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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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• SQL Saturday and Exploring Data Privacy

  - by Johnm

  I have been highly impressed with the growth of the SQL Saturday phenomenon. It seems that an announcement for a new wonderful event finds its way to my inbox on a daily basis. I have had the opportunity to attend the first of the SQL Saturday's for Tampa, Chicago, Louisville and recently my home town of Indianapolis. It is my hope that there will be many more in my future. This past weekend I had the honor of being selected to speak amid a great line up of speakers at SQL Saturday #82 in Indianapolis. My session topic/title was "Exploring Data Privacy". Below is a brief synopsis of my session: Data Privacy in a Nutshell        - Definition of data privacy        - Examples of personally identifiable data        - Examples of Sensitive data Laws and Stuff        - Various examples of laws, regulations and policies that influence the definition of data privacy        - General rules of thumb that encompasses most laws Your Data Footprint        - Who has personal information about you?        - What are you exchanging data privacy for?        - The amazing resilience of data        - The cost of data loss Weapons of Mass Protection       - Data classification       - Extended properties       - Database Object Schemas       - An extraordinarily brief introduction of encryption       - The amazing data professional  <-the most important point of the entire session! The subject of data privacy is one that is quickly making its way to the forefront of the mind of many data professionals. Somewhere out there someone is storing personally identifiable and other sensitive data about you. In some cases it is kept reasonably secure. In other cases it is kept in total exposure without the consideration of its potential of damage to you. Who has access to it and how is it being used? Are we being unnecessarily required to supply sensitive data in exchange for products and services? These are just a few questions on everyone's mind. As data loss events of grand scale hit the headlines in a more frequent succession, the level of frustration and urgency for a solution increases. I assembled this session with the intent to raise awareness of sensitive data and remind us all that we, data professionals, are the ones who have the greatest impact and influence on how sensitive data is regarded and protected. Mahatma Gandhi once said "Be the change you want to see in the world." This is guidance that I keep near to my heart as I approached this topic of data privacy.

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• Embracing Imperfection

  - by Johnm

  The pursuit of perfection is a road on which we often find ourselves traveling. It is an unpaved road filed with pot-holes and ruts that often destroy our stride. The shoulders of this road are lined with the bones and rotting carcasses of well planned projects, solutions and dreams of others who have dared the journey. Often the choice to engage in this travel is a compulsive one. We can't help but to pack our bags and make the trip. We justify it by equating it to the delivery of a quality product or service. We use our past travels as validation of our worthiness and value. Our shared experience, as tortured pilgrims of perfection, reveals that each odyssey that bewitched us resulted in a stark reminder of the very weaknesses and fears that we were attempting to mollify. The voice of the critic that berated us for the lack of craftsmanship was our own. Although, at the end of the journey our own critical voice was joined by the gnashing of teeth of those who could not reap the fruit of your labor due to its lack of timely delivery. There is another road in which to travel. It is the pursuit of embracing imperfection. The cost of traveling this route is your contribution to its eternal construction. Each segment is designed uniquely. At times it has the appearance of a patchwork quilt; while other times it is well organized and highly measured. In all cases, its construction has continually advanced and been utilized as each segment was delivered by its architect. Those who choose to select this spindle of these crossroads crack open the shells of their fears to reveal the vapor that is within. They construct their houses upon these shells. Through their hunger for mastery they wring every drop of nectar from failure and discard its husks to the ditches of this road. Through their efforts the thoroughfare begins to develop a personality of its own, a beautifully human one, rich with the strengths and weaknesses of all of its contributors. Like many of us, the pursuit of perfection has not served me well. In fact, I would say that it has been more damaging than it has been helpful. While the perfectionist in me occasionally makes its presence known, I consider myself a "recovering perfectionist". It is evident to me that there is immense beauty found in imperfection. I choose to embrace it. It is grounding. It is constructive. It is honest.

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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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• News From EAP Testing

  - by Fatherjack

  There is a phrase that goes something like “Watch the pennies and the pounds/dollars will take care of themselves”, meaning that if you pay attention to the small things then the larger things are going to fare well too. I am lucky enough to be a Friend of Red Gate and once in a while I get told about new features in their tools and have a test copy of the software to trial. I got one of those emails a week or so ago and I have been exploring the SQL Prompt 6 EAP since then. One really useful feature of long standing in SQL Prompt is the idea of a code snippet that is automatically pasted into the SSMS editor when you type a few key letters. For example I can type “ssf” and then press the tab key and the text is expanded to SELECT * FROM. There are lots of these combinations and it is possible to create your own really easily. To create your own you use the Snippet Manager interface to define the shortcut letters and the code that you want to have put in their place. Let’s look at an example. Say I am writing a blog about something and want to have the demo code create a temporary table. It might looks like this; The first time you run the code everything is fine, a lovely set of dates fill the results grid but run it a second time and this happens.   Yep, we didn’t destroy the temporary table so the CREATE statement fails when it finds the table already exists. No matter, I have a snippet created that takes care of this.   Nothing too technical here but you will see that in the Code section there is $CURSOR$, this isn’t a TSQL keyword but a marker for SQL Prompt to place the cursor in that position when the Code is pasted into the SSMS Editor. I just place my cursor above the CREATE statement and type “ifobj” – the shortcut for my code to DROP the temporary table – which has been defined in the Snippet Manager as below. This means I am right-away ready to type the name of the offending table. Pretty neat and it’s been very useful in saving me lots of time over many years.   The news for SQL Prompt 6 is that Red Gate have added a new Snippet Command of $PASTE$. Let’s alter our snippet to the following and try it out   Once again, we will type type “ifobj” in the SSMS Editor but first of all, highlight the name of the table #TestTable and copy it to your clipboard. Now type “ifobj” and press Tab… Wherever the string $PASTE$ is placed in the snippet, the contents of your clipboard are merged into the pasted TSQL. This means I don’t need to type the table name into the code snippet, it’s already there and I am seeing a fully functioning piece of TSQL ready to run. This means it is it even easier to write TSQL quickly and consistently. Attention to detail like this from Red Gate means that their developer tools stay on track to keep winning awards year after year and help take the hard work out of writing neat, accurate TSQL. If you want to try out SQL Prompt all the details are at http://www.red-gate.com/products/sql-development/sql-prompt/.

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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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• 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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• Learn Many Languages

  - by Jeff Foster

  My previous blog, Deliberate Practice, discussed the need for developers to “sharpen their pencil” continually, by setting aside time to learn how to tackle problems in different ways. However, the Sapir-Whorf hypothesis, a contested and somewhat-controversial concept from language theory, seems to hold reasonably true when applied to programming languages. It states that: “The structure of a language affects the ways in which its speakers conceptualize their world.” If you’re constrained by a single programming language, the one that dominates your day job, then you only have the tools of that language at your disposal to think about and solve a problem. For example, if you’ve only ever worked with Java, you would never think of passing a function to a method. A good developer needs to learn many languages. You may never deploy them in production, you may never ship code with them, but by learning a new language, you’ll have new ideas that will transfer to your current “day-job” language. With the abundant choices in programming languages, how does one choose which to learn? Alan Perlis sums it up best. “A language that doesn‘t affect the way you think about programming is not worth knowing“ With that in mind, here’s a selection of languages that I think are worth learning and that have certainly changed the way I think about tackling programming problems. Clojure Clojure is a Lisp-based language running on the Java Virtual Machine. The unique property of Lisp is homoiconicity, which means that a Lisp program is a Lisp data structure, and vice-versa. Since we can treat Lisp programs as Lisp data structures, we can write our code generation in the same style as our code. This gives Lisp a uniquely powerful macro system, and makes it ideal for implementing domain specific languages. Clojure also makes software transactional memory a first-class citizen, giving us a new approach to concurrency and dealing with the problems of shared state. Haskell Haskell is a strongly typed, functional programming language. Haskell’s type system is far richer than C# or Java, and allows us to push more of our application logic to compile-time safety. If it compiles, it usually works! Haskell is also a lazy language – we can work with infinite data structures. For example, in a board game we can generate the complete game tree, even if there are billions of possibilities, because the values are computed only as they are needed. Erlang Erlang is a functional language with a strong emphasis on reliability. Erlang’s approach to concurrency uses message passing instead of shared variables, with strong support from both the language itself and the virtual machine. Processes are extremely lightweight, and garbage collection doesn’t require all processes to be paused at the same time, making it feasible for a single program to use millions of processes at once, all without the mental overhead of managing shared state. The Benefits of Multilingualism By studying new languages, even if you won’t ever get the chance to use them in production, you will find yourself open to new ideas and ways of coding in your main language. For example, studying Haskell has taught me that you can do so much more with types and has changed my programming style in C#. A type represents some state a program should have, and a type should not be able to represent an invalid state. I often find myself refactoring methods like this… void SomeMethod(bool doThis, bool doThat) { if (!(doThis ^ doThat)) throw new ArgumentException(“At least one arg should be true”); if (doThis) DoThis(); if (doThat) DoThat(); } …into a type-based solution, like this: enum Action { DoThis, DoThat, Both }; void SomeMethod(Action action) { if (action == Action.DoThis || action == Action.Both) DoThis(); if (action == Action.DoThat || action == Action.Both) DoThat(); } At this point, I’ve removed the runtime exception in favor of a compile-time check. This is a trivial example, but is just one of many ideas that I’ve taken from one language and implemented in another.

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• Antenna Aligner part 2: Finding the right direction

  - by Chris George

  Last time I managed to get "my first app(tm)" built, published and running on my iPhone. This was really cool, a piece of my code running on my very own device. Ok, so I'm easily pleased! The next challenge was actually trying to determine what it was I wanted this app to do, and how to do it. Reverting back to good old paper and pen, I started sketching out designs for the app. I knew I wanted it to get a list of transmitters, then clicking on a transmitter would display a compass type view, with an arrow pointing the right way. I figured there would not be much point in continuing until I know I could do the graphical part of the project, i.e. the rotating compass, so armed with that reasoning (plus the fact I just wanted to get on and code!), I once again dived into visual studio. Using my friend (google) I found some example code for getting the compass data from the phone using the PhoneGap framework. // onSuccess: Get the current heading // function onSuccess(heading) {    alert('Heading: ' + heading); } navigator.compass.getCurrentHeading(onSuccess, onError); Using the ripple mobile emulator this showed that it was successfully getting the compass heading. But it didn't work when uploaded to my phone. It turns out that the examples I had been looking at were for PhoneGap 1.0, and Nomad uses PhoneGap 1.4.1. In 1.4.1, getCurrentHeading provides a compass object to onSuccess, not just a numeric value, so the code now looks like // onSuccess: Get the current magnetic heading // function onSuccess(heading) {    alert('Heading: ' + heading.magneticHeading); }; navigator.compass.getCurrentHeading(onSuccess, onError); So the lesson learnt from this... read the documentation for the version you are actually using! This does, however, lead to compatibility problems with ripple as it only supports 1.0 which is a real pain. I hope that the ripple system is updated sometime soon.

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• Data Model Dissonance

  - by Tony Davis

  So often at the start of the development of database applications, there is a premature rush to the keyboard. Unless, before we get there, we’ve mapped out and agreed the three data models, the Conceptual, the Logical and the Physical, then the inevitable refactoring will dog development work. It pays to get the data models sorted out up-front, however ‘agile’ you profess to be. The hardest model to get right, the most misunderstood, and the one most neglected by the various modeling tools, is the conceptual data model, and yet it is critical to all that follows. The conceptual model distils what the business understands about itself, and the way it operates. It represents the business rules that govern the required data, its constraints and its properties. The conceptual model uses the terminology of the business and defines the most important entities and their inter-relationships. Don’t assume that the organization’s understanding of these business rules is consistent or accurate. Too often, one department has a subtly different understanding of what an entity means and what it stores, from another. If our conceptual data model fails to resolve such inconsistencies, it will reduce data quality. If we don’t collect and measure the raw data in a consistent way across the whole business, how can we hope to perform meaningful aggregation? The conceptual data model has more to do with business than technology, and as such, developers often regard it as a worthy but rather arcane ceremony like saluting the flag or only eating fish on Friday. However, the consequences of getting it wrong have a direct and painful impact on many aspects of the project. If you adopt a silo-based (a.k.a. Domain driven) approach to development), you are still likely to suffer by starting with an incomplete knowledge of the domain. Even when you have surmounted these problems so that the data entities accurately reflect the business domain that the application represents, there are likely to be dire consequences from abandoning the goal of a shared, enterprise-wide understanding of the business. In reading this, you may recall experiences of the consequence of getting the conceptual data model wrong. I believe that Phil Factor, for example, witnessed the abandonment of a multi-million dollar banking project due to an inadequate conceptual analysis of how the bank defined a ‘customer’. We’d love to hear of any examples you know of development projects poleaxed by errors in the conceptual data model. Cheers, Tony

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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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• 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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• 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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• 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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• 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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• 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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• 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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• 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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• Separating text strings into a table of individual words in SQL via XML.

  - by Phil Factor

  p.MsoNormal {margin-top:0cm; margin-right:0cm; margin-bottom:10.0pt; margin-left:0cm; line-height:115%; font-size:11.0pt; font-family:"Calibri","sans-serif"; } Nearly nine years ago, Mike Rorke of the SQL Server 2005 XML team blogged ‘Querying Over Constructed XML Using Sub-queries’. I remember reading it at the time without being able to think of a use for what he was demonstrating. Just a few weeks ago, whilst preparing my article on searching strings, I got out my trusty function for splitting strings into words and something reminded me of the old blog. I’d been trying to think of a way of using XML to split strings reliably into words. The routine I devised turned out to be slightly slower than the iterative word chop I’ve always used in the past, so I didn’t publish it. It was then I suddenly remembered the old routine. Here is my version of it. I’ve unwrapped it from its obvious home in a function or procedure just so it is easy to appreciate. What it does is to chop a text string into individual words using XQuery and the good old nodes() method. I’ve benchmarked it and it is quicker than any of the SQL ways of doing it that I know about. Obviously, you can’t use the trick I described here to do it, because it is awkward to use REPLACE() on 1…n characters of whitespace. I’ll carry on using my iterative function since it is able to tell me the location of each word as a character-offset from the start, and also because this method leaves punctuation in (removing it takes time!). However, I can see other uses for this in passing lists as input or output parameters, or as return values.   if exists (Select * from sys.xml_schema_collections where name like 'WordList')   drop XML SCHEMA COLLECTION WordList go create xml schema collection WordList as ' <xs:schema xmlns:xs="http://www.w3.org/2001/XMLSchema"> <xs:element name="words">        <xs:simpleType>               <xs:list itemType="xs:string" />        </xs:simpleType> </xs:element> </xs:schema>'   go   DECLARE @string VARCHAR(MAX) –we'll get some sample data from the great Ogden Nash Select @String='This is a song to celebrate banks, Because they are full of money and you go into them and all you hear is clinks and clanks, Or maybe a sound like the wind in the trees on the hills, Which is the rustling of the thousand dollar bills. Most bankers dwell in marble halls, Which they get to dwell in because they encourage deposits and discourage withdrawals, And particularly because they all observe one rule which woe betides the banker who fails to heed it, Which is you must never lend any money to anybody unless they don''t need it. I know you, you cautious conservative banks! If people are worried about their rent it is your duty to deny them the loan of one nickel, yes, even one copper engraving of the martyred son of the late Nancy Hanks; Yes, if they request fifty dollars to pay for a baby you must look at them like Tarzan looking at an uppity ape in the jungle, And tell them what do they think a bank is, anyhow, they had better go get the money from their wife''s aunt or ungle. But suppose people come in and they have a million and they want another million to pile on top of it, Why, you brim with the milk of human kindness and you urge them to accept every drop of it, And you lend them the million so then they have two million and this gives them the idea that they would be better off with four, So they already have two million as security so you have no hesitation in lending them two more, And all the vice-presidents nod their heads in rhythm, And the only question asked is do the borrowers want the money sent or do they want to take it withm. Because I think they deserve our appreciation and thanks, the jackasses who go around saying that health and happi- ness are everything and money isn''t essential, Because as soon as they have to borrow some unimportant money to maintain their health and happiness they starve to death so they can''t go around any more sneering at good old money, which is nothing short of providential. '   –we now turn it into XML declare @xml_data xml(WordList)  set @xml_data='<words>'+ replace(@string,'&', '&amp;')+'</words>'    select T.ref.value('.', 'nvarchar(100)')  from (Select @xml_data.query('                      for $i in data(/words) return                      element li { $i }               '))  A(list) cross apply A.List.nodes('/li') T(ref)     …which gives (truncated, of course)…

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• Documentation and Test Assertions in Databases

  - by Phil Factor

  When I first worked with Sybase/SQL Server, we thought our databases were impressively large but they were, by today’s standards, pathetically small. We had one script to build the whole database. Every script I ever read was richly annotated; it was more like reading a document. Every table had a comment block, and every line would be commented too. At the end of each routine (e.g. procedure) was a quick integration test, or series of test assertions, to check that nothing in the build was broken. We simply ran the build script, stored in the Version Control System, and it pulled everything together in a logical sequence that not only created the database objects but pulled in the static data. This worked fine at the scale we had. The advantage was that one could, by reading the source code, reach a rapid understanding of how the database worked and how one could interface with it. The problem was that it was a system that meant that only one developer at the time could work on the database. It was very easy for a developer to execute accidentally the entire build script rather than the selected section on which he or she was working, thereby cleansing the database of everyone else’s work-in-progress and data. It soon became the fashion to work at the object level, so that programmers could check out individual views, tables, functions, constraints and rules and work on them independently. It was then that I noticed the trend to generate the source for the VCS retrospectively from the development server. Tables were worst affected. You can, of course, add or delete a table’s columns and constraints retrospectively, which means that the existing source no longer represents the current object. If, after your development work, you generate the source from the live table, then you get no block or line comments, and the source script is sprinkled with silly square-brackets and other confetti, thereby rendering it visually indigestible. Routines, too, were affected. In our system, every routine had a directly attached string of unit-tests. A retro-generated routine has no unit-tests or test assertions. Yes, one can still commit our test code to the VCS but it’s a separate module and teams end up running the whole suite of tests for every individual change, rather than just the tests for that routine, which doesn’t scale for database testing. With Extended properties, one can get the best of both worlds, and even use them to put blame, praise or annotations into your VCS. It requires a lot of work, though, particularly the script to generate the table. The problem is that there are no conventional names beyond ‘MS_Description’ for the special use of extended properties. This makes it difficult to do splendid things such ensuring the integrity of the build by running a suite of tests that are actually stored in extended properties within the database and therefore the VCS. We have lost the readability of database source code over the years, and largely jettisoned the use of test assertions as part of the database build. This is not unexpected in view of the increasing complexity of the structure of databases and number of programmers working on them. There must, surely, be a way of getting them back, but I sometimes wonder if I’m one of very few who miss them.

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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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• 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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• 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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• 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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