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  • ODI 11g – How to override SQL at runtime?

    - by David Allan
    Following on from the posting some time back entitled ‘ODI 11g – Simple, Powerful, Flexible’ here we push the envelope even further. Rather than just having the SQL we override defined statically in the interface design we will have it configurable via a variable….at runtime. Imagine you have a well defined interface shape that you want to be fulfilled and that shape can be satisfied from a number of different sources that is what this allows - or the ability for one interface to consume data from many different places using variables. The cool thing about ODI’s reference API and this is that it can be fantastically flexible and useful. When I use the variable as the option value, and I execute the top level scenario that uses this temporary interface I get prompted (or can get prompted to be correct) for the value of the variable. Note I am using the <@=odiRef.getObjectName("L","EMP", "SCOTT","D")@> notation for the table reference, since this is done at runtime, then the context will resolve to the correct table name etc. Each time I execute, I could use a different source provider (obviously some dependencies on KMs/technologies here). For example, the following groovy snippet first executes and the query uses SCOTT model with EMP, the next time it is from BOB model and the datastore OTHERS. m=new Properties(); m.put("DEMO.SQLSTR", "select empno, deptno from <@=odiRef.getObjectName("L","EMP", "SCOTT","D")@>"); s=new StartupParams(m); runtimeAgent.startScenario("TOP", null, s, null, "GLOBAL", 5, null, true); m2=new Properties(); m2.put("DEMO.SQLSTR", "select empno, deptno from <@=odiRef.getObjectName("L","OTHERS", "BOB","D")@>"); s2=new StartupParams(m); runtimeAgent.startScenario("TOP", null, s2, null, "GLOBAL", 5, null, true); You’ll need a patch to 11.1.1.6 for this type of capability, thanks to my ole buddy Ron Gonzalez from the Enterprise Management group for help pushing the envelope!

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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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  • Who Do You Turn To for Your Consumer Goods Sales and Marketing Needs

    - by ruth.donohue
    As a sales or marketing executive, you want the best software for managing your marketing, demand generation, trade promotion, customer/volume planning, and retail execution/monitoring activities and analysis. However, working with niche software vendors can result in a very disjointed user and support experience. It would be ideal to have just one end-to-end solution that could manage and optimize each of these processes...but is that just wishful thinking? Read this Gartner article to find out more!

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  • How does enterprise failover, such as with google.com, actually work?

    - by Alex Regan
    We have a few fedora systems that are configured for web, FTP, and email services. We'd like to mirror these services, so that we can provide near 100% reliability for our users. I'm a fairly experienced Linux administrator, but don't have much experience with redundant systems. What is the best way to do this? How does google and amazon do it? Google.com resolves to multiple IP addresses, but if my local desktop caches one of the IPs that are unreachable, I'm going to get a failed connection message. How do they prevent that from happening? If one of their servers goes down, how is it automatically redirected to another system, without the end-user ever knowing it? I understand there are failover devices, but they're only for failing over the system itself, not a complete network. Let's say we have the worst-case scenario, such as my primary system becomes inaccessible. What are the fundamental components that are used on Linux systems to provide this capability? I'm looking for concepts, or approaches, not answers like "check out openstack". What are the actual pieces that make up the solution? What has to be done to implement this capability? Hopefully my question is clear. I'd like to know what the pieces are that make up a failover system and what approach is taken by successful organizations that implement it. Thanks again, Alex

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  • Maintaining Revision Levels

    - by kyle.hatlestad
    A question that came up on an earlier blog post was how to limit the number of revisions on a piece of content. UCM does not inherently enforce any sort of limit on how many revisions you can have. It's unlimited. In some cases, there may be content that goes through lots of changes, but there just simply isn't a need to keep all of its revisions around. Deleting those revisions through the content information screen can be very cumbersome. And going through the Repository Manager applet can take time as well to filter and find the revisions to get rid of. But there is an easier way through the Archiver. The Export Query criteria in Archiver includes a very handy field called 'Revision Rank'. With revision labels, they typically go up as new revisions come in (e.g. 1, 2, 3, 4, etc...). But you can't really use this field to tell it to keep the top 5 revisions. Those top 5 revision numbers are always going up. But revision rank goes the opposite direction. The very latest revision is always 0. The previous revision to that is 1. Previous revision to that is 2. And so on and so forth. With revision rank, you can set your query to look for any Revision Rank greater or equal to 5. Now as older revisions move down the line, their revision rank gets higher and higher until they reach that threshold. Then when you run that archive export, you can choose to delete and remove those revisions. Running that export in Archiver is normally a manual process. But with Idc Command, you can script the process and have it run automatically from the server. Idc Command is a utility that allows you to run any of the content server services via the command line. You basically feed it a text file with the services and parameters defined along with the user to run it as. The Idc Command executable is located within the \bin\ directory: $ ./IdcCommand -f DeleteOlderRevisions.txt -u sysadmin -l delete_revisions.log In this example, our IdcCommand file to run the export and do the deletions would look like: IdcService=EXPORT_ARCHIVE aArchiveName=DeleteOlderRevisions aDoDelete=1 IDC_Name=idc dataSource=RevisionIDs <<EOD>> You can then use automated scheduling routines in the OS to run the command and command file at the frequency needed. Remember that you are deleting the revisions from within UCM, but they are still getting placed within the archive. So you will need to delete those batches to have them fully removed (or re-import if you need to recover them). For more information about Idc Command, you can find that in the Idc Command Reference Guide.

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  • How-to dynamically filter model-driven LOV

    - by Frank Nimphius
    Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Often developers need to filter a LOV query with information obtained from an ADF Faces form or other where. The sample below shows how to define a launch popup listener configured on the launchPopupListener property of the af:inputListOfValues component to filter a list of values. <af:inputListOfValues id="departmentIdId"    value="#{bindings.DepartmentId.inputValue}"                                          model="#{bindings.DepartmentId.listOfValuesModel}"    launchPopupListener="#{PopupLauncher.onPopupLaunch}" … >         … </af:inputListOfValues> A list of values is queried using a search binding that gets created in the PageDef file of a view when a lis of value component gets added. The managed bean code below looks this search binding up to then add a view criteria that filters the query. Note: There is no public API yet available for the FacesCtrlLOVBinding class, which is why I use the internal package class it in the example. public void onPopupLaunch(LaunchPopupEvent launchPopupEvent) {   BindingContext bctx = BindingContext.getCurrent();   BindingContainer bindings = bctx.getCurrentBindingsEntry();   FacesCtrlLOVBinding lov =        (FacesCtrlLOVBinding)bindings.get("DepartmentId");   ViewCriteriaManager vcm =   lov.getListIterBinding().getViewObject().getViewCriteriaManager();             //make sure the view criteria is cleared   vcm.removeViewCriteria(vcm.DFLT_VIEW_CRITERIA_NAME);   //create a new view criteria   ViewCriteria vc =          new ViewCriteria(lov.getListIterBinding().getViewObject());   //use the default view criteria name   //"__DefaultViewCriteria__"   vc.setName(vcm.DFLT_VIEW_CRITERIA_NAME);   //create a view criteria row for all queryable attributes   ViewCriteriaRow vcr = new ViewCriteriaRow(vc);   //for this sample I set the query filter to DepartmentId 60.   //You may determine it at runtime by reading it from a managed bean   //or binding layer   vcr.setAttribute("DepartmentId", 60);   //also note that the view criteria row consists of all attributes   //that belong to the LOV list view object, which means that you can   //filter on multiple attributes   vc.addRow(vcr);             lov.getListIterBinding().getViewObject().applyViewCriteria(vc); }  Note: Instead of using the vcm.DFLT_VIEW_CRITERIA_NAME name you can also define a custom name for the view criteria.

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  • PHP oci8 dll not loading on windows 64 bit XP. What am I doing wrong?

    - by user47354
    on win 64, I installed apache, php etc. Everything works fine, except the oracle part. I can connect to oracle from sql developer which means my tnsnames.ora file is correct. When apache starts, there are no errors in the logs. But when I try to connect to oracle from my database, oracle module php_oci8.dll is not loaded. What am I doing wrong? The oci8.dll line in php.ini is there, it is uncommented There are no errors in the apache logs extension_dir in php.ini file points to the correct location

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  • MySQL Cluster 7.2: Over 8x Higher Performance than Cluster 7.1

    - by Mat Keep
    0 0 1 893 5092 Homework 42 11 5974 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} Summary The scalability enhancements delivered by extensions to multi-threaded data nodes enables MySQL Cluster 7.2 to deliver over 8x higher performance than the previous MySQL Cluster 7.1 release on a recent benchmark What’s New in MySQL Cluster 7.2 MySQL Cluster 7.2 was released as GA (Generally Available) in February 2012, delivering many enhancements to performance on complex queries, new NoSQL Key / Value API, cross-data center replication and ease-of-use. These enhancements are summarized in the Figure below, and detailed in the MySQL Cluster New Features whitepaper Figure 1: Next Generation Web Services, Cross Data Center Replication and Ease-of-Use Once of the key enhancements delivered in MySQL Cluster 7.2 is extensions made to the multi-threading processes of the data nodes. Multi-Threaded Data Node Extensions The MySQL Cluster 7.2 data node is now functionally divided into seven thread types: 1) Local Data Manager threads (ldm). Note – these are sometimes also called LQH threads. 2) Transaction Coordinator threads (tc) 3) Asynchronous Replication threads (rep) 4) Schema Management threads (main) 5) Network receiver threads (recv) 6) Network send threads (send) 7) IO threads Each of these thread types are discussed in more detail below. MySQL Cluster 7.2 increases the maximum number of LDM threads from 4 to 16. The LDM contains the actual data, which means that when using 16 threads the data is more heavily partitioned (this is automatic in MySQL Cluster). Each LDM thread maintains its own set of data partitions, index partitions and REDO log. The number of LDM partitions per data node is not dynamically configurable, but it is possible, however, to map more than one partition onto each LDM thread, providing flexibility in modifying the number of LDM threads. The TC domain stores the state of in-flight transactions. This means that every new transaction can easily be assigned to a new TC thread. Testing has shown that in most cases 1 TC thread per 2 LDM threads is sufficient, and in many cases even 1 TC thread per 4 LDM threads is also acceptable. Testing also demonstrated that in some instances where the workload needed to sustain very high update loads it is necessary to configure 3 to 4 TC threads per 4 LDM threads. In the previous MySQL Cluster 7.1 release, only one TC thread was available. This limit has been increased to 16 TC threads in MySQL Cluster 7.2. The TC domain also manages the Adaptive Query Localization functionality introduced in MySQL Cluster 7.2 that significantly enhanced complex query performance by pushing JOIN operations down to the data nodes. Asynchronous Replication was separated into its own thread with the release of MySQL Cluster 7.1, and has not been modified in the latest 7.2 release. To scale the number of TC threads, it was necessary to separate the Schema Management domain from the TC domain. The schema management thread has little load, so is implemented with a single thread. The Network receiver domain was bound to 1 thread in MySQL Cluster 7.1. With the increase of threads in MySQL Cluster 7.2 it is also necessary to increase the number of recv threads to 8. This enables each receive thread to service one or more sockets used to communicate with other nodes the Cluster. The Network send thread is a new thread type introduced in MySQL Cluster 7.2. Previously other threads handled the sending operations themselves, which can provide for lower latency. To achieve highest throughput however, it has been necessary to create dedicated send threads, of which 8 can be configured. It is still possible to configure MySQL Cluster 7.2 to a legacy mode that does not use any of the send threads – useful for those workloads that are most sensitive to latency. The IO Thread is the final thread type and there have been no changes to this domain in MySQL Cluster 7.2. Multiple IO threads were already available, which could be configured to either one thread per open file, or to a fixed number of IO threads that handle the IO traffic. Except when using compression on disk, the IO threads typically have a very light load. Benchmarking the Scalability Enhancements The scalability enhancements discussed above have made it possible to scale CPU usage of each data node to more than 5x of that possible in MySQL Cluster 7.1. In addition, a number of bottlenecks have been removed, making it possible to scale data node performance by even more than 5x. Figure 2: MySQL Cluster 7.2 Delivers 8.4x Higher Performance than 7.1 The flexAsynch benchmark was used to compare MySQL Cluster 7.2 performance to 7.1 across an 8-node Intel Xeon x5670-based cluster of dual socket commodity servers (6 cores each). As the results demonstrate, MySQL Cluster 7.2 delivers over 8x higher performance per data nodes than MySQL Cluster 7.1. More details of this and other benchmarks will be published in a new whitepaper – coming soon, so stay tuned! In a following blog post, I’ll provide recommendations on optimum thread configurations for different types of server processor. You can also learn more from the Best Practices Guide to Optimizing Performance of MySQL Cluster Conclusion MySQL Cluster has achieved a range of impressive benchmark results, and set in context with the previous 7.1 release, is able to deliver over 8x higher performance per node. As a result, the multi-threaded data node extensions not only serve to increase performance of MySQL Cluster, they also enable users to achieve significantly improved levels of utilization from current and future generations of massively multi-core, multi-thread processor designs.

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  • Patching and PCI Compliance

    - by Joel Weise
    One of my friends and master of the security universe, Darren Moffat, pointed me to Dan Anderson's blog the other day.  Dan went to Toorcon which is a security conference where he went to a talk on security patching titled, "Stop Patching, for Stronger PCI Compliance".  I realize that often times speakers will use a headline grabbing title to create interest in their talk and this one certainly got my attention.  I did not go to the conference and did not see the presentation, so I can only go by what is in the Toorcon agenda summary and on Dan's blog, but the general statement to stop patching for stronger PCI compliance seems a bit misleading to me.  Clearly patching is important to all systems management and should be a part of any organization's security hygiene.  Further, PCI does require the patching of systems to maintain compliance.  So it's important to mention that organizations should not simply stop patching their systems; and I want to believe that was not the speakers intent. So let's look at PCI requirement 6: "Unscrupulous individuals use security vulnerabilities to gain privileged access to systems. Many of these vulnerabilities are fixed by vendor- provided security patches, which must be installed by the entities that manage the systems. All critical systems must have the most recently released, appropriate software patches to protect against exploitation and compromise of cardholder data by malicious individuals and malicious software." Notice the word "appropriate" in the requirement.  This is stated to give organizations some latitude and apply patches that make sense in their environment and that target the vulnerabilities in question.  Haven't we all seen a vulnerability scanner throw a false positive and flag some module and point to a recommended patch, only to realize that the module doesn't exist on our system?  Applying such a patch would obviously not be appropriate.  This does not mean an organization can ignore the fact they need to apply security patches.  It's pretty clear they must.  Of course, organizations have other options in terms of compliance when it comes to patching.  For example, they could remove a system from scope and make sure that system does not process or contain cardholder data.  [This may or may not be a significant undertaking.  I just wanted to point out that there are always options available.] PCI DSS requirement 6.1 also includes the following note: "Note: An organization may consider applying a risk-based approach to prioritize their patch installations. For example, by prioritizing critical infrastructure (for example, public-facing devices and systems, databases) higher than less-critical internal devices, to ensure high-priority systems and devices are addressed within one month, and addressing less critical devices and systems within three months." Notice there is no mention to stop patching one's systems.  And the note also states organization may apply a risk based approach. [A smart approach but also not mandated].  Such a risk based approach is not intended to remove the requirement to patch one's systems.  It is meant, as stated, to allow one to prioritize their patch installations.   So what does this mean to an organization that must comply with PCI DSS and maintain some sanity around their patch management and overall operational readiness?  I for one like to think that most organizations take a common sense and balanced approach to their business and security posture.  If patching is becoming an unbearable task, review why that is the case and possibly look for means to improve operational efficiencies; but also recognize that security is important to maintaining the availability and integrity of one's systems.  Likewise, whether we like it or not, the cyber-world we live in is getting more complex and threatening - and I dont think it's going to get better any time soon.

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  • FairScheduling Conventions in Hadoop

    - by dan.mcclary
    While scheduling and resource allocation control has been present in Hadoop since 0.20, a lot of people haven't discovered or utilized it in their initial investigations of the Hadoop ecosystem. We could chalk this up to many things: Organizations are still determining what their dataflow and analysis workloads will comprise Small deployments under tests aren't likely to show the signs of strains that would send someone looking for resource allocation options The default scheduling options -- the FairScheduler and the CapacityScheduler -- are not placed in the most prominent position within the Hadoop documentation. However, for production deployments, it's wise to start with at least the foundations of scheduling in place so that you can tune the cluster as workloads emerge. To do that, we have to ask ourselves something about what the off-the-rack scheduling options are. We have some choices: The FairScheduler, which will work to ensure resource allocations are enforced on a per-job basis. The CapacityScheduler, which will ensure resource allocations are enforced on a per-queue basis. Writing your own implementation of the abstract class org.apache.hadoop.mapred.job.TaskScheduler is an option, but usually overkill. If you're going to have several concurrent users and leverage the more interactive aspects of the Hadoop environment (e.g. Pig and Hive scripting), the FairScheduler is definitely the way to go. In particular, we can do user-specific pools so that default users get their fair share, and specific users are given the resources their workloads require. To enable fair scheduling, we're going to need to do a couple of things. First, we need to tell the JobTracker that we want to use scheduling and where we're going to be defining our allocations. We do this by adding the following to the mapred-site.xml file in HADOOP_HOME/conf: <property> <name>mapred.jobtracker.taskScheduler</name> <value>org.apache.hadoop.mapred.FairScheduler</value> </property> <property> <name>mapred.fairscheduler.allocation.file</name> <value>/path/to/allocations.xml</value> </property> <property> <name>mapred.fairscheduler.poolnameproperty</name> <value>pool.name</value> </property> <property> <name>pool.name</name> <value>${user.name}</name> </property> What we've done here is simply tell the JobTracker that we'd like to task scheduling to use the FairScheduler class rather than a single FIFO queue. Moreover, we're going to be defining our resource pools and allocations in a file called allocations.xml For reference, the allocation file is read every 15s or so, which allows for tuning allocations without having to take down the JobTracker. Our allocation file is now going to look a little like this <?xml version="1.0"?> <allocations> <pool name="dan"> <minMaps>5</minMaps> <minReduces>5</minReduces> <maxMaps>25</maxMaps> <maxReduces>25</maxReduces> <minSharePreemptionTimeout>300</minSharePreemptionTimeout> </pool> <mapreduce.job.user.name="dan"> <maxRunningJobs>6</maxRunningJobs> </user> <userMaxJobsDefault>3</userMaxJobsDefault> <fairSharePreemptionTimeout>600</fairSharePreemptionTimeout> </allocations> In this case, I've explicitly set my username to have upper and lower bounds on the maps and reduces, and allotted myself double the number of running jobs. Now, if I run hive or pig jobs from either the console or via the Hue web interface, I'll be treated "fairly" by the JobTracker. There's a lot more tweaking that can be done to the allocations file, so it's best to dig down into the description and start trying out allocations that might fit your workload.

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  • Create an AWS HVM Linux AMI from an Existing Paravirtual Linux AMI

    - by javacavaj
    Is it possible to create a hardware virtual machine (HVM) AMI from an existing paravirtual (PV) AMI. My initially thought was to start a new PV instance and use the ec2-create-image command to create a new image while specifying HVM as the virutalization type. However, ec2-create-image does not have a command line parameter to specify the virtualization type. Is there another way to go about doing this?

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  • ArchBeat Link-o-Rama for 2012-03-28

    - by Bob Rhubart
    Beware the 'Facebook Effect' when service-orienting information technology | Joe McKenrick www.zdnet.com Experiences seen with Facebook provide a fair warning to shared-service providers in enterprises. Cookbook: SES and UCM setup | George Maggessy blogs.oracle.com WebCenter A-Team member George Maggessy guides you through setting up the integration between UCM and SES. Using Oracle VM with Amazon EC2 | Marc Fielding www.pythian.com "If you’re planning on running Oracle VM with Amazon EC2, there are some important limitations you should know about," says Pythian's Marc Fielding. Oracle Enterprise Pack for Eclipse 12.1.1 update on OTN blogs.oracle.com Oracle Enterprise Pack for Eclipse (OEPE) 12.1.1.0.1 was released to OTN last week with support for new standards and several new features. Thought for the Day "If the mind really is the finest computer, then there are a lot of people out there who need to be rebooted." — Tim Bryce

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  • Memcached server: Is it a good practice to point two server urls to the same server?

    - by Niro
    I have a system where there are connections to a memcache server from several different files and servers. I would like to stay with one server but keep the option of increasing the number of memcache servers (for periods of of high traffic). My idea is to tell memcache there are two servers, while the two urls will point (by DNS) to a single server. In the future if I want I can add a server and change DNS without changing the code in many places. Is this a good practice? Is there a performance cost to the fact that there are two server connections but they both point to the same server? Any other idea how to achive instant expeandability of memcache capacity without need to change the code and deploy ?

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  • NGiNX + PHP5-fpm + CDN Tools (plugin)

    - by chris hough
    I am trying to activate the CDN tools plugin and I keep getting the following error: Fatal error: Allowed memory size of 67108864 bytes exhausted (tried to allocate 30720 bytes) in /srv/www/www.triathleteskitchen.com/wp-content/plugins/cdn-tools/cdn_classes/cloudfiles/cloudfiles_http.php on line 252 After extensive research on this issue in which I updated both of the following settings: max_execution_time = 300 memory_limit = 128M and verified the settings are active by setting up a dump phpinfo() page. Still no luck /cry I am curious if any php geeks better than me have any ideas or can point me in the right direction. Happy Holidays to you and your families :)

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  • obiee memory usage

    - by user554629
    Heap memory is a frequent customer topic. Here's the quick refresher, oriented towards AIX, but the principles apply to other unix implementations. 1. 32-bit processes have a maximum addressability of 4GB; usable application heap size of 2-3 GB.  On AIX it is controlled by an environment variable: export LDR_CNTRL=....=MAXDATA=0x080000000   # 2GB ( The leading zero is deliberate, not required )   1a. It is  possible to get 3.25GB  heap size for a 32-bit process using @DSA (Discontiguous Segment Allocation)     export LDR_CNTRL=MAXDATA=0xd0000000@DSA  # 3.25 GB 32-bit only        One side-effect of using AIX segments "c" and "d" is that shared libraries will be loaded privately, and not shared.        If you need the additional heap space, this is worth the trade-off.  This option is frequently used for 32-bit java.   1b. 64-bit processes have no need for the @DSA option. 2. 64-bit processes can double the 32-bit heap size to 4GB using: export LDR_CNTRL=....=MAXDATA=0x100000000  # 1 with 8-zeros    2a. But this setting would place the same memory limitations on obiee as a 32-bit process    2b. The major benefit of 64-bit is to break the binds of 32-bit addressing.  At a minimum, use 8GB export LDR_CNTRL=....=MAXDATA=0x200000000  # 2 with 8-zeros    2c.  Many large customers are providing extra safety to their servers by using 16GB: export LDR_CNTRL=....=MAXDATA=0x400000000  # 4 with 8-zeros There is no performance penalty for providing virtual memory allocations larger than required by the application.  - If the server only uses 2GB of space in 64-bit ... specifying 16GB just provides an upper bound cushion.    When an unexpected user query causes a sudden memory surge, the extra memory keeps the server running. 3.  The next benefit to 64-bit is that you can provide huge thread stack sizes for      strange queries that might otherwise crash the server.      nqsserver uses fast recursive algorithms to traverse complicated control structures.    This means lots of thread space to hold the stack frames.    3a. Stack frames mostly contain register values;  64-bit registers are twice as large as 32-bit          At a minimum you should  quadruple the size of the server stack threads in NQSConfig.INI          when migrating from 32- to 64-bit, to prevent a rogue query from crashing the server.           Allocate more than is normally necessary for safety.    3b. There is no penalty for allocating more stack size than you need ...           it is just virtual memory;   no real resources  are consumed until the extra space is needed.    3c. Increasing thread stack sizes may require the process heap size (MAXDATA) to be increased.          Heap space is used for dynamic memory requests, and for thread stacks.          No performance penalty to run with large heap and thread stack sizes.           In a 32-bit world, this safety would require careful planning to avoid exceeding 2GM usable storage.     3d. Increasing the number of threads also may require additional heap storage.          Most thread stack frames on obiee are allocated when the server is started,          and the real memory usage increases as threads run work. Does 2.8GB sound like a lot of memory for an AIX application server? - I guess it is what you are accustomed to seeing from "grandpa's applications". - One of the primary design goals of obiee is to trade memory for services ( db, query caches, etc) - 2.8GB is still well under the 4GB heap size allocated with MAXDATA=0x100000000 - 2.8GB process size is also possible even on 32-bit Windows applications - It is not unusual to receive a sudden request for 30MB of contiguous storage on obiee.- This is not a memory leak;  eventually the nqsserver storage will stabilize, but it may take days to do so. vmstat is the tool of choice to observe memory usage.  On AIX vmstat will show  something that may be  startling to some people ... that available free memory ( the 2nd column ) is always  trending toward zero ... no available free memory.  Some customers have concluded that "nearly zero memory free" means it is time to upgrade the server with more real memory.   After the upgrade, the server again shows very little free memory available. Should you be concerned about this?   Many customers are !!  Here is what is happening: - AIX filesystems are built on a paging model.   If you read/write a  filesystem block it is paged into memory ( no read/write system calls ) - This filesystem "page" has its own "backing store" on disk, the original filesystem block.   When the system needs the real memory page holding the file block, there is no need to "page out".    The page can be stolen immediately, because the original is still on disk in the filesystem. - The filesystem  pages tend to collect ... every filesystem block that was ever seen since    system boot is available in memory.  If another application needs the file block, it is retrieved with no physical I/O. What happens if the system does need the memory ... to satisfy a 30MB heap request by nqsserver, for example? - Since the filesystem blocks have their own backing store ( not on a paging device )   the kernel can just steal any filesystem block ... on a least-recently-used basis   to satisfy a new real memory request for "computation pages". No cause for alarm.   vmstat is accurately displaying whether all filesystem blocks have been touched, and now reside in memory.   Back to nqsserver:  when should you be worried about its memory footprint? Answer:  Almost never.   Stop monitoring it ... stop fussing over it ... stop trying to optimize it. This is a production application, and nqsserver uses the memory it requires to accomplish the job, based on demand. C'mon ... never worry?   I'm from New York ... worry is what we do best. Ok, here is the metric you should be watching, using vmstat: - Are you paging ... there are several columns of vmstat outputbash-2.04$ vmstat 3 3 System configuration: lcpu=4 mem=4096MB kthr    memory              page              faults        cpu    ----- ------------ ------------------------ ------------ -----------  r  b    avm   fre  re  pi  po  fr   sr  cy  in   sy  cs us sy id wa  0  0 208492  2600   0   0   0   0    0   0  13   45  73  0  0 99  0  0  0 208492  2600   0   0   0   0    0   0   9   12  77  0  0 99  0  0  0 208492  2600   0   0   0   0    0   0   9   40  86  0  0 99  0 avm is the "available free memory" indicator that trends toward zerore   is "re-page".  The kernel steals a real memory page for one process;  immediately repages back to original processpi  "page in".   A process memory page previously paged out, now paged back in because the process needs itpo "page out" A process memory block was paged out, because it was needed by some other process Light paging activity ( re, pi, po ) is not a concern for worry.   Processes get started, need some memory, go away. Sustained paging activity  is cause for concern.   obiee users are having a terrible day if these counters are always changing. Hang on ... if nqsserver needs that memory and I reduce MAXDATA to keep the process under control, won't the nqsserver process crash when the memory is needed? Yes it will.   It means that nqsserver is configured to require too much memory and there are  lots of options to reduce the real memory requirement.  - number of threads  - size of query cache  - size of sort But I need nqsserver to keep running. Real memory is over-committed.    Many things can cause this:- running all application processes on a single server    ... DB server, web servers, WebLogic/WebSphere, sawserver, nqsserver, etc.   You could move some of those to another host machine and communicate over the network  The need for real memory doesn't go away, it's just distributed to other host machines. - AIX LPAR is configured with too little memory.     The AIX admin needs to provide more real memory to the LPAR running obiee. - More memory to this LPAR affects other partitions. Then it's time to visit your friendly IBM rep and buy more memory.

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  • Developing an Implementation Plan with Iterations by Russ Pitts

    - by user535886
    Developing an Implementation Plan with Iterations by Russ Pitts  Ok, so you have come to grips with understanding that applying the iterative concept, as defined by OUM is simply breaking up the project effort you have estimated for each phase into one or more six week calendar duration blocks of work. Idea being the business user(s) or key recipient(s) of work product(s) being developed never go longer than six weeks without having some sort of review or prototyping of the work results for an iteration…”think-a-little”, “do-a-little”, and “show-a-little” in a six week or less timeframe…ideally the business user(s) or key recipients(s) are involved throughout. You also understand the OUM concept that you only plan for that which you have knowledge of. The concept further defined, a project plan initially is developed at a high-level, and becomes more detailed as project knowledge grows. Agreeing to this concept means you also have to admit to the fallacy that one can plan with precision beyond six weeks into a project…Anything beyond six weeks is a best guess in most cases when dealing with software implementation projects. Project planning, as defined by OUM begins with the Implementation Plan view, which is a very high-level perspective of the effort estimated for each of the five OUM phases, as well as the number of iterations within each phase. You might wonder how can you predict the number of iterations for each phase at this early point in the project. Remember project planning is not an exact science, and initially is high-level and abstract in nature, and then becomes more detailed and precise as the project proceeds. So where do you start in defining iterations for each phase for a project? The following are three easy steps to initially define the number of iterations for each phase: Step 1 => Start with identifying the known factors… …Prior to starting a project you should know: · The agreed upon time-period for an iteration (e.g 6 weeks, or 4 weeks, or…) within a phase (recommend keeping iteration time-period consistent within a phase, if not for the entire project) · The number of resources available for the project · The number of total number of man-day (effort) you have estimated for each of the five OUM phases of the project · The number of work days for a week Step 2 => Calculate the man-days of effort required for an iteration within a phase… Lets assume for the sake of this example there are 10 project resources, and you have estimated 2,536 man-days of work effort which will need to occur for the elaboration phase of the project. Let’s also assume a week for this project is defined as 5 business days, and that each iteration in the elaboration phase will last a calendar duration of 6 weeks. A simple calculation is performed to calculate the daily burn rate for a single iteration, which produces a result of… ((Number of resources * days per week) * duration of iteration) = Number of days required per iteration ((10 resources * 5 days/week) * 6 weeks) = 300 man days of effort required per iteration Step 3 => Calculate the number of iterations that can occur within a phase Next calculate the number of iterations that can occur for the amount of man-days of effort estimated for the phase being considered… (number of man-days of effort estimated / number of man-days required per iteration) = # of iterations for phase (2,536 man-days of estimated effort for phase / 300 man days of effort required per iteration) = 8.45 iterations, which should be rounded to a whole number such as 9 iterations* *Note - It is important to note this is an approximate calculation, not an exact science. This particular example is a simple one, which assumes all resources are utilized throughout the phase, including tech resources, etc. (rounding down or up to a whole number based on project factor considerations). It is also best in many cases to round up to higher number, as this provides some calendar scheduling contingency.

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  • OWSM Policy Repository in JDeveloper - Tips & Tricks - 11g

    - by Prakash Yamuna
    In this blog post I discussed about the OWSM Policy Repository that is embedded in JDeveloper. However some times people may run into issues with the embedded repository. Here is screen snapshot that shows the error you may run into (click on the image for larger image): If you run into "java.lang.IllegalArgumentException: WSM-04694 : An invalid directory was provided to connect to a file-base MDS repository." this caused due to spaces in the folder name. Here is a quick way to workaround this issue by running "Jdeveloper.exe - su". Hope people find this useful!

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  • ODI 11g - Scripting a Reverse Engineer

    - by David Allan
    A common question is related to how to script the reverse engineer using the ODI SDK. This follows on from some of my posts on scripting in general and accelerated model and topology setup. Check out this viewlet here to see how to define a reverse engineering process using ODI's package. Using the ODI SDK, you can script this up using the OdiPackage and StepOdiCommand classes as follows;  OdiPackage pkg = new OdiPackage(folder, "Pkg_Rev"+modName);   StepOdiCommand step1 = new StepOdiCommand(pkg,"step1_cmd_reset");   step1.setCommandExpression(new Expression("OdiReverseResetTable \"-MODEL="+mod.getModelId()+"\"",null, Expression.SqlGroupType.NONE));   StepOdiCommand step2 = new StepOdiCommand(pkg,"step2_cmd_reset");   step2.setCommandExpression(new Expression("OdiReverseGetMetaData \"-MODEL="+mod.getModelId()+"\"",null, Expression.SqlGroupType.NONE));   StepOdiCommand step3 = new StepOdiCommand(pkg,"step3_cmd_reset");   step3.setCommandExpression(new Expression("OdiReverseSetMetaData \"-MODEL="+mod.getModelId()+"\"",null, Expression.SqlGroupType.NONE));   pkg.setFirstStep(step1);   step1.setNextStepAfterSuccess(step2);   step2.setNextStepAfterSuccess(step3); The biggest leap of faith for users is getting to know which SDK classes have to be used to build the objects in the design, using StepOdiCommand isn't necessarily obvious, once you see it in action though it is very simple to use. The above snippet uses an OdiModel variable named mod, its a snippet I added to the accelerated model creation script in the post linked above.

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  • Future Tech Duke

    - by Tori Wieldt
    Do you like the new Duke? Have you gotten the new Duke screensaver yet? Follow @java or Like I <3 Java on Facebook and get the latest 3D, animated "Future Tech Duke" screensaver.   If you haven't already, register now to watch the global July 7 Java 7 community celebration and learn more about Java moving forward. We are looking for questions from the community to be asked during the panel Q & A. Enter your questions as a comment here, or tweet it with #java7. There's lots of great content being created for Java 7: technical articles, videos, updated web pages (can you say "layer cake?"), T-shirts, presentations, and there will be lots of Java 7 content in the new Java Magazine. See you at the Java 7 celebration event! Duke will be there!

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  • Gilda Garretón, a Java Developer and Parallelism Computing Researcher

    - by Yolande
    In a new interview titled “Gilda Garretón, a Java Developer and Parallelism Computing Research,” Garretón shares her first-hand experience developing with Java and Java 7 for very large-scale integration (VLSI) of computer-aided design (CAD). Garretón gives an insightful overview of how Java is contributing to the parallelism development and to the Electric VLSI Design Systems, an open source VLSI CAD application used as a research platform for new CAD algorithms as well as the research flow for hardware test chips.  Garretón considers that parallelism programming is hard and complex, yet important developments are taking place.  "With the addition of the concurrent package in Java SE 6 and the Fork/Join feature in Java SE 7, developers have a chance to rely more on existing frameworks and dedicate more time to the essence of their parallel algorithms." Read the full article here  

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  • EC2 Configuration

    - by user123683
    I am trying to create a server structure for my EC2 account. The design I have chosen consists of 2 instances running in different availability zones, elastic load balancer, an auto-scaling group with cloudwatch monitoring configured and a security group defining rules for access to the instances. This setup is to support an online web application written in PHP. I am trying to decide what is a better policy: Store MySQL DB on a separate Instance Store MySQL DB on an attached EBS volume (from what i know auto-scaling will not replicate the attached EBS volume but will generate new instances from a chosen AMI - is this view correct?) Regards the AMI I plan to use a basic Amazon linux 64 bit AMI, and install bastille (maybe OSSEC) but I am looking to also use an encrypted file system. Are there any issues using an encrypted file system and communication between the DB and webapp i neeed to be aware of? Are there any comms issues using the encrypted filesystem on the instance housing the webapp I was going to launch a second instance or attach a second volume in the second availability zone to act as a standby for the database - I'm just looking for some suggestions about how to get the two DB's to talk - will this be a big task Regards updates for security is it best to create a recent snapshot and just relaunch and allow Amazon to install updates on launch or is the yum update mechanism a suitable alternative - is it better practice to relaunch instead of updates being installed which force a restart. I plan to create two AMI snapshots one for the app server and one for the DB each with the same security measures in place - is this a reasonable - I just figure it is a better policy than having additional applications that are unnecessary included in a AMI that I intend on using. My plan for backup is to create periodic snapshots of the webapp and DB instances (if I use an additional EBS volume instead of separate instances my understanding is that the EBS volume will persist in S3 storage in the event of an unexpected termination and I can create snapshots of the volume backup purposes). Thanks in advance for suggestions and advice. I am new to EC2 and I may have described unnecessary overkill but I want to try implement what can be considered a best practice solution so all advice is appreciated.

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  • File sharing for small, distributed, non-technical, non-profit organization?

    - by mnmldave
    Problem: I've started volunteering for a small non-profit with fewer than five non-technical Windows users who need to share 20-30GB of files (Office documents, images, PDFs, etc.) amongst themselves online. Background: The users are accustomed to a Windows network share on a machine that backed up their data locally. An on-site "disaster" has forced them to work from their homes for awhile and to re-evaluate their file sharing needs (office was located in an old building with obvious electrical issues, etc.). Access to time from volunteers with IT experience seems to be difficult. Demonstrably minimizing energy consumption is a nice-to-have. I'm currently considering Jungle Disk (a Desktop account shared amongst the handful of employees since their TOS and my inquiries to their helpdesk seem to indicate this is permissible). It appears easy-to-use, inexpensive, secure, has backup functionality, and can scale to accomodate more data when needed. I've not used it myself though (have only used Dropbox for personal use) and systems isn't my area of expertise, so am worried I might be jumping on a bandwagon. That said, any suggestions, thoughts or similar experiences would be really appreciated.

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