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• Transaction Log filling up on SQL database set to Simple

  - by Will

  We have a database on a SQL 2005 server that is set to Simple transaction mode. The logging is set to 1 MB and is set to grow by 10% when it needs to. We keep running into an issue where the transaction log fills up and we need to shrink it. What could cause the transaction log to fill up when its set to Simple and unrestricted growth is allowed?

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• advise on pointing reporting service data sources

  - by pearcewg

  It's possible I am unable to resolve this because I have been spoiled in other DEV environments where I had one database server for each reporting server. I need some advise on how to point a single SQL Server reporting server to multiple database servers. These databases correspond to DEV, TEST and QA environments. The way the reporting is currently configured I am unable to toggle between environments gracefully. Any advise would be greatly appreciated.

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• Deleting text files based on date through SQL Server T-SQL

  - by SuperCoolMoss

  I need to delete .txt files in a particular directory based on date. Can I do this through T-SQL?

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• What is preferred method for searching table data using stored procedure?

  - by Mourya

  I have a customer table with Cust_Id, Name, City and search is based upon any or all of the above three. Which one Should I go for ? Dynamic SQL: declare @str varchar(1000) set @str = 'Select [Sno],[Cust_Id],[Name],[City],[Country],[State] from Customer where 1 = 1' if (@Cust_Id != '') set @str = @str + ' and Cust_Id = ''' + @Cust_Id + '''' if (@Name != '') set @str = @str + ' and Name like ''' + @Name + '%''' if (@City != '') set @str = @str + ' and City like ''' + @City + '%''' exec (@str) Simple query: select [Sno],[Cust_Id],[Name],[City],[Country],[State] from Customer where (@Cust_Id = '' or Cust_Id = @Cust_Id) and (@Name = '' or Name like @Name + '%') and (@City = '' or City like @City + '%') Which one should I prefer (1 or 2) and what are advantages? After going through everyone's suggestion , here is what i finally got. DECLARE @str NVARCHAR(1000) DECLARE @ParametersDefinition NVARCHAR(500) SET @ParametersDefinition = N'@InnerCust_Id varchar(10), @InnerName varchar(30),@InnerCity varchar(30)' SET @str = 'Select [Sno],[Cust_Id],[Name],[City],[Country],[State] from Customer where 1 = 1' IF(@Cust_Id != '') SET @str = @str + ' and Cust_Id = @InnerCust_Id' IF(@Name != '') SET @str = @str + ' and Name like @InnerName' IF(@City != '') SET @str = @str + ' and City like @InnerCity' -- ADD the % symbol for search based upon the LIKE keyword SELECT @Name = @Name + '%', @City = @City+ '%' EXEC sp_executesql @str, @ParametersDefinition, @InnerCust_Id = @Cust_Id, @InnerName = @Name, @InnerCity = @City; References : http://blogs.lessthandot.com/index.php/DataMgmt/DataDesign/changing-exec-to-sp_executesql-doesn-t-p http://msdn.microsoft.com/en-us/library/ms175170.aspx

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• Top 10 Reasons SQL Developer is Perfect for Oracle Beginners

  - by thatjeffsmith

  Learning new technologies can be daunting. If you’ve never used a Mac before, you’ll probably be a bit baffled at first. But, you’re probably at least coming from a desktop computing background (Windows), so you common frame of reference. But what if you’re just now learning to use a relational database? Yes, you’ve played with Access a bit, but now your employer or college instructor has charged you with becoming proficient with Oracle database. Here’s 10 reasons why I think Oracle SQL Developer is the perfect vehicle to help get you started. 1. It’s free No need to break into one of these… No start-up costs, no need to wrangle budget dollars from your company. Students don’t have any money after books and lab fees anyway. And most employees don’t like having to ask for ‘special’ software anyway. So avoid all of that and make sure the free stuff doesn’t suit your needs first. Upgrades are available on a regular base, also at no cost, and support is freely available via our public forums. 2. It will run pretty much anywhere Windows – check. OSX (Apple) – check. Unix – check. Linux – check. No need to start up a windows VM to run your Windows-only software in your lab machine. 3. Anyone can install it There’s no installer, no registry to be updated, no admin privs to be obtained. If you can download and extract files to your machine or USB storage device, you can run it. You can be up and running with SQL Developer in under 5 minutes. Here’s a video tutorial to see how to get started. 4. It’s ubiquitous I admit it, I learned a new word yesterday and I wanted an excuse to use it. SQL Developer’s everywhere. It’s had over 2,500,000 downloads in the past year, and is the one of the most downloaded items from OTN. This means if you need help, there’s someone sitting nearby you that can assist, and since they’re in the same tool as you, they’ll be speaking the same language. 5. Simple User Interface Up-up-down-down-Left-right-left-right-A-B-A-B-START will get you 30 lives, but you already knew that, right? You connect, you see your objects, you click on your objects. Or, you can use the worksheet to write your queries and programs in. There’s only one toolbar, and just a few buttons. If you’re like me, video games became less fun when each button had 6 action items mapped to it. I just want the good ole ‘A’, ‘B’, ‘SELECT’, and ‘START’ controls. If you’re new to Oracle, you shouldn’t have the double-workload of learning a new complicated tool as well. 6. It’s not a ‘black box’ Click through your objects, but also get the SQL that drives the GUI As you use the wizards to accomplish tasks for you, you can view the SQL statement being generated on your behalf. Just because you have a GUI, doesn’t mean you’re ceding your responsibility to learn the underlying code that makes the database work. 7. It’s four tools in one It’s not just a query tool. Maybe you need to design a data model first? Or maybe you need to migrate your Sybase ASE database to Oracle for a new project? Or maybe you need to create some reports? SQL Developer does all of that. So once you get comfortable with one part of the tool, the others will be much easier to pick up as your needs change. 8. Great learning resources available Videos, blogs, hands-on learning labs – you name it, we got it. Why wait for someone to train you, when you can train yourself at your own pace? 9. You can use it to teach yourself SQL Instead of being faced with the white-screen-of-panic, you can visually build your queries by dragging and dropping tables and views into the Query Builder. Yes, ‘just like Access’ – only better. And as you build your query, toggle to the Worksheet panel and see the SQL statement. Again, SQL Developer is not a black box. If you prefer to learn by trial and error, the worksheet will attempt to suggest the next bit of your SQL statement with it’s completion insight feature. And if you have syntax errors, those will be highlighted – just like your misspelled words in your favorite word processor. 10. It scales to match your experience level You won’t be a n00b forever. In 6-8 months, when you’re ready to tackle something a bit more complicated, like XML DB or Oracle Spatial, the tool is already there waiting on you. No need to go out and find the ‘advanced’ tool. 11. Wait, you said this was a ‘Top 10′ list? Yes. Yes, I did. I’m using this ‘trick’ to get you to continue reading because I’m going to say something you might not want to hear. Are you ready? Tools won’t replace experience, failure, hard work, and training. Just because you have the keys to the car, doesn’t mean you’re ready to head out on the race track. While SQL Developer reduces the barriers to entry, it does not completely remove them. Many experienced folks simply do not like tools. Rather, they don’t like the people that pick up tools without the know-how to properly use them. If you don’t understand what ‘TRUNCATE’ means, don’t try it out. Try picking up a book first. Of course, it’s very nice to have your own sandbox to play in, so you don’t upset the other children. That’s why I really like our Dev Days Database Virtual Box image. It’s your own database to learn and experiment with.

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• JAVA-SQL- Data Migration - ResultSets comparing Failing JUnit test

  - by user1865053

  I CANNOT get this JUnit Test to pass for the life of me. Can somebody point out where this has gone wrong. I am doing a data migration(MSSQL SERVER 2005), but I have the sourceDBUrl and the targetDCUrl the same URL so to narrow it down to syntax errors. So that is what I have, a syntax error. I am comparing the results of a table for the query SELECT programmeapproval, resourceapproval FROM tr_timesheet WHERE timesheetid = ? and the test always fails, but passes for other junit tests I have developed. I created 3 diffemt resultSetsEqual methods and none work. Yet, some other JUnit tests I have developed have PASSED. THE QUERY: SELECT timesheetid, programmeapproval, resourceapproval FROM tr_timesheet Returns three columns timesheetid (PK,int, not null) (populated with a range of numbers 2240 - 2282) programmeapproval (smallint,not null) (populated with the number 1 in every field) resourceapproval (smallint, not null) (populated with a number 1 in every field) When I run the query that is embedded in the code it only returns one row with the programmeapproval and resourceapproval columns and both field populated with the number 1. I have all jdbc drivers correctly installed and tested for connectivity. The JUnit Test is failing at this point according to the IDE. assertTrue(helper.resultSetsEqual2(sourceVal,targetVal)); This is the code: /*THIS IS A JUNIT CLASS****? package a7.unittests.dao; import static org.junit.Assert.assertTrue; import java.sql.Connection; import java.sql.PreparedStatement; import java.sql.ResultSet; import java.sql.Types; import org.junit.Test; import artemispm.tritonalerts.TimesheetAlert; public class UnitTestTimesheetAlert { @Test public void testQUERY_CHECKALERT() throws Exception{ UnitTestHelper helper = new UnitTestHelper(); Connection con = helper.getConnection(helper.sourceDBUrl); Connection conTarget = helper.getConnection(helper.targetDBUrl); PreparedStatement stmt = con.prepareStatement("select programmeapproval, resourceapproval from tr_timesheet where timesheetid = ?"); stmt.setInt(1, 2240); ResultSet sourceVal = stmt.executeQuery(); stmt = conTarget.prepareStatement("select programmeapproval, resourceapproval from tr_timesheet where timesheetid = ?"); stmt.setInt(1,2240); ResultSet targetVal = stmt.executeQuery(); assertTrue(helper.resultSetsEqual2(sourceVal,targetVal)); }} /*END**/ /*THIS IS A REGULAR CLASS**/ package a7.unittests.dao; import java.sql.Connection; import java.sql.DriverManager; import java.sql.ResultSet; import java.sql.ResultSetMetaData; import java.sql.SQLException; public class UnitTestHelper { static String sourceDBUrl = "jdbc:sqlserver://127.0.0.1:1433;databaseName=a7itm;user=a7user;password=a7user"; static String targetDBUrl = "jdbc:sqlserver://127.0.0.1:1433;databaseName=a7itm;user=a7user;password=a7user"; public Connection getConnection(String url)throws Exception{ return DriverManager.getConnection(url); } public boolean resultSetsEqual3 (ResultSet rs1, ResultSet rs2) throws SQLException { int col = 1; //ResultSetMetaData metadata = rs1.getMetaData(); //int count = metadata.getColumnCount(); while (rs1.next() && rs2.next()) { final Object res1 = rs1.getObject(col); final Object res2 = rs2.getObject(col); // Check values if (!res1.equals(res2)) { throw new RuntimeException(String.format("%s and %s aren't equal at common position %d", res1, res2, col)); } // rs1 and rs2 must reach last row in the same iteration if ((rs1.isLast() != rs2.isLast())) { throw new RuntimeException("The two ResultSets contains different number of columns!"); } } return true; } public boolean resultSetsEqual (ResultSet source, ResultSet target) throws SQLException{ while(source.next()) { target.next(); ResultSetMetaData metadata = source.getMetaData(); int count = metadata.getColumnCount(); for (int i =1; i<=count; i++) { if(source.getObject(i) != target.getObject(i)) { return false; } } } return true; } public boolean resultSetsEqual2 (ResultSet source, ResultSet target) throws SQLException{ while(source.next()) { target.next(); ResultSetMetaData metadata = source.getMetaData(); int count = metadata.getColumnCount(); for (int i =1; i<=count; i++) { if(source.getObject(i).equals(target.getObject(i))) { return false; } } } return true; } } /END***/ /*PASTED NEW CLASS - THIS IS A JUNIT TEST CLASS*/ package a7.unittests.dao; import static org.junit.Assert.*; import java.sql.Connection; import java.sql.DriverManager; import org.junit.Test; public class TestDatabaseConnection { @Test public void testConnection() throws Exception{ UnitTestHelper helper = new UnitTestHelper(); Connection con = helper.getConnection(helper.sourceDBUrl); Connection conTarget = helper.getConnection(helper.targetDBUrl); assertTrue(con != null && conTarget != null); } } /**END***/

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• Spatial data in the UK

  - by simonsabin

  I am just loving the fact that the Ordance Survey has now released a huge amount of data that can be used freely. I’ve downloaded the Panorama (tm) data http://www.ordnancesurvey.co.uk/oswebsite/products/land-form-panorama-contours/index.html . which is all the contours for the UK This I’ve loaded into SQL Server using Safe Computing’s FME ( http://www.safe.com/ ). This is because the data is a Autocad DXF file and translating that to SQL Server spatial data is not easy. The FME workbench is not...(read more)

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• SQL Monitor’s data repository

  - by Chris Lambrou

  As one of the developers of SQL Monitor, I often get requests passed on by our support people from customers who are looking to dip into SQL Monitor’s own data repository, in order to pull out bits of information that they’re interested in. Since there’s clearly interest out there in playing around directly with the data repository, I thought I’d write some blog posts to start to describe how it all works. The hardest part for me is knowing where to begin, since the schema of the data repository is pretty big. Hmmm… I guess it’s tricky for anyone to write anything but the most trivial of queries against the data repository without understanding the hierarchy of monitored objects, so perhaps my first post should start there. I always imagine that whenever a customer fires up SSMS and starts to explore their SQL Monitor data repository database, they become immediately bewildered by the schema – that was certainly my experience when I did so for the first time. The following query shows the number of different object types in the data repository schema: SELECT type_desc, COUNT(*) AS [count] FROM sys.objects GROUP BY type_desc ORDER BY type_desc;  type_desccount 1DEFAULT_CONSTRAINT63 2FOREIGN_KEY_CONSTRAINT181 3INTERNAL_TABLE3 4PRIMARY_KEY_CONSTRAINT190 5SERVICE_QUEUE3 6SQL_INLINE_TABLE_VALUED_FUNCTION381 7SQL_SCALAR_FUNCTION2 8SQL_STORED_PROCEDURE100 9SYSTEM_TABLE41 10UNIQUE_CONSTRAINT54 11USER_TABLE193 12VIEW124 With 193 tables, 124 views, 100 stored procedures and 381 table valued functions, that’s quite a hefty schema, and when you browse through it using SSMS, it can be a bit daunting at first. So, where to begin? Well, let’s narrow things down a bit and only look at the tables belonging to the data schema. That’s where all of the collected monitoring data is stored by SQL Monitor. The following query gives us the names of those tables: SELECT sch.name + '.' + obj.name AS [name] FROM sys.objects obj JOIN sys.schemas sch ON sch.schema_id = obj.schema_id WHERE obj.type_desc = 'USER_TABLE' AND sch.name = 'data' ORDER BY sch.name, obj.name; This query still returns 110 tables. I won’t show them all here, but let’s have a look at the first few of them:  name 1data.Cluster_Keys 2data.Cluster_Machine_ClockSkew_UnstableSamples 3data.Cluster_Machine_Cluster_StableSamples 4data.Cluster_Machine_Keys 5data.Cluster_Machine_LogicalDisk_Capacity_StableSamples 6data.Cluster_Machine_LogicalDisk_Keys 7data.Cluster_Machine_LogicalDisk_Sightings 8data.Cluster_Machine_LogicalDisk_UnstableSamples 9data.Cluster_Machine_LogicalDisk_Volume_StableSamples 10data.Cluster_Machine_Memory_Capacity_StableSamples 11data.Cluster_Machine_Memory_UnstableSamples 12data.Cluster_Machine_Network_Capacity_StableSamples 13data.Cluster_Machine_Network_Keys 14data.Cluster_Machine_Network_Sightings 15data.Cluster_Machine_Network_UnstableSamples 16data.Cluster_Machine_OperatingSystem_StableSamples 17data.Cluster_Machine_Ping_UnstableSamples 18data.Cluster_Machine_Process_Instances 19data.Cluster_Machine_Process_Keys 20data.Cluster_Machine_Process_Owner_Instances 21data.Cluster_Machine_Process_Sightings 22data.Cluster_Machine_Process_UnstableSamples 23… There are two things I want to draw your attention to: The table names describe a hierarchy of the different types of object that are monitored by SQL Monitor (e.g. clusters, machines and disks). For each object type in the hierarchy, there are multiple tables, ending in the suffixes _Keys, _Sightings, _StableSamples and _UnstableSamples. Not every object type has a table for every suffix, but the _Keys suffix is especially important and a _Keys table does indeed exist for every object type. In fact, if we limit the query to return only those tables ending in _Keys, we reveal the full object hierarchy: SELECT sch.name + '.' + obj.name AS [name] FROM sys.objects obj JOIN sys.schemas sch ON sch.schema_id = obj.schema_id WHERE obj.type_desc = 'USER_TABLE' AND sch.name = 'data' AND obj.name LIKE '%_Keys' ORDER BY sch.name, obj.name;  name 1data.Cluster_Keys 2data.Cluster_Machine_Keys 3data.Cluster_Machine_LogicalDisk_Keys 4data.Cluster_Machine_Network_Keys 5data.Cluster_Machine_Process_Keys 6data.Cluster_Machine_Services_Keys 7data.Cluster_ResourceGroup_Keys 8data.Cluster_ResourceGroup_Resource_Keys 9data.Cluster_SqlServer_Agent_Job_History_Keys 10data.Cluster_SqlServer_Agent_Job_Keys 11data.Cluster_SqlServer_Database_BackupType_Backup_Keys 12data.Cluster_SqlServer_Database_BackupType_Keys 13data.Cluster_SqlServer_Database_CustomMetric_Keys 14data.Cluster_SqlServer_Database_File_Keys 15data.Cluster_SqlServer_Database_Keys 16data.Cluster_SqlServer_Database_Table_Index_Keys 17data.Cluster_SqlServer_Database_Table_Keys 18data.Cluster_SqlServer_Error_Keys 19data.Cluster_SqlServer_Keys 20data.Cluster_SqlServer_Services_Keys 21data.Cluster_SqlServer_SqlProcess_Keys 22data.Cluster_SqlServer_TopQueries_Keys 23data.Cluster_SqlServer_Trace_Keys 24data.Group_Keys The full object type hierarchy looks like this: Cluster Machine LogicalDisk Network Process Services ResourceGroup Resource SqlServer Agent Job History Database BackupType Backup CustomMetric File Table Index Error Services SqlProcess TopQueries Trace Group Okay, but what about the individual objects themselves represented at each level in this hierarchy? Well that’s what the _Keys tables are for. This is probably best illustrated by way of a simple example – how can I query my own data repository to find the databases on my own PC for which monitoring data has been collected? Like this: SELECT clstr._Name AS cluster_name, srvr._Name AS instance_name, db._Name AS database_name FROM data.Cluster_SqlServer_Database_Keys db JOIN data.Cluster_SqlServer_Keys srvr ON db.ParentId = srvr.Id -- Note here how the parent of a Database is a Server JOIN data.Cluster_Keys clstr ON srvr.ParentId = clstr.Id -- Note here how the parent of a Server is a Cluster WHERE clstr._Name = 'dev-chrisl2' -- This is the hostname of my own PC ORDER BY clstr._Name, srvr._Name, db._Name;  cluster_nameinstance_namedatabase_name 1dev-chrisl2SqlMonitorData 2dev-chrisl2master 3dev-chrisl2model 4dev-chrisl2msdb 5dev-chrisl2mssqlsystemresource 6dev-chrisl2tempdb 7dev-chrisl2sql2005SqlMonitorData 8dev-chrisl2sql2005TestDatabase 9dev-chrisl2sql2005master 10dev-chrisl2sql2005model 11dev-chrisl2sql2005msdb 12dev-chrisl2sql2005mssqlsystemresource 13dev-chrisl2sql2005tempdb 14dev-chrisl2sql2008SqlMonitorData 15dev-chrisl2sql2008master 16dev-chrisl2sql2008model 17dev-chrisl2sql2008msdb 18dev-chrisl2sql2008mssqlsystemresource 19dev-chrisl2sql2008tempdb These results show that I have three SQL Server instances on my machine (a default instance, one named sql2005 and one named sql2008), and each instance has the usual set of system databases, along with a database named SqlMonitorData. Basically, this is where I test SQL Monitor on different versions of SQL Server, when I’m developing. There are a few important things we can learn from this query: Each _Keys table has a column named Id. This is the primary key. Each _Keys table has a column named ParentId. A foreign key relationship is defined between each _Keys table and its parent _Keys table in the hierarchy. There are two exceptions to this, Cluster_Keys and Group_Keys, because clusters and groups live at the root level of the object hierarchy. Each _Keys table has a column named _Name. This is used to uniquely identify objects in the table within the scope of the same shared parent object. Actually, that last item isn’t always true. In some cases, the _Name column is actually called something else. For example, the data.Cluster_Machine_Services_Keys table has a column named _ServiceName instead of _Name (sorry for the inconsistency). In other cases, a name isn’t sufficient to uniquely identify an object. For example, right now my PC has multiple processes running, all sharing the same name, Chrome (one for each tab open in my web-browser). In such cases, multiple columns are used to uniquely identify an object within the scope of the same shared parent object. Well, that’s it for now. I’ve given you enough information for you to explore the _Keys tables to see how objects are stored in your own data repositories. In a future post, I’ll try to explain how monitoring data is stored for each object, using the _StableSamples and _UnstableSamples tables. If you have any questions about this post, or suggestions for future posts, just submit them in the comments section below.

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• Data Governance 2010 Conference in San Diego

  - by Tony Ouk

  The Data Governance Annual Conference is one of the world's most authoritative and vendor neutral event on Data Governance and Data Quality.  The conference will focus on the "how-tos" from starting a data governance and stewardship program to attaining data governance maturity with specific topics on MDM.  This year's event will be hosted June 7 through June 10 in San Diego, California. For more information, including registration details, visit the Data Governance 2010 Conference website.

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• Slide-decks from recent Adelaide SQL Server UG meetings

  - by Rob Farley

  The UK has been well represented this summer at the Adelaide SQL Server User Group, with presentations from Chris Testa-O’Neill (isn’t that the right link? Maybe try this one) and Martin Cairney. The slides are available here and here. I thought I’d particularly mention Martin’s, and how it’s relevant to this month’s T-SQL Tuesday. Martin spoke about Policy-Based Management and the Enterprise Policy Management Framework – something which is remarkably under-used, and yet which can really impact your ability to look after environments. If you have policies set up, then you can easily test each of your SQL instances to see if they are still satisfying a set of policies as defined. Automation (the topic of this month’s T-SQL Tuesday) should mean that your life is made easier, thereby enabling to you to do more. It shouldn’t remove the human element, but should remove (most of) the human errors. People still need to manage the situation, and work out what needs to be done, etc. We haven’t reached a point where computers can replace people, but they are very good at replace the mundaneness and monotony of our jobs. They’ve made our lives more interesting (although many would rightly argue that they have also made our lives more complex) by letting us focus on the stuff that changes. Martin named his talk Put Your Feet Up, which nicely expresses the fact that managing systems shouldn’t be about running around checking things all the time. It must be about having systems in place which tell you when things aren’t going well. It’s never quite as simple as being able to actually put your feet up, but certainly no system should require constant attention. It’s definitely a policy we at LobsterPot adhere to, whether it’s an alert to let us know that an ETL package has run successfully, or a script that generates some code for a report. If things can be automated, it reduces the chance of error, reduces the repetitive nature of work, and in general, keeps both consultants and clients much happier.

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• How to search for newline or linebreak characters in Excel?

  - by Highly Irregular

  I've imported some data into Excel (from a text file) and it contains some sort of newline characters. It looks like this initially: If I hit F2 (to edit) then Enter (to save changes) on each of the cells with a newline (without actually editing anything), Excel automatically changes the layout to look like this: I don't want these newlines characters here, as it messes up data processing further down the track. How can I do a search for these to detect more of them? The usual search function doesn't accept an enter character as a search character.

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• Slide-decks from recent Adelaide SQL Server UG meetings

  - by Rob Farley

  The UK has been well represented this summer at the Adelaide SQL Server User Group, with presentations from Chris Testa-O’Neill (isn’t that the right link? Maybe try this one) and Martin Cairney. The slides are available here and here. I thought I’d particularly mention Martin’s, and how it’s relevant to this month’s T-SQL Tuesday. Martin spoke about Policy-Based Management and the Enterprise Policy Management Framework – something which is remarkably under-used, and yet which can really impact your ability to look after environments. If you have policies set up, then you can easily test each of your SQL instances to see if they are still satisfying a set of policies as defined. Automation (the topic of this month’s T-SQL Tuesday) should mean that your life is made easier, thereby enabling to you to do more. It shouldn’t remove the human element, but should remove (most of) the human errors. People still need to manage the situation, and work out what needs to be done, etc. We haven’t reached a point where computers can replace people, but they are very good at replace the mundaneness and monotony of our jobs. They’ve made our lives more interesting (although many would rightly argue that they have also made our lives more complex) by letting us focus on the stuff that changes. Martin named his talk Put Your Feet Up, which nicely expresses the fact that managing systems shouldn’t be about running around checking things all the time. It must be about having systems in place which tell you when things aren’t going well. It’s never quite as simple as being able to actually put your feet up, but certainly no system should require constant attention. It’s definitely a policy we at LobsterPot adhere to, whether it’s an alert to let us know that an ETL package has run successfully, or a script that generates some code for a report. If things can be automated, it reduces the chance of error, reduces the repetitive nature of work, and in general, keeps both consultants and clients much happier.

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• Oracle Data Integration 12c: Simplified, Future-Ready, High-Performance Solutions

  - by Thanos Terentes Printzios

  In today’s data-driven business environment, organizations need to cost-effectively manage the ever-growing streams of information originating both inside and outside the firewall and address emerging deployment styles like cloud, big data analytics, and real-time replication. Oracle Data Integration delivers pervasive and continuous access to timely and trusted data across heterogeneous systems. Oracle is enhancing its data integration offering announcing the general availability of 12c release for the key data integration products: Oracle Data Integrator 12c and Oracle GoldenGate 12c, delivering Simplified and High-Performance Solutions for Cloud, Big Data Analytics, and Real-Time Replication. The new release delivers extreme performance, increase IT productivity, and simplify deployment, while helping IT organizations to keep pace with new data-oriented technology trends including cloud computing, big data analytics, real-time business intelligence. With the 12c release Oracle becomes the new leader in the data integration and replication technologies as no other vendor offers such a complete set of data integration capabilities for pervasive, continuous access to trusted data across Oracle platforms as well as third-party systems and applications. Oracle Data Integration 12c release addresses data-driven organizations’ critical and evolving data integration requirements under 3 key themes: Future-Ready Solutions : Supporting Current and Emerging Initiatives Extreme Performance : Even higher performance than ever before Fast Time-to-Value : Higher IT Productivity and Simplified Solutions  With the new capabilities in Oracle Data Integrator 12c, customers can benefit from: Superior developer productivity, ease of use, and rapid time-to-market with the new flow-based mapping model, reusable mappings, and step-by-step debugger. Increased performance when executing data integration processes due to improved parallelism. Improved productivity and monitoring via tighter integration with Oracle GoldenGate 12c and Oracle Enterprise Manager 12c. Improved interoperability with Oracle Warehouse Builder which enables faster and easier migration to Oracle Data Integrator’s strategic data integration offering. Faster implementation of business analytics through Oracle Data Integrator pre-integrated with Oracle BI Applications’ latest release. Oracle Data Integrator also integrates simply and easily with Oracle Business Analytics tools, including OBI-EE and Oracle Hyperion. Support for loading and transforming big and fast data, enabled by integration with big data technologies: Hadoop, Hive, HDFS, and Oracle Big Data Appliance. Only Oracle GoldenGate provides the best-of-breed real-time replication of data in heterogeneous data environments. With the new capabilities in Oracle GoldenGate 12c, customers can benefit from: Simplified setup and management of Oracle GoldenGate 12c when using multiple database delivery processes via a new Coordinated Delivery feature for non-Oracle databases. Expanded heterogeneity through added support for the latest versions of major databases such as Sybase ASE v 15.7, MySQL NDB Clusters 7.2, and MySQL 5.6., as well as integration with Oracle Coherence. Enhanced high availability and data protection via integration with Oracle Data Guard and Fast-Start Failover integration. Enhanced security for credentials and encryption keys using Oracle Wallet. Real-time replication for databases hosted on public cloud environments supported by third-party clouds. Tight integration between Oracle Data Integrator 12c and Oracle GoldenGate 12c and other Oracle technologies, such as Oracle Database 12c and Oracle Applications, provides a number of benefits for organizations: Tight integration between Oracle Data Integrator 12c and Oracle GoldenGate 12c enables developers to leverage Oracle GoldenGate’s low overhead, real-time change data capture completely within the Oracle Data Integrator Studio without additional training. Integration with Oracle Database 12c provides a strong foundation for seamless private cloud deployments. Delivers real-time data for reporting, zero downtime migration, and improved performance and availability for Oracle Applications, such as Oracle E-Business Suite and ATG Web Commerce . Oracle’s data integration offering is optimized for Oracle Engineered Systems and is an integral part of Oracle’s fast data, real-time analytics strategy on Oracle Exadata Database Machine and Oracle Exalytics In-Memory Machine. Oracle Data Integrator 12c and Oracle GoldenGate 12c differentiate the new offering on data integration with these many new features. This is just a quick glimpse into Oracle Data Integrator 12c and Oracle GoldenGate 12c. Find out much more about the new release in the video webcast "Introducing 12c for Oracle Data Integration", where customer and partner speakers, including SolarWorld, BT, Rittman Mead will join us in launching the new release. Resource Kits Meet Oracle Data Integration 12c  Discover what's new with Oracle Goldengate 12c  Oracle EMEA DIS (Data Integration Solutions) Partner Community is available for all your questions, while additional partner focused webcasts will be made available through our blog here, so stay connected. For any questions please contact us at partner.imc-AT-beehiveonline.oracle-DOT-com Stay Connected Oracle Newsletters

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• Oracle SQL Developer: Single Object Compare

  - by thatjeffsmith

  There’s a nasty rumor going around that you can’t compare database objects and/or code in Oracle SQL Developer. So let’s put that to bed right now. First, here’s how to compare: PL/SQL to PL/SQL or a SQL statement to another SQL statement So now that that’s settled, why don’t we take a look at how to compare a single table, to another table – whether it’s in the same database or a different database. Database Diff There’s no additional licensing requirement here. If you have SQL Developer, you can use this feature. if you’re going to compare 1 table to another, make sure you ONLY have ‘tables’ checked And then, use this dialog to select your table(s): Move over the object(s) you want to compare over to the right hand side. And now we can move onto the results. The differences, side-by-side, and the script to make B look like A Common lines with differences are highlighted in blue, new lines are highlighted in red. So that’s why they are different, but here’s the script to synch up the differences: Read the script, TEST the script, apply the script. And that’s it. Well, that’s mostly it. If you have questions about how to compare a database object in a schema you don’t have the login information for, read this post next.

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• Validating Petabytes of Data with Regularity and Thoroughness

  - by rickramsey

  by Brian Zents When former Intel CEO Andy Grove said “only the paranoid survive,” he wasn’t necessarily talking about tape storage administrators, but it’s a lesson they’ve learned well. After all, tape storage is the last line of defense to prevent data loss, so tape administrators are extra cautious in making sure their data is secure. Not surprisingly, we are often asked for ways to validate tape media and the files on them. In the past, an administrator could validate the media, but doing so was often tedious or disruptive or both. The debut of the Data Integrity Validation (DIV) and Library Media Validation (LMV) features in the Oracle T10000C drive helped eliminate many of these pains. Also available with the Oracle T10000D drive, these features use hardware-assisted CRC checks that not only ensure the data is written correctly the first time, but also do so much more efficiently. Traditionally, a CRC check takes at least 25 seconds per 4GB file with a 2:1 compression ratio, but the T10000C/D drives can reduce the check to a maximum of nine seconds because the entire check is contained within the drive. No data needs to be sent to a host application. A time savings of at least 64 percent is extremely beneficial over the course of checking an entire 8.5TB T10000D tape. While the DIV and LMV features are better than anything else out there, what storage administrators really need is a way to check petabytes of data with regularity and thoroughness. With the launch of Oracle StorageTek Tape Analytics (STA) 2.0 in April, there is finally a solution that addresses this longstanding need. STA bundles these features into one interface to automate all media validation activities across all Oracle SL3000 and SL8500 tape libraries in an environment. And best of all, the validation process can be associated with the health checks an administrator would be doing already through STA. In fact, STA validates the media based on any of the following policies: Random Selection – Randomly selects media for validation whenever a validation drive in the standalone library or library complex is available. Media Health = Action – Selects media that have had a specified number of successive exchanges resulting in an Exchange Media Health of “Action.” You can specify from one to five exchanges. Media Health = Evaluate – Selects media that have had a specified number of successive exchanges resulting in an Exchange Media Health of “Evaluate.” You can specify from one to five exchanges. Media Health = Monitor – Selects media that have had a specified number of successive exchanges resulting in an Exchange Media Health of “Monitor.” You can specify from one to five exchanges. Extended Period of Non-Use – Selects media that have not had an exchange for a specified number of days. You can specify from 365 to 1,095 days (one to three years). Newly Entered – Selects media that have recently been entered into the library. Bad MIR Detected – Selects media with an exchange resulting in a “Bad MIR Detected” error. A bad media information record (MIR) indicates degraded high-speed access on the media. To avoid disrupting host operations, an administrator designates certain drives for media validation operations. If a host requests a file from media currently being validated, the host’s request takes priority. To ensure that the administrator really knows it is the media that is bad, as opposed to the drive, STA includes drive calibration and qualification features. In addition, validation requests can be re-prioritized or cancelled as needed. To ensure that a specific tape isn’t validated too often, STA prevents a tape from being validated twice within 24 hours via one of the policies described above. A tape can be validated more often if the administrator manually initiates the validation. When the validations are complete, STA reports the results. STA does not report simply a “good” or “bad” status. It also reports if media is even degraded so the administrator can migrate the data before there is a true failure. From that point, the administrators’ paranoia is relieved, as they have the necessary information to make a sound decision about the health of the tapes in their environment. About the Photograph Photograph taken by Rick Ramsey in Death Valley, California, May 2014 - Brian Follow OTN Garage on: Web | Facebook | Twitter | YouTube

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• Configure SQL Server to Allow Remote Connections

  - by Ben Griswold

  Okay. This post isn’t about configuring SQL to allow remote connections, but wait, I still may be able to help you out. "A network-related or instance-specific error occurred while establishing a connection to SQL Server. The server was not found or was not accessible. Verify that the instance name is correct and that SQL Server is configured to allow remote connections. (provider: Named Pipes Provider, error: 40 – Could not open a connection to SQL Server)" I love this exception. It summarized the issue and leads you down a path to solving the problem.  I do wish the bit about allowing remote connections was left out of the message though. I can’t think of a time when having remote connections disabled caused me grief.  Heck, I can’t ever remember how to enable remote connections unless I Google for the answer. Anyway, 9 out of 10 times, SQL Server simply isn’t running.  That’s why the exception occurs.  The next time this exception pops up, open up the services console and make sure SQL Server is started.  And if that’s not the problem, only then start digging into the other possible reasons for the failure.

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• Database Developers Can Now Save 20%

  - by stephen.garth

  Database developers can now increase productivity and save money at the same time. For a limited time, Oracle Store is offering a 20% discount on Oracle SQL Developer Data Modeler. Just enter the code SQLDDM at checkout to get the discount. Oracle SQL Developer Data Modeler is an independent, standalone product with a full spectrum of data and database modeling tools and utilities, including modeling for Entity Relationship Diagrams (ERD), Relational (database design), Data Type and Multi-dimensional modeling, full forward and reverse engineering and DDL code generation. SQL Developer Data Modeler can connect to any supported Oracle Database and is platform independent. Save 20% on Oracle SQL Developer Data Modeler at Oracle Store - Discount Code SQLDDM Find out more about Oracle SQL Developer and Oracle SQL Developer Data Modeler var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www."); document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E")); try { var pageTracker = _gat._getTracker("UA-13185312-1"); pageTracker._trackPageview(); } catch(err) {}

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• How to view special characters in SQL Management Studio

  - by B Z

  Sql 2005 I have a text column that has special characters stored e.g. CR, LF, but I don't know what they are. I would like to view these characters in management studio. Something like in Notepad ++ Show Symbol Show All Characters. My Goal: I am working on a data conversion from one database to another. When the data is converted and viewed in the native application it is displaying some funky characters like a pipe character. I would like to eliminate these characters during the conversion process.

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• Building a Data Mart with Pentaho Data Integration Video Review by Diethard Steiner, Packt Publishing

  - by Compudicted

  Originally posted on: http://geekswithblogs.net/Compudicted/archive/2014/06/01/building-a-data-mart-with-pentaho-data-integration-video-review-again.aspx The Building a Data Mart with Pentaho Data Integration Video by Diethard Steiner from Packt Publishing is more than just a course on how to use Pentaho Data Integration, it also implements and uses the principals of the Data Warehousing (and I even heard the name of Ralph Kimball in the video). Indeed, a video watcher should be familiar with its concepts as the Star Schema, Slowly Changing Dimension types, etc. so I suggest prior to watching this course to consider skimming through the Data Warehouse concepts (if unfamiliar) or even better, read the excellent Ralph’s The Data Warehouse Tooolkit. By the way, the author expands beyond using Pentaho along to MySQL and MonetDB which is a real icing on the cake! Indeed, I even suggest the name of the course should be ‘Building a Data Warehouse with Pentaho’. To successfully complete the course one needs to know some Linux (Ubuntu used in the course), the VI editor and the Bash command shell, but it seems that similar requirements would also apply to the Windows OS. Additionally, knowing some basic SQL would not hurt. As I had said, MonetDB is used in this course several times which seems to be not anymore complex than say MySQL, but based on what I read is very well suited for fast querying big volumes of data thanks to having a columnstore (vertical data storage). I don’t see what else can be a barrier, the material is very digestible. On this note, I must add that the author does not cover how to acquire the software, so here is what I found may help: Pentaho: the free Community Edition must be more than anyone needs to learn it. Or even go into a POC. MonetDB can be downloaded (exists for both, Linux and Windows) from http://goo.gl/FYxMy0 (just see the appropriate link on the left). The author seems to be using Eclipse to run SQL code, one can get it from http://goo.gl/5CcuN. To create, or edit database entities and/or schema otherwise one can use a universal tool called SQuirreL, get it from http://squirrel-sql.sourceforge.net.   Next, I must confess Diethard is very knowledgeable in what he does and beyond. However, there will be some accent heard to the user of the course especially if one’s mother tongue language is English, but it I got over it in a few chapters. I liked the rate at which the material is being presented, it makes me feel I paid for every second Eventually, my impressions are: Pentaho is an awesome ETL offering, it is worth learning it very much (I am an ETL fan and a heavy user of SSIS) MonetDB is nice, it tickles my fancy to know it more Data Warehousing, despite all the BigData tool offerings (Hive, Scoop, Pig on Hadoop), using the traditional tools still rocks Chapters 2 to 6 were the most fun to me with chapter 8 being the most difficult.   In terms of closing, I highly recommend this video to anyone who needs to grasp Pentaho concepts quick, likewise, the course is very well suited for any developer on a “supposed to be done yesterday” type of a project. It is for a beginner to intermediate level ETL/DW developer. But one would need to learn more on Data Warehousing and Pentaho, for such I recommend the 5 star Pentaho Data Integration 4 Cookbook. Enjoy it! Disclaimer: I received this video from the publisher for the purpose of a public review.

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• Building a Data Mart with Pentaho Data Integration Video Review by Diethard Steiner, Packt Publishing

  - by Compudicted

  Originally posted on: http://geekswithblogs.net/Compudicted/archive/2014/06/01/building-a-data-mart-with-pentaho-data-integration-video-review.aspx The Building a Data Mart with Pentaho Data Integration Video by Diethard Steiner from Packt Publishing is more than just a course on how to use Pentaho Data Integration, it also implements and uses the principals of the Data Warehousing (and I even heard the name of Ralph Kimball in the video). Indeed, a video watcher should be familiar with its concepts as the Star Schema, Slowly Changing Dimension types, etc. so I suggest prior to watching this course to consider skimming through the Data Warehouse concepts (if unfamiliar) or even better, read the excellent Ralph’s The Data Warehouse Tooolkit. By the way, the author expands beyond using Pentaho along to MySQL and MonetDB which is a real icing on the cake! Indeed, I even suggest the name of the course should be ‘Building a Data Warehouse with Pentaho’. To successfully complete the course one needs to know some Linux (Ubuntu used in the course), the VI editor and the Bash command shell, but it seems that similar requirements would also apply to the Weindows OS. Additionally, knowing some basic SQL would not hurt. As I had said, MonetDB is used in this course several times which seems to be not anymore complex than say MySQL, but based on what I read is very well suited for fast querying big volumes of data thanks to having a columnstore (vertical data storage). I don’t see what else can be a barrier, the material is very digestible. On this note, I must add that the author does not cover how to acquire the software, so here is what I found may help: Pentaho: the free Community Edition must be more than anyone needs to learn it. Or even go into a POC. MonetDB can be downloaded (exists for both, Linux and Windows) from http://goo.gl/FYxMy0 (just see the appropriate link on the left). The author seems to be using Eclipse to run SQL code, one can get it from http://goo.gl/5CcuN. To create, or edit database entities and/or schema otherwise one can use a universal tool called SQuirreL, get it from http://squirrel-sql.sourceforge.net.   Next, I must confess Diethard is very knowledgeable in what he does and beyond. However, there will be some accent heard to the user of the course especially if one’s mother tongue language is English, but it I got over it in a few chapters. I liked the rate at which the material is being presented, it makes me feel I paid for every second Eventually, my impressions are: Pentaho is an awesome ETL offering, it is worth learning it very much (I am an ETL fan and a heavy user of SSIS) MonetDB is nice, it tickles my fancy to know it more Data Warehousing, despite all the BigData tool offerings (Hive, Scoop, Pig on Hadoop), using the traditional tools still rocks Chapters 2 to 6 were the most fun to me with chapter 8 being the most difficult.   In terms of closing, I highly recommend this video to anyone who needs to grasp Pentaho concepts quick, likewise, the course is very well suited for any developer on a “supposed to be done yesterday” type of a project. It is for a beginner to intermediate level ETL/DW developer. But one would need to learn more on Data Warehousing and Pentaho, for such I recommend the 5 star Pentaho Data Integration 4 Cookbook. Enjoy it! Disclaimer: I received this video from the publisher for the purpose of a public review.

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• Internal Mutation of Persistent Data Structures

  - by Greg Ros

  To clarify, when I mean use the terms persistent and immutable on a data structure, I mean that: The state of the data structure remains unchanged for its lifetime. It always holds the same data, and the same operations always produce the same results. The data structure allows Add, Remove, and similar methods that return new objects of its kind, modified as instructed, that may or may not share some of the data of the original object. However, while a data structure may seem to the user as persistent, it may do other things under the hood. To be sure, all data structures are, internally, at least somewhere, based on mutable storage. If I were to base a persistent vector on an array, and copy it whenever Add is invoked, it would still be persistent, as long as I modify only locally created arrays. However, sometimes, you can greatly increase performance by mutating a data structure under the hood. In more, say, insidious, dangerous, and destructive ways. Ways that might leave the abstraction untouched, not letting the user know anything has changed about the data structure, but being critical in the implementation level. For example, let's say that we have a class called ArrayVector implemented using an array. Whenever you invoke Add, you get a ArrayVector build on top of a newly allocated array that has an additional item. A sequence of such updates will involve n array copies and allocations. Here is an illustration: However, let's say we implement a lazy mechanism that stores all sorts of updates -- such as Add, Set, and others in a queue. In this case, each update requires constant time (adding an item to a queue), and no array allocation is involved. When a user tries to get an item in the array, all the queued modifications are applied under the hood, requiring a single array allocation and copy (since we know exactly what data the final array will hold, and how big it will be). Future get operations will be performed on an empty cache, so they will take a single operation. But in order to implement this, we need to 'switch' or mutate the internal array to the new one, and empty the cache -- a very dangerous action. However, considering that in many circumstances (most updates are going to occur in sequence, after all), this can save a lot of time and memory, it might be worth it -- you will need to ensure exclusive access to the internal state, of course. This isn't a question about the efficacy of such a data structure. It's a more general question. Is it ever acceptable to mutate the internal state of a supposedly persistent or immutable object in destructive and dangerous ways? Does performance justify it? Would you still be able to call it immutable? Oh, and could you implement this sort of laziness without mutating the data structure in the specified fashion?

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• Sabre Manages Fast Data Growth with Oracle Data Integration Products

  - by Irem Radzik

  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} Last year at OpenWorld we announced Sabre Holding as a winner of the Fusion Middleware Innovation Awards. The Sabre team did an excellent job at leveraging cutting edge technologies for managing rapid data growth and exponential scalability demands they have experienced in the travel industry. Today we announced the details and specific benefits of Sabre’s new real-time data integration solution in a press release. Please take a look if you haven’t seen it yet. Sabre Holdings Deploys Oracle Data Integrator and Oracle GoldenGate to Support Rapid Customer Growth There are 3 different areas of benefits Sabre achieved by using Oracle Data Integration products: Manages 7X increase in data sources for the enterprise data warehouse Reduced infrastructure complexity Decreased time to market for new products and services by 30 percent. This simply shows that using latest technologies helps the companies to innovate robust solutions against today’s key data management challenges. And the benefit of using a next generation data integration technology is not only seen in the IT operations, but also in the business side. A better data integration solution for the enterprise data warehouse delivered the platform they need to accelerate how they service their customers, improving their competitive advantage. Tomorrow I will give another great example of innovation with next generation data integration from Oracle. We will be discussing the Fusion Middleware Innovation Awards 2012 winners and their results with using Oracle’s data integration products.

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• Building a Data Warehouse

  - by Paul

  I've seen tutorials articles and posts on how to build datawarehouses with star and snowflakes schemas, denormalization of OLTP databases fact and dimension tables and so on. Also seen comments like: Star schemas are for datamarts, at best. There is absolutely no way a true enterprise data warehouse could be represented in a star schema, or snowflake either. I want to create a database that will server for reporting services and maybe (if that isn't enough) install analisys services and extract reports and data from cubes. My question was : Is it really necesarry to redesign my current database and follow the star/snowflake schemas with fact and dimension tables ? Thank you

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• Working with Spatial Data Part II - Plotting Shapes and Storing Geocoded Data

  Continuing from Part I of the Spatial Data series we model an in-memory/persistent data repository for storing geocoded data and plot the data.

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• Is there still a place for tape storage?

  - by Jon Ericson

  We've backed up our data on LTO tapes for years and it's a real comfort to know we have everything on tape. A sister project and one of our data providers have both moved to 100% disk storage because the cost of disk has dropped so much. When we propose systems to potential customers these days we tend to downplay or not mention our use of tape systems for data storage since it might seem outdated. I feel more comfortable with having data saved in two separate formats: disks and tape. In addition, once data is securely written to tape, I feel (perhaps naively) that it's been permanently saved. Not having to rely on a RAID controller to be able to read back data is another plus for me. Do you see a place for tape backup these days?

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