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• Performance of java on different hardware?

  - by tangens

  In another SO question I asked why my java programs run faster on AMD than on Intel machines. But it seems that I'm the only one who has observed this. Now I would like to invite you to share the numbers of your local java performance with the SO community. I observed a big performance difference when watching the startup of JBoss on different hardware, so I set this program as the base for this comparison. For participation please download JBoss 5.1.0.GA and run: jboss-5.1.0.GA/bin/run.sh (or run.bat) This starts a standard configuration of JBoss without any extra applications. Then look for the last line of the start procedure which looks like this: [ServerImpl] JBoss (Microcontainer) [5.1.0.GA (build: SVNTag=JBoss_5_1_0_GA date=200905221634)] Started in 25s:264ms Please repeat this procedure until the printed time is somewhat stable and post this line together with some comments on your hardware (I used cpu-z to get the infos) and operating system like this: java version: 1.6.0_13 OS: Windows XP Board: ASUS M4A78T-E Processor: AMD Phenom II X3 720, 2.8 GHz RAM: 2*2 GB DDR3 (labeled 1333 MHz) GPU: NVIDIA GeForce 9400 GT disc: Seagate 1.5 TB (ST31500341AS) Use your votes to bring the fastest configuration to the top. I'm very curious about the results. EDIT: Up to now only a few members have shared their results. I'd really be interested in the results obtained with some other architectures. If someone works with a MAC (desktop) or runs an Intel i7 with less than 3 GHz, please once start JBoss and share your results. It will only take a few minutes.

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• Memory Bandwidth Performance for Modern Machines

  - by porgarmingduod

  I'm designing a real-time system that occasionally has to duplicate a large amount of memory. The memory consists of non-tiny regions, so I expect the copying performance will be fairly close to the maximum bandwidth the relevant components (CPU, RAM, MB) can do. This led me to wonder what kind of raw memory bandwidth modern commodity machine can muster? My aging Core2Duo gives me 1.5 GB/s if I use 1 thread to memcpy() (and understandably less if I memcpy() with both cores simultaneously.) While 1.5 GB is a fair amount of data, the real-time application I'm working on will have have something like 1/50th of a second, which means 30 MB. Basically, almost nothing. And perhaps worst of all, as I add multiple cores, I can process a lot more data without any increased performance for the needed duplication step. But a low-end Core2Due isn't exactly hot stuff these days. Are there any sites with information, such as actual benchmarks, on raw memory bandwidth on current and near-future hardware? Furthermore, for duplicating large amounts of data in memory, are there any shortcuts, or is memcpy() as good as it will get? Given a bunch of cores with nothing to do but duplicate as much memory as possible in a short amount of time, what's the best I can do?

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• Oracle: Insertion on an indexed table, avoiding duplicates. Looking for tips and advice.

  - by Tom

  Hi everyone, Im looking for the best solution (performance wise) to achieve this. I have to insert records into a table, avoiding duplicates. For example, take table A Insert into A ( Select DISTINCT [FIELDS] from B,C,D.. WHERE (JOIN CONDITIONS ON B,C,D..) AND NOT EXISTS ( SELECT * FROM A ATMP WHERE ATMP.SOMEKEY = A.SOMEKEY ) ); I have an index over A.SOMEKEY, just to optimize the NOT EXISTS query, but i realize that inserting on an indexed table will be a performance hit. So I was thinking of duplicating Table A in a Global Temporary Table, where I would keep the index. Then, removing the index from Table A and executing the query, but modified Insert into A ( Select DISTINCT [FIELDS] from B,C,D.. WHERE (JOIN CONDITIONS ON B,C,D..) AND NOT EXISTS ( SELECT * FROM GLOBAL_TEMPORARY_TABLE_A ATMP WHERE ATMP.SOMEKEY = A.SOMEKEY ) ); This would solve the "inserting on an index table", but I would have to update the Global Temporary A with each insertion I make. I'm kind of lost here, Is there a better way to achieve this? Thanks in advance,

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• Testing performance of queries in mysl

  - by Unreason

  I am trying to setup a script that would test performance of queries on a development mysql server. Here are more details: I have root access I am the only user accessing the server Mostly interested in InnoDB performance The queries I am optimizing are mostly search queries (SELECT ... LIKE '%xy%') What I want to do is to create reliable testing environment for measuring the speed of a single query, free from dependencies on other variables. Till now I have been using SQL_NO_CACHE, but sometimes the results of such tests also show caching behaviour - taking much longer to execute on the first run and taking less time on subsequent runs. If someone can explain this behaviour in full detail I might stick to using SQL_NO_CACHE; I do believe that it might be due to file system cache and/or caching of indexes used to execute the query, as this post explains. It is not clear to me when Buffer Pool and Key Buffer get invalidated or how they might interfere with testing. So, short of restarting mysql server, how would you recommend to setup an environment that would be reliable in determining if one query performs better then the other?

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• Lucene (.NET) Document stucture and performance suggestions.

  - by Josh Handel

  Hello, I am indexing about 100M documents that consist of a few string identifiers and a hundred or so numaric terms.. I won't be doing range queries, so I haven't dugg too deep into Numaric Field but I'm not thinking its the right choose here. My problem is that the query performance degrades quickly when I start adding OR criteria to my query.. All my queries are on specific numaric terms.. So a document looks like StringField:[someString] and N DataField:[someNumber].. I then query it with something like DataField:((+1 +(2 3)) (+75 +(3 5 52)) (+99 +88 +(102 155 199))). Currently these queries take about 7 to 16 seconds to run on my laptop.. I would like to make sure thats really the best they can do.. I am open to suggestions on field structure and query structure :-). Thanks Josh PS: I have already read over all the other lucene performance discussions on here, and on the Lucene wiki and at lucid imiagination... I'm a bit further down the rabbit hole then that...

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• Performance Difference between HttpContext user and Thread user

  - by atrueresistance

  I am wondering what the difference between HttpContext.Current.User.Identity.Name.ToString.ToLower and Thread.CurrentPrincipal.Identity.Name.ToString.ToLower. Both methods grab the username in my asp.net 3.5 web service. I decided to figure out if there was any difference in performance using a little program. Running from full Stop to Start Debugging in every run. Dim st As DateTime = DateAndTime.Now Try 'user = HttpContext.Current.User.Identity.Name.ToString.ToLower user = Thread.CurrentPrincipal.Identity.Name.ToString.ToLower Dim dif As TimeSpan = Now.Subtract(st) Dim break As String = "nothing" Catch ex As Exception user = "Undefined" End Try I set a breakpoint on break to read the value of dif. The results were the same for both methods. dif.Milliseconds 0 Integer dif.Ticks 0 Long Using a longer duration, loop 5,000 times results in these figures. Thread Method run 1 dif.Milliseconds 125 Integer dif.Ticks 1250000 Long run 2 dif.Milliseconds 0 Integer dif.Ticks 0 Long run 3 dif.Milliseconds 0 Integer dif.Ticks 0 Long HttpContext Method run 1 dif.Milliseconds 15 Integer dif.Ticks 156250 Long run 2 dif.Milliseconds 156 Integer dif.Ticks 1562500 Long run 3 dif.Milliseconds 0 Integer dif.Ticks 0 Long So I guess what is more prefered, or more compliant with webservice standards? If there is some type of a performance advantage, I can't really tell. Which one scales to larger environments easier?

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• Divide and conquer of large objects for GC performance

  - by Aperion

  At my work we're discussing different approaches to cleaning up a large amount of managed ~50-100MB memory.There are two approaches on the table (read: two senior devs can't agree) and not having the experience the rest of the team is unsure of what approach is more desirable, performance or maintainability. The data being collected is many small items, ~30000 which in turn contains other items, all objects are managed. There is a lot of references between these objects including event handlers but not to outside objects. We'll call this large group of objects and references as a single entity called a blob. Approach #1: Make sure all references to objects in the blob are severed and let the GC handle the blob and all the connections. Approach #2: Implement IDisposable on these objects then call dispose on these objects and set references to Nothing and remove handlers. The theory behind the second approach is since the large longer lived objects take longer to cleanup in the GC. So, by cutting the large objects into smaller bite size morsels the garbage collector will processes them faster, thus a performance gain. So I think the basic question is this: Does breaking apart large groups of interconnected objects optimize data for garbage collection or is better to keep them together and rely on the garbage collection algorithms to processes the data for you? I feel this is a case of pre-optimization, but I do not know enough of the GC to know what does help or hinder it.

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• Poor performance using RMI-proxies with Swing components

  - by Patrick

  I'm having huge performance issues when I add RMI proxy references to a Java Swing JList-component. I'm retrieving a list of user Profiles with RMI from a server. The retrieval itself takes just a second or so, so that's acceptable under the circumstances. However, when I try to add these proxies to a JList, with the help of a custom ListModel and a CellRenderer, it takes between 30-60 seconds to add about 180 objects. Since it is a list of users' names, it's preferrable to present them alphabetically. The biggest performance hit is when I sort the elements as they get added to the ListModel. Since the list will always be sorted, I opted to use the built-in Collections.binarySearch() to find the correct position for the next element to be added, and the comparator uses two methods that are defined by the Profile interface, namely getFirstName() and getLastName(). Is there any way to speed this process up, or am I simply implementing it the wrong way? Or is this a "feature" of RMI? I'd really love to be able to cache some of the data of the remote objects locally, to minimize the remote method calls.

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• SQL Server performance issue.

  - by Jit

  Hi Friends, I have been trying to analyze performance issue with SQL Server 2005. We have 30 jobs, one for each databases (30 databases, one per each client). The jobs run at early morning at an interval of 5 minutes. When I run the job individually for testing, for most of the databases it finishes in 7 to 9 minutes. But when these jobs run at early morning, I see few jobs taking 2 to 3 hours to finish and the same takes few minutes as mentioned above if ran independently. We dont have any other job scheduled during that time, other than these 30 jobs. If we restart the server then for 2 or so days all the jobs finishes in few minutes, but over the period of time (from 3rd day suddenly), few jobs start taking hours to finish. What could be the possible reason of performance degradation over the period of time? I verified all the SPs and we uses temp tables and I made sure none of the temp table is left without dropping at the end of SP. Let me know what are the possible reasons for such behavior. Appreciate your time and help. Thanks

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• Google app engine: Poor Performance with JDO + Datastore

  - by Bosh

  I have a simple data model that includes USERS: store basic information (key, name, phone # etc) RELATIONS: describe, e.g. a friendship between two users (supplying a relationship_type + two user keys) I'm getting very poor performance, for instance, if I try to print the first names of all of a user's friends. Say the user has 500 friends: I can fetch the list of friend user_ids very easily in a single query. But then, to pull out first names, I have to do 500 back-and-forth trips to the Datastore, each of which seems to take on the order of 30 ms. If this were SQL, I'd just do a JOIN and get the answer out fast. I understand there are rudimentary facilities for performing joins across un-owned relations in a relaxed implementation of JDO (as described at http://gae-java-persistence.blogspot.com) but they sound experimental and non-standard (e.g. my code won't work in any other JDO implementation). Is this really my best bet? Otherwise, how do people extract satisfactory performance from JDO/Datastore in this kind of (very common) situation? -Bosh

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• Silverlight performance with many loaded controls

  - by gius

  I have a SL application with many DataGrids (from Silverlight Toolkit), each on its own view. If several DataGrids are opened, changing between views (TabItems, for example) takes a long time (few seconds) and it freezes the whole application (UI thread). The more DataGrids are loaded, the longer the change takes. These DataGrids that slow the UI chanage might be on other places in the app and not even visible at that moment. But once they are opened (and loaded with data), they slow showing other DataGrids. Note that DataGrids are NOT disposed and then recreated again, they still remain in memory, only their parent control is being hidden and visible again. I have profiled the application. It shows that agcore.dll's SetValue function is the bottleneck. Unfortunately, debug symbols are not available for this Silverlight native library responsible for drawing. The problem is not in the DataGrid control - I tried to replace it with XCeed's grid and the performance when changing views is even worse. Do you have any idea how to solve this problem? Why more opened controls slow down other controls? I have created a sample that shows this issue: http://cenud.cz/PerfTest.zip UPDATE: Using VS11 profiler on the sample provided suggests that the problem could be in MeasureOverride being called many times (for each DataGridCell, I guess). But still, why is it slower as more controls are loaded elsewhere? Is there a way to improve the performance?

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• Mysql Performance Question - Essentially about normalizing efficiency

  - by freqmode

  Hi there. Just a quick question about database performance. I'll outline my site purpose below as background. I'm creating a dictionary site that saves the words users define to a database. What I'm wondering is whether or not to create a words table for each user or to keep one massive words table. This site will be used for entire schools so the single words table would be massive! The database structure is as follows: A user table with: User_ID PRIMARY KEY Username First Last Password Email Country Research Standings SendInfo Donated JoinedOn LastLogin Logins Correct Attempts Admin Active And one word table with: User_ID PRIMARY KEY Word Vocab Spell Defined DefinedAttempted Spelled SpelledAttempted Sentenced SentencedAttempted So what I'm asking is , performance-wise, should I create a new table for each user when they join the site - each user could have hundreds or thousands of words over time? Or is it better to have one massive table with thousands and thousands of records and filter by User_ID. I don't think I'll perform many table joins. My gut feeling is to create a new table for each user, but I thought I'd ask for expert advice! Thanks in advance.

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• Performance of Multiple Joins

  - by geeko

  Greetings Overflowers, I need to query against objects with many/complex spacial conditions. In relational databases that is translated to many joins (possibly 10+). I'm new to this business and wondering whether to go with MS SQL Server 2008 R2 or Oracle 11g or document-based solutions such as RavenDB or simply go with some spacial database (GIS)... Any thoughts ? Regards UPDATE: Thank you all for your answers. Would anybody opt for document/spatial databases ? My database would consist of tens of millions to few billion records. Mostly read-only. Almost no updates unless in case of mistakes in input. Overnight inserts and not that frequent. The join tables are predicted beforehand but the number of self joins (tables joining themselves multiple times) is not. Small pages of results from such queries are going to be viewed on an highly interactive website so response time is critical. Any predictions on how this can perform on MS SQL Server 2008 R2 or Oracle 11g ? I'm also concerned about boosting performance by adding more servers, which one scales better ? How about PostgresQL ?

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• Displaying performance metrics in a modern web app?

  - by Charles

  We're updating our ancient internal PHP application at work. Right now, we gather extensive performance measurements on every pageview, and log them to the database. Additionally, users requested that some of the metrics be displayed at the bottom of the page. This worked out pretty well for us, because the last thing that the application does on every request is include the file containing the HTML footer. The updated parts of the application use an MVC framework and a Dispatch/Request/Response loop. The page footer is no longer the last thing done. In fact, it could very well be the first thing done, before the rest of the page is created. Because we can grab the Response before it's returned to the user, we could try to include placeholders for the performance metrics in the footer and simply replace them with the actual numbers, but this strikes me as a bad idea somehow. How do you handle this in your modern web app? While we're using PHP, I'm curious how it's done in a Ruby/Rails app, and in your favorite Python framework.

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• Reduce durability in MySQL for performance

  - by Paul Prescod

  My site occasionally has fairly predictable bursts of traffic that increase the throughput by 100 times more than normal. For example, we are going to be featured on a television show, and I expect in the hour after the show, I'll get more than 100 times more traffic than normal. My understanding is that MySQL (InnoDB) generally keeps my data in a bunch of different places: RAM Buffers commitlog binary log actual tables All of the above places on my DB slave This is too much "durability" given that I'm on an EC2 node and most of the stuff goes across the same network pipe (file systems are network attached). Plus the drives are just slow. The data is not high value and I'd rather take a small chance of a few minutes of data loss rather than have a high probability of an outage when the crowd arrives. During these traffic bursts I would like to do all of that I/O only if I can afford it. I'd like to just keep as much in RAM as possible (I have a fair chunk of RAM compared to the data size that would be touched over an hour). If buffers get scarce, or the I/O channel is not too overloaded, then sure, I'd like things to go to the commitlog or binary log to be sent to the slave. If, and only if, the I/O channel is not overloaded, I'd like to write back to the actual tables. In other words, I'd like MySQL/InnoDB to use a "write back" cache algorithm rather than a "write through" cache algorithm. Can I convince it to do that? If this is not possible, I am interested in general MySQL write-performance optimization tips. Most of the docs are about optimizing read performance, but when I get a crowd of users, I am creating accounts for all of them, so that's a write-heavy workload.

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• PHP: Opening/closing tags & performance?

  - by Tom

  Hi, This may be a silly question, but as someone relatively new to PHP, I'm wondering if there are any performance-related issues to frequently opening and closing PHP tags in HTML template code, and if so, what might be best practices in terms of working with php tags? My question is not about the importance/correctness of closing tags, or about which type of code is more readable than another, but rather about how the document gets parsed/executed and what impact it might have on performance. To illustrate, consider the following two extremes: Mixing PHP and HTML tags: <?php echo '<tr> <td>'.$variable1.'</td> <td>'.$variable2.'</td> <td>'.$variable3.'</td> <td>'.$variable4.'</td> <td>'.$variable5.'</td> </tr>' ?> // PHP tag opened once Separating PHP and HTML tags: <tr> <td><?php echo $variable1 ?></td> <td><?php echo $variable2 ?></td> <td><?php echo $variable3 ?></td> <td><?php echo $variable4 ?></td> <td><?php echo $variable5 ?></td> </tr> // PHP tag opened five times Would be interested in hearing some views on this, even if it's just to hear that it makes no difference. Thanks.

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• Performance Problems with Django's F() Object

  - by JayhawksFan93

  Has anyone else noticed performance issues using Django's F() object? I am running Windows XP SP3 and developing against the Django trunk. A snippet of the models I'm using and the query I'm building are below. When I have the F() object in place, each call to a QuerySet method (e.g. filter, exclude, order_by, distinct, etc.) takes approximately 2 seconds, but when I comment out the F() clause the calls are sub-second. I had a co-worker test it on his Ubuntu machine, and he is not experiencing the same performance issues I am with the F() clause. Anyone else seeing this behavior? class Move (models.Model): state_meaning = models.CharField( max_length=16, db_index=True, blank=True, default='' ) drop = models.ForeignKey( Org, db_index=True, null=False, default=1, related_name='as_move_drop' ) class Split(models.Model): state_meaning = models.CharField( max_length=16, db_index=True, blank=True, default='' ) move = models.ForeignKey( Move, related_name='splits' ) pickup = models.ForeignKey( Org, db_index=True, null=False, default=1, related_name='as_split_pickup' ) pickup_date = models.DateField( null=True, default=None ) drop = models.ForeignKey( Org, db_index=True, null=False, default=1, related_name='as_split_drop' ) drop_date = models.DateField( null=True, default=None, db_index=True ) def get_splits(begin_date, end_date): qs = Split.objects \ .filter(state_meaning__in=['INPROGRESS','FULFILLED'], drop=F('move__drop'), # <<< the line in question pickup_date__lte=end_date) elapsed = timer.clock() - start print 'qs1 took %.3f' % elapsed start = timer.clock() qs = qs.filter(Q(drop_date__gte=begin_date) | Q(drop_date__isnull=True)) elapsed = timer.clock() - start print 'qs2 took %.3f' % elapsed start = timer.clock() qs = qs.exclude(move__state_meaning='UNFULFILLED') elapsed = timer.clock() - start print 'qs3 took %.3f' % elapsed start = timer.clock() qs = qs.order_by('pickup_date', 'drop_date') elapsed = timer.clock() - start print 'qs7 took %.3f' % elapsed start = timer.clock() qs = qs.distinct() elapsed = timer.clock() - start print 'qs8 took %.3f' % elapsed

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• Oracle Query Optimization: Why is My Second Query Faster?

  - by Patrick Cuff

  I was having some performance issues with an Oracle query, so I downloaded a trial of the Quest SQL Optimizer for Oracle, which made some changes that dramatically improved the query's performance. I'm not exactly sure why the recommended query had such an improvement; can anyone provide an explanation? Before: SELECT t1.version_id, t1.id, t2.field1, t3.person_id, t2.id FROM table1 t1, table2 t2, table3 t3 WHERE t1.id = t2.id AND t1.version_id = t2.version_id AND t2.id = 123 AND t1.version_id = t3.version_id AND t1.VERSION_NAME <> 'AA' order by t1.id Plan Cost: 831 Elapsed Time: 00:00:21.40 Number of Records: 40,717 After: SELECT /*+ USE_NL_WITH_INDEX(t1) */ t1.version_id, t1.id, t2.field1, t3.person_id, t2.id FROM table2 t2, table3 t3, table1 t1 WHERE t1.id = t2.id + 0 AND t1.version_id = t2.version_id + 0 AND t2.id = 123 AND t1.version_id = t3.version_id + 0 AND t1.VERSION_NAME || '' <> 'AA' AND t3.version_id = t2.version_id + 0 order by t1.id Plan Cost: 686 Elapsed Time: 00:00:00.95 Number of Records: 40,717 Questions: Why does re-arranging the order of the tables in the FROM clause help? Why does adding + 0 to the WHERE clause comparisons help? Why does || '' <> 'AA' in the WHERE clause VERSION_NAME comparison help? Is this a more efficient way of handling possible nulls on this column?

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• Window Management for Mac OS X

  - by Paolo Maffei

  Ok, I feel dumb. I've put many hours into this and found nothing, yet. When I was using Windows I had this little tool called WinSplit Revolution. What it did was letting you divide your screen into how many and of how much size you choose "virtual monitors". You set one time of you want to divide your monitor, then everytime WinSplit is opened the monitor is automatically divided into Virtual Monitors. Screenshots: http://www.google.com/images?hl=en&q=winsplit%20revolution&um=1&ie=UTF-8&source=og&sa=N&tab=wi&biw=1045&bih=499 I'm now using a 30' which i want almost always divided into 4 equal size "virtual monitors" (plus my mbp 13' those will be 5 1280x800 virtual monitors) Now I've switched to Mac OS X and can't find anything that does just this efficiently. I tried Divvy but I found no way to divide my screen into arbitrary "virtual monitors", I need a couple of clicks to select a 3x3 space on a 9x9 grid. Before starting coding something like this can you tell me if you already know of some software that does window management like this?

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• Sharing disk volumes across OpenVZ guests to reduce Package Management Overhead

  - by andyortlieb

  Is it feasible to create a single "master" OpenVZ guest who would only be used for package management, and use something like mount --bind on several other OpenVZ guests sort of trick them into using the environment installed by the master guest? The point of this would be so that users can maintain their own containers, and yet stay in sync with the master development environment, so they'll always have the latest & greatest requirements without worrying too much about system administration. If they need to install their own packages, could put them in /opt, or /usr/local (or set a path to their home directory)? To rephrase, I would like several (developer's, for example) OpenVZ guests whose /bin, /usr (and so on...) actually refer to the same disk location as that of a master OpenVZ guest who can be started up to install and update common packages for the environment to be shared by all of this group of OpenVZ guests. For what it's worth, we're running Debian 6. Edit: I have tried mounting (bind, and readonly) /bin, /lib, /sbin, /usr in this fashion and it refuses to start the containers stating that files are already mounted or otherwise in use: Starting container ... vzquota : (error) Quota on syscall for id 1102: Device or resource busy vzquota : (error) Possible reasons: vzquota : (error) - Container's root is already mounted vzquota : (error) - there are opened files inside Container's private area vzquota : (error) - your current working directory is inside Container's vzquota : (error) private area vzquota : (error) Currently used file(s): /var/lib/vz/private/1102/sbin /var/lib/vz/private/1102/usr /var/lib/vz/private/1102/lib /var/lib/vz/private/1102/bin vzquota on failed [3] If I unmount these four volumes, and start the guest, and then mount them after the guest has started, the guest never sees them mounted.

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• starting oracle 10g on ubuntu, Listener failed to start.

  - by tsegay

  I have installed oracle 10g on a ubuntu 10.x, This is my first time installation. After installing I tried to start it with the command below. tsegay@server-name:/u01/app/oracle/product/10.2.0/db_1/bin$ lsnrctl LSNRCTL for Linux: Version 10.2.0.1.0 - Production on 29-DEC-2010 22:46:51 Copyright (c) 1991, 2005, Oracle. All rights reserved. Welcome to LSNRCTL, type "help" for information. LSNRCTL> start Starting /u01/app/oracle/product/10.2.0/db_1/bin/tnslsnr: please wait... TNSLSNR for Linux: Version 10.2.0.1.0 - Production System parameter file is /u01/app/oracle/product/10.2.0/db_1/network/admin/listener.ora Log messages written to /u01/app/oracle/product/10.2.0/db_1/network/log/listener.log Error listening on: (DESCRIPTION=(ADDRESS=(PROTOCOL=IPC)(KEY=EXTPROC1))) TNS-12555: TNS:permission denied TNS-12560: TNS:protocol adapter error TNS-00525: Insufficient privilege for operation Linux Error: 1: Operation not permitted Listener failed to start. See the error message(s) above... my listener.ora file looks like this: # listener.ora Network Configuration File: /u01/app/oracle/product/10.2.0/db_1/network/admin/listener.ora # Generated by Oracle configuration tools. SID_LIST_LISTENER = (SID_LIST = (SID_DESC = (SID_NAME = PLSExtProc) (ORACLE_HOME = /u01/app/oracle/product/10.2.0/db_1) (PROGRAM = extproc) ) ) LISTENER = (DESCRIPTION_LIST = (DESCRIPTION = (ADDRESS = (PROTOCOL = IPC)(KEY = EXTPROC1)) (ADDRESS = (PROTOCOL = TCP)(HOST = acct-vmserver)(PORT = 1521)) ) ) I can guess the problem is with permission issue, But i dont know where I have to do the change on permission. Any help is appreciated ... EDIT## When i run with the command sudo, i got this tsegay@server-name:/u01/app/oracle/product/10.2.0/db_1$ sudo ./bin/lsnrctl start LSNRCTL for Linux: Version 10.2.0.1.0 - Production on 30-DEC-2010 01:01:03 Copyright (c) 1991, 2005, Oracle. All rights reserved. Starting ./bin/tnslsnr: please wait... ./bin/tnslsnr: error while loading shared libraries: libclntsh.so.10.1: cannot open shared object file: No such file or directory TNS-12547: TNS:lost contact TNS-12560: TNS:protocol adapter error TNS-00517: Lost contact Linux Error: 32: Broken pipe

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• 202 blog articles

  - by mprove

  All my blog articles under blogs.oracle.com since August 2005: 202 blog articles Apr 2012 blogs.oracle.com design patch Mar 2012 Interaction 12 - Critique Mar 2012 Typing. Clicking. Dancing. Feb 2012 Desktop Mobility in Hospitals with Oracle VDI /video Feb 2012 Interaction 12 in Dublin - Highlights of Day 3 Feb 2012 Interaction 12 in Dublin - Highlights of Day 2 Feb 2012 Interaction 12 in Dublin - Highlights of Day 1 Feb 2012 Shit Interaction Designers Say Feb 2012 Tips'n'Tricks for WebCenter #3: How to display custom page titles in Spaces Jan 2012 Tips'n'Tricks for WebCenter #2: How to create an Admin menu in Spaces and save a lot of time Jan 2012 Tips'n'Tricks for WebCenter #1: How to apply custom resources in Spaces Jan 2012 Merry XMas and a Happy 2012! Dec 2011 One Year Oracle SocialChat - The Movie Nov 2011 Frank Ludolph's Last Working Day Nov 2011 Hans Rosling at TED Oct 2011 200 Countries x 200 Years Oct 2011 Blog Aggregation for Desktop Virtualization Oct 2011 Oracle VDI at OOW 2011 Sep 2011 Design for Conversations & Conversations for Design Sep 2011 All Oracle UX Blogs Aug 2011 Farewell Loriot Aug 2011 Oracle VDI 3.3 Overview Aug 2011 Sutherland's Closing Remarks at HyperKult Aug 2011 Surface and Subface Aug 2011 Back to Childhood in UI Design Jul 2011 The Art of Engineering and The Engineering of Art Jul 2011 Oracle VDI Seminar - June-30 Jun 2011 SGD White Paper May 2011 TEDxHamburg Live Feed May 2011 Oracle VDI in 3 Minutes May 2011 Space Ship Earth 2011 May 2011 blog moving times Apr 2011 Frozen tag cloud Apr 2011 Oracle: Hardware Software Complete in 1953 Apr 2011 Interaction Design with Wireframes Apr 2011 A guide to closing down a project Feb 2011 Oracle VDI 3.2.2 Jan 2011 free VDI charts Jan 2011 Sun Founders Panel 2006 Dec 2010 Sutherland on Leadership Dec 2010 SocialChat: Efficiency of E20 Dec 2010 ALWAYS ON Desktop Virtualization Nov 2010 12,000 Desktops at JavaOne Nov 2010 SocialChat on Sharing Best Practices Oct 2010 Globe of Visitors Oct 2010 SocialChat about the Next Big Thing Oct 2010 Oracle VDI UX Story - Wireframes Oct 2010 What's a PC anyway? Oct 2010 SocialChat on Getting Things Done Oct 2010 SocialChat on Infoglut Oct 2010 IT Twenty Twenty Oct 2010 Desktop Virtualization Webcasts from OOW Oct 2010 Oracle VDI 3.2 Overview Sep 2010 Blog Usability Top 7 Sep 2010 100 and counting Aug 2010 Oracle'izing the VDI Blogs Aug 2010 SocialChat on Apple Aug 2010 SocialChat on Video Conferencing Aug 2010 Oracle VDI 3.2 - Features and Screenshots Aug 2010 SocialChat: Don't stop making waves Aug 2010 SocialChat: Giving Back to the Community Aug 2010 SocialChat on Learning in Meetings Aug 2010 iPAD's Natural User Interface Jul 2010 Last day for Sun Microsystems GmbH Jun 2010 SirValUse Celebration Snippets Jun 2010 10 years SirValUse - Happy Birthday! Jun 2010 Wim on Virtualization May 2010 New Home for Oracle VDI Apr 2010 Renaissance Slide Sorter Comments Apr 2010 Unboxing Sun Ray 3 Plus Apr 2010 Desktop Virtualisierung mit Sun VDI 3.1 Apr 2010 Blog Relaunch Mar 2010 Social Messaging Slides from CeBIT Mar 2010 Social Messaging Talk at CeBIT Feb 2010 Welcome Oracle Jan 2010 My last presentation at Sun Jan 2010 Ivan Sutherland on Leadership Jan 2010 Learning French with Sun VDI Jan 2010 Learning Danish with Sun Ray Jan 2010 VDI workshop in Nieuwegein Jan 2010 Happy New Year 2010 Jan 2010 On Creating Slides Dec 2009 Best VDI Ever Nov 2009 How to store the Big Bang Nov 2009 Social Enterprise Tools. Beipiel Sun. Nov 2009 Nov-19 Nov 2009 PDF and ODF links on your blog Nov 2009 Q&A on VDI and MySQL Cluster Nov 2009 Zürich next week: Swiss Intranet Summit 09 Nov 2009 Designing for a Sustainable World - World Usabiltiy Day, Nov-12 Nov 2009 How to export a desktop from VDI 3 Nov 2009 Virtualisation Roadshow in the UK Nov 2009 Project Wonderland at EDUCAUSE 09 Nov 2009 VDI Roadshow in Dublin, Nov-26, 2009 Nov 2009 Sun VDI at EDUCAUSE 09 Nov 2009 Sun VDI 3.1 Architecture and New Features Oct 2009 VDI 3.1 is Early-Access Sep 2009 Virtualization for MySQL on VMware Sep 2009 Silpion & 13. Stock Sommerparty Sep 2009 Sun Ray and VMware View 3.1.1 2009-08-31 New Set of Sun Ray Status Icons 2009-08-25 Virtualizing the VDI Core? 2009-08-23 World Usability Day Hamburg 2009 - CfP 2009-07-16 Rising Sun 2009-07-15 featuring twittermeme 2009-06-19 ISC09 Student Party on June-20 /Hamburg 2009-06-18 Before and behind the curtain of JavaOne 2009-06-09 20k desktops at JavaOne 2009-06-01 sweet microblogging 2009-05-25 VDI 3 - Why you need 3 VDI hosts and what you can do about that? 2009-05-21 IA Konferenz 2009 2009-05-20 Sun VDI 3 UX Story - Power of the Web 2009-05-06 Planet of Sun and Oracle User Experience Design 2009-04-22 Sun VDI 3 UX Story - User Research 2009-04-08 Sun VDI 3 UX Story - Concept Workshops 2009-04-06 Localized documentation for Sun Ray Connector for VMware View Manager 1.1 2009-04-03 Sun VDI 3 Press Release 2009-03-25 Sun VDI 3 launches today! 2009-03-25 Sun Ray Connector for VMware View Manager 1.1 Update 2009-03-11 desktop virtualization wiki relaunch 2009-03-06 VDI 3 at CeBIT hall 6, booth E36 2009-03-02 Keyboard layout problems with Sun Ray Connector for VMware VDM 2009-02-23 wikis.sun.com tips & tricks 2009-02-23 Sun VDI 3 is in Early Access 2009-02-09 VirtualCenter unable to decrypt passwords 2009-02-02 Sun & VMware Desktop Training 2009-01-30 VDI at next09? 2009-01-16 Sun VDI: How to use virtual machines with multiple network adapters 2009-01-07 Sun Ray and VMware View 2009-01-07 Hamburg World Usability Day 2008 - Webcasts 2009-01-06 Sun Ray Connector for VMware VDM slides 2008-12-15 mother of all demos 2008-12-08 Build your own Thumper 2008-12-03 Troubleshooting Sun Ray Connector for VMware VDM 2008-12-02 My Roller Tag Cloud 2008-11-28 Sun Ray Connector: SSL connection to VDM 2008-11-25 Setting up SSL and Sun Ray Connector for VMware VDM 2008-11-13 Inspiration for Today and Tomorrow 2008-10-23 Sun Ray Connector for VMware VDM released 2008-10-14 From Sketchpad to ILoveSketch 2008-10-09 Desktop Virtualization on Xing 2008-10-06 User Experience Forum on Xing 2008-10-06 Sun Ray Connector for VMware VDM certified 2008-09-17 Virtual Clouds over Las Vegas 2008-09-14 Bill Verplank sketches metaphors 2008-09-04 End of Early Access - Sun Ray Connector for VMware 2008-08-27 Early Access: Sun Ray Connector for VMware Virtual Desktop Manager 2008-08-12 Sun Virtual Desktop Connector - Insides on Recycling Part 2 2008-07-20 Sun Virtual Desktop Connector - Insides on Recycling Part 3 2008-07-20 Sun Virtual Desktop Connector - Insides on Recycling 2008-07-20 lost in wiki space 2008-07-07 Evolution of the Desktop 2008-06-17 Virtual Desktop Webcast 2008-06-16 Woodstock 2008-06-16 What's a Desktop PC anyway? 2008-06-09 Virtual-T-Box 2008-06-05 Virtualization Glossary 2008-05-06 Five User Experience Principles 2008-04-25 Virtualization News Feed 2008-04-21 Acetylcholinesterase - Second Season 2008-04-18 Acetylcholinesterase - End of Signal 2007-12-31 Produkt-Management ist... 2007-10-22 Usability Verbände, Verteiler und Netzwerke. 2007-10-02 The Meaning is the Message 2007-09-28 Visualization Methods 2007-09-10 Inhouse und Open Source Projekte – Usability verankern und Synergien nutzen 2007-09-03 Der Schwabe Darth Vader entdeckt das Virale Marketing 2007-08-29 Dick Hardt 3.0 on Identity 2.0 2007-08-27 quality of written text depends on the tool 2007-07-27 podcasts for reboot9 2007-06-04 It is the user's itch that need to be scratched 2007-05-25 A duel at reboot9 2007-05-14 Taxonomien und Folksonomien - Tagging als neues HCI-Element 2007-05-10 Dueling Interaction Models of Personal-Computing and Web-Computing 2007-03-01 22.März: Weizenbaum. Rebel at Work. /Filmpremiere Hamburg 2007-02-25 Bruce Sterling at UbiComp 2006 /webcast 2006-11-12 FSOSS 2006 /webcasts 2006-11-10 Highway 101 2006-11-09 User Experience Roundtable Hamburg: EuroGEL 2006 2006-11-08 Douglas Adams' Hyperland (BBC 1990) 2006-10-08 Taxonomien und Folksonomien – Tagging als neues HCI-Element 2006-09-13 Usability im Unternehmen 2006-09-13 Doug does HyperScope 2006-08-26 TED Talks and TechTalks 2006-08-21 Kai Krause über seine Freundschaft zu Douglas Adams 2006-07-20 Rebel At Work: Film Portrait on Weizenbaum 2006-07-04 Gabriele Fischer, mp3 2006-06-07 Dick Hardt at ETech 06 2006-06-05 Weinberger: From Control to Conversation 2006-04-16 Eye Tracking at User Experience Roundtable Hamburg 2006-04-14 dropping knowledge 2006-04-09 GEL 2005 2006-03-13 slide photos of reboot7 2006-03-04 Dick Hardt on Identity 2.0 2006-02-28 User Experience Newsletter #13: Versioning 2006-02-03 Ester Dyson on Choice and Happyness 2006-02-02 Requirements-Engineering im Spannungsfeld von Individual- und Produktsoftware 2006-01-15 User Experience Newsletter #12: Intuition Quiz 2005-11-30 User Experience und Requirements-Engineering für Software-Projekte 2005-10-31 Ivan Sutherland on "Research and Fun" 2005-10-18 Ars Electronica / Mensch und Computer 2005 2005-09-14 60 Jahre nach Memex: Über die Unvereinbarkeit von Desktop- und Web-Paradigma 2005-08-31 reboot 7 2005-06-30

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• Persevering & Friday Night Big Ideas

  - by Oracle Accelerate for Midsize Companies

  by Jim Lein, Oracle Midsize Programs Every successful company, personal accomplishment, and philanthropic endeavor starts with one good idea. I have my best ideas on Friday evenings. The creative side of my brain is stimulated by end of week endorphins. Free thinking. Anything is possible. But, as my kids love to remind me, most of Dad's Friday Night Big Ideas (FNBIs) fizzle on the drawing board. Usually there's one barrier blocking the way that seems insurmountable by noon on Monday. For example, trekking the 486 mile Colorado Trail is on my bucket list. Since I have a job, I'll have to do it in bits and pieces--day hikes, weekends, and a vacation week here and there. With my trick neck, backpacking is not an option. How to survive equip myself for overnight backcountry travel was that one seemingly insurmountable barrier.  Persevering Lewis and Clark wouldn't have given up so I explored options and, as I blogged about back in December, I had an FNBI to hire llamas to carry my load. Last weekend, that idea came to fruition. Early Saturday morning, I met up with Bill, the owner of Antero Llamas, for an overnight training expedition along segment 14 of the Colorado Trail with a string of twelve llamas. It was a crash course on learning how to saddle, load, pasture, and mediate squabbles. Amazingly, we left the trailhead with me, the complete novice, at the lead. Instead of trying to impart three decades of knowledge on me in two days, Bill taught me two things: "Go With the Flow" and "Plan B". It worked. There were times I would be lost in thought for long stretches of time until one snort would remind me that I had a string of twelve llamas trailing behind. A funny thing happened along the trail... Up until last Saturday, my plan had been to trek all 28 segments of the trail east to west and sequentially. Out of some self-imposed sense of decorum. That plan presented myriad logistical challenges such as impassable snow pack on the Continental Divide when segment 6 is up next. On Sunday, as we trekked along the base of 14,000 ft peaks, I applied Bill's llama handling philosophy to my quest and came up with a much more realistic and enjoyable strategy for achieving my goal.  Seize opportunities to hike regardless of order. Define my own segments. Go west to east for awhile if it makes more sense. Let the llamas carry more creature comforts. Chill out.  I will still set foot on all 486 miles of the trail. Technically, the end result will be the same.And I and my traveling companions--human and camelid--will enjoy the journey more. Much more. Got Big Ideas of Your Own? Check out Tongal. This growing Oracle customer works with brands to crowd source fantastic ideas for promoting products and services. Your great idea could earn you cash.  Looking for more news and information about Oracle Solutions for Midsize Companies? Read the latest Oracle for Midsize Companies Newsletter Sign-up to receive the latest communications from Oracle’s industry leaders and experts Jim Lein I evangelize Oracle's enterprise solutions for growing midsize companies. I recently celebrated 15 years with Oracle, having joined JD Edwards in 1999. I'm based in Evergreen, Colorado and love relating stories about creativity and innovation whether they be about software, live music, or the mountains. The views expressed here are my own, and not necessarily those of Oracle.

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• CFOs: Do You Have a Playbook for Growth?

  - by Oracle Accelerate for Midsize Companies

  by Jim Lein, Oracle Midsize Programs In most global markets, CFOs are optimistic about their company's growth opportunities. Deloitte's CFO Signals Report, "Time to Accelerate" found that: In the U.K. business optimism is at its highest level in three-and-a-half years Optimism in North America rose from a strong +42% last quarter (Q2 to Q3 2013) to an even stronger +54%. The inaugural Southeast Asia survey, 44% of CFOs reported a positive outlook despite worries over the Chinese economy and political uncertainty. Sustainable and profitable business growth doesn't usually happen by accident. Company's need a playbook for growth that's owned by the CFO. And today, that playbook must leverage the six enabling technologies--Social, Big Data, Mobile, Cloud, Analytics, and The Internet of Things (or, as Oracle president Mark Hurd explains, "The Internet of the People"). On Monday June 9 at  2:00 pm Eastern, CFO.com is hosting a webcast, "The CFO Playbook on Growth: How CFOs Can Boost Efficiency and Performance with Automation". 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:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} “Investing in technology begins with a business metric driven business case with clear tangible business results expected," says John Lieblang, Affiliate Partner with Waterstone Management Group. "The progressive CFO has learned how to forge a partnership with the CIO to align everyone in the 'result value chain' to be accountable for the business results not just for functional technology.” Click HERE to register  Looking for more news and information about Oracle Solutions for Midsize Companies? Read the latest Oracle for Midsize Companies Newsletter Sign-up to receive the latest communications from Oracle’s industry leaders and experts Jim Lein I evangelize Oracle's enterprise solutions for growing midsize companies. I recently celebrated 15 years with Oracle, having joined JD Edwards in 1999. I'm based in Evergreen, Colorado and love relating stories about creativity and innovation whether they be about software, live music, or the mountains. The views expressed here are my own, and not necessarily those of Oracle.

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• Partition Wise Joins

  - by jean-pierre.dijcks

  Some say they are the holy grail of parallel computing and PWJ is the basis for a shared nothing system and the only join method that is available on a shared nothing system (yes this is oversimplified!). The magic in Oracle is of course that is one of many ways to join data. And yes, this is the old flexibility vs. simplicity discussion all over, so I won't go there... the point is that what you must do in a shared nothing system, you can do in Oracle with the same speed and methods. The Theory A partition wise join is a join between (for simplicity) two tables that are partitioned on the same column with the same partitioning scheme. In shared nothing this is effectively hard partitioning locating data on a specific node / storage combo. In Oracle is is logical partitioning. If you now join the two tables on that partitioned column you can break up the join in smaller joins exactly along the partitions in the data. Since they are partitioned (grouped) into the same buckets, all values required to do the join live in the equivalent bucket on either sides. No need to talk to anyone else, no need to redistribute data to anyone else... in short, the optimal join method for parallel processing of two large data sets. PWJ's in Oracle Since we do not hard partition the data across nodes in Oracle we use the Partitioning option to the database to create the buckets, then set the Degree of Parallelism (or run Auto DOP - see here) and get our PWJs. The main questions always asked are: How many partitions should I create? What should my DOP be? In a shared nothing system the answer is of course, as many partitions as there are nodes which will be your DOP. In Oracle we do want you to look at the workload and concurrency, and once you know that to understand the following rules of thumb. Within Oracle we have more ways of joining of data, so it is important to understand some of the PWJ ideas and what it means if you have an uneven distribution across processes. Assume we have a simple scenario where we partition the data on a hash key resulting in 4 hash partitions (H1 -H4). We have 2 parallel processes that have been tasked with reading these partitions (P1 - P2). The work is evenly divided assuming the partitions are the same size and we can scan this in time t1 as shown below. Now assume that we have changed the system and have a 5th partition but still have our 2 workers P1 and P2. The time it takes is actually 50% more assuming the 5th partition has the same size as the original H1 - H4 partitions. In other words to scan these 5 partitions, the time t2 it takes is not 1/5th more expensive, it is a lot more expensive and some other join plans may now start to look exciting to the optimizer. Just to post the disclaimer, it is not as simple as I state it here, but you get the idea on how much more expensive this plan may now look... Based on this little example there are a few rules of thumb to follow to get the partition wise joins. First, choose a DOP that is a factor of two (2). So always choose something like 2, 4, 8, 16, 32 and so on... Second, choose a number of partitions that is larger or equal to 2* DOP. Third, make sure the number of partitions is divisible through 2 without orphans. This is also known as an even number... Fourth, choose a stable partition count strategy, which is typically hash, which can be a sub partitioning strategy rather than the main strategy (range - hash is a popular one). Fifth, make sure you do this on the join key between the two large tables you want to join (and this should be the obvious one...). Translating this into an example: DOP = 8 (determined based on concurrency or by using Auto DOP with a cap due to concurrency) says that the number of partitions >= 16. Number of hash (sub) partitions = 32, which gives each process four partitions to work on. This number is somewhat arbitrary and depends on your data and system. In this case my main reasoning is that if you get more room on the box you can easily move the DOP for the query to 16 without repartitioning... and of course it makes for no leftovers on the table... And yes, we recommend up-to-date statistics. And before you start complaining, do read this post on a cool way to do stats in 11.

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