Search Results

Search found 9542 results on 382 pages for 'row'.

Page 176/382 | < Previous Page | 172 173 174 175 176 177 178 179 180 181 182 183  | Next Page >

• IF statement within WHILE not working

  - by Ds.109

  I am working on a basic messaging system. This is to get all the messages and to make the row of the table that has an unread message Green. In the table, there is a column called 'msgread'. this is set to '0' by default. Therefore it should make any row with the msgread = 0 - green. this is only working for the first row of the table with the code i have - i verified that it is always getting a 0 value, however it only works the first time through in the while statement .. require('./connect.php'); $getmessages = "SELECT * FROM messages WHERE toperson = '" . $userid . "'"; echo $getmessages; $messages = mysql_query($getmessages); if(mysql_num_rows($messages) != 0) { $table = "<table><tr><th>From</th><th>Subject</th><th>Message</th></tr>"; while($results = mysql_fetch_array($messages)) { if(strlen($results[message]) < 30){ $message = $results[message]; } else { $message = substr($results[message], 0 ,30) . "..."; } if($results[msgread] == 0){ $table .= "<tr style='background:#9CFFB6'>"; $table .= "<td>" . $results[from] . "</td><td>" . $results[subject] . "</td><td><a href='viewmessage.php?id=" . $results[message_id] ."'>" . $message . "</a></td></tr>"; } else { $table .= "<tr>"; $table .= "<td>" . $results[from] . "</td><td>" . $results[subject] . "</td><td><a href='viewmessage.php?id=" . $results[message_id] ."'>" . $message . "</a></td></tr>"; } } echo $table ."</table>"; } else { echo "No Messages Found"; } There's all the code, including grabbing the info from the database. Thanks.

  Read the article

• Put empty spaces in an SQL select

  - by David Undy

  I'm having difficulty creating a month-count select query in SQL. Basically, I have a list of entries, all of which have a date associated with them. What I want the end result to be, is a list containing 12 rows (one for each month), and each row would contain the month number (1 for January, 2 for February, etc), and a count of how many entries had that month set as it's date. Something like this: Month - Count 1 - 12 2 - 0 3 - 7 4 - 0 5 - 9 6 - 0 I can get an result containing months that have a count of higher than 0, but if the month contains no entries, the row isn't created. I get this result just by doing SELECT Month(goalDate) as monthNumber, count(*) as monthCount FROM goalsList WHERE Year(goalDate) = 2012 GROUP BY Month(goalDate) ORDER BY monthNumber Thanks in advance for the help!

  Read the article

• Why does Cacti keep waiting for dead poller processes?

  - by Oliver Salzburg

  sorry for the length I am currently setting up a new Debian (6.0.5) server. I put Cacti (0.8.7g) on it yesterday and have been battling with it ever since. Initial issue The initial issue I was observing, was that my graphs weren't updating. So I checked my cacti.log and found this concerning message: POLLER: Poller[0] Maximum runtime of 298 seconds exceeded. Exiting. That can't be good, right? So I went checking and started poller.php myself (via sudo -u www-data php poller.php --force). It will pump out a lot of message (which all look like what I would expect) and then hang for a minute. After that 1 minute, it will loop the following message: Waiting on 1 of 1 pollers. This goes on for 4 more minutes until the process is forcefully ended for running longer than 300s. So far so good I went on for a good hour trying to determine what poller might still be running, until I got to the conclusion that there simply is no running poller. Debugging I checked poller.php to see how that warning is issued and why. On line 368, Cacti will retrieve the number of finished processes from the database and use that value to calculate how many processes are still running. So, let's see that value! I added the following debug code into poller.php: print "Finished: " . $finished_processes . " - Started: " . $started_processes . "\n"; Result This will print the following within seconds of starting poller.php: Finished: 0 - Started: 1 Waiting on 1 of 1 pollers. Finished: 1 - Started: 1 So the values are being read and are valid. Until we get to the part where it keeps looping: Finished: - Started: 1 Waiting on 1 of 1 pollers. Suddenly, the value is gone. Why? Putting var_dump() in there confirms the issue: NULL Finished: - Started: 1 Waiting on 1 of 1 pollers. The return value is NULL. How can that be when querying SELECT COUNT()...? (SELECT COUNT() should always return one result row, shouldn't it?) More debugging So I went into lib\database.php and had a look at that db_fetch_cell(). A bit of testing confirmed, that the result set is actually empty. So I added my own database query code in there to see what that would do: $finished_processes = db_fetch_cell("SELECT count(*) FROM poller_time WHERE poller_id=0 AND end_time>'0000-00-00 00:00:00'"); print "Finished: " . $finished_processes . " - Started: " . $started_processes . "\n"; $mysqli = new mysqli("localhost","cacti","cacti","cacti"); $result = $mysqli->query("SELECT COUNT(*) FROM poller_time WHERE poller_id=0 AND end_time>'0000-00-00 00:00:00';"); $row = $result->fetch_assoc(); var_dump( $row ); This will output Finished: - Started: 1 array(1) { ["COUNT(*)"]=> string(1) "2" } Waiting on 1 of 1 pollers. So, the data is there and can be accessed without any problems, just not with the method Cacti is using? Double-check that! I enabled MySQL logging to make sure I'm not imagining things. Sure enough, when the error message is looped, the cacti.log reads as if it was querying like mad: 06/29/2012 08:44:00 PM - CMDPHP: Poller[0] DEVEL: SQL Cell: "SELECT count(*) FROM cacti.poller_time WHERE poller_id=0 AND end_time>'0000-00-00 00:00:00'" 06/29/2012 08:44:01 PM - CMDPHP: Poller[0] DEVEL: SQL Cell: "SELECT count(*) FROM cacti.poller_time WHERE poller_id=0 AND end_time>'0000-00-00 00:00:00'" 06/29/2012 08:44:02 PM - CMDPHP: Poller[0] DEVEL: SQL Cell: "SELECT count(*) FROM cacti.poller_time WHERE poller_id=0 AND end_time>'0000-00-00 00:00:00'" But none of these queries are logged my MySQL. Yet, when I add my own database query code, it shows up just fine. What the heck is going on here?

  Read the article

• PHP crashing (seg-fault) under mod_fcgi, apache

  - by Andras Gyomrey

  I've been programming a site using: Zend Framework 1.11.5 (complete MVC) PHP 5.3.6 Apache 2.2.19 CentOS 5.6 i686 virtuozzo on vps cPanel WHM 11.30.1 (build 4) Mysql 5.1.56-log Mysqli API 5.1.56 The issue started here http://stackoverflow.com/questions/6769515/php-programming-seg-fault. In brief, php is giving me random segmentation-faults. [Wed Jul 20 17:45:34 2011] [error] mod_fcgid: process /usr/local/cpanel/cgi-sys/php5(11562) exit(communication error), get unexpected signal 11 [Wed Jul 20 17:45:34 2011] [warn] [client 190.78.208.30] (104)Connection reset by peer: mod_fcgid: error reading data from FastCGI server [Wed Jul 20 17:45:34 2011] [error] [client 190.78.208.30] Premature end of script headers: index.php About extensions. When i compile php with "--enable-debug" flag, i have to disable this line: zend_extension="/usr/local/IonCube/ioncube_loader_lin_5.3.so" Otherwise, the server doesn't accept requests and i get a "The connection with the server was reset". It is possible that i have to disable eaccelerator too because of the same reason. I still don't get why apache gets running it some times and some others not: extension="eaccelerator.so" Anyway, after i get httpd running, seg-faults can occurr randomly. If i don't compile php with "--enable-debug" flag, i can get DETERMINISTICALLY a php crash: <?php class Admin_DbController extends Controller_BaseController { public function updateSqlDefinitionsAction() { $db = Zend_Registry::get('db'); $row = $db->fetchRow("SHOW CREATE TABLE 222AFI"); } } ?> BUT if i compile php with "--enable-debug" flag, it's really hard to get this error. I must add some complexity to make it crash. I have to be doing many paralell requests for a few seconds to get a crash: <?php class Admin_DbController extends Controller_BaseController { public function updateSqlDefinitionsAction() { $db = Zend_Registry::get('db'); $tableList = $db->listTables(); foreach ($tableList as $tableName){ $row = $db->fetchRow("SHOW CREATE TABLE " . $db->quoteIdentifier($tableName)); file_put_contents( DB_DEFINITIONS_PATH . '/' . $tableName . '.sql', $row['Create Table'] . ';' ); } } } ?> Please notice this is the same script, but creating DDL for all tables in database rather than for one. It seems that if php is heavy loaded (with extensions and me doing many paralell requests) it's when i get php to crash. About starting httpd with "-X": i've tried. The thing is, it is already hard to make php crash with --enable-debug. With "-X" option (which only enables one child process) i can't do parallel requests. So i haven't been able to create to proper debug backtrace: https://bugs.php.net/bugs-generating-backtrace.php My concrete question is, what do i do to get a coredump? root@GWT4 [~]# httpd -V Server version: Apache/2.2.19 (Unix) Server built: Jul 20 2011 19:18:58 Cpanel::Easy::Apache v3.4.2 rev9999 Server's Module Magic Number: 20051115:28 Server loaded: APR 1.4.5, APR-Util 1.3.12 Compiled using: APR 1.4.5, APR-Util 1.3.12 Architecture: 32-bit Server MPM: Prefork threaded: no forked: yes (variable process count) Server compiled with.... -D APACHE_MPM_DIR="server/mpm/prefork" -D APR_HAS_SENDFILE -D APR_HAS_MMAP -D APR_HAVE_IPV6 (IPv4-mapped addresses enabled) -D APR_USE_SYSVSEM_SERIALIZE -D APR_USE_PTHREAD_SERIALIZE -D SINGLE_LISTEN_UNSERIALIZED_ACCEPT -D APR_HAS_OTHER_CHILD -D AP_HAVE_RELIABLE_PIPED_LOGS -D DYNAMIC_MODULE_LIMIT=128 -D HTTPD_ROOT="/usr/local/apache" -D SUEXEC_BIN="/usr/local/apache/bin/suexec" -D DEFAULT_PIDLOG="logs/httpd.pid" -D DEFAULT_SCOREBOARD="logs/apache_runtime_status" -D DEFAULT_LOCKFILE="logs/accept.lock" -D DEFAULT_ERRORLOG="logs/error_log" -D AP_TYPES_CONFIG_FILE="conf/mime.types" -D SERVER_CONFIG_FILE="conf/httpd.conf"

  Read the article

• SSIS Lookup component tuning tips

  - by jamiet

  Yesterday evening I attended a London meeting of the UK SQL Server User Group at Microsoft’s offices in London Victoria. As usual it was both a fun and informative evening and in particular there seemed to be a few questions arising about tuning the SSIS Lookup component; I rattled off some comments and figured it would be prudent to drop some of them into a dedicated blog post, hence the one you are reading right now. Scene setting A popular pattern in SSIS is to use a Lookup component to determine whether a record in the pipeline already exists in the intended destination table or not and I cover this pattern in my 2006 blog post Checking if a row exists and if it does, has it changed? (note to self: must rewrite that blog post for SSIS2008). Fundamentally the SSIS lookup component (when using FullCache option) sucks some data out of a database and holds it in memory so that it can be compared to data in the pipeline. One of the big benefits of using SSIS dataflows is that they process data one buffer at a time; that means that not all of the data from your source exists in the dataflow at the same time and is why a SSIS dataflow can process data volumes that far exceed the available memory. However, that only applies to data in the pipeline; for reasons that are hopefully obvious ALL of the data in the lookup set must exist in the memory cache for the duration of the dataflow’s execution which means that any memory used by the lookup cache will not be available to be used as a pipeline buffer. Moreover, there’s an obvious correlation between the amount of data in the lookup cache and the time it takes to charge that cache; the more data you have then the longer it will take to charge and the longer you have to wait until the dataflow actually starts to do anything. For these reasons your goal is simple: ensure that the lookup cache contains as little data as possible. General tips Here is a simple tick list you can follow in order to tune your lookups: Use a SQL statement to charge your cache, don’t just pick a table from the dropdown list made available to you. (Read why in SELECT *... or select from a dropdown in an OLE DB Source component?) Only pick the columns that you need, ignore everything else Make the database columns that your cache is populated from as narrow as possible. If a column is defined as VARCHAR(20) then SSIS will allocate 20 bytes for every value in that column – that is a big waste if the actual values are significantly less than 20 characters in length. Do you need DT_WSTR typed columns or will DT_STR suffice? DT_WSTR uses twice the amount of space to hold values that can be stored using a DT_STR so if you can use DT_STR, consider doing so. Same principle goes for the numerical datatypes DT_I2/DT_I4/DT_I8. Only populate the cache with data that you KNOW you will need. In other words, think about your WHERE clause! Thinking outside the box It is tempting to build a large monolithic dataflow that does many things, one of which is a Lookup. Often though you can make better use of your available resources by, well, mixing things up a little and here are a few ideas to get your creative juices flowing: There is no rule that says everything has to happen in a single dataflow. If you have some particularly resource intensive lookups then consider putting that lookup into a dataflow all of its own and using raw files to pass the pipeline data in and out of that dataflow. Know your data. If you think, for example, that the majority of your incoming rows will match with only a small subset of your lookup data then consider chaining multiple lookup components together; the first would use a FullCache containing that data subset and the remaining data that doesn’t find a match could be passed to a second lookup that perhaps uses a NoCache lookup thus negating the need to pull all of that least-used lookup data into memory. Do you need to process all of your incoming data all at once? If you can process different partitions of your data separately then you can partition your lookup cache as well. For example, if you are using a lookup to convert a location into a [LocationId] then why not process your data one region at a time? This will mean your lookup cache only has to contain data for the location that you are currently processing and with the ability of the Lookup in SSIS2008 and beyond to charge the cache using a dynamically built SQL statement you’ll be able to achieve it using the same dataflow and simply loop over it using a ForEach loop. Taking the previous data partitioning idea further … a dataflow can contain more than one data path so why not split your data using a conditional split component and, again, charge your lookup caches with only the data that they need for that partition. Lookups have two uses: to (1) find a matching row from the lookup set and (2) put attributes from that matching row into the pipeline. Ask yourself, do you need to do these two things at the same time? After all once you have the key column(s) from your lookup set then you can use that key to get the rest of attributes further downstream, perhaps even in another dataflow. Are you using the same lookup data set multiple times? If so, consider the file caching option in SSIS 2008 and beyond. Above all, experiment and be creative with different combinations. You may be surprised at what works. Final  thoughts If you want to know more about how the Lookup component differs in SSIS2008 from SSIS2005 then I have a dedicated blog post about that at Lookup component gets a makeover. I am on a mini-crusade at the moment to get a BULK MERGE feature into the database engine, the thinking being that if the database engine can quickly merge massive amounts of data in a similar manner to how it can insert massive amounts using BULK INSERT then that’s a lot of work that wouldn’t have to be done in the SSIS pipeline. If you think that is a good idea then go and vote for BULK MERGE on Connect. If you have any other tips to share then please stick them in the comments. Hope this helps! @Jamiet Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

  Read the article

• Dynamic Unpivot : SSIS Nugget

  - by jamiet

  A question on the SSIS forum earlier today asked: I need to dynamically unpivot some set of columns in my source file. Every month there is one new column and its set of Values. I want to unpivot it without editing my SSIS packages that is deployed Let’s be clear about what we mean by Unpivot. It is a normalisation technique that basically converts columns into rows. By way of example it converts something like this: AccountCode Jan Feb Mar AC1 100.00 150.00 125.00 AC2 45.00 75.50 90.00 into something like this: AccountCode Month Amount AC1 Jan 100.00 AC1 Feb 150.00 AC1 Mar 125.00 AC2 Jan 45.00 AC2 Feb 75.50 AC2 Mar 90.00 The Unpivot transformation in SSIS is perfectly capable of carrying out the operation defined in this example however in the case outlined in the aforementioned forum thread the problem was a little bit different. I interpreted it to mean that the number of columns could change and in that scenario the Unpivot transformation (and indeed the SSIS dataflow in general) is rendered useless because it expects that the number of columns will not change from what is specified at design-time. There is a workaround however. Assuming all of the columns that CAN exist will appear at the end of the rows, we can (1) import all of the columns in the file as just a single column, (2) use a script component to loop over all the values in that “column” and (3) output each one as a column all of its own. Let’s go over that in a bit more detail.   I’ve prepared a data file that shows some data that we want to unpivot which shows some customers and their mythical shopping lists (it has column names in the first row): We use a Flat File Connection Manager to specify the format of our data file to SSIS: and a Flat File Source Adapter to put it into the dataflow (no need a for a screenshot of that one – its very basic). Notice that the values that we want to unpivot all exist in a column called [Groceries]. Now onto the script component where the real work goes on, although the code is pretty simple: Here I show a screenshot of this executing along with some data viewers. As you can see we have successfully pulled out all of the values into a row all of their own thus accomplishing the Dynamic Unpivot that the forum poster was after. If you want to run the demo for yourself then I have uploaded the demo package and source file up to my SkyDrive: http://cid-550f681dad532637.skydrive.live.com/self.aspx/Public/BlogShare/20100529/Dynamic%20Unpivot.zip Simply extract the two files into a folder, make sure the Connection Manager is pointing to the file, and execute! Hope this is useful. @Jamiet Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

  Read the article

• Analytic functions – they’re not aggregates

  - by Rob Farley

  SQL 2012 brings us a bunch of new analytic functions, together with enhancements to the OVER clause. People who have known me over the years will remember that I’m a big fan of the OVER clause and the types of things that it brings us when applied to aggregate functions, as well as the ranking functions that it enables. The OVER clause was introduced in SQL Server 2005, and remained frustratingly unchanged until SQL Server 2012. This post is going to look at a particular aspect of the analytic functions though (not the enhancements to the OVER clause). When I give presentations about the analytic functions around Australia as part of the tour of SQL Saturdays (starting in Brisbane this Thursday), and in Chicago next month, I’ll make sure it’s sufficiently well described. But for this post – I’m going to skip that and assume you get it. The analytic functions introduced in SQL 2012 seem to come in pairs – FIRST_VALUE and LAST_VALUE, LAG and LEAD, CUME_DIST and PERCENT_RANK, PERCENTILE_CONT and PERCENTILE_DISC. Perhaps frustratingly, they take slightly different forms as well. The ones I want to look at now are FIRST_VALUE and LAST_VALUE, and PERCENTILE_CONT and PERCENTILE_DISC. The reason I’m pulling this ones out is that they always produce the same result within their partitions (if you’re applying them to the whole partition). Consider the following query: SELECT     YEAR(OrderDate),     FIRST_VALUE(TotalDue)         OVER (PARTITION BY YEAR(OrderDate)               ORDER BY OrderDate, SalesOrderID               RANGE BETWEEN UNBOUNDED PRECEDING                         AND UNBOUNDED FOLLOWING),     LAST_VALUE(TotalDue)         OVER (PARTITION BY YEAR(OrderDate)               ORDER BY OrderDate, SalesOrderID               RANGE BETWEEN UNBOUNDED PRECEDING                         AND UNBOUNDED FOLLOWING),     PERCENTILE_CONT(0.95)         WITHIN GROUP (ORDER BY TotalDue)         OVER (PARTITION BY YEAR(OrderDate)),     PERCENTILE_DISC(0.95)         WITHIN GROUP (ORDER BY TotalDue)         OVER (PARTITION BY YEAR(OrderDate)) FROM Sales.SalesOrderHeader ; This is designed to get the TotalDue for the first order of the year, the last order of the year, and also the 95% percentile, using both the continuous and discrete methods (‘discrete’ means it picks the closest one from the values available – ‘continuous’ means it will happily use something between, similar to what you would do for a traditional median of four values). I’m sure you can imagine the results – a different value for each field, but within each year, all the rows the same. Notice that I’m not grouping by the year. Nor am I filtering. This query gives us a result for every row in the SalesOrderHeader table – 31465 in this case (using the original AdventureWorks that dates back to the SQL 2005 days). The RANGE BETWEEN bit in FIRST_VALUE and LAST_VALUE is needed to make sure that we’re considering all the rows available. If we don’t specify that, it assumes we only mean “RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW”, which means that LAST_VALUE ends up being the row we’re looking at. At this point you might think about other environments such as Access or Reporting Services, and remember aggregate functions like FIRST. We really should be able to do something like: SELECT     YEAR(OrderDate),     FIRST_VALUE(TotalDue)         OVER (PARTITION BY YEAR(OrderDate)               ORDER BY OrderDate, SalesOrderID               RANGE BETWEEN UNBOUNDED PRECEDING                         AND UNBOUNDED FOLLOWING) FROM Sales.SalesOrderHeader GROUP BY YEAR(OrderDate) ; But you can’t. You get that age-old error: Msg 8120, Level 16, State 1, Line 5 Column 'Sales.SalesOrderHeader.OrderDate' is invalid in the select list because it is not contained in either an aggregate function or the GROUP BY clause. Msg 8120, Level 16, State 1, Line 5 Column 'Sales.SalesOrderHeader.SalesOrderID' is invalid in the select list because it is not contained in either an aggregate function or the GROUP BY clause. Hmm. You see, FIRST_VALUE isn’t an aggregate function. None of these analytic functions are. There are too many things involved for SQL to realise that the values produced might be identical within the group. Furthermore, you can’t even surround it in a MAX. Then you get a different error, telling you that you can’t use windowed functions in the context of an aggregate. And so we end up grouping by doing a DISTINCT. SELECT DISTINCT     YEAR(OrderDate),         FIRST_VALUE(TotalDue)              OVER (PARTITION BY YEAR(OrderDate)                   ORDER BY OrderDate, SalesOrderID                   RANGE BETWEEN UNBOUNDED PRECEDING                             AND UNBOUNDED FOLLOWING),         LAST_VALUE(TotalDue)             OVER (PARTITION BY YEAR(OrderDate)                   ORDER BY OrderDate, SalesOrderID                   RANGE BETWEEN UNBOUNDED PRECEDING                             AND UNBOUNDED FOLLOWING),     PERCENTILE_CONT(0.95)          WITHIN GROUP (ORDER BY TotalDue)         OVER (PARTITION BY YEAR(OrderDate)),     PERCENTILE_DISC(0.95)         WITHIN GROUP (ORDER BY TotalDue)         OVER (PARTITION BY YEAR(OrderDate)) FROM Sales.SalesOrderHeader ; I’m sorry. It’s just the way it goes. Hopefully it’ll change the future, but for now, it’s what you’ll have to do. If we look in the execution plan, we see that it’s incredibly ugly, and actually works out the results of these analytic functions for all 31465 rows, finally performing the distinct operation to convert it into the four rows we get in the results. You might be able to achieve a better plan using things like TOP, or the kind of calculation that I used in http://sqlblog.com/blogs/rob_farley/archive/2011/08/23/t-sql-thoughts-about-the-95th-percentile.aspx (which is how PERCENTILE_CONT works), but it’s definitely convenient to use these functions, and in time, I’m sure we’ll see good improvements in the way that they are implemented. Oh, and this post should be good for fellow SQL Server MVP Nigel Sammy’s T-SQL Tuesday this month.

  Read the article

• Cannot insert explicit value for identity column in table ‘table’ when IDENTITY_INSERT is set to OFF

  - by Derek D.

  This error occurs when trying to insert into a column containing an identity. An Identity column is not able to be inserted into without the use of a special command mentioned below. Identity columns are columns that automatically increment when a value is inserted into a row. They are commonly used [...]

  Read the article

• How to find and fix performance problems in ORM powered applications

  - by FransBouma

  Once in a while we get requests about how to fix performance problems with our framework. As it comes down to following the same steps and looking into the same things every single time, I decided to write a blogpost about it instead, so more people can learn from this and solve performance problems in their O/R mapper powered applications. In some parts it's focused on LLBLGen Pro but it's also usable for other O/R mapping frameworks, as the vast majority of performance problems in O/R mapper powered applications are not specific for a certain O/R mapper framework. Too often, the developer looks at the wrong part of the application, trying to fix what isn't a problem in that part, and getting frustrated that 'things are so slow with <insert your favorite framework X here>'. I'm in the O/R mapper business for a long time now (almost 10 years, full time) and as it's a small world, we O/R mapper developers know almost all tricks to pull off by now: we all know what to do to make task ABC faster and what compromises (because there are almost always compromises) to deal with if we decide to make ABC faster that way. Some O/R mapper frameworks are faster in X, others in Y, but you can be sure the difference is mainly a result of a compromise some developers are willing to deal with and others aren't. That's why the O/R mapper frameworks on the market today are different in many ways, even though they all fetch and save entities from and to a database. I'm not suggesting there's no room for improvement in today's O/R mapper frameworks, there always is, but it's not a matter of 'the slowness of the application is caused by the O/R mapper' anymore. Perhaps query generation can be optimized a bit here, row materialization can be optimized a bit there, but it's mainly coming down to milliseconds. Still worth it if you're a framework developer, but it's not much compared to the time spend inside databases and in user code: if a complete fetch takes 40ms or 50ms (from call to entity object collection), it won't make a difference for your application as that 10ms difference won't be noticed. That's why it's very important to find the real locations of the problems so developers can fix them properly and don't get frustrated because their quest to get a fast, performing application failed. Performance tuning basics and rules Finding and fixing performance problems in any application is a strict procedure with four prescribed steps: isolate, analyze, interpret and fix, in that order. It's key that you don't skip a step nor make assumptions: these steps help you find the reason of a problem which seems to be there, and how to fix it or leave it as-is. Skipping a step, or when you assume things will be bad/slow without doing analysis will lead to the path of premature optimization and won't actually solve your problems, only create new ones. The most important rule of finding and fixing performance problems in software is that you have to understand what 'performance problem' actually means. Most developers will say "when a piece of software / code is slow, you have a performance problem". But is that actually the case? If I write a Linq query which will aggregate, group and sort 5 million rows from several tables to produce a resultset of 10 rows, it might take more than a couple of milliseconds before that resultset is ready to be consumed by other logic. If I solely look at the Linq query, the code consuming the resultset of the 10 rows and then look at the time it takes to complete the whole procedure, it will appear to me to be slow: all that time taken to produce and consume 10 rows? But if you look closer, if you analyze and interpret the situation, you'll see it does a tremendous amount of work, and in that light it might even be extremely fast. With every performance problem you encounter, always do realize that what you're trying to solve is perhaps not a technical problem at all, but a perception problem. The second most important rule you have to understand is based on the old saying "Penny wise, Pound Foolish": the part which takes e.g. 5% of the total time T for a given task isn't worth optimizing if you have another part which takes a much larger part of the total time T for that same given task. Optimizing parts which are relatively insignificant for the total time taken is not going to bring you better results overall, even if you totally optimize that part away. This is the core reason why analysis of the complete set of application parts which participate in a given task is key to being successful in solving performance problems: No analysis -> no problem -> no solution. One warning up front: hunting for performance will always include making compromises. Fast software can be made maintainable, but if you want to squeeze as much performance out of your software, you will inevitably be faced with the dilemma of compromising one or more from the group {readability, maintainability, features} for the extra performance you think you'll gain. It's then up to you to decide whether it's worth it. In almost all cases it's not. The reason for this is simple: the vast majority of performance problems can be solved by implementing the proper algorithms, the ones with proven Big O-characteristics so you know the performance you'll get plus you know the algorithm will work. The time taken by the algorithm implementing code is inevitable: you already implemented the best algorithm. You might find some optimizations on the technical level but in general these are minor. Let's look at the four steps to see how they guide us through the quest to find and fix performance problems. Isolate The first thing you need to do is to isolate the areas in your application which are assumed to be slow. For example, if your application is a web application and a given page is taking several seconds or even minutes to load, it's a good candidate to check out. It's important to start with the isolate step because it allows you to focus on a single code path per area with a clear begin and end and ignore the rest. The rest of the steps are taken per identified problematic area. Keep in mind that isolation focuses on tasks in an application, not code snippets. A task is something that's started in your application by either another task or the user, or another program, and has a beginning and an end. You can see a task as a piece of functionality offered by your application.  Analyze Once you've determined the problem areas, you have to perform analysis on the code paths of each area, to see where the performance problems occur and which areas are not the problem. This is a multi-layered effort: an application which uses an O/R mapper typically consists of multiple parts: there's likely some kind of interface (web, webservice, windows etc.), a part which controls the interface and business logic, the O/R mapper part and the RDBMS, all connected with either a network or inter-process connections provided by the OS or other means. Each of these parts, including the connectivity plumbing, eat up a part of the total time it takes to complete a task, e.g. load a webpage with all orders of a given customer X. To understand which parts participate in the task / area we're investigating and how much they contribute to the total time taken to complete the task, analysis of each participating task is essential. Start with the code you wrote which starts the task, analyze the code and track the path it follows through your application. What does the code do along the way, verify whether it's correct or not. Analyze whether you have implemented the right algorithms in your code for this particular area. Remember we're looking at one area at a time, which means we're ignoring all other code paths, just the code path of the current problematic area, from begin to end and back. Don't dig in and start optimizing at the code level just yet. We're just analyzing. If your analysis reveals big architectural stupidity, it's perhaps a good idea to rethink the architecture at this point. For the rest, we're analyzing which means we collect data about what could be wrong, for each participating part of the complete application. Reviewing the code you wrote is a good tool to get deeper understanding of what is going on for a given task but ultimately it lacks precision and overview what really happens: humans aren't good code interpreters, computers are. We therefore need to utilize tools to get deeper understanding about which parts contribute how much time to the total task, triggered by which other parts and for example how many times are they called. There are two different kind of tools which are necessary: .NET profilers and O/R mapper / RDBMS profilers. .NET profiling .NET profilers (e.g. dotTrace by JetBrains or Ants by Red Gate software) show exactly which pieces of code are called, how many times they're called, and the time it took to run that piece of code, at the method level and sometimes even at the line level. The .NET profilers are essential tools for understanding whether the time taken to complete a given task / area in your application is consumed by .NET code, where exactly in your code, the path to that code, how many times that code was called by other code and thus reveals where hotspots are located: the areas where a solution can be found. Importantly, they also reveal which areas can be left alone: remember our penny wise pound foolish saying: if a profiler reveals that a group of methods are fast, or don't contribute much to the total time taken for a given task, ignore them. Even if the code in them is perhaps complex and looks like a candidate for optimization: you can work all day on that, it won't matter.  As we're focusing on a single area of the application, it's best to start profiling right before you actually activate the task/area. Most .NET profilers support this by starting the application without starting the profiling procedure just yet. You navigate to the particular part which is slow, start profiling in the profiler, in your application you perform the actions which are considered slow, and afterwards you get a snapshot in the profiler. The snapshot contains the data collected by the profiler during the slow action, so most data is produced by code in the area to investigate. This is important, because it allows you to stay focused on a single area. O/R mapper and RDBMS profiling .NET profilers give you a good insight in the .NET side of things, but not in the RDBMS side of the application. As this article is about O/R mapper powered applications, we're also looking at databases, and the software making it possible to consume the database in your application: the O/R mapper. To understand which parts of the O/R mapper and database participate how much to the total time taken for task T, we need different tools. There are two kind of tools focusing on O/R mappers and database performance profiling: O/R mapper profilers and RDBMS profilers. For O/R mapper profilers, you can look at LLBLGen Prof by hibernating rhinos or the Linq to Sql/LLBLGen Pro profiler by Huagati. Hibernating rhinos also have profilers for other O/R mappers like NHibernate (NHProf) and Entity Framework (EFProf) and work the same as LLBLGen Prof. For RDBMS profilers, you have to look whether the RDBMS vendor has a profiler. For example for SQL Server, the profiler is shipped with SQL Server, for Oracle it's build into the RDBMS, however there are also 3rd party tools. Which tool you're using isn't really important, what's important is that you get insight in which queries are executed during the task / area we're currently focused on and how long they took. Here, the O/R mapper profilers have an advantage as they collect the time it took to execute the query from the application's perspective so they also collect the time it took to transport data across the network. This is important because a query which returns a massive resultset or a resultset with large blob/clob/ntext/image fields takes more time to get transported across the network than a small resultset and a database profiler doesn't take this into account most of the time. Another tool to use in this case, which is more low level and not all O/R mappers support it (though LLBLGen Pro and NHibernate as well do) is tracing: most O/R mappers offer some form of tracing or logging system which you can use to collect the SQL generated and executed and often also other activity behind the scenes. While tracing can produce a tremendous amount of data in some cases, it also gives insight in what's going on. Interpret After we've completed the analysis step it's time to look at the data we've collected. We've done code reviews to see whether we've done anything stupid and which parts actually take place and if the proper algorithms have been implemented. We've done .NET profiling to see which parts are choke points and how much time they contribute to the total time taken to complete the task we're investigating. We've performed O/R mapper profiling and RDBMS profiling to see which queries were executed during the task, how many queries were generated and executed and how long they took to complete, including network transportation. All this data reveals two things: which parts are big contributors to the total time taken and which parts are irrelevant. Both aspects are very important. The parts which are irrelevant (i.e. don't contribute significantly to the total time taken) can be ignored from now on, we won't look at them. The parts which contribute a lot to the total time taken are important to look at. We now have to first look at the .NET profiler results, to see whether the time taken is consumed in our own code, in .NET framework code, in the O/R mapper itself or somewhere else. For example if most of the time is consumed by DbCommand.ExecuteReader, the time it took to complete the task is depending on the time the data is fetched from the database. If there was just 1 query executed, according to tracing or O/R mapper profilers / RDBMS profilers, check whether that query is optimal, uses indexes or has to deal with a lot of data. Interpret means that you follow the path from begin to end through the data collected and determine where, along the path, the most time is contributed. It also means that you have to check whether this was expected or is totally unexpected. My previous example of the 10 row resultset of a query which groups millions of rows will likely reveal that a long time is spend inside the database and almost no time is spend in the .NET code, meaning the RDBMS part contributes the most to the total time taken, the rest is compared to that time, irrelevant. Considering the vastness of the source data set, it's expected this will take some time. However, does it need tweaking? Perhaps all possible tweaks are already in place. In the interpret step you then have to decide that further action in this area is necessary or not, based on what the analysis results show: if the analysis results were unexpected and in the area where the most time is contributed to the total time taken is room for improvement, action should be taken. If not, you can only accept the situation and move on. In all cases, document your decision together with the analysis you've done. If you decide that the perceived performance problem is actually expected due to the nature of the task performed, it's essential that in the future when someone else looks at the application and starts asking questions you can answer them properly and new analysis is only necessary if situations changed. Fix After interpreting the analysis results you've concluded that some areas need adjustment. This is the fix step: you're actively correcting the performance problem with proper action targeted at the real cause. In many cases related to O/R mapper powered applications it means you'll use different features of the O/R mapper to achieve the same goal, or apply optimizations at the RDBMS level. It could also mean you apply caching inside your application (compromise memory consumption over performance) to avoid unnecessary re-querying data and re-consuming the results. After applying a change, it's key you re-do the analysis and interpretation steps: compare the results and expectations with what you had before, to see whether your actions had any effect or whether it moved the problem to a different part of the application. Don't fall into the trap to do partly analysis: do the full analysis again: .NET profiling and O/R mapper / RDBMS profiling. It might very well be that the changes you've made make one part faster but another part significantly slower, in such a way that the overall problem hasn't changed at all. Performance tuning is dealing with compromises and making choices: to use one feature over the other, to accept a higher memory footprint, to go away from the strict-OO path and execute queries directly onto the RDBMS, these are choices and compromises which will cross your path if you want to fix performance problems with respect to O/R mappers or data-access and databases in general. In most cases it's not a big issue: alternatives are often good choices too and the compromises aren't that hard to deal with. What is important is that you document why you made a choice, a compromise: which analysis data, which interpretation led you to the choice made. This is key for good maintainability in the years to come. Most common performance problems with O/R mappers Below is an incomplete list of common performance problems related to data-access / O/R mappers / RDBMS code. It will help you with fixing the hotspots you found in the interpretation step. SELECT N+1: (Lazy-loading specific). Lazy loading triggered performance bottlenecks. Consider a list of Orders bound to a grid. You have a Field mapped onto a related field in Order, Customer.CompanyName. Showing this column in the grid will make the grid fetch (indirectly) for each row the Customer row. This means you'll get for the single list not 1 query (for the orders) but 1+(the number of orders shown) queries. To solve this: use eager loading using a prefetch path to fetch the customers with the orders. SELECT N+1 is easy to spot with an O/R mapper profiler or RDBMS profiler: if you see a lot of identical queries executed at once, you have this problem. Prefetch paths using many path nodes or sorting, or limiting. Eager loading problem. Prefetch paths can help with performance, but as 1 query is fetched per node, it can be the number of data fetched in a child node is bigger than you think. Also consider that data in every node is merged on the client within the parent. This is fast, but it also can take some time if you fetch massive amounts of entities. If you keep fetches small, you can use tuning parameters like the ParameterizedPrefetchPathThreshold setting to get more optimal queries. Deep inheritance hierarchies of type Target Per Entity/Type. If you use inheritance of type Target per Entity / Type (each type in the inheritance hierarchy is mapped onto its own table/view), fetches will join subtype- and supertype tables in many cases, which can lead to a lot of performance problems if the hierarchy has many types. With this problem, keep inheritance to a minimum if possible, or switch to a hierarchy of type Target Per Hierarchy, which means all entities in the inheritance hierarchy are mapped onto the same table/view. Of course this has its own set of drawbacks, but it's a compromise you might want to take. Fetching massive amounts of data by fetching large lists of entities. LLBLGen Pro supports paging (and limiting the # of rows returned), which is often key to process through large sets of data. Use paging on the RDBMS if possible (so a query is executed which returns only the rows in the page requested). When using paging in a web application, be sure that you switch server-side paging on on the datasourcecontrol used. In this case, paging on the grid alone is not enough: this can lead to fetching a lot of data which is then loaded into the grid and paged there. Keep note that analyzing queries for paging could lead to the false assumption that paging doesn't occur, e.g. when the query contains a field of type ntext/image/clob/blob and DISTINCT can't be applied while it should have (e.g. due to a join): the datareader will do DISTINCT filtering on the client. this is a little slower but it does perform paging functionality on the data-reader so it won't fetch all rows even if the query suggests it does. Fetch massive amounts of data because blob/clob/ntext/image fields aren't excluded. LLBLGen Pro supports field exclusion for queries. You can exclude fields (also in prefetch paths) per query to avoid fetching all fields of an entity, e.g. when you don't need them for the logic consuming the resultset. Excluding fields can greatly reduce the amount of time spend on data-transport across the network. Use this optimization if you see that there's a big difference between query execution time on the RDBMS and the time reported by the .NET profiler for the ExecuteReader method call. Doing client-side aggregates/scalar calculations by consuming a lot of data. If possible, try to formulate a scalar query or group by query using the projection system or GetScalar functionality of LLBLGen Pro to do data consumption on the RDBMS server. It's far more efficient to process data on the RDBMS server than to first load it all in memory, then traverse the data in-memory to calculate a value. Using .ToList() constructs inside linq queries. It might be you use .ToList() somewhere in a Linq query which makes the query be run partially in-memory. Example: var q = from c in metaData.Customers.ToList() where c.Country=="Norway" select c; This will actually fetch all customers in-memory and do an in-memory filtering, as the linq query is defined on an IEnumerable<T>, and not on the IQueryable<T>. Linq is nice, but it can often be a bit unclear where some parts of a Linq query might run. Fetching all entities to delete into memory first. To delete a set of entities it's rather inefficient to first fetch them all into memory and then delete them one by one. It's more efficient to execute a DELETE FROM ... WHERE query on the database directly to delete the entities in one go. LLBLGen Pro supports this feature, and so do some other O/R mappers. It's not always possible to do this operation in the context of an O/R mapper however: if an O/R mapper relies on a cache, these kind of operations are likely not supported because they make it impossible to track whether an entity is actually removed from the DB and thus can be removed from the cache. Fetching all entities to update with an expression into memory first. Similar to the previous point: it is more efficient to update a set of entities directly with a single UPDATE query using an expression instead of fetching the entities into memory first and then updating the entities in a loop, and afterwards saving them. It might however be a compromise you don't want to take as it is working around the idea of having an object graph in memory which is manipulated and instead makes the code fully aware there's a RDBMS somewhere. Conclusion Performance tuning is almost always about compromises and making choices. It's also about knowing where to look and how the systems in play behave and should behave. The four steps I provided should help you stay focused on the real problem and lead you towards the solution. Knowing how to optimally use the systems participating in your own code (.NET framework, O/R mapper, RDBMS, network/services) is key for success as well as knowing what's going on inside the application you built. I hope you'll find this guide useful in tracking down performance problems and dealing with them in a useful way.  

  Read the article

• Global Cache CR Requested But Current Block Received

  - by Liu Maclean(???)

  ????????«MINSCN?Cache Fusion Read Consistent» ????,???????????? ??????????????????: SQL> select * from V$version; BANNER -------------------------------------------------------------------------------- Oracle Database 11g Enterprise Edition Release 11.2.0.3.0 - 64bit Production PL/SQL Release 11.2.0.3.0 - Production CORE 11.2.0.3.0 Production TNS for Linux: Version 11.2.0.3.0 - Production NLSRTL Version 11.2.0.3.0 - Production SQL> select count(*) from gv$instance; COUNT(*) ---------- 2 SQL> select * from global_name; GLOBAL_NAME -------------------------------------------------------------------------------- www.oracledatabase12g.com ?11gR2 2??RAC??????????status???XG,????Xcurrent block???INSTANCE 2?hold?,?????INSTANCE 1?????????,?????: SQL> select * from test; ID ---------- 1 2 SQL> select dbms_rowid.rowid_block_number(rowid),dbms_rowid.rowid_relative_fno(rowid) from test; DBMS_ROWID.ROWID_BLOCK_NUMBER(ROWID) DBMS_ROWID.ROWID_RELATIVE_FNO(ROWID) ------------------------------------ ------------------------------------ 89233 1 89233 1 SQL> alter system flush buffer_cache; System altered. INSTANCE 1 Session A: SQL> update test set id=id+1 where id=1; 1 row updated. INSTANCE 1 Session B: SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 1 0 3 1755287 SQL> oradebug setmypid; Statement processed. SQL> oradebug dump gc_elements 255; Statement processed. SQL> oradebug tracefile_name; /s01/orabase/diag/rdbms/vprod/VPROD1/trace/VPROD1_ora_19111.trc GLOBAL CACHE ELEMENT DUMP (address: 0xa4ff3080): id1: 0x15c91 id2: 0x1 pkey: OBJ#76896 block: (1/89233) lock: X rls: 0x0 acq: 0x0 latch: 3 flags: 0x20 fair: 0 recovery: 0 fpin: 'kdswh11: kdst_fetch' bscn: 0x0.146e20 bctx: (nil) write: 0 scan: 0x0 lcp: (nil) lnk: [NULL] lch: [0xa9f6a6f8,0xa9f6a6f8] seq: 32 hist: 58 145:0 118 66 144:0 192 352 197 48 121 113 424 180 58 LIST OF BUFFERS LINKED TO THIS GLOBAL CACHE ELEMENT: flg: 0x02000001 lflg: 0x1 state: XCURRENT tsn: 0 tsh: 2 addr: 0xa9f6a5c8 obj: 76896 cls: DATA bscn: 0x0.1ac898 BH (0xa9f6a5c8) file#: 1 rdba: 0x00415c91 (1/89233) class: 1 ba: 0xa9e56000 set: 5 pool: 3 bsz: 8192 bsi: 0 sflg: 3 pwc: 0,15 dbwrid: 0 obj: 76896 objn: 76896 tsn: 0 afn: 1 hint: f hash: [0x91f4e970,0xbae9d5b8] lru: [0x91f58848,0xa9f6a828] lru-flags: debug_dump obj-flags: object_ckpt_list ckptq: [0x9df6d1d8,0xa9f6a740] fileq: [0xa2ece670,0xbdf4ed68] objq: [0xb4964e00,0xb4964e00] objaq: [0xb4964de0,0xb4964de0] st: XCURRENT md: NULL fpin: 'kdswh11: kdst_fetch' tch: 2 le: 0xa4ff3080 flags: buffer_dirty redo_since_read LRBA: [0x19.5671.0] LSCN: [0x0.1ac898] HSCN: [0x0.1ac898] HSUB: [1] buffer tsn: 0 rdba: 0x00415c91 (1/89233) scn: 0x0000.001ac898 seq: 0x01 flg: 0x00 tail: 0xc8980601 frmt: 0x02 chkval: 0x0000 type: 0x06=trans data ??????block: (1/89233)?GLOBAL CACHE ELEMENT DUMP?LOCK????X ??XG , ??????Current Block????Instance??modify???,????????????? ????Instance 2 ????: Instance 2 Session C: SQL> update test set id=id+1 where id=2; 1 row updated. Instance 2 Session D: SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 1 0 3 1756658 SQL> oradebug setmypid; Statement processed. SQL> oradebug dump gc_elements 255; Statement processed. SQL> oradebug tracefile_name; /s01/orabase/diag/rdbms/vprod/VPROD2/trace/VPROD2_ora_13038.trc GLOBAL CACHE ELEMENT DUMP (address: 0x89fb25a0): id1: 0x15c91 id2: 0x1 pkey: OBJ#76896 block: (1/89233) lock: XG rls: 0x0 acq: 0x0 latch: 3 flags: 0x20 fair: 0 recovery: 0 fpin: 'kduwh01: kdusru' bscn: 0x0.1acdf3 bctx: (nil) write: 0 scan: 0x0 lcp: (nil) lnk: [NULL] lch: [0x96f4cf80,0x96f4cf80] seq: 61 hist: 324 21 143:0 19 16 352 329 144:6 14 7 352 197 LIST OF BUFFERS LINKED TO THIS GLOBAL CACHE ELEMENT: flg: 0x0a000001 state: XCURRENT tsn: 0 tsh: 1 addr: 0x96f4ce50 obj: 76896 cls: DATA bscn: 0x0.1acdf6 BH (0x96f4ce50) file#: 1 rdba: 0x00415c91 (1/89233) class: 1 ba: 0x96bd4000 set: 5 pool: 3 bsz: 8192 bsi: 0 sflg: 2 pwc: 0,15 dbwrid: 0 obj: 76896 objn: 76896 tsn: 0 afn: 1 hint: f hash: [0x96ee1fe8,0xbae9d5b8] lru: [0x96f4d0b0,0x96f4cdc0] obj-flags: object_ckpt_list ckptq: [0xbdf519b8,0x96f4d5a8] fileq: [0xbdf519d8,0xbdf519d8] objq: [0xb4a47b90,0xb4a47b90] objaq: [0x96f4d0e8,0xb4a47b70] st: XCURRENT md: NULL fpin: 'kduwh01: kdusru' tch: 1 le: 0x89fb25a0 flags: buffer_dirty redo_since_read remote_transfered LRBA: [0x11.9e18.0] LSCN: [0x0.1acdf6] HSCN: [0x0.1acdf6] HSUB: [1] buffer tsn: 0 rdba: 0x00415c91 (1/89233) scn: 0x0000.001acdf6 seq: 0x01 flg: 0x00 tail: 0xcdf60601 frmt: 0x02 chkval: 0x0000 type: 0x06=trans data GCS CLIENT 0x89fb2618,6 resp[(nil),0x15c91.1] pkey 76896.0 grant 2 cvt 0 mdrole 0x42 st 0x100 lst 0x20 GRANTQ rl G0 master 1 owner 2 sid 0 remote[(nil),0] hist 0x94121c601163423c history 0x3c.0x4.0xd.0xb.0x1.0xc.0x7.0x9.0x14.0x1. cflag 0x0 sender 1 flags 0x0 replay# 0 abast (nil).x0.1 dbmap (nil) disk: 0x0000.00000000 write request: 0x0000.00000000 pi scn: 0x0000.00000000 sq[(nil),(nil)] msgseq 0x1 updseq 0x0 reqids[6,0,0] infop (nil) lockseq x2b8 pkey 76896.0 hv 93 [stat 0x0, 1->1, wm 32768, RMno 0, reminc 18, dom 0] kjga st 0x4, step 0.0.0, cinc 20, rmno 6, flags 0x0 lb 0, hb 0, myb 15250, drmb 15250, apifrz 0 ?Instance 2??????block: (1/89233)? GLOBAL CACHE ELEMENT Lock Convert?lock: XG ????GC_ELEMENTS DUMP???XCUR Cache Fusion?,???????X$ VIEW,??? X$LE X$KJBR X$KJBL, ???X$ VIEW???????????????????: INSTANCE 2 Session D: SELECT * FROM x$le WHERE le_addr IN (SELECT le_addr FROM x$bh WHERE obj IN (SELECT data_object_id FROM dba_objects WHERE owner = 'SYS' AND object_name = 'TEST') AND class = 1 AND state != 3); ADDR INDX INST_ID LE_ADDR LE_ID1 LE_ID2 ---------------- ---------- ---------- ---------------- ---------- ---------- LE_RLS LE_ACQ LE_FLAGS LE_MODE LE_WRITE LE_LOCAL LE_RECOVERY ---------- ---------- ---------- ---------- ---------- ---------- ----------- LE_BLKS LE_TIME LE_KJBL ---------- ---------- ---------------- 00007F94CA14CF60 7003 2 0000000089FB25A0 89233 1 0 0 32 2 0 1 0 1 0 0000000089FB2618 PCM Resource NAME?[ID1][ID2],[BL]???, ID1?ID2 ??blockno? fileno????, ??????????GC_elements dump?? id1: 0x15c91 id2: 0×1 pkey: OBJ#76896 block: (1/89233)?? ,?  kjblname ? kjbrname ??”[0x15c91][0x1],[BL]” ??: INSTANCE 2 Session D: SQL> set linesize 80 pagesize 1400 SQL> SELECT * 2 FROM x$kjbl l 3 WHERE l.kjblname LIKE '%[0x15c91][0x1],[BL]%'; ADDR INDX INST_ID KJBLLOCKP KJBLGRANT KJBLREQUE ---------------- ---------- ---------- ---------------- --------- --------- KJBLROLE KJBLRESP KJBLNAME ---------- ---------------- ------------------------------ KJBLNAME2 KJBLQUEUE ------------------------------ ---------- KJBLLOCKST KJBLWRITING ---------------------------------------------------------------- ----------- KJBLREQWRITE KJBLOWNER KJBLMASTER KJBLBLOCKED KJBLBLOCKER KJBLSID KJBLRDOMID ------------ ---------- ---------- ----------- ----------- ---------- ---------- KJBLPKEY ---------- 00007F94CA22A288 451 2 0000000089FB2618 KJUSEREX KJUSERNL 0 00 [0x15c91][0x1],[BL][ext 0x0,0x 89233,1,BL 0 GRANTED 0 0 1 0 0 0 0 0 76896 SQL> SELECT r.* FROM x$kjbr r WHERE r.kjbrname LIKE '%[0x15c91][0x1],[BL]%'; no rows selected Instance 1 session B: SQL> SELECT r.* FROM x$kjbr r WHERE r.kjbrname LIKE '%[0x15c91][0x1],[BL]%'; ADDR INDX INST_ID KJBRRESP KJBRGRANT KJBRNCVL ---------------- ---------- ---------- ---------------- --------- --------- KJBRROLE KJBRNAME KJBRMASTER KJBRGRANTQ ---------- ------------------------------ ---------- ---------------- KJBRCVTQ KJBRWRITER KJBRSID KJBRRDOMID KJBRPKEY ---------------- ---------------- ---------- ---------- ---------- 00007F801ACA68F8 1355 1 00000000B5A62AE0 KJUSEREX KJUSERNL 0 [0x15c91][0x1],[BL][ext 0x0,0x 0 00000000B48BB330 00 00 0 0 76896 ??????Instance 1???block: (1/89233),??????Instance 2 build cr block ????Instance 1, ?????????? ????? Instance 1? Foreground Process ? Instance 2?LMS??????RAC  TRACE: Instance 2: [oracle@vrh2 ~]$ ps -ef|grep ora_lms|grep -v grep oracle 23364 1 0 Apr29 ? 00:33:15 ora_lms0_VPROD2 SQL> oradebug setospid 23364 Oracle pid: 13, Unix process pid: 23364, image: [email protected] (LMS0) SQL> oradebug event 10046 trace name context forever,level 8:10708 trace name context forever,level 103: trace[rac.*] disk high; Statement processed. SQL> oradebug tracefile_name /s01/orabase/diag/rdbms/vprod/VPROD2/trace/VPROD2_lms0_23364.trc Instance 1 session B : SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 3 1756658 3 1756661 3 1755287 Instance 1 session A : SQL> alter session set events '10046 trace name context forever,level 8:10708 trace name context forever,level 103: trace[rac.*] disk high'; Session altered. SQL> select * from test; ID ---------- 2 2 SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 3 1761520 ?x$BH?????,???????Instance 1???build??CR block,????? TRACE ??: Instance 1 foreground Process: PARSING IN CURSOR #140336527348792 len=18 dep=0 uid=0 oct=3 lid=0 tim=1335939136125254 hv=1689401402 ad='b1a4c828' sqlid='c99yw1xkb4f1u' select * from test END OF STMT PARSE #140336527348792:c=2999,e=2860,p=0,cr=0,cu=0,mis=1,r=0,dep=0,og=1,plh=1357081020,tim=1335939136125253 EXEC #140336527348792:c=0,e=40,p=0,cr=0,cu=0,mis=0,r=0,dep=0,og=1,plh=1357081020,tim=1335939136125373 WAIT #140336527348792: nam='SQL*Net message to client' ela= 6 driver id=1650815232 #bytes=1 p3=0 obj#=0 tim=1335939136125420 *** 2012-05-02 02:12:16.125 kclscrs: req=0 block=1/89233 2012-05-02 02:12:16.125574 : kjbcro[0x15c91.1 76896.0][4] *** 2012-05-02 02:12:16.125 kclscrs: req=0 typ=nowait-abort *** 2012-05-02 02:12:16.125 kclscrs: bid=1:3:1:0:f:1e:0:0:10:0:0:0:1:2:4:1:20:0:0:0:c3:49:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:4:3:2:1:2:0:1c:0:4d:26:a3:52:0:0:0:0:c7:c:ca:62:c3:49:0:0:0:0:1:0:14:8e:47:76:1:2:dc:5:a9:fe:17:75:0:0:0:0:0:0:0:0:0:0:0:0:99:ed:0:0:0:0:0:0:10:0:0:0 2012-05-02 02:12:16.125718 : kjbcro[0x15c91.1 76896.0][4] 2012-05-02 02:12:16.125751 : GSIPC:GMBQ: buff 0xba0ee018, queue 0xbb79a7b8, pool 0x60013fa0, freeq 0, nxt 0xbb79a7b8, prv 0xbb79a7b8 2012-05-02 02:12:16.125780 : kjbsentscn[0x0.1ae0f0][to 2] 2012-05-02 02:12:16.125806 : GSIPC:SENDM: send msg 0xba0ee088 dest x20001 seq 177740 type 36 tkts xff0000 mlen x1680198 2012-05-02 02:12:16.125918 : kjbmscr(0x15c91.1)reqid=0x8(req 0xa4ff30f8)(rinst 1)hldr 2(infosz 200)(lseq x2b8) 2012-05-02 02:12:16.126959 : GSIPC:KSXPCB: msg 0xba0ee088 status 30, type 36, dest 2, rcvr 1 *** 2012-05-02 02:12:16.127 kclwcrs: wait=0 tm=1233 *** 2012-05-02 02:12:16.127 kclwcrs: got 1 blocks from ksxprcv WAIT #140336527348792: nam='gc cr block 2-way' ela= 1233 p1=1 p2=89233 p3=1 obj#=76896 tim=1335939136127199 2012-05-02 02:12:16.127272 : kjbcrcomplete[0x15c91.1 76896.0][0] 2012-05-02 02:12:16.127309 : kjbrcvdscn[0x0.1ae0f0][from 2][idx 2012-05-02 02:12:16.127329 : kjbrcvdscn[no bscn <= rscn 0x0.1ae0f0][from 2] ???? kjbcro[0x15c91.1 76896.0][4] kjbsentscn[0x0.1ae0f0][to 2] ?Instance 2??SCN=1ae0f0=1761520? block: (1/89233),???’gc cr block 2-way’ ??,?????????CR block? Instance 2 LMS TRACE 2012-05-02 02:12:15.634057 : GSIPC:RCVD: ksxp msg 0x7f16e1598588 sndr 1 seq 0.177740 type 36 tkts 0 2012-05-02 02:12:15.634094 : GSIPC:RCVD: watq msg 0x7f16e1598588 sndr 1, seq 177740, type 36, tkts 0 2012-05-02 02:12:15.634108 : GSIPC:TKT: collect msg 0x7f16e1598588 from 1 for rcvr -1, tickets 0 2012-05-02 02:12:15.634162 : kjbrcvdscn[0x0.1ae0f0][from 1][idx 2012-05-02 02:12:15.634186 : kjbrcvdscn[no bscn1, wm 32768, RMno 0, reminc 18, dom 0] kjga st 0x4, step 0.0.0, cinc 20, rmno 6, flags 0x0 lb 0, hb 0, myb 15250, drmb 15250, apifrz 0 GCS CLIENT END 2012-05-02 02:12:15.635211 : kjbdowncvt[0x15c91.1 76896.0][1][options x0] 2012-05-02 02:12:15.635230 : GSIPC:AMBUF: rcv buff 0x7f16e1c56420, pool rcvbuf, rqlen 1103 2012-05-02 02:12:15.635308 : GSIPC:GPBMSG: new bmsg 0x7f16e1c56490 mb 0x7f16e1c56420 msg 0x7f16e1c564b0 mlen 152 dest x101 flushsz -1 2012-05-02 02:12:15.635334 : kjbmslset(0x15c91.1)) seq 0x4 reqid=0x6 (shadow 0xb48bb330.xb)(rsn 2)(mas@1) 2012-05-02 02:12:15.635355 : GSIPC:SPBMSG: send bmsg 0x7f16e1c56490 blen 184 msg 0x7f16e1c564b0 mtype 33 attr|dest x30101 bsz|fsz x1ffff 2012-05-02 02:12:15.635377 : GSIPC:SNDQ: enq msg 0x7f16e1c56490, type 65521 seq 118669, inst 1, receiver 1, queued 1 *** 2012-05-02 02:12:15.635 kclccctx: cleanup copy 0x7f16e1d94798 2012-05-02 02:12:15.635479 : [kjmpmsgi:compl][type 36][msg 0x7f16e1598588][seq 177740.0][qtime 0][ptime 1257] 2012-05-02 02:12:15.635511 : GSIPC:BSEND: flushing sndq 0xb491dd28, id 1, dcx 0xbc516778, inst 1, rcvr 1 qlen 0 1 2012-05-02 02:12:15.635536 : GSIPC:BSEND: no batch1 msg 0x7f16e1c56490 type 65521 len 184 dest (1:1) 2012-05-02 02:12:15.635557 : kjbsentscn[0x0.1ae0f1][to 1] 2012-05-02 02:12:15.635578 : GSIPC:SENDM: send msg 0x7f16e1c56490 dest x10001 seq 118669 type 65521 tkts x10002 mlen xb800e8 WAIT #0: nam='gcs remote message' ela= 180 waittime=1 poll=0 event=0 obj#=0 tim=1335939135635819 2012-05-02 02:12:15.635853 : GSIPC:RCVD: ksxp msg 0x7f16e167e0b0 sndr 1 seq 0.177741 type 32 tkts 0 2012-05-02 02:12:15.635875 : GSIPC:RCVD: watq msg 0x7f16e167e0b0 sndr 1, seq 177741, type 32, tkts 0 2012-05-02 02:12:15.636012 : GSIPC:TKT: collect msg 0x7f16e167e0b0 from 1 for rcvr -1, tickets 0 2012-05-02 02:12:15.636040 : kjbrcvdscn[0x0.1ae0f1][from 1][idx 2012-05-02 02:12:15.636060 : kjbrcvdscn[no bscn <= rscn 0x0.1ae0f1][from 1] 2012-05-02 02:12:15.636082 : GSIPC:TKT: dest (1:1) rtkt not acked 1  unassigned bufs 0  tkts 0  newbufs 0 2012-05-02 02:12:15.636102 : GSIPC:TKT: remove ctx dest (1:1) 2012-05-02 02:12:15.636125 : [kjmxmpm][type 32][seq 0.177741][msg 0x7f16e167e0b0][from 1] 2012-05-02 02:12:15.636146 : kjbmpocr(0xb0.6)seq 0x1,reqid=0x23a,(client 0x9fff7b58,0x1)(from 1)(lseq xdf0) 2????LMS????????? ??gcs remote message GSIPC ????SCN=[0x0.1ae0f0] block=1/89233???,??BAST kjbmpbast(0x15c91.1),?? block=1/89233??????? ??fairness??(?11.2.0.3???_fairness_threshold=2),?current block?KCL: F156: fairness downconvert,?Xcurrent DownConvert? Scurrent: Instance 2: SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 2 0 3 1756658 ??Instance 2 LMS ?cr block??? kjbmslset(0x15c91.1)) ????SEND QUEUE GSIPC:SNDQ: enq msg 0x7f16e1c56490? ???????Instance 1???? block: (1/89233)??? ??????: Instance 2: SQL> select CURRENT_RESULTS,LIGHT_WORKS from v$cr_block_server; CURRENT_RESULTS LIGHT_WORKS --------------- ----------- 29273 437 Instance 1 session A: SQL> SQL> select * from test; ID ---------- 2 2 SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 3 1761942 3 1761932 1 0 3 1761520 Instance 2: SQL> select CURRENT_RESULTS,LIGHT_WORKS from v$cr_block_server; CURRENT_RESULTS LIGHT_WORKS --------------- ----------- 29274 437 select * from test END OF STMT PARSE #140336529675592:c=0,e=337,p=0,cr=0,cu=0,mis=0,r=0,dep=0,og=1,plh=1357081020,tim=1335939668940051 EXEC #140336529675592:c=0,e=96,p=0,cr=0,cu=0,mis=0,r=0,dep=0,og=1,plh=1357081020,tim=1335939668940204 WAIT #140336529675592: nam='SQL*Net message to client' ela= 5 driver id=1650815232 #bytes=1 p3=0 obj#=0 tim=1335939668940348 *** 2012-05-02 02:21:08.940 kclscrs: req=0 block=1/89233 2012-05-02 02:21:08.940676 : kjbcro[0x15c91.1 76896.0][5] *** 2012-05-02 02:21:08.940 kclscrs: req=0 typ=nowait-abort *** 2012-05-02 02:21:08.940 kclscrs: bid=1:3:1:0:f:21:0:0:10:0:0:0:1:2:4:1:20:0:0:0:c3:49:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:4:3:2:1:2:0:1f:0:4d:26:a3:52:0:0:0:0:c7:c:ca:62:c3:49:0:0:0:0:1:0:17:8e:47:76:1:2:dc:5:a9:fe:17:75:0:0:0:0:0:0:0:0:0:0:0:0:99:ed:0:0:0:0:0:0:10:0:0:0 2012-05-02 02:21:08.940799 : kjbcro[0x15c91.1 76896.0][5] 2012-05-02 02:21:08.940833 : GSIPC:GMBQ: buff 0xba0ee018, queue 0xbb79a7b8, pool 0x60013fa0, freeq 0, nxt 0xbb79a7b8, prv 0xbb79a7b8 2012-05-02 02:21:08.940859 : kjbsentscn[0x0.1ae28c][to 2] 2012-05-02 02:21:08.940870 : GSIPC:SENDM: send msg 0xba0ee088 dest x20001 seq 177810 type 36 tkts xff0000 mlen x1680198 2012-05-02 02:21:08.940976 : kjbmscr(0x15c91.1)reqid=0xa(req 0xa4ff30f8)(rinst 1)hldr 2(infosz 200)(lseq x2b8) 2012-05-02 02:21:08.941314 : GSIPC:KSXPCB: msg 0xba0ee088 status 30, type 36, dest 2, rcvr 1 *** 2012-05-02 02:21:08.941 kclwcrs: wait=0 tm=707 *** 2012-05-02 02:21:08.941 kclwcrs: got 1 blocks from ksxprcv 2012-05-02 02:21:08.941818 : kjbassume[0x15c91.1][sender 2][mymode x1][myrole x0][srole x0][flgs x0][spiscn 0x0.0][swscn 0x0.0] 2012-05-02 02:21:08.941852 : kjbrcvdscn[0x0.1ae28d][from 2][idx 2012-05-02 02:21:08.941871 : kjbrcvdscn[no bscn ??????????????SCN=[0x0.1ae28c]=1761932 Version?CR block, ????receive????Xcurrent Block??SCN=1ae28d=1761933,Instance 1???Xcurrent Block???build????????SCN=1761932?CR BLOCK, ????????Current block,?????????'gc current block 2-way'? ?????????????request current block,?????kjbcro;?????Instance 2?LMS???????Current Block: Instance 2 LMS trace: 2012-05-02 02:21:08.448743 : GSIPC:RCVD: ksxp msg 0x7f16e14a4398 sndr 1 seq 0.177810 type 36 tkts 0 2012-05-02 02:21:08.448778 : GSIPC:RCVD: watq msg 0x7f16e14a4398 sndr 1, seq 177810, type 36, tkts 0 2012-05-02 02:21:08.448798 : GSIPC:TKT: collect msg 0x7f16e14a4398 from 1 for rcvr -1, tickets 0 2012-05-02 02:21:08.448816 : kjbrcvdscn[0x0.1ae28c][from 1][idx 2012-05-02 02:21:08.448834 : kjbrcvdscn[no bscn <= rscn 0x0.1ae28c][from 1] 2012-05-02 02:21:08.448857 : GSIPC:TKT: dest (1:1) rtkt not acked 2  unassigned bufs 0  tkts 0  newbufs 0 2012-05-02 02:21:08.448875 : GSIPC:TKT: remove ctx dest (1:1) 2012-05-02 02:21:08.448970 : [kjmxmpm][type 36][seq 0.177810][msg 0x7f16e14a4398][from 1] 2012-05-02 02:21:08.448993 : kjbmpbast(0x15c91.1) reqid=0x6 (req 0xa4ff30f8)(reqinst 1)(reqid 10)(flags x0) *** 2012-05-02 02:21:08.449 kclcrrf: req=48054 block=1/89233 *** 2012-05-02 02:21:08.449 kcl_compress_block: compressed: 6 free space: 7680 2012-05-02 02:21:08.449085 : kjbsentscn[0x0.1ae28d][to 1] 2012-05-02 02:21:08.449142 : kjbdeliver[to 1][0xa4ff30f8][10][current 1] 2012-05-02 02:21:08.449164 : kjbmssch(reqlock 0xa4ff30f8,10)(to 1)(bsz 344) 2012-05-02 02:21:08.449183 : GSIPC:AMBUF: rcv buff 0x7f16e18bcec8, pool rcvbuf, rqlen 1102 *** 2012-05-02 02:21:08.449 kclccctx: cleanup copy 0x7f16e1d94838 *** 2012-05-02 02:21:08.449 kcltouched: touch seconds 3271 *** 2012-05-02 02:21:08.449 kclgrantlk: req=48054 2012-05-02 02:21:08.449347 : [kjmpmsgi:compl][type 36][msg 0x7f16e14a4398][seq 177810.0][qtime 0][ptime 1119] WAIT #0: nam='gcs remote message' ela= 568 waittime=1 poll=0 event=0 obj#=0 tim=1335939668449962 2012-05-02 02:21:08.450001 : GSIPC:RCVD: ksxp msg 0x7f16e1bb22a0 sndr 1 seq 0.177811 type 32 tkts 0 2012-05-02 02:21:08.450024 : GSIPC:RCVD: watq msg 0x7f16e1bb22a0 sndr 1, seq 177811, type 32, tkts 0 2012-05-02 02:21:08.450043 : GSIPC:TKT: collect msg 0x7f16e1bb22a0 from 1 for rcvr -1, tickets 0 2012-05-02 02:21:08.450060 : kjbrcvdscn[0x0.1ae28e][from 1][idx 2012-05-02 02:21:08.450078 : kjbrcvdscn[no bscn <= rscn 0x0.1ae28e][from 1] 2012-05-02 02:21:08.450097 : GSIPC:TKT: dest (1:1) rtkt not acked 3  unassigned bufs 0  tkts 0  newbufs 0 2012-05-02 02:21:08.450116 : GSIPC:TKT: remove ctx dest (1:1) 2012-05-02 02:21:08.450136 : [kjmxmpm][type 32][seq 0.177811][msg 0x7f16e1bb22a0][from 1] 2012-05-02 02:21:08.450155 : kjbmpocr(0xb0.6)seq 0x1,reqid=0x23e,(client 0x9fff7b58,0x1)(from 1)(lseq xdf4) ???Instance 2??LMS???,???build cr block,??????Instance 1?????Current Block??????Instance 2??v$cr_block_server??????LIGHT_WORKS?????current block transfer??????,??????? CR server? Light Work Rule(Light Work Rule?8i Cr Server?????????,?Remote LMS?? build CR????????,resource holder?LMS???????block,????CR build If creating the consistent read version block involves too much work (such as reading blocks from disk), then the holder sends the block to the requestor, and the requestor completes the CR fabrication. The holder maintains a fairness counter of CR requests. After the fairness threshold is reached, the holder downgrades it to lock mode.)? ??????? CR Request ????Current Block?? ???:??????class?block,CR server??????? ??undo block?? undo header block?CR quest, LMS????Current Block, ????? ???? ??????? block cleanout? CR  Version??????? ???????? data blocks, ??????? CR quest  & CR received?(???????Light Work Rule,LMS"??"), ??Current Block??DownConvert???S lock,??LMS???????ship??current version?block? ??????? , ?????? ,???????DownConvert?????”_fairness_threshold“???200,????Xcurrent Block?????Scurrent, ????LMS?????Current Version?Data Block: SQL> show parameter fair NAME TYPE VALUE ------------------------------------ ----------- ------------------------------ _fairness_threshold integer 200 Instance 1: SQL> update test set id=id+1 where id=4; 1 row updated. Instance 2: SQL> update test set id=id+1 where id=2; 1 row updated. SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 1 0 3 1838166 ?Instance 1? ????,? ??instance 2? v$cr_block_server?? instance 1 SQL> select * from test; ID ---------- 10 3 instance 2: SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 1 0 3 1883707 8 0 SQL> select * from test; ID ---------- 10 3 SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 1 0 3 1883707 8 0 ................... SQL> / STATE CR_SCN_BAS ---------- ---------- 2 0 3 1883707 3 1883695 repeat cr request on Instance 1 SQL> / STATE CR_SCN_BAS ---------- ---------- 8 0 3 1883707 3 1883695 ??????_fairness_threshold????????,?????200 ????????CR serve??Downgrade?lock, ????data block? CR Request????Receive? Current Block?

  Read the article

• AutoAudit 1.10c

  - by Paul Nielsen

  AutoAudit is a free SQL Server (2005, 2008) Code-Gen utility that creates Audit Trail Triggers with: · Created, Modified, and RowVersion (incrementing INT) columns to table · Creates View to reconstruct deleted rows · Creates UDF to reconstruct Row History · Schema Audit Trigger to track schema changes · Re-code-gens triggers when Alter Table changes the table Version 1.10c Adds: · Createdby and ModifiedBy columns. Pass the user to the column and AutoAudit records that username instead of the Suser_Sname...(read more)

  Read the article

• SQL Windowing screencast session for Cuppa Corner - rolling totals, data cleansing

  - by tonyrogerson

  In this 10 minute screencast I go through the basics of what I term windowing, which is basically the technique of filtering to a set of rows given a specific value, for instance a Sub-Query that aggregates or a join that returns more than just one row (for instance on a one to one relationship). http://sqlserverfaq.com/content/SQL-Basic-Windowing-using-Joins.aspx SQL below... USE tempdb go CREATE TABLE RollingTotals_Nesting ( client_id int not null, transaction_date date not null, transaction_amount...(read more)

  Read the article

• Stairway to SQL Server Indexes: Step 1, Introduction to Indexes

  Indexes are the database objects that enable SQL Server to satisfy each data access request from a client application with the minimum amount of effort, resulting in the maximum performance of individual requests while also reducing the impact of one request upon another. Prerequisites: Familiarity with the following relational database concepts: Table, row, primary key, foreign key Join SQL Backup’s 35,000+ customers to compress and strengthen your backups "SQL Backup will be a REAL boost to any DBA lucky enough to use it." Jonathan Allen. Download a free trial now.

  Read the article

• Paper on Linux memory access techniques sought

  - by James

  Over on stackoverflow someone posted a link to a paper written by a Linux kernel engineer about how to use computers and RAM. He started off by explaining how RAM works (right down to the flip-flops) and then went on to discuss performance problems associated with operations on matrices (column vs row accesses), offered solutions and then dealt with some stuff MMX instructions can do. Sorry it's a bit vague but I can't find it anywhere. I think the guy had a Scandinavian name, possibly Anders

  Read the article

• Thank You for a Great Welcome for Oracle GoldenGate 11g Release 2

  - by Irem Radzik

  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:Calibri; mso-fareast-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Yesterday morning we had two launch webcasts for Oracle GoldenGate 11g Release 2. I had the pleasure to present, as well as moderate the Q&A panels in both of these webcasts. Both events had hundreds of live attendees, sending us over 150 questions. Even though we left 30 minutes for Q&A, it was not nearly enough time to address for all the insightful questions our audience sent. Our product management team and I really appreciate the interaction we had yesterday and we are starting to respond back with outstanding questions today. Oracle GoldenGate’s new release launch also had great welcome from the media. You can find the links for various articles on the new release below: ITBusinessEdge Oracle Embraces Cross-Platform Data Integration Information Week: Oracle Real-Time Advance Taps Compressed Data Integration Developer News, Oracle GoldenGate Adds Deeper Oracle Integration, Extends Real-Time Performance CIO, Oracle GoldenGate Buddies Up with Sibling Software DBTA, Real-Time Data Integration: Oracle GoldenGate 11g Release 2 Now Available CBR Oracle unveils GoldenGate 11g Release 2 real-time data integration application In this blog, I want to address some of the frequently asked questions that came up during the webcasts. You can find the top questions and their answers along with related resources below. We will continue to address frequently asked questions via future blogs. Q: Will the new Integrated Capture for Oracle Database replace the Classic Capture? If not, which one do I use when? A: No, Classic Capture will be around for long time. Core platform specific features, bug fixes, and patches will be available for both Capture processes.Oracle Database specific features will be only available in the Integrated Capture. The Integrated Capture for Oracle Database is an option for users that need to capture data from compressed tables or need support for XML data types, XA on RAC. Users who don’t leverage these features should continue to use our Classic Capture. For more information on Oracle GoldenGate 11g Release 2 I recommend to check out the White paper: Oracle GoldenGate 11gR2 New Features as well as other technical white papers we have on OTN.                                                         For those of you coming to OpenWorld, please attend the related session: Extracting Data in Oracle GoldenGate Integrated Capture Mode, Monday Oct 1st 1:45pm Moscone South – 102 to learn more about this new feature. Q: What is new in Conflict Detection and Resolution? And how does it work? A: There are now pre-built functions to identify the conditions under which an error occurs and how to handle the record when the condition occurs. Error conditions handled include inserts into a target table where the row already exists, updates or deletes to target table rows that exist, but the original source data (before columns) do not match the existing data in the target row, and updates or deletes where the row does not exist in the target database table.Foreach of these conditions a method to handle the error is specified.  Please check out our recent blog on this topic and the White paper: Oracle GoldenGate 11gR2 New Features white paper.  Also, for those attending OpenWorld please attend the session: Best Practices for Conflict Detection and Resolution in Oracle GoldenGate for Active/Active-  Wednesday Oct 3rd  3:30pm Mascone 3000 Q: Does Oracle GoldenGate Veridata and the Management Pack require additional licenses, or is it incorporated with the GoldenGate license? A: Oracle GoldenGate Veridata and Oracle Management Pack for Oracle GoldenGate are additional products and require separate licenses. Please check out Oracle's price list here. Q: Does GoldenGate - Oracle Enterprise Manager Plug-in require additional license? A: Oracle Enterprise Manager Plug-in is included in the Oracle Management Pack for Oracle GoldenGate license, which is separate from Oracle GoldenGate license. There is no separate license for the Enterprise Manager Plug-in by itself. Oracle GoldenGate Monitor, Oracle GoldenGate Director, and Enterprise Manager Plug-in are included in the Management Pack for Oracle GoldenGate license. Please check out Management Pack for Oracle GoldenGate data sheet for more info on this product bundle. Q: Is Oracle GoldenGate replacing Oracle Streams product? A: Oracle GoldenGate is the strategic data replication product. Therefore, Oracle Streams will continue to be supported, but will not be actively enhanced. Rather, the best elements of Oracle Streams will be added to Oracle GoldenGate. Conflict management is one of them and with the latest release Oracle GoldenGate has a more advanced conflict management offering. Current customers depending on Oracle Streams will continue to be fully supported. Q: How is Oracle GoldenGate different than Oracle Data Integrator? A: Oracle Data Integrator is designed for fast bulk data movement and transformation between heterogeneous systems, while GoldenGate is designed for real-time movement of transactions between heterogeneous systems. These two products are completely complementary where GoldenGate provides low-impact real-time change data capture and delivery to a staging area on the target. And Oracle Data Integrator transforms this data and loads the DW tables. In fact, Oracle Data Integrator integrates with GoldenGate to use GoldenGate’s Capture process as one option for its CDC mechanism. We have several customers that deployed GoldenGate and ODI together to feed real-time data to their data warehousing solutions. Please also check out Oracle Data Integrator Changed Data Capture with Oracle GoldenGate Data Sheet (PDF). Thank you again very much for welcoming Oracle GoldenGate 11g Release 2 and stay in touch with us for more exciting news, updates, and events.

  Read the article

• Text Trimming in Silverlight 4

  - by dwahlin

  Silverlight 4 has a lot of great features that can be used to build consumer and Line of Business (LOB) applications. Although Webcam support, RichTextBox, MEF, WebBrowser and other new features are pretty exciting, I’m actually enjoying some of the more simple features that have been added such as text trimming, built-in wheel scrolling with ScrollViewer and data binding enhancements such as StringFormat. In this post I’ll give a quick introduction to a simple yet productive feature called text trimming and show how it eliminates a lot of code compared to Silverlight 3. The TextBlock control contains a new property in Silverlight 4 called TextTrimming that can be used to add an ellipsis (…) to text that doesn’t fit into a specific area on the user interface. Before the TextTrimming property was available I used a value converter to trim text which meant passing in a specific number of characters that I wanted to show by using a parameter: public class StringTruncateConverter : IValueConverter { #region IValueConverter Members public object Convert(object value, Type targetType, object parameter, System.Globalization.CultureInfo culture) { int maxLength; if (int.TryParse(parameter.ToString(), out maxLength)) { string val = (value == null) ? null : value.ToString(); if (val != null && val.Length > maxLength) { return val.Substring(0, maxLength) + ".."; } } return value; } public object ConvertBack(object value, Type targetType, object parameter, System.Globalization.CultureInfo culture) { throw new NotImplementedException(); } #endregion } To use the StringTruncateConverter I'd define the standard xmlns prefix that referenced the namespace and assembly, add the class into the application’s Resources section and then use the class while data binding as shown next: <TextBlock Grid.Column="1" Grid.Row="3" ToolTipService.ToolTip="{Binding ReportSummary.ProjectManagers}" Text="{Binding ReportSummary.ProjectManagers, Converter={StaticResource StringTruncateConverter},ConverterParameter=16}" Style="{StaticResource SummaryValueStyle}" /> With Silverlight 4 I can define the TextTrimming property directly in XAML or use the new Property window in Visual Studio 2010 to set it to a value of WordEllipsis (the default value is None): <TextBlock Grid.Column="1" Grid.Row="4" ToolTipService.ToolTip="{Binding ReportSummary.ProjectCoordinators}" Text="{Binding ReportSummary.ProjectCoordinators}" TextTrimming="WordEllipsis" Style="{StaticResource SummaryValueStyle}"/> The end result is a nice trimming of the text that doesn’t fit into the target area as shown with the Coordinator and Foremen sections below. My data binding statements are now much smaller and I can eliminate the StringTruncateConverter class completely.   For more information about onsite, online and video training, mentoring and consulting solutions for .NET, SharePoint or Silverlight please visit http://www.thewahlingroup.com.

  Read the article

• GoldenGate 12c Trail Encryption and Credentials with Oracle Wallet

  - by hamsun

  I have been asked more than once whether the Oracle Wallet supports GoldenGate trail encryption. Although GoldenGate has supported encryption with the ENCKEYS file for years, Oracle GoldenGate 12c now also supports encryption using the Oracle Wallet. This helps improve security and makes it easier to administer. Two types of wallets can be configured in Oracle GoldenGate 12c: The wallet that holds the master keys, used with trail or TCP/IP encryption and decryption, stored in the new 12c dirwlt/cwallet.sso file.   The wallet that holds the Oracle Database user IDs and passwords stored in the ‘credential store’ stored in the new 12c dircrd/cwallet.sso file.   A wallet can be created using a ‘create wallet’  command.  Adding a master key to an existing wallet is easy using ‘open wallet’ and ‘add masterkey’ commands.   GGSCI (EDLVC3R27P0) 42> open wallet Opened wallet at location 'dirwlt'. GGSCI (EDLVC3R27P0) 43> add masterkey Master key 'OGG_DEFAULT_MASTERKEY' added to wallet at location 'dirwlt'.   Existing GUI Wallet utilities that come with other products such as the Oracle Database “Oracle Wallet Manager” do not work on this version of the wallet. The default Oracle Wallet can be changed.   GGSCI (EDLVC3R27P0) 44> sh ls -ltr ./dirwlt/* -rw-r----- 1 oracle oinstall 685 May 30 05:24 ./dirwlt/cwallet.sso GGSCI (EDLVC3R27P0) 45> info masterkey Masterkey Name:                 OGG_DEFAULT_MASTERKEY Creation Date:                  Fri May 30 05:24:04 2014 Version:        Creation Date:                  Status: 1               Fri May 30 05:24:04 2014        Current   The second wallet file is used for the credential used to connect to a database, without exposing the user id or password. Once it is configured, this file can be copied so that credentials are available to connect to the source or target database.   GGSCI (EDLVC3R27P0) 48> sh cp ./dircrd/cwallet.sso $GG_EURO_HOME/dircrd GGSCI (EDLVC3R27P0) 49> sh ls -ltr ./dircrd/* -rw-r----- 1 oracle oinstall 709 May 28 05:39 ./dircrd/cwallet.sso   The encryption wallet file can also be copied to the target machine so the replicat has access to the master key to decrypt records that are encrypted in the trail. Similar to the old ENCKEYS file, the master keys wallet created on the source host must either be stored in a centrally available disk or copied to all GoldenGate target hosts. The wallet is in a platform-independent format, although it is not certified for the iSeries, z/OS, and NonStop platforms.   GGSCI (EDLVC3R27P0) 50> sh cp ./dirwlt/cwallet.sso $GG_EURO_HOME/dirwlt   The new 12c UserIdAlias parameter is used to locate the credential in the wallet so the source user id and password does not need to be stored as a parameter as long as it is in the wallet.   GGSCI (EDLVC3R27P0) 52> view param extwest extract extwest exttrail ./dirdat/ew useridalias gguamer table west.*; The EncryptTrail parameter is used to encrypt the trail using the Advanced Encryption Standard and can be used with a primary extract or pump extract. GGSCI (EDLVC3R27P0) 54> view param pwest extract pwest encrypttrail AES256 rmthost easthost, mgrport 15001 rmttrail ./dirdat/pe passthru table west.*;   Once the extracts are running, records can be encrypted using the wallet.   GGSCI (EDLVC3R27P0) 60> info extract *west EXTRACT    EXTWEST   Last Started 2014-05-30 05:26   Status RUNNING Checkpoint Lag       00:00:17 (updated 00:00:01 ago) Process ID           24982 Log Read Checkpoint  Oracle Integrated Redo Logs                      2014-05-30 05:25:53                      SCN 0.0 (0) EXTRACT    PWEST     Last Started 2014-05-30 05:26   Status RUNNING Checkpoint Lag       24:02:32 (updated 00:00:05 ago) Process ID           24983 Log Read Checkpoint  File ./dirdat/ew000004                      2014-05-29 05:23:34.748949  RBA 1483   The ‘info masterkey’ command is used to confirm the wallet contains the key after copying it to the target machine. The key is needed to decrypt the data in the trail before the replicat applies the changes to the target database.   GGSCI (EDLVC3R27P0) 41> open wallet Opened wallet at location 'dirwlt'. GGSCI (EDLVC3R27P0) 42> info masterkey Masterkey Name:                 OGG_DEFAULT_MASTERKEY Creation Date:                  Fri May 30 05:24:04 2014 Version:        Creation Date:                  Status: 1               Fri May 30 05:24:04 2014        Current   Once the replicat is running, records can be decrypted using the wallet.   GGSCI (EDLVC3R27P0) 44> info reast REPLICAT   REAST     Last Started 2014-05-30 05:28   Status RUNNING INTEGRATED Checkpoint Lag       00:00:00 (updated 00:00:02 ago) Process ID           25057 Log Read Checkpoint  File ./dirdat/pe000004                      2014-05-30 05:28:16.000000  RBA 1546   There is no need for the DecryptTrail parameter when using the Oracle Wallet, unlike when using the ENCKEYS file.   GGSCI (EDLVC3R27P0) 45> view params reast replicat reast assumetargetdefs discardfile ./dirrpt/reast.dsc, purge useridalias ggueuro map west.*, target east.*;   Once a record is inserted into the source table and committed, the encryption can be verified using logdump and then querying the target table.   AMER_SQL>insert into west.branch values (50, 80071); 1 row created.   AMER_SQL>commit; Commit complete.   The following encrypted record can be found using logdump. Logdump 40 >n 2014/05/30 05:28:30.001.154 Insert               Len    28 RBA 1546 Name: WEST.BRANCH After  Image:                                             Partition 4   G  s    0a3e 1ba3 d924 5c02 eade db3f 61a9 164d 8b53 4331 | .>...$\....?a..M.SC1   554f e65a 5185 0257                               | UO.ZQ..W  Bad compressed block, found length of  7075 (x1ba3), RBA 1546   GGS tokens: TokenID x52 'R' ORAROWID         Info x00  Length   20  4141 4157 7649 4141 4741 4141 4144 7541 4170 0001 | AAAWvIAAGAAAADuAAp..  TokenID x4c 'L' LOGCSN           Info x00  Length    7  3231 3632 3934 33                                 | 2162943  TokenID x36 '6' TRANID           Info x00  Length   10  3130 2e31 372e 3135 3031                          | 10.17.1501  The replicat automatically decrypted this record from the trail and then inserted the row to the target table using the wallet. This select verifies the row was inserted into the target database and the data is not encrypted. EURO_SQL>select * from branch where branch_number=50; BRANCH_NUMBER                  BRANCH_ZIP -------------                                   ----------    50                                              80071   Book a seat in an upcoming Oracle GoldenGate 12c: Fundamentals for Oracle course now to learn more about GoldenGate 12c new features including how to use GoldenGate with the Oracle wallet, credentials, integrated extracts, integrated replicats, the Oracle Universal Installer, and other new features. Looking for another course? View all Oracle GoldenGate training.   Randy Richeson joined Oracle University as a Senior Principal Instructor in March 2005. He is an Oracle Certified Professional (10g-12c) and a GoldenGate Certified Implementation Specialist (10-11g). He has taught GoldenGate since 2010 and also has experience teaching other technical curriculums including GoldenGate Monitor, Veridata, JD Edwards, PeopleSoft, and the Oracle Application Server.

  Read the article

• WPF PropertyGrid - MVVM techniques

  How to build a multicolumn ListView that selects cell templates based on the row data type; and how to create a ViewModel on the fly for each cell template.

  Read the article

• MVP in 2010

  Microsoft has just named me an MVP for the seventh time in a row!More .NET adventures with me expected in 2010......Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

  Read the article

• The blocking nature of aggregates

  - by Rob Farley

  I wrote a post recently about how query tuning isn’t just about how quickly the query runs – that if you have something (such as SSIS) that is consuming your data (and probably introducing a bottleneck), then it might be more important to have a query which focuses on getting the first bit of data out. You can read that post here.  In particular, we looked at two operators that could be used to ensure that a query returns only Distinct rows. and The Sort operator pulls in all the data, sorts it (discarding duplicates), and then pushes out the remaining rows. The Hash Match operator performs a Hashing function on each row as it comes in, and then looks to see if it’s created a Hash it’s seen before. If not, it pushes the row out. The Sort method is quicker, but has to wait until it’s gathered all the data before it can do the sort, and therefore blocks the data flow. But that was my last post. This one’s a bit different. This post is going to look at how Aggregate functions work, which ties nicely into this month’s T-SQL Tuesday. I’ve frequently explained about the fact that DISTINCT and GROUP BY are essentially the same function, although DISTINCT is the poorer cousin because you have less control over it, and you can’t apply aggregate functions. Just like the operators used for Distinct, there are different flavours of Aggregate operators – coming in blocking and non-blocking varieties. The example I like to use to explain this is a pile of playing cards. If I’m handed a pile of cards and asked to count how many cards there are in each suit, it’s going to help if the cards are already ordered. Suppose I’m playing a game of Bridge, I can easily glance at my hand and count how many there are in each suit, because I keep the pile of cards in order. Moving from left to right, I could tell you I have four Hearts in my hand, even before I’ve got to the end. By telling you that I have four Hearts as soon as I know, I demonstrate the principle of a non-blocking operation. This is known as a Stream Aggregate operation. It requires input which is sorted by whichever columns the grouping is on, and it will release a row as soon as the group changes – when I encounter a Spade, I know I don’t have any more Hearts in my hand. Alternatively, if the pile of cards are not sorted, I won’t know how many Hearts I have until I’ve looked through all the cards. In fact, to count them, I basically need to put them into little piles, and when I’ve finished making all those piles, I can count how many there are in each. Because I don’t know any of the final numbers until I’ve seen all the cards, this is blocking. This performs the aggregate function using a Hash Match. Observant readers will remember this from my Distinct example. You might remember that my earlier Hash Match operation – used for Distinct Flow – wasn’t blocking. But this one is. They’re essentially doing a similar operation, applying a Hash function to some data and seeing if the set of values have been seen before, but before, it needs more information than the mere existence of a new set of values, it needs to consider how many of them there are. A lot is dependent here on whether the data coming out of the source is sorted or not, and this is largely determined by the indexes that are being used. If you look in the Properties of an Index Scan, you’ll be able to see whether the order of the data is required by the plan. A property called Ordered will demonstrate this. In this particular example, the second plan is significantly faster, but is dependent on having ordered data. In fact, if I force a Stream Aggregate on unordered data (which I’m doing by telling it to use a different index), a Sort operation is needed, which makes my plan a lot slower. This is all very straight-forward stuff, and information that most people are fully aware of. I’m sure you’ve all read my good friend Paul White (@sql_kiwi)’s post on how the Query Optimizer chooses which type of aggregate function to apply. But let’s take a look at SQL Server Integration Services. SSIS gives us a Aggregate transformation for use in Data Flow Tasks, but it’s described as Blocking. The definitive article on Performance Tuning SSIS uses Sort and Aggregate as examples of Blocking Transformations. I’ve just shown you that Aggregate operations used by the Query Optimizer are not always blocking, but that the SSIS Aggregate component is an example of a blocking transformation. But is it always the case? After all, there are plenty of SSIS Performance Tuning talks out there that describe the value of sorted data in Data Flow Tasks, describing the IsSorted property that can be set through the Advanced Editor of your Source component. And so I set about testing the Aggregate transformation in SSIS, to prove for sure whether providing Sorted data would let the Aggregate transform behave like a Stream Aggregate. (Of course, I knew the answer already, but it helps to be able to demonstrate these things). A query that will produce a million rows in order was in order. Let me rephrase. I used a query which produced the numbers from 1 to 1000000, in a single field, ordered. The IsSorted flag was set on the source output, with the only column as SortKey 1. Performing an Aggregate function over this (counting the number of rows per distinct number) should produce an additional column with 1 in it. If this were being done in T-SQL, the ordered data would allow a Stream Aggregate to be used. In fact, if the Query Optimizer saw that the field had a Unique Index on it, it would be able to skip the Aggregate function completely, and just insert the value 1. This is a shortcut I wouldn’t be expecting from SSIS, but certainly the Stream behaviour would be nice. Unfortunately, it’s not the case. As you can see from the screenshots above, the data is pouring into the Aggregate function, and not being released until all million rows have been seen. It’s not doing a Stream Aggregate at all. This is expected behaviour. (I put that in bold, because I want you to realise this.) An SSIS transformation is a piece of code that runs. It’s a physical operation. When you write T-SQL and ask for an aggregation to be done, it’s a logical operation. The physical operation is either a Stream Aggregate or a Hash Match. In SSIS, you’re telling the system that you want a generic Aggregation, that will have to work with whatever data is passed in. I’m not saying that it wouldn’t be possible to make a sometimes-blocking aggregation component in SSIS. A Custom Component could be created which could detect whether the SortKeys columns of the input matched the Grouping columns of the Aggregation, and either call the blocking code or the non-blocking code as appropriate. One day I’ll make one of those, and publish it on my blog. I’ve done it before with a Script Component, but as Script components are single-use, I was able to handle the data knowing everything about my data flow already. As per my previous post – there are a lot of aspects in which tuning SSIS and tuning execution plans use similar concepts. In both situations, it really helps to have a feel for what’s going on behind the scenes. Considering whether an operation is blocking or not is extremely relevant to performance, and that it’s not always obvious from the surface. In a future post, I’ll show the impact of blocking v non-blocking and synchronous v asynchronous components in SSIS, using some of LobsterPot’s Script Components and Custom Components as examples. When I get that sorted, I’ll make a Stream Aggregate component available for download.

  Read the article

• The blocking nature of aggregates

  - by Rob Farley

  I wrote a post recently about how query tuning isn’t just about how quickly the query runs – that if you have something (such as SSIS) that is consuming your data (and probably introducing a bottleneck), then it might be more important to have a query which focuses on getting the first bit of data out. You can read that post here.  In particular, we looked at two operators that could be used to ensure that a query returns only Distinct rows. and The Sort operator pulls in all the data, sorts it (discarding duplicates), and then pushes out the remaining rows. The Hash Match operator performs a Hashing function on each row as it comes in, and then looks to see if it’s created a Hash it’s seen before. If not, it pushes the row out. The Sort method is quicker, but has to wait until it’s gathered all the data before it can do the sort, and therefore blocks the data flow. But that was my last post. This one’s a bit different. This post is going to look at how Aggregate functions work, which ties nicely into this month’s T-SQL Tuesday. I’ve frequently explained about the fact that DISTINCT and GROUP BY are essentially the same function, although DISTINCT is the poorer cousin because you have less control over it, and you can’t apply aggregate functions. Just like the operators used for Distinct, there are different flavours of Aggregate operators – coming in blocking and non-blocking varieties. The example I like to use to explain this is a pile of playing cards. If I’m handed a pile of cards and asked to count how many cards there are in each suit, it’s going to help if the cards are already ordered. Suppose I’m playing a game of Bridge, I can easily glance at my hand and count how many there are in each suit, because I keep the pile of cards in order. Moving from left to right, I could tell you I have four Hearts in my hand, even before I’ve got to the end. By telling you that I have four Hearts as soon as I know, I demonstrate the principle of a non-blocking operation. This is known as a Stream Aggregate operation. It requires input which is sorted by whichever columns the grouping is on, and it will release a row as soon as the group changes – when I encounter a Spade, I know I don’t have any more Hearts in my hand. Alternatively, if the pile of cards are not sorted, I won’t know how many Hearts I have until I’ve looked through all the cards. In fact, to count them, I basically need to put them into little piles, and when I’ve finished making all those piles, I can count how many there are in each. Because I don’t know any of the final numbers until I’ve seen all the cards, this is blocking. This performs the aggregate function using a Hash Match. Observant readers will remember this from my Distinct example. You might remember that my earlier Hash Match operation – used for Distinct Flow – wasn’t blocking. But this one is. They’re essentially doing a similar operation, applying a Hash function to some data and seeing if the set of values have been seen before, but before, it needs more information than the mere existence of a new set of values, it needs to consider how many of them there are. A lot is dependent here on whether the data coming out of the source is sorted or not, and this is largely determined by the indexes that are being used. If you look in the Properties of an Index Scan, you’ll be able to see whether the order of the data is required by the plan. A property called Ordered will demonstrate this. In this particular example, the second plan is significantly faster, but is dependent on having ordered data. In fact, if I force a Stream Aggregate on unordered data (which I’m doing by telling it to use a different index), a Sort operation is needed, which makes my plan a lot slower. This is all very straight-forward stuff, and information that most people are fully aware of. I’m sure you’ve all read my good friend Paul White (@sql_kiwi)’s post on how the Query Optimizer chooses which type of aggregate function to apply. But let’s take a look at SQL Server Integration Services. SSIS gives us a Aggregate transformation for use in Data Flow Tasks, but it’s described as Blocking. The definitive article on Performance Tuning SSIS uses Sort and Aggregate as examples of Blocking Transformations. I’ve just shown you that Aggregate operations used by the Query Optimizer are not always blocking, but that the SSIS Aggregate component is an example of a blocking transformation. But is it always the case? After all, there are plenty of SSIS Performance Tuning talks out there that describe the value of sorted data in Data Flow Tasks, describing the IsSorted property that can be set through the Advanced Editor of your Source component. And so I set about testing the Aggregate transformation in SSIS, to prove for sure whether providing Sorted data would let the Aggregate transform behave like a Stream Aggregate. (Of course, I knew the answer already, but it helps to be able to demonstrate these things). A query that will produce a million rows in order was in order. Let me rephrase. I used a query which produced the numbers from 1 to 1000000, in a single field, ordered. The IsSorted flag was set on the source output, with the only column as SortKey 1. Performing an Aggregate function over this (counting the number of rows per distinct number) should produce an additional column with 1 in it. If this were being done in T-SQL, the ordered data would allow a Stream Aggregate to be used. In fact, if the Query Optimizer saw that the field had a Unique Index on it, it would be able to skip the Aggregate function completely, and just insert the value 1. This is a shortcut I wouldn’t be expecting from SSIS, but certainly the Stream behaviour would be nice. Unfortunately, it’s not the case. As you can see from the screenshots above, the data is pouring into the Aggregate function, and not being released until all million rows have been seen. It’s not doing a Stream Aggregate at all. This is expected behaviour. (I put that in bold, because I want you to realise this.) An SSIS transformation is a piece of code that runs. It’s a physical operation. When you write T-SQL and ask for an aggregation to be done, it’s a logical operation. The physical operation is either a Stream Aggregate or a Hash Match. In SSIS, you’re telling the system that you want a generic Aggregation, that will have to work with whatever data is passed in. I’m not saying that it wouldn’t be possible to make a sometimes-blocking aggregation component in SSIS. A Custom Component could be created which could detect whether the SortKeys columns of the input matched the Grouping columns of the Aggregation, and either call the blocking code or the non-blocking code as appropriate. One day I’ll make one of those, and publish it on my blog. I’ve done it before with a Script Component, but as Script components are single-use, I was able to handle the data knowing everything about my data flow already. As per my previous post – there are a lot of aspects in which tuning SSIS and tuning execution plans use similar concepts. In both situations, it really helps to have a feel for what’s going on behind the scenes. Considering whether an operation is blocking or not is extremely relevant to performance, and that it’s not always obvious from the surface. In a future post, I’ll show the impact of blocking v non-blocking and synchronous v asynchronous components in SSIS, using some of LobsterPot’s Script Components and Custom Components as examples. When I get that sorted, I’ll make a Stream Aggregate component available for download.

  Read the article

• COLUMNS_UPDATED() for audit triggers

  - by Piotr Rodak

  In SQL Server 2005, triggers are pretty much the only option if you want to audit changes to a table. There are many ways you can decide to store the change information. You may decide to store every changed row as a whole, either in a history table or as xml in audit table. The former case requires having a history table with exactly same schema as the audited table, the latter makes data retrieval and management of the table a bit tricky. Both approaches also suffer from the tendency to consume...(read more)

  Read the article

• Oracle Tutor: Create Accessible Content for the Disabled Community

  - by emily.chorba(at)oracle.com

  For many reasons--legal, business, and ethical--Oracle recognizes the need for its applications, and our customers' and partners' products built with our tools, to be usable by the disabled community. The following features of Tutor Author and Publisher software facilitate the creation of accessible HTML content for the disabled community.TablesThe following formatting guidelines will ensure that Tutor documents containing tables will be accessible once they are converted to HTML.• Determine whether a table is a "data table" or whether you are using a table simply for formatting. If it's a data table, you must use a heading for each column, and you should format this heading row as "table heading" style and select Table > Heading Rows Repeat.• For non data tables, it is not necessary to include a heading row.GraphicsTo create accessible graphics, add a caption to the graphic. In Microsoft Office 2000 and greater, right-click on the graphic and select Format Picture > Web (tab) > Alternative Text or select the graphic then Format > Picture > Web (tab) Alternative Text. Enter the appropriate information in the dialog box.When a document containing a graphic with alternative text is converted to HTML by Tutor, the HTML document will contain the appropriate accessibility information.Javascript elementsThe tabbed format and other javascript elements in the HTML version of the Tutor documents may not be accessible to all users. A link to an accessible/printable version of the document is available in the upper right corner of all Tutor documents.Repetitive dataIf repetitive data such as the distribution section and the ownership section are causing accessibility issues with your Tutor documents, you can insert a bookmark in the appropriate location of the document, and, when the document is converted to HTML, the bookmark will be converted to an A NAME reference (also known as an internal link). With this reference, you can create a link in Header.txt that can be prepended to each Tutor document that allows the user to bypass repetitive sections. Tutor and Oracle ApplicationsRegarding accessibility, please check Oracle's website on accessibility http://www.oracle.com/accessibility/ to find out what version of E-Business Suite is certified to work with screen readers. Oracle Tutor 11.5.6A and greater works with screen readers such as JAWS.There is no certification between Oracle Tutor and Oracle Applications because there are no related dependencies. It doesn't matter which version of the Oracle Applications you are running. Therefore, it is possible to use Oracle Tutor with earlier versions of Oracle Applications.Oracle Business Process Converter and Oracle ApplicationsOracle Business Process Converter (OBPC) converts Visio, XPDL, and Tutor models to Oracle Business Process Architect and Oracle Business Process Management. The OBPC is one of a collection of plugins to Oracle JDeveloper. Please see the VPAT as the same considerations apply.Learn MoreFor more information about Tutor, visit Oracle.Com or the Tutor Blog. Post your questions at the Tutor Forum. Emily ChorbaPrinciple Product Manager Oracle Tutor & BPM

  Read the article

• Common header file for C++ and JavaScipt

  - by paperjam

  I have an app that runs a C++ server backend and Javascript on the client. I would like to define certain strings once only, for both pieces of code. For example, I might have a CSS class "row-hover" - I want to define this class name in one place only in case I change it later. Is there an easy way to include, or read, some sort of common definitions file into both C++ and JavaScript? Ideally as a compile / preprocessing step but any neat approach good.

  Read the article

• Integrating Oracle Hyperion Smart View Data Queries with MS Word and Power Point

  - by Andreea Vaduva

  Untitled Document table { border: thin solid; } Most Smart View users probably appreciate that they can use just one add-in to access data from the different sources they might work with, like Oracle Essbase, Oracle Hyperion Planning, Oracle Hyperion Financial Management and others. But not all of them are aware of the options to integrate data analyses not only in Excel, but also in MS Word or Power Point. While in the past, copying and pasting single numbers or tables from a recent analysis in Excel made the pasted content a static snapshot, copying so called Data Points now creates dynamic, updateable references to the data source. It also provides additional nice features, which can make life easier and less stressful for Smart View users. So, how does this option work: after building an ad-hoc analysis with Smart View as usual in an Excel worksheet, any area including data cells/numbers from the database can be highlighted in order to copy data points - even single data cells only.   TIP It is not necessary to highlight and copy the row or column descriptions   Next from the Smart View ribbon select Copy Data Point. Then transfer to the Word or Power Point document into which the selected content should be copied. Note that in these Office programs you will find a menu item Smart View;from it select the Paste Data Point icon. The copied details from the Excel report will be pasted, but showing #NEED_REFRESH in the data cells instead of the original numbers. =After clicking the Refresh icon on the Smart View menu the data will be retrieved and displayed. (Maybe at that moment a login window pops up and you need to provide your credentials.) It works in the same way if you just copy one single number without any row or column descriptions, for example in order to incorporate it into a continuous text: Before refresh: After refresh: From now on for any subsequent updates of the data shown in your documents you only need to refresh data by clicking the Refresh button on the Smart View menu, without copying and pasting the context or content again. As you might realize, trying out this feature on your own, there won’t be any Point of View shown in the Office document. Also you have seen in the example, where only a single data cell was copied, that there aren’t any member names or row/column descriptions copied, which are usually required in an ad-hoc report in order to exactly define where data comes from or how data is queried from the source. Well, these definitions are not visible, but they are transferred to the Word or Power Point document as well. They are stored in the background for each individual data cell copied and can be made visible by double-clicking the data cell as shown in the following screen shot (but which is taken from another context).   So for each cell/number the complete connection information is stored along with the exact member/cell intersection from the database. And that’s not all: you have the chance now to exchange the members originally selected in the Point of View (POV) in the Excel report. Remember, at that time we had the following selection:   By selecting the Manage POV option from the Smart View meny in Word or Power Point…   … the following POV Manager – Queries window opens:   You can now change your selection for each dimension from the original POV by either double-clicking the dimension member in the lower right box under POV: or by selecting the Member Selector icon on the top right hand side of the window. After confirming your changes you need to refresh your document again. Be aware, that this will update all (!) numbers taken from one and the same original Excel sheet, even if they appear in different locations in your Office document, reflecting your recent changes in the POV. TIP Build your original report already in a way that dimensions you might want to change from within Word or Power Point are placed in the POV. And there is another really nice feature I wouldn’t like to miss mentioning: Using Dynamic Data Points in the way described above, you will never miss or need to search again for your original Excel sheet from which values were taken and copied as data points into an Office document. Because from even only one single data cell Smart View is able to recreate the entire original report content with just a few clicks: Select one of the numbers from within your Word or Power Point document by double-clicking.   Then select the Visualize in Excel option from the Smart View menu. Excel will open and Smart View will rebuild the entire original report, including POV settings, and retrieve all data from the most recent actual state of the database. (It might be necessary to provide your credentials before data is displayed.) However, in order to make this work, an active online connection to your databases on the server is necessary and at least read access to the retrieved data. But apart from this, your newly built Excel report is fully functional for ad-hoc analysis and can be used in the common way for drilling, pivoting and all the other known functions and features. So far about embedding Dynamic Data Points into Office documents and linking them back into Excel worksheets. You can apply this in the described way with ad-hoc analyses directly on Essbase databases or using Hyperion Planning and Hyperion Financial Management ad-hoc web forms. If you are also interested in other new features and smart enhancements in Essbase or Hyperion Planning stay tuned for coming articles or check our training courses and web presentations. You can find general information about offerings for the Essbase and Planning curriculum or other Oracle-Hyperion products here (please make sure to select your country/region at the top of this page) or in the OU Learning paths section , where Planning, Essbase and other Hyperion products can be found under the Fusion Middleware heading (again, please select the right country/region). Or drop me a note directly: [email protected] . About the Author: Bernhard Kinkel started working for Hyperion Solutions as a Presales Consultant and Consultant in 1998 and moved to Hyperion Education Services in 1999. He joined Oracle University in 2007 where he is a Principal Education Consultant. Based on these many years of working with Hyperion products he has detailed product knowledge across several versions. He delivers both classroom and live virtual courses. His areas of expertise are Oracle/Hyperion Essbase, Oracle Hyperion Planning and Hyperion Web Analysis.  

  Read the article

< Previous Page | 172 173 174 175 176 177 178 179 180 181 182 183  | Next Page >