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  • Reading 'Index Status' graph in Google Webmaster tools

    - by sam
    I recently found a bunch of old files that had been ftp'ed to a live production server by mistake on a static (html / css / js) site. I manually deleted these files, but today when checking in Google Webmaster tools i found this graph below. The 'update' marker is from 3/9/14, what i can work out is what Google is trying to tell me, are they saying that : There was a ranking update like Penguin or Panda and they penalized my site and un-indexed a load of pages which they thought were junk.. OR Is this showing that I updated the site by deleting the files on the server on 3/9/14 OR Is this something else ?

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  • Optimizing MySQL for ALTER TABLE of InnoDB

    - by schuilr
    Sometime soon we will need to make schema changes to our production database. We need to minimize downtime for this effort, however, the ALTER TABLE statements are going to run for quite a while. Our largest tables have 150 million records, largest table file is 50G. All tables are InnoDB, and it was set up as one big data file (instead of a file-per-table). We're running MySQL 5.0.46 on an 8 core machine, 16G memory and a RAID10 config. I have some experience with MySQL tuning, but this usually focusses on reads or writes from multiple clients. There is lots of info to be found on the Internet on this subject, however, there seems to be very little information available on best practices for (temporarily) tuning your MySQL server to speed up ALTER TABLE on InnoDB tables, or for INSERT INTO .. SELECT FROM (we will probably use this instead of ALTER TABLE to have some more opportunities to speed things up a bit). The schema changes we are planning to do is adding a integer column to all tables and make it the primary key, instead of the current primary key. We need to keep the 'old' column as well so overwriting the existing values is not an option. What would be the ideal settings to get this task done as quick as possible?

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  • ALTER TABLE without locking the table?

    - by Daniel
    When doing an ALTER TABLE statement in MySQL, the whole table is read-locked for the duration of the statement. If it's a big table, that means insert or update statements could be locked for a looooong time. Is there a way to do a "hot alter", like adding a column in such a way that the table is still updatable throughout the process? Mostly I'm interested in a solution for MySQL but I'd be interested in other RDBMS if MySQL can't do it. To clarify, my purpose is simply to avoid downtime when a new feature that requires an extra table column is pushed to production. Any database schema will change over time, that's just a fact of life. I don't see why we should accept that these changes must inevitably result in downtime; that's just weak.

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  • Apache not finding index.php by default, set rule for routing through index.php

    - by eoinoc
    Apache on the server is set to find index.php by default, and that works for a normal folder. However, I have a .htaccess rule to route all requests through my routing script: RewriteEngine On RewriteCond %{REQUEST_FILENAME} !-f RewriteRule ^(.*)$ index.php [QSA,L] With these .htaccess contents, the server returns a 404 error. Only by specifying /index.php does the routing script get called. Any tips on what I am doing wrong?

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  • 403 error on index file

    - by John L.
    When I try to access index.py in my server root through http://domain/, I get a 403 Forbidden error, but when I can access it through http://domain/index.py. In my server logs it says "Options ExecCGI is off in this directory: /var/www/index.py". However, my httpd.conf entry for that directory is the same as the ones for other directories, and getting to index.py works fine. My permissions are set to 755 for index.py. I also tried making a php file and naming it index.php, and it works from both domain/ and domain/index.php. Here is my httpd.conf entry: <Directory /var/www> Options Indexes Includes FollowSymLinks MultiViews AllowOverride All Order allow,deny Allow from all AddHandler cgi-script .cgi AddHandler cgi-script .pl AddHandler cgi-script .py Options +ExecCGI DirectoryIndex index.html index.php index.py </Directory> Thanks

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  • Oracle ALTER DATABASE OPEN

    - by Tom
    Hi everyone, Im having some trouble with an oracle database. Every time i try to connect, i get this message. ORA-01033: ORACLE initialization or shutdown in progress I searched the web, and found that the solution is to execute an alter database open command, but what I dont understand is where should i execute if, since I cant connect to the database. Am I missing something? Thanks in advance

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  • ALTER TABLE error

    - by Travis
    Can someone explain to me why I am receiving the following error? I want to rename the column "exerciseID" to "ID" in a mysql table using the following syntax. ALTER TABLE `exercises` CHANGE `exerciseID` `ID` INT( 11 ) NOT NULL AUTO_INCREMENT However I receive the following error: MySQL said: #1025 - Error on rename of './balance/#sql-de_110e' to './balance/exercises' (errno: 150) Any suggestions would be much appreciated

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  • Forward web request for directory index ('/') to an index.htm page in JBoss 4.0.5

    - by The Pretender
    I am using JBoss 4.0.5.GA to run a set of java applications. One of them is a web frontend, using Spring 1.4. URL mappings are configured in a way that 'fake' pages from request URLs are mapped to controllers. That means that when someone requests /index.htm, there's no actual 'index.htm' on disk, and that request maps to a specific conroller which then renders a jsp view. So the problem is as follows: I need to tell JBoss to somehow forward all requests for directory indices to corresponding 'index.htm' URLs like so: / ? /index.htm; /news/ ? /news/index.htm; /foo/bar/baz/ ? /foo/bar/baz/index.htm and so on. I can't use Tomcat's welcome-file-list feature because it looks for those files on disk, while all 'index.htm's are fake and don't actually exist on disk.

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  • Search Files (Preferably with index) on Windows 2000 Server

    - by ThinkBohemian
    I have many files on a windows server 2000 machine that is setup to act as a networked disk drive, is there anyway I can index the files and make that index available as a search to more people than just me? Bonus if the index can look inside of documents such as readme.txt? If there is no easy way to do this globaly (for all users) Is there a way I could generate and store an index locally on my computer? If this is the wrong place to ask this question, any advice on community more suited?

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  • Createing a new Index in SQL when current records don't meet that index

    - by Jonathan
    Hey all- I'd like to add an index to a table that already contains data. I know that there a few records currently in the table that are not unique with this new index. Clearly, MySQL won't let me add the index until all of them are. I need a query to identify the rows which currently have the same index. I can then delete or modify these rows as necessary. The new index contains 6 fields. Thanks- Jonathan

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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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  • 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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  • MySQL foreign key creation with alter table command

    - by user313338
    I created some tables using MySQL Workbench, and then did forward ‘forward engineer’ to create scripts to create these tables. BUT, the scripts lead me to a number of problems. One of which involves the foreign keys. So I tried creating separate foreign key additions using alter table and I am still getting problems. The code is below (the set statements, drop/create statements I left in … though I don’t think they should matter for this): SET @OLD_UNIQUE_CHECKS=@@UNIQUE_CHECKS, UNIQUE_CHECKS=0; SET @OLD_FOREIGN_KEY_CHECKS=@@FOREIGN_KEY_CHECKS, FOREIGN_KEY_CHECKS=0; SET @OLD_SQL_MODE=@@SQL_MODE, SQL_MODE='TRADITIONAL'; DROP SCHEMA IF EXISTS `mydb` ; CREATE SCHEMA IF NOT EXISTS `mydb` DEFAULT CHARACTER SET latin1 COLLATE latin1_swedish_ci ; -- ----------------------------------------------------- -- Table `mydb`.`User` -- ----------------------------------------------------- DROP TABLE IF EXISTS `mydb`.`User` ; CREATE TABLE IF NOT EXISTS `mydb`.`User` ( `UserName` VARCHAR(35) NOT NULL , `Num_Accts` INT NOT NULL , `Password` VARCHAR(45) NULL , `Email` VARCHAR(45) NULL , `User_ID` INT NOT NULL AUTO_INCREMENT , PRIMARY KEY (`User_ID`) ) ENGINE = InnoDB; -- ----------------------------------------------------- -- Table `mydb`.`User_Space` -- ----------------------------------------------------- DROP TABLE IF EXISTS `mydb`.`User_Space` ; CREATE TABLE IF NOT EXISTS `mydb`.`User_Space` ( `User_UserName` VARCHAR(35) NOT NULL , `User_Space_ID` INT NOT NULL AUTO_INCREMENT , PRIMARY KEY (`User_Space_ID`), FOREIGN KEY (`User_UserName`) REFERENCES `mydb`.`User` (`UserName`) ON UPDATE CASCADE ON DELETE CASCADE) ENGINE = InnoDB; SET SQL_MODE=@OLD_SQL_MODE; SET FOREIGN_KEY_CHECKS=@OLD_FOREIGN_KEY_CHECKS; SET UNIQUE_CHECKS=@OLD_UNIQUE_CHECKS; The error this produces is: Error Code: 1005 Can't create table 'mydb.user_space' (errno: 150) Anybody know what the heck I’m doing wrong?? And anybody else have problems with the script generation done by mysql workbench? It’s a nice tool, but annoying that it pumps out scripts that don’t work for me. [As an fyi here’s the script it auto-generates: SET @OLD_UNIQUE_CHECKS=@@UNIQUE_CHECKS, UNIQUE_CHECKS=0; SET @OLD_FOREIGN_KEY_CHECKS=@@FOREIGN_KEY_CHECKS, FOREIGN_KEY_CHECKS=0; SET @OLD_SQL_MODE=@@SQL_MODE, SQL_MODE='TRADITIONAL'; DROP SCHEMA IF EXISTS `mydb` ; CREATE SCHEMA IF NOT EXISTS `mydb` DEFAULT CHARACTER SET latin1 COLLATE latin1_swedish_ci ; -- ----------------------------------------------------- -- Table `mydb`.`User` -- ----------------------------------------------------- DROP TABLE IF EXISTS `mydb`.`User` ; CREATE TABLE IF NOT EXISTS `mydb`.`User` ( `UserName` VARCHAR(35) NOT NULL , `Num_Accts` INT NOT NULL , `Password` VARCHAR(45) NULL , `Email` VARCHAR(45) NULL , `User_ID` INT NOT NULL AUTO_INCREMENT , PRIMARY KEY (`User_ID`) ) ENGINE = InnoDB; -- ----------------------------------------------------- -- Table `mydb`.`User_Space` -- ----------------------------------------------------- DROP TABLE IF EXISTS `mydb`.`User_Space` ; CREATE TABLE IF NOT EXISTS `mydb`.`User_Space` ( `User_Space_ID` INT NOT NULL AUTO_INCREMENT , PRIMARY KEY (`User_Space_ID`) , INDEX `User_ID` () , CONSTRAINT `User_ID` FOREIGN KEY () REFERENCES `mydb`.`User` () ON DELETE NO ACTION ON UPDATE NO ACTION) ENGINE = InnoDB; SET SQL_MODE=@OLD_SQL_MODE; SET FOREIGN_KEY_CHECKS=@OLD_FOREIGN_KEY_CHECKS; SET UNIQUE_CHECKS=@OLD_UNIQUE_CHECKS; ** Thanks!]

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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

    - by yellowstar
    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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  • Instead of alter table column to turn IDENTITY on and off, turn IDENTITY_INSERT on and off

    - by Kevin Shyr
    First of all, I don't know which version of SQL this post (http://www.techonthenet.com/sql/tables/alter_table.php) is based on, but at least for Microsoft SQL Server 2008, the syntax is not: ALTER TABLE [table_name] MODIFY [column_name] [data_type] NOT NULL; Instead, it should be: ALTER TABLE [table_name] ALTER COLUMN [column_name] [data_type] NOT NULL;   Then, as several posts point out, you can't use T-SQL to run an existing column into an IDENTITY column.  Instead, use the IDENTITY_INSERT to copy data from other tables.  http://msdn.microsoft.com/en-us/library/ms188059.aspx SET IDENTITY_INSERT [table_name] ON INSERT .... SET IDENTITY_INSERT [table_name] OFF     http://www.sqlservercentral.com/Forums/Topic126147-8-1.aspx http://www.sqlteam.com/forums/topic.asp?TOPIC_ID=65257

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