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  • mysql inserts & updates optimized

    - by user271619
    This is an optimization question, mostly. I have many forms on my sites that do simple Inserts and Updates. (Nothing complicated) But, several of the form's input fields are not necessary and may be left empty. (again, nothing complicated) However, my SQL query will have all columns in the Statement. My question, is it best to optimize the Inserts/Update queries appropriately? And only apply the columns that are changed into the query? We all hear that we shouldn't use the "SELECT *" query, unless it's absolutely needed for displaying all columns. But what about Inserts & Updates? Hope this makes sense. I'm sure any amount of optimization is acceptable. But I never really hear about this, specifically, from anyone.

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  • Separate tables or single table with queries?

    - by Joe
    I'm making an employee information database. I need to handle separated employees. Should I a. set up a query with a macro to send separated employees to a separate table, or b. just add a flag to the single table denoting separation? I understand that it's best practice to take choice b, and the one reason I can think of for this is that any structural changes I make to the table later will have to be done in both places. But it also seems like setting up a flag forces me to filter out that flag for basically every useful query I'm going to make in the future.

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  • SQL SERVER – Simple Demo of New Cardinality Estimation Features of SQL Server 2014

    - by Pinal Dave
    SQL Server 2014 has new cardinality estimation logic/algorithm. The cardinality estimation logic is responsible for quality of query plans and majorly responsible for improving performance for any query. This logic was not updated for quite a while, but in the latest version of SQL Server 2104 this logic is re-designed. The new logic now incorporates various assumptions and algorithms of OLTP and warehousing workload. Cardinality estimates are a prediction of the number of rows in the query result. The query optimizer uses these estimates to choose a plan for executing the query. The quality of the query plan has a direct impact on improving query performance. ~ Souce MSDN Let us see a quick example of how cardinality improves performance for a query. I will be using the AdventureWorks database for my example. Before we start with this demonstration, remember that even though you have SQL Server 2014 to see the effect of new cardinality estimates, you will need your database compatibility mode set to 120 which is for SQL Server 2014. If your server instance of SQL Server 2014 but you have set up your database compatibility mode to 110 or any other earlier version, you will get performance from your query like older version of SQL Server. Now we will execute following query in two different compatibility mode and see its performance. (Note that my SQL Server instance is of version 2014). USE AdventureWorks2014 GO -- ------------------------------- -- NEW Cardinality Estimation ALTER DATABASE AdventureWorks2014 SET COMPATIBILITY_LEVEL = 120 GO EXEC [dbo].[uspGetManagerEmployees] 44 GO -- ------------------------------- -- Old Cardinality Estimation ALTER DATABASE AdventureWorks2014 SET COMPATIBILITY_LEVEL = 110 GO EXEC [dbo].[uspGetManagerEmployees] 44 GO Result of Statistics IO Compatibility level 120 Table ‘Person’. Scan count 0, logical reads 6, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Employee’. Scan count 2, logical reads 7, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Worktable’. Scan count 0, logical reads 0, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Worktable’. Scan count 2, logical reads 7, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Compatibility level 110 Table ‘Worktable’. Scan count 2, logical reads 7, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Person’. Scan count 0, logical reads 137, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Employee’. Scan count 2, logical reads 7, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Table ‘Worktable’. Scan count 0, logical reads 0, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. You will notice in the case of compatibility level 110 there 137 logical read from table person where as in the case of compatibility level 120 there are only 6 physical reads from table person. This drastically improves the performance of the query. If we enable execution plan, we can see the same as well. I hope you will find this quick example helpful. You can read more about this in my latest Pluralsight Course. Reference: Pinal Dave (http://blog.SQLAuthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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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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  • SQL SERVER – Identifying guest User using Policy Based Management

    - by pinaldave
    If you are following my recent blog posts, you may have noticed that I’ve been writing a lot about Guest User in SQL Server. Here are all the blog posts which I have written on this subject: SQL SERVER – Disable Guest Account – Serious Security Issue SQL SERVER – Force Removing User from Database – Fix: Error: Could not drop login ‘test’ as the user is currently logged in SQL SERVER – Detecting guest User Permissions – guest User Access Status SQL SERVER – guest User and MSDB Database – Enable guest User on MSDB Database One of the requests I received was whether we could create a policy that would prevent users unable guest user in user databases. Well, here is a quick tutorial to answer this. Let us see how quickly we can do it. Requirements Check if the guest user is disabled in all the user-created databases. Exclude master, tempdb and msdb database for guest user validation. We will create the following conditions based on the above two requirements: If the name of the user is ‘guest’ If the user has connect (@hasDBAccess) permission in the database Check in All user databases, except: master, tempDB and msdb Once we create two conditions, we will create a policy which will validate the conditions. Condition 1: Is the User Guest? Expand the Database >> Management >> Policy Management >> Conditions Right click on the Conditions, and click on “New Condition…”. First we will create a condition where we will validate if the user name is ‘guest’, and if it’s so, then we will further validate if it has DB access. Check the image for the necessary configuration for condition: Facet: User Expression: @Name = ‘guest’ Condition 2: Does the User have DBAccess? Expand the Database >> Management >> Policy Management >> Conditions Right click on Conditions and click on “New Condition…”. Now we will validate if the user has DB access. Check the image for necessary configuration for condition: Facet: User Expression: @hasDBAccess = False Condition 3: Exclude Databases Expand the Database >> Management >> Policy Management >> Conditions Write click on Conditions and click on “New Condition…” Now we will create condition where we will validate if database name is master, tempdb or msdb and if database name is any of them, we will not validate our first one condition with them. Check the image for necessary configuration for condition: Facet: Database Expression: @Name != ‘msdb’ AND @Name != ‘tempdb’ AND @Name != ‘master’ The next step will be creating a policy which will enforce these conditions. Creating a Policy Right click on Policies and click “New Policy…” Here, we justify what condition we want to validate against what the target is. Condition: Has User DBAccess Target Database: Every Database except (master, tempdb and MSDB) Target User: Every User in Target Database with name ‘guest’ Now we have options for two evaluation modes: 1) On Demand and 2) On Schedule We will select On Demand in this example; however, you can change the mode to On Schedule through the drop down menu, and select the interval of the evaluation of the policy. Evaluate the Policies We have selected OnDemand as our policy evaluation mode. We will now evaluate by means of executing Evaluate policy. Click on Evaluate and it will give the following result: The result demonstrates that one of the databases has a policy violation. Username guest is enabled in AdventureWorks database. You can disable the guest user by running the following code in AdventureWorks database. USE AdventureWorks; REVOKE CONNECT FROM guest; Once you run above query, you can already evaluate the policy again. Notice that the policy violation is fixed now. You can change the method of the evaluation policy to On Schedule and validate policy on interval. You can check the history of the policy and detect the violation. Quiz I have created three conditions to check if the guest user has database access or not. Now I want to ask you: Is it possible to do the same with 2 conditions? If yes, HOW? If no, WHY NOT? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Best Practices, CodeProject, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology Tagged: Policy Management

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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

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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

    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

  • 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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  • 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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  • 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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  • MS Access CrossTab query - across 3 tables

    - by Prembo
    Hi, I have the following 3 tables: 1) Sweetness Table FruitIndex CountryIndex Sweetness 1 1 10 1 2 20 1 3 400 2 1 50 2 2 123 2 3 1 3 1 49 3 2 40 3 3 2 2) Fruit Name Table FruitIndex FruitName 1 Apple 2 Orange 3 Peaches 3) Country Name Table CountryIndex CountryName 1 UnitedStates 2 Canada 3 Mexico I'm trying to perform a CrossTab SQL query to end up with: Fruit\Country UnitedStates Canada Mexico Apple 10 20 400 Orange 50 123 1 Peaches 49 40 2 The challenging part is to label the rows/columns with the relevant names from the Name tables. I can use MS Access to design 2 queries, create the joins the fruit/country names table with the Sweetness table perform crosstab query However I'm having trouble doing this in a single query. I've attempted nesting the 1st query's SQL into the 2nd, but it doesn't seem to work. Unfortunately, my solution needs to be be wholly SQL, as it is an embedded SQL query (cannot rely on query designer in MS Access, etc.). Any help greatly appreciated. Prembo.

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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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  • Force database read to master if slave data is stale

    - by Jeff Storey
    I previously asked a specific question about this database replication for new user signup to which I got an answer, but I want to ask this in the more general sense. I have a database setup in which I am using a master/slave combination. I am using the slaves for load balancing (the data itself is partitioned/sharded across multiple databases, but each database has X slaves for load balancing). Let's say I write some data to the master. Now I do a subsequent read which hits a slave, but the slave has not yet caught up to the master. Is there a way (which can be done quickly since it will happen frequently) to determine if the data is stale in the slave so I can then route to the master? In my previous question, it was suggested to do simultaneous writes to the cache and the database. This solution seems practical, but there is still a chance that the data may have been removed from the cache but not yet updated in the slave. A possible solution is to ensure the cache is big enough (based on the typical application load) so the data will not be evicted within the time frame it takes to replicate the data. This seems like it may be feasible. Can anyone provide additional insight into this question? Thanks!

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  • How to back up a database with thousands of files

    - by Neal
    I am working with a Fedora server that runs a customized software package. The server software is quite old, and its database consists of 1,723 files. The database files are constantly changing - they continually grow and changes are not necessarily appended to the end. So right now, we currently back up every 24 hours at midnight when all users are off of the system and the database is in an internally consistent state. The problem is that we have the potential to lose an entire day's worth of work, which would be unrecoverable. So I'd like to know if there is a way to take some sort of an instantaneous snapshot of these database files that we could back up every 30 minutes or so. I've read about Linux LVM snapshots, and am thinking that I might be able to do accomplish the goal by taking a snapshot, rsync'ing the files to a backup server, then dropping the snapshot. But I've never done this before,so I don't know if this is the "right" fix. Any ideas on this? Any better solutions? Thanks!

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  • Synchronize Active Directory to Database

    - by Tommy Jakobsen
    We are in a situation where we would like to offer our customers to be able to manage their users themselves. It is around 300 customers with up to a total of 10.000 users. Besides creating, updating and removing users, they will very often read information about users for statics and other useful informations available. All this functionality, should be available from an Intranet web page (.NET Framework 4) that the users will access through Citrix or similar. Now the problem is that we would really like the users not to query AD directly for each request, but rather make them hit a database that is synchronized with AD. It would be sufficient to run this synchronization a few time each day (maybe every 5. hour). When they create a user, it should not be available right away, but reviewed and then created within two days (the next step would be to remove this manual review, but that's out of scope for this question). What do you think about this synchronization of AD? Does anyone have any experience with it and is it something that is done in other organizations, where you will have lots of requests which is better handled by a database than AD (I presume)? Are there any techniques out there for writing such a script that synchronizes AD with database tables? My primary concern is the groups/members relations which can be rather complicated. Or are there software that synchronizes AD with a database? Any comments will be much appreciated. Thank you.

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  • SQL SERVER – DMV – sys.dm_os_waiting_tasks and sys.dm_exec_requests – Wait Type – Day 4 of 28

    - by pinaldave
    Previously, we covered the DMV sys.dm_os_wait_stats, and also saw how it can be useful to identify the major resource bottleneck. However, at the same time, we discussed that this is only useful when we are looking at an instance-level picture. Quite often we want to know about the processes going in our server at the given instant. Here is the query for the same. This DMV is written taking the following into consideration: we want to analyze the queries that are currently running or which have recently ran and their plan is still in the cache. SELECT dm_ws.wait_duration_ms, dm_ws.wait_type, dm_es.status, dm_t.TEXT, dm_qp.query_plan, dm_ws.session_ID, dm_es.cpu_time, dm_es.memory_usage, dm_es.logical_reads, dm_es.total_elapsed_time, dm_es.program_name, DB_NAME(dm_r.database_id) DatabaseName, -- Optional columns dm_ws.blocking_session_id, dm_r.wait_resource, dm_es.login_name, dm_r.command, dm_r.last_wait_type FROM sys.dm_os_waiting_tasks dm_ws INNER JOIN sys.dm_exec_requests dm_r ON dm_ws.session_id = dm_r.session_id INNER JOIN sys.dm_exec_sessions dm_es ON dm_es.session_id = dm_r.session_id CROSS APPLY sys.dm_exec_sql_text (dm_r.sql_handle) dm_t CROSS APPLY sys.dm_exec_query_plan (dm_r.plan_handle) dm_qp WHERE dm_es.is_user_process = 1 GO You can change CROSS APPLY to OUTER APPLY if you want to see all the details which are omitted because of the plan cache. Let us analyze the result of the above query and see how it can be helpful to identify the query and the kind of wait type it creates. Click to Enlarage The above query will return various columns. There are various columns that provide very important details. e.g. wait_duration_ms – it indicates current wait for the query that executes at that point of time. wait_type – it indicates the current wait type for the query text – indicates the query text query_plan – when clicked on the same, it will display the query plans There are many other important information like CPU_time, memory_usage, and logical_reads, which can be read from the query as well. In future posts on this series, we will see how once identified wait type we can attempt to reduce the same. Read all the post in the Wait Types and Queue series. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: DMV, Pinal Dave, PostADay, SQL, SQL Authority, SQL DMV, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • Oracle OpenWorld 2012: Focus On Oracle Database

    - by jgelhaus
    As Oracle OpenWorld approaches and you work to plan your schedule.  We know there's a lot to sort through.  To help we've put together some Oracle Database Focus On Documents to help guide you through the database sessions at the show. Oracle Database Oracle Database Application Development Oracle Database Security Oracle Spatial and Graph Oracle Enterprise Manager Cloud Control 12c (and Private Cloud) Big Data Oracle Exadata Data Warehousing High Availability Oracle Database Utilities Oracle Database Upgrade See you in San Francisco!

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