Search Results

Search found 1544 results on 62 pages for 'heap corruption'.

Page 8/62 | < Previous Page | 4 5 6 7 8 9 10 11 12 13 14 15  | Next Page >

  • How are Implicit-Heap dynamic Storage Binding and Dynamic type binding similar?

    - by Appy
    "Concepts of Programming languages" by Robert Sebesta says - Implicit Heap-Dynamic Storage Binding: Implicit Heap-Dynamic variables are bound to heap storage only when they are assigned values. It is similar to dynamic type binding. Can anyone explain the similarity with suitable examples. I understand the meaning of both the phrases, but I am an amateur when it comes to in-depth details.

    Read the article

  • Running out of memory while analyzing a Java Heap Dump

    - by Abel Morelos
    Hi, I have a curious problem, I need to analyze a Java heap dump (from an IBM JRE) which has 1.5GB in size, the problem is that while analyzing the dump (I've tried HeapAnalyzer and the IBM Memory Analyzer 0.5) the tools runs out of memory I can't really analyze the dump. I have 3GB of RAM in my machine, but seems like it's not enough to analyze the 1.5 GB dump, My question is, do you know a specific tool for heap dump analysis (supporting IBM JRE dumps) that I could run with the amount of memory I have? Thanks.

    Read the article

  • Why might the Large Object Heap grow rather than throw an exception?

    - by Unsliced
    In a previous question I asked possible programatic ways of maximising the largest block allocatable on the LOH. I'm still seeing the problems, but now I'm trying to get my head around why the LOH seems to grow and shrink in size, yet I'm still seeing OutOfMemoryExceptions that tally with what others have reported as being due to LOH fragmentation. Why might one call to, for example, StringBuilder.EnsureCapacity throw an OutOfMemoryException for me, but another call from somewhere else result in the LOH expanding in size (according to the performance counters, it is growing and shrinking)?

    Read the article

  • read-only memory and heap memory

    - by benjamin button
    hi, AFAIK, string literals are stored in read only memory in case of C language. where is this actually present on the hardware. as per my knowledge heap is on RAM.correct me if i am wrong. how different is heap from read only memory? is it OS dependant?

    Read the article

  • Visual Studio - how to find source of heap corruption errors

    - by Danne
    Hi, I wonder if there is a good way to find the source code that causes a heap corruption error, given the memory address of the of the data that was written 'outside' the allocated heap block in Visual Studio; Dedicated (0008) free list element 26F7F670 is wrong size (dead) (Trying to write down some notes on how to find memory errors) Thanks in advance!

    Read the article

  • Java JRE: Setting default heap size

    - by AndiDog
    I'm having trouble with Java on a virtual server, it always gives me the following error: # java Error occurred during initialization of VM Could not reserve enough space for object heap Could not create the Java virtual machine. I first solved this by using the CACAO virtual machine (of OpenJDK, by putting it first in jvm.cfg), but then I run into problems with my web application (Play! framework based, gives me nasty LinkageErrors). So I cannot use that VM. Instead I'd like to just use the normal server VM and set -Xmx128M by default. How can I do that? Related: this question

    Read the article

  • Is stack address shared by Heap addresses ??

    - by numerical25
    I read On most operating systems, the addresses in memory starts from highest to lowest. So I am wondering if the heap, stack, and global memory all fall under the same ordering..? If I created... pointerType* pointer = new pointerType //creates memory address 0xffffff And then created a local varible on the stack localObject object would localObjects address be 0xfffffe Or is heap and stack ordering completely different.

    Read the article

  • Private heap or manage memory self

    - by Max
    Hello all, I know we could take some advantages from creating private heap of Windows especially for frequently allocated and de-allocated small chunks. But I think the normal approach is to allocate a large memory from default heap and manage the allocations and de-allocations ourselves. My question is which way is advantages and disadvantage between those two ways? Thanks, Max

    Read the article

  • Is an Object the smallest pageable unit in the Heap?

    - by DonnieKun
    Hi, If I have a 2 GB ram and I have an 2 instances of an Object which is 1.5 GB each, the operating system will help and context switch the pages to and from harddisk. What if I have 1 instances but is 3 GB. Can the same paging method breakdown this instances into 2 pages? Or will I encounter out-of-memory issue? Thanks.

    Read the article

  • Network corruption - corrupt downloads, corrupt streams, etc.

    - by rfrankel
    I've been having some problems with my home LAN. Downloaded executables won't run, my remote desktop sessions keep getting interrupted due to encryption errors, flash video streams show visible corruption (both Hulu and YouTube), and I've had a couple downloads for which the md5 hashes don't match. The problem has even occurred with a couple images embedded in webpages, though that's rare enough (presumably because images are relatively smaller files). I've had this problem across two Windows machines and a Mac, so it's neither machine-specific nor at the app or OS level. Comcast claims it's nothing to do with them, and my Linksys/Cisco RV016 router is out of warranty, so I have no access to official support. When I log into my router, it shows no error packets or dropped packets received. I plugged a laptop directly into the router and was able to download a 5.5 MB file and verify its MD5 hash, which is not proof that the problem is downstream of the router, but makes it seem quite likely, since I failed to download the same file several times from two desktops (one Mac, one Windows). Could this be a wiring problem? If so, is there any way clever/elegant to determine which wiring is faulty with just software? If I can avoid tracing all the wires throughout my entire house it would make my life quite a bit easier.

    Read the article

  • KeePass lost password and/or corruption due to Dropbox/KeePassX

    - by GummiV
    I started using Keepass about a month ago to hold my passwords and online accounts info. Everything was stored in a single .kdb file, only protected with a password. I'm using Windows 7. Now Keepass can't open my .kdb file with the error "Invalid/wrong key". I'm fairly confident I have the right password. Altough I might have mixed up a few letters I've tried about two dozen different combinations to minimize that possibility - but can't rule it out though. My guess is however that the .kdb file got corrupted, either due to Dropbox syncing (only using it on one computer though) or because I edited the file using KeePassX on Ubuntu (dual boot on the same computer, accessing a mounted Win7 NTFS partition), or possibly a combination of both. I have tried restoring older versions(even the original one) from Dropbox and trying out all possible passwords without any luck. (which does seem to rule out KeePassX as the culprit, since oldest copies are before I edited the file from Ubuntu) I have tried opening the file with the "Repair KeePass Database file" which always gives the "0xA Invalid/corrupt file structure" (the same error for when a wrong password is typed). I was wondering if there was any way for me to salvage my hard-gathered data. I know generally that brute force cracking is not feasible, but since I can remember probably more than half of the usernames/passwords, any maybe the fact that one of them does come up fairly often (my go-to pass for trivial stuff), that might simplify the brute force process to a doable time frame. Maybe the brute-force thing might incorporate the fact that I know the password length and what characters it's made from. (If we assume corruption, not a password-blackout on my part) I could do some programming if there are any libraries or routines that I could use. Other people seem to have had a similar probem http://forums.dropbox.com/topic.php?id=6199 http://forums.dropbox.com/topic.php?id=9139 http://www.keepassx.org/forum/viewtopic.php?t=1967&f=1 So hopefully this question will become a suitible resource for people when searching the web. Feel free to tell me if you think this should rather be a community wiki.

    Read the article

  • java max heap size, how much is too much

    - by brad
    I'm having issues with a JRuby (rails) app running in tomcat. Occasionally page requests can take up to a minute to return (even though the rails logs processed the request in seconds so it's obviously a tomcat issue). I'm wondering what settings are optimal for the java heap size. I know there's no definitive answer, but I thought maybe someone could comment on my setup. I'm on a small EC2 instance which has 1.7g ram. I have the following JAVA_OPTS: -Xmx1536m -Xms256m -XX:MaxPermSize=256m -XX:+CMSClassUnloadingEnabled My first thought is that Xmx is too high. If I only have 1.7gb and I allocated 1.5gb to java, i feel like I'll get a lot of paging. Typically my java process shows (in top) 1.1g res memory and 2g virtual. I also read somewhere that setting the Xms and Xmx to the same size will help as it eliminates time spend on memory allocation. I'm not a java person but I've been tasked with figuring out this problem and I'm trying to find out where to start. Any tips are greatly appreciated!! update I've started analyzing the garbage collection dumps using -XX:+PrintGCDetails When i notice these occasional long load times, the gc logs go nuts. the last one I did (which took 25s to complete) I had gc log lines such as: 1720.267: [GC 1720.267: [DefNew: 27712K->16K(31104K), 0.0068020 secs] 281792K->254096K(444112K), 0.0069440 secs] 1720.294: [GC 1720.294: [DefNew: 27728K->0K(31104K), 0.0343340 secs] 281808K->254080K(444112K), 0.0344910 secs] about 300 of them on a single request!!! Now, I don't totally understand why it's always GC'ng from ~28m down to 0 over and over.

    Read the article

  • Method for finding memory leak in large Java heap dumps

    - by Rickard von Essen
    I have to find a memory leak in a Java application. I have some experience with this but would like advice on a methodology/strategy for this. Any reference and advice is welcome. About our situation: Heap dumps are larger than 1 GB We have heap dumps from 5 occasions. We don't have any test case to provoke this. It only happens in the (massive) system test environment after at least a weeks usage. The system is built on a internally developed legacy framework with so many design flaws that they are impossible to count them all. Nobody understands the framework in depth. It has been transfered to one guy in India who barely keeps up with answering e-mails. We have done snapshot heap dumps over time and concluded that there is not a single component increasing over time. It is everything that grows slowly. The above points us in the direction that it is the frameworks homegrown ORM system that increases its usage without limits. (This system maps objects to files?! So not really a ORM) Question: What is the methodology that helped you succeed with hunting down leaks in a enterprise scale application?

    Read the article

  • ??????????? - Java SE Embedded 8

    - by kshimizu-Oracle
    Java?OS??????1?????????????????????????????????3?????????????? HEAP: Java????????????????????????????????? NON-HEAP: NON-HEAP????JVM???????????????????Code Cache?Metaspace???2????????????? Code Cache: ????JIT??????????????????????????? Metaspace: HEAP??????????????????????????   JavaVM??????????: VM?????????????????? ??????????????? ????????????????????????????????????????????????????????????????????????? HEAP?Java Mission Control???????????????????? (????)? ????Java SE?????????????API????????????????????????????????????? Mission Control?????API?????????????????????????????????API??????????????? HEAP???????????? VM????????"-Xmx"???????????????? java.lang.Runtime.maxMemory(); ?????HEAP????????? ?????VM????????"-Xms"? ????????????? "-Xms"???????"-Xmx"?????????? java.lang.Runtime.totalMemory(); ???????????HEAP????????????? java.lang.Runtime.freeMemory(); ??NON-HEAP???????????? API??????????? Java Mission Control?????????? ????????????Java Mission Control??????????????????????? ????"NON_HEAP"?????????NON-HEAP?????? ???? HEAP????NON-HEAP?????????????? Java VM???????????????????????????????????????? ?????????????????????????????????? ????HEAP/NON-HEAP?????????????????????????? OS?????????????? Linux???????procfs?Java??????????????????? (VmHWM or VmRSS) ????? ????HEAP/NON-HEAP??????????????????????????? ?????????????????? ??????JVM?????????????????? ?????????????????JVM???????????????????? ???JVM?????? ????????????? Embedded??JVM?????????? ??Embedded???Oracle JVM??????CPU????????????????????????????????????????? ??????CPU??????????????????????????????????????? Minimal/Client/Server??JVM???????????????? ????JVM??????????????????? ??????Compact????????????????? ? 2 - 3?????? Concept Guide (http://docs.oracle.com/javase/8/embedded/embedded-concepts/basic-concepts.htm) ???????? ??JVM??????????? ????????????????????? -Xms: ??????????? ?????????? ?????????????????????????????????????????????????? -Xmx: ??????????? -XX:ReservedCodeCacheSize: Code Cache??????? ?) JIT??????????????Code Cache????????????0???????? -Xint: JIT??????????? ????????????? JIT?????????????????????? ????????????????? -Xss: ???????????????????? ????????????????????????? ????????????????????????????? -XX:CompileThreshold: JIT?????????????????????????????????? ?????????????????????? ????????? ?????????????????? Code Cache?????????? ?????????? ????????????????????? ????????????????????????? ??????????????????????? ?????????????????????

    Read the article

  • 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.

    Read the article

  • Construct an array from an existing array

    - by Luv
    Given an array of integers A[1...n-1] where 'N' is the length of array A[ ]. Construct an array B such that B[i] = min(A[i], A[i+1], ..., A[i+K-1]), where K will be given. Array B will have N-K+1 elements. We can solve the problem using min-heaps Construct min-heap for k elements - O(k) For every next element delete the first element and insert the new element and heapify Hence Worst Case Time - O( (n-k+1)*k ) + O(k) Space - O(k) Can we do it better?

    Read the article

  • Payables Master Generic Datafix (MGD) Now Checks For Even More EBTax Corruption!!

    - by MargaretW
    The Payables MGD is a vital diagnostic that all R12/12.1 customers need to run regularly to check the data integrity of their Payables system. This script does not make any changes to your system, so it’s risk free and it produces a HTML formatted output showing which data corruption issues have been detected and provides the Doc ID’s that will be needed to fix them. This MGD diagnostic (version 120.92 and above) is even better than it used to be as it now checks for 11 new EBTax corruption signatures that Support was seeing on a consistent basis. These lengthy Service Requests could have been avoided with one run of the MGD which tells you right away if you have data corruption. It’s the first thing our Payables support engineers will have you run when you log an SR so why not be one step ahead? The new EBTax signatures that were included in this latest update to the MGD are pulled from the following common solutions documents: R12 E-Business Tax/Payables Data-Fixes: Cause and action to handle ZX_LINES_SUMMARY_U1 issue Doc ID 1152123.1 EB-Tax Data Corruption Issues & Recommended Solutions Doc ID 1316316.1 The specific issues that are now screened are detailed below: 1. TAXABLE_BASIS_FORMULA and MANUALLY_ENTERED_FLAG mismatch 2. ESTABLISHMENT_ID mismatch 3. TRX_NUMBER mismatch 4. TAX_RATE mismatch 5. Currency Conversion related columns mismatch in Migrated Invoices 6. HISTORICAL_FLAG and RECORD_TYPE_CODE mismatch 7. ADJUSTED_DOC_TRX_LEVEL_TYPE is NULL or APPLIED_FROM_TRX_LEVEL_TYPE is NULL 8. Missing Reversal Tax Distributions For Tax Distributions 9. Tax Lines for discarded or cancelled Transaction Lines are not marked as cancelled 10. Error AP_ERR_TAX_DIST_SYNC 11. AP_UNFROZEN_DIST_EXIST/Unfrozen Tax Distributions exist for this invoice Get Proactive – Check your system for these common EBTax issues and fix the data before it causes a problem. Access the MGD note and watch the video that explains how it works here - R12: Master GDF Diagnostic to Validate Data Related to Invoices, Payments, Accounting, Suppliers and EBTax [VIDEO] Doc ID 1360390.1

    Read the article

  • Getting java.lang.OutOfMemoryError: Java heap space

    - by user1371176
    I am getting an Exception in thread "HSQLDB Connection @3c50507" java.lang.OutOfMemoryError: Java heap space, when running a JSP. what is the thing that is out of memory? eclipse, HSQLDB or Tomcat?? i am using all that in a Mac OS X 10.7.4 When i start HSQLDB, then i get by console this exception: [Server@122ce908]: From command line, use [Ctrl]+[C] to abort abruptly Exception in thread "HSQLDB Connection @2e716cb7" java.lang.OutOfMemoryError: Java heap space at org.hsqldb.lib.HsqlByteArrayOutputStream.ensureRoom(Unknown Source) at org.hsqldb.rowio.RowOutputBinary.ensureRoom(Unknown Source) at org.hsqldb.lib.HsqlByteArrayOutputStream.write(Unknown Source) at org.hsqldb.rowio.RowOutputBinary.writeByteArray(Unknown Source) at org.hsqldb.rowio.RowOutputBinary.writeBinary(Unknown Source) at org.hsqldb.rowio.RowOutputBase.writeData(Unknown Source) at org.hsqldb.Result.write(Unknown Source) at org.hsqldb.Result.write(Unknown Source) at org.hsqldb.ServerConnection.run(Unknown Source) at java.lang.Thread.run(Thread.java:680) What does this all mean?

    Read the article

  • Pointer-based binary heap implementation

    - by Derek Chiang
    Is it even possible to implement a binary heap using pointers rather than an array? I have searched around the internet (including SO) and no answer can be found. The main problem here is that, how do you keep track of the last pointer? When you insert X into the heap, you place X at the last pointer and then bubble it up. Now, where does the last pointer point to? And also, what happens when you want to remove the root? You exchange the root with the last element, and then bubble the new root down. Now, how do you know what's the new "last element" that you need when you remove root again?

    Read the article

  • Allocation Target of std::aligned_storage (stack or heap?)

    - by Zenikoder
    I've been trying to get my head around the TR1 addition known as aligned_storage. Whilst reading the following documents N2165, N3190 and N2140 I can't for the life of me see a statement where it clearly describes stack or heap nature of the memory being used. I've had a look at the implementation provided by msvc2010, boost and gcc they all provide a stack based solution centered around the use of a union. In short: Is the memory type (stack or heap) used by aligned_storage implementation defined or is it always meant to be stack based? and, What the is the specific document that defines/determines that?

    Read the article

< Previous Page | 4 5 6 7 8 9 10 11 12 13 14 15  | Next Page >