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  • Using Oracle Database's 11gR2 New ASM Features During ASM Migration

    Oracle Database 11gR2 offers several new Automatic Storage Management features for managing both Oracle database files as well as files stored within its new ASM Clustered File System. This article illustrates how to upgrade an Oracle database quickly and efficiently from version 11gR1 to 11gR2 and then migrate all of its database files so they&#146;re resident within ASM-managed storage.

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  • Initial Look: Storing SQL Compact Data on a Windows Phone 7 Series

    - by Nikita Polyakov
    Ok, the title is misleading – I’ll admit it, but there is a way to store your data in Windows Phone 7 Series. Windows Phone 7 Silverlight solutions have what is called Isolated Storage. [XNA has content storage as well] At this time there is no port of SQL Compact engine for Silverlight Isolated Storage. There is no wind of such intention. [That was a question way before WP7 was even rumored to have Silverlight.] There a few options: 1. Microsoft recommends you “simply” use client-server or cloud approach here. But this is not an option for Offline. 2. Use the new Offline/CacheMode with Sync Framework as shown in the Building Offline Web Apps Using Microsoft Sync Framework MIX10 presentation see 19:10 for Silverlight portion [go to 22:10 mark to see the app]. 3. Use XlmSerializer to dumb your objects to a XML file into the Isolated Storage. Good for small data. 4. Experiment with C#SQLite for Silverlight that has been shown to work in WP7 emulator, read more. 5. Roll your own file format and read/write from it. Think good ol’ CSV. Good for when you want 1million row table ;)   Is Microsoft aware of this possible limitation? Yes. What are they doing about it? I don’t know. See #1 and #2 above as the official guidance for now. What should you do about it? Don’t be too quick to dismiss WP7 because you think you’ll “need” SQL Compact. As lot of us will be playing with these possible solutions, I will be sure to update you on further discoveries. Remember that the tools [even the emulator] released at MIX are CTP grade and might not have all the features. Stay up to date: Watch the @wp7dev account if you are on Twitter. And watch the Windows Phone Dev Website and Blog. More information and detail is sure to come about WP7 Dev, as Windows Phone is planned to launch “Holidays” 2010. [For example Office will be discussed in June from the latest news, June is TechEd 2010 timeframe btw]

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  • World Record Performance on PeopleSoft Enterprise Financials Benchmark on SPARC T4-2

    - by Brian
    Oracle's SPARC T4-2 server achieved World Record performance on Oracle's PeopleSoft Enterprise Financials 9.1 executing 20 Million Journals lines in 8.92 minutes on Oracle Database 11g Release 2 running on Oracle Solaris 11. This is the first result published on this version of the benchmark. The SPARC T4-2 server was able to process 20 million general ledger journal edit and post batch jobs in 8.92 minutes on this benchmark that reflects a large customer environment that utilizes a back-end database of nearly 500 GB. This benchmark demonstrates that the SPARC T4-2 server with PeopleSoft Financials 9.1 can easily process 100 million journal lines in less than 1 hour. The SPARC T4-2 server delivered more than 146 MB/sec of IO throughput with Oracle Database 11g running on Oracle Solaris 11. Performance Landscape Results are presented for PeopleSoft Financials Benchmark 9.1. Results obtained with PeopleSoft Financials Benchmark 9.1 are not comparable to the the previous version of the benchmark, PeopleSoft Financials Benchmark 9.0, due to significant change in data model and supports only batch. PeopleSoft Financials Benchmark, Version 9.1 Solution Under Test Batch (min) SPARC T4-2 (2 x SPARC T4, 2.85 GHz) 8.92 Results from PeopleSoft Financials Benchmark 9.0. PeopleSoft Financials Benchmark, Version 9.0 Solution Under Test Batch (min) Batch with Online (min) SPARC Enterprise M4000 (Web/App) SPARC Enterprise M5000 (DB) 33.09 34.72 SPARC T3-1 (Web/App) SPARC Enterprise M5000 (DB) 35.82 37.01 Configuration Summary Hardware Configuration: 1 x SPARC T4-2 server 2 x SPARC T4 processors, 2.85 GHz 128 GB memory Storage Configuration: 1 x Sun Storage F5100 Flash Array (for database and redo logs) 2 x Sun Storage 2540-M2 arrays and 2 x Sun Storage 2501-M2 arrays (for backup) Software Configuration: Oracle Solaris 11 11/11 SRU 7.5 Oracle Database 11g Release 2 (11.2.0.3) PeopleSoft Financials 9.1 Feature Pack 2 PeopleSoft Supply Chain Management 9.1 Feature Pack 2 PeopleSoft PeopleTools 8.52 latest patch - 8.52.03 Oracle WebLogic Server 10.3.5 Java Platform, Standard Edition Development Kit 6 Update 32 Benchmark Description The PeopleSoft Enterprise Financials 9.1 benchmark emulates a large enterprise that processes and validates a large number of financial journal transactions before posting the journal entry to the ledger. The validation process certifies that the journal entries are accurate, ensuring that ChartFields values are valid, debits and credits equal out, and inter/intra-units are balanced. Once validated, the entries are processed, ensuring that each journal line posts to the correct target ledger, and then changes the journal status to posted. In this benchmark, the Journal Edit & Post is set up to edit and post both Inter-Unit and Regular multi-currency journals. The benchmark processes 20 million journal lines using AppEngine for edits and Cobol for post processes. See Also Oracle PeopleSoft Benchmark White Papers oracle.com SPARC T4-2 Server oracle.com OTN PeopleSoft Financial Management oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 1 October 2012.

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  • Azure Flavor for the Sharepoint Media Component

    - by spano
    Some time ago I wrote about a Media Processing Component for Sharepoint that I was working on. It is a Media Assets list for Sharepoint that lets you choose where to store the blob files. It provides also intelligence for encoding videos, generating thumbnail and poster images, obtaining media metadata, etc. On that first post the component was explained in detail, with the original 3 storage flavors: Sharepoint list, Virtual Directoy or FTP. The storage manager is extensible, so a new flavor was...(read more)

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  • Overview of the IBM BladeCenter

    IBM BladeCenter switches provide the small to mid size business with a number of tactical advantages. Companies can increase storage efficiency by permitting a sharing of disc storage across multiple... [Author: Bob Wall Jr. - Computers and Internet - April 10, 2010]

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  • Customer Support Spotlight: Clemson University

    - by cwarticki
    I've begun a Customer Support Spotlight series that highlights our wonderful customers and Oracle loyalists.  A week ago I visited Clemson University.  As I travel to visit and educate our customers, I provide many useful tips/tricks and support best practices (as found on my blog and twitter). Most of all, I always discover an Oracle gem who deserves recognition for their hard work and advocacy. Meet George Manley.  George is a Storage Engineer who has worked in Clemson's Data Center all through college, partially in the Hardware Architecture group and partially in the Storage group. George and the rest of the Storage Team work with most all of the storage technologies that they have here at Clemson. This includes a wide array of different vendors' disk arrays, with the most of them being Oracle/Sun 2540's.  He also works with SAM/QFS, ACSLS, and our SL8500 Tape Libraries (all three Oracle/Sun products). (pictured L to R, Matt Schoger (Oracle), Mark Flores (Oracle) and George Manley) George was kind enough to take us for a data center tour.  It was amazing.  I rarely get to see the inside of data centers, and this one was massive. Clemson Computing and Information Technology’s physical resources include the main data center located in the Information Technology Center at the Innovation Campus and Technology Park. The core of Clemson’s computing infrastructure, the data center has 21,000 sq ft of raised floor and is powered by a 14MW substation. The ITC power capacity is 4.5MW.  The data center is the home of both enterprise and HPC systems, and is staffed by CCIT staff on a 24 hour basis from a state of the art network operations center within the ITC. A smaller business continuance data center is located on the main campus.  The data center serves a wide variety of purposes including HPC (supercomputing) resources which are shared with other Universities throughout the state, the state's medicaid processing system, and nearly all other needs for Clemson University. Yes, that's no typo (14,256 cores and 37TB of memory!!! Thanks for the tour George and thank you very much for your time.  The tour was fantastic. I enjoyed getting to know your team and I look forward to many successes from Clemson using Oracle products. -Chris WartickiGlobal Customer Management

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  • Nouvelle certification sur le système de stockage New Certification Pillar Axiom 600

    - by swalker
    Vous pouvez dès à présent passer l'examen Pillar Axiom 600 Storage System Essentials (1Z0-581) en version bêta. Décrochez cet examen pour devenir Spécialiste de l'implémentation des systèmes de stockage Pillar Axiom 600. Les partenaires Oracle peuvent bénéficier de bons gratuits ! Si vous souhaitez recevoir un bon gratuit pour l’examen bêta, veuillez envoyer votre demande à l’adresse [email protected] sans oublier de préciser votre nom, votre adresse email professionnelle, le nom de votre société ainsi que le nom de l'examen : Examen Pillar Axiom 600 Storage System Essentials Beta.

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  • Creating a Simple PHP Blog in Azure

    - by Josh Holmes
    In this post, I want to walk through creating a simple Azure application that will show a few pages, leverage Blob storage, Table storage and generally get you started doing PHP on Azure development. In short, we are going to write a very simple PHP Blog engine for Azure. To be very clear, this is not a pro blog engine and I don’t recommend using it in production. It’s a » read more.

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  • Best partition Scheme for Ubuntu Server

    - by K.K Patel
    I am going to deploy Ubuntu server having Following servers on it Bind server, dhcp server, LAMP Server, Openssh Server, Ldap server, Monodb database, FTP server,mail server, Samba server, NFS server , in future I want to set Openstack for PAAS. Currently I have Raid 5 with 10TB. How should I make my Partition Scheme So never get problem in future and easily expand Storage size. Suggest me such a partition Scheme with giving specific percentage of Storage to partitions like /, /boot, /var, /etc. Thanks In advance

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  • Cost Comparison Hard Disk Drive to Solid State Drive on Price per Gigabyte - dispelling a myth!

    - by tonyrogerson
    It is often said that Hard Disk Drive storage is significantly cheaper per GiByte than Solid State Devices – this is wholly inaccurate within the database space. People need to look at the cost of the complete solution and not just a single component part in isolation to what is really required to meet the business requirement. Buying a single Hitachi Ultrastar 600GB 3.5” SAS 15Krpm hard disk drive will cost approximately £239.60 (http://scan.co.uk, 22nd March 2012) compared to an OCZ 600GB Z-Drive R4 CM84 PCIe costing £2,316.54 (http://scan.co.uk, 22nd March 2012); I’ve not included FusionIO ioDrive because there is no public pricing available for it – something I never understand and personally when companies do this I immediately think what are they hiding, luckily in FusionIO’s case the product is proven though is expensive compared to OCZ enterprise offerings. On the face of it the single 15Krpm hard disk has a price per GB of £0.39, the SSD £3.86; this is what you will see in the press and this is what sales people will use in comparing the two technologies – do not be fooled by this bullshit people! What is the requirement? The requirement is the database will have a static size of 400GB kept static through archiving so growth and trim will balance the database size, the client requires resilience, there will be several hundred call centre staff querying the database where queries will read a small amount of data but there will be no hot spot in the data so the randomness will come across the entire 400GB of the database, estimates predict that the IOps required will be approximately 4,000IOps at peak times, because it’s a call centre system the IO latency is important and must remain below 5ms per IO. The balance between read and write is 70% read, 30% write. The requirement is now defined and we have three of the most important pieces of the puzzle – space required, estimated IOps and maximum latency per IO. Something to consider with regard SQL Server; write activity requires synchronous IO to the storage media specifically the transaction log; that means the write thread will wait until the IO is completed and hardened off until the thread can continue execution, the requirement has stated that 30% of the system activity will be write so we can expect a high amount of synchronous activity. The hardware solution needs to be defined; two possible solutions: hard disk or solid state based; the real question now is how many hard disks are required to achieve the IO throughput, the latency and resilience, ditto for the solid state. Hard Drive solution On a test on an HP DL380, P410i controller using IOMeter against a single 15Krpm 146GB SAS drive, the throughput given on a transfer size of 8KiB against a 40GiB file on a freshly formatted disk where the partition is the only partition on the disk thus the 40GiB file is on the outer edge of the drive so more sectors can be read before head movement is required: For 100% sequential IO at a queue depth of 16 with 8 worker threads 43,537 IOps at an average latency of 2.93ms (340 MiB/s), for 100% random IO at the same queue depth and worker threads 3,733 IOps at an average latency of 34.06ms (34 MiB/s). The same test was done on the same disk but the test file was 130GiB: For 100% sequential IO at a queue depth of 16 with 8 worker threads 43,537 IOps at an average latency of 2.93ms (340 MiB/s), for 100% random IO at the same queue depth and worker threads 528 IOps at an average latency of 217.49ms (4 MiB/s). From the result it is clear random performance gets worse as the disk fills up – I’m currently writing an article on short stroking which will cover this in detail. Given the work load is random in nature looking at the random performance of the single drive when only 40 GiB of the 146 GB is used gives near the IOps required but the latency is way out. Luckily I have tested 6 x 15Krpm 146GB SAS 15Krpm drives in a RAID 0 using the same test methodology, for the same test above on a 130 GiB for each drive added the performance boost is near linear, for each drive added throughput goes up by 5 MiB/sec, IOps by 700 IOps and latency reducing nearly 50% per drive added (172 ms, 94 ms, 65 ms, 47 ms, 37 ms, 30 ms). This is because the same 130GiB is spread out more as you add drives 130 / 1, 130 / 2, 130 / 3 etc. so implicit short stroking is occurring because there is less file on each drive so less head movement required. The best latency is still 30 ms but we have the IOps required now, but that’s on a 130GiB file and not the 400GiB we need. Some reality check here: a) the drive randomness is more likely to be 50/50 and not a full 100% but the above has highlighted the effect randomness has on the drive and the more a drive fills with data the worse the effect. For argument sake let us assume that for the given workload we need 8 disks to do the job, for resilience reasons we will need 16 because we need to RAID 1+0 them in order to get the throughput and the resilience, RAID 5 would degrade performance. Cost for hard drives: 16 x £239.60 = £3,833.60 For the hard drives we will need disk controllers and a separate external disk array because the likelihood is that the server itself won’t take the drives, a quick spec off DELL for a PowerVault MD1220 which gives the dual pathing with 16 disks 146GB 15Krpm 2.5” disks is priced at £7,438.00, note its probably more once we had two controller cards to sit in the server in, racking etc. Minimum cost taking the DELL quote as an example is therefore: {Cost of Hardware} / {Storage Required} £7,438.60 / 400 = £18.595 per GB £18.59 per GiB is a far cry from the £0.39 we had been told by the salesman and the myth. Yes, the storage array is composed of 16 x 146 disks in RAID 10 (therefore 8 usable) giving an effective usable storage availability of 1168GB but the actual storage requirement is only 400 and the extra disks have had to be purchased to get the  IOps up. Solid State Drive solution A single card significantly exceeds the IOps and latency required, for resilience two will be required. ( £2,316.54 * 2 ) / 400 = £11.58 per GB With the SSD solution only two PCIe sockets are required, no external disk units, no additional controllers, no redundant controllers etc. Conclusion I hope by showing you an example that the myth that hard disk drives are cheaper per GiB than Solid State has now been dispelled - £11.58 per GB for SSD compared to £18.59 for Hard Disk. I’ve not even touched on the running costs, compare the costs of running 18 hard disks, that’s a lot of heat and power compared to two PCIe cards!Just a quick note: I've left a fair amount of information out due to this being a blog! If in doubt, email me :)I'll also deal with the myth that SSD's wear out at a later date as well - that's just way over done still, yes, 5 years ago, but now - no.

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  • Windows Azure Recipe: Big Data

    - by Clint Edmonson
    As the name implies, what we’re talking about here is the explosion of electronic data that comes from huge volumes of transactions, devices, and sensors being captured by businesses today. This data often comes in unstructured formats and/or too fast for us to effectively process in real time. Collectively, we call these the 4 big data V’s: Volume, Velocity, Variety, and Variability. These qualities make this type of data best managed by NoSQL systems like Hadoop, rather than by conventional Relational Database Management System (RDBMS). We know that there are patterns hidden inside this data that might provide competitive insight into market trends.  The key is knowing when and how to leverage these “No SQL” tools combined with traditional business such as SQL-based relational databases and warehouses and other business intelligence tools. Drivers Petabyte scale data collection and storage Business intelligence and insight Solution The sketch below shows one of many big data solutions using Hadoop’s unique highly scalable storage and parallel processing capabilities combined with Microsoft Office’s Business Intelligence Components to access the data in the cluster. Ingredients Hadoop – this big data industry heavyweight provides both large scale data storage infrastructure and a highly parallelized map-reduce processing engine to crunch through the data efficiently. Here are the key pieces of the environment: Pig - a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs. Mahout - a machine learning library with algorithms for clustering, classification and batch based collaborative filtering that are implemented on top of Apache Hadoop using the map/reduce paradigm. Hive - data warehouse software built on top of Apache Hadoop that facilitates querying and managing large datasets residing in distributed storage. Directly accessible to Microsoft Office and other consumers via add-ins and the Hive ODBC data driver. Pegasus - a Peta-scale graph mining system that runs in parallel, distributed manner on top of Hadoop and that provides algorithms for important graph mining tasks such as Degree, PageRank, Random Walk with Restart (RWR), Radius, and Connected Components. Sqoop - a tool designed for efficiently transferring bulk data between Apache Hadoop and structured data stores such as relational databases. Flume - a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large log data amounts to HDFS. Database – directly accessible to Hadoop via the Sqoop based Microsoft SQL Server Connector for Apache Hadoop, data can be efficiently transferred to traditional relational data stores for replication, reporting, or other needs. Reporting – provides easily consumable reporting when combined with a database being fed from the Hadoop environment. Training These links point to online Windows Azure training labs where you can learn more about the individual ingredients described above. Hadoop Learning Resources (20+ tutorials and labs) Huge collection of resources for learning about all aspects of Apache Hadoop-based development on Windows Azure and the Hadoop and Windows Azure Ecosystems SQL Azure (7 labs) Microsoft SQL Azure delivers on the Microsoft Data Platform vision of extending the SQL Server capabilities to the cloud as web-based services, enabling you to store structured, semi-structured, and unstructured data. See my Windows Azure Resource Guide for more guidance on how to get started, including links web portals, training kits, samples, and blogs related to Windows Azure.

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  • Neo4J and Azure and VS2012 and Windows 8

    - by Chris Skardon
    Now, I know that this has been written about, but both of the main places (http://www.richard-banks.org/2011/02/running-neo4j-on-azure.html and http://blog.neo4j.org/2011/02/announcing-neo4j-on-windows-azure.html) utilise VS2010, and well, I’m on VS2012 and Windows 8. Not that I think Win 8 had anything to do with it really, anyhews! I’m going to begin from the beginning, this is my first foray into running something on Azure, so it’s been a bit of a learning curve. But luckily the Neo4J guys have got us started, so let’s download the VS2010 solution: http://neo4j.org/get?file=Neo4j.Azure.Server.zip OK, the other thing we’ll need is the VS2012 Azure SDK, so let’s get that as well: http://www.windowsazure.com/en-us/develop/downloads/ (I just did the full install). Now, unzip the VS2010 solution and let’s open it in VS2012: <your location>\Neo4j.Azure.Server\Neo4j.Azure.Server.sln One-way-upgrade? Yer! Ignore the migration report – we don’t care! Let’s build that sucker… Ahhh 14 errors… WindowsAzure does not exist in the namespace ‘Microsoft’ Not a problem right? We’ve installed the SDK, just need to update the references: We can ignore the Test projects, they don’t use Azure, we’re interested in the other projects, so what we’ll do is remove the broken references, and add the correct ones, so expand the references bit of each project: hunt out those yellow exclamation marks, and delete them! You’ll need to add the right ones back in (listed below), when you go to the ‘Add Reference’ dialog make sure you have ‘Assemblies’ and ‘Framework’ selected before you seach (and search for ‘microsoft.win’ to narrow it down) So the references you need for each project are: CollectDiagnosticsData Microsoft.WindowsAzure.Diagnostics Microsoft.WindowsAzure.StorageClient Diversify.WindowsAzure.ServiceRuntime Microsoft.WindowsAzure.CloudDrive Microsoft.WindowsAzure.ServiceRuntime Microsoft.WindowsAzure.StorageClient Right, so let’s build again… Sweet! No errors.   Now we need to setup our Blobs, I’m assuming you are using the most up-to-date Java you happened to have downloaded :) in my case that’s JRE7, and that is located in: C:\Program Files (x86)\Java\jre7 So, zip up that folder into whatever you want to call it, I went with jre7.zip, and stuck it in a temp folder for now. In that same temp folder I also copied the neo4j zip I was using: neo4j-community-1.7.2-windows.zip OK, now, we need to get these into our Blob storage, this is where a lot of stuff becomes unstuck - I didn’t find any applications that helped me use the blob storage, one would crash (because my internet speed is so slow) and the other just didn’t work – sure it looked like it had worked, but when push came to shove it didn’t. So this is how I got my files into Blob (local first): 1. Run the ‘Storage Emulator’ (just search for that in the start menu) 2. That takes a little while to start up so fire up another instance of Visual Studio in the mean time, and create a new Console Application. 3. Manage Nuget Packages for that solution and add ‘Windows Azure Storage’ Now you’re set up to add the code: public static void Main() { CloudStorageAccount cloudStorageAccount = CloudStorageAccount.DevelopmentStorageAccount; CloudBlobClient client = cloudStorageAccount.CreateCloudBlobClient(); client.Timeout = TimeSpan.FromMinutes(30); CloudBlobContainer container = client.GetContainerReference("neo4j"); //This will create it as well   UploadBlob(container, "jre7.zip", "c:\\temp\\jre7.zip"); UploadBlob(container, "neo4j-community-1.7.2-windows.zip", "c:\\temp\\neo4j-community-1.7.2-windows.zip"); }   private static void UploadBlob(CloudBlobContainer container, string blobName, string filename) { CloudBlob blob = container.GetBlobReference(blobName);   using (FileStream fileStream = File.OpenRead(filename)) blob.UploadFromStream(fileStream); } This will upload the files to your local storage account (to switch to an Azure one, you’ll need to create a storage account, and use those credentials when you make your CloudStorageAccount above) To test you’ve got them uploaded correctly, go to: http://localhost:10000/devstoreaccount1/neo4j/jre7.zip and you will hopefully download the zip file you just uploaded. Now that those files are there, we are ready for some final configuration… Right click on the Neo4jServerHost role in the Neo4j.Azure.Server cloud project: Click on the ‘Settings’ tab and we’ll need to do some changes – by default, the 1.7.2 edition of neo4J unzips to: neo4j-community-1.7.2 So, we need to update all the ‘neo4j-1.3.M02’ directories to be ‘neo4j-community-1.7.2’, we also need to update the Java runtime location, so we start with this: and end with this: Now, I also changed the Endpoints settings, to be HTTP (from TCP) and to have a port of 7410 (mainly because that’s straight down on the numpad) The last ‘gotcha’ is some hard coded consts, which had me looking for ages, they are in the ‘ConfigSettings’ class of the ‘Neo4jServerHost’ project, and the ones we’re interested in are: Neo4jFileName JavaZipFileName Change those both to what that should be. OK Nearly there (I promise)! Run the ‘Compute Emulator’ (same deal with the Start menu), in your system tray you should have an Azure icon, when the compute emulator is up and running, right click on the icon and select ‘Show Compute Emulator UI’ The last steps! Make sure the ‘Neo4j.Azure.Server’ cloud project is set up as the start project and let’s hit F5 tension mounts, the build takes place (you need to accept the UAC warning) and VS does it’s stuff. If you look at the Compute Emulator UI you’ll see some log stuff (which you’ll need if this goes awry – but it won’t don’t worry!) In a bit, the console and a Java window will pop up: Then the console will bog off, leaving just the Java one, and if we switch back to the Compute Emulator UI and scroll up we should be able to see a line telling us the port number we’ve been assigned (in my case 7411): (If you can’t see it, don’t worry.. press CTRL+A on the emulator, then CTRL+C, copy all the text and paste it into something like Notepad, then just do a Find for ‘port’ you’ll soon see it) Go to your favourite browser, and head to: http://localhost:YOURPORT/ and you should see the WebAdmin! See you on the cloud side hopefully! Chris PS Other gotchas! OK, I’ve been caught out a couple of times: I had an instance of Neo4J running as a service on my machine, the Azure instance wanted to run the https version of the server on the same port as the Service was running on, and so Java would complain that the port was already in use.. The first time I converted the project, it didn’t update the version of the Azure library to load, in the App.Config of the Neo4jServerHost project, and VS would throw an exception saying it couldn’t find the Azure dll version 1.0.0.0.

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  • Using the jQuery UI Library in a MVC 3 Application to Build a Dialog Form

    - by ChrisD
    Using a simulated dialog window is a nice way to handle inline data editing. The jQuery UI has a UI widget for a dialog window that makes it easy to get up and running with it in your application. With the release of ASP.NET MVC 3, Microsoft included the jQuery UI scripts and files in the MVC 3 project templates for Visual Studio. With the release of the MVC 3 Tools Update, Microsoft implemented the inclusion of those with NuGet as packages. That means we can get up and running using the latest version of the jQuery UI with minimal effort. To the code! Another that might interested you about JQuery Mobile and ASP.NET MVC 3 with C#. If you are starting with a new MVC 3 application and have the Tools Update then you are a NuGet update and a <link> and <script> tag away from adding the jQuery UI to your project. If you are using an existing MVC project you can still get the jQuery UI library added to your project via NuGet and then add the link and script tags. Assuming that you have pulled down the latest version (at the time of this publish it was 1.8.13) you can add the following link and script tags to your <head> tag: < link href = "@Url.Content(" ~ / Content / themes / base / jquery . ui . all . css ")" rel = "Stylesheet" type = "text/css" /> < script src = "@Url.Content(" ~ / Scripts / jquery-ui-1 . 8 . 13 . min . js ")" type = "text/javascript" ></ script > The jQuery UI library relies upon the CSS scripts and some image files to handle rendering of its widgets (you can choose a different theme or role your own if you like). Adding these to the stock _Layout.cshtml file results in the following markup: <!DOCTYPE html> < html > < head >     < meta charset = "utf-8" />     < title > @ViewBag.Title </ title >     < link href = "@Url.Content(" ~ / Content / Site . css ")" rel = "stylesheet" type = "text/css" />     <link href="@Url.Content("~/Content/themes/base/jquery.ui.all.css")" rel="Stylesheet" type="text/css" />     <script src="@Url.Content("~/Scripts/jquery-1.5.1.min.js")" type="text/javascript"></script>     <script src="@Url.Content("~/Scripts/modernizr-1.7.min . js ")" type = "text/javascript" ></ script >     < script src = "@Url.Content(" ~ / Scripts / jquery-ui-1 . 8 . 13 . min . js ")" type = "text/javascript" ></ script > </ head > < body >     @RenderBody() </ body > </ html > Our example will involve building a list of notes with an id, title and description. Each note can be edited and new notes can be added. The user will never have to leave the single page of notes to manage the note data. The add and edit forms will be delivered in a jQuery UI dialog widget and the note list content will get reloaded via an AJAX call after each change to the list. To begin, we need to craft a model and a data management class. We will do this so we can simulate data storage and get a feel for the workflow of the user experience. The first class named Note will have properties to represent our data model. namespace Website . Models {     public class Note     {         public int Id { get ; set ; }         public string Title { get ; set ; }         public string Body { get ; set ; }     } } The second class named NoteManager will be used to set up our simulated data storage and provide methods for querying and updating the data. We will take a look at the class content as a whole and then walk through each method after. using System . Collections . ObjectModel ; using System . Linq ; using System . Web ; namespace Website . Models {     public class NoteManager     {         public Collection < Note > Notes         {             get             {                 if ( HttpRuntime . Cache [ "Notes" ] == null )                     this . loadInitialData ();                 return ( Collection < Note >) HttpRuntime . Cache [ "Notes" ];             }         }         private void loadInitialData ()         {             var notes = new Collection < Note >();             notes . Add ( new Note                           {                               Id = 1 ,                               Title = "Set DVR for Sunday" ,                               Body = "Don't forget to record Game of Thrones!"                           });             notes . Add ( new Note                           {                               Id = 2 ,                               Title = "Read MVC article" ,                               Body = "Check out the new iwantmymvc.com post"                           });             notes . Add ( new Note                           {                               Id = 3 ,                               Title = "Pick up kid" ,                               Body = "Daughter out of school at 1:30pm on Thursday. Don't forget!"                           });             notes . Add ( new Note                           {                               Id = 4 ,                               Title = "Paint" ,                               Body = "Finish the 2nd coat in the bathroom"                           });             HttpRuntime . Cache [ "Notes" ] = notes ;         }         public Collection < Note > GetAll ()         {             return Notes ;         }         public Note GetById ( int id )         {             return Notes . Where ( i => i . Id == id ). FirstOrDefault ();         }         public int Save ( Note item )         {             if ( item . Id <= 0 )                 return saveAsNew ( item );             var existingNote = Notes . Where ( i => i . Id == item . Id ). FirstOrDefault ();             existingNote . Title = item . Title ;             existingNote . Body = item . Body ;             return existingNote . Id ;         }         private int saveAsNew ( Note item )         {             item . Id = Notes . Count + 1 ;             Notes . Add ( item );             return item . Id ;         }     } } The class has a property named Notes that is read only and handles instantiating a collection of Note objects in the runtime cache if it doesn't exist, and then returns the collection from the cache. This property is there to give us a simulated storage so that we didn't have to add a full blown database (beyond the scope of this post). The private method loadInitialData handles pre-filling the collection of Note objects with some initial data and stuffs them into the cache. Both of these chunks of code would be refactored out with a move to a real means of data storage. The GetAll and GetById methods access our simulated data storage to return all of our notes or a specific note by id. The Save method takes in a Note object, checks to see if it has an Id less than or equal to zero (we assume that an Id that is not greater than zero represents a note that is new) and if so, calls the private method saveAsNew . If the Note item sent in has an Id , the code finds that Note in the simulated storage, updates the Title and Description , and returns the Id value. The saveAsNew method sets the Id , adds it to the simulated storage, and returns the Id value. The increment of the Id is simulated here by getting the current count of the note collection and adding 1 to it. The setting of the Id is the only other chunk of code that would be refactored out when moving to a different data storage approach. With our model and data manager code in place we can turn our attention to the controller and views. We can do all of our work in a single controller. If we use a HomeController , we can add an action method named Index that will return our main view. An action method named List will get all of our Note objects from our manager and return a partial view. We will use some jQuery to make an AJAX call to that action method and update our main view with the partial view content returned. Since the jQuery AJAX call will cache the call to the content in Internet Explorer by default (a setting in jQuery), we will decorate the List, Create and Edit action methods with the OutputCache attribute and a duration of 0. This will send the no-cache flag back in the header of the content to the browser and jQuery will pick that up and not cache the AJAX call. The Create action method instantiates a new Note model object and returns a partial view, specifying the NoteForm.cshtml view file and passing in the model. The NoteForm view is used for the add and edit functionality. The Edit action method takes in the Id of the note to be edited, loads the Note model object based on that Id , and does the same return of the partial view as the Create method. The Save method takes in the posted Note object and sends it to the manager to save. It is decorated with the HttpPost attribute to ensure that it will only be available via a POST. It returns a Json object with a property named Success that can be used by the UX to verify everything went well (we won't use that in our example). Both the add and edit actions in the UX will post to the Save action method, allowing us to reduce the amount of unique jQuery we need to write in our view. The contents of the HomeController.cs file: using System . Web . Mvc ; using Website . Models ; namespace Website . Controllers {     public class HomeController : Controller     {         public ActionResult Index ()         {             return View ();         }         [ OutputCache ( Duration = 0 )]         public ActionResult List ()         {             var manager = new NoteManager ();             var model = manager . GetAll ();             return PartialView ( model );         }         [ OutputCache ( Duration = 0 )]         public ActionResult Create ()         {             var model = new Note ();             return PartialView ( "NoteForm" , model );         }         [ OutputCache ( Duration = 0 )]         public ActionResult Edit ( int id )         {             var manager = new NoteManager ();             var model = manager . GetById ( id );             return PartialView ( "NoteForm" , model );         }         [ HttpPost ]         public JsonResult Save ( Note note )         {             var manager = new NoteManager ();             var noteId = manager . Save ( note );             return Json ( new { Success = noteId > 0 });         }     } } The view for the note form, NoteForm.cshtml , looks like so: @model Website . Models . Note @using ( Html . BeginForm ( "Save" , "Home" , FormMethod . Post , new { id = "NoteForm" })) { @Html . Hidden ( "Id" ) < label class = "Title" >     < span > Title < /span><br / >     @Html . TextBox ( "Title" ) < /label> <label class="Body">     <span>Body</ span >< br />     @Html . TextArea ( "Body" ) < /label> } It is a strongly typed view for our Note model class. We give the <form> element an id attribute so that we can reference it via jQuery. The <label> and <span> tags give our UX some structure that we can style with some CSS. The List.cshtml view is used to render out a <ul> element with all of our notes. @model IEnumerable < Website . Models . Note > < ul class = "NotesList" >     @foreach ( var note in Model )     {     < li >         @note . Title < br />         @note . Body < br />         < span class = "EditLink ButtonLink" noteid = "@note.Id" > Edit < /span>     </ li >     } < /ul> This view is strongly typed as well. It includes a <span> tag that we will use as an edit button. We add a custom attribute named noteid to the <span> tag that we can use in our jQuery to identify the Id of the note object we want to edit. The view, Index.cshtml , contains a bit of html block structure and all of our jQuery logic code. @ {     ViewBag . Title = "Index" ; } < h2 > Notes < /h2> <div id="NoteListBlock"></ div > < span class = "AddLink ButtonLink" > Add New Note < /span> <div id="NoteDialog" title="" class="Hidden"></ div > < script type = "text/javascript" >     $ ( function () {         $ ( "#NoteDialog" ). dialog ({             autoOpen : false , width : 400 , height : 330 , modal : true ,             buttons : {                 "Save" : function () {                     $ . post ( "/Home/Save" ,                         $ ( "#NoteForm" ). serialize (),                         function () {                             $ ( "#NoteDialog" ). dialog ( "close" );                             LoadList ();                         });                 },                 Cancel : function () { $ ( this ). dialog ( "close" ); }             }         });         $ ( ".EditLink" ). live ( "click" , function () {             var id = $ ( this ). attr ( "noteid" );             $ ( "#NoteDialog" ). html ( "" )                 . dialog ( "option" , "title" , "Edit Note" )                 . load ( "/Home/Edit/" + id , function () { $ ( "#NoteDialog" ). dialog ( "open" ); });         });         $ ( ".AddLink" ). click ( function () {             $ ( "#NoteDialog" ). html ( "" )                 . dialog ( "option" , "title" , "Add Note" )                 . load ( "/Home/Create" , function () { $ ( "#NoteDialog" ). dialog ( "open" ); });         });         LoadList ();     });     function LoadList () {         $ ( "#NoteListBlock" ). load ( "/Home/List" );     } < /script> The <div> tag with the id attribute of "NoteListBlock" is used as a container target for the load of the partial view content of our List action method. It starts out empty and will get loaded with content via jQuery once the DOM is loaded. The <div> tag with the id attribute of "NoteDialog" is the element for our dialog widget. The jQuery UI library will use the title attribute for the text in the dialog widget top header bar. We start out with it empty here and will dynamically change the text via jQuery based on the request to either add or edit a note. This <div> tag is given a CSS class named "Hidden" that will set the display:none style on the element. Since our call to the jQuery UI method to make the element a dialog widget will occur in the jQuery document ready code block, the end user will see the <div> element rendered in their browser as the page renders and then it will hide after that jQuery call. Adding the display:hidden to the <div> element via CSS will ensure that it is never rendered until the user triggers the request to open the dialog. The jQuery document load block contains the setup for the dialog node, click event bindings for the edit and add links, and a call to a JavaScript function called LoadList that handles the AJAX call to the List action method. The .dialog() method is called on the "NoteDialog" <div> element and the options are set for the dialog widget. The buttons option defines 2 buttons and their click actions. The first is the "Save" button (the text in quotations is used as the text for the button) that will do an AJAX post to our Save action method and send the serialized form data from the note form (targeted with the id attribute "NoteForm"). Upon completion it will close the dialog widget and call the LoadList to update the UX without a redirect. The "Cancel" button simply closes the dialog widget. The .live() method handles binding a function to the "click" event on all elements with the CSS class named EditLink . We use the .live() method because it will catch and bind our function to elements even as the DOM changes. Since we will be constantly changing the note list as we add and edit we want to ensure that the edit links get wired up with click events. The function for the click event on the edit links gets the noteid attribute and stores it in a local variable. Then it clears out the HTML in the dialog element (to ensure a fresh start), calls the .dialog() method and sets the "title" option (this sets the title attribute value), and then calls the .load() AJAX method to hit our Edit action method and inject the returned content into the "NoteDialog" <div> element. Once the .load() method is complete it opens the dialog widget. The click event binding for the add link is similar to the edit, only we don't need to get the id value and we load the Create action method. This binding is done via the .click() method because it will only be bound on the initial load of the page. The add button will always exist. Finally, we toss in some CSS in the Content/Site.css file to style our form and the add/edit links. . ButtonLink { color : Blue ; cursor : pointer ; } . ButtonLink : hover { text - decoration : underline ; } . Hidden { display : none ; } #NoteForm label { display:block; margin-bottom:6px; } #NoteForm label > span { font-weight:bold; } #NoteForm input[type=text] { width:350px; } #NoteForm textarea { width:350px; height:80px; } With all of our code in place we can do an F5 and see our list of notes: If we click on an edit link we will get the dialog widget with the correct note data loaded: And if we click on the add new note link we will get the dialog widget with the empty form: The end result of our solution tree for our sample:

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  • Christmas in the Clouds

    - by andrewbrust
    I have been spending the last 2 weeks immersing myself in a number of Windows Azure and SQL Azure technologies.  And in setting up a new business (I’ll speak more about that in the future), I have also become a customer of Microsoft’s BPOS (Business Productivity Online Services).  In short, it has been a fortnight of Microsoft cloud computing. On the Azure side, I’ve looked, of course, at Web Roles and Worker Roles.  But I’ve also looked at Azure Storage’s REST API (including coding to it directly), I’ve looked at Azure Drive and the new VM Role; I’ve looked quite a bit at SQL Azure (including the project “Houston” Silverlight UI) and I’ve looked at SQL Azure labs’ OData service too. I’ve also looked at DataMarket and its integration with both PowerPivot and native Excel.  Then there’s AppFabric Caching, SQL Azure Reporting (what I could learn of it) and the Visual Studio tooling for Azure, including the storage of certificate-based credentials.  And to round it out with some user stuff, on the BPOS side, I’ve been working with Exchange Online, SharePoint Online and LiveMeeting. I have to say I like a lot of what I’ve been seeing.  Azure’s not perfect, and BPOS certainly isn’t either.  But there’s good stuff in all these products, and there’s a lot of value. Azure Goes Deep Most people know that Web and Worker roles put the platform in charge of spinning virtual machines up and down, and keeping them up to date. But you can go way beyond that now.  The still-in-beta VM Role gives you the power to craft the machine (much as does Amazon’s EC2), though it takes away the platform’s self-managing attributes.  It still spins instances up and down, making drive storage non-durable, but Azure Drive gives you the ability to store VHD files as blobs and mount them as virtual hard drives that are readable and writeable.  Whether with Azure Storage or SQL Azure, Azure does data.  And OData is everywhere.  Azure Table Storage supports an OData Interface.  So does SQL Azure and so does DataMarket (the former project “Dallas”).  That means that Azure data repositories aren’t just straightforward to provision and configure…they’re also easy to program against, from just about any programming environment, in a RESTful manner.  And for more .NET-centric implementations, Azure AppFabric caching takes the technology formerly known as “Velocity” and throws it up into the cloud, speeding data access even more. Snapping in Place Once you get the hang of it, this stuff just starts to work in a way that becomes natural to understand.  I wasn’t expecting that, and I was really happy to discover it. In retrospect, I am not surprised, because I think the various Azure teams are the center of gravity for Redmond’s innovation right now.  The products belie this and so do my observations of the product teams’ motivation and high morale.  It is really good to see this; Microsoft needs to lead somewhere, and they need to be seen as the underdog while doing so.  With Azure, both requirements are in place.   BPOS: Bad Acronym, Easy Setup BPOS is about products you already know; Exchange, SharePoint, Live Meeting and Office Communications Server.  As such, it’s hard not to be underwhelmed by BPOS.  Until you realize how easy it makes it to get all that stuff set up.  I would say that from sign-up to productive use took me about 45 minutes…and that included the time necessary to wrestle with my DNS provider, set up Outlook and my SmartPhone up to talk to the Exchange account, create my SharePoint site collection, and configure the Outlook Conferencing add-in to talk to the provisioned Live Meeting account. Never before did I think setting up my own Exchange mail could come anywhere close to the simplicity of setting up an SMTP/POP account, and yet BPOS actually made it faster.   What I want from my Azure Christmas Next Year Not everything about Microsoft’s cloud is good.  I close this post with a list of things I’d like to see addressed: BPOS offerings are still based on the 2007 Wave of Microsoft server technologies.  We need to get to 2010, and fast.  Arguably, the 2010 products should have been released to the off-premises channel before the on-premise sone.  Office 365 can’t come fast enough. Azure’s Internet tooling and domain naming, is scattered and confusing.  Deployed ASP.NET applications go to cloudapp.net; SQL Azure and Azure storage work off windows.net.  The Azure portal and Project Houston are at azure.com.  Then there’s appfabriclabs.com and sqlazurelabs.com.  There is a new Silverlight portal that replaces most, but not all of the HTML ones.  And Project Houston is Silvelright-based too, though separate from the Silverlight portal tooling. Microsoft is the king off tooling.  They should not make me keep an entire OneNote notebook full of portal links, account names, access keys, assemblies and namespaces and do so much CTRL-C/CTRL-V work.  I’d like to see more project templates, have them automatically reference the appropriate assemblies, generate the right using/Imports statements and prime my config files with the right markup.  Then I want a UI that lets me log in with my Live ID and pick the appropriate project, database, namespace and key string to get set up fast. Beta programs, if they’re open, should onboard me quickly.  I know the process is difficult and everyone’s going as fast as they can.  But I don’t know why it’s so difficult or why it takes so long.  Getting developers up to speed on new features quickly helps popularize the platform.  Make this a priority. Make Azure accessible from the simplicity platforms, i.e. ASP.NET Web Pages (Razor) and LightSwitch.  Support .NET 4 now.  Make WebMatrix, IIS Express and SQL Compact work with the Azure development fabric. Have HTML helpers make Azure programming easier.  Have LightSwitch work with SQL Azure and not require SQL Express.  LightSwitch has some promising Azure integration now.  But we need more.  WebMatrix has none and that’s just silly, now that the Extra Small Instance is being introduced. The Windows Azure Platform Training Kit is great.  But I want Microsoft to make it even better and I want them to evangelize it much more aggressively.  There’s a lot of good material on Azure development out there, but it’s scattered in the same way that the platform is.   The Training Kit ties a lot of disparate stuff together nicely.  Make it known. Should Old Acquaintance Be Forgot All in all, diving deep into Azure was a good way to end the year.  Diving deeper into Azure should a great way to spend next year, not just for me, but for Microsoft too.

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  • #DAX Query Plan in SQL Server 2012 #Tabular

    - by Marco Russo (SQLBI)
    The SQL Server Profiler provides you many information regarding the internal behavior of DAX queries sent to a BISM Tabular model. Similar to MDX, also in DAX there is a Formula Engine (FE) and a Storage Engine (SE). The SE is usually handled by Vertipaq (unless you are using DirectQuery mode) and Vertipaq SE Query classes of events gives you a SQL-like syntax that represents the query sent to the storage engine. Another interesting class of events is the DAX Query Plan , which contains a couple...(read more)

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  • Apprentice Boot Camp in South Africa (Part 1)

    - by Tim Koekkoek
    By Maximilian Michel (DE), Jorge Garnacho (ES), Daniel Maull (UK), Adam Griffiths (UK), Guillermo De Las Nieves (ES), Catriona McGill (UK), Ed Dunlop (UK) The Boot Camp in South Africa was an amazing experience for all of us. The minute we landed, we were made to feel at home from our host Patrick Fitzgerald. The whole family who run the Guest House were also very friendly and always keen to help us. Since we had people from South Africa to show us all the amazing sights and their traditional ways to live their lives, the two weeks were very enjoyable for all of us and we came much closer together as a group. You can read this in the following parts of this report. Enjoy! The first group of Apprentices in Oracle (from left to right): Maximilian Michel (DE), Jorge Garnacho (ES), Daniel Maull (UK), Adam Griffiths (UK), Guillermo De Las Nieves (ES), Catriona McGill (UK), Ed Dunlop (UK) The Training Well, it’s time to talk about the main purpose of our trip to South Africa: the training. Two weeks, two courses. Servers and Storage. Two weeks to learn as much as possible and get the certificate. First week: Eben Pretorius with Servers Boot Camp. Learning about: • Machines: T1000, T2000, T3, T4, M series; • How to connect to the machines: serial and network connections; • Levels of software: ALOM, ILOM, OBP and of course the operating system, Solaris Combined with the practical part (screwdriver in one hand, and antistatic wristband on the other) makes quite a lot of stuff! But fortunately, Eben was able to tell us about everything without making our brains explode. For the second week: Storage Boot Camp with Deon Van Vuuren. Taking a look at the content: • Storage machines; • Connectors and protocols: SCSi, SAS, SATA Fiber Channel. Again, huge amounts of information, but Deon definitely did a great job and helped us learn it all. At the end, there was just one question left. Were we able to pass the exam and get the certificate? Well, what can we say? Just take a closer look at the picture above and make your conclusions! Our lovely Oracle office in Woodmead (near Johannesburg) We are all very proud to receive certification in “Server and Storage Support Fundamentals” together with our trainer Deon Van Vuuren. In summary, in case that you don't remember any of the above, the allies for a field engineer are: • System Handbook • EIS-DVD • A proper toolkit With these tools by our side, we’ll be unbeatable!  In the next article later this week, you can find part 2 of our experiences!

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  • Neue Zertifizierung von Pillar Axiom 600 Speichersystem

    - by swalker
    Sie haben nun die Möglichkeit, die Beta-Prüfung für Pillar Axiom 600 Storage System Essentials (1Z0-581) vorzunehmen. Wenn Sie die Prüfung bestehen, können Sie Implementierungsspezialist für Pillar Axiom 600 Speichersysteme werden! Für Oracle Partner sind kostenlose Gutscheine erhältlich. Wenn Sie einen kostenlosen Gutschein für die Beta-Prüfung erhalten möchten, senden Sie Ihre Anfrage an [email protected] und geben Sie bitte Ihren Namen, Ihre geschäftliche E-Mail-Adresse, Ihr Unternehmen und den Namen der Prüfung (Pillar Axiom 600 Storage System Essentials Beta) an.

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  • Some Oracle VM 3 updates

    - by wcoekaer
    Today we did another patch set update for Oracle VM 3 (3.0.3-build 227). This can be downloaded from My Oracle Support as patch ID 14736185. There are quite a few updates in here and I highly recommend any Oracle VM 3 customer or user to install this update. This patch can be installed on top of Oracle VM 3.0 versions 3.0.2 and 3.0.3. The patch is cumulative for 3.0.3. So if you already installed patch update 1 (3.0.3-150) then this will just be incremental on top of that and brings you to 3.0.3-build 227. There is a readme file which contains the patchlist in the patch info. The following patches are released on ULN for Oracle VM server 3.0 : initscripts-8.45.30-2.100.18.el5.x86_64 The inittab file and the /etc/init.d scripts. kernel-ovs-2.6.32.21-45.6.x86_64 The Linux kernel kernel-ovs-firmware-2.6.32.21-45.6.x86_64 Firmware files used by the Linux kernel osc-oracle-ocfs2-0.1.0-35.el5.noarch Oracle Storage Connect ocfs2 Plugin osc-plugin-manager-1.2.8-9.el5.3.noarch Oracle Storage Connect Plugin Infrastructure osc-plugin-manager-devel-1.2.8-9.el5.3.noarch Oracle Storage Connect Plugin Development ovs-agent-3.0.3-41.6.x86_64 Agent for Oracle VM xen-4.0.0-81.el5.1.x86_64 Xen is a virtual machine monitor xen-devel-4.0.0-81.el5.1.x86_64 Development libraries for Xen tools xen-tools-4.0.0-81.el5.1.x86_64 Various tooling for the manipulation of Xen instances Errata emails will be sent in the next few days with details on the above updates. Or you will find them here. I also did an update of my Oracle VM utilities to 0.4.0. They are also available from My Oracle Support, patch ID 14736239. These utils can be unzipped and installed on the server running Oracle VM Manager. Typically in /u01/app/oracle/ovm-manager-3/ovm_utils. There is a set of man pages in /u01/app/oracle/ovm-manager-3/ovm_utils/man/man8. There now are 6 commands : ovm_vmcontrol : VM level operations ovm_servercontrol : server level operations ovm_vmdisks : virtual disk/physical location mapping for VM disks ovm_vmmessage : message passing utility between the manager and the VM tools (in the Oracle VM templates) ovm_repocontrol : repository level operations ovm_poolcontrol : pool level operations Some of the new changes : at a pool level, acknowledge events and cascade to servers and virtual machines with outstanding events at a pool level, do a rescan of the storage for fibrechannel/iscsi disks if you add new devices (it does this operation then on every running server) at a repository level, fixup a device if it had a failed create repository at a repository level, refresh the repository and this will update the free space in the UI for ocfs2 repositories at a server level, acknowledge server events and cascade to virtual machines if needed at a VM level, acknowledge VM events at a VM level, bind vcpus to cores with vcpuset/vcpuget Please see the man pages and remember that these tools are just written As Is - no SRs... (per the documentation) Hopefully they are useful.

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  • Windows Azure – Write, Run or Use Software

    - by BuckWoody
    Windows Azure is a platform that has you covered, whether you need to write software, run software that is already written, or Install and use “canned” software whether you or someone else wrote it. Like any platform, it’s a set of tools you can use where it makes sense to solve a problem. The primary location for Windows Azure information is located at http://windowsazure.com. You can find everything there from the development kits for writing software to pricing, licensing and tutorials on all of that. I have a few links here for learning to use Windows Azure – although it’s best if you focus not on the tools, but what you want to solve. I’ve got it broken down here into various sections, so you can quickly locate things you want to know. I’ll include resources here from Microsoft and elsewhere – I use these same resources in the Architectural Design Sessions (ADS) I do with my clients worldwide. Write Software Also called “Platform as a Service” (PaaS), Windows Azure has lots of components you can use together or separately that allow you to write software in .NET or various Open Source languages to work completely online, or in partnership with code you have on-premises or both – even if you’re using other cloud providers. Keep in mind that all of the features you see here can be used together, or independently. For instance, you might only use a Web Site, or use Storage, but you can use both together. You can access all of these components through standard REST API calls, or using our Software Development Kit’s API’s, which are a lot easier. In any case, you simply use Visual Studio, Eclipse, Cloud9 IDE, or even a text editor to write your code from a Mac, PC or Linux.  Components you can use: Azure Web Sites: Windows Azure Web Sites allow you to quickly write an deploy websites, without setting a Virtual Machine, installing a web server or configuring complex settings. They work alone, with other Windows Azure Web Sites, or with other parts of Windows Azure. Web and Worker Roles: Windows Azure Web Roles give you a full stateless computing instance with Internet Information Services (IIS) installed and configured. Windows Azure Worker Roles give you a full stateless computing instance without Information Services (IIS) installed, often used in a "Services" mode. Scale-out is achieved either manually or programmatically under your control. Storage: Windows Azure Storage types include Blobs to store raw binary data, Tables to use key/value pair data (like NoSQL data structures), Queues that allow interaction between stateless roles, and a relational SQL Server database. Other Services: Windows Azure has many other services such as a security mechanism, a Cache (memcacheD compliant), a Service Bus, a Traffic Manager and more. Once again, these features can be used with a Windows Azure project, or alone based on your needs. Various Languages: Windows Azure supports the .NET stack of languages, as well as many Open-Source languages like Java, Python, PHP, Ruby, NodeJS, C++ and more.   Use Software Also called “Software as a Service” (SaaS) this often means consumer or business-level software like Hotmail or Office 365. In other words, you simply log on, use the software, and log off – there’s nothing to install, and little to even configure. For the Information Technology professional, however, It’s not quite the same. We want software that provides services, but in a platform. That means we want things like Hadoop or other software we don’t want to have to install and configure.  Components you can use: Kits: Various software “kits” or packages are supported with just a few clicks, such as Umbraco, Wordpress, and others. Windows Azure Media Services: Windows Azure Media Services is a suite of services that allows you to upload media for encoding, processing and even streaming – or even one or more of those functions. We can add DRM and even commercials to your media if you like. Windows Azure Media Services is used to stream large events all the way down to small training videos. High Performance Computing and “Big Data”: Windows Azure allows you to scale to huge workloads using a few clicks to deploy Hadoop Clusters or the High Performance Computing (HPC) nodes, accepting HPC Jobs, Pig and Hive Jobs, and even interfacing with Microsoft Excel. Windows Azure Marketplace: Windows Azure Marketplace offers data and programs you can quickly implement and use – some free, some for-fee.   Run Software Also known as “Infrastructure as a Service” (IaaS), this offering allows you to build or simply choose a Virtual Machine to run server-based software.  Components you can use: Persistent Virtual Machines: You can choose to install Windows Server, Windows Server with Active Directory, with SQL Server, or even SharePoint from a pre-configured gallery. You can configure your own server images with standard Hyper-V technology and load them yourselves – and even bring them back when you’re done. As a new offering, we also even allow you to select various distributions of Linux – a first for Microsoft. Windows Azure Connect: You can connect your on-premises networks to Windows Azure Instances. Storage: Windows Azure Storage can be used as a remote backup, a hybrid storage location and more using software or even hardware appliances.   Decision Matrix With all of these options, you can use Windows Azure to solve just about any computing problem. It’s often hard to know when to use something on-premises, in the cloud, and what kind of service to use. I’ve used a decision matrix in the last couple of years to take a particular problem and choose the proper technology to solve it. It’s all about options – there is no “silver bullet”, whether that’s Windows Azure or any other set of functions. I take the problem, decide which particular component I want to own and control – and choose the column that has that box darkened. For instance, if I have to control the wiring for a solution (a requirement in some military and government installations), that means the “Networking” component needs to be dark, and so I select the “On Premises” column for that particular solution. If I just need the solution provided and I want no control at all, I can look as “Software as a Service” solutions. Security, Pricing, and Other Info  Security: Security is one of the first questions you should ask in any distributed computing environment. We have certification info, coding guidelines and more, even a general “Request for Information” RFI Response already created for you.   Pricing: Are there licenses? How much does this cost? Is there a way to estimate the costs in this new environment? New Features: Many new features were added to Windows Azure - a good roundup of those changes can be found here. Support: Software Support on Virtual Machines, general support.    

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  • Class instance clustering in object reference graph for multi-entries serialization

    - by Juh_
    My question is on the best way to cluster a graph of class instances (i.e. objects, the graph nodes) linked by object references (the -directed- edges of the graph) around specifically marked objects. To explain better my question, let me explain my motivation: I currently use a moderately complex system to serialize the data used in my projects: "marked" objects have a specific attributes which stores a "saving entry": the path to an associated file on disc (but it could be done for any storage type providing the suitable interface) Those object can then be serialized automatically (eg: obj.save()) The serialization of a marked object 'a' contains implicitly all objects 'b' for which 'a' has a reference to, directly s.t: a.b = b, or indirectly s.t.: a.c.b = b for some object 'c' This is very simple and basically define specific storage entries to specific objects. I have then "container" type objects that: can be serialized similarly (in fact their are or can-be "marked") they don't serialize in their storage entries the "marked" objects (with direct reference): if a and a.b are both marked, a.save() calls b.save() and stores a.b = storage_entry(b) So, if I serialize 'a', it will serialize automatically all objects that can be reached from 'a' through the object reference graph, possibly in multiples entries. That is what I want, and is usually provides the functionalities I need. However, it is very ad-hoc and there are some structural limitations to this approach: the multi-entry saving can only works through direct connections in "container" objects, and there are situations with undefined behavior such as if two "marked" objects 'a'and 'b' both have a reference to an unmarked object 'c'. In this case my system will stores 'c' in both 'a' and 'b' making an implicit copy which not only double the storage size, but also change the object reference graph after re-loading. I am thinking of generalizing the process. Apart for the practical questions on implementation (I am coding in python, and use Pickle to serialize my objects), there is a general question on the way to attach (cluster) unmarked objects to marked ones. So, my questions are: What are the important issues that should be considered? Basically why not just use any graph parsing algorithm with the "attach to last marked node" behavior. Is there any work done on this problem, practical or theoretical, that I should be aware of? Note: I added the tag graph-database because I think the answer might come from that fields, even if the question is not.

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  • eSTEP Newsletter October 2012 now available

    - by uwes
    Dear Partners,We would like to inform you that the October '12 issue of our Newsletter is now available.The issue contains information to the following topics:News from CorpOracle Announces Oracle Solaris 11.1 at Oracle OpenWorld; Oracle Announces Oracle Exadata X3 Database In-Memory Machine; Oracle Enterprise Manager 12c introduces New Tools and Programs for Partners; Oracle Unveils First Industry-Specific Engineered System - the Oracle Networks Applications Platform,;  Oracle Unveils Expanded Oracle Cloud Offerings; Oracle Outlines Plans to Make the Future Java During JavaOne 2012 Strategy Keynote; Some interesting Java Facts and Figures; Oracle Announces MySQL 5.6 Release Candidate Technical Section What's up with LDoms (4 tech articles); Oracle SPARC T4 Systems cut Complexity, cost of Cryptographic Tasks; PeopleSoft Enterprise Financials 9.1; PeopleSoft HCM 9.1 combined online and batch benchmark,; Product Update Bulletin Oracle Solaris Cluster Oct 2012; Sun ZFS Storage 7420; SPARC Product Line Update; SPARC M-series -  New DAT 160 plus EOL of M3000 series; SPARC SuperCluster and SPARC T4 Servers Included in Enterprise Reference Architecture Sizing Tool; Oracle MagazineLearning & EventsRecently delivered Techcasts: An Update after the Oracle Open World, An Update on OVM Server for SPARC; Update to Oracle Database ApplianceReferencesBridgestone Aircraft Tire Reduces Required Disk Capacity by 50% with Virtualized Storage Solution; Fiat Group Automobiles Aligns Operational Decisions with Strategy by Using End-to-End Enterprise Performance Management System; Birkbeck, University of London Develops World-Class Computer Science Facilities While Reducing Costs with Ultrareliable and Scalable Data Infrastructure How toIntroducing Oracle System Assistant; How to Prepare a ZFS Storage Appliance to Serve as a Storage Device; Migrating Oracle Solaris 8 P2V with Oracle Database 10.2 and ASM; White paper on Best Practices for Building a Virtualized SPARC Computing Environment, How to extend the Oracle Solaris Studio IDE with NetBeans Plug-Ins; How I simplified Oracle Database 11g Installation on Oracle Linux 6You find the Newsletter on our portal under eSTEP News ---> Latest Newsletter. You will need to provide your email address and the pin below to get access. Link to the portal is shown below.URL: http://launch.oracle.com/PIN: eSTEP_2011Previous published Newsletters can be found under the Archived Newsletters section and more useful information under the Events, Download and Links tab. Feel free to explore and any feedback is appreciated to help us improve the service and information we deliver.Thanks and best regards,Partner HW Enablement EMEA

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  • Online ALTER TABLE in MySQL 5.6

    - by Marko Mäkelä
    This is the low-level view of data dictionary language (DDL) operations in the InnoDB storage engine in MySQL 5.6. John Russell gave a more high-level view in his blog post April 2012 Labs Release – Online DDL Improvements. MySQL before the InnoDB Plugin Traditionally, the MySQL storage engine interface has taken a minimalistic approach to data definition language. The only natively supported operations were CREATE TABLE, DROP TABLE and RENAME TABLE. Consider the following example: CREATE TABLE t(a INT); INSERT INTO t VALUES (1),(2),(3); CREATE INDEX a ON t(a); DROP TABLE t; The CREATE INDEX statement would be executed roughly as follows: CREATE TABLE temp(a INT, INDEX(a)); INSERT INTO temp SELECT * FROM t; RENAME TABLE t TO temp2; RENAME TABLE temp TO t; DROP TABLE temp2; You could imagine that the database could crash when copying all rows from the original table to the new one. For example, it could run out of file space. Then, on restart, InnoDB would roll back the huge INSERT transaction. To fix things a little, a hack was added to ha_innobase::write_row for committing the transaction every 10,000 rows. Still, it was frustrating that even a simple DROP INDEX would make the table unavailable for modifications for a long time. Fast Index Creation in the InnoDB Plugin of MySQL 5.1 MySQL 5.1 introduced a new interface for CREATE INDEX and DROP INDEX. The old table-copying approach can still be forced by SET old_alter_table=0. This interface is used in MySQL 5.5 and in the InnoDB Plugin for MySQL 5.1. Apart from the ability to do a quick DROP INDEX, the main advantage is that InnoDB will execute a merge-sort algorithm before inserting the index records into each index that is being created. This should speed up the insert into the secondary index B-trees and potentially result in a better B-tree fill factor. The 5.1 ALTER TABLE interface was not perfect. For example, DROP FOREIGN KEY still invoked the table copy. Renaming columns could conflict with InnoDB foreign key constraints. Combining ADD KEY and DROP KEY in ALTER TABLE was problematic and not atomic inside the storage engine. The ALTER TABLE interface in MySQL 5.6 The ALTER TABLE storage engine interface was completely rewritten in MySQL 5.6. Instead of introducing a method call for every conceivable operation, MySQL 5.6 introduced a handful of methods, and data structures that keep track of the requested changes. In MySQL 5.6, online ALTER TABLE operation can be requested by specifying LOCK=NONE. Also LOCK=SHARED and LOCK=EXCLUSIVE are available. The old-style table copying can be requested by ALGORITHM=COPY. That one will require at least LOCK=SHARED. From the InnoDB point of view, anything that is possible with LOCK=EXCLUSIVE is also possible with LOCK=SHARED. Most ALGORITHM=INPLACE operations inside InnoDB can be executed online (LOCK=NONE). InnoDB will always require an exclusive table lock in two phases of the operation. The execution phases are tied to a number of methods: handler::check_if_supported_inplace_alter Checks if the storage engine can perform all requested operations, and if so, what kind of locking is needed. handler::prepare_inplace_alter_table InnoDB uses this method to set up the data dictionary cache for upcoming CREATE INDEX operation. We need stubs for the new indexes, so that we can keep track of changes to the table during online index creation. Also, crash recovery would drop any indexes that were incomplete at the time of the crash. handler::inplace_alter_table In InnoDB, this method is used for creating secondary indexes or for rebuilding the table. This is the ‘main’ phase that can be executed online (with concurrent writes to the table). handler::commit_inplace_alter_table This is where the operation is committed or rolled back. Here, InnoDB would drop any indexes, rename any columns, drop or add foreign keys, and finalize a table rebuild or index creation. It would also discard any logs that were set up for online index creation or table rebuild. The prepare and commit phases require an exclusive lock, blocking all access to the table. If MySQL times out while upgrading the table meta-data lock for the commit phase, it will roll back the ALTER TABLE operation. In MySQL 5.6, data definition language operations are still not fully atomic, because the data dictionary is split. Part of it is inside InnoDB data dictionary tables. Part of the information is only available in the *.frm file, which is not covered by any crash recovery log. But, there is a single commit phase inside the storage engine. Online Secondary Index Creation It may occur that an index needs to be created on a new column to speed up queries. But, it may be unacceptable to block modifications on the table while creating the index. It turns out that it is conceptually not so hard to support online index creation. All we need is some more execution phases: Set up a stub for the index, for logging changes. Scan the table for index records. Sort the index records. Bulk load the index records. Apply the logged changes. Replace the stub with the actual index. Threads that modify the table will log the operations to the logs of each index that is being created. Errors, such as log overflow or uniqueness violations, will only be flagged by the ALTER TABLE thread. The log is conceptually similar to the InnoDB change buffer. The bulk load of index records will bypass record locking. We still generate redo log for writing the index pages. It would suffice to log page allocations only, and to flush the index pages from the buffer pool to the file system upon completion. Native ALTER TABLE Starting with MySQL 5.6, InnoDB supports most ALTER TABLE operations natively. The notable exceptions are changes to the column type, ADD FOREIGN KEY except when foreign_key_checks=0, and changes to tables that contain FULLTEXT indexes. The keyword ALGORITHM=INPLACE is somewhat misleading, because certain operations cannot be performed in-place. For example, changing the ROW_FORMAT of a table requires a rebuild. Online operation (LOCK=NONE) is not allowed in the following cases: when adding an AUTO_INCREMENT column, when the table contains FULLTEXT indexes or a hidden FTS_DOC_ID column, or when there are FOREIGN KEY constraints referring to the table, with ON…CASCADE or ON…SET NULL option. The FOREIGN KEY limitations are needed, because MySQL does not acquire meta-data locks on the child or parent tables when executing SQL statements. Theoretically, InnoDB could support operations like ADD COLUMN and DROP COLUMN in-place, by lazily converting the table to a newer format. This would require that the data dictionary keep multiple versions of the table definition. For simplicity, we will copy the entire table, even for DROP COLUMN. The bulk copying of the table will bypass record locking and undo logging. For facilitating online operation, a temporary log will be associated with the clustered index of table. Threads that modify the table will also write the changes to the log. When altering the table, we skip all records that have been marked for deletion. In this way, we can simply discard any undo log records that were not yet purged from the original table. Off-page columns, or BLOBs, are an important consideration. We suspend the purge of delete-marked records if it would free any off-page columns from the old table. This is because the BLOBs can be needed when applying changes from the log. We have special logging for handling the ROLLBACK of an INSERT that inserted new off-page columns. This is because the columns will be freed at rollback.

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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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