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  • Oracle T4CPreparedStatement memory leaks?

    - by Jay
    A little background on the application that I am gonna talk about in the next few lines: XYZ is a data masking workbench eclipse RCP application: You give it a source table column, and a target table column, it would apply a trasformation (encryption/shuffling/etc) and copy the row data from source table to target table. Now, when I mask n tables at a time, n threads are launched by this app. Here is the issue: I have run into a production issue on first roll out of the above said app. Unfortunately, I don't have any logs to get to the root. However, I tried to run this app in test region and do a stress test. When I collected .hprof files and ran 'em through an analyzer (yourKit), I noticed that objects of oracle.jdbc.driver.T4CPreparedStatement was retaining heap. The analysis also tells me that one of my classes is holding a reference to this preparedstatement object and thereby, n threads have n such objects. T4CPreparedStatement seemed to have character arrays: lastBoundChars and bindChars each of size char[300000]. So, I researched a bit (google!), obtained ojdbc6.jar and tried decompiling T4CPreparedStatement. I see that T4CPreparedStatement extends OraclePreparedStatement, which dynamically manages array size of lastBoundChars and bindChars. So, my questions here are: Have you ever run into an issue like this? Do you know the significance of lastBoundChars / bindChars? I am new to profiling, so do you think I am not doing it correct? (I also ran the hprofs through MAT - and this was the main identified issue - so, I don't really think I could be wrong?) I have found something similar on the web here: http://forums.oracle.com/forums/thread.jspa?messageID=2860681 Appreciate your suggestions / advice.

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  • Delphi: Fast(er) widestring concatenation

    - by Ian Boyd
    i have a function who's job is to convert an ADO Recordset into html: class function RecordsetToHtml(const rs: _Recordset): WideString; And the guts of the function involves a lot of wide string concatenation: while not rs.EOF do begin Result := Result+CRLF+ '<TR>'; for i := 0 to rs.Fields.Count-1 do Result := Result+'<TD>'+VarAsString(rs.Fields[i].Value)+'</TD>'; Result := Result+'</TR>'; rs.MoveNext; end; With a few thousand results, the function takes, what any user would feel, is too long to run. The Delphi Sampling Profiler shows that 99.3% of the time is spent in widestring concatenation (@WStrCatN and @WstrCat). Can anyone think of a way to improve widestring concatenation? i don't think Delphi 5 has any kind of string builder. And Format doesn't support Unicode. And to make sure nobody tries to weasel out: pretend you are implementing the interface: IRecordsetToHtml = interface(IUnknown) function RecordsetToHtml(const rs: _Recordset): WideString; end; Update One I thought of using an IXMLDOMDocument, to build up the HTML as xml. But then i realized that the final HTML would be xhtml and not html - a subtle, but important, difference. Update Two Microsoft knowledge base article: How To Improve String Concatenation Performance

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  • Webbased data modelling and management tool

    - by pixeldude
    Is there a web-based tool available, where I am able to... ...define data models (like in a database admin tool) ...fill in data (in custom web forms, not too generic) with basic features like completion ...import data from CSV oder Excel Sheets ...export data to CSV or SQL ...create snapshots of my data models (versions, diff, etc.) ...share my data models ...discuss/collaborate with other people about my data models Well, I can develop something like this in PHP or with Ruby or whatever. But this is such a common task, where the application support could be a lot better. And it would be language and database independent. This would help to maintain data models in different versions and you can maybe share your data models with others, extend it with your team members, etc. There is a website called FreeBase, which allows you to define a data entity model and fill in data, which also has export features, but I need to define my own data model with my own granularity and structure. And it should not be shared in public if I don't want to. How do you solve problems like this yourself?

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  • Slow retrieval of data in SQLITE takes a long using ContentProvider

    - by Arlyn
    I have an application in Android (running 4.0.3) that stores a lot of data in Table A. Table A resides in SQLite Database. I am using a ContentProvider as an abstraction layer above the database. Lots of data here means almost 80,000 records per month. Table A is structured like this: String SQL_CREATE_TABLE = "CREATE TABLE IF NOT EXISTS " + TABLE_A + " ( " + COLUMN_ID + " INTEGER PRIMARY KEY NOT NULL" + "," + COLUMN_GROUPNO + " INTEGER NOT NULL DEFAULT(0)" + "," + COLUMN_TIMESTAMP + " DATETIME UNIQUE NOT NULL" + "," + COLUMN_TAG + " TEXT" + "," + COLUMN_VALUE + " REAL NOT NULL" + "," + COLUMN_DEVICEID + " TEXT NOT NULL" + "," + COLUMN_NEW + " NUMERIC NOT NULL DEFAULT(1)" + " )"; Here is the index statement: String SQL_CREATE_INDEX_TIMESTAMP = "CREATE INDEX IF NOT EXISTS " + TABLE_A + "_" + COLUMN_TIMESTAMP + " ON " + TABLE_A + " (" + COLUMN_TIMESTAMP + ") "; I have defined the columns as well as the table name as String Constants. I am already experiencing significant slow down when retrieving this data from Table A. The problem is that when I retrieve data from this table, I first put it in an ArrayList and then I display it. Obviously, this is possibly the wrong way of doing things. I am trying to find a better way to approach this problem using a ContentProvider. But this is not the problem that bothers me. The problem is for some reason, it takes a lot longer to retrieve data from other tables which have only upto 12 records maximum. I see this delay increase as the number of records in Table A increase. This does not make any sense. I can understand the delay if I retrieve data from Table A, but why the delay in retrieving data from other tables. To clarify, I do not experience this delay if Table A is empty or has less than 3000 records. What could be the problem?

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  • Update table instantly or “Bulk” Update in database later? And is it advisable?

    - by Mestika
    Hi, I have a question regarding a semi-constant update in a database. In short it is regarding a checkout function on a web page, which each time the checkout function is evoked it do five steps. I want to try to optimize this function and have my eye on a step where I update a table each time the checkout is performed. I take the information retrieved from the shopping cart and then update the table in question. I do have some indexes on the table, the gain from those are greater than leaving them so this is a cost I’m willing to take. Now, my question is. Could it in some way regarding to performance be better to not update the table instantly but collect every checkout items and save them in some way (maybe in a file) and then at a specific time (or several times) at day take this file and then update the table with the new information. Then I started thinking about if there was a possibility to use some sort of Bulk Update to take a file, hashmap, array (or?) and then update it. And I’m using IBM DB2 version 9.7 Mestika

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  • SQL SERVER – What is Spatial Database? – Developing with SQL Server Spatial and Deep Dive into Spati

    - by pinaldave
    What is Spatial Database? A spatial database is a database that is optimized to store and query data related to objects in space, including points, lines and polygons. While typical databases can understand various numeric and character types of data, additional functionality needs to be added for databases to process spatial data types. (Source: Wikipedia) Today I will be talking about the same subject at Microsoft TechEd India. If you want to learn about how to spatial aspect of data and how to integrate them with SQL Server this is the perfect session for you. Spatial is very special concept of SQL Server and I really like how it is implemented in SQL Server. In general Performance Tuning and Query Optimization is something I always have enjoyed in my professional life. Index are my best friends and many time, by implementing and many time by removing I have improved the performance of the system. In this session, I will be talking about Index along with Spatial Data. As Spatial Database is very interesting concept, I will cover super short but very interesting 10 quick slides about this subject. I will make sure in very first 20 mins, you will understand following topics Introduction to Spatial Database One line definition Understanding Spatial Indexing Index Internals Query/Performance Tuning Query Hinting/Cost Analysis Spatial Index Catalog Views Performance Troubleshooting Finding Optimal Index using Spatial Index SP Common Errors Index Maintenance This slides decks will be followed by around 30 mins demo which will have story of geometry, geography, index internals and performance tuning. If you are interested in learning how GIS works and how SQL Server out of the box supports this wonderful tools, you will really like how the story is told. I am sure all people who attend the event will know how the Bangalore is positioned on the map of India. I will take example of Bangalore and Hyderabad and demonstrate how index can improve the performance. Well there are lots of story to tell in the session, and I will be opening this session with the beautiful script of Botticelli’s Birth of Venus created by Michael J. Swart. I will also demonstrate few real life scenario where I will be talking about Spatial Database and its usage. Do not miss this session. At the end of session there will be book awarded to best participant. My session details: Session 3: Developing with SQL Server Spatial and Deep Dive into Spatial Indexing Date: April 14, 2010 Time: 5:00pm-6:00pm Microsoft SQL Server 2008 delivers new spatial data types that enable you to consume, use, and extend location-based data through spatial-enabled applications. Attend this session to learn how to use spatial functionality in next version of SQL Server to build and optimize spatial queries. This session outlines the new geography data type to store geodetic spatial data and perform operations on it, use the new geometry data type to store planar spatial data and perform operations on it, take advantage of new spatial indexes for high performance queries, use the new spatial results tab to quickly and easily view spatial query results directly from within Management Studio, extend spatial data capabilities by building or integrating location-enabled applications through support for spatial standards and specifications and much more. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Index, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority Author Visit, T SQL, Technology Tagged: Spatial Database

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  • Advanced Data Source Engine coming to Telerik Reporting Q1 2010

    This is the final blog post from the pre-release series. In it we are going to share with you some of the updates coming to our reporting solution in Q1 2010. A new Declarative Data Source Engine will be added to Telerik Reporting, that will allow full control over data management, and deliver significant gains in rendering performance and memory consumption. Some of the engines new features will be: Data source parameters - those parameters will be used to limit data retrieved from the data source to just the data needed for the report. Data source parameters are processed on the data source side, however only queried data is fetched to the reporting engine, rather than the full data source. This leads to lower memory consumption, because data operations are performed on queried data only, rather than on all data. As a result, only the queried data needs to be stored in the memory vs. the whole dataset, which was the case with the old approach Support for stored procedures - they will assist in achieving a consistent implementation of logic across applications, and are especially practical for performing repetitive tasks. A stored procedure stores the SQL statements and logic, which can then be executed in different reports and/or applications. Stored Procedures will not only save development time, but they will also improve performance, because each stored procedure is compiled on the data base server once, and then is reutilized. In Telerik Reporting, the stored procedure will also be parameterized, where elements of the SQL statement will be bound to parameters. These parameterized SQL queries will be handled through the data source parameters, and are evaluated at run time. Using parameterized SQL queries will improve the performance and decrease the memory footprint of your application, because they will be applied directly on the database server and only the necessary data will be downloaded on the middle tier or client machine; Calculated fields through expressions - with the help of the new reporting engine you will be able to use field values in formulas to come up with a calculated field. A calculated field is a user defined field that is computed "on the fly" and does not exist in the data source, but can perform calculations using the data of the data source object it belongs to. Calculated fields are very handy for adding frequently used formulas to your reports; Improved performance and optimized in-memory OLAP engine - the new data source will come with several improvements in how aggregates are calculated, and memory is managed. As a result, you may experience between 30% (for simpler reports) and 400% (for calculation-intensive reports) in rendering performance, and about 50% decrease in memory consumption. Full design time support through wizards - Declarative data sources are a great advance and will save developers countless hours of coding. In Q1 2010, and true to Telerik Reportings essence, using the new data source engine and its features requires little to no coding, because we have extended most of the wizards to support the new functionality. The newly extended wizards are available in VS2005/VS2008/VS2010 design-time. More features will be revealed on the product's what's new page when the new version is officially released in a few days. Also make sure you attend the free webinar on Thursday, March 11th that will be dedicated to the updates in Telerik Reporting Q1 2010. 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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  • BizTalk Cross Reference Data Management Strategy

    - by charlie.mott
    Article Source: http://geekswithblogs.net/charliemott This article describes an approach to the management of cross reference data for BizTalk.  Some articles about the BizTalk Cross Referencing features can be found here: http://home.comcast.net/~sdwoodgate/xrefseed.zip http://geekswithblogs.net/michaelstephenson/archive/2006/12/24/101995.aspx http://geekswithblogs.net/charliemott/archive/2009/04/20/value-vs.id-cross-referencing-in-biztalk.aspx Options Current options to managing this data include: Maintaining xml files in the format that can be used by the out-of-the-box BTSXRefImport.exe utility. Use of user interfaces that have been developed to manage this data: BizTalk Cross Referencing Tool XRef XML Creation Tool However, there are the following issues with the above options: The 'BizTalk Cross Referencing Tool' requires a separate database to manage.  The 'XRef XML Creation' tool has no means of persisting the data settings. The 'BizTalk Cross Referencing tool' generates integers in the common id field. I prefer to use a string (e.g. acme.country.uk). This is more readable. (see naming conventions below). Both UI tools continue to use BTSXRefImport.exe.  This utility replaces all xref data. This can be a problem in continuous integration environments that support multiple clients or BizTalk target instances.  If you upload the data for one client it would destroy the data for another client.  Yet in TFS where builds run concurrently, this would break unit tests. Alternative Approach In response to these issues, I instead use simple SQL scripts to directly populate the BizTalkMgmtDb xref tables combined with a data namepacing strategy to isolate client data. Naming Conventions All data keys use namespace prefixing.  The pattern will be <companyName>.<data Type>.  The naming conventions will be to use lower casing for all items.  The data must follow this pattern to isolate it from other company cross-reference data.  The table below shows some sample data. (Note: this data uses the 'ID' cross-reference tables.  the same principles apply for the 'value' cross-referencing tables). Table.Field Description Sample Data xref_AppType.appType Application Types acme.erp acme.portal acme.assetmanagement xref_AppInstance.appInstance Application Instances (each will have a corresponding application type). acme.dynamics.ax acme.dynamics.crm acme.sharepoint acme.maximo xref_IDXRef.idXRef Holds the cross reference data types. acme.taxcode acme.country xref_IDXRefData.CommonID Holds each cross reference type value used by the canonical schemas. acme.vatcode.exmpt acme.vatcode.std acme.country.usa acme.country.uk xref_IDXRefData.AppID This holds the value for each application instance and each xref type. GBP USD SQL Scripts The data to be stored in the BizTalkMgmtDb xref tables will be managed by SQL scripts stored in a database project in the visual studio solution. File(s) Description Build.cmd A sqlcmd script to deploy data by running the SQL scripts below.  (This can be run as part of the MSBuild process).   acme.purgexref.sql SQL script to clear acme.* data from the xref tables.  As such, this will not impact data for any other company. acme.applicationInstances.sql   SQL script to insert application type and application instance data.   acme.vatcode.sql acme.country.sql etc ...  There will be a separate SQL script to insert each cross-reference data type and application specific values for these types.

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  • Master Note for Generic Data Warehousing

    - by lajos.varady(at)oracle.com
    ++++++++++++++++++++++++++++++++++++++++++++++++++++ The complete and the most recent version of this article can be viewed from My Oracle Support Knowledge Section. Master Note for Generic Data Warehousing [ID 1269175.1] ++++++++++++++++++++++++++++++++++++++++++++++++++++In this Document   Purpose   Master Note for Generic Data Warehousing      Components covered      Oracle Database Data Warehousing specific documents for recent versions      Technology Network Product Homes      Master Notes available in My Oracle Support      White Papers      Technical Presentations Platforms: 1-914CU; This document is being delivered to you via Oracle Support's Rapid Visibility (RaV) process and therefore has not been subject to an independent technical review. Applies to: Oracle Server - Enterprise Edition - Version: 9.2.0.1 to 11.2.0.2 - Release: 9.2 to 11.2Information in this document applies to any platform. Purpose Provide navigation path Master Note for Generic Data Warehousing Components covered Read Only Materialized ViewsQuery RewriteDatabase Object PartitioningParallel Execution and Parallel QueryDatabase CompressionTransportable TablespacesOracle Online Analytical Processing (OLAP)Oracle Data MiningOracle Database Data Warehousing specific documents for recent versions 11g Release 2 (11.2)11g Release 1 (11.1)10g Release 2 (10.2)10g Release 1 (10.1)9i Release 2 (9.2)9i Release 1 (9.0)Technology Network Product HomesOracle Partitioning Advanced CompressionOracle Data MiningOracle OLAPMaster Notes available in My Oracle SupportThese technical articles have been written by Oracle Support Engineers to provide proactive and top level information and knowledge about the components of thedatabase we handle under the "Database Datawarehousing".Note 1166564.1 Master Note: Transportable Tablespaces (TTS) -- Common Questions and IssuesNote 1087507.1 Master Note for MVIEW 'ORA-' error diagnosis. For Materialized View CREATE or REFRESHNote 1102801.1 Master Note: How to Get a 10046 trace for a Parallel QueryNote 1097154.1 Master Note Parallel Execution Wait Events Note 1107593.1 Master Note for the Oracle OLAP OptionNote 1087643.1 Master Note for Oracle Data MiningNote 1215173.1 Master Note for Query RewriteNote 1223705.1 Master Note for OLTP Compression Note 1269175.1 Master Note for Generic Data WarehousingWhite Papers Transportable Tablespaces white papers Database Upgrade Using Transportable Tablespaces:Oracle Database 11g Release 1 (February 2009) Platform Migration Using Transportable Database Oracle Database 11g and 10g Release 2 (August 2008) Database Upgrade using Transportable Tablespaces: Oracle Database 10g Release 2 (April 2007) Platform Migration using Transportable Tablespaces: Oracle Database 10g Release 2 (April 2007)Parallel Execution and Parallel Query white papers Best Practices for Workload Management of a Data Warehouse on the Sun Oracle Database Machine (June 2010) Effective resource utilization by In-Memory Parallel Execution in Oracle Real Application Clusters 11g Release 2 (Feb 2010) Parallel Execution Fundamentals in Oracle Database 11g Release 2 (November 2009) Parallel Execution with Oracle Database 10g Release 2 (June 2005)Oracle Data Mining white paper Oracle Data Mining 11g Release 2 (March 2010)Partitioning white papers Partitioning with Oracle Database 11g Release 2 (September 2009) Partitioning in Oracle Database 11g (June 2007)Materialized Views and Query Rewrite white papers Oracle Materialized Views  and Query Rewrite (May 2005) Improving Performance using Query Rewrite in Oracle Database 10g (December 2003)Database Compression white papers Advanced Compression with Oracle Database 11g Release 2 (September 2009) Table Compression in Oracle Database 10g Release 2 (May 2005)Oracle OLAP white papers On-line Analytic Processing with Oracle Database 11g Release 2 (September 2009) Using Oracle Business Intelligence Enterprise Edition with the OLAP Option to Oracle Database 11g (July 2008)Generic white papers Enabling Pervasive BI through a Practical Data Warehouse Reference Architecture (February 2010) Optimizing and Protecting Storage with Oracle Database 11g Release 2 (November 2009) Oracle Database 11g for Data Warehousing and Business Intelligence (August 2009) Best practices for a Data Warehouse on Oracle Database 11g (September 2008)Technical PresentationsA selection of ObE - Oracle by Examples documents: Generic Using Basic Database Functionality for Data Warehousing (10g) Partitioning Manipulating Partitions in Oracle Database (11g Release 1) Using High-Speed Data Loading and Rolling Window Operations with Partitioning (11g Release 1) Using Partitioned Outer Join to Fill Gaps in Sparse Data (10g) Materialized View and Query Rewrite Using Materialized Views and Query Rewrite Capabilities (10g) Using the SQLAccess Advisor to Recommend Materialized Views and Indexes (10g) Oracle OLAP Using Microsoft Excel With Oracle 11g Cubes (how to analyze data in Oracle OLAP Cubes using Excel's native capabilities) Using Oracle OLAP 11g With Oracle BI Enterprise Edition (Creating OBIEE Metadata for OLAP 11g Cubes and querying those in BI Answers) Building OLAP 11g Cubes Querying OLAP 11g Cubes Creating Interactive APEX Reports Over OLAP 11g CubesSelection of presentations from the BIWA website:Extreme Data Warehousing With Exadata  by Hermann Baer (July 2010) (slides 2.5MB, recording 54MB)Data Mining Made Easy! Introducing Oracle Data Miner 11g Release 2 New "Work flow" GUI   by Charlie Berger (May 2010) (slides 4.8MB, recording 85MB )Best Practices for Deploying a Data Warehouse on Oracle Database 11g  by Maria Colgan (December 2009)  (slides 3MB, recording 18MB, white paper 3MB )

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  • How to give my user permission to add/edit files on local apache server? [duplicate]

    - by Logan
    Possible Duplicate: How to make Apache run as current user I'm setting up my local test server again, and I seem to have forgotten how to successfully set up the LAMP server. I have installed LAMP server via tasksel command and I have configured the /var/www directory according to a guide I've found: After the lamp server installation you will need write permissions to the /var/www directory. Follow these steps to configure permissions. Add your user to the www-data group sudo usermod -a -G www-data <your user name> now add the /var/www folder to the www-data group sudo chgrp -R www-data /var/www now give write permissions to the www-data group sudo chmod -R g+w /var/www So logan user is now part of www-data group and the file/folder permissions look like the output below: logan@computer:/var/www$ ls -lart total 172 -rw-r--r-- 1 www-data www-data 1997 Oct 23 2010 wp-links-opml.php -rw-r--r-- 1 www-data www-data 3177 Nov 1 2010 wp-config-sample.php -rw-r--r-- 1 www-data www-data 3700 Jan 8 2012 wp-trackback.php -rw-r--r-- 1 www-data www-data 271 Jan 8 2012 wp-blog-header.php -rw-r--r-- 1 www-data www-data 395 Jan 8 2012 index.php -rw-r--r-- 1 www-data www-data 3522 Apr 10 2012 wp-comments-post.php -rw-r--r-- 1 www-data www-data 19929 May 6 2012 license.txt -rw-r--r-- 1 www-data www-data 18219 Sep 11 08:27 wp-signup.php -rw-r--r-- 1 www-data www-data 2719 Sep 11 16:11 xmlrpc.php -rw-r--r-- 1 www-data www-data 2718 Sep 23 12:57 wp-cron.php -rw-r--r-- 1 www-data www-data 7723 Sep 25 01:26 wp-mail.php -rw-r--r-- 1 www-data www-data 2408 Oct 26 15:40 wp-load.php -rw-r--r-- 1 www-data www-data 4663 Nov 17 10:11 wp-activate.php -rw-r--r-- 1 www-data www-data 9899 Nov 22 04:52 wp-settings.php -rw-r--r-- 1 www-data www-data 9175 Nov 29 19:57 readme.html -rw-r--r-- 1 www-data www-data 29310 Nov 30 08:40 wp-login.php drwxr-xr-x 14 root root 4096 Dec 24 17:41 .. drwx------ 9 www-data www-data 4096 Dec 26 16:11 wp-admin drwx------ 9 www-data www-data 4096 Dec 26 16:11 wp-includes -rw-rw-rw- 1 www-data www-data 3448 Dec 26 16:14 wp-config.php drwxrwxr-x 5 www-data www-data 4096 Dec 26 16:14 . drwx------ 6 www-data www-data 4096 Dec 26 16:19 wp-content Things work perfectly at http://localhost, I can view the website fine. The thing with this is that I will be working on a plugin for wordpress and I don't want to deal with separate owners under www directory to create or modify files/folders. When I give my user the ownership of /var/www recursively as logan:www-data I can create/modify files but cannot view the http://localhost. I get a Forbidden error. I'm assuming that this is because of the Apache's configuration? Which one is healthier or easier considering this is just a local test website, configuring apache to give user logan to view website and chmod /var/www logan:logan so that I can create files etc. without any sudo commands; or is it easier to configure user groups to get www-data user to act like my logan user? (Idk how that's possible, maybe putting www-data user under logan group?) Please shed some light to this subject. All I want is to be able to create/modifiy files under my user, and yet to be able to successfully view http://localhost I appreciate the help!

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  • Oracle Enterprise Data Quality: Ever Integration-ready

    - by Mala Narasimharajan
    It is closing in on a year now since Oracle’s acquisition of Datanomic, and the addition of Oracle Enterprise Data Quality (EDQ) to the Oracle software family. The big move has caused some big shifts in emphasis and some very encouraging excitement from the field.  To give an illustration, combined with a shameless promotion of how EDQ can help to give quick insights into your data, I did a quick Phrase Profile of the subject field of emails to the Global EDQ mailing list since it was set up last September. The results revealed a very clear theme:   Integration, Integration, Integration! As well as the important Siebel and Oracle Data Integrator (ODI) integrations, we have been asked about integration with a huge variety of Oracle applications, including EBS, Peoplesoft, CRM on Demand, Fusion, DRM, Endeca, RightNow, and more - and we have not stood still! While it would not have been possible to develop specific pre-integrations with all of the above within a year, we have developed a package of feature-rich out-of-the-box web services and batch processes that can be plugged into any application or middleware technology with ease. And with Siebel, they work out of the box. Oracle Enterprise Data Quality version 9.0.4 includes the Customer Data Services (CDS) pack – a ready set of standard processes with standard interfaces, to provide integrated: Address verification and cleansing  Individual matching Organization matching The services can are suitable for either Batch or Real-Time processing, and are enabled for international data, with simple configuration options driving the set of locale-specific dictionaries that are used. For example, large dictionaries are provided to support international name transcription and variant matching, including highly specialized handling for Arabic, Japanese, Chinese and Korean data. In total across all locales, CDS includes well over a million dictionary entries.   Excerpt from EDQ’s CDS Individual Name Standardization Dictionary CDS has been developed to replace the OEM of Informatica Identity Resolution (IIR) for attached Data Quality on the Oracle price list, but does this in a way that creates a ‘best of both worlds’ situation for customers, who can harness not only the out-of-the-box functionality of pre-packaged matching and standardization services, but also the flexibility of OEDQ if they want to customize the interfaces or the process logic, without having to learn more than one product. From a competitive point of view, we believe this stands us in good stead against our key competitors, including Informatica, who have separate ‘Identity Resolution’ and general DQ products, and IBM, who provide limited out-of-the-box capabilities (with a steep learning curve) in both their QualityStage data quality and Initiate matching products. Here is a brief guide to the main services provided in the pack: Address Verification and Standardization EDQ’s CDS Address Cleaning Process The Address Verification and Standardization service uses EDQ Address Verification (an OEM of Loqate software) to verify and clean addresses in either real-time or batch. The Address Verification processor is wrapped in an EDQ process – this adds significant capabilities over calling the underlying Address Verification API directly, specifically: Country-specific thresholds to determine when to accept the verification result (and therefore to change the input address) based on the confidence level of the API Optimization of address verification by pre-standardizing data where required Formatting of output addresses into the input address fields normally used by applications Adding descriptions of the address verification and geocoding return codes The process can then be used to provide real-time and batch address cleansing in any application; such as a simple web page calling address cleaning and geocoding as part of a check on individual data.     Duplicate Prevention Unlike Informatica Identity Resolution (IIR), EDQ uses stateless services for duplicate prevention to avoid issues caused by complex replication and synchronization of large volume customer data. When a record is added or updated in an application, the EDQ Cluster Key Generation service is called, and returns a number of key values. These are used to select other records (‘candidates’) that may match in the application data (which has been pre-seeded with keys using the same service). The ‘driving record’ (the new or updated record) is then presented along with all selected candidates to the EDQ Matching Service, which decides which of the candidates are a good match with the driving record, and scores them according to the strength of match. In this model, complex multi-locale EDQ techniques can be used to generate the keys and ensure that the right balance between performance and matching effectiveness is maintained, while ensuring that the application retains control of data integrity and transactional commits. The process is explained below: EDQ Duplicate Prevention Architecture Note that where the integration is with a hub, there may be an additional call to the Cluster Key Generation service if the master record has changed due to merges with other records (and therefore needs to have new key values generated before commit). Batch Matching In order to allow customers to use different match rules in batch to real-time, separate matching templates are provided for batch matching. For example, some customers want to minimize intervention in key user flows (such as adding new customers) in front end applications, but to conduct a more exhaustive match on a regular basis in the back office. The batch matching jobs are also used when migrating data between systems, and in this case normally a more precise (and automated) type of matching is required, in order to minimize the review work performed by Data Stewards.  In batch matching, data is captured into EDQ using its standard interfaces, and records are standardized, clustered and matched in an EDQ job before matches are written out. As with all EDQ jobs, batch matching may be called from Oracle Data Integrator (ODI) if required. When working with Siebel CRM (or master data in Siebel UCM), Siebel’s Data Quality Manager is used to instigate batch jobs, and a shared staging database is used to write records for matching and to consume match results. The CDS batch matching processes automatically adjust to Siebel’s ‘Full Match’ (match all records against each other) and ‘Incremental Match’ (match a subset of records against all of their selected candidates) modes. The Future The Customer Data Services Pack is an important part of the Oracle strategy for EDQ, offering a clear path to making Data Quality Assurance an integral part of enterprise applications, and providing a strong value proposition for adopting EDQ. We are planning various additions and improvements, including: An out-of-the-box Data Quality Dashboard Even more comprehensive international data handling Address search (suggesting multiple results) Integrated address matching The EDQ Customer Data Services Pack is part of the Enterprise Data Quality Media Pack, available for download at http://www.oracle.com/technetwork/middleware/oedq/downloads/index.html.

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  • As a game developer, which data structure use for develop the game? [duplicate]

    - by Rizwanabbasi
    This question already has an answer here: When should vector/list be used? 5 answers We are developing a game for bank robbery. The game plots a bank robbery. Lots of people witness that robbery. Our game will load the lists of suspected offenders while the players (witnesses) will have to identify the offenders of this robbery. Game should load list of offenders to identify the one as quickly as possible. Admin can add/remove offenders in the lists and two or more lists of offenders can also be merged into one (to show it to the player). As a game developer, which data structure we should use for develop the game? Justify your selection with solid arguments. Remember the most critical requirement is that the list should load super fast.

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  • Master Data Management Implementation Styles

    - by david.butler(at)oracle.com
    In any Master Data Management solution deployment, one of the key decisions to be made is the choice of the MDM architecture. Gartner and other analysts describe some different Hub deployment styles, which must be supported by a best of breed MDM solution in order to guarantee the success of the deployment project.   Registry Style: In a Registry Style MDM Hub, the various source systems publish their data and a subscribing Hub stores only the source system IDs, the Foreign Keys (record IDs on source systems) and the key data values needed for matching. The Hub runs the cleansing and matching algorithms and assigns unique global identifiers to the matched records, but does not send any data back to the source systems. The Registry Style MDM Hub uses data federation capabilities to build the "virtual" golden view of the master entity from the connected systems.   Consolidation Style: The Consolidation Style MDM Hub has a physically instantiated, "golden" record stored in the central Hub. The authoring of the data remains distributed across the spoke systems and the master data can be updated based on events, but is not guaranteed to be up to date. The master data in this case is usually not used for transactions, but rather supports reporting; however, it can also be used for reference operationally.   Coexistence Style: The Coexistence Style MDM Hub involves master data that's authored and stored in numerous spoke systems, but includes a physically instantiated golden record in the central Hub and harmonized master data across the application portfolio. The golden record is constructed in the same manner as in the consolidation style, and, in the operational world, Consolidation Style MDM Hubs often evolve into the Coexistence Style. The key difference is that in this architectural style the master data stored in the central MDM system is selectively published out to the subscribing spoke systems.   Transaction Style: In this architecture, the Hub stores, enhances and maintains all the relevant (master) data attributes. It becomes the authoritative source of truth and publishes this valuable information back to the respective source systems. The Hub publishes and writes back the various data elements to the source systems after the linking, cleansing, matching and enriching algorithms have done their work. Upstream, transactional applications can read master data from the MDM Hub, and, potentially, all spoke systems subscribe to updates published from the central system in a form of harmonization. The Hub needs to support merging of master records. Security and visibility policies at the data attribute level need to be supported by the Transaction Style hub, as well.   Adaptive Transaction Style: This is similar to the Transaction Style, but additionally provides the capability to respond to diverse information and process requests across the enterprise. This style emerged most recently to address the limitations of the above approaches. With the Adaptive Transaction Style, the Hub is built as a platform for consolidating data from disparate third party and internal sources and for serving unified master entity views to operational applications, analytical systems or both. This approach delivers a real-time Hub that has a reliable, persistent foundation of master reference and relationship data, along with all the history and lineage of data changes needed for audit and compliance tracking. On top of this persistent master data foundation, the Hub can dynamically aggregate transaction data on demand from different source systems to deliver the unified golden view to downstream systems. Data can also be accessed through batch interfaces, published to a message bus or served through a real-time services layer. New data sources can be readily added in this approach by extending the data model and by configuring the new source mappings and the survivorship rules, meaning that all legacy data hubs can be leveraged to contribute their records/rules into the new transaction hub. Finally, through rich user interfaces for data stewardship, it allows exception handling by business analysts to keep it current with business rules/practices while maintaining the reliability of best-of-breed master records.   Confederation Style: In this architectural style, several Hubs are maintained at departmental and/or agency and/or territorial level, and each of them are connected to the other Hubs either directly or via a central Super-Hub. Each Domain level Hub can be implemented using any of the previously described styles, but normally the Central Super-Hub is a Registry Style one. This is particularly important for Public Sector organizations, where most of the time it is practically or legally impossible to store in a single central hub all the relevant constituent information from all departments.   Oracle MDM Solutions can be deployed according to any of the above MDM architectural styles, and have been specifically designed to fully support the Transaction and Adaptive Transaction styles. Oracle MDM Solutions provide strong data federation and integration capabilities which are key to enabling the use of the Confederated Hub as a possible architectural style approach. Don't lock yourself into a solution that cannot evolve with your needs. With Oracle's support for any type of deployment architecture, its ability to leverage the outstanding capabilities of the Oracle technology stack, and its open interfaces for non-Oracle technology stacks, Oracle MDM Solutions provide a low TCO and a quick ROI by enabling a phased implementation strategy.

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  • What's a good data structure solution for a scene manager in XNA?

    - by tunnuz
    Hello, I'm playing with XNA for a game project of myself, I had previous exposure to OpenGL and worked a bit with Ogre, so I'm trying to get the same concepts working on XNA. Specifically I'm trying to add to XNA a scene manager to handle hierarchical transforms, frustum (maybe even occlusion) culling and transparency object sorting. My plan was to build a tree scene manager to handle hierarchical transforms and lighting, and then use an Octree for frustum culling and object sorting. The problem is how to do geometry sorting to support transparencies correctly. I know that sorting is very expensive if done on a per-polygon basis, so expensive that it is not even managed by Ogre. But still images from Ogre look right. Any ideas on how to do it and which data structures to use and their capabilities? I know people around is using: Octrees Kd-trees (someone on GameDev forum said that these are far better than Octrees) BSP (which should handle per-polygon ordering but are very expensive) BVH (but just for frustum and occlusion culling) Thank you Tunnuz

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  • Columnstore Case Study #2: Columnstore faster than SSAS Cube at DevCon Security

    - by aspiringgeek
    Preamble This is the second in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in my big deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. See also Columnstore Case Study #1: MSIT SONAR Aggregations Why Columnstore? As stated previously, If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. The Customer DevCon Security provides home & business security services & has been in business for 135 years. I met DevCon personnel while speaking to the Utah County SQL User Group on 20 February 2012. (Thanks to TJ Belt (b|@tjaybelt) & Ben Miller (b|@DBADuck) for the invitation which serendipitously coincided with the height of ski season.) The App: DevCon Security Reporting: Optimized & Ad Hoc Queries DevCon users interrogate a SQL Server 2012 Analysis Services cube via SSRS. In addition, the SQL Server 2012 relational back end is the target of ad hoc queries; this DW back end is refreshed nightly during a brief maintenance window via conventional table partition switching. SSRS, SSAS, & MDX Conventional relational structures were unable to provide adequate performance for user interaction for the SSRS reports. An SSAS solution was implemented requiring personnel to ramp up technically, including learning enough MDX to satisfy requirements. Ad Hoc Queries Even though the fact table is relatively small—only 22 million rows & 33GB—the table was a typical DW table in terms of its width: 137 columns, any of which could be the target of ad hoc interrogation. As is common in DW reporting scenarios such as this, it is often nearly to optimize for such queries using conventional indexing. DevCon DBAs & developers attended PASS 2012 & were introduced to the marvels of columnstore in a session presented by Klaus Aschenbrenner (b|@Aschenbrenner) The Details Classic vs. columnstore before-&-after metrics are impressive. Scenario Conventional Structures Columnstore ? SSRS via SSAS 10 - 12 seconds 1 second >10x Ad Hoc 5-7 minutes (300 - 420 seconds) 1 - 2 seconds >100x Here are two charts characterizing this data graphically.  The first is a linear representation of Report Duration (in seconds) for Conventional Structures vs. Columnstore Indexes.  As is so often the case when we chart such significant deltas, the linear scale doesn’t expose some the dramatically improved values corresponding to the columnstore metrics.  Just to make it fair here’s the same data represented logarithmically; yet even here the values corresponding to 1 –2 seconds aren’t visible.  The Wins Performance: Even prior to columnstore implementation, at 10 - 12 seconds canned report performance against the SSAS cube was tolerable. Yet the 1 second performance afterward is clearly better. As significant as that is, imagine the user experience re: ad hoc interrogation. The difference between several minutes vs. one or two seconds is a game changer, literally changing the way users interact with their data—no mental context switching, no wondering when the results will appear, no preoccupation with the spinning mind-numbing hurry-up-&-wait indicators.  As we’ve commonly found elsewhere, columnstore indexes here provided performance improvements of one, two, or more orders of magnitude. Simplified Infrastructure: Because in this case a nonclustered columnstore index on a conventional DW table was faster than an Analysis Services cube, the entire SSAS infrastructure was rendered superfluous & was retired. PASS Rocks: Once again, the value of attending PASS is proven out. The trip to Charlotte combined with eager & enquiring minds let directly to this success story. Find out more about the next PASS Summit here, hosted this year in Seattle on November 4 - 7, 2014. DevCon BI Team Lead Nathan Allan provided this unsolicited feedback: “What we found was pretty awesome. It has been a game changer for us in terms of the flexibility we can offer people that would like to get to the data in different ways.” Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the second in a series of reports on columnstore implementations, results from DevCon Security, a live customer production app for which performance increased by factors of from 10x to 100x for all report queries, including canned queries as well as reducing time for results for ad hoc queries from 5 - 7 minutes to 1 - 2 seconds. As a result of columnstore performance, the customer retired their SSAS infrastructure. I invite you to consider leveraging columnstore in your own environment. Let me know if you have any questions.

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  • Best practices for upgrading user data when updating versions of software

    - by Javy
    In my code I check the current version of the software on launch and compare it to the version stored in the user's data file(s). If the version is newer, then I call different methods to update the old data to the newer data version, if necessary. I usually have to make a new method to convert the data with each update that changes user data in some way, and cannot remove the old ones in case there was someone who missed an update. So the app must be able to go through each method call and update their data until they get their data current. With larger data sets, this could be a problem. In addition, I recently had a brief discussion with another StackOverflow user this and he indicated he always appended a date stamp to the filename to manage data versions, although his reasoning as to why this was better than storing the version data in the file itself was unclear. Since I've rarely seen management of user data versions in books I've read, I'm curious what are the best practices for naming user data files and procedures for updating older data to newer versions.

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  • How to tackle archived who-is personal data with opt-out?

    - by defaye
    As far as I understand it, it is possible to opt-out (in the UK at least) of having your address details displayed on who-is information of a domain for non-trading individuals. What I want to know is, after opt-out, how do individuals combat archived data? Is there any enforcement of this? How many who-is websites are there which archive data and what rights do we have to force them to remove that data without paying absurd fees? In the case of capitulating to these scoundrels, what point is it in paying for the removal of archived data if that data can presumably resurface on another who-is repository? In other words, what strategy is one supposed to take, besides being wiser after the fact?

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  • Ado.net performance:What does SNIReadSync do?

    - by Beatles1692
    We have a query that takes 2 seconds to run in Sql Server Management Studio but it takes 13 seconds to be shown on a client screen. I used dotTrace to profile my source code and noticed there is this SNIReadSync method (part of ADO.net assemblies)that takes a lot of time to do its job(9 seconds).I ran my source over server so I could omit the network effects and the result was the same. It doesn't matter if I'm using OleDBConnection or SqlConnection. It doesn't matter if I'm using a DataReader or a DataSet. Connection pooling does not solve this issue(as my result shows). I googled this issue and I couldn't find an answer to the question that what this method is actually doing and how we can improve it. here's what I found on StakOverFlow that's not helpful either: http://stackoverflow.com/questions/1610874/snireadsync-executing-between-120-500-ms-for-a-simple-query-what-do-i-look-for

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  • C# XDocument Attribute Performance Concerns

    - by Dested
    I have a loaded XDocument that I need to grab all the attributes that equal a certain value and is of a certain element efficiently. My current IEnumerable<XElement> vm; if (!cacher2.TryGetValue(name,out vm)) { vm = project.Descendants(XName.Get(name)); cacher2.Add(name, vm); } XElement[] abdl = (vm.Where(a => a.Attribute(attribute).Value == ab)).ToArray(); cacher2 is a Dictionary<string,IEnumerable<XElement>> The ToArray is so I can evaluate the expression now. I dont think this causes any real speed concerns. The problem is the Where itself. I am searching through anywhere from 1 to 10k items. Any help?

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  • Improving long-polling Ajax performance

    - by Bears will eat you
    I'm writing a webapp (Firefox-compatible only) which uses long polling (via jQuery's ajax abilities) to send more-or-less constant updates from the server to the client. I'm concerned about the effects of leaving this running for long periods of time, say, all day or overnight. The basic code skeleton is this: function processResults(xml) { // do stuff with the xml from the server } function fetch() { setTimeout(function () { $.ajax({ type: 'GET', url: 'foo/bar/baz', dataType: 'xml', success: function (xml) { processResults(xml); fetch(); }, error: function (xhr, type, exception) { if (xhr.status === 0) { console.log('XMLHttpRequest cancelled'); } else { console.debug(xhr); fetch(); } } }); }, 500); } (The half-second "sleep" is so that the client doesn't hammer the server if the updates are coming back to the client quickly - which they usually are.) After leaving this running overnight, it tends to make Firefox crawl. I'd been thinking that this could be partially caused by a large stack depth since I've basically written an infinitely recursive function. However, if I use Firebug and throw a breakpoint into fetch, it looks like this is not the case. The stack that Firebug shows me is only about 4 or 5 frames deep, even after an hour. One of the solutions I'm considering is changing my recursive function to an iterative one, but I can't figure out how I would insert the delay in between Ajax requests without spinning. I've looked at the JS 1.7 "yield" keyword but I can't quite wrap my head around it, to figure out if it's what I need here. Is the best solution just to do a hard refresh on the page periodically, say, once every hour? Is there a better/leaner long-polling design pattern that won't put a hurt on the browser even after running for 8 or 12 hours? Or should I just skip the long polling altogether and use a different "constant update" pattern since I usually know how frequently the server will have a response for me?

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  • Updating multiple Sprites - AS3 performance best practices

    - by dani
    Within the container "BubbleContainer" I have multiple "Bubble sprites". Each bubble's graphics object (a circle) is updated on a timer event. Let's say I have 50 Bubble sprites and each circle's radius should be updated with a mathematical formula. How do I organize this logic? How do I update all Bubble sprites within the BubbleContainer? (should I call a bubble.update() function or make a temporary reference to the graphics object?) Where do I put the Math logic? (as static functions?)

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  • jQuery selector performance

    - by rahul
    I have the following two code blocks. Code block 1 var checkboxes = $("div.c1 > input:checkbox.c2", "#main"); var totalCheckboxes = checkboxes.length; var checkedCheckboxes = checkboxes.filter(":checked").length; Code block 2 var totalCheckBoxes = $("div.c1 > input:checkbox.c2", "#main").length; var checkedCheckBoxes = $("div.c1 > input:checkbox.c2:checked", "#main").length; Which one of the above will be faster? Thanks, Rahul

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  • Performance penalty of typecasting and boxing/unboxing types in C# when storing generic values

    - by kitsune
    I have a set-up similar to WPF's DependencyProperty and DependencyObject system. My properties however are generic. A BucketProperty has a static GlobalIndex (defined in BucketPropertyBase) which tracks all BucketProperties. A Bucket can have many BucketProperties of any type. A Bucket saves and gets the actual values of these BucketProperties... now my question is, how to deal with the storage of these values, and what is the penalty of using a typecasting when retrieving them? I currently use an array of BucketEntries that save the property values as simple objects. Is there any better way of saving and returning these values? Beneath is a simpliefied version: public class BucketProperty<T> : BucketPropertyBase { } public class Bucket { private BucketEntry[] _bucketEntries; public void SaveValue<T>(BucketProperty<T> property, T value) { SaveBucketEntry(property.GlobalIndex, value) } public T GetValue<T>(BucketProperty<T> property) { return (T)FindBucketEntry(property.GlobalIndex).Value; } } public class BucketEntry { private object _value; private uint _index; public BucketEntry(uint globalIndex, object value) { ... } }

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  • Elisp performance on Windows and Linux

    - by JasonFruit
    I have the following dead simple elisp functions; the first removes the fill breaks from the current paragraph, and the second loops through the current document applying the first to each paragraph in turn, in effect removing all single line-breaks from the document. It runs fast on my low-spec Puppy Linux box using emacs 22.3 (10 seconds for 600 pages of Thomas Aquinas), but when I go to a powerful Windows XP machine with emacs 21.3, it takes almost an hour to do the same document. What can I do to make it run as well on the Windows machine with emacs 21.3? (defun remove-line-breaks () "Remove line endings in a paragraph." (interactive) (let ((fill-column 90002000)) (fill-paragraph nil))) : (defun remove-all-line-breaks () "Remove all single line-breaks in a document" (interactive) (while (not (= (point) (buffer-end 1))) (remove-line-breaks) (next-line 1))) Forgive my poor elisp; I'm having great fun learning Lisp and starting to use the power of emacs, but I'm new to it yet.

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  • Auto load a specific link at various time intervals

    - by user228837
    Here's what I need to do. I'm using Google Chrome. I have page that auto-reloads every 5 seconds using a script: javascript: timeout=prompt("Set timeout [s]"); current=location.href; if(timeout>0) setTimeout('reload()',1000*timeout); else location.replace(current); function reload() { setTimeout('reload()',1000*timeout); fr4me='<frameset cols=\'*\'>\n<frame src=\''+current+'\'/>'; fr4me+='</frameset>'; with(document){write(fr4me);void(close())}; } I found that script by Googling. The reason why the page auto-reloads every 5 seconds is I'm waiting for a specific link or url to appear in the page. It appears at random times. Once I see the link I'm waiting for, I immediately click the link. That's fine. But I want more. What I want is the page will auto-reload and I want it to auto-detect the the link I'm waiting for. Once the script finds the link I'm waiting for, it automatically loads that link on a new tab or page. For example, I'm auto-reloading www.example.com. I'm waiting for a specific url "BUY NOW". When the page auto-reloads, it checks if there's a url "BUY NOW". If it sees one, it should automatically open that link. Thanks.

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