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  • Exposing a service to external systems - How should I design the contract?

    - by Larsi
    Hi! I know this question is been asked before here but still I'm not sure what to select. My service will be called from many 3 party system in the enterprise. I'm almost sure the information the service will collect (MyBigClassWithAllInfo) will change during the products lifetime. Is it still a good idea to expose objects? This is basically what my two alternatives: [ServiceContract] public interface ICollectStuffService { [OperationContract] SetDataResponseMsg SetData(SetDataRequestMsg dataRequestMsg); } // Alternative 1: Put all data inside a xml file [DataContract] public class SetDataRequestMsg { [DataMember] public string Body { get; set; } [DataMember] public string OtherPropertiesThatMightBeHandy { get; set; } // ?? } // Alternative 2: Expose the objects [DataContract] public class SetDataRequestMsg { [DataMember] public Header Header { get; set; } [DataMember] public MyBigClassWithAllInfo ExposedObject { get; set; } } public class SetDataResponseMsg { [DataMember] public ServiceError Error { get; set; } } The xml file would look like this: <?xml version="1.0" encoding="utf-8"?> <Message>   <Header>     <InfoAboutTheSender>...</InfoAboutTheSender>   </Header>   <StuffToCollectWithAllTheInfo>   <stuff1>...</stuff1> </StuffToCollectWithAllTheInfo> </Message> Any thought on how this service should be implemented? Thanks Larsi

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  • eSTEP Newsletter November 2012

    - by uwes
    Dear Partners,We would like to inform you that the November '12 issue of our Newsletter is now available.The issue contains information to the following topics: News from CorpOracle Celebrates 25 Years of SPARC Innovation; IDC White Papers Finds Growing Customer Comfort with Oracle Solaris Operating System; Oracle Buys Instantis; Pillar Axiom OpenWorld Highlights; Announcement Oracle Solaris 11.1 Availability (data sheet, new features, FAQ's, corporate pages, internal blog, download links, Oracle shop); Announcing StorageTek VSM 6; Announcement Oracle Solaris Cluster 4.1 Availability (new features, FAQ's, cluster corp page, download site, shop for media); Announcement: Oracle Database Appliance 2.4 patch update becomes available Technical SectionOracle White papers on SPARC SuperCluster; Understanding Parallel Execution; With LTFS, Tape is Gaining Storage Ground with additional link to How to Create Oracle Solaris 11 Zones with Oracle Enterprise Manager Ops Center; Provisioning Capabilities of Oracle Enterprise Ops Center Manager 12c; Maximizing your SPARC T4 Oracle Solaris Application Performance with the following articles: SPARC T4 Servers Set World Record on Siebel CRM 8.1.1.4 Benchmark, SPARC T4-Based Highly Scalable Solutions Posts New World Record on SPECjEnterprise2010 Benchmark, SPARC T4 Server Delivers Outstanding Performance on Oracle Business Intelligence Enterprise Edition 11g; Oracle SUN ZFS Storage Appliance Reference Architecture for VMware vSphere4;  Why 4K? - George Wilson's ZFS Day Talk; Pillar Axiom 600 with connected subjects: Oracle Introduces Pillar Axiom Release 5 Storage System Software, Driving down the high cost of Storage, This Provisioning with Pilar Axiom 600, Pillar Axiom 600- System overview and architecture; Migrate to Oracle;s SPARC Systems; Top 5 Reasons to Migrate to Oracle's SPARC Systems Learning & EventsRecently delivered Techcasts: Learning Paths; Oracle Database 11g: Database Administration (New) - Learning Path; Webcast: Drill Down on Disaster Recovery; What are Oracle Users Doing to Improve Availability and Disaster Recovery; SAP NetWeaver and Oracle Exadata Database Machine ReferencesARTstor Selects Oracle’s Sun ZFS Storage 7420 Appliances To Support Rapidly Growing Digital Image Library, Scottish Widows Cuts Sales Administration 20%, Reduces Time to Prepare Reports by 75%, and Achieves Return on Investment in First Year, Oracle's CRM Cloud Service Powers Innovation: Applications on Demand; Technology on Demand, How toHow to Migrate Your Data to Oracle Solaris 11 Using Shadow Migration; Using svcbundle to Create SMF Manifests and Profiles in Oracle Solaris 11; How to prepare a Sun ZFS Storage Appliance to Serve as a Storage Devise with Oracle Enterprise Manager Ops Center 12c; Command Summary: Basic Operations with the Image Packaging System In Oracle Solaris 11; How to Update to Oracle Solaris 11.1 Using the Image Packaging System, How to Migrate Oracle Database from Oracle Solaris 8 to Oracle Solaris 11;  Setting Up, Configuring, and Using an Oracle WebLogic Server Cluster; Ease the Chaos with Automated Patching: Oracle Enterprise Manager Cloud Control 12c; Book excerpt: Oracle Exalogic Elastic Cloud Handbook You 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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  • OPN Specialized Latest News (15th November)

    - by swalker
    HELPING YOU TO SPECIALIZE WebCenter Implementation Specialist Exam Preparation Webcasts: WebCenter Content And WebCenter Portal Oracle Partner Network would like to invite you to Refresh Courses for WebCenter Content and WebCenter Portal, to help partners to prepare for the WebCenter Implementation Specialist EXAMS. This is a 3 hours intensive refresher partner-only training session, providing attendees with an overview of WebCenter Content and WebCenter Portal functions and related topics. After the refresher part you will be able to take the relevant Implementation Specialist EXAM depending on your personal focus. NOTE: This is only suitable for experienced WebCenter Content or WebCenter Portal practitioners Who should attend? Partner Consultants who want to become an Oracle WebCenter Content or a WebCenter Portal Certified Implementation Specialist or both, that will help them to differentiate themselves in front of customers and support their Companies to become Specialized. Webcast Details: Click here to read more... Specialized Partners Only! New Service to Promote Your Events The Partner Event Publisher has just been made available to all specialized partners in EMEA.  Partners now have the opportunity to publish their events to the Oracle.com/events site and spread the word on their upcoming live in-person and/or live webcast events. Click here to read more information and watch a short video demo. VADs Get Specialized Effective November 1, 2011 , VADs, with a valid Value Added Distributor Agreement will no longer be required to meet customer reference requirements outlined in the business criteria section in order to become specialized. VADs must continue meet all other business and competency criteria set forth in the applicable Knowledge Zone prior to specialization approval. New Certification Pillar Axiom 600 Storage System Your opportunity to take the Pillar Axiom 600 Storage System Essentials (1Z0-581) Exam is vailable now in beta. Pass the exam so you can become a Pillar Axiom 600 Storage Systems Implementation Specialist! Free vouchers are available for Oracle Partners! If you would like to receive a free Beta exam voucher, please send your request to [email protected] and include your name, business email address, company, and the Exam name Pillar Axiom 600 Storage System Essentials Beta exam. New Certification Available: Oracle Utilities Customer Care and Billing Oracle Utilities Customer Care and Billing 2 Essentials (1Z0-562) is a solution designed to help you meet market windows and regulatory deadlines while enjoying a low total cost of ownership and a high return on investment. Take the exam now to become an  Oracle Utilities Customer Care and Billing 2 Essentials Implementation Specialists. MEASURING YOUR SUCCESS We had 1674 Specialized Partners covering 5364 Specializations. Please note that due to OPN contract renewals at any given point in time there are valid Specialized Partners and Specializations which are temporarily not captured in the total statistics. An incremental 1961 individuals were accredited as Implementation Specialists giving an EMEA cumulative total of 9598 Implementation Specialists 26 ISVs obtained one or more Ready's, for a total of 53 Ready's Don't forget! You can submit your own press releases to Oracle! Every time you achieve specialization we'd like to support you getting the message out! Press guidelines and a submission link can be found on the OPN Portal here.

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  • eSTEP Newsletter November 2012

    - by mseika
    Dear Partners,We would like to inform you that the November '12 issue of our Newsletter is now available.The issue contains information to the following topics: News from CorpOracle Celebrates 25 Years of SPARC Innovation; IDC White Papers Finds Growing Customer Comfort with Oracle Solaris Operating System; Oracle Buys Instantis; Pillar Axiom OpenWorld Highlights; Announcement Oracle Solaris 11.1 Availability (data sheet, new features, FAQ's, corporate pages, internal blog, download links, Oracle shop); Announcing StorageTek VSM 6; Announcement Oracle Solaris Cluster 4.1 Availability (new features, FAQ's, cluster corp page, download site, shop for media); Announcement: Oracle Database Appliance 2.4 patch update becomes available Technical SectionOracle White papers on SPARC SuperCluster; Understanding Parallel Execution; With LTFS, Tape is Gaining Storage Ground with additional link to How to Create Oracle Solaris 11 Zones with Oracle Enterprise Manager Ops Center; Provisioning Capabilities of Oracle Enterprise Ops Center Manager 12c; Maximizing your SPARC T4 Oracle Solaris Application Performance with the following articles: SPARC T4 Servers Set World Record on Siebel CRM 8.1.1.4 Benchmark, SPARC T4-Based Highly Scalable Solutions Posts New World Record on SPECjEnterprise2010 Benchmark, SPARC T4 Server Delivers Outstanding Performance on Oracle Business Intelligence Enterprise Edition 11g; Oracle SUN ZFS Storage Appliance Reference Architecture for VMware vSphere4; Why 4K? - George Wilson's ZFS Day Talk; Pillar Axiom 600 with connected subjects: Oracle Introduces Pillar Axiom Release 5 Storage System Software, Driving down the high cost of Storage, This Provisioning with Pilar Axiom 600, Pillar Axiom 600- System overview and architecture; Migrate to Oracle;s SPARC Systems; Top 5 Reasons to Migrate to Oracle's SPARC Systems Learning & EventsRecently delivered Techcasts: Learning Paths; Oracle Database 11g: Database Administration (New) - Learning Path; Webcast: Drill Down on Disaster Recovery; What are Oracle Users Doing to Improve Availability and Disaster Recovery; SAP NetWeaver and Oracle Exadata Database Machine ReferencesARTstor Selects Oracle’s Sun ZFS Storage 7420 Appliances To Support Rapidly Growing Digital Image Library, Scottish Widows Cuts Sales Administration 20%, Reduces Time to Prepare Reports by 75%, and Achieves Return on Investment in First Year, Oracle's CRM Cloud Service Powers Innovation: Applications on Demand; Technology on Demand, How toHow to Migrate Your Data to Oracle Solaris 11 Using Shadow Migration; Using svcbundle to Create SMF Manifests and Profiles in Oracle Solaris 11; How to prepare a Sun ZFS Storage Appliance to Serve as a Storage Devise with Oracle Enterprise Manager Ops Center 12c; Command Summary: Basic Operations with the Image Packaging System In Oracle Solaris 11; How to Update to Oracle Solaris 11.1 Using the Image Packaging System, How to Migrate Oracle Database from Oracle Solaris 8 to Oracle Solaris 11; Setting Up, Configuring, and Using an Oracle WebLogic Server Cluster; Ease the Chaos with Automated Patching: Oracle Enterprise Manager Cloud Control 12c; Book excerpt: Oracle Exalogic Elastic Cloud HandbookYou 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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  • How to export SSIS to Microsoft Excel without additional software?

    - by Dr. Zim
    This question is long winded because I have been updating the question over a very long time trying to get SSIS to properly export Excel data. I managed to solve this issue, although not correctly. Aside from someone providing a correct answer, the solution listed in this question is not terrible. The only answer I found was to create a single row named range wide enough for my columns. In the named range put sample data and hide it. SSIS appends the data and reads metadata from the single row (that is close enough for it to drop stuff in it). The data takes the format of the hidden single row. This allows headers, etc. WOW what a pain in the butt. It will take over 450 days of exports to recover the time lost. However, I still love SSIS and will continue to use it because it is still way better than Filemaker LOL. My next attempt will be doing the same thing in the report server. Original question notes: If you are in Sql Server Integrations Services designer and want to export data to an Excel file starting on something other than the first line, lets say the forth line, how do you specify this? I tried going in to the Excel Destination of the Data Flow, changed the AccessMode to OpenRowSet from Variable, then set the variable to "YPlatters$A4:I20000" This fails saying it cannot find the sheet. The sheet is called YPlatters. I thought you could specify (Sheet$)(Starting Cell):(Ending Cell)? Update Apparently in Excel you can select a set of cells and name them with the name box. This allows you to select the name instead of the sheet without the $ dollar sign. Oddly enough, whatever the range you specify, it appends the data to the next row after the range. Oddly, as you add data, it increases the named selection's row count. Another odd thing is the data takes the format of the last line of the range specified. My header rows are bold. If I specify a range that ends with the header row, the data appends to the row below, and makes all the entries bold. if you specify one row lower, it puts a blank line between the header row and the data, but the data is not bold. Another update No matter what I try, SSIS samples the "first row" of the file and sets the metadata according to what it finds. However, if you have sample data that has a value of zero but is formatted as the first row, it treats that column as text and inserts numeric values with a single quote in front ('123.34). I also tried headers that do not reflect the data types of the columns. I tried changing the metadata of the Excel destination, but it always changes it back when I run the project, then fails saying it will truncate data. If I tell it to ignore errors, it imports everything except that column. Several days of several hours a piece later... Another update I tried every combination. A mostly working example is to create the named range starting with the column headers. Format your column headers as you want the data to look as the data takes on this format. In my example, these exist from A4 to E4, which is my defined range. SSIS appends to the row after the defined range, so defining A4 to E68 appends the rows starting at A69. You define the Connection as having the first row contains the field names. It takes on the metadata of the header row, oddly, not the second row, and it guesses at the data type, not the formatted data type of the column, i.e., headers are text, so all my metadata is text. If your headers are bold, so is all of your data. I even tried making a sample data row without success... I don't think anyone actually uses Excel with the default MS SSIS export. If you could define the "insert range" (A5 to E5) with no header row and format those columns (currency, not bold, etc.) without it skipping a row in Excel, this would be very helpful. From what I gather, noone uses SSIS to export Excel without a third party connection manager. Any ideas on how to set this up properly so that data is formatted correctly, i.e., the metadata read from Excel is proper to the real data, and formatting inherits from the first row of data, not the headers in Excel? One last update (July 17, 2009) I got this to work very well. One thing I added to Excel was the IMEX=1 in the Excel connection string: "Excel 8.0;HDR=Yes;IMEX=1". This forces Excel (I think) to look at all rows to see what kind of data is in it. Generally, this does not drop information, say for instance if you have a zip code then about 9 rows down you have a zip+4, Excel without this blanks that field entirely without error. With IMEX=1, it recognizes that Zip is actually a character field instead of numeric. And of course, one more update (August 27, 2009) The IMEX=1 will succeed importing data with missing contents in the first 8 rows, but it will fail exporting data where no data exists. So, have it on your import connection string, but not your export Excel connection string. I have to say, after so much fiddling, it works pretty well.

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  • SSRS 2005: How do I make available varbinary data for download in a report?

    - by Angelo
    Hi, SSRS newbie question here... I have a table where one column is varbinary(max) data. I would like to make a report that makes this data available for download as a hyperlink so the user can just click on the item and get a file download dialog for the binary data. In this particular case, the binary data happens to be the content of old pdf files, but that shouldn't matter. I tried searching around but I can't find any pointers on how to do this. It seems to me that it should be possible. There are ways to display images in a report using varbinary data, so it makes sense that one should be able to make arbitrary binary data downloadable on a report, right?

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  • Is there a format or service for resume/CV data?

    - by Ben Dauphinee
    I have noticed through the process of signing up for various freelance and job seeking or professional network sites that they all want your resume/CV data. And I am really getting tired of copy/pasting this data, especially since I have a website. Is there a standard format or service somewhere that I do not know about for this data? If not, does anyone want to help me build something like this out? I'm thinking a service similar to OpenID that allows you to maintain a central resume to have your data pulled from. No more filling in the same data over and over, and having to maintain the copies on any of the plethora of websites that have that data. Takers?

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  • How best to convert CakePHP date picker form data to a PHP DateTime object?

    - by Daren Thomas
    I'm doing this in app/views/mymodel/add.ctp: <?php echo $form->input('Mymodel.mydatefield'); ?> And then, in app/controllers/mymodel_controller.php: function add() { # ... (if we have some submitted data) $datestring = $this->data['Mymodel']['mydatefield']['year'] . '-' . $this->data['Mymodel']['mydatefield']['month'] . '-' . $this->data['Mymodel']['mydatefield']['day']; $mydatefield = DateTime::createFromFormat('Y-m-d', $datestring); } There absolutly has to be a better way to do this - I just haven't found the CakePHP way yet... What I would like to do is: function add() { # ... (if we have some submitted data) $mydatefield = $this->data['Mymodel']['mydatefiled']; # obviously doesn't work }

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  • How to think in data stores instead of databases?

    - by Jim
    As an example, Google App Engine uses data stores, not a database, to store data. Does anybody have any tips for using data stores instead of databases? It seems I've trained my mind to think 100% in object relationships that map directly to table structures, and now it's hard to see anything differently. I can understand some of the benefits of data stores (e.g. performance and the ability to distribute data), but some good database functionality is sacrificed (e.g. joins). Does anybody who has worked with data stores like BigTable have any good advice to working with them?

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  • How can I structure and recode messy categorical data in R?

    - by briandk
    I'm struggling with how to best structure categorical data that's messy, and comes from a dataset I'll need to clean. The Coding Scheme I'm analyzing data from a university science course exam. We're looking at patterns in student responses, and we developed a coding scheme to represent the kinds of things students are doing in their answers. A subset of the coding scheme is shown below. Note that within each major code (1, 2, 3) are nested non-unique sub-codes (a, b, ...). What the Raw Data Looks Like I've created an anonymized, raw subset of my actual data which you can view here. Part of my problem is that those who coded the data noticed that some students displayed multiple patterns. The coders' solution was to create enough columns (reason1, reason2, ...) to hold students with multiple patterns. That becomes important because the order (reason1, reason2) is arbitrary--two students (like student 41 and student 42 in my dataset) who correctly applied "dependency" should both register in an analysis, regardless of whether 3a appears in the reason column or the reason2 column. How Can I Best Structure Student Data? Part of my problem is that in the raw data, not all students display the same patterns, or the same number of them, in the same order. Some students may do just one thing, others may do several. So, an abstracted representation of example students might look like this: Note in the example above that student002 and student003 both are coded as "1b", although I've deliberately shown the order as different to reflect the reality of my data. My (Practical) Questions Should I concatenate reason1, reason2, ... into one column? How can I (re)code the reasons in R to reflect the multiplicity for some students? Thanks I realize this question is as much about good data conceptualization as it is about specific features of R, but I thought it would be appropriate to ask it here. If you feel it's inappropriate for me to ask the question, please let me know in the comments, and stackoverflow will automatically flood my inbox with sadface emoticons. If I haven't been specific enough, please let me know and I'll do my best to be clearer.

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  • Showing a loading spinner only if the data has not been cached.

    - by Aaron Mc Adam
    Hi guys, Currently, my code shows a loading spinner gif, returns the data and caches it. However, once the data has been cached, there is a flicker of the loading gif for a split second before the data gets loaded in. It's distracting and I'd like to get rid of it. I think I'm using the wrong method in the beforeSend function here: $.ajax({ type : "GET", cache : false, url : "book_data.php", data : { keywords : keywords, page : page }, beforeSend : function() { $('.jPag-pages li:not(.cached)').each(function (i) { $('#searchResults').html('<p id="loader">Loading...<img src="../assets/images/ajax-loader.gif" alt="Loading..." /></p>'); }); }, success : function(data) { $('.jPag-current').parent().addClass('cached'); $('#searchResults').replaceWith($(data).find('#searchResults')).find('table.sortable tbody tr:odd').addClass('odd'); detailPage(); selectForm(); } });

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  • Is there a way to only backup a SQL 2005 database structure fully, but only the data in a certain se

    - by TheSoftwareJedi
    I have several schemas in my database, and the largest one ("large" meaning disk space consumed) is my "web" schema which is a denormalized copy of data in the operational schemas. This denormalized data is able to be reconstructed at anytime, and is merely there for extremely fast read purposes. Since the data is redundant, and VERY large - I'd like to exclude it from being backed up. I already have stored procedures that can regenerate all of the data in that schema in a couple of hours - for use in the event of a failure. I assume I can split the tables in this schema out to another data file or such (ideally even on another drive for faster reads), but is there a way to never have that data file backup, yet still in the event of a failure its structure could be restored (and other DDL stuff like procs, views, etc)? Somewhat related, can I also have these tables not do transaction logging, if I go to "Full" backup mode for the rest of the database?

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  • Assigning a variable of a struct that contains an instance of a class to another variable

    - by xport
    In my understanding, assigning a variable of a struct to another variable of the same type will make a copy. But this rule seems broken as shown on the following figure. Could you explain why this happened? using System; namespace ReferenceInValue { class Inner { public int data; public Inner(int data) { this.data = data; } } struct Outer { public Inner inner; public Outer(int data) { this.inner = new Inner(data); } } class Program { static void Main(string[] args) { Outer p1 = new Outer(1); Outer p2 = p1; Console.WriteLine("p1:{0}, p2:{1}", p1.inner.data, p2.inner.data); p1.inner.data = 2; Console.WriteLine("p1:{0}, p2:{1}", p1.inner.data, p2.inner.data); p2.inner.data = 3; Console.WriteLine("p1:{0}, p2:{1}", p1.inner.data, p2.inner.data); Console.ReadKey(); } } }

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  • How do I write raw binary data in Python?

    - by Chris B.
    I've got a Python program that stores and writes data to a file. The data is raw binary data, stored internally as str. I'm writing it out through a utf-8 codec. However, I get UnicodeDecodeError: 'charmap' codec can't decode byte 0x8d in position 25: character maps to <undefined> in the cp1252.py file. This looks to me like Python is trying to interpret the data using the default code page. But it doesn't have a default code page. That's why I'm using str, not unicode. I guess my questions are: How do I represent raw binary data in memory, in Python? When I'm writing raw binary data out through a codec, how do I encode/unencode it?

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  • What are the repercussions of not checking existing data when adding a foreign key?

    - by scottm
    I've inherited a database that doesn't exactly strive for data integrity. I am trying to add some foreign keys to change that, but there is data in some tables that doesn't fit the constraints. Most likely, the data won't be used again so I want to know what problems I might face by leaving it there. The other option I see is to move it into some kind of table without referential constraints, just for historical purposes. So, what are the repercussions of not checking existing data? If I create a foreign key constraint on a table and don't check existing data, will all new data inserted into the table be enforced?

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  • Want to save data field from form into two columns of two models.

    - by vette982
    I have a Profile model with a hasOne relationship to a Detail model. I have a registration form that saves data into both model's tables, but I want the username field from the profile model to be copied over to the usernamefield in the details model so that each has the same username. function new_account() { if(!empty($this->data)) { $this->Profile->modified = date("Y-m-d H:i:s"); if($this->Profile->save($this->data)) { $this->data['Detail']['profile_id'] = $this->Profile->id; $this->data['Detail']['username'] = $this->Profile->username; $this->Profile->Detail->save($this->data); $this->Session->setFlash('Your registration was successful.'); $this->redirect(array('action'=>'index')); } } } This code in my Profile controller gives me the error: Undefined property: Profile::$username Any ideas?

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  • How the existing data to be if entity structure modified or deleted on GAE?

    - by Eonil
    GAE recommends using JDO/JPA. But I have serious question about using OODB like them. JDO based on user's class structure. And data structure should be modified continually as service advances. So, If data(entity) class property being removed, what happened to existing data on the property? If data(entity) class renamed for refactoring reason, how the JDO know those renaming? Or all data loss? Major point is "How JDO/GAE/BigTable applies modification of class into existing entity structure and data?".

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  • What's the most simple way to retrieve all data from a table and save it back in .NET 3.5?

    - by zoman
    I have a number of tables containing some basic (business related) mapping data. What's the most simple way to load the data from those tables, then save the modified values back. (all data should be replaced in the tables) An ORM is out of question as I would like to avoid creating domain objects for each table. The actual editing of the data is not an issue. (it is exported into Excel where the data is edited, then the file is uploaded with the modified data) The technology is .NET 3.5 (ASP.NET MVC) and SQL Server 2005. Thanks.

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  • best way to store php data on a page for use with javascript/jquery?

    - by Haroldo
    Ok, so im trying to work out the fastest way of storing data on my page without slowing the page load: I need to store information in the page to be later used by jquery. My page is an events page and i want to attach data to each event anchor. there are 100+ events to attach data to. The events anchors are created with a php loop, so i could create the data elements within this loop using either use un-semantic tags ie *rel="some_data"* create a jquery.data() for each iteration of the loop or i could run the loop again, separately, this time inside script tags with jquery.data(); would really appreciate any thoughts on this!

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  • Offsite data storage for simple app, or a similar supported persistence mechanism?

    - by jdk
    Question Is there a usable facebook entry point to the Data Storage API that facebook lists on their app admin page for developers, or should I consider an alternate mechanism? What alternative mechanisms exist to simply persist my information offsite (away from my server app) without stuffing it into a cookie that's prone to expire? ... Background The facebook Data Store Admin tool is made available in a facebook App's Settings as seen here: (continue reading below) However when I visit the DataStoreAdmin link nothing works (i.e. clicking the buttons to define the data store types and objects does nothing - I have tried different browsers). The Wiki page for Data Store API hasn't been updated recently and the second last update says the beta Data Store was taken offline. It seems odd the link would be readily available and highly visible at the top of the App configuration area if indeed it's defunct. I was hoping some kind of key/value pair solution to remove the data calls from my own server.

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  • How to convert searchTwitter results (from library(twitteR)) into a data.frame?

    - by analyticsPierce
    I am working on saving twitter search results into a database (SQL Server) and am getting an error when I pull the search results from twitteR. If I execute: library(twitteR) puppy <- as.data.frame(searchTwitter("puppy", session=getCurlHandle(),num=100)) I get an error of: Error in as.data.frame.default(x[[i]], optional = TRUE) : cannot coerce class structure("status", package = "twitteR") into a data.frame This is important because in order to use RODBC to add this to a table using sqlSave it needs to be a data.frame. At least that's the error message I got: Error in sqlSave(localSQLServer, puppy, tablename = "puppy_staging", : should be a data frame So does anyone have any suggestions on how to coerce the list to a data.frame or how I can load the list through RODBC?

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  • RabbitMQ as a proxy between a data store and a producer ?

    - by hyperboreean
    I have some code that produces lots of data that should be stored in the database. The problem is that the database can't keep with the data that it gets produced. So I am wondering whether some kind of queuing mechanism would help in this situation - I am thinking in particular at RabiitMQ and whether is feasible to have the data stored in its queues until some consumer gets the data out of it and pushes it to the database. Also, I am not particular interested whether that data made it to the database or not because pretty soon, the same data will be updated.

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  • SPARC T4-4 Beats 8-CPU IBM POWER7 on TPC-H @3000GB Benchmark

    - by Brian
    Oracle's SPARC T4-4 server delivered a world record TPC-H @3000GB benchmark result for systems with four processors. This result beats eight processor results from IBM (POWER7) and HP (x86). The SPARC T4-4 server also delivered better performance per core than these eight processor systems from IBM and HP. Comparisons below are based upon system to system comparisons, highlighting Oracle's complete software and hardware solution. This database world record result used Oracle's Sun Storage 2540-M2 arrays (rotating disk) connected to a SPARC T4-4 server running Oracle Solaris 11 and Oracle Database 11g Release 2 demonstrating the power of Oracle's integrated hardware and software solution. The SPARC T4-4 server based configuration achieved a TPC-H scale factor 3000 world record for four processor systems of 205,792 QphH@3000GB with price/performance of $4.10/QphH@3000GB. The SPARC T4-4 server with four SPARC T4 processors (total of 32 cores) is 7% faster than the IBM Power 780 server with eight POWER7 processors (total of 32 cores) on the TPC-H @3000GB benchmark. The SPARC T4-4 server is 36% better in price performance compared to the IBM Power 780 server on the TPC-H @3000GB Benchmark. The SPARC T4-4 server is 29% faster than the IBM Power 780 for data loading. The SPARC T4-4 server is up to 3.4 times faster than the IBM Power 780 server for the Refresh Function. The SPARC T4-4 server with four SPARC T4 processors is 27% faster than the HP ProLiant DL980 G7 server with eight x86 processors on the TPC-H @3000GB benchmark. The SPARC T4-4 server is 52% faster than the HP ProLiant DL980 G7 server for data loading. The SPARC T4-4 server is up to 3.2 times faster than the HP ProLiant DL980 G7 for the Refresh Function. The SPARC T4-4 server achieved a peak IO rate from the Oracle database of 17 GB/sec. This rate was independent of the storage used, as demonstrated by the TPC-H @3000TB benchmark which used twelve Sun Storage 2540-M2 arrays (rotating disk) and the TPC-H @1000TB benchmark which used four Sun Storage F5100 Flash Array devices (flash storage). [*] The SPARC T4-4 server showed linear scaling from TPC-H @1000GB to TPC-H @3000GB. This demonstrates that the SPARC T4-4 server can handle the increasingly larger databases required of DSS systems. [*] The SPARC T4-4 server benchmark results demonstrate a complete solution of building Decision Support Systems including data loading, business questions and refreshing data. Each phase usually has a time constraint and the SPARC T4-4 server shows superior performance during each phase. [*] The TPC believes that comparisons of results published with different scale factors are misleading and discourages such comparisons. Performance Landscape The table lists the leading TPC-H @3000GB results for non-clustered systems. TPC-H @3000GB, Non-Clustered Systems System Processor P/C/T – Memory Composite(QphH) $/perf($/QphH) Power(QppH) Throughput(QthH) Database Available SPARC Enterprise M9000 3.0 GHz SPARC64 VII+ 64/256/256 – 1024 GB 386,478.3 $18.19 316,835.8 471,428.6 Oracle 11g R2 09/22/11 SPARC T4-4 3.0 GHz SPARC T4 4/32/256 – 1024 GB 205,792.0 $4.10 190,325.1 222,515.9 Oracle 11g R2 05/31/12 SPARC Enterprise M9000 2.88 GHz SPARC64 VII 32/128/256 – 512 GB 198,907.5 $15.27 182,350.7 216,967.7 Oracle 11g R2 12/09/10 IBM Power 780 4.1 GHz POWER7 8/32/128 – 1024 GB 192,001.1 $6.37 210,368.4 175,237.4 Sybase 15.4 11/30/11 HP ProLiant DL980 G7 2.27 GHz Intel Xeon X7560 8/64/128 – 512 GB 162,601.7 $2.68 185,297.7 142,685.6 SQL Server 2008 10/13/10 P/C/T = Processors, Cores, Threads QphH = the Composite Metric (bigger is better) $/QphH = the Price/Performance metric in USD (smaller is better) QppH = the Power Numerical Quantity QthH = the Throughput Numerical Quantity The following table lists data load times and refresh function times during the power run. TPC-H @3000GB, Non-Clustered Systems Database Load & Database Refresh System Processor Data Loading(h:m:s) T4Advan RF1(sec) T4Advan RF2(sec) T4Advan SPARC T4-4 3.0 GHz SPARC T4 04:08:29 1.0x 67.1 1.0x 39.5 1.0x IBM Power 780 4.1 GHz POWER7 05:51:50 1.5x 147.3 2.2x 133.2 3.4x HP ProLiant DL980 G7 2.27 GHz Intel Xeon X7560 08:35:17 2.1x 173.0 2.6x 126.3 3.2x Data Loading = database load time RF1 = power test first refresh transaction RF2 = power test second refresh transaction T4 Advan = the ratio of time to T4 time Complete benchmark results found at the TPC benchmark website http://www.tpc.org. Configuration Summary and Results Hardware Configuration: SPARC T4-4 server 4 x SPARC T4 3.0 GHz processors (total of 32 cores, 128 threads) 1024 GB memory 8 x internal SAS (8 x 300 GB) disk drives External Storage: 12 x Sun Storage 2540-M2 array storage, each with 12 x 15K RPM 300 GB drives, 2 controllers, 2 GB cache Software Configuration: Oracle Solaris 11 11/11 Oracle Database 11g Release 2 Enterprise Edition Audited Results: Database Size: 3000 GB (Scale Factor 3000) TPC-H Composite: 205,792.0 QphH@3000GB Price/performance: $4.10/QphH@3000GB Available: 05/31/2012 Total 3 year Cost: $843,656 TPC-H Power: 190,325.1 TPC-H Throughput: 222,515.9 Database Load Time: 4:08:29 Benchmark Description The TPC-H benchmark is a performance benchmark established by the Transaction Processing Council (TPC) to demonstrate Data Warehousing/Decision Support Systems (DSS). TPC-H measurements are produced for customers to evaluate the performance of various DSS systems. These queries and updates are executed against a standard database under controlled conditions. Performance projections and comparisons between different TPC-H Database sizes (100GB, 300GB, 1000GB, 3000GB, 10000GB, 30000GB and 100000GB) are not allowed by the TPC. TPC-H is a data warehousing-oriented, non-industry-specific benchmark that consists of a large number of complex queries typical of decision support applications. It also includes some insert and delete activity that is intended to simulate loading and purging data from a warehouse. TPC-H measures the combined performance of a particular database manager on a specific computer system. The main performance metric reported by TPC-H is called the TPC-H Composite Query-per-Hour Performance Metric (QphH@SF, where SF is the number of GB of raw data, referred to as the scale factor). QphH@SF is intended to summarize the ability of the system to process queries in both single and multiple user modes. The benchmark requires reporting of price/performance, which is the ratio of the total HW/SW cost plus 3 years maintenance to the QphH. A secondary metric is the storage efficiency, which is the ratio of total configured disk space in GB to the scale factor. Key Points and Best Practices Twelve Sun Storage 2540-M2 arrays were used for the benchmark. Each Sun Storage 2540-M2 array contains 12 15K RPM drives and is connected to a single dual port 8Gb FC HBA using 2 ports. Each Sun Storage 2540-M2 array showed 1.5 GB/sec for sequential read operations and showed linear scaling, achieving 18 GB/sec with twelve Sun Storage 2540-M2 arrays. These were stand alone IO tests. The peak IO rate measured from the Oracle database was 17 GB/sec. Oracle Solaris 11 11/11 required very little system tuning. Some vendors try to make the point that storage ratios are of customer concern. However, storage ratio size has more to do with disk layout and the increasing capacities of disks – so this is not an important metric in which to compare systems. The SPARC T4-4 server and Oracle Solaris efficiently managed the system load of over one thousand Oracle Database parallel processes. Six Sun Storage 2540-M2 arrays were mirrored to another six Sun Storage 2540-M2 arrays on which all of the Oracle database files were placed. IO performance was high and balanced across all the arrays. The TPC-H Refresh Function (RF) simulates periodical refresh portion of Data Warehouse by adding new sales and deleting old sales data. Parallel DML (parallel insert and delete in this case) and database log performance are a key for this function and the SPARC T4-4 server outperformed both the IBM POWER7 server and HP ProLiant DL980 G7 server. (See the RF columns above.) See Also Transaction Processing Performance Council (TPC) Home Page Ideas International Benchmark Page SPARC T4-4 Server oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Sun Storage 2540-M2 Array oracle.com OTN Disclosure Statement TPC-H, QphH, $/QphH are trademarks of Transaction Processing Performance Council (TPC). For more information, see www.tpc.org. SPARC T4-4 205,792.0 QphH@3000GB, $4.10/QphH@3000GB, available 5/31/12, 4 processors, 32 cores, 256 threads; IBM Power 780 QphH@3000GB, 192,001.1 QphH@3000GB, $6.37/QphH@3000GB, available 11/30/11, 8 processors, 32 cores, 128 threads; HP ProLiant DL980 G7 162,601.7 QphH@3000GB, $2.68/QphH@3000GB available 10/13/10, 8 processors, 64 cores, 128 threads.

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  • Oracle OpenWorld 2013 – Wrap up by Sven Bernhardt

    - by JuergenKress
    OOW 2013 is over and we’re heading home, so it is time to lean back and reflecting about the impressions we have from the conference. First of all: OOW was great! It was a pleasure to be a part of it. As already mentioned in our last blog article: It was the biggest OOW ever. Parallel to the conference the America’s Cup took place in San Francisco and the Oracle Team America won. Amazing job by the team and again congratulations from our side Back to the conference. The main topics for us are: Oracle SOA / BPM Suite 12c Adaptive Case management (ACM) Big Data Fast Data Cloud Mobile Below we will go a little more into detail, what are the key takeaways regarding the mentioned points: Oracle SOA / BPM Suite 12c During the five days at OOW, first details of the upcoming major release of Oracle SOA Suite 12c and Oracle BPM Suite 12c have been introduced. Some new key features are: Managed File Transfer (MFT) for transferring big files from a source to a target location Enhanced REST support by introducing a new REST binding Introduction of a generic cloud adapter, which can be used to connect to different cloud providers, like Salesforce Enhanced analytics with BAM, which has been totally reengineered (BAM Console now also runs in Firefox!) Introduction of templates (OSB pipelines, component templates, BPEL activities templates) EM as a single monitoring console OSB design-time integration into JDeveloper (Really great!) Enterprise modeling capabilities in BPM Composer These are only a few points from what is coming with 12c. We are really looking forward for the new realese to come out, because this seems to be really great stuff. The suite becomes more and more integrated. From 10g to 11g it was an evolution in terms of developing SOA-based applications. With 12c, Oracle continues it’s way – very impressive. Adaptive Case Management Another fantastic topic was Adaptive Case Management (ACM). The Oracle PMs did a great job especially at the demo grounds in showing the upcoming Case Management UI (will be available in 11g with the next BPM Suite MLR Patch), the roadmap and the differences between traditional business process modeling. They have been very busy during the conference because a lot of partners and customers have been interested Big Data Big Data is one of the current hype themes. Because of huge data amounts from different internal or external sources, the handling of these data becomes more and more challenging. Companies have a need for analyzing the data to optimize their business. The challenge is here: the amount of data is growing daily! To store and analyze the data efficiently, it is necessary to have a scalable and flexible infrastructure. Here it is important that hardware and software are engineered to work together. Therefore several new features of the Oracle Database 12c, like the new in-memory option, have been presented by Larry Ellison himself. From a hardware side new server machines like Fujitsu M10 or new processors, such as Oracle’s new M6-32 have been announced. The performance improvements, when using one of these hardware components in connection with the improved software solutions were really impressive. For more details about this, please take look at our previous blog post. Regarding Big Data, Oracle also introduced their Big Data architecture, which consists of: Oracle Big Data Appliance that is preconfigured with Hadoop Oracle Exdata which stores a huge amount of data efficently, to achieve optimal query performance Oracle Exalytics as a fast and scalable Business analytics system Analysis of the stored data can be performed using SQL, by streaming the data directly from Hadoop to an Oracle Database 12c. Alternatively the analysis can be directly implemented in Hadoop using “R”. In addition Oracle BI Tools can be used to analyze the data. Fast Data Fast Data is a complementary approach to Big Data. A huge amount of mostly unstructured data comes in via different channels with a high frequency. The analysis of these data streams is also important for companies, because the incoming data has to be analyzed regarding business-relevant patterns in real-time. Therefore these patterns must be identified efficiently and performant. To do so, in-memory grid solutions in combination with Oracle Coherence and Oracle Event Processing demonstrated very impressive how efficient real-time data processing can be. One example for Fast Data solutions that was shown during the OOW was the analysis of twitter streams regarding customer satisfaction. The feeds with negative words like “bad” or “worse” have been filtered and after a defined treshold has been reached in a certain timeframe, a business event was triggered. Cloud Another key trend in the IT market is of course Cloud Computing and what it means for companies and their businesses. Oracle announced their Cloud strategy and vision – companies can focus on their real business while all of the applications are available via Cloud. This also includes Oracle Database or Oracle Weblogic, so that companies can also build, deploy and run their own applications within the cloud. Three different approaches have been introduced: Infrastructure as a Service (IaaS) Platform as a Service (PaaS) Software as a Service (SaaS) Using the IaaS approach only the infrastructure components will be managed in the Cloud. Customers will be very flexible regarding memory, storage or number of CPUs because those parameters can be adjusted elastically. The PaaS approach means that besides the infrastructure also the platforms (such as databases or application servers) necessary for running applications will be provided within the Cloud. Here customers can also decide, if installation and management of these infrastructure components should be done by Oracle. The SaaS approach describes the most complete one, hence all applications a company uses are managed in the Cloud. Oracle is planning to provide all of their applications, like ERP systems or HR applications, as Cloud services. In conclusion this seems to be a very forward-thinking strategy, which opens up new possibilities for customers to manage their infrastructure and applications in a flexible, scalable and future-oriented manner. As you can see, our OOW days have been very very interresting. We collected many helpful informations for our projects. The new innovations presented at the confernce are great and being part of this was even greater! We are looking forward to next years’ conference! Links: http://www.oracle.com/openworld/index.html http://thecattlecrew.wordpress.com/2013/09/23/first-impressions-from-oracle-open-world-2013 SOA & BPM Partner Community For regular information on Oracle SOA Suite become a member in the SOA & BPM Partner Community for registration please visit www.oracle.com/goto/emea/soa (OPN account required) If you need support with your account please contact the Oracle Partner Business Center. Blog Twitter LinkedIn Facebook Wiki Mix Forum Technorati Tags: cattleCrew,Sven Bernhard,OOW2013,SOA Community,Oracle SOA,Oracle BPM,Community,OPN,Jürgen Kress

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  • External File Upload Optimizations for Windows Azure

    - by rgillen
    [Cross posted from here: http://rob.gillenfamily.net/post/External-File-Upload-Optimizations-for-Windows-Azure.aspx] I’m wrapping up a bit of the work we’ve been doing on data movement optimizations for cloud computing and the latest set of data yielded some interesting points I thought I’d share. The work done here is not really rocket science but may, in some ways, be slightly counter-intuitive and therefore seemed worthy of posting. Summary: for those who don’t like to read detailed posts or don’t have time, the synopsis is that if you are uploading data to Azure, block your data (even down to 1MB) and upload in parallel. Set your block size based on your source file size, but if you must choose a fixed value, use 1MB. Following the above will result in significant performance gains… upwards of 10x-24x and a reduction in overall file transfer time of upwards of 90% (eg, uploading a 1GB file averaged 46.37 minutes prior to optimizations and averaged 1.86 minutes afterwards). Detail: For those of you who want more detail, or think that the claims at the end of the preceding paragraph are over-reaching, what follows is information and code supporting these claims. As the title would indicate, these tests were run from our research facility pointing to the Azure cloud (specifically US North Central as it is physically closest to us) and do not represent intra-cloud results… we have performed intra-cloud tests and the overall results are similar in notion but the data rates are significantly different as well as the tipping points for the various block sizes… this will be detailed separately). We started by building a very simple console application that would loop through a directory and upload each file to Azure storage. This application used the shipping storage client library from the 1.1 version of the azure tools. The only real variation from the client library is that we added code to collect and record the duration (in ms) and size (in bytes) for each file transferred. The code is available here. We then created a directory that had a collection of files for the following sizes: 2KB, 32KB, 64KB, 128KB, 512KB, 1MB, 5MB, 10MB, 25MB, 50MB, 100MB, 250MB, 500MB, 750MB, and 1GB (50 files for each size listed). These files contained randomly-generated binary data and do not benefit from compression (a separate discussion topic). Our file generation tool is available here. The baseline was established by running the application described above against the directory containing all of the data files. This application uploads the files in a random order so as to avoid transferring all of the files of a given size sequentially and thereby spreading the affects of periodic Internet delays across the collection of results.  We then ran some scripts to split the resulting data and generate some reports. The raw data collected for our non-optimized tests is available via the links in the Related Resources section at the bottom of this post. For each file size, we calculated the average upload time (and standard deviation) and the average transfer rate (and standard deviation). As you likely are aware, transferring data across the Internet is susceptible to many transient delays which can cause anomalies in the resulting data. It is for this reason that we randomized the order of source file processing as well as executed the tests 50x for each file size. We expect that these steps will yield a sufficiently balanced set of results. Once the baseline was collected and analyzed, we updated the test harness application with some methods to split the source file into user-defined block sizes and then to upload those blocks in parallel (using the PutBlock() method of Azure storage). The parallelization was handled by simply relying on the Parallel Extensions to .NET to provide a Parallel.For loop (see linked source for specific implementation details in Program.cs, line 173 and following… less than 100 lines total). Once all of the blocks were uploaded, we called PutBlockList() to assemble/commit the file in Azure storage. For each block transferred, the MD5 was calculated and sent ensuring that the bits that arrived matched was was intended. The timer for the blocked/parallelized transfer method wraps the entire process (source file splitting, block transfer, MD5 validation, file committal). A diagram of the process is as follows: We then tested the affects of blocking & parallelizing the transfers by running the updated application against the same source set and did a parameter sweep on the block size including 256KB, 512KB, 1MB, 2MB, and 4MB (our assumption was that anything lower than 256KB wasn’t worth the trouble and 4MB is the maximum size of a block supported by Azure). The raw data for the parallel tests is available via the links in the Related Resources section at the bottom of this post. This data was processed and then compared against the single-threaded / non-optimized transfer numbers and the results were encouraging. The Excel version of the results is available here. Two semi-obvious points need to be made prior to reviewing the data. The first is that if the block size is larger than the source file size you will end up with a “negative optimization” due to the overhead of attempting to block and parallelize. The second is that as the files get smaller, the clock-time cost of blocking and parallelizing (overhead) is more apparent and can tend towards negative optimizations. For this reason (and is supported in the raw data provided in the linked worksheet) the charts and dialog below ignore source file sizes less than 1MB. (click chart for full size image) The chart above illustrates some interesting points about the results: When the block size is smaller than the source file, performance increases but as the block size approaches and then passes the source file size, you see decreasing benefit to the point of negative gains (see the values for the 1MB file size) For some of the moderately-sized source files, small blocks (256KB) are best As the size of the source file gets larger (see values for 50MB and up), the smallest block size is not the most efficient (presumably due, at least in part, to the increased number of blocks, increased number of individual transfer requests, and reassembly/committal costs). Once you pass the 250MB source file size, the difference in rate for 1MB to 4MB blocks is more-or-less constant The 1MB block size gives the best average improvement (~16x) but the optimal approach would be to vary the block size based on the size of the source file.    (click chart for full size image) The above is another view of the same data as the prior chart just with the axis changed (x-axis represents file size and plotted data shows improvement by block size). It again highlights the fact that the 1MB block size is probably the best overall size but highlights the benefits of some of the other block sizes at different source file sizes. This last chart shows the change in total duration of the file uploads based on different block sizes for the source file sizes. Nothing really new here other than this view of the data highlights the negative affects of poorly choosing a block size for smaller files.   Summary What we have found so far is that blocking your file uploads and uploading them in parallel results in significant performance improvements. Further, utilizing extension methods and the Task Parallel Library (.NET 4.0) make short work of altering the shipping client library to provide this functionality while minimizing the amount of change to existing applications that might be using the client library for other interactions.   Related Resources Source code for upload test application Source code for random file generator ODatas feed of raw data from non-optimized transfer tests Experiment Metadata Experiment Datasets 2KB Uploads 32KB Uploads 64KB Uploads 128KB Uploads 256KB Uploads 512KB Uploads 1MB Uploads 5MB Uploads 10MB Uploads 25MB Uploads 50MB Uploads 100MB Uploads 250MB Uploads 500MB Uploads 750MB Uploads 1GB Uploads Raw Data OData feeds of raw data from blocked/parallelized transfer tests Experiment Metadata Experiment Datasets Raw Data 256KB Blocks 512KB Blocks 1MB Blocks 2MB Blocks 4MB Blocks Excel worksheet showing summarizations and comparisons

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