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• Extending QuickBooks Reporting with the QuickBooks ADO.NET Data Provider

  - by dataintegration

  The ADO.NET Provider for QuickBooks comes with several reports you may request from QuickBooks by default. However, there are many more that are not readily available. The ADO.NET Provider for QuickBooks makes it easy for you to create new reports and customize existing ones. In this article, we will illustrate how to create your own report and retrieve it from the Server Explorer in Visual Studio. For this example we will show how to create an Item Profitability Report. Creating the report script file Step 1: Download the sample reports available here. Extract them to a folder of your choice. Step 2: Make a copy of the ReportGeneralSummary.rsd file and rename it to ItemProfitability.rsd. Then open the file in any text editor. Step 3: Open the installation directory of the ADO.NET Provider for QuickBooks. Under the \db\ folder, locate the ReportJob.rsb file. Open this file in another text editor. Note: Although we are using ReportJob.rsb for this example, other reports may be contained in other Report*.rsb files. We recommend consulting the included help file and first locating the Report stored procedure and ReportType you are looking for. Otherwise, you may open each Report*.rsb file and look under the "reporttype" input for the report you are attempting to create. Step 4: First, let's rename the title of ItemProfitability.rsd. Near the top of the file you will see a title and description. Change the title to match the name of the file. Change the description to anything you like. For example: <rsb:info title="ItemProfitability" description="Executes my custom report."> Just below the Title, there are a number of columns. The Id represents the row number. The RowType represents the type of data returned by QuickBooks. The ColumnValue* columns represent all of the column data returned by QuickBooks. In some instances, we may need to add additional ColumnValue columns. Step 5: To add additional ColumnValue columns, simply copy the last column, paste it directly below, and continue increasing the numerical value at end of the attribute name. For example: <attr name="ColumnValue9" xs:type="string" readonly="true" required="false" desc="Represents a column of data."/> <attr name="ColumnValue10" xs:type="string" readonly="true" required="false" desc="Represents a column of data."/> <attr name="ColumnValue11" xs:type="string" readonly="true" required="false" desc="Represents a column of data."/> <attr name="ColumnValue12" xs:type="string" readonly="true" required="false" desc="Represents a column of data."/> ... Caution: Do not rename the ColumnValue* definitions themselves. They are generalized so that we can understand each type of report returned by QuickBooks. Renaming them to something other than ColumnValue* will cause your columns to return with null values. Step 6: Now let's update the available inputs for the table. From the ReportJob.rsb file, copy all of the input elements into ItemProfitability under the "Psuedo-Column definitions" comment. You will be replacing the existing input elements in ItemProfitability with inputs from ReportJob. When you are done, it should look like this: <!-- Psuedo-Column definitions --> <input name="reporttype" description="The type of the report." value="ITEMESTIMATESVSACTUALS,ITEMPROFITABILITY,JOBESTIMATESVSACTUALSDETAIL,JOBESTIMATESVSACTUALSSUMMARY,JOBPROFITABILITYDETAIL,JOBPROFITABILITYSUMMARY," default="ITEMESTIMATESVSACTUALS" /> <input name="reportperiod" description="Report date range in the format (fromdate:todate), and either value may be omitted for an open ended range (e.g. 2009-12-25:). Supported date format: yyyy-MM-dd." /> <input name="reportdaterangemacro" description="Use a predefined date range." value="ALL,TODAY,THISWEEK,THISWEEKTODATE,THISMONTH,THISMONTHTODATE,THISQUARTER,THISQUARTERTODATE,THISYEAR,THISYEARTODATE,YESTERDAY,LASTWEEK,LASTWEEKTODATE,LASTMONTH,LASTMONTHTODATE,LASTQUARTER,LASTQUARTERTODATE,LASTYEAR,LASTYEARTODATE,NEXTWEEK,NEXTFOURWEEKS,NEXTMONTH,NEXTQUARTER,NEXTYEAR," default="ALL" /> ... Step 7: Now let's update the operationname attribute. This needs to match the same operationname used by ReportJob. After you have copied the correct value from ReportJob.rsb, the operationname in ItemProfitability should look like so: <rsb:set attr="operationname" value="qbReportJob"/> Step 8: There is one more thing we can do to make this a true Item Profitability report. We can remove the reporttype input and hardcode the value. To do this, copy and paste the rsb:set used for operationname. Then rename the attr and value to match the name and value you want to use. For example: <rsb:set attr="operationname" value="qbReportJob"/> <rsb:set attr="reporttype" value="ITEMPROFITABILITY"/> After this you can remove the input for reporttype. Now that you have your own report file, we can move on to displaying the report in the Visual Studio server explorer. Accessing the report through the Data Provider Step 1: Open Visual Studio. In the Server Explorer, configure a new connection with the QuickBooks Data Provider. Step 2: For the Location connection string property, enter the directory where the new report has been saved to. Step 3: The new report should appear as a new view in the Server Explorer. Let's retrieve data from it. Step 4: You can specify any inputs in the WHERE clause. New Report Example Script To help you get started using this new QuickBooks Data Provider report, you will need to download the QuickBooks ADO.NET Data Provider and the fully functional sample script.

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• Working with Reporting Services Filters–Part 1

  - by smisner

  There are two ways that you can filter data in Reporting Services. The first way, which usually provides a faster performance, is to use query parameters to apply a filter using the WHERE clause in a SQL statement. In that case, the structure of the filter depends upon the syntax recognized by the source database. Another way to filter data in Reporting Services is to apply a filter to a dataset, data region, or a group. Using this latter method, you can even apply multiple filters. However, the use of filter operators or the setup of multiple filters is not always obvious, so in this series of posts, I'll provide some more information about the configuration of filters. First, why not use query parameters exclusively for filtering? Here are a few reasons: You might want to apply a filter to part of the report, but not all of the report. Your dataset might retrieve data from a stored procedure, and doesn't allow you to pass a query parameter for filtering purposes. Your report might be set up as a snapshot on the report server and, in that case, cannot be dynamically filtered based on a query parameter. Next, let's look at how to set up a report filter in general. The process is the same whether you are applying the filter to a dataset, data region, or a group. When you go to the Filters page in the Properties dialog box for whichever of these items you selected (dataset, data region, group), you click the Add button to create a new filter. The interface looks like this: The Expression field is usually a field in the dataset, so to make it easier for you to make a selection,the drop-down list displays all of the current dataset fields. But notice the expression button to the right, which means that you can set up any type of expression-not just a dataset field. To the right of the expression button, you'll find a data type drop-down list. It's important to specify the correct data type for the field or expression you're using. Now for the operators. Here's a list of the options that you have: This Operator Performs This Action =, <>, >, >=, <, <=, Like Compares expression to value Top N, Bottom N Compares expression to Top (Bottom) set of N values (N = integer) Top %, Bottom % Compares expression to Top (Bottom) N percent of values (N = integer or float) Between Determines whether expression is between two values, inclusive In Determines whether expression is found in list of values Last, the Value is what you're comparing to the expression using the operator. The construction of a filter using some operators (=, <>, >, etc.) is fairly simple. If my dataset (for AdventureWorks data) has a Category field, and I have a parameter that prompts the user for a single category, I can set up a filter like this: Expression Data Type Operator Value [Category] Text = [@Category] But if I set the parameter to accept multiple values, I need to change the operator from = to In, just as I would have to do if I were using a query parameter. The parameter expression, [@Category], which translates to =Parameters!Category.Value, doesn’t need to change because it represents an array as soon as I change the parameter to allow multiple values. The “In” operator requires an array. With that in mind, let’s consider a variation on Value. Let’s say that I have a parameter that prompts the user for a particular year – and for simplicity’s sake, this parameter only allows a single value, and I have an expression that evaluates the previous year based on the user’s selection. Then I want to use these two values in two separate filters with an OR condition. That is, I want to filter either by the year selected OR by the year that was computed. If I create two filters, one for each year (as shown below), then the report will only display results if BOTH filter conditions are met – which would never be true. Expression Data Type Operator Value [CalendarYear] Integer = [@Year] [CalendarYear] Integer = =Parameters!Year.Value-1 To handle this scenario, we need to create a single filter that uses the “In” operator, and then set up the Value expression as an array. To create an array, we use the Split function after creating a string that concatenates the two values (highlighted in yellow) as shown below. Expression Data Type Operator Value =Cstr(Fields!CalendarYear.Value) Text In =Split( CStr(Parameters!Year.Value) + ”,” + CStr(Parameters!Year.Value-1) , “,”) Note that in this case, I had to apply a string conversion on the year integer so that I could concatenate the parameter selection with the calculated year. Pay attention to the second argument of the Split function—you must use a comma delimiter for the result to work correctly with the In operator. I also had to change the Expression value from [CalendarYear] (or =Fields!CalendarYear.Value) so that the expression would return a string that I could compare with the values in the string array. More fun with filter expressions in future posts!

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• OS Analytics with Oracle Enterprise Manager (by Eran Steiner)

  - by Zeynep Koch

  Oracle Enterprise Manager Ops Center provides a feature called "OS Analytics". This feature allows you to get a better understanding of how the Operating System is being utilized. You can research the historical usage as well as real time data. This post will show how you can benefit from OS Analytics and how it works behind the scenes. The recording of our call to discuss this blog is available here: https://oracleconferencing.webex.com/oracleconferencing/ldr.php?AT=pb&SP=MC&rID=71517797&rKey=4ec9d4a3508564b3Download the presentation here See also: Blog about Alert Monitoring and Problem Notification Blog about Using Operational Profiles to Install Packages and other content Here is quick summary of what you can do with OS Analytics in Ops Center: View historical charts and real time value of CPU, memory, network and disk utilization Find the top CPU and Memory processes in real time or at a certain historical day Determine proper monitoring thresholds based on historical data Drill down into a process details Where to start To start with OS Analytics, choose the OS asset in the tree and click the Analytics tab. You can see the CPU utilization, Memory utilization and Network utilization, along with the current real time top 5 processes in each category (click the image to see a larger version):  In the above screen, you can click each of the top 5 processes to see a more detailed view of that process. Here is an example of one of the processes: One of the cool things is that you can see the process tree for this process along with some port binding and open file descriptors. Next, click the "Processes" tab to see real time information of all the processes on the machine: An interesting column is the "Target" column. If you configured Ops Center to work with Enterprise Manager Cloud Control, then the two products will talk to each other and Ops Center will display the correlated target from Cloud Control in this table. If you are only using Ops Center - this column will remain empty. The "Threshold" tab is particularly helpful - you can view historical trends of different monitored values and based on the graph - determine what the monitoring values should be: You can ask Ops Center to suggest monitoring levels based on the historical values or you can set your own. The different colors in the graph represent the current set levels: Red for critical, Yellow for warning and Blue for Information, allowing you to quickly see how they're positioned against real data. It's important to note that when looking at longer periods, Ops Center smooths out the data and uses averages. So when looking at values such as CPU Usage, try shorter time frames which are more detailed, such as one hour or one day. Applying new monitoring values When first applying new values to monitored attributes - a popup will come up asking if it's OK to get you out of the current Monitoring Policy. This is OK if you want to either have custom monitoring for a specific machine, or if you want to use this current machine as a "Gold image" and extract a Monitoring Policy from it. You can later apply the new Monitoring Policy to other machines and also set it as a default Monitoring Profile. Once you're done with applying the different monitoring values, you can review and change them in the "Monitoring" tab. You can also click the "Extract a Monitoring Policy" in the actions pane on the right to save all the new values to a new Monitoring Policy, which can then be found under "Plan Management" -> "Monitoring Policies". Visiting the past Under the "History" tab you can "go back in time". This is very helpful when you know that a machine was busy a few hours ago (perhaps in the middle of the night?), but you were not around to take a look at it in real time. Here's a view into yesterday's data on one of the machines: You can see an interesting CPU spike happening at around 3:30 am along with some memory use. In the bottom table you can see the top 5 CPU and Memory consumers at the requested time. Very quickly you can see that this spike is related to the Solaris 11 IPS repository synchronization process using the "pkgrecv" command. The "time machine" doesn't stop here - you can also view historical data to determine which of the zones was the busiest at a given time: Under the hood The data collected is stored on each of the agents under /var/opt/sun/xvm/analytics/historical/ An "os.zip" file exists for the main OS. Inside you will find many small text files, named after the Epoch time stamp in which they were taken If you have any zones, there will be a file called "guests.zip" containing the same small files for all the zones, as well as a folder with the name of the zone along with "os.zip" in it If this is the Enterprise Controller or the Proxy Controller, you will have folders called "proxy" and "sat" in which you will find the "os.zip" for that controller The actual script collecting the data can be viewed for debugging purposes as well: On Linux, the location is: /opt/sun/xvmoc/private/os_analytics/collect If you would like to redirect all the standard error into a file for debugging, touch the following file and the output will go into it: # touch /tmp/.collect.stderr   The temporary data is collected under /var/opt/sun/xvm/analytics/.collectdb until it is zipped. If you would like to review the properties for the Analytics, you can view those per each agent in /opt/sun/n1gc/lib/XVM.properties. Find the section "Analytics configurable properties for OS and VSC" to view the Analytics specific values. I hope you find this helpful! Please post questions in the comments below. Eran Steiner

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• Scripting out Contained Database Users

  - by Argenis

    Today’s blog post comes from a Twitter thread on which @SQLSoldier, @sqlstudent144 and @SQLTaiob were discussing the internals of contained database users. Unless you have been living under a rock, you’ve heard about the concept of contained users within a SQL Server database (hit the link if you have not). In this article I’d like to show you that you can, indeed, script out contained database users and recreate them on another database, as either contained users or as good old fashioned logins/server principals as well. Why would this be useful? Well, because you would not need to know the password for the user in order to recreate it on another instance. I know there is a limited number of scenarios where this would be necessary, but nonetheless I figured I’d throw this blog post to show how it can be done. A more obscure use case: with the password hash (which I’m about to show you how to obtain) you could also crack the password using a utility like hashcat, as highlighted on this SQLServerCentral article. The Investigation SQL Server uses System Base Tables to save the password hashes of logins and contained database users. For logins it uses sys.sysxlgns, whereas for contained database users it leverages sys.sysowners. I’ll show you what I do to figure this stuff out: I create a login/contained user, and then I immediately browse the transaction log with, for example, fn_dblog. It’s pretty obvious that only two base tables touched by the operation are sys.sysxlgns, and also sys.sysprivs – the latter is used to track permissions. If I connect to the DAC on my instance, I can query for the password hash of this login I’ve just created. A few interesting things about this hash. This was taken on my laptop, and I happen to be running SQL Server 2014 RTM CU2, which is the latest public build of SQL Server 2014 as of time of writing. In 2008 R2 and prior versions (back to 2000), the password hashes would start with 0x0100. The reason why this changed is because starting with SQL Server 2012 password hashes are kept using a SHA512 algorithm, as opposed to SHA-1 (used since 2000) or Snefru (used in 6.5 and 7.0). SHA-1 is nowadays deemed unsafe and is very easy to crack. For regular SQL logins, this information is exposed through the sys.sql_logins catalog view, so there is really no need to connect to the DAC to grab an SID/password hash pair. For contained database users, there is (currently) no method of obtaining SID or password hashes without connecting to the DAC. If we create a contained database user, this is what we get from the transaction log: Note that the System Base Table used in this case is sys.sysowners. sys.sysprivs is used as well, and again this is to track permissions. To query sys.sysowners, you would have to connect to the DAC, as I mentioned previously. And this is what you would get: There are other ways to figure out what SQL Server uses under the hood to store contained database user password hashes, like looking at the execution plan for a query to sys.dm_db_uncontained_entities (Thanks, Robert Davis!) SIDs, Logins, Contained Users, and Why You Care…Or Not. One of the reasons behind the existence of Contained Users was the concept of portability of databases: it is really painful to maintain Server Principals (Logins) synced across most shared-nothing SQL Server HA/DR technologies (Mirroring, Availability Groups, and Log Shipping). Often times you would need the Security Identifier (SID) of these logins to match across instances, and that meant that you had to fetch whatever SID was assigned to the login on the principal instance so you could recreate it on a secondary. With contained users you normally wouldn’t care about SIDs, as the users are always available (and synced, as long as synchronization takes place) across instances. Now you might be presented some particular requirement that might specify that SIDs synced between logins on certain instances and contained database users on other databases. How would you go about creating a contained database user with a specific SID? The answer is that you can’t do it directly, but there’s a little trick that would allow you to do it. Create a login with a specified SID and password hash, create a user for that server principal on a partially contained database, then migrate that user to contained using the system stored procedure sp_user_migrate_to_contained, then drop the login. CREATE LOGIN <login_name> WITH PASSWORD = <password_hash> HASHED, SID = <sid> ; GO USE <partially_contained_db>; GO CREATE USER <user_name> FROM LOGIN <login_name>; GO EXEC sp_migrate_user_to_contained @username = <user_name>, @rename = N’keep_name’, @disablelogin = N‘disable_login’; GO DROP LOGIN <login_name>; GO Here’s how this skeleton would look like in action: And now I have a contained user with a specified SID and password hash. In my example above, I renamed the user after migrated it to contained so that it is, hopefully, easier to understand. Enjoy!

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• Big Data – Buzz Words: What is Hadoop – Day 6 of 21

  - by Pinal Dave

  In yesterday’s blog post we learned what is NoSQL. In this article we will take a quick look at one of the four most important buzz words which goes around Big Data – Hadoop. What is Hadoop? Apache Hadoop is an open-source, free and Java based software framework offers a powerful distributed platform to store and manage Big Data. It is licensed under an Apache V2 license. It runs applications on large clusters of commodity hardware and it processes thousands of terabytes of data on thousands of the nodes. Hadoop is inspired from Google’s MapReduce and Google File System (GFS) papers. The major advantage of Hadoop framework is that it provides reliability and high availability. What are the core components of Hadoop? There are two major components of the Hadoop framework and both fo them does two of the important task for it. Hadoop MapReduce is the method to split a larger data problem into smaller chunk and distribute it to many different commodity servers. Each server have their own set of resources and they have processed them locally. Once the commodity server has processed the data they send it back collectively to main server. This is effectively a process where we process large data effectively and efficiently. (We will understand this in tomorrow’s blog post). Hadoop Distributed File System (HDFS) is a virtual file system. There is a big difference between any other file system and Hadoop. When we move a file on HDFS, it is automatically split into many small pieces. These small chunks of the file are replicated and stored on other servers (usually 3) for the fault tolerance or high availability. (We will understand this in the day after tomorrow’s blog post). Besides above two core components Hadoop project also contains following modules as well. Hadoop Common: Common utilities for the other Hadoop modules Hadoop Yarn: A framework for job scheduling and cluster resource management There are a few other projects (like Pig, Hive) related to above Hadoop as well which we will gradually explore in later blog posts. A Multi-node Hadoop Cluster Architecture Now let us quickly see the architecture of the a multi-node Hadoop cluster. A small Hadoop cluster includes a single master node and multiple worker or slave node. As discussed earlier, the entire cluster contains two layers. One of the layer of MapReduce Layer and another is of HDFC Layer. Each of these layer have its own relevant component. The master node consists of a JobTracker, TaskTracker, NameNode and DataNode. A slave or worker node consists of a DataNode and TaskTracker. It is also possible that slave node or worker node is only data or compute node. The matter of the fact that is the key feature of the Hadoop. In this introductory blog post we will stop here while describing the architecture of Hadoop. In a future blog post of this 31 day series we will explore various components of Hadoop Architecture in Detail. Why Use Hadoop? There are many advantages of using Hadoop. Let me quickly list them over here: Robust and Scalable – We can add new nodes as needed as well modify them. Affordable and Cost Effective – We do not need any special hardware for running Hadoop. We can just use commodity server. Adaptive and Flexible – Hadoop is built keeping in mind that it will handle structured and unstructured data. Highly Available and Fault Tolerant – When a node fails, the Hadoop framework automatically fails over to another node. Why Hadoop is named as Hadoop? In year 2005 Hadoop was created by Doug Cutting and Mike Cafarella while working at Yahoo. Doug Cutting named Hadoop after his son’s toy elephant. Tomorrow In tomorrow’s blog post we will discuss Buzz Word – MapReduce. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• Visual Studio Little Wonders: Box Selection

  - by James Michael Hare

  So this week I decided I’d do a Little Wonder of a different kind and focus on an underused IDE improvement: Visual Studio’s Box Selection capability. This is a handy feature that many people still don’t realize was made available in Visual Studio 2010 (and beyond).  True, there have been other editors in the past with this capability, but now that it’s fully part of Visual Studio we can enjoy it’s goodness from within our own IDE. So, for those of you who don’t know what box selection is and what it allows you to do, read on! Sometimes, we want to select beyond the horizontal… The problem with traditional text selection in many editors is that it is horizontally oriented.  Sure, you can select multiple rows, but if you do you will pull in the entire row (at least for the middle rows).  Under the old selection scheme, if you wanted to select a portion of text from each row (a “box” of text) you were out of luck.  Box selection rectifies this by allowing you to select a box of text that bounded by a selection rectangle that you can grow horizontally or vertically.  So let’s think a situation that could occur where this comes in handy. Let’s say, for instance, that we are defining an enum in our code that we want to be able to translate into some string values (possibly to be stored in a database, output to screen, etc.). Perhaps such an enum would look like this: 1: public enum OrderType 2: { 3: Buy, // buy shares of a commodity 4: Sell, // sell shares of a commodity 5: Exchange, // exchange one commodity for another 6: Cancel, // cancel an order for a commodity 7: } 8:  Now, let’s say we are in the process of creating a Dictionary<K,V> to translate our OrderType: 1: var translator = new Dictionary<OrderType, string> 2: { 3: // do I really want to retype all this??? 4: }; Yes the example above is contrived so that we will pull some garbage if we do a multi-line select. I could select the lines above using the traditional multi-line selection: And then paste them into the translator code, which would result in this: 1: var translator = new Dictionary<OrderType, string> 2: { 3: Buy, // buy shares of a commodity 4: Sell, // sell shares of a commodity 5: Exchange, // exchange one commodity for another 6: Cancel, // cancel an order for a commodity 7: }; But I have a lot of junk there, sure I can manually clear it out, or use some search and replace magic, but if this were hundreds of lines instead of just a few that would quickly become cumbersome. The Box Selection Now that we have the ability to create box selections, we can select the box of text to delete!  Most of us are familiar with the fact we can drag the mouse (or hold [Shift] and use the arrow keys) to create a selection that can span multiple rows: Box selection, however, actually allows us to select a box instead of the typical horizontal lines: Then we can press the [delete] key and the pesky comments are all gone! You can do this either by holding down [Alt] while you select with your mouse, or by holding down [Alt+Shift] and using the arrow keys on the keyboard to grow the box horizontally or vertically. So now we have: 1: var translator = new Dictionary<OrderType, string> 2: { 3: Buy, 4: Sell, 5: Exchange, 6: Cancel, 7: }; Which is closer, but we still need an opening curly, the string to translate to, and the closing curly and comma. Fortunately, again, this is easy with box selections due to the fact box selection can even work for a zero-width selection! That is, hold down [Alt] and either drag down with no width, or hold down [Alt+Shift] and arrow down and you will define a selection range with no width, essentially, a vertical line selection: Notice the faint selection line on the right? So why is this useful? Well, just like with any selected range, we can type and it will replace the selection. What does this mean for box selections? It means that we can insert the same text all the way down on each line! If we have the same selection above, and type a curly and a space, we’d get: Imagine doing this over hundreds of lines and think of what a time saver it could be! Now make a zero-width selection on the other side: And type a curly and a comma, and we’d get: So close! Now finally, imagine we’ve already defined these strings somewhere and want to paste them in: 1: const private string BuyText = "Buy Shares"; 2: const private string SellText = "Sell Shares"; 3: const private string ExchangeText = "Exchange"; 4: const private string CancelText = "Cancel"; We can, again, use our box selection to pull out the constant names: And clicking copy (or [CTRL+C]) and then selecting a range to paste into: And finally clicking paste (or [CTRL+V]) to get the final result: 1: var translator = new Dictionary<OrderType, string> 2: { 3: { Buy, BuyText }, 4: { Sell, SellText }, 5: { Exchange, ExchangeText }, 6: { Cancel, CancelText }, 7: };   Sure, this was a contrived example, but I’m sure you’ll agree that it adds myriad possibilities of new ways to copy and paste vertical selections, as well as inserting text across a vertical slice. Summary: While box selection has been around in other editors, we finally get to experience it in VS2010 and beyond. It is extremely handy for selecting columns of information for cutting, copying, and pasting. In addition, it allows you to create a zero-width vertical insertion point that can be used to enter the same text across multiple rows. Imagine the time you can save adding repetitive code across multiple lines!  Try it, the more you use it, the more you’ll love it! Technorati Tags: C#,CSharp,.NET,Visual Studio,Little Wonders,Box Selection

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• Trace File Source Adapter

  The Trace File Source adapter is a useful addition to your SSIS toolbox.  It allows you to read 2005 and 2008 profiler traces stored as .trc files and read them into the Data Flow.  From there you can perform filtering and analysis using the power of SSIS. There is no need for a SQL Server connection this just uses the trace file. Example Usages Cache warming for SQL Server Analysis Services Reading the flight recorder Find out the longest running queries on a server Analyze statements for CPU, memory by user or some other criteria you choose Properties The Trace File Source adapter has two properties, both of which combine to control the source trace file that is read at runtime. SQL Server 2005 and SQL Server 2008 trace files are supported for both the Database Engine (SQL Server) and Analysis Services. The properties are managed by the Editor form or can be set directly from the Properties Grid in Visual Studio. Property Type Description AccessMode Enumeration This property determines how the Filename property is interpreted. The values available are: DirectInput Variable Filename String This property holds the path for trace file to load (*.trc). The value is either a full path, or the name of a variable which contains the full path to the trace file, depending on the AccessMode property. Trace Column Definition Hopefully the majority of you can skip this section entirely, but if you encounter some problems processing a trace file this may explain it and allow you to fix the problem. The component is built upon the trace management API provided by Microsoft. Unfortunately API methods that expose the schema of a trace file have known issues and are unreliable, put simply the data often differs from what was specified. To overcome these limitations the component uses  some simple XML files. These files enable the trace column data types and sizing attributes to be overridden. For example SQL Server Profiler or TMO generated structures define EventClass as an integer, but the real value is a string. TraceDataColumnsSQL.xml  - SQL Server Database Engine Trace Columns TraceDataColumnsAS.xml    - SQL Server Analysis Services Trace Columns The files can be found in the %ProgramFiles%\Microsoft SQL Server\100\DTS\PipelineComponents folder, e.g. "C:\Program Files\Microsoft SQL Server\100\DTS\PipelineComponents\TraceDataColumnsSQL.xml" "C:\Program Files\Microsoft SQL Server\100\DTS\PipelineComponents\TraceDataColumnsAS.xml" If at runtime the component encounters a type conversion or sizing error it is most likely due to a discrepancy between the column definition as reported by the API and the actual value encountered. Whilst most common issues have already been fixed through these files we have implemented specific exception traps to direct you to the files to enable you to fix any further issues due to different usage or data scenarios that we have not tested. An example error that you can fix through these files is shown below. Buffer exception writing value to column 'Column Name'. The string value is 999 characters in length, the column is only 111. Columns can be overridden by the TraceDataColumns XML files in "C:\Program Files\Microsoft SQL Server\100\DTS\PipelineComponents\TraceDataColumnsAS.xml". Installation The component is provided as an MSI file which you can download and run to install it. This simply places the files on disk in the correct locations and also installs the assemblies in the Global Assembly Cache as per Microsoft’s recommendations. You may need to restart the SQL Server Integration Services service, as this caches information about what components are installed, as well as restarting any open instances of Business Intelligence Development Studio (BIDS) / Visual Studio that you may be using to build your SSIS packages. Finally you will have to add the transformation to the Visual Studio toolbox manually. Right-click the toolbox, and select Choose Items.... Select the SSIS Data Flow Items tab, and then check the Trace File Source transformation in the Choose Toolbox Items window. This process has been described in detail in the related FAQ entry for How do I install a task or transform component? We recommend you follow best practice and apply the current Microsoft SQL Server Service pack to your SQL Server servers and workstations. Please note that the Microsoft Trace classes used in the component are not supported on 64-bit platforms. To use the Trace File Source on a 64-bit host you need to ensure you have the 32-bit (x86) tools available, and the way you execute your package is setup to use them, please see the help topic 64-bit Considerations for Integration Services for more details. Downloads Trace Sources for SQL Server 2005 -- Trace Sources for SQL Server 2008 Version History SQL Server 2008 Version 2.0.0.382 - SQL Sever 2008 public release. (9 Apr 2009) SQL Server 2005 Version 1.0.0.321 - SQL Server 2005 public release. (18 Nov 2008) -- Screenshots

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• What Counts For a DBA: Simplicity

  - by Louis Davidson

  Too many computer processes do an apparently simple task in a bizarrely complex way. They remind me of this strip by one of my favorite artists: Rube Goldberg. In order to keep the boss from knowing one was late, a process is devised whereby the cuckoo clock kisses a live cuckoo bird, who then pulls a string, which triggers a hat flinging, which in turn lands on a rod that removes a typewriter cover…and so on. We rely on creating automated processes to keep on top of tasks. DBAs have a lot of tasks to perform: backups, performance tuning, data movement, system monitoring, and of course, avoiding being noticed.  Every day, there are many steps to perform to maintain the database infrastructure, including: checking physical structures, re-indexing tables where needed, backing up the databases, checking those backups, running the ETL, and preparing the daily reports and yes, all of these processes have to complete before you can call it a day, and probably before many others have started that same day. Some of these tasks are just naturally complicated on their own. Other tasks become complicated because the database architecture is excessively rigid, and we often discover during “production testing” that certain processes need to be changed because the written requirements barely resembled the actual customer requirements.   Then, with no time to change that rigid structure, we are forced to heap layer upon layer of code onto the problematic processes. Instead of a slight table change and a new index, we end up with 4 new ETL processes, 20 temp tables, 30 extra queries, and 1000 lines of SQL code.  Report writers then need to build reports and make magical numbers appear from those toxic data structures that are overly complex and probably filled with inconsistent data. What starts out as a collection of fairly simple tasks turns into a Goldbergian nightmare of daily processes that are likely to cause your dinner to be interrupted by the smartphone doing the vibration dance that signifies trouble at the mill. So what to do? Well, if it is at all possible, simplify the problem by either going into the code and refactoring the complex code to simple, or taking all of the processes and simplifying them into small, independent, easily-tested steps.  The former approach usually requires an agreement on changing underlying structures that requires countless mind-numbing meetings; while the latter can generally be done to any complex process without the same frustration or anger, though it will still leave you with lots of steps to complete, the ability to test each step independently will definitely increase the quality of the overall process (and with each step reporting status back, finding an actual problem within the process will be definitely less unpleasant.) We all know the principle behind simplifying a sequence of processes because we learned it in math classes in our early years of attending school, starting with elementary school. In my 4 years (ok, 9 years) of undergraduate work, I remember pretty much one thing from my many math classes that I apply daily to my career as a data architect, data programmer, and as an occasional indentured DBA: “show your work”. This process of showing your work was my first lesson in simplification. Each step in the process was in fact, far simpler than the entire process.  When you were working an equation that took both sides of 4 sheets of paper, showing your work was important because the teacher could see every step, judge it, and mark it accordingly.  So often I would make an error in the first few lines of a problem which meant that the rest of the work was actually moving me closer to a very wrong answer, no matter how correct the math was in the subsequent steps. Yet, when I got my grade back, I would sometimes be pleasantly surprised. I passed, yet missed every problem on the test. But why? While I got the fact that 1+1=2 wrong in every problem, the teacher could see that I was using the right process. In a computer process, the process is very similar. We take complex processes, show our work by storing intermediate values, and test each step independently. When a process has 100 steps, each step becomes a simple step that is tested and verified, such that there will be 100 places where data is stored, validated, and can be checked off as complete. If you get step 1 of 100 wrong, you can fix it and be confident (that if you did your job of testing the other steps better than the one you had to repair,) that the rest of the process works. If you have 100 steps, and store the state of the process exactly once, the resulting testable chunk of code will be far more complex and finding the error will require checking all 100 steps as one, and usually it would be easier to find a specific needle in a stack of similarly shaped needles.  The goal is to strive for simplicity either in the solution, or at least by simplifying every process down to as many, independent, testable, simple tasks as possible.  For the tasks that really can’t be done completely independently, minimally take those tasks and break them down into simpler steps that can be tested independently.  Like working out division problems longhand, have each step of the larger problem verified and tested.

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• NoSQL Java API for MySQL Cluster: Questions & Answers

  - by Mat Keep

  The MySQL Cluster engineering team recently ran a live webinar, available now on-demand demonstrating the ClusterJ and ClusterJPA NoSQL APIs for MySQL Cluster, and how these can be used in building real-time, high scale Java-based services that require continuous availability. Attendees asked a number of great questions during the webinar, and I thought it would be useful to share those here, so others are also able to learn more about the Java NoSQL APIs. First, a little bit about why we developed these APIs and why they are interesting to Java developers. ClusterJ and Cluster JPA ClusterJ is a Java interface to MySQL Cluster that provides either a static or dynamic domain object model, similar to the data model used by JDO, JPA, and Hibernate. A simple API gives users extremely high performance for common operations: insert, delete, update, and query. ClusterJPA works with ClusterJ to extend functionality, including - Persistent classes - Relationships - Joins in queries - Lazy loading - Table and index creation from object model By eliminating data transformations via SQL, users get lower data access latency and higher throughput. In addition, Java developers have a more natural programming method to directly manage their data, with a complete, feature-rich solution for Object/Relational Mapping. As a result, the development of Java applications is simplified with faster development cycles resulting in accelerated time to market for new services. MySQL Cluster offers multiple NoSQL APIs alongside Java: - Memcached for a persistent, high performance, write-scalable Key/Value store, - HTTP/REST via an Apache module - C++ via the NDB API for the lowest absolute latency. Developers can use SQL as well as NoSQL APIs for access to the same data set via multiple query patterns – from simple Primary Key lookups or inserts to complex cross-shard JOINs using Adaptive Query Localization Marrying NoSQL and SQL access to an ACID-compliant database offers developers a number of benefits. MySQL Cluster’s distributed, shared-nothing architecture with auto-sharding and real time performance makes it a great fit for workloads requiring high volume OLTP. Users also get the added flexibility of being able to run real-time analytics across the same OLTP data set for real-time business insight. OK – hopefully you now have a better idea of why ClusterJ and JPA are available. Now, for the Q&A. Q & A Q. Why would I use Connector/J vs. ClusterJ? A. Partly it's a question of whether you prefer to work with SQL (Connector/J) or objects (ClusterJ). Performance of ClusterJ will be better as there is no need to pass through the MySQL Server. A ClusterJ operation can only act on a single table (e.g. no joins) - ClusterJPA extends that capability Q. Can I mix different APIs (ie ClusterJ, Connector/J) in our application for different query types? A. Yes. You can mix and match all of the API types, SQL, JDBC, ODBC, ClusterJ, Memcached, REST, C++. They all access the exact same data in the data nodes. Update through one API and new data is instantly visible to all of the others. Q. How many TCP connections would a SessionFactory instance create for a cluster of 8 data nodes? A. SessionFactory has a connection to the mgmd (management node) but otherwise is just a vehicle to create Sessions. Without using connection pooling, a SessionFactory will have one connection open with each data node. Using optional connection pooling allows multiple connections from the SessionFactory to increase throughput. Q. Can you give details of how Cluster J optimizes sharding to enhance performance of distributed query processing? A. Each data node in a cluster runs a Transaction Coordinator (TC), which begins and ends the transaction, but also serves as a resource to operate on the result rows. While an API node (such as a ClusterJ process) can send queries to any TC/data node, there are performance gains if the TC is where most of the result data is stored. ClusterJ computes the shard (partition) key to choose the data node where the row resides as the TC. Q. What happens if we perform two primary key lookups within the same transaction? Are they sent to the data node in one transaction? A. ClusterJ will send identical PK lookups to the same data node. Q. How is distributed query processing handled by MySQL Cluster ? A. If the data is split between data nodes then all of the information will be transparently combined and passed back to the application. The session will connect to a data node - typically by hashing the primary key - which then interacts with its neighboring nodes to collect the data needed to fulfil the query. Q. Can I use Foreign Keys with MySQL Cluster A. Support for Foreign Keys is included in the MySQL Cluster 7.3 Early Access release Summary The NoSQL Java APIs are packaged with MySQL Cluster, available for download here so feel free to take them for a spin today! Key Resources MySQL Cluster on-line demo  MySQL ClusterJ and JPA On-demand webinar  MySQL ClusterJ and JPA documentation MySQL ClusterJ and JPA whitepaper and tutorial

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• IBM Keynote: (hardware,software)–>{IBM.java.patterns}

  - by Janice J. Heiss

  On Sunday evening, September 30, 2012, Jason McGee, IBM Distinguished Engineer and Chief Architect Cloud Computing, along with John Duimovich IBM Distinguished Engineer and Java CTO, gave an information- and idea-rich keynote that left Java developers with much to ponder.Their focus was on the challenges to make Java more efficient and productive given the hardware and software environments of 2012. “One idea that is very interesting is the idea of multi-tenancy,” said McGee, “and how we can move up the spectrum. In traditional systems, we ran applications on dedicated middleware, operating systems and hardware. A lot of customers still run that way. Now people introduce hardware virtualization and share the hardware. That is good but there is a lot more we can do. We can share middleware and the application itself.” McGee challenged developers to better enable the Java language to function in these higher density models. He spoke about the need to describe patterns that help us grasp the full environment that an application needs, whether it’s a web or full enterprise application. Developers need to understand the resources that an application interacts with in a way that is simple and straightforward. The task is to then automate that deployment so that the complexity of infrastructure can be by-passed and developers can live in a simpler world where the cloud can automatically configure the needed environment. McGee argued that the key, something IBM has been working on, is to use a simpler pattern that allows a cloud-based architecture to embrace the entire infrastructure required for an application and make it highly available, scalable and able to recover from failure. The cloud-based architecture would automate the complexity of setting up and managing the infrastructure. IBM has been trying to realize this vision for customers so they can describe their Java application environment simply and allow the cloud to automate the deployment and management of applications. “The point,” explained McGee, “is to package the executable used to describe applications, to drop it into a shared system and let that system provide some intelligence about how to deploy and manage those applications.”John Duimovich on Improvements in JavaMcGee then brought onstage IBM’s Distinguished Engineer and CTO for Java, John Duimovich, who showed the audience ways to deploy Java applications more efficiently.Duimovich explained that, “When you run lots of copies of Java in the cloud or any hypervisor virtualized system, there are a lot of duplications of code and jar files. IBM has a facility called ‘shared classes’ where we put shared code, read only artefacts in a cache that is sharable across hypervisors.” By putting JIT code in ahead of time, he explained that the application server will use 20% less memory and operate 30% faster.  He described another example of how the JVM allows for the maximum amount of sharing that manages the tenants and file sockets and memory use through throttling and control. Duimovich touched on the “thin is in” model and IBM’s Liberty Profile and lightweight runtime for the cloud, which allows for greater efficiency in interacting with the cloud.Duimovich discussed the confusion Java developers experience when, for example, the hypervisor tells them that that they have 8 and then 4 and then 16 cores. “Because hypervisors are virtualized, they can change based on resource needs across the hypervisor layer. You may have 10 instances of an operation system and you may need to reallocate memory, " explained Duimovich.  He showed how to resize LPARs, reallocate CPUs and migrate applications as needed. He explained how application servers can resize thread pools and better use resources based on information from the hypervisors.Java Challenges in Hardware and SoftwareMcGee ended the keynote with a summary of upcoming hardware and software challenges for the Java platform. He noted that one reason developers love Java is it allows them to ignore differences in hardware. He stated that the most important things happening in hardware were in network and storage – in developments such as the speed of SSD, the exploitation of high-speed, low-latency networking, and recent developments such as storage-class memory, and non-volatile main memory. “So we are challenged to maintain the benefits of Java and the abstraction it provides from hardware while still exploiting the new innovations in hardware,” said McGee.McGee discussed transactional messaging applications where developers send messages transactionally persist a message to storage, something traditionally done by backing messages on spinning disks, something mostly outdated. “Now,” he pointed out, “we would use SSD and store it in Flash and get 70,000 messages a second. If we stored it using a PCI express-based flash memory device, it is still Flash but put on a PCI express bus on a card closer to the CPU. This way I get 300,000 messages a second and 25% improvement in latency.” McGee’s central point was that hardware has a huge impact on the performance and scalability of applications. New technologies are enabling developers to build classes of Java applications previously unheard of. “We need to be able to balance these things in Java – we need to maintain the abstraction but also be able to exploit the evolution of hardware technology,” said McGee. According to McGee, IBM's current focus is on systems wherein hardware and software are shipped together in what are called Expert Integrated Systems – systems that are pre-optimized, and pre-integrated together. McGee closed IBM’s engaging and thought-provoking keynote by pointing out that the use of Java in complex applications is increasingly being augmented by a host of other languages with strong communities around them – JavaScript, JRuby, Scala, Python and so forth. Java developers now must understand the strengths and weaknesses of such newcomers as applications increasingly involve a complex interconnection of languages.

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• Why would GLCapabilities.setHardwareAccelerated(true/false) have no effect on performance?

  - by Luke

  I've got a JOGL application in which I am rendering 1 million textures (all the same texture) and 1 million lines between those textures. Basically it's a ball-and-stick graph. I am storing the vertices in a vertex array on the card and referencing them via index arrays, which are also stored on the card. Each pass through the draw loop I am basically doing this: gl.glBindBuffer(GL.GL_ARRAY_BUFFER, <buffer id>); gl.glBindBuffer(GL.GL_ELEMENT_ARRAY_BUFFER, <buffer id>); gl.glDrawElements(GL.GL_POINTS, <size>, GL.GL_UNSIGNED_INT, 0); gl.glBindBuffer(GL.GL_ARRAY_BUFFER, <buffer id>); gl.glBindBuffer(GL.GL_ELEMENT_ARRAY_BUFFER, <buffer id>); gl.glDrawElements(GL.GL_LINES, <size>, GL.GL_UNSIGNED_INT, 0); I noticed that the JOGL library is pegging one of my CPU cores. Every frame, the run method internal to the library is taking quite long. I'm not sure why this is happening since I have called setHardwareAccelerated(true) on the GLCapabilities used to create my canvas. What's more interesting is that I changed it to setHardwareAccelerated(false) and there was no impact on the performance at all. Is it possible that my code is not using hardware rendering even when it is set to true? Is there any way to check? EDIT: As suggested, I have tested breaking my calls up into smaller chunks. I have tried using glDrawRangeElements and respecting the limits that it requests. All of these simply resulted in the same pegged CPU usage and worse framerates. I have also narrowed the problem down to a simpler example where I just render 4 million textures (no lines). The draw loop then just doing this: gl.glEnableClientState(GL.GL_VERTEX_ARRAY); gl.glEnableClientState(GL.GL_INDEX_ARRAY); gl.glClear(GL.GL_COLOR_BUFFER_BIT | GL.GL_DEPTH_BUFFER_BIT); gl.glMatrixMode(GL.GL_MODELVIEW); gl.glLoadIdentity(); <... Camera and transform related code ...> gl.glEnableVertexAttribArray(0); gl.glEnable(GL.GL_TEXTURE_2D); gl.glAlphaFunc(GL.GL_GREATER, ALPHA_TEST_LIMIT); gl.glEnable(GL.GL_ALPHA_TEST); <... Bind texture ...> gl.glBindBuffer(GL.GL_ARRAY_BUFFER, <buffer id>); gl.glBindBuffer(GL.GL_ELEMENT_ARRAY_BUFFER, <buffer id>); gl.glDrawElements(GL.GL_POINTS, <size>, GL.GL_UNSIGNED_INT, 0); gl.glDisable(GL.GL_TEXTURE_2D); gl.glDisable(GL.GL_ALPHA_TEST); gl.glDisableVertexAttribArray(0); gl.glFlush(); Where the first buffer contains 12 million floats (the x,y,z coords of the 4 million textures) and the second (element) buffer contains 4 million integers. In this simple example it is simply the integers 0 through 3999999. I really want to know what is being done in software that is pegging my CPU, and how I can make it stop (if I can). My buffers are generated by the following code: gl.glBindBuffer(GL.GL_ARRAY_BUFFER, <buffer id>); gl.glBufferData(GL.GL_ARRAY_BUFFER, <size> * BufferUtil.SIZEOF_FLOAT, <buffer>, GL.GL_STATIC_DRAW); gl.glVertexAttribPointer(0, 3, GL.GL_FLOAT, false, 0, 0); and: gl.glBindBuffer(GL.GL_ELEMENT_ARRAY_BUFFER, <buffer id>); gl.glBufferData(GL.GL_ELEMENT_ARRAY_BUFFER, <size> * BufferUtil.SIZEOF_INT, <buffer>, GL.GL_STATIC_DRAW); ADDITIONAL INFO: Here is my initialization code: gl.setSwapInterval(1); //Also tried 0 gl.glShadeModel(GL.GL_SMOOTH); gl.glClearDepth(1.0f); gl.glEnable(GL.GL_DEPTH_TEST); gl.glDepthFunc(GL.GL_LESS); gl.glHint(GL.GL_PERSPECTIVE_CORRECTION_HINT, GL.GL_FASTEST); gl.glPointParameterfv(GL.GL_POINT_DISTANCE_ATTENUATION, POINT_DISTANCE_ATTENUATION, 0); gl.glPointParameterfv(GL.GL_POINT_SIZE_MIN, MIN_POINT_SIZE, 0); gl.glPointParameterfv(GL.GL_POINT_SIZE_MAX, MAX_POINT_SIZE, 0); gl.glPointSize(POINT_SIZE); gl.glTexEnvf(GL.GL_POINT_SPRITE, GL.GL_COORD_REPLACE, GL.GL_TRUE); gl.glEnable(GL.GL_POINT_SPRITE); gl.glClearColor(clearColor.getX(), clearColor.getY(), clearColor.getZ(), 0.0f); Also, I'm not sure if this helps or not, but when I drag the entire graph off the screen, the FPS shoots back up and the CPU usage falls to 0%. This seems obvious and intuitive to me, but I thought that might give a hint to someone else.

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• ISACA Webcast follow up: Managing High Risk Access and Compliance with a Platform Approach to Privileged Account Management

  - by Darin Pendergraft

  Last week we presented how Oracle Privileged Account Manager (OPAM) could be used to manage high risk, privileged accounts.  If you missed the webcast, here is a link to the replay: ISACA replay archive (NOTE: you will need to use Internet Explorer to view the archive) For those of you that did join us on the call, you will know that I only had a little bit of time for Q&A, and was only able to answer a few of the questions that came in.  So I wanted to devote this blog to answering the outstanding questions.  Here they are. 1. Can OPAM track admin or DBA activity details during a password check-out session? Oracle Audit Vault is monitoring these activities which can be correlated to check-out events. 2. How would OPAM handle simultaneous requests? OPAM can be configured to allow for shared passwords.  By default sharing is turned off. 3. How long are the passwords valid?  Are the admins required to manually check them in? Password expiration can be configured and set in the password policy according to your corporate standards.  You can specify if you want forced check-in or not. 4. Can 2-factor authentication be used with OPAM? Yes - 2-factor integration with OPAM is provided by integration with Oracle Access Manager, and Oracle Adaptive Access Manager. 5. How do you control access to OPAM to ensure that OPAM admins don't override the functionality to access privileged accounts? OPAM provides separation of duties by using Admin Roles to manage access to targets and privileged accounts and to control which operations admins can perform. 6. How and where are the passwords stored in OPAM? OPAM uses Oracle Platform Security Services (OPSS) Credential Store Framework (CSF) to securely store passwords.  This is the same system used by Oracle Applications. 7. Does OPAM support hierarchical/level based privileges?  Is the log maintained for independent review/audit? Yes. OPAM uses the Fusion Middleware (FMW) Audit Framework to store all OPAM related events in a dedicated audit database.  8. Does OPAM support emergency access in the case where approvers are not available until later? Yes.  OPAM can be configured to release a password under a "break-glass" emergency scenario. 9. Does OPAM work with AIX? Yes supported UNIX version are listed in the "certified component section" of the UNIX connector guide at:http://docs.oracle.com/cd/E22999_01/doc.111/e17694/intro.htm#autoId0 10. Does OPAM integrate with Sun Identity Manager? Yes.  OPAM can be integrated with SIM using the REST  APIs.  OPAM has direct integration with Oracle Identity Manager 11gR2. 11. Is OPAM available today and what does it cost? Yes.  OPAM is available now.  Ask your Oracle Account Manager for pricing. 12. Can OPAM be used in SAP environments? Yes, supported SAP version are listed in the "certified component section" of the SAP  connector guide here: http://docs.oracle.com/cd/E22999_01/doc.111/e25327/intro.htm#autoId0 13. How would this product integrate, if at all, with access to a particular field in the DB that need additional security such as SSN's? OPAM can work with DB Vault and DB Firewall to provide the fine grained access control for databases. 14. Is VM supported? As a deployment platform Oracle VM is supported. For further details about supported Virtualization Technologies see Oracle Fusion Middleware Supported System configurations here: http://www.oracle.com/technetwork/middleware/ias/downloads/fusion-certification-100350.html 15. Where did this (OPAM) technology come from? OPAM was built by Oracle Engineering. 16. Are all Linux flavors supported?  How about BSD? BSD is not supported. For supported UNIX version see the "certified component section" of the UNIX connector guide http://docs.oracle.com/cd/E22999_01/doc.111/e17694/intro.htm#autoId0 17. What happens if users don't check passwords in at the end of a work task? In OPAM a time frame can be defined how long a password can be checked out. The security admin can force a check-in at any given time. 18. is MySQL supported? Yes, supported DB version are listed in the "certified component section" of the DB connector guide here: http://docs.oracle.com/cd/E22999_01/doc.111/e28315/intro.htm#BABGJJHA 19. What happens when OPAM crashes and you need to use the password? OPAM can be configured for high availability, but if required, OPAM data can be backed up/recovered.  See the OPAM admin guide. 20. Is OPAM Standalone product or does it leverage other components from IDM? OPAM can be run stand-alone, but will also leverage other IDM components

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• Windows Azure Recipe: Enterprise LOBs

  - by Clint Edmonson

  Enterprises are more and more dependent on their specialized internal Line of Business (LOB) applications than ever before. Naturally, the more software they leverage on-premises, the more infrastructure they need manage. It’s frequently the case that our customers simply can’t scale up their hardware purchases and operational staff as fast as internal demand for software requires. The result is that getting new or enhanced applications in the hands of business users becomes slower and more expensive every day. Being able to quickly deliver applications in a rapidly changing business environment while maintaining high standards of corporate security is a challenge that can be met right now by moving enterprise LOBs out into the cloud and leveraging Azure’s Access Control services. In fact, we’re seeing many of our customers (both large and small) see huge benefits from moving their web based business applications such as corporate help desks, expense tracking, travel portals, timesheets, and more to Windows Azure. Drivers Cost Reduction Time to market Security Solution Here’s a sketch of how many Windows Azure Enterprise LOBs are being architected and deployed: Ingredients Web Role – this will host the core of the application. Each web role is a virtual machine hosting an application written in ASP.NET (or optionally php, or node.js). The number of web roles can be scaled up or down as needed to handle peak and non-peak traffic loads. Many Java based applications are also being deployed to Windows Azure with a little more effort. Database – every modern web application needs to store data. SQL Azure databases look and act exactly like their on-premise siblings but are fault tolerant and have data redundancy built in. Access Control – this service is necessary to establish federated identity between the cloud hosted application and an enterprise’s corporate network. It works in conjunction with a secure token service (STS) that is hosted on-premises to establish the corporate user’s identity and credentials. The source code for an on-premises STS is provided in the Windows Azure training kit and merely needs to be customized for the corporate environment and published on a publicly accessible corporate web site. Once set up, corporate users see a near seamless single sign-on experience. Reporting – businesses live and die by their reports and SQL Azure Reporting, based on SQL Server Reporting 2008 R2, can serve up reports with tables, charts, maps, gauges, and more. These reports can be accessed from the Windows Azure Portal, through a web browser, or directly from applications. Service Bus (optional) – if deep integration with other applications and systems is needed, the service bus is the answer. It enables secure service layer communication between applications hosted behind firewalls in on-premises or partner datacenters and applications hosted inside Windows Azure. The Service Bus provides the ability to securely expose just the information and services that are necessary to create a simpler, more secure architecture than opening up a full blown VPN. Data Sync (optional) – in cases where the data stored in the cloud needs to be shared internally, establishing a secure one-way or two-way data-sync connection between the on-premises and off-premises databases is a perfect option. It can be very granular, allowing us to specify exactly what tables and columns to synchronize, setup filters to sync only a subset of rows, set the conflict resolution policy for two-way sync, and specify how frequently data should be synchronized Training Labs These links point to online Windows Azure training labs where you can learn more about the individual ingredients described above. (Note: The entire Windows Azure Training Kit can also be downloaded for offline use.) Windows Azure (16 labs) Windows Azure is an internet-scale cloud computing and services platform hosted in Microsoft data centers, which provides an operating system and a set of developer services which can be used individually or together. It gives developers the choice to build web applications; applications running on connected devices, PCs, or servers; or hybrid solutions offering the best of both worlds. New or enhanced applications can be built using existing skills with the Visual Studio development environment and the .NET Framework. With its standards-based and interoperable approach, the services platform supports multiple internet protocols, including HTTP, REST, SOAP, and plain XML SQL Azure (7 labs) Microsoft SQL Azure delivers on the Microsoft Data Platform vision of extending the SQL Server capabilities to the cloud as web-based services, enabling you to store structured, semi-structured, and unstructured data. Windows Azure Services (9 labs) As applications collaborate across organizational boundaries, ensuring secure transactions across disparate security domains is crucial but difficult to implement. Windows Azure Services provides hosted authentication and access control using powerful, secure, standards-based infrastructure. See my Windows Azure Resource Guide for more guidance on how to get started, including links web portals, training kits, samples, and blogs related to Windows Azure.

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• PASS Summit 2011 &ndash; Part III

  - by Tara Kizer

  Well we’re about a month past PASS Summit 2011, and yet I haven’t finished blogging my notes! Between work and home life, I haven’t been able to come up for air in a bit.  Now on to my notes… On Thursday of the PASS Summit 2011, I attended Klaus Aschenbrenner’s (blog|twitter) “Advanced SQL Server 2008 Troubleshooting”, Joe Webb’s (blog|twitter) “SQL Server Locking & Blocking Made Simple”, Kalen Delaney’s (blog|twitter) “What Happened? Exploring the Plan Cache”, and Paul Randal’s (blog|twitter) “More DBA Mythbusters”.  I think my head grew two times in size from the Thursday sessions.  Just WOW! I took a ton of notes in Klaus' session.  He took a deep dive into how to troubleshoot performance problems.  Here is how he goes about solving a performance problem: Start by checking the wait stats DMV System health Memory issues I/O issues I normally start with blocking and then hit the wait stats.  Here’s the wait stat query (Paul Randal’s) that I use when working on a performance problem.  He highlighted a few waits to be aware of such as WRITELOG (indicates IO subsystem problem), SOS_SCHEDULER_YIELD (indicates CPU problem), and PAGEIOLATCH_XX (indicates an IO subsystem problem or a buffer pool problem).  Regarding memory issues, Klaus recommended that as a bare minimum, one should set the “max server memory (MB)” in sp_configure to 2GB or 10% reserved for the OS (whichever comes first).  This is just a starting point though! Regarding I/O issues, Klaus talked about disk partition alignment, which can improve SQL I/O performance by up to 100%.  You should use 64kb for NTFS cluster, and it’s automatic in Windows 2008 R2. Joe’s locking and blocking presentation was a good session to really clear up the fog in my mind about locking.  One takeaway that I had no idea could be done was that you can set a timeout in T-SQL code view LOCK_TIMEOUT.  If you do this via the application, you should trap error 1222. Kalen’s session went into execution plans.  The minimum size of a plan is 24k.  This adds up fast especially if you have a lot of plans that don’t get reused much.  You can use sys.dm_exec_cached_plans to check how often a plan is being reused by checking the usecounts column.  She said that we can use DBCC FLUSHPROCINDB to clear out the stored procedure cache for a specific database.  I didn’t know we had this available, so this was great to hear.  This will be less intrusive when an emergency comes up where I’ve needed to run DBCC FREEPROCCACHE. Kalen said one should enable “optimize for ad hoc workloads” if you have an adhoc loc.  This stores only a 300-byte stub of the first plan, and if it gets run again, it’ll store the whole thing.  This helps with plan cache bloat.  I have a lot of systems that use prepared statements, and Kalen says we simulate those calls by using sp_executesql.  Cool! Paul did a series of posts last year to debunk various myths and misconceptions around SQL Server.  He continues to debunk things via “DBA Mythbusters”.  You can get a PDF of a bunch of these here.  One of the myths he went over is the number of tempdb data files that you should have.  Back in 2000, the recommendation was to have as many tempdb data files as there are CPU cores on your server.  This no longer holds true due to the numerous cores we have on our servers.  Paul says you should start out with 1/4 to 1/2 the number of cores and work your way up from there.  BUT!  Paul likes what Bob Ward (twitter) says on this topic: 8 or less cores –> set number of files equal to the number of cores Greater than 8 cores –> start with 8 files and increase in blocks of 4 One common myth out there is to set your MAXDOP to 1 for an OLTP workload with high CXPACKET waits.  Instead of that, dig deeper first.  Look for missing indexes, out-of-date statistics, increase the “cost threshold for parallelism” setting, and perhaps set MAXDOP at the query level.  Paul stressed that you should not plan a backup strategy but instead plan a restore strategy.  What are your recoverability requirements?  Once you know that, now plan out your backups. As Paul always does, he talked about DBCC CHECKDB.  He said how fabulous it is.  I didn’t want to interrupt the presentation, so after his session had ended, I asked Paul about the need to run DBCC CHECKDB on your mirror systems.  You could have data corruption occur at the mirror and not at the principal server.  If you aren’t checking for data corruption on your mirror systems, you could be failing over to a corrupt database in the case of a disaster or even a planned failover.  You can’t run DBCC CHECKDB against the mirrored database, but you can run it against a snapshot off the mirrored database.

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• iPack -The iOS Application Packager

  - by user13277780

  iOS applications are distributed in .ipa archive files. These files are regular zip files which contain application resources and executable-s. To protect them from unauthorized modifications and to provide identification of their sources, the content of the archives is signed. The signature is included in the application executable of an.ipa archive and protects the executable file itself and the associated resource files. Apple provides native Mac OS tools for signing iOS executable-s (which are actually generic Mach-O code signing tools), but these tools are not generally available on other platforms. To provide a multi-platform development environment for JavaFX based iOS applications, we ported iOS signing and packaging to Java and created a dedicated ipack tool for it. The iPack tool can be used as a last step of creating .ipa package on various operating systems. Prototype has been tested by creating a final distributable for JavaFX application that runs on iPad, all done on Windows 7. Source Code The source code of iPac tool is in OpenJFX project repository. You can find it in: <openjfx root>/rt/tools/ios/Maven/ipack To build the iPack tool use: rt/tools/ios/Maven/ipack$ mvn package After building, you can run the tool: java -jar <path to ipack.jar> <arguments>  Signing keystore The tool uses a java key store to read the signing certificate and the associated private key. To prepare such keystore users can use keytool from JDK. One possible scenario is to import an existing private key and the certificate from a key store used on Mac OS: To list the content of an existing key store and identify the source alias: keytool -list -keystore <src keystore>.p12 -storetype pkcs12 -storepass <src keystore password> To create Java key store and import the private key with its certificate to the keys store: keytool -importkeystore \ -destkeystore <dst keystore> -deststorepass <dst keystore password> \ -srckeystore <src keystore>.p12 -srcstorepass <src keystore password> -srcstoretype pkcs12 \ -srcalias <src alias> -destalias <dst alias> -destkeypass <dst key password> Another scenario would be to generate a private / public key pair directly in a Java key store and create a certificate request from it. After sending the request to Apple one can then import the certificate response back to the Java key store and complete the signing certificate entry. In both scenarios the resulting alias in the Java key store will contain only a single (leaf) certificate. This can be verified with the following command: keytool -list -v -keystore <ipack keystore> -storepass <keystore password> When looking at the Certificate chain length entry, the number next to it is 1. When an executable file is signed on Mac OS, the resulting signature (in CMS format) includes the whole certificate chain up to the Apple Root CA. The ipack tool includes only the chain which is stored under the alias specified on the command line. So to have the whole chain in the signature we need to replace the single certificate entry under the alias with the corresponding full certificate chain. To do that we need first to create the chain in a separate file. It is easy to create such chain when working with certificates in Base-64 encoded PEM format. A certificate chain can be created by concatenating PEM certificates, which should form the chain, into a single file. For iOS signing we need the following certificates in our chain: Apple Root CA Apple Worldwide Developer Relations CA Our signing leaf certificate To convert a certificate from the binary DER format (.der, .cer) to PEM format: keytool -importcert -noprompt -keystore temp.ks -storepass temppwd -alias tempcert -file <certificate>.cer keytool -exportcert -keystore temp.ks -storepass temppwd -alias tempcert -rfc -file <certificate>.pem To export the signing certificate into PEM format: keytool -exportcert -keystore <ipack keystore> -storepass <keystore password> -alias <signing alias> -rfc -file SigningCert.pem After constructing a chain from AppleIncRootCertificate.pem, AppleWWDRCA.pem andSigningCert.pem, it can be imported back into the keystore with: keytool -importcert -noprompt -keystore <ipack keystore> -storepass <keystore password> -alias <signing alias> -keypass <key password> -file SigningCertChain.pem To summarize, the following example shows the full certificate chain replacement process: keytool -importcert -noprompt -keystore temp.ks -storepass temppwd -alias tempcert1 -file AppleIncRootCertificate.cer keytool -exportcert -keystore temp.ks -storepass temppwd -alias tempcert1 -rfc -file AppleIncRootCertificate.pem keytool -importcert -noprompt -keystore temp.ks -storepass temppwd -alias tempcert2 -file AppleWWDRCA.cer keytool -exportcert -keystore temp.ks -storepass temppwd -alias tempcert2 -rfc -file AppleWWDRCA.pem keytool -exportcert -keystore ipack.ks -storepass keystorepwd -alias mycert -rfc -file SigningCert.pem cat SigningCert.pem AppleWWDRCA.pem AppleIncRootCertificate.pem >SigningCertChain.pem keytool -importcert -noprompt -keystore ipack.ks -storepass keystorepwd -alias mycert -keypass keypwd -file SigningCertChain.pem keytool -list -v -keystore ipack.ks -storepass keystorepwd Usage When the ipack tool is started with no arguments it prints the following usage information: -appname MyApplication -appid com.myorg.MyApplication     Usage: ipack <archive> <signing opts> <application opts> [ <application opts> ... ] Signing options: -keystore <keystore> keystore to use for signing -storepass <password> keystore password -alias <alias> alias for the signing certificate chain and the associated private key -keypass <password> password for the private key Application options: -basedir <directory> base directory from which to derive relative paths -appdir <directory> directory with the application executable and resources -appname <file> name of the application executable -appid <id> application identifier Example: ipack MyApplication.ipa -keystore ipack.ks -storepass keystorepwd -alias mycert -keypass keypwd -basedir mysources/MyApplication/dist -appdir Payload/MyApplication.app -appname MyApplication -appid com.myorg.MyApplication    

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• Imaging: Paper Paper Everywhere, but None Should be in Sight

  - by Kellsey Ruppel

  Author: Vikrant Korde, Technical Architect, Aurionpro's Oracle Implementation Services team My wedding photos are stored in several empty shoeboxes. Yes...I got married before digital photography was mainstream...which means I'm old. But my parents are really old. They have shoeboxes filled with vacation photos on slides (I doubt many of you have even seen a home slide projector...and I hope you never do!). Neither me nor my parents should have shoeboxes filled with any form of photographs whatsoever. They should obviously live in the digital world...with no physical versions in sight (other than a few framed on our walls). Businesses grapple with similar challenges. But instead of shoeboxes, they have file cabinets and warehouses jam packed with paper invoices, legal documents, human resource files, material safety data sheets, incident reports, and the list goes on and on. In fact, regulatory and compliance rules govern many industries, requiring that this paperwork is available for any number of years. It's a real challenge...especially trying to find archived documents quickly and many times with no backup. Which brings us to a set of technologies called Image Process Management (or simply Imaging or Image Processing) that are transforming these antiquated, paper-based processes. Oracle's WebCenter Content Imaging solution is a combination of their WebCenter suite, which offers a robust set of content and document management features, and their Business Process Management (BPM) suite, which helps to automate business processes through the definition of workflows and business rules. Overall, the solution provides an enterprise-class platform for end-to-end management of document images within transactional business processes. It's a solution that provides all of the capabilities needed - from document capture and recognition, to imaging and workflow - to effectively transform your ‘shoeboxes’ of files into digitally managed assets that comply with strict industry regulations. The terminology can be quite overwhelming if you're new to the space, so we've provided a summary of the primary components of the solution below, along with a short description of the two paths that can be executed to load images of scanned documents into Oracle's WebCenter suite. WebCenter Imaging (WCI): the electronic document repository that provides security, annotations, and search capabilities, and is the primary user interface for managing work items in the imaging solution SOA & BPM Suites (workflow): provide business process management capabilities, including human tasks, workflow management, service integration, and all other standard SOA features. It's interesting to note that there a number of 'jumpstart' processes available to help accelerate the integration of business applications, such as the accounts payable invoice processing solution for E-Business Suite that facilitates the processing of large volumes of invoices WebCenter Enterprise Capture (WEC): expedites the capture process of paper documents to digital images, offering high volume scanning and importing from email, and allows for flexible indexing options WebCenter Forms Recognition (WFR): automatically recognizes, categorizes, and extracts information from paper documents with greatly reduced human intervention WebCenter Content: the backend content server that provides versioning, security, and content storage There are two paths that can be executed to send data from WebCenter Capture to WebCenter Imaging, both of which are described below: 1. Direct Flow - This is the simplest and quickest way to push an image scanned from WebCenter Enterprise Capture (WEC) to WebCenter Imaging (WCI), using the bare minimum metadata. The WEC activities are defined below: The paper document is scanned (or imported from email). The scanned image is indexed using a predefined indexing profile. The image is committed directly into the process flow 2. WFR (WebCenter Forms Recognition) Flow - This is the more complex process, during which data is extracted from the image using a series of operations including Optical Character Recognition (OCR), Classification, Extraction, and Export. This process creates three files (Tiff, XML, and TXT), which are fed to the WCI Input Agent (the high speed import/filing module). The WCI Input Agent directory is a standard ingestion method for adding content to WebCenter Imaging, the process for doing so is described below: WEC commits the batch using the respective commit profile. A TIFF file is created, passing data through the file name by including values separated by "_" (underscores). WFR completes OCR, classification, extraction, export, and pulls the data from the image. In addition to the TIFF file, which contains the document image, an XML file containing the extracted data, and a TXT file containing the metadata that will be filled in WCI, are also created. All three files are exported to WCI's Input agent directory. Based on previously defined "input masks", the WCI Input Agent will pick up the seeding file (often the TXT file). Finally, the TIFF file is pushed in UCM and a unique web-viewable URL is created. Based on the mapping data read from the TXT file, a new record is created in the WCI application.  Although these processes may seem complex, each Oracle component works seamlessly together to achieve a high performing and scalable platform. The solution has been field tested at some of the largest enterprises in the world and has transformed millions and millions of paper-based documents to more easily manageable digital assets. For more information on how an Imaging solution can help your business, please contact [email protected] (for U.S. West inquiries) or [email protected] (for U.S. East inquiries). About the Author: Vikrant is a Technical Architect in Aurionpro's Oracle Implementation Services team, where he delivers WebCenter-based Content and Imaging solutions to Fortune 1000 clients. With more than twelve years of experience designing, developing, and implementing Java-based software solutions, Vikrant was one of the founding members of Aurionpro's WebCenter-based offshore delivery team. He can be reached at [email protected].

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• SSIS: Building SQL databases on-the-fly using concatenated SQL scripts

  - by DrJohn

  Over the years I have developed many techniques which help automate the whole SQL Server build process. In my current process, where I need to build entire OLAP data marts on-the-fly, I make regular use of a simple but very effective mechanism to concatenate all the SQL Scripts together from my SSMS (SQL Server Management Studio) projects. This proves invaluable because in two clicks I can redeploy an entire SQL Server database with all tables, views, stored procedures etc. Indeed, I can also use the concatenated SQL scripts with SSIS to build SQL Server databases on-the-fly. You may be surprised to learn that I often redeploy the database several times per day, or even several times per hour, during the development process. This is because the deployment errors are logged and you can quickly see where SQL Scripts have object dependency errors. For example, after changing a table structure you may have forgotten to change any related views. The deployment log immediately points out all the objects which failed to build so you can fix and redeploy the database very quickly. The alternative approach (i.e. doing changes in the database directly using the SSMS UI) would require you to check all dependent objects before making changes. The chances are that you will miss something and wonder why your app returns the wrong data – a common problem caused by changing a table without re-creating dependent views. Using SQL Projects in SSMS A great many developers fail to make use of SQL Projects in SSMS (SQL Server Management Studio). To me they are invaluable way of organizing your SQL Scripts. The screenshot below shows a typical SSMS solution made up of several projects – one project for tables, another for views etc. The key point is that the projects naturally fall into the right order in file system because of the project name. The number in the folder or file name ensures that the projects the SQL scripts are concatenated together in the order that they need to be executed. Hence the script filenames start with 100, 110 etc. Concatenating SQL Scripts To concatenate the SQL Scripts together into one file, I use notepad.exe to create a simple batch file (see example screenshot) which uses the TYPE command to write the content of the SQL Script files into a combined file. As the SQL Scripts are in several folders, I simply use several TYPE command multiple times and append the output together. If you are unfamiliar with batch files, you may not know that the angled bracket (>) means write output of the program into a file. Two angled brackets (>>) means append output of this program into a file. So the command-line DIR > filelist.txt would write the content of the DIR command into a file called filelist.txt. In the example shown above, the concatenated file is called SB_DDS.sql If, like me you place the concatenated file under source code control, then the source code control system will change the file's attribute to "read-only" which in turn would cause the TYPE command to fail. The ATTRIB command can be used to remove the read-only flag. Using SQLCmd to execute the concatenated file Now that the SQL Scripts are all in one big file, we can execute the script against a database using SQLCmd using another batch file as shown below: SQLCmd has numerous options, but the script shown above simply executes the SS_DDS.sql file against the SB_DDS_DB database on the local machine and logs the errors to a file called SB_DDS.log. So after executing the batch file you can simply check the error log to see if your database built without a hitch. If you have errors, then simply fix the source files, re-create the concatenated file and re-run the SQLCmd to rebuild the database. This two click operation allows you to quickly identify and fix errors in your entire database definition.Using SSIS to execute the concatenated file To execute the concatenated SQL script using SSIS, you simply drop an Execute SQL task into your package and set the database connection as normal and then select File Connection as the SQLSourceType (as shown below). Create a file connection to your concatenated SQL script and you are ready to go.   Tips and TricksAdd a new-line at end of every fileThe most common problem encountered with this approach is that the GO statement on the last line of one file is placed on the same line as the comment at the top of the next file by the TYPE command. The easy fix to this is to ensure all your files have a new-line at the end.Remove all USE database statementsThe SQLCmd identifies which database the script should be run against.  So you should remove all USE database commands from your scripts - otherwise you may get unintentional side effects!!Do the Create Database separatelyIf you are using SSIS to create the database as well as create the objects and populate the database, then invoke the CREATE DATABASE command against the master database using a separate package before calling the package that executes the concatenated SQL script.    

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• Design Pattern for Complex Data Modeling

  - by Aaron Hayman

  I'm developing a program that has a SQL database as a backing store. As a very broad description, the program itself allows a user to generate records in any number of user-defined tables and make connections between them. As for specs: Any record generated must be able to be connected to any other record in any other user table (excluding itself...the record, not the table). These "connections" are directional, and the list of connections a record has is user ordered. Moreover, a record must "know" of connections made from it to others as well as connections made to it from others. The connections are kind of the point of this program, so there is a strong possibility that the number of connections made is very high, especially if the user is using the software as intended. A record's field can also include aggregate information from it's connections (like obtaining average, sum, etc) that must be updated on change from another record it's connected to. To conserve memory, only relevant information must be loaded at any one time (can't load the entire database in memory at load and go from there). I cannot assume the backing store is local. Right now it is, but eventually this program will include syncing to a remote db. Neither the user tables, connections or records are known at design time as they are user generated. I've spent a lot of time trying to figure out how to design the backing store and the object model to best fit these specs. In my first design attempt on this, I had one object managing all a table's records and connections. I attempted this first because it kept the memory footprint smaller (records and connections were simple dicts), but maintaining aggregate and link information between tables became....onerous (ie...a huge spaghettified mess). Tracing dependencies using this method almost became impossible. Instead, I've settled on a distributed graph model where each record and connection is 'aware' of what's around it by managing it own data and connections to other records. Doing this increases my memory footprint but also let me create a faulting system so connections/records aren't loaded into memory until they're needed. It's also much easier to code: trace dependencies, eliminate cycling recursive updates, etc. My biggest problem is storing/loading the connections. I'm not happy with any of my current solutions/ideas so I wanted to ask and see if anybody else has any ideas of how this should be structured. Connections are fairly simple. They contain: fromRecordID, fromTableID, fromRecordOrder, toRecordID, toTableID, toRecordOrder. Here's what I've come up with so far: Store all the connections in one big table. If I do this, either I load all connections at once (one big db call) or make a call every time a user table is loaded. The big issue here: the size of the connections table has the potential to be huge, and I'm afraid it would slow things down. Store in separate tables all the outgoing connections for each user table. This is probably the worst idea I've had. Now my connections are 'spread out' over multiple tables (one for each user table), which means I have to make a separate DB called to each table (or make a huge join) just to find all the incoming connections for a particular user table. I've avoided making "one big ass table", but I'm not sure the cost is worth it. Store in separate tables all outgoing AND incoming connections for each user table (using a flag to distinguish between incoming vs outgoing). This is the idea I'm leaning towards, but it will essentially double the total DB storage for all the connections (as each connection will be stored in two tables). It also means I have to make sure connection information is kept in sync in both places. This is obviously not ideal but it does mean that when I load a user table, I only need to load one 'connection' table and have all the information I need. This also presents a separate problem, that of connection object creation. Since each user table has a list of all connections, there are two opportunities for a connection object to be made. However, connections objects (designed to facilitate communication between records) should only be created once. This means I'll have to devise a common caching/factory object to make sure only one connection object is made per connection. Does anybody have any ideas of a better way to do this? Once I've committed to a particular design pattern I'm pretty much stuck with it, so I want to make sure I've come up with the best one possible.

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• Anatomy of a .NET Assembly - CLR metadata 2

  - by Simon Cooper

  Before we look any further at the CLR metadata, we need a quick diversion to understand how the metadata is actually stored. Encoding table information As an example, we'll have a look at a row in the TypeDef table. According to the spec, each TypeDef consists of the following: Flags specifying various properties of the class, including visibility. The name of the type. The namespace of the type. What type this type extends. The field list of this type. The method list of this type. How is all this data actually represented? Offset & RID encoding Most assemblies don't need to use a 4 byte value to specify heap offsets and RIDs everywhere, however we can't hard-code every offset and RID to be 2 bytes long as there could conceivably be more than 65535 items in a heap or more than 65535 fields or types defined in an assembly. So heap offsets and RIDs are only represented in the full 4 bytes if it is required; in the header information at the top of the #~ stream are 3 bits indicating if the #Strings, #GUID, or #Blob heaps use 2 or 4 bytes (the #US stream is not accessed from metadata), and the rowcount of each table. If the rowcount for a particular table is greater than 65535 then all RIDs referencing that table throughout the metadata use 4 bytes, else only 2 bytes are used. Coded tokens Not every field in a table row references a single predefined table. For example, in the TypeDef extends field, a type can extend another TypeDef (a type in the same assembly), a TypeRef (a type in a different assembly), or a TypeSpec (an instantiation of a generic type). A token would have to be used to let us specify the table along with the RID. Tokens are always 4 bytes long; again, this is rather wasteful of space. Cutting the RID down to 2 bytes would make each token 3 bytes long, which isn't really an optimum size for computers to read from memory or disk. However, every use of a token in the metadata tables can only point to a limited subset of the metadata tables. For the extends field, we only need to be able to specify one of 3 tables, which we can do using 2 bits: 0x0: TypeDef 0x1: TypeRef 0x2: TypeSpec We could therefore compress the 4-byte token that would otherwise be needed into a coded token of type TypeDefOrRef. For each type of coded token, the least significant bits encode the table the token points to, and the rest of the bits encode the RID within that table. We can work out whether each type of coded token needs 2 or 4 bytes to represent it by working out whether the maximum RID of every table that the coded token type can point to will fit in the space available. The space available for the RID depends on the type of coded token; a TypeOrMethodDef coded token only needs 1 bit to specify the table, leaving 15 bits available for the RID before a 4-byte representation is needed, whereas a HasCustomAttribute coded token can point to one of 18 different tables, and so needs 5 bits to specify the table, only leaving 11 bits for the RID before 4 bytes are needed to represent that coded token type. For example, a 2-byte TypeDefOrRef coded token with the value 0x0321 has the following bit pattern: 0 3 2 1 0000 0011 0010 0001 The first two bits specify the table - TypeRef; the other bits specify the RID. Because we've used the first two bits, we've got to shift everything along two bits: 000000 1100 1000 This gives us a RID of 0xc8. If any one of the TypeDef, TypeRef or TypeSpec tables had more than 16383 rows (2^14 - 1), then 4 bytes would need to be used to represent all TypeDefOrRef coded tokens throughout the metadata tables. Lists The third representation we need to consider is 1-to-many references; each TypeDef refers to a list of FieldDef and MethodDef belonging to that type. If we were to specify every FieldDef and MethodDef individually then each TypeDef would be very large and a variable size, which isn't ideal. There is a way of specifying a list of references without explicitly specifying every item; if we order the MethodDef and FieldDef tables by the owning type, then the field list and method list in a TypeDef only have to be a single RID pointing at the first FieldDef or MethodDef belonging to that type; the end of the list can be inferred by the field list and method list RIDs of the next row in the TypeDef table. Going back to the TypeDef If we have a look back at the definition of a TypeDef, we end up with the following reprensentation for each row: Flags - always 4 bytes Name - a #Strings heap offset. Namespace - a #Strings heap offset. Extends - a TypeDefOrRef coded token. FieldList - a single RID to the FieldDef table. MethodList - a single RID to the MethodDef table. So, depending on the number of entries in the heaps and tables within the assembly, the rows in the TypeDef table can be as small as 14 bytes, or as large as 24 bytes. Now we've had a look at how information is encoded within the metadata tables, in the next post we can see how they are arranged on disk.

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• InnoDB Compression Improvements in MySQL 5.6

  - by Inaam Rana

  MySQL 5.6 comes with significant improvements for the compression support inside InnoDB. The enhancements that we'll talk about in this piece are also a good example of community contributions. The work on these was conceived, implemented and contributed by the engineers at Facebook. Before we plunge into the details let us familiarize ourselves with some of the key concepts surrounding InnoDB compression. In InnoDB compressed pages are fixed size. Supported sizes are 1, 2, 4, 8 and 16K. The compressed page size is specified at table creation time. InnoDB uses zlib for compression. InnoDB buffer pool will attempt to cache compressed pages like normal pages. However, whenever a page is actively used by a transaction, we'll always have the uncompressed version of the page as well i.e.: we can have a page in the buffer pool in compressed only form or in a state where we have both the compressed page and uncompressed version but we'll never have a page in uncompressed only form. On-disk we'll always only have the compressed page. When both compressed and uncompressed images are present in the buffer pool they are always kept in sync i.e.: changes are applied to both atomically. Recompression happens when changes are made to the compressed data. In order to minimize recompressions InnoDB maintains a modification log within a compressed page. This is the extra space available in the page after compression and it is used to log modifications to the compressed data thus avoiding recompressions. DELETE (and ROLLBACK of DELETE) and purge can be performed without recompressing the page. This is because the delete-mark bit and the system fields DB_TRX_ID and DB_ROLL_PTR are stored in uncompressed format on the compressed page. A record can be purged by shuffling entries in the compressed page directory. This can also be useful for updates of indexed columns, because UPDATE of a key is mapped to INSERT+DELETE+purge. A compression failure happens when we attempt to recompress a page and it does not fit in the fixed size. In such case, we first try to reorganize the page and attempt to recompress and if that fails as well then we split the page into two and recompress both pages. Now lets talk about the three major improvements that we made in MySQL 5.6.Logging of Compressed Page Images:InnoDB used to log entire compressed data on the page to the redo logs when recompression happens. This was an extra safety measure to guard against the rare case where an attempt is made to do recovery using a different zlib version from the one that was used before the crash. Because recovery is a page level operation in InnoDB we have to be sure that all recompress attempts must succeed without causing a btree page split. However, writing entire compressed data images to the redo log files not only makes the operation heavy duty but can also adversely affect flushing activity. This happens because redo space is used in a circular fashion and when we generate much more than normal redo we fill up the space much more quickly and in order to reuse the redo space we have to flush the corresponding dirty pages from the buffer pool.Starting with MySQL 5.6 a new global configuration parameter innodb_log_compressed_pages. The default value is true which is same as the current behavior. If you are sure that you are not going to attempt to recover from a crash using a different version of zlib then you should set this parameter to false. This is a dynamic parameter.Compression Level:You can now set the compression level that zlib should choose to compress the data. The global parameter is innodb_compression_level - the default value is 6 (the zlib default) and allowed values are 1 to 9. Again the parameter is dynamic i.e.: you can change it on the fly.Dynamic Padding to Reduce Compression Failures:Compression failures are expensive in terms of CPU. We go through the hoops of recompress, failure, reorganize, recompress, failure and finally page split. At the same time, how often we encounter compression failure depends largely on the compressibility of the data. In MySQL 5.6, courtesy of Facebook engineers, we have an adaptive algorithm based on per-index statistics that we gather about compression operations. The idea is that if a certain index/table is experiencing too many compression failures then we should try to pack the 16K uncompressed version of the page less densely i.e.: we let some space in the 16K page go unused in an attempt that the recompression won't end up in a failure. In other words, we dynamically keep adding 'pad' to the 16K page till we get compression failures within an agreeable range. It works the other way as well, that is we'll keep removing the pad if failure rate is fairly low. To tune the padding effort two configuration variables are exposed. innodb_compression_failure_threshold_pct: default 5, range 0 - 100,dynamic, implies the percentage of compress ops to fail before we start using to padding. Value 0 has a special meaning of disabling the padding. innodb_compression_pad_pct_max: default 50, range 0 - 75, dynamic, the  maximum percentage of uncompressed data page that can be reserved as pad.

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• To Bit or Not To Bit

  - by Johnm

  'Twas a long day of troubleshooting and firefighting and now, with most of the office vacant, you face a blank scripting window to create a new table in his database. Many questions circle your mind like dirty water gurgling down the bathtub drain: "How normalized should this table be?", "Should I use an identity column?", "NVarchar or Varchar?", "Should this column be NULLABLE?", "I wonder what apple blue cheese bacon cheesecake tastes like?" Well, there are times when the mind goes it's own direction. A Bit About Bit At some point during your table creation efforts you will encounter the decision of whether to use the bit data type for a column. The bit data type is an integer data type that recognizes only the values of 1, 0 and NULL as valid. This data type is often utilized to store yes/no or true/false values. An example of its use would be a column called [IsGasoline] which would be intended to contain the value of 1 if the row's subject (a car) had a gasoline engine and a 0 if the subject did not have a gasoline engine. The bit data type can even be found in some of the system tables of SQL Server. For example, the sysssispackages table in the msdb database which contains SQL Server Integration Services Package information for the packages stored in SQL Server. This table contains a column called [IsEncrypted]. A value of 1 indicates that the package has been encrypted while the value of 0 indicates that it is not. I have learned that the most effective way to disperse the crowd that surrounds the office coffee machine is to engage into SQL Server debates. The bit data type has been one of the most reoccurring, as well as the most enjoyable, of these topics. It contains a practical side and a philosophical side. Practical Consideration This data type certainly has its place and is a valuable option for database design; but it is often used in situations where the answer is really not a pure true/false response. In addition, true/false values are not very informative or scalable. Let's use the previously noted [IsGasoline] column for illustration. While on the surface it appears to be a rather simple question when evaluating a car: "Does the car have a gasoline engine?" If the person entering data is entering a row for a Jeep Liberty, the response would be a 1 since it has a gasoline engine. If the person is entering data is entering a row for a Chevrolet Volt, the response would be a 0 since it is an electric engine. What happens when a person is entering a row for the gasoline/electric hybrid Toyota Prius? Would one person's conclusion be consistent with another person's conclusion? The argument could be made that the current intent for the database is to be used only for pure gasoline and pure electric engines; but this is where the scalability issue comes into play. With the use of a bit data type a database modification and data conversion would be required if the business decided to take on hybrid engines. Whereas, alternatively, if the int data type were used as a foreign key to a reference table containing the engine type options, the change to include the hybrid option would only require an entry into the reference table. Philosophical Consideration Since the bit data type is often used for true/false or yes/no data (also called Boolean) it presents a philosophical conundrum of what to do about the allowance of the NULL value. The inclusion of NULL in a true/false or yes/no response simply violates the logical principle of bivalence which states that "every proposition is either true or false". If NULL is not true, then it must be false. The mathematical laws of Boolean logic support this concept by stating that the only valid values of this scenario are 1 and 0. There is another way to look at this conundrum: NULL is also considered to be the absence of a response. In other words, it is the equivalent to "undecided". Anyone who watches the news can tell you that polls always include an "undecided" option. This could be considered a valid option in the world of yes/no/dunno. Through out all of these considerations I have discovered one absolute certainty: When you have found a person, or group of persons, who are willing to entertain a philosophical debate of the bit data type, you have found some true friends.

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• Upgrading Agent Controllers in Oracle Enterprise Manager Ops Center 12c

  - by S Stelting

  Oracle Enterprise Manager Ops Center 12c recently released an upgrade for Solaris Agent Controllers. In this week's blog post, we'll show you how to upgrade agent controllers. Detailed instructions about upgrading Agent Controllers are available in the product documentation here. This blog post uses an Enterprise Controller which is configured for connected mode operation. If you'd like to apply the agent update in a disconnected installation, additional instructions are available here. Step 1: Download Agent Controller Updates With a connected mode Ops Center installation, you can check for product updates at any time by selecting the Enterprise Controller from the left-hand Administration navigation tab. Select the right-hand Action link “Ops Center Downloads” to open a pop-up dialog displaying any new product updates. In this example, the Enterprise Controller has already been upgraded to the latest version (Update 1, also shown as build version 2076) so only the Agent Controller updates will appear. There are three updates available: one for Solaris 10 X86, one for Solaris 8-10 SPARC, and one for all versions of Solaris 11. Note that the last update in the screen shot is the Solaris 11 update; for details on any of the downloads, place your mouse over the information icon under the details column for a pop-up text region. Select the software to download and click the Next button to display the Ops Center license agreement. Review and click the check box to accept the license agreement, then click the Next button to begin downloading the software. The status screen shows the current download status. If desired, you can perform the downloads as a background job. Simply click the check box, then click the next button to proceed to the summary screen. The summary screen shows the updates to be downloaded as well as the current status. Clicking the Finish button will close the dialog and return to the Browser UI. The download job will continue to run in Ops Center and progress can still be viewed from the jobs menu at the bottom of the browser window. Step 2: Check the Version of Existing Agent Controllers After the download job completes, you can check the availability of agent updates as well as the current versions of your Agent Controllers from the left-hand Assets navigation tab. Select “Operating Systems” from the pull-down tab lets to display only OS assets. Next, select “Solaris” in the left-hand tab to display the Solaris assets. Finally, select the Summary tab in the center display panel to show which versions of agent controllers are installed in your data center. Notice that a few of the OS assets are not displayed in the Agent Controllers tab. Ops Center will not display OS instances which do not have an Agent Controller installation. This includes Enterprise Controllers and Proxy Controllers (unless the agent has been activated on the OS instance) and and OS instances using agentless management. For Agent Controllers which support an update, the version of agent software (in this example, 2083) appears to the right of the currently installed version. Step 3: Upgrade Your Agent Controllers If desired, you can upgrade agent controllers from the previous screen by selecting the desired systems and clicking the upgrade button. Alternatively, you can click the link “Upgrade All Agent Controllers” in the right-hand Actions menu: In either case, a pop-up dialog lets you start the upgrade process. The first screen in the dialog lets you choose the upgrade method: Ops Center provides three ways to upgrade agent controllers: Automatic Upgrade: If Agent Controllers are running on all assets, Ops Center can automatically upgrade the software to the latest version without requiring any login credentials to the system SSH using a single set of credentials: If all assets use the same login credentials, you can apply a single set to all assets for the upgrade process. The log-in credentials are the same ones used for asset discovery and management, which are stored in the Plan Management navigation tab under Credentials. SSH using individual credentials: If assets use different login credentials, you can select a different set for each asset. After selecting the upgrade method, click the Next button to proceed to the summary screen. Click the Finish button to close the pop-up dialog and start the upgrade job for the agent controllers. The upgrade job runs a series of tasks in parallel, and will upgrade all agents which have been selected. Once the job completes, the OS instances in your data center will be upgraded and running the latest version of Agent Controller software.

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• FAQ: Highlight GridView Row on Click and Retain Selected Row on Postback

  - by Vincent Maverick Durano

  A couple of months ago I’ve written a simple demo about “Highlighting GridView Row on MouseOver”. I’ve noticed many members in the forums (http://forums.asp.net) are asking how to highlight row in GridView and retain the selected row across postbacks. So I’ve decided to write this post to demonstrate how to implement it as reference to others who might need it. In this demo I going to use a combination of plain JavaScript and jQuery to do the client-side manipulation. I presumed that you already know how to bind the grid with data because I will not include the codes for populating the GridView here. For binding the gridview you can refer this post: Binding GridView with Data the ADO.Net way or this one: GridView Custom Paging with LINQ. To get started let’s implement the highlighting of GridView row on row click and retain the selected row on postback.  For simplicity I set up the page like this: <asp:Content ID="Content2" ContentPlaceHolderID="MainContent" runat="server"> <h2>You have selected Row: (<asp:Label ID="Label1" runat="server" />)</h2> <asp:HiddenField ID="hfCurrentRowIndex" runat="server"></asp:HiddenField> <asp:HiddenField ID="hfParentContainer" runat="server"></asp:HiddenField> <asp:Button ID="Button1" runat="server" onclick="Button1_Click" Text="Trigger Postback" /> <asp:GridView ID="grdCustomer" runat="server" AutoGenerateColumns="false" onrowdatabound="grdCustomer_RowDataBound"> <Columns> <asp:BoundField DataField="Company" HeaderText="Company" /> <asp:BoundField DataField="Name" HeaderText="Name" /> <asp:BoundField DataField="Title" HeaderText="Title" /> <asp:BoundField DataField="Address" HeaderText="Address" /> </Columns> </asp:GridView> </asp:Content>   Note: Since the action is done at the client-side, when we do a postback like (clicking on a button) the page will be re-created and you will lose the highlighted row. This is normal because the the server doesn't know anything about the client/browser not unless if you do something to notify the server that something has changed. To persist the settings we will use some HiddenFields control to store the data so that when it postback we can reference the value from there. Now here’s the JavaScript functions below: <asp:content id="Content1" runat="server" contentplaceholderid="HeadContent"> <script src="http://ajax.googleapis.com/ajax/libs/jquery/1.4/jquery.min.js" type="text/javascript"></script> <script type="text/javascript">       var prevRowIndex;       function ChangeRowColor(row, rowIndex) {           var parent = document.getElementById(row);           var currentRowIndex = parseInt(rowIndex) + 1;                 if (prevRowIndex == currentRowIndex) {               return;           }           else if (prevRowIndex != null) {               parent.rows[prevRowIndex].style.backgroundColor = "#FFFFFF";           }                 parent.rows[currentRowIndex].style.backgroundColor = "#FFFFD6";                 prevRowIndex = currentRowIndex;                 $('#<%= Label1.ClientID %>').text(currentRowIndex);                 $('#<%= hfParentContainer.ClientID %>').val(row);           $('#<%= hfCurrentRowIndex.ClientID %>').val(rowIndex);       }             $(function () {           RetainSelectedRow();       });             function RetainSelectedRow() {           var parent = $('#<%= hfParentContainer.ClientID %>').val();           var currentIndex = $('#<%= hfCurrentRowIndex.ClientID %>').val();           if (parent != null) {               ChangeRowColor(parent, currentIndex);           }       }          </script> </asp:content>   The ChangeRowColor() is the function that sets the background color of the selected row. It is also where we set the previous row and rowIndex values in HiddenFields.  The $(function(){}); is a short-hand for the jQuery document.ready event. This event will be fired once the page is posted back to the server that’s why we call the function RetainSelectedRow(). The RetainSelectedRow() function is where we referenced the current selected values stored from the HiddenFields and pass these values to the ChangeRowColor() function to retain the highlighted row. Finally, here’s the code behind part: protected void grdCustomer_RowDataBound(object sender, GridViewRowEventArgs e) { if (e.Row.RowType == DataControlRowType.DataRow) { e.Row.Attributes.Add("onclick", string.Format("ChangeRowColor('{0}','{1}');", e.Row.ClientID, e.Row.RowIndex)); } } The code above is responsible for attaching the javascript onclick event for each row and call the ChangeRowColor() function and passing the e.Row.ClientID and e.Row.RowIndex to the function. Here’s the sample output below:   That’s it! I hope someone find this post useful! Technorati Tags: jQuery,GridView,JavaScript,TipTricks

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• Working with packed dates in SSIS

  - by Jim Giercyk

  One of the challenges recently thrown my way was to read an EBCDIC flat file, decode packed dates, and insert the dates into a SQL table.  For those unfamiliar with packed data, it is a way to store data at the nibble level (half a byte), and was often used by mainframe programmers to conserve storage space.  In the case of my input file, the dates were 2 bytes long and  represented the number of days that have past since 01/01/1950.  My first thought was, in the words of Scooby, Hmmmmph?  But, I love a good challenge, so I dove in. Reading in the flat file was rather simple.  The only difference between reading an EBCDIC and an ASCII file is the Code Page option in the connection manager.  In my case, I needed to use Code Page 1140 for EBCDIC (I could have also used Code Page 37).       Once the code page is set correctly, SSIS can understand what it is reading and it will convert the output to the default code page, 1252.  However, packed data is either unreadable or produces non-alphabetic characters, as we can see in the preview window.   Column 1 is actually the packed date, columns 0 and 2 are the values in the rest of the file.  We are only interested in Column 1, which is a 2 byte field representing a packed date.  We know that 2 bytes of packed data can be stored in 1 byte of character data, so we are working with 4 packed digits in 2 character bytes.  If you are confused, stay tuned….this will make sense in a minute.   Right-click on your Flat File Source shape and select “Show Advanced Editor”. Here is where the magic begins. By changing the properties of the output columns, we can access the packed digits from each byte. By default, the Output Column data type is DT_STR. Since we want to look at the bytes individually and not the entire string, change the data type to DT_BYTES. Next, and most important, set UseBinaryFormat to TRUE. This will write the HEX VALUES of the output string instead of writing the character values.  Now we are getting somewhere! Next, you will need to use a Data Conversion shape in your Data Flow to transform the 2 position byte stream to a 4 position Unicode string containing the packed data.  You need the string to be 4 bytes long because it will contain the 4 packed digits.  Here is what that should look like in the Data Conversion shape: Direct the output of your data flow to a test table or file to see the results.  In my case, I created a test table.  The results looked like this:     Hold on a second!  That doesn't look like a date at all.  No, of course not.  It is a hex number which represents the days which have passed between 01/01/1950 and the date.  We have to convert the Hex value to a decimal value, and use the DATEADD function to get a date value.  Luckily, I have created a function to convert Hex to Decimal:   -- ============================================= -- Author:        Jim Giercyk -- Create date: March, 2012 -- Description:    Converts a Hex string to a decimal value -- ============================================= CREATE FUNCTION [dbo].[ftn_HexToDec] (     @hexValue NVARCHAR(6) ) RETURNS DECIMAL AS BEGIN     -- Declare the return variable here DECLARE @decValue DECIMAL IF @hexValue LIKE '0x%' SET @hexValue = SUBSTRING(@hexValue,3,4) DECLARE @decTab TABLE ( decPos1 VARCHAR(2), decPos2 VARCHAR(2), decPos3 VARCHAR(2), decPos4 VARCHAR(2) ) DECLARE @pos1 VARCHAR(1) = SUBSTRING(@hexValue,1,1) DECLARE @pos2 VARCHAR(1) = SUBSTRING(@hexValue,2,1) DECLARE @pos3 VARCHAR(1) = SUBSTRING(@hexValue,3,1) DECLARE @pos4 VARCHAR(1) = SUBSTRING(@hexValue,4,1) INSERT @decTab VALUES (CASE               WHEN @pos1 = 'A' THEN '10'                 WHEN @pos1 = 'B' THEN '11'               WHEN @pos1 = 'C' THEN '12'               WHEN @pos1 = 'D' THEN '13'               WHEN @pos1 = 'E' THEN '14'               WHEN @pos1 = 'F' THEN '15'               ELSE @pos1              END, CASE               WHEN @pos2 = 'A' THEN '10'                 WHEN @pos2 = 'B' THEN '11'               WHEN @pos2 = 'C' THEN '12'               WHEN @pos2 = 'D' THEN '13'               WHEN @pos2 = 'E' THEN '14'               WHEN @pos2 = 'F' THEN '15'               ELSE @pos2              END, CASE               WHEN @pos3 = 'A' THEN '10'                 WHEN @pos3 = 'B' THEN '11'               WHEN @pos3 = 'C' THEN '12'               WHEN @pos3 = 'D' THEN '13'               WHEN @pos3 = 'E' THEN '14'               WHEN @pos3 = 'F' THEN '15'               ELSE @pos3              END, CASE               WHEN @pos4 = 'A' THEN '10'                 WHEN @pos4 = 'B' THEN '11'               WHEN @pos4 = 'C' THEN '12'               WHEN @pos4 = 'D' THEN '13'               WHEN @pos4 = 'E' THEN '14'               WHEN @pos4 = 'F' THEN '15'               ELSE @pos4              END) SET @decValue = (CONVERT(INT,(SELECT decPos4 FROM @decTab)))         +                 (CONVERT(INT,(SELECT decPos3 FROM @decTab))*16)      +                 (CONVERT(INT,(SELECT decPos2 FROM @decTab))*(16*16)) +                 (CONVERT(INT,(SELECT decPos1 FROM @decTab))*(16*16*16))     RETURN @decValue END GO     Making use of the function, I found the decimal conversion, added that number of days to 01/01/1950 and FINALLY arrived at my “unpacked relative date”.  Here is the query I used to retrieve the formatted date, and the result set which was returned: SELECT [packedDate] AS 'Hex Value',        dbo.ftn_HexToDec([packedDate]) AS 'Decimal Value',        CONVERT(DATE,DATEADD(day,dbo.ftn_HexToDec([packedDate]),'01/01/1950'),101) AS 'Relative String Date'   FROM [dbo].[Output Table]         This technique can be used any time you need to retrieve the hex value of a character string in SSIS.  The date example may be a bit difficult to understand at first, but with SSIS becoming the preferred tool for enterprise level integration for many companies, there is no doubt that developers will encounter these types of requirements with regularity in the future. Please feel free to contact me if you have any questions.

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• XNA: Huge Tile Map, long load times

  - by Zach

  Recently I built a tile map generator for a game project. What I am very proud of is that I finally got it to the point where I can have a GIANT 2D map build perfectly on my PC. About 120000pixels by 40000 pixels. I can go larger actually, but I have only 1 draw back. #1 ram, the map currently draws about 320MB of ram and I know the Xbox allows 512MB I think? #2 It takes 20 mins for the map to build then display on the Xbox, on my PC it take less then a few seconds. I need to bring that 20 minutes of generating from 20 mins to how ever little bit I can, and how can a lower the amount of RAM usage while still being able to generate my map. Right now everything is stored in Jagged Arrays, each piece generating in a size of 1280x720 (the mother piece). Up to the amount that I need, every block is exactly 40x40 pixels however the blocks get removed from a List or regenerated in a List depending how close the mother piece is to the player. Saving A LOT of CPU, so at all times its no more then looping through 5184 some blocks. Well at least I'm sure of this. But how can I lower my RAM usage without hurting the size of the map, and how can I lower these INSANE loading times? EDIT: Let me explain my self better. Also I'd like to let everyone know now that I'm inexperienced with many of these things. So here is an example of the arrays I'm using. Here is the overall in a shorter term: int[][] array = new int[30][]; array[0] = new int[] { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 }; array[1] = new int[] { 1, 3, 3, 3, 3, 1, 0, 0, 0, 0, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 }; that goes on for around 30 arrays downward. Now for every time it hits a 1, it goes and generates a tile map 1280x720 and it does that exactly the way it does it above. This is how I loop through those arrays: for (int i = 0; i < array.Length; i += 1) { for (int h = 0; h < array[i].Length; h += 1) { } { Now how the tiles are drawn and removed is something like this: public void Draw(SpriteBatch spriteBatch, Vector2 cam) { if (cam.X >= this.Position.X - 1280) { if (cam.X <= this.Position.X + 2560) { if (cam.Y >= this.Position.Y - 720) { if (cam.Y <= this.Position.Y + 1440) { if (visible) { if (once == 0) { once = 1; visible = false; regen(); } } for (int i = Tiles.Count - 1; i >= 0; i--) { Tiles[i].Draw(spriteBatch, cam); } for (int i = unWalkTiles.Count - 1; i >= 0; i--) { unWalkTiles[i].Draw(spriteBatch, cam); } } else { once = 0; for (int i = Tiles.Count - 1; i >= 0; i--) { Tiles.RemoveAt(i); } for (int i = unWalkTiles.Count - 1; i >= 0; i--) { unWalkTiles.RemoveAt(i); } } } else { once = 0; for (int i = Tiles.Count - 1; i >= 0; i--) { Tiles.RemoveAt(i); } for (int i = unWalkTiles.Count - 1; i >= 0; i--) { unWalkTiles.RemoveAt(i); } } } else { once = 0; for (int i = Tiles.Count - 1; i >= 0; i--) { Tiles.RemoveAt(i); } for (int i = unWalkTiles.Count - 1; i >= 0; i--) { unWalkTiles.RemoveAt(i); } } } else { once = 0; for (int i = Tiles.Count - 1; i >= 0; i--) { Tiles.RemoveAt(i); } for (int i = unWalkTiles.Count - 1; i >= 0; i--) { unWalkTiles.RemoveAt(i); } } } } If you guys still need more information just ask in the comments.

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