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  • Does my approach for building a real time monitoring system make sense? [closed]

    - by sameer
    I am developing an application that will display a dashboard that will display data from different SQL databases. This needs to happen in almost real time, our refresh time is about 5 minutes. My approach so far is: Develop a Windows service to accumulate the data from various SQL Server instances. Persist those details into a SQL DB, from which the dashboard will display them on the web page. Trigger fetching of data from the Windows service will every x minutes. The details of the SQL Server instances will be stored in the SQL DB which the Windows service will be referring. Does my approach make sense?

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  • Is there other ways to do insert/update/delete on a remote oracle database?

    - by gunbuster363
    I asked a question recently concerning the speed of execution of insert/update/delete using JDBC driver in a remote machine, but the problem cannot be solved easily. I would like to ask, is there any other way to execute the insert/update/delete to the oracle? The current situation is this: the DB is on a seperate machine than the java program used to update the DB. I looked up the internet and found people suggesting using pure sql or pl/sql to do the update, is that possible? And do we need to operate the sql or pl/sql in a local machine? Because I have no knowledge about pl/sql, so I am not sure if we can create some kind of script and call it on a remote machine. Let say the situation is like this: the input data is on machine A, and the original java program are also on machine A, but the oracle is on machine B. is there any other approach other than JDBC?

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  • 11g???????????????

    - by Liu Maclean(???)
    11g???????????????? ??11g?auto stats gather job????auto task?,???10g?????????: SQL> select client_name,status from DBA_AUTOTASK_CLIENT; CLIENT_NAME STATUS ---------------------------------------------------------------- -------- auto optimizer stats collection ENABLED auto space advisor ENABLED sql tuning advisor ENABLED begin DBMS_AUTO_TASK_ADMIN.DISABLE(client_name => 'auto optimizer stats collection', operation => NULL, window_name => NULL); end; / PL/SQL procedure successfully completed. SQL> select client_name,status from DBA_AUTOTASK_CLIENT; CLIENT_NAME STATUS ---------------------------------------------------------------- -------- auto optimizer stats collection DISABLED auto space advisor ENABLED sql tuning advisor ENABLED

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  • Basics of Join Predicate Pushdown in Oracle

    - by Maria Colgan
    Happy New Year to all of our readers! We hope you all had a great holiday season. We start the new year by continuing our series on Optimizer transformations. This time it is the turn of Predicate Pushdown. I would like to thank Rafi Ahmed for the content of this blog.Normally, a view cannot be joined with an index-based nested loop (i.e., index access) join, since a view, in contrast with a base table, does not have an index defined on it. A view can only be joined with other tables using three methods: hash, nested loop, and sort-merge joins. Introduction The join predicate pushdown (JPPD) transformation allows a view to be joined with index-based nested-loop join method, which may provide a more optimal alternative. In the join predicate pushdown transformation, the view remains a separate query block, but it contains the join predicate, which is pushed down from its containing query block into the view. The view thus becomes correlated and must be evaluated for each row of the outer query block. These pushed-down join predicates, once inside the view, open up new index access paths on the base tables inside the view; this allows the view to be joined with index-based nested-loop join method, thereby enabling the optimizer to select an efficient execution plan. The join predicate pushdown transformation is not always optimal. The join predicate pushed-down view becomes correlated and it must be evaluated for each outer row; if there is a large number of outer rows, the cost of evaluating the view multiple times may make the nested-loop join suboptimal, and therefore joining the view with hash or sort-merge join method may be more efficient. The decision whether to push down join predicates into a view is determined by evaluating the costs of the outer query with and without the join predicate pushdown transformation under Oracle's cost-based query transformation framework. The join predicate pushdown transformation applies to both non-mergeable views and mergeable views and to pre-defined and inline views as well as to views generated internally by the optimizer during various transformations. The following shows the types of views on which join predicate pushdown is currently supported. UNION ALL/UNION view Outer-joined view Anti-joined view Semi-joined view DISTINCT view GROUP-BY view Examples Consider query A, which has an outer-joined view V. The view cannot be merged, as it contains two tables, and the join between these two tables must be performed before the join between the view and the outer table T4. A: SELECT T4.unique1, V.unique3 FROM T_4K T4,            (SELECT T10.unique3, T10.hundred, T10.ten             FROM T_5K T5, T_10K T10             WHERE T5.unique3 = T10.unique3) VWHERE T4.unique3 = V.hundred(+) AND       T4.ten = V.ten(+) AND       T4.thousand = 5; The following shows the non-default plan for query A generated by disabling join predicate pushdown. When query A undergoes join predicate pushdown, it yields query B. Note that query B is expressed in a non-standard SQL and shows an internal representation of the query. B: SELECT T4.unique1, V.unique3 FROM T_4K T4,           (SELECT T10.unique3, T10.hundred, T10.ten             FROM T_5K T5, T_10K T10             WHERE T5.unique3 = T10.unique3             AND T4.unique3 = V.hundred(+)             AND T4.ten = V.ten(+)) V WHERE T4.thousand = 5; The execution plan for query B is shown below. In the execution plan BX, note the keyword 'VIEW PUSHED PREDICATE' indicates that the view has undergone the join predicate pushdown transformation. The join predicates (shown here in red) have been moved into the view V; these join predicates open up index access paths thereby enabling index-based nested-loop join of the view. With join predicate pushdown, the cost of query A has come down from 62 to 32.  As mentioned earlier, the join predicate pushdown transformation is cost-based, and a join predicate pushed-down plan is selected only when it reduces the overall cost. Consider another example of a query C, which contains a view with the UNION ALL set operator.C: SELECT R.unique1, V.unique3 FROM T_5K R,            (SELECT T1.unique3, T2.unique1+T1.unique1             FROM T_5K T1, T_10K T2             WHERE T1.unique1 = T2.unique1             UNION ALL             SELECT T1.unique3, T2.unique2             FROM G_4K T1, T_10K T2             WHERE T1.unique1 = T2.unique1) V WHERE R.unique3 = V.unique3 and R.thousand < 1; The execution plan of query C is shown below. In the above, 'VIEW UNION ALL PUSHED PREDICATE' indicates that the UNION ALL view has undergone the join predicate pushdown transformation. As can be seen, here the join predicate has been replicated and pushed inside every branch of the UNION ALL view. The join predicates (shown here in red) open up index access paths thereby enabling index-based nested loop join of the view. Consider query D as an example of join predicate pushdown into a distinct view. We have the following cardinalities of the tables involved in query D: Sales (1,016,271), Customers (50,000), and Costs (787,766).  D: SELECT C.cust_last_name, C.cust_city FROM customers C,            (SELECT DISTINCT S.cust_id             FROM sales S, costs CT             WHERE S.prod_id = CT.prod_id and CT.unit_price > 70) V WHERE C.cust_state_province = 'CA' and C.cust_id = V.cust_id; The execution plan of query D is shown below. As shown in XD, when query D undergoes join predicate pushdown transformation, the expensive DISTINCT operator is removed and the join is converted into a semi-join; this is possible, since all the SELECT list items of the view participate in an equi-join with the outer tables. Under similar conditions, when a group-by view undergoes join predicate pushdown transformation, the expensive group-by operator can also be removed. With the join predicate pushdown transformation, the elapsed time of query D came down from 63 seconds to 5 seconds. Since distinct and group-by views are mergeable views, the cost-based transformation framework also compares the cost of merging the view with that of join predicate pushdown in selecting the most optimal execution plan. Summary We have tried to illustrate the basic ideas behind join predicate pushdown on different types of views by showing example queries that are quite simple. Oracle can handle far more complex queries and other types of views not shown here in the examples. Again many thanks to Rafi Ahmed for the content of this blog post.

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  • SSISDB Analysis Script on Gist

    - by Davide Mauri
    I've created two simple, yet very useful, script to extract some useful data to quickly monitor SSIS packages execution in SQL Server 2012 and after.get-ssis-execution-status  get-ssis-data-pumped-rows  I've started to use gist since it comes very handy, for this "quick'n'dirty" scripts and snippets, and you can find the above scripts and others (hopefully the number will increase over time...I plan to use gist to store all the code snippet I used to store in a dedicated folder on my machine) there.Now, back to the aforementioned scripts. The first one ("get-ssis-execution-status") returns a list of all executed and executing packages along with latest successful and running executions (so that on can have an idea of the expected run time)error messageswarning messages related to duplicate rows found in lookupsthe second one ("get-ssis-data-pumped-rows") returns information on DataFlows status. Here there's something interesting, IMHO. Nothing exceptional, let it be clear, but nonetheless useful: the script extract information on destinations and row sent to destinations right from the messages produced by the DataFlow component. This helps to quickly understand how many rows as been sent and where...without having to increase the logging level.Enjoy! PSI haven't tested it with SQL Server 2014, but AFAIK they should work without problems. Of course any feedback on this is welcome. 

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  • Cost justification for buying a 32GB superfast Alienware M18x with a price tag of around £5K ($10K)

    - by tonyrogerson
    When considering buying a laptop that’s going to cost me around £5,000 I really need to justify the purchase from a business perspective; my Lenovo W700 has served me very well for the last 2 years, it’s an extremely good machine and as solid as a rock (and as heavy), alas though it is limited to the 8GB. As SQL Server 2012 approaches and with my interest in working in the Business Intelligence space over the next year or two it is clear I need a powerful machine that I can run a full infrastructure though virtualised. My requirements For High Availability / Disaster Recovery research and demonstration Machine for a domain controller Four machines in a shared disk cluster (SQL Server Clustering active – active etc.) Five  machines in a file share cluster (SQL Server Availability Groups) For Business Intelligence research and demonstration Not entirely sure how many machine I want to run here, but it would be to cover the entire BI stack in an enterprise setting, sharepoint, sql server etc. For Big Data Research I have a fondness for the NoSQL approach to scalability and dealing with large volumes so I need a number of machines to research VoltDB, Hadoop etc. As you can see the requirements for a SQL Server consultant to service their clients well is considerable; will 8GB suffice, alas no, it will no longer do. I’m a very strong believer that in order to do your job well you must expense it, short cuts only cost you time, waiting 5 minutes instead of an hour for something to run not only saves me time but my clients time, I can do things quicker and more importantly I can demonstrate concepts. My W700 with the 8GB of RAM and SSD’s cost me around £3.5K two years ago, to be honest I’ve not got the full use I wanted out of it but the machine has had the power when I’ve needed it, it’s served me and my clients well. Alienware now do a model (the M18x) with 32GB of RAM; yes 32GB in a laptop! Dual drives so I can whack a couple of really good SSD’s in there, a quad core with hyper threading i7 and a decent speed. I can reduce the cost of the memory by getting it from Crucial, so instead of £1.5K for 32GB it will be around £900, I can also cost save on the SSD as well. The beauty about the M18x is that it is USB3.0, SATA 3 and also really importantly has eSATA, running VM’s will never be easier, I can have a removeable SSD with my VM’s on it and can plug it into my home machine or laptop – an ideal world! The initial outlay of £5K is peanuts compared to the benefits I’ll give my clients, I will be able to present real enterprise concepts, I’ll also be able to give training on those real enterprise concepts and with real, albeit virtualised machines.

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  • DBCC MEMUSAGE in 2005/8 ?

    - by steveh99999
    I used to like using undocumented command DBCC MEMUSAGE in SQL 2000 to see which tables were using space in SQL data cache. In SQL 2005, this command is not longer present. Instead a DMV – sys.dm_os_buffer_descriptors – can be used to display data cache contents,  but this doesn’t quite give you the same output as DBCC MEMUSAGE. I’m also aware that you can use Quest’s spotlight tool to view a summary of data cache contents. Using  this post by Umachandar Jayachandran  of Microsoft, I was able to create the following equivalent for SQL 2005/8. I’ve wrapped Umachandar’s original query in a CTE to produce summary information :- ;WITH memusage_CTE AS (SELECT bd.database_id, bd.file_id, bd.page_id, bd.page_type , COALESCE(p1.object_id, p2.object_id) AS object_id , COALESCE(p1.index_id, p2.index_id) AS index_id , bd.row_count, bd.free_space_in_bytes, CONVERT(TINYINT,bd.is_modified) AS 'DirtyPage' FROM sys.dm_os_buffer_descriptors AS bd JOIN sys.allocation_units AS au ON au.allocation_unit_id = bd.allocation_unit_id OUTER APPLY ( SELECT TOP(1) p.object_id, p.index_id FROM sys.partitions AS p WHERE p.hobt_id = au.container_id AND au.type IN (1, 3) ) AS p1 OUTER APPLY ( SELECT TOP(1) p.object_id, p.index_id FROM sys.partitions AS p WHERE p.partition_id = au.container_id AND au.type = 2 ) AS p2 WHERE  bd.database_id = DB_ID() AND bd.page_type IN ('DATA_PAGE', 'INDEX_PAGE') ) SELECT TOP 20 DB_NAME(database_id) AS 'Database',OBJECT_NAME(object_id,database_id) AS 'Table Name', index_id,COUNT(*) AS 'Pages in Cache', SUM(dirtyPage) AS 'Dirty Pages' FROM memusage_CTE GROUP BY database_id, object_id, index_id ORDER BY COUNT(*) DESC I’m not 100% happy with the results of the above query however… I’ve noticed that on a busy BizTalk messageBox database  it will return information on pages that contain GHOST rows – . ie where data has already been deleted but has yet to be cleaned-up by a background process – I’m need to investigate further why cache on this server apparently contains so much GHOST data… For more information on the background ghost cleanup process, see this article by Paul Randall. However, I think the results of this query should still be of interest to a DBA. I have another post to come shortly regarding an example I encountered where this information proved useful to me… I notice in SQL 2008, sys.dm_os_buffer_descriptors gained an extra column – numa_mode – I’m interested to see how this is populated and how useful this column can be on a NUMA-enabled system. I’m assuming in theory you could use this column to help analyse how your tables are spread across Numa-enabled data-cache ?

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  • .NET 4: &ldquo;Slim&rdquo;-style performance boost!

    - by Vitus
    RTM version of .NET 4 and Visual Studio 2010 is available, and now we can do some test with it. Parallel Extensions is one of the most valuable part of .NET 4.0. It’s a set of good tools for easily consuming multicore hardware power. And it also contains some “upgraded” sync primitives – Slim-version. For example, it include updated variant of widely known ManualResetEvent. For people, who don’t know about it: you can sync concurrency execution of some pieces of code with this sync primitive. Instance of ManualResetEvent can be in 2 states: signaled and non-signaled. Transition between it possible by Set() and Reset() methods call. Some shortly explanation: Thread 1 Thread 2 Time mre.Reset(); mre.WaitOne(); //code execution 0 //wating //code execution 1 //wating //code execution 2 //wating //code execution 3 //wating mre.Set(); 4 //code execution //… 5 Upgraded version of this primitive is ManualResetEventSlim. The idea in decreasing performance cost in case, when only 1 thread use it. Main concept in the “hybrid sync schema”, which can be done as following:   internal sealed class SimpleHybridLock : IDisposable { private Int32 m_waiters = 0; private AutoResetEvent m_waiterLock = new AutoResetEvent(false);   public void Enter() { if (Interlocked.Increment(ref m_waiters) == 1) return; m_waiterLock.WaitOne(); }   public void Leave() { if (Interlocked.Decrement(ref m_waiters) == 0) return; m_waiterLock.Set(); }   public void Dispose() { m_waiterLock.Dispose(); } } It’s a sample from Jeffry Richter’s book “CLR via C#”, 3rd edition. Primitive SimpleHybridLock have two public methods: Enter() and Leave(). You can put your concurrency-critical code between calls of these methods, and it would executed in only one thread at the moment. Code is really simple: first thread, called Enter(), increase counter. Second thread also increase counter, and suspend while m_waiterLock is not signaled. So, if we don’t have concurrent access to our lock, “heavy” methods WaitOne() and Set() will not called. It’s can give some performance bonus. ManualResetEvent use the similar idea. Of course, it have more “smart” technics inside, like a checking of recursive calls, and so on. I want to know a real difference between classic ManualResetEvent realization, and new –Slim. I wrote a simple “benchmark”: class Program { static void Main(string[] args) { ManualResetEventSlim mres = new ManualResetEventSlim(false); ManualResetEventSlim mres2 = new ManualResetEventSlim(false);   ManualResetEvent mre = new ManualResetEvent(false);   long total = 0; int COUNT = 50;   for (int i = 0; i < COUNT; i++) { mres2.Reset(); Stopwatch sw = Stopwatch.StartNew();   ThreadPool.QueueUserWorkItem((obj) => { //Method(mres, true); Method2(mre, true); mres2.Set(); }); //Method(mres, false); Method2(mre, false);   mres2.Wait(); sw.Stop();   Console.WriteLine("Pass {0}: {1} ms", i, sw.ElapsedMilliseconds); total += sw.ElapsedMilliseconds; }   Console.WriteLine(); Console.WriteLine("==============================="); Console.WriteLine("Done in average=" + total / (double)COUNT); Console.ReadLine(); }   private static void Method(ManualResetEventSlim mre, bool value) { for (int i = 0; i < 9000000; i++) { if (value) { mre.Set(); } else { mre.Reset(); } } }   private static void Method2(ManualResetEvent mre, bool value) { for (int i = 0; i < 9000000; i++) { if (value) { mre.Set(); } else { mre.Reset(); } } } } I use 2 concurrent thread (the main thread and one from thread pool) for setting and resetting ManualResetEvents, and try to run test COUNT times, and calculate average execution time. Here is the results (I get it on my dual core notebook with T7250 CPU and Windows 7 x64): ManualResetEvent ManualResetEventSlim Difference is obvious and serious – in 10 times! So, I think preferable way is using ManualResetEventSlim, because not always on calling Set() and Reset() will be called “heavy” methods for working with Windows kernel-mode objects. It’s a small and nice improvement! ;)

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  • SSAS: Utility to check you have the correct data types and sizes in your cube definition

    - by DrJohn
    This blog describes a tool I developed which allows you to compare the data types and data sizes found in the cube’s data source view with the data types/sizes of the corresponding dimensional attribute.  Why is this important?  Well when creating named queries in a cube’s data source view, it is often necessary to use the SQL CAST or CONVERT operation to change the data type to something more appropriate for SSAS.  This is particularly important when your cube is based on an Oracle data source or using custom SQL queries rather than views in the relational database.   The problem with BIDS is that if you change the underlying SQL query, then the size of the data type in the dimension does not update automatically.  This then causes problems during deployment whereby processing the dimension fails because the data in the relational database is wider than that allowed by the dimensional attribute. In particular, if you use some string manipulation functions provided by SQL Server or Oracle in your queries, you may find that the 10 character string you expect suddenly turns into an 8,000 character monster.  For example, the SQL Server function REPLACE returns column with a width of 8,000 characters.  So if you use this function in the named query in your DSV, you will get a column width of 8,000 characters.  Although the Oracle REPLACE function is far more intelligent, the generated column size could still be way bigger than the maximum length of the data actually in the field. Now this may not be a problem when prototyping, but in your production cubes you really should clean up this kind of thing as these massive strings will add to processing times and storage space. Similarly, you do not want to forget to change the size of the dimension attribute if your database columns increase in size. Introducing CheckCubeDataTypes Utiltity The CheckCubeDataTypes application extracts all the data types and data sizes for all attributes in the cube and compares them to the data types and data sizes in the cube’s data source view.  It then generates an Excel CSV file which contains all this metadata along with a flag indicating if there is a mismatch between the DSV and the dimensional attribute.  Note that the app not only checks all the attribute keys but also the name and value columns for each attribute. Another benefit of having the metadata held in a CSV text file format is that you can place the file under source code control.  This allows you to compare the metadata of the previous cube release with your new release to highlight problems introduced by new development. You can download the C# source code from here: CheckCubeDataTypes.zip A typical example of the output Excel CSV file is shown below - note that the last column shows a data size mismatch by TRUE appearing in the column

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  • Does it take time to deallocate memory?

    - by jm1234567890
    I have a C++ program which, during execution, will allocate about 3-8Gb of memory to store a hash table (I use tr1/unordered_map) and various other data structures. However, at the end of execution, there will be a long pause before returning to shell. For example, at the very end of my main function I have std::cout << "End of execution" << endl; But the execution of my program will go something like $ ./program do stuff... End of execution [long pause of maybe 2 min] $ -- returns to shell Is this expected behavior or am I doing something wrong? I'm guessing that the program is deallocating the memory at the end. But, commercial applications which use large amounts of memory (such as photoshop) do not exhibit this pause when you close the application. Please advise :)

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  • NHibernate and Composite Key References

    - by Rich
    I have a weird situation. I have three entities, Company, Employee, Plan and Participation (in retirement plan). Company PK: Company ID Plan PK: Company ID, Plan ID Employee PK: Company ID, SSN, Employee ID Participation PK: Company ID, SSN, Plan ID The problem is in linking the employee to the participation. From a DB perspective, participation should have Employee ID in the PK (it's not even in table). But it doesn't. NHibernate won't let me map the "has many" because the link expects 3 columns (since Employee PK has 3 columns), but I'd only provide 2. Any ideas on how to do this?

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  • How do I make a Java ResultSet available in my jsp?

    - by melling
    I'd like to swap out an sql:query for some Java code that builds a complex query with several parameters. The current sql is a simple select. <sql:query var="result" dataSource="${dSource}" sql="select * from TABLE " </sql:query How do I take my Java ResultSet (ie. rs = stmt.executeQuery(sql);) and make the results available in my JSP so I can do this textbook JSP? To be more clear, I want to remove the above query and replace it with Java. <% ResultSet rs = stmt.executeQuery(sql); // Messy code will be in some Controller % <c:forEach var="row" items="${result.rows}" <c:out value="${row.name}"/ </c:forEach Do I set the session/page variable in the Java section or is there some EL trick that I can use to access the variable?

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  • 2 TADOQUERY master and Detail tablefilter insert

    - by ml
    How can i work with 2 Tadoquery and work like a Tadoquery (master) Tadotable(detail) !! var tempvar : Variant; begin Edit1.text:=Ano.value; Begin with Ano_planeamento do //Laço de consulta por codigo Begin Close; SQL.Clear; SQL.Add('SELECT * from planeamento_ano'); SQL.Add('Where ano LIKE ''%'+Edit1.text+'%'''); Open; end; end; tempvar := Ano_planeamento.fieldbyname('ano').value; planeamento.close; if tempvar <> null then begin planeamento.SQL.Clear; planeamento.SQL.add('SELECT * FROM planeamento'); planeamento.SQL.add(' WHERE ano = '); planeamento.SQL.add('''' + tempvar + ''''); // here i nead to filter by .... planeamento.open;

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  • Error during data INSERT in php

    - by nectar
    here my code- $sql = "INSERT INTO tblpin ('pinId', 'ownerId', 'usedby', 'status') VALUES "; for($i=0; $i0) { $sql .= ", "; } $sql .= "('$pin[$i]', '$ownerid', 'Free', '1')"; } $sql .= ";"; echo $sql; mysql_query($sql); if(mysql_affected_rows() 0) { echo "done"; } else { echo "Fail"; } output: ** INSERT INTO tblpin ('pinId', 'ownerId', 'usedby', 'status') VALUES ('13837927', 'admin', 'Free', '1'), ('59576082', 'admin', 'Free', '1'); Fail why it is not inserting values when $sql query is right?

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  • SQL Error (2003): Can't connect to MySQL server on 'X.X.X.X.' (10051) - What does this error mean?

    - by BeeS
    I get following error when i try to connect via "HeidiSQL" to my database server (local network) SQL Error (2003): Can't connect to MySQL server on 'X.X.X.X.' (10051) SSH Connection via Putty works fine. I checked the my.cnf file on the server (Ubuntu), but settings like bind_address are correct. Is it possible that my wireless modem (SpeedTouch) makes this trouble? (Because my provider changed the download speed) !? Thank you very much for your help!

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  • How could I import Postgres data dumps into MS SQL?

    - by dean nolan
    I have some data that is from a Postgres database dump (not csv or anything) and I am looking to get it into MS SQL. Is there an easy way to do this or a free tool that doesn't have limits on data import size etc? The Postgres is on a Debian VM and I could export it to csv in there but I am new to Linux and don't know how I would transfer it from the VM to Win 7. Thanks

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  • FTP Publishing with the new Windows Azure Release

    - by Harish Ranganathan
    There is a good chance you might have stumbled upon the new Windows Azure Release that we made on June 6th.  Scott Guthrie’s Post quite summarizes the overall new features. One of my favorite features is the Windows Azure Websites and the ability to do publish files to Azure using your FTP Client. Windows Azure Websites offers low cost (free upto 10 websites) web hosting where you can deploy any website that can run on IIS 7.0, quickly. The earlier releases of Azure SDKs and the Azure platform support .NET 3.5 & above for running your applications.  This was a constraint for many since there are/were a lot of ASP.NET 2.0 applications built over time and simply to put it on Azure, many of you were skeptical to migrate it to .NET 4. Windows Azure Websites offer the flexibility of running IIS 7.0 supported .NET Versions which means you can run .NET 1.1, 2.0, 3.5 and .NET 4.  Not just that! You can also run classic ASP Applications. Windows Azure Websites don’t need you to go through the complexity of adding the Cloud Project Template and then publishing the Configuration Files.  Lets take a step by step understanding of Websites and publishing using FTP. I downloaded the Club Website Starter Kit from http://www.asp.net/downloads/starter-kits/club It also requires a database and I downloaded the SQL Scripts and created a SQL Server Database called Club. This installs a Web Site Project Template.  Note that I am running Windows 8 Release Preview and Visual Studio 2012 RC.  After installing the template, select File – New – Website and don’t forget to choose the Framework version as .NET 2.0 You can see the “Club Website Starter Kit” .  Once you select the Website gets created.  You would encounter a warning indicating that the Club Website Starter Kit uses SQL Express and the recommended database is LocalDB Express.  Click ok to continue.  Once the Website is created open up the Web.config and locate the “ClubSiteDB” connection string.  By default, it points to a SQL Express Database.  Instead configure it to use your local SQL Server. Also, open up Global.asax and comment out the following line if (!Roles.RoleExists("Administrators")) Roles.CreateRole("Administrators"); There seems to be an issue in the code that doesn’t create the role.  Post that, hit CTRL+F5 and you should be able to see the Website Running, as below So, now we have the Club Starter Kit site up running locally.  Moving to Azure Visit http://manage.windowsazure.com/ and sign up for a trial account.  This allows you to host up to 10 websites for free and a host of other benefits.  The free Websites can be extended to an year without any charge.  Once you have signed up, sign in to the portal using the Live ID used for sign up. After signing in, you would be presented with the “All Items” listing page which lists, Websites, Cloud Services, Databases etc.,  If this is the first time, you wouldn’t find anything. Click on the “Websites” link from the left menu.  Click on “New” in the bottom and it should show up a dialog.  In the same, select Website and click on “Quick Create” and in the URL Textbox, specify “MyFirstDemo” and click the “Create Web Site” link below. It should take a few seconds to create the Website.  Once the Website is created, click on the listing and it should open up the Dashboard.  Since we haven’t done anything yet, there shouldn’t be any statistics Click on the “Download publish profile” link in the right bottom.  This file has the FTP publishing settings. Also, if you scroll down you can see the FTP URL for this site.  It should typically start ftp://waws-xxxx-xxx-xxxx In the downloaded publish profile file, you can also find the ftp URL.  Pick the following from this file publishUrl (the 2nd one, the one that features after publishMethod =”FTP”) and the userName and userPWD that follows. Note that we have everything required to publish the files.  But since the Club Starter Kit uses Databases, we need to have the Database running on SQL Azure.  Go back to the Main Menu and click on “New” in the bottom but this time select “SQL Database” and provide “Club” as Database name for “Quick Create” If this is the first time a Server would be created.  Otherwise, it would pickup the existing server name. Once the database is created, you can use the SQL Azure Migration Wizard http://sqlazuremw.codeplex.com/ and provide the credentials to connect to local database and then the SQL Azure database for migrating the “Club” database.  The migration wizard UI hasn’t changed much and is the same as explained by me in one my posts earlier http://geekswithblogs.net/ranganh/archive/2009/09/29/taking-your-northwind-database-to-sql-azure-and-binding-it.aspx Once the database is migrated, come back to the main screen and click on the Database base in the Azure Management Portal.  It opens up the dashboard of the database.  Click on “Show connection Strings” and it would popup a list of connection string formats.  Choose the ADO.NET connection string and after editing the password with the password that you provided when creating the database server in the Azure Portal, paste it into the config file of the Club Starter Kit Website.  Just to reiterate, the connection string key is ClubSiteDB. Try running the Website once to ensure that the application though running locally could connect to the SQL Database running on Azure. Once you are able to run the website successfully, we are all set to do the FTP Publishing. Download your favorite FTP tool.  I use http://filezilla-project.org/ In the Host Textbox, paste the FTP URL that you picked up from the publish profile file and also paste the username and password.  Click on “QuickConnect”.  If everything is fine, you should be able to connect to the remote server.  If it is successfully connected, you can see the wwwroot folder of the Website, running in Azure Make sure on the “Local Site” in the left, you choose the path to the folder of your Website.  Open up the Website folder on the left such that it lists all the files and folders inside.  Select all of them and click select “Upload” or simply drag and drop all the files to the root folder that is listed above.  Once the publishing is done, you should be able to hit the SiteURL that you can find the dashboard page of the website.  In our case, it would be http://MyFirstDemo.azurewebsites.net That’s it, we have now done FTP publishing in Azure and that too we are running a .NET 2.0 Website on Azure. Cheers !!!

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  • Oracle Database 12 c New Partition Maintenance Features by Gwen Lazenby

    - by hamsun
    One of my favourite new features in Oracle Database 12c is the ability to perform partition maintenance operations on multiple partitions. This means we can now add, drop, truncate and merge multiple partitions in one operation, and can split a single partition into more than two partitions also in just one command. This would certainly have made my life slightly easier had it been available when I administered a data warehouse at Oracle 9i. To demonstrate this new functionality and syntax, I am going to create two tables, ORDERS and ORDERS_ITEMS which have a parent-child relationship. ORDERS is to be partitioned using range partitioning on the ORDER_DATE column, and ORDER_ITEMS is going to partitioned using reference partitioning and its foreign key relationship with the ORDERS table. This form of partitioning was a new feature in 11g and means that any partition maintenance operations performed on the ORDERS table will also take place on the ORDER_ITEMS table as well. First create the ORDERS table - SQL CREATE TABLE orders ( order_id NUMBER(12), order_date TIMESTAMP, order_mode VARCHAR2(8), customer_id NUMBER(6), order_status NUMBER(2), order_total NUMBER(8,2), sales_rep_id NUMBER(6), promotion_id NUMBER(6), CONSTRAINT orders_pk PRIMARY KEY(order_id) ) PARTITION BY RANGE(order_date) (PARTITION Q1_2007 VALUES LESS THAN (TO_DATE('01-APR-2007','DD-MON-YYYY')), PARTITION Q2_2007 VALUES LESS THAN (TO_DATE('01-JUL-2007','DD-MON-YYYY')), PARTITION Q3_2007 VALUES LESS THAN (TO_DATE('01-OCT-2007','DD-MON-YYYY')), PARTITION Q4_2007 VALUES LESS THAN (TO_DATE('01-JAN-2008','DD-MON-YYYY')) ); Table created. Now the ORDER_ITEMS table SQL CREATE TABLE order_items ( order_id NUMBER(12) NOT NULL, line_item_id NUMBER(3) NOT NULL, product_id NUMBER(6) NOT NULL, unit_price NUMBER(8,2), quantity NUMBER(8), CONSTRAINT order_items_fk FOREIGN KEY(order_id) REFERENCES orders(order_id) on delete cascade) PARTITION BY REFERENCE(order_items_fk) tablespace example; Table created. Now look at DBA_TAB_PARTITIONS to get details of what partitions we have in the two tables – SQL select table_name,partition_name, partition_position position, high_value from dba_tab_partitions where table_owner='SH' and table_name like 'ORDER_%' order by partition_position, table_name; TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Q1_2007 1 TIMESTAMP' 2007-04-01 00:00:00' ORDER_ITEMS Q1_2007 1 ORDERS Q2_2007 2 TIMESTAMP' 2007-07-01 00:00:00' ORDER_ITEMS Q2_2007 2 ORDERS Q3_2007 3 TIMESTAMP' 2007-10-01 00:00:00' ORDER_ITEMS Q3_2007 3 ORDERS Q4_2007 4 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Q4_2007 4 Just as an aside it is also now possible in 12c to use interval partitioning on reference partitioned tables. In 11g it was not possible to combine these two new partitioning features. For our first example of the new 12cfunctionality, let us add all the partitions necessary for 2008 to the tables using one command. Notice that the partition specification part of the add command is identical in format to the partition specification part of the create command as shown above - SQL alter table orders add PARTITION Q1_2008 VALUES LESS THAN (TO_DATE('01-APR-2008','DD-MON-YYYY')), PARTITION Q2_2008 VALUES LESS THAN (TO_DATE('01-JUL-2008','DD-MON-YYYY')), PARTITION Q3_2008 VALUES LESS THAN (TO_DATE('01-OCT-2008','DD-MON-YYYY')), PARTITION Q4_2008 VALUES LESS THAN (TO_DATE('01-JAN-2009','DD-MON-YYYY')); Table altered. Now look at DBA_TAB_PARTITIONS and we can see that the 4 new partitions have been added to both tables – SQL select table_name,partition_name, partition_position position, high_value from dba_tab_partitions where table_owner='SH' and table_name like 'ORDER_%' order by partition_position, table_name; TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Q1_2007 1 TIMESTAMP' 2007-04-01 00:00:00' ORDER_ITEMS Q1_2007 1 ORDERS Q2_2007 2 TIMESTAMP' 2007-07-01 00:00:00' ORDER_ITEMS Q2_2007 2 ORDERS Q3_2007 3 TIMESTAMP' 2007-10-01 00:00:00' ORDER_ITEMS Q3_2007 3 ORDERS Q4_2007 4 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Q4_2007 4 ORDERS Q1_2008 5 TIMESTAMP' 2008-04-01 00:00:00' ORDER_ITEMS Q1_2008 5 ORDERS Q2_2008 6 TIMESTAMP' 2008-07-01 00:00:00' ORDER_ITEM Q2_2008 6 ORDERS Q3_2008 7 TIMESTAMP' 2008-10-01 00:00:00' ORDER_ITEMS Q3_2008 7 ORDERS Q4_2008 8 TIMESTAMP' 2009-01-01 00:00:00' ORDER_ITEMS Q4_2008 8 Next, we can drop or truncate multiple partitions by giving a comma separated list in the alter table command. Note the use of the plural ‘partitions’ in the command as opposed to the singular ‘partition’ prior to 12c– SQL alter table orders drop partitions Q3_2008,Q2_2008,Q1_2008; Table altered. Now look at DBA_TAB_PARTITIONS and we can see that the 3 partitions have been dropped in both the two tables – TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Q1_2007 1 TIMESTAMP' 2007-04-01 00:00:00' ORDER_ITEMS Q1_2007 1 ORDERS Q2_2007 2 TIMESTAMP' 2007-07-01 00:00:00' ORDER_ITEMS Q2_2007 2 ORDERS Q3_2007 3 TIMESTAMP' 2007-10-01 00:00:00' ORDER_ITEMS Q3_2007 3 ORDERS Q4_2007 4 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Q4_2007 4 ORDERS Q4_2008 5 TIMESTAMP' 2009-01-01 00:00:00' ORDER_ITEMS Q4_2008 5 Now let us merge all the 2007 partitions together to form one single partition – SQL alter table orders merge partitions Q1_2005, Q2_2005, Q3_2005, Q4_2005 into partition Y_2007; Table altered. TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Y_2007 1 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Y_2007 1 ORDERS Q4_2008 2 TIMESTAMP' 2009-01-01 00:00:00' ORDER_ITEMS Q4_2008 2 Splitting partitions is a slightly more involved. In the case of range partitioning one of the new partitions must have no high value defined, and in list partitioning one of the new partitions must have no list of values defined. I call these partitions the ‘everything else’ partitions, and will contain any rows contained in the original partition that are not contained in the any of the other new partitions. For example, let us split the Y_2007 partition back into 4 quarterly partitions – SQL alter table orders split partition Y_2007 into (PARTITION Q1_2007 VALUES LESS THAN (TO_DATE('01-APR-2007','DD-MON-YYYY')), PARTITION Q2_2007 VALUES LESS THAN (TO_DATE('01-JUL-2007','DD-MON-YYYY')), PARTITION Q3_2007 VALUES LESS THAN (TO_DATE('01-OCT-2007','DD-MON-YYYY')), PARTITION Q4_2007); Now look at DBA_TAB_PARTITIONS to get details of the new partitions – TABLE_NAME PARTITION_NAME POSITION HIGH_VALUE -------------- --------------- -------- ------------------------- ORDERS Q1_2007 1 TIMESTAMP' 2007-04-01 00:00:00' ORDER_ITEMS Q1_2007 1 ORDERS Q2_2007 2 TIMESTAMP' 2007-07-01 00:00:00' ORDER_ITEMS Q2_2007 2 ORDERS Q3_2007 3 TIMESTAMP' 2007-10-01 00:00:00' ORDER_ITEMS Q3_2007 3 ORDERS Q4_2007 4 TIMESTAMP' 2008-01-01 00:00:00' ORDER_ITEMS Q4_2007 4 ORDERS Q4_2008 5 TIMESTAMP' 2009-01-01 00:00:00' ORDER_ITEMS Q4_2008 5 Partition Q4_2007 has a high value equal to the high value of the original Y_2007 partition, and so has inherited its upper boundary from the partition that was split. As for a list partitioning example let look at the following another table, SALES_PAR_LIST, which has 2 partitions, Americas and Europe and a partitioning key of country_name. SQL select table_name,partition_name, high_value from dba_tab_partitions where table_owner='SH' and table_name = 'SALES_PAR_LIST'; TABLE_NAME PARTITION_NAME HIGH_VALUE -------------- --------------- ----------------------------- SALES_PAR_LIST AMERICAS 'Argentina', 'Canada', 'Peru', 'USA', 'Honduras', 'Brazil', 'Nicaragua' SALES_PAR_LIST EUROPE 'France', 'Spain', 'Ireland', 'Germany', 'Belgium', 'Portugal', 'Denmark' Now split the Americas partition into 3 partitions – SQL alter table sales_par_list split partition americas into (partition south_america values ('Argentina','Peru','Brazil'), partition north_america values('Canada','USA'), partition central_america); Table altered. Note that no list of values was given for the ‘Central America’ partition. However it should have inherited any values in the original ‘Americas’ partition that were not assigned to either the ‘North America’ or ‘South America’ partitions. We can confirm this by looking at the DBA_TAB_PARTITIONS view. SQL select table_name,partition_name, high_value from dba_tab_partitions where table_owner='SH' and table_name = 'SALES_PAR_LIST'; TABLE_NAME PARTITION_NAME HIGH_VALUE --------------- --------------- -------------------------------- SALES_PAR_LIST SOUTH_AMERICA 'Argentina', 'Peru', 'Brazil' SALES_PAR_LIST NORTH_AMERICA 'Canada', 'USA' SALES_PAR_LIST CENTRAL_AMERICA 'Honduras', 'Nicaragua' SALES_PAR_LIST EUROPE 'France', 'Spain', 'Ireland', 'Germany', 'Belgium', 'Portugal', 'Denmark' In conclusion, I hope that DBA’s whose work involves maintaining partitions will find the operations a bit more straight forward to carry out once they have upgraded to Oracle Database 12c. Gwen Lazenby is a Principal Training Consultant at Oracle. She is part of Oracle University's Core Technology delivery team based in the UK, teaching Database Administration and Linux courses. Her specialist topics include using Oracle Partitioning and Parallelism in Data Warehouse environments, as well as Oracle Spatial and RMAN.

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  • Add Recaptcha and GridView to an ASP.NET 3.5 Guestbook using MS SQL Server and VB.NET

    This is the conclusion to a four-part ASP.NET 3.5 guest book application tutorial series. In this last part you will learn how to integrate Recaptcha which is used to prevent spam automatic bot submission. Also to be discussed is how to add a GridView web control which is used to display all guest book comments retrieved from the database.... Download a Free Trial of Windows 7 Reduce Management Costs and Improve Productivity with Windows 7

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  • Cannot connect to Amazon RDS

    - by Justin
    I have created an Amazon RDS database under the free tier (SQL Server Express, micro instance etc.), but I cannot connect to the server using Microsoft SQL Server Management Studio. I have configured the security group of the database instance (default) to accept my IP address. I am following the connection guide from amazon located here The error I receive is: Cannot connect to databaseName.c***rnqg***v.us-east-1.rds.amazonaws.com,1433. 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: TCP Provider, error: 0 - A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond.) (Microsoft SQL Server, Error: 10060) I am using Server type "Database Engine" and using SQL Server Authentication.

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  • List of resources for database continuous integration

    - by David Atkinson
    Because there is so little information on database continuous integration out in the wild, I've taken it upon myself to aggregate as much as possible and post the links to this blog. Because it's my area of expertise, this will focus on SQL Server and Red Gate tooling, although I am keen to include any quality articles that discuss the topic in general terms. Please let me know if you find a resource that I haven't listed! General database Continuous Integration · What is Database Continuous Integration? (David Atkinson) · Continuous Integration for SQL Server Databases (Troy Hunt) · Installing NAnt to drive database continuous integration (David Atkinson) · Continuous Integration Tip #3 - Version your Databases as part of your automated build (Doug Rathbone) · How the "migrations" approach makes database continuous integration possible (David Atkinson) · Continuous Integration for the Database (Keith Bloom) Setting up Continuous Integration with Red Gate tools · Continuous integration for databases using Red Gate tools - A technical overview (White Paper, Roger Hart and David Atkinson) · Continuous integration for databases using Red Gate SQL tools (Product pages) · Database continuous integration step by step (David Atkinson) · Database Continuous Integration with Red Gate Tools (video, David Atkinson) · Database schema synchronisation with RedGate (Vincent Brouillet) · Database continuous integration and deployment with Red Gate tools (David Duffett) · Automated database releases with TeamCity and Red Gate (Troy Hunt) · How to build a database from source control (David Atkinson) · Continuous Integration Automated Database Update Process (Lance Lyons) Other · Evolutionary Database Design (Martin Fowler) · Recipes for Continuous Database Integration: Evolutionary Database Development (book, Pramod J Sadalage) · Recipes for Continuous Database Integration (book, Pramod Sadalage) · The Red Gate Guide to SQL Server Team-based Development (book, Phil Factor, Grant Fritchey, Alex Kuznetsov, Mladen Prajdic) · Using SQL Test Database Unit Testing with TeamCity Continuous Integration (Dave Green) · Continuous Database Integration (covers MySQL, Perason Education) Technorati Tags: SQL Server,Continous Integration

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  • Migrate from MySQL to PostgreSQL on Linux (Kubuntu)

    - by Dave Jarvis
    Storyline Trying to migrate a database from MySQL to PostgreSQL. All the documentation I have read covers, in great detail, how to migrate the structure. I have found very little documentation on migrating the data. The schema has 13 tables (which have been migrated successfully) and 9 GB of data. MySQL version: 5.1.x PostgreSQL version: 8.4.x I want to use the R programming language to analyze the data using SQL select statements; PostgreSQL has PL/R, but MySQL has nothing (as far as I can tell). A long time ago in a galaxy far, far away... Create the database location (/var has insufficient space; also dislike having the PostgreSQL version number everywhere -- upgrading would break scripts!): sudo mkdir -p /home/postgres/main sudo cp -Rp /var/lib/postgresql/8.4/main /home/postgres sudo chown -R postgres.postgres /home/postgres sudo chmod -R 700 /home/postgres sudo usermod -d /home/postgres/ postgres All good to here. Next, restart the server and configure the database using these installation instructions: sudo apt-get install postgresql pgadmin3 sudo /etc/init.d/postgresql-8.4 stop sudo vi /etc/postgresql/8.4/main/postgresql.conf Change data_directory to /home/postgres/main sudo /etc/init.d/postgresql-8.4 start sudo -u postgres psql postgres \password postgres sudo -u postgres createdb climate pgadmin3 Use pgadmin3 to configure the database and create a schema. A New Hope The episode began in a remote shell known as bash, with both databases running, and the installation of a command with a most unusual logo: SQL Fairy. perl Makefile.PL sudo make install sudo apt-get install perl-doc (strangely, it is not called perldoc) perldoc SQL::Translator::Manual Extract a PostgreSQL-friendly DDL and all the MySQL data: sqlt -f DBI --dsn dbi:mysql:climate --db-user user --db-password password -t PostgreSQL > climate-pg-ddl.sql mysqldump --skip-add-locks --complete-insert --no-create-db --no-create-info --quick --result-file="climate-my.sql" --databases climate --skip-comments -u root -p The Database Strikes Back Recreate the structure in PostgreSQL as follows: pgadmin3 (switch to it) Click the Execute arbitrary SQL queries icon Open climate-pg-ddl.sql Search for TABLE " replace with TABLE climate." (insert the schema name climate) Search for on " replace with on climate." (insert the schema name climate) Press F5 to execute This results in: Query returned successfully with no result in 122 ms. Replies of the Jedi At this point I am stumped. Where do I go from here (what are the steps) to convert climate-my.sql to climate-pg.sql so that they can be executed against PostgreSQL? How to I make sure the indexes are copied over correctly (to maintain referential integrity; I don't have constraints at the moment to ease the transition)? How do I ensure that adding new rows in PostgreSQL will start enumerating from the index of the last row inserted (and not conflict with an existing primary key from the sequence)? Resources A fair bit of information was needed to get this far: https://help.ubuntu.com/community/PostgreSQL http://articles.sitepoint.com/article/site-mysql-postgresql-1 http://wiki.postgresql.org/wiki/Converting_from_other_Databases_to_PostgreSQL#MySQL http://pgfoundry.org/frs/shownotes.php?release_id=810 http://sqlfairy.sourceforge.net/ Thank you!

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  • SmartAssembly Support: How to change the maps folder

    - by Bart Read
    If you've set up SmartAssembly to store error reports in a SQL Server database, you'll also have specified a folder for the map files that are used to de-obfuscate error reports (see Figure 1). Whilst you can change the database easily enough you can't change the map folder path via the UI - if you click on it, it'll just open the folder in Explorer - but never fear, you can change it manually and fortunately it's not that difficult. (If you want to get to these settings click the Tools > Options link on the left-hand side of the SmartAssembly main window.)   Figure 1. Error reports database settings in SmartAssembly. The folder path is actually stored in the database, so you just need to open up SQL Server Management Studio, connect to the SQL Server where your error reports database is stored, then open a new query on the SmartAssembly database by right-clicking on it in the Object Explorer, then clicking New Query (see figure 2).     Figure 2. Opening a new query against the SmartAssembly error reports database in SQL Server. Now execute the following SQL query in the new query window: SELECT * FROM dbo.Information You should find that you get a result set rather like that shown in figure 3. You can see that the map folder path is stored in the MapFolderNetworkPath column.   Figure 3. Contents of the dbo.Information table, showing the map folder path I set in SmartAssembly. All I need to do to change this is execute the following SQL: UPDATE dbo.Information SET MapFolderNetworkPath = '\\UNCPATHTONEWFOLDER' WHERE MapFolderNetworkPath = '\\dev-ltbart\SAMaps' This will change the map folder path to whatever I supply in the SET clause. Once you've done this, you can verify the change by executing the following again: SELECT * FROM dbo.Information You should find the result set contains the new path you've set.

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  • Master Note for Generic Data Warehousing

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

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