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  • Mounting Solaris UFS partition on Debian(with FreeBSD kernel)

    - by hayalci
    I have some disks that were being used on a Solaris system. The disks are formatted as UFS. I attached them to a Debian system (with FreeBSD kernel. Debian/kFreeBSD), but I cannot mount them. $ mount -t ufs /dev/da2s1 /mnt/diska mount: /dev/da2s1 : Invalid argument Also the tunefs.ufs does not work; $ tunefs.ufs -p /dev/da2s1 tunefs.ufs: /dev/da2s1: could not read superblock to fill out disk Is there an incompatibility between FreeBSD UFS and Solaris UFS? Is it possible to mount one, under the other OS ? Note: tunefs.ufs works on the root partition $ tunefs.ufs -p /dev/da7s2 tunefs.ufs: ACLs: (-a) disabled tunefs.ufs: MAC multilabel: (-l) disabled tunefs.ufs: soft updates: (-n) disabled tunefs.ufs: gjournal: (-J) disabled tunefs.ufs: maximum blocks per file in a cylinder group: (-e) 2048 tunefs.ufs: average file size: (-f) 16384 tunefs.ufs: average number of files in a directory: (-s) 64 tunefs.ufs: minimum percentage of free space: (-m) 8% tunefs.ufs: optimization preference: (-o) time tunefs.ufs: volume label: (-L)

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  • How to measure that a host is good for users in Egypt ?

    - by Sherif Buzz
    Hi all, I currently have a site that's hosted in Texas. The majority of my users are from Egypt and I'm a bit concerned that the current hosting is not the optimal in terms of performance. The site is not slow but for how can I know if, for example, hosting it in Europe or Asia is better ? To clarify I need to know there is a way that I can test different hosting options - for example how can I test the average response time between Egypt and a host in Texas, the average response time between Egypt and a host in the UK ?

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  • How to make variable range of cells?

    - by Ertai
    In A column I have a set of numbers (over 1 000). I want to get average of ten of them (a1:a10) and wrtite into next column (B). Now I want to get next ten numbers and get average of them (a11:a20). And so on... How to get this if in C1 i would have number which is range (i.e 10 = a1:a10/a11:a20 ; i.e 25 a1:a25/a26:a50) of the cells? When I change C1 value I want to column B to update automaticaly? Is this possible?

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  • I know this is a stupid question but... How many websites can my server potentially hold?

    - by Daniel Kindler
    Sorry for the "noob" question, but... About how many medium-sized websites with average traffic could this server hold? Just like the average website, kind of like a small business site. How many sites could this server hold, but still maintain nice, decent speed? PowerEdge R510 PE R510 Chassis for Up to Four 3.5" Cabled Hard Drives, LED edit Processor Intel® Xeon® E5630 2.53Ghz, 12M Cache,Turbo, HT, 1066MHz Max Mem edit Memory 8GB Memory (4x2GB), 1333MHz Single Ranked UDIMMs for 1 Procs, Optimized edit Operating System SUSE Linux Enterprise Server 10, SP3, Up To 32 CPU Lic, 1 YR Sub, DIB, Media edit Red Hat Enterprise Linux Licensing Hard Drives 250GB 7.2K RPM SATA 3.5" Cabled Hard Drive edit Hard Drives 1TB 7.2K RPM SATA 3.5" Cabled Hard Drive edit Hard Drives 2 X 2TB 7.2K RPM SATA 3.5in Cabled Hard Drive Hard Drive Configuration No RAID, Embedded SATA Controller for x4 Chassis edit Power Supply 480 Watt Non-Redundant Power Supply edit Thank you!

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  • How many websites can my server potentially hold?

    - by Daniel Kindler
    Sorry for the "noob" question, but... About how many medium-sized websites with average traffic could this server hold? Just like the average website, kind of like a small business site. How many sites could this server hold, but still maintain nice, decent speed? PowerEdge R510 PE R510 Chassis for Up to Four 3.5" Cabled Hard Drives, LED edit Processor Intel® Xeon® E5630 2.53Ghz, 12M Cache,Turbo, HT, 1066MHz Max Mem edit Memory 8GB Memory (4x2GB), 1333MHz Single Ranked UDIMMs for 1 Procs, Optimized edit Operating System SUSE Linux Enterprise Server 10, SP3, Up To 32 CPU Lic, 1 YR Sub, DIB, Media edit Red Hat Enterprise Linux Licensing Hard Drives 250GB 7.2K RPM SATA 3.5" Cabled Hard Drive edit Hard Drives 1TB 7.2K RPM SATA 3.5" Cabled Hard Drive edit Hard Drives 2 X 2TB 7.2K RPM SATA 3.5in Cabled Hard Drive Hard Drive Configuration No RAID, Embedded SATA Controller for x4 Chassis edit Power Supply 480 Watt Non-Redundant Power Supply edit Thank you!

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  • Server Requirement and Cost for an android Application [duplicate]

    - by CagkanToptas
    This question already has an answer here: How do you do load testing and capacity planning for web sites? 3 answers Can you help me with my capacity planning? 2 answers I am working on a project which is an android application. For my project proposal, I need to calculate what is my server requirements to overcome the traffic I explained below? and if possible, I want to learn what is approximate cost of such server? I am giving the maximum expected values for calculation : -Database will be in mysql (Average service time of DB is 100-110ms in my computer[i5,4GB Ram]) -A request will transfer 150Kb data for each request on average. -Total user count : 1m -Active user count : 50k -Estimated request/sec for 1 active user : 0.06 -Total expected request/second to the server = ~5000 I am expecting this traffic between 20:00-1:00 everyday and then this values will decrease to 1/10 rest of the day. Is there any solution to this? [e.g increasing server capacity in a specific time period everyday to reduce cost]

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  • Progress bar in a Flash MP3 Player

    - by Deryck
    Hi I have coded a simple XML driven MP3 player. I have used Sound and SoundChannel objects and method but I can´t find a way of make a progress bar. I don´t need a loading progress I need a song progress status bar. Canbd anybody help me? Thanks. UPDATE: Theres is the code. var musicReq: URLRequest; var thumbReq: URLRequest; var music:Sound = new Sound(); var sndC:SoundChannel; var currentSnd:Sound = music; var position:Number; var currentIndex:Number = 0; var songPaused:Boolean; var songStopped:Boolean; var lineClr:uint; var changeClr:Boolean; var xml:XML; var songList:XMLList; var loader:URLLoader = new URLLoader(); loader.addEventListener(Event.COMPLETE, Loaded); loader.load(new URLRequest("musiclist.xml")); var thumbHd:MovieClip = new MovieClip(); thumbHd.x = 50; thumbHd.y = 70; addChild(thumbHd); function Loaded(e:Event):void{ xml = new XML(e.target.data); songList = xml.song; musicReq = new URLRequest(songList[0].url); thumbReq = new URLRequest(songList[0].thumb); music.load(musicReq); sndC = music.play(); title_txt.text = songList[0].title + " - " + songList[0].artist; loadThumb(); sndC.addEventListener(Event.SOUND_COMPLETE, nextSong); } function loadThumb():void{ var thumbLoader:Loader = new Loader(); thumbReq = new URLRequest(songList[currentIndex].thumb); thumbLoader.load(thumbReq); thumbLoader.contentLoaderInfo.addEventListener(Event.COMPLETE, thumbLoaded); } function thumbLoaded(e:Event):void { var thumb:Bitmap = (Bitmap)(e.target.content); var holder:MovieClip = thumbHd; holder.addChild(thumb); } prevBtn.addEventListener(MouseEvent.CLICK, prevSong); nextBtn.addEventListener(MouseEvent.CLICK, nextSong); playBtn.addEventListener(MouseEvent.CLICK, playSong); function prevSong(e:Event):void{ if(currentIndex 0){ currentIndex--; } else{ currentIndex = songList.length() - 1; } var prevReq:URLRequest = new URLRequest(songList[currentIndex].url); var prevPlay:Sound = new Sound(prevReq); sndC.stop(); title_txt.text = songList[currentIndex].title + " - " + songList[currentIndex].artist; sndC = prevPlay.play(); currentSnd = prevPlay; songPaused = false; loadThumb(); sndC.addEventListener(Event.SOUND_COMPLETE, nextSong); } function nextSong(e:Event):void { if(currentIndex And here the code for the lenght and position. It´s inside a MovieClip. That´s why I use absolute path for find the Sound object. this.addEventListener(Event.ENTER_FRAME, moveSpeaker); var initWidth:Number = this.SpkCone.width; var initHeight:Number = this.SpkCone.height; var rootObj:Object = root; function moveSpeaker(eventArgs:Event) { var average:Number = ((rootObj.audioPlayer_mc.sndC.leftPeak + rootObj.audioPlayer_mc.sndC.rightPeak) / 2) * 10; // trace(average); // trace(initWidth + ":" + initHeight); trace(rootObj.audioPlayer_mc.sndC.position + "/" + rootObj.audioPlayer_mc.music.length); this.SpkCone.width = initWidth + average; this.SpkCone.height = initHeight + average; }

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  • Getting timing consistency in Linux

    - by Jim Hunziker
    I can't seem to get a simple program (with lots of memory access) to achieve consistent timing in Linux. I'm using a 2.6 kernel, and the program is being run on a dual-core processor with realtime priority. I'm trying to disable cache effects by declaring the memory arrays as volatile. Below are the results and the program. What are some possible sources of the outliers? Results: Number of trials: 100 Range: 0.021732s to 0.085596s Average Time: 0.058094s Standard Deviation: 0.006944s Extreme Outliers (2 SDs away from mean): 7 Average Time, excluding extreme outliers: 0.059273s Program: #include <stdio.h> #include <stdlib.h> #include <math.h> #include <sched.h> #include <sys/time.h> #define NUM_POINTS 5000000 #define REPS 100 unsigned long long getTimestamp() { unsigned long long usecCount; struct timeval timeVal; gettimeofday(&timeVal, 0); usecCount = timeVal.tv_sec * (unsigned long long) 1000000; usecCount += timeVal.tv_usec; return (usecCount); } double convertTimestampToSecs(unsigned long long timestamp) { return (timestamp / (double) 1000000); } int main(int argc, char* argv[]) { unsigned long long start, stop; double times[REPS]; double sum = 0; double scale, avg, newavg, median; double stddev = 0; double maxval = -1.0, minval = 1000000.0; int i, j, freq, count; int outliers = 0; struct sched_param sparam; sched_getparam(getpid(), &sparam); sparam.sched_priority = sched_get_priority_max(SCHED_FIFO); sched_setscheduler(getpid(), SCHED_FIFO, &sparam); volatile float* data; volatile float* results; data = calloc(NUM_POINTS, sizeof(float)); results = calloc(NUM_POINTS, sizeof(float)); for (i = 0; i < REPS; ++i) { start = getTimestamp(); for (j = 0; j < NUM_POINTS; ++j) { results[j] = data[j]; } stop = getTimestamp(); times[i] = convertTimestampToSecs(stop-start); } free(data); free(results); for (i = 0; i < REPS; i++) { sum += times[i]; if (times[i] > maxval) maxval = times[i]; if (times[i] < minval) minval = times[i]; } avg = sum/REPS; for (i = 0; i < REPS; i++) stddev += (times[i] - avg)*(times[i] - avg); stddev /= REPS; stddev = sqrt(stddev); for (i = 0; i < REPS; i++) { if (times[i] > avg + 2*stddev || times[i] < avg - 2*stddev) { sum -= times[i]; outliers++; } } newavg = sum/(REPS-outliers); printf("Number of trials: %d\n", REPS); printf("Range: %fs to %fs\n", minval, maxval); printf("Average Time: %fs\n", avg); printf("Standard Deviation: %fs\n", stddev); printf("Extreme Outliers (2 SDs away from mean): %d\n", outliers); printf("Average Time, excluding extreme outliers: %fs\n", newavg); return 0; }

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  • How to gain accurate results with Painter's algorithm?

    - by pimvdb
    A while ago I asked how to determine when a face is overlapping another. The advice was to use a Z-buffer. However, I cannot use a Z-buffer in my current project and hence I would like to use the Painter's algorithm. I have no good clue as to when a surface is behind or in front of another, though. I've tried numerous methods but they all fail in edge cases, or they fail even in general cases. This is a list of sorting methods I've tried so far: Distance to midpoint of each face Average distance to each vertex of each face Average z value of each vertex Higest z value of vertices of each face and draw those first Lowest z value of vertices of each face and draw those last The problem is that a face might have a closer distance but is still further away. All these methods seem unreliable. Edit: For example, in the following image the surface with the blue point as midpoint is painted over the surface with the red point as midpoint, because the blue point is closer. However, this is because the surface of the red point is larger and the midpoint is further away. The surface with the red point should be painted over the blue one, because it is closer, whilst the midpoint distance says the opposite. What exactly is used in the Painter's algorithm to determine the order in which objects should be drawn?

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  • How to manage a developer who has poor communication skills

    - by djcredo
    I manage a small team of developers on an application which is in the mid-point of its lifecycle, within a big firm. This unfortunately means there is commonly a 30/70 split of Programming tasks to "other technical work". This work includes: Working with DBA / Unix / Network / Loadbalancer teams on various tasks Placing & managing orders for hardware or infrastructure in different regions Running tests that have not yet been migrated to CI Analysis Support / Investigation Its fair to say that the Developers would all prefer to be coding, rather than doing these more mundane tasks, so I try to hand out the fun programming jobs evenly amongst the team. Most of the team was hired because, though they may not have the elite programming skills to write their own compiler / game engine / high-frequency trading system etc., they are good communicators who "can get stuff done", work with other teams, and somewhat navigate the complex beaurocracy here. They are good developers, but they are also good all-round technical staff. However, one member of the team probably has above-average coding skills, but below-average communication skills. Traditionally, the previous Development Manager tended to give him the Programming tasks and not the more mundane tasks listed above. However, I don't feel that this is fair to the rest of the team, who have shown an aptitute for developing a well-rounded skillset that is commonly required in a big-business IT department. What should I do in this situation? If I continue to give him more programming work, I know that it will be done faster (and conversly, I would expect him to complete the other work slower). But it goes against my principles, and promotes the idea that you can carve out a "comfortable niche" for yourself simply by being bad at the tasks you don't like.

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  • Solving Big Problems with Oracle R Enterprise, Part II

    - by dbayard
    Part II – Solving Big Problems with Oracle R Enterprise In the first post in this series (see https://blogs.oracle.com/R/entry/solving_big_problems_with_oracle), we showed how you can use R to perform historical rate of return calculations against investment data sourced from a spreadsheet.  We demonstrated the calculations against sample data for a small set of accounts.  While this worked fine, in the real-world the problem is much bigger because the amount of data is much bigger.  So much bigger that our approach in the previous post won’t scale to meet the real-world needs. From our previous post, here are the challenges we need to conquer: The actual data that needs to be used lives in a database, not in a spreadsheet The actual data is much, much bigger- too big to fit into the normal R memory space and too big to want to move across the network The overall process needs to run fast- much faster than a single processor The actual data needs to be kept secured- another reason to not want to move it from the database and across the network And the process of calculating the IRR needs to be integrated together with other database ETL activities, so that IRR’s can be calculated as part of the data warehouse refresh processes In this post, we will show how we moved from sample data environment to working with full-scale data.  This post is based on actual work we did for a financial services customer during a recent proof-of-concept. Getting started with the Database At this point, we have some sample data and our IRR function.  We were at a similar point in our customer proof-of-concept exercise- we had sample data but we did not have the full customer data yet.  So our database was empty.  But, this was easily rectified by leveraging the transparency features of Oracle R Enterprise (see https://blogs.oracle.com/R/entry/analyzing_big_data_using_the).  The following code shows how we took our sample data SimpleMWRRData and easily turned it into a new Oracle database table called IRR_DATA via ore.create().  The code also shows how we can access the database table IRR_DATA as if it was a normal R data.frame named IRR_DATA. If we go to sql*plus, we can also check out our new IRR_DATA table: At this point, we now have our sample data loaded in the database as a normal Oracle table called IRR_DATA.  So, we now proceeded to test our R function working with database data. As our first test, we retrieved the data from a single account from the IRR_DATA table, pull it into local R memory, then call our IRR function.  This worked.  No SQL coding required! Going from Crawling to Walking Now that we have shown using our R code with database-resident data for a single account, we wanted to experiment with doing this for multiple accounts.  In other words, we wanted to implement the split-apply-combine technique we discussed in our first post in this series.  Fortunately, Oracle R Enterprise provides a very scalable way to do this with a function called ore.groupApply().  You can read more about ore.groupApply() here: https://blogs.oracle.com/R/entry/analyzing_big_data_using_the1 Here is an example of how we ask ORE to take our IRR_DATA table in the database, split it by the ACCOUNT column, apply a function that calls our SimpleMWRR() calculation, and then combine the results. (If you are following along at home, be sure to have installed our myIRR package on your database server via  “R CMD INSTALL myIRR”). The interesting thing about ore.groupApply is that the calculation is not actually performed in my desktop R environment from which I am running.  What actually happens is that ore.groupApply uses the Oracle database to perform the work.  And the Oracle database is what actually splits the IRR_DATA table by ACCOUNT.  Then the Oracle database takes the data for each account and sends it to an embedded R engine running on the database server to apply our R function.  Then the Oracle database combines all the individual results from the calls to the R function. This is significant because now the embedded R engine only needs to deal with the data for a single account at a time.  Regardless of whether we have 20 accounts or 1 million accounts or more, the R engine that performs the calculation does not care.  Given that normal R has a finite amount of memory to hold data, the ore.groupApply approach overcomes the R memory scalability problem since we only need to fit the data from a single account in R memory (not all of the data for all of the accounts). Additionally, the IRR_DATA does not need to be sent from the database to my desktop R program.  Even though I am invoking ore.groupApply from my desktop R program, because the actual SimpleMWRR calculation is run by the embedded R engine on the database server, the IRR_DATA does not need to leave the database server- this is both a performance benefit because network transmission of large amounts of data take time and a security benefit because it is harder to protect private data once you start shipping around your intranet. Another benefit, which we will discuss in a few paragraphs, is the ability to leverage Oracle database parallelism to run these calculations for dozens of accounts at once. From Walking to Running ore.groupApply is rather nice, but it still has the drawback that I run this from a desktop R instance.  This is not ideal for integrating into typical operational processes like nightly data warehouse refreshes or monthly statement generation.  But, this is not an issue for ORE.  Oracle R Enterprise lets us run this from the database using regular SQL, which is easily integrated into standard operations.  That is extremely exciting and the way we actually did these calculations in the customer proof. As part of Oracle R Enterprise, it provides a SQL equivalent to ore.groupApply which it refers to as “rqGroupEval”.  To use rqGroupEval via SQL, there is a bit of simple setup needed.  Basically, the Oracle Database needs to know the structure of the input table and the grouping column, which we are able to define using the database’s pipeline table function mechanisms. Here is the setup script: At this point, our initial setup of rqGroupEval is done for the IRR_DATA table.  The next step is to define our R function to the database.  We do that via a call to ORE’s rqScriptCreate. Now we can test it.  The SQL you use to run rqGroupEval uses the Oracle database pipeline table function syntax.  The first argument to irr_dataGroupEval is a cursor defining our input.  You can add additional where clauses and subqueries to this cursor as appropriate.  The second argument is any additional inputs to the R function.  The third argument is the text of a dummy select statement.  The dummy select statement is used by the database to identify the columns and datatypes to expect the R function to return.  The fourth argument is the column of the input table to split/group by.  The final argument is the name of the R function as you defined it when you called rqScriptCreate(). The Real-World Results In our real customer proof-of-concept, we had more sophisticated calculation requirements than shown in this simplified blog example.  For instance, we had to perform the rate of return calculations for 5 separate time periods, so the R code was enhanced to do so.  In addition, some accounts needed a time-weighted rate of return to be calculated, so we extended our approach and added an R function to do that.  And finally, there were also a few more real-world data irregularities that we needed to account for, so we added logic to our R functions to deal with those exceptions.  For the full-scale customer test, we loaded the customer data onto a Half-Rack Exadata X2-2 Database Machine.  As our half-rack had 48 physical cores (and 96 threads if you consider hyperthreading), we wanted to take advantage of that CPU horsepower to speed up our calculations.  To do so with ORE, it is as simple as leveraging the Oracle Database Parallel Query features.  Let’s look at the SQL used in the customer proof: Notice that we use a parallel hint on the cursor that is the input to our rqGroupEval function.  That is all we need to do to enable Oracle to use parallel R engines. Here are a few screenshots of what this SQL looked like in the Real-Time SQL Monitor when we ran this during the proof of concept (hint: you might need to right-click on these images to be able to view the images full-screen to see the entire image): From the above, you can notice a few things (numbers 1 thru 5 below correspond with highlighted numbers on the images above.  You may need to right click on the above images and view the images full-screen to see the entire image): The SQL completed in 110 seconds (1.8minutes) We calculated rate of returns for 5 time periods for each of 911k accounts (the number of actual rows returned by the IRRSTAGEGROUPEVAL operation) We accessed 103m rows of detailed cash flow/market value data (the number of actual rows returned by the IRR_STAGE2 operation) We ran with 72 degrees of parallelism spread across 4 database servers Most of our 110seconds was spent in the “External Procedure call” event On average, we performed 8,200 executions of our R function per second (110s/911k accounts) On average, each execution was passed 110 rows of data (103m detail rows/911k accounts) On average, we did 41,000 single time period rate of return calculations per second (each of the 8,200 executions of our R function did rate of return calculations for 5 time periods) On average, we processed over 900,000 rows of database data in R per second (103m detail rows/110s) R + Oracle R Enterprise: Best of R + Best of Oracle Database This blog post series started by describing a real customer problem: how to perform a lot of calculations on a lot of data in a short period of time.  While standard R proved to be a very good fit for writing the necessary calculations, the challenge of working with a lot of data in a short period of time remained. This blog post series showed how Oracle R Enterprise enables R to be used in conjunction with the Oracle Database to overcome the data volume and performance issues (as well as simplifying the operations and security issues).  It also showed that we could calculate 5 time periods of rate of returns for almost a million individual accounts in less than 2 minutes. In a future post, we will take the same R function and show how Oracle R Connector for Hadoop can be used in the Hadoop world.  In that next post, instead of having our data in an Oracle database, our data will live in Hadoop and we will how to use the Oracle R Connector for Hadoop and other Oracle Big Data Connectors to move data between Hadoop, R, and the Oracle Database easily.

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  • Whats the greatest most impressive programing feat you ever witnessed? [closed]

    - by David Reis
    Everyone knows of the old adage that the best programmers can be orders of magnitude better than the average. I've personally seen good code and programmers, but never something so absurd. So the questions is, what is the most impressive feat of programming you ever witnessed or heard of? You can define impressive by: The scope of the task at hand e.g. John single handedly developed the framework for his company, a work comparable in scope to what the other 200 employed were doing combined. Speed e.g. Stu programmed an entire real time multi-tasking app OS on an weekened including its own C compiler and shell command line tools Complexity e.g. Jane rearchitected our entire 10 millon LOC app to work in a cluster of servers. And she did it in an afternoon. Quality e.g. Charles's code had a rate of defects per LOC 100 times lesser than the company average. Furthermore he code was clean and understandable by all. Obviously, the more of these characteristics combined, and the more extreme each of them, the more impressive is the feat. So, let me have it. What's the most absurd feat you can recount? Please provide as much detail as possible and try to avoid urban legends or exaggerations. Post only what you can actually vouch for. Bonus questions: Was the herculean task a one-of, or did the individual regularly amazed people? How do you explain such impressive performance? How was the programmer recognized for such awesome work?

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  • Building Queries Systematically

    - by Jeremy Smyth
    The SQL language is a bit like a toolkit for data. It consists of lots of little fiddly bits of syntax that, taken together, allow you to build complex edifices and return powerful results. For the uninitiated, the many tools can be quite confusing, and it's sometimes difficult to decide how to go about the process of building non-trivial queries, that is, queries that are more than a simple SELECT a, b FROM c; A System for Building Queries When you're building queries, you could use a system like the following:  Decide which fields contain the values you want to use in our output, and how you wish to alias those fields Values you want to see in your output Values you want to use in calculations . For example, to calculate margin on a product, you could calculate price - cost and give it the alias margin. Values you want to filter with. For example, you might only want to see products that weigh more than 2Kg or that are blue. The weight or colour columns could contain that information. Values you want to order by. For example you might want the most expensive products first, and the least last. You could use the price column in descending order to achieve that. Assuming the fields you've picked in point 1 are in multiple tables, find the connections between those tables Look for relationships between tables and identify the columns that implement those relationships. For example, The Orders table could have a CustomerID field referencing the same column in the Customers table. Sometimes the problem doesn't use relationships but rests on a different field; sometimes the query is looking for a coincidence of fact rather than a foreign key constraint. For example you might have sales representatives who live in the same state as a customer; this information is normally not used in relationships, but if your query is for organizing events where sales representatives meet customers, it's useful in that query. In such a case you would record the names of columns at either end of such a connection. Sometimes relationships require a bridge, a junction table that wasn't identified in point 1 above but is needed to connect tables you need; these are used in "many-to-many relationships". In these cases you need to record the columns in each table that connect to similar columns in other tables. Construct a join or series of joins using the fields and tables identified in point 2 above. This becomes your FROM clause. Filter using some of the fields in point 1 above. This becomes your WHERE clause. Construct an ORDER BY clause using values from point 1 above that are relevant to the desired order of the output rows. Project the result using the remainder of the fields in point 1 above. This becomes your SELECT clause. A Worked Example   Let's say you want to query the world database to find a list of countries (with their capitals) and the change in GNP, using the difference between the GNP and GNPOld columns, and that you only want to see results for countries with a population greater than 100,000,000. Using the system described above, we could do the following:  The Country.Name and City.Name columns contain the name of the country and city respectively.  The change in GNP comes from the calculation GNP - GNPOld. Both those columns are in the Country table. This calculation is also used to order the output, in descending order To see only countries with a population greater than 100,000,000, you need the Population field of the Country table. There is also a Population field in the City table, so you'll need to specify the table name to disambiguate. You can also represent a number like 100 million as 100e6 instead of 100000000 to make it easier to read. Because the fields come from the Country and City tables, you'll need to join them. There are two relationships between these tables: Each city is hosted within a country, and the city's CountryCode column identifies that country. Also, each country has a capital city, whose ID is contained within the country's Capital column. This latter relationship is the one to use, so the relevant columns and the condition that uses them is represented by the following FROM clause:  FROM Country JOIN City ON Country.Capital = City.ID The statement should only return countries with a population greater than 100,000,000. Country.Population is the relevant column, so the WHERE clause becomes:  WHERE Country.Population > 100e6  To sort the result set in reverse order of difference in GNP, you could use either the calculation, or the position in the output (it's the third column): ORDER BY GNP - GNPOld or ORDER BY 3 Finally, project the columns you wish to see by constructing the SELECT clause: SELECT Country.Name AS Country, City.Name AS Capital,        GNP - GNPOld AS `Difference in GNP`  The whole statement ends up looking like this:  mysql> SELECT Country.Name AS Country, City.Name AS Capital, -> GNP - GNPOld AS `Difference in GNP` -> FROM Country JOIN City ON Country.Capital = City.ID -> WHERE Country.Population > 100e6 -> ORDER BY 3 DESC; +--------------------+------------+-------------------+ | Country            | Capital    | Difference in GNP | +--------------------+------------+-------------------+ | United States | Washington | 399800.00 | | China | Peking | 64549.00 | | India | New Delhi | 16542.00 | | Nigeria | Abuja | 7084.00 | | Pakistan | Islamabad | 2740.00 | | Bangladesh | Dhaka | 886.00 | | Brazil | Brasília | -27369.00 | | Indonesia | Jakarta | -130020.00 | | Russian Federation | Moscow | -166381.00 | | Japan | Tokyo | -405596.00 | +--------------------+------------+-------------------+ 10 rows in set (0.00 sec) Queries with Aggregates and GROUP BY While this system might work well for many queries, it doesn't cater for situations where you have complex summaries and aggregation. For aggregation, you'd start with choosing which columns to view in the output, but this time you'd construct them as aggregate expressions. For example, you could look at the average population, or the count of distinct regions.You could also perform more complex aggregations, such as the average of GNP per head of population calculated as AVG(GNP/Population). Having chosen the values to appear in the output, you must choose how to aggregate those values. A useful way to think about this is that every aggregate query is of the form X, Y per Z. The SELECT clause contains the expressions for X and Y, as already described, and Z becomes your GROUP BY clause. Ordinarily you would also include Z in the query so you see how you are grouping, so the output becomes Z, X, Y per Z.  As an example, consider the following, which shows a count of  countries and the average population per continent:  mysql> SELECT Continent, COUNT(Name), AVG(Population)     -> FROM Country     -> GROUP BY Continent; +---------------+-------------+-----------------+ | Continent     | COUNT(Name) | AVG(Population) | +---------------+-------------+-----------------+ | Asia          |          51 |   72647562.7451 | | Europe        |          46 |   15871186.9565 | | North America |          37 |   13053864.8649 | | Africa        |          58 |   13525431.0345 | | Oceania       |          28 |    1085755.3571 | | Antarctica    |           5 |          0.0000 | | South America |          14 |   24698571.4286 | +---------------+-------------+-----------------+ 7 rows in set (0.00 sec) In this case, X is the number of countries, Y is the average population, and Z is the continent. Of course, you could have more fields in the SELECT clause, and  more fields in the GROUP BY clause as you require. You would also normally alias columns to make the output more suited to your requirements. More Complex Queries  Queries can get considerably more interesting than this. You could also add joins and other expressions to your aggregate query, as in the earlier part of this post. You could have more complex conditions in the WHERE clause. Similarly, you could use queries such as these in subqueries of yet more complex super-queries. Each technique becomes another tool in your toolbox, until before you know it you're writing queries across 15 tables that take two pages to write out. But that's for another day...

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  • Should we choose Java over C# or we should consider using Mono?

    - by A. Karimi
    We are a small team of independent developers with an average experience of 7 years in C#/.NET platform. We almost work on small to average web application projects that allows us to choose our favorite platform. I believe that our current platform (C#/.NET) allows us to be more productive than if we were working in Java but what makes me think about choosing Java over C# is the costs and the community (of the open source). Our projects allow us even work with various frameworks as well as various platforms. For example we can even use Nancy. So we are able to decrease the costs by using Mono which can be deployed on Linux servers. But I'm looking for a complete ecosystem (IDE/Platform/Production Environment) that decreases our costs and makes us feel completely supported by the community. As an example of issues I've experienced with MonoDevelop, I can refer to the poor support of the Razor syntax on MonoDevelop. As another example, We are using "VS 2012 Express for Web" as our IDE to decrease the costs but as you know it doesn't support plugins and I have serious problems with XML comments (I missed GhostDoc). We strongly believe in strongly-typed programming languages so please don't offer the other languages and platforms such as Ruby, PHP, etc. Now I want to choose between: Keep going on C#, buy some products and be hopeful about openness of .NET ecosystem and its open source community. Changing the platform and start using the Java open source ecosystem

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  • Information about how much time in spent in a function, based on the input of this function

    - by olchauvin
    Is there a (quantitative) tool to measure performance of functions based on its input? So far, the tools I used to measure performance of my code, tells me how much time I spent in functions (like Jetbrain Dottrace for .Net), but I'd like to have more information about the parameters passed to the function in order to know which parameters impact the most the performance. Let's say that I have function like that: int myFunction(int myParam1, int myParam 2) { // Do and return something based on the value of myParam1 and myParam2. // The code is likely to use if, for, while, switch, etc.... } If would like a tool that would allow me to tell me how much time is spent in myFunction based on the value of myParam1 and myParam2. For example, the tool would give me a result looking like this: For "myFunction" : value | value | Number of | Average myParam1 | myParam2 | call | time ---------|----------|-----------|-------- 1 | 5 | 500 | 301 ms 2 | 5 | 250 | 1253 ms 3 | 7 | 1268 | 538 ms ... That would mean that myFunction has been call 500 times with myParam1=1 and myParam2=5, and that with those parameters, it took on average 301ms to return a value. The idea behind that is to do some statistical optimization by organizing my code such that, the blocs of codes that are the most likely to be executed are tested before the one that are less likely to be executed. To put it bluntly, if I know which values are used the most, I can reorganize the if/while/for etc.. structure of the function (and the whole program) to optimize it. I'd like to find such tools for C++, Java or.Net. Note: I am not looking for technical tips to optimize the code (like passing parameters as const, inlining functions, initializing the capacity of vectors and the like).

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  • Software vs Network Engineer (Salary, Difficulty, Learning, Happiness)

    - by B Z
    What are your thoughts on being a Software Engineer vs a Network Engineer? I've been on the software field for almost 10 years now and although I still have a great deal of fun (and challenges), I am starting to think it could be better on the "other" side. Not to degrade network engineers (i know there are many great ones out there), it seems (in general) their job is easier, the learning curve from average to good is not as steep, job is less stressful and pay is better on average. I think as software developer I could make the switch to networking and still enjoy working with computers and feel productive. I spend an enormous amount of time learning about software, practices, new technologies, new patters, etc...I think I could spend a much smaller amount of time learning about networking and be just as "good". What are your thoughts? EDIT: This is not about making easy money. Networking and Software are closely related, I love computers and programming, but if I can work with both, make more money and have less stress in my life and can spend more time with my family, then I am willing to consider a change and hence I am looking for advice that Do or Don't support this view.

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  • How to sync client and server at the first frame

    - by wheelinlight
    I'm making a game where an authoritative server sends information to all clients about states and positions for objects in a 3d world. The player can control his character by clicking on the screen to set a destination for the character, much like in the Diablo series. I've read most information I can find online about interpolation, reconciliation, and general networking architecture (Valve's for instance). I think I understand everything but one thing seems to be missing in every article I read. Let say we have an interpolation delay of 100ms, server tickrate=50ms, latency=200ms; How do I know when 100ms has past on the client? If the server sends the first update on t=0, can I assume it arrives at t=200, therefore assuming that all packets takes the same amount of time to reach the client? What if the first packet arrives a little quick, for instance at t=150. I would then be starting the client with t=150 and at t=250 it will think it has past 100ms since its connect to the server when it in fact only 50ms has past. Hopefully the above paragraph is understandable. The summarized question would be: How do I know at what tick to start simulating the client? EDIT: This is how I ended up doing it: The client keeps a clock (approximately) in sync with the server. The client then simulates the world at simulationTime = syncedTime - avg(RTT)/2 - interpolationTime The round-trip time can fluctuate so therefore I average it out over time. By only keeping the most recent values when calculating the average I hope to adapt to more permanent changes in latency. It's still to early to draw any conclusion. I'm currently simulating bad network connections, but it's looking good so far. Anyone see any possible problems?

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  • Randomly and uniquely iterating over a range

    - by Synetech
    Say you have a range of values (or anything else) and you want to iterate over the range and stop at some indeterminate point. Because the stopping value could be anywhere in the range, iterating sequentially is no good because it causes the early values to be accessed more often than later values (which is bad for things that wear out), and also because it reduces performance since it must traverse extra values. Randomly iterating is better because it will (on average) increase the hit-rate so that fewer values have to be accessed before finding the right one, and also distribute the accesses more evenly (again, on average). The problem is that the standard method of randomly jumping around will result in values being accessed multiple times, and has no automatic way of determining when each value has been checked and thus the whole range has been exhausted. One simplified and contrived solution could be to make a list of each value, pick one at random, then remove it. Each time through the loop, you pick one fromt he set of remaining items. Unfortunately this only works for small lists. As a (forced) example, say you are creating a game where the program tries to guess what number you picked and shows how many guess it took. The range is between 0-255 and instead of asking Is it 0? Is it 1? Is it 2?…, you have it guess randomly. You could create a list of 255 numbers, pick randomly and remove it. But what if the range was between 0-232? You can’t really create a 4-billion item list. I’ve seen a couple of implementations RNGs that are supposed to provide a uniform distribution, but none that area also supposed to be unique, i.e., no repeated values. So is there a practical way to randomly, and uniquely iterate over a range?

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  • Dirt compression from vehicle tires

    - by Mungoid
    So I kinda have this working but its not correct because it just averages, so I wanted to know if anyone here has any ideas. I'm trying to simulate loose dirt compression under the tires of a vehicle to reduce the potential bumpiness of 'chunky' terrain. Currently how I do this is that I have a bounding box shape around my tires, set a little lower so they intersect with the terrain. Each frame, I (currently) average all of the heights of each point in the terrain that are within the box bounds of that tire, and then set them all to that average. Clearly this won't work in most cases because, for example, if i'm on a hill, the terrain will deform way too much. One way I thought was to have a max and min amount the points could raise and lower but that still doesn't seem to work properly and sometimes looks more like steps than smooth dirt. I wanna say that there is probably a bit more to this that what i'm currently doing but I am not sure where to look. Could anyone here shed some light on this subject? Would I benefit any by maybe looking up some smoothing algorith or something similar?

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  • At what point does programming become a useful skill?

    - by Elip
    This is probably a very difficult question to answer, because of its subjectivity, but even a vague guess would help me out: Now that Khan Academy is beginning to offer Computer Science lectures I'm getting an itch to learn programming again. I maybe am a bit more technical than your average computer user, using Ubuntu as my OS, LaTeX for writing and I know some small tricks like regular expressions or boolean search for google. However from my previous attempts to learn programming, I realized I do not have a natural aptitude for it and I also don't seem to enjoy the process. But I am fairly certain that a basic proficiency in programming could prove to be very beneficial for me career wise; I also often get ideas for little scripts that I cannot implement. My question is: Let's say you study programming 1 hour / day on average. At what point will you become good enough so that programming can be used for automating tasks and actually saving time? Do you think programming is worth picking up if you never have the ambition to make it your career or even your hobby, but use it strictly for utility purposes?

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  • SQL SERVER – PAGEIOLATCH_DT, PAGEIOLATCH_EX, PAGEIOLATCH_KP, PAGEIOLATCH_SH, PAGEIOLATCH_UP – Wait Type – Day 9 of 28

    - by pinaldave
    It is very easy to say that you replace your hardware as that is not up to the mark. In reality, it is very difficult to implement. It is really hard to convince an infrastructure team to change any hardware because they are not performing at their best. I had a nightmare related to this issue in a deal with an infrastructure team as I suggested that they replace their faulty hardware. This is because they were initially not accepting the fact that it is the fault of their hardware. But it is really easy to say “Trust me, I am correct”, while it is equally important that you put some logical reasoning along with this statement. PAGEIOLATCH_XX is such a kind of those wait stats that we would directly like to blame on the underlying subsystem. Of course, most of the time, it is correct – the underlying subsystem is usually the problem. From Book On-Line: PAGEIOLATCH_DT Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Destroy mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_EX Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Exclusive mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_KP Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Keep mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_SH Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Shared mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_UP Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Update mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_XX Explanation: Simply put, this particular wait type occurs when any of the tasks is waiting for data from the disk to move to the buffer cache. ReducingPAGEIOLATCH_XX wait: Just like any other wait type, this is again a very challenging and interesting subject to resolve. Here are a few things you can experiment on: Improve your IO subsystem speed (read the first paragraph of this article, if you have not read it, I repeat that it is easy to say a step like this than to actually implement or do it). This type of wait stats can also happen due to memory pressure or any other memory issues. Putting aside the issue of a faulty IO subsystem, this wait type warrants proper analysis of the memory counters. If due to any reasons, the memory is not optimal and unable to receive the IO data. This situation can create this kind of wait type. Proper placing of files is very important. We should check file system for the proper placement of files – LDF and MDF on separate drive, TempDB on separate drive, hot spot tables on separate filegroup (and on separate disk), etc. Check the File Statistics and see if there is higher IO Read and IO Write Stall SQL SERVER – Get File Statistics Using fn_virtualfilestats. It is very possible that there are no proper indexes on the system and there are lots of table scans and heap scans. Creating proper index can reduce the IO bandwidth considerably. If SQL Server can use appropriate cover index instead of clustered index, it can significantly reduce lots of CPU, Memory and IO (considering cover index has much lesser columns than cluster table and all other it depends conditions). You can refer to the two articles’ links below previously written by me that talk about how to optimize indexes. Create Missing Indexes Drop Unused Indexes Updating statistics can help the Query Optimizer to render optimal plan, which can only be either directly or indirectly. I have seen that updating statistics with full scan (again, if your database is huge and you cannot do this – never mind!) can provide optimal information to SQL Server optimizer leading to efficient plan. Checking Memory Related Perfmon Counters SQLServer: Memory Manager\Memory Grants Pending (Consistent higher value than 0-2) SQLServer: Memory Manager\Memory Grants Outstanding (Consistent higher value, Benchmark) SQLServer: Buffer Manager\Buffer Hit Cache Ratio (Higher is better, greater than 90% for usually smooth running system) SQLServer: Buffer Manager\Page Life Expectancy (Consistent lower value than 300 seconds) Memory: Available Mbytes (Information only) Memory: Page Faults/sec (Benchmark only) Memory: Pages/sec (Benchmark only) Checking Disk Related Perfmon Counters Average Disk sec/Read (Consistent higher value than 4-8 millisecond is not good) Average Disk sec/Write (Consistent higher value than 4-8 millisecond is not good) Average Disk Read/Write Queue Length (Consistent higher value than benchmark is not good) Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All of the discussions of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • SQL SERVER – LCK_M_XXX – Wait Type – Day 15 of 28

    - by pinaldave
    Locking is a mechanism used by the SQL Server Database Engine to synchronize access by multiple users to the same piece of data, at the same time. In simpler words, it maintains the integrity of data by protecting (or preventing) access to the database object. From Book On-Line: LCK_M_BU Occurs when a task is waiting to acquire a Bulk Update (BU) lock. LCK_M_IS Occurs when a task is waiting to acquire an Intent Shared (IS) lock. LCK_M_IU Occurs when a task is waiting to acquire an Intent Update (IU) lock. LCK_M_IX Occurs when a task is waiting to acquire an Intent Exclusive (IX) lock. LCK_M_S Occurs when a task is waiting to acquire a Shared lock. LCK_M_SCH_M Occurs when a task is waiting to acquire a Schema Modify lock. LCK_M_SCH_S Occurs when a task is waiting to acquire a Schema Share lock. LCK_M_SIU Occurs when a task is waiting to acquire a Shared With Intent Update lock. LCK_M_SIX Occurs when a task is waiting to acquire a Shared With Intent Exclusive lock. LCK_M_U Occurs when a task is waiting to acquire an Update lock. LCK_M_UIX Occurs when a task is waiting to acquire an Update With Intent Exclusive lock. LCK_M_X Occurs when a task is waiting to acquire an Exclusive lock. LCK_M_XXX Explanation: I think the explanation of this wait type is the simplest. When any task is waiting to acquire lock on any resource, this particular wait type occurs. The common reason for the task to be waiting to put lock on the resource is that the resource is already locked and some other operations may be going on within it. This wait also indicates that resources are not available or are occupied at the moment due to some reasons. There is a good chance that the waiting queries start to time out if this wait type is very high. Client application may degrade the performance as well. You can use various methods to find blocking queries: EXEC sp_who2 SQL SERVER – Quickest Way to Identify Blocking Query and Resolution – Dirty Solution DMV – sys.dm_tran_locks DMV – sys.dm_os_waiting_tasks Reducing LCK_M_XXX wait: Check the Explicit Transactions. If transactions are very long, this wait type can start building up because of other waiting transactions. Keep the transactions small. Serialization Isolation can build up this wait type. If that is an acceptable isolation for your business, this wait type may be natural. The default isolation of SQL Server is ‘Read Committed’. One of my clients has changed their isolation to “Read Uncommitted”. I strongly discourage the use of this because this will probably lead to having lots of dirty data in the database. Identify blocking queries mentioned using various methods described above, and then optimize them. Partition can be one of the options to consider because this will allow transactions to execute concurrently on different partitions. If there are runaway queries, use timeout. (Please discuss this solution with your database architect first as timeout can work against you). Check if there is no memory and IO-related issue using the following counters: Checking Memory Related Perfmon Counters SQLServer: Memory Manager\Memory Grants Pending (Consistent higher value than 0-2) SQLServer: Memory Manager\Memory Grants Outstanding (Consistent higher value, Benchmark) SQLServer: Buffer Manager\Buffer Hit Cache Ratio (Higher is better, greater than 90% for usually smooth running system) SQLServer: Buffer Manager\Page Life Expectancy (Consistent lower value than 300 seconds) Memory: Available Mbytes (Information only) Memory: Page Faults/sec (Benchmark only) Memory: Pages/sec (Benchmark only) Checking Disk Related Perfmon Counters Average Disk sec/Read (Consistent higher value than 4-8 millisecond is not good) Average Disk sec/Write (Consistent higher value than 4-8 millisecond is not good) Average Disk Read/Write Queue Length (Consistent higher value than benchmark is not good) Read all the post in the Wait Types and Queue series. Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All the discussion of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • SQL SERVER – SSMS: Backup and Restore Events Report

    - by Pinal Dave
    A DBA wears multiple hats and in fact does more than what an eye can see. One of the core task of a DBA is to take backups. This looks so trivial that most developers shrug this off as the only activity a DBA might be doing. I have huge respect for DBA’s all around the world because even if they seem cool with all the scripting, automation, maintenance works round the clock to keep the business working almost 365 days 24×7, their worth is knowing that one day when the systems / HDD crashes and you have an important delivery to make. So these backup tasks / maintenance jobs that have been done come handy and are no more trivial as they might seem to be as considered by many. So the important question like: “When was the last backup taken?”, “How much time did the last backup take?”, “What type of backup was taken last?” etc are tricky questions and this report lands answers to the same in a jiffy. So the SSMS report, we are talking can be used to find backups and restore operation done for the selected database. Whenever we perform any backup or restore operation, the information is stored in the msdb database. This report can utilize that information and provide information about the size, time taken and also the file location for those operations. Here is how this report can be launched.   Once we launch this report, we can see 4 major sections shown as listed below. Average Time Taken For Backup Operations Successful Backup Operations Backup Operation Errors Successful Restore Operations Let us look at each section next. Average Time Taken For Backup Operations Information shown in “Average Time Taken For Backup Operations” section is taken from a backupset table in the msdb database. Here is the query and the expanded version of that particular section USE msdb; SELECT (ROW_NUMBER() OVER (ORDER BY t1.TYPE))%2 AS l1 ,       1 AS l2 ,       1 AS l3 ,       t1.TYPE AS [type] ,       (AVG(DATEDIFF(ss,backup_start_date, backup_finish_date)))/60.0 AS AverageBackupDuration FROM backupset t1 INNER JOIN sys.databases t3 ON ( t1.database_name = t3.name) WHERE t3.name = N'AdventureWorks2014' GROUP BY t1.TYPE ORDER BY t1.TYPE On my small database the time taken for differential backup was less than a minute, hence the value of zero is displayed. This is an important piece of backup operation which might help you in planning maintenance windows. Successful Backup Operations Here is the expanded version of this section.   This information is derived from various backup tracking tables from msdb database.  Here is the simplified version of the query which can be used separately as well. SELECT * FROM sys.databases t1 INNER JOIN backupset t3 ON (t3.database_name = t1.name) LEFT OUTER JOIN backupmediaset t5 ON ( t3.media_set_id = t5.media_set_id) LEFT OUTER JOIN backupmediafamily t6 ON ( t6.media_set_id = t5.media_set_id) WHERE (t1.name = N'AdventureWorks2014') ORDER BY backup_start_date DESC,t3.backup_set_id,t6.physical_device_name; The report does some calculations to show the data in a more readable format. For example, the backup size is shown in KB, MB or GB. I have expanded first row by clicking on (+) on “Device type” column. That has shown me the path of the physical backup file. Personally looking at this section, the Backup Size, Device Type and Backup Name are critical and are worth a note. As mentioned in the previous section, this section also has the Duration embedded inside it. Backup Operation Errors This section of the report gets data from default trace. You might wonder how. One of the event which is tracked by default trace is “ErrorLog”. This means that whatever message is written to errorlog gets written to default trace file as well. Interestingly, whenever there is a backup failure, an error message is written to ERRORLOG and hence default trace. This section takes advantage of that and shows the information. We can read below message under this section, which confirms above logic. No backup operations errors occurred for (AdventureWorks2014) database in the recent past or default trace is not enabled. Successful Restore Operations This section may not be very useful in production server (do you perform a restore of database?) but might be useful in the development and log shipping secondary environment, where we might be interested to see restore operations for a particular database. Here is the expanded version of the section. To fill this section of the report, I have restored the same backups which were taken to populate earlier sections. Here is the simplified version of the query used to populate this output. USE msdb; SELECT * FROM restorehistory t1 LEFT OUTER JOIN restorefile t2 ON ( t1.restore_history_id = t2.restore_history_id) LEFT OUTER JOIN backupset t3 ON ( t1.backup_set_id = t3.backup_set_id) WHERE t1.destination_database_name = N'AdventureWorks2014' ORDER BY restore_date DESC,  t1.restore_history_id,t2.destination_phys_name Have you ever looked at the backup strategy of your key databases? Are they in sync and do we have scope for improvements? Then this is the report to analyze after a week or month of maintenance plans running in your database. Do chime in with what are the strategies you are using in your environments. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Backup and Restore, SQL Query, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL Tagged: SQL Reports

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  • T-SQL Tuesday #33: Trick Shots: Undocumented, Underdocumented, and Unknown Conspiracies!

    - by Most Valuable Yak (Rob Volk)
    Mike Fal (b | t) is hosting this month's T-SQL Tuesday on Trick Shots.  I love this choice because I've been preoccupied with sneaky/tricky/evil SQL Server stuff for a long time and have been presenting on it for the past year.  Mike's directives were "Show us a cool trick or process you developed…It doesn’t have to be useful", which most of my blogging definitely fits, and "Tell us what you learned from this trick…tell us how it gave you insight in to how SQL Server works", which is definitely a new concept.  I've done a lot of reading and watching on SQL Server Internals and even attended training, but sometimes I need to go explore on my own, using my own tools and techniques.  It's an itch I get every few months, and, well, it sure beats workin'. I've found some people to be intimidated by SQL Server's internals, and I'll admit there are A LOT of internals to keep track of, but there are tons of excellent resources that clearly document most of them, and show how knowing even the basics of internals can dramatically improve your database's performance.  It may seem like rocket science, or even brain surgery, but you don't have to be a genius to understand it. Although being an "evil genius" can help you learn some things they haven't told you about. ;) This blog post isn't a traditional "deep dive" into internals, it's more of an approach to find out how a program works.  It utilizes an extremely handy tool from an even more extremely handy suite of tools, Sysinternals.  I'm not the only one who finds Sysinternals useful for SQL Server: Argenis Fernandez (b | t), Microsoft employee and former T-SQL Tuesday host, has an excellent presentation on how to troubleshoot SQL Server using Sysinternals, and I highly recommend it.  Argenis didn't cover the Strings.exe utility, but I'll be using it to "hack" the SQL Server executable (DLL and EXE) files. Please note that I'm not promoting software piracy or applying these techniques to attack SQL Server via internal knowledge. This is strictly educational and doesn't reveal any proprietary Microsoft information.  And since Argenis works for Microsoft and demonstrated Sysinternals with SQL Server, I'll just let him take the blame for it. :P (The truth is I've used Strings.exe on SQL Server before I ever met Argenis.) Once you download and install Strings.exe you can run it from the command line.  For our purposes we'll want to run this in the Binn folder of your SQL Server instance (I'm referencing SQL Server 2012 RTM): cd "C:\Program Files\Microsoft SQL Server\MSSQL11\MSSQL\Binn" C:\Program Files\Microsoft SQL Server\MSSQL11\MSSQL\Binn> strings *sql*.dll > sqldll.txt C:\Program Files\Microsoft SQL Server\MSSQL11\MSSQL\Binn> strings *sql*.exe > sqlexe.txt   I've limited myself to DLLs and EXEs that have "sql" in their names.  There are quite a few more but I haven't examined them in any detail. (Homework assignment for you!) If you run this yourself you'll get 2 text files, one with all the extracted strings from every SQL DLL file, and the other with the SQL EXE strings.  You can open these in Notepad, but you're better off using Notepad++, EditPad, Emacs, Vim or another more powerful text editor, as these will be several megabytes in size. And when you do open it…you'll find…a TON of gibberish.  (If you think that's bad, just try opening the raw DLL or EXE file in Notepad.  And by the way, don't do this in production, or even on a running instance of SQL Server.)  Even if you don't clean up the file, you can still use your editor's search function to find a keyword like "SELECT" or some other item you expect to be there.  As dumb as this sounds, I sometimes spend my lunch break just scanning the raw text for anything interesting.  I'm boring like that. Sometimes though, having these files available can lead to some incredible learning experiences.  For me the most recent time was after reading Joe Sack's post on non-parallel plan reasons.  He mentions a new SQL Server 2012 execution plan element called NonParallelPlanReason, and demonstrates a query that generates "MaxDOPSetToOne".  Joe (formerly on the Microsoft SQL Server product team, so he knows this stuff) mentioned that this new element was not currently documented and tried a few more examples to see what other reasons could be generated. Since I'd already run Strings.exe on the SQL Server DLLs and EXE files, it was easy to run grep/find/findstr for MaxDOPSetToOne on those extracts.  Once I found which files it belonged to (sqlmin.dll) I opened the text to see if the other reasons were listed.  As you can see in my comment on Joe's blog, there were about 20 additional non-parallel reasons.  And while it's not "documentation" of this underdocumented feature, the names are pretty self-explanatory about what can prevent parallel processing. I especially like the ones about cursors – more ammo! - and am curious about the PDW compilation and Cloud DB replication reasons. One reason completely stumped me: NoParallelHekatonPlan.  What the heck is a hekaton?  Google and Wikipedia were vague, and the top results were not in English.  I found one reference to Greek, stating "hekaton" can be translated as "hundredfold"; with a little more Wikipedia-ing this leads to hecto, the prefix for "one hundred" as a unit of measure.  I'm not sure why Microsoft chose hekaton for such a plan name, but having already learned some Greek I figured I might as well dig some more in the DLL text for hekaton.  Here's what I found: hekaton_slow_param_passing Occurs when a Hekaton procedure call dispatch goes to slow parameter passing code path The reason why Hekaton parameter passing code took the slow code path hekaton_slow_param_pass_reason sp_deploy_hekaton_database sp_undeploy_hekaton_database sp_drop_hekaton_database sp_checkpoint_hekaton_database sp_restore_hekaton_database e:\sql11_main_t\sql\ntdbms\hekaton\sqlhost\sqllang\hkproc.cpp e:\sql11_main_t\sql\ntdbms\hekaton\sqlhost\sqllang\matgen.cpp e:\sql11_main_t\sql\ntdbms\hekaton\sqlhost\sqllang\matquery.cpp e:\sql11_main_t\sql\ntdbms\hekaton\sqlhost\sqllang\sqlmeta.cpp e:\sql11_main_t\sql\ntdbms\hekaton\sqlhost\sqllang\resultset.cpp Interesting!  The first 4 entries (in red) mention parameters and "slow code".  Could this be the foundation of the mythical DBCC RUNFASTER command?  Have I been passing my parameters the slow way all this time? And what about those sp_xxxx_hekaton_database procedures (in blue)? Could THEY be the secret to a faster SQL Server? Could they promise a "hundredfold" improvement in performance?  Are these special, super-undocumented DIB (databases in black)? I decided to look in the SQL Server system views for any objects with hekaton in the name, or references to them, in hopes of discovering some new code that would answer all my questions: SELECT name FROM sys.all_objects WHERE name LIKE '%hekaton%' SELECT name FROM sys.all_objects WHERE object_definition(OBJECT_ID) LIKE '%hekaton%' Which revealed: name ------------------------ (0 row(s) affected) name ------------------------ sp_createstats sp_recompile sp_updatestats (3 row(s) affected)   Hmm.  Well that didn't find much.  Looks like these procedures are seriously undocumented, unknown, perhaps forbidden knowledge. Maybe a part of some unspeakable evil? (No, I'm not paranoid, I just like mysteries and thought that punching this up with that kind of thing might keep you reading.  I know I'd fall asleep without it.) OK, so let's check out those 3 procedures and see what they reveal when I search for "Hekaton": sp_createstats: -- filter out local temp tables, Hekaton tables, and tables for which current user has no permissions -- Note that OBJECTPROPERTY returns NULL on type="IT" tables, thus we only call it on type='U' tables   OK, that's interesting, let's go looking down a little further: ((@table_type<>'U') or (0 = OBJECTPROPERTY(@table_id, 'TableIsInMemory'))) and -- Hekaton table   Wellllll, that tells us a few new things: There's such a thing as Hekaton tables (UPDATE: I'm not the only one to have found them!) They are not standard user tables and probably not in memory UPDATE: I misinterpreted this because I didn't read all the code when I wrote this blog post. The OBJECTPROPERTY function has an undocumented TableIsInMemory option Let's check out sp_recompile: -- (3) Must not be a Hekaton procedure.   And once again go a little further: if (ObjectProperty(@objid, 'IsExecuted') <> 0 AND ObjectProperty(@objid, 'IsInlineFunction') = 0 AND ObjectProperty(@objid, 'IsView') = 0 AND -- Hekaton procedure cannot be recompiled -- Make them go through schema version bumping branch, which will fail ObjectProperty(@objid, 'ExecIsCompiledProc') = 0)   And now we learn that hekaton procedures also exist, they can't be recompiled, there's a "schema version bumping branch" somewhere, and OBJECTPROPERTY has another undocumented option, ExecIsCompiledProc.  (If you experiment with this you'll find this option returns null, I think it only works when called from a system object.) This is neat! Sadly sp_updatestats doesn't reveal anything new, the comments about hekaton are the same as sp_createstats.  But we've ALSO discovered undocumented features for the OBJECTPROPERTY function, which we can now search for: SELECT name, object_definition(OBJECT_ID) FROM sys.all_objects WHERE object_definition(OBJECT_ID) LIKE '%OBJECTPROPERTY(%'   I'll leave that to you as more homework.  I should add that searching the system procedures was recommended long ago by the late, great Ken Henderson, in his Guru's Guide books, as a great way to find undocumented features.  That seems to be really good advice! Now if you're a programmer/hacker, you've probably been drooling over the last 5 entries for hekaton (in green), because these are the names of source code files for SQL Server!  Does this mean we can access the source code for SQL Server?  As The Oracle suggested to Neo, can we return to The Source??? Actually, no. Well, maybe a little bit.  While you won't get the actual source code from the compiled DLL and EXE files, you'll get references to source files, debugging symbols, variables and module names, error messages, and even the startup flags for SQL Server.  And if you search for "DBCC" or "CHECKDB" you'll find a really nice section listing all the DBCC commands, including the undocumented ones.  Granted those are pretty easy to find online, but you may be surprised what those web sites DIDN'T tell you! (And neither will I, go look for yourself!)  And as we saw earlier, you'll also find execution plan elements, query processing rules, and who knows what else.  It's also instructive to see how Microsoft organizes their source directories, how various components (storage engine, query processor, Full Text, AlwaysOn/HADR) are split into smaller modules. There are over 2000 source file references, go do some exploring! So what did we learn?  We can pull strings out of executable files, search them for known items, browse them for unknown items, and use the results to examine internal code to learn even more things about SQL Server.  We've even learned how to use command-line utilities!  We are now 1337 h4X0rz!  (Not really.  I hate that leetspeak crap.) Although, I must confess I might've gone too far with the "conspiracy" part of this post.  I apologize for that, it's just my overactive imagination.  There's really no hidden agenda or conspiracy regarding SQL Server internals.  It's not The Matrix.  It's not like you'd find anything like that in there: Attach Matrix Database DM_MATRIX_COMM_PIPELINES MATRIXXACTPARTICIPANTS dm_matrix_agents   Alright, enough of this paranoid ranting!  Microsoft are not really evil!  It's not like they're The Borg from Star Trek: ALTER FEDERATION DROP ALTER FEDERATION SPLIT DROP FEDERATION   #tsql2sday

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  • Sun Fire X4800 M2 Delivers World Record TPC-C for x86 Systems

    - by Brian
    Oracle's Sun Fire X4800 M2 server equipped with eight 2.4 GHz Intel Xeon Processor E7-8870 chips obtained a result of 5,055,888 tpmC on the TPC-C benchmark. This result is a world record for x86 servers. Oracle demonstrated this world record database performance running Oracle Database 11g Release 2 Enterprise Edition with Partitioning. The Sun Fire X4800 M2 server delivered a new x86 TPC-C world record of 5,055,888 tpmC with a price performance of $0.89/tpmC using Oracle Database 11g Release 2. This configuration is available 06/26/12. The Sun Fire X4800 M2 server delivers 3.0x times better performance than the next 8-processor result, an IBM System p 570 equipped with POWER6 processors. The Sun Fire X4800 M2 server has 3.1x times better price/performance than the 8-processor 4.7GHz POWER6 IBM System p 570. The Sun Fire X4800 M2 server has 1.6x times better performance than the 4-processor IBM x3850 X5 system equipped with Intel Xeon processors. This is the first TPC-C result on any system using eight Intel Xeon Processor E7-8800 Series chips. The Sun Fire X4800 M2 server is the first x86 system to get over 5 million tpmC. The Oracle solution utilized Oracle Linux operating system and Oracle Database 11g Enterprise Edition Release 2 with Partitioning to produce the x86 world record TPC-C benchmark performance. Performance Landscape Select TPC-C results (sorted by tpmC, bigger is better) System p/c/t tpmC Price/tpmC Avail Database MemorySize Sun Fire X4800 M2 8/80/160 5,055,888 0.89 USD 6/26/2012 Oracle 11g R2 4 TB IBM x3850 X5 4/40/80 3,014,684 0.59 USD 7/11/2011 DB2 ESE 9.7 3 TB IBM x3850 X5 4/32/64 2,308,099 0.60 USD 5/20/2011 DB2 ESE 9.7 1.5 TB IBM System p 570 8/16/32 1,616,162 3.54 USD 11/21/2007 DB2 9.0 2 TB p/c/t - processors, cores, threads Avail - availability date Oracle and IBM TPC-C Response times System tpmC Response Time (sec) New Order 90th% Response Time (sec) New Order Average Sun Fire X4800 M2 5,055,888 0.210 0.166 IBM x3850 X5 3,014,684 0.500 0.272 Ratios - Oracle Better 1.6x 1.4x 1.3x Oracle uses average new order response time for comparison between Oracle and IBM. Graphs of Oracle's and IBM's response times for New-Order can be found in the full disclosure reports on TPC's website TPC-C Official Result Page. Configuration Summary and Results Hardware Configuration: Server Sun Fire X4800 M2 server 8 x 2.4 GHz Intel Xeon Processor E7-8870 4 TB memory 8 x 300 GB 10K RPM SAS internal disks 8 x Dual port 8 Gbs FC HBA Data Storage 10 x Sun Fire X4270 M2 servers configured as COMSTAR heads, each with 1 x 3.06 GHz Intel Xeon X5675 processor 8 GB memory 10 x 2 TB 7.2K RPM 3.5" SAS disks 2 x Sun Storage F5100 Flash Array storage (1.92 TB each) 1 x Brocade 5300 switches Redo Storage 2 x Sun Fire X4270 M2 servers configured as COMSTAR heads, each with 1 x 3.06 GHz Intel Xeon X5675 processor 8 GB memory 11 x 2 TB 7.2K RPM 3.5" SAS disks Clients 8 x Sun Fire X4170 M2 servers, each with 2 x 3.06 GHz Intel Xeon X5675 processors 48 GB memory 2 x 300 GB 10K RPM SAS disks Software Configuration: Oracle Linux (Sun Fire 4800 M2) Oracle Solaris 11 Express (COMSTAR for Sun Fire X4270 M2) Oracle Solaris 10 9/10 (Sun Fire X4170 M2) Oracle Database 11g Release 2 Enterprise Edition with Partitioning Oracle iPlanet Web Server 7.0 U5 Tuxedo CFS-R Tier 1 Results: System: Sun Fire X4800 M2 tpmC: 5,055,888 Price/tpmC: 0.89 USD Available: 6/26/2012 Database: Oracle Database 11g Cluster: no New Order Average Response: 0.166 seconds Benchmark Description TPC-C is an OLTP system benchmark. It simulates a complete environment where a population of terminal operators executes transactions against a database. The benchmark is centered around the principal activities (transactions) of an order-entry environment. These transactions include entering and delivering orders, recording payments, checking the status of orders, and monitoring the level of stock at the warehouses. Key Points and Best Practices Oracle Database 11g Release 2 Enterprise Edition with Partitioning scales easily to this high level of performance. COMSTAR (Common Multiprotocol SCSI Target) is the software framework that enables an Oracle Solaris host to serve as a SCSI Target platform. COMSTAR uses a modular approach to break the huge task of handling all the different pieces in a SCSI target subsystem into independent functional modules which are glued together by the SCSI Target Mode Framework (STMF). The modules implementing functionality at SCSI level (disk, tape, medium changer etc.) are not required to know about the underlying transport. And the modules implementing the transport protocol (FC, iSCSI, etc.) are not aware of the SCSI-level functionality of the packets they are transporting. The framework hides the details of allocation providing execution context and cleanup of SCSI commands and associated resources and simplifies the task of writing the SCSI or transport modules. Oracle iPlanet Web Server middleware is used for the client tier of the benchmark. Each web server instance supports more than a quarter-million users while satisfying the response time requirement from the TPC-C benchmark. See Also Oracle Press Release -- Sun Fire X4800 M2 TPC-C Executive Summary tpc.org Complete Sun Fire X4800 M2 TPC-C Full Disclosure Report tpc.org Transaction Processing Performance Council (TPC) Home Page Ideas International Benchmark Page Sun Fire X4800 M2 Server oracle.com OTN Oracle Linux oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Sun Storage F5100 Flash Array oracle.com OTN Disclosure Statement TPC Benchmark C, tpmC, and TPC-C are trademarks of the Transaction Processing Performance Council (TPC). Sun Fire X4800 M2 (8/80/160) with Oracle Database 11g Release 2 Enterprise Edition with Partitioning, 5,055,888 tpmC, $0.89 USD/tpmC, available 6/26/2012. IBM x3850 X5 (4/40/80) with DB2 ESE 9.7, 3,014,684 tpmC, $0.59 USD/tpmC, available 7/11/2011. IBM x3850 X5 (4/32/64) with DB2 ESE 9.7, 2,308,099 tpmC, $0.60 USD/tpmC, available 5/20/2011. IBM System p 570 (8/16/32) with DB2 9.0, 1,616,162 tpmC, $3.54 USD/tpmC, available 11/21/2007. Source: http://www.tpc.org/tpcc, results as of 7/15/2011.

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