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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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• Auto DOP and Concurrency

  - by jean-pierre.dijcks

  After spending some time in the cloud, I figured it is time to come down to earth and start discussing some of the new Auto DOP features some more. As Database Machines (the v2 machine runs Oracle Database 11.2) are effectively selling like hotcakes, it makes some sense to talk about the new parallel features in more detail. For basic understanding make sure you have read the initial post. The focus there is on Auto DOP and queuing, which is to some extend the focus here. But now I want to discuss the concurrency a little and explain some of the relevant parameters and their impact, specifically in a situation with concurrency on the system. The goal of Auto DOP The idea behind calculating the Automatic Degree of Parallelism is to find the highest possible DOP (ideal DOP) that still scales. In other words, if we were to increase the DOP even more  above a certain DOP we would see a tailing off of the performance curve and the resource cost / performance would become less optimal. Therefore the ideal DOP is the best resource/performance point for that statement. The goal of Queuing On a normal production system we should see statements running concurrently. On a Database Machine we typically see high concurrency rates, so we need to find a way to deal with both high DOP’s and high concurrency. Queuing is intended to make sure we Don’t throttle down a DOP because other statements are running on the system Stay within the physical limits of a system’s processing power Instead of making statements go at a lower DOP we queue them to make sure they will get all the resources they want to run efficiently without trashing the system. The theory – and hopefully – practice is that by giving a statement the optimal DOP the sum of all statements runs faster with queuing than without queuing. Increasing the Number of Potential Parallel Statements To determine how many statements we will consider running in parallel a single parameter should be looked at. That parameter is called PARALLEL_MIN_TIME_THRESHOLD. The default value is set to 10 seconds. So far there is nothing new here…, but do realize that anything serial (e.g. that stays under the threshold) goes straight into processing as is not considered in the rest of this post. Now, if you have a system where you have two groups of queries, serial short running and potentially parallel long running ones, you may want to worry only about the long running ones with this parallel statement threshold. As an example, lets assume the short running stuff runs on average between 1 and 15 seconds in serial (and the business is quite happy with that). The long running stuff is in the realm of 1 – 5 minutes. It might be a good choice to set the threshold to somewhere north of 30 seconds. That way the short running queries all run serial as they do today (if it ain’t broken, don’t fix it) and allows the long running ones to be evaluated for (higher degrees of) parallelism. This makes sense because the longer running ones are (at least in theory) more interesting to unleash a parallel processing model on and the benefits of running these in parallel are much more significant (again, that is mostly the case). Setting a Maximum DOP for a Statement Now that you know how to control how many of your statements are considered to run in parallel, lets talk about the specific degree of any given statement that will be evaluated. As the initial post describes this is controlled by PARALLEL_DEGREE_LIMIT. This parameter controls the degree on the entire cluster and by default it is CPU (meaning it equals Default DOP). For the sake of an example, let’s say our Default DOP is 32. Looking at our 5 minute queries from the previous paragraph, the limit to 32 means that none of the statements that are evaluated for Auto DOP ever runs at more than DOP of 32. Concurrently Running a High DOP A basic assumption about running high DOP statements at high concurrency is that you at some point in time (and this is true on any parallel processing platform!) will run into a resource limitation. And yes, you can then buy more hardware (e.g. expand the Database Machine in Oracle’s case), but that is not the point of this post… The goal is to find a balance between the highest possible DOP for each statement and the number of statements running concurrently, but with an emphasis on running each statement at that highest efficiency DOP. The PARALLEL_SERVER_TARGET parameter is the all important concurrency slider here. Setting this parameter to a higher number means more statements get to run at their maximum parallel degree before queuing kicks in.  PARALLEL_SERVER_TARGET is set per instance (so needs to be set to the same value on all 8 nodes in a full rack Database Machine). Just as a side note, this parameter is set in processes, not in DOP, which equates to 4* Default DOP (2 processes for a DOP, default value is 2 * Default DOP, hence a default of 4 * Default DOP). Let’s say we have PARALLEL_SERVER_TARGET set to 128. With our limit set to 32 (the default) we are able to run 4 statements concurrently at the highest DOP possible on this system before we start queuing. If these 4 statements are running, any next statement will be queued. To run a system at high concurrency the PARALLEL_SERVER_TARGET should be raised from its default to be much closer (start with 60% or so) to PARALLEL_MAX_SERVERS. By using both PARALLEL_SERVER_TARGET and PARALLEL_DEGREE_LIMIT you can control easily how many statements run concurrently at good DOPs without excessive queuing. Because each workload is a little different, it makes sense to plan ahead and look at these parameters and set these based on your requirements.

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• Optimizing collision engine bottleneck

  - by Vittorio Romeo

  Foreword: I'm aware that optimizing this bottleneck is not a necessity - the engine is already very fast. I, however, for fun and educational purposes, would love to find a way to make the engine even faster. I'm creating a general-purpose C++ 2D collision detection/response engine, with an emphasis on flexibility and speed. Here's a very basic diagram of its architecture: Basically, the main class is World, which owns (manages memory) of a ResolverBase*, a SpatialBase* and a vector<Body*>. SpatialBase is a pure virtual class which deals with broad-phase collision detection. ResolverBase is a pure virtual class which deals with collision resolution. The bodies communicate to the World::SpatialBase* with SpatialInfo objects, owned by the bodies themselves. There currenly is one spatial class: Grid : SpatialBase, which is a basic fixed 2D grid. It has it's own info class, GridInfo : SpatialInfo. Here's how its architecture looks: The Grid class owns a 2D array of Cell*. The Cell class contains two collection of (not owned) Body*: a vector<Body*> which contains all the bodies that are in the cell, and a map<int, vector<Body*>> which contains all the bodies that are in the cell, divided in groups. Bodies, in fact, have a groupId int that is used for collision groups. GridInfo objects also contain non-owning pointers to the cells the body is in. As I previously said, the engine is based on groups. Body::getGroups() returns a vector<int> of all the groups the body is part of. Body::getGroupsToCheck() returns a vector<int> of all the groups the body has to check collision against. Bodies can occupy more than a single cell. GridInfo always stores non-owning pointers to the occupied cells. After the bodies move, collision detection happens. We assume that all bodies are axis-aligned bounding boxes. How broad-phase collision detection works: Part 1: spatial info update For each Body body: Top-leftmost occupied cell and bottom-rightmost occupied cells are calculated. If they differ from the previous cells, body.gridInfo.cells is cleared, and filled with all the cells the body occupies (2D for loop from the top-leftmost cell to the bottom-rightmost cell). body is now guaranteed to know what cells it occupies. For a performance boost, it stores a pointer to every map<int, vector<Body*>> of every cell it occupies where the int is a group of body->getGroupsToCheck(). These pointers get stored in gridInfo->queries, which is simply a vector<map<int, vector<Body*>>*>. body is now guaranteed to have a pointer to every vector<Body*> of bodies of groups it needs to check collision against. These pointers are stored in gridInfo->queries. Part 2: actual collision checks For each Body body: body clears and fills a vector<Body*> bodiesToCheck, which contains all the bodies it needs to check against. Duplicates are avoided (bodies can belong to more than one group) by checking if bodiesToCheck already contains the body we're trying to add. const vector<Body*>& GridInfo::getBodiesToCheck() { bodiesToCheck.clear(); for(const auto& q : queries) for(const auto& b : *q) if(!contains(bodiesToCheck, b)) bodiesToCheck.push_back(b); return bodiesToCheck; } The GridInfo::getBodiesToCheck() method IS THE BOTTLENECK. The bodiesToCheck vector must be filled for every body update because bodies could have moved meanwhile. It also needs to prevent duplicate collision checks. The contains function simply checks if the vector already contains a body with std::find. Collision is checked and resolved for every body in bodiesToCheck. That's it. So, I've been trying to optimize this broad-phase collision detection for quite a while now. Every time I try something else than the current architecture/setup, something doesn't go as planned or I make assumption about the simulation that later are proven to be false. My question is: how can I optimize the broad-phase of my collision engine maintaining the grouped bodies approach? Is there some kind of magic C++ optimization that can be applied here? Can the architecture be redesigned in order to allow for more performance? Actual implementation: SSVSCollsion Body.h, Body.cpp World.h, World.cpp Grid.h, Grid.cpp Cell.h, Cell.cpp GridInfo.h, GridInfo.cpp

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• SQL SERVER – Weekly Series – Memory Lane – #006

  - by pinaldave

  Here is the list of selected articles of SQLAuthority.com across all these years. Instead of just listing all the articles I have selected a few of my most favorite articles and have listed them here with additional notes below it. Let me know which one of the following is your favorite article from memory lane. 2006 This was my very first year of blogging so I was every day learning something new. As I have said many times, that blogging was never an intention. I had really not understood what exactly I am working on or beginning when I was beginning blogging in 2006. I had never knew that my life was going to change forever, once I started blogging. When I look back all of this year, I am happy that we are here together. 2007 IT Outsourcing to India – Top 10 Reasons Companies Outsource Outsourcing is about trust, collaboration and success. Helping other countries in need has been always the course of mankind, outsourcing is nothing different then that. With information technology and process improvements increasing the complexity, costs and skills required to accomplish routine tasks as well as challenging complex tasks, companies are outsourcing such tasks to providers who have the expertise to perform them at lower costs , with greater value and quality outcome. UDF – Remove Duplicate Chars From String This was a very interesting function I wrote in my early career. I am still using this function when I have to remove duplicate chars from strings. I have yet to come across a scenario where it does not work so I keep on using it till today. Please leave a comment if there is any better solution to this problem. FIX : Error : 3702 Cannot drop database because it is currently in use This is a very generic error when DROP Database is command is executed and the database is not dropped. The common mistake user is kept the connection open with this database and trying to drop the database. The database cannot be dropped if there is any other connection open along with it. It is always a good idea to take database in single user mode before dropping it. Here is the quick tutorial regarding how to bring the database in single user mode: Using T-SQL | Using SSMS. 2008 Install SQL Server 2008 – How to Upgrade to SQL Server 2008 – Installation Tutorial This was indeed one of the most popular articles in SQL Server 2008. Lots of people wanted to learn how to install SQL SErver 2008 but they were facing various issues while installation. I build this tutorial which becomes reference points for many. Default Collation of SQL Server 2008 What is the collation of SQL Server 2008 default installations? I often see this question confusing many experienced developers as well. Well the answer is in following image. Ahmedabad SQL Server User Group Meeting – November 2008 User group meetings are fun, now a days I am going to User Group meetings every week but there was a case when I have been just a beginner on this subject. The bug of the community was caught on me years ago when I started to present in Ahmedabad and Gandhinagar SQ LServer User Groups. 2009 Validate an XML document in TSQL using XSD My friend Jacob Sebastian wrote an excellent article on the subject XML and XSD. Because of the ‘eXtensible’ nature of XML (eXtensible Markup Language), often there is a requirement to restrict and validate the content of an XML document to a pre-defined structure and values. XSD (XML Schema Definition Language) is the W3C recommended language for describing and validating XML documents. SQL Server implements XSD as XML Schema Collections. Star Join Query Optimization At present, when queries are sent to very large databases, millions of rows are returned. Also the users have to go through extended query response times when joining multiple tables are involved with such queries. ‘Star Join Query Optimization’ is a new feature of SQL Server 2008 Enterprise Edition. This mechanism uses bitmap filtering for improving the performance of some types of queries by the effective retrieval of rows from fact tables. 2010 These puzzles are very interesting and intriguing – there was lots of interest on this subject. If you have free time this weekend. You may want to try them out. SQL SERVER – Challenge – Puzzle – Usage of FAST Hint (Solution)  SQL SERVER – Puzzle – Challenge – Error While Converting Money to Decimal (Solution)  SQL SERVER – Challenge – Puzzle – Why does RIGHT JOIN Exists (Open)  Additionally, I had great fun presenting SQL Server Performance Tuning seminar at fantastic locations in Hyderabad. Installing AdventeWorks Database This has been the most popular request I have received on my blog. Here is the quick video about how one can install AdventureWorks. 2011 Effect of SET NOCOUNT on @@ROWCOUNT There was an interesting incident once while I was presenting a session. I wrote a code and suddenly 10 hands went up in the air.  This was a bit surprise to me as I do not know why they all got alerted. I assumed that there should be something wrong with either project, screen or my display. However the real reason was very interesting – I suggest you read the complete blog post to understand this interesting scenario. Error: Deleting Offline Database and Creating the Same Name This is very interesting because once a user deletes the offline database the MDF and LDF file still exists and if the user attempts to create a new database with the same name it will give error. I found this very interesting and the blog explains the concept very quickly. Have you ever faced a similar situation? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Memory Lane, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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• Common usecases and techniques when integrating a 3rd party application with Oracle Sales Cloud

  - by asantaga

  Over the last year or so I've see a lot of partners migrating and integrate their applications with Oracle Sales Cloud. Interestingly I'd say 60% of the partners use the same set of design patterns over and over again. Most of the time I see that they want to embed their application into Oracle Sales Cloud, within a tab usually, perhaps click on a link to their application (passing some piece of data + credentials) and then within their application update sales cloud again using webservices. Here are some examples of the different use-cases I've seen , and how partners are embedding their applications into Sales Cloud, NB : The following examples use the "Desktop" User Interface rather than the Newer "Simplified User Interface", I'll update the sample application soon but the integration patterns are precisely the same Use Case 1 :  Navigator "Link out" to third party application This is an example of where the developer has added a link to the global navigator and this links out to the 3rd Party Application. Typically one doesn't pass any contextual data with the exception of perhaps user credentials, or better still JWT Token. Techniques Used   Adding Link to Menu Item Using JWT Token in Sales Cloud Use Case 2 : Application Embedded within the Sales Cloud Dashboard Within the Oracle Sales Cloud application there is a tab called "Sales", within this tab its possible to embed a SubTab and embed a iFrame pointing to your application. To do this the developer simply needs to edit the page in customization mode, add the tab and then add the iFrame, simples! The developer can pass credentials/JWT Token and some other pieces of data but not object data (ie the current OpportunityID etc)  Techniques Used Adding a page to the dashboard  Using JWT Token in Sales Cloud  Use Case 3 : Embedding a Tab and Context Linking out from a Sales Cloud object to the 3rd party application In this usecase the developer embeds two components into Oracle Sales Cloud. The first is a SubTab showing summary data to the user (a quote in our case) and then secondly a hyperlink, (although it could be a button) which when clicked navigates the user to the 3rd party application. In this case the developer almost always passes context specific data (i.e. the opportunityId) and a security token (username password combo or JWT Token). The third party application usually takes the data, perhaps queries more data using the Sales Cloud SOAP/WebService interface and then displays the resulting mashup to the user for further processing. When the user has finished their work in the 3rd party application they normally navigate back to Oracle Sales Cloud using what's called a "DeepLink", ie taking them back to the object [opportunity in our case] they came from. This image visually shows a "Happy Path" a user may follow, and combines linking out to an application , webservice calls and deep linking back to Sales Cloud. Techniques Used Extending a SalesCloud application with a custom button Using JWT Token in Sales Cloud Extending Oracle Sales Cloud [Opportnity] with a custom tab exposing External Content Retrieving Data from Oracle Sales cloud using WebServices Coding some groovy script to generate the URLs required (Doc 1571200.1 on MyOracle Support) DeepLinking to specific Oracle Sales Cloud Pages (Doc 1516151.1 on My Oracle Support) Use-Case 4 :  Server Side processing/synchronization This usecase focuses on the Server Side processing of data, in this case synchronizing data. Here the 3rd party application is running on a "timer", e.g. cron or similar, and when triggered it queries data from Oracle Sales Cloud, then it queries data from the 3rd party application, determines the deltas and then inserts the data where required. Specifically here we are calling Oracle Sales Cloud using SOAP/WebServices and the 3rd party application is being communicated to using the REST API, for Oracle Sales Cloud one would use standard JAX-WS WebService calls and for REST one would use the JAX-RS api and perhap the Jackson api for managing JSON objects.. This is a very common use case and one which specifically lends itself to using the Oracle Java Cloud Service as the ideal application server where to host the mediator between the two applications.  Techniques Used Using JWT Token in Sales Cloud Integrating with the Oracle Java Cloud Service Retrieving Data from Oracle Sales cloud using WebServices General Resources The above is just a small set of techniques and use-cases which are used today. There are plenty of other sources of documentation and resources available on the internet but to get you started here are a few of my favourite places  Sales Cloud General Documentation Sales Cloud Customize Tab is useful for general customization of Sales Cloud Sales Cloud Integration Tab focuses on the 3rd party integration techniques  Official Oracle Fusion Developer Relations Blog Official Oracle Fusion Developer Relations YouTube Channel Enjoy integrating! 

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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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• Converting LINQ to Twitter to Twitter API v1.1

  - by Joe Mayo

  Twitter recently updated their API to v1.1 (Current status: API v1.1). Naturally, LINQ to Twitter  needed to be updated too. This blog post outlines the changes made to LINQ to Twitter during this conversion and highlights important features that LINQ to Twitter developers will want to know. Overall Impact Generally speaking, Twitter API v1.1 is semantically very much the same as it’s predecessor. The base URL changed and so did a few resource segments, but the resources themselves are still intact. The good news is that LINQ to Twitter has always shielded the developer from this plumbing, so the entities, types, and filters didn’t change much at all.  The following sections describe what did  change. Authentication In Twitter API v1.0 authentication was not required for some resources, such as user timelines and search. However, that’s all changed because *all* queries must be authenticated in Twitter API v1.1. LINQ to Twitter has various types of authorizers you can use, supporting whatever OAuth options are available via Twitter.  You can see the LINQ to Twitter documentation, Securing Your Applications, for more info on OAuth support. The New Search One of the larger changes to the API was Search. To be more specific, the Search entity now contains a List<Status>, named Statuses, to hold results.  Additionally, any meta-data associated with the search is now in a property named SearchMetaData. The change to the Search entity and responses is the big change, but the good news is that your Search query syntax doesn’t change. Different Rate Limits The issue of rate limits itself is contentious, but this discussion is focused on the coding experience and I’ll leave the politics to those who prefer to engage in that activity. What’s important here is that both headers and resources have changed. You should review Twitter’s Rate Limit documentation to understand what the changes mean.  A quick explanation is that rate limits are applied individually to each resource in 15 minute time intervals. In LINQ to Twitter these changes surface on the Help entity, via HelpType.RateLimits. The RateLimits query has a Resources filter where you can specify a comma-separated list of categories to return rate limit info for.  The results materialize in the RateLimits dictionary, keyed on category. The Help entity also has a RateLimitsAuthorizationContext, holding the Access Token for the user performing queries – and to whom the rate limits apply. In addition to the new RateLimits query, there are new RateLimit headers that appear in the query response, whose HTTP header name is of the form X-Rate-Limit… which is different from the previous header name. LINQ to Twitter surfaces these headers via the existing properties of the TwitterContext instance. For anyone who retrieved rate limit information via the Headers property of TwitterContext, you should be aware of the new header names.  I haven’t done anything with Feature rate limit properties yet, but they appear to no longer be available – this will require more follow-up. Error Handling Twitter API v1.1 has a new format for Error Codes & Responses. LINQ to Twitter wraps these messages in the TwitterQueryException, which has been updated appropriately. The Message property of TwitterQueryException now reflects the Twitter error message, when available. There’s also a new ErrorCode that’s populated with the message error code. Parameters Most parameters stayed the same, but one of interest is Include Entities (different from LINQ to Twitter data object entities). Entities are metadata hanging off tweets, that provide start/end position in the tweet and other information for mentions, urls, hash tags, and media. Entities used to not be included unless you specified you wanted them. Now, in v1.1, entities are included by default for all APIs that return a Status.  If you were always setting IncludeEntities to true, then you won’t see a change. However, be aware that you’ll now be receiving additional data in your response from Twitter, which will explain a sudden increase in bandwidth utilization. This might or might not  matter to you  depending on the requirements of your application, but you should be aware of it. Everything Else There might be small changes here and there that I haven’t mentioned, but these were the ones you should be most aware of.  Streams didn’t change, but Twitter will be deprecating username/password authentication on public streams, in favor of OAuth, so you’ll be seeing me make that change some time in the future.  Also, Twitter will continue to evolve the API and you can expect that LINQ to Twitter will change accordingly. Summary The big changes to Twitter API were Authentication, Search, Rate Limits, and Error Handling. All API calls must be authenticated. You’ll need to change your code to read Search results differently, but the query is much the same as you use now. There’s a new RateLimits API, one of the Help queries.  Also, the new error messages are integrated into TwitterQueryException. Besides these changes, I expect  most others to be small or affect a smaller percentage of developers.  You can get the latest version of LINQ to Twitter from NuGet or visit the LINQ to Twitter download page at CodePlex.com.   @JoeMayo

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• NDepend Evaluation: Part 3

  - by Anthony Trudeau

  NDepend is a Visual Studio add-in designed for intense code analysis with the goal of high code quality. NDepend uses a number of metrics and aggregates the data in pleasing static and active visual reports. My evaluation of NDepend will be broken up into several different parts. In the first part of the evaluation I looked at installing the add-in.  And in the last part I went over my first impressions including an overview of the features.  In this installment I provide a little more detail on a few of the features that I really like. Dependency Matrix The dependency matrix is one of the rich visual components provided with NDepend.  At a glance it lets you know where you have coupling problems including cycles.  It does this with number indicating the weight of the dependency and a color-coding that indicates the nature of the dependency. Green and blue cells are direct dependencies (with the difference being whether the relationship is from row-to-column or column-to-row).  Black cells are the ones that you really want to know about.  These indicate that you have a cycle.  That is, type A refers to type B and type B also refers to Type A. But, that’s not the end of the story.  A handy pop-up appears when you hover over the cell in question.  It explains the color, the dependency, and provides several interesting links that will teach you more than you want to know about the dependency. You can double-click the problem cells to explode the dependency.  That will show the dependencies on a method-by-method basis allowing you to more easily target and fix the problem.  When you’re done you can click the back button on the toolbar. Dependency Graph The dependency graph is another component provided.  It’s complementary to the dependency matrix, but it isn’t as easy to identify dependency issues using the window. On a positive note, it does provide more information than the matrix. My biggest issue with the dependency graph is determining what is shown.  This was not readily obvious.  I ended up using the navigation buttons to get an acceptable view.  I would have liked to choose what I see. Once you see the types you want you can get a decent idea of coupling strength based on the width of the dependency lines.  Double-arrowed lines are problematic and are shown in red.  The size of the boxes will be related to the metric being displayed.  This is controlled using the Box Size drop-down in the toolbar.  Personally, I don’t find the size of the box to be helpful, so I change it to Constant Font. One nice thing about the display is that you can see the entire path of dependencies when you hover over a type.  This is done by color-coding the dependencies and dependants.  It would be nice if selecting the box for the type would lock the highlighting in place. I did find a perhaps unintended work-around to the color-coding.  You can lock the color-coding in by hovering over the type, right-clicking, and then clicking on the canvas area to clear the pop-up menu.  You can then do whatever with it including saving it to an image file with the color-coding. CQL NDepend uses a code query language (CQL) to work with your code just like it was a database.  CQL cannot be confused with the robustness of T-SQL or even LINQ, but it represents an impressive attempt at providing an expressive way to enumerate and interrogate your code. There are two main windows you’ll use when working with CQL.  The CQL Query Explorer allows you to define what queries (rules) are run as part of a report – I immediately unselected rules that I don’t want in my results.  The CQL Query Edit window is where you can view or author your own rules.  The explorer window is pretty self-explanatory, so I won’t mention it further other than to say that any queries you author will appear in the custom group. Authoring your own queries is really hard to screw-up.  The Intellisense-like pop-ups tell you what you can do while making composition easy.  I was able to create a query within two minutes of playing with the editor.  My query warns if any types that are interfaces don’t start with an “I”. WARN IF Count > 0 IN SELECT TYPES WHERE IsInterface AND !NameLike “I” The results from the CQL Query Edit window are immediate. That fact makes it useful for ad hoc querying.  It’s worth mentioning two things that could make the experience smoother.  First, out of habit from using Visual Studio I expect to be able to scroll and press Tab to select an item in the list (like Intellisense).  You have to press Enter when you scroll to the item you want.  Second, the commands are case-sensitive.  I don’t see a really good reason to enforce that. CQL has a lot of potential not just in enforcing code quality, but also enforcing architectural constraints that your enterprise has defined. Up Next My next update will be the final part of the evaluation.  I will summarize my experience and provide my conclusions on the NDepend add-in. ** View Part 1 of the Evaluation ** ** View Part 2 of the Evaluation ** Disclaimer: Patrick Smacchia contacted me about reviewing NDepend. I received a free license in return for sharing my experiences and talking about the capabilities of the add-in on this site. There is no expectation of a positive review elicited from the author of NDepend.

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• Developing Schema Compare for Oracle (Part 6): 9i Query Performance

  - by Simon Cooper

  All throughout the EAP and beta versions of Schema Compare for Oracle, our main request was support for Oracle 9i. After releasing version 1.0 with support for 10g and 11g, our next step was then to get version 1.1 of SCfO out with support for 9i. However, there were some significant problems that we had to overcome first. This post will concentrate on query execution time. When we first tested SCfO on a 9i server, after accounting for various changes to the data dictionary, we found that database registration was taking a long time. And I mean a looooooong time. The same database that on 10g or 11g would take a couple of minutes to register would be taking upwards of 30 mins on 9i. Obviously, this is not ideal, so a poke around the query execution plans was required. As an example, let's take the table population query - the one that reads ALL_TABLES and joins it with a few other dictionary views to get us back our list of tables. On 10g, this query takes 5.6 seconds. On 9i, it takes 89.47 seconds. The difference in execution plan is even more dramatic - here's the (edited) execution plan on 10g: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 108K| 939 || 1 | SORT ORDER BY | | 108K| 939 || 2 | NESTED LOOPS OUTER | | 108K| 938 ||* 3 | HASH JOIN RIGHT OUTER | | 103K| 762 || 4 | VIEW | ALL_EXTERNAL_LOCATIONS | 2058 | 3 ||* 20 | HASH JOIN RIGHT OUTER | | 73472 | 759 || 21 | VIEW | ALL_EXTERNAL_TABLES | 2097 | 3 ||* 34 | HASH JOIN RIGHT OUTER | | 39920 | 755 || 35 | VIEW | ALL_MVIEWS | 51 | 7 || 58 | NESTED LOOPS OUTER | | 39104 | 748 || 59 | VIEW | ALL_TABLES | 6704 | 668 || 89 | VIEW PUSHED PREDICATE | ALL_TAB_COMMENTS | 2025 | 5 || 106 | VIEW | ALL_PART_TABLES | 277 | 11 |------------------------------------------------------------------------------- And the same query on 9i: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 16P| 55G|| 1 | SORT ORDER BY | | 16P| 55G|| 2 | NESTED LOOPS OUTER | | 16P| 862M|| 3 | NESTED LOOPS OUTER | | 5251G| 992K|| 4 | NESTED LOOPS OUTER | | 4243M| 2578 || 5 | NESTED LOOPS OUTER | | 2669K| 1440 ||* 6 | HASH JOIN OUTER | | 398K| 302 || 7 | VIEW | ALL_TABLES | 342K| 276 || 29 | VIEW | ALL_MVIEWS | 51 | 20 ||* 50 | VIEW PUSHED PREDICATE | ALL_TAB_COMMENTS | 2043 | ||* 66 | VIEW PUSHED PREDICATE | ALL_EXTERNAL_TABLES | 1777K| ||* 80 | VIEW PUSHED PREDICATE | ALL_EXTERNAL_LOCATIONS | 1744K| ||* 96 | VIEW | ALL_PART_TABLES | 852K| |------------------------------------------------------------------------------- Have a look at the cost column. 10g's overall query cost is 939, and 9i is 55,000,000,000 (or more precisely, 55,496,472,769). It's also having to process far more data. What on earth could be causing this huge difference in query cost? After trawling through the '10g New Features' documentation, we found item 1.9.2.21. Before 10g, Oracle advised that you do not collect statistics on data dictionary objects. From 10g, it advised that you do collect statistics on the data dictionary; for our queries, Oracle therefore knows what sort of data is in the dictionary tables, and so can generate an efficient execution plan. On 9i, no statistics are present on the system tables, so Oracle has to use the Rule Based Optimizer, which turns most LEFT JOINs into nested loops. If we force 9i to use hash joins, like 10g, we get a much better plan: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 7587K| 3704 || 1 | SORT ORDER BY | | 7587K| 3704 ||* 2 | HASH JOIN OUTER | | 7587K| 822 ||* 3 | HASH JOIN OUTER | | 5262K| 616 ||* 4 | HASH JOIN OUTER | | 2980K| 465 ||* 5 | HASH JOIN OUTER | | 710K| 432 ||* 6 | HASH JOIN OUTER | | 398K| 302 || 7 | VIEW | ALL_TABLES | 342K| 276 || 29 | VIEW | ALL_MVIEWS | 51 | 20 || 50 | VIEW | ALL_PART_TABLES | 852K| 104 || 78 | VIEW | ALL_TAB_COMMENTS | 2043 | 14 || 93 | VIEW | ALL_EXTERNAL_LOCATIONS | 1744K| 31 || 106 | VIEW | ALL_EXTERNAL_TABLES | 1777K| 28 |------------------------------------------------------------------------------- That's much more like it. This drops the execution time down to 24 seconds. Not as good as 10g, but still an improvement. There are still several problems with this, however. 10g introduced a new join method - a right outer hash join (used in the first execution plan). The 9i query optimizer doesn't have this option available, so forcing a hash join means it has to hash the ALL_TABLES table, and furthermore re-hash it for every hash join in the execution plan; this could be thousands and thousands of rows. And although forcing hash joins somewhat alleviates this problem on our test systems, there's no guarantee that this will improve the execution time on customers' systems; it may even increase the time it takes (say, if all their tables are partitioned, or they've got a lot of materialized views). Ideally, we would want a solution that provides a speedup whatever the input. To try and get some ideas, we asked some oracle performance specialists to see if they had any ideas or tips. Their recommendation was to add a hidden hook into the product that allowed users to specify their own query hints, or even rewrite the queries entirely. However, we would prefer not to take that approach; as well as a lot of new infrastructure & a rewrite of the population code, it would have meant that any users of 9i would have to spend some time optimizing it to get it working on their system before they could use the product. Another approach was needed. All our population queries have a very specific pattern - a base table provides most of the information we need (ALL_TABLES for tables, or ALL_TAB_COLS for columns) and we do a left join to extra subsidiary tables that fill in gaps (for instance, ALL_PART_TABLES for partition information). All the left joins use the same set of columns to join on (typically the object owner & name), so we could re-use the hash information for each join, rather than re-hashing the same columns for every join. To allow us to do this, along with various other performance improvements that could be done for the specific query pattern we were using, we read all the tables individually and do a hash join on the client. Fortunately, this 'pure' algorithmic problem is the kind that can be very well optimized for expected real-world situations; as well as storing row data we're not using in the hash key on disk, we use very specific memory-efficient data structures to store all the information we need. This allows us to achieve a database population time that is as fast as on 10g, and even (in some situations) slightly faster, and a memory overhead of roughly 150 bytes per row of data in the result set (for schemas with 10,000 tables in that means an extra 1.4MB memory being used during population). Next: fun with the 9i dictionary views.

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• "Guiding" a Domain Expert to Retire from Programming

  - by James Kolpack

  I've got a friend who does IT at a local non-profit where they're using a custom web application which is no longer supported by the company who built it. (out of business, support was too expensive, I'm not sure...) Development on this app started around 10+ years ago so the technologies being harnessed are pretty out of date now - classic asp using vbscript and SQL Server 2000. The application domain is in the realm of government bookkeeping - so even though the development team is long gone, there are often new requirements of this software. Enter the... The domain expert. This is an middle aged accounting whiz without much (or any?) prior development experience. He studied the pages, code and queries and learned how to ape the style of the original team which, believe me, is mediocre at best. He's very clever and very tenacious but has no experience in software beyond what he's picked up from this app. Otherwise, he's a pleasant guy to talk to and definitely knows his domain. My friend in IT, and probably his superiors in the company, want him out of the code. They view him as wasting his expertise on coding tasks he shouldn't be doing. My friend got me involved with a few small contracts which I handled without much problem - other than somewhat of a communication barrier with the domain expert. He explained the requirements very quickly, assuming prior knowledge of the domain which I do not have. This is partially his normal style, and I think maybe a bit of resentment from my involvement. So, I think he feels like the owner of the code and has entrenched himself in a development position. So... his coding technique. One of his latest endeavors was to make a page that only he could reach (theoretically - the security model for the system is wretched) where he can enter a raw SQL query, run it, and save the query to run again later. A report that I worked on had been originally implemented by him using 6 distinct queries, 3 or 4 temp tables to coordinate the data between the queries, and the final result obtained by importing the data from the final query into Access and doing a pivot and some formatting. It worked - well, some of the results were incorrect - but at what a cost! (I implemented the report in a single query with at least 1/10th the amount of code.) He edits code in notepad. He doesn't seem to know about online reference material for the languages. I recently read an article on Dr. Dobbs titled "What Makes Bad Programmers Different" - and instantly thought of our domain expert. From the article: Their code is large, messy, and bug laden. They have very superficial knowledge of their problem domain and their tools. Their code has a lot of copy/paste and they have very little interest in techniques that reduce it. The fail to account for edge cases, while inefficiently dealing with the general case. They never have time to comment their code or break it into smaller pieces. Empirical evidence plays no little role in their decisions. 5.5 out of 6. My friend is wanting me to argue the case to their management - specifically, I got this email from their manager to respond to: ...Also, I need to talk to you about what effect there is from Domain Expert continuing to make edits to the live environment. If that is a problem for you I need to know so I can have his access blocked. Some examples would help. In my opinion, from a technical standpoint, it's dangerous to have him making changes without any oversight. On the other hand, I'm just doing one-off contracts at this point and don't have much desire to get involved deeply enough that I'm essentially arguing as one of the Bobs from Office Space. I'd like to help my friend out - but I feel like I'm getting in the middle of a political battle. More importantly - if I do get involved and suggest that his editing privileges be removed, it needs to be handled carefully so that doesn't feel belittled. He is beyond a doubt the foremost expert on this system. I'm hoping this is familiar territory for some other stackechangers, because I'm feeling a little bewildered. How should I respond? Should I argue that he shouldn't be allowed to touch the code? Should I phrase it as "no single developer, no matter how experienced, should be working on production code unchecked"? Should I argue to keep him involved with the code, but with a review process? Should I say "glad I could help, but uh, I'm busy now!" Other options? Thanks a bunch!

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• Guide to reduce TFS database growth using the Test Attachment Cleaner

  - by terje

  Recently there has been several reports on TFS databases growing too fast and growing too big.  Notable this has been observed when one has started to use more features of the Testing system.  Also, the TFS 2010 handles test results differently from TFS 2008, and this leads to more data stored in the TFS databases. As a consequence of this there has been released some tools to remove unneeded data in the database, and also some fixes to correct for bugs which has been found and corrected during this process.  Further some preventive practices and maintenance rules should be adopted. A lot of people have blogged about this, among these are: Anu’s very important blog post here describes both the problem and solutions to handle it.  She describes both the Test Attachment Cleaner tool, and also some QFE/CU releases to fix some underlying bugs which prevented the tool from being fully effective. Brian Harry’s blog post here describes the problem too This forum thread describes the problem with some solution hints. Ravi Shanker’s blog post here describes best practices on solving this (TBP) Grant Holidays blogpost here describes strategies to use the Test Attachment Cleaner both to detect space problems and how to rectify them.   The problem can be divided into the following areas: Publishing of test results from builds Publishing of manual test results and their attachments in particular Publishing of deployment binaries for use during a test run Bugs in SQL server preventing total cleanup of data (All the published data above is published into the TFS database as attachments.) The test results will include all data being collected during the run.  Some of this data can grow rather large, like IntelliTrace logs and video recordings.   Also the pushing of binaries which happen for automated test runs, including tests run during a build using code coverage which will include all the files in the deployment folder, contributes a lot to the size of the attached data.   In order to handle this systematically, I have set up a 3-stage process: Find out if you have a database space issue Set up your TFS server to minimize potential database issues If you have the “problem”, clean up the database and otherwise keep it clean   Analyze the data Are your database( s) growing ?  Are unused test results growing out of proportion ? To find out about this you need to query your TFS database for some of the information, and use the Test Attachment Cleaner (TAC) to obtain some  more detailed information. If you don’t have too many databases you can use the SQL Server reports from within the Management Studio to analyze the database and table sizes. Or, you can use a set of queries . I find queries often faster to use because I can tweak them the way I want them.  But be aware that these queries are non-documented and non-supported and may change when the product team wants to change them. If you have multiple Project Collections, find out which might have problems: (Disclaimer: The queries below work on TFS 2010. They will not work on Dev-11, since the table structure have been changed.  I will try to update them for Dev-11 when it is released.) Open a SQL Management Studio session onto the SQL Server where you have your TFS Databases. Use the query below to find the Project Collection databases and their sizes, in descending size order.  use master select DB_NAME(database_id) AS DBName, (size/128) SizeInMB FROM sys.master_files where type=0 and substring(db_name(database_id),1,4)='Tfs_' and DB_NAME(database_id)<>'Tfs_Configuration' order by size desc Doing this on one of our SQL servers gives the following results: It is pretty easy to see on which collection to start the work   Find out which tables are possibly too large Keep a special watch out for the Tfs_Attachment table. Use the script at the bottom of Grant’s blog to find the table sizes in descending size order. In our case we got this result: From Grant’s blog we learnt that the tbl_Content is in the Version Control category, so the major only big issue we have here is the tbl_AttachmentContent.   Find out which team projects have possibly too large attachments In order to use the TAC to find and eventually delete attachment data we need to find out which team projects have these attachments. The team project is a required parameter to the TAC. Use the following query to find this, replace the collection database name with whatever applies in your case:   use Tfs_DefaultCollection select p.projectname, sum(a.compressedlength)/1024/1024 as sizeInMB from dbo.tbl_Attachment as a inner join tbl_testrun as tr on a.testrunid=tr.testrunid inner join tbl_project as p on p.projectid=tr.projectid group by p.projectname order by sum(a.compressedlength) desc In our case we got this result (had to remove some names), out of more than 100 team projects accumulated over quite some years: As can be seen here it is pretty obvious the “Byggtjeneste – Projects” are the main team project to take care of, with the ones on lines 2-4 as the next ones.  Check which attachment types takes up the most space It can be nice to know which attachment types takes up the space, so run the following query: use Tfs_DefaultCollection select a.attachmenttype, sum(a.compressedlength)/1024/1024 as sizeInMB from dbo.tbl_Attachment as a inner join tbl_testrun as tr on a.testrunid=tr.testrunid inner join tbl_project as p on p.projectid=tr.projectid group by a.attachmenttype order by sum(a.compressedlength) desc We then got this result: From this it is pretty obvious that the problem here is the binary files, as also mentioned in Anu’s blog. Check which file types, by their extension, takes up the most space Run the following query use Tfs_DefaultCollection select SUBSTRING(filename,len(filename)-CHARINDEX('.',REVERSE(filename))+2,999)as Extension, sum(compressedlength)/1024 as SizeInKB from tbl_Attachment group by SUBSTRING(filename,len(filename)-CHARINDEX('.',REVERSE(filename))+2,999) order by sum(compressedlength) desc This gives a result like this:   Now you should have collected enough information to tell you what to do – if you got to do something, and some of the information you need in order to set up your TAC settings file, both for a cleanup and for scheduled maintenance later.    Get your TFS server and environment properly set up Even if you have got the problem or if have yet not got the problem, you should ensure the TFS server is set up so that the risk of getting into this problem is minimized.  To ensure this you should install the following set of updates and components. The assumption is that your TFS Server is at SP1 level. Install the QFE for KB2608743 – which also contains detailed instructions on its use, download from here. The QFE changes the default settings to not upload deployed binaries, which are used in automated test runs. Binaries will still be uploaded if: Code coverage is enabled in the test settings. You change the UploadDeploymentItem to true in the testsettings file. Be aware that this might be reset back to false by another user which haven't installed this QFE. The hotfix should be installed to The build servers (the build agents) The machine hosting the Test Controller Local development computers (Visual Studio) Local test computers (MTM) It is not required to install it to the TFS Server, test agents or the build controller – it has no effect on these programs. If you use the SQL Server 2008 R2 you should also install the CU 10 (or later).  This CU fixes a potential problem of hanging “ghost” files.  This seems to happen only in certain trigger situations, but to ensure it doesn’t bite you, it is better to make sure this CU is installed. There is no such CU for SQL Server 2008 pre-R2 Work around:  If you suspect hanging ghost files, they can be – with some mental effort, deduced from the ghost counters using the following SQL query: use master SELECT DB_NAME(database_id) as 'database',OBJECT_NAME(object_id) as 'objectname', index_type_desc,ghost_record_count,version_ghost_record_count,record_count,avg_record_size_in_bytes FROM sys.dm_db_index_physical_stats (DB_ID(N'<DatabaseName>'), OBJECT_ID(N'<TableName>'), NULL, NULL , 'DETAILED') The problem is a stalled ghost cleanup process.  Restarting the SQL server after having stopped all components that depends on it, like the TFS Server and SPS services – that is all applications that connect to the SQL server. Then restart the SQL server, and finally start up all dependent processes again.  (I would guess a complete server reboot would do the trick too.) After this the ghost cleanup process will run properly again. The fix will come in the next CU cycle for SQL Server R2 SP1.  The R2 pre-SP1 and R2 SP1 have separate maintenance cycles, and are maintained individually. Each have its own set of CU’s. When it comes I will add the link here to that CU. The "hanging ghost file” issue came up after one have run the TAC, and deleted enourmes amount of data.  The SQL Server can get into this hanging state (without the QFE) in certain cases due to this. And of course, install and set up the Test Attachment Cleaner command line power tool.  This should be done following some guidelines from Ravi Shanker: “When you run TAC, ensure that you are deleting small chunks of data at regular intervals (say run TAC every night at 3AM to delete data that is between age 730 to 731 days) – this will ensure that small amounts of data are being deleted and SQL ghosted record cleanup can catch up with the number of deletes performed. “ This rule minimizes the risk of the ghosted hang problem to occur, and further makes it easier for the SQL server ghosting process to work smoothly. “Run DBCC SHRINKDB post the ghosted records are cleaned up to physically reclaim the space on the file system” This is the last step in a 3 step process of removing SQL server data. First they are logically deleted. Then they are cleaned out by the ghosting process, and finally removed using the shrinkdb command. Cleaning out the attachments The TAC is run from the command line using a set of parameters and controlled by a settingsfile.  The parameters point out a server uri including the team project collection and also point at a specific team project. So in order to run this for multiple team projects regularly one has to set up a script to run the TAC multiple times, once for each team project.  When you install the TAC there is a very useful readme file in the same directory. When the deployment binaries are published to the TFS server, ALL items are published up from the deployment folder. That often means much more files than you would assume are necessary. This is a brute force technique. It works, but you need to take care when cleaning up. Grant has shown how their settings file looks in his blog post, removing all attachments older than 180 days , as long as there are no active workitems connected to them. This setting can be useful to clean out all items, both in a clean-up once operation, and in a general There are two scenarios we need to consider: Cleaning up an existing overgrown database Maintaining a server to avoid an overgrown database using scheduled TAC   1. Cleaning up a database which has grown too big due to these attachments. This job is a “Once” job.  We do this once and then move on to make sure it won’t happen again, by taking the actions in 2) below.  In this scenario you should only consider the large files. Your goal should be to simply reduce the size, and don’t bother about  the smaller stuff. That can be left a scheduled TAC cleanup ( 2 below). Here you can use a very general settings file, and just remove the large attachments, or you can choose to remove any old items.  Grant’s settings file is an example of the last one.  A settings file to remove only large attachments could look like this: <!-- Scenario : Remove large files --> <DeletionCriteria> <TestRun /> <Attachment> <SizeInMB GreaterThan="10" /> </Attachment> </DeletionCriteria> Or like this: If you want only to remove dll’s and pdb’s about that size, add an Extensions-section.  Without that section, all extensions will be deleted. <!-- Scenario : Remove large files of type dll's and pdb's --> <DeletionCriteria> <TestRun /> <Attachment> <SizeInMB GreaterThan="10" /> <Extensions> <Include value="dll" /> <Include value="pdb" /> </Extensions> </Attachment> </DeletionCriteria> Before you start up your scheduled maintenance, you should clear out all older items. 2. Scheduled maintenance using the TAC If you run a schedule every night, and remove old items, and also remove them in small batches.  It is important to run this often, like every night, in order to keep the number of deleted items low. That way the SQL ghost process works better. One approach could be to delete all items older than some number of days, let’s say 180 days. This could be combined with restricting it to keep attachments with active or resolved bugs.  Doing this every night ensures that only small amounts of data is deleted. <!-- Scenario : Remove old items except if they have active or resolved bugs --> <DeletionCriteria> <TestRun> <AgeInDays OlderThan="180" /> </TestRun> <Attachment /> <LinkedBugs> <Exclude state="Active" /> <Exclude state="Resolved"/> </LinkedBugs> </DeletionCriteria> In my experience there are projects which are left with active or resolved workitems, akthough no further work is done.  It can be wise to have a cleanup process with no restrictions on linked bugs at all. Note that you then have to remove the whole LinkedBugs section. A approach which could work better here is to do a two step approach, use the schedule above to with no LinkedBugs as a sweeper cleaning task taking away all data older than you could care about.  Then have another scheduled TAC task to take out more specifically attachments that you are not likely to use. This task could be much more specific, and based on your analysis clean out what you know is troublesome data. <!-- Scenario : Remove specific files early --> <DeletionCriteria> <TestRun > <AgeInDays OlderThan="30" /> </TestRun> <Attachment> <SizeInMB GreaterThan="10" /> <Extensions> <Include value="iTrace"/> <Include value="dll"/> <Include value="pdb"/> <Include value="wmv"/> </Extensions> </Attachment> <LinkedBugs> <Exclude state="Active" /> <Exclude state="Resolved" /> </LinkedBugs> </DeletionCriteria> The readme document for the TAC says that it recognizes “internal” extensions, but it does recognize any extension. To run the tool do the following command: tcmpt attachmentcleanup /collection:your_tfs_collection_url /teamproject:your_team_project /settingsfile:path_to_settingsfile /outputfile:%temp%/teamproject.tcmpt.log /mode:delete   Shrinking the database You could run a shrink database command after the TAC has run in cases where there are a lot of data being deleted.  In this case you SHOULD do it, to free up all that space.  But, after the shrink operation you should do a rebuild indexes, since the shrink operation will leave the database in a very fragmented state, which will reduce performance. Note that you need to rebuild indexes, reorganizing is not enough. For smaller amounts of data you should NOT shrink the database, since the data will be reused by the SQL server when it need to add more records.  In fact, it is regarded as a bad practice to shrink the database regularly.  So on a daily maintenance schedule you should NOT shrink the database. To shrink the database you do a DBCC SHRINKDATABASE command, and then follow up with a DBCC INDEXDEFRAG afterwards.  I find the easiest way to do this is to create a SQL Maintenance plan including the Shrink Database Task and the Rebuild Index Task and just execute it when you need to do this.

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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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• More CPU cores may not always lead to better performance – MAXDOP and query memory distribution in spotlight

  - by sqlworkshops

  More hardware normally delivers better performance, but there are exceptions where it can hinder performance. Understanding these exceptions and working around it is a major part of SQL Server performance tuning.   When a memory allocating query executes in parallel, SQL Server distributes memory to each task that is executing part of the query in parallel. In our example the sort operator that executes in parallel divides the memory across all tasks assuming even distribution of rows. Common memory allocating queries are that perform Sort and do Hash Match operations like Hash Join or Hash Aggregation or Hash Union.   In reality, how often are column values evenly distributed, think about an example; are employees working for your company distributed evenly across all the Zip codes or mainly concentrated in the headquarters? What happens when you sort result set based on Zip codes? Do all products in the catalog sell equally or are few products hot selling items?   One of my customers tested the below example on a 24 core server with various MAXDOP settings and here are the results:MAXDOP 1: CPU time = 1185 ms, elapsed time = 1188 msMAXDOP 4: CPU time = 1981 ms, elapsed time = 1568 msMAXDOP 8: CPU time = 1918 ms, elapsed time = 1619 msMAXDOP 12: CPU time = 2367 ms, elapsed time = 2258 msMAXDOP 16: CPU time = 2540 ms, elapsed time = 2579 msMAXDOP 20: CPU time = 2470 ms, elapsed time = 2534 msMAXDOP 0: CPU time = 2809 ms, elapsed time = 2721 ms - all 24 cores.In the above test, when the data was evenly distributed, the elapsed time of parallel query was always lower than serial query.   Why does the query get slower and slower with more CPU cores / higher MAXDOP? Maybe you can answer this question after reading the article; let me know: [email protected].   Well you get the point, let’s see an example.   The best way to learn is to practice. To create the below tables and reproduce the behavior, join the mailing list by using this link: www.sqlworkshops.com/ml and I will send you the table creation script.   Let’s update the Employees table with 49 out of 50 employees located in Zip code 2001. update Employees set Zip = EmployeeID / 400 + 1 where EmployeeID % 50 = 1 update Employees set Zip = 2001 where EmployeeID % 50 != 1 go update statistics Employees with fullscan go   Let’s create the temporary table #FireDrill with all possible Zip codes. drop table #FireDrill go create table #FireDrill (Zip int primary key) insert into #FireDrill select distinct Zip from Employees update statistics #FireDrill with fullscan go  Let’s execute the query serially with MAXDOP 1. --Example provided by www.sqlworkshops.com --Execute query with uneven Zip code distribution --First serially with MAXDOP 1 set statistics time on go declare @EmployeeID int, @EmployeeName varchar(48),@zip int select @EmployeeName = e.EmployeeName, @zip = e.Zip from Employees e       inner join #FireDrill fd on (e.Zip = fd.Zip)       order by e.Zip option (maxdop 1) goThe query took 1011 ms to complete.   The execution plan shows the 77816 KB of memory was granted while the estimated rows were 799624.  No Sort Warnings in SQL Server Profiler.  Now let’s execute the query in parallel with MAXDOP 0. --Example provided by www.sqlworkshops.com --Execute query with uneven Zip code distribution --In parallel with MAXDOP 0 set statistics time on go declare @EmployeeID int, @EmployeeName varchar(48),@zip int select @EmployeeName = e.EmployeeName, @zip = e.Zip from Employees e       inner join #FireDrill fd on (e.Zip = fd.Zip)       order by e.Zip option (maxdop 0) go The query took 1912 ms to complete.  The execution plan shows the 79360 KB of memory was granted while the estimated rows were 799624.  The estimated number of rows between serial and parallel plan are the same. The parallel plan has slightly more memory granted due to additional overhead. Sort properties shows the rows are unevenly distributed over the 4 threads.   Sort Warnings in SQL Server Profiler.   Intermediate Summary: The reason for the higher duration with parallel plan was sort spill. This is due to uneven distribution of employees over Zip codes, especially concentration of 49 out of 50 employees in Zip code 2001. Now let’s update the Employees table and distribute employees evenly across all Zip codes.   update Employees set Zip = EmployeeID / 400 + 1 go update statistics Employees with fullscan go  Let’s execute the query serially with MAXDOP 1. --Example provided by www.sqlworkshops.com --Execute query with uneven Zip code distribution --Serially with MAXDOP 1 set statistics time on go declare @EmployeeID int, @EmployeeName varchar(48),@zip int select @EmployeeName = e.EmployeeName, @zip = e.Zip from Employees e       inner join #FireDrill fd on (e.Zip = fd.Zip)       order by e.Zip option (maxdop 1) go   The query took 751 ms to complete.  The execution plan shows the 77816 KB of memory was granted while the estimated rows were 784707.  No Sort Warnings in SQL Server Profiler.   Now let’s execute the query in parallel with MAXDOP 0. --Example provided by www.sqlworkshops.com --Execute query with uneven Zip code distribution --In parallel with MAXDOP 0 set statistics time on go declare @EmployeeID int, @EmployeeName varchar(48),@zip int select @EmployeeName = e.EmployeeName, @zip = e.Zip from Employees e       inner join #FireDrill fd on (e.Zip = fd.Zip)       order by e.Zip option (maxdop 0) go The query took 661 ms to complete.  The execution plan shows the 79360 KB of memory was granted while the estimated rows were 784707.  Sort properties shows the rows are evenly distributed over the 4 threads. No Sort Warnings in SQL Server Profiler.    Intermediate Summary: When employees were distributed unevenly, concentrated on 1 Zip code, parallel sort spilled while serial sort performed well without spilling to tempdb. When the employees were distributed evenly across all Zip codes, parallel sort and serial sort did not spill to tempdb. This shows uneven data distribution may affect the performance of some parallel queries negatively. For detailed discussion of memory allocation, refer to webcasts available at www.sqlworkshops.com/webcasts.     Some of you might conclude from the above execution times that parallel query is not faster even when there is no spill. Below you can see when we are joining limited amount of Zip codes, parallel query will be fasted since it can use Bitmap Filtering.   Let’s update the Employees table with 49 out of 50 employees located in Zip code 2001. update Employees set Zip = EmployeeID / 400 + 1 where EmployeeID % 50 = 1 update Employees set Zip = 2001 where EmployeeID % 50 != 1 go update statistics Employees with fullscan go  Let’s create the temporary table #FireDrill with limited Zip codes. drop table #FireDrill go create table #FireDrill (Zip int primary key) insert into #FireDrill select distinct Zip       from Employees where Zip between 1800 and 2001 update statistics #FireDrill with fullscan go  Let’s execute the query serially with MAXDOP 1. --Example provided by www.sqlworkshops.com --Execute query with uneven Zip code distribution --Serially with MAXDOP 1 set statistics time on go declare @EmployeeID int, @EmployeeName varchar(48),@zip int select @EmployeeName = e.EmployeeName, @zip = e.Zip from Employees e       inner join #FireDrill fd on (e.Zip = fd.Zip)       order by e.Zip option (maxdop 1) go The query took 989 ms to complete.  The execution plan shows the 77816 KB of memory was granted while the estimated rows were 785594. No Sort Warnings in SQL Server Profiler.  Now let’s execute the query in parallel with MAXDOP 0. --Example provided by www.sqlworkshops.com --Execute query with uneven Zip code distribution --In parallel with MAXDOP 0 set statistics time on go declare @EmployeeID int, @EmployeeName varchar(48),@zip int select @EmployeeName = e.EmployeeName, @zip = e.Zip from Employees e       inner join #FireDrill fd on (e.Zip = fd.Zip)       order by e.Zip option (maxdop 0) go The query took 1799 ms to complete.  The execution plan shows the 79360 KB of memory was granted while the estimated rows were 785594.  Sort Warnings in SQL Server Profiler.    The estimated number of rows between serial and parallel plan are the same. The parallel plan has slightly more memory granted due to additional overhead.  Intermediate Summary: The reason for the higher duration with parallel plan even with limited amount of Zip codes was sort spill. This is due to uneven distribution of employees over Zip codes, especially concentration of 49 out of 50 employees in Zip code 2001.   Now let’s update the Employees table and distribute employees evenly across all Zip codes. update Employees set Zip = EmployeeID / 400 + 1 go update statistics Employees with fullscan go Let’s execute the query serially with MAXDOP 1. --Example provided by www.sqlworkshops.com --Execute query with uneven Zip code distribution --Serially with MAXDOP 1 set statistics time on go declare @EmployeeID int, @EmployeeName varchar(48),@zip int select @EmployeeName = e.EmployeeName, @zip = e.Zip from Employees e       inner join #FireDrill fd on (e.Zip = fd.Zip)       order by e.Zip option (maxdop 1) go The query took 250  ms to complete.  The execution plan shows the 9016 KB of memory was granted while the estimated rows were 79973.8.  No Sort Warnings in SQL Server Profiler.  Now let’s execute the query in parallel with MAXDOP 0.  --Example provided by www.sqlworkshops.com --Execute query with uneven Zip code distribution --In parallel with MAXDOP 0 set statistics time on go declare @EmployeeID int, @EmployeeName varchar(48),@zip int select @EmployeeName = e.EmployeeName, @zip = e.Zip from Employees e       inner join #FireDrill fd on (e.Zip = fd.Zip)       order by e.Zip option (maxdop 0) go The query took 85 ms to complete.  The execution plan shows the 13152 KB of memory was granted while the estimated rows were 784707.  No Sort Warnings in SQL Server Profiler.    Here you see, parallel query is much faster than serial query since SQL Server is using Bitmap Filtering to eliminate rows before the hash join.   Parallel queries are very good for performance, but in some cases it can hinder performance. If one identifies the reason for these hindrances, then it is possible to get the best out of parallelism. I covered many aspects of monitoring and tuning parallel queries in webcasts (www.sqlworkshops.com/webcasts) and articles (www.sqlworkshops.com/articles). I suggest you to watch the webcasts and read the articles to better understand how to identify and tune parallel query performance issues.   Summary: One has to avoid sort spill over tempdb and the chances of spills are higher when a query executes in parallel with uneven data distribution. Parallel query brings its own advantage, reduced elapsed time and reduced work with Bitmap Filtering. So it is important to understand how to avoid spills over tempdb and when to execute a query in parallel.   I explain these concepts with detailed examples in my webcasts (www.sqlworkshops.com/webcasts), I recommend you to watch them. The best way to learn is to practice. To create the above tables and reproduce the behavior, join the mailing list at www.sqlworkshops.com/ml and I will send you the relevant SQL Scripts.   Register for the upcoming 3 Day Level 400 Microsoft SQL Server 2008 and SQL Server 2005 Performance Monitoring & Tuning Hands-on Workshop in London, United Kingdom during March 15-17, 2011, click here to register / Microsoft UK TechNet.These are hands-on workshops with a maximum of 12 participants and not lectures. For consulting engagements click here.   Disclaimer and copyright information:This article refers to organizations and products that may be the trademarks or registered trademarks of their various owners. Copyright of this article belongs to R Meyyappan / www.sqlworkshops.com. You may freely use the ideas and concepts discussed in this article with acknowledgement (www.sqlworkshops.com), but you may not claim any of it as your own work. This article is for informational purposes only; you use any of the suggestions given here entirely at your own risk.   Register for the upcoming 3 Day Level 400 Microsoft SQL Server 2008 and SQL Server 2005 Performance Monitoring & Tuning Hands-on Workshop in London, United Kingdom during March 15-17, 2011, click here to register / Microsoft UK TechNet.These are hands-on workshops with a maximum of 12 participants and not lectures. For consulting engagements click here.   R Meyyappan [email protected] LinkedIn: http://at.linkedin.com/in/rmeyyappan  

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• 10 Essential Tools for building ASP.NET Websites

  - by Stephen Walther

  I recently put together a simple public website created with ASP.NET for my company at Superexpert.com. I was surprised by the number of free tools that I ended up using to put together the website. Therefore, I thought it would be interesting to create a list of essential tools for building ASP.NET websites. These tools work equally well with both ASP.NET Web Forms and ASP.NET MVC. Performance Tools After reading Steve Souders two (very excellent) books on front-end website performance High Performance Web Sites and Even Faster Web Sites, I have been super sensitive to front-end website performance. According to Souders’ Performance Golden Rule: “Optimize front-end performance first, that's where 80% or more of the end-user response time is spent” You can use the tools below to reduce the size of the images, JavaScript files, and CSS files used by an ASP.NET application. 1. Sprite and Image Optimization Framework CSS sprites were first described in an article written for A List Apart entitled CSS sprites: Image Slicing’s Kiss of Death. When you use sprites, you combine multiple images used by a website into a single image. Next, you use CSS trickery to display particular sub-images from the combined image in a webpage. The primary advantage of sprites is that they reduce the number of requests required to display a webpage. Requesting a single large image is faster than requesting multiple small images. In general, the more resources – images, JavaScript files, CSS files – that must be moved across the wire, the slower your website. However, most people avoid using sprites because they require a lot of work. You need to combine all of the images and write just the right CSS rules to display the sub-images. The Microsoft Sprite and Image Optimization Framework enables you to avoid all of this work. The framework combines the images for you automatically. Furthermore, the framework includes an ASP.NET Web Forms control and an ASP.NET MVC helper that makes it easy to display the sub-images. You can download the Sprite and Image Optimization Framework from CodePlex at http://aspnet.codeplex.com/releases/view/50869. The Sprite and Image Optimization Framework was written by Morgan McClean who worked in the office next to mine at Microsoft. Morgan was a scary smart Intern from Canada and we discussed the Framework while he was building it (I was really excited to learn that he was working on it). Morgan added some great advanced features to this framework. For example, the Sprite and Image Optimization Framework supports something called image inlining. When you use image inlining, the actual image is stored in the CSS file. Here’s an example of what image inlining looks like: .Home_StephenWalther_small-jpg { width:75px; height:100px; background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAEsAAABkCAIAAABB1lpeAAAAB GdBTUEAALGOfPtRkwAAACBjSFJNAACHDwAAjA8AAP1SAACBQAAAfXkAAOmLAAA85QAAGcxzPIV3AAAKL s+zNfREAAAAASUVORK5CYII=) no-repeat 0% 0%; } The actual image (in this case a picture of me that is displayed on the home page of the Superexpert.com website) is stored in the CSS file. If you visit the Superexpert.com website then very few separate images are downloaded. For example, all of the images with a red border in the screenshot below take advantage of CSS sprites: Unfortunately, there are some significant Gotchas that you need to be aware of when using the Sprite and Image Optimization Framework. There are workarounds for these Gotchas. I plan to write about these Gotchas and workarounds in a future blog entry. 2. Microsoft Ajax Minifier Whenever possible you should combine, minify, compress, and cache with a far future header all of your JavaScript and CSS files. The Microsoft Ajax Minifier makes it easy to minify JavaScript and CSS files. Don’t confuse minification and compression. You need to do both. According to Souders, you can reduce the size of a JavaScript file by an additional 20% (on average) by minifying a JavaScript file after you compress the file. When you minify a JavaScript or CSS file, you use various tricks to reduce the size of the file before you compress the file. For example, you can minify a JavaScript file by replacing long JavaScript variables names with short variables names and removing unnecessary white space and comments. You can minify a CSS file by doing such things as replacing long color names such as #ffffff with shorter equivalents such as #fff. The Microsoft Ajax Minifier was created by Microsoft employee Ron Logan. Internally, this tool was being used by several large Microsoft websites. We also used the tool heavily on the ASP.NET team. I convinced Ron to publish the tool on CodePlex so that everyone in the world could take advantage of it. You can download the tool from the ASP.NET Ajax website and read documentation for the tool here. I created the installer for the Microsoft Ajax Minifier. When creating the installer, I also created a Visual Studio build task to make it easy to minify all of your JavaScript and CSS files whenever you do a build within Visual Studio automatically. Read the Ajax Minifier Quick Start to learn how to configure the build task. 3. ySlow The ySlow tool is a free add-on for Firefox created by Yahoo that enables you to test the front-end of your website. For example, here are the current test results for the Superexpert.com website: The Superexpert.com website has an overall score of B (not perfect but not bad). The ySlow tool is not perfect. For example, the Superexpert.com website received a failing grade of F for not using a Content Delivery Network even though the website using the Microsoft Ajax Content Delivery Network for JavaScript files such as jQuery. Uptime After publishing a website live to the world, you want to ensure that the website does not encounter any issues and that it stays live. I use the following tools to monitor the Superexpert.com website now that it is live. 4. ELMAH ELMAH stands for Error Logging Modules and Handlers for ASP.NET. ELMAH enables you to record any errors that happen at your website so you can review them in the future. You can download ELMAH for free from the ELMAH project website. ELMAH works great with both ASP.NET Web Forms and ASP.NET MVC. You can configure ELMAH to store errors in a number of different stores including XML files, the Event Log, an Access database, a SQL database, an Oracle database, or in computer RAM. You also can configure ELMAH to email error messages to you when they happen. By default, you can access ELMAH by requesting the elmah.axd page from a website with ELMAH installed. Here’s what the elmah page looks like from the Superexpert.com website (this page is password-protected because secret information can be revealed in an error message): If you click on a particular error message, you can view the original Yellow Screen ASP.NET error message (even when the error message was never displayed to the actual user). I installed ELMAH by taking advantage of the new package manager for ASP.NET named NuGet (originally named NuPack). You can read the details about NuGet in the following blog entry by Scott Guthrie. You can download NuGet from CodePlex. 5. Pingdom I use Pingdom to verify that the Superexpert.com website is always up. You can sign up for Pingdom by visiting Pingdom.com. You can use Pingdom to monitor a single website for free. At the Pingdom website, you configure the frequency that your website gets pinged. I verify that the Superexpert.com website is up every 5 minutes. I have the Pingdom service verify that it can retrieve the string “Contact Us” from the website homepage. If your website goes down, you can configure Pingdom so that it sends an email, Twitter, SMS, or iPhone alert. I use the Pingdom iPhone app which looks like this: 6. Host Tracker If your website does go down then you need some way of determining whether it is a problem with your local network or if your website is down for everyone. I use a website named Host-Tracker.com to check how badly a website is down. Here’s what the Host-Tracker website displays for the Superexpert.com website when the website can be successfully pinged from everywhere in the world: Notice that Host-Tracker pinged the Superexpert.com website from 68 locations including Roubaix, France and Scranton, PA. Debugging I mean debugging in the broadest possible sense. I use the following tools when building a website to verify that I have not made a mistake. 7. HTML Spell Checker Why doesn’t Visual Studio have a built-in spell checker? Don’t know – I’ve always found this mysterious. Fortunately, however, a former member of the ASP.NET team wrote a free spell checker that you can use with your ASP.NET pages. I find a spell checker indispensible. It is easy to delude yourself that you are capable of perfect spelling. I’m always super embarrassed when I actually run the spell checking tool and discover all of my spelling mistakes. The fastest way to add the HTML Spell Checker extension to Visual Studio is to select the menu option Tools, Extension Manager within Visual Studio. Click on Online Gallery and search for HTML Spell Checker: 8. IIS SEO Toolkit If people cannot find your website through Google then you should not even bother to create it. Microsoft has a great extension for IIS named the IIS Search Engine Optimization Toolkit that you can use to identify issue with your website that would hurt its page rank. You also can use this tool to quickly create a sitemap for your website that you can submit to Google or Bing. You can even generate the sitemap for an ASP.NET MVC website. Here’s what the report overview for the Superexpert.com website looks like: Notice that the Sueprexpert.com website had plenty of violations. For example, there are 65 cases in which a page has a broken hyperlink. You can drill into these violations to identity the exact page and location where these violations occur. 9. LinqPad If your ASP.NET website accesses a database then you should be using LINQ to Entities with the Entity Framework. Using LINQ involves some magic. LINQ queries written in C# get converted into SQL queries for you. If you are not careful about how you write your LINQ queries, you could unintentionally build a really badly performing website. LinqPad is a free tool that enables you to experiment with your LINQ queries. It even works with Microsoft SQL CE 4 and Azure. You can use LinqPad to execute a LINQ to Entities query and see the results. You also can use it to see the resulting SQL that gets executed against the database: 10. .NET Reflector I use .NET Reflector daily. The .NET Reflector tool enables you to take any assembly and disassemble the assembly into C# or VB.NET code. You can use .NET Reflector to see the “Source Code” of an assembly even when you do not have the actual source code. You can download a free version of .NET Reflector from the Redgate website. I use .NET Reflector primarily to help me understand what code is doing internally. For example, I used .NET Reflector with the Sprite and Image Optimization Framework to better understand how the MVC Image helper works. Here’s part of the disassembled code from the Image helper class: Summary In this blog entry, I’ve discussed several of the tools that I used to create the Superexpert.com website. These are tools that I use to improve the performance, improve the SEO, verify the uptime, or debug the Superexpert.com website. All of the tools discussed in this blog entry are free. Furthermore, all of these tools work with both ASP.NET Web Forms and ASP.NET MVC. Let me know if there are any tools that you use daily when building ASP.NET websites.

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• CodePlex Daily Summary for Thursday, December 16, 2010

  CodePlex Daily Summary for Thursday, December 16, 2010Popular ReleasesSharpDropBox Client for .NET: WP7 SharpDropBox Client - 0.1 Technology Preview: I decided to go ahead and release this. It works well for simple browsing folder structure/downloading files (and login works). See samples for an example of how to use it. I am in progress with a couple other methods which aren't currently working.SQL Monitor: SQL Monitor 2.9: 1. automatically set sql for new query if a object is selected(table/sp/function/view)uComponents: uComponents v2.0.1: This release: Fixes a critical issue with IIS 6. Removes various script error issues in Internet Explorer Supports the media picker with advanced dialog and preview. uComponents is a collaborative project for creating components for Umbraco including data types, XSLT extensions, controls and more. Containing 20 data-types, 7 XSLT extension libraries, keyboard short-cuts, drag-n-drop functionality, as well as great developer utilities - uComponents is one of the must-have packages for a...SplendidCRM: SplendidCRM 5.0 Community Edition: SplendidCRM Software has adopted the GNU Affero General Public License Version 3 (AGPLv3) for its Community Edition. This release includes the full set of SQL source code in the Community Edition, something that was previously only available in the Professional and Enterprise Editions. An article on the subject of Commercial Open-Source licensing has been posted at http://www.codeproject.com/KB/architecture/splendid-guide-article6.aspx.DotSpatial: DotSpatial 12-15-2010: This release contains a few minor bug fixes and hopefully the GDAL libraries for the 3.5 x86 build actually built to the correct directory this time.DotNetNuke® Community Edition: 05.06.01 Beta: This is the initial Beta of DotNetNuke 5.6.1. See the DotNetNuke Roadmap a full list of changes in this release.MSBuild Extension Pack: December 2010: Release Blog Post The MSBuild Extension Pack December 2010 release provides a collection of over 380 MSBuild tasks. A high level summary of what the tasks currently cover includes the following: System Items: Active Directory, Certificates, COM+, Console, Date and Time, Drives, Environment Variables, Event Logs, Files and Folders, FTP, GAC, Network, Performance Counters, Registry, Services, Sound Code: Assemblies, AsyncExec, CAB Files, Code Signing, DynamicExecute, File Detokenisation, GU...Access Control Service Samples and Documentation (Labs): Samples-R3: Contains latest ACS samples (corresponding to R3 release) that show how to integrate ACS with web services, ASP.NET websites (Web Forms and MVC) and on how to interact with the ACS Management Service. The Readmes for these samples are available here.TweetSharp: TweetSharp v2.0.0.0 - Preview 5: Documentation for this release may be found at http://tweetsharp.codeplex.com/wikipage?title=UserGuide&referringTitle=Documentation. Note: This code is currently preview quality. Preview 5 ChangesMaintenance release with user reported fixes Preview 4 ChangesReintroduced fluent interface support via satellite assembly Added entities support, entity segmentation, and ITweetable/ITweeter interfaces for client development Numerous fixes reported by preview users Preview 3 ChangesNumerous ...EnhSim: EnhSim 2.2.2 ALPHA: 2.2.2 ALPHAThis release adds in the changes for 4.03a at level 85 To use this release, you must have the Microsoft Visual C++ 2010 Redistributable Package installed. This can be downloaded from http://www.microsoft.com/downloads/en/details.aspx?FamilyID=A7B7A05E-6DE6-4D3A-A423-37BF0912DB84 To use the GUI you must have the .NET 4.0 Framework installed. This can be downloaded from http://www.microsoft.com/downloads/en/details.aspx?FamilyID=9cfb2d51-5ff4-4491-b0e5-b386f32c0992 - The spirit ...Silverlight Contrib: Silverlight Contrib 2010.1.0: 2010.1.0 New FeaturesCompatibility Release for Silverlight 4 and Visual Studio 2010FlickrNet API Library: 3.1.4000: Newest release. Now contains dedicated Windows Phone 7 DLL as well as all previous DLLs. Also contains Windows Help file documentation now as standard.mojoPortal: 2.3.5.8: see release notes on mojoportal.com http://www.mojoportal.com/mojoportal-2358-released.aspx Note that we have separate deployment packages for .NET 3.5 and .NET 4.0 The deployment package downloads on this page are pre-compiled and ready for production deployment, they contain no C# source code. To download the source code see the Source Code Tab I recommend getting the latest source code using TortoiseHG, you can get the source code corresponding to this release here.Microsoft All-In-One Code Framework: Visual Studio 2010 Code Samples 2010-12-13: Code samples for Visual Studio 2010Wii Backup Fusion: Wii Backup Fusion 0.9 Beta: - Aqua or brushed metal style for Mac OS X - Shows selection count beside ID - Game list selection mode via settings - Compare Files <-> WBFS game lists - Verify game images/DVD/WBFS - WIT command line for log (via settings) - Cancel possibility for loading games process - Progress infos while loading games - Localization for dates - UTF-8 support - Shortcuts added - View game infos in browser - Transfer infos for log - All transfer routines rewritten - Extract image from image/WBFS - Support....NETTER Code Starter Pack: v1.0.beta: '.NETTER Code Starter Pack ' contains a gallery of Visual Studio 2010 solutions leveraging latest and new technologies and frameworks based on Microsoft .NET Framework. Each Visual Studio solution included here is focused to provide a very simple starting point for cutting edge development technologies and framework, using well known Northwind database (for database driven scenarios). The current release of this project includes starter samples for the following technologies: ASP.NET Dynamic...NuGet (formerly NuPack): NuGet 1.0 Release Candidate: NuGet is a free, open source developer focused package management system for the .NET platform intent on simplifying the process of incorporating third party libraries into a .NET application during development. This release is a Visual Studio 2010 extension and contains the the Package Manager Console and the Add Package Dialog. This new build targets the newer feed (http://go.microsoft.com/fwlink/?LinkID=206669) and package format. See http://nupack.codeplex.com/documentation?title=Nuspe...Free Silverlight & WPF Chart Control - Visifire: Visifire Silverlight, WPF Charts v3.6.5 Released: Hi, Today we are releasing final version of Visifire, v3.6.5 with the following new feature: * New property AutoFitToPlotArea has been introduced in DataSeries. AutoFitToPlotArea will bring bubbles inside the PlotArea in order to avoid clipping of bubbles in bubble chart. You can visit Visifire documentation to know more. http://www.visifire.com/visifirechartsdocumentation.php Also this release includes few bug fixes: * Chart threw exception while adding new Axis in Chart using Vi...PHPExcel: PHPExcel 1.7.5 Production: DonationsDonate via PayPal via PayPal. If you want to, we can also add your name / company on our Donation Acknowledgements page. PEAR channelWe now also have a full PEAR channel! Here's how to use it: New installation: pear channel-discover pear.pearplex.net pear install pearplex/PHPExcel Or if you've already installed PHPExcel before: pear upgrade pearplex/PHPExcel The official page can be found at http://pearplex.net. Want to contribute?Please refer the Contribute page.??????????: All-In-One Code Framework ??? 2010-12-10: ?????All-In-One Code Framework（??） 2010?12??????！！http://i3.codeplex.com/Project/Download/FileDownload.aspx?ProjectName=1code&DownloadId=128165 ?????release?，???????ASP.NET, WinForm, Silverlight????12?Sample Code。???，??????????sample code。 ?????：http://blog.csdn.net/sjb5201/archive/2010/12/13/6072675.aspx ??，??????MSDN????????????。 http://social.msdn.microsoft.com/Forums/zh-CN/codezhchs/threads ?????????????????，??Email ????New ProjectsAchievement Information System: AchIS is a software which documented all about student's prestigeAutoMock: AutoMock saves you time when writing unit tests by wiring up all the dependencies as mocks for the class under test.Basic samples: Basic C# samplesBCrypt.Net: A .Net port of jBCrypt implemented in C#. It uses a variant of the Blowfish encryption algorithm’s keying schedule, and introduces a work factor, which allows you to determine how expensive the hash function will be, allowing the algorithm to be "future-proof".Desafio Dot.Net: Projeto para o Desafio DotNetEDAFramework: This is a Estimation of Distribution Algorithm framework.Fluxions: Fluxions is a 3D Graphics Engine designed to make writing simple graphics or visualization projects easy. It is ideal for writing computer games or scientific type work where you need to easily prototype an idea. It includes support for writing OpenGL apps with GLUT or SDL.Guruzan.Com: Guruzan.Com is a new way to share your ideas and especially your claims.. We are about the create a next generation social network which will bring improved standarts and innovations for internet sharing. Our project includes many students from different countries...HotCold: This game loads a board of squares, of which one is randomly selected as the "HOT" square. The goal is to find the "HOT" square in the fewest clicks possible. .InSim.NET: A .NET InSim library for the racing simulator Live for Speed.Javascript Utils: JavaScript Utilitieskoppees: Mingi veebiliidesKVB-Abfahrtstafel: Die KVB-Abfahrtstafel erlaubt es, sich einige Haltestellentafeln im Netz der Kölner Verkehrsbetriebe - inklusive Störungsmeldungen - schon vor dem Verlassen des Büros/Hauses/Hotels am PC anzusehen. Besonders bei miesem Wetter eine echte Erleichterung.Lessons in PivotViewer: The Silverlight PivotViewer is a great control with a great deal of potential. However, there are a lot of questions on how to use and customize the PivotViewer. This project will attempt to answer those questions by providing a series of lessons on the PivotViewer.Liuyi: liuyiLiuyi.network: Liuyi.networkMiniDouBan: MiniDouBanN2F Yverdon Database Helper: A class to aid in performing simple database queries within N2F Yverdon. Also provides the capability to store queries for later use.N2F Yverdon Form Helper: A system that allows interaction with web forms in a fashion similar to that of ASP.NET MVC model binding.N2F Yverdon Sanitizers: A system to help ease the pain of sanitizing data. The system comes with some basic sanitizers as well as the framework necessary to enable easy development of custom sanitizers.Next Question: By Relavance: Next Question makes it easier for System Users, Administrators, Business Analysts, etc to run ad-hoc queries on any data store. Regardless of the type or location of the information, Next Question removes the need for T-SQL programmers to write explicit queries to answer businessNPicConvertDemo: azure test/demo/example projectOpenSprints: OpenSprints for WindowsPML_FahrradVerleih: PML_FahrradVerleih PMS ProjektPowerLib: PowerLib extends .NET Base Class Library functionality with algorithms and data structures. First release would be at next week.ProJect Manager Software: Project Manager Softwareqxtplatform: qxtplatformSencha Direct Stack based on ASP.NET MVC: This project focuses on creating ExtJS/Sencha Direct server stack using ASP.NET MVC.SqlExecuter: Simply run sql scripts against a SQL Server databaseSystem8: Experimental Silverlight project to help understand system 8's behavior (mehod of calibration bottom-quark tagging).TeamManager: Team management software based on silverlight application. It use PRISM and MEF to have flexible and extensible architecture.Umbraco Single Item Picker: Extention to the Umbraco, needs to pick: - Content pages, - Media items, - File System Objects, - Member Items in more "better way" additionally control returns not only item name(title) but also extended information (path, icon). WebSharper Community Samples: WebSharper Community SamplesWindows Phone 7 Charts: Charting component for Windows Phone 7 applications.Windows Phone 7 Silverlight ZXing Barcode Scanning Library: ZXing (pronounced "zebra crossing") is an open-source, multi-format 1D/2D barcode image processing library originally implemented by Google in Java. This is a Silverlight port of the csharp ZXing port created by Suraj Supekar at revision 1202 in the SVN repository. WPF RCON: WPF RCON is a RCON client for COD4 servers. It's RCON library + WPF GUI. It's developed in C#. It's far from being complete.

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• Problem setting up Master-Master Replication in MySQL

  - by Andrew

  I am attempting to setup Master-Master Replication on two MySQL database servers. I have followed the steps in this guide, but it fails in the middle of Step 4 with SHOW MASTER STATUS; It simply returns an empty set. I get the same 3 errors in both servers' logs. MySQL errors on SQL1: [ERROR] Failed to open the relay log './sql1-relay-bin.000001' (relay_log_pos 4) [ERROR] Could not find target log during relay log initialization [ERROR] Failed to initialize the master info structure MySQL Errors on SQL2: [ERROR] Failed to open the relay log './sql2-relay-bin.000001' (relay_log_pos 4) [ERROR] Could not find target log during relay log initialization [ERROR] Failed to initialize the master info structure The errors make no sense because I'm not referencing those files in any of my configurations. I'm using Ubuntu Server 10.04 x64 and my configuration files are copied below. I don't know where to go from here or how to troubleshoot this. Please help. Thanks. /etc/mysql/my.cnf on SQL1: # # The MySQL database server configuration file. # # You can copy this to one of: # - "/etc/mysql/my.cnf" to set global options, # - "~/.my.cnf" to set user-specific options. # # One can use all long options that the program supports. # Run program with --help to get a list of available options and with # --print-defaults to see which it would actually understand and use. # # For explanations see # http://dev.mysql.com/doc/mysql/en/server-system-variables.html # This will be passed to all mysql clients # It has been reported that passwords should be enclosed with ticks/quotes # escpecially if they contain "#" chars... # Remember to edit /etc/mysql/debian.cnf when changing the socket location. [client] port = 3306 socket = /var/run/mysqld/mysqld.sock # Here is entries for some specific programs # The following values assume you have at least 32M ram # This was formally known as [safe_mysqld]. Both versions are currently parsed. [mysqld_safe] socket = /var/run/mysqld/mysqld.sock nice = 0 [mysqld] # # * Basic Settings # # # * IMPORTANT # If you make changes to these settings and your system uses apparmor, you may # also need to also adjust /etc/apparmor.d/usr.sbin.mysqld. # user = mysql socket = /var/run/mysqld/mysqld.sock port = 3306 basedir = /usr datadir = /var/lib/mysql tmpdir = /tmp skip-external-locking # # Instead of skip-networking the default is now to listen only on # localhost which is more compatible and is not less secure. bind-address = <SQL1's IP> # # * Fine Tuning # key_buffer = 16M max_allowed_packet = 16M thread_stack = 192K thread_cache_size = 8 # This replaces the startup script and checks MyISAM tables if needed # the first time they are touched myisam-recover = BACKUP #max_connections = 100 #table_cache = 64 #thread_concurrency = 10 # # * Query Cache Configuration # query_cache_limit = 1M query_cache_size = 16M # # * Logging and Replication # # Both location gets rotated by the cronjob. # Be aware that this log type is a performance killer. # As of 5.1 you can enable the log at runtime! #general_log_file = /var/log/mysql/mysql.log #general_log = 1 log_error = /var/log/mysql/error.log # Here you can see queries with especially long duration #log_slow_queries = /var/log/mysql/mysql-slow.log #long_query_time = 2 #log-queries-not-using-indexes # # The following can be used as easy to replay backup logs or for replication. # note: if you are setting up a replication slave, see README.Debian about # other settings you may need to change. server-id = 1 replicate-same-server-id = 0 auto-increment-increment = 2 auto-increment-offset = 1 master-host = <SQL2's IP> master-user = slave_user master-password = "slave_password" master-connect-retry = 60 replicate-do-db = db1 log-bin= /var/log/mysql/mysql-bin.log binlog-do-db = db1 binlog-ignore-db = mysql relay-log = /var/lib/mysql/slave-relay.log relay-log-index = /var/lib/mysql/slave-relay-log.index expire_logs_days = 10 max_binlog_size = 500M # # * InnoDB # # InnoDB is enabled by default with a 10MB datafile in /var/lib/mysql/. # Read the manual for more InnoDB related options. There are many! # # * Security Features # # Read the manual, too, if you want chroot! # chroot = /var/lib/mysql/ # # For generating SSL certificates I recommend the OpenSSL GUI "tinyca". # # ssl-ca=/etc/mysql/cacert.pem # ssl-cert=/etc/mysql/server-cert.pem # ssl-key=/etc/mysql/server-key.pem [mysqldump] quick quote-names max_allowed_packet = 16M [mysql] #no-auto-rehash # faster start of mysql but no tab completition [isamchk] key_buffer = 16M # # * IMPORTANT: Additional settings that can override those from this file! # The files must end with '.cnf', otherwise they'll be ignored. # !includedir /etc/mysql/conf.d/ /etc/mysql/my.cnf on SQL2: # # The MySQL database server configuration file. # # You can copy this to one of: # - "/etc/mysql/my.cnf" to set global options, # - "~/.my.cnf" to set user-specific options. # # One can use all long options that the program supports. # Run program with --help to get a list of available options and with # --print-defaults to see which it would actually understand and use. # # For explanations see # http://dev.mysql.com/doc/mysql/en/server-system-variables.html # This will be passed to all mysql clients # It has been reported that passwords should be enclosed with ticks/quotes # escpecially if they contain "#" chars... # Remember to edit /etc/mysql/debian.cnf when changing the socket location. [client] port = 3306 socket = /var/run/mysqld/mysqld.sock # Here is entries for some specific programs # The following values assume you have at least 32M ram # This was formally known as [safe_mysqld]. Both versions are currently parsed. [mysqld_safe] socket = /var/run/mysqld/mysqld.sock nice = 0 [mysqld] # # * Basic Settings # # # * IMPORTANT # If you make changes to these settings and your system uses apparmor, you may # also need to also adjust /etc/apparmor.d/usr.sbin.mysqld. # user = mysql socket = /var/run/mysqld/mysqld.sock port = 3306 basedir = /usr datadir = /var/lib/mysql tmpdir = /tmp skip-external-locking # # Instead of skip-networking the default is now to listen only on # localhost which is more compatible and is not less secure. bind-address = <SQL2's IP> # # * Fine Tuning # key_buffer = 16M max_allowed_packet = 16M thread_stack = 192K thread_cache_size = 8 # This replaces the startup script and checks MyISAM tables if needed # the first time they are touched myisam-recover = BACKUP #max_connections = 100 #table_cache = 64 #thread_concurrency = 10 # # * Query Cache Configuration # query_cache_limit = 1M query_cache_size = 16M # # * Logging and Replication # # Both location gets rotated by the cronjob. # Be aware that this log type is a performance killer. # As of 5.1 you can enable the log at runtime! #general_log_file = /var/log/mysql/mysql.log #general_log = 1 log_error = /var/log/mysql/error.log # Here you can see queries with especially long duration #log_slow_queries = /var/log/mysql/mysql-slow.log #long_query_time = 2 #log-queries-not-using-indexes # # The following can be used as easy to replay backup logs or for replication. # note: if you are setting up a replication slave, see README.Debian about # other settings you may need to change. server-id = 2 replicate-same-server-id = 0 auto-increment-increment = 2 auto-increment-offset = 2 master-host = <SQL1's IP> master-user = slave_user master-password = "slave_password" master-connect-retry = 60 replicate-do-db = db1 log-bin= /var/log/mysql/mysql-bin.log binlog-do-db = db1 binlog-ignore-db = mysql relay-log = /var/lib/mysql/slave-relay.log relay-log-index = /var/lib/mysql/slave-relay-log.index expire_logs_days = 10 max_binlog_size = 500M # # * InnoDB # # InnoDB is enabled by default with a 10MB datafile in /var/lib/mysql/. # Read the manual for more InnoDB related options. There are many! # # * Security Features # # Read the manual, too, if you want chroot! # chroot = /var/lib/mysql/ # # For generating SSL certificates I recommend the OpenSSL GUI "tinyca". # # ssl-ca=/etc/mysql/cacert.pem # ssl-cert=/etc/mysql/server-cert.pem # ssl-key=/etc/mysql/server-key.pem [mysqldump] quick quote-names max_allowed_packet = 16M [mysql] #no-auto-rehash # faster start of mysql but no tab completition [isamchk] key_buffer = 16M # # * IMPORTANT: Additional settings that can override those from this file! # The files must end with '.cnf', otherwise they'll be ignored. # !includedir /etc/mysql/conf.d/

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• Visual Studio DataSet Designer Refresh Tables

  - by LnDCobra

  In visual studio datasource designer(The screen where you have all the UML Diagrams including relations) is there any way to refresh a table and its relations/foreign key constraints without refreshing the whole table? The way I am doing it at the moment is removing the table and adding it again. This adds all the relations and refreshes all fields. Also if I change a fields data type, is there a way to automatically refresh all the fields in the datasource? Again without deleting the table and adding it again. Reason for this is because some of my TableAdapters have quite a number of complex queries attached to them and when I remove the table the adapter gets removed as well including all its queries. I am using Visual Studio 2008 and connecting to a MySQL database.

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• Problem using SQLDMO/Vb6 against SQL2008

  - by E.J. Brennan

  I have a client, that uses SQLDMO for a portion of a custom application that was written against SQL 2000, and they recently upgraded to SQL2008. The majority of the app still runs fine (doesn't use SQLDMO), but the admin functions which rely on SQLDMO stopped working. I installed the SQL2005 backward compatibility pack, and now SQLDMO partially works, i.e. I can run "select" type queries, but any "Update" queries fail with the error message: to connect to the server you must use SQL Server management studio or sql server management objects (SMO) Any thoughts? Should the backward compatibility pack give me ALL the functionality back, or is this a known issue? BTW: I realize SQLDMO has been deprecated and will go away next release, none-the-less I need to do what I can to solve the problem at hand.

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• "Executing SQL directly; no cursor" error when using SCOPE_IDENTITY/IDENT_CURRENT

  - by Chris

  There wasn't much on google about this error, so I'm askin here. I'm switching a PHP web application from using MySQL to SQL Server 2008 (using ODBC, not php_mssql). Running queries or anything else isn't a problem, but when I try to do scope_identity (or any similar functions), I get the error "Executing SQL directly; no cursor". I'm doing this immediately after an insert, so it should still be in scope. Running the same insert statement then query for the insert ID works fine in SQL Server Management Studio. Here's my code right now (everything else in the database wrapper class works fine for other queries, so I'll assume it isn't relevant right now): function insert_id(){ return $this->query_first("SELECT SCOPE_IDENTITY() as insert_id"); } query_first being a function that returns the first result from the first field of a query (basically the equivalent of execute_scalar() on .net). The full error message: Warning: odbc_exec() [function.odbc-exec]: SQL error: [Microsoft][SQL Server Native Client 10.0][SQL Server]Executing SQL directly; no cursor., SQL state 01000 in SQLExecDirect in C:[...]\Database_MSSQL.php on line 110

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• Delphi 2010 Datasnap - Design Query

  - by Matt

  I am investigating moving a thick client SQL based Delphi application to Multi Tier thin clients, and have been looking at using Datasnap in Delphi 2010. I have worked through the White Paper written by Bob Swart and extended this further. My main question really is that I want to make the server side efficient in terms of connections and SQL Queries due to multiple queries being run and remaining open at the same time to interrogate data, can anyone point me in a direction for guidance on how to design a real world Datasnap Server application, as the demo's don't go into enough detail. Thanks Matt

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• Using Raw SQL with Doctrine

  - by Levi Hackwith

  I have some extremely complex queries that I need to use to generate a report in my application. I'm using symfony as my framework and doctrine as my ORM. My question is this: What is the best way to pass in highly-complex sql queries directly to Doctrine without converting them to the Doctrine Query Language? I've been reading about the Raw_SQL extension but it appears that you still need to pass the query in sections (like from()). Is there anything for just dumping in a bunch of raw sql commands?

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• Occasional Deadlock.

  - by Carl Robinson

  Im having trouble with a web application that will deadlock occasionally There are 3 queries involved. 2 are trying to update a table UPDATE AttendanceRoll SET ErrorFlag = 0 WHERE ContractID = @ContractID AND DATEPART(month,AttendanceDate) = DATEPART(month,@Month_Beginning) AND DATEPART(year,AttendanceDate) = DATEPART(year,@Month_Beginning) and one is trying to insert into the table INSERT INTO AttendanceRoll (AttendanceDate, ContractID, PersonID, StartTime, EndTime, Hours, AbsenceReason, UpdateCount, SplitShiftID, ModifiedBy, ModifiedDate) SELECT @P33, @P34, @P35, CONVERT(datetime,REPLACE( @P36 ,&apos;.&apos;,&apos;:&apos;)), CONVERT(datetime,REPLACE( @P37 ,&apos;.&apos;,&apos;:&apos;)), @P38, @P39, @P40, 1, @P41, GETDATE() The deadlock graph shows a kind of circular arangement of page locks and an exchange event and the 2 update queries have the same server process id. If anyone has any ideas about how I should go about solving this issue it would be most appreciated. I have the deadlock graph that I can post if anybody needs to see it. Thanks Carl R

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• Hibernate Criteria: Add restrictions to Criteria and DetachedCriteria

  - by Gilean

  Currently our queries add a variety of Restrictions to ensure the results are considered active or live. These Restrictions are used in several places/queries so a method was setup similar to public Criteria addStandardCriteria(Criteria criteria, ...) { // Add restrictions, create aliases based on parameters // and other non-trivial logic criteria.add(...); return criteria; } This has worked fine so far, but now this standard criteria needs to be added to a subquery using DetachedCriteria. Is there a way to modify this method to accept Criteria or DetachedCriteria or a Better way to add restrictions?

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• getting count(*) using createSQLQuery in hibernate?

  - by JohnSmith

  I have several sql queries that I simply want to fire at the database. I am using hibernate throughout the whole application, so i would prefer to use hibernate to call this sql queries. In the example below i want to get count + name, but cant figure out how to get that info when i use createSQLQuery(). I have seen workarounds where people only need to get out a single "count()" from the result, but in this case I am using count() + a column as ouput SELECT count(*), a.name as count FROM user a WHERE a.user_id IN (SELECT b.user_id FROM user b) GROUP BY a.name HAVING COUNT(*) BETWEEN 2 AND 5; fyi, the above query would deliver a result like this if i call it directly on the database: 1, John 2, Donald 1, Ralph ...

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• DynamicQuery: How to select a column with linq query that takes parameters

  - by Richard77

  Hello, We want to set up a directory of all the organizations working with us. They are incredibly diverse (government, embassy, private companies, and organizations depending on them ). So, I've resolved to create 2 tables. Table 1 will treat all the organizations equally, i.e. it'll collect all the basic information (name, address, phone number, etc.). Table 2 will establish the hierarchy among all the organizations. For instance, Program for illiterate adults depends on the National Institute for Social Security which depends on the Labor Ministry. In the Hierarchy table, each column represents a level. So, for the example above, (i)Labor Ministry - Level1(column1), (ii)National Institute for Social Security - Level2(column2), (iii)Program for illiterate adults - Level3(column3). To attach an organization to an hierarchy, the user needs to go level by level(i.e. column by column). So, there will be at least 3 situations: If an adequate hierarchy exists for an organization(for instance, level1: US Embassy), that organization can be added (For instance, level2: USAID).-- US Embassy/USAID, and so on. How about if one or more levels are missing? - then they need to be added How about if the hierarchy need to be modified? -- not every thing need to be modified. I do not have any choice but working by level (i.e. column by column). I does not make sense to have all the levels in one form as the user need to navigate hierarchies to find the right one to attach an organization. Let's say, I have those queries in my repository (just that you get the idea). Query1 var orgHierarchy = (from orgH in db.Hierarchy select orgH.Level1).FirstOrDefault; Query2 var orgHierarchy = (from orgH in db.Hierarchy select orgH.Level2).FirstOrDefault; Query3, Query4, etc. The above queries are the same except for the property queried (level1, level2, level3, etc.) Question: Is there a general way of writing the above queries in one? So that the user can track an hierarchy level by level to attach an organization. In other words, not knowing in advance which column to query, I still need to be able to do so depending on some conditions. For instance, an organization X depends on Y. Knowing that Y is somewhere on the 3rd level, I'll go to the 4th level, linking X to Y. I need to select (not manually) a column with only one query that takes parameters. Thanks for helping

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