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  • Are there any viable DNS or LDAP alternatives for distributed key/value storage and retrieval?

    - by makerofthings7
    I'm working on a software app that needs distributed decentralized name resolution, and isn't bound to TCP/IP. Or more precisely, I need to store a "key" and look up it's value, and the key may be a string, a number, or any other realistic data type. Examples: With a phone number, look up a name. (or with an area code, redirect to the server that handles that exchange) With an IP Address get a DNS name, or a Whois contact (string value) With a string, get an IP, ( like a DNS TXT or SRV record). I'm thinking out of the box here and looking for any software that allows for this. (more info below) Are there any secure, scalable DNS alternatives that have gained notoriety? I could ask on StackOverflow, but think the infrastructure groups would have better insight on this. Edit More info: I'm looking at "Namecoin" the DNS version of Bitcoin, and since that project is faltering, I'm looking at alternative ways to store name-value pairs, with an optional qualifier. I think a name value pair is of global interest is useful, but on a limited scale. Namecoin tried to be too much, and ended up becoming nothing. I'm trying to solve that problem in researching alternatives and applying distributed technologies where applicable. Bitcoin/Namecoin offers a Distributed Hash Table, which has some positive aspects, but not useful for DNS, except for root servers.

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  • SQLAuthority News – Mark the Date: October 16, 2013 – Introducing NuoDB Blackbirds: THE Distributed Database

    - by Pinal Dave
    I am very excited to announce first on this blog about the release of NuoDB Blackbirds (NuoDB Release 2.0). NuoDB is my favorite application to work with data now a days. They are increasingly gaining market share as well as brining out new features with their every new release. I was very excited when I learned that NuoDB is releasing their flagship release of 2.0 on October 16, 2013. Interesting enough I will be in USA while this release happens and I will be watching it live during my day time. Even though if I had to stay up the entire night to just watch this release, I would do it. Here is the details of the announcements: Introducing NuoDB Blackbirds: THE Distributed Database Date: October 16, 2013 Time: 1:00 PM EDT Location: Online Registration Link What is the best DBMS architecture to handle today’s and tomorrow’s evolving needs? The days of shared disk are over. The times are “a-changin” and IT infrastructure has to change with them. Join NuoDB live for the introduction of our latest major product release, NuoDB Blackbirds, and take a look at why the NuoDB distributed database architecture is the only answer for customers like Fathom Voice, a leading provider of Voice Over IP (VoIP). NuoDB CEO, Barry Morris, welcomes Cameron Weeks, CEO of Fathom Voice to discuss how his company is using DBMS to break away from the pack and become the hottest player in VoIP. The webcast will include demonstrations of a single, logical database running in multiple geographies and a live Q&A. If due to any reason, you cannot watch it live, do not worry at all, just register at this Registration Link, as after the event you will get the link to watch the event on-demand. You can watch the launch event at any time if you have registered for the launch. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: NuoDB

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  • Test Data in a Distributed System

    - by Davin Tryon
    A question that has been vexing me lately has been about how to effectively test (end-to-end) features in a distributed system. Particuarly, how to effectively manage (through time) test data for feature testing. The system in question is a typical SOA setup. The composition is done in JavaScript when call to several REST APIs. Each service is built as an independent block. Each service has some kind of persistent storage (SQL Server in most cases). The main issue at the moment is how to approach test data when testing end-to-end features. Functional end-to-end testing occurs through the UI, and it is therefore necessary for test data to be set up before the test run (this could be manual or automated testing). As is typical in a distributed system, identifiers from one service are used as a link in another service. So, some level of synchronization needs to be present in the data to effectively test. What is the best way to manage and set up this data after a successful deployment to a test environment? For example, is it better to manage this test data inside each service? Or package it together with the testing suite? Does that testing suite exist as a separate project? I'm interested in design guidance about how to store and manage this test data as the application features evolve.

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  • Distributed Rendering in the UDK and Unity

    - by N0xus
    At the moment I'm looking at getting a game engine to run in a CAVE environment. So far, during my research I've seen a lot of people being able to get both Unity and the Unreal engine up and running in a CAVE (someone did get CryEngine to work in one, but there is little research data about it). As of yet, I have not cemented my final choice of engine for use in the next stage of my project. I've experience in both, so the learning curve will be gentle on both. And both of the engines offer stereoscopic rendering, either already inbuilt with ReadD (Unreal) or by doing it yourself (Unity). Both can also make use of other input devices as well, such as the kinect or other devices. So again, both engines are still on the table. For the last bit of my preliminary research, I was advised to see if either, or both engines could do distributed rendering. I was advised this, as the final game we make could go into a variety of differently sized CAVEs. The one I have access to is roughly 2.4m x 3m cubed, and have been duly informed that this one is a "baby" compared to others. So, finally onto my question: Can either the Unreal Engine, or Unity Engine make it possible for developers to allow distributed rendering? Either through in built devices, or by creating my own plugin / script?

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  • Communication Between Different Technologies in a Distributed Application

    - by sjtaheri
    I had to a incorporate several legacy applications and services in a network-distributed application. The existing services and applications are written using different languages and technologies, including: java, C#.Net and C++; all running on MS Windows machines. Now I'm wondering about the communication mechanism between them. What is the simple and standard way? Thanks! PS. communications include simple message sending and remote method invocations.

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  • Ubuntu - Upgrade to 10.4 - general error mounting filesystems

    - by JC Denton
    Hello All, Using upgrade manager I upgraded my 8.x LTS installation to 10.4. After rebooting the system failed encountered an error and dropped into the recovery console. It appeared to be a problem caused by ureadahead as described here: http://ubuntuguide.net/howto-fix-ureadahead-problem-after-upgrading-to-ubuntu-10-04. So I renamed ureadahead.conf to ureadahead.moved (after remounting the partition rw). this did not help so I renamed the file back again. After rebooting the following error appears: ureadahead terminated with status 5. udev_monitor_new_from_netlink: error getting socket: Invalid Argument mountall:mountall.c:3204 assertion failed in main: udev_monitor = udev_monitor_new_from_netlink(udev,"udev") init: mountall main process (2532) killed by ABRT signal. General error mounting filesystems How will I get my system to boot again properly? thanks

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  • Cross-platform, human-readable, du on root partition that truly ignores other filesystems

    - by nice_line
    I hate this so much: Linux builtsowell 2.6.18-274.7.1.el5 #1 SMP Mon Oct 17 11:57:14 EDT 2011 x86_64 x86_64 x86_64 GNU/Linux df -kh Filesystem Size Used Avail Use% Mounted on /dev/mapper/mpath0p2 8.8G 8.7G 90M 99% / /dev/mapper/mpath0p6 2.0G 37M 1.9G 2% /tmp /dev/mapper/mpath0p3 5.9G 670M 4.9G 12% /var /dev/mapper/mpath0p1 494M 86M 384M 19% /boot /dev/mapper/mpath0p7 7.3G 187M 6.7G 3% /home tmpfs 48G 6.2G 42G 14% /dev/shm /dev/mapper/o10g.bin 25G 7.4G 17G 32% /app/SIP/logs /dev/mapper/o11g.bin 25G 11G 14G 43% /o11g tmpfs 4.0K 0 4.0K 0% /dev/vx lunmonster1q:/vol/oradb_backup/epmxs1q1 686G 507G 180G 74% /rpmqa/backup lunmonster1q:/vol/oradb_redo/bisxs1q1 4.0G 1.6G 2.5G 38% /bisxs1q/rdoctl1 lunmonster1q:/vol/oradb_backup/bisxs1q1 686G 507G 180G 74% /bisxs1q/backup lunmonster1q:/vol/oradb_exp/bisxs1q1 2.0T 1.1T 984G 52% /bisxs1q/exp lunmonster2q:/vol/oradb_home/bisxs1q1 10G 174M 9.9G 2% /bisxs1q/home lunmonster2q:/vol/oradb_data/bisxs1q1 52G 5.2G 47G 10% /bisxs1q/oradata lunmonster1q:/vol/oradb_redo/bisxs1q2 4.0G 1.6G 2.5G 38% /bisxs1q/rdoctl2 ip-address1:/vol/oradb_home/cspxs1q1 10G 184M 9.9G 2% /cspxs1q/home ip-address2:/vol/oradb_backup/cspxs1q1 674G 314G 360G 47% /cspxs1q/backup ip-address2:/vol/oradb_redo/cspxs1q1 4.0G 1.5G 2.6G 37% /cspxs1q/rdoctl1 ip-address2:/vol/oradb_exp/cspxs1q1 4.1T 1.5T 2.6T 37% /cspxs1q/exp ip-address2:/vol/oradb_redo/cspxs1q2 4.0G 1.5G 2.6G 37% /cspxs1q/rdoctl2 ip-address1:/vol/oradb_data/cspxs1q1 160G 23G 138G 15% /cspxs1q/oradata lunmonster1q:/vol/oradb_exp/epmxs1q1 2.0T 1.1T 984G 52% /epmxs1q/exp lunmonster2q:/vol/oradb_home/epmxs1q1 10G 80M 10G 1% /epmxs1q/home lunmonster2q:/vol/oradb_data/epmxs1q1 330G 249G 82G 76% /epmxs1q/oradata lunmonster1q:/vol/oradb_redo/epmxs1q2 5.0G 609M 4.5G 12% /epmxs1q/rdoctl2 lunmonster1q:/vol/oradb_redo/epmxs1q1 5.0G 609M 4.5G 12% /epmxs1q/rdoctl1 /dev/vx/dsk/slaxs1q/slaxs1q-vol1 183G 17G 157G 10% /slaxs1q/backup /dev/vx/dsk/slaxs1q/slaxs1q-vol4 173G 58G 106G 36% /slaxs1q/oradata /dev/vx/dsk/slaxs1q/slaxs1q-vol5 75G 952M 71G 2% /slaxs1q/exp /dev/vx/dsk/slaxs1q/slaxs1q-vol2 9.8G 381M 8.9G 5% /slaxs1q/home /dev/vx/dsk/slaxs1q/slaxs1q-vol6 4.0G 1.6G 2.2G 42% /slaxs1q/rdoctl1 /dev/vx/dsk/slaxs1q/slaxs1q-vol3 4.0G 1.6G 2.2G 42% /slaxs1q/rdoctl2 /dev/mapper/appoem 30G 1.3G 27G 5% /app/em Yet, I equally, if not quite a bit more, also hate this: SunOS solarious 5.10 Generic_147440-19 sun4u sparc SUNW,SPARC-Enterprise Filesystem size used avail capacity Mounted on kiddie001Q_rpool/ROOT/s10s_u8wos_08a 8G 7.7G 1.3G 96% / /devices 0K 0K 0K 0% /devices ctfs 0K 0K 0K 0% /system/contract proc 0K 0K 0K 0% /proc mnttab 0K 0K 0K 0% /etc/mnttab swap 15G 1.8M 15G 1% /etc/svc/volatile objfs 0K 0K 0K 0% /system/object sharefs 0K 0K 0K 0% /etc/dfs/sharetab fd 0K 0K 0K 0% /dev/fd kiddie001Q_rpool/ROOT/s10s_u8wos_08a/var 31G 8.3G 6.6G 56% /var swap 512M 4.6M 507M 1% /tmp swap 15G 88K 15G 1% /var/run swap 15G 0K 15G 0% /dev/vx/dmp swap 15G 0K 15G 0% /dev/vx/rdmp /dev/dsk/c3t4d4s0 3 20G 279G 41G 88% /fs_storage /dev/vx/dsk/oracle/ora10g-vol1 292G 214G 73G 75% /o10g /dev/vx/dsk/oec/oec-vol1 64G 33G 31G 52% /oec/runway /dev/vx/dsk/oracle/ora9i-vol1 64G 33G 31G 59% /o9i /dev/vx/dsk/home 23G 18G 4.7G 80% /export/home /dev/vx/dsk/dbwork/dbwork-vol1 292G 214G 73G 92% /db03/wk01 /dev/vx/dsk/oradg/ebusredovol 2.0G 475M 1.5G 24% /u21 /dev/vx/dsk/oradg/ebusbckupvol 200G 32G 166G 17% /u31 /dev/vx/dsk/oradg/ebuscrtlvol 2.0G 475M 1.5G 24% /u20 kiddie001Q_rpool 31G 97K 6.6G 1% /kiddie001Q_rpool monsterfiler002q:/vol/ebiz_patches_nfs/NSA0304 203G 173G 29G 86% /oracle/patches /dev/odm 0K 0K 0K 0% /dev/odm The people with the authority don't rotate logs or delete packages after install in my environment. Standards, remediation, cohesion...all fancy foreign words to me. ============== How am I supposed to deal with / filesystem full issues across multiple platforms that have a devastating number of mounts? On Red Hat el5, du -x apparently avoids traversal into other filesystems. While this may be so, it does not appear to do anything if run from the / directory. On Solaris 10, the equivalent flag is du -d, which apparently packs no surprises, allowing Sun to uphold its legacy of inconvenience effortlessly. (I'm hoping I've just been doing it wrong.) I offer up for sacrifice my Frankenstein's monster. Tell me how ugly it is. Tell me I should download forbidden 3rd party software. Tell me I should perform unauthorized coreutils updates, piecemeal, across 2000 systems, with no single sign-on, no authorized keys, and no network update capability. Then, please help me make this bastard better: pwd / du * | egrep -v "$(echo $(df | awk '{print $1 "\n" $5 "\n" $6}' | \ cut -d\/ -f2-5 | egrep -v "[0-9]|^$|Filesystem|Use|Available|Mounted|blocks|vol|swap")| \ sed 's/ /\|/g')" | egrep -v "proc|sys|media|selinux|dev|platform|system|tmp|tmpfs|mnt|kernel" | \ cut -d\/ -f1-2 | sort -k2 -k1,1nr | uniq -f1 | sort -k1,1n | cut -f2 | xargs du -shx | \ egrep "G|[5-9][0-9]M|[1-9][0-9][0-9]M" My biggest failure and regret is that it still requires a single character edit for Solaris: pwd / du * | egrep -v "$(echo $(df | awk '{print $1 "\n" $5 "\n" $6}' | \ cut -d\/ -f2-5 | egrep -v "[0-9]|^$|Filesystem|Use|Available|Mounted|blocks|vol|swap")| \ sed 's/ /\|/g')" | egrep -v "proc|sys|media|selinux|dev|platform|system|tmp|tmpfs|mnt|kernel" | \ cut -d\/ -f1-2 | sort -k2 -k1,1nr | uniq -f1 | sort -k1,1n | cut -f2 | xargs du -shd | \ egrep "G|[5-9][0-9]M|[1-9][0-9][0-9]M" This will exclude all non / filesystems in a du search from the / directory by basically munging an egrepped df from a second pipe-delimited egrep regex subshell exclusion that is naturally further excluded upon by a third egrep in what I would like to refer to as "the whale." The munge-fest frantically escalates into some xargs du recycling where -x/-d is actually useful, and a final, gratuitous egrep spits out a list of directories that almost feels like an accomplishment: Linux: 54M etc/gconf 61M opt/quest 77M opt 118M usr/ ##===\ 149M etc 154M root 303M lib/modules 313M usr/java ##====\ 331M lib 357M usr/lib64 ##=====\ 433M usr/lib ##========\ 1.1G usr/share ##=======\ 3.2G usr/local ##========\ 5.4G usr ##<=============Ascending order to parent 94M app/SIP ##<==\ 94M app ##<=======Were reported as 7gb and then corrected by second du with -x. Solaris: 63M etc 490M bb 570M root/cores.ric.20100415 1.7G oec/archive 1.1G root/packages 2.2G root 1.7G oec Guess what? It's really slow. Edit: Are there any bash one-liner heroes out there than can turn my bloated abomination into divine intervention, or at least something resembling gingerly copypasta?

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  • Syncing Large Directories/Filesystems using USB Drive [closed]

    - by Alan Lue
    Does anyone have a solution for syncing large directories/filesystems using just a USB flash drive (and specifically without using a network connection)? The objective is simply to sync a user directory between two computers. The contents of the user directory could amount to a large quantity of data—say, a quantity larger than could be stored on any single USB drive—but the aggregate size of changes that must be propagated by a single sync could easily fit on a USB drive. As an example, suppose a user directory is already synchronized between a desktop and a laptop computer. Here's a use case: Some changes are made in the user directory on the desktop. We mount a USB drive onto the desktop and copy whatever changes need to be applied to the laptop user directory in order to synchronize the desktop and laptop user directories. We now mount the USB drive onto the laptop and apply the changes. The desktop and laptop user directories are now synchronized. Any ideas? Alan

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  • Syncing Large Directories/Filesystems using USB Drive

    - by Alan Lue
    Does anyone have a solution for syncing large directories/filesystems using just a USB flash drive (and specifically without using a network connection)? The objective is simply to sync a user directory between two computers. The contents of the user directory could amount to a large quantity of data—say, a quantity larger than could be stored on any single USB drive—but the aggregate size of changes that must be propagated by a single sync could easily fit on a USB drive. As an example, suppose a user directory is already synchronized between a desktop and a laptop computer. Here's a use case: Some changes are made in the user directory on the desktop. We mount a USB drive onto the desktop and copy whatever changes need to be applied to the laptop user directory in order to synchronize the desktop and laptop user directories. We now mount the USB drive onto the laptop and apply the changes. The desktop and laptop user directories are now synchronized. Any ideas? Alan

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  • SQL SERVER – Shard No More – An Innovative Look at Distributed Peer-to-peer SQL Database

    - by pinaldave
    There is no doubt that SQL databases play an important role in modern applications. In an ideal world, a single database can handle hundreds of incoming connections from multiple clients and scale to accommodate the related transactions. However the world is not ideal and databases are often a cause of major headaches when applications need to scale to accommodate more connections, transactions, or both. In order to overcome scaling issues, application developers often resort to administrative acrobatics, also known as database sharding. Sharding helps to improve application performance and throughput by splitting the database into two or more shards. Unfortunately, this practice also requires application developers to code transactional consistency into their applications. Getting transactional consistency across multiple SQL database shards can prove to be very difficult. Sharding requires developers to think about things like rollbacks, constraints, and referential integrity across tables within their applications when these types of concerns are best handled by the database. It also makes other common operations such as joins, searches, and memory management very difficult. In short, the very solution implemented to overcome throughput issues becomes a bottleneck in and of itself. What if database sharding was no longer required to scale your application? Let me explain. For the past several months I have been following and writing about NuoDB, a hot new SQL database technology out of Cambridge, MA. NuoDB is officially out of beta and they have recently released their first release candidate so I decided to dig into the database in a little more detail. Their architecture is very interesting and exciting because it completely eliminates the need to shard a database to achieve higher throughput. Each NuoDB database consists of at least three or more processes that enable a single database to run across multiple hosts. These processes include a Broker, a Transaction Engine and a Storage Manager.  Brokers are responsible for connecting client applications to Transaction Engines and maintain a global view of the network to keep track of the multiple Transaction Engines available at any time. Transaction Engines are in-memory processes that client applications connect to for processing SQL transactions. Storage Managers are responsible for persisting data to disk and serving up records to the Transaction Managers if they don’t exist in memory. The secret to NuoDB’s approach to solving the sharding problem is that it is a truly distributed, peer-to-peer, SQL database. Each of its processes can be deployed across multiple hosts. When client applications need to connect to a Transaction Engine, the Broker will automatically route the request to the most available process. Since multiple Transaction Engines and Storage Managers running across multiple host machines represent a single logical database, you never have to resort to sharding to get the throughput your application requires. NuoDB is a new pioneer in the SQL database world. They are making database scalability simple by eliminating the need for acrobatics such as sharding, and they are also making general administration of the database simpler as well.  Their distributed database appears to you as a user like a single SQL Server database.  With their RC1 release they have also provided a web based administrative console that they call NuoConsole. This tool makes it extremely easy to deploy and manage NuoDB processes across one or multiple hosts with the click of a mouse button. See for yourself by downloading NuoDB here. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: CodeProject, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology Tagged: NuoDB

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  • Discussion of a Distributed Data Storage implementation

    - by fegol
    I want to implement a distributed data storage using a client/server architecture. Each data item will be stored persistently in disk in one of several remote servers. The client uses a library to update and query the data, shielding the client from its actual location. This should allow a client to associate keys (String) to values(byte[]), much as a Map does. The system must ensure that the amount of data stored in each server is approximately the same. The set of servers is known beforehand by other servers and clients. Both the client and the server will be written in Java, using sockets, threads, and files. I open this topic with the objective of discussing the best way to implement this idea, assuming simplicity, what are the issues of this implementation, performance measurements and discussion of the limitations.

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  • Azure Futures - Distributed Computing and Number Crunching

    - by JoshReuben
    "the biggest Azure customers today are the ones using HPC on-premises at the current time" - http://www.zdnet.com/blog/microsoft/windows-azure-futures-turning-the-cloud-into-a-supercomputer/8592?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+zdnet%2Fmicrosoft+%28ZDNet+All+About+Microsoft%29&utm_content=Google+Reader   Orleans Framework for cloud computing - http://research.microsoft.com/en-us/projects/orleans     HPC on Azure - http://www.zdnet.com/blog/microsoft/microsoft-finalizes-its-latest-supercomputing-operating-system-release/7414   Dryad is Microsoft’s competitor to Google MapReduce and Apache Hadoop  - http://www.zdnet.com/blog/microsoft/microsoft-takes-a-step-toward-commercializing-its-dryad-distributed-computing-technologies/8255?tag=mantle_skin;content   SQL Server Analysis Services DataMining in the cloud - http://www.sqlmag.com/article/reporting2/azure-data-mining-in-the-cloud.aspx

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  • Distributed Computing - Hybrid Systems Considerations

    When the Cloud was new, it was often presented as an 'all or nothing' solution. Nowadays, the canny Systems Architect will exploit the best advantages of 'cloud' distributed computing in the right place, and use in-house services where most appropriate. So what are the issues that govern these architectural decisions? What can SQL Monitor 3.2 monitor?Whatever you think is most important. Use custom metrics to monitor and alert on data that's most important for your environment. Find out more.

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  • What is the best Linux filesystem for MySQL (InnoDB)?

    - by Continuation
    I tried to look for benchmark on the performances of various filesystems with MySQL InnoDB but couldn't find any. My database workload is the typical web-based OLTP, about 90% read, 10% write. Random IO. Among popular filesystems such as ext3, ext4, xfs, jfs, Reiserfs, Reiser4, etc. which one do you think is the best for MySQL?

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  • What filesystem comes closest to matching NTFS for support of ACLs, and highly-granular permissioning?

    - by warren
    It seems that most other filesystems handle the basic *nix permissions (ugo±rwx), with maybe an addition here or there. Or can be "made" to handle ACLs through the use of other tools on top of the system. On the wikipedia pages about filesystems (http://en.wikipedia.org/wiki/List%5Fof%5Ffile%5Fsystems & http://en.wikipedia.org/wiki/Comparison%5Fof%5Ffile%5Fsystems), it appears that while some do support extended meta-data, none support natively the level of permissioning that NTFS does. Am I wrong in this understanding?

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  • Distributed computing for a company? Is there such a 'free' thing?

    - by Jakub
    I am new to the whole distributed computing / cloud thing. But I had an idea at work for our multimedia stuff like movie encoding / cpu intensive things tasks (which sometimes take a few hours). Is there a 'free' (linux?) way to go about using a Windows machine, and offsetting those cpu cycles for that task to say 10 servers that are generally idle (cpu wise)? I'm just curious if there is a way to do this or am I just grasping at straws here. My thought is that a 'cloud' setup would achieve this, however like I stated initially, I am a total newbie when it comes to it. This is just an idea, looking for some thoughts? Anyone achieve this?

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  • Healthcare and Distributed Data Don't Mix

    - by [email protected]
    How many times have you heard the story?  Hard disk goes missing, USB thumb drive goes missing, laptop goes missing...Not a week goes by that we don't hear about our data going missing...  Healthcare data is a big one, but we hear about credit card data, pricing info, corporate intellectual property...  When I have spoken at Security and IT conferences part of my message is "Why do you give your users data to lose in the first place?"  I don't suggest they can't have access to it...in fact I work for the company that provides the premiere data security and desktop solutions that DO provide access.  Access isn't the issue.  'Keeping the data' is the issue.We are all human - we all make mistakes... I fault no one for having their car stolen or that they dropped a USB thumb drive. (well, except the thieves - I can certainly find some fault there)  Where I find fault is in policy (or lack thereof sometimes) that allows users to carry around private, and important, data with them.  Mr. Director of IT - It is your fault, not theirs.  Ms. CSO - Look in the mirror.It isn't like one can't find a network to access the data from.  You are on a network right now.  How many Wireless ones (wifi, mifi, cellular...) are there around you, right now?  Allowing employees to remove data from the confines of (wait for it... ) THE DATA CENTER is just plain indefensible when it isn't required.  The argument that the laptop had a password and the hard disk was encrypted is ridiculous.  An encrypted drive tells thieves that before they sell the stolen unit for $75, they should crack the encryption and ascertain what the REAL value of the laptop is... credit card info, Identity info, pricing lists, banking transactions... a veritable treasure trove of info people give away on an 'encrypted disk'.What started this latest rant on lack of data control was an article in Government Health IT that was forwarded to me by Denny Olson, an Oracle Principal Sales Consultant in Minnesota.  The full article is here, but the point was that a couple laptops went missing in a couple different cases, and.. well... no one knows where the data is, and yes - they were loaded with patient info.  What were you thinking?Obviously you can't steal data form a Sun Ray appliance... since it has no data, nor any storage to keep the data on, and Secure Global Desktop allows access from Macs, Linux and Windows client devices...  but in all cases, there is no keeping the data unless you explicitly allow for it in your policy.   Since you can get at the data securely from any network, why would you want to take personal responsibility for it?  Both Sun Rays and Secure Global Desktop are widely used in Healthcare... but clearly not widely enough.We need to do a better job of getting the message out -  Healthcare (or insert your business type here) and distributed data don't mix. Then add Hot Desking and 'follow me printing' and you have something that Clinicians (and CSOs) love.Thanks for putting up my blood pressure, Denny.

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  • Jini : single server with multiple clients

    - by user200340
    Hi all, I have a question about how to make multiple clients can access a single file located on server side and keep the file consistent. I have a simple PhoneBook server-client Jini program running at the moment, and server only provides some getter functions to clients, such as getName(String number), getNumber(String name) from a PhoneBook class(serializable), phonebook data are stored in a text file (phonebook.txt) at the moment. I have tried to implement some functions allowing to write a new records into the phonebook.txt file. If the writing record (name) is existing, an integer number will be added into the writing record. for example the existing phonebook.txt is .... John 01-01010101 .... if the writing record is "John 01-12345678",then "John_1 01-12345678" will be writen into phonebook.txt However, if i start with two clients A and B (on the same machine using localhost), and A tries to write "John 01-11111111", B tries to write "John 01-22222222". The early record will be overwritten later record. So, there must be something i did complete wrong. My client and server code are just like Jini HelloWorld example. My server side code is . 1. LookupDiscovery with parameter new String[]{""}; 2. DiscoveryListener for LookupDiscovery 3. registrations are saved into a HashTable 4. for every discovered lookup service, i use registrar to register the ServiceItem, ServiceItem contains a null attributeSets, a null serviceId, and a service. The client code has: 1. LookupDiscovery with parameter new String[]{""}; 2. DiscoveryListener for LookupDiscovery 3. a ServiceTemplate with null attributeSets, a null serviceId and a type, the type is the interface class. 4. for each found ServiceRegistrar, if it can find the looking for ServiceTemplate, the returned Object is cast into the type of the interface class. I have tried to google more details, and i found JavaSpace could be the one i missed. But i am still not sure about it (i only start Jini for a very short time). So any help would be greatly appreciated.

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  • A leader election algorithm for an oriented hypercube

    - by mick
    I'm stuck with some problem where I have to design a leader election algorithm for an oriented hypercube. This should be done by using a tournament with a number of rounds equal to the dimension D of the hypercube. In each stage d, with 1 <= d < D two candidate leaders of neighbouring d-dimensional hypercubes should compete to become the single candidate leader of the (d+1)-dimensional hypercube that is the union of their respective hypercubes.

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  • Odd company release cycle: Go Distributed Source Control?

    - by MrLane
    sorry about this long post, but I think it is worth it! I have just started with a small .NET shop that operates quite a bit differently to other places that I have worked. Unlike any of my previous positions, the software written here is targetted at multiple customers and not every customer gets the latest release of the software at the same time. As such, there is no "current production version." When a customer does get an update, they also get all of the features added to he software since their last update, which could be a long time ago. The software is highly configurable and features can be turned on and off: so called "feature toggles." Release cycles are very tight here, in fact they are not on a shedule: when a feature is complete the software is deployed to the relevant customer. The team only last year moved from Visual Source Safe to Team Foundation Server. The problem is they still use TFS as if it were VSS and enforce Checkout locks on a single code branch. Whenever a bug fix gets put out into the field (even for a single customer) they simply build whatever is in TFS, test the bug was fixed and deploy to the customer! (Myself coming from a pharma and medical devices software background this is unbeliveable!). The result is that half baked dev code gets put into production without being even tested. Bugs are always slipping into release builds, but often a customer who just got a build will not see these bugs if they don't use the feature the bug is in. The director knows this is a problem as the company is starting to grow all of a sudden with some big clients coming on board and more smaller ones. I have been asked to look at source control options in order to eliminate deploying of buggy or unfinished code but to not sacrifice the somewhat asyncronous nature of the teams releases. I have used VSS, TFS, SVN and Bazaar in my career, but TFS is where most of my experience has been. Previously most teams I have worked with use a two or three branch solution of Dev-Test-Prod, where for a month developers work directly in Dev and then changes are merged to Test then Prod, or promoted "when its done" rather than on a fixed cycle. Automated builds were used, using either Cruise Control or Team Build. In my previous job Bazaar was used sitting on top of SVN: devs worked in their own small feature branches then pushed their changes to SVN (which was tied into TeamCity). This was nice in that it was easy to isolate changes and share them with other peoples branches. With both of these models there was a central dev and prod (and sometimes test) branch through which code was pushed (and labels were used to mark builds in prod from which releases were made...and these were made into branches for bug fixes to releases and merged back to dev). This doesn't really suit the way of working here, however: there is no order to when various features will be released, they get pushed when they are complete. With this requirement the "continuous integration" approach as I see it breaks down. To get a new feature out with continuous integration it has to be pushed via dev-test-prod and that will capture any unfinished work in dev. I am thinking that to overcome this we should go down a heavily feature branched model with NO dev-test-prod branches, rather the source should exist as a series of feature branches which when development work is complete are locked, tested, fixed, locked, tested and then released. Other feature branches can grab changes from other branches when they need/want, so eventually all changes get absorbed into everyone elses. This fits very much down a pure Bazaar model from what I experienced at my last job. As flexible as this sounds it just seems odd to not have a dev trunk or prod branch somewhere, and I am worried about branches forking never to re-integrate, or small late changes made that never get pulled across to other branches and developers complaining about merge disasters... What are peoples thoughts on this? A second final question: I am somewhat confused about the exact definition of distributed source control: some people seem to suggest it is about just not having a central repository like TFS or SVN, some say it is about being disconnected (SVN is 90% disconnected and TFS has a perfectly functional offline mode) and others say it is about Feature Branching and ease of merging between branches with no parent-child relationship (TFS also has baseless merging!). Perhaps this is a second question!

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  • Any Open Source Pregel like framework for distributed processing of large Graphs?

    - by Akshay Bhat
    Google has described a novel framework for distributed processing on Massive Graphs. http://portal.acm.org/citation.cfm?id=1582716.1582723 I wanted to know if similar to Hadoop (Map-Reduce) are there any open source implementations of this framework? I am actually in process of writing a Pseudo distributed one using python and multiprocessing module and thus wanted to know if someone else has also tried implementing it. Since public information about this framework is extremely scarce. (A link above and a blog post at Google Research)

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  • How to mirror filesystems with millions of hardlinks?

    - by Thomas Berger
    We have one big problem at the moment: We need to mirror a filesystem for one of our customers. Thats usual not really a problem, but here it is: On this filesystem there is one folder with millions of hardlinks (yes! MILLIONS!). rsync requires more then 4 days to just build the filelist. We use the following rsync options: rsync -Havz --progress serverA:/data/cms /data/ Has anyone a idea how to speed up this rsync, or use alternatives? We could not use dd as the target disk is smaller then the source.

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