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  • Will having many timers affect my game performance?

    - by iQue
    I'm making a game for android, and earlier today I was trying to add some cool stuff to my game. The problem is this thing needs like 5 timers. I build my timers like this: timer += deltaTime; if(timer >= 2.0f){ doStuff; timer -= 2.0f; } // this timers gets stuff done every 2 secs Will having to many timers like this, getting checked every frame, screw up my games performance? The effect I wanted to add was a crosshair every 2 sec, then remove it after 2 sec and do a timed animation. So an array of crosshairs dependent on a bunch of timers to be exact. This caused my game to shut down when used, so thats why Im wondering if using that many timers causes my game to flip out.

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  • How can I improve overall system performance?

    - by Decio Lira
    What are your tips for improving overall system performance on ubuntu? Inspired by this question I realized that some default settings may be rather conservative on Ubuntu and that it's possible to tweak it with little or no risk if you wish to make it faster. This is not meant to be application specific (e.g. make firefox load pages faster), but system wide. Preferably 1 tip per answer, with enough detail for people to implement it. A couple of mine would be: Install Preload (via Software Center or sudo apt-get install preload); Change Swappiness value - "which controls the degree to which the kernel prefers to swap when it tries to free memory"; What are yours? PS: Since this is not intended to have a unique answer but rather, several useful tips, I'm making this community wiki out-of-the-box.

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  • Improving grepping over a huge file performance

    - by rogerio_marcio
    I have FILE_A which has over 300K lines and FILE_B which has over 30M lines. I created a bash script that greps each line in FILE_A over in FILE_B and writes the result of the grep to a new file. This whole process is taking over 5+ hours. I'm looking for suggestions on whether you see any way of improving the performance of my script. I'm using grep -F -m 1 as the grep command. FILE_A looks like this: 123456789 123455321 and FILE_B is like this: 123456789,123456789,730025400149993, 123455321,123455321,730025400126097, So with bash I have a while loop that picks the next line in FILE_A and greps it over in FILE_B. When the pattern is found in FILE_B i write it to result.txt. while read -r line; do grep -F -m1 $line 30MFile done < 300KFile Thanks a lot in advance for your help.

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  • Performance tracking/monitoring in games

    - by vitaliy kotik
    Let's say I have an online game with a downloadable client / browser plugin. I want to track performance of my software and automatically send summary to the server. Let it be fps, latency, load time, physics step calc. time, whatever... I also want tools to perform data analysis: per session stats, per hardware stats, avgs, totals, diagrams, etc. So that I could see what are the real world hotspots / bottlenecks. Is there any common out-of-the-box / SaS solution?

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  • Poor mobile performance when running from Eclipse

    - by Yajirobe_LOL
    So after weeks of thinking my rendering code was bad, I accidentally discovered the following: Running my game on a Nexus S From Eclipse (Debug as - Android application): 12fps From the device while still attached to USB (getting log info in Eclipse still): 24fps From the device while not attached via USB: 56fps I was wondering if anyone else has issues like this? I mean, the problem really isn't a problem since the final release build will likely have good performance, but for the time being I don't want to have to keep (un)plugging my device in and out when testing code all day long. Is there some remedy for this or does anyone have any input/advice? Thanks.

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  • Setter Validation can affect performance?

    - by TiagoBrenck
    Whitin a scenario where you use an ORM to map your entities to the DB, and you have setter validations (nullable, date lower than today validation, etc) every time the ORM get a result, it will pass into the setter to instance the object. If I have a grid that usually returns 500 records, I assume that for each record it passes on all validations. If my entity has 5 setter validations, than I have passed in 2.500 validations. Does those 2.500 validations will affect the performance? If was 15.000 validation, it will be different? In my opinion, and according to this answer (http://stackoverflow.com/questions/4893558/calling-setters-from-a-constructor/4893604#4893604), setter validation is usefull than constructors validation. Is there a way to avoid unecessary validation, since I am safe that the values I send to DB when saving the entity wont change until I edit it on my system?

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  • Video capture Performance

    - by volting
    I have noticed high CPU utilization in a number of applications (except mplayer) which read from the embedded webcam on my laptop. Bizarrely CPU utilization varies proportionately to the level of illumination present. I know that that high CPU usage has nothing to do with rendering the video, as I have written a simple app using the OpenCV library to simply grab frames from the webcam, and cpu usage is still high. I think that mplayer might be using my GPU (and the other apps aren't), but since its not an issue with rendering, I dont think this explains anything. Cheese Low light --- ~12% CPU Bright Light ---- ~63% CPU Camorama Low light --- ~7% CPU Bright Light ---- ~30% CPU Opencv C++ library, (display in a single highgui window) Low light --- ~13% CPU Bright Light ---- ~40% CPU (same test on windows 7, 4-9%) Mplayer No problem, 1-2% regardless of light levels Note: If all I want't to do is capture a feed from my webcam I would use mplayer and forget about it, but I'm developing an application which uses the OpenCV to capture a video feed among other things, performance is important.

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  • game performance

    - by iQue
    I'm making a game for android, and earlier today I was trying to add some cool stuff to my game. The problem is this thing needs like 5 timers. I build my timers like this: timer += deltaTime; if(timer >= 2.0f){ doStuff; timer -= 2.0f; } // this timers gets stuff done every 2 secs Will having to many timers like this, getting checked every frame, screw up my games performance? The effect I wanted to add was a crosshair every 2 sec, then remove it after 2 sec and do a timed animation. So an array of crosshairs dependent on a bunch of timers to be exact. This caused my game to shut down when used, so thats why Im wondering if using that many timers causes my game to flip out.

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  • WCF Service Layer in n-layered application: performance considerations

    - by Marconline
    Hi all. When I went to University, teachers used to say that in good structured application you have presentation layer, business layer and data layer. This is what I heard for more than 5 years. When I started working I discovered that this is true but sometimes is better to have more than just three layers. Two or three days ago I discovered this article by John Papa that explain how to use Entity Framework in layered application. According to that article you should have: UI Layer and Presentation Layer (Model View Pattern) Service Layer (WCF) Business Layer Data Access Layer Service Layer is, to me, one of the best ideas I've ever heard since I work. Your UI is then completely "diconnected" from Business and Data Layer. Now when I went deeper by looking into provided source code, I began to have some questions. Can you help me in answering them? Question #0: is this a good enterpise application template in your opinion? Question #1: where should I host the service layer? Should it be a Windows Service or what else? Question #2: in the source code provided the service layer expose just an endpoint with WSHttpBinding. This is the most interoperable binding but (I think) the worst in terms of performances (due to serialization and deserializations of objects). Do you agree? Question #3: if you agree with me at Question 2, which kind of binding would you use? Looking forward to hear from you. Have a nice weekend! Marco

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  • Missing processor/memory counters in the Windows XP Performance Monitor application (perfmon)

    - by Jader Dias
    Perfmon is a Windows utility that helps the developer to find bottlenecks in his applications, by measuring system counters. I was reading a perfmon tutorial and from this list of essential counters I have found the following ones on my machine: PhysicalDisk\Bytes/sec_Total Network Interface\Bytes Total/Sec\nic name But I haven't found the following counters nowhere: Processor\% Processor Time_Total Process\Working Set_Total Memory\Available MBytes Where do I find them? Note that my Windows is pt-BR (instead of en-US). Where do I find language specific documentation for windows tools like PerfMon?

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  • Performance profiler for a java application

    - by Nitin Garg
    I need to optimize a java application. It makes some 3rd party calls. I need some good tool to accurately measure the time taken by individual api calls. To give an idea of complexity- the application takes a data source file containing 10 lakh rows, and it takes around one hour to complete the processing. As a part of processing , it makes some 3rd party calls (including some network calls). I need to identify which calls are taking more time then others, and based on that, find out a way to optimize the application. Any suggestions would be appreciated.

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  • Performance-Driven Development

    - by BuckWoody
    I was reading a blog yesterday about the evils of SELECT *. The author pointed out that it's almost always a bad idea to use SELECT * for a query, but in the case of SQL Azure (or any cloud database, for that matter) it's especially bad, since you're paying for each transmission that comes down the line. A very good point indeed. This got me to thinking - shouldn't we treat ALL programming that way? In other words, wouldn't it make sense to pretend that we are paying for every chunk of data - a little less for a bit, a lot more for a BLOB or VARCHAR(MAX), that sort of thing? In effect, we really are paying for that. Which led me to the thought of Performance-Driven Development, or the act of programming with the goal of having the fastest code from the very outset. This isn't an original title, since a quick Bing-search shows me a couple of offerings from Forrester and a professional in Israel who already used that title, but the general idea I'm thinking of is assigning a "cost" to each code round-trip, be it network, storage, trip time and other variables, and then rewarding the developers that come up with the fastest code. I wonder what kind of throughput and round-trip times you could get if your developers were paid on a scale of how fast the application performed... Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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  • Performance Enhancement in Full-Text Search Query

    - by Calvin Sun
    Ever since its first release, we are continuing consolidating and developing InnoDB Full-Text Search feature. There is one recent improvement that worth blogging about. It is an effort with MySQL Optimizer team that simplifies some common queries’ Query Plans and dramatically shorted the query time. I will describe the issue, our solution and the end result by some performance numbers to demonstrate our efforts in continuing enhancement the Full-Text Search capability. The Issue: As we had discussed in previous Blogs, InnoDB implements Full-Text index as reversed auxiliary tables. The query once parsed will be reinterpreted into several queries into related auxiliary tables and then results are merged and consolidated to come up with the final result. So at the end of the query, we’ll have all matching records on hand, sorted by their ranking or by their Doc IDs. Unfortunately, MySQL’s optimizer and query processing had been initially designed for MyISAM Full-Text index, and sometimes did not fully utilize the complete result package from InnoDB. Here are a couple examples: Case 1: Query result ordered by Rank with only top N results: mysql> SELECT FTS_DOC_ID, MATCH (title, body) AGAINST ('database') AS SCORE FROM articles ORDER BY score DESC LIMIT 1; In this query, user tries to retrieve a single record with highest ranking. It should have a quick answer once we have all the matching documents on hand, especially if there are ranked. However, before this change, MySQL would almost retrieve rankings for almost every row in the table, sort them and them come with the top rank result. This whole retrieve and sort is quite unnecessary given the InnoDB already have the answer. In a real life case, user could have millions of rows, so in the old scheme, it would retrieve millions of rows' ranking and sort them, even if our FTS already found there are two 3 matched rows. Apparently, the million ranking retrieve is done in vain. In above case, it should just ask for 3 matched rows' ranking, all other rows' ranking are 0. If it want the top ranking, then it can just get the first record from our already sorted result. Case 2: Select Count(*) on matching records: mysql> SELECT COUNT(*) FROM articles WHERE MATCH (title,body) AGAINST ('database' IN NATURAL LANGUAGE MODE); In this case, InnoDB search can find matching rows quickly and will have all matching rows. However, before our change, in the old scheme, every row in the table was requested by MySQL one by one, just to check whether its ranking is larger than 0, and later comes up a count. In fact, there is no need for MySQL to fetch all rows, instead InnoDB already had all the matching records. The only thing need is to call an InnoDB API to retrieve the count The difference can be huge. Following query output shows how big the difference can be: mysql> select count(*) from searchindex_inno where match(si_title, si_text) against ('people')  +----------+ | count(*) | +----------+ | 666877 | +----------+ 1 row in set (16 min 17.37 sec) So the query took almost 16 minutes. Let’s see how long the InnoDB can come up the result. In InnoDB, you can obtain extra diagnostic printout by turning on “innodb_ft_enable_diag_print”, this will print out extra query info: Error log: keynr=2, 'people' NL search Total docs: 10954826 Total words: 0 UNION: Searching: 'people' Processing time: 2 secs: row(s) 666877: error: 10 ft_init() ft_init_ext() keynr=2, 'people' NL search Total docs: 10954826 Total words: 0 UNION: Searching: 'people' Processing time: 3 secs: row(s) 666877: error: 10 Output shows it only took InnoDB only 3 seconds to get the result, while the whole query took 16 minutes to finish. So large amount of time has been wasted on the un-needed row fetching. The Solution: The solution is obvious. MySQL can skip some of its steps, optimize its plan and obtain useful information directly from InnoDB. Some of savings from doing this include: 1) Avoid redundant sorting. Since InnoDB already sorted the result according to ranking. MySQL Query Processing layer does not need to sort to get top matching results. 2) Avoid row by row fetching to get the matching count. InnoDB provides all the matching records. All those not in the result list should all have ranking of 0, and no need to be retrieved. And InnoDB has a count of total matching records on hand. No need to recount. 3) Covered index scan. InnoDB results always contains the matching records' Document ID and their ranking. So if only the Document ID and ranking is needed, there is no need to go to user table to fetch the record itself. 4) Narrow the search result early, reduce the user table access. If the user wants to get top N matching records, we do not need to fetch all matching records from user table. We should be able to first select TOP N matching DOC IDs, and then only fetch corresponding records with these Doc IDs. Performance Results and comparison with MyISAM The result by this change is very obvious. I includes six testing result performed by Alexander Rubin just to demonstrate how fast the InnoDB query now becomes when comparing MyISAM Full-Text Search. These tests are base on the English Wikipedia data of 5.4 Million rows and approximately 16G table. The test was performed on a machine with 1 CPU Dual Core, SSD drive, 8G of RAM and InnoDB_buffer_pool is set to 8 GB. Table 1: SELECT with LIMIT CLAUSE mysql> SELECT si_title, match(si_title, si_text) against('family') as rel FROM si WHERE match(si_title, si_text) against('family') ORDER BY rel desc LIMIT 10; InnoDB MyISAM Times Faster Time for the query 1.63 sec 3 min 26.31 sec 127 You can see for this particular query (retrieve top 10 records), InnoDB Full-Text Search is now approximately 127 times faster than MyISAM. Table 2: SELECT COUNT QUERY mysql>select count(*) from si where match(si_title, si_text) against('family‘); +----------+ | count(*) | +----------+ | 293955 | +----------+ InnoDB MyISAM Times Faster Time for the query 1.35 sec 28 min 59.59 sec 1289 In this particular case, where there are 293k matching results, InnoDB took only 1.35 second to get all of them, while take MyISAM almost half an hour, that is about 1289 times faster!. Table 3: SELECT ID with ORDER BY and LIMIT CLAUSE for selected terms mysql> SELECT <ID>, match(si_title, si_text) against(<TERM>) as rel FROM si_<TB> WHERE match(si_title, si_text) against (<TERM>) ORDER BY rel desc LIMIT 10; Term InnoDB (time to execute) MyISAM(time to execute) Times Faster family 0.5 sec 5.05 sec 10.1 family film 0.95 sec 25.39 sec 26.7 Pizza restaurant orange county California 0.93 sec 32.03 sec 34.4 President united states of America 2.5 sec 36.98 sec 14.8 Table 4: SELECT title and text with ORDER BY and LIMIT CLAUSE for selected terms mysql> SELECT <ID>, si_title, si_text, ... as rel FROM si_<TB> WHERE match(si_title, si_text) against (<TERM>) ORDER BY rel desc LIMIT 10; Term InnoDB (time to execute) MyISAM(time to execute) Times Faster family 0.61 sec 41.65 sec 68.3 family film 1.15 sec 47.17 sec 41.0 Pizza restaurant orange county california 1.03 sec 48.2 sec 46.8 President united states of america 2.49 sec 44.61 sec 17.9 Table 5: SELECT ID with ORDER BY and LIMIT CLAUSE for selected terms mysql> SELECT <ID>, match(si_title, si_text) against(<TERM>) as rel  FROM si_<TB> WHERE match(si_title, si_text) against (<TERM>) ORDER BY rel desc LIMIT 10; Term InnoDB (time to execute) MyISAM(time to execute) Times Faster family 0.5 sec 5.05 sec 10.1 family film 0.95 sec 25.39 sec 26.7 Pizza restaurant orange county califormia 0.93 sec 32.03 sec 34.4 President united states of america 2.5 sec 36.98 sec 14.8 Table 6: SELECT COUNT(*) mysql> SELECT count(*) FROM si_<TB> WHERE match(si_title, si_text) against (<TERM>) LIMIT 10; Term InnoDB (time to execute) MyISAM(time to execute) Times Faster family 0.47 sec 82 sec 174.5 family film 0.83 sec 131 sec 157.8 Pizza restaurant orange county califormia 0.74 sec 106 sec 143.2 President united states of america 1.96 sec 220 sec 112.2  Again, table 3 to table 6 all showing InnoDB consistently outperform MyISAM in these queries by a large margin. It becomes obvious the InnoDB has great advantage over MyISAM in handling large data search. Summary: These results demonstrate the great performance we could achieve by making MySQL optimizer and InnoDB Full-Text Search more tightly coupled. I think there are still many cases that InnoDB’s result info have not been fully taken advantage of, which means we still have great room to improve. And we will continuously explore the area, and get more dramatic results for InnoDB full-text searches. Jimmy Yang, September 29, 2012

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  • What causes bad performance in consumer apps?

    - by Crashworks
    My Comcast DVR takes at least three seconds to respond to every remote control keypress, making the simple task of watching television into a frustrating button-mashing experience. My iPhone takes at least fifteen seconds to display text messages and crashes ¼ of the times I try to bring up the iPad app; simply receiving and reading an email often takes well over a minute. Even the navcom in my car has mushy and unresponsive controls, often swallowing successive inputs if I make them less than a few seconds apart. These are all fixed-hardware end-consumer appliances for which usability should be paramount, and yet they all fail at basic responsiveness and latency. Their software is just too slow. What's behind this? Is it a technical problem, or a social one? Who or what is responsible? Is it because these were all written in managed, garbage-collected languages rather than native code? Is it the individual programmers who wrote the software for these devices? In all of these cases the app developers knew exactly what hardware platform they were targeting and what its capabilities were; did they not take it into account? Is it the guy who goes around repeating "optimization is the root of all evil," did he lead them astray? Was it a mentality of "oh it's just an additional 100ms" each time until all those milliseconds add up to minutes? Is it my fault, for having bought these products in the first place? This is a subjective question, with no single answer, but I'm often frustrated to see so many answers here saying "oh, don't worry about code speed, performance doesn't matter" when clearly at some point it does matter for the end-user who gets stuck with a slow, unresponsive, awful experience. So, at what point did things go wrong for these products? What can we as programmers do to avoid inflicting this pain on our own customers?

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  • Do or can robots cause considerable performance issues?

    - by Anicho
    So the question in the title is exactly what I am trying to find out. My case is: At work we are in a discussion with team members who seem to think bots will cause us problems relating to performance when running on our services website. Out setup: Lets say I have site www.mysite.co.uk this is a shop window to our online services which sit on www.mysiteonline.co.uk. When people search in google for mysite they see mysiteonline.co.uk as well as mysite.co.uk. Cases against stopping bots crawling: We don't store gb's of data publicly available on the web Most friendly bots, if they were to cause issues would have done so already In our instance the bots can't crawl the site because it requires username & password Stopping bots with robot .txt causes an issue with seo (ref.1) If it was a malicious bot, it would ignore robot.txt or meta tags anyway Ref 1. If we were to block mysiteonline.co.uk from having robots crawl this will affect seo rankings and make it inconvenient for users who actively search for mysite to find mysiteonline. Which we can prove is the case for a good portion of our users.

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  • android game performance regarding timers

    - by iQue
    Im new to the game-dev world and I have a tendancy to over-simplify my code, and sometimes this costs me alot fo memory. Im using a custom TimerTask that looks like this: public class Task extends TimerTask { private MainGamePanel panel; public Task(MainGamePanel panel) { this.panel=panel; } /** * When the timer executes, this code is run. */ public void run() { panel.createEnemies(); } } this task calls this method from my view: public void createEnemies() { Bitmap bmp = BitmapFactory.decodeResource(getResources(), R.drawable.female); if(enemyCounter < 24){ enemies.add(new Enemy(bmp, this)); } enemyCounter++; } Since I call this in the onCreate-method instead of in my views contructor (because My enemies need to get width and height of view). Im wondering if this will work when I have multiple levels in game (start a new intent). And if this kind of timer really is the best way to add a delay between the spawning-time of my enemies performance-wise. adding code for my timer if any1 came here cus they dont understand timers: private Timer timer1 = new Timer(); private long delay1 = 5*1000; // 5 sec delay public void surfaceCreated(SurfaceHolder holder) { timer1.schedule(new Task(this), 0, delay1); //I call my timer and add the delay thread.setRunning(true); thread.start(); }

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  • 12.10 visual performance using nvidia driver

    - by user100485
    My fresh ubuntu 12.10 install is slow, not something extreme but dragging windows, switching workspaces and things like that are just slow and look horrible. it feels like the fps is dropping in a game. Doing some photoshop work in windows was even a relief! This effect gets worse if I connect my external monitor. My system is an intel pentium dual core T4500 with 4gb memory and a GeForce 8200M G/integrated/SSE2 graphics chip. Nothing fancy but should be able to run ok. My "experience" in ubuntu is set to standard. (MSI cr500 laptop) I've installed the nvidia drivers, tried current and experimental and the experimental drivers seem to perform a bit better but overall bad anyway. I set the mode to adaptive in the nvidia-settings tool and it goes to maximum setting directly and doesn't come back. Using htop I found out that compiz or the X server always use a few percent of my cpu, more than I think it should and the time consumed is 5:18 for compiz, 4:33 for /usr/bin/X and 2:41 for google chrome(about 30 tabs open so not too strange I think.) What can I do to increase the visual performance cause this makes me not want to use ubuntu in public!

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  • Count a row VS Save the Row count after each update

    - by SAFAD
    I want to know whether saving row count in a table is better than counting it each time of the proccess. Quick Example : A visitor goes to Group Clan, the page displays clan information and Members who have joined the group,Should the page look for all the users who joined the clan and count them, or just display the number of members already saved in table ? I think the first one is not possible to get manipulated with but IT MIGHT cost performance Your Ideas ?

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  • SQL SERVER – What is Incremental Statistics? – Performance improvements in SQL Server 2014 – Part 1

    - by Pinal Dave
    This is the first part of the series Incremental Statistics. Here is the index of the complete series. What is Incremental Statistics? – Performance improvements in SQL Server 2014 – Part 1 Simple Example of Incremental Statistics – Performance improvements in SQL Server 2014 – Part 2 DMV to Identify Incremental Statistics – Performance improvements in SQL Server 2014 – Part 3 Statistics are considered one of the most important aspects of SQL Server Performance Tuning. You might have often heard the phrase, with related to performance tuning. “Update Statistics before you take any other steps to tune performance”. Honestly, I have said above statement many times and many times, I have personally updated statistics before I start to do any performance tuning exercise. You may agree or disagree to the point, but there is no denial that Statistics play an extremely vital role in the performance tuning. SQL Server 2014 has a new feature called Incremental Statistics. I have been playing with this feature for quite a while and I find that very interesting. After spending some time with this feature, I decided to write about this subject over here. New in SQL Server 2014 – Incremental Statistics Well, it seems like lots of people wants to start using SQL Server 2014′s new feature of Incremetnal Statistics. However, let us understand what actually this feature does and how it can help. I will try to simplify this feature first before I start working on the demo code. Code for all versions of SQL Server Here is the code which you can execute on all versions of SQL Server and it will update the statistics of your table. The keyword which you should pay attention is WITH FULLSCAN. It will scan the entire table and build brand new statistics for you which your SQL Server Performance Tuning engine can use for better estimation of your execution plan. UPDATE STATISTICS TableName(StatisticsName) WITH FULLSCAN Who should learn about this? Why? If you are using partitions in your database, you should consider about implementing this feature. Otherwise, this feature is pretty much not applicable to you. Well, if you are using single partition and your table data is in a single place, you still have to update your statistics the same way you have been doing. If you are using multiple partitions, this may be a very useful feature for you. In most cases, users have multiple partitions because they have lots of data in their table. Each partition will have data which belongs to itself. Now it is very common that each partition are populated separately in SQL Server. Real World Example For example, if your table contains data which is related to sales, you will have plenty of entries in your table. It will be a good idea to divide the partition into multiple filegroups for example, you can divide this table into 3 semesters or 4 quarters or even 12 months. Let us assume that we have divided our table into 12 different partitions. Now for the month of January, our first partition will be populated and for the month of February our second partition will be populated. Now assume, that you have plenty of the data in your first and second partition. Now the month of March has just started and your third partition has started to populate. Due to some reason, if you want to update your statistics, what will you do? In SQL Server 2012 and earlier version You will just use the code of WITH FULLSCAN and update the entire table. That means even though you have only data in third partition you will still update the entire table. This will be VERY resource intensive process as you will be updating the statistics of the partition 1 and 2 where data has not changed at all. In SQL Server 2014 You will just update the partition of Partition 3. There is a special syntax where you can now specify which partition you want to update now. The impact of this is that it is smartly merging the new data with old statistics and update the entire statistics without doing FULLSCAN of your entire table. This has a huge impact on performance. Remember that the new feature in SQL Server 2014 does not change anything besides the capability to update a single partition. However, there is one feature which is indeed attractive. Previously, when table data were changed 20% at that time, statistics update were triggered. However, now the same threshold is applicable to a single partition. That means if your partition faces 20% data, change it will also trigger partition level statistics update which, when merged to your final statistics will give you better performance. In summary If you are not using a partition, this feature is not applicable to you. If you are using a partition, this feature can be very helpful to you. Tomorrow: We will see working code of SQL Server 2014 Incremental Statistics. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: SQL Statistics, Statistics

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  • Increase application performance

    - by Prayos
    I'm writing a program for a company that will generate a daily report for them. All of the data that they use for this report is stored in a local SQLite database. For this report, the utilize pretty much every bit of the information in the database. So currently, when I query the datbase, I retrieve everything, and store the information in lists. Here's what I've got: using (var dataReader = _connection.Select(query)) { if (dataReader.HasRows) { while (dataReader.Read()) { _date.Add(Convert.ToDateTime(dataReader["date"])); _measured.Add(Convert.ToDouble(dataReader["measured_dist"])); _bit.Add(Convert.ToDouble(dataReader["bit_loc"])); _psi.Add(Convert.ToDouble(dataReader["pump_press"])); _time.Add(Convert.ToDateTime(dataReader["timestamp"])); _fob.Add(Convert.ToDouble(dataReader["force_on_bit"])); _torque.Add(Convert.ToDouble(dataReader["torque"])); _rpm.Add(Convert.ToDouble(dataReader["rpm"])); _pumpOneSpm.Add(Convert.ToDouble(dataReader["pump_1_strokes_pm"])); _pumpTwoSpm.Add(Convert.ToDouble(dataReader["pump_2_strokes_pm"])); _pullForce.Add(Convert.ToDouble(dataReader["pull_force"])); _gpm.Add(Convert.ToDouble(dataReader["flow"])); } } } I then utilize these lists for the calculations. Obviously, the more information that is in this database, the longer the initial query will take. I'm curious if there is a way to increase the performance of the query at all? Thanks for any and all help. EDIT One of the report rows is called Daily Drilling Hours. For this calculation, I use this method: // Retrieves the timestamps where measured depth == bit depth and PSI >= 50 public double CalculateDailyProjectDrillingHours(DateTime date) { var dailyTimeStamps = _time.Where((t, i) => _date[i].Equals(date) && _measured[i].Equals(_bit[i]) && _psi[i] >= 50).ToList(); return _dailyDrillingHours = Convert.ToDouble(Math.Round(TimeCalculations(dailyTimeStamps).TotalHours, 2, MidpointRounding.AwayFromZero)); } // Checks that the interval is less than 10, then adds the interval to the total time private static TimeSpan TimeCalculations(IList<DateTime> timeStamps) { var interval = new TimeSpan(0, 0, 10); var totalTime = new TimeSpan(); TimeSpan timeDifference; for (var j = 0; j < timeStamps.Count - 1; j++) { if (timeStamps[j + 1].Subtract(timeStamps[j]) <= interval) { timeDifference = timeStamps[j + 1].Subtract(timeStamps[j]); totalTime = totalTime.Add(timeDifference); } } return totalTime; }

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  • How to use caching to increase render performance?

    - by Christian Ivicevic
    First of all I am going to cover the basic design of my 2d tile-based engine written with SDL in C++, then I will point out what I am up to and where I need some hints. Concept of my engine My engine uses the concept of GameScreens which are stored on a stack in the main game class. The main methods of a screen are usually LoadContent, Render, Update and InitMultithreading. (I use the last one because I am using v8 as a JavaScript bridge to the engine. The main game loop then renders the top screen on the stack (if there is one; otherwise, it exits the game) - actually it calls the render methods, but stores all items to be rendered in a list. After gathering all this information the methods like SDL_BlitSurface are called by my GameUIRenderer which draws the enqueued content and then draws some overlay. The code looks like this: while(Game is running) { Handle input if(Screens on stack == 0) exit Update timer etc. Clear the screen Peek the screen on the stack and collect information on what to render Actually render the enqueue screen stuff and some overlay etc. Flip the screen } The GameUIRenderer uses as hinted a std::vector<std::shared_ptr<ImageToRender>> to hold all necessary information described by this class: class ImageToRender { private: SDL_Surface* image; int x, y, w, h, xOffset, yOffset; }; This bunch of attributes is usually needed if I have a texture atlas with all tiles in one SDL_Surface and then the engine should crop one specific area and draw this to the screen. The GameUIRenderer::Render() method then just iterates over all elements and renders them something like this: std::for_each( this->m_vImageVector.begin(), this->m_vImageVector.end(), [this](std::shared_ptr<ImageToRender> pCurrentImage) { SDL_Rect rc = { pCurrentImage->x, pCurrentImage->y, 0, 0 }; // For the sake of simplicity ignore offsets... SDL_Rect srcRect = { 0, 0, pCurrentImage->w, pCurrentImage->h }; SDL_BlitSurface(pCurrentImage->pImage, &srcRect, g_pFramework->GetScreen(), &rc); } ); this->m_vImageVector.clear(); Current ideas which need to be reviewed The specified approach works really good and IMHO it is really has a good structure, however the performance could be definitely increased. I would like to know what do you suggest, how to implement efficient caching of surfaces etc so that there is no need to redraw the same scene over and over again? The map itself would be almost static, only when the player moves, we would need to move the map. Furthermore animated entities would either require updates of the whole map or updates of only the specific areas the entities are currently moving in. My first approaches were to include a flag IsTainted which should be used by the GameUIRenderer to decide whether to redraw everything or use cached version (or to not render anything so that we do not have to Clear the screen and let the last frame persist). However this seems to be quite messy if I have to manually handle in my Render method of the screen class if something has changed or not.

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  • HPCM 11.1.2.x - Outline Optimisation for Calculation Performance

    - by Jane Story
    When an HPCM application is first created, it is likely that you will want to carry out some optimisation on the HPCM application’s Essbase outline in order to improve calculation execution times. There are several things that you may wish to consider. Because at least one dense dimension for an application is required to deploy from HPCM to Essbase, “Measures” and “AllocationType”, as the only required dimensions in an HPCM application, are created dense by default. However, for optimisation reasons, you may wish to consider changing this default dense/sparse configuration. In general, calculation scripts in HPCM execute best when they are targeting destinations with one or more dense dimensions. Therefore, consider your largest target stage i.e. the stage with the most assignment destinations and choose that as a dense dimension. When optimising an outline in this way, it is not possible to have a dense dimension in every target stage and so testing with the dense/sparse settings in every stage is the key to finding the best configuration for each individual application. It is not possible to change the dense/sparse setting of individual cloned dimensions from EPMA. When a dimension that is to be repeated in multiple stages, and therefore cloned, is defined in EPMA, every instance of that dimension has the same storage setting. However, such manual changes may not be preserved in all cases. Please see below for full explanation. However, once the application has been deployed from EPMA to HPCM and from HPCM to Essbase, it is possible to make the dense/sparse changes to a cloned dimension directly in Essbase. This can be done by editing the properties of the outline in Essbase Administration Services (EAS) and manually changing the dense/sparse settings of individual dimensions. There are two methods of deployment from HPCM to Essbase from 11.1.2.1. There is a “replace” deploy method and an “update” deploy method: “Replace” will delete the Essbase application and replace it. If this method is chosen, then any changes made directly on the Essbase outline will be lost. If you use the update deploy method (with or without archiving and reloading data), then the Essbase outline, including any manual changes you have made (i.e. changes to dense/sparse settings of the cloned dimensions), will be preserved. Notes If you are using the calculation optimisation technique mentioned in a previous blog to calculate multiple POVs (https://blogs.oracle.com/pa/entry/hpcm_11_1_2_optimising) and you are calculating all members of that POV dimension (e.g. all months in the Period dimension) then you could consider making that dimension dense. Always review Block sizes after all changes! The maximum block size recommended in the Essbase Database Administrator’s Guide is 100k for 32 bit Essbase and 200k for 64 bit Essbase. However, calculations may perform better with a larger than recommended block size provided that sufficient memory is available on the Essbase server. Test different configurations to determine the most optimal solution for your HPCM application. Please note that this blog article covers HPCM outline optimisation only. Additional performance tuning can be achieved by methodically testing database settings i.e data cache, index cache and/or commit block settings. For more information on Essbase tuning best practices, please review these items in the Essbase Database Administrators Guide. For additional information on the commit block setting, please see the previous PA blog article https://blogs.oracle.com/pa/entry/essbase_11_1_2_commit

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  • New Whitepaper: Oracle E-Business Suite on Exadata

    - by Steven Chan
    Our Maximum Availability Architecture (MAA) team has quietly been amassing a formidable set of whitepapers about the Oracle Exadata Database Machine.  They're available here:MAA Best Practices - Exadata Database MachineIf you're one of the lucky ones with access to this hardware platform, you'll be pleased to hear that the MAA team has just published a new whitepaper with best practices for EBS environments:Oracle E-Business Suite on ExadataThis whitepaper covers the following topics:Getting to Exadata -- a high level overview of fresh installation on, and migration to, Exadata Database Machine with pointers to more detailed documentation High Availability and Disaster Recovery -- an overview of our MAA best practices with pointers to our detailed MAA Best Practices documentation Performance and Scalability -- best practices for running Oracle E-Business Suite on Exadata Database Machine based on our internal testing

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  • Is there a PHP benchmark that meets these specific criteria? [closed]

    - by Alex R
    I'm working on a tool which converts PHP code to Scala. As one of the finishing touches, I'm in need of a really good (er, somewhat biased) benchmark. By dumb luck my first benchmark attempt was with some code which uses bcmath extensively, which unfortunately is 1000x slower in Java, making the Scala code 22x slower overall than the original PHP. So I'm looking for some meaningful PHP benchmark with the following characteristics: The PHP source needs to be in a single file. It should solve a real-world problem. No silly looping over empty methods etc. I need it to be simple to setup - no databases, hard-to-find input files, etc. Simple text input and output preferred. It should not use features that are slow in Java (BigInteger, trigonometric functions, etc). It should not use exoteric or dynamic PHP functions (e.g. no "eval" or "variable vars"). It should not over-rely on built-in libraries, e.g. MD5, crypt, etc. It should not be I/O bound. A CPU-bound memory-hungry algorithm is preferred. Basically, intensive OO operations, integer and string manipulation, recursion, etc would be great. Thanks

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  • theoretical and practical matrix multiplication FLOP

    - by mjr
    I wrote traditional matrix multiplication in c++ and tried to measure and compare its theoretical and practical FLOP. As I know inner loop of MM has 2 operation therefore simple MM theoretical Flops is 2*n*n*n (2n^3) but in practice I get something like 4n^3 + number of operation which is 2 i.e. 6n^3 also if I just try to add up only one array a[i][j]++ practical flops then calculate like 3n^3 and not n^3 as you see again it is 2n^3 +1 operation and not 1 operation * n^3 . This is in case if I use 1D array in three nested loops as Matrix multiplication and compare flop, practical flop is the same (near) the theoretical flop and depend exactly as the number of operation in inner loop.I could not find the reason for this behaviour. what is the reason in both case? I know that theoretical flop is not the same as practical one because of some operations like load etc. system specification: Intel core2duo E4500 3700g memory L2 cache 2M x64 fedora 17 sample results: Matrix matrix multiplication 512*512 Real_time: 1.718368 Proc_time: 1.227672 Total flpops: 807,107,072 MFLOPS: 657.429016 Real_time: 3.608078 Proc_time: 3.042272 Total flpops: 807,024,448 MFLOPS: 265.270355 theoretical flop: 2*512*512*512=268,435,456 Practical flops= 6*512^3 =807,107,072 Using 1 dimensional array float d[size][size]:512 or any size for (int j = 0; j < size; ++j) { for (int k = 0; k < size; ++k) { d[k]=d[k]+e[k]+f[k]+g[k]+r; } } Real_time: 0.002288 Proc_time: 0.002260 Total flpops: 1,048,578 MFLOPS: 464.027161 theroretical flop: *4n^2=4*512^2=1,048,576* practical flop : 4n^2+overhead (other operation?)=1,048,578 3 loop version: Real_time: 1.282257 Proc_time: 1.155990 Total flpops: 536,872,000 MFLOPS: 464.426117 theoretical flop:4n^3 = 536,870,912 practical flop: *4n^3=4*512^3+overheads(other operation?)=536,872,000* thank you

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