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  • SQL version control methodology

    - by Tom H.
    There are several questions on SO about version control for SQL and lots of resources on the web, but I can't find something that quite covers what I'm trying to do. First off, I'm talking about a methodology here. I'm familiar with the various source control applications out there and I'm familiar with tools like Red Gate's SQL Compare, etc. and I know how to write an application to check things in and out of my source control system automatically. If there is a tool which would be particularly helpful in providing a whole new methodology or which have a useful and uncommon functionality then great, but for the tasks mentioned above I'm already set. The requirements that I'm trying to meet are: The database schema and look-up table data are versioned DML scripts for data fixes to larger tables are versioned A server can be promoted from version N to version N + X where X may not always be 1 Code isn't duplicated within the version control system - for example, if I add a column to a table I don't want to have to make sure that the change is in both a create script and an alter script The system needs to support multiple clients who are at various versions for the application (trying to get them all up to within 1 or 2 releases, but not there yet) Some organizations keep incremental change scripts in their version control and to get from version N to N + 3 you would have to run scripts for N-N+1 then N+1-N+2 then N+2-N+3. Some of these scripts can be repetitive (for example, a column is added but then later it is altered to change the data type). We're trying to avoid that repetitiveness since some of the client DBs can be very large, so these changes might take longer than necessary. Some organizations will simply keep a full database build script at each version level then use a tool like SQL Compare to bring a database up to one of those versions. The problem here is that intermixing DML scripts can be a problem. Imagine a scenario where I add a column, use a DML script to fill said column, then in a later version that column name is changed. Perhaps there is some hybrid solution? Maybe I'm just asking for too much? Any ideas or suggestions would be greatly appreciated though. If the moderators think that this would be more appropriate as a community wiki, please let me know. Thanks!

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  • Can PHP and Oracle pass complex types to each other?

    - by RenderIn
    I want to pass/bind an array of (key1, key2) to an Oracle PL/SQL stored procedure using PHP. I'm able to bind primitive types and arrays of primitive types, but haven't found a way to pass complex datatypes back and forth. Is this unsupported? So far I've been having to pass along multiple arrays -- one for each subtype in my complex type -- and then depend on their indexes to reconstitute them in the procedure.

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  • Push Notifications in Android Platform

    - by Vinod
    I am looking to write an app which received pushed alerts from a server. I found a couple of methods to do this. 1) SMS - Intercept the incoming SMS and initiate a pull from the server 2) Poll the server periodically Each has its own limitations. SMS- no guarantee on arrival time. Poll may drain the battery. Do you have a better suggestion please?. Thanks much.

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  • servlet ArrayList and HashMap problem witch result

    - by nonameplum
    Hi, I have that code List<Map<String, Object>> data = new ArrayList<Map<String, Object>>(); Map<String, Object> item = new HashMap<String, Object>(); data.clear(); item.clear(); int i = 0; while (i < 5){    item.put("id", i);    i++;    out.println("id: " + item.get("id"));    out.println("--------------------------");    data.add(item); } for(i=0 ; i<5 ; i++){    out.println("print data[" + i + "]" + data.get(i)); } Result of that is: id: 0 -------------------------- id: 1 -------------------------- id: 2 -------------------------- id: 3 -------------------------- id: 4 -------------------------- print data[0]{id=4} print data[1]{id=4} print data[2]{id=4} print data[3]{id=4} print data[4]{id=4} Why only last element is stored?

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  • NSPredicate (Core Data fetch) to filter on an attribute value being present in a supplied set (list)

    - by starbaseweb
    I'm trying to create a fetch predicate that is the analog to the SQL "IN" statement, and the syntax to do so with NSPredicate escapes me. Here's what I have so far (the relevant excerpt from my fetching routine): NSFetchRequest *request = [[[NSFetchRequest alloc] init] autorelease]; NSEntityDescription *entity = [NSEntityDescription entityForName: @"BodyPartCategory" inManagedObjectContext:_context]; [request setEntity:entity]; NSPredicate *predicate = [NSPredicate predicateWithFormat:@"(name IN %@)", [RPBodyPartCategory defaultBodyPartCategoryNames]]; [request setPredicate:predicate]; The entity "BodyPartCategory" has a string attribute "name". I have a list of names (just NSString objects) in an NSArray as returned by: [RPBodyPartCategory defaultBodyPartCategoryNames] So let's say that array has string such as {@"Liver", @"Kidney", @"Thyroid"} ... etc. I want to fetch all 'BodyPartCategory' instances whose name attribute matches one of the strings in the set provided (technically NSArray but I can make it an NSSet). In SQL, this would be something like: SELECT * FROM BodyPartCategories WHERE name IN ('Liver', 'Kidney', 'Thyroid') I've gone through various portions of the Predicate Programming Guide, but I don't see this simple use case covered. Pointers/help much appreciated!

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  • Write a program for a report derived from the data in the data file JEWELRY. The data is to be input

    - by Taylor
    here is the JEWELRY file 0011 Money_Clip 2.000 50.00 Other 0035 Paperweight 1.625 175.00 Other 0457 Cuff_Bracelet 2.375 150.00 Bracelet 0465 Links_Bracelet 7.125 425.00 Bracelet 0585 Key_Chain 1.325 50.00 Other 0595 Cuff_Links 0.625 525.00 Other 0935 Royale_Pendant 0.625 975.00 Pendant 1092 Bordeaux_Cross 1.625 425.00 Cross 1105 Victory_Medallion 0.875 30.00 Pendant 1111 Marquis_Cross 1.375 70.00 Cross 1160 Christina_Ring 0.500 175.00 Ring 1511 French_Clips 0.687 375.00 Other 1717 Pebble_Pendant 1.250 45.00 Pendant 1725 Folded_Pendant 1.250 45.00 Pendant 1730 Curio_Pendant 1.063 275.00 Pendant this is the program i have used #include <iostream> #include <string> #include <iomanip> #include <fstream> using namespace std; struct productJewelry { string name; double amount; int itemCode; double size; string group; }; int main() { // declare variables ifstream inFile; int count=0; int x=0; productJewelry product[50]; inFile.open("jewelry.txt"); // file must be in same folder if (inFile.fail()) cout << "failed"; cout << fixed << showpoint; // fixed format, two decimal places cout << setprecision(2); while (inFile.peek() != EOF) { // cout << count << " : "; count++; inFile>> product[x].itemCode; inFile>> product[x].name; inFile>> product[x].size; inFile>> product[x].amount; inFile>> product[x].group; // cout << product[x].itemCode << ", " << product[x].name << ", "<< product[x].size << ", " << product[x].amount << endl; x++; if (inFile.peek() == '\n') inFile.ignore(1, '\n'); } inFile.close(); string temp; bool swap; do { swap = false; for (int x=0; x<count;x++) { if (product[x].name>product[x+1].name) { //these 3 lines are to swap elements in array temp=product[x].name; product[x].name=product[x+1].name; product[x+1].name=temp; swap=true; } } } while (swap); for (x=0; x< count; x++) { //cout<< product[x].itemCode<<" "; //cout<< product[x].name <<" "; //cout<< product[x].size <<" "; //cout<< product[x].amount<<" "; //cout<< product[x].group<<" "<<endl; } system("pause"); // to freeze Dev-c++ output screen return 0; } // end main

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  • What's the consequence when Core Data detects an optimistic locking failure when trying to save?

    - by dontWatchMyProfile
    I get it: When a managed object context saves, the snapshots of all edited objects are compared against the values in the persistent store to see if the PS has changed since the snapshot was made. If it did change, then there's a conflict and optimistic locking failed, according to Apple. But now, what's the consequence of this? What happens next? What are my options in this case?

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  • C++ Programming in Linux Platform

    - by viswanathan
    I am a software engineer and i work in VC++, C++ in WIndows OS. Are there any major differences when it comes to coding in C++ in Linux environment. Or is it just some adjustments that we have to make when we need to code in C++ in Linux.

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  • SQL SERVER – Shrinking NDF and MDF Files – Readers’ Opinion

    - by pinaldave
    Previously, I had written a blog post about SQL SERVER – Shrinking NDF and MDF Files – A Safe Operation. After that, I have written the following blog post that talks about the advantage and disadvantage of Shrinking and why one should not be Shrinking a file SQL SERVER – SHRINKFILE and TRUNCATE Log File in SQL Server 2008. On this subject, SQL Server Expert Imran Mohammed left an excellent comment. I just feel that his comment is worth a big article itself. For everybody to read his wonderful explanation, I am posting this blog post here. Thanks Imran! Shrinking Database always creates performance degradation and increases fragmentation in the database. I suggest that you keep that in mind before you start reading the following comment. If you are going to say Shrinking Database is bad and evil, here I am saying it first and loud. Now, the comment of Imran is written while keeping in mind only the process showing how the Shrinking Database Operation works. Imran has already explained his understanding and requests further explanation. I have removed the Best Practices section from Imran’s comments, as there are a few corrections. Comments from Imran - Before I explain to you the concept of Shrink Database, let us understand the concept of Database Files. When we create a new database inside the SQL Server, it is typical that SQl Server creates two physical files in the Operating System: one with .MDF Extension, and another with .LDF Extension. .MDF is called as Primary Data File. .LDF is called as Transactional Log file. If you add one or more data files to a database, the physical file that will be created in the Operating System will have an extension of .NDF, which is called as Secondary Data File; whereas, when you add one or more log files to a database, the physical file that will be created in the Operating System will have the same extension as .LDF. The questions now are, “Why does a new data file have a different extension (.NDF)?”, “Why is it called as a secondary data file?” and, “Why is .MDF file called as a primary data file?” Answers: Note: The following explanation is based on my limited knowledge of SQL Server, so experts please do comment. A data file with a .MDF extension is called a Primary Data File, and the reason behind it is that it contains Database Catalogs. Catalogs mean Meta Data. Meta Data is “Data about Data”. An example for Meta Data includes system objects that store information about other objects, except the data stored by the users. sysobjects stores information about all objects in that database. sysindexes stores information about all indexes and rows of every table in that database. syscolumns stores information about all columns that each table has in that database. sysusers stores how many users that database has. Although Meta Data stores information about other objects, it is not the transactional data that a user enters; rather, it’s a system data about the data. Because Primary Data File (.MDF) contains important information about the database, it is treated as a special file. It is given the name Primary Data file because it contains the Database Catalogs. This file is present in the Primary File Group. You can always create additional objects (Tables, indexes etc.) in the Primary data file (This file is present in the Primary File group), by mentioning that you want to create this object under the Primary File Group. Any additional data file that you add to the database will have only transactional data but no Meta Data, so that’s why it is called as the Secondary Data File. It is given the extension name .NDF so that the user can easily identify whether a specific data file is a Primary Data File or a Secondary Data File(s). There are many advantages of storing data in different files that are under different file groups. You can put your read only in the tables in one file (file group) and read-write tables in another file (file group) and take a backup of only the file group that has read the write data, so that you can avoid taking the backup of a read-only data that cannot be altered. Creating additional files in different physical hard disks also improves I/O performance. A real-time scenario where we use Files could be this one: Let’s say you have created a database called MYDB in the D-Drive which has a 50 GB space. You also have 1 Database File (.MDF) and 1 Log File on D-Drive and suppose that all of that 50 GB space has been used up and you do not have any free space left but you still want to add an additional space to the database. One easy option would be to add one more physical hard disk to the server, add new data file to MYDB database and create this new data file in a new hard disk then move some of the objects from one file to another, and put the file group under which you added new file as default File group, so that any new object that is created gets into the new files, unless specified. Now that we got a basic idea of what data files are, what type of data they store and why they are named the way they are, let’s move on to the next topic, Shrinking. First of all, I disagree with the Microsoft terminology for naming this feature as “Shrinking”. Shrinking, in regular terms, means to reduce the size of a file by means of compressing it. BUT in SQL Server, Shrinking DOES NOT mean compressing. Shrinking in SQL Server means to remove an empty space from database files and release the empty space either to the Operating System or to SQL Server. Let’s examine this through an example. Let’s say you have a database “MYDB” with a size of 50 GB that has a free space of about 20 GB, which means 30GB in the database is filled with data and the 20 GB of space is free in the database because it is not currently utilized by the SQL Server (Database); it is reserved and not yet in use. If you choose to shrink the database and to release an empty space to Operating System, and MIND YOU, you can only shrink the database size to 30 GB (in our example). You cannot shrink the database to a size less than what is filled with data. So, if you have a database that is full and has no empty space in the data file and log file (you don’t have an extra disk space to set Auto growth option ON), YOU CANNOT issue the SHRINK Database/File command, because of two reasons: There is no empty space to be released because the Shrink command does not compress the database; it only removes the empty space from the database files and there is no empty space. Remember, the Shrink command is a logged operation. When we perform the Shrink operation, this information is logged in the log file. If there is no empty space in the log file, SQL Server cannot write to the log file and you cannot shrink a database. Now answering your questions: (1) Q: What are the USEDPAGES & ESTIMATEDPAGES that appear on the Results Pane after using the DBCC SHRINKDATABASE (NorthWind, 10) ? A: According to Books Online (For SQL Server 2000): UsedPages: the number of 8-KB pages currently used by the file. EstimatedPages: the number of 8-KB pages that SQL Server estimates the file could be shrunk down to. Important Note: Before asking any question, make sure you go through Books Online or search on the Google once. The reasons for doing so have many advantages: 1. If someone else already has had this question before, chances that it is already answered are more than 50 %. 2. This reduces your waiting time for the answer. (2) Q: What is the difference between Shrinking the Database using DBCC command like the one above & shrinking it from the Enterprise Manager Console by Right-Clicking the database, going to TASKS & then selecting SHRINK Option, on a SQL Server 2000 environment? A: As far as my knowledge goes, there is no difference, both will work the same way, one advantage of using this command from query analyzer is, your console won’t be freezed. You can do perform your regular activities using Enterprise Manager. (3) Q: What is this .NDF file that is discussed above? I have never heard of it. What is it used for? Is it used by end-users, DBAs or the SERVER/SYSTEM itself? A: .NDF File is a secondary data file. You never heard of it because when database is created, SQL Server creates database by default with only 1 data file (.MDF) and 1 log file (.LDF) or however your model database has been setup, because a model database is a template used every time you create a new database using the CREATE DATABASE Command. Unless you have added an extra data file, you will not see it. This file is used by the SQL Server to store data which are saved by the users. Hope this information helps. I would like to as the experts to please comment if what I understand is not what the Microsoft guys meant. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Readers Contribution, Readers Question, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • EPM Infrastructure Tuning Guide v11.1.2.2 / 11.1.2.3

    - by Ahmed Awan
    Applies To: This edition applies to only 11.1.2.2, 11.1.2.3. One of the most challenging aspects of performance tuning is knowing where to begin. To maximize Oracle EPM System performance, all components need to be monitored, analyzed, and tuned. This guide describe the techniques used to monitor performance and the techniques for optimizing the performance of EPM components. TOP TUNING RECOMMENDATIONS FOR EPM SYSTEM: Performance tuning Oracle Hyperion EPM system is a complex and iterative process. To get you started, we have created a list of recommendations to help you optimize your Oracle Hyperion EPM system performance. This chapter includes the following sections that provide a quick start for performance tuning Oracle EPM products. Note these performance tuning techniques are applicable to nearly all Oracle EPM products such as Financial PM Applications, Essbase, Reporting and Foundation services. 1. Tune Operating Systems parameters. 2. Tune Oracle WebLogic Server (WLS) parameters. 3. Tune 64bit Java Virtual Machines (JVM). 4. Tune 32bit Java Virtual Machines (JVM). 5. Tune HTTP Server parameters. 6. Tune HTTP Server Compression / Caching. 7. Tune Oracle Database Parameters. 8. Tune Reporting And Analysis Framework (RAF) Services. 9. Tune Oracle ADF parameters. Click to Download the EPM 11.1.2.3 Infrastructure Tuning Whitepaper (Right click or option-click the link and choose "Save As..." to download this pdf file)

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  • MySQL Connect: What to Expect From the Wondrous Land of MySQL Cluster

    - by Mat Keep
    The MySQL Connect conference is only a couple of weeks away, with MySQL engineers, support teams, consultants and community aces busy putting the final touches to their talks. There will be many exciting new announcements and sharing of best practices at the conference, covering the range of MySQL technologies. MySQL Cluster will a big part of this, so I wanted to share some key sessions for those of you who plan on attending, as well as some resources for those who are not lucky enough to be able to make the trip, but who can't afford to miss the key news. Of course, this is no substitute to actually being there….and the good news is that registration is still open ;-) Roadmap: Whats New in MySQL Cluster Saturday 29th, 1300-1400, in Golden Gate room 5.                                                                                        Bernd Ocklin, director of MySQL Cluster development, and myself will be taking a look at what follows the latest MySQL Cluster 7.2 release. I don't want to give to much away - lets just say its not often you can add powerful new functionality to a product while at the same time making life radically simpler for its users. For those not making it to the Conference, a live webinar repeating the talk is scheduled for Thursday 25th October at 09.00 pacific time. Hold the date, registration will be open for that soon and published to our MySQL Webinars page Best Practices Getting Started with MySQL Cluster, Hands-On Lab Saturday 29th, 1600-1700, in Plaza Room A.                                                              Santo Leto, one of our lead MySQL Cluster support engineers, regularly works with users new to MySQL Cluster, assisting them in installation, configuration, scaling, etc. In this lab, Santo will share best-practices in getting started. Delivering Breakthrough Performance with MySQL Cluster Saturday 29th, 1730-1830, in Golden Gate room 5. Frazer Clement, lead MySQL Cluster software engineer, will demonstrate how to translate the awesome Cluster benchmarks (remember 1 BILLION UPDATEs per minute ?!) into real-world performance. You can also get some best practices from our new MySQL Cluster performance guide  MySQL Cluster BoF Saturday 29th, 1900-2000, room Golden Gate 5.                                                                                                           Come and get a demonstration of new tools for the installation and configuration of MySQL Cluster, and spend time with the engineering team discussing any questions or issues you may have. Developing High-Throughput Services with NoSQL APIs to InnoDB and MySQL Cluster Sunday 30th, 1145 - 1245, in Golden Gate room 7.   In this session, JD Duncan and Andrew Morgan will present how to get started with both Memcached and new NoSQL APIs. JD and I recently ran a webinar demonstrating how to build simple Twitter-like services with Memcached and MySQL Cluster. The replay is available for download.  Case Studies: MySQL Cluster @ El Chavo, Latin America’s #1 Facebook Game Sunday 30th, 1745 - 1845, in Golden Gate room 4.                             Playful Play deployed MySQL Cluster CGE to power their market leading social game. This session will discuss the challenges they faced, why they selected MySQL Cluster and their experiences to date. You can read more about Playful Play and MySQL Cluster here  A Journey into NoSQLand: MySQL’s NoSQL Implementation Sunday 30th, 1345 - 1445, in Golden Gate room 4.                                          Lig Turmelle, web DBA at Kaplan Professional and esteemed Oracle Ace, will discuss her experiences working with the NoSQL interfaces for both MySQL Cluster and InnoDB Evaluating MySQL HA Alternatives Saturday 29th, 1430-1530, room Golden Gate 5                                                                                   Henrik Ingo, former member of the MySQL sales engineering team, will provide an overview of various HA technologies for MySQL, starting with replication, progressing to InnoDB, Galera and MySQL Cluster What about the other stuff? Of course MySQL Connect has much, much more than MySQL Cluster. There will be lots on replication (which I'll blog about soon), MySQL 5.6, InnoDB, cloud, etc, etc. Take a look at the full Content Catalog to see more. If you are attending, I hope to see you at one of the Cluster sessions...and remember, registration is still open

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  • SQL SERVER – GUID vs INT – Your Opinion

    - by pinaldave
    I think the title is clear what I am going to write in your post. This is age old problem and I want to compile the list stating advantages and disadvantages of using GUID and INT as a Primary Key or Clustered Index or Both (the usual case). Let me start a list by suggesting one advantage and one disadvantage in each case. INT Advantage: Numeric values (and specifically integers) are better for performance when used in joins, indexes and conditions. Numeric values are easier to understand for application users if they are displayed. Disadvantage: If your table is large, it is quite possible it will run out of it and after some numeric value there will be no additional identity to use. GUID Advantage: Unique across the server. Disadvantage: String values are not as optimal as integer values for performance when used in joins, indexes and conditions. More storage space is required than INT. Please note that I am looking to create list of all the generic comparisons. There can be special cases where the stated information is incorrect, feel free to comment on the same. Please leave your opinion and advice in comment section. I will combine a final list and update this blog after a week. By listing your name in post, I will also give due credit. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Constraint and Keys, SQL Data Storage, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • Data Web Controls Enhancements in ASP.NET 4.0

    Traditionally, developers using Web controls enjoyed increased productivity but at the cost of control over the rendered markup. For instance, many ASP.NET controls automatically wrap their content in <table> for layout or styling purposes. This behavior runs counter to the web standards that have evolved over the past several years, which favor cleaner, terser HTML; sparing use of tables; and Cascading Style Sheets (CSS) for layout and styling. Furthermore, the <table> elements and other automatically-added content makes it harder to both style the Web controls using CSS and to work with the controls from client-side script. One of the aims of ASP.NET version 4.0 is to give Web Form developers greater control over the markup rendered by Web controls. Last week's article, Take Control Of Web Control ClientID Values in ASP.NET 4.0, highlighted how new properties in ASP.NET 4.0 give the developer more say over how a Web control's ID property is translated into a client-side id attribute. In addition to these ClientID-related properties, many Web controls in ASP.NET 4.0 include properties that allow the page developer to instruct the control to not emit extraneous markup, or to use an HTML element other than <table>. This article explores a number of enhancements made to the data Web controls in ASP.NET 4.0. As you'll see, most of these enhancements give the developer greater control over the rendered markup. Read on to learn more! Read More >

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  • Data Web Controls Enhancements in ASP.NET 4.0

    Traditionally, developers using Web controls enjoyed increased productivity but at the cost of control over the rendered markup. For instance, many ASP.NET controls automatically wrap their content in <table> for layout or styling purposes. This behavior runs counter to the web standards that have evolved over the past several years, which favor cleaner, terser HTML; sparing use of tables; and Cascading Style Sheets (CSS) for layout and styling. Furthermore, the <table> elements and other automatically-added content makes it harder to both style the Web controls using CSS and to work with the controls from client-side script. One of the aims of ASP.NET version 4.0 is to give Web Form developers greater control over the markup rendered by Web controls. Last week's article, Take Control Of Web Control ClientID Values in ASP.NET 4.0, highlighted how new properties in ASP.NET 4.0 give the developer more say over how a Web control's ID property is translated into a client-side id attribute. In addition to these ClientID-related properties, many Web controls in ASP.NET 4.0 include properties that allow the page developer to instruct the control to not emit extraneous markup, or to use an HTML element other than <table>. This article explores a number of enhancements made to the data Web controls in ASP.NET 4.0. As you'll see, most of these enhancements give the developer greater control over the rendered markup. Read on to learn more! Read More >Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • Twitter status id conundrum

    - by jamiet
    I have an interest, a slightly perverse one some might say, in using online services and trying to figure out what the underlying (logical) data model is and in this day and age Twitter is one that lends itself very well to scrutiny. Consider this recent tweet of mine: The URL that enables you to see that tweet is http://twitter.com/jamiet/status/12154647354. We can interpret that URL to mean "a tweet by jamiet with an id of 12154647354" and hence we might further assume that the unique identifier for the tweet is {jamiet,12154647354}. However, its well-known that Twitter gives each status a unique ID regardless of who tweeted it so we might expect we could reach that tweet just by using a URL of http://twitter.com/status/12154647354 however (at the time of writing) that only redirects to Twitter's homepage. That seems strange to me especially given that we can use Twitter's API to access information about that tweet using only the id of the status. Witness http://api.twitter.com/1/statuses/show/12154647354.xml: [We can also access a JSON version of that information using http://api.twitter.com/1/statuses/show/12154647354.json] I'm puzzled as to why a tweet can't be accessed using on the main twitter website using the id alone. Anyone have any suggestions? @jamiet Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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  • SQL SERVER – Plan Cache and Data Cache in Memory

    - by pinaldave
    I get following question almost all the time when I go for consultations or training. I often end up providing the scripts to my clients and attendees. Instead of writing new blog post, today in this single blog post, I am going to cover both the script and going to link to original blog posts where I have mentioned about this blog post. Plan Cache in Memory USE AdventureWorks GO SELECT [text], cp.size_in_bytes, plan_handle FROM sys.dm_exec_cached_plans AS cp CROSS APPLY sys.dm_exec_sql_text(plan_handle) WHERE cp.cacheobjtype = N'Compiled Plan' ORDER BY cp.size_in_bytes DESC GO Further explanation of this script is over here: SQL SERVER – Plan Cache – Retrieve and Remove – A Simple Script Data Cache in Memory USE AdventureWorks GO SELECT COUNT(*) AS cached_pages_count, name AS BaseTableName, IndexName, IndexTypeDesc FROM sys.dm_os_buffer_descriptors AS bd INNER JOIN ( SELECT s_obj.name, s_obj.index_id, s_obj.allocation_unit_id, s_obj.OBJECT_ID, i.name IndexName, i.type_desc IndexTypeDesc FROM ( SELECT OBJECT_NAME(OBJECT_ID) AS name, index_id ,allocation_unit_id, OBJECT_ID FROM sys.allocation_units AS au INNER JOIN sys.partitions AS p ON au.container_id = p.hobt_id AND (au.TYPE = 1 OR au.TYPE = 3) UNION ALL SELECT OBJECT_NAME(OBJECT_ID) AS name, index_id, allocation_unit_id, OBJECT_ID FROM sys.allocation_units AS au INNER JOIN sys.partitions AS p ON au.container_id = p.partition_id AND au.TYPE = 2 ) AS s_obj LEFT JOIN sys.indexes i ON i.index_id = s_obj.index_id AND i.OBJECT_ID = s_obj.OBJECT_ID ) AS obj ON bd.allocation_unit_id = obj.allocation_unit_id WHERE database_id = DB_ID() GROUP BY name, index_id, IndexName, IndexTypeDesc ORDER BY cached_pages_count DESC; GO Further explanation of this script is over here: SQL SERVER – Get Query Plan Along with Query Text and Execution Count Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL Tagged: SQL Memory

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  • links for 2010-04-12

    - by Bob Rhubart
    Andy Mulholland: We need innovation! What does that mean? "The most common response would seem to be ‘I will know it when I see it’, which suggests business success is based on ‘getting lucky’. As you might expect business schools don’t agree with this and as A G Lafley, author of several works on the topic comments: 'Innovation is risky, but it’s not random. Innovators have a disciplined invention process.'" Capgemini CTO blogger Andy Mulholland. (tags: entarch enterprisearchitecture innovation) @eelzinga: lEAI/Oracle Service Bus testing with Citrus Framework, part2 IT-Eye's Eric Elzinga continues his series with a test of a scenario that is part of a customer's middleware architecture. (tags: oracle otn ESB soa citrus) @fteter: Collaborate 10 - What Looks Good To Me Oracle ACE Director Floyd Teter from NASA's JPL shares quick previews of his Collaborate 10 presentations, along with a list of some sessions he plans to attend. (tags: oracle otn oracleace collaborate2010) Mark Rittman: OWB11gR2 for Windows Now Available Oracle ACE Director Mark Rittman of Rittman Mead shares insight on the recent Oracle Warehouse Builder release, along with a list of articles on the new features in Oracle Database 11gR2. (tags: oracle otn datewarehousing businessintelligence 11gr2)

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  • How to cross-reference many character encodings with ASCII OR UTFx?

    - by Garet Claborn
    I'm working with a binary structure, the goal of which is to index the significance of specific bits for any character encoding so that we may trigger events while doing specific checks against the profile. Each character encoding scheme has an associated system record. This record's leading value will be a C++ unsigned long long binary value and signifies the length, in bits, of encoded characters. Following the length are three values, each is a bit field of that length. offset_mask - defines the occurrence of non-printable characters within the min,max of print_mask range_mask - defines the occurrence of the most popular 50% of printable characters print_mask - defines the occurrence value of printable characters The structure of profiles has changed from the op of this question. Most likely I will try to factorize or compress these values in the long-term instead of starting out with ranges after reading more. I have to write some of the core functionality for these main reasons. It has to fit into a particular event architecture we are using, Better understanding of character encoding. I'm about to need it. Integrating into non-linear design is excluding many libraries without special hooks. I'm unsure if there is a standard, cross-encoding mechanism for communicating such data already. I'm just starting to look into how chardet might do profiling as suggested by @amon. The Unicode BOM would be easily enough (for my current project) if all encodings were Unicode. Of course ideally, one would like to support all encodings, but I'm not asking about implementation - only the general case. How can these profiles be efficiently populated, to produce a set of bitmasks which we can use to match strings with common characters in multiple languages? If you have any editing suggestions please feel free, I am a lightweight when it comes to localization, which is why I'm trying to reach out to the more experienced. Any caveats you may be able to help with will be appreciated.

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  • ODI 11g – How to override SQL at runtime?

    - by David Allan
    Following on from the posting some time back entitled ‘ODI 11g – Simple, Powerful, Flexible’ here we push the envelope even further. Rather than just having the SQL we override defined statically in the interface design we will have it configurable via a variable….at runtime. Imagine you have a well defined interface shape that you want to be fulfilled and that shape can be satisfied from a number of different sources that is what this allows - or the ability for one interface to consume data from many different places using variables. The cool thing about ODI’s reference API and this is that it can be fantastically flexible and useful. When I use the variable as the option value, and I execute the top level scenario that uses this temporary interface I get prompted (or can get prompted to be correct) for the value of the variable. Note I am using the <@=odiRef.getObjectName("L","EMP", "SCOTT","D")@> notation for the table reference, since this is done at runtime, then the context will resolve to the correct table name etc. Each time I execute, I could use a different source provider (obviously some dependencies on KMs/technologies here). For example, the following groovy snippet first executes and the query uses SCOTT model with EMP, the next time it is from BOB model and the datastore OTHERS. m=new Properties(); m.put("DEMO.SQLSTR", "select empno, deptno from <@=odiRef.getObjectName("L","EMP", "SCOTT","D")@>"); s=new StartupParams(m); runtimeAgent.startScenario("TOP", null, s, null, "GLOBAL", 5, null, true); m2=new Properties(); m2.put("DEMO.SQLSTR", "select empno, deptno from <@=odiRef.getObjectName("L","OTHERS", "BOB","D")@>"); s2=new StartupParams(m); runtimeAgent.startScenario("TOP", null, s2, null, "GLOBAL", 5, null, true); You’ll need a patch to 11.1.1.6 for this type of capability, thanks to my ole buddy Ron Gonzalez from the Enterprise Management group for help pushing the envelope!

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  • SQL Authority News – Download SQL Server Data Type Conversion Chart

    - by pinaldave
    Datatypes are very important concepts of SQL Server and there are quite often need to convert them from one datatypes to another datatype. I have seen that deveoper often get confused when they have to convert the datatype. There are two important concept when it is about datatype conversion. Implicit Conversion: Implicit conversions are those conversions that occur without specifying either the CAST or CONVERT function. Explicit Conversions: Explicit conversions are those conversions that require the CAST or CONVERT function to be specified. What it means is that if you are trying to convert value from datetime2 to time or from tinyint to int, SQL Server will automatically convert (implicit conversation) for you. However, if you are attempting to convert timestamp to smalldatetime or datetime to int you will need to explicitely convert them using either CAST or CONVERT function as well appropriate parameters. Let us see a quick example of Implict Conversion and Explict Conversion. Implicit Conversion: Explicit Conversion: You can see from above example that how we need both of the types of conversion in different situation. There are so many different datatypes and it is humanly impossible to know which datatype require implicit and which require explicit conversion. Additionally there are cases when the conversion is not possible as well. Microsoft have published a chart where the grid displays various conversion possibilities as well a quick guide. Download SQL Server Data Type Conversion Chart Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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