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• How to generate sample XML documents from their DTD or XSD?

  - by lindelof

  We are developing an application that involves a substantial amount of XML transformations. We do not have any proper input test data per se, only DTD or XSD files. We'd like to generate our test data ourselves from these files. Is there an easy/free way to do that? Edit There are apparently no free tools for this, and I agree that OxygenXML is one of the best tools for this.

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• Making a grid on iPhone using Opengl

  - by TheGambler

  I'm trying to make a grid similar to what you would see in these geo games(geoDefense/geometry wars). I'm wanting to apply separate transformation matrixes to each to create different effects. So, it makes since to me that I need to draw each square separately to that I can apply a different transformation to each one. The problem I'm having is mapping these grids out or connecting the squares. The coordinate systems is still confusing to me. I know it would be easy just to create a huge triangle strip but I'm not able to figure out a way to apply separate transformations to each square( quad ) if I use triangle strips. So first question: Can you apply different transformations to quads if you use a triangle strip to draw a huge grid? If so, any tips suggestions on how to do so? If not, how does one usually connect textures without using triangle strips? Here is my coord setup: const GLfloat zNear = 0.01, zFar = 1000.0, fieldOfView = 45.0; GLfloat size; glEnable(GL_DEPTH_TEST); glMatrixMode(GL_PROJECTION); size = zNear * tanf(DEGREES_TO_RADIANS(fieldOfView) / 2.0); CGRect rect = view.bounds; glFrustumf(-size, size, -size / (rect.size.width / rect.size.height), size / (rect.size.width / rect.size.height), zNear, zFar); glViewport(0, 0, rect.size.width, rect.size.height); Here is my draw: - (void)drawView:(GLView*)view; { int loop; //glColor4f(1.0, 1.0, 1.0, 0.5); glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT); //Grid Loop for( loop = 0; loop < kNumberSectionsInGrid; loop++ ) { //glLoadIdentity(); static Matrix3D shearMatrix; Matrix3DSetShear(shearMatrix, 0.2, 0.2); static Matrix3D finalMatrix; //Matrix3DMultiply(temp2Matrix, shearMatrix, finalMatrix); glLoadMatrixf(shearMatrix); glTranslatef(-1.0f,(float)loop,-3.0f); glScalef(0.1, 0.1, 0.0); Vertex3D vertices[] = { {-1.0, 1.0, 0.5}, { 1.0, 1.0, 0.5}, { -1.0, -1.0, 0.5}, { 1.0, -1.0, 0.5} }; static const Vector3D normals[] = { {0.0, 0.0, 1.0}, {0.0, 0.0, 1.0}, {0.0, 0.0, 1.0}, {0.0, 0.0, 1.0}, }; GLfloat texCoords[] = { 0.0, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 0.0 }; glEnableClientState(GL_VERTEX_ARRAY); glEnableClientState(GL_NORMAL_ARRAY); glEnableClientState(GL_TEXTURE_COORD_ARRAY); glBindTexture(GL_TEXTURE_2D, texture[0]); glVertexPointer(3, GL_FLOAT, 0, vertices); glNormalPointer(GL_FLOAT, 0, normals); glTexCoordPointer(2, GL_FLOAT, 0, texCoords); glDrawArrays(GL_TRIANGLE_STRIP, 0, 4); glDisableClientState(GL_VERTEX_ARRAY); glDisableClientState(GL_NORMAL_ARRAY); glDisableClientState(GL_TEXTURE_COORD_ARRAY); } } glMatrixMode(GL_MODELVIEW);

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• SSIS Lookup component only returns matching rows when using partial mode

  - by Myat Htut

  I am attempting to use a lookup transformation in my data transformation package and all of the other lookup transformations went well but one component returns the matching rows only when I enable the partial cache mode. If I use the full cache mode, all data is routed to the error path. I am using SQL 2005 SSIS. Any help appreciated..

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• How to rotate UIViews?

  - by user717452

  The Twitter app is a tab bar app on the iPhone. Nothing in any of the tabs will rotate, yet, when you click on a link from a tweet, the view controller that is pushed on top of it IS allowed to rotate. The only rotations I have ever doe is from tilting the device, landscape or portrait, but I don't understand how to use 2d transformations and animations to rotate views. How do you rotate any view with that's a subclass of UIView?

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• How do I generate Entity Framework 4.0 classes from the command line that have different names than

  - by Josh Kodroff

  I want to generate Entity Framework 4.0 classes from a (legacy) database from a command line, but I have 2 transformations I want: Tables/columns are lowerCamelCase and I want my classes/members to be UpperCamelCase. I want to suffix my classes with "Dto". Any idea how this might be accomplished? I'm a total newbie to EF, but I have a decent understanding of Linq to Sql and was able to accomplish the same task by doing: sqlmetal - dbml - xml mapping file and .cs file.

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• What does "object affine" mean?

  - by mafutrct

  What does "object affine" mean? For instance, there are object affine thread pools. While I understand both thread pools and affine transformations in math, I can't think of an association between them.

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• Capturing and Transforming ASP.NET Output with Response.Filter

  - by Rick Strahl

  During one of my Handlers and Modules session at DevConnections this week one of the attendees asked a question that I didn’t have an immediate answer for. Basically he wanted to capture response output completely and then apply some filtering to the output – effectively injecting some additional content into the page AFTER the page had completely rendered. Specifically the output should be captured from anywhere – not just a page and have this code injected into the page. Some time ago I posted some code that allows you to capture ASP.NET Page output by overriding the Render() method, capturing the HtmlTextWriter() and reading its content, modifying the rendered data as text then writing it back out. I’ve actually used this approach on a few occasions and it works fine for ASP.NET pages. But this obviously won’t work outside of the Page class environment and it’s not really generic – you have to create a custom page class in order to handle the output capture. [updated 11/16/2009 – updated ResponseFilterStream implementation and a few additional notes based on comments] Enter Response.Filter However, ASP.NET includes a Response.Filter which can be used – well to filter output. Basically Response.Filter is a stream through which the OutputStream is piped back to the Web Server (indirectly). As content is written into the Response object, the filter stream receives the appropriate Stream commands like Write, Flush and Close as well as read operations although for a Response.Filter that’s uncommon to be hit. The Response.Filter can be programmatically replaced at runtime which allows you to effectively intercept all output generation that runs through ASP.NET. A common Example: Dynamic GZip Encoding A rather common use of Response.Filter hooking up code based, dynamic  GZip compression for requests which is dead simple by applying a GZipStream (or DeflateStream) to Response.Filter. The following generic routines can be used very easily to detect GZip capability of the client and compress response output with a single line of code and a couple of library helper routines: WebUtils.GZipEncodePage(); which is handled with a few lines of reusable code and a couple of static helper methods: /// <summary> ///Sets up the current page or handler to use GZip through a Response.Filter ///IMPORTANT:  ///You have to call this method before any output is generated! /// </summary> public static void GZipEncodePage() {     HttpResponse Response = HttpContext.Current.Response;     if(IsGZipSupported())     {         stringAcceptEncoding = HttpContext.Current.Request.Headers["Accept-Encoding"];         if(AcceptEncoding.Contains("deflate"))         {             Response.Filter = newSystem.IO.Compression.DeflateStream(Response.Filter,                                        System.IO.Compression.CompressionMode.Compress);             Response.AppendHeader("Content-Encoding", "deflate");         }         else        {             Response.Filter = newSystem.IO.Compression.GZipStream(Response.Filter,                                       System.IO.Compression.CompressionMode.Compress);             Response.AppendHeader("Content-Encoding", "gzip");                            }     }     // Allow proxy servers to cache encoded and unencoded versions separately    Response.AppendHeader("Vary", "Content-Encoding"); } /// <summary> /// Determines if GZip is supported /// </summary> /// <returns></returns> public static bool IsGZipSupported() { string AcceptEncoding = HttpContext.Current.Request.Headers["Accept-Encoding"]; if (!string.IsNullOrEmpty(AcceptEncoding) && (AcceptEncoding.Contains("gzip") || AcceptEncoding.Contains("deflate"))) return true; return false; } GZipStream and DeflateStream are streams that are assigned to Response.Filter and by doing so apply the appropriate compression on the active Response. Response.Filter content is chunked So to implement a Response.Filter effectively requires only that you implement a custom stream and handle the Write() method to capture Response output as it’s written. At first blush this seems very simple – you capture the output in Write, transform it and write out the transformed content in one pass. And that indeed works for small amounts of content. But you see, the problem is that output is written in small buffer chunks (a little less than 16k it appears) rather than just a single Write() statement into the stream, which makes perfect sense for ASP.NET to stream data back to IIS in smaller chunks to minimize memory usage en route. Unfortunately this also makes it a more difficult to implement any filtering routines since you don’t directly get access to all of the response content which is problematic especially if those filtering routines require you to look at the ENTIRE response in order to transform or capture the output as is needed for the solution the gentleman in my session asked for. So in order to address this a slightly different approach is required that basically captures all the Write() buffers passed into a cached stream and then making the stream available only when it’s complete and ready to be flushed. As I was thinking about the implementation I also started thinking about the few instances when I’ve used Response.Filter implementations. Each time I had to create a new Stream subclass and create my custom functionality but in the end each implementation did the same thing – capturing output and transforming it. I thought there should be an easier way to do this by creating a re-usable Stream class that can handle stream transformations that are common to Response.Filter implementations. Creating a semi-generic Response Filter Stream Class What I ended up with is a ResponseFilterStream class that provides a handful of Events that allow you to capture and/or transform Response content. The class implements a subclass of Stream and then overrides Write() and Flush() to handle capturing and transformation operations. By exposing events it’s easy to hook up capture or transformation operations via single focused methods. ResponseFilterStream exposes the following events: CaptureStream, CaptureString Captures the output only and provides either a MemoryStream or String with the final page output. Capture is hooked to the Flush() operation of the stream. TransformStream, TransformString Allows you to transform the complete response output with events that receive a MemoryStream or String respectively and can you modify the output then return it back as a return value. The transformed output is then written back out in a single chunk to the response output stream. These events capture all output internally first then write the entire buffer into the response. TransformWrite, TransformWriteString Allows you to transform the Response data as it is written in its original chunk size in the Stream’s Write() method. Unlike TransformStream/TransformString which operate on the complete output, these events only see the current chunk of data written. This is more efficient as there’s no caching involved, but can cause problems due to searched content splitting over multiple chunks. Using this implementation, creating a custom Response.Filter transformation becomes as simple as the following code. To hook up the Response.Filter using the MemoryStream version event: ResponseFilterStream filter = new ResponseFilterStream(Response.Filter); filter.TransformStream += filter_TransformStream; Response.Filter = filter; and the event handler to do the transformation: MemoryStream filter_TransformStream(MemoryStream ms) { Encoding encoding = HttpContext.Current.Response.ContentEncoding; string output = encoding.GetString(ms.ToArray()); output = FixPaths(output); ms = new MemoryStream(output.Length); byte[] buffer = encoding.GetBytes(output); ms.Write(buffer,0,buffer.Length); return ms; } private string FixPaths(string output) { string path = HttpContext.Current.Request.ApplicationPath; // override root path wonkiness if (path == "/") path = ""; output = output.Replace("\"~/", "\"" + path + "/").Replace("'~/", "'" + path + "/"); return output; } The idea of the event handler is that you can do whatever you want to the stream and return back a stream – either the same one that’s been modified or a brand new one – which is then sent back to as the final response. The above code can be simplified even more by using the string version events which handle the stream to string conversions for you: ResponseFilterStream filter = new ResponseFilterStream(Response.Filter); filter.TransformString += filter_TransformString; Response.Filter = filter; and the event handler to do the transformation calling the same FixPaths method shown above: string filter_TransformString(string output) { return FixPaths(output); } The events for capturing output and capturing and transforming chunks work in a very similar way. By using events to handle the transformations ResponseFilterStream becomes a reusable component and we don’t have to create a new stream class or subclass an existing Stream based classed. By the way, the example used here is kind of a cool trick which transforms “~/” expressions inside of the final generated HTML output – even in plain HTML controls not HTML controls – and transforms them into the appropriate application relative path in the same way that ResolveUrl would do. So you can write plain old HTML like this: <a href=”~/default.aspx”>Home</a>  and have it turned into: <a href=”/myVirtual/default.aspx”>Home</a>  without having to use an ASP.NET control like Hyperlink or Image or having to constantly use: <img src=”<%= ResolveUrl(“~/images/home.gif”) %>” /> in MVC applications (which frankly is one of the most annoying things about MVC especially given the path hell that extension-less and endpoint-less URLs impose). I can’t take credit for this idea. While discussing the Response.Filter issues on Twitter a hint from Dylan Beattie who pointed me at one of his examples which does something similar. I thought the idea was cool enough to use an example for future demos of Response.Filter functionality in ASP.NET next I time I do the Modules and Handlers talk (which was great fun BTW). How practical this is is debatable however since there’s definitely some overhead to using a Response.Filter in general and especially on one that caches the output and the re-writes it later. Make sure to test for performance anytime you use Response.Filter hookup and make sure it' doesn’t end up killing perf on you. You’ve been warned :-}. How does ResponseFilterStream work? The big win of this implementation IMHO is that it’s a reusable  component – so for implementation there’s no new class, no subclassing – you simply attach to an event to implement an event handler method with a straight forward signature to retrieve the stream or string you’re interested in. The implementation is based on a subclass of Stream as is required in order to handle the Response.Filter requirements. What’s different than other implementations I’ve seen in various places is that it supports capturing output as a whole to allow retrieving the full response output for capture or modification. The exception are the TransformWrite and TransformWrite events which operate only active chunk of data written by the Response. For captured output, the Write() method captures output into an internal MemoryStream that is cached until writing is complete. So Write() is called when ASP.NET writes to the Response stream, but the filter doesn’t pass on the Write immediately to the filter’s internal stream. The data is cached and only when the Flush() method is called to finalize the Stream’s output do we actually send the cached stream off for transformation (if the events are hooked up) and THEN finally write out the returned content in one big chunk. Here’s the implementation of ResponseFilterStream: /// <summary> /// A semi-generic Stream implementation for Response.Filter with /// an event interface for handling Content transformations via /// Stream or String. /// <remarks> /// Use with care for large output as this implementation copies /// the output into a memory stream and so increases memory usage. /// </remarks> /// </summary> public class ResponseFilterStream : Stream { /// <summary> /// The original stream /// </summary> Stream _stream; /// <summary> /// Current position in the original stream /// </summary> long _position; /// <summary> /// Stream that original content is read into /// and then passed to TransformStream function /// </summary> MemoryStream _cacheStream = new MemoryStream(5000); /// <summary> /// Internal pointer that that keeps track of the size /// of the cacheStream /// </summary> int _cachePointer = 0; /// <summary> /// /// </summary> /// <param name="responseStream"></param> public ResponseFilterStream(Stream responseStream) { _stream = responseStream; } /// <summary> /// Determines whether the stream is captured /// </summary> private bool IsCaptured { get { if (CaptureStream != null || CaptureString != null || TransformStream != null || TransformString != null) return true; return false; } } /// <summary> /// Determines whether the Write method is outputting data immediately /// or delaying output until Flush() is fired. /// </summary> private bool IsOutputDelayed { get { if (TransformStream != null || TransformString != null) return true; return false; } } /// <summary> /// Event that captures Response output and makes it available /// as a MemoryStream instance. Output is captured but won't /// affect Response output. /// </summary> public event Action<MemoryStream> CaptureStream; /// <summary> /// Event that captures Response output and makes it available /// as a string. Output is captured but won't affect Response output. /// </summary> public event Action<string> CaptureString; /// <summary> /// Event that allows you transform the stream as each chunk of /// the output is written in the Write() operation of the stream. /// This means that that it's possible/likely that the input /// buffer will not contain the full response output but only /// one of potentially many chunks. /// /// This event is called as part of the filter stream's Write() /// operation. /// </summary> public event Func<byte[], byte[]> TransformWrite; /// <summary> /// Event that allows you to transform the response stream as /// each chunk of bytep[] output is written during the stream's write /// operation. This means it's possibly/likely that the string /// passed to the handler only contains a portion of the full /// output. Typical buffer chunks are around 16k a piece. /// /// This event is called as part of the stream's Write operation. /// </summary> public event Func<string, string> TransformWriteString; /// <summary> /// This event allows capturing and transformation of the entire /// output stream by caching all write operations and delaying final /// response output until Flush() is called on the stream. /// </summary> public event Func<MemoryStream, MemoryStream> TransformStream; /// <summary> /// Event that can be hooked up to handle Response.Filter /// Transformation. Passed a string that you can modify and /// return back as a return value. The modified content /// will become the final output. /// </summary> public event Func<string, string> TransformString; protected virtual void OnCaptureStream(MemoryStream ms) { if (CaptureStream != null) CaptureStream(ms); } private void OnCaptureStringInternal(MemoryStream ms) { if (CaptureString != null) { string content = HttpContext.Current.Response.ContentEncoding.GetString(ms.ToArray()); OnCaptureString(content); } } protected virtual void OnCaptureString(string output) { if (CaptureString != null) CaptureString(output); } protected virtual byte[] OnTransformWrite(byte[] buffer) { if (TransformWrite != null) return TransformWrite(buffer); return buffer; } private byte[] OnTransformWriteStringInternal(byte[] buffer) { Encoding encoding = HttpContext.Current.Response.ContentEncoding; string output = OnTransformWriteString(encoding.GetString(buffer)); return encoding.GetBytes(output); } private string OnTransformWriteString(string value) { if (TransformWriteString != null) return TransformWriteString(value); return value; } protected virtual MemoryStream OnTransformCompleteStream(MemoryStream ms) { if (TransformStream != null) return TransformStream(ms); return ms; } /// <summary> /// Allows transforming of strings /// /// Note this handler is internal and not meant to be overridden /// as the TransformString Event has to be hooked up in order /// for this handler to even fire to avoid the overhead of string /// conversion on every pass through. /// </summary> /// <param name="responseText"></param> /// <returns></returns> private string OnTransformCompleteString(string responseText) { if (TransformString != null) TransformString(responseText); return responseText; } /// <summary> /// Wrapper method form OnTransformString that handles /// stream to string and vice versa conversions /// </summary> /// <param name="ms"></param> /// <returns></returns> internal MemoryStream OnTransformCompleteStringInternal(MemoryStream ms) { if (TransformString == null) return ms; //string content = ms.GetAsString(); string content = HttpContext.Current.Response.ContentEncoding.GetString(ms.ToArray()); content = TransformString(content); byte[] buffer = HttpContext.Current.Response.ContentEncoding.GetBytes(content); ms = new MemoryStream(); ms.Write(buffer, 0, buffer.Length); //ms.WriteString(content); return ms; } /// <summary> /// /// </summary> public override bool CanRead { get { return true; } } public override bool CanSeek { get { return true; } } /// <summary> /// /// </summary> public override bool CanWrite { get { return true; } } /// <summary> /// /// </summary> public override long Length { get { return 0; } } /// <summary> /// /// </summary> public override long Position { get { return _position; } set { _position = value; } } /// <summary> /// /// </summary> /// <param name="offset"></param> /// <param name="direction"></param> /// <returns></returns> public override long Seek(long offset, System.IO.SeekOrigin direction) { return _stream.Seek(offset, direction); } /// <summary> /// /// </summary> /// <param name="length"></param> public override void SetLength(long length) { _stream.SetLength(length); } /// <summary> /// /// </summary> public override void Close() { _stream.Close(); } /// <summary> /// Override flush by writing out the cached stream data /// </summary> public override void Flush() { if (IsCaptured && _cacheStream.Length > 0) { // Check for transform implementations _cacheStream = OnTransformCompleteStream(_cacheStream); _cacheStream = OnTransformCompleteStringInternal(_cacheStream); OnCaptureStream(_cacheStream); OnCaptureStringInternal(_cacheStream); // write the stream back out if output was delayed if (IsOutputDelayed) _stream.Write(_cacheStream.ToArray(), 0, (int)_cacheStream.Length); // Clear the cache once we've written it out _cacheStream.SetLength(0); } // default flush behavior _stream.Flush(); } /// <summary> /// /// </summary> /// <param name="buffer"></param> /// <param name="offset"></param> /// <param name="count"></param> /// <returns></returns> public override int Read(byte[] buffer, int offset, int count) { return _stream.Read(buffer, offset, count); } /// <summary> /// Overriden to capture output written by ASP.NET and captured /// into a cached stream that is written out later when Flush() /// is called. /// </summary> /// <param name="buffer"></param> /// <param name="offset"></param> /// <param name="count"></param> public override void Write(byte[] buffer, int offset, int count) { if ( IsCaptured ) { // copy to holding buffer only - we'll write out later _cacheStream.Write(buffer, 0, count); _cachePointer += count; } // just transform this buffer if (TransformWrite != null) buffer = OnTransformWrite(buffer); if (TransformWriteString != null) buffer = OnTransformWriteStringInternal(buffer); if (!IsOutputDelayed) _stream.Write(buffer, offset, buffer.Length); } } The key features are the events and corresponding OnXXX methods that handle the event hookups, and the Write() and Flush() methods of the stream implementation. All the rest of the members tend to be plain jane passthrough stream implementation code without much consequence. I do love the way Action<t> and Func<T> make it so easy to create the event signatures for the various events – sweet. A few Things to consider Performance Response.Filter is not great for performance in general as it adds another layer of indirection to the ASP.NET output pipeline, and this implementation in particular adds a memory hit as it basically duplicates the response output into the cached memory stream which is necessary since you may have to look at the entire response. If you have large pages in particular this can cause potentially serious memory pressure in your server application. So be careful of wholesale adoption of this (or other) Response.Filters. Make sure to do some performance testing to ensure it’s not killing your app’s performance. Response.Filter works everywhere A few questions came up in comments and discussion as to capturing ALL output hitting the site and – yes you can definitely do that by assigning a Response.Filter inside of a module. If you do this however you’ll want to be very careful and decide which content you actually want to capture especially in IIS 7 which passes ALL content – including static images/CSS etc. through the ASP.NET pipeline. So it is important to filter only on what you’re looking for – like the page extension or maybe more effectively the Response.ContentType. Response.Filter Chaining Originally I thought that filter chaining doesn’t work at all due to a bug in the stream implementation code. But it’s quite possible to assign multiple filters to the Response.Filter property. So the following actually works to both compress the output and apply the transformed content: WebUtils.GZipEncodePage(); ResponseFilterStream filter = new ResponseFilterStream(Response.Filter); filter.TransformString += filter_TransformString; Response.Filter = filter; However the following does not work resulting in invalid content encoding errors: ResponseFilterStream filter = new ResponseFilterStream(Response.Filter); filter.TransformString += filter_TransformString; Response.Filter = filter; WebUtils.GZipEncodePage(); In other words multiple Response filters can work together but it depends entirely on the implementation whether they can be chained or in which order they can be chained. In this case running the GZip/Deflate stream filters apparently relies on the original content length of the output and chokes when the content is modified. But if attaching the compression first it works fine as unintuitive as that may seem. Resources Download example code Capture Output from ASP.NET Pages © Rick Strahl, West Wind Technologies, 2005-2010Posted in ASP.NET  

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• Fun with Aggregates

  - by Paul White

  There are interesting things to be learned from even the simplest queries.  For example, imagine you are given the task of writing a query to list AdventureWorks product names where the product has at least one entry in the transaction history table, but fewer than ten. One possible query to meet that specification is: SELECT p.Name FROM Production.Product AS p JOIN Production.TransactionHistory AS th ON p.ProductID = th.ProductID GROUP BY p.ProductID, p.Name HAVING COUNT_BIG(*) < 10; That query correctly returns 23 rows (execution plan and data sample shown below): The execution plan looks a bit different from the written form of the query: the base tables are accessed in reverse order, and the aggregation is performed before the join.  The general idea is to read all rows from the history table, compute the count of rows grouped by ProductID, merge join the results to the Product table on ProductID, and finally filter to only return rows where the count is less than ten. This ‘fully-optimized’ plan has an estimated cost of around 0.33 units.  The reason for the quote marks there is that this plan is not quite as optimal as it could be – surely it would make sense to push the Filter down past the join too?  To answer that, let’s look at some other ways to formulate this query.  This being SQL, there are any number of ways to write logically-equivalent query specifications, so we’ll just look at a couple of interesting ones.  The first query is an attempt to reverse-engineer T-SQL from the optimized query plan shown above.  It joins the result of pre-aggregating the history table to the Product table before filtering: SELECT p.Name FROM ( SELECT th.ProductID, cnt = COUNT_BIG(*) FROM Production.TransactionHistory AS th GROUP BY th.ProductID ) AS q1 JOIN Production.Product AS p ON p.ProductID = q1.ProductID WHERE q1.cnt < 10; Perhaps a little surprisingly, we get a slightly different execution plan: The results are the same (23 rows) but this time the Filter is pushed below the join!  The optimizer chooses nested loops for the join, because the cardinality estimate for rows passing the Filter is a bit low (estimate 1 versus 23 actual), though you can force a merge join with a hint and the Filter still appears below the join.  In yet another variation, the < 10 predicate can be ‘manually pushed’ by specifying it in a HAVING clause in the “q1” sub-query instead of in the WHERE clause as written above. The reason this predicate can be pushed past the join in this query form, but not in the original formulation is simply an optimizer limitation – it does make efforts (primarily during the simplification phase) to encourage logically-equivalent query specifications to produce the same execution plan, but the implementation is not completely comprehensive. Moving on to a second example, the following query specification results from phrasing the requirement as “list the products where there exists fewer than ten correlated rows in the history table”: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) < 10 ); Unfortunately, this query produces an incorrect result (86 rows): The problem is that it lists products with no history rows, though the reasons are interesting.  The COUNT_BIG(*) in the EXISTS clause is a scalar aggregate (meaning there is no GROUP BY clause) and scalar aggregates always produce a value, even when the input is an empty set.  In the case of the COUNT aggregate, the result of aggregating the empty set is zero (the other standard aggregates produce a NULL).  To make the point really clear, let’s look at product 709, which happens to be one for which no history rows exist: -- Scalar aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709;   -- Vector aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709 GROUP BY th.ProductID; The estimated execution plans for these two statements are almost identical: You might expect the Stream Aggregate to have a Group By for the second statement, but this is not the case.  The query includes an equality comparison to a constant value (709), so all qualified rows are guaranteed to have the same value for ProductID and the Group By is optimized away. In fact there are some minor differences between the two plans (the first is auto-parameterized and qualifies for trivial plan, whereas the second is not auto-parameterized and requires cost-based optimization), but there is nothing to indicate that one is a scalar aggregate and the other is a vector aggregate.  This is something I would like to see exposed in show plan so I suggested it on Connect.  Anyway, the results of running the two queries show the difference at runtime: The scalar aggregate (no GROUP BY) returns a result of zero, whereas the vector aggregate (with a GROUP BY clause) returns nothing at all.  Returning to our EXISTS query, we could ‘fix’ it by changing the HAVING clause to reject rows where the scalar aggregate returns zero: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) BETWEEN 1 AND 9 ); The query now returns the correct 23 rows: Unfortunately, the execution plan is less efficient now – it has an estimated cost of 0.78 compared to 0.33 for the earlier plans.  Let’s try adding a redundant GROUP BY instead of changing the HAVING clause: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY th.ProductID HAVING COUNT_BIG(*) < 10 ); Not only do we now get correct results (23 rows), this is the execution plan: I like to compare that plan to quantum physics: if you don’t find it shocking, you haven’t understood it properly :)  The simple addition of a redundant GROUP BY has resulted in the EXISTS form of the query being transformed into exactly the same optimal plan we found earlier.  What’s more, in SQL Server 2008 and later, we can replace the odd-looking GROUP BY with an explicit GROUP BY on the empty set: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ); I offer that as an alternative because some people find it more intuitive (and it perhaps has more geek value too).  Whichever way you prefer, it’s rather satisfying to note that the result of the sub-query does not exist for a particular correlated value where a vector aggregate is used (the scalar COUNT aggregate always returns a value, even if zero, so it always ‘EXISTS’ regardless which ProductID is logically being evaluated). The following query forms also produce the optimal plan and correct results, so long as a vector aggregate is used (you can probably find more equivalent query forms): WHERE Clause SELECT p.Name FROM Production.Product AS p WHERE ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) < 10; APPLY SELECT p.Name FROM Production.Product AS p CROSS APPLY ( SELECT NULL FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ) AS ca (dummy); FROM Clause SELECT q1.Name FROM ( SELECT p.Name, cnt = ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) FROM Production.Product AS p ) AS q1 WHERE q1.cnt < 10; This last example uses SUM(1) instead of COUNT and does not require a vector aggregate…you should be able to work out why :) SELECT q.Name FROM ( SELECT p.Name, cnt = ( SELECT SUM(1) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID ) FROM Production.Product AS p ) AS q WHERE q.cnt < 10; The semantics of SQL aggregates are rather odd in places.  It definitely pays to get to know the rules, and to be careful to check whether your queries are using scalar or vector aggregates.  As we have seen, query plans do not show in which ‘mode’ an aggregate is running and getting it wrong can cause poor performance, wrong results, or both. © 2012 Paul White Twitter: @SQL_Kiwi email: [email protected]

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• Big Data Matters with ODI12c

  - by Madhu Nair

  contributed by Mike Eisterer On October 17th, 2013, Oracle announced the release of Oracle Data Integrator 12c (ODI12c).  This release signifies improvements to Oracle’s Data Integration portfolio of solutions, particularly Big Data integration. Why Big Data = Big Business Organizations are gaining greater insights and actionability through increased storage, processing and analytical benefits offered by Big Data solutions.  New technologies and frameworks like HDFS, NoSQL, Hive and MapReduce support these benefits now. As further data is collected, analytical requirements increase and the complexity of managing transformations and aggregations of data compounds and organizations are in need for scalable Data Integration solutions. ODI12c provides enterprise solutions for the movement, translation and transformation of information and data heterogeneously and in Big Data Environments through: The ability for existing ODI and SQL developers to leverage new Big Data technologies. A metadata focused approach for cataloging, defining and reusing Big Data technologies, mappings and process executions. Integration between many heterogeneous environments and technologies such as HDFS and Hive. Generation of Hive Query Language. Working with Big Data using Knowledge Modules  ODI12c provides developers with the ability to define sources and targets and visually develop mappings to effect the movement and transformation of data.  As the mappings are created, ODI12c leverages a rich library of prebuilt integrations, known as Knowledge Modules (KMs).  These KMs are contextual to the technologies and platforms to be integrated.  Steps and actions needed to manage the data integration are pre-built and configured within the KMs.  The Oracle Data Integrator Application Adapter for Hadoop provides a series of KMs, specifically designed to integrate with Big Data Technologies.  The Big Data KMs include: Check Knowledge Module Reverse Engineer Knowledge Module Hive Transform Knowledge Module Hive Control Append Knowledge Module File to Hive (LOAD DATA) Knowledge Module File-Hive to Oracle (OLH-OSCH) Knowledge Module  Nothing to beat an Example: To demonstrate the use of the KMs which are part of the ODI Application Adapter for Hadoop, a mapping may be defined to move data between files and Hive targets.  The mapping is defined by dragging the source and target into the mapping, performing the attribute (column) mapping (see Figure 1) and then selecting the KM which will govern the process.  In this mapping example, movie data is being moved from an HDFS source into a Hive table.  Some of the attributes, such as “CUSTID to custid”, have been mapped over. Figure 1  Defining the Mapping Before the proper KM can be assigned to define the technology for the mapping, it needs to be added to the ODI project.  The Big Data KMs have been made available to the project through the KM import process.   Generally, this is done prior to defining the mapping. Figure 2  Importing the Big Data Knowledge Modules Following the import, the KMs are available in the Designer Navigator. v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} Normal 0 false false false EN-US ZH-TW 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:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Figure 3  The Project View in Designer, Showing Installed IKMs Once the KM is imported, it may be assigned to the mapping target.  This is done by selecting the Physical View of the mapping and examining the Properties of the Target.  In this case MOVIAPP_LOG_STAGE is the target of our mapping. Figure 4  Physical View of the Mapping and Assigning the Big Data Knowledge Module to the Target Alternative KMs may have been selected as well, providing flexibility and abstracting the logical mapping from the physical implementation.  Our mapping may be applied to other technologies as well. The mapping is now complete and is ready to run.  We will see more in a future blog about running a mapping to load Hive. To complete the quick ODI for Big Data Overview, let us take a closer look at what the IKM File to Hive is doing for us.  ODI provides differentiated capabilities by defining the process and steps which normally would have to be manually developed, tested and implemented into the KM.  As shown in figure 5, the KM is preparing the Hive session, managing the Hive tables, performing the initial load from HDFS and then performing the insert into Hive.  HDFS and Hive options are selected graphically, as shown in the properties in Figure 4. Figure 5  Process and Steps Managed by the KM What’s Next Big Data being the shape shifting business challenge it is is fast evolving into the deciding factor between market leaders and others. Now that an introduction to ODI and Big Data has been provided, look for additional blogs coming soon using the Knowledge Modules which make up the Oracle Data Integrator Application Adapter for Hadoop: Importing Big Data Metadata into ODI, Testing Data Stores and Loading Hive Targets Generating Transformations using Hive Query language Loading Oracle from Hadoop Sources For more information now, please visit the Oracle Data Integrator Application Adapter for Hadoop web site, http://www.oracle.com/us/products/middleware/data-integration/hadoop/overview/index.html Do not forget to tune in to the ODI12c Executive Launch webcast on the 12th to hear more about ODI12c and GG12c. Normal 0 false false false EN-US ZH-TW 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:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";}

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• Fun with Aggregates

  - by Paul White

  There are interesting things to be learned from even the simplest queries.  For example, imagine you are given the task of writing a query to list AdventureWorks product names where the product has at least one entry in the transaction history table, but fewer than ten. One possible query to meet that specification is: SELECT p.Name FROM Production.Product AS p JOIN Production.TransactionHistory AS th ON p.ProductID = th.ProductID GROUP BY p.ProductID, p.Name HAVING COUNT_BIG(*) < 10; That query correctly returns 23 rows (execution plan and data sample shown below): The execution plan looks a bit different from the written form of the query: the base tables are accessed in reverse order, and the aggregation is performed before the join.  The general idea is to read all rows from the history table, compute the count of rows grouped by ProductID, merge join the results to the Product table on ProductID, and finally filter to only return rows where the count is less than ten. This ‘fully-optimized’ plan has an estimated cost of around 0.33 units.  The reason for the quote marks there is that this plan is not quite as optimal as it could be – surely it would make sense to push the Filter down past the join too?  To answer that, let’s look at some other ways to formulate this query.  This being SQL, there are any number of ways to write logically-equivalent query specifications, so we’ll just look at a couple of interesting ones.  The first query is an attempt to reverse-engineer T-SQL from the optimized query plan shown above.  It joins the result of pre-aggregating the history table to the Product table before filtering: SELECT p.Name FROM ( SELECT th.ProductID, cnt = COUNT_BIG(*) FROM Production.TransactionHistory AS th GROUP BY th.ProductID ) AS q1 JOIN Production.Product AS p ON p.ProductID = q1.ProductID WHERE q1.cnt < 10; Perhaps a little surprisingly, we get a slightly different execution plan: The results are the same (23 rows) but this time the Filter is pushed below the join!  The optimizer chooses nested loops for the join, because the cardinality estimate for rows passing the Filter is a bit low (estimate 1 versus 23 actual), though you can force a merge join with a hint and the Filter still appears below the join.  In yet another variation, the < 10 predicate can be ‘manually pushed’ by specifying it in a HAVING clause in the “q1” sub-query instead of in the WHERE clause as written above. The reason this predicate can be pushed past the join in this query form, but not in the original formulation is simply an optimizer limitation – it does make efforts (primarily during the simplification phase) to encourage logically-equivalent query specifications to produce the same execution plan, but the implementation is not completely comprehensive. Moving on to a second example, the following query specification results from phrasing the requirement as “list the products where there exists fewer than ten correlated rows in the history table”: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) < 10 ); Unfortunately, this query produces an incorrect result (86 rows): The problem is that it lists products with no history rows, though the reasons are interesting.  The COUNT_BIG(*) in the EXISTS clause is a scalar aggregate (meaning there is no GROUP BY clause) and scalar aggregates always produce a value, even when the input is an empty set.  In the case of the COUNT aggregate, the result of aggregating the empty set is zero (the other standard aggregates produce a NULL).  To make the point really clear, let’s look at product 709, which happens to be one for which no history rows exist: -- Scalar aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709;   -- Vector aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709 GROUP BY th.ProductID; The estimated execution plans for these two statements are almost identical: You might expect the Stream Aggregate to have a Group By for the second statement, but this is not the case.  The query includes an equality comparison to a constant value (709), so all qualified rows are guaranteed to have the same value for ProductID and the Group By is optimized away. In fact there are some minor differences between the two plans (the first is auto-parameterized and qualifies for trivial plan, whereas the second is not auto-parameterized and requires cost-based optimization), but there is nothing to indicate that one is a scalar aggregate and the other is a vector aggregate.  This is something I would like to see exposed in show plan so I suggested it on Connect.  Anyway, the results of running the two queries show the difference at runtime: The scalar aggregate (no GROUP BY) returns a result of zero, whereas the vector aggregate (with a GROUP BY clause) returns nothing at all.  Returning to our EXISTS query, we could ‘fix’ it by changing the HAVING clause to reject rows where the scalar aggregate returns zero: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) BETWEEN 1 AND 9 ); The query now returns the correct 23 rows: Unfortunately, the execution plan is less efficient now – it has an estimated cost of 0.78 compared to 0.33 for the earlier plans.  Let’s try adding a redundant GROUP BY instead of changing the HAVING clause: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY th.ProductID HAVING COUNT_BIG(*) < 10 ); Not only do we now get correct results (23 rows), this is the execution plan: I like to compare that plan to quantum physics: if you don’t find it shocking, you haven’t understood it properly :)  The simple addition of a redundant GROUP BY has resulted in the EXISTS form of the query being transformed into exactly the same optimal plan we found earlier.  What’s more, in SQL Server 2008 and later, we can replace the odd-looking GROUP BY with an explicit GROUP BY on the empty set: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ); I offer that as an alternative because some people find it more intuitive (and it perhaps has more geek value too).  Whichever way you prefer, it’s rather satisfying to note that the result of the sub-query does not exist for a particular correlated value where a vector aggregate is used (the scalar COUNT aggregate always returns a value, even if zero, so it always ‘EXISTS’ regardless which ProductID is logically being evaluated). The following query forms also produce the optimal plan and correct results, so long as a vector aggregate is used (you can probably find more equivalent query forms): WHERE Clause SELECT p.Name FROM Production.Product AS p WHERE ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) < 10; APPLY SELECT p.Name FROM Production.Product AS p CROSS APPLY ( SELECT NULL FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ) AS ca (dummy); FROM Clause SELECT q1.Name FROM ( SELECT p.Name, cnt = ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) FROM Production.Product AS p ) AS q1 WHERE q1.cnt < 10; This last example uses SUM(1) instead of COUNT and does not require a vector aggregate…you should be able to work out why :) SELECT q.Name FROM ( SELECT p.Name, cnt = ( SELECT SUM(1) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID ) FROM Production.Product AS p ) AS q WHERE q.cnt < 10; The semantics of SQL aggregates are rather odd in places.  It definitely pays to get to know the rules, and to be careful to check whether your queries are using scalar or vector aggregates.  As we have seen, query plans do not show in which ‘mode’ an aggregate is running and getting it wrong can cause poor performance, wrong results, or both. © 2012 Paul White Twitter: @SQL_Kiwi email: [email protected]

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• BI Applications overview

  - by sv744

  Welcome to Oracle BI applications blog! This blog will talk about various features, general roadmap, description of functionality and implementation steps related to Oracle BI applications. In the first post we start with an overview of the BI apps and will delve deeper into some of the topics below in the upcoming weeks and months. If there are other topics you would like us to talk about, pl feel free to provide feedback on that. The Oracle BI applications are a set of pre-built applications that enable pervasive BI by providing role-based insight for each functional area, including sales, service, marketing, contact center, finance, supplier/supply chain, HR/workforce, and executive management. For example, Sales Analytics includes role-based applications for sales executives, sales management, as well as front-line sales reps, each of whom have different needs. The applications integrate and transform data from a range of enterprise sources—including Siebel, Oracle, PeopleSoft, SAP, and others—into actionable intelligence for each business function and user role. This blog  starts with the key benefits and characteristics of Oracle BI applications. In a series of subsequent blogs, each of these points will be explained in detail. Why BI apps? Demonstrate the value of BI to a business user, show reports / dashboards / model that can answer their business questions as part of the sales cycle. Demonstrate technical feasibility of BI project and significantly lower risk and improve success Build Vs Buy benefit Don’t have to start with a blank sheet of paper. Help consolidate disparate systems Data integration in M&A situations Insulate BI consumers from changes in the OLTP Present OLTP data and highlight issues of poor data / missing data – and improve data quality and accuracy Prebuilt Integrations BI apps support prebuilt integrations against leading ERP sources: Fusion Applications, E- Business Suite, Peoplesoft, JD Edwards, Siebel, SAP Co-developed with inputs from functional experts in BI and Applications teams. Out of the box dimensional model to source model mappings Multi source and Multi Instance support Rich Data Model    BI apps have a very rich dimensionsal data model built over 10 years that incorporates best practises from BI modeling perspective as well as reflect the source system complexities  Thanks for reading a long post, and be on the lookout for future posts.  We will look forward to your valuable feedback on these topics as well as suggestions on what other topics would you like us to cover. I Conformed dimensional model across all business subject areas allows cross functional reporting, e.g. customer / supplier 360 Over 360 fact tables across 7 product areas CRM – 145, SCM – 47, Financials – 28, Procurement – 20, HCM – 27, Projects – 18, Campus Solutions – 21, PLM - 56 Supported by 300 physical dimensions Support for extensive calendars; Gregorian, enterprise and ledger based Conformed data model and metrics for real time vs warehouse based reporting  Multi-tenant enabled Extensive BI related transformations BI apps ETL and data integration support various transformations required for dimensional models and reporting requirements. All these have been distilled into common patterns and abstracted logic which can be readily reused across different modules Slowly Changing Dimension support Hierarchy flattening support Row / Column Hybrid Hierarchy Flattening As Is vs. As Was hierarchy support Currency Conversion :-  Support for 3 corporate, CRM, ledger and transaction currencies UOM conversion Internationalization / Localization Dynamic Data translations Code standardization (Domains) Historical Snapshots Cycle and process lifecycle computations Balance Facts Equalization of GL accounting chartfields/segments Standardized values for categorizing GL accounts Reconciliation between GL and subledgers to track accounted/transferred/posted transactions to GL Materialization of data only available through costly and complex APIs e.g. Fusion Payroll, EBS / Fusion Accruals Complex event Interpretation of source data – E.g. o    What constitutes a transfer o    Deriving supervisors via position hierarchy o    Deriving primary assignment in PSFT o    Categorizing and transposition to measures of Payroll Balances to specific metrics to support side by side comparison of measures of for example Fixed Salary, Variable Salary, Tax, Bonus, Overtime Payments. o    Counting of Events – E.g. converting events to fact counters so that for example the number of hires can easily be added up and compared alongside the total transfers and terminations. Multi pass processing of multiple sources e.g. headcount, salary, promotion, performance to allow side to side comparison. Adding value to data to aid analysis through banding, additional domain classifications and groupings to allow higher level analytical reporting and data discovery Calculation of complex measures examples: o    COGs, DSO, DPO, Inventory turns  etc o    Transfers within a Hierarchy or out of / into a hierarchy relative to view point in hierarchy. Configurability and Extensibility support  BI apps offer support for extensibility for various entities as automated extensibility or part of extension methodology Key Flex fields and Descriptive Flex support  Extensible attribute support (JDE)  Conformed Domains ETL Architecture BI apps offer a modular adapter architecture which allows support of multiple product lines into a single conformed model Multi Source Multi Technology Orchestration – creates load plan taking into account task dependencies and customers deployment to generate a plan based on a customers of multiple complex etl tasks Plan optimization allowing parallel ETL tasks Oracle: Bit map indexes and partition management High availability support    Follow the sun support. TCO BI apps support several utilities / capabilities that help with overall total cost of ownership and ensure a rapid implementation Improved cost of ownership – lower cost to deploy On-going support for new versions of the source application Task based setups flows Data Lineage Functional setup performed in Web UI by Functional person Configuration Test to Production support Security BI apps support both data and object security enabling implementations to quickly configure the application as per the reporting security needs Fine grain object security at report / dashboard and presentation catalog level Data Security integration with source systems  Extensible to support external data security rules Extensive Set of KPIs Over 7000 base and derived metrics across all modules Time series calculations (YoY, % growth etc) Common Currency and UOM reporting Cross subject area KPIs (analyzing HR vs GL data, drill from GL to AP/AR, etc) Prebuilt reports and dashboards 3000+ prebuilt reports supporting a large number of industries Hundreds of role based dashboards Dynamic currency conversion at dashboard level Highly tuned Performance The BI apps have been tuned over the years for both a very performant ETL and dashboard performance. The applications use best practises and advanced database features to enable the best possible performance. Optimized data model for BI and analytic queries Prebuilt aggregates& the ability for customers to create their own aggregates easily on warehouse facts allows for scalable end user performance Incremental extracts and loads Incremental Aggregate build Automatic table index and statistics management Parallel ETL loads Source system deletes handling Low latency extract with Golden Gate Micro ETL support Bitmap Indexes Partitioning support Modularized deployment, start small and add other subject areas seamlessly Source Specfic Staging and Real Time Schema Support for source specific operational reporting schema for EBS, PSFT, Siebel and JDE Application Integrations The BI apps also allow for integration with source systems as well as other applications that provide value add through BI and enable BI consumption during operational decision making Embedded dashboards for Fusion, EBS and Siebel applications Action Link support Marketing Segmentation Sales Predictor Dashboard Territory Management External Integrations The BI apps data integration choices include support for loading extenral data External data enrichment choices : UNSPSC, Item class etc. Extensible Spend Classification Broad Deployment Choices Exalytics support Databases :  Oracle, Exadata, Teradata, DB2, MSSQL ETL tool of choice : ODI (coming), Informatica Extensible and Customizable Extensible architecture and Methodology to add custom and external content Upgradable across releases

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• Oracle Support Master Note for Troubleshooting Advanced Queuing and Oracle Streams Propagation Issues (Doc ID 233099.1)

  - by faye.todd(at)oracle.com

  Master Note for Troubleshooting Advanced Queuing and Oracle Streams Propagation Issues (Doc ID 233099.1) Copyright (c) 2010, Oracle Corporation. All Rights Reserved. In this Document  Purpose  Last Review Date  Instructions for the Reader  Troubleshooting Details     1. Scope and Application      2. Definitions and Classifications     3. How to Use This Guide     4. Basic AQ Propagation Troubleshooting     5. Additional Troubleshooting Steps for AQ Propagation of User-Enqueued and Dequeued Messages     6. Additional Troubleshooting Steps for Propagation in an Oracle Streams Environment     7. Performance Issues  References Applies to: Oracle Server - Enterprise Edition - Version: 8.1.7.0 to 11.2.0.2 - Release: 8.1.7 to 11.2Information in this document applies to any platform. Purpose This document presents a step-by-step methodology for troubleshooting and resolving problems with Advanced Queuing Propagation in both Streams and basic Advanced Queuing environments. It also serves as a master reference for other more specific notes on Oracle Streams Propagation and Advanced Queuing Propagation issues. Last Review Date December 20, 2010 Instructions for the Reader A Troubleshooting Guide is provided to assist in debugging a specific issue. When possible, diagnostic tools are included in the document to assist in troubleshooting. Troubleshooting Details 1. Scope and Application This note is intended for Database Administrators of Oracle databases where issues are being encountered with propagating messages between advanced queues, whether the queues are used for user-created messaging systems or for Oracle Streams. It contains troubleshooting steps and links to notes for further problem resolution.It can also be used a template to document a problem when it is necessary to engage Oracle Support Services. Knowing what is NOT happening can frequently speed up the resolution process by focusing solely on the pertinent problem area. This guide is divided into five parts: Section 2: Definitions and Classifications (discusses the different types and features of propagations possible - helpful for understanding the rest of the guide) Section 3: How to Use this Guide (to be used as a start part for determining the scope of the problem and what sections to consult) Section 4. Basic AQ propagation troubleshooting (applies to both AQ propagation of user enqueued and dequeued messages as well as Oracle Streams propagations) Section 5. Additional troubleshooting steps for AQ propagation of user enqueued and dequeued messages Section 6. Additional troubleshooting steps for Oracle Streams propagation Section 7. Performance issues 2. Definitions and Classifications Given the potential scope of issues that can be encountered with AQ propagation, the first recommended step is to do some basic diagnosis to determine the type of problem that is being encountered. 2.1. What Type of Propagation is Being Used? 2.1.1. Buffered Messaging For an advanced queue, messages can be maintained on disk (persistent messaging) or in memory (buffered messaging). To determine if a queue is buffered or not, reference the GV_$BUFFERED_QUEUES view. If the queue does not appear in this view, it is persistent. 2.1.2. Propagation mode - queue-to-dblink vs queue-to-queue As of 10.2, an AQ propagation can also be defined as queue-to-dblink, or queue-to-queue: queue-to-dblink: The propagation delivers messages or events from the source queue to all subscribing queues at the destination database identified by the dblink. A single propagation schedule is used to propagate messages to all subscribing queues. Hence any changes made to this schedule will affect message delivery to all the subscribing queues. This mode does not support multiple propagations from the same source queue to the same target database. queue-to-queue: Added in 10.2, this propagation mode delivers messages or events from the source queue to a specific destination queue identified on the database link. This allows the user to have fine-grained control on the propagation schedule for message delivery. This new propagation mode also supports transparent failover when propagating to a destination Oracle RAC system. With queue-to-queue propagation, you are no longer required to re-point a database link if the owner instance of the queue fails on Oracle RAC. This mode supports multiple propagations to the same target database if the target queues are different. The default is queue-to-dblink. To verify if queue-to-queue propagation is being used, in non-Streams environments query DBA_QUEUE_SCHEDULES.DESTINATION - if a remote queue is listed along with the remote database link, then queue-to-queue propagation is being used. For Streams environments, the DBA_PROPAGATION.QUEUE_TO_QUEUE column can be checked.See the following note for a method to switch between the two modes:Document 827473.1 How to alter propagation from queue-to-queue to queue-to-dblink 2.1.3. Combined Capture and Apply (CCA) for Streams In 11g Oracle Streams environments, an optimization called Combined Capture and Apply (CCA) is implemented by default when possible. Although a propagation is configured in this case, Streams does not use it; instead it passes information directly from capture to an apply receiver. To see if CCA is in use: COLUMN CAPTURE_NAME HEADING 'Capture Name' FORMAT A30COLUMN OPTIMIZATION HEADING 'CCA Mode?' FORMAT A10SELECT CAPTURE_NAME, DECODE(OPTIMIZATION,0, 'No','Yes') OPTIMIZATIONFROM V$STREAMS_CAPTURE; Also, see the following note:Document 463820.1 Streams Combined Capture and Apply in 11g 2.2. Queue Table Compatibility There are three types of queue table compatibility. In more recent databases, queue tables may be present in all three modes of compatibility: 8.0 - earliest version, deprecated in 10.2 onwards 8.1 - support added for RAC, asynchronous notification, secure queues, queue level access control, rule-based subscribers, separate storage of history information 10.0 - if the database is in 10.1-compatible mode, then the default value for queue table compatibility is 10.0 2.3. Single vs Multiple Consumer Queue Tables If more than one recipient can dequeue a message from a queue, then its queue table is multiple consumer. You can propagate messages from a multiple-consumer queue to a single-consumer queue. Propagation from a single-consumer queue to a multiple-consumer queue is not possible. 3. How to Use This Guide 3.1. Are Messages Being Propagated at All, or is the Propagation Just Slow? Run the following query on the source database for the propagation (assuming that it is running): select TOTAL_NUMBER from DBA_QUEUE_SCHEDULES where QNAME='<source_queue_name>'; If TOTAL_NUMBER is increasing, then propagation is most likely functioning, although it may be slow. For performance issues, see Section 7. 3.2. Propagation Between Persistent User-Created Queues See Sections 4 and 5 (and optionally Section 6 if performance is an issue). 3.3. Propagation Between Buffered User-Created Queues See Sections 4, 5, and 6 (and optionally Section 7 if performance is an issue). 3.4. Propagation between Oracle Streams Queues (without Combined Capture and Apply (CCA) Optimization) See Sections 4 and 6 (and optionally Section 7 if performance is an issue). 3.5. Propagation between Oracle Streams Queues (with Combined Capture and Apply (CCA) Optimization) Although an AQ propagation is not used directly in this case, some characteristics of the message transfer are inferred from the propagation parameters used. Some parts of Sections 4 and 6 still apply. 3.6. Messaging Gateway Propagations This note does not apply to Messaging Gateway propagations. 4. Basic AQ Propagation Troubleshooting 4.1. Double-check Your Code Make sure that you are consistent in your usage of the database link(s) names, queue names, etc. It may be useful to plot a diagram of which queues are connected via which database links to make sure that the logical structure is correct. 4.2. Verify that Job Queue Processes are Running 4.2.1. Versions 10.2 and Lower - DBA_JOBS Package For versions 10.2 and lower, a scheduled propagation is managed by DBMS_JOB package. The propagation is performed by job queue process background processes. Therefore we need to verify that there are sufficient processes available for the propagation process. We should have at least 4 job queue processes running and preferably more depending on the number of other jobs running in the database. It should be noted that for AQ specific work, AQ will only ever use half of the job queue processes available.An issue caused by an inadequate job queue processes parameter setting is described in the following note:Document 298015.1 Kwqjswproc:Excep After Loop: Assigning To Self 4.2.1.1. Job Queue Processes in Initalization Parameter File The parameter JOB_QUEUE_PROCESSES in the init.ora/spfile should be > 0. The value can be changed dynamically via connect / as sysdbaalter system set JOB_QUEUE_PROCESSES=10; 4.2.1.2. Job Queue Processes in Memory The following command will show how many job queue processes are currentlyin use by this instance (this may be different than what is in the init.ora/spfile): connect / as sysdbashow parameter job; 4.2.1.3. OS PIDs Corresponding to Job Queue Processes Identify the operating system process ids (spids) of job queue processes involved in propagation via select p.SPID, p.PROGRAM from V$PROCESS p, DBA_JOBS_RUNNING jr, V$SESSION s, DBA_JOBS j where s.SID=jr.SID and s.PADDR=p.ADDR and jr.JOB=j.JOBand j.WHAT like '%sys.dbms_aqadm.aq$_propaq(job)%'; and these SPIDs can be used to check at the operating system level that they exist.In 8i a job queue process will have a name similar to: ora_snp1_<instance_name>.In 9i onwards you will see a coordinator process: ora_cjq0_ and multiple slave processes: ora_jnnn_<instance_name>, where nnn is an integer between 1 and 999. 4.2.2. Version 11.1 and Above - Oracle Scheduler In version 11.1 and above, Oracle Scheduler is used to perform AQ and Streams propagations. Oracle Scheduler automatically tunes the number of slave processes for these jobs based on the load on the computer system, and the JOB_QUEUE_PROCESSES initialization parameter is only used to specify the maximum number of slave processes. Therefore, the JOB_QUEUE_PROCESSES initialization parameter does not need to be set (it defaults to a very high number), unless you want to limit the number of slaves that can be created. If JOB_QUEUE_PROCESSES = 0, no propagation jobs will run.See the following note for a discussion of Oracle Streams 11g and Oracle Scheduler:Document 1083608.1 11g Streams and Oracle Scheduler 4.2.2.1. Job Queue Processes in Initalization Parameter File The parameter JOB_QUEUE_PROCESSES in the init.ora/spfile should be > 0, and preferably be left at its default value. The value can be changed dynamically via connect / as sysdbaalter system set JOB_QUEUE_PROCESSES=10; To set the JOB_QUEUE_PROCESSES parameter to its default value, run: connect / as sysdbaalter system reset JOB_QUEUE_PROCESSES; and then bounce the instance. 4.2.2.2. Job Queue Processes in Memory The following command will show how many job queue processes are currently in use by this instance (this may be different than what is in the init.ora/spfile): connect / as sysdbashow parameter job; 4.2.2.3. OS PIDs Corresponding to Job Queue Processes Identify the operating system process ids (SPIDs) of job queue processes involved in propagation via col PROGRAM for a30select p.SPID, p.PROGRAM, j.JOB_namefrom v$PROCESS p, DBA_SCHEDULER_RUNNING_JOBS jr, V$SESSION s, DBA_SCHEDULER_JOBS j where s.SID=jr.SESSION_ID and s.PADDR=p.ADDRand jr.JOB_name=j.JOB_NAME and j.JOB_NAME like '%AQ_JOB$_%'; and these SPIDs can be used to check at the operating system level that they exist.You will see a coordinator process: ora_cjq0_ and multiple slave processes: ora_jnnn_<instance_name>, where nnn is an integer between 1 and 999. 4.3. Check the Alert Log and Any Associated Trace Files The first place to check for propagation failures is the alert logs at all sites (local and if relevant all remote sites). When a job queue process attempts to execute a schedule and fails it will always write an error stack to the alert log. This error stack will also be written in a job queue process trace file, which will be written to the BACKGROUND_DUMP_DEST location for 10.2 and below, and in the DIAGNOSTIC_DEST location for 11g. The fact that errors are written to the alert log demonstrates that the schedule is executing. This means that the problem could be with the set up of the schedule. In this example the ORA-02068 demonstrates that the failure was at the remote site. Further investigation revealed that the remote database was not open, hence the ORA-03114 error. Starting the database resolved the problem. Thu Feb 14 10:40:05 2002 Propagation Schedule for (AQADM.MULTIPLEQ, SHANE816.WORLD) encountered following error:ORA-04052: error occurred when looking up Remote object [email protected]: error occurred at recursive SQL level 4ORA-02068: following severe error from SHANE816ORA-03114: not connected to ORACLEORA-06512: at "SYS.DBMS_AQADM_SYS", line 4770ORA-06512: at "SYS.DBMS_AQADM", line 548ORA-06512: at line 1 Other potential errors that may be written to the alert log can be found in the following notes:Document 827184.1 AQ Propagation with CLOB data types Fails with ORA-22990 (11.1)Document 846297.1 AQ Propagation Fails : ORA-00600[kope2upic2954] or Ora-00600[Kghsstream_copyn] (10.2, 11.1)Document 731292.1 ORA-25215 Reported on Local Propagation When Using Transformation with ANYDATA queue tables (10.2, 11.1, 11.2)Document 365093.1 ORA-07445 [kwqppay2aqe()+7360] Reported on Propagation of a Transformed Message (10.1, 10.2)Document 219416.1 Advanced Queuing Propagation Fails with ORA-22922 (9.0)Document 1203544.1 AQ Propagation Aborted with ORA-600 [ociksin: invalid status] on SYS.DBMS_AQADM_SYS.AQ$_PROPAGATION_PROCEDURE After Upgrade (11.1, 11.2)Document 1087324.1 ORA-01405 ORA-01422 reported by Advanced Queuing Propagation schedules after RAC reconfiguration (10.2)Document 1079577.1 Advanced Queuing Propagation Fails With "ORA-22370 incorrect usage of method" (9.2, 10.2, 11.1, 11.2)Document 332792.1 ORA-04061 error relating to SYS.DBMS_PRVTAQIP reported when setting up Statspack (8.1, 9.0, 9.2, 10.1)Document 353325.1 ORA-24056: Internal inconsistency for QUEUE <queue_name> and destination <dblink> (8.1, 9.0, 9.2, 10.1, 10.2, 11.1, 11.2)Document 787367.1 ORA-22275 reported on Propagating Messages with LOB component when propagating between 10.1 and 10.2 (10.1, 10.2)Document 566622.1 ORA-22275 when propagating >4K AQ$_JMS_TEXT_MESSAGEs from 9.2.0.8 to 10.2.0.1 (9.2, 10.1)Document 731539.1 ORA-29268: HTTP client error 401 Unauthorized Error when the AQ Servlet attempts to Propagate a message via HTTP (9.0, 9.2, 10.1, 10.2, 11.1)Document 253131.1 Concurrent Writes May Corrupt LOB Segment When Using Auto Segment Space Management (ORA-1555) (9.2)Document 118884.1 How to unschedule a propagation schedule stuck in pending stateDocument 222992.1 DBMS_AQADM.DISABLE_PROPAGATION_SCHEDULE Returns ORA-24082Document 282987.1 Propagated Messages marked UNDELIVERABLE after Drop and Recreate Of Remote QueueDocument 1204080.1 AQ Propagation Failing With ORA-25329 After Upgraded From 8i or 9i to 10g or 11g.Document 1233675.1 AQ Propagation stops after upgrade to 11.2.0.1 ORA-30757 4.3.1. Errors Related to Incorrect Network Configuration The most common propagation errors result from an incorrect network configuration. The list below contains common errors caused by tnsnames.ora file or database links being configured incorrectly: - ORA-12154: TNS:could not resolve service name- ORA-12505: TNS:listener does not currently know of SID given in connect descriptor- ORA-12514: TNS:listener could not resolve SERVICE_NAME - ORA-12541: TNS-12541 TNS:no listener 4.4. Check the Database Links Exist and are Functioning Correctly For schedules to remote databases confirm the database link exists via. SQL> col DBLINK for a45SQL> select QNAME, NVL(REGEXP_SUBSTR(DESTINATION, '[^@]+', 1, 2), DESTINATION) dblink2 from DBA_QUEUE_SCHEDULES3 where MESSAGE_DELIVERY_MODE = 'PERSISTENT';QNAME DBLINK------------------------------ ---------------------------------------------MY_QUEUE ORCL102B.WORLD Connect as the owner of the link and select across it to verify it works and connects to the database we expect. i.e. select * from ALL_QUEUES@ ORCL102B.WORLD; You need to ensure that the userid that scheduled the propagation (using DBMS_AQADM.SCHEDULE_PROPAGATION or DBMS_PROPAGATION_ADM.CREATE_PROPAGATION if using Streams) has access to the database link for the destination. 4.5. Has Propagation Been Correctly Scheduled? Check that the propagation schedule has been created and that a job queue process has been assigned. Look for the entry in DBA_QUEUE_SCHEDULES and SYS.AQ$_SCHEDULES for your schedule. For 10g and below, check that it has a JOBNO entry in SYS.AQ$_SCHEDULES, and that there is an entry in DBA_JOBS with that JOBNO. For 11g and above, check that the schedule has a JOB_NAME entry in SYS.AQ$_SCHEDULES, and that there is an entry in DBA_SCHEDULER_JOBS with that JOB_NAME. Check the destination is as intended and spelled correctly. SQL> select SCHEMA, QNAME, DESTINATION, SCHEDULE_DISABLED, PROCESS_NAME from DBA_QUEUE_SCHEDULES;SCHEMA QNAME DESTINATION S PROCESS------- ---------- ------------------ - -----------AQADM MULTIPLEQ AQ$_LOCAL N J000 AQ$_LOCAL in the destination column shows that the queue to which we are propagating to is in the same database as the source queue. If the propagation was to a remote (different) database, a database link will be in the DESTINATION column. The entry in the SCHEDULE_DISABLED column, N, means that the schedule is NOT disabled. If Y (yes) appears in this column, propagation is disabled and the schedule will not be executed. If not using Oracle Streams, propagation should resume once you have enabled the schedule by invoking DBMS_AQADM.ENABLE_PROPAGATION_SCHEDULE (for 10.2 Oracle Streams and above, the DBMS_PROPAGATION_ADM.START_PROPAGATION procedure should be used). The PROCESS_NAME is the name of the job queue process currently allocated to execute the schedule. This process is allocated dynamically at execution time. If the PROCESS_NAME column is null (empty) the schedule is not currently executing. You may need to execute this statement a number of times to verify if a process is being allocated. If a process is at some time allocated to the schedule, it is attempting to execute. SQL> select SCHEMA, QNAME, LAST_RUN_DATE, NEXT_RUN_DATE from DBA_QUEUE_SCHEDULES;SCHEMA QNAME LAST_RUN_DATE NEXT_RUN_DATE------ ----- ----------------------- ----------------------- AQADM MULTIPLEQ 13-FEB-2002 13:18:57 13-FEB-2002 13:20:30 In 11g, these dates are expressed in TIMESTAMP WITH TIME ZONE datatypes. If the NEXT_RUN_DATE and NEXT_RUN_TIME columns are null when this statement is executed, the scheduled propagation is currently in progress. If they never change it would suggest that the schedule itself is never executing. If the next scheduled execution is too far away, change the NEXT_TIME parameter of the schedule so that schedules are executed more frequently (assuming that the window is not set to be infinite). Parameters of a schedule can be changed using the DBMS_AQADM.ALTER_PROPAGATION_SCHEDULE call. In 10g and below, scheduling propagation posts a job in the DBA_JOBS view. The columns are more or less the same as DBA_QUEUE_SCHEDULES so you just need to recognize the job and verify that it exists. SQL> select JOB, WHAT from DBA_JOBS where WHAT like '%sys.dbms_aqadm.aq$_propaq(job)%';JOB WHAT---- ----------------- 720 next_date := sys.dbms_aqadm.aq$_propaq(job); For 11g, scheduling propagation posts a job in DBA_SCHEDULER_JOBS instead: SQL> select JOB_NAME from DBA_SCHEDULER_JOBS where JOB_NAME like 'AQ_JOB$_%';JOB_NAME------------------------------AQ_JOB$_41 If no job exists, check DBA_QUEUE_SCHEDULES to make sure that the schedule has not been disabled. For 10g and below, the job number is dynamic for AQ propagation schedules. The procedure that is executed to expedite a propagation schedule runs, removes itself from DBA_JOBS, and then reposts a new job for the next scheduled propagation. The job number should therefore always increment unless the schedule has been set up to run indefinitely. 4.6. Is the Schedule Executing but Failing to Complete? Run the following query: SQL> select FAILURES, LAST_ERROR_MSG from DBA_QUEUE_SCHEDULES;FAILURES LAST_ERROR_MSG------------ -----------------------1 ORA-25207: enqueue failed, queue AQADM.INQ is disabled from enqueueingORA-02063: preceding line from SHANE816 The failures column shows how many times we have attempted to execute the schedule and failed. Oracle will attempt to execute the schedule 16 times after which it will be removed from the DBA_JOBS or DBA_SCHEDULER_JOBS view and the schedule will become disabled. The column DBA_QUEUE_SCHEDULES.SCHEDULE_DISABLED will show 'Y'. For 11g and above, the DBA_SCHEDULER_JOBS.STATE column will show 'BROKEN' for the job corresponding to DBA_QUEUE_SCHEDULES.JOB_NAME. Prior to 10g the back off algorithm for failures was exponential, whereas from 10g onwards it is linear. The propagation will become disabled on the 17th attempt. Only the last execution failure will be reflected in the LAST_ERROR_MSG column. That is, if the schedule fails 5 times for 5 different reasons, only the last set of errors will be recorded in DBA_QUEUE_SCHEDULES. Any errors need to be resolved to allow propagation to continue. If propagation has also become disabled due to 17 failures, first resolve the reason for the error and then re-enable the schedule using the DBMS_AQADM.ENABLE_PROPAGATION_SCHEDULE procedure, or DBMS_PROPAGATION_ADM.START_PROPAGATION if using 10.2 or above Oracle Streams. As soon as the schedule executes successfully the error message entries will be deleted. Oracle does not keep a history of past failures. However, when using Oracle Streams, the errors will be retained in the DBA_PROPAGATION view even after the schedule resumes successfully. See the following note for instructions on how to clear out the errors from the DBA_PROPAGATION view:Document 808136.1 How to clear the old errors from DBA_PROPAGATION view?If a schedule is active and no errors are being reported then the source queue may not have any messages to be propagated. 4.7. Do the Propagation Notification Queue Table and Queue Exist? Check to see that the propagation notification queue table and queue exist and are enabled for enqueue and dequeue. Propagation makes use of the propagation notification queue for handling propagation run-time events, and the messages in this queue are stored in a SYS-owned queue table. This queue should never be stopped or dropped and the corresponding queue table never be dropped. 10g and belowThe propagation notification queue table is of the format SYS.AQ$_PROP_TABLE_n, where 'n' is the RAC instance number, i.e. '1' for a non-RAC environment. This queue and queue table are created implicitly when propagation is first scheduled. If propagation has been scheduled and these objects do not exist, try unscheduling and rescheduling propagation. If they still do not exist contact Oracle Support. SQL> select QUEUE_TABLE from DBA_QUEUE_TABLES2 where QUEUE_TABLE like '%PROP_TABLE%' and OWNER = 'SYS';QUEUE_TABLE------------------------------AQ$_PROP_TABLE_1SQL> select NAME, ENQUEUE_ENABLED, DEQUEUE_ENABLED2 from DBA_QUEUES where owner='SYS'3 and QUEUE_TABLE like '%PROP_TABLE%';NAME ENQUEUE DEQUEUE------------------------------ ------- -------AQ$_PROP_NOTIFY_1 YES YESAQ$_AQ$_PROP_TABLE_1_E NO NO If the AQ$_PROP_NOTIFY_1 queue is not enabled for enqueue or dequeue, it should be so enabled using DBMS_AQADM.START_QUEUE. However, the exception queue AQ$_AQ$_PROP_TABLE_1_E should not be enabled for enqueue or dequeue.11g and aboveThe propagation notification queue table is of the format SYS.AQ_PROP_TABLE, and is created when the database is created. If they do not exist, contact Oracle Support. SQL> select QUEUE_TABLE from DBA_QUEUE_TABLES2 where QUEUE_TABLE like '%PROP_TABLE%' and OWNER = 'SYS';QUEUE_TABLE------------------------------AQ_PROP_TABLESQL> select NAME, ENQUEUE_ENABLED, DEQUEUE_ENABLED2 from DBA_QUEUES where owner='SYS'3 and QUEUE_TABLE like '%PROP_TABLE%';NAME ENQUEUE DEQUEUE------------------------------ ------- -------AQ_PROP_NOTIFY YES YESAQ$_AQ_PROP_TABLE_E NO NO If the AQ_PROP_NOTIFY queue is not enabled for enqueue or dequeue, it should be so enabled using DBMS_AQADM.START_QUEUE. However, the exception queue AQ$_AQ$_PROP_TABLE_E should not be enabled for enqueue or dequeue. 4.8. Does the Remote Queue Exist and is it Enabled for Enqueueing? Check that the remote queue the propagation is transferring messages to exists and is enabled for enqueue: SQL> select DESTINATION from USER_QUEUE_SCHEDULES where QNAME = 'OUTQ';DESTINATION-----------------------------------------------------------------------------"AQADM"."INQ"@M2V102.ESSQL> select OWNER, NAME, ENQUEUE_ENABLED, DEQUEUE_ENABLED from [email protected];OWNER NAME ENQUEUE DEQUEUE-------- ------ ----------- -----------AQADM INQ YES YES 4.9. Do the Target and Source Database Charactersets Differ? If a message fails to propagate, check the database charactersets of the source and target databases. Investigate whether the same message can propagate between the databases with the same characterset or it is only a particular combination of charactersets which causes a problem. 4.10. Check the Queue Table Type Agreement Propagation is not possible between queue tables which have types that differ in some respect. One way to determine if this is the case is to run the DBMS_AQADM.VERIFY_QUEUE_TYPES procedure for the two queues that the propagation operates on. If the types do not agree, DBMS_AQADM.VERIFY_QUEUE_TYPES will return '0'.For AQ propagation between databases which have different NLS_LENGTH_SEMANTICS settings, propagation will not work, unless the queues are Oracle Streams ANYDATA queues.See the following notes for issues caused by lack of type agreement:Document 1079577.1 Advanced Queuing Propagation Fails With "ORA-22370: incorrect usage of method"Document 282987.1 Propagated Messages marked UNDELIVERABLE after Drop and Recreate Of Remote QueueDocument 353754.1 Streams Messaging Propagation Fails between Single and Multi-byte Charactersets when using Chararacter Length Semantics in the ADT 4.11. Enable Propagation Tracing 4.11.1. System Level This is set it in the init.ora/spfile as follows: event="24040 trace name context forever, level 10" and restart the instanceThis event cannot be set dynamically with an alter system command until version 10.2: SQL> alter system set events '24040 trace name context forever, level 10'; To unset the event: SQL> alter system set events '24040 trace name context off'; Debugging information will be logged to job queue trace file(s) (jnnn) as propagation takes place. You can check the trace file for errors, and for statements indicating that messages have been sent. For the most part the trace information is understandable. This trace should also be uploaded to Oracle Support if a service request is created. 4.11.2. Attaching to a Specific Process We can also attach to an existing job queue processes that is running a propagation schedule and trace it individually using the oradebug utility, as follows:10.2 and below connect / as sysdbaselect p.SPID, p.PROGRAM from v$PROCESS p, DBA_JOBS_RUNNING jr, V$SESSION s, DBA_JOBS j where s.SID=jr.SID and s.PADDR=p.ADDR and jr.JOB=j.JOB and j.WHAT like '%sys.dbms_aqadm.aq$_propaq(job)%';-- For the process id (SPID) attach to it via oradebug and generate the following traceoradebug setospid <SPID>oradebug unlimitoradebug Event 10046 trace name context forever, level 12oradebug Event 24040 trace name context forever, level 10-- Trace the process for 5 minutesoradebug Event 10046 trace name context offoradebug Event 24040 trace name context off-- The following command returns the pathname/filename to the file being written tooradebug tracefile_name 11g connect / as sysdbacol PROGRAM for a30select p.SPID, p.PROGRAM, j.JOB_NAMEfrom v$PROCESS p, DBA_SCHEDULER_RUNNING_JOBS jr, V$SESSION s, DBA_SCHEDULER_JOBS j where s.SID=jr.SESSION_ID and s.PADDR=p.ADDR and jr.JOB_NAME=j.JOB_NAME and j.JOB_NAME like '%AQ_JOB$_%';-- For the process id (SPID) attach to it via oradebug and generate the following traceoradebug setospid <SPID>oradebug unlimitoradebug Event 10046 trace name context forever, level 12oradebug Event 24040 trace name context forever, level 10-- Trace the process for 5 minutesoradebug Event 10046 trace name context offoradebug Event 24040 trace name context off-- The following command returns the pathname/filename to the file being written tooradebug tracefile_name 4.11.3. Further Tracing The previous tracing steps only trace the job queue process executing the propagation on the source. At times it is useful to trace the propagation receiver process (the session which is enqueueing the messages into the target queue) on the target database which is associated with the job queue process on the source database.These following queries provide ways of identifying the processes involved in propagation so that you can attach to them via oradebug to generate trace information.In order to identify the propagation receiver process you need to execute the query as a user with privileges to access the v$ views in both the local and remote databases so the database link must connect as a user with those privileges in the remote database. The <DBLINK> in the queries should be replaced by the appropriate database link.The queries have two forms due to the differences between operating systems. The value returned by 'Rem Process' is the operating system identifier of the propagation receiver on the remote database. Once identified, this process can be attached to and traced on the remote database using the commands given in Section 4.11.2.10.2 and below - Windows select pl.SPID "JobQ Process", pl.PROGRAM, sr.PROCESS "Rem Process" from v$PROCESS pl, DBA_JOBS_RUNNING jr, V$SESSION s, DBA_JOBS j, V$SESSION@<DBLINK> sr where s.SID=jr.SID and s.PADDR=pl.ADDR and jr.JOB=j.JOB and j.WHAT like '%sys.dbms_aqadm.aq$_propaq(job)%' and pl.SPID=substr(sr.PROCESS, instr(sr.PROCESS,':')+1); 10.2 and below - Unix select pl.SPID "JobQ Process", pl.PROGRAM, sr.PROCESS "Rem Process" from V$PROCESS pl, DBA_JOBS_RUNNING jr, V$SESSION s, DBA_JOBS j, V$SESSION@<DBLINK> sr where s.SID=jr.SID and s.PADDR=pl.ADDR and jr.JOB=j.JOB and j.WHAT like '%sys.dbms_aqadm.aq$_propaq(job)%' and pl.SPID=sr.PROCESS; 11g - Windows select pl.SPID "JobQ Process", pl.PROGRAM, sr.PROCESS "Rem Process" from V$PROCESS pl, DBA_SCHEDULER_RUNNING_JOBS jr, V$SESSION s, DBA_SCHEDULER_JOBS j, V$SESSION@<DBLINK> sr where s.SID=jr.SESSION_ID and s.PADDR=pl.ADDR and jr.JOB_NAME=j.JOB_NAME and j.JOB_NAME like '%AQ_JOB$_%%' and pl.SPID=substr(sr.PROCESS, instr(sr.PROCESS,':')+1); 11g - Unix select pl.SPID "JobQ Process", pl.PROGRAM, sr.PROCESS "Rem Process" from V$PROCESS pl, DBA_SCHEDULER_RUNNING_JOBS jr, V$SESSION s, DBA_SCHEDULER_JOBS j, V$SESSION@<DBLINK> sr where s.SID=jr.SESSION_ID and s.PADDR=pl.ADDR and jr.JOB_NAME=j.JOB_NAME and j.JOB_NAME like '%AQ_JOB$_%%' and pl.SPID=sr.PROCESS;   5. Additional Troubleshooting Steps for AQ Propagation of User-Enqueued and Dequeued Messages 5.1. Check the Privileges of All Users Involved Ensure that the owner of the database link has the necessary privileges on the aq packages. SQL> select TABLE_NAME, PRIVILEGE from USER_TAB_PRIVS;TABLE_NAME PRIVILEGE------------------------------ ----------------------------------------DBMS_LOCK EXECUTEDBMS_AQ EXECUTEDBMS_AQADM EXECUTEDBMS_AQ_BQVIEW EXECUTEQT52814_BUFFER SELECT Note that when queue table is created, a view called QT<nnn>_BUFFER is created in the SYS schema, and the queue table owner is given SELECT privileges on it. The <nnn> corresponds to the object_id of the associated queue table. SQL> select * from USER_ROLE_PRIVS;USERNAME GRANTED_ROLE ADM DEF OS_------------------------------ ------------------------------ ---- ---- ---AQ_USER1 AQ_ADMINISTRATOR_ROLE NO YES NOAQ_USER1 CONNECT NO YES NOAQ_USER1 RESOURCE NO YES NO It is good practice to configure central AQ administrative user. All admin and processing jobs are created, executed and administered as this user. This configuration is not mandatory however, and the database link can be owned by any existing queue user. If this latter configuration is used, ensure that the connecting user has the necessary privileges on the AQ packages and objects involved. Privileges for an AQ Administrative user Execute on DBMS_AQADM Execute on DBMS_AQ Granted the AQ_ADMINISTRATOR_ROLE Privileges for an AQ user Execute on DBMS_AQ Execute on the message payload Enqueue privileges on the remote queue Dequeue privileges on the originating queue Privileges need to be confirmed on both sites when propagation is scheduled to remote destinations. Verify that the user ID used to login to the destination through the database link has been granted privileges to use AQ. 5.2. Verify Queue Payload Types AQ will not propagate messages from one queue to another if the payload types of the two queues are not verified to be equivalent. An AQ administrator can verify if the source and destination's payload types match by executing the DBMS_AQADM.VERIFY_QUEUE_TYPES procedure. The results of the type checking will be stored in the SYS.AQ$_MESSAGE_TYPES table. This table can be accessed using the object identifier OID of the source queue and the address database link of the destination queue, i.e. [schema.]queue_name[@destination]. Prior to Oracle 9i the payload (message type) had to be the same for all the queue tables involved in propagation. From Oracle9i onwards a transformation can be used so that payloads can be converted from one type to another. The following procedural call made on the source database can verify whether we can propagate between the source and the destination queue tables. connect aq_user1/[email protected] serverout onDECLARErc_value number;BEGINDBMS_AQADM.VERIFY_QUEUE_TYPES(src_queue_name => 'AQ_USER1.Q_1', dest_queue_name => 'AQ_USER2.Q_2',destination => 'dbl_aq_user2.es',rc => rc_value);dbms_output.put_line('rc_value code is '||rc_value);END;/ If propagation is possible then the return code value will be 1. If it is 0 then propagation is not possible and further investigation of the types and transformations used by and in conjunction with the queue tables is required. With regard to comparison of the types the following sql can be used to extract the DDL for a specific type with' %' changed appropriately on the source and target. This can then be compared for the source and target. SET LONG 20000 set pagesize 50 EXECUTE DBMS_METADATA.SET_TRANSFORM_PARAM(DBMS_METADATA.SESSION_TRANSFORM, 'STORAGE',false); SELECT DBMS_METADATA.GET_DDL('TYPE',t.type_name) from user_types t WHERE t.type_name like '%'; EXECUTE DBMS_METADATA.SET_TRANSFORM_PARAM(DBMS_METADATA.SESSION_TRANSFORM, 'DEFAULT'); 5.3. Check Message State and Destination The first step in this process is to identify the queue table associated with the problem source queue. Although you schedule propagation for a specific queue, most of the meta-data associated with that queue is stored in the underlying queue table. The following statement finds the queue table for a given queue (note that this is a multiple-consumer queue table). SQL> select QUEUE_TABLE from DBA_QUEUES where NAME = 'MULTIPLEQ';QUEUE_TABLE --------------------MULTIPLEQTABLE For a small amount of messages in a multiple-consumer queue table, the following query can be run: SQL> select MSG_STATE, CONSUMER_NAME, ADDRESS from AQ$MULTIPLEQTABLE where QUEUE = 'MULTIPLEQ';MSG_STATE CONSUMER_NAME ADDRESS-------------- ----------------------- -------------READY AQUSER2 [email protected] AQUSER1READY AQUSER3 AQADM.INQ In this example we see 2 messages ready to be propagated to remote queues and 1 that is not. If the address column is blank, the message is not scheduled for propagation and can only be dequeued from the queue upon which it was enqueued. The MSG_STATE column values are discussed in Document 102330.1 Advanced Queueing MSG_STATE Values and their Interpretation. If the address column has a value, the message has been enqueued for propagation to another queue. The first row in the example includes a database link (@M2V102.ES). This demonstrates that the message should be propagated to a queue at a remote database. The third row does not include a database link so will be propagated to a queue that resides on the same database as the source queue. The consumer name is the intended recipient at the target queue. Note that we are not querying the base queue table directly; rather, we are querying a view that is available on top of every queue table, AQ$<queue_table_name>.A more realistic query in an environment where the queue table contains thousands of messages is8.0.3-compatible multiple-consumer queue table and all compatibility single-consumer queue tables select count(*), MSG_STATE, QUEUE from AQ$<queue_table_name>  group by MSG_STATE, QUEUE; 8.1.3 and 10.0-compatible queue tables select count(*), MSG_STATE, QUEUE, CONSUMER_NAME from AQ$<queue_table_name>group by MSG_STATE, QUEUE, CONSUMER_NAME; For multiple-consumer queue tables, if you did not see the expected CONSUMER_NAME , check the syntax of the enqueue code and verify the recipients are declared correctly. If a recipients list is not used on enqueue, check the subscriber list in the AQ$_<queue_table_name>_S view (note that a single-consumer queue table does not have a subscriber view. This view records all members of the default subscription list which were added using the DBMS_AQADM.ADD_SUBSCRIBER procedure and also those enqueued using a recipient list. SQL> select QUEUE, NAME, ADDRESS from AQ$MULTIPLEQTABLE_S;QUEUE NAME ADDRESS---------- ----------- -------------MULTIPLEQ AQUSER2 [email protected] AQUSER1 In this example we have 2 subscribers registered with the queue. We have a local subscriber AQUSER1, and a remote subscriber AQUSER2, on the queue INQ, owned by AQADM, at M2V102.ES. Unless overridden with a recipient list during enqueue every message enqueued to this queue will be propagated to INQ at M2V102.ES.For 8.1 style and above multiple consumer queue tables, you can also check the following information at the target: select CONSUMER_NAME, DEQ_TXN_ID, DEQ_TIME, DEQ_USER_ID, PROPAGATED_MSGID from AQ$<queue_table_name> where QUEUE = '<QUEUE_NAME>'; For 8.0 style queues, if the queue table supports multiple consumers you can obtain the same information from the history column of the queue table: select h.CONSUMER, h.TRANSACTION_ID, h.DEQ_TIME, h.DEQ_USER, h.PROPAGATED_MSGIDfrom AQ$<queue_table_name> t, table(t.history) h where t.Q_NAME = '<QUEUE_NAME>'; A non-NULL TRANSACTION_ID indicates that the message was successfully propagated. Further, the DEQ_TIME indicates the time of propagation, the DEQ_USER indicates the userid used for propagation, and the PROPAGATED_MSGID indicates the message ID of the message that was enqueued at the destination. 6. Additional Troubleshooting Steps for Propagation in an Oracle Streams Environment 6.1. Is the Propagation Enabled? For a propagation job to propagate messages, the propagation must be enabled. For Streams, a special view called DBA_PROPAGATION exists to convey information about Streams propagations. If messages are not being propagated by a propagation as expected, then the propagation might not be enabled. To query for this: SELECT p.PROPAGATION_NAME, DECODE(s.SCHEDULE_DISABLED, 'Y', 'Disabled','N', 'Enabled') SCHEDULE_DISABLED, s.PROCESS_NAME, s.FAILURES, s.LAST_ERROR_MSGFROM DBA_QUEUE_SCHEDULES s, DBA_PROPAGATION pWHERE p.DESTINATION_DBLINK = NVL(REGEXP_SUBSTR(s.DESTINATION, '[^@]+', 1, 2), s.DESTINATION) AND s.SCHEMA = p.SOURCE_QUEUE_OWNER AND s.QNAME = p.SOURCE_QUEUE_NAME AND MESSAGE_DELIVERY_MODE = 'PERSISTENT' order by PROPAGATION_NAME; At times, the propagation job may become "broken" or fail to start after an error has been encountered or after a database restart. If an error is indicated by the above query, an attempt to disable the propagation and then re-enable it can be made. In the examples below, for the propagation named STRMADMIN_PROPAGATE where the queue name is STREAMS_QUEUE owned by STRMADMIN and the destination database link is ORCL2.WORLD, the commands would be:10.2 and above exec dbms_propagation_adm.stop_propagation('STRMADMIN_PROPAGATE'); exec dbms_propagation_adm.start_propagation('STRMADMIN_PROPAGATE'); If the above does not fix the problem, stop the propagation specifying the force parameter (2nd parameter on stop_propagation) as TRUE: exec dbms_propagation_adm.stop_propagation('STRMADMIN_PROPAGATE',true); exec dbms_propagation_adm.start_propagation('STRMADMIN_PROPAGATE'); The statistics for the propagation as well as any old error messages are cleared when the force parameter is set to TRUE. Therefore if the propagation schedule is stopped with FORCE set to TRUE, and upon restart there is still an error message in DBA_PROPAGATION, then the error message is current.9.2 or 10.1 exec dbms_aqadm.disable_propagation_schedule('STRMADMIN.STREAMS_QUEUE','ORCL2.WORLD'); exec dbms.aqadm.enable_propagation_schedule('STRMADMIN.STREAMS_QUEUE','ORCL2.WORLD'); If the above does not fix the problem, perform an unschedule of propagation and then schedule_propagation: exec dbms_aqadm.unschedule_propagation('STRMADMIN.STREAMS_QUEUE','ORCL2.WORLD'); exec dbms_aqadm.schedule_propagation('STRMADMIN.STREAMS_QUEUE','ORCL2.WORLD'); Typically if the error from the first query in Section 6.1 recurs after restarting the propagation as shown above, further troubleshooting of the error is needed. 6.2. Check Propagation Rule Sets and Transformations Inspect the configuration of the rules in the rule set that is associated with the propagation process to make sure that they evaluate to TRUE as expected. If not, then the object or schema will not be propagated. Remember that when a negative rule evaluates to TRUE, the specified object or schema will not be propagated. Finally inspect any rule-based transformations that are implemented with propagation to make sure they are changing the data in the intended way.The following query shows what rule sets are assigned to a propagation: select PROPAGATION_NAME, RULE_SET_OWNER||'.'||RULE_SET_NAME "Positive Rule Set",NEGATIVE_RULE_SET_OWNER||'.'||NEGATIVE_RULE_SET_NAME "Negative Rule Set"from DBA_PROPAGATION; The next two queries list the propagation rules and their conditions. The first is for the positive rule set, the second is for the negative rule set: set long 4000select rsr.RULE_SET_OWNER||'.'||rsr.RULE_SET_NAME RULE_SET ,rsr.RULE_OWNER||'.'||rsr.RULE_NAME RULE_NAME,r.RULE_CONDITION CONDITION fromDBA_RULE_SET_RULES rsr, DBA_RULES rwhere rsr.RULE_NAME = r.RULE_NAME and rsr.RULE_OWNER = r.RULE_OWNER and RULE_SET_NAME in(select RULE_SET_NAME from DBA_PROPAGATION) order by rsr.RULE_SET_OWNER, rsr.RULE_SET_NAME;   set long 4000select c.PROPAGATION_NAME, rsr.RULE_SET_OWNER||'.'||rsr.RULE_SET_NAME RULE_SET ,rsr.RULE_OWNER||'.'||rsr.RULE_NAME RULE_NAME,r.RULE_CONDITION CONDITION fromDBA_RULE_SET_RULES rsr, DBA_RULES r ,DBA_PROPAGATION cwhere rsr.RULE_NAME = r.RULE_NAME and rsr.RULE_OWNER = r.RULE_OWNER andrsr.RULE_SET_OWNER=c.NEGATIVE_RULE_SET_OWNER and rsr.RULE_SET_NAME=c.NEGATIVE_RULE_SET_NAMEand rsr.RULE_SET_NAME in(select NEGATIVE_RULE_SET_NAME from DBA_PROPAGATION) order by rsr.RULE_SET_OWNER, rsr.RULE_SET_NAME; 6.3. Determining the Total Number of Messages and Bytes Propagated As in Section 3.1, determining if messages are flowing can be instructive to see whether the propagation is entirely hung or just slow. If the propagation is not in flow control (see Section 6.5.2), but the statistics are incrementing slowly, there may be a performance issue. For Streams implementations two views are available that can assist with this that can show the number of messages sent by a propagation, as well as the number of acknowledgements being returned from the target site: the V$PROPAGATION_SENDER view at the Source site and the V$PROPAGATION_RECEIVER view at the destination site. It is helpful to query both to determine if messages are being delivered to the target. Look for the statistics to increase.Source: select QUEUE_SCHEMA, QUEUE_NAME, DBLINK,HIGH_WATER_MARK, ACKNOWLEDGEMENT, TOTAL_MSGS, TOTAL_BYTESfrom V$PROPAGATION_SENDER; Target: select SRC_QUEUE_SCHEMA, SRC_QUEUE_NAME, SRC_DBNAME, DST_QUEUE_SCHEMA, DST_QUEUE_NAME, HIGH_WATER_MARK, ACKNOWLEDGEMENT, TOTAL_MSGS from V$PROPAGATION_RECEIVER; 6.4. Check Buffered Subscribers The V$BUFFERED_SUBSCRIBERS view displays information about subscribers for all buffered queues in the instance. This view can be queried to make sure that the site that the propagation is propagating to is listed as a subscriber address for the site being propagated from: select QUEUE_SCHEMA, QUEUE_NAME, SUBSCRIBER_ADDRESS from V$BUFFERED_SUBSCRIBERS; The SUBSCRIBER_ADDRESS column will not be populated when the propagation is local (between queues on the same database). 6.5. Common Streams Propagation Errors 6.5.1. ORA-02082: A loopback database link must have a connection qualifier. This error can occur if you use the Streams Setup Wizard in Oracle Enterprise Manager without first configuring the GLOBAL_NAME for your database. 6.5.2. ORA-25307: Enqueue rate too high. Enable flow control DBA_QUEUE_SCHEDULES will display this informational message for propagation when the automatic flow control (10g feature of Streams) has been invoked.Similar to Streams capture processes, a Streams propagation process can also go into a state of 'flow control. This is an informative message that indicates flow control has been automatically enabled to reduce the rate at which messages are being enqueued into at target queue.This typically occurs when the target site is unable to keep up with the rate of messages flowing from the source site. Other than checking that the apply process is running normally on the target site, usually no action is required by the DBA. Propagation and the capture process will be resumed automatically when the target site is able to accept more messages.The following document contains more information:Document 302109.1 Streams Propagation Error: ORA-25307 Enqueue rate too high. Enable flow controlSee the following document for one potential cause of this situation:Document 1097115.1 Oracle Streams Apply Reader is in 'Paused' State 6.5.3. ORA-25315 unsupported configuration for propagation of buffered messages This error typically occurs when the target database is RAC and usually indicates that an attempt was made to propagate buffered messages with the database link pointing to an instance in the destination database which is not the owner instance of the destination queue. To resolve the problem, use queue-to-queue propagation for buffered messages. 6.5.4. ORA-600 [KWQBMCRCPTS101] after dropping / recreating propagation For cause/fixes refer to:Document 421237.1 ORA-600 [KWQBMCRCPTS101] reported by a Qmon slave process after dropping a Streams Propagation 6.5.5. Stopping or Dropping a Streams Propagation Hangs See the following note:Document 1159787.1 Troubleshooting Streams Propagation When It is Not Functioning and Attempts to Stop It Hang 6.6. Streams Propagation-Related Notes for Common Issues Document 437838.1 Streams Specific PatchesDocument 749181.1 How to Recover Streams After Dropping PropagationDocument 368912.1 Queue to Queue Propagation Schedule encountered ORA-12514 in a RAC environmentDocument 564649.1 ORA-02068/ORA-03114/ORA-03113 Errors From Streams Propagation Process - Remote Database is Available and Unschedule/Reschedule Does Not ResolveDocument 553017.1 Stream Propagation Process Errors Ora-4052 Ora-6554 From 11g To 10201Document 944846.1 Streams Propagation Fails Ora-7445 [kohrsmc]Document 745601.1 ORA-23603 'STREAMS enqueue aborted due to low SGA' Error from Streams Propagation, and V$STREAMS_CAPTURE.STATE Hanging on 'Enqueuing Message'Document 333068.1 ORA-23603: Streams Enqueue Aborted Eue To Low SGADocument 363496.1 Ora-25315 Propagating on RAC StreamsDocument 368237.1 Unable to Unschedule Propagation. Streams Queue is InvalidDocument 436332.1 dbms_propagation_adm.stop_propagation hangsDocument 727389.1 Propagation Fails With ORA-12528Document 730911.1 ORA-4063 Is Reported After Dropping Negative Prop.RulesetDocument 460471.1 Propagation Blocked by Qmon Process - Streams_queue_table / 'library cache lock' waitsDocument 1165583.1 ORA-600 [kwqpuspse0-ack] In Streams EnvironmentDocument 1059029.1 Combined Capture and Apply (CCA) : Capture aborts : ORA-1422 after schedule_propagationDocument 556309.1 Changing Propagation/ queue_to_queue : false -> true does does not work; no LCRs propagatedDocument 839568.1 Propagation failing with error: ORA-01536: space quota exceeded for tablespace ''Document 311021.1 Streams Propagation Process : Ora 12154 After Reboot with Transparent Application Failover TAF configuredDocument 359971.1 STREAMS propagation to Primary of physical Standby configuation errors with Ora-01033, Ora-02068Document 1101616.1 DBMS_PROPAGATION_ADM.DROP_PROPAGATION FAILS WITH ORA-1747 7. Performance Issues A propagation may seem to be slow if the queries from Sections 3.1 and 6.3 show that the message statistics are not changing quickly. In Oracle Streams, this more usually is due to a slow apply process at the target rather than a slow propagation. Propagation could be inferred to be slow if the message statistics are changing, and the state of a capture process according to V$STREAMS_CAPTURE.STATE is PAUSED FOR FLOW CONTROL, but an ORA-25307 'Enqueue rate too high. Enable flow control' warning is NOT observed in DBA_QUEUE_SCHEDULES per Section 6.5.2. If this is the case, see the following notes / white papers for suggestions to increase performance:Document 335516.1 Master Note for Streams Performance RecommendationsDocument 730036.1 Overview for Troubleshooting Streams Performance IssuesDocument 780733.1 Streams Propagation Tuning with Network ParametersWhite Paper: http://www.oracle.com/technetwork/database/features/availability/maa-wp-10gr2-streams-performance-130059.pdfWhite Paper: Oracle Streams Configuration Best Practices: Oracle Database 10g Release 10.2, http://www.oracle.com/technetwork/database/features/availability/maa-10gr2-streams-configuration-132039.pdf, See APPENDIX A: USING STREAMS CONFIGURATIONS OVER A NETWORKFor basic AQ propagation, the network tuning in the aforementioned Appendix A of the white paper 'Oracle Streams Configuration Best Practices: Oracle Database 10g Release 10.2' is applicable. References NOTE:102330.1 - Advanced Queueing MSG_STATE Values and their InterpretationNOTE:102771.1 - Advanced Queueing Propagation using PL/SQLNOTE:1059029.1 - Combined Capture and Apply (CCA) : Capture aborts : ORA-1422 after schedule_propagationNOTE:1079577.1 - Advanced Queuing Propagation Fails With "ORA-22370: incorrect usage of method"NOTE:1083608.1 - 11g Streams and Oracle SchedulerNOTE:1087324.1 - ORA-01405 ORA-01422 reported by Adavanced Queueing Propagation schedules after RAC reconfigurationNOTE:1097115.1 - Oracle Streams Apply Reader is in 'Paused' StateNOTE:1101616.1 - DBMS_PROPAGATION_ADM.DROP_PROPAGATION FAILS WITH ORA-1747NOTE:1159787.1 - Troubleshooting Streams Propagation When It is Not Functioning and Attempts to Stop It HangNOTE:1165583.1 - ORA-600 [kwqpuspse0-ack] In Streams EnvironmentNOTE:118884.1 - How to unschedule a propagation schedule stuck in pending stateNOTE:1203544.1 - AQ PROPAGATION ABORTED WITH ORA-600[OCIKSIN: INVALID STATUS] ON SYS.DBMS_AQADM_SYS.AQ$_PROPAGATION_PROCEDURE AFTER UPGRADENOTE:1204080.1 - AQ Propagation Failing With ORA-25329 After Upgraded From 8i or 9i to 10g or 11g.NOTE:219416.1 - Advanced Queuing Propagation fails with ORA-22922NOTE:222992.1 - DBMS_AQADM.DISABLE_PROPAGATION_SCHEDULE Returns ORA-24082NOTE:253131.1 - Concurrent Writes May Corrupt LOB Segment When Using Auto Segment Space Management (ORA-1555)NOTE:282987.1 - Propagated Messages marked UNDELIVERABLE after Drop and Recreate Of Remote QueueNOTE:298015.1 - Kwqjswproc:Excep After Loop: Assigning To SelfNOTE:302109.1 - Streams Propagation Error: ORA-25307 Enqueue rate too high. Enable flow controlNOTE:311021.1 - Streams Propagation Process : Ora 12154 After Reboot with Transparent Application Failover TAF configuredNOTE:332792.1 - ORA-04061 error relating to SYS.DBMS_PRVTAQIP reported when setting up StatspackNOTE:333068.1 - ORA-23603: Streams Enqueue Aborted Eue To Low SGANOTE:335516.1 - Master Note for Streams Performance RecommendationsNOTE:353325.1 - ORA-24056: Internal inconsistency for QUEUE and destination NOTE:353754.1 - Streams Messaging Propagation Fails between Single and Multi-byte Charactersets when using Chararacter Length Semantics in the ADT.NOTE:359971.1 - STREAMS propagation to Primary of physical Standby configuation errors with Ora-01033, Ora-02068NOTE:363496.1 - Ora-25315 Propagating on RAC StreamsNOTE:365093.1 - ORA-07445 [kwqppay2aqe()+7360] reported on Propagation of a Transformed MessageNOTE:368237.1 - Unable to Unschedule Propagation. Streams Queue is InvalidNOTE:368912.1 - Queue to Queue Propagation Schedule encountered ORA-12514 in a RAC environmentNOTE:421237.1 - ORA-600 [KWQBMCRCPTS101] reported by a Qmon slave process after dropping a Streams PropagationNOTE:436332.1 - dbms_propagation_adm.stop_propagation hangsNOTE:437838.1 - Streams Specific PatchesNOTE:460471.1 - Propagation Blocked by Qmon Process - Streams_queue_table / 'library cache lock' waitsNOTE:463820.1 - Streams Combined Capture and Apply in 11gNOTE:553017.1 - Stream Propagation Process Errors Ora-4052 Ora-6554 From 11g To 10201NOTE:556309.1 - Changing Propagation/ queue_to_queue : false -> true does does not work; no LCRs propagatedNOTE:564649.1 - ORA-02068/ORA-03114/ORA-03113 Errors From Streams Propagation Process - Remote Database is Available and Unschedule/Reschedule Does Not ResolveNOTE:566622.1 - ORA-22275 when propagating >4K AQ$_JMS_TEXT_MESSAGEs from 9.2.0.8 to 10.2.0.1NOTE:727389.1 - Propagation Fails With ORA-12528NOTE:730036.1 - Overview for Troubleshooting Streams Performance IssuesNOTE:730911.1 - ORA-4063 Is Reported After Dropping Negative Prop.RulesetNOTE:731292.1 - ORA-25215 Reported On Local Propagation When Using Transformation with ANYDATA queue tablesNOTE:731539.1 - ORA-29268: HTTP client error 401 Unauthorized Error when the AQ Servlet attempts to Propagate a message via HTTPNOTE:745601.1 - ORA-23603 'STREAMS enqueue aborted due to low SGA' Error from Streams Propagation, and V$STREAMS_CAPTURE.STATE Hanging on 'Enqueuing Message'NOTE:749181.1 - How to Recover Streams After Dropping PropagationNOTE:780733.1 - Streams Propagation Tuning with Network ParametersNOTE:787367.1 - ORA-22275 reported on Propagating Messages with LOB component when propagating between 10.1 and 10.2NOTE:808136.1 - How to clear the old errors from DBA_PROPAGATION view ?NOTE:827184.1 - AQ Propagation with CLOB data types Fails with ORA-22990NOTE:827473.1 - How to alter propagation from queue_to_queue to queue_to_dblinkNOTE:839568.1 - Propagation failing with error: ORA-01536: space quota exceeded for tablespace ''NOTE:846297.1 - AQ Propagation Fails : ORA-00600[kope2upic2954] or Ora-00600[Kghsstream_copyn]NOTE:944846.1 - Streams Propagation Fails Ora-7445 [kohrsmc]

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• Exception: Zend Extension ./filename.php does not exist

  - by safarov

  When i try to execute php file though CLI this message appear: Exception: Zend Extension ./filename.php does not exist But while run like this /usr/local/bin/php -q -r "echo 'test';" works as expected I tried to figure out what causing this, no success yet. Here some information about enviroment may be usefull: I have eaccelerator installed (working ok). In php.ini: zend_extension="/usr/local/lib/php/extensions/no-debug-non-zts-20100525/eaccelerator.so" eaccelerator.shm_size="16" eaccelerator.cache_dir="/var/cache/eaccelerator" eaccelerator.enable="1" eaccelerator.optimizer="1" eaccelerator.check_mtime="1" eaccelerator.debug="0" eaccelerator.filter="" eaccelerator.shm_ttl="0" eaccelerator.shm_prune_period="0" eaccelerator.shm_only="0" Apache and all sites are working Content of filename.php #!/usr/local/bin/php -q <?php echo 'test'; ?> What is the problem ?

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• Differences in memory consumption between two identical D7 sites?

  - by aendrew

  I'm running Drupal on a news site that has a lot of different View blocks on the front page (~5 total, all cached). In trying to reduce the memory footprint of the site, I've checked out source from SVN to a local development install to try and convert some of those blocks into more optimized code. Here's the weird thing. Devel module lists memory consumption at 50mb on the Production site (Running Nginx, PHP 5.2.17, XCache and Zend Optimizer.) but only 14mb on my development site (Running Apache2, PHP 5.2.13 and XCache). These are nearly-identical versions of the same site — frankly, the Production site should use even less memory as I've disabled some of the modules running on the Dev site. Any idea why this might be the case?

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• TCP Tweaking options and Results: Any suggestions?

  - by krishnakumar

  I first tried with the default windows XP TCP option(It doesn't have TCPWindowSize option and TCP1323 in its Registry setting). I dynamically set those options using TCP optimizer. Here I list out the result with and without TCP Tweaking option. I see no major improvements in TCP after increasing window size optimally too. What value should I set to increase the performance? Results: Without any window size and MTU setting from server to client (receiving) TCPWindowSize : MTU : TTL: Size:586 MB total duration : 03:47 With window size extension from server to client (receiving) Bandwidth :100 Mbps Latency: 100ms BDP :1250000 TCPWindowSize : 1250000 MTU :1500 TTL:128 Size:586MB total duration : 03:44 With window size extension from server to client (receiving) TCPWindowSize :64240 MTU :1500 TTL :112 Size: 586MB total duration : 03:49

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• eAccelerator ignore my new setting?

  - by Mwebe Nkrumah

  Hi, Im using eAccelerator 0.9.5.2, CentOS 5.3, lighttpd 1.4.22 But because eAccelerator is cached in RAM, I needs too much RAM. So Im trying to cache in hard disk. (my website is not generate money, so Im thinking about cheaper solution) So, I modify /etc/php.d/eaccelerator.ini with below codes: extension="eaccelerator.so" eaccelerator.shm_size="12" eaccelerator.cache_dir="/var/cache/eaccelerator" eaccelerator.enable="1" eaccelerator.optimizer="1" eaccelerator.check_mtime="0" eaccelerator.debug="0" eaccelerator.filter="" eaccelerator.shm_max="20M" eaccelerator.shm_ttl="1800" eaccelerator.shm_prune_period="0" eaccelerator.shm_only="0" eaccelerator.compress="0" eaccelerator.compress_level="9" eaccelerator.keys="disk_only" eaccelerator.sessions="disk_only" eaccelerator.content="disk_only" So, the output of phpinfo() as below: http://img175.imageshack.us/img175/1104/screenshggot.png But after using "disk_only" in eAccelerator and restart lighttpd & php-cgi using killall, my RAM usage is still high for php-cgi. Reboot the server also not works. The data is created in cache directory, but RAM usage is still high.

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• Does anyone still use Iometer?

  - by Brian T Hannan

  "Iometer is an I/O subsystem measurement and characterization tool for single and clustered systems. It is used as a benchmark and troubleshooting tool and is easily configured to replicate the behaviour of many popular applications." link text Does anyone still use this tool? It seems helpful, but I'm not sure if it's for the thing I am trying to work on. I am trying create a benchmark computer performance test that can be run before and after a Windows Optimization program does its stuff (ex: PC Optimizer Pro or CCleaner). I want to be able to make a quick statement like CCleaner makes the computer run 50% faster or something along those lines. Are there any newer tools like this one?

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• Xdebug 2.0.5 with Zend Server CE PHP5.2.12 possible?

  - by notbrain

  I'm using Zend Server CE with PHP 5.2.12 on OSX Snow Leopard and want to use Xdebug. I've turned off Zend Data Cache, Zend Optimizer+, and Zend Debugger in the console. When I run $ cd ~/Downloads/xdebug-2.0.5 $ /usr/local/zend/bin/phpize I get Configuring for: PHP Api Version: 20041225 Zend Module Api No: 20060613 Zend Extension Api No: 220060519 The PHP API Version, 20041225, seems to be off from the documentation (aka wrong). When I continue installation with $ ./configure ---with-php-config=/usr/local/zend/bin/php-config $ make $ sudo make install The installed xdebug.so seems to be the wrong one. Which version of xdebug do I need for this PHP API version? The Zend API numbers are ok. I'm just confused at why the PHP API Version doesn't match. PHP Warning: PHP Startup: Unable to load dynamic library '/usr/local/zend/lib/php_extensions/xdebug.so' - (null) in Unknown on line 0 PHP 5.2.12 (cli) (built: Feb 17 2010 13:39:36)

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• 503 error Varnish cache when eAccelerator is started

  - by Netismine

  I have a Magento installation running on x-large Amazon server. I have Varnish, memcached and eAccelerator installed on the server. At first everything was working fine, but then at some point it stopped working, throwing 503 error with Varnish cache stamp below it. When I disable eaccelerator, error is gone and site is working. This is my eaccelerator config: extension="eaccelerator.so" eaccelerator.shm_size = "512" eaccelerator.cache_dir = "/var/cache/php-eaccelerator" eaccelerator.enable = "1" eaccelerator.optimizer = "1" eaccelerator.debug = 0 eaccelerator.log_file = "/var/log/httpd/eaccelerator_log" eaccelerator.name_space = "" eaccelerator.check_mtime = "1" eaccelerator.filter = "" eaccelerator.shm_ttl = "0" eaccelerator.shm_prune_period = "0" eaccelerator.shm_only = "0" eaccelerator.allowed_admin_path = "" any hints?

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• How can I fix a computer that is literally too slow to do anything?

  - by fredley

  I'm troubleshooting a Windows 7 PC for a friend. A couple of days ago it started running 'slow'. It turns out 'slow' is about 15 minutes to the first glimpse of the desktop, and another 30 to show icons. It is possible to open Task Manager, and nothing seems awry, CPU usage at 1-5%, plenty of memory free. The machine is clearly infested with malware though, in particular a program called 'Optimizer Pro' is demanding money to 'remove 5102 files slowing down my computer'. This seems highly suspicious. My problem is though, that I can't access msconfig (I left it for a couple of hours after having hopefully typed it into the Start Menu and hit enter - nothing seems to have loaded), or anything at all basically. I can boot from a Linux Live CD, but can I actually do anything useful from there? System Restore hasn't fixed it either, and Safe Mode exhibits the same behavior.

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• How can I fix a computer that is infested with malware and is extremely unresponsive? [closed]

  - by fredley

  Possible Duplicate: How do I get rid of malicious spyware, malware, viruses or rootkits from my PC? I'm troubleshooting a Windows 7 PC for a friend. A couple of days ago it started running 'slow'. It turns out 'slow' is about 15 minutes to the first glimpse of the desktop, and another 30 to show icons. It is possible to open Task Manager, and nothing seems awry, CPU usage at 1-5%, plenty of memory free. The machine is clearly infested with malware though, in particular a program called 'Optimizer Pro' is demanding money to 'remove 5102 files slowing down my computer'. This seems highly suspicious. My problem is though, that I can't access msconfig (I left it for a couple of hours after having hopefully typed it into the Start Menu and hit enter - nothing seems to have loaded), or anything at all basically. I can boot from a Linux Live CD, but can I actually do anything useful from there? System Restore hasn't fixed it either, and Safe Mode exhibits the same behavior.

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• My wireless network slows down every 7.5 minutes when my desktop is switched on

  - by Dog Ears

  My network has lag spikes lasting for a few seconds every 7.5 mins. The spikes also effect any other computer connected connected to my wirless router at the time. My wife has to connect her laptop via a cable to prevent the lag causing problems when she's VPNing into her work. If I switch my PC off the problem goes away! I've got an Edimax 7728ln 802.11n wireless card and Speedtouch 585v7 (I'm with Be) I've Tried... Updated the drivers from Edimax website: 2.0.3.0 (it does say 3.0.2.0 in devices properties though) WLAN Optimizer doesn't seem to be helping What can I do?

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• Search Replace extended in a html file

  - by Fake4d

  i have a little question. I have a big html file and want to replace lots of things inside a lot of times. The only problem i cant solve is a replace with a variable. Example: <image src="start_files\0002.jpg" style="width:216pt; height:162"> should be transformed in <a href="start_files\0002.jpg" target="_blank"><image src="start_files\0002.jpg" style="width:216pt; height:162"></a> do you have an idea how to do it? I have a windows system with Notepad2 and Notepad++ and i could install a new tool if needed. (like Windows SED). The best solution would be a batch solution where i can add other transformations. Hope you have got good ideas! Thanks forward, Fake4d

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• SQL SERVER – Identify Most Resource Intensive Queries – SQL in Sixty Seconds #028 – Video

  - by pinaldave

  During performance tuning conversation the very first question people often ask is what are the queries offending the server or in another word let us identify the queries which are the most resource intensive. The resources are often described as either Memory, CPU or IO. When we talk about the queries the same is applicable for them as well. The query which is doing lots of reads or writes are for sure resource intensive as well query which are taking maximum CPU time. Performance tuning is a very deep subject and we all have our own preference regarding what should be the first step to tuning and what should be looked with the salt of grain. Though there is no denying that a query which uses more resources than what it should be using for sure require tuning. There are many ways to do identify query using intense resources (e.g. Extended events etc) but in this one we will go by simple DMV. There is a small gotcha we all have to remember about usage of DMV is that it only brings back results from existing cache. So if you have a query which is very resource intensive but is not cached or if you have explicitly removed the query from the cache it will be not part of the result returned by this DMV. It is quite possible that a query is aged and removed from the cache if your cache is not huge. If your cache is large you may want to be careful in running this query during business hours as this query itself can be resource intensive. Get Script to identify resource intensive query from Here Related Tips in SQL in Sixty Seconds: SQL SERVER – Find Most Expensive Queries Using DMV Simple Example to Configure Resource Governor – Introduction to Resource Governor SQL SERVER – DMV – sys.dm_exec_query_optimizer_info – Statistics of Optimizer SQL SERVER – Wait Stats – Wait Types – Wait Queues – Day 0 of 28 Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Database, Pinal Dave, PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Query, SQL Scripts, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL, Technology, Video Tagged: Excel

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• Writing a Book, and Moving my Blog

  - by Ben Nevarez

  I started blogging about SQL Server here at SQLblog back in July, 2009 and it was a lot of fun, I enjoyed it a lot. Then later, after a series of blog posts about the Query Optimizer, I was invited to write an entire book about that same topic. But after a few months I realized that it was going to be hard to continue both blogging and writing chapters for a book, this in addition to my regular day job, so I decided to stop blogging for a little while.   Now that I have finished the last chapter of the book and I am working on the final chapter reviews, I decided to start blogging again. This time I am moving my blog to   http://www.benjaminnevarez.com   Same as my previous posts I plan to write about my topics of interest, like the relational engine, and basically anything related to SQL Server. Hopefully you find my new blog interesting and useful.   Finally, I would like to thank Adam for allowing me to blog here. Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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