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  • SQL SERVER – Size of Index Table for Each Index – Solution 2

    - by pinaldave
    Earlier I had ran puzzle where I asked question regarding size of index table for each index in database over here SQL SERVER – Size of Index Table – A Puzzle to Find Index Size for Each Index on Table. I had received good amount answers and I had blogged about that here SQL SERVER – Size of Index Table for Each Index – Solution. As a comment to that blog I have received another very interesting comment and that provides near accurate answers to original question. Many thanks to Rama Mathanmohan for providing wonderful solution. SELECT OBJECT_NAME(i.OBJECT_ID) AS TableName, i.name AS IndexName, i.index_id AS IndexID, 8 * SUM(a.used_pages) AS 'Indexsize(KB)' FROM sys.indexes AS i JOIN sys.partitions AS p ON p.OBJECT_ID = i.OBJECT_ID AND p.index_id = i.index_id JOIN sys.allocation_units AS a ON a.container_id = p.partition_id GROUP BY i.OBJECT_ID,i.index_id,i.name ORDER BY OBJECT_NAME(i.OBJECT_ID),i.index_id Let me know if you have any better script for the same. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Pinal Dave, Readers Contribution, SQL, SQL Authority, SQL Data Storage, SQL Index, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Microsoft’s 22tracks Music Service now Available in All Browsers

    - by Akemi Iwaya
    Are you tired of listening to the same old music and looking for something new to listen to? Then 22tracks from Microsoft is definitely worth a look! This online music service is available in your favorite browser, does not require an account to use, and lets you listen to music from multiple international sources! If you are curious about 22tracks, then the following excerpt and video sum up the service very nicely. From the blog post: The concept behind 22tracks is simple: 22 local top DJs from cities like Amsterdam, Brussels, London and Paris share their genre’s 22 hottest tracks of the moment. Each city boosts its own team of specialized DJs bringing you the newest tracks in their genre. When you get ready to select (or change to) another set of tracks, just click on the desired city at the top of the browser window, then click on the appropriate set from the drop-down list. 22tracks Homepage 22tracks and Internet Explorer team up to bring you a completely new online music experience [22tracks Blog] 22tracks about [YouTube] [via BetaNews and The Next Web]

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  • Determine arc-length of a Catmull-Rom spline

    - by Wouter
    I have a path that is defined by a concatenation of Catmull-Rom splines. I use the static method Vector2.CatmullRom in XNA that allows for interpolation between points with a value going from 0 to 1. Not every spline in this path has the same length. This causes speed differences if I let the weight go at a constant speed for every spline while proceeding along the path. I can remedy this by letting the speed of the weight be dependent on the length of the spline. How can I determine the length of such a spline? Should I just approximate by cutting the spline into 10 straight lines and sum their lengths? I'm using this for dynamic texture mapping on a generated mesh defined by splines.

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  • Introducing SQLPeople - the Blog Series!

    - by andyleonard
    Introduction The first 50.5 weeks of 2010 have been interesting, to say the least. My experiences in 2010 can best be summed up in a single word: educational. I've learned a lot this year! One important thread wove its way through my 2010 experiences... Relationships Are Everything How we interact defines community. Relationships define community. Our community is more than the sum of our members. Trust and respect are the capital of community. And just like money, this capital can be invested, exchanged,...(read more)

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  • The JRockit Performance Counters

    - by Marcus Hirt
    Every now and then I get a question regarding what the attributes in the PerfCounters dynamic MBean represent. Now, all the MBeans under the oracle.jrockit.management (bea.jrockit.management pre R28) domain are part of what we call JMXMAPI (the JRockit JMX based Management API), which is unsupported. Therefore there is no official documentation for the API. I did however write a bit about JMXMAPI in my recent JRockit book, Oracle JRockit: The Definitive Guide. The information in the table below is from that book: Counter Description java.cls.loadedClasses The number of classes loaded since the start of the JVM. java.cls.unloadedClasses The number of classes unloaded since the start of the JVM. java.property.java.class.path The class path of the JVM. java.property.java.endorsed.dirs The endorsed dirs. See the Endorsed Standards Override Mechanism. java.property.java.ext.dirs The ext dirs, which are searched for jars that should be automatically put on the classpath. See the Java documentation for java.ext.dirs. java.property.java.home The root of the JDK or JRE installation. java.property.java.library.path The library path used to find user libraries. java.property.java.vm.version The JRockit version. java.rt.vmArgs The list of VM arguments. java.threads.daemon The number of running daemon threads. java.threads.live The total number of running threads. java.threads.livePeak The peak number of threads that has been running since JRockit was started. java.threads.nonDaemon The number of non-daemon threads running. java.threads.started The total number of threads started since the start of JRockit. jrockit.gc.latest.heapSize The current heap size in bytes. jrockit.gc.latest.nurserySize The current nursery size in bytes. jrockit.gc.latest.oc.compaction.time How long, in ticks, the last compaction lasted. Reset to 0 if compaction is skipped. jrockit.gc.latest.oc.heapUsedAfter Used heap at the end of the last OC, in bytes. jrockit.gc.latest.oc.heapUsedBefore Used heap at the start of the last OC, in bytes. jrockit.gc.latest.oc.number The number of OCs that have occurred so far. jrockit.gc.latest.oc.sumOfPauses The paused time for the last OC, in ticks. jrockit.gc.latest.oc.time The time the last OC took, in ticks. jrockit.gc.latest.yc.sumOfPauses The paused time for the last YC, in ticks. jrockit.gc.latest.yc.time The time the last YC took, in ticks. jrockit.gc.max.oc.individualPause The longest OC pause so far, in ticks. jrockit.gc.max.yc.individualPause The longest YC pause so far, in ticks. jrockit.gc.total.oc.compaction.externalAborted Number of aborted external compactions so far. jrockit.gc.total.oc.compaction.internalAborted Number of aborted internal compactions so far. jrockit.gc.total.oc.compaction.internalSkipped Number of skipped internal compactions so far. jrockit.gc.total.oc.compaction.time The total time spent doing compaction so far, in ticks. jrockit.gc.total.oc.ompaction.externalSkipped Number of skipped external compactions so far. jrockit.gc.total.oc.pauseTime The sum of all OC pause times so far, in ticks. jrockit.gc.total.oc.time The total time spent doing OC so far, in ticks. jrockit.gc.total.pageFaults The number of page faults that have occurred during GC so far. jrockit.gc.total.yc.pauseTime The sum of all YC pause times, in ticks. jrockit.gc.total.yc.promotedObjects The number of objects that all YCs have promoted. jrockit.gc.total.yc.promotedSize The total number of bytes that all YCs have promoted, in bytes. jrockit.gc.total.yc.time The total time spent doing YC, in ticks. oracle.ci.jit.count The number of methods JIT compiled. oracle.ci.jit.timeTotal The total time spent JIT compiling, in ticks. oracle.ci.opt.count The number of methods optimized. oracle.ci.opt.timeTotal The total time spent optimizing, in ticks. oracle.rt.counterFrequency Used to convert ticks values to seconds. Note that many of these counters are excellent choices for attributes to plot in the Management Console. Also note that many values are in ticks – to convert them to seconds, divide by the value in the oracle.rt.counterFrequency counter.

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  • Understanding G1 GC Logs

    - by poonam
    The purpose of this post is to explain the meaning of GC logs generated with some tracing and diagnostic options for G1 GC. We will take a look at the output generated with PrintGCDetails which is a product flag and provides the most detailed level of information. Along with that, we will also look at the output of two diagnostic flags that get enabled with -XX:+UnlockDiagnosticVMOptions option - G1PrintRegionLivenessInfo that prints the occupancy and the amount of space used by live objects in each region at the end of the marking cycle and G1PrintHeapRegions that provides detailed information on the heap regions being allocated and reclaimed. We will be looking at the logs generated with JDK 1.7.0_04 using these options. Option -XX:+PrintGCDetails Here's a sample log of G1 collection generated with PrintGCDetails. 0.522: [GC pause (young), 0.15877971 secs] [Parallel Time: 157.1 ms] [GC Worker Start (ms): 522.1 522.2 522.2 522.2 Avg: 522.2, Min: 522.1, Max: 522.2, Diff: 0.1] [Ext Root Scanning (ms): 1.6 1.5 1.6 1.9 Avg: 1.7, Min: 1.5, Max: 1.9, Diff: 0.4] [Update RS (ms): 38.7 38.8 50.6 37.3 Avg: 41.3, Min: 37.3, Max: 50.6, Diff: 13.3] [Processed Buffers : 2 2 3 2 Sum: 9, Avg: 2, Min: 2, Max: 3, Diff: 1] [Scan RS (ms): 9.9 9.7 0.0 9.7 Avg: 7.3, Min: 0.0, Max: 9.9, Diff: 9.9] [Object Copy (ms): 106.7 106.8 104.6 107.9 Avg: 106.5, Min: 104.6, Max: 107.9, Diff: 3.3] [Termination (ms): 0.0 0.0 0.0 0.0 Avg: 0.0, Min: 0.0, Max: 0.0, Diff: 0.0] [Termination Attempts : 1 4 4 6 Sum: 15, Avg: 3, Min: 1, Max: 6, Diff: 5] [GC Worker End (ms): 679.1 679.1 679.1 679.1 Avg: 679.1, Min: 679.1, Max: 679.1, Diff: 0.1] [GC Worker (ms): 156.9 157.0 156.9 156.9 Avg: 156.9, Min: 156.9, Max: 157.0, Diff: 0.1] [GC Worker Other (ms): 0.3 0.3 0.3 0.3 Avg: 0.3, Min: 0.3, Max: 0.3, Diff: 0.0] [Clear CT: 0.1 ms] [Other: 1.5 ms] [Choose CSet: 0.0 ms] [Ref Proc: 0.3 ms] [Ref Enq: 0.0 ms] [Free CSet: 0.3 ms] [Eden: 12M(12M)->0B(10M) Survivors: 0B->2048K Heap: 13M(64M)->9739K(64M)] [Times: user=0.59 sys=0.02, real=0.16 secs] This is the typical log of an Evacuation Pause (G1 collection) in which live objects are copied from one set of regions (young OR young+old) to another set. It is a stop-the-world activity and all the application threads are stopped at a safepoint during this time. This pause is made up of several sub-tasks indicated by the indentation in the log entries. Here's is the top most line that gets printed for the Evacuation Pause. 0.522: [GC pause (young), 0.15877971 secs] This is the highest level information telling us that it is an Evacuation Pause that started at 0.522 secs from the start of the process, in which all the regions being evacuated are Young i.e. Eden and Survivor regions. This collection took 0.15877971 secs to finish. Evacuation Pauses can be mixed as well. In which case the set of regions selected include all of the young regions as well as some old regions. 1.730: [GC pause (mixed), 0.32714353 secs] Let's take a look at all the sub-tasks performed in this Evacuation Pause. [Parallel Time: 157.1 ms] Parallel Time is the total elapsed time spent by all the parallel GC worker threads. The following lines correspond to the parallel tasks performed by these worker threads in this total parallel time, which in this case is 157.1 ms. [GC Worker Start (ms): 522.1 522.2 522.2 522.2Avg: 522.2, Min: 522.1, Max: 522.2, Diff: 0.1] The first line tells us the start time of each of the worker thread in milliseconds. The start times are ordered with respect to the worker thread ids – thread 0 started at 522.1ms and thread 1 started at 522.2ms from the start of the process. The second line tells the Avg, Min, Max and Diff of the start times of all of the worker threads. [Ext Root Scanning (ms): 1.6 1.5 1.6 1.9 Avg: 1.7, Min: 1.5, Max: 1.9, Diff: 0.4] This gives us the time spent by each worker thread scanning the roots (globals, registers, thread stacks and VM data structures). Here, thread 0 took 1.6ms to perform the root scanning task and thread 1 took 1.5 ms. The second line clearly shows the Avg, Min, Max and Diff of the times spent by all the worker threads. [Update RS (ms): 38.7 38.8 50.6 37.3 Avg: 41.3, Min: 37.3, Max: 50.6, Diff: 13.3] Update RS gives us the time each thread spent in updating the Remembered Sets. Remembered Sets are the data structures that keep track of the references that point into a heap region. Mutator threads keep changing the object graph and thus the references that point into a particular region. We keep track of these changes in buffers called Update Buffers. The Update RS sub-task processes the update buffers that were not able to be processed concurrently, and updates the corresponding remembered sets of all regions. [Processed Buffers : 2 2 3 2Sum: 9, Avg: 2, Min: 2, Max: 3, Diff: 1] This tells us the number of Update Buffers (mentioned above) processed by each worker thread. [Scan RS (ms): 9.9 9.7 0.0 9.7 Avg: 7.3, Min: 0.0, Max: 9.9, Diff: 9.9] These are the times each worker thread had spent in scanning the Remembered Sets. Remembered Set of a region contains cards that correspond to the references pointing into that region. This phase scans those cards looking for the references pointing into all the regions of the collection set. [Object Copy (ms): 106.7 106.8 104.6 107.9 Avg: 106.5, Min: 104.6, Max: 107.9, Diff: 3.3] These are the times spent by each worker thread copying live objects from the regions in the Collection Set to the other regions. [Termination (ms): 0.0 0.0 0.0 0.0 Avg: 0.0, Min: 0.0, Max: 0.0, Diff: 0.0] Termination time is the time spent by the worker thread offering to terminate. But before terminating, it checks the work queues of other threads and if there are still object references in other work queues, it tries to steal object references, and if it succeeds in stealing a reference, it processes that and offers to terminate again. [Termination Attempts : 1 4 4 6 Sum: 15, Avg: 3, Min: 1, Max: 6, Diff: 5] This gives the number of times each thread has offered to terminate. [GC Worker End (ms): 679.1 679.1 679.1 679.1 Avg: 679.1, Min: 679.1, Max: 679.1, Diff: 0.1] These are the times in milliseconds at which each worker thread stopped. [GC Worker (ms): 156.9 157.0 156.9 156.9 Avg: 156.9, Min: 156.9, Max: 157.0, Diff: 0.1] These are the total lifetimes of each worker thread. [GC Worker Other (ms): 0.3 0.3 0.3 0.3Avg: 0.3, Min: 0.3, Max: 0.3, Diff: 0.0] These are the times that each worker thread spent in performing some other tasks that we have not accounted above for the total Parallel Time. [Clear CT: 0.1 ms] This is the time spent in clearing the Card Table. This task is performed in serial mode. [Other: 1.5 ms] Time spent in the some other tasks listed below. The following sub-tasks (which individually may be parallelized) are performed serially. [Choose CSet: 0.0 ms] Time spent in selecting the regions for the Collection Set. [Ref Proc: 0.3 ms] Total time spent in processing Reference objects. [Ref Enq: 0.0 ms] Time spent in enqueuing references to the ReferenceQueues. [Free CSet: 0.3 ms] Time spent in freeing the collection set data structure. [Eden: 12M(12M)->0B(13M) Survivors: 0B->2048K Heap: 14M(64M)->9739K(64M)] This line gives the details on the heap size changes with the Evacuation Pause. This shows that Eden had the occupancy of 12M and its capacity was also 12M before the collection. After the collection, its occupancy got reduced to 0 since everything is evacuated/promoted from Eden during a collection, and its target size grew to 13M. The new Eden capacity of 13M is not reserved at this point. This value is the target size of the Eden. Regions are added to Eden as the demand is made and when the added regions reach to the target size, we start the next collection. Similarly, Survivors had the occupancy of 0 bytes and it grew to 2048K after the collection. The total heap occupancy and capacity was 14M and 64M receptively before the collection and it became 9739K and 64M after the collection. Apart from the evacuation pauses, G1 also performs concurrent-marking to build the live data information of regions. 1.416: [GC pause (young) (initial-mark), 0.62417980 secs] ….... 2.042: [GC concurrent-root-region-scan-start] 2.067: [GC concurrent-root-region-scan-end, 0.0251507] 2.068: [GC concurrent-mark-start] 3.198: [GC concurrent-mark-reset-for-overflow] 4.053: [GC concurrent-mark-end, 1.9849672 sec] 4.055: [GC remark 4.055: [GC ref-proc, 0.0000254 secs], 0.0030184 secs] [Times: user=0.00 sys=0.00, real=0.00 secs] 4.088: [GC cleanup 117M->106M(138M), 0.0015198 secs] [Times: user=0.00 sys=0.00, real=0.00 secs] 4.090: [GC concurrent-cleanup-start] 4.091: [GC concurrent-cleanup-end, 0.0002721] The first phase of a marking cycle is Initial Marking where all the objects directly reachable from the roots are marked and this phase is piggy-backed on a fully young Evacuation Pause. 2.042: [GC concurrent-root-region-scan-start] This marks the start of a concurrent phase that scans the set of root-regions which are directly reachable from the survivors of the initial marking phase. 2.067: [GC concurrent-root-region-scan-end, 0.0251507] End of the concurrent root region scan phase and it lasted for 0.0251507 seconds. 2.068: [GC concurrent-mark-start] Start of the concurrent marking at 2.068 secs from the start of the process. 3.198: [GC concurrent-mark-reset-for-overflow] This indicates that the global marking stack had became full and there was an overflow of the stack. Concurrent marking detected this overflow and had to reset the data structures to start the marking again. 4.053: [GC concurrent-mark-end, 1.9849672 sec] End of the concurrent marking phase and it lasted for 1.9849672 seconds. 4.055: [GC remark 4.055: [GC ref-proc, 0.0000254 secs], 0.0030184 secs] This corresponds to the remark phase which is a stop-the-world phase. It completes the left over marking work (SATB buffers processing) from the previous phase. In this case, this phase took 0.0030184 secs and out of which 0.0000254 secs were spent on Reference processing. 4.088: [GC cleanup 117M->106M(138M), 0.0015198 secs] Cleanup phase which is again a stop-the-world phase. It goes through the marking information of all the regions, computes the live data information of each region, resets the marking data structures and sorts the regions according to their gc-efficiency. In this example, the total heap size is 138M and after the live data counting it was found that the total live data size dropped down from 117M to 106M. 4.090: [GC concurrent-cleanup-start] This concurrent cleanup phase frees up the regions that were found to be empty (didn't contain any live data) during the previous stop-the-world phase. 4.091: [GC concurrent-cleanup-end, 0.0002721] Concurrent cleanup phase took 0.0002721 secs to free up the empty regions. Option -XX:G1PrintRegionLivenessInfo Now, let's look at the output generated with the flag G1PrintRegionLivenessInfo. This is a diagnostic option and gets enabled with -XX:+UnlockDiagnosticVMOptions. G1PrintRegionLivenessInfo prints the live data information of each region during the Cleanup phase of the concurrent-marking cycle. 26.896: [GC cleanup ### PHASE Post-Marking @ 26.896### HEAP committed: 0x02e00000-0x0fe00000 reserved: 0x02e00000-0x12e00000 region-size: 1048576 Cleanup phase of the concurrent-marking cycle started at 26.896 secs from the start of the process and this live data information is being printed after the marking phase. Committed G1 heap ranges from 0x02e00000 to 0x0fe00000 and the total G1 heap reserved by JVM is from 0x02e00000 to 0x12e00000. Each region in the G1 heap is of size 1048576 bytes. ### type address-range used prev-live next-live gc-eff### (bytes) (bytes) (bytes) (bytes/ms) This is the header of the output that tells us about the type of the region, address-range of the region, used space in the region, live bytes in the region with respect to the previous marking cycle, live bytes in the region with respect to the current marking cycle and the GC efficiency of that region. ### FREE 0x02e00000-0x02f00000 0 0 0 0.0 This is a Free region. ### OLD 0x02f00000-0x03000000 1048576 1038592 1038592 0.0 Old region with address-range from 0x02f00000 to 0x03000000. Total used space in the region is 1048576 bytes, live bytes as per the previous marking cycle are 1038592 and live bytes with respect to the current marking cycle are also 1038592. The GC efficiency has been computed as 0. ### EDEN 0x03400000-0x03500000 20992 20992 20992 0.0 This is an Eden region. ### HUMS 0x0ae00000-0x0af00000 1048576 1048576 1048576 0.0### HUMC 0x0af00000-0x0b000000 1048576 1048576 1048576 0.0### HUMC 0x0b000000-0x0b100000 1048576 1048576 1048576 0.0### HUMC 0x0b100000-0x0b200000 1048576 1048576 1048576 0.0### HUMC 0x0b200000-0x0b300000 1048576 1048576 1048576 0.0### HUMC 0x0b300000-0x0b400000 1048576 1048576 1048576 0.0### HUMC 0x0b400000-0x0b500000 1001480 1001480 1001480 0.0 These are the continuous set of regions called Humongous regions for storing a large object. HUMS (Humongous starts) marks the start of the set of humongous regions and HUMC (Humongous continues) tags the subsequent regions of the humongous regions set. ### SURV 0x09300000-0x09400000 16384 16384 16384 0.0 This is a Survivor region. ### SUMMARY capacity: 208.00 MB used: 150.16 MB / 72.19 % prev-live: 149.78 MB / 72.01 % next-live: 142.82 MB / 68.66 % At the end, a summary is printed listing the capacity, the used space and the change in the liveness after the completion of concurrent marking. In this case, G1 heap capacity is 208MB, total used space is 150.16MB which is 72.19% of the total heap size, live data in the previous marking was 149.78MB which was 72.01% of the total heap size and the live data as per the current marking is 142.82MB which is 68.66% of the total heap size. Option -XX:+G1PrintHeapRegions G1PrintHeapRegions option logs the regions related events when regions are committed, allocated into or are reclaimed. COMMIT/UNCOMMIT events G1HR COMMIT [0x6e900000,0x6ea00000]G1HR COMMIT [0x6ea00000,0x6eb00000] Here, the heap is being initialized or expanded and the region (with bottom: 0x6eb00000 and end: 0x6ec00000) is being freshly committed. COMMIT events are always generated in order i.e. the next COMMIT event will always be for the uncommitted region with the lowest address. G1HR UNCOMMIT [0x72700000,0x72800000]G1HR UNCOMMIT [0x72600000,0x72700000] Opposite to COMMIT. The heap got shrunk at the end of a Full GC and the regions are being uncommitted. Like COMMIT, UNCOMMIT events are also generated in order i.e. the next UNCOMMIT event will always be for the committed region with the highest address. GC Cycle events G1HR #StartGC 7G1HR CSET 0x6e900000G1HR REUSE 0x70500000G1HR ALLOC(Old) 0x6f800000G1HR RETIRE 0x6f800000 0x6f821b20G1HR #EndGC 7 This shows start and end of an Evacuation pause. This event is followed by a GC counter tracking both evacuation pauses and Full GCs. Here, this is the 7th GC since the start of the process. G1HR #StartFullGC 17G1HR UNCOMMIT [0x6ed00000,0x6ee00000]G1HR POST-COMPACTION(Old) 0x6e800000 0x6e854f58G1HR #EndFullGC 17 Shows start and end of a Full GC. This event is also followed by the same GC counter as above. This is the 17th GC since the start of the process. ALLOC events G1HR ALLOC(Eden) 0x6e800000 The region with bottom 0x6e800000 just started being used for allocation. In this case it is an Eden region and allocated into by a mutator thread. G1HR ALLOC(StartsH) 0x6ec00000 0x6ed00000G1HR ALLOC(ContinuesH) 0x6ed00000 0x6e000000 Regions being used for the allocation of Humongous object. The object spans over two regions. G1HR ALLOC(SingleH) 0x6f900000 0x6f9eb010 Single region being used for the allocation of Humongous object. G1HR COMMIT [0x6ee00000,0x6ef00000]G1HR COMMIT [0x6ef00000,0x6f000000]G1HR COMMIT [0x6f000000,0x6f100000]G1HR COMMIT [0x6f100000,0x6f200000]G1HR ALLOC(StartsH) 0x6ee00000 0x6ef00000G1HR ALLOC(ContinuesH) 0x6ef00000 0x6f000000G1HR ALLOC(ContinuesH) 0x6f000000 0x6f100000G1HR ALLOC(ContinuesH) 0x6f100000 0x6f102010 Here, Humongous object allocation request could not be satisfied by the free committed regions that existed in the heap, so the heap needed to be expanded. Thus new regions are committed and then allocated into for the Humongous object. G1HR ALLOC(Old) 0x6f800000 Old region started being used for allocation during GC. G1HR ALLOC(Survivor) 0x6fa00000 Region being used for copying old objects into during a GC. Note that Eden and Humongous ALLOC events are generated outside the GC boundaries and Old and Survivor ALLOC events are generated inside the GC boundaries. Other Events G1HR RETIRE 0x6e800000 0x6e87bd98 Retire and stop using the region having bottom 0x6e800000 and top 0x6e87bd98 for allocation. Note that most regions are full when they are retired and we omit those events to reduce the output volume. A region is retired when another region of the same type is allocated or we reach the start or end of a GC(depending on the region). So for Eden regions: For example: 1. ALLOC(Eden) Foo2. ALLOC(Eden) Bar3. StartGC At point 2, Foo has just been retired and it was full. At point 3, Bar was retired and it was full. If they were not full when they were retired, we will have a RETIRE event: 1. ALLOC(Eden) Foo2. RETIRE Foo top3. ALLOC(Eden) Bar4. StartGC G1HR CSET 0x6e900000 Region (bottom: 0x6e900000) is selected for the Collection Set. The region might have been selected for the collection set earlier (i.e. when it was allocated). However, we generate the CSET events for all regions in the CSet at the start of a GC to make sure there's no confusion about which regions are part of the CSet. G1HR POST-COMPACTION(Old) 0x6e800000 0x6e839858 POST-COMPACTION event is generated for each non-empty region in the heap after a full compaction. A full compaction moves objects around, so we don't know what the resulting shape of the heap is (which regions were written to, which were emptied, etc.). To deal with this, we generate a POST-COMPACTION event for each non-empty region with its type (old/humongous) and the heap boundaries. At this point we should only have Old and Humongous regions, as we have collapsed the young generation, so we should not have eden and survivors. POST-COMPACTION events are generated within the Full GC boundary. G1HR CLEANUP 0x6f400000G1HR CLEANUP 0x6f300000G1HR CLEANUP 0x6f200000 These regions were found empty after remark phase of Concurrent Marking and are reclaimed shortly afterwards. G1HR #StartGC 5G1HR CSET 0x6f400000G1HR CSET 0x6e900000G1HR REUSE 0x6f800000 At the end of a GC we retire the old region we are allocating into. Given that its not full, we will carry on allocating into it during the next GC. This is what REUSE means. In the above case 0x6f800000 should have been the last region with an ALLOC(Old) event during the previous GC and should have been retired before the end of the previous GC. G1HR ALLOC-FORCE(Eden) 0x6f800000 A specialization of ALLOC which indicates that we have reached the max desired number of the particular region type (in this case: Eden), but we decided to allocate one more. Currently it's only used for Eden regions when we extend the young generation because we cannot do a GC as the GC-Locker is active. G1HR EVAC-FAILURE 0x6f800000 During a GC, we have failed to evacuate an object from the given region as the heap is full and there is no space left to copy the object. This event is generated within GC boundaries and exactly once for each region from which we failed to evacuate objects. When Heap Regions are reclaimed ? It is also worth mentioning when the heap regions in the G1 heap are reclaimed. All regions that are in the CSet (the ones that appear in CSET events) are reclaimed at the end of a GC. The exception to that are regions with EVAC-FAILURE events. All regions with CLEANUP events are reclaimed. After a Full GC some regions get reclaimed (the ones from which we moved the objects out). But that is not shown explicitly, instead the non-empty regions that are left in the heap are printed out with the POST-COMPACTION events.

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  • Third-Grade Math Class

    - by andyleonard
    An Odd Thing Happened... ... when I was in third grade math class: I was handed a sheet of arithmetic problems to solve. There were maybe 20 problems on the page and we were given the remainder of the class to complete them. I don't remember how much time remained in the class, I remember I finished working on the problems before my classmates. That wasn't the odd part. The odd part was that I started working on the first problem, concentrating pretty hard. I worked the sum and moved to the next...(read more)

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  • Aggregating cache data from OCEP in CQL

    - by Manju James
    There are several use cases where OCEP applications need to join stream data with external data, such as data available in a Coherence cache. OCEP’s streaming language, CQL, supports simple cache-key based joins of stream data with data in Coherence (more complex queries will be supported in a future release). However, there are instances where you may need to aggregate the data in Coherence based on input data from a stream. This blog describes a sample that does just that. For our sample, we will use a simplified credit card fraud detection use case. The input to this sample application is a stream of credit card transaction data. The input stream contains information like the credit card ID, transaction time and transaction amount. The purpose of this application is to detect suspicious transactions and send out a warning event. For the sake of simplicity, we will assume that all transactions with amounts greater than $1000 are suspicious. The transaction history is available in a Coherence distributed cache. For every suspicious transaction detected, a warning event must be sent with maximum amount, total amount and total number of transactions over the past 30 days, as shown in the diagram below. Application Input Stream input to the EPN contains events of type CCTransactionEvent. This input has to be joined with the cache with all credit card transactions. The cache is configured in the EPN as shown below: <wlevs:caching-system id="CohCacheSystem" provider="coherence"/> <wlevs:cache id="CCTransactionsCache" value-type="CCTransactionEvent" key-properties="cardID, transactionTime" caching-system="CohCacheSystem"> </wlevs:cache> Application Output The output that must be produced by the application is a fraud warning event. This event is configured in the spring file as shown below. Source for cardHistory property can be seen here. <wlevs:event-type type-name="FraudWarningEvent"> <wlevs:properties type="tuple"> <wlevs:property name="cardID" type="CHAR"/> <wlevs:property name="transactionTime" type="BIGINT"/> <wlevs:property name="transactionAmount" type="DOUBLE"/> <wlevs:property name="cardHistory" type="OBJECT"/> </wlevs:properties </wlevs:event-type> Cache Data Aggregation using Java Cartridge In the output warning event, cardHistory property contains data from the cache aggregated over the past 30 days. To get this information, we use a java cartridge method. This method uses Coherence’s query API on credit card transactions cache to get the required information. Therefore, the java cartridge method requires a reference to the cache. This may be set up by configuring it in the spring context file as shown below: <bean class="com.oracle.cep.ccfraud.CCTransactionsAggregator"> <property name="cache" ref="CCTransactionsCache"/> </bean> This is used by the java class to set a static property: public void setCache(Map cache) { s_cache = (NamedCache) cache; } The code snippet below shows how the total of all the transaction amounts in the past 30 days is computed. Rest of the information required by CardHistory object is calculated in a similar manner. Complete source of this class can be found here. To find out more information about using Coherence's API to query a cache, please refer Coherence Developer’s Guide. public static CreditHistoryData(String cardID) { … Filter filter = QueryHelper.createFilter("cardID = :cardID and transactionTime :transactionTime", map); CardHistoryData history = new CardHistoryData(); Double sum = (Double) s_cache.aggregate(filter, new DoubleSum("getTransactionAmount")); history.setTotalAmount(sum); … return history; } The java cartridge method is used from CQL as seen below: select cardID, transactionTime, transactionAmount, CCTransactionsAggregator.execute(cardID) as cardHistory from inputChannel where transactionAmount1000 This produces a warning event, with history data, for every credit card transaction over $1000. That is all there is to it. The complete source for the sample application, along with the configuration files, is available here. In the sample, I use a simple java bean to load the cache with initial transaction history data. An input adapter is used to create and send transaction events for the input stream.

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  • Box2d too much for Circle/Circle collision detection?

    - by Joey Green
    I'm using cocos2d to program a game and am using box2d for collision detection. Everything in my game is a circle and for some reason I'm having a problem with some times things are not being detected as a collision when they should be. I'm thinking of rolling up my own collision detection since I don't think it would be too hard. Questions are: Would this approach work for collision detection between circles? a. get radius of circle A and circle B. b. get distance of the center of circle A and circle B c. if the distance is greater than or equal to the sum of circle A radius and circle B radius then we have a hit Should box2d be used for such simple collision detection? There are no physics in this game.

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  • Rails noob - How to work on data stored in models

    - by Raghav Kanwal
    I'm a beginner to Ruby and Rails, and I have made a couple applications like a Microposts clone and a Todo-List for starters, but I'm starting work on another project. I've got 2 models - user and tracker, you log in via the username which is authenticated and you can log down data which is stored in the tracker table. The tracker has a column named "Calories" and I would like Rails to sum all of the values entered if they are on the same date, and output the result which is subtracted from, say 3000 in a new statement after the display of the model. I know what I'm talking about is just ruby code, im just not sure how to incorporate it. :( Could someone please guide me through this? And also link me to some guides/tutorials which teach working on data from models? Thank you :)

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  • Security of keyctl

    - by ftiaronsem
    Hello alltogether Today I set up an ecryptfs directory, which is automatically mounted at login via pam. To do so i followed the guide in the ecryptfs readme ecryptfs-readme To sum up, I now have a key stored in the usser session keyring. The first thing I do not understand is why this key is only showing up via keyctl show and not with the gnome-gui "Passwords and encryption keys". The second thing I am curious about is the security. I assume that my passphrase is somehow stored on the harddisk. But how exactly and how secure is this? Thanks in advance

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  • Need Help With Finding SEO Company/Individual

    - by three3
    Hi everyone, I am fairly new to SEO and I have done all of the tactics and operations that I know to do to help my site rank to the number 1 spot on Google. I know that no one can guarantee the number 1 spot on Google or on any other search engine but I cannot even seem to get my website to the first page of Google's search results. My company is looking to hire a company or individual to work on our SEO. Does anyone here know of an SEO company or individual that has had good results in the past with getting a website to the front of Google, and preferably to the number 1 spot on Google? We are willing to pay a large sum of money for our keywords to rank on the front of Google search results. Any suggestions are welcome. Thanks John

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  • Need Help With Finding SEO Company/Individual

    - by three3
    I am fairly new to SEO and I have done all of the tactics and operations that I know to do to help my site rank to the number 1 spot on Google. I know that no one can guarantee the number 1 spot on Google or on any other search engine but I cannot even seem to get my website to the first page of Google's search results. My company is looking to hire a company or individual to work on our SEO. Does anyone here know of an SEO company or individual that has had good results in the past with getting a website to the front of Google, and preferably to the number 1 spot on Google? We are willing to pay a large sum of money for our keywords to rank on the front of Google search results. Any suggestions are welcome. Thanks John

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  • Trigger Happy

    - by Tim Dexter
    Its been a while, I know, we’ll say no more OK? I’ll just write …In the latest BIP 11.1.1.6 release and if I’m really honest; the release before this (we'll call it dot 5 for brevity.) The boys and gals in the engine room have been real busy enhancing BIP with some new functionality. Those of you that use the scheduling engine in OBIEE may already know and use the ‘conditional scheduling’ feature. This allows you to be more intelligent about what reports get run and sent to folks on a scheduled basis. You create a ‘trigger’ analysis (answer) that is executed at schedule time prior to the main report. When the schedule rolls around, the trigger is run, if it returns rows, then the main report is run and delivered. If there are no rows returned, then the main report is not run. Useful right? Your users are not bombarded with 20 reports in their inbox every week that they need to wade throu. They get a handful that they know they need to look at. If you ensure you use conditional formatting in the report then they can find the anomalous data in the reports very quickly and move on to the rest of their day more quickly. You could even think of OBIEE as a virtual team member, scouring the data on your behalf 24/7 and letting you know when its found an issue.BI Publisher, wanting the team t-shirt and the khaki pants, has followed suit. You can now set up ‘triggers’ for it to execute before it runs the main report. Just like its big brother, if the scheduled report trigger returns rows of data; it then executes the main report. Otherwise, the report is skipped until the next schedule time rolls around. Sound familiar?BIP differs a little, in that you only need to construct a query to act as the trigger rather than a complete report. Let assume we have a monthly wage by department report on a schedule. We only want to send the report to managers if their departmental wages reach and/or exceed a certain amount. The toughest part about this is coming up with the SQL to test the business rule you want to implement. For my example, its not that tough: select d.department_name, sum(e.salary) as wage_total from employees e, departments d where d.department_id = e.department_id group by d.department_name having sum(e.salary) > 230000 We're looking for departments where the wage cost is greater than 230,000 Dexter Dollars! With a bit of messing I found out you can parametrize the query. Users can then set a value at schedule time if they need to. To create the trigger is straightforward enough. You can create multiple triggers for users to select at schedule time. Notice I also used a parameter in the query, :wamount. Note the matching parameter in the tree on the left. You also dont need to return multiple columns, one is fine, the key is if there are rows returned. You can build the rest of your report as usual. At scheduling time the Schedule tab has a bit more on it. If your users want to set the trigger, they check the Use Trigger box. The page will then pop fields to pick the appropriate trigger they want to use, even a trigger on another data model if needed. Note it will also ask for the parameter value associated with the trigger. At this point you should note that the data model does not make a distinction between trigger and data model (extract) parameters. So users will see the parameters on the General and Schedule tabs. If per chance you do need to just have a trigger parameters. You can just hide them from the report using the Parameters popup in the report designer, just un-check the 'Show' box I have tested the opposite case where you do not want main report parameters seen in the trigger section. BIP handles that for you! Once the report hits its allotted schedule time, the trigger is executed. Based on the results the report will either run or be 'skipped.' Now, you have a smarter scheduler that will only deliver reports when folks need to see them and take action on the contents. More official info here for developers and here for users.

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  • Extreme Optimization – Numerical Algorithm Support

    - by JoshReuben
    Function Delegates Many calculations involve the repeated evaluation of one or more user-supplied functions eg Numerical integration. The EO MathLib provides delegate types for common function signatures and the FunctionFactory class can generate new delegates from existing ones. RealFunction delegate - takes one Double parameter – can encapsulate most of the static methods of the System.Math class, as well as the classes in the Extreme.Mathematics.SpecialFunctions namespace: var sin = new RealFunction(Math.Sin); var result = sin(1); BivariateRealFunction delegate - takes two Double parameters: var atan2 = new BivariateRealFunction (Math.Atan2); var result = atan2(1, 2); TrivariateRealFunction delegate – represents a function takes three Double arguments ParameterizedRealFunction delegate - represents a function taking one Integer and one Double argument that returns a real number. The Pow method implements such a function, but the arguments need order re-arrangement: static double Power(int exponent, double x) { return ElementaryFunctions.Pow(x, exponent); } ... var power = new ParameterizedRealFunction(Power); var result = power(6, 3.2); A ComplexFunction delegate - represents a function that takes an Extreme.Mathematics.DoubleComplex argument and also returns a complex number. MultivariateRealFunction delegate - represents a function that takes an Extreme.Mathematics.LinearAlgebra.Vector argument and returns a real number. MultivariateVectorFunction delegate - represents a function that takes a Vector argument and returns a Vector. FastMultivariateVectorFunction delegate - represents a function that takes an input Vector argument and an output Matrix argument – avoiding object construction  The FunctionFactory class RealFromBivariateRealFunction and RealFromParameterizedRealFunction helper methods - transform BivariateRealFunction or a ParameterizedRealFunction into a RealFunction delegate by fixing one of the arguments, and treating this as a new function of a single argument. var tenthPower = FunctionFactory.RealFromParameterizedRealFunction(power, 10); var result = tenthPower(x); Note: There is no direct way to do this programmatically in C# - in F# you have partial value functions where you supply a subset of the arguments (as a travelling closure) that the function expects. When you omit arguments, F# generates a new function that holds onto/remembers the arguments you passed in and "waits" for the other parameters to be supplied. let sumVals x y = x + y     let sumX = sumVals 10     // Note: no 2nd param supplied.     // sumX is a new function generated from partially applied sumVals.     // ie "sumX is a partial application of sumVals." let sum = sumX 20     // Invokes sumX, passing in expected int (parameter y from original)  val sumVals : int -> int -> int val sumX : (int -> int) val sum : int = 30 RealFunctionsToVectorFunction and RealFunctionsToFastVectorFunction helper methods - combines an array of delegates returning a real number or a vector into vector or matrix functions. The resulting vector function returns a vector whose components are the function values of the delegates in the array. var funcVector = FunctionFactory.RealFunctionsToVectorFunction(     new MultivariateRealFunction(myFunc1),     new MultivariateRealFunction(myFunc2));  The IterativeAlgorithm<T> abstract base class Iterative algorithms are common in numerical computing - a method is executed repeatedly until a certain condition is reached, approximating the result of a calculation with increasing accuracy until a certain threshold is reached. If the desired accuracy is achieved, the algorithm is said to converge. This base class is derived by many classes in the Extreme.Mathematics.EquationSolvers and Extreme.Mathematics.Optimization namespaces, as well as the ManagedIterativeAlgorithm class which contains a driver method that manages the iteration process.  The ConvergenceTest abstract base class This class is used to specify algorithm Termination , convergence and results - calculates an estimate for the error, and signals termination of the algorithm when the error is below a specified tolerance. Termination Criteria - specify the success condition as the difference between some quantity and its actual value is within a certain tolerance – 2 ways: absolute error - difference between the result and the actual value. relative error is the difference between the result and the actual value relative to the size of the result. Tolerance property - specify trade-off between accuracy and execution time. The lower the tolerance, the longer it will take for the algorithm to obtain a result within that tolerance. Most algorithms in the EO NumLib have a default value of MachineConstants.SqrtEpsilon - gives slightly less than 8 digits of accuracy. ConvergenceCriterion property - specify under what condition the algorithm is assumed to converge. Using the ConvergenceCriterion enum: WithinAbsoluteTolerance / WithinRelativeTolerance / WithinAnyTolerance / NumberOfIterations Active property - selectively ignore certain convergence tests Error property - returns the estimated error after a run MaxIterations / MaxEvaluations properties - Other Termination Criteria - If the algorithm cannot achieve the desired accuracy, the algorithm still has to end – according to an absolute boundary. Status property - indicates how the algorithm terminated - the AlgorithmStatus enum values:NoResult / Busy / Converged (ended normally - The desired accuracy has been achieved) / IterationLimitExceeded / EvaluationLimitExceeded / RoundOffError / BadFunction / Divergent / ConvergedToFalseSolution. After the iteration terminates, the Status should be inspected to verify that the algorithm terminated normally. Alternatively, you can set the ThrowExceptionOnFailure to true. Result property - returns the result of the algorithm. This property contains the best available estimate, even if the desired accuracy was not obtained. IterationsNeeded / EvaluationsNeeded properties - returns the number of iterations required to obtain the result, number of function evaluations.  Concrete Types of Convergence Test classes SimpleConvergenceTest class - test if a value is close to zero or very small compared to another value. VectorConvergenceTest class - test convergence of vectors. This class has two additional properties. The Norm property specifies which norm is to be used when calculating the size of the vector - the VectorConvergenceNorm enum values: EuclidianNorm / Maximum / SumOfAbsoluteValues. The ErrorMeasure property specifies how the error is to be measured – VectorConvergenceErrorMeasure enum values: Norm / Componentwise ConvergenceTestCollection class - represent a combination of tests. The Quantifier property is a ConvergenceTestQuantifier enum that specifies how the tests in the collection are to be combined: Any / All  The AlgorithmHelper Class inherits from IterativeAlgorithm<T> and exposes two methods for convergence testing. IsValueWithinTolerance<T> method - determines whether a value is close to another value to within an algorithm's requested tolerance. IsIntervalWithinTolerance<T> method - determines whether an interval is within an algorithm's requested tolerance.

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  • Self Documenting Code Vs. Commented Code

    - by Phill
    I had a search but didn't find what I was looking for, please feel free to link me if this question has already being asked. Earlier this month this post was made: http://net.tutsplus.com/tutorials/php/why-youre-a-bad-php-programmer/ Basically to sum it up, you're a bad programmer if you don't write comments. My personal opinion is that code should be descriptive and mostly not require comment's unless the code cannot be self describing. In the example given // Get the extension off the image filename $pieces = explode('.', $image_name); $extension = array_pop($pieces); The author said this code should be given a comment, my personal opinion is the code should be a function call that is descriptive: $extension = GetFileExtension($image_filename); However in the comments someone actually made just that suggestion: http://net.tutsplus.com/tutorials/php/why-youre-a-bad-php-programmer/comment-page-2/#comment-357130 The author responded by saying the commenter was "one of those people", i.e, a bad programmer. What are everyone elses views on Self Describing Code vs Commenting Code?

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  • Wildcards!

    - by Tim Dexter
    Yes, its been a while, Im sorry, mumble, mumble ... no excuses. Well other than its been, as my son would say 'hecka busy.' On a brighter note I see Kan has been posting some cool stuff in my absence, long may he continue! I received a question today asking about using a wildcard in a template, something like: <?if:INVOICE = 'MLP*'?> where * is the wildcard Well that particular try does not work but you can do it without building your own wildcard function. XSL, the underpinning language of the RTF templates, has some useful string functions - you can find them listed here. I used the starts-with function to achieve a simple wildcard scenario but the contains can be used in conjunction with some of the others to build something more sophisticated. Assume I have a a list of friends and the amounts of money they owe me ... Im very generous and my interest rates a pretty competitive :0) <ROWSET> <ROW> <NAME>Andy</NAME> <AMT>100</AMT> </ROW> <ROW> <NAME>Andrew</NAME> <AMT>60</AMT> </ROW> <ROW> <NAME>Aaron</NAME> <AMT>50</AMT> </ROW> <ROW> <NAME>Alice</NAME> <AMT>40</AMT> </ROW> <ROW> <NAME>Bob</NAME> <AMT>10</AMT> </ROW> <ROW> <NAME>Bill</NAME> <AMT>100</AMT> </ROW> Now, listing my friends is easy enough <for-each:ROW> <NAME> <AMT> <end for-each> but lets say I just want to see all my friends beginning with 'A'. To do that I can use an XPATH expression to filter the data and tack it on to the for-each expression. This is more efficient that using an 'if' statement just inside the for-each. <?for-each:ROW[starts-with(NAME,'A')]?> will find me all the A's. The square braces denote the start of the XPATH expression. starts-with is the function Im calling and Im passing the value I want to check i.e. NAME and the string Im looking for. Just substitute in the characters you are looking for. You can of course use the function in a if statement too. <?if:starts-with(NAME,'A')?><?attribute@incontext:color;'red'?><?end if?> Notice I removed the square braces, this will highlight text red if the name begins with an 'A' You can even use the function to do conditional calculations: <?sum (AMT[starts-with(../NAME,'A')])?> Sum only the amounts where the name begins with an 'A' Notice the square braces are back, its a function we want to apply to the AMT field. Also notice that we need to use ../NAME. The AMT and NAME elements are at the same level in the tree, so when we are at the AMT level we need the ../ to go up a level to then come back down to test the NAME value. I have built out the above functions in a sample template here. Huge prizes for the first person to come up with a 'true' wildcard solution i.e. if NAME like '*im*exter* demand cash now!

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  • Informed TDD &ndash; Kata &ldquo;To Roman Numerals&rdquo;

    - by Ralf Westphal
    Originally posted on: http://geekswithblogs.net/theArchitectsNapkin/archive/2014/05/28/informed-tdd-ndash-kata-ldquoto-roman-numeralsrdquo.aspxIn a comment on my article on what I call Informed TDD (ITDD) reader gustav asked how this approach would apply to the kata “To Roman Numerals”. And whether ITDD wasn´t a violation of TDD´s principle of leaving out “advanced topics like mocks”. I like to respond with this article to his questions. There´s more to say than fits into a commentary. Mocks and TDD I don´t see in how far TDD is avoiding or opposed to mocks. TDD and mocks are orthogonal. TDD is about pocess, mocks are about structure and costs. Maybe by moving forward in tiny red+green+refactor steps less need arises for mocks. But then… if the functionality you need to implement requires “expensive” resource access you can´t avoid using mocks. Because you don´t want to constantly run all your tests against the real resource. True, in ITDD mocks seem to be in almost inflationary use. That´s not what you usually see in TDD demonstrations. However, there´s a reason for that as I tried to explain. I don´t use mocks as proxies for “expensive” resource. Rather they are stand-ins for functionality not yet implemented. They allow me to get a test green on a high level of abstraction. That way I can move forward in a top-down fashion. But if you think of mocks as “advanced” or if you don´t want to use a tool like JustMock, then you don´t need to use mocks. You just need to stand the sight of red tests for a little longer ;-) Let me show you what I mean by that by doing a kata. ITDD for “To Roman Numerals” gustav asked for the kata “To Roman Numerals”. I won´t explain the requirements again. You can find descriptions and TDD demonstrations all over the internet, like this one from Corey Haines. Now here is, how I would do this kata differently. 1. Analyse A demonstration of TDD should never skip the analysis phase. It should be made explicit. The requirements should be formalized and acceptance test cases should be compiled. “Formalization” in this case to me means describing the API of the required functionality. “[D]esign a program to work with Roman numerals” like written in this “requirement document” is not enough to start software development. Coding should only begin, if the interface between the “system under development” and its context is clear. If this interface is not readily recognizable from the requirements, it has to be developed first. Exploration of interface alternatives might be in order. It might be necessary to show several interface mock-ups to the customer – even if that´s you fellow developer. Designing the interface is a task of it´s own. It should not be mixed with implementing the required functionality behind the interface. Unfortunately, though, this happens quite often in TDD demonstrations. TDD is used to explore the API and implement it at the same time. To me that´s a violation of the Single Responsibility Principle (SRP) which not only should hold for software functional units but also for tasks or activities. In the case of this kata the API fortunately is obvious. Just one function is needed: string ToRoman(int arabic). And it lives in a class ArabicRomanConversions. Now what about acceptance test cases? There are hardly any stated in the kata descriptions. Roman numerals are explained, but no specific test cases from the point of view of a customer. So I just “invent” some acceptance test cases by picking roman numerals from a wikipedia article. They are supposed to be just “typical examples” without special meaning. Given the acceptance test cases I then try to develop an understanding of the problem domain. I´ll spare you that. The domain is trivial and is explain in almost all kata descriptions. How roman numerals are built is not difficult to understand. What´s more difficult, though, might be to find an efficient solution to convert into them automatically. 2. Solve The usual TDD demonstration skips a solution finding phase. Like the interface exploration it´s mixed in with the implementation. But I don´t think this is how it should be done. I even think this is not how it really works for the people demonstrating TDD. They´re simplifying their true software development process because they want to show a streamlined TDD process. I doubt this is helping anybody. Before you code you better have a plan what to code. This does not mean you have to do “Big Design Up-Front”. It just means: Have a clear picture of the logical solution in your head before you start to build a physical solution (code). Evidently such a solution can only be as good as your understanding of the problem. If that´s limited your solution will be limited, too. Fortunately, in the case of this kata your understanding does not need to be limited. Thus the logical solution does not need to be limited or preliminary or tentative. That does not mean you need to know every line of code in advance. It just means you know the rough structure of your implementation beforehand. Because it should mirror the process described by the logical or conceptual solution. Here´s my solution approach: The arabic “encoding” of numbers represents them as an ordered set of powers of 10. Each digit is a factor to multiply a power of ten with. The “encoding” 123 is the short form for a set like this: {1*10^2, 2*10^1, 3*10^0}. And the number is the sum of the set members. The roman “encoding” is different. There is no base (like 10 for arabic numbers), there are just digits of different value, and they have to be written in descending order. The “encoding” XVI is short for [10, 5, 1]. And the number is still the sum of the members of this list. The roman “encoding” thus is simpler than the arabic. Each “digit” can be taken at face value. No multiplication with a base required. But what about IV which looks like a contradiction to the above rule? It is not – if you accept roman “digits” not to be limited to be single characters only. Usually I, V, X, L, C, D, M are viewed as “digits”, and IV, IX etc. are viewed as nuisances preventing a simple solution. All looks different, though, once IV, IX etc. are taken as “digits”. Then MCMLIV is just a sum: M+CM+L+IV which is 1000+900+50+4. Whereas before it would have been understood as M-C+M+L-I+V – which is more difficult because here some “digits” get subtracted. Here´s the list of roman “digits” with their values: {1, I}, {4, IV}, {5, V}, {9, IX}, {10, X}, {40, XL}, {50, L}, {90, XC}, {100, C}, {400, CD}, {500, D}, {900, CM}, {1000, M} Since I take IV, IX etc. as “digits” translating an arabic number becomes trivial. I just need to find the values of the roman “digits” making up the number, e.g. 1954 is made up of 1000, 900, 50, and 4. I call those “digits” factors. If I move from the highest factor (M=1000) to the lowest (I=1) then translation is a two phase process: Find all the factors Translate the factors found Compile the roman representation Translation is just a look-up. Finding, though, needs some calculation: Find the highest remaining factor fitting in the value Remember and subtract it from the value Repeat with remaining value and remaining factors Please note: This is just an algorithm. It´s not code, even though it might be close. Being so close to code in my solution approach is due to the triviality of the problem. In more realistic examples the conceptual solution would be on a higher level of abstraction. With this solution in hand I finally can do what TDD advocates: find and prioritize test cases. As I can see from the small process description above, there are two aspects to test: Test the translation Test the compilation Test finding the factors Testing the translation primarily means to check if the map of factors and digits is comprehensive. That´s simple, even though it might be tedious. Testing the compilation is trivial. Testing factor finding, though, is a tad more complicated. I can think of several steps: First check, if an arabic number equal to a factor is processed correctly (e.g. 1000=M). Then check if an arabic number consisting of two consecutive factors (e.g. 1900=[M,CM]) is processed correctly. Then check, if a number consisting of the same factor twice is processed correctly (e.g. 2000=[M,M]). Finally check, if an arabic number consisting of non-consecutive factors (e.g. 1400=[M,CD]) is processed correctly. I feel I can start an implementation now. If something becomes more complicated than expected I can slow down and repeat this process. 3. Implement First I write a test for the acceptance test cases. It´s red because there´s no implementation even of the API. That´s in conformance with “TDD lore”, I´d say: Next I implement the API: The acceptance test now is formally correct, but still red of course. This will not change even now that I zoom in. Because my goal is not to most quickly satisfy these tests, but to implement my solution in a stepwise manner. That I do by “faking” it: I just “assume” three functions to represent the transformation process of my solution: My hypothesis is that those three functions in conjunction produce correct results on the API-level. I just have to implement them correctly. That´s what I´m trying now – one by one. I start with a simple “detail function”: Translate(). And I start with all the test cases in the obvious equivalence partition: As you can see I dare to test a private method. Yes. That´s a white box test. But as you´ll see it won´t make my tests brittle. It serves a purpose right here and now: it lets me focus on getting one aspect of my solution right. Here´s the implementation to satisfy the test: It´s as simple as possible. Right how TDD wants me to do it: KISS. Now for the second equivalence partition: translating multiple factors. (It´a pattern: if you need to do something repeatedly separate the tests for doing it once and doing it multiple times.) In this partition I just need a single test case, I guess. Stepping up from a single translation to multiple translations is no rocket science: Usually I would have implemented the final code right away. Splitting it in two steps is just for “educational purposes” here. How small your implementation steps are is a matter of your programming competency. Some “see” the final code right away before their mental eye – others need to work their way towards it. Having two tests I find more important. Now for the next low hanging fruit: compilation. It´s even simpler than translation. A single test is enough, I guess. And normally I would not even have bothered to write that one, because the implementation is so simple. I don´t need to test .NET framework functionality. But again: if it serves the educational purpose… Finally the most complicated part of the solution: finding the factors. There are several equivalence partitions. But still I decide to write just a single test, since the structure of the test data is the same for all partitions: Again, I´m faking the implementation first: I focus on just the first test case. No looping yet. Faking lets me stay on a high level of abstraction. I can write down the implementation of the solution without bothering myself with details of how to actually accomplish the feat. That´s left for a drill down with a test of the fake function: There are two main equivalence partitions, I guess: either the first factor is appropriate or some next. The implementation seems easy. Both test cases are green. (Of course this only works on the premise that there´s always a matching factor. Which is the case since the smallest factor is 1.) And the first of the equivalence partitions on the higher level also is satisfied: Great, I can move on. Now for more than a single factor: Interestingly not just one test becomes green now, but all of them. Great! You might say, then I must have done not the simplest thing possible. And I would reply: I don´t care. I did the most obvious thing. But I also find this loop very simple. Even simpler than a recursion of which I had thought briefly during the problem solving phase. And by the way: Also the acceptance tests went green: Mission accomplished. At least functionality wise. Now I´ve to tidy up things a bit. TDD calls for refactoring. Not uch refactoring is needed, because I wrote the code in top-down fashion. I faked it until I made it. I endured red tests on higher levels while lower levels weren´t perfected yet. But this way I saved myself from refactoring tediousness. At the end, though, some refactoring is required. But maybe in a different way than you would expect. That´s why I rather call it “cleanup”. First I remove duplication. There are two places where factors are defined: in Translate() and in Find_factors(). So I factor the map out into a class constant. Which leads to a small conversion in Find_factors(): And now for the big cleanup: I remove all tests of private methods. They are scaffolding tests to me. They only have temporary value. They are brittle. Only acceptance tests need to remain. However, I carry over the single “digit” tests from Translate() to the acceptance test. I find them valuable to keep, since the other acceptance tests only exercise a subset of all roman “digits”. This then is my final test class: And this is the final production code: Test coverage as reported by NCrunch is 100%: Reflexion Is this the smallest possible code base for this kata? Sure not. You´ll find more concise solutions on the internet. But LOC are of relatively little concern – as long as I can understand the code quickly. So called “elegant” code, however, often is not easy to understand. The same goes for KISS code – especially if left unrefactored, as it is often the case. That´s why I progressed from requirements to final code the way I did. I first understood and solved the problem on a conceptual level. Then I implemented it top down according to my design. I also could have implemented it bottom-up, since I knew some bottom of the solution. That´s the leaves of the functional decomposition tree. Where things became fuzzy, since the design did not cover any more details as with Find_factors(), I repeated the process in the small, so to speak: fake some top level, endure red high level tests, while first solving a simpler problem. Using scaffolding tests (to be thrown away at the end) brought two advantages: Encapsulation of the implementation details was not compromised. Naturally private methods could stay private. I did not need to make them internal or public just to be able to test them. I was able to write focused tests for small aspects of the solution. No need to test everything through the solution root, the API. The bottom line thus for me is: Informed TDD produces cleaner code in a systematic way. It conforms to core principles of programming: Single Responsibility Principle and/or Separation of Concerns. Distinct roles in development – being a researcher, being an engineer, being a craftsman – are represented as different phases. First find what, what there is. Then devise a solution. Then code the solution, manifest the solution in code. Writing tests first is a good practice. But it should not be taken dogmatic. And above all it should not be overloaded with purposes. And finally: moving from top to bottom through a design produces refactored code right away. Clean code thus almost is inevitable – and not left to a refactoring step at the end which is skipped often for different reasons.   PS: Yes, I have done this kata several times. But that has only an impact on the time needed for phases 1 and 2. I won´t skip them because of that. And there are no shortcuts during implementation because of that.

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  • ING: Scaling Role Management and Access Certification to Thousands of Applications

    - by Tanu Sood
    Organizations deal with employee and user access certifications in different ways.  There’s collation of multiple spreadsheets, an intense two-week exercise by managers or use of access certification tools to do so across a handful of applications. But for most organizations compliance is about certifying user access for thousands of employees across hundreds of systems. Managing and auditing millions of entitlement combinations on a periodic basis poses a huge scale challenge. ING solved the compliance scale challenge using an Identity Platform approach. Join the live webcast featuring ING’s enterprise architect, Mark Robison, as he discusses how a platform approach offers value that is greater than the sum of its parts and enables ING to successfully meet their security and compliance goals. Mark will also share his implementation experiences and discuss the key requirements to manage the complexity and scale of access certification efforts at ING. Mark will be joined by Neil Gandhi, Principal Product Manager for Oracle Identity Analytics. Live WebcastING: Scaling Role Management and Access Certification to Thousands of ApplicationsWednesday, April 11th at 10 am Pacific/ 1 pm EasternRegister Today

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  • For normal mapping, why can we not simply add the tangent normal to the surface normal?

    - by sebf
    I am looking at implementing bump mapping (which in all implementations I have seen is really normal mapping), and so far all I have read says that to do this, we create a matrix to convert from world-space to tangent-space, in order to transform the lights and eye direction vectors into tangent space, so that the vectors from the normal map may be used directly in place of those passed through from the vertex shader. What I do not understand though, is why we cannot just use the normalised sum of the sampled-normal vector, and the surface-normal? (assuming we already transform and pass through the surface normal for the existing lighting functions) Take the diagram below; the normal is simply the deviation from the 'reference normal' for any given coordinate system, correct? And transforming the surface normal of a mapped surface from world space to tangent space makes it equivalent to the tangent space 'reference normal', no? If so, why do we transform all lighting vectors into tangent space, instead of simply transforming the sampled tangent once in the pixel shader?

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  • Software Licenses: No Distribution and Private Selling Using Dual Licenses

    - by user102945
    Hi I recently wrote a couple of WordPress Themes in PHP and was wondering what license i should put on it. I don't mind users reusing my code but i don't want them to be able to sell and redistribute my themes as i want to retain that right. I heard somewhere that an all rights reserved link would stop the distributing etc. Is that true or do i need to include another license and dual license my Themes. So to sum it up i want to use a license to stop others from selling and distributing my themes, while at the same time letting others use the code if they want to.

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  • Multiple volumetric lights

    - by notabene
    I recently read this GPU GEMS 3 article Volumetric Light Scattering as a Post-Process. I like the idea to add volumetric light property to realtime render i'm working on. Question is will it work for multiple lights? Our renderer uses one render pass per light and uses additive blending to sum incoming light. I'm mostly convinced that it have to work nice. Do you agree? Maybe there can be problem where light rays crosses each other.

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  • DBMS agnostic - What to name the COUNT column from a SQL Query

    - by cyberkiwi
    I have trouble naming the COUNT() column from SQL queries and will swap between various variants _Count [Count] (sql, or "count" or backticks for MySQL etc) C Cnt CountSomething (where "something" is the field being counted, or "CountAll") NoOfRows RowCount etc Has anyone come up with any name that you are happy with and always use without hesitation? This is bothering me because after joining SO just recently, my answers have shown this tendency of flip-flopping with no consistency. I need to get this sorted. Please help. (While we're at it, what do you use for SUM etc?) Note: Before you close this question, consider that this one was not: What's the best name for a non-mutating “add” method on an immutable collection?

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  • Project Euler 13: (Iron)Python

    - by Ben Griswold
    In my attempt to learn (Iron)Python out in the open, here’s my solution for Project Euler Problem 13.  As always, any feedback is welcome. # Euler 13 # http://projecteuler.net/index.php?section=problems&id=13 # Work out the first ten digits of the sum of the # following one-hundred 50-digit numbers. import time start = time.time() number_string = '\ 37107287533902102798797998220837590246510135740250\ 46376937677490009712648124896970078050417018260538\ 74324986199524741059474233309513058123726617309629\ 91942213363574161572522430563301811072406154908250\ 23067588207539346171171980310421047513778063246676\ 89261670696623633820136378418383684178734361726757\ 28112879812849979408065481931592621691275889832738\ 44274228917432520321923589422876796487670272189318\ 47451445736001306439091167216856844588711603153276\ 70386486105843025439939619828917593665686757934951\ 62176457141856560629502157223196586755079324193331\ 64906352462741904929101432445813822663347944758178\ 92575867718337217661963751590579239728245598838407\ 58203565325359399008402633568948830189458628227828\ 80181199384826282014278194139940567587151170094390\ 35398664372827112653829987240784473053190104293586\ 86515506006295864861532075273371959191420517255829\ 71693888707715466499115593487603532921714970056938\ 54370070576826684624621495650076471787294438377604\ 53282654108756828443191190634694037855217779295145\ 36123272525000296071075082563815656710885258350721\ 45876576172410976447339110607218265236877223636045\ 17423706905851860660448207621209813287860733969412\ 81142660418086830619328460811191061556940512689692\ 51934325451728388641918047049293215058642563049483\ 62467221648435076201727918039944693004732956340691\ 15732444386908125794514089057706229429197107928209\ 55037687525678773091862540744969844508330393682126\ 18336384825330154686196124348767681297534375946515\ 80386287592878490201521685554828717201219257766954\ 78182833757993103614740356856449095527097864797581\ 16726320100436897842553539920931837441497806860984\ 48403098129077791799088218795327364475675590848030\ 87086987551392711854517078544161852424320693150332\ 59959406895756536782107074926966537676326235447210\ 69793950679652694742597709739166693763042633987085\ 41052684708299085211399427365734116182760315001271\ 65378607361501080857009149939512557028198746004375\ 35829035317434717326932123578154982629742552737307\ 94953759765105305946966067683156574377167401875275\ 88902802571733229619176668713819931811048770190271\ 25267680276078003013678680992525463401061632866526\ 36270218540497705585629946580636237993140746255962\ 24074486908231174977792365466257246923322810917141\ 91430288197103288597806669760892938638285025333403\ 34413065578016127815921815005561868836468420090470\ 23053081172816430487623791969842487255036638784583\ 11487696932154902810424020138335124462181441773470\ 63783299490636259666498587618221225225512486764533\ 67720186971698544312419572409913959008952310058822\ 95548255300263520781532296796249481641953868218774\ 76085327132285723110424803456124867697064507995236\ 37774242535411291684276865538926205024910326572967\ 23701913275725675285653248258265463092207058596522\ 29798860272258331913126375147341994889534765745501\ 18495701454879288984856827726077713721403798879715\ 38298203783031473527721580348144513491373226651381\ 34829543829199918180278916522431027392251122869539\ 40957953066405232632538044100059654939159879593635\ 29746152185502371307642255121183693803580388584903\ 41698116222072977186158236678424689157993532961922\ 62467957194401269043877107275048102390895523597457\ 23189706772547915061505504953922979530901129967519\ 86188088225875314529584099251203829009407770775672\ 11306739708304724483816533873502340845647058077308\ 82959174767140363198008187129011875491310547126581\ 97623331044818386269515456334926366572897563400500\ 42846280183517070527831839425882145521227251250327\ 55121603546981200581762165212827652751691296897789\ 32238195734329339946437501907836945765883352399886\ 75506164965184775180738168837861091527357929701337\ 62177842752192623401942399639168044983993173312731\ 32924185707147349566916674687634660915035914677504\ 99518671430235219628894890102423325116913619626622\ 73267460800591547471830798392868535206946944540724\ 76841822524674417161514036427982273348055556214818\ 97142617910342598647204516893989422179826088076852\ 87783646182799346313767754307809363333018982642090\ 10848802521674670883215120185883543223812876952786\ 71329612474782464538636993009049310363619763878039\ 62184073572399794223406235393808339651327408011116\ 66627891981488087797941876876144230030984490851411\ 60661826293682836764744779239180335110989069790714\ 85786944089552990653640447425576083659976645795096\ 66024396409905389607120198219976047599490197230297\ 64913982680032973156037120041377903785566085089252\ 16730939319872750275468906903707539413042652315011\ 94809377245048795150954100921645863754710598436791\ 78639167021187492431995700641917969777599028300699\ 15368713711936614952811305876380278410754449733078\ 40789923115535562561142322423255033685442488917353\ 44889911501440648020369068063960672322193204149535\ 41503128880339536053299340368006977710650566631954\ 81234880673210146739058568557934581403627822703280\ 82616570773948327592232845941706525094512325230608\ 22918802058777319719839450180888072429661980811197\ 77158542502016545090413245809786882778948721859617\ 72107838435069186155435662884062257473692284509516\ 20849603980134001723930671666823555245252804609722\ 53503534226472524250874054075591789781264330331690' total = 0 for i in xrange(0, 100 * 50 - 1, 50): total += int(number_string[i:i+49]) print str(total)[:10] print "Elapsed Time:", (time.time() - start) * 1000, "millisecs" a=raw_input('Press return to continue')

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  • Write a program consisting of a main module and three other modules

    - by user106080
    The owner of a super supermarket would like to have a program that computes the monthly gross pay of their employees as well as the employees’s net pay. The input for this program is the employee id number, hourly rate of pay, and number of regular and overtime hours hours worked. Gross pay is the sum of the wages earnes from regular hours; overtime is 1.5 times the regular rate. Net pay is gross pay hours; overtime is paid at 1.5 times the regular rate. Net pay is the gross pay minus deductions. Assume that deduction are taken for tax withholding (50 percent of gross pay) and parking ($10.00 per month) you will need the following variables: EmployeeID (a string) HourRate is (a float) RegHours (a float) ; GrossPay (a float);Tax (afloat) Parking (a float) OverTimeHours (a float) NetPay (a float) GrossPay = Regularhours* HourRate+OverTimeHours*(HourRate*1.5) NetPay= GrossPay – (GrossPay*Tax) – Parking

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