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  • How to merge VB.NET WEB Project with C#.NET MVC project

    - by Thushara Perera
    Hi All, I've got an existing asp.net project written in vb.net need to merge into C# ASP.NET MVC 1.0 application. I couldn't find a good article on this. I have successfully created a sample project and merge it. It works successfully. But when merge it into my real project it does not work. I've used C#.csproj project file and deleted VB project file. for the merging i could find a good article this link successful on sample project not with the real project. good one: http://www.packtpub.com/article/mixing-asp.net-webforms-and-asp.net-mvc how it is possible to merge VB Default.aspx, C# Default.aspx and VB Global.asax, C# Global.asax. Can I used VB.vbproj file insted of csproj Thanks Thushara Perera

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  • using araxis merge for folder comparison on git branches (OSX)

    - by memo
    I know how to setup araxis merge to be my git diff / merge tool, so if I do git difftool it automatically launches araxis merge. However if I do git difftool upstream/master (to see all the differences between current branch and upstream/master), it launches the app one by one for every single file that is different. Is there a way of setting it up so I can get a folder comparison type view, and then go down and view each file diff as I choose? i.e. similar to this http://www.araxis.com/merge_mac/overview2.html The only way I've found to do this is to clone my repo into a new folder, switch to the branch there, and then do a normal araxis merge folder comparison.

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  • SCD2 + Merge Statement + MSSQL

    - by Nev_Rahd
    I am trying work out with MERGE statment to Insert / Update Dimension Table of Type SCD2 My source is a Table var to Merge with Dimension table. My Merget statement is throwing an error as: The target table 'DM.DATA_ERROR.ERROR_DIMENSION' of the INSERT statement cannot be on either side of a (primary key, foreign key) relationship when the FROM clause contains a nested INSERT, UPDATE, DELETE, or MERGE statement. Found reference constraint 'FK_ERROR_DIMENSION_to_AUDIT_CreatedBy'. My Merge Statement: DECLARE @DATAERROROBJECT AS [ERROR_DIMENSION] INSERT INTO DM.DATA_ERROR.ERROR_DIMENSION SELECT ERROR_CODE, DATA_STREAM_ID, [ERROR_SEVERITY], DATA_QUALITY_RATING, ERROR_LONG_DESCRIPTION, ERROR_DESCRIPTION, VALIDATION_RULE, ERROR_TYPE, ERROR_CLASS, VALID_FROM, VALID_TO, CURR_FLAG, CREATED_BY_AUDIT_SK, UPDATED_BY_AUDIT_SK FROM (MERGE DM.DATA_ERROR.ERROR_DIMENSION ED USING @DATAERROROBJECT OBJ ON(ED.ERROR_CODE = OBJ.ERROR_CODE AND ED.DATA_STREAM_ID = OBJ.DATA_STREAM_ID) WHEN NOT MATCHED THEN INSERT VALUES( OBJ.ERROR_CODE ,OBJ.DATA_STREAM_ID ,OBJ.[ERROR_SEVERITY] ,OBJ.DATA_QUALITY_RATING ,OBJ.ERROR_LONG_DESCRIPTION ,OBJ.ERROR_DESCRIPTION ,OBJ.VALIDATION_RULE ,OBJ.ERROR_TYPE ,OBJ.ERROR_CLASS ,GETDATE() ,'9999-12-13' ,'Y' ,1 ,1 ) WHEN MATCHED AND ED.CURR_FLAG = 'Y' AND ( ED.[ERROR_SEVERITY] <> OBJ.[ERROR_SEVERITY] OR ED.[DATA_QUALITY_RATING] <> OBJ.[DATA_QUALITY_RATING] OR ED.[ERROR_LONG_DESCRIPTION] <> OBJ.[ERROR_LONG_DESCRIPTION] OR ED.[ERROR_DESCRIPTION] <> OBJ.[ERROR_DESCRIPTION] OR ED.[VALIDATION_RULE] <> OBJ.[VALIDATION_RULE] OR ED.[ERROR_TYPE] <> OBJ.[ERROR_TYPE] OR ED.[ERROR_CLASS] <> OBJ.[ERROR_CLASS] ) THEN UPDATE SET ED.CURR_FLAG = 'N', ED.VALID_TO = GETDATE() OUTPUT $ACTION ACTION_OUT, OBJ.ERROR_CODE ERROR_CODE, OBJ.DATA_STREAM_ID DATA_STREAM_ID, OBJ.[ERROR_SEVERITY] [ERROR_SEVERITY], OBJ.DATA_QUALITY_RATING DATA_QUALITY_RATING, OBJ.ERROR_LONG_DESCRIPTION ERROR_LONG_DESCRIPTION, OBJ.ERROR_DESCRIPTION ERROR_DESCRIPTION, OBJ.VALIDATION_RULE VALIDATION_RULE, OBJ.ERROR_TYPE ERROR_TYPE, OBJ.ERROR_CLASS ERROR_CLASS, GETDATE() VALID_FROM, '9999-12-31' VALID_TO, 'Y' CURR_FLAG, 555 CREATED_BY_AUDIT_SK, 555 UPDATED_BY_AUDIT_SK ) AS MERGE_OUT WHERE MERGE_OUT.ACTION_OUT = 'UPDATE'; What am i doing wrong ?

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  • SVN Merge returns nothing...

    - by Mike
    Here is the scenario: Windows Vista environment. SVN version 1.6.11. I'm on my branch directory. I want to update my branch with a particular change from my trunk. Using command line (using SlikSVN) I enter the following and it returns nothing (returns a blank line and no merge occurs): svn merge -r 11846:11891 http://trunk//AppConstants.java When I do the equivalent using Tortoise SVN, it says "Completed" but nothing gets merged either. When I do a svn diff I clearly see the differences I want to merge in from the trunk to my branch. The diff command I am using is svn diff -r 11846:11891 http://trunk//AppConstants.java. Can anyone figure why no merge occurs? Thanks!!!

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  • Diff/Merge functionality for objects (not files!)

    - by gehho
    I have a collection of objects of the same type, let's call it DataItem. The user can view and edit these items in an editor. It should also be possible to compare and merge different items, i.e. some sort of diff/merge for DataItem instances. The DIFF functionality should compare all (relevant) properties/fields of the items and detect possible differences. The MERGE functionality should then be able to merge two instances by applying selected differences to one of the items. For example (pseudo objects): DataItem1 { DataItem2 { Prop1 = 10 Prop1 = 10 Prop2 = 25 Prop2 = 13 Prop3 = 0 Prop3 = 5 Coll = { 7, 4, 8 } Coll = { 7, 4, 8, 12 } } } Now, the user should be provided with a list of differences (i.e. Prop2, Prop3, and Coll) and he should be able to select which differences he wants to eliminate by assigning the value from one item to the other. He should also be able to choose if he wants to assign the value from DataItem1 to DataItem2 or vice versa. Are there common practices which should be used to implement this functionality? Since the same editor should also provide undo/redo functionality (using the Command pattern), I was thinking about reusing the ICommand implementations because both scenarios basically handle with property assignments, collection changes, and so on... My idea was to create Difference objects with ICommand properties which can be used to perform a merge operation for this specific Difference. Btw: The programming language will be C# with .NET 3.5SP1/4.0. However, I think this is more of a language-independent question. Any design pattern/idea/whatsoever is welcome!

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  • Efficient alternatives to merge for larger data.frames R

    - by Etienne Low-Décarie
    I am looking for an efficient (both computer resource wise and learning/implementation wise) method to merge two larger (size1 million / 300 KB RData file) data frames. "merge" in base R and "join" in plyr appear to use up all my memory effectively crashing my system. Example load test data frame and try test.merged<-merge(test, test) or test.merged<-join(test, test, type="all") - The following post provides a list of merge and alternatives: How to join data frames in R (inner, outer, left, right)? The following allows object size inspection: https://heuristically.wordpress.com/2010/01/04/r-memory-usage-statistics-variable/ Data produced by anonym

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  • merge values from excel file into .html file opened in word 2007

    - by Kelbizzle
    I have this newsletter I've written. I want to be able to use the values in the rows and some how have them merged into this html file I have opened in word. Sort of like a mail merge. In the newsletter I have 3 urls that look like: www.mydomain.com/php?id= I want to be able to replace all of the urls for all 230 records in the excel file. With something like: www.mydomain.com/?id=$id Where $id would get replaced with the id of the record. And the same goes for the rest of the rows like $firstname $lastname $email $phone number Is there a simple way to do this?

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  • SVN Merge two reposiories - what about the UUIDs?

    - by grant007
    Hi, This is my scenario: Originally had two seperate repositories, I need to merge these into one repository. I don't care too much about the history in these repositories. I created a new repository and can import the repositories no problem. The issue is with users working copies, I can ask them to switch --relocate them however there is the issue of the UUID which will be different for each original repository: I can only reassign the UUID in the new repository to match one of the original repositories. So what is the best method to resolve this issue? (I suspect/hope I am going about this wrong...) Any ideas appreciated! -Grant.

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  • Problems with merge replication

    - by jess
    Hi, We are developing a multi-user desktop application with users located in different countries. The platform is - .net 3.5, SQL Server 2008, WinForms. Now, my client has used the help of a DBA who has implemented merge replication. To facilitate replication, we made all our primary keys as GUID. Now, we are facing these issues with replication - subscribers expiration sometimes stops replication and we have found no clean way to re-add every change to db schema requires to poll the whole data all over again! This seems to be strange, what could be the problem here? Also, sometimes we have duplicate keys, and that too stops replication I am sure these issues can be resolved. Maybe, we have not gone the right way to implement. Can you suggest how to go about implementing. Or, is the above information enough to diagnose the problem?

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  • Merge Visio files

    - by David Stratton
    I know I can do this manually by using copy/paste but I'm looking for a simpler way. Does anyone know of a quick and easy way to merge Visio documents? I have several Visio vsd files, all of which are the same internal document type (Flowchart - US Units). Each of these has between 1 and 15 pages. I'd like to combine them all into one Visio file. I'm using Visio for Enterprise Architects (11.4301.8221) so if there's a procedure for doing it in that version, that's what I'm looking for, but a 3rd party tool or a macro would work as well.

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  • Colour table cells in Microsoft Word after mail merge

    - by James
    I have an Excel spreadsheet of student data. For each of 30 topics, students are traffic lighted R, A or G (for red, amber, green) in the spreadsheet. I am mail merging individual result print-outs in Word 2010. However, rather than printing the letter R/A/G next to each topic, I would rather change the background colour of the cell to that colour. How can I do this? Is there an option with merge fields or can it be done with a macro (please provide sample code if so - I don't have experience with macros!)

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  • excel - merge cells including a zip code

    - by evanmcd
    Hi all, I have the need to merge a bunch of cells that comprise an address (street, city, state, zip) into a single cell. No problem except with the zip code. The zip cell has only 4 digits for any zip that starts with 0. So, I change it's format to be Special - Zip Code. That makes the cell itself show the beginning 0, but the merged cell still does not show the leading 0. Does anyone know how to get the leading 0 in the merged column? Thanks Evan

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  • Merge Publication Data Partition Snapshot generation

    - by David Osborn
    I have a merge publication in SQL 2008 R2 with data partitions and I am wondering when I should generate the snapshots for the data partitions. I get an error sometimes when bringing a new subscribe online related to the partition snapshot being out of date and I am wondering if this has to do with the publication snapshot being scheduled at the same time as the partition snapshots. I'm not really sure how the partition snapshot gets generated, but it appears maybe it is getting generated before the publication snapshot. If this is the case how should I be scheduling the partition snapshots to get generated? Should I set them to run x number of minutes after the publication snapshot? this seems kind of poor to do in case the publication snapshot takes awhile or fails. It seems to me the publication snapshot should just run the data partition snapshot agents when it is done if this is the case.

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  • Which non-clustered index should I use?

    - by Junior Mayhé
    Here I am studying nonclustered indexes on SQL Server Management Studio. I've created a table with more than 1 million records. This table has a primary key. CREATE TABLE [dbo].[Customers]( [CustomerId] [int] IDENTITY(1,1) NOT NULL, [CustomerName] [varchar](100) NOT NULL, [Deleted] [bit] NOT NULL, [Active] [bit] NOT NULL, CONSTRAINT [PK_Customers] PRIMARY KEY CLUSTERED ( [CustomerId] ASC )WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY] ) ON [PRIMARY] This is the query I'll be using to see what execution plan is showing: SELECT CustomerName FROM Customers Well, executing this command with no additional non-clustered index, it leads the execution plan to show me: I/O cost = 3.45646 Operator cost = 4.57715 Now I'm trying to see if it's possible to improve performance, so I've created a non-clustered index for this table: 1) First non-clustered index CREATE NONCLUSTERED INDEX [IX_CustomerID_CustomerName] ON [dbo].[Customers] ( [CustomerId] ASC, [CustomerName] ASC )WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, SORT_IN_TEMPDB = OFF, IGNORE_DUP_KEY = OFF, DROP_EXISTING = OFF, ONLINE = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY] GO Executing again the select against Customers table, the execution plan shows me: I/O cost = 2.79942 Operator cost = 3.92001 It seems better. Now I've deleted this just created non-clustered index, in order to create a new one: 2) First non-clustered index CREATE NONCLUSTERED INDEX [IX_CustomerIDIncludeCustomerName] ON [dbo].[Customers] ( [CustomerId] ASC ) INCLUDE ( [CustomerName]) WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, SORT_IN_TEMPDB = OFF, IGNORE_DUP_KEY = OFF, DROP_EXISTING = OFF, ONLINE = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY] GO With this new non-clustered index, I've executed the select statement again and the execution plan shows me the same result: I/O cost = 2.79942 Operator cost = 3.92001 So, which non-clustered index should I use? Why the costs are the same on execution plan for I/O and Operator? Am I doing something wrong or this is expected? thank you

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  • Create an index only on certain rows in mysql

    - by dhruvbird
    So, I have this funny requirement of creating an index on a table only on a certain set of rows. This is what my table looks like: USER: userid, friendid, created, blah0, blah1, ..., blahN Now, I'd like to create an index on: (userid, friendid, created) but only on those rows where userid = friendid. The reason being that this index is only going to be used to satisfy queries where the WHERE clause contains "userid = friendid". There will be many rows where this is NOT the case, and I really don't want to waste all that extra space on the index. Another option would be to create a table (query table) which is populated on insert/update of this table and create a trigger to do so, but again I am guessing an index on that table would mean that the data would be stored twice. How does mysql store Primary Keys? I mean is the table ordered on the Primary Key or is it ordered by insert order and the PK is like a normal unique index? I checked up on clustered indexes (http://dev.mysql.com/doc/refman/5.0/en/innodb-index-types.html), but it seems only InnoDB supports them. I am using MyISAM (I mention this because then I could have created a clustered index on these 3 fields in the query table). I am basically looking for something like this: ALTER TABLE USERS ADD INDEX (userid, friendid, created) WHERE userid=friendid

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  • SQL Server 2005 Merge Replication to SQL Server CE 3.5

    - by user33067
    Hi, In my organization, we have a SQL Server 2005 database server (DBServer). Users of an application will normally be connected to DBServer, but, occasionally, would like to disconnect and continue their work on a laptop using SQL Server Compact Edition 3.5 (SQLCE). Due to this, we have been looking into using Merge Replication between the DBServer and SQLCE. From what I have read about this process, IIS must be installed on "the server"... yet, I have found no indication to whether this is talking about DBServer or SQLCE. I had assumed the documentation was referring to DBServer and proposed this to our networking staff. That idea was quickly put to rest as it is not our policy to install IIS on an internal server. This is where our SQL Server 2005 web server (WebServer) entered the picture. The idea being that IIS would be installed on WebServer and would be the conduit for DBServer and SQLCE to communicate. This sounded like a good idea at first, until I started looking for documentation on this type of setup. Everything I have been able deals with a DBServer -- SQLCE -- DBServer setup... nothing on DBServer -- WebServer -- SQLCE -- WebServer -- DBServer. Questions: Is going with a 3 server setup ideal? Does anyone have documentation on this type of setup? Does IIS even need to be running on one of the big servers, or can it just run off the laptop with SQLCE on it? (I'd really like this option ;))

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  • Html index page and files in that directory

    - by Frank
    On my web site, there is an index page, but if I take out that index page, users will see the files in that directory, for instance my site is : XYZ.com and I have a directory called "My_Dir", so when a user typed in "XYZ.com/My_Dir" he will see the index.html if there is one, but if it's not there, he will see a list of all my files inside "My_Dir", so is it safe to assume that with an index page in any of my sub directories, I can hide all the files in those directories from users, in other words if I have "123.txt, abc.html and index.html" in "My_Dir", users won't be able to see "123.txt, abc.html" because of the existence of "index.html" [ unless of course I mention those two files inside index.html ] ? Frank

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  • VS 11 Beta merge tool is awesome, except for resovling conflicts

    - by deadlydog
    If you've downloaded the new VS 11 Beta and done any merging, then you've probably seen the new diff and merge tools built into VS 11.  They are awesome, and by far a vast improvement over the ones included in VS 2010.  There is one problem with the merge tool though, and in my opinion it is huge.Basically the problem with the new VS 11 Beta merge tool is that when you are resolving conflicts after performing a merge, you cannot tell what changes were made in each file where the code is conflicting.  Was the conflicting code added, deleted, or modified in the source and target branches?  I don't know (without explicitly opening up the history of both the source and target files), and the merge tool doesn't tell me.  In my opinion this is a huge fail on the part of the designers/developers of the merge tool, as it actually forces me to either spend an extra minute for every conflict to view the source and target file history, or to go back to use the merge tool in VS 2010 to properly assess which changes I should take.I submitted this as a bug to Microsoft, but they say that this is intentional by design. WHAT?! So they purposely crippled their tool in order to make it pretty and keep the look consistent with the new diff tool?  That's like purposely putting a little hole in the bottom of your cup for design reasons to make it look cool.  Sure, the cup looks cool, but I'm not going to use it if it leaks all over the place and doesn't do the job that it is intended for. Bah! but I digress.Because this bug is apparently a feature, they asked me to open up a "feature request" to have the problem fixed. Please go vote up both my bug submission and the feature request so that this tool will actually be useful by the time the final VS 11 product is released.

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  • Unexpected performance curve from CPython merge sort

    - by vkazanov
    I have implemented a naive merge sorting algorithm in Python. Algorithm and test code is below: import time import random import matplotlib.pyplot as plt import math from collections import deque def sort(unsorted): if len(unsorted) <= 1: return unsorted to_merge = deque(deque([elem]) for elem in unsorted) while len(to_merge) > 1: left = to_merge.popleft() right = to_merge.popleft() to_merge.append(merge(left, right)) return to_merge.pop() def merge(left, right): result = deque() while left or right: if left and right: elem = left.popleft() if left[0] > right[0] else right.popleft() elif not left and right: elem = right.popleft() elif not right and left: elem = left.popleft() result.append(elem) return result LOOP_COUNT = 100 START_N = 1 END_N = 1000 def test(fun, test_data): start = time.clock() for _ in xrange(LOOP_COUNT): fun(test_data) return time.clock() - start def run_test(): timings, elem_nums = [], [] test_data = random.sample(xrange(100000), END_N) for i in xrange(START_N, END_N): loop_test_data = test_data[:i] elapsed = test(sort, loop_test_data) timings.append(elapsed) elem_nums.append(len(loop_test_data)) print "%f s --- %d elems" % (elapsed, len(loop_test_data)) plt.plot(elem_nums, timings) plt.show() run_test() As much as I can see everything is OK and I should get a nice N*logN curve as a result. But the picture differs a bit: Things I've tried to investigate the issue: PyPy. The curve is ok. Disabled the GC using the gc module. Wrong guess. Debug output showed that it doesn't even run until the end of the test. Memory profiling using meliae - nothing special or suspicious. ` I had another implementation (a recursive one using the same merge function), it acts the similar way. The more full test cycles I create - the more "jumps" there are in the curve. So how can this behaviour be explained and - hopefully - fixed? UPD: changed lists to collections.deque UPD2: added the full test code UPD3: I use Python 2.7.1 on a Ubuntu 11.04 OS, using a quad-core 2Hz notebook. I tried to turn of most of all other processes: the number of spikes went down but at least one of them was still there.

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  • What options are there to do a mail merge?

    - by Jon Cage
    I tried (and failed) to do a mail merge to send a generic(ish) mail merge to send a bunch of emails using Thunderbird with the the Mail Merge addon but couldn't get it to work. What other options exist to quickly and simply set up a mail merge under windows?

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  • Upload File to Windows Azure Blob in Chunks through ASP.NET MVC, JavaScript and HTML5

    - by Shaun
    Originally posted on: http://geekswithblogs.net/shaunxu/archive/2013/07/01/upload-file-to-windows-azure-blob-in-chunks-through-asp.net.aspxMany people are using Windows Azure Blob Storage to store their data in the cloud. Blob storage provides 99.9% availability with easy-to-use API through .NET SDK and HTTP REST. For example, we can store JavaScript files, images, documents in blob storage when we are building an ASP.NET web application on a Web Role in Windows Azure. Or we can store our VHD files in blob and mount it as a hard drive in our cloud service. If you are familiar with Windows Azure, you should know that there are two kinds of blob: page blob and block blob. The page blob is optimized for random read and write, which is very useful when you need to store VHD files. The block blob is optimized for sequential/chunk read and write, which has more common usage. Since we can upload block blob in blocks through BlockBlob.PutBlock, and them commit them as a whole blob with invoking the BlockBlob.PutBlockList, it is very powerful to upload large files, as we can upload blocks in parallel, and provide pause-resume feature. There are many documents, articles and blog posts described on how to upload a block blob. Most of them are focus on the server side, which means when you had received a big file, stream or binaries, how to upload them into blob storage in blocks through .NET SDK.  But the problem is, how can we upload these large files from client side, for example, a browser. This questioned to me when I was working with a Chinese customer to help them build a network disk production on top of azure. The end users upload their files from the web portal, and then the files will be stored in blob storage from the Web Role. My goal is to find the best way to transform the file from client (end user’s machine) to the server (Web Role) through browser. In this post I will demonstrate and describe what I had done, to upload large file in chunks with high speed, and save them as blocks into Windows Azure Blob Storage.   Traditional Upload, Works with Limitation The simplest way to implement this requirement is to create a web page with a form that contains a file input element and a submit button. 1: @using (Html.BeginForm("About", "Index", FormMethod.Post, new { enctype = "multipart/form-data" })) 2: { 3: <input type="file" name="file" /> 4: <input type="submit" value="upload" /> 5: } And then in the backend controller, we retrieve the whole content of this file and upload it in to the blob storage through .NET SDK. We can split the file in blocks and upload them in parallel and commit. The code had been well blogged in the community. 1: [HttpPost] 2: public ActionResult About(HttpPostedFileBase file) 3: { 4: var container = _client.GetContainerReference("test"); 5: container.CreateIfNotExists(); 6: var blob = container.GetBlockBlobReference(file.FileName); 7: var blockDataList = new Dictionary<string, byte[]>(); 8: using (var stream = file.InputStream) 9: { 10: var blockSizeInKB = 1024; 11: var offset = 0; 12: var index = 0; 13: while (offset < stream.Length) 14: { 15: var readLength = Math.Min(1024 * blockSizeInKB, (int)stream.Length - offset); 16: var blockData = new byte[readLength]; 17: offset += stream.Read(blockData, 0, readLength); 18: blockDataList.Add(Convert.ToBase64String(BitConverter.GetBytes(index)), blockData); 19:  20: index++; 21: } 22: } 23:  24: Parallel.ForEach(blockDataList, (bi) => 25: { 26: blob.PutBlock(bi.Key, new MemoryStream(bi.Value), null); 27: }); 28: blob.PutBlockList(blockDataList.Select(b => b.Key).ToArray()); 29:  30: return RedirectToAction("About"); 31: } This works perfect if we selected an image, a music or a small video to upload. But if I selected a large file, let’s say a 6GB HD-movie, after upload for about few minutes the page will be shown as below and the upload will be terminated. In ASP.NET there is a limitation of request length and the maximized request length is defined in the web.config file. It’s a number which less than about 4GB. So if we want to upload a really big file, we cannot simply implement in this way. Also, in Windows Azure, a cloud service network load balancer will terminate the connection if exceed the timeout period. From my test the timeout looks like 2 - 3 minutes. Hence, when we need to upload a large file we cannot just use the basic HTML elements. Besides the limitation mentioned above, the simple HTML file upload cannot provide rich upload experience such as chunk upload, pause and pause-resume. So we need to find a better way to upload large file from the client to the server.   Upload in Chunks through HTML5 and JavaScript In order to break those limitation mentioned above we will try to upload the large file in chunks. This takes some benefit to us such as - No request size limitation: Since we upload in chunks, we can define the request size for each chunks regardless how big the entire file is. - No timeout problem: The size of chunks are controlled by us, which means we should be able to make sure request for each chunk upload will not exceed the timeout period of both ASP.NET and Windows Azure load balancer. It was a big challenge to upload big file in chunks until we have HTML5. There are some new features and improvements introduced in HTML5 and we will use them to implement our solution.   In HTML5, the File interface had been improved with a new method called “slice”. It can be used to read part of the file by specifying the start byte index and the end byte index. For example if the entire file was 1024 bytes, file.slice(512, 768) will read the part of this file from the 512nd byte to 768th byte, and return a new object of interface called "Blob”, which you can treat as an array of bytes. In fact,  a Blob object represents a file-like object of immutable, raw data. The File interface is based on Blob, inheriting blob functionality and expanding it to support files on the user's system. For more information about the Blob please refer here. File and Blob is very useful to implement the chunk upload. We will use File interface to represent the file the user selected from the browser and then use File.slice to read the file in chunks in the size we wanted. For example, if we wanted to upload a 10MB file with 512KB chunks, then we can read it in 512KB blobs by using File.slice in a loop.   Assuming we have a web page as below. User can select a file, an input box to specify the block size in KB and a button to start upload. 1: <div> 2: <input type="file" id="upload_files" name="files[]" /><br /> 3: Block Size: <input type="number" id="block_size" value="512" name="block_size" />KB<br /> 4: <input type="button" id="upload_button_blob" name="upload" value="upload (blob)" /> 5: </div> Then we can have the JavaScript function to upload the file in chunks when user clicked the button. 1: <script type="text/javascript"> 1: 2: $(function () { 3: $("#upload_button_blob").click(function () { 4: }); 5: });</script> Firstly we need to ensure the client browser supports the interfaces we are going to use. Just try to invoke the File, Blob and FormData from the “window” object. If any of them is “undefined” the condition result will be “false” which means your browser doesn’t support these premium feature and it’s time for you to get your browser updated. FormData is another new feature we are going to use in the future. It could generate a temporary form for us. We will use this interface to create a form with chunk and associated metadata when invoked the service through ajax. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: if (window.File && window.Blob && window.FormData) { 4: alert("Your brwoser is awesome, let's rock!"); 5: } 6: else { 7: alert("Oh man plz update to a modern browser before try is cool stuff out."); 8: return; 9: } 10: }); Each browser supports these interfaces by their own implementation and currently the Blob, File and File.slice are supported by Chrome 21, FireFox 13, IE 10, Opera 12 and Safari 5.1 or higher. After that we worked on the files the user selected one by one since in HTML5, user can select multiple files in one file input box. 1: var files = $("#upload_files")[0].files; 2: for (var i = 0; i < files.length; i++) { 3: var file = files[i]; 4: var fileSize = file.size; 5: var fileName = file.name; 6: } Next, we calculated the start index and end index for each chunks based on the size the user specified from the browser. We put them into an array with the file name and the index, which will be used when we upload chunks into Windows Azure Blob Storage as blocks since we need to specify the target blob name and the block index. At the same time we will store the list of all indexes into another variant which will be used to commit blocks into blob in Azure Storage once all chunks had been uploaded successfully. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10:  11: // calculate the start and end byte index for each blocks(chunks) 12: // with the index, file name and index list for future using 13: var blockSizeInKB = $("#block_size").val(); 14: var blockSize = blockSizeInKB * 1024; 15: var blocks = []; 16: var offset = 0; 17: var index = 0; 18: var list = ""; 19: while (offset < fileSize) { 20: var start = offset; 21: var end = Math.min(offset + blockSize, fileSize); 22:  23: blocks.push({ 24: name: fileName, 25: index: index, 26: start: start, 27: end: end 28: }); 29: list += index + ","; 30:  31: offset = end; 32: index++; 33: } 34: } 35: }); Now we have all chunks’ information ready. The next step should be upload them one by one to the server side, and at the server side when received a chunk it will upload as a block into Blob Storage, and finally commit them with the index list through BlockBlobClient.PutBlockList. But since all these invokes are ajax calling, which means not synchronized call. So we need to introduce a new JavaScript library to help us coordinate the asynchronize operation, which named “async.js”. You can download this JavaScript library here, and you can find the document here. I will not explain this library too much in this post. We will put all procedures we want to execute as a function array, and pass into the proper function defined in async.js to let it help us to control the execution sequence, in series or in parallel. Hence we will define an array and put the function for chunk upload into this array. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4:  5: // start to upload each files in chunks 6: var files = $("#upload_files")[0].files; 7: for (var i = 0; i < files.length; i++) { 8: var file = files[i]; 9: var fileSize = file.size; 10: var fileName = file.name; 11: // calculate the start and end byte index for each blocks(chunks) 12: // with the index, file name and index list for future using 13: ... ... 14:  15: // define the function array and push all chunk upload operation into this array 16: blocks.forEach(function (block) { 17: putBlocks.push(function (callback) { 18: }); 19: }); 20: } 21: }); 22: }); As you can see, I used File.slice method to read each chunks based on the start and end byte index we calculated previously, and constructed a temporary HTML form with the file name, chunk index and chunk data through another new feature in HTML5 named FormData. Then post this form to the backend server through jQuery.ajax. This is the key part of our solution. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: blocks.forEach(function (block) { 15: putBlocks.push(function (callback) { 16: // load blob based on the start and end index for each chunks 17: var blob = file.slice(block.start, block.end); 18: // put the file name, index and blob into a temporary from 19: var fd = new FormData(); 20: fd.append("name", block.name); 21: fd.append("index", block.index); 22: fd.append("file", blob); 23: // post the form to backend service (asp.net mvc controller action) 24: $.ajax({ 25: url: "/Home/UploadInFormData", 26: data: fd, 27: processData: false, 28: contentType: "multipart/form-data", 29: type: "POST", 30: success: function (result) { 31: if (!result.success) { 32: alert(result.error); 33: } 34: callback(null, block.index); 35: } 36: }); 37: }); 38: }); 39: } 40: }); Then we will invoke these functions one by one by using the async.js. And once all functions had been executed successfully I invoked another ajax call to the backend service to commit all these chunks (blocks) as the blob in Windows Azure Storage. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.series(putBlocks, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: }); That’s all in the client side. The outline of our logic would be - Calculate the start and end byte index for each chunks based on the block size. - Defined the functions of reading the chunk form file and upload the content to the backend service through ajax. - Execute the functions defined in previous step with “async.js”. - Commit the chunks by invoking the backend service in Windows Azure Storage finally.   Save Chunks as Blocks into Blob Storage In above we finished the client size JavaScript code. It uploaded the file in chunks to the backend service which we are going to implement in this step. We will use ASP.NET MVC as our backend service, and it will receive the chunks, upload into Windows Azure Bob Storage in blocks, then finally commit as one blob. As in the client side we uploaded chunks by invoking the ajax call to the URL "/Home/UploadInFormData", I created a new action under the Index controller and it only accepts HTTP POST request. 1: [HttpPost] 2: public JsonResult UploadInFormData() 3: { 4: var error = string.Empty; 5: try 6: { 7: } 8: catch (Exception e) 9: { 10: error = e.ToString(); 11: } 12:  13: return new JsonResult() 14: { 15: Data = new 16: { 17: success = string.IsNullOrWhiteSpace(error), 18: error = error 19: } 20: }; 21: } Then I retrieved the file name, index and the chunk content from the Request.Form object, which was passed from our client side. And then, used the Windows Azure SDK to create a blob container (in this case we will use the container named “test”.) and create a blob reference with the blob name (same as the file name). Then uploaded the chunk as a block of this blob with the index, since in Blob Storage each block must have an index (ID) associated with so that finally we can put all blocks as one blob by specifying their block ID list. 1: [HttpPost] 2: public JsonResult UploadInFormData() 3: { 4: var error = string.Empty; 5: try 6: { 7: var name = Request.Form["name"]; 8: var index = int.Parse(Request.Form["index"]); 9: var file = Request.Files[0]; 10: var id = Convert.ToBase64String(BitConverter.GetBytes(index)); 11:  12: var container = _client.GetContainerReference("test"); 13: container.CreateIfNotExists(); 14: var blob = container.GetBlockBlobReference(name); 15: blob.PutBlock(id, file.InputStream, null); 16: } 17: catch (Exception e) 18: { 19: error = e.ToString(); 20: } 21:  22: return new JsonResult() 23: { 24: Data = new 25: { 26: success = string.IsNullOrWhiteSpace(error), 27: error = error 28: } 29: }; 30: } Next, I created another action to commit the blocks into blob once all chunks had been uploaded. Similarly, I retrieved the blob name from the Request.Form. I also retrieved the chunks ID list, which is the block ID list from the Request.Form in a string format, split them as a list, then invoked the BlockBlob.PutBlockList method. After that our blob will be shown in the container and ready to be download. 1: [HttpPost] 2: public JsonResult Commit() 3: { 4: var error = string.Empty; 5: try 6: { 7: var name = Request.Form["name"]; 8: var list = Request.Form["list"]; 9: var ids = list 10: .Split(',') 11: .Where(id => !string.IsNullOrWhiteSpace(id)) 12: .Select(id => Convert.ToBase64String(BitConverter.GetBytes(int.Parse(id)))) 13: .ToArray(); 14:  15: var container = _client.GetContainerReference("test"); 16: container.CreateIfNotExists(); 17: var blob = container.GetBlockBlobReference(name); 18: blob.PutBlockList(ids); 19: } 20: catch (Exception e) 21: { 22: error = e.ToString(); 23: } 24:  25: return new JsonResult() 26: { 27: Data = new 28: { 29: success = string.IsNullOrWhiteSpace(error), 30: error = error 31: } 32: }; 33: } Now we finished all code we need. The whole process of uploading would be like this below. Below is the full client side JavaScript code. 1: <script type="text/javascript" src="~/Scripts/async.js"></script> 2: <script type="text/javascript"> 3: $(function () { 4: $("#upload_button_blob").click(function () { 5: // assert the browser support html5 6: if (window.File && window.Blob && window.FormData) { 7: alert("Your brwoser is awesome, let's rock!"); 8: } 9: else { 10: alert("Oh man plz update to a modern browser before try is cool stuff out."); 11: return; 12: } 13:  14: // start to upload each files in chunks 15: var files = $("#upload_files")[0].files; 16: for (var i = 0; i < files.length; i++) { 17: var file = files[i]; 18: var fileSize = file.size; 19: var fileName = file.name; 20:  21: // calculate the start and end byte index for each blocks(chunks) 22: // with the index, file name and index list for future using 23: var blockSizeInKB = $("#block_size").val(); 24: var blockSize = blockSizeInKB * 1024; 25: var blocks = []; 26: var offset = 0; 27: var index = 0; 28: var list = ""; 29: while (offset < fileSize) { 30: var start = offset; 31: var end = Math.min(offset + blockSize, fileSize); 32:  33: blocks.push({ 34: name: fileName, 35: index: index, 36: start: start, 37: end: end 38: }); 39: list += index + ","; 40:  41: offset = end; 42: index++; 43: } 44:  45: // define the function array and push all chunk upload operation into this array 46: var putBlocks = []; 47: blocks.forEach(function (block) { 48: putBlocks.push(function (callback) { 49: // load blob based on the start and end index for each chunks 50: var blob = file.slice(block.start, block.end); 51: // put the file name, index and blob into a temporary from 52: var fd = new FormData(); 53: fd.append("name", block.name); 54: fd.append("index", block.index); 55: fd.append("file", blob); 56: // post the form to backend service (asp.net mvc controller action) 57: $.ajax({ 58: url: "/Home/UploadInFormData", 59: data: fd, 60: processData: false, 61: contentType: "multipart/form-data", 62: type: "POST", 63: success: function (result) { 64: if (!result.success) { 65: alert(result.error); 66: } 67: callback(null, block.index); 68: } 69: }); 70: }); 71: }); 72:  73: // invoke the functions one by one 74: // then invoke the commit ajax call to put blocks into blob in azure storage 75: async.series(putBlocks, function (error, result) { 76: var data = { 77: name: fileName, 78: list: list 79: }; 80: $.post("/Home/Commit", data, function (result) { 81: if (!result.success) { 82: alert(result.error); 83: } 84: else { 85: alert("done!"); 86: } 87: }); 88: }); 89: } 90: }); 91: }); 92: </script> And below is the full ASP.NET MVC controller code. 1: public class HomeController : Controller 2: { 3: private CloudStorageAccount _account; 4: private CloudBlobClient _client; 5:  6: public HomeController() 7: : base() 8: { 9: _account = CloudStorageAccount.Parse(CloudConfigurationManager.GetSetting("DataConnectionString")); 10: _client = _account.CreateCloudBlobClient(); 11: } 12:  13: public ActionResult Index() 14: { 15: ViewBag.Message = "Modify this template to jump-start your ASP.NET MVC application."; 16:  17: return View(); 18: } 19:  20: [HttpPost] 21: public JsonResult UploadInFormData() 22: { 23: var error = string.Empty; 24: try 25: { 26: var name = Request.Form["name"]; 27: var index = int.Parse(Request.Form["index"]); 28: var file = Request.Files[0]; 29: var id = Convert.ToBase64String(BitConverter.GetBytes(index)); 30:  31: var container = _client.GetContainerReference("test"); 32: container.CreateIfNotExists(); 33: var blob = container.GetBlockBlobReference(name); 34: blob.PutBlock(id, file.InputStream, null); 35: } 36: catch (Exception e) 37: { 38: error = e.ToString(); 39: } 40:  41: return new JsonResult() 42: { 43: Data = new 44: { 45: success = string.IsNullOrWhiteSpace(error), 46: error = error 47: } 48: }; 49: } 50:  51: [HttpPost] 52: public JsonResult Commit() 53: { 54: var error = string.Empty; 55: try 56: { 57: var name = Request.Form["name"]; 58: var list = Request.Form["list"]; 59: var ids = list 60: .Split(',') 61: .Where(id => !string.IsNullOrWhiteSpace(id)) 62: .Select(id => Convert.ToBase64String(BitConverter.GetBytes(int.Parse(id)))) 63: .ToArray(); 64:  65: var container = _client.GetContainerReference("test"); 66: container.CreateIfNotExists(); 67: var blob = container.GetBlockBlobReference(name); 68: blob.PutBlockList(ids); 69: } 70: catch (Exception e) 71: { 72: error = e.ToString(); 73: } 74:  75: return new JsonResult() 76: { 77: Data = new 78: { 79: success = string.IsNullOrWhiteSpace(error), 80: error = error 81: } 82: }; 83: } 84: } And if we selected a file from the browser we will see our application will upload chunks in the size we specified to the server through ajax call in background, and then commit all chunks in one blob. Then we can find the blob in our Windows Azure Blob Storage.   Optimized by Parallel Upload In previous example we just uploaded our file in chunks. This solved the problem that ASP.NET MVC request content size limitation as well as the Windows Azure load balancer timeout. But it might introduce the performance problem since we uploaded chunks in sequence. In order to improve the upload performance we could modify our client side code a bit to make the upload operation invoked in parallel. The good news is that, “async.js” library provides the parallel execution function. If you remembered the code we invoke the service to upload chunks, it utilized “async.series” which means all functions will be executed in sequence. Now we will change this code to “async.parallel”. This will invoke all functions in parallel. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.parallel(putBlocks, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: }); In this way all chunks will be uploaded to the server side at the same time to maximize the bandwidth usage. This should work if the file was not very large and the chunk size was not very small. But for large file this might introduce another problem that too many ajax calls are sent to the server at the same time. So the best solution should be, upload the chunks in parallel with maximum concurrency limitation. The code below specified the concurrency limitation to 4, which means at the most only 4 ajax calls could be invoked at the same time. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.parallelLimit(putBlocks, 4, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: });   Summary In this post we discussed how to upload files in chunks to the backend service and then upload them into Windows Azure Blob Storage in blocks. We focused on the frontend side and leverage three new feature introduced in HTML 5 which are - File.slice: Read part of the file by specifying the start and end byte index. - Blob: File-like interface which contains the part of the file content. - FormData: Temporary form element that we can pass the chunk alone with some metadata to the backend service. Then we discussed the performance consideration of chunk uploading. Sequence upload cannot provide maximized upload speed, but the unlimited parallel upload might crash the browser and server if too many chunks. So we finally came up with the solution to upload chunks in parallel with the concurrency limitation. We also demonstrated how to utilize “async.js” JavaScript library to help us control the asynchronize call and the parallel limitation.   Regarding the chunk size and the parallel limitation value there is no “best” value. You need to test vary composition and find out the best one for your particular scenario. It depends on the local bandwidth, client machine cores and the server side (Windows Azure Cloud Service Virtual Machine) cores, memory and bandwidth. Below is one of my performance test result. The client machine was Windows 8 IE 10 with 4 cores. I was using Microsoft Cooperation Network. The web site was hosted on Windows Azure China North data center (in Beijing) with one small web role (1.7GB 1 core CPU, 1.75GB memory with 100Mbps bandwidth). The test cases were - Chunk size: 512KB, 1MB, 2MB, 4MB. - Upload Mode: Sequence, parallel (unlimited), parallel with limit (4 threads, 8 threads). - Chunk Format: base64 string, binaries. - Target file: 100MB. - Each case was tested 3 times. Below is the test result chart. Some thoughts, but not guidance or best practice: - Parallel gets better performance than series. - No significant performance improvement between parallel 4 threads and 8 threads. - Transform with binaries provides better performance than base64. - In all cases, chunk size in 1MB - 2MB gets better performance.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • SQL Server Index cost

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    I have read that one of the tradeoffs for adding table indexes in SQL Server is the increased cost of insert/update/delete queries to benefit the performance of select queries. I can conceptually understand what happens in the case of an insert because SQL Server has to write entries into each index matching the new rows, but update and delete are a little more murky to me because I can't quite wrap my head around what the database engine has to do. Let's take DELETE as an example and assume I have the following schema (pardon the pseudo-SQL) TABLE Foo col1 int ,col2 int ,col3 int ,col4 int PRIMARY KEY (col1,col2) INDEX IX_1 col3 INCLUDE col4 Now, if I issue the statement DELETE FROM Foo WHERE col1=12 AND col2 > 34 I understand what the engine must do to update the table (or clustered index if you prefer). The index is set up to make it easy to find the range of rows to be removed and do so. However, at this point it also needs to update IX_1 and the query that I gave it gives no obvious efficient way for the database engine to find the rows to update. Is it forced to do a full index scan at this point? Does the engine read the rows from the clustered index first and generate a smarter internal delete against the index? It might help me to wrap my head around this if I understood better what is going on under the hood, but I guess my real question is this. I have a database that is spending a significant amount of time in delete and I'm trying to figure out what I can do about it. When I display the execution plan for the deletion, it just shows an entry for "Clustered Index Delete" on table Foo which lists in the details section the other indices that need to be updated but I don't get any indication of the relative cost of these other indices. Are they all equal in this case? Is there some way that I can estimate the impact of removing one or more of these indices without having to actually try it?

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