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  • Implementing Database Settings Using Policy Based Management

    - by Ashish Kumar Mehta
    Introduction Database Administrators have always had a tough time to ensuring that all the SQL Servers administered by them are configured according to the policies and standards of organization. Using SQL Server’s  Policy Based Management feature DBAs can now manage one or more instances of SQL Server 2008 and check for policy compliance issues. In this article we will utilize Policy Based Management (aka Declarative Management Framework or DMF) feature of SQL Server to implement and verify database settings on all production databases. It is best practice to enforce the below settings on each Production database. However, it can be tedious to go through each database and then check whether the below database settings are implemented across databases. In this article I will explain it to you how to utilize the Policy Based Management Feature of SQL Server 2008 to create a policy to verify these settings on all databases and in cases of non-complaince how to bring them back into complaince. Database setting to enforce on each user database : Auto Close and Auto Shrink Properties of database set to False Auto Create Statistics and Auto Update Statistics set to True Compatibility Level of all the user database set as 100 Page Verify set as CHECKSUM Recovery Model of all user database set to Full Restrict Access set as MULTI_USER Configure a Policy to Verify Database Settings 1. Connect to SQL Server 2008 Instance using SQL Server Management Studio 2. In the Object Explorer, Click on Management > Policy Management and you will be able to see Policies, Conditions & Facets as child nodes 3. Right click Policies and then select New Policy…. from the drop down list as shown in the snippet below to open the  Create New Policy Popup window. 4. In the Create New Policy popup window you need to provide the name of the policy as “Implementing and Verify Database Settings for Production Databases” and then click the drop down list under Check Condition. As highlighted in the snippet below click on the New Condition… option to open up the Create New Condition window. 5. In the Create New Condition popup window you need to provide the name of the condition as “Verify and Change Database Settings”. In the Facet drop down list you need to choose the Facet as Database Options as shown in the snippet below. Under Expression you need to select Field value as @AutoClose and then choose Operator value as ‘ = ‘ and finally choose Value as False. Now that you have successfully added the first field you can now go ahead and add rest of the fields as shown in the snippet below. Once you have successfully added all the above shown fields of Database Options Facet, click OK to save the changes and to return to the parent Create New Policy – Implementing and Verify Database Settings for Production Database windows where you will see that the newly created condition “Verify and Change Database Settings” is selected by default. Continues…

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  • In MySQL, what is the most effective query design for joining large tables with many to many relatio

    - by lighthouse65
    In our application, we collect data on automotive engine performance -- basically source data on engine performance based on the engine type, the vehicle running it and the engine design. Currently, the basis for new row inserts is an engine on-off period; we monitor performance variables based on a change in engine state from active to inactive and vice versa. The related engineState table looks like this: +---------+-----------+---------------+---------------------+---------------------+-----------------+ | vehicle | engine | engine_state | state_start_time | state_end_time | engine_variable | +---------+-----------+---------------+---------------------+---------------------+-----------------+ | 080025 | E01 | active | 2008-01-24 16:19:15 | 2008-01-24 16:24:45 | 720 | | 080028 | E02 | inactive | 2008-01-24 16:19:25 | 2008-01-24 16:22:17 | 304 | +---------+-----------+---------------+---------------------+---------------------+-----------------+ For a specific analysis, we would like to analyze table content based on a row granularity of minutes, rather than the current basis of active / inactive engine state. For this, we are thinking of creating a simple productionMinute table with a row for each minute in the period we are analyzing and joining the productionMinute and engineEvent tables on the date-time columns in each table. So if our period of analysis is from 2009-12-01 to 2010-02-28, we would create a new table with 129,600 rows, one for each minute of each day for that three-month period. The first few rows of the productionMinute table: +---------------------+ | production_minute | +---------------------+ | 2009-12-01 00:00 | | 2009-12-01 00:01 | | 2009-12-01 00:02 | | 2009-12-01 00:03 | +---------------------+ The join between the tables would be engineState AS es LEFT JOIN productionMinute AS pm ON es.state_start_time <= pm.production_minute AND pm.production_minute <= es.event_end_time. This join, however, brings up multiple environmental issues: The engineState table has 5 million rows and the productionMinute table has 130,000 rows When an engineState row spans more than one minute (i.e. the difference between es.state_start_time and es.state_end_time is greater than one minute), as is the case in the example above, there are multiple productionMinute table rows that join to a single engineState table row When there is more than one engine in operation during any given minute, also as per the example above, multiple engineState table rows join to a single productionMinute row In testing our logic and using only a small table extract (one day rather than 3 months, for the productionMinute table) the query takes over an hour to generate. In researching this item in order to improve performance so that it would be feasible to query three months of data, our thoughts were to create a temporary table from the engineEvent one, eliminating any table data that is not critical for the analysis, and joining the temporary table to the productionMinute table. We are also planning on experimenting with different joins -- specifically an inner join -- to see if that would improve performance. What is the best query design for joining tables with the many:many relationship between the join predicates as outlined above? What is the best join type (left / right, inner)?

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  • Whether to use UNION or OR in SQL Server Queries

    - by Dinesh Asanka
    Recently I came across with an article on DB2 about using Union instead of OR. So I thought of carrying out a research on SQL Server on what scenarios UNION is optimal in and which scenarios OR would be best. I will analyze this with a few scenarios using samples taken  from the AdventureWorks database Sales.SalesOrderDetail table. Scenario 1: Selecting all columns So we are going to select all columns and you have a non-clustered index on the ProductID column. --Query 1 : OR SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 OR ProductID =709 OR ProductID =998 OR ProductID =875 OR ProductID =976 OR ProductID =874 --Query 2 : UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 709 UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 998 UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 875 UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 976 UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 874 So query 1 is using OR and the later is using UNION. Let us analyze the execution plans for these queries. Query 1 Query 2 As expected Query 1 will use Clustered Index Scan but Query 2, uses all sorts of things. In this case, since it is using multiple CPUs you might have CX_PACKET waits as well. Let’s look at the profiler results for these two queries: CPU Reads Duration Row Counts OR 78 1252 389 3854 UNION 250 7495 660 3854 You can see from the above table the UNION query is not performing well as the  OR query though both are retuning same no of rows (3854).These results indicate that, for the above scenario UNION should be used. Scenario 2: Non-Clustered and Clustered Index Columns only --Query 1 : OR SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 714 OR ProductID =709 OR ProductID =998 OR ProductID =875 OR ProductID =976 OR ProductID =874 GO --Query 2 : UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 714 UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 709 UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 998 UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 875 UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 976 UNION SELECT ProductID,SalesOrderID, SalesOrderDetailID FROM Sales.SalesOrderDetail WHERE ProductID = 874 GO So this time, we will be selecting only index columns, which means these queries will avoid a data page lookup. As in the previous case we will analyze the execution plans: Query 1 Query 2 Again, Query 2 is more complex than Query 1. Let us look at the profile analysis: CPU Reads Duration Row Counts OR 0 24 208 3854 UNION 0 38 193 3854 In this analyzis, there is only slight difference between OR and UNION. Scenario 3: Selecting all columns for different fields Up to now, we were using only one column (ProductID) in the where clause.  What if we have two columns for where clauses and let us assume both are covered by non-clustered indexes? --Query 1 : OR SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 OR CarrierTrackingNumber LIKE 'D0B8%' --Query 2 : UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 UNION SELECT * FROM Sales.SalesOrderDetail WHERE CarrierTrackingNumber  LIKE 'D0B8%' Query 1 Query 2: As we can see, the query plan for the second query has improved. Let us see the profiler results. CPU Reads Duration Row Counts OR 47 1278 443 1228 UNION 31 1334 400 1228 So in this case too, there is little difference between OR and UNION. Scenario 4: Selecting Clustered index columns for different fields Now let us go only with clustered indexes: --Query 1 : OR SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 OR CarrierTrackingNumber LIKE 'D0B8%' --Query 2 : UNION SELECT * FROM Sales.SalesOrderDetail WHERE ProductID = 714 UNION SELECT * FROM Sales.SalesOrderDetail WHERE CarrierTrackingNumber  LIKE 'D0B8%' Query 1 Query 2 Now both execution plans are almost identical except is an additional Stream Aggregate is used in the first query. This means UNION has advantage over OR in this scenario. Let us see profiler results for these queries again. CPU Reads Duration Row Counts OR 0 319 366 1228 UNION 0 50 193 1228 Now see the differences, in this scenario UNION has somewhat of an advantage over OR. Conclusion Using UNION or OR depends on the scenario you are faced with. So you need to do your analyzing before selecting the appropriate method. Also, above the four scenarios are not all an exhaustive list of scenarios, I selected those for the broad description purposes only.

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  • Monitor SQL Server Replication Jobs

    - by Yaniv Etrogi
    The Replication infrastructure in SQL Server is implemented using SQL Server Agent to execute the various components involved in the form of a job (e.g. LogReader agent job, Distribution agent job, Merge agent job) SQL Server jobs execute a binary executable file which is basically C++ code. You can download all the scripts for this article here SQL Server Job Schedules By default each of job has only one schedule that is set to Start automatically when SQL Server Agent starts. This schedule ensures that when ever the SQL Server Agent service is started all the replication components are also put into action. This is OK and makes sense but there is one problem with this default configuration that needs improvement  -  if for any reason one of the components fails it remains down in a stopped state.   Unless you monitor the status of each component you will typically get to know about such a failure from a customer complaint as a result of missing data or data that is not up to date at the subscriber level. Furthermore, having any of these components in a stopped state can lead to more severe problems if not corrected within a short time. The action required to improve on this default settings is in fact very simple. Adding a second schedule that is set as a Daily Reoccurring schedule which runs every 1 minute does the trick. SQL Server Agent’s scheduler module knows how to handle overlapping schedules so if the job is already being executed by another schedule it will not get executed again at the same time. So, in the event of a failure the failed job remains down for at most 60 seconds. Many DBAs are not aware of this capability and so search for more complex solutions such as having an additional dedicated job running an external code in VBS or another scripting language that detects replication jobs in a stopped state and starts them but there is no need to seek such external solutions when what is needed can be accomplished by T-SQL code. SQL Server Jobs Status In addition to the 1 minute schedule we also want to ensure that key components in the replication are enabled so I can search for those components by their Category, and set their status to enabled in case they are disabled, by executing the stored procedure MonitorEnableReplicationAgents. The jobs that I typically have handled are listed below but you may want to extend this, so below is the query to return all jobs along with their category. SELECT category_id, name FROM msdb.dbo.syscategories ORDER BY category_id; Distribution Cleanup LogReader Agent Distribution Agent Snapshot Agent Jobs By default when a publication is created, a snapshot agent job also gets created with a daily schedule. I see more organizations where the snapshot agent job does not need to be executed automatically by the SQL Server Agent  scheduler than organizations who   need a new snapshot generated automatically. To assure this setting is in place I created the stored procedure MonitorSnapshotAgentsSchedules which disables snapshot agent jobs and also deletes the job schedule. It is worth mentioning that when the publication property immediate_sync is turned off then the snapshot files are not created when the Snapshot agent is executed by the job. You control this property when the publication is created with a parameter called @immediate_sync passed to sp_addpublication and for an existing publication you can use sp_changepublication. Implementation The scripts assume the existence of a database named PerfDB. Steps: Run the scripts to create the stored procedures in the PerfDB database. Create a job that executes the stored procedures every hour. -- Verify that the 1_Minute schedule exists. EXEC PerfDB.dbo.MonitorReplicationAgentsSchedules @CategoryId = 10; /* Distribution */ EXEC PerfDB.dbo.MonitorReplicationAgentsSchedules @CategoryId = 13; /* LogReader */ -- Verify all replication agents are enabled. EXEC PerfDB.dbo.MonitorEnableReplicationAgents @CategoryId = 10; /* Distribution */ EXEC PerfDB.dbo.MonitorEnableReplicationAgents @CategoryId = 13; /* LogReader */ EXEC PerfDB.dbo.MonitorEnableReplicationAgents @CategoryId = 11; /* Distribution clean up */ -- Verify that Snapshot agents are disabled and have no schedule EXEC PerfDB.dbo.MonitorSnapshotAgentsSchedules; Want to read more of about replication? Check at my replication posts at my blog.

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  • Manage and Monitor Identity Ranges in SQL Server Transactional Replication

    - by Yaniv Etrogi
    Problem When using transactional replication to replicate data in a one way topology from a publisher to a read-only subscriber(s) there is no need to manage identity ranges. However, when using  transactional replication to replicate data in a two way replication topology - between two or more servers there is a need to manage identity ranges in order to prevent a situation where an INSERT commands fails on a PRIMARY KEY violation error  due to the replicated row being inserted having a value for the identity column which already exists at the destination database. Solution There are two ways to address this situation: Assign a range of identity values per each server. Work with parallel identity values. The first method requires some maintenance while the second method does not and so the scripts provided with this article are very useful for anyone using the first method. I will explore this in more detail later in the article. In the first solution set server1 to work in the range of 1 to 1,000,000,000 and server2 to work in the range of 1,000,000,001 to 2,000,000,000.  The ranges are set and defined using the DBCC CHECKIDENT command and when the ranges in this example are well maintained you meet the goal of preventing the INSERT commands to fall due to a PRIMARY KEY violation. The first insert at server1 will get the identity value of 1, the second insert will get the value of 2 and so on while on server2 the first insert will get the identity value of 1000000001, the second insert 1000000002 and so on thus avoiding a conflict. Be aware that when a row is inserted the identity value (seed) is generated as part of the insert command at each server and the inserted row is replicated. The replicated row includes the identity column’s value so the data remains consistent across all servers but you will be able to tell on what server the original insert took place due the range that  the identity value belongs to. In the second solution you do not manage ranges but enforce a situation in which identity values can never get overlapped by setting the first identity value (seed) and the increment property one time only during the CREATE TABLE command of each table. So a table on server1 looks like this: CREATE TABLE T1 (  c1 int NOT NULL IDENTITY(1, 5) PRIMARY KEY CLUSTERED ,c2 int NOT NULL ); And a table on server2 looks like this: CREATE TABLE T1(  c1 int NOT NULL IDENTITY(2, 5) PRIMARY KEY CLUSTERED ,c2 int NOT NULL ); When these two tables are inserted the results of the identity values look like this: Server1:  1, 6, 11, 16, 21, 26… Server2:  2, 7, 12, 17, 22, 27… This assures no identity values conflicts while leaving a room for 3 additional servers to participate in this same environment. You can go up to 9 servers using this method by setting an increment value of 9 instead of 5 as I used in this example. Continues…

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  • Altering a Column Which has a Default Constraint

    - by Dinesh Asanka
    Setting up a default column is a common task for  developers.  But, are we naming those default constraints explicitly? In the below  table creation, for the column, sys_DateTime the default value Getdate() will be allocated. CREATE TABLE SampleTable (ID int identity(1,1), Sys_DateTime Datetime DEFAULT getdate() ) We can check the relevant information from the system catalogs from following query. SELECT sc.name TableName, dc.name DefaultName, dc.definition, OBJECT_NAME(dc.parent_object_id) TableName, dc.is_system_named  FROM sys.default_constraints dc INNER JOIN sys.columns sc ON dc.parent_object_id = sc.object_id AND dc.parent_column_id = sc.column_id and results would be: Most of the above columns are self-explanatory. The last column, is_system_named, is to identify whether the default name was given by the system. As you know, in the above case, since we didn’t provide  any default name, the  system will generate a default name for you. But the problem with these names is that they can differ from environment to environment.  If example if I create this table in different table the default name could be DF__SampleTab__Sys_D__7E6CC920 Now let us create another default and explicitly name it: CREATE TABLE SampleTable2 (ID int identity(1,1), Sys_DateTime Datetime )   ALTER TABLE SampleTable2 ADD CONSTRAINT DF_sys_DateTime_Getdate DEFAULT( Getdate()) FOR Sys_DateTime If we run the previous query again we will be returned the below output. And you can see that last created default name has 0 for is_system_named. Now let us say I want to change the data type of the sys_DateTime column to something else: ALTER TABLE SampleTable2 ALTER COLUMN Sys_DateTime Date This will generate the below error: Msg 5074, Level 16, State 1, Line 1 The object ‘DF_sys_DateTime_Getdate’ is dependent on column ‘Sys_DateTime’. Msg 4922, Level 16, State 9, Line 1 ALTER TABLE ALTER COLUMN Sys_DateTime failed because one or more objects access this column. This means, you need to drop the default constraint before altering it: ALTER TABLE [dbo].[SampleTable2] DROP CONSTRAINT [DF_sys_DateTime_Getdate] ALTER TABLE SampleTable2 ALTER COLUMN Sys_DateTime Date   ALTER TABLE [dbo].[SampleTable2] ADD CONSTRAINT [DF_sys_DateTime_Getdate] DEFAULT (getdate()) FOR [Sys_DateTime] If you have a system named default constraint that can differ from environment to environment and so you cannot drop it as before, you can use the below code template: DECLARE @defaultname VARCHAR(255) DECLARE @executesql VARCHAR(1000)   SELECT @defaultname = dc.name FROM sys.default_constraints dc INNER JOIN sys.columns sc ON dc.parent_object_id = sc.object_id AND dc.parent_column_id = sc.column_id WHERE OBJECT_NAME (parent_object_id) = 'SampleTable' AND sc.name ='Sys_DateTime' SET @executesql = 'ALTER TABLE SampleTable DROP CONSTRAINT ' + @defaultname EXEC( @executesql) ALTER TABLE SampleTable ALTER COLUMN Sys_DateTime Date ALTER TABLE [dbo].[SampleTable] ADD DEFAULT (Getdate()) FOR [Sys_DateTime]

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  • Upgrade SSIS 2005 Packages to SSIS 2008

    There are several enhancements in SSIS 2008 such as enhanced lookup transformation, the development environment for Script Task and Script Component changing from VSA to VSTA, etc. If you intend to upgrade your SSIS 2005 packages to SSIS 2008 ... [Read Full Article]

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  • Using The Data Mining Query Task in SSIS

    SQL Server Integration Services (SSIS) is a Business Intelligence tool which can be used by database developers or administrators to perform Extract, Transform & Load (ETL) operations. In my previous article Using Analysis Services Processing Task & Analysis Services ... [Read Full Article]

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  • WPF Reusing Xaml Effectively

    - by Steve
    Hi, I've recently been working on a project using WPF to produce a diagram. In this I must show text alongside symbols that illustrate information associated with the text. To draw the symbols I initially used some png images I had produced. Within my diagram these images appeared blurry and only looked worse when zoomed in on. To improve on this I decided I would use a vector rather than a rastor image format. Below is the method I used to get the rastor image from a file path: protected Image GetSymbolImage(string symbolPath, int symbolHeight) { Image symbol = new Image(); symbol.Height = symbolHeight; BitmapImage bitmapImage = new BitmapImage(); bitmapImage.BeginInit(); bitmapImage.UriSource = new Uri(symbolPath); bitmapImage.DecodePixelHeight = symbolHeight; bitmapImage.EndInit(); symbol.Source = bitmapImage; return symbol; } Unfortunately this does not recognise vector image formats. So instead I used a method like the following, where "path" is the file path to a vector image of the format .xaml: public static Canvas LoadXamlCanvas(string path) { //if a file exists at the specified path if (File.Exists(path)) { //store the text in the file string text = File.ReadAllText(path); //produce a canvas from the text StringReader stringReader = new StringReader(text); XmlReader xmlReader = XmlReader.Create(stringReader); Canvas c = (Canvas)XamlReader.Load(xmlReader); //return the canvas return c; } return null; } This worked but drastically killed performance when called repeatedly. I found the logic necessary for text to canvas conversion (see above) was the main cause of the performance problem therefore embedding the .xaml images would not alone resolve the performance issue. I tried using this method only on the initial load of my application and storing the resulting canvases in a dictionary that could later be accessed much quicker but I later realised when using the canvases within the dictionary I would have to make copies of them. All the logic I found online associated with making copies used a XamlWriter and XamlReader which would again just introduce a performance problem. The solution I used was to copy the contents of each .xaml image into its own user control and then make use of these user controls where appropriate. This means I now display vector graphics and performance is much better. However this solution to me seems pretty clumsy. I'm new to WPF and wonder if there is some built in way of storing and reusing xaml throughout an application? Apologies for the length of this question. I thought having a record of my attempts might help someone with any similar problem. Thanks.

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  • Using Full Text Search in SQL Server 2008

    Introduction SQL Server 2008 Full-Text Search feature can be used by application developers to execute full-text search queries against character based data residing in  a SQL Server table. To use full text search the developer must create a full-text ... [Read Full Article]

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  • Understanding WCF Hosting

     WCF is a flagship product from  Microsoft for developing distributed application using SOA. Prior to WCF   traditional ASMX Web services were hosted only on Internet Information Services (IIS). The hosting options for WCF services are significantly enhanced from ... [Read Full Article]

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  • A High Level Comparison Between Oracle and SQL Server

    Organisations often employ a number of database platforms in their information system architecture. It is not uncommon to see medium to large sized companies using three to four different RDBMS packages. Consequently the DBAs these companies look for often ... [Read Full Article]

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  • Migrating from hand-written persistence layer to ORM

    - by Sergey Mikhanov
    Hi community, We are currently evaluating options for migrating from hand-written persistence layer to ORM. We have a bunch of legacy persistent objects (~200), that implement simple interface like this: interface JDBC { public long getId(); public void setId(long id); public void retrieve(); public void setDataSource(DataSource ds); } When retrieve() is called, object populates itself by issuing handwritten SQL queries to the connection provided using the ID it received in the setter (this usually is the only parameter to the query). It manages its statements, result sets, etc itself. Some of the objects have special flavors of retrive() method, like retrieveByName(), in this case a different SQL is issued. Queries could be quite complex, we often join several tables to populate the sets representing relations to other objects, sometimes join queries are issued on-demand in the specific getter (lazy loading). So basically, we have implemented most of the ORM's functionality manually. The reason for that was performance. We have very strong requirements for speed, and back in 2005 (when this code was written) performance tests has shown that none of mainstream ORMs were that fast as hand-written SQL. The problems we are facing now that make us think of ORM are: Most of the paths in this code are well-tested and are stable. However, some rarely-used code is prone to result set and connection leaks that are very hard to detect We are currently squeezing some additional performance by adding caching to our persistence layer and it's a huge pain to maintain the cached objects manually in this setup Support of this code when DB schema changes is a big problem. I am looking for an advice on what could be the best alternative for us. As far as I know, ORMs has advanced in last 5 years, so it might be that now there's one that offers an acceptable performance. As I see this issue, we need to address those points: Find some way to reuse at least some of the written SQL to express mappings Have the possibility to issue native SQL queries without the necessity to manually decompose their results (i.e. avoid manual rs.getInt(42) as they are very sensitive to schema changes) Add a non-intrusive caching layer Keep the performance figures. Is there any ORM framework you could recommend with regards to that?

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  • Shared Datasets in SQL Server 2008 R2

    This article leverages the examples and concepts explained in the Part I through Part IV of the spatial data series which develops a "BI-Satellite" app. Overview In the spatial data series we ... [Read Full Article]

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