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  • Are there sources of email marketing data available?

    - by Gortron
    Are sources of email marketing data available to the public? I would like to see email marketing data to see what kind of content a business sends out, the frequency of sending, the number of people emailed, especially the resulting open rates and click through rates. Are businesses willing to share data on their previous email marketing campaigns without divulging their contact list? I would like to use this data to create an application to help businesses create better newsletters by using this data as a benchmark, basically sharing what works and what doesn't for each industry.

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  • The SQL Beat Podcast-Capturing a SQL Rockstar

    - by SQLBeat
      This is the first permissible (waiting for signed disclaimers) episode of the SQL Beat Podcast featuring the gracious and famous Thomas La Rock. We talk about gay marriage, abortion, SQL community and a 9 inch pipe with a hole in it at the tip. No really. If there ever was a gentleman, SQL Rockstar is one and I want to thank him from the bottom of my digital recorder for agreeing to talk to me and my audience. All forty of them will appreciate the candor. Enjoy World. I did. Oh and a special rock start drum intro from me to you. CLICK HERE TO PLAY >>

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  • The SQL Beat Podcast–Capturing a SQL Rockstar

    - by SQLBeat
      This is the first permissible (waiting for signed disclaimers) episode of the SQL Beat Podcast featuring the gracious and famous Thomas La Rock. We talk about gay marriage, abortion, SQL community and a 9 inch pipe with a hole in it at the tip. No really. If there ever was a gentleman, SQL Rockstar is one and I want to thank him from the bottom of my digital recorder for agreeing to talk to me and my audience. All forty of them will appreciate the candor. Enjoy World. I did. Oh and a special rock start drum intro from me to you. CLICK BELOW TO LISTEN >>>>>>>>>CLICK HERE TO PLAY >>>>>>>>> CLICK ABOVE TO SPEAR A FISH INSTEAD

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  • Extending SSIS with custom Data Flow components (Presentation)

    Download the slides and sample code from my Extending SSIS with custom Data Flow components presentation, first presented at the SQLBits II (The SQL) Community Conference. Abstract Get some real-world insights into developing data flow components for SSIS. This starts with an introduction to the data flow pipeline engine, and explains the real differences between adapters and the three sub-types of transformation. Understanding how the different types of component behave and manage data is key to writing components of your own, and probably should but be required knowledge for anyone building packages at all. Using sample code throughout, I will show you how to write components, as well as highlighting best practice and lessons learned. The sample code includes fully working example projects for source, destination and transformation components. Presentation & Samples (358KB) Extending SSIS with custom Data Flow components.zip

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  • Select,Insert,Update and Delete data with LINQ to SQL in an ASP.Net application

    - by nikolaosk
    As you might have guessed I am continuing my LINQ to SQL posts. I am teaching a course right now on ADO.Net 3.5 (LINQ & EF) and I know a lot of people who have learned through my blog and my style of writing. I am going to use a step by step example to demonstrate how to select,update,insert,delete data through LINQ to SQL into the database. If you want to have a look on how to return data from a database with LINQ to SQL and stored procedures click here . If you want to have a look on how to...(read more)

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  • How to use OO for data analysis? [closed]

    - by Konsta
    In which ways could object-orientation (OO) make my data analysis more efficient and let me reuse more of my code? The data analysis can be broken up into get data (from db or csv or similar) transform data (filter, group/pivot, ...) display/plot (graph timeseries, create tables, etc.) I mostly use Python and its Pandas and Matplotlib packages for this besides some DB connectivity (SQL). Almost all of my code is a functional/procedural mix. While I have started to create a data object for a certain collection of time series, I wonder if there are OO design patterns/approaches for other parts of the process that might increase efficiency?

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  • Markup format or script for data files?

    - by Aaron
    The game I'm designing will be mainly written in a high level scripting language (leaning towards either Lua or Squirrel) with a C++ core. In addition to scripts I'm also going to need different data files. Many data files will be for static information such as graphical assets and monster types. I'd also want to create and update data files at runtime for user information like option settings and game saves. Can I get away with using plain script files (i.e. .lua or .nut files) for my data files, or is it better to use dedicated markup formats like XML or YAML? If I use script files, loaded separately from my true scripts, then I wouldn't need an extra library to read those files. Scripting languages like Lua also have table syntax that lend themselves towards data definition. On the other hand I'd have to write my own schema check code. These languages also don't seem to support serialization "out of the box" like the markup format libraries do.

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  • Data Movement and the Decision Matrix

    - by BuckWoody
    Maybe it’s my military background, or maybe I’ve always had this predilection, but I like to use two devices when I need to make a complex decision: A checklist and a decision matrix. I like to use a checklist because it ensures that I remember the big bits of what I need to do, and brings up questions or areas that I didn’t think about when evaluating options for the decision. And the decision matrix – that’s the thing I use to actually lay out those options. It’s simply a spreadsheet-like grid (I use Excel, but paper and pencil works as well) that lays out the requirements or advantages for the decision across the top, and the options I have on the left-hand side. Then in the “cells” I put whether or not that option on the left will meet the requirement in that column. I then simply “weight” each cell to organize the choices by best-fit. The right answer (or answers) will float right to the top. I was asked yesterday about options for moving data in SQL Server to another system. There are just dozens of ways to do this, from bcp to Replication, each with certain advantages and costs. But asking the questions for the top row first helped me show the person that it isn’t a particular technology that is important, it’s laying out those requirements and thinking about which elements are more important than the other. For instance, is it more important to have the data moved all the time, or is it OK if that happens once in a while? Does the data have to move in two directions or just one? All of these will help that answer jump right out. Try it sometime – it’s a great learning exercise, since it will force you to focus on filling out the matrix. The answer is out there, Neo. Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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  • Windows Server, SQL Server [on hold]

    - by user136329
    I will give high level details of my requirement. We have one web application which accesses the database through SYBASE. The following technologies being used. Visual Studio 2010 .NET frame work 4.5 and for reporting Crystal Report. These are housed on windows server 2008. And for Database we use different servers. We are thinking of moving to SQL Server to be able to utilize the reporting features. My question is does SQL Server can be part of Windows Server 2008 R2 or we needed to have additional server for SQL?

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  • Winner of the 2012 Government Big Data Solutions Award

    - by Jean-Pierre Dijcks
    Hot off the press: The winner of the 2012 Government Big Data Solutions Aware is the National Cancer Institute!! Read all the details on CTOLabs.com. A short excerpt to wet your appetite: "... This solution, based on the Oracle Big Data Appliance with the Cloudera Distribution of Apache Hadoop (CDH), leverages capabilities available from the Big Data community today in pioneering ways that can serve a broad range of researchers. The promising approach of this solution is repeatable across many other Big Data challenges for bioinfomatics, making this approach worthy of its selection as the 2012 Government Big Data Solution Award." Read the entire post. Congrats to the entire team!!

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  • What criteria would I use SQL Stream Insight vs TPL Dataflow [closed]

    - by makerofthings7
    There is an add-in to the Task Parallel Library (TPL) called TPL Dataflow that allows a variety of data processing scenarios. It seems that there are some parallels to the SQL Stream Insight product, however since SQL's Stream Insight has some interesting licensing around it, and it has a better performance depending on what license I get... I found myself asking myself should I use TPL Dataflow and not have any licensing issues, and possibly better performance. Can anyone tell me if performance is a valid criteria for comparing SQL Stream Insight vs TPL Dataflow? What other criteria should I be looking at when comparing the two?

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  • What''s easy extensible technique to store game data?

    - by Miro
    I'm looking for library/technique for storing my game resources - levels, object (effects,world info), items(price,effects,...), NPC(visual info, behavior), everything except graphics/audio stuff. I've seen lua used for Awesome WM configuration. protobuf looks good, but it seems to be designed for network communication. I've tried to write my own parser, but as the project grows it's more and more harder to manage it and catch all the bugs. My requiremets: stability easy extension of data without need to convert older versions to newer good(don't have to be the best) performance of loading not much coding not XML!

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  • Rebuilding CoasterBuzz, Part II: Hot data objects

    - by Jeff
    This is the second post, originally from my personal blog, in a series about rebuilding one of my Web sites, which has been around for 12 years. More: Part I: Evolution, and death to WCF After the rush to get moving on stuff, I temporarily lost interest. I went almost two weeks without touching the project, in part because the next thing on my backlog was doing up a bunch of administrative pages. So boring. Unfortunately, because most of the site's content is user-generated, you need some facilities for editing data. CoasterBuzz has a database full of amusement parks and roller coasters. The entities enjoy the relationships that you would expect, though they're further defined by "instances" of a coaster, to define one that has moved between parks as one, with different names and operational dates. And of course, there are pictures and news items, too. It's not horribly complex, except when you have to account for a name change and display just the newest name. In all previous versions, data access was straight SQL. As so much of the old code was rooted in 2003, with some changes in 2008, there wasn't much in the way of ORM frameworks going on then. Let me rephrase that, I mostly wasn't interested in ORM's. Since that time, I used a little LINQ to SQL in some projects, and a whole bunch of nHibernate while at Microsoft. Through all of that experience, I have to admit that these frameworks are often a bigger pain in the ass than not. They're great for basic crud operations, but when you start having all kinds of exotic relationships, they get difficult, and generate all kinds of weird SQL under the covers. The black box can quickly turn into a black hole. Sometimes you end up having to build all kinds of new expertise to do things "right" with a framework. Still, despite my reservations, I used the newer version of Entity Framework, with the "code first" modeling, in a science project and I really liked it. Since it's just a right-click away with NuGet, I figured I'd give it a shot here. My initial effort was spent defining the context class, which requires a bit of work because I deviate quite a bit from the conventions that EF uses, starting with table names. Then throw some partial querying of certain tables (where you'll find image data), and you're splitting tables across several objects (navigation properties). I won't go into the details, because these are all things that are well documented around the Internet, but there was a minor learning curve there. The basics of reading data using EF are fantastic. For example, a roller coaster object has a park associated with it, as well as a number of instances (if it was ever relocated), and there also might be a big banner image for it. This is stupid easy to use because it takes one line of code in your repository class, and by the time you pass it to the view, you have a rich object graph that has everything you need to display stuff. Likewise, editing simple data is also, well, simple. For this goodness, thank the ASP.NET MVC framework. The UpdateModel() method on the controllers is very elegant. Remember the old days of assigning all kinds of properties to objects in your Webforms code-behind? What a time consuming mess that used to be. Even if you're not using an ORM tool, having hydrated objects come off the wire is such a time saver. Not everything is easy, though. When you have to persist a complex graph of objects, particularly if they were composed in the user interface with all kinds of AJAX elements and list boxes, it's not just a simple matter of submitting the form. There were a few instances where I ended up going back to "old-fashioned" SQL just in the interest of time. It's not that I couldn't do what I needed with EF, it's just that the efficiency, both my own and that of the generated SQL, wasn't good. Since EF context objects expose a database connection object, you can use that to do the old school ADO.NET stuff you've done for a decade. Using various extension methods from POP Forums' data project, it was a breeze. You just have to stick to your decision, in this case. When you start messing with SQL directly, you can't go back in the same code to messing with entities because EF doesn't know what you're changing. Not really a big deal. There are a number of take-aways from using EF. The first is that you write a lot less code, which has always been a desired outcome of ORM's. The other lesson, and I particularly learned this the hard way working on the MSDN forums back in the day, is that trying to retrofit an ORM framework into an existing schema isn't fun at all. The CoasterBuzz database isn't bad, but there are design decisions I'd make differently if I were starting from scratch. Now that I have some of this stuff done, I feel like I can start to move on to the more interesting things on the backlog. There's a lot to do, but at least it's fun stuff, and not more forms that will be used infrequently.

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  • The SQL Beat Podcast-Capturing a SQL Rockstar

    - by SQLBeat
    This is the first permissible (waiting for signed disclaimers) episode of the SQL Beat Podcast featuring the gracious and famous Thomas La Rock. We talk about gay marriage, abortion, SQL community and generally convivial and ergonomic as will be witnessed by THAT LONG PIPE IN THE CHAIR. If there ever was a gentleman, SQL Rockstar is one and I want to thank him from the bottom of my digital recorder for agreeing to talk to me and my audience. All forty of them will appreciate the candor. Enjoy World. I did. Oh and a special rock start drum intro from me to you. CLICK HERE TO PLAY

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  • Getting data from a webpage in a stable and efficient way

    - by Mike Heremans
    Recently I've learned that using a regex to parse the HTML of a website to get the data you need isn't the best course of action. So my question is simple: What then, is the best / most efficient and a generally stable way to get this data? I should note that: There are no API's There is no other source where I can get the data from (no databases, feeds and such) There is no access to the source files. (Data from public websites) Let's say the data is normal text, displayed in a table in a html page I'm currently using python for my project but a language independent solution/tips would be nice. As a side question: How would you go about it when the webpage is constructed by Ajax calls?

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  • SQL and Database: Where to start! [closed]

    - by Nizar
    First of all I just know HTML and CSS (this is my background in web development and design) and I have found that before I move to a server-side language I need to learn about databases and SQL. My first question: Do you think this order of learning is good (I mean to learn SQL after HTML and CSS)? My secod related question: Do I have to learn a lot about SQL and databases? or just the basics? and if you know any good beginners books please write their titles.

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  • Passing integer lists in a sql query, best practices

    - by Artiom Chilaru
    I'm currently looking at ways to pass lists of integers in a SQL query, and try to decide which of them is best in which situation, what are the benefots of each, and what are the pitfalls, what should be avoided :) Right now I know of 3 ways that we currently use in our application. 1) Table valued parameter: Create a new Table Valued Parameter in sql server: CREATE TYPE [dbo].[TVP_INT] AS TABLE( [ID] [int] NOT NULL ) Then run the query against it: using (var conn = new SqlConnection(DataContext.GetDefaultConnectionString)) { var comm = conn.CreateCommand(); comm.CommandType = CommandType.Text; comm.CommandText = @" UPDATE DA SET [tsLastImportAttempt] = CURRENT_TIMESTAMP FROM [Account] DA JOIN @values IDs ON DA.ID = IDs.ID"; comm.Parameters.Add(new SqlParameter("values", downloadResults.Select(d => d.ID).ToDataTable()) { TypeName = "TVP_INT" }); conn.Open(); comm.ExecuteScalar(); } The major disadvantages of this method is the fact that Linq doesn't support table valued params (if you create an SP with a TVP param, linq won't be able to run it) :( 2) Convert the list to Binary and use it in Linq! This is a bit better.. Create an SP, and you can run it within linq :) To do this, the SP will have an IMAGE parameter, and we'll be using a user defined function (udf) to convert this to a table.. We currently have implementations of this function written in C++ and in assembly, both have pretty much the same performance :) Basically, each integer is represented by 4 bytes, and passed to the SP. In .NET we have an extension method that convers an IEnumerable to a byte array The extension method: public static Byte[] ToBinary(this IEnumerable intList) { return ToBinaryEnum(intList).ToArray(); } private static IEnumerable<Byte> ToBinaryEnum(IEnumerable<Int32> intList) { IEnumerator<Int32> marker = intList.GetEnumerator(); while (marker.MoveNext()) { Byte[] result = BitConverter.GetBytes(marker.Current); Array.Reverse(result); foreach (byte b in result) yield return b; } } The SP: CREATE PROCEDURE [Accounts-UpdateImportAttempts] @values IMAGE AS BEGIN UPDATE DA SET [tsLastImportAttempt] = CURRENT_TIMESTAMP FROM [Account] DA JOIN dbo.udfIntegerArray(@values, 4) IDs ON DA.ID = IDs.Value4 END And we can use it by running the SP directly, or in any linq query we need using (var db = new DataContext()) { db.Accounts_UpdateImportAttempts(downloadResults.Select(d => d.ID).ToBinary()); // or var accounts = db.Accounts .Where(a => db.udfIntegerArray(downloadResults.Select(d => d.ID).ToBinary(), 4) .Select(i => i.Value4) .Contains(a.ID)); } This method has the benefit of using compiled queries in linq (which will have the same sql definition, and query plan, so will also be cached), and can be used in SPs as well. Both these methods are theoretically unlimited, so you can pass millions of ints at a time :) 3) The simple linq .Contains() It's a more simple approach, and is perfect in simple scenarios. But is of course limited by this. using (var db = new DataContext()) { var accounts = db.Accounts .Where(a => downloadResults.Select(d => d.ID).Contains(a.ID)); } The biggest drawback of this method is that each integer in the downloadResults variable will be passed as a separate int.. In this case, the query is limited by sql (max allowed parameters in a sql query, which is a couple of thousand, if I remember right). So I'd like to ask.. What do you think is the best of these, and what other methods and approaches have I missed?

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  • Linq to SQL Problem System.Data.Linq.IdentityManager.StandardIdentityManager.MultiKeyManager

    - by luckyluke
    I have a really tricky thing going up here. My project has around 100 tables and they are all mapped by LINQ. Everything works fine in a dev and test environment. These enviroments are MS Win 2008 r2 servers with SQL 2008 sp1 databases. IIS and SQL are on a different machines. Now on production enviroment which is MS Win 2003 x64 web farm + geoclustered SQL 2008 IT DOES not work. All I get is the exception System.IndexOutOfRangeException: Index was outside the bounds of the array. at System.Data.Linq.IdentityManager.StandardIdentityManager.MultiKeyManager3.TryCreateKeyFr>om Values(Object[] values, MultiKey& k) at System.Data.Linq.IdentityManager.StandardIdentityManager.IdentityCache2.Find(Object[] keyValues) at System.Data.Linq.ChangeProcessor.GetOtherItem(MetaAssociation assoc, Object instance) at System.Data.Linq.ChangeProcessor.BuildEdgeMaps() at System.Data.Linq.ChangeProcessor.SubmitChanges(ConflictMode failureMode) at System.Data.Linq.DataContext.SubmitChanges(ConflictMode failureMode) at ERS.IIMP.Services.ExposuresSrv.Update(Int32 ExpID, Int32 AssID) Services\ExposuresSrv.cs` My question is What the hell. They have precisely the same DBML, the DB has exactly THE SAME structure (when I get the DB from prod to TEST and mount it eveything works just great), the binaries on the WEB Server are the same. I seriously do not know what to do.... Did anyone found that Linq works on one env and does not on the second?? I mam really lost here. I really hope You can help me:)

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  • What data structure to use / data persistence

    - by Dave
    I have an app where I need one table of information with the following fields: field 1 - int or char field 2 - string (max 10 char) field 3 - string (max 20 char) field 4 - float I need the program to filter on field 1 based upon a segmented control and select a field 2 from a picker. From this data I need to look up field 4 to use in a calculation. Total records will be about 200. I never see it go above 400 - 500. I am going to use a singleton which I am able to do, I just need help with the structure for this with data persistence. What type of data structure should I use for this and should I use NSNumber, NSString, etc. or old data types like float, Char, etc. I thought about a struct put into an array but there is probably a better way. This is new to me so any help or reference to examples would be great. I also thought about a plist or dictionary but it looks like it is just a lookup and a field which obviously won't work. Core data looked like overkill to me. Also, with any recommendation how should I get initial data into it? I want the user to be able to edit and add to the database. Sorry for the old terms, you can see what generation I am from... Thanks in advance!!!!

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  • Node.js Adventure - Storage Services and Service Runtime

    - by Shaun
    When I described on how to host a Node.js application on Windows Azure, one of questions might be raised about how to consume the vary Windows Azure services, such as the storage, service bus, access control, etc.. Interact with windows azure services is available in Node.js through the Windows Azure Node.js SDK, which is a module available in NPM. In this post I would like to describe on how to use Windows Azure Storage (a.k.a. WAS) as well as the service runtime.   Consume Windows Azure Storage Let’s firstly have a look on how to consume WAS through Node.js. As we know in the previous post we can host Node.js application on Windows Azure Web Site (a.k.a. WAWS) as well as Windows Azure Cloud Service (a.k.a. WACS). In theory, WAWS is also built on top of WACS worker roles with some more features. Hence in this post I will only demonstrate for hosting in WACS worker role. The Node.js code can be used when consuming WAS when hosted on WAWS. But since there’s no roles in WAWS, the code for consuming service runtime mentioned in the next section cannot be used for WAWS node application. We can use the solution that I created in my last post. Alternatively we can create a new windows azure project in Visual Studio with a worker role, add the “node.exe” and “index.js” and install “express” and “node-sqlserver” modules, make all files as “Copy always”. In order to use windows azure services we need to have Windows Azure Node.js SDK, as knows as a module named “azure” which can be installed through NPM. Once we downloaded and installed, we need to include them in our worker role project and make them as “Copy always”. You can use my “Copy all always” tool mentioned in my last post to update the currently worker role project file. You can also find the source code of this tool here. The source code of Windows Azure SDK for Node.js can be found in its GitHub page. It contains two parts. One is a CLI tool which provides a cross platform command line package for Mac and Linux to manage WAWS and Windows Azure Virtual Machines (a.k.a. WAVM). The other is a library for managing and consuming vary windows azure services includes tables, blobs, queues, service bus and the service runtime. I will not cover all of them but will only demonstrate on how to use tables and service runtime information in this post. You can find the full document of this SDK here. Back to Visual Studio and open the “index.js”, let’s continue our application from the last post, which was working against Windows Azure SQL Database (a.k.a. WASD). The code should looks like this. 1: var express = require("express"); 2: var sql = require("node-sqlserver"); 3:  4: var connectionString = "Driver={SQL Server Native Client 10.0};Server=tcp:ac6271ya9e.database.windows.net,1433;Database=synctile;Uid=shaunxu@ac6271ya9e;Pwd={PASSWORD};Encrypt=yes;Connection Timeout=30;"; 5: var port = 80; 6:  7: var app = express(); 8:  9: app.configure(function () { 10: app.use(express.bodyParser()); 11: }); 12:  13: app.get("/", function (req, res) { 14: sql.open(connectionString, function (err, conn) { 15: if (err) { 16: console.log(err); 17: res.send(500, "Cannot open connection."); 18: } 19: else { 20: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 21: if (err) { 22: console.log(err); 23: res.send(500, "Cannot retrieve records."); 24: } 25: else { 26: res.json(results); 27: } 28: }); 29: } 30: }); 31: }); 32:  33: app.get("/text/:key/:culture", function (req, res) { 34: sql.open(connectionString, function (err, conn) { 35: if (err) { 36: console.log(err); 37: res.send(500, "Cannot open connection."); 38: } 39: else { 40: var key = req.params.key; 41: var culture = req.params.culture; 42: var command = "SELECT * FROM [Resource] WHERE [Key] = '" + key + "' AND [Culture] = '" + culture + "'"; 43: conn.queryRaw(command, function (err, results) { 44: if (err) { 45: console.log(err); 46: res.send(500, "Cannot retrieve records."); 47: } 48: else { 49: res.json(results); 50: } 51: }); 52: } 53: }); 54: }); 55:  56: app.get("/sproc/:key/:culture", function (req, res) { 57: sql.open(connectionString, function (err, conn) { 58: if (err) { 59: console.log(err); 60: res.send(500, "Cannot open connection."); 61: } 62: else { 63: var key = req.params.key; 64: var culture = req.params.culture; 65: var command = "EXEC GetItem '" + key + "', '" + culture + "'"; 66: conn.queryRaw(command, function (err, results) { 67: if (err) { 68: console.log(err); 69: res.send(500, "Cannot retrieve records."); 70: } 71: else { 72: res.json(results); 73: } 74: }); 75: } 76: }); 77: }); 78:  79: app.post("/new", function (req, res) { 80: var key = req.body.key; 81: var culture = req.body.culture; 82: var val = req.body.val; 83:  84: sql.open(connectionString, function (err, conn) { 85: if (err) { 86: console.log(err); 87: res.send(500, "Cannot open connection."); 88: } 89: else { 90: var command = "INSERT INTO [Resource] VALUES ('" + key + "', '" + culture + "', N'" + val + "')"; 91: conn.queryRaw(command, function (err, results) { 92: if (err) { 93: console.log(err); 94: res.send(500, "Cannot retrieve records."); 95: } 96: else { 97: res.send(200, "Inserted Successful"); 98: } 99: }); 100: } 101: }); 102: }); 103:  104: app.listen(port); Now let’s create a new function, copy the records from WASD to table service. 1. Delete the table named “resource”. 2. Create a new table named “resource”. These 2 steps ensures that we have an empty table. 3. Load all records from the “resource” table in WASD. 4. For each records loaded from WASD, insert them into the table one by one. 5. Prompt to user when finished. In order to use table service we need the storage account and key, which can be found from the developer portal. Just select the storage account and click the Manage Keys button. Then create two local variants in our Node.js application for the storage account name and key. Since we need to use WAS we need to import the azure module. Also I created another variant stored the table name. In order to work with table service I need to create the storage client for table service. This is very similar as the Windows Azure SDK for .NET. As the code below I created a new variant named “client” and use “createTableService”, specified my storage account name and key. 1: var azure = require("azure"); 2: var storageAccountName = "synctile"; 3: var storageAccountKey = "/cOy9L7xysXOgPYU9FjDvjrRAhaMX/5tnOpcjqloPNDJYucbgTy7MOrAW7CbUg6PjaDdmyl+6pkwUnKETsPVNw=="; 4: var tableName = "resource"; 5: var client = azure.createTableService(storageAccountName, storageAccountKey); Now create a new function for URL “/was/init” so that we can trigger it through browser. Then in this function we will firstly load all records from WASD. 1: app.get("/was/init", function (req, res) { 2: // load all records from windows azure sql database 3: sql.open(connectionString, function (err, conn) { 4: if (err) { 5: console.log(err); 6: res.send(500, "Cannot open connection."); 7: } 8: else { 9: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 10: if (err) { 11: console.log(err); 12: res.send(500, "Cannot retrieve records."); 13: } 14: else { 15: if (results.rows.length > 0) { 16: // begin to transform the records into table service 17: } 18: } 19: }); 20: } 21: }); 22: }); When we succeed loaded all records we can start to transform them into table service. First I need to recreate the table in table service. This can be done by deleting and creating the table through table client I had just created previously. 1: app.get("/was/init", function (req, res) { 2: // load all records from windows azure sql database 3: sql.open(connectionString, function (err, conn) { 4: if (err) { 5: console.log(err); 6: res.send(500, "Cannot open connection."); 7: } 8: else { 9: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 10: if (err) { 11: console.log(err); 12: res.send(500, "Cannot retrieve records."); 13: } 14: else { 15: if (results.rows.length > 0) { 16: // begin to transform the records into table service 17: // recreate the table named 'resource' 18: client.deleteTable(tableName, function (error) { 19: client.createTableIfNotExists(tableName, function (error) { 20: if (error) { 21: error["target"] = "createTableIfNotExists"; 22: res.send(500, error); 23: } 24: else { 25: // transform the records 26: } 27: }); 28: }); 29: } 30: } 31: }); 32: } 33: }); 34: }); As you can see, the azure SDK provide its methods in callback pattern. In fact, almost all modules in Node.js use the callback pattern. For example, when I deleted a table I invoked “deleteTable” method, provided the name of the table and a callback function which will be performed when the table had been deleted or failed. Underlying, the azure module will perform the table deletion operation in POSIX async threads pool asynchronously. And once it’s done the callback function will be performed. This is the reason we need to nest the table creation code inside the deletion function. If we perform the table creation code after the deletion code then they will be invoked in parallel. Next, for each records in WASD I created an entity and then insert into the table service. Finally I send the response to the browser. Can you find a bug in the code below? I will describe it later in this post. 1: app.get("/was/init", function (req, res) { 2: // load all records from windows azure sql database 3: sql.open(connectionString, function (err, conn) { 4: if (err) { 5: console.log(err); 6: res.send(500, "Cannot open connection."); 7: } 8: else { 9: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 10: if (err) { 11: console.log(err); 12: res.send(500, "Cannot retrieve records."); 13: } 14: else { 15: if (results.rows.length > 0) { 16: // begin to transform the records into table service 17: // recreate the table named 'resource' 18: client.deleteTable(tableName, function (error) { 19: client.createTableIfNotExists(tableName, function (error) { 20: if (error) { 21: error["target"] = "createTableIfNotExists"; 22: res.send(500, error); 23: } 24: else { 25: // transform the records 26: for (var i = 0; i < results.rows.length; i++) { 27: var entity = { 28: "PartitionKey": results.rows[i][1], 29: "RowKey": results.rows[i][0], 30: "Value": results.rows[i][2] 31: }; 32: client.insertEntity(tableName, entity, function (error) { 33: if (error) { 34: error["target"] = "insertEntity"; 35: res.send(500, error); 36: } 37: else { 38: console.log("entity inserted"); 39: } 40: }); 41: } 42: // send the 43: console.log("all done"); 44: res.send(200, "All done!"); 45: } 46: }); 47: }); 48: } 49: } 50: }); 51: } 52: }); 53: }); Now we can publish it to the cloud and have a try. But normally we’d better test it at the local emulator first. In Node.js SDK there are three build-in properties which provides the account name, key and host address for local storage emulator. We can use them to initialize our table service client. We also need to change the SQL connection string to let it use my local database. The code will be changed as below. 1: // windows azure sql database 2: //var connectionString = "Driver={SQL Server Native Client 10.0};Server=tcp:ac6271ya9e.database.windows.net,1433;Database=synctile;Uid=shaunxu@ac6271ya9e;Pwd=eszqu94XZY;Encrypt=yes;Connection Timeout=30;"; 3: // sql server 4: var connectionString = "Driver={SQL Server Native Client 11.0};Server={.};Database={Caspar};Trusted_Connection={Yes};"; 5:  6: var azure = require("azure"); 7: var storageAccountName = "synctile"; 8: var storageAccountKey = "/cOy9L7xysXOgPYU9FjDvjrRAhaMX/5tnOpcjqloPNDJYucbgTy7MOrAW7CbUg6PjaDdmyl+6pkwUnKETsPVNw=="; 9: var tableName = "resource"; 10: // windows azure storage 11: //var client = azure.createTableService(storageAccountName, storageAccountKey); 12: // local storage emulator 13: var client = azure.createTableService(azure.ServiceClient.DEVSTORE_STORAGE_ACCOUNT, azure.ServiceClient.DEVSTORE_STORAGE_ACCESS_KEY, azure.ServiceClient.DEVSTORE_TABLE_HOST); Now let’s run the application and navigate to “localhost:12345/was/init” as I hosted it on port 12345. We can find it transformed the data from my local database to local table service. Everything looks fine. But there is a bug in my code. If we have a look on the Node.js command window we will find that it sent response before all records had been inserted, which is not what I expected. The reason is that, as I mentioned before, Node.js perform all IO operations in non-blocking model. When we inserted the records we executed the table service insert method in parallel, and the operation of sending response was also executed in parallel, even though I wrote it at the end of my logic. The correct logic should be, when all entities had been copied to table service with no error, then I will send response to the browser, otherwise I should send error message to the browser. To do so I need to import another module named “async”, which helps us to coordinate our asynchronous code. Install the module and import it at the beginning of the code. Then we can use its “forEach” method for the asynchronous code of inserting table entities. The first argument of “forEach” is the array that will be performed. The second argument is the operation for each items in the array. And the third argument will be invoked then all items had been performed or any errors occurred. Here we can send our response to browser. 1: app.get("/was/init", function (req, res) { 2: // load all records from windows azure sql database 3: sql.open(connectionString, function (err, conn) { 4: if (err) { 5: console.log(err); 6: res.send(500, "Cannot open connection."); 7: } 8: else { 9: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 10: if (err) { 11: console.log(err); 12: res.send(500, "Cannot retrieve records."); 13: } 14: else { 15: if (results.rows.length > 0) { 16: // begin to transform the records into table service 17: // recreate the table named 'resource' 18: client.deleteTable(tableName, function (error) { 19: client.createTableIfNotExists(tableName, function (error) { 20: if (error) { 21: error["target"] = "createTableIfNotExists"; 22: res.send(500, error); 23: } 24: else { 25: async.forEach(results.rows, 26: // transform the records 27: function (row, callback) { 28: var entity = { 29: "PartitionKey": row[1], 30: "RowKey": row[0], 31: "Value": row[2] 32: }; 33: client.insertEntity(tableName, entity, function (error) { 34: if (error) { 35: callback(error); 36: } 37: else { 38: console.log("entity inserted."); 39: callback(null); 40: } 41: }); 42: }, 43: // send reponse 44: function (error) { 45: if (error) { 46: error["target"] = "insertEntity"; 47: res.send(500, error); 48: } 49: else { 50: console.log("all done"); 51: res.send(200, "All done!"); 52: } 53: } 54: ); 55: } 56: }); 57: }); 58: } 59: } 60: }); 61: } 62: }); 63: }); Run it locally and now we can find the response was sent after all entities had been inserted. Query entities against table service is simple as well. Just use the “queryEntity” method from the table service client and providing the partition key and row key. We can also provide a complex query criteria as well, for example the code here. In the code below I queried an entity by the partition key and row key, and return the proper localization value in response. 1: app.get("/was/:key/:culture", function (req, res) { 2: var key = req.params.key; 3: var culture = req.params.culture; 4: client.queryEntity(tableName, culture, key, function (error, entity) { 5: if (error) { 6: res.send(500, error); 7: } 8: else { 9: res.json(entity); 10: } 11: }); 12: }); And then tested it on local emulator. Finally if we want to publish this application to the cloud we should change the database connection string and storage account. For more information about how to consume blob and queue service, as well as the service bus please refer to the MSDN page.   Consume Service Runtime As I mentioned above, before we published our application to the cloud we need to change the connection string and account information in our code. But if you had played with WACS you should have known that the service runtime provides the ability to retrieve configuration settings, endpoints and local resource information at runtime. Which means we can have these values defined in CSCFG and CSDEF files and then the runtime should be able to retrieve the proper values. For example we can add some role settings though the property window of the role, specify the connection string and storage account for cloud and local. And the can also use the endpoint which defined in role environment to our Node.js application. In Node.js SDK we can get an object from “azure.RoleEnvironment”, which provides the functionalities to retrieve the configuration settings and endpoints, etc.. In the code below I defined the connection string variants and then use the SDK to retrieve and initialize the table client. 1: var connectionString = ""; 2: var storageAccountName = ""; 3: var storageAccountKey = ""; 4: var tableName = ""; 5: var client; 6:  7: azure.RoleEnvironment.getConfigurationSettings(function (error, settings) { 8: if (error) { 9: console.log("ERROR: getConfigurationSettings"); 10: console.log(JSON.stringify(error)); 11: } 12: else { 13: console.log(JSON.stringify(settings)); 14: connectionString = settings["SqlConnectionString"]; 15: storageAccountName = settings["StorageAccountName"]; 16: storageAccountKey = settings["StorageAccountKey"]; 17: tableName = settings["TableName"]; 18:  19: console.log("connectionString = %s", connectionString); 20: console.log("storageAccountName = %s", storageAccountName); 21: console.log("storageAccountKey = %s", storageAccountKey); 22: console.log("tableName = %s", tableName); 23:  24: client = azure.createTableService(storageAccountName, storageAccountKey); 25: } 26: }); In this way we don’t need to amend the code for the configurations between local and cloud environment since the service runtime will take care of it. At the end of the code we will listen the application on the port retrieved from SDK as well. 1: azure.RoleEnvironment.getCurrentRoleInstance(function (error, instance) { 2: if (error) { 3: console.log("ERROR: getCurrentRoleInstance"); 4: console.log(JSON.stringify(error)); 5: } 6: else { 7: console.log(JSON.stringify(instance)); 8: if (instance["endpoints"] && instance["endpoints"]["nodejs"]) { 9: var endpoint = instance["endpoints"]["nodejs"]; 10: app.listen(endpoint["port"]); 11: } 12: else { 13: app.listen(8080); 14: } 15: } 16: }); But if we tested the application right now we will find that it cannot retrieve any values from service runtime. This is because by default, the entry point of this role was defined to the worker role class. In windows azure environment the service runtime will open a named pipeline to the entry point instance, so that it can connect to the runtime and retrieve values. But in this case, since the entry point was worker role and the Node.js was opened inside the role, the named pipeline was established between our worker role class and service runtime, so our Node.js application cannot use it. To fix this problem we need to open the CSDEF file under the azure project, add a new element named Runtime. Then add an element named EntryPoint which specify the Node.js command line. So that the Node.js application will have the connection to service runtime, then it’s able to read the configurations. Start the Node.js at local emulator we can find it retrieved the connections, storage account for local. And if we publish our application to azure then it works with WASD and storage service through the configurations for cloud.   Summary In this post I demonstrated how to use Windows Azure SDK for Node.js to interact with storage service, especially the table service. I also demonstrated on how to use WACS service runtime, how to retrieve the configuration settings and the endpoint information. And in order to make the service runtime available to my Node.js application I need to create an entry point element in CSDEF file and set “node.exe” as the entry point. I used five posts to introduce and demonstrate on how to run a Node.js application on Windows platform, how to use Windows Azure Web Site and Windows Azure Cloud Service worker role to host our Node.js application. I also described how to work with other services provided by Windows Azure platform through Windows Azure SDK for Node.js. Node.js is a very new and young network application platform. But since it’s very simple and easy to learn and deploy, as well as, it utilizes single thread non-blocking IO model, Node.js became more and more popular on web application and web service development especially for those IO sensitive projects. And as Node.js is very good at scaling-out, it’s more useful on cloud computing platform. Use Node.js on Windows platform is new, too. The modules for SQL database and Windows Azure SDK are still under development and enhancement. It doesn’t support SQL parameter in “node-sqlserver”. It does support using storage connection string to create the storage client in “azure”. But Microsoft is working on make them easier to use, working on add more features and functionalities.   PS, you can download the source code here. You can download the source code of my “Copy all always” tool here.   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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  • BULK INSERT from one table to another all on the server

    - by steve_d
    I have to copy a bunch of data from one database table into another. I can't use SELECT ... INTO because one of the columns is an identity column. Also, I have some changes to make to the schema. I was able to use the export data wizard to create an SSIS package, which I then edited in Visual Studio 2005 to make the changes desired and whatnot. It's certainly faster than an INSERT INTO, but it seems silly to me to download the data to a different computer just to upload it back again. (Assuming that I am correct that that's what the SSIS package is doing). Is there an equivalent to BULK INSERT that runs directly on the server, allows keeping identity values, and pulls data from a table? (as far as I can tell, BULK INSERT can only pull data from a file) Edit: I do know about IDENTITY_INSERT, but because there is a fair amount of data involved, INSERT INTO ... SELECT is kinda of slow. SSIS/BULK INSERT dumps the data into the table without regards to indexes and logging and whatnot, so it's faster. (Of course creating the clustered index on the table once it's populated is not fast, but it's still faster than the INSERT INTO...SELECT that I tried in my first attempt) Edit 2: The schema changes include (but are not limited to) the following: 1. Splitting one table into two new tables. In the future each will have its own IDENTITY column, but for the migration I think it will be simplest to use the identity from the original table as the identity for the both new tables. Once the migration is over one of the tables will have a one-to-many relationship to the other. 2. Moving columns from one table to another. 3. Deleting some cross reference tables that only cross referenced 1-to-1. Instead the reference will be a foreign key in one of the two tables. 4. Some new columns will be created with default values. 5. Some tables aren’t changing at all, but I have to copy them over due to the "put it all in a new DB" request.

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  • Microsoft Tech-Ed North America 2010 - SQL Server Upgrade, 2000 - 2005 - 2008: Notes and Best Practi

    - by ssqa.net
    It is just a week to go for Tech-Ed North America 2010 in New Orleans, this time also I'm speaking at this conference on the subject - SQL Server Upgrade, 2000 - 2005 - 2008: Notes and Best Practices from the Field... more from here .. It is a coincedence that this is the 2nd time the same talk has been selected in Tech-Ed North America for the topic I have presented in SQLBits before....(read more)

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  • Attention users running SQL Server 2008 & 2008 R2!

    - by AaronBertrand
    In April and May, Microsoft released cumulative updates for SQL Server 2008 and 2008 R2 (I blogged about them here and here ). They are: CU #11 for 2008 SP3 (10.00.5840) ( KB #2834048 ) CU #12 for 2008 R2 SP1 (10.50.2874) ( KB #2828727 ) CU #6 for 2008 R2 SP2 (10.50.4279) ( KB #2830140 ) Sometime after that, looks like the next day, both downloads were pulled, allegedly due to an index corruption issue (if you believe the commentary on the Release Services blog post for CU #6 ) or due to an issue...(read more)

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  • Using a "white list" for extracting terms for Text Mining

    - by [email protected]
    In Part 1 of my post on "Generating cluster names from a document clustering model" (part 1, part 2, part 3), I showed how to build a clustering model from text documents using Oracle Data Miner, which automates preparing data for text mining. In this process we specified a custom stoplist and lexer and relied on Oracle Text to identify important terms.  However, there is an alternative approach, the white list, which uses a thesaurus object with the Oracle Text CTXRULE index to allow you to specify the important terms. INTRODUCTIONA stoplist is used to exclude, i.e., black list, specific words in your documents from being indexed. For example, words like a, if, and, or, and but normally add no value when text mining. Other words can also be excluded if they do not help to differentiate documents, e.g., the word Oracle is ubiquitous in the Oracle product literature. One problem with stoplists is determining which words to specify. This usually requires inspecting the terms that are extracted, manually identifying which ones you don't want, and then re-indexing the documents to determine if you missed any. Since a corpus of documents could contain thousands of words, this could be a tedious exercise. Moreover, since every word is considered as an individual token, a term excluded in one context may be needed to help identify a term in another context. For example, in our Oracle product literature example, the words "Oracle Data Mining" taken individually are not particular helpful. The term "Oracle" may be found in nearly all documents, as with the term "Data." The term "Mining" is more unique, but could also refer to the Mining industry. If we exclude "Oracle" and "Data" by specifying them in the stoplist, we lose valuable information. But it we include them, they may introduce too much noise. Still, when you have a broad vocabulary or don't have a list of specific terms of interest, you rely on the text engine to identify important terms, often by computing the term frequency - inverse document frequency metric. (This is effectively a weight associated with each term indicating its relative importance in a document within a collection of documents. We'll revisit this later.) The results using this technique is often quite valuable. As noted above, an alternative to the subtractive nature of the stoplist is to specify a white list, or a list of terms--perhaps multi-word--that we want to extract and use for data mining. The obvious downside to this approach is the need to specify the set of terms of interest. However, this may not be as daunting a task as it seems. For example, in a given domain (Oracle product literature), there is often a recognized glossary, or a list of keywords and phrases (Oracle product names, industry names, product categories, etc.). Being able to identify multi-word terms, e.g., "Oracle Data Mining" or "Customer Relationship Management" as a single token can greatly increase the quality of the data mining results. The remainder of this post and subsequent posts will focus on how to produce a dataset that contains white list terms, suitable for mining. CREATING A WHITE LIST We'll leverage the thesaurus capability of Oracle Text. Using a thesaurus, we create a set of rules that are in effect our mapping from single and multi-word terms to the tokens used to represent those terms. For example, "Oracle Data Mining" becomes "ORACLEDATAMINING." First, we'll create and populate a mapping table called my_term_token_map. All text has been converted to upper case and values in the TERM column are intended to be mapped to the token in the TOKEN column. TERM                                TOKEN DATA MINING                         DATAMINING ORACLE DATA MINING                  ORACLEDATAMINING 11G                                 ORACLE11G JAVA                                JAVA CRM                                 CRM CUSTOMER RELATIONSHIP MANAGEMENT    CRM ... Next, we'll create a thesaurus object my_thesaurus and a rules table my_thesaurus_rules: CTX_THES.CREATE_THESAURUS('my_thesaurus', FALSE); CREATE TABLE my_thesaurus_rules (main_term     VARCHAR2(100),                                  query_string  VARCHAR2(400)); We next populate the thesaurus object and rules table using the term token map. A cursor is defined over my_term_token_map. As we iterate over  the rows, we insert a synonym relationship 'SYN' into the thesaurus. We also insert into the table my_thesaurus_rules the main term, and the corresponding query string, which specifies synonyms for the token in the thesaurus. DECLARE   cursor c2 is     select token, term     from my_term_token_map; BEGIN   for r_c2 in c2 loop     CTX_THES.CREATE_RELATION('my_thesaurus',r_c2.token,'SYN',r_c2.term);     EXECUTE IMMEDIATE 'insert into my_thesaurus_rules values                        (:1,''SYN(' || r_c2.token || ', my_thesaurus)'')'     using r_c2.token;   end loop; END; We are effectively inserting the token to return and the corresponding query that will look up synonyms in our thesaurus into the my_thesaurus_rules table, for example:     'ORACLEDATAMINING'        SYN ('ORACLEDATAMINING', my_thesaurus)At this point, we create a CTXRULE index on the my_thesaurus_rules table: create index my_thesaurus_rules_idx on        my_thesaurus_rules(query_string)        indextype is ctxsys.ctxrule; In my next post, this index will be used to extract the tokens that match each of the rules specified. We'll then compute the tf-idf weights for each of the terms and create a nested table suitable for mining.

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  • SQL University: Parallelism Week - Introduction

    - by Adam Machanic
    Welcome to Parallelism Week at SQL University . My name is Adam Machanic, and I'm your professor. Imagine having 8 brains, or 16, or 32. Imagine being able to break up complex thoughts and distribute them across your many brains, so that you could solve problems faster. Now quit imagining that, because you're human and you're stuck with only one brain, and you only get access to the entire thing if you're lucky enough to have avoided abusing too many recreational drugs. For your database server,...(read more)

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