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  • How do I efficiently write a "toggle database value" function in AJAX?

    - by AmbroseChapel
    Say I have a website which shows the user ten images and asks them to categorise each image by clicking on buttons. A button for "funny", a button for "scary", a button for "pretty" and so on. These buttons aren't exclusive. A picture can be both funny and scary. The user clicks the "funny" button. An AJAX request is sent off to the database to mark that image as funny. The "funny" button lights up, by assigning a class in the DOM to mark it as "on". But the user made a mistake. They meant to hit the next button over. They should click "funny" again to turn it off, right? At this point I'm not sure whats the most efficient way to proceed. The database knows that the "funny" flag is set, but it's inefficient to query the database every time a button is clicked to say, is this flag set or not, then go on with a second database call to toggle it. Should I infer the state of the database flag from the DOM, i.e. if that button has the class "on" then the flag must be set, and branch at that point? Or would it be better to have a data structure in Javascript in the page which duplicates the state of each image in the database, so that every time I set the database flag to true, I also set the value in the Javascript data to true and so on?

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  • Do I need a spatial index in my database?

    - by Sanoj
    I am designing an application that needs to save geometric shapes in a database. I haven't choosen the database management system yet. In my application, all database queries will have an bounding box as input, and as output I want all shapes within that database. I know that databases with a spatial index is used for this kind of application. But in my application there will not be any queries of type "give me objects nearby x/y" or other more complex queries that are useful in a GIS application. I am planning of having a database without a spatial index and have queries looking like: SELECT * FROM shapes WHERE x < max_x AND x > min_x AND y < max_y AND y > min_y And have an index on the columns x (double) and y (double). As long I can see, I don't really need a database with an spatial index, howsoever my application is close to that kind of applications. And even if I would like to have nearby queries, then I could create a big enough bounding box around that point. Or will this lead to poor performance? Do I really need a spatial database? And when is a spatial index needed?

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  • VLOOKUP in Excel, part 2: Using VLOOKUP without a database

    - by Mark Virtue
    In a recent article, we introduced the Excel function called VLOOKUP and explained how it could be used to retrieve information from a database into a cell in a local worksheet.  In that article we mentioned that there were two uses for VLOOKUP, and only one of them dealt with querying databases.  In this article, the second and final in the VLOOKUP series, we examine this other, lesser known use for the VLOOKUP function. If you haven’t already done so, please read the first VLOOKUP article – this article will assume that many of the concepts explained in that article are already known to the reader. When working with databases, VLOOKUP is passed a “unique identifier” that serves to identify which data record we wish to find in the database (e.g. a product code or customer ID).  This unique identifier must exist in the database, otherwise VLOOKUP returns us an error.  In this article, we will examine a way of using VLOOKUP where the identifier doesn’t need to exist in the database at all.  It’s almost as if VLOOKUP can adopt a “near enough is good enough” approach to returning the data we’re looking for.  In certain circumstances, this is exactly what we need. We will illustrate this article with a real-world example – that of calculating the commissions that are generated on a set of sales figures.  We will start with a very simple scenario, and then progressively make it more complex, until the only rational solution to the problem is to use VLOOKUP.  The initial scenario in our fictitious company works like this:  If a salesperson creates more than $30,000 worth of sales in a given year, the commission they earn on those sales is 30%.  Otherwise their commission is only 20%.  So far this is a pretty simple worksheet: To use this worksheet, the salesperson enters their sales figures in cell B1, and the formula in cell B2 calculates the correct commission rate they are entitled to receive, which is used in cell B3 to calculate the total commission that the salesperson is owed (which is a simple multiplication of B1 and B2). The cell B2 contains the only interesting part of this worksheet – the formula for deciding which commission rate to use: the one below the threshold of $30,000, or the one above the threshold.  This formula makes use of the Excel function called IF.  For those readers that are not familiar with IF, it works like this: IF(condition,value if true,value if false) Where the condition is an expression that evaluates to either true or false.  In the example above, the condition is the expression B1<B5, which can be read as “Is B1 less than B5?”, or, put another way, “Are the total sales less than the threshold”.  If the answer to this question is “yes” (true), then we use the value if true parameter of the function, namely B6 in this case – the commission rate if the sales total was below the threshold.  If the answer to the question is “no” (false), then we use the value if false parameter of the function, namely B7 in this case – the commission rate if the sales total was above the threshold. As you can see, using a sales total of $20,000 gives us a commission rate of 20% in cell B2.  If we enter a value of $40,000, we get a different commission rate: So our spreadsheet is working. Let’s make it more complex.  Let’s introduce a second threshold:  If the salesperson earns more than $40,000, then their commission rate increases to 40%: Easy enough to understand in the real world, but in cell B2 our formula is getting more complex.  If you look closely at the formula, you’ll see that the third parameter of the original IF function (the value if false) is now an entire IF function in its own right.  This is called a nested function (a function within a function).  It’s perfectly valid in Excel (it even works!), but it’s harder to read and understand. We’re not going to go into the nuts and bolts of how and why this works, nor will we examine the nuances of nested functions.  This is a tutorial on VLOOKUP, not on Excel in general. Anyway, it gets worse!  What about when we decide that if they earn more than $50,000 then they’re entitled to 50% commission, and if they earn more than $60,000 then they’re entitled to 60% commission? Now the formula in cell B2, while correct, has become virtually unreadable.  No-one should have to write formulae where the functions are nested four levels deep!  Surely there must be a simpler way? There certainly is.  VLOOKUP to the rescue! Let’s redesign the worksheet a bit.  We’ll keep all the same figures, but organize it in a new way, a more tabular way: Take a moment and verify for yourself that the new Rate Table works exactly the same as the series of thresholds above. Conceptually, what we’re about to do is use VLOOKUP to look up the salesperson’s sales total (from B1) in the rate table and return to us the corresponding commission rate.  Note that the salesperson may have indeed created sales that are not one of the five values in the rate table ($0, $30,000, $40,000, $50,000 or $60,000).  They may have created sales of $34,988.  It’s important to note that $34,988 does not appear in the rate table.  Let’s see if VLOOKUP can solve our problem anyway… We select cell B2 (the location we want to put our formula), and then insert the VLOOKUP function from the Formulas tab: The Function Arguments box for VLOOKUP appears.  We fill in the arguments (parameters) one by one, starting with the Lookup_value, which is, in this case, the sales total from cell B1.  We place the cursor in the Lookup_value field and then click once on cell B1: Next we need to specify to VLOOKUP what table to lookup this data in.  In this example, it’s the rate table, of course.  We place the cursor in the Table_array field, and then highlight the entire rate table – excluding the headings: Next we must specify which column in the table contains the information we want our formula to return to us.  In this case we want the commission rate, which is found in the second column in the table, so we therefore enter a 2 into the Col_index_num field: Finally we enter a value in the Range_lookup field. Important:  It is the use of this field that differentiates the two ways of using VLOOKUP.  To use VLOOKUP with a database, this final parameter, Range_lookup, must always be set to FALSE, but with this other use of VLOOKUP, we must either leave it blank or enter a value of TRUE.  When using VLOOKUP, it is vital that you make the correct choice for this final parameter. To be explicit, we will enter a value of true in the Range_lookup field.  It would also be fine to leave it blank, as this is the default value: We have completed all the parameters.  We now click the OK button, and Excel builds our VLOOKUP formula for us: If we experiment with a few different sales total amounts, we can satisfy ourselves that the formula is working. Conclusion In the “database” version of VLOOKUP, where the Range_lookup parameter is FALSE, the value passed in the first parameter (Lookup_value) must be present in the database.  In other words, we’re looking for an exact match. But in this other use of VLOOKUP, we are not necessarily looking for an exact match.  In this case, “near enough is good enough”.  But what do we mean by “near enough”?  Let’s use an example:  When searching for a commission rate on a sales total of $34,988, our VLOOKUP formula will return us a value of 30%, which is the correct answer.  Why did it choose the row in the table containing 30% ?  What, in fact, does “near enough” mean in this case?  Let’s be precise: When Range_lookup is set to TRUE (or omitted), VLOOKUP will look in column 1 and match the highest value that is not greater than the Lookup_value parameter. It’s also important to note that for this system to work, the table must be sorted in ascending order on column 1! If you would like to practice with VLOOKUP, the sample file illustrated in this article can be downloaded from here. Similar Articles Productive Geek Tips Using VLOOKUP in ExcelImport Microsoft Access Data Into ExcelImport an Access Database into ExcelCopy a Group of Cells in Excel 2007 to the Clipboard as an ImageShare Access Data with Excel in Office 2010 TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips DVDFab 6 Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 Quickly Schedule Meetings With NeedtoMeet Share Flickr Photos On Facebook Automatically Are You Blocked On Gtalk? Find out Discover Latest Android Apps On AppBrain The Ultimate Guide For YouTube Lovers Will it Blend? iPad Edition

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  • SQL SERVER – 3 Online SQL Courses at Pluralsight and Free Learning Resources

    - by pinaldave
    Usain Bolt is an inspiration for all. He broke his own record multiple times because he wanted to do better! Read more about him on wikipedia. He is great and indeed fastest man on the planet. Usain Bolt – World’s Fastest Man “Can you teach me SQL Server Performance Tuning?” This is one of the most popular questions which I receive all the time. The answer is YES. I would love to do performance tuning training for anyone, anywhere.  It is my favorite thing to do, and it is my favorite thing to train others in.  If possible, I would love to do training 24 hours a day, 7 days a week, 365 days a year.  To me, it doesn’t feel like a job. Of course, as much as I would love to do performance tuning 24/7/365, obviously I am just one human being and can only be in one place t one time.  It is also very difficult to train more than one person at a time, and it is difficult to train two or more people at a time, especially when the two people are at different levels.  I am also limited by geography.  I live in India, and adjust to my own time zone.  Trying to teach a live course from India to someone whose time zone is 12 or more hours off of mine is very difficult.  If I am trying to teach at 2 am, I am sure I am not at my best! There was only one solution to scale – Online Trainings. I have built 3 different courses on SQL Server Performance Tuning with Pluralsight. Now I have no problem – I am 100% scalable and available 24/7 and 365. You can make me say the same things again and again till you find it right. I am in your mobile, PC as well as on XBOX. This is why I am such a big fan of online courses.  I have recorded many performance tuning classes and you can easily access them online, at your own time.  And don’t think that just because these aren’t live classes you won’t be able to get any feedback from me.  I encourage all my viewers to go ahead and ask me questions by e-mail, Twitter, Facebook, or whatever way you can get a hold of me. Here are details of three of my courses with Pluralsight. I suggest you go over the description of the course. As an author of the course, I have few FREE codes for watching the free courses. Please leave a comment with your valid email address, I will send a few of them to random winners. SQL Server Performance: Introduction to Query Tuning  SQL Server performance tuning is an art to master – for developers and DBAs alike. This course takes a systematic approach to planning, analyzing, debugging and troubleshooting common query-related performance problems. This includes an introduction to understanding execution plans inside SQL Server. In this almost four hour course we cover following important concepts. Introduction 10:22 Execution Plan Basics 45:59 Essential Indexing Techniques 20:19 Query Design for Performance 50:16 Performance Tuning Tools 01:15:14 Tips and Tricks 25:53 Checklist: Performance Tuning 07:13 The duration of each module is mentioned besides the name of the module. SQL Server Performance: Indexing Basics This course teaches you how to master the art of performance tuning SQL Server by better understanding indexes. In this almost two hour course we cover following important concepts. Introduction 02:03 Fundamentals of Indexing 22:21 Practical Indexing Implementation Techniques 37:25 Index Maintenance 16:33 Introduction to ColumnstoreIndex 08:06 Indexing Practical Performance Tips and Tricks 24:56 Checklist : Index and Performance 07:29 The duration of each module is mentioned besides the name of the module. SQL Server Questions and Answers This course is designed to help you better understand how to use SQL Server effectively. The course presents many of the common misconceptions about SQL Server, and then carefully debunks those misconceptions with clear explanations and short but compelling demos, showing you how SQL Server really works. In this almost 2 hours and 15 minutes course we cover following important concepts. Introduction 00:54 Retrieving IDENTITY value using @@IDENTITY 08:38 Concepts Related to Identity Values 04:15 Difference between WHERE and HAVING 05:52 Order in WHERE clause 07:29 Concepts Around Temporary Tables and Table Variables 09:03 Are stored procedures pre-compiled? 05:09 UNIQUE INDEX and NULLs problem 06:40 DELETE VS TRUNCATE 06:07 Locks and Duration of Transactions 15:11 Nested Transaction and Rollback 09:16 Understanding Date/Time Datatypes 07:40 Differences between VARCHAR and NVARCHAR datatypes 06:38 Precedence of DENY and GRANT security permissions 05:29 Identify Blocking Process 06:37 NULLS usage with Dynamic SQL 08:03 Appendix Tips and Tricks with Tools 20:44 The duration of each module is mentioned besides the name of the module. SQL in Sixty Seconds You will have to login and to get subscribed to the courses to view them. Here are my free video learning resources SQL in Sixty Seconds. These are 60 second video which I have built on various subjects related to SQL Server. Do let me know what you think about them? Here are three of my latest videos: Identify Most Resource Intensive Queries – SQL in Sixty Seconds #028 Copy Column Headers from Resultset – SQL in Sixty Seconds #027 Effect of Collation on Resultset – SQL in Sixty Seconds #026 You can watch and learn at your own pace.  Then you can easily ask me any questions you have.  E-mail is easiest, but for really tough questions I’m willing to talk on Skype, Gtalk, or even Facebook chat.  Please do watch and then talk with me, I am always available on the internet! Here is the video of the world’s fastest man.Usain St. Leo Bolt inspires us that we all do better than best. We can go the next level of our own record. We all can improve if we have a will and dedication.  Watch the video from 5:00 mark. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQL Training, SQLServer, T SQL, Technology, Video

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  • ODI - Creating a Repository in a 12c Pluggable Database

    - by David Allan
    To install ODI 11g into an Oracle 12c pluggable database, one way is to connect using a TNS string to the pluggable database service that is executing. For example when I installed my master repository, I used a JDBC URL such as; jdbc:oracle:thin:@(DESCRIPTION=(ADDRESS_LIST=(ADDRESS=(PROTOCOL=TCP)(HOST=mydbserver)(PORT=1522)))(CONNECT_DATA=(SERVER=DEDICATED)(SERVICE_NAME=PDBORA12.US.ORACLE.COM)))   I used the above approach rather than the host:port:sid which is a common mechanism many users use to quickly get up and going. Below you can see the repository creation wizard in action, I used the 11g release and simply installed the master and work repository into my pluggable database. Be wise with your repository IDs, I simply used the default, but you should be aware that these are key in larger deployments. The database in 12c has much more tighter control on users and resources, so just getting the user creating with sufficient resource on tablespaces etc in 12c was a little more work. Once you have the repositories up and running, then the fun starts using the 12c features. More to come.

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  • SQL SERVER – Weekly Series – Memory Lane – #035

    - by Pinal Dave
    Here is the list of selected articles of SQLAuthority.com across all these years. Instead of just listing all the articles I have selected a few of my most favorite articles and have listed them here with additional notes below it. Let me know which one of the following is your favorite article from memory lane. 2007 Row Overflow Data Explanation  In SQL Server 2005 one table row can contain more than one varchar(8000) fields. One more thing, the exclusions has exclusions also the limit of each individual column max width of 8000 bytes does not apply to varchar(max), nvarchar(max), varbinary(max), text, image or xml data type columns. Comparison Index Fragmentation, Index De-Fragmentation, Index Rebuild – SQL SERVER 2000 and SQL SERVER 2005 An old but like a gold article. Talks about lots of concepts related to Index and the difference from earlier version to the newer version. I strongly suggest that everyone should read this article just to understand how SQL Server has moved forward with the technology. Improvements in TempDB SQL Server 2005 had come up with quite a lots of improvements and this blog post describes them and explains the same. If you ask me what is my the most favorite article from early career. I must point out to this article as when I wrote this one I personally have learned a lot of new things. Recompile All The Stored Procedure on Specific TableI prefer to recompile all the stored procedure on the table, which has faced mass insert or update. sp_recompiles marks stored procedures to recompile when they execute next time. This blog post explains the same with the help of a script.  2008 SQLAuthority Download – SQL Server Cheatsheet You can download and print this cheat sheet and use it for your personal reference. If you have any suggestions, please let me know and I will see if I can update this SQL Server cheat sheet. Difference Between DBMS and RDBMS What is the difference between DBMS and RDBMS? DBMS – Data Base Management System RDBMS – Relational Data Base Management System or Relational DBMS High Availability – Hot Add Memory Hot Add CPU and Hot Add Memory are extremely interesting features of the SQL Server, however, personally I have not witness them heavily used. These features also have few restriction as well. I blogged about them in detail. 2009 Delete Duplicate Rows I have demonstrated in this blog post how one can identify and delete duplicate rows. Interesting Observation of Logon Trigger On All Servers – Solution The question I put forth in my previous article was – In single login why the trigger fires multiple times; it should be fired only once. I received numerous answers in thread as well as in my MVP private news group. Now, let us discuss the answer for the same. The answer is – It happens because multiple SQL Server services are running as well as intellisense is turned on. Blog post demonstrates how we can do the same with the help of SQL scripts. Management Studio New Features I have selected my favorite 5 features and blogged about it. IntelliSense for Query Editing Multi Server Query Query Editor Regions Object Explorer Enhancements Activity Monitors Maximum Number of Index per Table One of the questions I asked in my user group was – What is the maximum number of Index per table? I received lots of answers to this question but only two answers are correct. Let us now take a look at them in this blog post. 2010 Default Statistics on Column – Automatic Statistics on Column The truth is, Statistics can be in a table even though there is no Index in it. If you have the auto- create and/or auto-update Statistics feature turned on for SQL Server database, Statistics will be automatically created on the Column based on a few conditions. Please read my previously posted article, SQL SERVER – When are Statistics Updated – What triggers Statistics to Update, for the specific conditions when Statistics is updated. 2011 T-SQL Scripts to Find Maximum between Two Numbers In this blog post there are two different scripts listed which demonstrates way to find the maximum number between two numbers. I need your help, which one of the script do you think is the most accurate way to find maximum number? Find Details for Statistics of Whole Database – DMV – T-SQL Script I was recently asked is there a single script which can provide all the necessary details about statistics for any database. This question made me write following script. I was initially planning to use sp_helpstats command but I remembered that this is marked to be deprecated in future. 2012 Introduction to Function SIGN SIGN Function is very fundamental function. It will return the value 1, -1 or 0. If your value is negative it will return you negative -1 and if it is positive it will return you positive +1. Let us start with a simple small example. Template Browser – A Very Important and Useful Feature of SSMS Templates are like a quick cheat sheet or quick reference. Templates are available to create objects like databases, tables, views, indexes, stored procedures, triggers, statistics, and functions. Templates are also available for Analysis Services as well. The template scripts contain parameters to help you customize the code. You can Replace Template Parameters dialog box to insert values into the script. An invalid floating point operation occurred If you run any of the above functions they will give you an error related to invalid floating point. Honestly there is no workaround except passing the function appropriate values. SQRT of a negative number will give you result in real numbers which is not supported at this point of time as well LOG of a negative number is not possible (because logarithm is the inverse function of an exponential function and the exponential function is NEVER negative). Validating Spatial Object with IsValidDetailed Function SQL Server 2012 has introduced the new function IsValidDetailed(). This function has made my life very easy. In simple words, this function will check if the spatial object passed is valid or not. If it is valid it will give information that it is valid. If the spatial object is not valid it will return the answer that it is not valid and the reason for the same. This makes it very easy to debug the issue and make the necessary correction. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Memory Lane, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Database Developers Can Now Save 20%

    - by stephen.garth
    Database developers can now increase productivity and save money at the same time. For a limited time, Oracle Store is offering a 20% discount on Oracle SQL Developer Data Modeler. Just enter the code SQLDDM at checkout to get the discount. Oracle SQL Developer Data Modeler is an independent, standalone product with a full spectrum of data and database modeling tools and utilities, including modeling for Entity Relationship Diagrams (ERD), Relational (database design), Data Type and Multi-dimensional modeling, full forward and reverse engineering and DDL code generation. SQL Developer Data Modeler can connect to any supported Oracle Database and is platform independent. Save 20% on Oracle SQL Developer Data Modeler at Oracle Store - Discount Code SQLDDM Find out more about Oracle SQL Developer and Oracle SQL Developer Data Modeler var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www."); document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E")); try { var pageTracker = _gat._getTracker("UA-13185312-1"); pageTracker._trackPageview(); } catch(err) {}

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  • HealthSouth Upgrades to Oracle Database 11g Release 2 and Oracle RAC

    - by jenny.gelhausen
    HealthSouth Corporation, the nation's largest provider of inpatient rehabilitation services, has upgraded to Oracle Database 11g Release 2 underneath PeopleSoft Enterprise Human Capital Management. Additionally, HealthSouth improved the availability and performance of its Oracle PeopleSoft Enterprise applications and Enterprise Data Warehouse using Oracle Database 11g and Oracle Real Application Clusters. Oracle Database options -- Oracle Advanced Compression and Oracle Partitioning are key to HealthSouth's data lifecycle management practices and to utilizing storage systems more efficiently. Using compression on both partitioned as well as non-partitioned tables in its data warehouse, HealthSouth has seen a 4X storage reduction without any cost to performance. "Oracle Database 11g, along with Oracle Real Application Clusters, Advanced Compression and Partitioning, all lend themselves to delivering highly available, performant data warehousing," said Henry Lovoy, Data Manager, HealthSouth Corporation. Press Release var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www."); document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E")); try { var pageTracker = _gat._getTracker("UA-13185312-1"); pageTracker._trackPageview(); } catch(err) {}

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  • SQL SERVER – SSIS Look Up Component – Cache Mode – Notes from the Field #028

    - by Pinal Dave
    [Notes from Pinal]: Lots of people think that SSIS is all about arranging various operations together in one logical flow. Well, the understanding is absolutely correct, but the implementation of the same is not as easy as it seems. Similarly most of the people think lookup component is just component which does look up for additional information and does not pay much attention to it. Due to the same reason they do not pay attention to the same and eventually get very bad performance. Linchpin People are database coaches and wellness experts for a data driven world. In this 28th episode of the Notes from the Fields series database expert Tim Mitchell (partner at Linchpin People) shares very interesting conversation related to how to write a good lookup component with Cache Mode. In SQL Server Integration Services, the lookup component is one of the most frequently used tools for data validation and completion.  The lookup component is provided as a means to virtually join one set of data to another to validate and/or retrieve missing values.  Properly configured, it is reliable and reasonably fast. Among the many settings available on the lookup component, one of the most critical is the cache mode.  This selection will determine whether and how the distinct lookup values are cached during package execution.  It is critical to know how cache modes affect the result of the lookup and the performance of the package, as choosing the wrong setting can lead to poorly performing packages, and in some cases, incorrect results. Full Cache The full cache mode setting is the default cache mode selection in the SSIS lookup transformation.  Like the name implies, full cache mode will cause the lookup transformation to retrieve and store in SSIS cache the entire set of data from the specified lookup location.  As a result, the data flow in which the lookup transformation resides will not start processing any data buffers until all of the rows from the lookup query have been cached in SSIS. The most commonly used cache mode is the full cache setting, and for good reason.  The full cache setting has the most practical applications, and should be considered the go-to cache setting when dealing with an untested set of data. With a moderately sized set of reference data, a lookup transformation using full cache mode usually performs well.  Full cache mode does not require multiple round trips to the database, since the entire reference result set is cached prior to data flow execution. There are a few potential gotchas to be aware of when using full cache mode.  First, you can see some performance issues – memory pressure in particular – when using full cache mode against large sets of reference data.  If the table you use for the lookup is very large (either deep or wide, or perhaps both), there’s going to be a performance cost associated with retrieving and caching all of that data.  Also, keep in mind that when doing a lookup on character data, full cache mode will always do a case-sensitive (and in some cases, space-sensitive) string comparison even if your database is set to a case-insensitive collation.  This is because the in-memory lookup uses a .NET string comparison (which is case- and space-sensitive) as opposed to a database string comparison (which may be case sensitive, depending on collation).  There’s a relatively easy workaround in which you can use the UPPER() or LOWER() function in the pipeline data and the reference data to ensure that case differences do not impact the success of your lookup operation.  Again, neither of these present a reason to avoid full cache mode, but should be used to determine whether full cache mode should be used in a given situation. Full cache mode is ideally useful when one or all of the following conditions exist: The size of the reference data set is small to moderately sized The size of the pipeline data set (the data you are comparing to the lookup table) is large, is unknown at design time, or is unpredictable Each distinct key value(s) in the pipeline data set is expected to be found multiple times in that set of data Partial Cache When using the partial cache setting, lookup values will still be cached, but only as each distinct value is encountered in the data flow.  Initially, each distinct value will be retrieved individually from the specified source, and then cached.  To be clear, this is a row-by-row lookup for each distinct key value(s). This is a less frequently used cache setting because it addresses a narrower set of scenarios.  Because each distinct key value(s) combination requires a relational round trip to the lookup source, performance can be an issue, especially with a large pipeline data set to be compared to the lookup data set.  If you have, for example, a million records from your pipeline data source, you have the potential for doing a million lookup queries against your lookup data source (depending on the number of distinct values in the key column(s)).  Therefore, one has to be keenly aware of the expected row count and value distribution of the pipeline data to safely use partial cache mode. Using partial cache mode is ideally suited for the conditions below: The size of the data in the pipeline (more specifically, the number of distinct key column) is relatively small The size of the lookup data is too large to effectively store in cache The lookup source is well indexed to allow for fast retrieval of row-by-row values No Cache As you might guess, selecting no cache mode will not add any values to the lookup cache in SSIS.  As a result, every single row in the pipeline data set will require a query against the lookup source.  Since no data is cached, it is possible to save a small amount of overhead in SSIS memory in cases where key values are not reused.  In the real world, I don’t see a lot of use of the no cache setting, but I can imagine some edge cases where it might be useful. As such, it’s critical to know your data before choosing this option.  Obviously, performance will be an issue with anything other than small sets of data, as the no cache setting requires row-by-row processing of all of the data in the pipeline. I would recommend considering the no cache mode only when all of the below conditions are true: The reference data set is too large to reasonably be loaded into SSIS memory The pipeline data set is small and is not expected to grow There are expected to be very few or no duplicates of the key values(s) in the pipeline data set (i.e., there would be no benefit from caching these values) Conclusion The cache mode, an often-overlooked setting on the SSIS lookup component, represents an important design decision in your SSIS data flow.  Choosing the right lookup cache mode directly impacts the fidelity of your results and the performance of package execution.  Know how this selection impacts your ETL loads, and you’ll end up with more reliable, faster packages. If you want me to take a look at your server and its settings, or if your server is facing any issue we can Fix Your SQL Server. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Notes from the Field, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: SSIS

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  • Oracle Database 12c By Example – SQL Developer and Multitenant

    - by thatjeffsmith
    As you may have heard, Oracle Database 12c is now available. In addition to the binaries and docs going out, we also published a few new Oracle By Example (OBE) chapters. You can find those links here on our product page. Do you know who found these, practically the minute they were published? An enterprising DBA-extraordinaire who was just happening to be presenting at the ODTUG KScope13 conference in New Orleans. He thought it would be a good idea to download the new software over a hotel WIFI, install and create a new multitenant database, watch a few OBEs, and then demo that live for his ‘SQL Developer for DBAs‘ session. Pretty crazy, right? Well, he did it, and I was there to watch. Way cool. You can listen to @leight0nn tell his story in his own words via this ODTUG interview with @oraclenered. In case you’re too giddy to sit through the video, I’ll give you a preview – he succesfully cloned a pluggable database in about a minute with only a couple of clicks using Oracle SQL Developer 3.2.20.09 while connected to a 12c database.

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  • Join Oracle Database at Microsoft TechEd next week.

    - by Mandy Ho
    For the past nine years, Oracle has been a proud sponsor of Microsoft TechEd. TechEd is Mircosoft's premier technology conference for IT professionals and developers. This year, Oracle will demonstrate its latest database software for MS Windows, including Oracle Database 11g Enterprise and Express editions, TimesTen and MySQL.  Developers can learn how to develop .Net applications for the Oracle Database using the latest technologies, such as Entity Framework, LINQ and WCF Data Services. Attendees can also learn the new MySQL features enabling rapid installation, GUI Based application design, backup & recovery and much more within a Windows environment. Oracle will have a BOF (Birds of a Feather Session) on Tuesday, June 12, from 3:15 to 4:30. The topic will be Big Data: The Next Frontier for Innovation, Competition and Productivity. Otherwise you can visit Oracle everyday during the expo hours from Mon, June 11 to Thursday, June 14 at our booth #613. Talk to experts on TimesTen and MySQL on Windows and .NET. Also, we will have our 3D interactive demos on Oracle's engineered systems showing off Oracle Exadata, Database Appliance and more. Visit  http://northamerica.msteched.com/ for more information. 

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  • Announcing Oracle Database Mobile Server 11gR2

    - by Eric Jensen
    I'm pleased to announce that Oracle Database Mobile Server 11gR2 has been released. It's available now for download by existing customers, or anyone who wants to try it out. New features include: Support for J2ME platforms, specifically CDC platforms including OJEC(this is in addition to our existing support for Java SE and SE Embedded) Per-application integration with Berkeley DB on Android Server-side support for Apache TomEE platform Adding support for Oracle Java Micro Edition Embedded Client (OJEC for short) is an important milestone for us; it enables Database Mobile Server to work with any of the incredibly wide array of devices that run J2ME. In particular, it enables management of  networks of embedded devices, AKA machine to machine (M2M) networks. As these types of networks become more common in areas like healthcare, automotive, and manufacturing, we're seeing demand for Database Mobile Server from new and different areas. This is in addition to our existing array of mobile device use cases. The Android integration feature with Berkeley DB represents the completion of phase I of our Android support plan, we now offer a full set of sync, device and app management features for that platform. Going forward, we plan to continue the dual-focus approach, supporting mobile platforms such as Android, and iOS (hint) on the one hand, and networks of embedded M2M devices on the other. In either case, Database Mobile Server continues to be the best way to connect data-driven applications to an Oracle backend.

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  • Flashback Database

    - by Sebastian Solbach (DBA Community)
    Flashback Database bezeichnet die Funktionalität der Oracle Datenbank, die Datenbank zeitlich auf einen bestimmten Punkt, respektive eine bestimmte System Change Number (SCN) zurücksetzen zu können - vergleichbar mit einem Rückspulknopf eines Kassettenrekorders oder der Rücksetztaste eines CD-Players. Mag dieses Vorgehen bei Produktivsystemen eher selten Einsatz finden, da beim Rücksetzten alle Daten nach dem zurückgesetzten Zeitpunkt verloren wären (es sei denn man würde dieser vorher exportieren), gibt es gerade für Test- oder Standby Systeme viele Einsatzmöglichkeiten: Rücksetzten des Systems bei fehlgeschlagenen Applikations-Upgrade Alternatives Point in Time Recovery (PITR) mit anschließendem Roll Forward (besonders geeignet bei Standby Systemen) Testdatenbank mit definiertem, reproduzierbaren Ausgangspunkt (z.B. für Real Application Testing) Datenbank Upgrade Test Einige bestehende Datenbank Funktionalitäten verwenden Flashback Database implizit: Snapshot Standby Reinstanziierung der Standby (z.B. bei Fast Start Failover) Obwohl diese Funktionalität gerade für Standby Systeme und Testsysteme bestens geeignet ist, gibt es eine gewisse Zurückhaltung Flashback Database einzusetzen. Eine Ursache ist oft die Angst vor zusätzlicher Last, die das Schreiben der Flashback Logs erzeugt, sowie der zusätzlich benötigte Plattenplatz. Dabei ist die Last im Normalfall relativ gering (ca. 5%) und auch der zusätzlich benötigte Platz für die Flashback Logs lässt sich relativ genau bestimmen. Ebenfalls wird häufig nicht beachtet, dass es auch ohne das explizite Einschalten der Flashback Logs möglich ist, einen garantieren Rücksetzpunkt (Guaranteed Restore Point kurz GRP) festzulegen, und die Datenbank dann auf diesen Restore Point zurückzusetzen. Das Setzen eines garantierten Rücksetzpunktes funktioniert in 11gR2 im laufenden Betrieb. Wie dies genau funktioniert, welche Unterschiede es zum generellen Einschalten von Flashback Logs gibt, wie man Flashback Database monitoren kann und was es sonst noch zu berücksichtigen gibt, damit beschäftigt sich dieser Tipp.

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  • SQL Server Database Settings

    - by rbishop
    For those using Data Relationship Management on Oracle DB this does not apply, but for those using Microsoft SQL Server it is highly recommended that you run with Snapshot Isolation Mode. The Data Governance module will not function correctly without this mode enabled. All new Data Relationship Management repositories are created with this mode enabled by default. This mode makes SQL Server (2005+) behave more like Oracle DB where readers simply see older versions of rows while a write is in progress, instead of readers being blocked by locks while a write takes place. Many common sources of deadlocks are eliminated. For example, if one user starts a 5 minute transaction updating half the rows in a table, without snapshot isolation everyone else reading the table will be blocked waiting. With snapshot isolation, they will see the rows as they were before the write transaction started. Conversely, if the readers had started first, the writer won't be stuck waiting for them to finish reading... the writes can begin immediately without affecting the current transactions. To make this change, make sure no one is using the target database (eg: put it into single-user mode), then run these commands: ALTER DATABASE [DB] SET ALLOW_SNAPSHOT_ISOLATION ONALTER DATABASE [DB] SET READ_COMMITTED_SNAPSHOT ON Please make sure you coordinate with your DBA team to ensure tempdb is appropriately setup to support snapshot isolation mode, as the extra row versions are stored in tempdb until the transactions are committed. Let me take this opportunity to extremely strongly highly recommend that you use solid state storage for your databases with appropriate iSCSI, FiberChannel, or SAN bandwidth. The performance gains are significant and there is no excuse for not using 100% solid state storage in 2013. Actually unless you need to store petabytes of archival data, there is no excuse for using hard drives in any systems, whether laptops, desktops, application servers, or database servers. The productivity benefits alone are tremendous, not to mention power consumption, heat, etc.

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  • Oracle NoSQL Database: Cleaner Performance

    - by Charles Lamb
    In an earlier post I noted that Berkeley DB Java Edition cleaner performance had improved significantly in release 5.x. From an Oracle NoSQL Database point of view, this is important because Berkeley DB Java Edition is the core storage engine for Oracle NoSQL Database. Many contemporary NoSQL Databases utilize log based (i.e. append-only) storage systems and it is well-understood that these architectures also require a "cleaning" or "compaction" mechanism (effectively a garbage collector) to free up unused space. 10 years ago when we set out to write a new Berkeley DB storage architecture for the BDB Java Edition ("JE") we knew that the corresponding compaction mechanism would take years to perfect. "Cleaning", or GC, is a hard problem to solve and it has taken all of those years of experience, bug fixes, tuning exercises, user deployment, and user feedback to bring it to the mature point it is at today. Reports like Vinoth Chandar's where he observes a 20x improvement validate the maturity of JE's cleaner. Cleaner performance has a direct impact on predictability and throughput in Oracle NoSQL Database. A cleaner that is too aggressive will consume too many resources and negatively affect system throughput. A cleaner that is not aggressive enough will allow the disk storage to become inefficient over time. It has to Work well out of the box, and Needs to be configurable so that customers can tune it for their specific workloads and requirements. The JE Cleaner has been field tested in production for many years managing instances with hundreds of GBs to TBs of data. The maturity of the cleaner and the entire underlying JE storage system is one of the key advantages that Oracle NoSQL Database brings to the table -- we haven't had to reinvent the wheel.

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  • Service Catalogs for Database as a Service

    - by B R Clouse
    At the end of last month, I had the opportunity to present a speaking session at Oracle OpenWorld: Database as a Service: Creating a Database Cloud Service Catalog.  The session was well-attended which would have surprised me several months ago when I started researching this topic.  At that time, I thought of service catalogs as something trivial which could be explained in a few simple slides.  But while looking at all the different options and approaches available, I came to learn that designing a succinct and effective catalog is not a trivial task, and mistakes can lead to confusion and unintended side effects.  And when the room filled up, my new point of view was confirmed. In case you missed the session, or were able to attend but would like more details, I've posted a white paper that covers the topics from the session, and more.  We start with an overview of the components of a service catalog: And then look at several customer case studies of service catalogs for DBaaS.  Synthesizing those examples, we summarize the main options for defining the service categories and their levels.  We end with a template for defining Bronze | Silver | Gold service tiers for Oracle Database Services. The paper is now available here - watch for updates as we work to expand some sections and incorporate readers' feedback (hint - that includes your feedback). Visit our OTN page for additional Database Cloud collateral.

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  • How do I construct a Django reverse/url using query args?

    - by Andrew Dalke
    I have URLs like http://example.com/depict?smiles=CO&width=200&height=200 (and with several other optional arguments) My urls.py contains: urlpatterns = patterns('', (r'^$', 'cansmi.index'), (r'^cansmi$', 'cansmi.cansmi'), url(r'^depict$', cyclops.django.depict, name="cyclops-depict"), I can go to that URL and get the 200x200 PNG that was constructed, so I know that part works. In my template from the "cansmi.cansmi" response I want to construct a URL for the named template "cyclops-depict" given some query parameters. I thought I could do {% url cyclops-depict smiles=input_smiles width=200 height=200 %} where "input_smiles" is an input to the template via a form submission. In this case it's the string "CO" and I thought it would create a URL like the one at top. This template fails with a TemplateSyntaxError: Caught an exception while rendering: Reverse for 'cyclops-depict' with arguments '()' and keyword arguments '{'smiles': u'CO', 'height': 200, 'width': 200}' not found. This is a rather common error message both here on StackOverflow and elsewhere. In every case I found, people were using them with parameters in the URL path regexp, which is not the case I have where the parameters go into the query. That means I'm doing it wrong. How do I do it right? That is, I want to construct the full URL, including path and query parameters, using something in the template. For reference, % python manage.py shell Python 2.6.1 (r261:67515, Feb 11 2010, 00:51:29) [GCC 4.2.1 (Apple Inc. build 5646)] on darwin Type "help", "copyright", "credits" or "license" for more information. (InteractiveConsole) >>> from django.core.urlresolvers import reverse >>> reverse("cyclops-depict", kwargs=dict()) '/depict' >>> reverse("cyclops-depict", kwargs=dict(smiles="CO")) Traceback (most recent call last): File "<console>", line 1, in <module> File "/Library/Python/2.6/site-packages/django/core/urlresolvers.py", line 356, in reverse *args, **kwargs))) File "/Library/Python/2.6/site-packages/django/core/urlresolvers.py", line 302, in reverse "arguments '%s' not found." % (lookup_view_s, args, kwargs)) NoReverseMatch: Reverse for 'cyclops-depict' with arguments '()' and keyword arguments '{'smiles': 'CO'}' not found.

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  • How to add a column via a query which counts the total rows with a specific criteria in a table with circular relationship in MS ACCESS 2007

    - by Xaqron
    I have a simple table "Employees" with this fields: ID, ParentID, Name ParentID is Nullable since an employee may have no Manager. This table has a one-to-many relationship with itself: ID --one--to--many--> ParentID Now I want a query which returns this columns: Name, Count of rows where their ParentID equals to the current row ID (the row is the manager of that rows) Sample Table: ID | ParentID | Name ====================== 1 | 0 | John ---------------------- 2 | 1 | Bob ---------------------- 3 | 1 | Alice ---------------------- 4 | 3 | Jack This way I can find an employee is the manager of how many other employees. The result should be something like this: Name | Count of Employees ========================== John | 2 -------------- Bob | 0 -------------- Alice | 1 -------------- Jack | 0 How can I achieve this in MS ACCESS 2007? * I have tried built-in query builder without any success.

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  • Is there a way to optimize this update query?

    - by SchlaWiener
    I have a master table called "parent" and a related table called "childs" Now I run a query against the master table to update some values with the sum from the child table like this. UPDATE master m SET quantity1 = (SELECT SUM(quantity1) FROM childs c WHERE c.master_id = m.id), quantity2 = (SELECT SUM(quantity2) FROM childs c WHERE c.master_id = m.id), count = (SELECT COUNT(*) FROM childs c WHERE c.master_id = m.id) WHERE master_id = 666; Which works as expected but is not a good style because I basically make multiple SELECT querys on the same result. Is there a way to optimize that? (Making a query first and storing the values is not an option. I tried this: UPDATE master m SET (quantity1, quantity2, count) = ( SELECT SUM(quantity1), SUM(quantity2), COUNT(*) FROM childs c WHERE c.master_id = m.id ) WHERE master_id = 666; but that doesn't work.

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  • How can I build my SQL query from these tables?

    - by vee
    Hi All, I'm thinking of building query from these 2 tables (on SQL Server 2008). I have 2 tables as shown below: Table 1 MemberId . MemberName . Percentage . Amount1 00000001 AAA 1.0 100 00000002 BBB 1.2 800 00000003 ZZZ 1.0 700 Table 2 MemberId . MemberName . Percentage . Amount2 00000002 BBB 1.5 500 00000002 BBB 1.6 100 00000002 BBB 1.6 150 The result I want is MemberId . MemberName . Percentage . Amount . NettAmount 00000001 AAA 1.0 100 100 00000002 BBB 1.2 800 50 <-- 800-(500+100+150) 00000002 BBB 1.5 500 500 00000002 BBB 1.6 650 650 00000003 ZZZ 1.0 700 700 50 comes from 800 in Table1 minus sum of Amount2 in table2 for MemberID=00000002 Plz someone help me to build the query to reach this result. Thank you in advance.

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  • How do I increase Relevance value in an advanced MySQL query?

    - by morgant
    I've got a MySQL query similar to the following: SELECT *, MATCH (`Description`) AGAINST ('+ipod +touch ' IN BOOLEAN MODE) * 8 + MATCH(`Description`) AGAINST ('ipod touch' IN BOOLEAN MODE) AS Relevance FROM products WHERE ( MATCH (`Description`) AGAINST ('+ipod +touch' IN BOOLEAN MODE) OR MATCH(`LongDescription`) AGAINST ('+ipod +touch' IN BOOLEAN MODE) ) HAVING Relevance > 1 ORDER BY Relevance DESC Now, I've made the query more advanced by also searching for UPC: SELECT *, MATCH (`Description`) AGAINST ('+ipod +touch ' IN BOOLEAN MODE) * 8 + MATCH(`Description`) AGAINST ('ipod touch' IN BOOLEAN MODE) + `UPC` = '123456789012' * 16 AS Relevance FROM products WHERE ( MATCH (`Description`) AGAINST ('+ipod +touch' IN BOOLEAN MODE) OR MATCH(`LongDescription`) AGAINST ('+ipod +touch' IN BOOLEAN MODE) ) AND `UPC` = '123456789012' HAVING Relevance > 1 ORDER BY Relevance DESC That'll return results, but the fact that I had a successful match on the UPC does not increase the value of Relevance. Can I only do that kind of calculation w/full text searches like MATCH() AGAINST()? Clarification: Okay, so my real question is, why does the following not have a Relevance = 16? SELECT `UPC`, `UPC` = '123456789012' * 16 AS Relevance FROM products WHERE `UPC` = '123456789012' HAVING Relevance > 1 ORDER BY Relevance DESC

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  • When using Query Syntax in C# "Enumeration yielded no results". How to retrieve output

    - by Shantanu Gupta
    I have created this query to fetch some result from database. Here is my table structure. What exaclty is happening. DtMapGuestDepartment as Table 1 DtDepartment as Table 2 Are being used var dept_list= from map in DtMapGuestDepartment.AsEnumerable() where map.Field<Nullable<long>>("GUEST_ID") == DRowGuestPI.Field<Nullable<long>>("PK_GUEST_ID") join dept in DtDepartment.AsEnumerable() on map.Field<Nullable<long>>("DEPARTMENT_ID") equals dept.Field<Nullable<long>>("DEPARTMENT_ID") select dept.Field<string>("DEPARTMENT_ID"); I am performing this query on DataTables and expect it to return me a datatable. Here I want to select distinct department from Table 1 as well which will be my next quest. Please answer to that also if possible.

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  • How can I write a MySQL query to check multiple rows?

    - by Matt
    I have a MySQL table containing data on product features: feature_id feature_product_id feature_finder_id feature_text feature_status_yn 1 1 1 Webcam y 2 1 1 Speakers y 3 1 1 Bluray n I want to write a MySQL query that allows me to search for all products that have a 'y' feature_status_yn value for a given feature_product_id and return the feature_product_id. The aim is to use this as a search tool to allow me to filter results to product IDs only matching the requested feature set. A query of SELECT feature_id FROM product_features WHERE feature_finder_id = '1' AND feature_status_yn = 'y' will return all of the features of a given product. But how can I select all products (feature_product_id) that have a 'y' value when they are on separate lines? Multiple queries might be one way to do it, but I'm wondering whether there's a more elegant solution based purely in SQL.

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