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• Taking our Friendships to the next level.

  - by RedAndTheCommunity

  Red Gate have been running the Friends of Red Gate program for years now, and over that time we've built some great relationships with some truly awesome members of the SQL and .NET communities. When I took over the running of the program from Annabel in 2011, I was overwhelmed by the enthusiasm and commitment of our Friends. There were just so many of them, however, that it was hard to make the most of the relationships we had with people, and I wanted to fix that. I decided to survey all our Friends, to find out what they wanted to get out of, and put into, being in the Friends of Red Gate (FoRG) program. From the results of that survey, I identified 30 FoRGs that were really willing and able to go that step further to help Red Gate improve their tools, improve their relationship with the community, and improve the Friends of Red Gate program. Those 30 Friends of Red Gate have been awarded 'FoRG+' status. That means they'll: Have a closer relationship with the product teams, by getting involved in projects Have even more access to the inside track about the tools they're interested in Get the opportunity to come visit us at the Red Gate office and really influence the development of the tools. Plus more, depending on how the individual FoRG+ wants to work with us. This doesn't mean I've forgotten our other Friends; I'm working on ways to improve their experience of the Friends of Red Gate program. I'll write about them in another post. If you're an existing Friend of Red Gate, and you're interested in finding out how to get involved in the FoRG+ program, then I'd love to chat to you. For anyone that's interested in joining the Friend of Red Gate program, take a look at the web page dedicated to the program, and get in touch at [email protected] to be put on the waiting list for our 2013 program.

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• Monitoring Baseline

  - by Grant Fritchey

  Knowing what's happening on your servers is important, that's monitoring. Knowing what happened on your server is establishing a baseline. You need to do both. I really enjoyed this blog post by Ted Krueger (blog|twitter). It's not enough to know what happened in the last hour or yesterday, you need to compare today to last week, especially if you released software this weekend. You need to compare today to 30 days ago in order to begin to establish future projections. How your data has changed over 30 days is a great indicator how it's going to change for the next 30. No, it's not perfect, but predicting the future is not exactly a science, just ask your local weatherman. Red Gate's SQL Monitor can show you the last week, the last 30 days, the last year, or all data you've collected (if you choose to keep a year's worth of data or more, please have PLENTY of storage standing by). You have a lot of choice and control here over how much data you store. Here's the configuration window showing how you can set this up: This is for version 2.3 of SQL Monitor, so if you're running an older version, you might want to update. The key point is, a baseline simply represents a moment in time in your server. The ability to compare now to then is what you're looking for in order to really have a useful baseline as Ted lays out so well in his post.

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• Developing Schema Compare for Oracle (Part 6): 9i Query Performance

  - by Simon Cooper

  All throughout the EAP and beta versions of Schema Compare for Oracle, our main request was support for Oracle 9i. After releasing version 1.0 with support for 10g and 11g, our next step was then to get version 1.1 of SCfO out with support for 9i. However, there were some significant problems that we had to overcome first. This post will concentrate on query execution time. When we first tested SCfO on a 9i server, after accounting for various changes to the data dictionary, we found that database registration was taking a long time. And I mean a looooooong time. The same database that on 10g or 11g would take a couple of minutes to register would be taking upwards of 30 mins on 9i. Obviously, this is not ideal, so a poke around the query execution plans was required. As an example, let's take the table population query - the one that reads ALL_TABLES and joins it with a few other dictionary views to get us back our list of tables. On 10g, this query takes 5.6 seconds. On 9i, it takes 89.47 seconds. The difference in execution plan is even more dramatic - here's the (edited) execution plan on 10g: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 108K| 939 || 1 | SORT ORDER BY | | 108K| 939 || 2 | NESTED LOOPS OUTER | | 108K| 938 ||* 3 | HASH JOIN RIGHT OUTER | | 103K| 762 || 4 | VIEW | ALL_EXTERNAL_LOCATIONS | 2058 | 3 ||* 20 | HASH JOIN RIGHT OUTER | | 73472 | 759 || 21 | VIEW | ALL_EXTERNAL_TABLES | 2097 | 3 ||* 34 | HASH JOIN RIGHT OUTER | | 39920 | 755 || 35 | VIEW | ALL_MVIEWS | 51 | 7 || 58 | NESTED LOOPS OUTER | | 39104 | 748 || 59 | VIEW | ALL_TABLES | 6704 | 668 || 89 | VIEW PUSHED PREDICATE | ALL_TAB_COMMENTS | 2025 | 5 || 106 | VIEW | ALL_PART_TABLES | 277 | 11 |------------------------------------------------------------------------------- And the same query on 9i: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 16P| 55G|| 1 | SORT ORDER BY | | 16P| 55G|| 2 | NESTED LOOPS OUTER | | 16P| 862M|| 3 | NESTED LOOPS OUTER | | 5251G| 992K|| 4 | NESTED LOOPS OUTER | | 4243M| 2578 || 5 | NESTED LOOPS OUTER | | 2669K| 1440 ||* 6 | HASH JOIN OUTER | | 398K| 302 || 7 | VIEW | ALL_TABLES | 342K| 276 || 29 | VIEW | ALL_MVIEWS | 51 | 20 ||* 50 | VIEW PUSHED PREDICATE | ALL_TAB_COMMENTS | 2043 | ||* 66 | VIEW PUSHED PREDICATE | ALL_EXTERNAL_TABLES | 1777K| ||* 80 | VIEW PUSHED PREDICATE | ALL_EXTERNAL_LOCATIONS | 1744K| ||* 96 | VIEW | ALL_PART_TABLES | 852K| |------------------------------------------------------------------------------- Have a look at the cost column. 10g's overall query cost is 939, and 9i is 55,000,000,000 (or more precisely, 55,496,472,769). It's also having to process far more data. What on earth could be causing this huge difference in query cost? After trawling through the '10g New Features' documentation, we found item 1.9.2.21. Before 10g, Oracle advised that you do not collect statistics on data dictionary objects. From 10g, it advised that you do collect statistics on the data dictionary; for our queries, Oracle therefore knows what sort of data is in the dictionary tables, and so can generate an efficient execution plan. On 9i, no statistics are present on the system tables, so Oracle has to use the Rule Based Optimizer, which turns most LEFT JOINs into nested loops. If we force 9i to use hash joins, like 10g, we get a much better plan: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 7587K| 3704 || 1 | SORT ORDER BY | | 7587K| 3704 ||* 2 | HASH JOIN OUTER | | 7587K| 822 ||* 3 | HASH JOIN OUTER | | 5262K| 616 ||* 4 | HASH JOIN OUTER | | 2980K| 465 ||* 5 | HASH JOIN OUTER | | 710K| 432 ||* 6 | HASH JOIN OUTER | | 398K| 302 || 7 | VIEW | ALL_TABLES | 342K| 276 || 29 | VIEW | ALL_MVIEWS | 51 | 20 || 50 | VIEW | ALL_PART_TABLES | 852K| 104 || 78 | VIEW | ALL_TAB_COMMENTS | 2043 | 14 || 93 | VIEW | ALL_EXTERNAL_LOCATIONS | 1744K| 31 || 106 | VIEW | ALL_EXTERNAL_TABLES | 1777K| 28 |------------------------------------------------------------------------------- That's much more like it. This drops the execution time down to 24 seconds. Not as good as 10g, but still an improvement. There are still several problems with this, however. 10g introduced a new join method - a right outer hash join (used in the first execution plan). The 9i query optimizer doesn't have this option available, so forcing a hash join means it has to hash the ALL_TABLES table, and furthermore re-hash it for every hash join in the execution plan; this could be thousands and thousands of rows. And although forcing hash joins somewhat alleviates this problem on our test systems, there's no guarantee that this will improve the execution time on customers' systems; it may even increase the time it takes (say, if all their tables are partitioned, or they've got a lot of materialized views). Ideally, we would want a solution that provides a speedup whatever the input. To try and get some ideas, we asked some oracle performance specialists to see if they had any ideas or tips. Their recommendation was to add a hidden hook into the product that allowed users to specify their own query hints, or even rewrite the queries entirely. However, we would prefer not to take that approach; as well as a lot of new infrastructure & a rewrite of the population code, it would have meant that any users of 9i would have to spend some time optimizing it to get it working on their system before they could use the product. Another approach was needed. All our population queries have a very specific pattern - a base table provides most of the information we need (ALL_TABLES for tables, or ALL_TAB_COLS for columns) and we do a left join to extra subsidiary tables that fill in gaps (for instance, ALL_PART_TABLES for partition information). All the left joins use the same set of columns to join on (typically the object owner & name), so we could re-use the hash information for each join, rather than re-hashing the same columns for every join. To allow us to do this, along with various other performance improvements that could be done for the specific query pattern we were using, we read all the tables individually and do a hash join on the client. Fortunately, this 'pure' algorithmic problem is the kind that can be very well optimized for expected real-world situations; as well as storing row data we're not using in the hash key on disk, we use very specific memory-efficient data structures to store all the information we need. This allows us to achieve a database population time that is as fast as on 10g, and even (in some situations) slightly faster, and a memory overhead of roughly 150 bytes per row of data in the result set (for schemas with 10,000 tables in that means an extra 1.4MB memory being used during population). Next: fun with the 9i dictionary views.

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• Azure

  - by Grant Fritchey

  I've been tasked to learn SQL Azure, as well as test all the Red Gate products on it. My one, BIG, fear has been that I'll receive some mongo bill in the mail because I've exceeded the MSDN testing limit. I know people that have had that problem. I've been trying to keep an eye on my usage, but, let's face it, it's not something I think about every day. But now I don't have to. Red Gate has been working with Azure, long before I showed up. They already released a little piece of software that I just found out about, it's called CloudTally. It gathers your usage and sends you a daily email so you can know if you're starting to approach that limit. Check it out, it's free.

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• Sharing My Thoughts on Space Flight

  - by Grant Fritchey

  This went out in the DBA newsletter from Red Gate, but I enjoyed writing it so much, I thought I'd share it to a wider audience: I grew up watching the US space program. I watched men walk on the moon for the first time in 1969, when I was only six years old. From that moment on, I dreamed of going into space. I studied aeronautics and tried to get into the Air Force Academy, all in preparation for my long career as an astronaut. Clearly, that didn't quite work out for me. But it sure could for you. At Red Gate, we're running a new contest: DBA in Space. The prize is a sub-orbital flight. When I first got word of this contest, my immediate response was, "And you need me to go right away and do a test flight? Excellent!" No, no test flight needed, plus I was pretty low on the list of volunteers. "That's OK, I'll just enter." Then I was told that, as a Red Gate employee, I couldn't win. My next response was, "I quit".eventually, I was talked down off the ledge, and agreed to help make this special for some other DBA. Many (most?) of us are science fiction fans, either the soft science of Star Trek and Star Wars, or the hard science of Niven and Pournelle, or Allen Steele. We watched the Shuttles go up and land. We've been dreaming of our own trips into orbit and our vacation-home on the Moon for a long, long time. All that might not arrive on schedule, but you've got a shot at breaking clear of the atmosphere. The first stage is a video quiz, starring Brad McGehee, and it's live at www.DBAinSpace.com now. Go for it. Good luck and God speed!

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• Developing Schema Compare for Oracle (Part 4): Script Configuration

  - by Simon Cooper

  If you've had a chance to play around with the Schema Compare for Oracle beta, you may have come across this screen in the synchronization wizard: This screen is one of the few screens that, along with the project configuration form, doesn't come from SQL Compare. This screen was designed to solve a couple of issues that, although aren't specific to Oracle, are much more of a problem than on SQL Server: Datatype conversions and NOT NULL columns. 1. Datatype conversions SQL Server is generally quite forgiving when it comes to datatype conversions using ALTER TABLE. For example, you can convert from a VARCHAR to INT using ALTER TABLE as long as all the character values are parsable as integers. Oracle, on the other hand, only allows ALTER TABLE conversions that don't change the internal data format. Essentially, every change that requires an actual datatype conversion has to be done using a rebuild with a conversion function. That's OK, as we can simply hard-code the various conversion functions for the valid datatype conversions and insert those into the rebuild SELECT list. However, as there always is with Oracle, there's a catch. Have a look at the NUMTODSINTERVAL function. As well as specifying the value (or column) to convert, you have to specify an interval_unit, which tells oracle how to interpret the input number. We can't hardcode a default for this parameter, as it is entirely dependent on the user's data context! So, in order to convert NUMBER to INTERVAL DAY TO SECOND/INTERVAL YEAR TO MONTH, we need to have feedback from the user as to what to put in this parameter while we're generating the sync script - this requires a new step in the engine action/script generation to insert these values into the script, as well as new UI to allow the user to specify these values in a sensible fashion. In implementing the engine and UI infrastructure to allow this it made much more sense to implement it for any rebuild datatype conversion, not just NUMBER to INTERVALs. For conversions which we can do, we pre-fill the 'value' box with the appropriate function from the documentation. The user can also type in arbitary SQL expressions, which allows the user to specify optional format parameters for the relevant conversion functions, or indeed call their own functions to convert between values that don't have a built-in conversion defined. As the value gets inserted as-is into the rebuild SELECT list, any expression that is valid in that context can be specified as the conversion value. 2. NOT NULL columns Another problem that is solved by the new step in the sync wizard is adding a NOT NULL column to a table. If the table contains data (as most database tables do), you can't just add a NOT NULL column, as Oracle doesn't know what value to put in the new column for existing rows - the DDL statement will fail. There are actually 3 separate scenarios for this problem that have separate solutions within the engine: Adding a NOT NULL column to a table without a rebuild Here, the workaround is to add a column default with an appropriate value to the column you're adding: ALTER TABLE tbl1 ADD newcol NUMBER DEFAULT <value> NOT NULL; Note, however, there is something to bear in mind about this solution; once specified on a column, a default cannot be removed. To 'remove' a default from a column you change it to have a default of NULL, hence there's code in the engine to treat a NULL default the same as no default at all. Adding a NOT NULL column to a table, where a separate change forced a table rebuild Fortunately, in this case, a column default is not required - we can simply insert the default value into the rebuild SELECT clause. Changing an existing NULL to a NOT NULL column To implement this, we run an UPDATE command before the ALTER TABLE to change all the NULLs in the column to the required default value. For all three, we need some way of allowing the user to specify a default value to use instead of NULL; as this is essentially the same problem as datatype conversion (inserting values into the sync script), we can re-use the UI and engine implementation of datatype conversion values. We also provide the option to alter the new column to allow NULLs, or to ignore the problem completely. Note that there is the same (long-running) problem in SQL Compare, but it is much more of an issue in Oracle as you cannot easily roll back executed DDL statements if the script fails at some point during execution. Furthermore, the engine of SQL Compare is far less conducive to inserting user-supplied values into the generated script. As we're writing the Schema Compare engine from scratch, we used what we learnt from the SQL Compare engine and designed it to be far more modular, which makes inserting procedures like this much easier.

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• LiveMeeting VC PowerShell PASS – Troubleshooting SQL Server with PowerShell

  - by Laerte Junior

  Guys, join me on Wednesday July 18th 12 noon EDT (GMT -4) for a presentation called Troubleshooting SQL Server With PowerShell. It will be in English, so please make allowances for this. I’m sure that you’re aware that my English is not perfect, but it is not so bad. I will do my best, you can be sure. The registration link will be available soon from PowerShell.sqlpass.org, so I hope to see you there. It will be a session without slides. Just code; pure PowerShell code. Trust me, We will see a lot of COOL stuff.Big thanks to Aaron Nelson (@sqlvariant) for the opportunity! Here are some more details about the presentation: “Troubleshooting SQL Server with PowerShell – The Next Level’ It is normal for us to have to face poorly performing queries or even complete failure in our SQL server environments. This can happen for a variety of reasons including poor Database Designs, hardware failure, improperly-configured systems and OS Updates applied without testing. As Database Administrators, we need to take precaution to minimize the impact of these problems when they occur, and so we need the tools and methodology required to identify and solve issues quickly. In this Session we will use PowerShell to explore some common troubleshooting techniques used in our day-to-day work as s DBA. This will include a variety of such activities including Gathering Performance Counters in several servers at the same time using background jobs, identifying Blocked Sessions and Reading & filtering the SQL Error Log even if the Instance is offline The approach will be using some advanced PowerShell techniques that allow us to scale the code for multiple servers and run the data collection in asynchronous mode.

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• Last Chance At Space

  - by Grant Fritchey

  All entries for the DBA In Space contest have to be in by this Friday, the 18th. I’m so jealous of all of you who can enter this contest. Just think about it. You’re getting a chance to take a sub-orbital rocket ride. But, here’s the kicker, the chances are limited to data professionals. That’s a pretty small sub-set when you think about it. Further, you have to gotten the answers to the quiz questions correct, which only takes a little bit of honest research, but come on. That further limits the result set. You’ve really got an excellent shot at this (and the jealousy rears it’s ugly head again). If you haven’t finished your entry, go on over to the link and get it taken care of. There’s really no reason to not do it. Oh, and by the way, if you’re one of those (I’d say crazy) people who don’t want to ride the rocket, you can take the prize in cash. Although I’d be mighty disappointed in you if you did.

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• Optimizing Transaction Log Throughput

  As a DBA, it is vital to manage transaction log growth explicitly, rather than let SQL Server auto-growth events "manage" it for you. If you undersize the log, and then let SQL Server auto-grow it in small increments, you'll end up with a very fragmented log. Examples in the article, extracted from SQL Server Transaction Log Management by Tony Davis and Gail Shaw, demonstrate how this can have a significant impact on the performance of any SQL Server operations that need to read the log.

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• Software Tuned to Humanity

  - by Phil Factor

  I learned a great deal from a cynical old programmer who once told me that the ideal length of time for a compiler to do its work was the same time it took to roll a cigarette. For development work, this is oh so true. After intently looking at the editing window for an hour or so, it was a relief to look up, stretch, focus the eyes on something else, and roll the possibly-metaphorical cigarette. This was software tuned to humanity. Likewise, a user’s perception of the “ideal” time that an application will take to move from frame to frame, to retrieve information, or to process their input has remained remarkably static for about thirty years, at around 200 ms. Anything else appears, and always has, to be either fast or slow. This could explain why commercial applications, unlike games, simulations and communications, aren’t noticeably faster now than they were when I started programming in the Seventies. Sure, they do a great deal more, but the SLAs that I negotiated in the 1980s for application performance are very similar to what they are nowadays. To prove to myself that this wasn’t just some rose-tinted misperception on my part, I cranked up a Z80-based Jonos CP/M machine (1985) in the roof-space. Within 20 seconds from cold, it had loaded Wordstar and I was ready to write. OK, I got it wrong: some things were faster 30 years ago. Sure, I’d now have had all sorts of animations, wizzy graphics, and other comforting features, but it seems a pity that we have used all that extra CPU and memory to increase the scope of what we develop, and the graphical prettiness, but not to speed the processes needed to complete a business procedure. Never mind the weight, the response time’s great! To achieve 200 ms response times on a Z80, or similar, performance considerations influenced everything one did as a developer. If it meant writing an entire application in assembly code, applying every smart algorithm, and shortcut imaginable to get the application to perform to spec, then so be it. As a result, I’m a dyed-in-the-wool performance freak and find it difficult to change my habits. Conversely, many developers now seem to feel quite differently. While all will acknowledge that performance is important, it’s no longer the virtue is once was, and other factors such as user-experience now take precedence. Am I wrong? If not, then perhaps we need a new school of development technique to rival Agile, dedicated once again to producing applications that smoke the rear wheels rather than pootle elegantly to the shops; that forgo skeuomorphism, cute animation, or architectural elegance in favor of the smell of hot rubber. I struggle to name an application I use that is truly notable for its blistering performance, and would dearly love one to do my everyday work – just as long as it doesn’t go faster than my brain.

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• New features in SQL Prompt 6.4

  - by Tom Crossman

  We’re pleased to announce a new beta version of SQL Prompt. We’ve been trying out a few new core technologies, and used them to add features and bug fixes suggested by users on the SQL Prompt forum and suggestions forum. You can download the SQL Prompt 6.4 beta here (zip file). Let us know what you think! New features Execute current statement In a query window, you can now execute the SQL statement under your cursor by pressing Shift + F5. For example, if you have a query containing two statements and your cursor is placed on the second statement: When you press Shift + F5, only the second statement is executed:   Insert semicolons You can now use SQL Prompt to automatically insert missing semicolons after each statement in a query. To insert semicolons, go to the SQL Prompt menu and click Insert Semicolons. Alternatively, hold Ctrl and press B then C. BEGIN…END block highlighting When you place your cursor over a BEGIN or END keyword, SQL Prompt now automatically highlights the matching keyword: Rename variables and aliases You can now use SQL Prompt to rename all occurrences of a variable or alias in a query. To rename a variable or alias, place your cursor over an instance of the variable or alias you want to rename and press F2: Improved loading dialog box The database loading dialog box now shows actual progress, and you can cancel loading databases:   Single suggestion improvement SQL Prompt no longer suggests keywords if the keyword has been typed and no other suggestions exist. Performance improvement SQL Prompt now has less impact on Management Studio start up time. What do you think? We want to hear your feedback about the beta. If you have any suggestions, or bugs to report, tell us on the SQL Prompt forum or our suggestions forum.

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• Getting the URL to the Content Type Hub Programmatically in SharePoint 2010

  - by Damon

  Many organizations use the content-type hub to manage content-types in their SharePoint 2010 environment.  As a developer in these types of organizations, you may one day find yourself in need of getting the URL of the content type hub programmatically.  Here is a quick snippet that demonstrates how to do it fairly painlessly: public static Uri GetContentTypeHubUri(SPSite site) {     TaxonomySession session = new TaxonomySession(site);     return Session.DefaultSiteCollectionTermStore         .ContentTypePublishingHub; }

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• C# 5: At last, async without the pain

  - by Alex.Davies

  For me, the best feature in Visual Studio 11 is the async and await keywords that come with C# 5. I am a big fan of asynchronous programming: it frees up resources, in particular the thread that a piece of code needs to run in. That lets that thread run something else, while waiting for your long-running operation to complete. That's really important if that thread is the UI thread, or if it's holding a lock because it accesses some data structure. Before C# 5, I think I was about the only person in the world who really cared about asynchronous programming. The trouble was that you had to go to extreme lengths to make code asynchronous. I would forever be writing methods that, instead of returning a value, accepted an extra argument that is a "continuation". Then, when calling the method, I'd have to pass a lambda in to it, which contained all the stuff that needed to happen after the method finished. Here is a real snippet of code that is in .NET Demon: m_BuildControl.FilterEnabledForBuilding(     projects,     enabledProjects = m_OutOfDateProjectFinder.FilterNeedsBuilding(         enabledProjects,         newDirtyProjects =         {             // Mark any currently broken projects as dirty             newDirtyProjects.UnionWith(m_BrokenProjects);             // Copy what we found into the set of dirty things             m_DirtyProjects = newDirtyProjects;             RunSomeBuilds();         })); It's just obtuse. Who puts a lambda inside a lambda like that? Well, me obviously. But surely enabledProjects should just be the return value of FilterEnabledForBuilding? And newDirtyProjects should just be the return value of FilterNeedsBuilding? C# 5 async/await lets you write asynchronous code without it looking so stupid. Here's what I plan to change that code to, once we upgrade to VS 11: var enabledProjects = await m_BuildControl.FilterEnabledForBuilding(projects); var newDirtyProjects = await m_OutOfDateProjectFinder.FilterNeedsBuilding(enabledProjects); // Mark any currently broken projects as dirty newDirtyProjects.UnionWith(m_BrokenProjects); // Copy what we found into the set of dirty things m_DirtyProjects = newDirtyProjects; RunSomeBuilds(); Much easier to read! But how is this the same code? If we were on the UI thread, doesn't the UI thread have to block while FilterEnabledForBuilding runs? No, it doesn't, and that's the magic of the await keyword! It cuts your method up into its constituent pieces, much like I did manually with lambdas before. When you run it, only the piece up to the first await actually runs. The rest is passed to FilterEnabledForBuilding as a continuation, which will get called back whenever that method is finished. In the meantime, our thread returns, and can go back to making the UI responsive, or whatever else threads do in their spare time. This is actually a massive simplification, and if you're interested in all the gory details, and speed hacks that the await keyword actually does for you, I recommend Jon Skeet's blog posts about it.

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• Subterranean IL: Exception handling 2

  - by Simon Cooper

  Control flow in and around exception handlers is tightly controlled, due to the various ways the handler blocks can be executed. To start off with, I'll describe what SEH does when an exception is thrown. Handling exceptions When an exception is thrown, the CLR stops program execution at the throw statement and searches up the call stack looking for an appropriate handler; catch clauses are analyzed, and filter blocks are executed (I'll be looking at filter blocks in a later post). Then, when an appropriate catch or filter handler is found, the stack is unwound to that handler, executing successive finally and fault handlers in their own stack contexts along the way, and program execution continues at the start of the catch handler. Because catch, fault, finally and filter blocks can be executed essentially out of the blue by the SEH mechanism, without any reference to preceding instructions, you can't use arbitary branches in and out of exception handler blocks. Instead, you need to use specific instructions for control flow out of handler blocks: leave, endfinally/endfault, and endfilter. Exception handler control flow try blocks You cannot branch into or out of a try block or its handler using normal control flow instructions. The only way of entering a try block is by either falling through from preceding instructions, or by branching to the first instruction in the block. Once you are inside a try block, you can only leave it by throwing an exception or using the leave <label> instruction to jump to somewhere outside the block and its handler. The leave instructions signals the CLR to execute any finally handlers around the block. Most importantly, you cannot fall out of the block, and you cannot use a ret to return from the containing method (unlike in C#); you have to use leave to branch to a ret elsewhere in the method. As a side effect, leave empties the stack. catch blocks The only way of entering a catch block is if it is run by the SEH. At the start of the block execution, the thrown exception will be the only thing on the stack. The only way of leaving a catch block is to use throw, rethrow, or leave, in a similar way to try blocks. However, one thing you can do is use a leave to branch back to an arbitary place in the handler's try block! In other words, you can do this: .try { // ... newobj instance void [mscorlib]System.Exception::.ctor() throw MidTry: // ... leave.s RestOfMethod } catch [mscorlib]System.Exception { // ... leave.s MidTry } RestOfMethod: // ... As far as I know, this mechanism is not exposed in C# or VB. finally/fault blocks The only way of entering a finally or fault block is via the SEH, either as the result of a leave instruction in the corresponding try block, or as part of handling an exception. The only way to leave a finally or fault block is to use endfinally or endfault (both compile to the same binary representation), which continues execution after the finally/fault block, or, if the block was executed as part of handling an exception, signals that the SEH can continue walking the stack. filter blocks I'll be covering filters in a separate blog posts. They're quite different to the others, and have their own special semantics. Phew! Complicated stuff, but it's important to know if you're writing or outputting exception handlers in IL. Dealing with the C# compiler is probably best saved for the next post.

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• PowerShell and SMO – be careful how you iterate

  - by Fatherjack

  I’ve yet to have a totally smooth experience with PowerShell and it was late on Friday when I crashed into this problem. I haven’t investigated if this is a generally well understood circumstance and if it is then I apologise for repeating everything. Scenario: I wanted to scan a number of server for many properties, including existing logins and to identify which accounts are bestowed with sysadmin privileges. A great task to pass to PowerShell, so with a heavy heart I started up PowerShellISE and started typing. The script doesn’t come easily to me but I follow the logic of SMO and the properties and methods available with the language so it seemed something I should be able to master. Version #1 of my script. And the results it returns when executed against my home laptop server. These results looked good and for a long time I was concerned with other parts of the script, for all intents and purposes quite happy that this was an accurate assessment of the server. Let’s just review my logic for each step of the code at the top. Lines 1 to 7 just set up our variables and write out the header message Line 8 our first loop, to go through each login on the server Line 10 an inner loop that will assess each role name that each login has been assigned Line 11 a test to see if each role has the name ‘sysadmin’ Line 13 write out the login name with a bright format as it is a sysadmin login Line 17 write out the login name with no formatting It is quite possible that here someone with more PowerShell experience than me will be shouting at their screen pointing at the error I made but to me this made total sense. Until I altered the code, I altered lines 6 and 7 of code above to be: $c = $Svr.Logins.Count write-host “There are $c Logins on the server” This changed my output to look like this: This started alarm bells ringing – there are clearly not 13 logins listed So, let’s see where things are going wrong, edit the script so it looks like this. I’ve highlighted the changes to make Running this code shows me these results Our $n variable should count up by one for each login returned and We are clearly missing some logins. I referenced this list back to Management Studio for my server and see the Logins as below, where there are clearly 13 logins. We see a Login called Annette in SSMS but not in the script results so I opened that up and looked at its properties and it’s server roles in particular. The account has only public access to the server. Inspection of the other logins that the PowerShell script misses out show they too are only members of the public role. Right now I can’t work out whether there is a good reason for this and if it should be expected behaviour or not. Please spend a few minutes to leave a comment if you have an opinion or theory for this. How to get the full list of logins. Clearly I needed to get a full list of the logins so set about reviewing my code to see if there was a better way to iterate through the roles for each login. This is the code that I came up with and I think it is doing everything that I need it to. It gives me the expected results like this: So it seems that the ListMembers() method is the trouble maker in my first versions of the code. I would have expected that ListMembers should return Logins that are only members of the public role, certainly Technet makes no reference to it being left out in it’s Login.ListMembers details. Suffice to say, it’s a lesson learned and I will approach using it with caution in future circumstances.

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• Writing Efficient SQL: Set-Based Speed Phreakery

  Phil Factor's SQL Speed Phreak challenge is an event where coders battle to produce the fastest code to solve a common reporting problem on large data sets. It isn't that easy on the spectators, since the programmers don't score extra points for commenting their code. Mercifully, Kathi is on hand to explain some of the TSQL coding secrets that go to producing blistering performance.

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• Google I/O 2011: Accelerated Android Rendering

  Google I/O 2011: Accelerated Android Rendering Romain Guy, Chet Haase Android 3.0 introduced a new hardware accelerated 2D rendering pipeline. In this talk, you will be introduced to the overall graphics architecture of the Android platform and get acquainted with the various rendering APIs at your disposal. You will learn how to choose the one that best fits your application. This talk will also deliver tips and tricks on how to use the new hardware accelerated pipeline to its full potential. From: GoogleDevelopers Views: 11086 62 ratings Time: 48:58 More in Science & Technology

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• The Cobra Programming Language

  There are suddenly a number of strong alternatives to C# or VB. F#, IronPython and Iron Ruby are now joined by an open-source alternative called Cobra. Phil is taken by surprise at a language that is so intuitive to use that it is almost like pseudocode.

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• Set-based Speed Phreakery: The FIFO Stock Inventory SQL Problem

  The SQL Speed Freak Challenge is a no-holds-barred competition to find the fastest way in SQL Server to perform a real-life database task. It is the programming equivalent of drag racing, but without the commentary box. Kathi has stepped in to explain what happened with the second challenge and why some SQL ran faster than others.

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• What Counts for A DBA - Logic

  - by drsql

  "There are 10 kinds of people in the world. Those who will always wonder why there are only two items in my list and those who will figured it out the first time they saw this very old joke."  Those readers who will give up immediately and get frustrated with me for not explaining it to them are not likely going to be great technical professionals of any sort, much less a programmer or administrator who will be constantly dealing with the common failures that make up a DBA's day.  Many of these people will stare at this like a dog staring at a traffic signal and still have no more idea of how to decipher the riddle. Without explanation they will give up, call the joke "stupid" and, feeling quite superior, walk away indignantly to their job likely flipping patties of meat-by-product. As a data professional or any programmer who has strayed  to this very data-oriented blog, you would, if you are worth your weight in air, either have recognized immediately what was going on, or felt a bit ignorant.  Your friends are chuckling over the joke, but why is it funny? Unfortunately you left your smartphone at home on the dresser because you were up late last night programming and were running late to work (again), so you will either have to fake a laugh or figure it out.  Digging through the joke, you figure out that the word "two" is the most important part, since initially the joke mentioned 10. Hmm, why did they spell out two, but not ten? Maybe 10 could be interpreted a different way?  As a DBA, this sort of logic comes into play every day, and sometimes it doesn't involve nerdy riddles or Star Wars folklore.  When you turn on your computer and get the dreaded blue screen of death, you don't immediately cry to the help desk and sit on your thumbs and whine about not being able to work. Do that and your co-workers will question your nerd-hood; I know I certainly would. You figure out the problem, and when you have it narrowed down, you call the help desk and tell them what the problem is, usually having to explain that yes, you did in fact try to reboot before calling.  Of course, sometimes humility does come in to play when you reach the end of your abilities, but the ‘end of abilities’ is not something any of us recognize readily. It is handy to have the ability to use logic to solve uncommon problems: It becomes especially useful when you are trying to solve a data-related problem such as a query performance issue, and the way that you approach things will tell your coworkers a great deal about your abilities.  The novice is likely to immediately take the approach of  trying to add more indexes or blaming the hardware. As you become more and more experienced, it becomes increasingly obvious that performance issues are a very complex topic. A query may be slow for a myriad of reasons, from concurrency issues, a poor query plan because of a parameter value (like parameter sniffing,) poor coding standards, or just because it is a complex query that is going to be slow sometimes. Some queries that you will deal with may have twenty joins and hundreds of search criteria, and it can take a lot of thought to determine what is going on.  You can usually figure out the problem to almost any query by using basic knowledge of how joins and queries work, together with the help of such things as the query plan, profiler or monitoring tools.  It is not unlikely that it can take a full day’s work to understand some queries, breaking them down into smaller queries to find a very tiny problem. Not every time will you actually find the problem, and it is part of the process to occasionally admit that the problem is random, and everything works fine now.  Sometimes, it is necessary to realize that a problem is outside of your current knowledge, and admit temporary defeat: You can, at least, narrow down the source of the problem by looking logically at all of the possible solutions. By doing this, you can satisfy your curiosity and learn more about what the actual problem was. For example, in the joke, had you never been exposed to the concept of binary numbers, there is no way you could have known that binary - 10 = decimal - 2, but you could have logically come to the conclusion that 10 must not mean ten in the context of the joke, and at that point you are that much closer to getting the joke and at least won't feel so ignorant.

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• Exploring SQL Server table metadata with SSMS and TSQL

  Phil shows how to start squeezing powerful magic from SSMS for doing a detailed exploration of the metadata of your routines and tables, in this third part to his series on exploring your database schema with SQL.

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• Network Administrators Past, Present, and Future

  Even in the short time that PCs have been signficantly networked, what it means to be a SysAdmin has changed dramatically. From the first LAN parties to the lumbering infrastructures of today, the role of SysAdmin has evolved and adapted to the shifting needs of users and corporations alike. Brien Posey has been on the front line of it all, and considers the future of this thus-far essential IT role.

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• Feature Usage Reporting in Early Access Programs

  After doing Web development, you can get very used to the luxury of having basic information about your users' machines and browsers. With their permission, you can also get the same information from an application, and can even get more targeted anonymous information that will tell you how the features are used. Kevin explains how this can be used with early access builds to improve the reliability and usability of applications.

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• Aspect-oriented Programming and Code Contracts in ASP.NET MVC

  There are some aspects to application programming, such as logging, tracing, profiling, authentication and authorization that cut across the business objects. These are difficult to deal with in an object-oriented paradigm without resorting to code-injection, code-duplication or interdependencies. In ASP.NET MVC, you can use attributes in the form of action filters to provide a neater way of implementing these cross-curring concerns.

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• A TDD Journey: 1-Trials and Tribulations

  Test-Driven Development (TDD) has a misleading name, because the objective is to design and specify that the system you are developing behaves in the ways that the customer expects, and to prove that it does so for the lifetime of the system. It isn't an intuitive way of coding but by automating the specifications of a system, we end up with tests and documentation as a by-product. Michael Sorens starts an introduction to TDD that is more of a journey in six parts:

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