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  • split a database web application - good idea or bad idea?

    - by Khou
    Is it a bad idea to split up a application and the database? Application1 uses database1 on ServerX Application2 uses database2 on ServerY Both application communicates over web service API, they are apart of the same application, one application is used to manage user's profile/personal data, while the other application is used to manages user's financial data. Or should just put them together and just use 1 database on the same server?

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  • How to choose between UUIDs, autoincrement/sequence keys and sequence tables for database primary keys?

    - by Tim
    I'm looking at the pros and cons of these three primary methods of coming up with primary keys for database rows. So assuming I am using a database that supports more than one of these methods, is there a simple heuristic to determine what the best option would be for me? How do considerations such a distributed/multiple masters, performance requirements, ORM use, security and testing have on the choice? Any unexpected drawbacks that one might run into?

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  • How to restore your production database without needing additional storage

    - by David Atkinson
    Production databases can get very large. This in itself is to be expected, but when a copy of the database is needed the database must be restored, requiring additional and costly storage.  For example, if you want to give each developer a full copy of your production server, you’ll need n times the storage cost for your n-developer team. The same is true for any test databases that are created during the course of your project lifecycle. If you’ve read my previous blog posts, you’ll be aware that I’ve been focusing on the database continuous integration theme. In my CI setup I create a “production”-equivalent database directly from its source control representation, and use this to test my upgrade scripts. Despite this being a perfectly valid and practical thing to do as part of a CI setup, it’s not the exact equivalent to running the upgrade script on a copy of the actual production database. So why shouldn’t I instead simply restore the most recent production backup as part of my CI process? There are two reasons why this would be impractical. 1. My CI environment isn’t an exact copy of my production environment. Indeed, this would be the case in a perfect world, and it is strongly recommended as a good practice if you follow Jez Humble and David Farley’s “Continuous Delivery” teachings, but in practical terms this might not always be possible, especially where storage is concerned. It may just not be possible to restore a huge production database on the environment you’ve been allotted. 2. It’s not just about the storage requirements, it’s also the time it takes to do the restore. The whole point of continuous integration is that you are alerted as early as possible whether the build (yes, the database upgrade script counts!) is broken. If I have to run an hour-long restore each time I commit a change to source control I’m just not going to get the feedback quickly enough to react. So what’s the solution? Red Gate has a technology, SQL Virtual Restore, that is able to restore a database without using up additional storage. Although this sounds too good to be true, the explanation is quite simple (although I’m sure the technical implementation details under the hood are quite complex!) Instead of restoring the backup in the conventional sense, SQL Virtual Restore will effectively mount the backup using its HyperBac technology. It creates a data and log file, .vmdf, and .vldf, that becomes the delta between the .bak file and the virtual database. This means that both read and write operations are permitted on a virtual database as from SQL Server’s point of view it is no different from a conventional database. Instead of doubling the storage requirements upon a restore, there is no ‘duplicate’ storage requirements, other than the trivially small virtual log and data files (see illustration below). The benefit is magnified the more databases you mount to the same backup file. This technique could be used to provide a large development team a full development instance of a large production database. It is also incredibly easy to set up. Once SQL Virtual Restore is installed, you simply run a conventional RESTORE command to create the virtual database. This is what I have running as part of a nightly “release test” process triggered by my CI tool. RESTORE DATABASE WidgetProduction_Virtual FROM DISK=N'D:\VirtualDatabase\WidgetProduction.bak' WITH MOVE N'WidgetProduction' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_WidgetProduction_Virtual.vmdf', MOVE N'WidgetProduction_log' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_log_WidgetProduction_Virtual.vldf', NORECOVERY, STATS=1, REPLACE GO RESTORE DATABASE WidgetProduction_Virtual WITH RECOVERY   Note the only change from what you would do normally is the naming of the .vmdf and .vldf files. SQL Virtual Restore intercepts this by monitoring the extension and applies its magic, ensuring the ‘virtual’ restore happens rather than the conventional storage-heavy restore. My automated release test then applies the upgrade scripts to the virtual production database and runs some validation tests, giving me confidence that were I to run this on production for real, all would go smoothly. For illustration, here is my 8Gb production database: And its corresponding backup file: Here are the .vldf and .vmdf files, which represent the only additional used storage for the new database following the virtual restore.   The beauty of this product is its simplicity. Once it is installed, the interaction with the backup and virtual database is exactly the same as before, as the clever stuff is being done at a lower level. SQL Virtual Restore can be downloaded as a fully functional 14-day trial. Technorati Tags: SQL Server

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  • How to restore your production database without needing additional storage

    - by David Atkinson
    Production databases can get very large. This in itself is to be expected, but when a copy of the database is needed the database must be restored, requiring additional and costly storage.  For example, if you want to give each developer a full copy of your production server, you'll need n times the storage cost for your n-developer team. The same is true for any test databases that are created during the course of your project lifecycle. If you've read my previous blog posts, you'll be aware that I've been focusing on the database continuous integration theme. In my CI setup I create a "production"-equivalent database directly from its source control representation, and use this to test my upgrade scripts. Despite this being a perfectly valid and practical thing to do as part of a CI setup, it's not the exact equivalent to running the upgrade script on a copy of the actual production database. So why shouldn't I instead simply restore the most recent production backup as part of my CI process? There are two reasons why this would be impractical. 1. My CI environment isn't an exact copy of my production environment. Indeed, this would be the case in a perfect world, and it is strongly recommended as a good practice if you follow Jez Humble and David Farley's "Continuous Delivery" teachings, but in practical terms this might not always be possible, especially where storage is concerned. It may just not be possible to restore a huge production database on the environment you've been allotted. 2. It's not just about the storage requirements, it's also the time it takes to do the restore. The whole point of continuous integration is that you are alerted as early as possible whether the build (yes, the database upgrade script counts!) is broken. If I have to run an hour-long restore each time I commit a change to source control I'm just not going to get the feedback quickly enough to react. So what's the solution? Red Gate has a technology, SQL Virtual Restore, that is able to restore a database without using up additional storage. Although this sounds too good to be true, the explanation is quite simple (although I'm sure the technical implementation details under the hood are quite complex!) Instead of restoring the backup in the conventional sense, SQL Virtual Restore will effectively mount the backup using its HyperBac technology. It creates a data and log file, .vmdf, and .vldf, that becomes the delta between the .bak file and the virtual database. This means that both read and write operations are permitted on a virtual database as from SQL Server's point of view it is no different from a conventional database. Instead of doubling the storage requirements upon a restore, there is no 'duplicate' storage requirements, other than the trivially small virtual log and data files (see illustration below). The benefit is magnified the more databases you mount to the same backup file. This technique could be used to provide a large development team a full development instance of a large production database. It is also incredibly easy to set up. Once SQL Virtual Restore is installed, you simply run a conventional RESTORE command to create the virtual database. This is what I have running as part of a nightly "release test" process triggered by my CI tool. RESTORE DATABASE WidgetProduction_virtual FROM DISK=N'C:\WidgetWF\ProdBackup\WidgetProduction.bak' WITH MOVE N'WidgetProduction' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_WidgetProduction_Virtual.vmdf', MOVE N'WidgetProduction_log' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_log_WidgetProduction_Virtual.vldf', NORECOVERY, STATS=1, REPLACE GO RESTORE DATABASE mydatabase WITH RECOVERY   Note the only change from what you would do normally is the naming of the .vmdf and .vldf files. SQL Virtual Restore intercepts this by monitoring the extension and applies its magic, ensuring the 'virtual' restore happens rather than the conventional storage-heavy restore. My automated release test then applies the upgrade scripts to the virtual production database and runs some validation tests, giving me confidence that were I to run this on production for real, all would go smoothly. For illustration, here is my 8Gb production database: And its corresponding backup file: Here are the .vldf and .vmdf files, which represent the only additional used storage for the new database following the virtual restore.   The beauty of this product is its simplicity. Once it is installed, the interaction with the backup and virtual database is exactly the same as before, as the clever stuff is being done at a lower level. SQL Virtual Restore can be downloaded as a fully functional 14-day trial. Technorati Tags: SQL Server

    Read the article

  • How to restore your production database without needing additional storage

    - by David Atkinson
    Production databases can get very large. This in itself is to be expected, but when a copy of the database is needed the database must be restored, requiring additional and costly storage.  For example, if you want to give each developer a full copy of your production server, you'll need n times the storage cost for your n-developer team. The same is true for any test databases that are created during the course of your project lifecycle. If you've read my previous blog posts, you'll be aware that I've been focusing on the database continuous integration theme. In my CI setup I create a "production"-equivalent database directly from its source control representation, and use this to test my upgrade scripts. Despite this being a perfectly valid and practical thing to do as part of a CI setup, it's not the exact equivalent to running the upgrade script on a copy of the actual production database. So why shouldn't I instead simply restore the most recent production backup as part of my CI process? There are two reasons why this would be impractical. 1. My CI environment isn't an exact copy of my production environment. Indeed, this would be the case in a perfect world, and it is strongly recommended as a good practice if you follow Jez Humble and David Farley's "Continuous Delivery" teachings, but in practical terms this might not always be possible, especially where storage is concerned. It may just not be possible to restore a huge production database on the environment you've been allotted. 2. It's not just about the storage requirements, it's also the time it takes to do the restore. The whole point of continuous integration is that you are alerted as early as possible whether the build (yes, the database upgrade script counts!) is broken. If I have to run an hour-long restore each time I commit a change to source control I'm just not going to get the feedback quickly enough to react. So what's the solution? Red Gate has a technology, SQL Virtual Restore, that is able to restore a database without using up additional storage. Although this sounds too good to be true, the explanation is quite simple (although I'm sure the technical implementation details under the hood are quite complex!) Instead of restoring the backup in the conventional sense, SQL Virtual Restore will effectively mount the backup using its HyperBac technology. It creates a data and log file, .vmdf, and .vldf, that becomes the delta between the .bak file and the virtual database. This means that both read and write operations are permitted on a virtual database as from SQL Server's point of view it is no different from a conventional database. Instead of doubling the storage requirements upon a restore, there is no 'duplicate' storage requirements, other than the trivially small virtual log and data files (see illustration below). The benefit is magnified the more databases you mount to the same backup file. This technique could be used to provide a large development team a full development instance of a large production database. It is also incredibly easy to set up. Once SQL Virtual Restore is installed, you simply run a conventional RESTORE command to create the virtual database. This is what I have running as part of a nightly "release test" process triggered by my CI tool. RESTORE DATABASE WidgetProduction_virtual FROM DISK=N'C:\WidgetWF\ProdBackup\WidgetProduction.bak' WITH MOVE N'WidgetProduction' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_WidgetProduction_Virtual.vmdf', MOVE N'WidgetProduction_log' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_log_WidgetProduction_Virtual.vldf', NORECOVERY, STATS=1, REPLACE GO RESTORE DATABASE mydatabase WITH RECOVERY   Note the only change from what you would do normally is the naming of the .vmdf and .vldf files. SQL Virtual Restore intercepts this by monitoring the extension and applies its magic, ensuring the 'virtual' restore happens rather than the conventional storage-heavy restore. My automated release test then applies the upgrade scripts to the virtual production database and runs some validation tests, giving me confidence that were I to run this on production for real, all would go smoothly. For illustration, here is my 8Gb production database: And its corresponding backup file: Here are the .vldf and .vmdf files, which represent the only additional used storage for the new database following the virtual restore.   The beauty of this product is its simplicity. Once it is installed, the interaction with the backup and virtual database is exactly the same as before, as the clever stuff is being done at a lower level. SQL Virtual Restore can be downloaded as a fully functional 14-day trial. Technorati Tags: SQL Server

    Read the article

  • What's the format of Real World Performance Day?

    - by william.hardie
    A question that has cropped a lot of late is "what's the format of Real World Performance Day?" Not an unreasonable question you might think. Sure enough, a quick check of the Independent Oracle User Group's website tells us a bit about the Real World Performance Day event, but no formal agenda? This was one of the questions I posed to Tom Kyte (one of the main presenters) in our recent podcast. Tom tells us that this isn't your traditional event where one speaker follows another with loads of slides. In fact, the Real World Performance Day features Tom and fellow Oracle performance experts - Andrew Holdsworth and Graham Wood - continuously on stage throughout the day. All three will be discussing database performance challenges and solutions from development, architectural design and management perspectives. There's going to be multi-terabyte demos on show, less of the traditional slides, and more interactive debate and discussion going on. Tune-in and hear what else Tom has to say about this fairly unique event!

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  • ROracle support for TimesTen In-Memory Database

    - by Sam Drake
    Today's guest post comes from Jason Feldhaus, a Consulting Member of Technical Staff in the TimesTen Database organization at Oracle.  He shares with us a sample session using ROracle with the TimesTen In-Memory database.  Beginning in version 1.1-4, ROracle includes support for the Oracle Times Ten In-Memory Database, version 11.2.2. TimesTen is a relational database providing very fast and high throughput through its memory-centric architecture.  TimesTen is designed for low latency, high-volume data, and event and transaction management. A TimesTen database resides entirely in memory, so no disk I/O is required for transactions and query operations. TimesTen is used in applications requiring very fast and predictable response time, such as real-time financial services trading applications and large web applications. TimesTen can be used as the database of record or as a relational cache database to Oracle Database. ROracle provides an interface between R and the database, providing the rich functionality of the R statistical programming environment using the SQL query language. ROracle uses the OCI libraries to handle database connections, providing much better performance than standard ODBC.The latest ROracle enhancements include: Support for Oracle TimesTen In-Memory Database Support for Date-Time using R's POSIXct/POSIXlt data types RAW, BLOB and BFILE data type support Option to specify number of rows per fetch operation Option to prefetch LOB data Break support using Ctrl-C Statement caching support Times Ten 11.2.2 contains enhanced support for analytics workloads and complex queries: Analytic functions: AVG, SUM, COUNT, MAX, MIN, DENSE_RANK, RANK, ROW_NUMBER, FIRST_VALUE and LAST_VALUE Analytic clauses: OVER PARTITION BY and OVER ORDER BY Multidimensional grouping operators: Grouping clauses: GROUP BY CUBE, GROUP BY ROLLUP, GROUP BY GROUPING SETS Grouping functions: GROUP, GROUPING_ID, GROUP_ID WITH clause, which allows repeated references to a named subquery block Aggregate expressions over DISTINCT expressions General expressions that return a character string in the source or a pattern within the LIKE predicate Ability to order nulls first or last in a sort result (NULLS FIRST or NULLS LAST in the ORDER BY clause) Note: Some functionality is only available with Oracle Exalytics, refer to the TimesTen product licensing document for details. Connecting to TimesTen is easy with ROracle. Simply install and load the ROracle package and load the driver. > install.packages("ROracle") > library(ROracle) Loading required package: DBI > drv <- dbDriver("Oracle") Once the ROracle package is installed, create a database connection object and connect to a TimesTen direct driver DSN as the OS user. > conn <- dbConnect(drv, username ="", password="", dbname = "localhost/SampleDb_1122:timesten_direct") You have the option to report the server type - Oracle or TimesTen? > print (paste ("Server type =", dbGetInfo (conn)$serverType)) [1] "Server type = TimesTen IMDB" To create tables in the database using R data frame objects, use the function dbWriteTable. In the following example we write the built-in iris data frame to TimesTen. The iris data set is a small example data set containing 150 rows and 5 columns. We include it here not to highlight performance, but so users can easily run this example in their R session. > dbWriteTable (conn, "IRIS", iris, overwrite=TRUE, ora.number=FALSE) [1] TRUE Verify that the newly created IRIS table is available in the database. To list the available tables and table columns in the database, use dbListTables and dbListFields, respectively. > dbListTables (conn) [1] "IRIS" > dbListFields (conn, "IRIS") [1] "SEPAL.LENGTH" "SEPAL.WIDTH" "PETAL.LENGTH" "PETAL.WIDTH" "SPECIES" To retrieve a summary of the data from the database we need to save the results to a local object. The following call saves the results of the query as a local R object, iris.summary. The ROracle function dbGetQuery is used to execute an arbitrary SQL statement against the database. When connected to TimesTen, the SQL statement is processed completely within main memory for the fastest response time. > iris.summary <- dbGetQuery(conn, 'SELECT SPECIES, AVG ("SEPAL.LENGTH") AS AVG_SLENGTH, AVG ("SEPAL.WIDTH") AS AVG_SWIDTH, AVG ("PETAL.LENGTH") AS AVG_PLENGTH, AVG ("PETAL.WIDTH") AS AVG_PWIDTH FROM IRIS GROUP BY ROLLUP (SPECIES)') > iris.summary SPECIES AVG_SLENGTH AVG_SWIDTH AVG_PLENGTH AVG_PWIDTH 1 setosa 5.006000 3.428000 1.462 0.246000 2 versicolor 5.936000 2.770000 4.260 1.326000 3 virginica 6.588000 2.974000 5.552 2.026000 4 <NA> 5.843333 3.057333 3.758 1.199333 Finally, disconnect from the TimesTen Database. > dbCommit (conn) [1] TRUE > dbDisconnect (conn) [1] TRUE We encourage you download Oracle software for evaluation from the Oracle Technology Network. See these links for our software: Times Ten In-Memory Database,  ROracle.  As always, we welcome comments and questions on the TimesTen and  Oracle R technical forums.

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  • Analysing Group & Individual Member Performance -RUP

    - by user23871
    I am writing a report which requires the analysis of performance of each individual team member. This is for a software development project developed using the Unified Process (UP). I was just wondering if there are any existing group & individual appraisal metrics used so I don't have to reinvent the wheel... EDIT This is by no means correct but something like: Individual Contribution (IC) = time spent (individual) / time spent (total) = Performance = ? (should use individual contribution (IC) combined with something to gain a measure of overall performance).... Maybe I am talking complete hash and I know generally its really difficult to analyse performance with numbers but any mathematicians out there that can lend a hand or know a somewhat more accurate method of analysing performance than arbitrary marking (e.g. 8 out 10)

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  • SQL SERVER – ?Finding Out What Changed in a Deleted Database – Notes from the Field #041

    - by Pinal Dave
    [Note from Pinal]: This is a 41th episode of Notes from the Field series. The real world is full of challenges. When we are reading theory or book, we sometimes do not realize how real world reacts works and that is why we have the series notes from the field, which is extremely popular with developers and DBA. Let us talk about interesting problem of how to figure out what has changed in the DELETED database. Well, you think I am just throwing the words but in reality this kind of problems are making our DBA’s life interesting and in this blog post we have amazing story from Brian Kelley about the same subject. In this episode of the Notes from the Field series database expert Brian Kelley explains a how to find out what has changed in deleted database. Read the experience of Brian in his own words. Sometimes, one of the hardest questions to answer is, “What changed?” A similar question is, “Did anything change other than what we expected to change?” The First Place to Check – Schema Changes History Report: Pinal has recently written on the Schema Changes History report and its requirement for the Default Trace to be enabled. This is always the first place I look when I am trying to answer these questions. There are a couple of obvious limitations with the Schema Changes History report. First, while it reports what changed, when it changed, and who changed it, other than the base DDL operation (CREATE, ALTER, DELETE), it does not present what the changes actually were. This is not something covered by the default trace. Second, the default trace has a fixed size. When it hits that size, the changes begin to overwrite. As a result, if you wait too long, especially on a busy database server, you may find your changes rolled off. But the Database Has Been Deleted! Pinal cited another issue, and that’s the inability to run the Schema Changes History report if the database has been dropped. Thankfully, all is not lost. One thing to remember is that the Schema Changes History report is ultimately driven by the Default Trace. As you may have guess, it’s a trace, like any other database trace. And the Default Trace does write to disk. The trace files are written to the defined LOG directory for that SQL Server instance and have a prefix of log_: Therefore, you can read the trace files like any other. Tip: Copy the files to a working directory. Otherwise, you may occasionally receive a file in use error. With the Default Trace files, if you ask the question early enough, you can see the information for a deleted database just the same as any other database. Testing with a Deleted Database: Here’s a short script that will create a database, create a schema, create an object, and then drop the database. Without the database, you can’t do a standard Schema Changes History report. CREATE DATABASE DeleteMe; GO USE DeleteMe; GO CREATE SCHEMA Test AUTHORIZATION dbo; GO CREATE TABLE Test.Foo (FooID INT); GO USE MASTER; GO DROP DATABASE DeleteMe; GO This sets up the perfect situation where we can’t retrieve the information using the Schema Changes History report but where it’s still available. Finding the Information: I’ve sorted the columns so I can see the Event Subclass, the Start Time, the Database Name, the Object Name, and the Object Type at the front, but otherwise, I’m just looking at the trace files using SQL Profiler. As you can see, the information is definitely there: Therefore, even in the case of a dropped/deleted database, you can still determine who did what and when. You can even determine who dropped the database (loginame is captured). The key is to get the default trace files in a timely manner in order to extract the information. If you want to get started with performance tuning and database security with the help of experts, read more over at Fix Your SQL Server. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Notes from the Field, PostADay, SQL, SQL Authority, SQL Query, SQL Security, SQL Server, SQL Tips and Tricks, T SQL

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  • Installation of Access Database Engine 32-bit Fails

    - by Rayzor78
    I am trying to install Access Database Engine 2007 32-bit. The splash screen comes up, you click "Next", then it fails with the error: Installation ended prematurely because of an error You click "OK" and another error window says: The installation of the package failed. The exact same situation happens when I try this with Access Database Engine 2010 32-bit. This production server is running Windows Server 2008 R2 SP1 64-bit. Before I tried installing Access Database Engine 32-bit, I first needed to install Microsoft Office 2010 Pro (Excel and Office Tools only). I tried the 32-bit version on the production server since that is how I set it up in our Dev environment. No luck. The 32-bit version would not install. I did NOT get the error "You have 64-bit components of Office installed". I simply received the exact same two errors listed above. So, I knew that 32-bit/64-bit did not really matter for the Office install for my project, so I installed 64-bit of Office Pro 2010 (Excel and Office Tools only) with no problems. I have a requirement that I need to have the 32-bit version of the Access Database Engine installed. 2007 or 2010, doesn't matter. I cannot use the 64-bit version of Access Database Engine 2010 because my SSIS package will not work with it. I require the 32-bit version. I've tried several steps to try to get it installed. I seriously think that the production server has some aversion to installing 32-bit applications. Here's what I've tried: Tried installing via command line with the "/passive" switch....no luck. Tried numerous iterations to copy the install file to the server (downloaded a fresh copy directly to the server, downloaded a fresh copy to my local machine then copied it over, copied it over zipped up) (http://social.msdn.microsoft.com/Forums/en-US/sqldataaccess/thread/efd3c1f0-07cd-45ca-a626-2dd0c7ac3e9f). Tried Method 1 from this link. Could not try Method 2 because it requires a server reboot and in my environment that requires a long change management process. I've verified that I am a local administrator on the server. (Evidence, I am able to install other applications (office 64-bit per above)). Verified that there are no other office products that should be blocking the installation. The fore-mentioned install of Excel 2010 64-bit was the first Office product installed on the server. VERY ODD: To test my theory that the production server does not like 32-bit applications, I installed something lightweight. I installed 7-Zip 32-bit on the production server with no problems whatsoever. Here are some things that I have not tried (i will follow-up once I do): Method 2 (as mentioned above). Requires a server reboot. Have not verified that the Dev and Production environments are 100% identical. I've done a cursory check and on the surface they appear to be the same (same OS and SP version). I need to do a deeper dive to be 100% certain. I had no problems in my Dev environment. In Dev, I installed Office 2010 Pro 64-bit (Excel & Office Tools only) then via command line w/ the "/passive" switch, installed Access Database Engine 2010 32-bit. I don't know what else to try. Any suggestions or comments?

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  • ROracle support for TimesTen In-Memory Database

    - by Sherry LaMonica
    Today's guest post comes from Jason Feldhaus, a Consulting Member of Technical Staff in the TimesTen Database organization at Oracle.  He shares with us a sample session using ROracle with the TimesTen In-Memory database.  Beginning in version 1.1-4, ROracle includes support for the Oracle Times Ten In-Memory Database, version 11.2.2. TimesTen is a relational database providing very fast and high throughput through its memory-centric architecture.  TimesTen is designed for low latency, high-volume data, and event and transaction management. A TimesTen database resides entirely in memory, so no disk I/O is required for transactions and query operations. TimesTen is used in applications requiring very fast and predictable response time, such as real-time financial services trading applications and large web applications. TimesTen can be used as the database of record or as a relational cache database to Oracle Database. ROracle provides an interface between R and the database, providing the rich functionality of the R statistical programming environment using the SQL query language. ROracle uses the OCI libraries to handle database connections, providing much better performance than standard ODBC.The latest ROracle enhancements include: Support for Oracle TimesTen In-Memory Database Support for Date-Time using R's POSIXct/POSIXlt data types RAW, BLOB and BFILE data type support Option to specify number of rows per fetch operation Option to prefetch LOB data Break support using Ctrl-C Statement caching support Times Ten 11.2.2 contains enhanced support for analytics workloads and complex queries: Analytic functions: AVG, SUM, COUNT, MAX, MIN, DENSE_RANK, RANK, ROW_NUMBER, FIRST_VALUE and LAST_VALUE Analytic clauses: OVER PARTITION BY and OVER ORDER BY Multidimensional grouping operators: Grouping clauses: GROUP BY CUBE, GROUP BY ROLLUP, GROUP BY GROUPING SETS Grouping functions: GROUP, GROUPING_ID, GROUP_ID WITH clause, which allows repeated references to a named subquery block Aggregate expressions over DISTINCT expressions General expressions that return a character string in the source or a pattern within the LIKE predicate Ability to order nulls first or last in a sort result (NULLS FIRST or NULLS LAST in the ORDER BY clause) Note: Some functionality is only available with Oracle Exalytics, refer to the TimesTen product licensing document for details. Connecting to TimesTen is easy with ROracle. Simply install and load the ROracle package and load the driver. > install.packages("ROracle") > library(ROracle) Loading required package: DBI > drv <- dbDriver("Oracle") Once the ROracle package is installed, create a database connection object and connect to a TimesTen direct driver DSN as the OS user. > conn <- dbConnect(drv, username ="", password="", dbname = "localhost/SampleDb_1122:timesten_direct") You have the option to report the server type - Oracle or TimesTen? > print (paste ("Server type =", dbGetInfo (conn)$serverType)) [1] "Server type = TimesTen IMDB" To create tables in the database using R data frame objects, use the function dbWriteTable. In the following example we write the built-in iris data frame to TimesTen. The iris data set is a small example data set containing 150 rows and 5 columns. We include it here not to highlight performance, but so users can easily run this example in their R session. > dbWriteTable (conn, "IRIS", iris, overwrite=TRUE, ora.number=FALSE) [1] TRUE Verify that the newly created IRIS table is available in the database. To list the available tables and table columns in the database, use dbListTables and dbListFields, respectively. > dbListTables (conn) [1] "IRIS" > dbListFields (conn, "IRIS") [1] "SEPAL.LENGTH" "SEPAL.WIDTH" "PETAL.LENGTH" "PETAL.WIDTH" "SPECIES" To retrieve a summary of the data from the database we need to save the results to a local object. The following call saves the results of the query as a local R object, iris.summary. The ROracle function dbGetQuery is used to execute an arbitrary SQL statement against the database. When connected to TimesTen, the SQL statement is processed completely within main memory for the fastest response time. > iris.summary <- dbGetQuery(conn, 'SELECT SPECIES, AVG ("SEPAL.LENGTH") AS AVG_SLENGTH, AVG ("SEPAL.WIDTH") AS AVG_SWIDTH, AVG ("PETAL.LENGTH") AS AVG_PLENGTH, AVG ("PETAL.WIDTH") AS AVG_PWIDTH FROM IRIS GROUP BY ROLLUP (SPECIES)') > iris.summary SPECIES AVG_SLENGTH AVG_SWIDTH AVG_PLENGTH AVG_PWIDTH 1 setosa 5.006000 3.428000 1.462 0.246000 2 versicolor 5.936000 2.770000 4.260 1.326000 3 virginica 6.588000 2.974000 5.552 2.026000 4 <NA> 5.843333 3.057333 3.758 1.199333 Finally, disconnect from the TimesTen Database. > dbCommit (conn) [1] TRUE > dbDisconnect (conn) [1] TRUE We encourage you download Oracle software for evaluation from the Oracle Technology Network. See these links for our software: Times Ten In-Memory Database,  ROracle.  As always, we welcome comments and questions on the TimesTen and  Oracle R technical forums.

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  • Strange performance behaviour for 64 bit modulo operation

    - by codymanix
    The last three of these method calls take approx. double the time than the first four. The only difference is that their arguments doesn't fit in integer anymore. But should this matter? The parameter is declared to be long, so it should use long for calculation anyway. Does the modulo operation use another algorithm for numbersmaxint? I am using amd athlon64 3200+, winxp sp3 and vs2008. Stopwatch sw = new Stopwatch(); TestLong(sw, int.MaxValue - 3l); TestLong(sw, int.MaxValue - 2l); TestLong(sw, int.MaxValue - 1l); TestLong(sw, int.MaxValue); TestLong(sw, int.MaxValue + 1l); TestLong(sw, int.MaxValue + 2l); TestLong(sw, int.MaxValue + 3l); Console.ReadLine(); static void TestLong(Stopwatch sw, long num) { long n = 0; sw.Reset(); sw.Start(); for (long i = 3; i < 20000000; i++) { n += num % i; } sw.Stop(); Console.WriteLine(sw.Elapsed); } EDIT: I now tried the same with C and the issue does not occur here, all modulo operations take the same time, in release and in debug mode with and without optimizations turned on: #include "stdafx.h" #include "time.h" #include "limits.h" static void TestLong(long long num) { long long n = 0; clock_t t = clock(); for (long long i = 3; i < 20000000LL*100; i++) { n += num % i; } printf("%d - %lld\n", clock()-t, n); } int main() { printf("%i %i %i %i\n\n", sizeof (int), sizeof(long), sizeof(long long), sizeof(void*)); TestLong(3); TestLong(10); TestLong(131); TestLong(INT_MAX - 1L); TestLong(UINT_MAX +1LL); TestLong(INT_MAX + 1LL); TestLong(LLONG_MAX-1LL); getchar(); return 0; } EDIT2: Thanks for the great suggestions. I found that both .net and c (in debug as well as in release mode) does't not use atomically cpu instructions to calculate the remainder but they call a function that does. In the c program I could get the name of it which is "_allrem". It also displayed full source comments for this file so I found the information that this algorithm special cases the 32bit divisors instead of dividends which was the case in the .net application. I also found out that the performance of the c program really is only affected by the value of the divisor but not the dividend. Another test showed that the performance of the remainder function in the .net program depends on both the dividend and divisor. BTW: Even simple additions of long long values are calculated by a consecutive add and adc instructions. So even if my processor calls itself 64bit, it really isn't :( EDIT3: I now ran the c app on a windows 7 x64 edition, compiled with visual studio 2010. The funny thing is, the performance behavior stays the same, although now (I checked the assembly source) true 64 bit instructions are used.

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  • C# performance varying due to memory

    - by user1107474
    Hope this is a valid post here, its a combination of C# issues and hardware. I am benchmarking our server because we have found problems with the performance of our quant library (written in C#). I have simulated the same performance issues with some simple C# code- performing very heavy memory-usage. The code below is in a function which is spawned from a threadpool, up to a maximum of 32 threads (because our server has 4x CPUs x 8 cores each). This is all on .Net 3.5 The problem is that we are getting wildly differing performance. I run the below function 1000 times. The average time taken for the code to run could be, say, 3.5s, but the fastest will only be 1.2s and the slowest will be 7s- for the exact same function! I have graphed the memory usage against the timings and there doesnt appear to be any correlation with the GC kicking in. One thing I did notice is that when running in a single thread the timings are identical and there is no wild deviation. I have also tested CPU-bound algorithms and the timings are identical too. This has made us wonder if the memory bus just cannot cope. I was wondering could this be another .net or C# problem, or is it something related to our hardware? Would this be the same experience if I had used C++, or Java?? We are using 4x Intel x7550 with 32GB ram. Is there any way around this problem in general? Stopwatch watch = new Stopwatch(); watch.Start(); List<byte> list1 = new List<byte>(); List<byte> list2 = new List<byte>(); List<byte> list3 = new List<byte>(); int Size1 = 10000000; int Size2 = 2 * Size1; int Size3 = Size1; for (int i = 0; i < Size1; i++) { list1.Add(57); } for (int i = 0; i < Size2; i = i + 2) { list2.Add(56); } for (int i = 0; i < Size3; i++) { byte temp = list1.ElementAt(i); byte temp2 = list2.ElementAt(i); list3.Add(temp); list2[i] = temp; list1[i] = temp2; } watch.Stop(); (the code is just meant to stress out the memory) I would include the threadpool code, but we used a non-standard threadpool library. EDIT: I have reduced "size1" to 100000, which basically doesn't use much memory and I still get a lot of jitter. This suggests it's not the amount of memory being transferred, but the frequency of memory grabs?

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  • AS 400 Performance from .Net iSeries Provider

    - by Nathan
    Hey all, First off, I am not an AS 400 guy - at all. So please forgive me for asking any noobish questions here. Basically, I am working on a .Net application that needs to access the AS400 for some real-time data. Although I have the system working, I am getting very different performance results between queries. Typically, when I make the 1st request against a SPROC on the AS400, I am seeing ~ 14 seconds to get the full data set. After that initial call, any subsequent calls usually only take ~ 1 second to return. This performance improvement remains for ~ 20 mins or so before it takes 14 seconds again. The interesting part with this is that, if the stored procedure is executed directly on the iSeries Navigator, it always returns within milliseconds (no change in response time). I wonder if it is a caching / execution plan issue but I can only apply my SQL SERVER logic to the AS400, which is not always a match. Any suggestions on what I can do to recieve a more consistant response time or simply insight as to why the AS400 is acting in this manner when I was using the iSeries Data Provider for .Net? Is there a better access method that I should use? Just in case, here's the code I am using to connect to the AS400 Dim Conn As New IBM.Data.DB2.iSeries.iDB2Connection(ConnectionString) Dim Cmd As New IBM.Data.DB2.iSeries.iDB2Command("SPROC_NAME_HERE", Conn) Cmd.CommandType = CommandType.StoredProcedure Using Conn Conn.Open() Dim Reader = Cmd.ExecuteReader() Using Reader While Reader.Read() 'Do Something End While Reader.Close() End Using Conn.Close() End Using

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  • MySQL performance - 100Mb ethernet vs 1Gb ethernet

    - by Rob Penridge
    Hi All I've just started a new job and noticed that the analysts computers are connected to the network at 100Mbps. The ODBC queries we run against the MySQL server can easily return 500MB+ and it seems at times when the servers are under high load the DBAs kill low priority jobs as they are taking too long to run. My question is this... How much of this server time is spent executing the request, and how much time is spent returning the data to the client? Could the query speeds be improved by upgrading the network connections to 1Gbps? (Updated for the why): The database in question was built to accomodate reporting needs and contains massive amounts of data. We usually work with subsets of this data at a granular level in external applications such as SAS or Excel, hence the reason for the large amounts of data being transmitted. The queries are not poorly structured - they are very simple and the appropriate joins/indexes etc are being used. I've removed 'query' from the Title of the post as I realised this question is more to do with general MySQL performance rather than query related performance. I was kind of hoping that someone with a Gigabit connection may be able to actually quantify some results for me here by running a query that returns a decent amount of data, then they could limit their connection speed to 100Mb and rerun the same query. Hopefully this could be done in an environment where loads are reasonably stable so as not to skew the results. If ethernet speed can improve the situation I wanted some quantifiable results to help argue my case for upgrading the network connections. Thanks Rob

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  • iPhone openGLES performance tuning

    - by genesys
    Hey there! I'm trying now for quite a while to optimize the framerate of my game without really making progress. I'm running on the newest iPhone SDK and have a iPhone 3G 3.1.2 device. I invoke arround 150 drawcalls, rendering about 1900 Triangles in total (all objects are textured using two texturelayers and multitexturing. most textures come from the same textureAtlasTexture stored in pvrtc 2bpp compressed texture). This renders on my phone at arround 30 fps, which appears to me to be way too low for only 1900 triangles. I tried many things to optimize the performance, including batching together the objects, transforming the vertices on the CPU and rendering them in a single drawcall. this yelds 8 drawcalls (as oposed to 150 drawcalls), but performance is about the same (fps drop to arround 26fps) I'm using 32byte vertices stored in an interleaved array (12bytes position, 12bytes normals, 8bytes uv). I'm rendering triangleLists and the vertices are ordered in TriStrip order. I did some profiling but I don't really know how to interprete it. instruments-sampling using Instruments and Sampling yelds this result: http://neo.cycovery.com/instruments_sampling.gif telling me that a lot of time is spent in "mach_msg_trap". I googled for it and it seems this function is called in order to wait for some other things. But wait for what?? instruments-openGL instruments with the openGL module yelds this result: http://neo.cycovery.com/intstruments_openglES_debug.gif but here i have really no idea what those numbers are telling me shark profiling: profiling with shark didn't tell me much either: http://neo.cycovery.com/shark_profile_release.gif the largest number is 10%, spent by DrawTriangles - and the whole rest is spent in very small percentage functions Can anyone tell me what else I could do in order to figure out the bottleneck and could help me to interprete those profiling information? Thanks a lot!

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  • Need Advice on building the database. all in one table or split?

    - by Ibrahim Azhar Armar
    hello, i am developing an application for a real-estate company. the problem i am facing is about implementing the database. however i am just confused on which way to adopt i would appreciate if you could help me out in reasoning the database implementation. here is my situation. a) i have to store the property details in the database. b) the properties have approximately 4-5 categories to which it will belong for ex : resedential, commnercial, industrial etc. c) now the categories have sub-categories. for example. a residential category will have sub category such as. Apartment / Independent House / Villa / Farm House/ Studio Apartment etc. and hence same way commercial and industrial or agricultural will too have sub-categories. d) each sub-categories will have to store the different values. like a resident will have features like Bedrooms/ kitchens / Hall / bathroom etc. the features depends on the sub categories. for an example on how i would want to implement my application you can have a look at this site. http://www.magicbricks.com/bricks/postProperty.html i could possibly think of the solution like this. a) create four to five tables depending upon the categories which will be existing(the problem is categories might increase in the future). b) create different tables for all the features, location, price, description and merge the common property table into one. for example all the property will have the common entity such as location, total area, etc. what would you advice for me given the current situation. thank you

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  • Java performance problem with LinkedBlockingQueue

    - by lofthouses
    Hello, this is my first post on stackoverflow...i hope someone can help me i have a big performance regression with Java 6 LinkedBlockingQueue. In the first thread i generate some objects which i push in to the queue In the second thread i pull these objects out. The performance regression occurs when the take() method of the LinkedBlockingQueue is called frequently. I monitored the whole program and the take() method claimed the most time overall. And the throughput goes from ~58Mb/s to 0.9Mb/s... the queue pop and take methods ar called with a static method from this class public class C_myMessageQueue { private static final LinkedBlockingQueue<C_myMessageObject> x_queue = new LinkedBlockingQueue<C_myMessageObject>( 50000 ); /** * @param message * @throws InterruptedException * @throws NullPointerException */ public static void addMyMessage( C_myMessageObject message ) throws InterruptedException, NullPointerException { x_queue.put( message ); } /** * @return Die erste message der MesseageQueue * @throws InterruptedException */ public static C_myMessageObject getMyMessage() throws InterruptedException { return x_queue.take(); } } how can i tune the take() method to accomplish at least 25Mb/s, or is there a other class i can use which will block when the "queue" is full or empty. kind regards Bart P.S.: sorry for my bad english, i'm from germany ;)

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  • Reporting System architecture for better performance

    - by pauloya
    Hi, We have a product that runs Sql Server Express 2005 and uses mainly ASP.NET. The database has around 200 tables, with a few (4 or 5) that can grow from 300 to 5000 rows per day and keep a history of 5 years, so they can grow to have 10 million rows. We have built a reporting platform, that allows customers to build reports based on templates, fields and filters. We face performance problems almost since the beginning, we try to keep reports display under 10 seconds but some of them go up to 25 seconds (specially on those customers with long history). We keep checking indexes and trying to improve the queries but we get the feeling that there's only so much we can do. Off course the fact that the queries are generated dynamically doesn't help with the optimization. We also added a few tables that keep redundant data, but then we have the added problem of maintaining this data up to date, and also Sql Express has a limit on the size of databases. We are now facing a point where we have to decide if we want to give up real time reports, or maybe cut the history to be able to have better performance. I would like to ask what is the recommended approach for this kind of systems. Also, should we start looking for third party tools/platforms? I know OLAP can be an option but can we make it work on Sql Server Express, or at least with a license that is cheap enough to distribute to thousands of deployments? Thanks

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  • Poor LLVM JIT performance

    - by Paul J. Lucas
    I have a legacy C++ application that constructs a tree of C++ objects. I want to use LLVM to call class constructors to create said tree. The generated LLVM code is fairly straight-forward and looks repeated sequences of: ; ... %11 = getelementptr [11 x i8*]* %Value_array1, i64 0, i64 1 %12 = call i8* @T_string_M_new_A_2Pv(i8* %heap, i8* getelementptr inbounds ([10 x i8]* @0, i64 0, i64 0)) %13 = call i8* @T_QueryLoc_M_new_A_2Pv4i(i8* %heap, i8* %12, i32 1, i32 1, i32 4, i32 5) %14 = call i8* @T_GlobalEnvironment_M_getItemFactory_A_Pv(i8* %heap) %15 = call i8* @T_xs_integer_M_new_A_Pvl(i8* %heap, i64 2) %16 = call i8* @T_ItemFactory_M_createInteger_A_3Pv(i8* %heap, i8* %14, i8* %15) %17 = call i8* @T_SingletonIterator_M_new_A_4Pv(i8* %heap, i8* %2, i8* %13, i8* %16) store i8* %17, i8** %11, align 8 ; ... Where each T_ function is a C "thunk" that calls some C++ constructor, e.g.: void* T_string_M_new_A_2Pv( void *v_value ) { string *const value = static_cast<string*>( v_value ); return new string( value ); } The thunks are necessary, of course, because LLVM knows nothing about C++. The T_ functions are added to the ExecutionEngine in use via ExecutionEngine::addGlobalMapping(). When this code is JIT'd, the performance of the JIT'ing itself is very poor. I've generated a call-graph using kcachegrind. I don't understand all the numbers (and this PDF seems not to include commas where it should), but if you look at the left fork, the bottom two ovals, Schedule... is called 16K times and setHeightToAtLeas... is called 37K times. On the right fork, RAGreed... is called 35K times. Those are far too many calls to anything for what's mostly a simple sequence of call LLVM instructions. Something seems horribly wrong. Any ideas on how to improve the performance of the JIT'ing?

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