More Product Information Go To External: ZFS Storage Appliance Oracle.com page External: ZFS Storage Appliance Oracle Technical Network.com page External: Software download support.oracle.com page

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  • How To Support Multiple SQL Server Package Configurations in SSIS

    I have several applications that use SSIS packages and I want to be able to store all the configurations together in a single table when I deploy. When a package executes I need a way of specifying the "application" and having SSIS automatically handle the package configuration based on the application. Compress live data by 73% Red Gate's SQL Storage Compress reduces the size of live SQL Server databases, saving you disk space and storage costs. Learn more.

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  • Handling Constraint Violations and Errors in SQL Server

    The database developer can, of course, throw all errors back to the application developer to deal with, but this is neither kind nor necessary. How errors are dealt with is dependent on the application, but the process itself isn't entirely obvious. Compress live data by 73% Red Gate's SQL Storage Compress reduces the size of live SQL Server databases, saving you disk space and storage costs. Learn more.

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  • Hassle-free Backup with Deja Dup

    <b>Linux Pro Magazine:</b> "The Dé Dup backup utility may not be the most powerful or flexible backup tool out there, but it does have its advantages. Its straightforward interface makes it dead-easy to configure backups, while the support for the Amazon S3 storage back-end is a boon for users looking for unlimited backup storage on the cheap."

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  • Web Development Resources - A Guide on How to Sell Online

    You need to actualize things. First, you need to look at the budget and choose the right web host for you. This web host is an important resource for you to be able to have a site that will cater your system storage and other things such as uploading and storage keeping. This host site will be very helpful in getting the right steps for the web design you will make as well the complexity of the matter.

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  • LOB Pointer Indexing Proposal

    - by jchang
    My observations are that IO to lob pages (and row overflow pages as well?) is restricted to synchronous IO, which can result in serious problems when these reside on disk drive storage. Even if the storage system is comprised of hundreds of HDDs, the realizable IO performance to lob pages is that of a single disk, with some improvement in parallel execution plans. The reason for this appears to be that each thread must work its way through a page to find the lob pointer information, and then generates...(read more)

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  • SQL SERVER – Integrate Your Data with Skyvia – Cloud ETL Solution

    - by Pinal Dave
    In our days data integration often becomes a key aspect of business success. For business analysts it’s very important to get integrated data from various sources, such as relational databases, cloud CRMs, etc. to make correct and successful decisions. There are various data integration solutions on market, and today I will tell about one of them – Skyvia. Skyvia is a cloud data integration service, which allows integrating data in cloud CRMs and different relational databases. It is a completely online solution and does not require anything except for a browser. Skyvia provides powerful etl tools for data import, export, replication, and synchronization for SQL Server and other databases and cloud CRMs. You can use Skyvia data import tools to load data from various sources to SQL Server (and SQL Azure). Skyvia supports such cloud CRMs as Salesforce and Microsoft Dynamics CRM and such databases as MySQL and PostgreSQL. You even can migrate data from SQL Server to SQL Server, or from SQL Server to other databases and cloud CRMs. Additionally Skyvia supports import of CSV files, either uploaded manually or stored on cloud file storage services, such as Dropbox, Box, Google Drive, or FTP servers. When data import is not enough, Skyvia offers bidirectional data synchronization. With this tool, you can synchronize SQL Server data with other databases and cloud CRMs. After performing the first synchronization, Skyvia tracks data changes in the synchronized data storages. In SQL Server databases (and other relational databases) it creates additional tracking tables and triggers. This allows synchronizing only the changed data. Skyvia also maps records by their primary key values to each other, so it does not require different sources to have the same primary key structure. It still can match the corresponding records without having to add any additional columns or changing data structure. The only requirement for synchronization is that primary keys must be autogenerated. With Skyvia it’s not necessary for data to have the same structure in integrated data storages. Skyvia supports powerful mapping mechanisms that allow synchronizing data with completely different structure. It provides support for complex mathematical and string expressions when mapping data, using lookups, etc. You may use data splitting – loading data from a single CSV file or source table to multiple related target tables. Or you may load data from several source CSV files or tables to several related target tables. In each case Skyvia preserves data relations. It builds corresponding relations between the target data automatically. When you often work with cloud CRM data, native CRM data reporting and analysis tools may be not enough for you. And there is a vast set of professional data analysis and reporting tools available for SQL Server. With Skyvia you can quickly copy your cloud CRM data to an SQL Server database and apply corresponding SQL Server tools to the data. In such case you can use Skyvia data replication tools. It allows you to quickly copy cloud CRM data to SQL Server or other databases without customizing any mapping. You need just to specify columns to copy data from. Target database tables will be created automatically. Skyvia offers powerful filtering settings to replicate only the records you need. Skyvia also provides capability to export data from SQL Server (including SQL Azure) and other databases and cloud CRMs to CSV files. These files can be either downloadable manually or loaded to cloud file storages or FTP server. You can use export, for example, to backup SQL Azure data to Dropbox. Any data integration operation can be scheduled for automatic execution. Thus, you can automate your SQL Azure data backup or data synchronization – just configure it once, then schedule it, and benefit from automatic data integration with Skyvia. Currently registration and using Skyvia is completely free, so you can try it yourself and find out whether its data migration and integration tools suits for you. Visit this link to register on Skyvia: https://app.skyvia.com/register Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Cloud Computing

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  • DATEFROMPARTS

    - by jamiet
    I recently overheard a remark by Greg Low in which he said something akin to "the most interesting parts of a new SQL Server release are the myriad of small things that are in there that make a developer's life easier" (I'm paraphrasing because I can't remember the actual quote but it was something like that). The new DATEFROMPARTS function is a classic example of that . It simply takes three integer parameters and builds a date out of them (if you have used DateSerial in Reporting Services then you'll understand). Take the following code which generates the first and last day of some given years: SELECT 2008 AS Yr INTO #Years UNION ALL SELECT 2009 UNION ALL SELECT 2010 UNION ALL SELECT 2011 UNION ALL SELECT 2012SELECT [FirstDayOfYear] = CONVERT(DATE,CONVERT(CHAR(8),((y.[Yr] * 10000) + 101))),      [LastDayOfYear] = CONVERT(DATE,CONVERT(CHAR(8),((y.[Yr] * 10000) + 1231)))FROM   #Years y here are the results: That code is pretty gnarly though with those CONVERTs in there and, worse, if the character string is constructed in a certain way then it could fail due to localisation, check this out: SET LANGUAGE french;SELECT dt,Month_Name=DATENAME(mm,dt)FROM   (       SELECT  dt = CONVERT(DATETIME,CONVERT(CHAR(4),y.[Yr]) + N'-01-02')       FROM    #Years y       )d;SET LANGUAGE us_english;SELECT dt,Month_Name=DATENAME(mm,dt)FROM   (       SELECT  dt = CONVERT(DATETIME,CONVERT(CHAR(4),y.[Yr]) + N'-01-02')       FROM    #Years y       )d; Notice how the datetime has been converted differently based on the language setting. When French, the string "2012-01-02" gets interpreted as 1st February whereas when us_english the same string is interpreted as 2nd January. Instead of all this CONVERTing nastiness we have DATEFROMPARTS: SELECT [FirstDayOfYear] = DATEFROMPARTS(y.[Yr],1,1),    [LasttDayOfYear] = DATEFROMPARTS(y.[Yr],12,31)FROM   #Years y How much nicer is that? The bad news of course is that you have to upgrade to SQL Server 2012 or migrate to SQL Azure if you want to use it, as is the way of the world! Don't forget that if you want to try this code out on SQL Azure right this second, for free, you can do so by connecting up to AdventureWorks On Azure. You don't even need to have SSMS handy - a browser that runs Silverlight will do just fine. Simply head to https://mhknbn2kdz.database.windows.net/ and use the following credentials: Database AdventureWorks2012 User sqlfamily Password sqlf@m1ly One caveat, SELECT INTO doesn't work on SQL Azure so you'll have to use this instead: DECLARE @y TABLE ( [Yr] INT);INSERT @y([Yr])SELECT 2008 AS Yr UNION ALL SELECT 2009 UNION ALL SELECT 2010 UNION ALL SELECT 2011 UNION ALL SELECT 2012;SELECT [FirstDayOfYear] = DATEFROMPARTS(y.[Yr],1,1),      [LastDayOfYear] = DATEFROMPARTS(y.[Yr],12,31)FROM @y y;SELECT [FirstDayOfYear] = CONVERT(DATE,CONVERT(CHAR(8),((y.[Yr] * 10000) + 101))),      [LastDayOfYear] = CONVERT(DATE,CONVERT(CHAR(8),((y.[Yr] * 10000) + 1231)))FROM @y y; @Jamiet

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  • Cloud Adoption Challenges

    - by Herve Roggero
    Originally posted on: http://geekswithblogs.net/hroggero/archive/2013/11/07/cloud-adoption-challenges.aspxWhile cloud computing makes sense for most organizations and countless projects, I have seen customers significantly struggle with cloud adoption challenges. This blog post is not an attempt to provide a generic assessment of cloud adoption; rather it is an account of personal experiences in the field, some of which may or may not apply to your organization. Cloud First, Burst? In the rush to cloud adoption some companies have made the decision to redesign their core system with a cloud first approach. However a cloud first approach means that the system may not work anymore on-premises after it has been redesigned, specifically if the system depends on Platform as a Service (PaaS) components (such as Azure Tables). While PaaS makes sense when your company is in a position to adopt the cloud exclusively, it can be difficult to leverage with systems that need to work in different clouds or on-premises. As a result, some companies are starting to rethink their cloud strategy by designing for on-premises first, and modify only the necessary components to burst when needed in the cloud. This generally means that the components need to work equally well in any environment, which requires leveraging Infrastructure as a Service (IaaS) or additional investments for PaaS applications, or both.  What’s the Problem? Although most companies can benefit from cloud computing, not all of them can clearly identify a business reason for doing so other than in very generic terms. I heard many companies claim “it’s cheaper”, or “it allows us to scale”, without any specific metric or clear strategy behind the adoption decision. Other companies have a very clear strategy behind cloud adoption and can precisely articulate business benefits, such as “we have a 500% increase in traffic twice a year, so we need to burst in the cloud to avoid doubling our network and server capacity”. Understanding the problem being solved through by adopting cloud computing can significantly help organizations determine the optimum path and timeline to adoption. Performance or Scalability? I stopped counting the number of times I heard “the cloud doesn’t scale; our database runs faster on a laptop”.  While performance and scalability are related concepts, they are nonetheless different in nature. Performance is a measure of response time under a given load (meaning with a specific number of users), while scalability is the performance curve over various loads. For example one system could see great performance with 100 users, but timeout with 1,000 users, in which case the system wouldn’t scale. However another system could have average performance with 100 users, but display the exact same performance with 1,000,000 users, in which case the system would scale. Understanding that cloud computing does not usually provide high performance, but instead provides the tools necessary to build a scalable system (usually using PaaS services such as queuing and data federation), is fundamental to proper cloud adoption. Uptime? Last but not least, you may want to read the Service Level Agreement of your cloud provider in detail if you haven’t done so. If you are expecting 99.99% uptime annually you may be in for a surprise. Depending on the component being used, there may be no associated SLA at all! Other components may be restarted at any time, or services may experience failover conditions weekly ( or more) based on current overall conditions of the cloud service provider, most of which are outside of your control. As a result, for PaaS cloud environments (and to a certain extent some IaaS systems), applications need to assume failure and gracefully retry to be successful in the cloud in order to provide service continuity to end users. About Herve Roggero Herve Roggero, Windows Azure MVP, is the founder of Blue Syntax Consulting (http://www.bluesyntax.net). Herve's experience includes software development, architecture, database administration and senior management with both global corporations and startup companies. Herve holds multiple certifications, including an MCDBA, MCSE, MCSD. He also holds a Master's degree in Business Administration from Indiana University. Herve is the co-author of "PRO SQL Azure" and “PRO SQL Server 2012 Practices” from Apress, a PluralSight author, and runs the Azure Florida Association.

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  • Exchange ActiveSync Exception

    - by Dmeglio
    One of the users on my network is having an issue with his iPhone syncing via ActiveSync. Overall it's working, but every now and then he gets a "Synchronization with your iPhone failed for 3 items." I asked him to go into OWA and turn on the Mobile Phone logging. I looked through the logs and this is what stood out to me: SyncCommand_GenerateResponsesXmlNode_AddChange_Exception : Microsoft.Exchange.Data.Storage.PropertyErrorException: Property: [{00062008-0000-0000-c000-000000000046}:0x8501] ReminderMinutesBeforeStartInternal, PropertyErrorCode: NotFound, PropertyErrorDescription: . at Microsoft.Exchange.Data.Storage.PropertyBag.ThrowIfPropertyError(StorePropertyDefinition propertyDefinition, Object propertyValue) at Microsoft.Exchange.Data.Storage.StoreObject.GetProperty(PropertyDefinition propertyDefinition) at Microsoft.Exchange.Data.Storage.MeetingMessage.get_Item(PropertyDefinition propertyDefinition) at Microsoft.Exchange.AirSync.SchemaConverter.XSO.XsoMeetingRequestProperty.get_NestedData() at Microsoft.Exchange.AirSync.SchemaConverter.AirSync.AirSyncMeetingRequestProperty.InternalCopyFrom(IProperty srcProperty) at Microsoft.Exchange.AirSync.SchemaConverter.AirSync.AirSyncProperty.CopyFrom(IProperty srcProperty) at Microsoft.Exchange.AirSync.SchemaConverter.AirSync.AirSyncDataObject.CopyFrom(IProperty srcRootProperty) at Microsoft.Exchange.AirSync.SyncCollection.ConvertServerToClientObject(ISyncItem syncItem, XmlNode airSyncParentNode, SyncOperation changeObject) at Microsoft.Exchange.AirSync.SyncCollection.GenerateCommandsXmlNode(XmlDocument xmlResponse, IAirSyncVersionFactory versionFactory, String deviceType, ProtocolLogger protocolLogger, MailboxLogger mailboxLogger) Does anyone have any idea what might cause this? We have 4 iPhone users connected to our Exchange via ActiveSync. Right now, this seems to be the only user experiencing this issue. I'd appreciate any help anyone can provide. Thanks.

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  • "postgres blocked for more than 120 seconds" - is my db still consistent?

    - by nn4l
    I am using an iscsi volume on an Open-E storage system for several virtual machines running on a XenServer host. Occasionally, when there is a very high disk I/O load on the virtual machines (and therefore also on the storage system), I got this error message on the vm consoles: [2594520.161701] INFO: task kjournald:117 blocked for more than 120 seconds. [2594520.161787] "echo 0 > /proc/sys/kernel/hung_task_timeout_secs" disables this message. [2594520.162194] INFO: task flush-202:0:229 blocked for more than 120 seconds. [2594520.162274] "echo 0 > /proc/sys/kernel/hung_task_timeout_secs" disables this message. [2594520.162801] INFO: task postgres:1567 blocked for more than 120 seconds. [2594520.162882] "echo 0 > /proc/sys/kernel/hung_task_timeout_secs" disables this message. I understand this error message is caused by the kernel to inform that these processes haven't been run for 120 seconds, most likely because a disk access to the storage system has not yet been processed. But what is the effect on the processes. For example, will the postgres process eventually write its data when the storage system is idle again after a few minutes, so that all data is still consistent? Or will it abort the write, leaving some tables in an inconsistent state? I certainly expect that the former should be the case - if the disk access is slow, postgres (or any other affected process) should just wait as long as it takes. I can live with the application hanging for a few minutes. But if there is a chance for data corruption then any of these errors is really bad news. Please advise what to do here.

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