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  • What's up with LDoms: Part 1 - Introduction & Basic Concepts

    - by Stefan Hinker
    LDoms - the correct name is Oracle VM Server for SPARC - have been around for quite a while now.  But to my surprise, I get more and more requests to explain how they work or to give advise on how to make good use of them.  This made me think that writing up a few articles discussing the different features would be a good idea.  Now - I don't intend to rewrite the LDoms Admin Guide or to copy and reformat the (hopefully) well known "Beginners Guide to LDoms" by Tony Shoumack from 2007.  Those documents are very recommendable - especially the Beginners Guide, although based on LDoms 1.0, is still a good place to begin with.  However, LDoms have come a long way since then, and I hope to contribute to their adoption by discussing how they work and what features there are today.  In this and the following posts, I will use the term "LDoms" as a common abbreviation for Oracle VM Server for SPARC, just because it's a lot shorter and easier to type (and presumably, read). So, just to get everyone on the same baseline, lets briefly discuss the basic concepts of virtualization with LDoms.  LDoms make use of a hypervisor as a layer of abstraction between real, physical hardware and virtual hardware.  This virtual hardware is then used to create a number of guest systems which each behave very similar to a system running on bare metal:  Each has its own OBP, each will install its own copy of the Solaris OS and each will see a certain amount of CPU, memory, disk and network resources available to it.  Unlike some other type 1 hypervisors running on x86 hardware, the SPARC hypervisor is embedded in the system firmware and makes use both of supporting functions in the sun4v SPARC instruction set as well as the overall CPU architecture to fulfill its function. The CMT architecture of the supporting CPUs (T1 through T4) provide a large number of cores and threads to the OS.  For example, the current T4 CPU has eight cores, each running 8 threads, for a total of 64 threads per socket.  To the OS, this looks like 64 CPUs.  The SPARC hypervisor, when creating guest systems, simply assigns a certain number of these threads exclusively to one guest, thus avoiding the overhead of having to schedule OS threads to CPUs, as do typical x86 hypervisors.  The hypervisor only assigns CPUs and then steps aside.  It is not involved in the actual work being dispatched from the OS to the CPU, all it does is maintain isolation between different guests. Likewise, memory is assigned exclusively to individual guests.  Here,  the hypervisor provides generic mappings between the physical hardware addresses and the guest's views on memory.  Again, the hypervisor is not involved in the actual memory access, it only maintains isolation between guests. During the inital setup of a system with LDoms, you start with one special domain, called the Control Domain.  Initially, this domain owns all the hardware available in the system, including all CPUs, all RAM and all IO resources.  If you'd be running the system un-virtualized, this would be what you'd be working with.  To allow for guests, you first resize this initial domain (also called a primary domain in LDoms speak), assigning it a small amount of CPU and memory.  This frees up most of the available CPU and memory resources for guest domains.  IO is a little more complex, but very straightforward.  When LDoms 1.0 first came out, the only way to provide IO to guest systems was to create virtual disk and network services and attach guests to these services.  In the meantime, several different ways to connect guest domains to IO have been developed, the most recent one being SR-IOV support for network devices released in version 2.2 of Oracle VM Server for SPARC. I will cover these more advanced features in detail later.  For now, lets have a short look at the initial way IO was virtualized in LDoms: For virtualized IO, you create two services, one "Virtual Disk Service" or vds, and one "Virtual Switch" or vswitch.  You can, of course, also create more of these, but that's more advanced than I want to cover in this introduction.  These IO services now connect real, physical IO resources like a disk LUN or a networt port to the virtual devices that are assigned to guest domains.  For disk IO, the normal case would be to connect a physical LUN (or some other storage option that I'll discuss later) to one specific guest.  That guest would be assigned a virtual disk, which would appear to be just like a real LUN to the guest, while the IO is actually routed through the virtual disk service down to the physical device.  For network, the vswitch acts very much like a real, physical ethernet switch - you connect one physical port to it for outside connectivity and define one or more connections per guest, just like you would plug cables between a real switch and a real system. For completeness, there is another service that provides console access to guest domains which mimics the behavior of serial terminal servers. The connections between the virtual devices on the guest's side and the virtual IO services in the primary domain are created by the hypervisor.  It uses so called "Logical Domain Channels" or LDCs to create point-to-point connections between all of these devices and services.  These LDCs work very similar to high speed serial connections and are configured automatically whenever the Control Domain adds or removes virtual IO. To see all this in action, now lets look at a first example.  I will start with a newly installed machine and configure the control domain so that it's ready to create guest systems. In a first step, after we've installed the software, let's start the virtual console service and downsize the primary domain.  root@sun # ldm list NAME STATE FLAGS CONS VCPU MEMORY UTIL UPTIME primary active -n-c-- UART 512 261632M 0.3% 2d 13h 58m root@sun # ldm add-vconscon port-range=5000-5100 \ primary-console primary root@sun # svcadm enable vntsd root@sun # svcs vntsd STATE STIME FMRI online 9:53:21 svc:/ldoms/vntsd:default root@sun # ldm set-vcpu 16 primary root@sun # ldm set-mau 1 primary root@sun # ldm start-reconf primary root@sun # ldm set-memory 7680m primary root@sun # ldm add-config initial root@sun # shutdown -y -g0 -i6 So what have I done: I've defined a range of ports (5000-5100) for the virtual network terminal service and then started that service.  The vnts will later provide console connections to guest systems, very much like serial NTS's do in the physical world. Next, I assigned 16 vCPUs (on this platform, a T3-4, that's two cores) to the primary domain, freeing the rest up for future guest systems.  I also assigned one MAU to this domain.  A MAU is a crypto unit in the T3 CPU.  These need to be explicitly assigned to domains, just like CPU or memory.  (This is no longer the case with T4 systems, where crypto is always available everywhere.) Before I reassigned the memory, I started what's called a "delayed reconfiguration" session.  That avoids actually doing the change right away, which would take a considerable amount of time in this case.  Instead, I'll need to reboot once I'm all done.  I've assigned 7680MB of RAM to the primary.  That's 8GB less the 512MB which the hypervisor uses for it's own private purposes.  You can, depending on your needs, work with less.  I'll spend a dedicated article on sizing, discussing the pros and cons in detail. Finally, just before the reboot, I saved my work on the ILOM, to make this configuration available after a powercycle of the box.  (It'll always be available after a simple reboot, but the ILOM needs to know the configuration of the hypervisor after a power-cycle, before the primary domain is booted.) Now, lets create a first disk service and a first virtual switch which is connected to the physical network device igb2. We will later use these to connect virtual disks and virtual network ports of our guest systems to real world storage and network. root@sun # ldm add-vds primary-vds root@sun # ldm add-vswitch net-dev=igb2 switch-primary primary You are free to choose whatever names you like for the virtual disk service and the virtual switch.  I strongly recommend that you choose names that make sense to you and describe the function of each service in the context of your implementation.  For the vswitch, for example, you could choose names like "admin-vswitch" or "production-network" etc. This already concludes the configuration of the control domain.  We've freed up considerable amounts of CPU and RAM for guest systems and created the necessary infrastructure - console, vts and vswitch - so that guests systems can actually interact with the outside world.  The system is now ready to create guests, which I'll describe in the next section. For further reading, here are some recommendable links: The LDoms 2.2 Admin Guide The "Beginners Guide to LDoms" The LDoms Information Center on MOS LDoms on OTN

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  • Concurrent Business Events

    - by Manoj Madhusoodanan
    This blog describes the various business events related to concurrent requests.In the concurrent program definition screen we can see the various business events which are attached to concurrent processing. Following are the actual definition of above business events. Each event will have following parameters. Create subscriptions to above business events.Before testing enable profile option 'Concurrent: Business Intelligence Integration Enable' to Yes. ExampleI have created a scenario.Whenever my concurrent request completes normally I want to send out file as attachment to my mail.So following components I have created.1) Host file deployed on $XXCUST_TOP/bin to send mail.It accepts mail ids,subject and output file.(Code here)2) Concurrent Program to send mail which points to above host file.3) Subscription package to oracle.apps.fnd.concurrent.request.completed.(Code here)Choose a concurrent program which you want to send the out file as attachment.Check Request Completed check box.Submit the program.If it completes normally the business event subscription program will send the out file as attachment to the specified mail id.

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  • Fix: Azure Disabled over 49 cents? Beware of using a Java Virtual Machine on Microsoft Azure

    - by Ken Cox [MVP]
    I love my MSDN Azure account. I can spin up a demo/dev app or VM in seconds. In fact, it is so easy to create a virtual machine that Azure shut down my whole account! Last night I spun up a Java Virtual Machine to play with some Android stuff. My mistake was that I didn’t read the Virtual Machine pricing warning: “I have a MSDN Azure Benefit subscription. Can I use my monthly Azure credits to purchase Oracle software?” “No, Azure credits in our MSDN offers are not applicable to Oracle software. In order to purchase Oracle software in the MSDN Azure Benefit subscription, customers need to turn off their {0} spending limit and pay at the regular pay-as-you-go rate. Otherwise, Oracle usage will hit the {1} spending limit and the subscription will be immediately disabled.”  Immediately disabled? Yup. Everything connected to the subscription was shut off, deallocated, rendered useless - even the free Web sites and the free Sendgrid email service.  The fix? I had to remove the spending limit from my account so I could pay $0.49 (49 cents) for the JVM usage. I still had $134.10 in credits remaining for regular usage with 6 days left in the billing month.  Now the restoration/clean-up begins… figuring out how to get the web sites and services back online.  To me, the preferable way would be for Azure to warn me when setting up a JVM that I had no way of paying for the service. In the alternative, shut down just the offending services – the ones that can’t be covered by the regular credits. What a mess.

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  • How John Got 15x Improvement Without Really Trying

    - by rchrd
    The following article was published on a Sun Microsystems website a number of years ago by John Feo. It is still useful and worth preserving. So I'm republishing it here.  How I Got 15x Improvement Without Really Trying John Feo, Sun Microsystems Taking ten "personal" program codes used in scientific and engineering research, the author was able to get from 2 to 15 times performance improvement easily by applying some simple general optimization techniques. Introduction Scientific research based on computer simulation depends on the simulation for advancement. The research can advance only as fast as the computational codes can execute. The codes' efficiency determines both the rate and quality of results. In the same amount of time, a faster program can generate more results and can carry out a more detailed simulation of physical phenomena than a slower program. Highly optimized programs help science advance quickly and insure that monies supporting scientific research are used as effectively as possible. Scientific computer codes divide into three broad categories: ISV, community, and personal. ISV codes are large, mature production codes developed and sold commercially. The codes improve slowly over time both in methods and capabilities, and they are well tuned for most vendor platforms. Since the codes are mature and complex, there are few opportunities to improve their performance solely through code optimization. Improvements of 10% to 15% are typical. Examples of ISV codes are DYNA3D, Gaussian, and Nastran. Community codes are non-commercial production codes used by a particular research field. Generally, they are developed and distributed by a single academic or research institution with assistance from the community. Most users just run the codes, but some develop new methods and extensions that feed back into the general release. The codes are available on most vendor platforms. Since these codes are younger than ISV codes, there are more opportunities to optimize the source code. Improvements of 50% are not unusual. Examples of community codes are AMBER, CHARM, BLAST, and FASTA. Personal codes are those written by single users or small research groups for their own use. These codes are not distributed, but may be passed from professor-to-student or student-to-student over several years. They form the primordial ocean of applications from which community and ISV codes emerge. Government research grants pay for the development of most personal codes. This paper reports on the nature and performance of this class of codes. Over the last year, I have looked at over two dozen personal codes from more than a dozen research institutions. The codes cover a variety of scientific fields, including astronomy, atmospheric sciences, bioinformatics, biology, chemistry, geology, and physics. The sources range from a few hundred lines to more than ten thousand lines, and are written in Fortran, Fortran 90, C, and C++. For the most part, the codes are modular, documented, and written in a clear, straightforward manner. They do not use complex language features, advanced data structures, programming tricks, or libraries. I had little trouble understanding what the codes did or how data structures were used. Most came with a makefile. Surprisingly, only one of the applications is parallel. All developers have access to parallel machines, so availability is not an issue. Several tried to parallelize their applications, but stopped after encountering difficulties. Lack of education and a perception that parallelism is difficult prevented most from trying. I parallelized several of the codes using OpenMP, and did not judge any of the codes as difficult to parallelize. Even more surprising than the lack of parallelism is the inefficiency of the codes. I was able to get large improvements in performance in a matter of a few days applying simple optimization techniques. Table 1 lists ten representative codes [names and affiliation are omitted to preserve anonymity]. Improvements on one processor range from 2x to 15.5x with a simple average of 4.75x. I did not use sophisticated performance tools or drill deep into the program's execution character as one would do when tuning ISV or community codes. Using only a profiler and source line timers, I identified inefficient sections of code and improved their performance by inspection. The changes were at a high level. I am sure there is another factor of 2 or 3 in each code, and more if the codes are parallelized. The study’s results show that personal scientific codes are running many times slower than they should and that the problem is pervasive. Computational scientists are not sloppy programmers; however, few are trained in the art of computer programming or code optimization. I found that most have a working knowledge of some programming language and standard software engineering practices; but they do not know, or think about, how to make their programs run faster. They simply do not know the standard techniques used to make codes run faster. In fact, they do not even perceive that such techniques exist. The case studies described in this paper show that applying simple, well known techniques can significantly increase the performance of personal codes. It is important that the scientific community and the Government agencies that support scientific research find ways to better educate academic scientific programmers. The inefficiency of their codes is so bad that it is retarding both the quality and progress of scientific research. # cacheperformance redundantoperations loopstructures performanceimprovement 1 x x 15.5 2 x 2.8 3 x x 2.5 4 x 2.1 5 x x 2.0 6 x 5.0 7 x 5.8 8 x 6.3 9 2.2 10 x x 3.3 Table 1 — Area of improvement and performance gains of 10 codes The remainder of the paper is organized as follows: sections 2, 3, and 4 discuss the three most common sources of inefficiencies in the codes studied. These are cache performance, redundant operations, and loop structures. Each section includes several examples. The last section summaries the work and suggests a possible solution to the issues raised. Optimizing cache performance Commodity microprocessor systems use caches to increase memory bandwidth and reduce memory latencies. Typical latencies from processor to L1, L2, local, and remote memory are 3, 10, 50, and 200 cycles, respectively. Moreover, bandwidth falls off dramatically as memory distances increase. Programs that do not use cache effectively run many times slower than programs that do. When optimizing for cache, the biggest performance gains are achieved by accessing data in cache order and reusing data to amortize the overhead of cache misses. Secondary considerations are prefetching, associativity, and replacement; however, the understanding and analysis required to optimize for the latter are probably beyond the capabilities of the non-expert. Much can be gained simply by accessing data in the correct order and maximizing data reuse. 6 out of the 10 codes studied here benefited from such high level optimizations. Array Accesses The most important cache optimization is the most basic: accessing Fortran array elements in column order and C array elements in row order. Four of the ten codes—1, 2, 4, and 10—got it wrong. Compilers will restructure nested loops to optimize cache performance, but may not do so if the loop structure is too complex, or the loop body includes conditionals, complex addressing, or function calls. In code 1, the compiler failed to invert a key loop because of complex addressing do I = 0, 1010, delta_x IM = I - delta_x IP = I + delta_x do J = 5, 995, delta_x JM = J - delta_x JP = J + delta_x T1 = CA1(IP, J) + CA1(I, JP) T2 = CA1(IM, J) + CA1(I, JM) S1 = T1 + T2 - 4 * CA1(I, J) CA(I, J) = CA1(I, J) + D * S1 end do end do In code 2, the culprit is conditionals do I = 1, N do J = 1, N If (IFLAG(I,J) .EQ. 0) then T1 = Value(I, J-1) T2 = Value(I-1, J) T3 = Value(I, J) T4 = Value(I+1, J) T5 = Value(I, J+1) Value(I,J) = 0.25 * (T1 + T2 + T5 + T4) Delta = ABS(T3 - Value(I,J)) If (Delta .GT. MaxDelta) MaxDelta = Delta endif enddo enddo I fixed both programs by inverting the loops by hand. Code 10 has three-dimensional arrays and triply nested loops. The structure of the most computationally intensive loops is too complex to invert automatically or by hand. The only practical solution is to transpose the arrays so that the dimension accessed by the innermost loop is in cache order. The arrays can be transposed at construction or prior to entering a computationally intensive section of code. The former requires all array references to be modified, while the latter is cost effective only if the cost of the transpose is amortized over many accesses. I used the second approach to optimize code 10. Code 5 has four-dimensional arrays and loops are nested four deep. For all of the reasons cited above the compiler is not able to restructure three key loops. Assume C arrays and let the four dimensions of the arrays be i, j, k, and l. In the original code, the index structure of the three loops is L1: for i L2: for i L3: for i for l for l for j for k for j for k for j for k for l So only L3 accesses array elements in cache order. L1 is a very complex loop—much too complex to invert. I brought the loop into cache alignment by transposing the second and fourth dimensions of the arrays. Since the code uses a macro to compute all array indexes, I effected the transpose at construction and changed the macro appropriately. The dimensions of the new arrays are now: i, l, k, and j. L3 is a simple loop and easily inverted. L2 has a loop-carried scalar dependence in k. By promoting the scalar name that carries the dependence to an array, I was able to invert the third and fourth subloops aligning the loop with cache. Code 5 is by far the most difficult of the four codes to optimize for array accesses; but the knowledge required to fix the problems is no more than that required for the other codes. I would judge this code at the limits of, but not beyond, the capabilities of appropriately trained computational scientists. Array Strides When a cache miss occurs, a line (64 bytes) rather than just one word is loaded into the cache. If data is accessed stride 1, than the cost of the miss is amortized over 8 words. Any stride other than one reduces the cost savings. Two of the ten codes studied suffered from non-unit strides. The codes represent two important classes of "strided" codes. Code 1 employs a multi-grid algorithm to reduce time to convergence. The grids are every tenth, fifth, second, and unit element. Since time to convergence is inversely proportional to the distance between elements, coarse grids converge quickly providing good starting values for finer grids. The better starting values further reduce the time to convergence. The downside is that grids of every nth element, n > 1, introduce non-unit strides into the computation. In the original code, much of the savings of the multi-grid algorithm were lost due to this problem. I eliminated the problem by compressing (copying) coarse grids into continuous memory, and rewriting the computation as a function of the compressed grid. On convergence, I copied the final values of the compressed grid back to the original grid. The savings gained from unit stride access of the compressed grid more than paid for the cost of copying. Using compressed grids, the loop from code 1 included in the previous section becomes do j = 1, GZ do i = 1, GZ T1 = CA(i+0, j-1) + CA(i-1, j+0) T4 = CA1(i+1, j+0) + CA1(i+0, j+1) S1 = T1 + T4 - 4 * CA1(i+0, j+0) CA(i+0, j+0) = CA1(i+0, j+0) + DD * S1 enddo enddo where CA and CA1 are compressed arrays of size GZ. Code 7 traverses a list of objects selecting objects for later processing. The labels of the selected objects are stored in an array. The selection step has unit stride, but the processing steps have irregular stride. A fix is to save the parameters of the selected objects in temporary arrays as they are selected, and pass the temporary arrays to the processing functions. The fix is practical if the same parameters are used in selection as in processing, or if processing comprises a series of distinct steps which use overlapping subsets of the parameters. Both conditions are true for code 7, so I achieved significant improvement by copying parameters to temporary arrays during selection. Data reuse In the previous sections, we optimized for spatial locality. It is also important to optimize for temporal locality. Once read, a datum should be used as much as possible before it is forced from cache. Loop fusion and loop unrolling are two techniques that increase temporal locality. Unfortunately, both techniques increase register pressure—as loop bodies become larger, the number of registers required to hold temporary values grows. Once register spilling occurs, any gains evaporate quickly. For multiprocessors with small register sets or small caches, the sweet spot can be very small. In the ten codes presented here, I found no opportunities for loop fusion and only two opportunities for loop unrolling (codes 1 and 3). In code 1, unrolling the outer and inner loop one iteration increases the number of result values computed by the loop body from 1 to 4, do J = 1, GZ-2, 2 do I = 1, GZ-2, 2 T1 = CA1(i+0, j-1) + CA1(i-1, j+0) T2 = CA1(i+1, j-1) + CA1(i+0, j+0) T3 = CA1(i+0, j+0) + CA1(i-1, j+1) T4 = CA1(i+1, j+0) + CA1(i+0, j+1) T5 = CA1(i+2, j+0) + CA1(i+1, j+1) T6 = CA1(i+1, j+1) + CA1(i+0, j+2) T7 = CA1(i+2, j+1) + CA1(i+1, j+2) S1 = T1 + T4 - 4 * CA1(i+0, j+0) S2 = T2 + T5 - 4 * CA1(i+1, j+0) S3 = T3 + T6 - 4 * CA1(i+0, j+1) S4 = T4 + T7 - 4 * CA1(i+1, j+1) CA(i+0, j+0) = CA1(i+0, j+0) + DD * S1 CA(i+1, j+0) = CA1(i+1, j+0) + DD * S2 CA(i+0, j+1) = CA1(i+0, j+1) + DD * S3 CA(i+1, j+1) = CA1(i+1, j+1) + DD * S4 enddo enddo The loop body executes 12 reads, whereas as the rolled loop shown in the previous section executes 20 reads to compute the same four values. In code 3, two loops are unrolled 8 times and one loop is unrolled 4 times. Here is the before for (k = 0; k < NK[u]; k++) { sum = 0.0; for (y = 0; y < NY; y++) { sum += W[y][u][k] * delta[y]; } backprop[i++]=sum; } and after code for (k = 0; k < KK - 8; k+=8) { sum0 = 0.0; sum1 = 0.0; sum2 = 0.0; sum3 = 0.0; sum4 = 0.0; sum5 = 0.0; sum6 = 0.0; sum7 = 0.0; for (y = 0; y < NY; y++) { sum0 += W[y][0][k+0] * delta[y]; sum1 += W[y][0][k+1] * delta[y]; sum2 += W[y][0][k+2] * delta[y]; sum3 += W[y][0][k+3] * delta[y]; sum4 += W[y][0][k+4] * delta[y]; sum5 += W[y][0][k+5] * delta[y]; sum6 += W[y][0][k+6] * delta[y]; sum7 += W[y][0][k+7] * delta[y]; } backprop[k+0] = sum0; backprop[k+1] = sum1; backprop[k+2] = sum2; backprop[k+3] = sum3; backprop[k+4] = sum4; backprop[k+5] = sum5; backprop[k+6] = sum6; backprop[k+7] = sum7; } for one of the loops unrolled 8 times. Optimizing for temporal locality is the most difficult optimization considered in this paper. The concepts are not difficult, but the sweet spot is small. Identifying where the program can benefit from loop unrolling or loop fusion is not trivial. Moreover, it takes some effort to get it right. Still, educating scientific programmers about temporal locality and teaching them how to optimize for it will pay dividends. Reducing instruction count Execution time is a function of instruction count. Reduce the count and you usually reduce the time. The best solution is to use a more efficient algorithm; that is, an algorithm whose order of complexity is smaller, that converges quicker, or is more accurate. Optimizing source code without changing the algorithm yields smaller, but still significant, gains. This paper considers only the latter because the intent is to study how much better codes can run if written by programmers schooled in basic code optimization techniques. The ten codes studied benefited from three types of "instruction reducing" optimizations. The two most prevalent were hoisting invariant memory and data operations out of inner loops. The third was eliminating unnecessary data copying. The nature of these inefficiencies is language dependent. Memory operations The semantics of C make it difficult for the compiler to determine all the invariant memory operations in a loop. The problem is particularly acute for loops in functions since the compiler may not know the values of the function's parameters at every call site when compiling the function. Most compilers support pragmas to help resolve ambiguities; however, these pragmas are not comprehensive and there is no standard syntax. To guarantee that invariant memory operations are not executed repetitively, the user has little choice but to hoist the operations by hand. The problem is not as severe in Fortran programs because in the absence of equivalence statements, it is a violation of the language's semantics for two names to share memory. Codes 3 and 5 are C programs. In both cases, the compiler did not hoist all invariant memory operations from inner loops. Consider the following loop from code 3 for (y = 0; y < NY; y++) { i = 0; for (u = 0; u < NU; u++) { for (k = 0; k < NK[u]; k++) { dW[y][u][k] += delta[y] * I1[i++]; } } } Since dW[y][u] can point to the same memory space as delta for one or more values of y and u, assignment to dW[y][u][k] may change the value of delta[y]. In reality, dW and delta do not overlap in memory, so I rewrote the loop as for (y = 0; y < NY; y++) { i = 0; Dy = delta[y]; for (u = 0; u < NU; u++) { for (k = 0; k < NK[u]; k++) { dW[y][u][k] += Dy * I1[i++]; } } } Failure to hoist invariant memory operations may be due to complex address calculations. If the compiler can not determine that the address calculation is invariant, then it can hoist neither the calculation nor the associated memory operations. As noted above, code 5 uses a macro to address four-dimensional arrays #define MAT4D(a,q,i,j,k) (double *)((a)->data + (q)*(a)->strides[0] + (i)*(a)->strides[3] + (j)*(a)->strides[2] + (k)*(a)->strides[1]) The macro is too complex for the compiler to understand and so, it does not identify any subexpressions as loop invariant. The simplest way to eliminate the address calculation from the innermost loop (over i) is to define a0 = MAT4D(a,q,0,j,k) before the loop and then replace all instances of *MAT4D(a,q,i,j,k) in the loop with a0[i] A similar problem appears in code 6, a Fortran program. The key loop in this program is do n1 = 1, nh nx1 = (n1 - 1) / nz + 1 nz1 = n1 - nz * (nx1 - 1) do n2 = 1, nh nx2 = (n2 - 1) / nz + 1 nz2 = n2 - nz * (nx2 - 1) ndx = nx2 - nx1 ndy = nz2 - nz1 gxx = grn(1,ndx,ndy) gyy = grn(2,ndx,ndy) gxy = grn(3,ndx,ndy) balance(n1,1) = balance(n1,1) + (force(n2,1) * gxx + force(n2,2) * gxy) * h1 balance(n1,2) = balance(n1,2) + (force(n2,1) * gxy + force(n2,2) * gyy)*h1 end do end do The programmer has written this loop well—there are no loop invariant operations with respect to n1 and n2. However, the loop resides within an iterative loop over time and the index calculations are independent with respect to time. Trading space for time, I precomputed the index values prior to the entering the time loop and stored the values in two arrays. I then replaced the index calculations with reads of the arrays. Data operations Ways to reduce data operations can appear in many forms. Implementing a more efficient algorithm produces the biggest gains. The closest I came to an algorithm change was in code 4. This code computes the inner product of K-vectors A(i) and B(j), 0 = i < N, 0 = j < M, for most values of i and j. Since the program computes most of the NM possible inner products, it is more efficient to compute all the inner products in one triply-nested loop rather than one at a time when needed. The savings accrue from reading A(i) once for all B(j) vectors and from loop unrolling. for (i = 0; i < N; i+=8) { for (j = 0; j < M; j++) { sum0 = 0.0; sum1 = 0.0; sum2 = 0.0; sum3 = 0.0; sum4 = 0.0; sum5 = 0.0; sum6 = 0.0; sum7 = 0.0; for (k = 0; k < K; k++) { sum0 += A[i+0][k] * B[j][k]; sum1 += A[i+1][k] * B[j][k]; sum2 += A[i+2][k] * B[j][k]; sum3 += A[i+3][k] * B[j][k]; sum4 += A[i+4][k] * B[j][k]; sum5 += A[i+5][k] * B[j][k]; sum6 += A[i+6][k] * B[j][k]; sum7 += A[i+7][k] * B[j][k]; } C[i+0][j] = sum0; C[i+1][j] = sum1; C[i+2][j] = sum2; C[i+3][j] = sum3; C[i+4][j] = sum4; C[i+5][j] = sum5; C[i+6][j] = sum6; C[i+7][j] = sum7; }} This change requires knowledge of a typical run; i.e., that most inner products are computed. The reasons for the change, however, derive from basic optimization concepts. It is the type of change easily made at development time by a knowledgeable programmer. In code 5, we have the data version of the index optimization in code 6. Here a very expensive computation is a function of the loop indices and so cannot be hoisted out of the loop; however, the computation is invariant with respect to an outer iterative loop over time. We can compute its value for each iteration of the computation loop prior to entering the time loop and save the values in an array. The increase in memory required to store the values is small in comparison to the large savings in time. The main loop in Code 8 is doubly nested. The inner loop includes a series of guarded computations; some are a function of the inner loop index but not the outer loop index while others are a function of the outer loop index but not the inner loop index for (j = 0; j < N; j++) { for (i = 0; i < M; i++) { r = i * hrmax; R = A[j]; temp = (PRM[3] == 0.0) ? 1.0 : pow(r, PRM[3]); high = temp * kcoeff * B[j] * PRM[2] * PRM[4]; low = high * PRM[6] * PRM[6] / (1.0 + pow(PRM[4] * PRM[6], 2.0)); kap = (R > PRM[6]) ? high * R * R / (1.0 + pow(PRM[4]*r, 2.0) : low * pow(R/PRM[6], PRM[5]); < rest of loop omitted > }} Note that the value of temp is invariant to j. Thus, we can hoist the computation for temp out of the loop and save its values in an array. for (i = 0; i < M; i++) { r = i * hrmax; TEMP[i] = pow(r, PRM[3]); } [N.B. – the case for PRM[3] = 0 is omitted and will be reintroduced later.] We now hoist out of the inner loop the computations invariant to i. Since the conditional guarding the value of kap is invariant to i, it behooves us to hoist the computation out of the inner loop, thereby executing the guard once rather than M times. The final version of the code is for (j = 0; j < N; j++) { R = rig[j] / 1000.; tmp1 = kcoeff * par[2] * beta[j] * par[4]; tmp2 = 1.0 + (par[4] * par[4] * par[6] * par[6]); tmp3 = 1.0 + (par[4] * par[4] * R * R); tmp4 = par[6] * par[6] / tmp2; tmp5 = R * R / tmp3; tmp6 = pow(R / par[6], par[5]); if ((par[3] == 0.0) && (R > par[6])) { for (i = 1; i <= imax1; i++) KAP[i] = tmp1 * tmp5; } else if ((par[3] == 0.0) && (R <= par[6])) { for (i = 1; i <= imax1; i++) KAP[i] = tmp1 * tmp4 * tmp6; } else if ((par[3] != 0.0) && (R > par[6])) { for (i = 1; i <= imax1; i++) KAP[i] = tmp1 * TEMP[i] * tmp5; } else if ((par[3] != 0.0) && (R <= par[6])) { for (i = 1; i <= imax1; i++) KAP[i] = tmp1 * TEMP[i] * tmp4 * tmp6; } for (i = 0; i < M; i++) { kap = KAP[i]; r = i * hrmax; < rest of loop omitted > } } Maybe not the prettiest piece of code, but certainly much more efficient than the original loop, Copy operations Several programs unnecessarily copy data from one data structure to another. This problem occurs in both Fortran and C programs, although it manifests itself differently in the two languages. Code 1 declares two arrays—one for old values and one for new values. At the end of each iteration, the array of new values is copied to the array of old values to reset the data structures for the next iteration. This problem occurs in Fortran programs not included in this study and in both Fortran 77 and Fortran 90 code. Introducing pointers to the arrays and swapping pointer values is an obvious way to eliminate the copying; but pointers is not a feature that many Fortran programmers know well or are comfortable using. An easy solution not involving pointers is to extend the dimension of the value array by 1 and use the last dimension to differentiate between arrays at different times. For example, if the data space is N x N, declare the array (N, N, 2). Then store the problem’s initial values in (_, _, 2) and define the scalar names new = 2 and old = 1. At the start of each iteration, swap old and new to reset the arrays. The old–new copy problem did not appear in any C program. In programs that had new and old values, the code swapped pointers to reset data structures. Where unnecessary coping did occur is in structure assignment and parameter passing. Structures in C are handled much like scalars. Assignment causes the data space of the right-hand name to be copied to the data space of the left-hand name. Similarly, when a structure is passed to a function, the data space of the actual parameter is copied to the data space of the formal parameter. If the structure is large and the assignment or function call is in an inner loop, then copying costs can grow quite large. While none of the ten programs considered here manifested this problem, it did occur in programs not included in the study. A simple fix is always to refer to structures via pointers. Optimizing loop structures Since scientific programs spend almost all their time in loops, efficient loops are the key to good performance. Conditionals, function calls, little instruction level parallelism, and large numbers of temporary values make it difficult for the compiler to generate tightly packed, highly efficient code. Conditionals and function calls introduce jumps that disrupt code flow. Users should eliminate or isolate conditionls to their own loops as much as possible. Often logical expressions can be substituted for if-then-else statements. For example, code 2 includes the following snippet MaxDelta = 0.0 do J = 1, N do I = 1, M < code omitted > Delta = abs(OldValue ? NewValue) if (Delta > MaxDelta) MaxDelta = Delta enddo enddo if (MaxDelta .gt. 0.001) goto 200 Since the only use of MaxDelta is to control the jump to 200 and all that matters is whether or not it is greater than 0.001, I made MaxDelta a boolean and rewrote the snippet as MaxDelta = .false. do J = 1, N do I = 1, M < code omitted > Delta = abs(OldValue ? NewValue) MaxDelta = MaxDelta .or. (Delta .gt. 0.001) enddo enddo if (MaxDelta) goto 200 thereby, eliminating the conditional expression from the inner loop. A microprocessor can execute many instructions per instruction cycle. Typically, it can execute one or more memory, floating point, integer, and jump operations. To be executed simultaneously, the operations must be independent. Thick loops tend to have more instruction level parallelism than thin loops. Moreover, they reduce memory traffice by maximizing data reuse. Loop unrolling and loop fusion are two techniques to increase the size of loop bodies. Several of the codes studied benefitted from loop unrolling, but none benefitted from loop fusion. This observation is not too surpising since it is the general tendency of programmers to write thick loops. As loops become thicker, the number of temporary values grows, increasing register pressure. If registers spill, then memory traffic increases and code flow is disrupted. A thick loop with many temporary values may execute slower than an equivalent series of thin loops. The biggest gain will be achieved if the thick loop can be split into a series of independent loops eliminating the need to write and read temporary arrays. I found such an occasion in code 10 where I split the loop do i = 1, n do j = 1, m A24(j,i)= S24(j,i) * T24(j,i) + S25(j,i) * U25(j,i) B24(j,i)= S24(j,i) * T25(j,i) + S25(j,i) * U24(j,i) A25(j,i)= S24(j,i) * C24(j,i) + S25(j,i) * V24(j,i) B25(j,i)= S24(j,i) * U25(j,i) + S25(j,i) * V25(j,i) C24(j,i)= S26(j,i) * T26(j,i) + S27(j,i) * U26(j,i) D24(j,i)= S26(j,i) * T27(j,i) + S27(j,i) * V26(j,i) C25(j,i)= S27(j,i) * S28(j,i) + S26(j,i) * U28(j,i) D25(j,i)= S27(j,i) * T28(j,i) + S26(j,i) * V28(j,i) end do end do into two disjoint loops do i = 1, n do j = 1, m A24(j,i)= S24(j,i) * T24(j,i) + S25(j,i) * U25(j,i) B24(j,i)= S24(j,i) * T25(j,i) + S25(j,i) * U24(j,i) A25(j,i)= S24(j,i) * C24(j,i) + S25(j,i) * V24(j,i) B25(j,i)= S24(j,i) * U25(j,i) + S25(j,i) * V25(j,i) end do end do do i = 1, n do j = 1, m C24(j,i)= S26(j,i) * T26(j,i) + S27(j,i) * U26(j,i) D24(j,i)= S26(j,i) * T27(j,i) + S27(j,i) * V26(j,i) C25(j,i)= S27(j,i) * S28(j,i) + S26(j,i) * U28(j,i) D25(j,i)= S27(j,i) * T28(j,i) + S26(j,i) * V28(j,i) end do end do Conclusions Over the course of the last year, I have had the opportunity to work with over two dozen academic scientific programmers at leading research universities. Their research interests span a broad range of scientific fields. Except for two programs that relied almost exclusively on library routines (matrix multiply and fast Fourier transform), I was able to improve significantly the single processor performance of all codes. Improvements range from 2x to 15.5x with a simple average of 4.75x. Changes to the source code were at a very high level. I did not use sophisticated techniques or programming tools to discover inefficiencies or effect the changes. Only one code was parallel despite the availability of parallel systems to all developers. Clearly, we have a problem—personal scientific research codes are highly inefficient and not running parallel. The developers are unaware of simple optimization techniques to make programs run faster. They lack education in the art of code optimization and parallel programming. I do not believe we can fix the problem by publishing additional books or training manuals. To date, the developers in questions have not studied the books or manual available, and are unlikely to do so in the future. Short courses are a possible solution, but I believe they are too concentrated to be much use. The general concepts can be taught in a three or four day course, but that is not enough time for students to practice what they learn and acquire the experience to apply and extend the concepts to their codes. Practice is the key to becoming proficient at optimization. I recommend that graduate students be required to take a semester length course in optimization and parallel programming. We would never give someone access to state-of-the-art scientific equipment costing hundreds of thousands of dollars without first requiring them to demonstrate that they know how to use the equipment. Yet the criterion for time on state-of-the-art supercomputers is at most an interesting project. Requestors are never asked to demonstrate that they know how to use the system, or can use the system effectively. A semester course would teach them the required skills. Government agencies that fund academic scientific research pay for most of the computer systems supporting scientific research as well as the development of most personal scientific codes. These agencies should require graduate schools to offer a course in optimization and parallel programming as a requirement for funding. About the Author John Feo received his Ph.D. in Computer Science from The University of Texas at Austin in 1986. After graduate school, Dr. Feo worked at Lawrence Livermore National Laboratory where he was the Group Leader of the Computer Research Group and principal investigator of the Sisal Language Project. In 1997, Dr. Feo joined Tera Computer Company where he was project manager for the MTA, and oversaw the programming and evaluation of the MTA at the San Diego Supercomputer Center. In 2000, Dr. Feo joined Sun Microsystems as an HPC application specialist. He works with university research groups to optimize and parallelize scientific codes. Dr. Feo has published over two dozen research articles in the areas of parallel parallel programming, parallel programming languages, and application performance.

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  • The UIManager Pattern

    - by Duncan Mills
    One of the most common mistakes that I see when reviewing ADF application code, is the sin of storing UI component references, most commonly things like table or tree components in Session or PageFlow scope. The reasons why this is bad are simple; firstly, these UI object references are not serializable so would not survive a session migration between servers and secondly there is no guarantee that the framework will re-use the same component tree from request to request, although in practice it generally does do so. So there danger here is, that at best you end up with an NPE after you session has migrated, and at worse, you end up pinning old generations of the component tree happily eating up your precious memory. So that's clear, we should never. ever, be storing references to components anywhere other than request scope (or maybe backing bean scope). So double check the scope of those binding attributes that map component references into a managed bean in your applications.  Why is it Such a Common Mistake?  At this point I want to examine why there is this urge to hold onto these references anyway? After all, JSF will obligingly populate your backing beans with the fresh and correct reference when needed.   In most cases, it seems that the rational is down to a lack of distinction within the application between what is data and what is presentation. I think perhaps, a cause of this is the logical separation between business data behind the ADF data binding (#{bindings}) façade and the UI components themselves. Developers tend to think, OK this is my data layer behind the bindings object and everything else is just UI.  Of course that's not the case.  The UI layer itself will have state which is intrinsically linked to the UI presentation rather than the business model, but at the same time should not be tighly bound to a specific instance of any single UI component. So here's the problem.  I think developers try and use the UI components as state-holders for this kind of data, rather than using them to represent that state. An example of this might be something like the selection state of a tabset (panelTabbed), you might be interested in knowing what the currently disclosed tab is. The temptation that leads to the component reference sin is to go and ask the tabset what the selection is.  That of course is fine in context - e.g. a handler within the same request scoped bean that's got the binding to the tabset. However, it leads to problems when you subsequently want the same information outside of the immediate scope.  The simple solution seems to be to chuck that component reference into session scope and then you can simply re-check in the same way, leading of course to this mistake. Turn it on its Head  So the correct solution to this is to turn the problem on its head. If you are going to be interested in the value or state of some component outside of the immediate request context then it becomes persistent state (persistent in the sense that it extends beyond the lifespan of a single request). So you need to externalize that state outside of the component and have the component reference and manipulate that state as needed rather than owning it. This is what I call the UIManager pattern.  Defining the Pattern The  UIManager pattern really is very simple. The premise is that every application should define a session scoped managed bean, appropriately named UIManger, which is specifically responsible for holding this persistent UI component related state.  The actual makeup of the UIManger class varies depending on a needs of the application and the amount of state that needs to be stored. Generally I'll start off with a Map in which individual flags can be created as required, although you could opt for a more formal set of typed member variables with getters and setters, or indeed a mix. This UIManager class is defined as a session scoped managed bean (#{uiManager}) in the faces-config.xml.  The pattern is to then inject this instance of the class into any other managed bean (usually request scope) that needs it using a managed property.  So typically you'll have something like this:   <managed-bean>     <managed-bean-name>uiManager</managed-bean-name>     <managed-bean-class>oracle.demo.view.state.UIManager</managed-bean-class>     <managed-bean-scope>session</managed-bean-scope>   </managed-bean>  When is then injected into any backing bean that needs it:    <managed-bean>     <managed-bean-name>mainPageBB</managed-bean-name>     <managed-bean-class>oracle.demo.view.MainBacking</managed-bean-class>     <managed-bean-scope>request</managed-bean-scope>     <managed-property>       <property-name>uiManager</property-name>       <property-class>oracle.demo.view.state.UIManager</property-class>       <value>#{uiManager}</value>     </managed-property>   </managed-bean> In this case the backing bean in question needs a member variable to hold and reference the UIManager: private UIManager _uiManager;  Which should be exposed via a getter and setter pair with names that match the managed property name (e.g. setUiManager(UIManager _uiManager), getUiManager()).  This will then give your code within the backing bean full access to the UI state. UI components in the page can, of course, directly reference the uiManager bean in their properties, for example, going back to the tab-set example you might have something like this: <af:paneltabbed>   <af:showDetailItem text="First"                disclosed="#{uiManager.settings['MAIN_TABSET_STATE'].['FIRST']}"> ...   </af:showDetailItem>   <af:showDetailItem text="Second"                      disclosed="#{uiManager.settings['MAIN_TABSET_STATE'].['SECOND']}">     ...   </af:showDetailItem>   ... </af:panelTabbed> Where in this case the settings member within the UI Manger is a Map which contains a Map of Booleans for each tab under the MAIN_TABSET_STATE key. (Just an example you could choose to store just an identifier for the selected tab or whatever, how you choose to store the state within UI Manger is up to you.) Get into the Habit So we can see that the UIManager pattern is not great strain to implement for an application and can even be retrofitted to an existing application with ease. The point is, however, that you should always take this approach rather than committing the sin of persistent component references which will bite you in the future or shotgun scattered UI flags on the session which are hard to maintain.  If you take the approach of always accessing all UI state via the uiManager, or perhaps a pageScope focused variant of it, you'll find your applications much easier to understand and maintain. Do it today!

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  • About Entitlement Grants in ADF Security of JDeveloper 11.1.1.4

    - 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;} Oracle JDeveloper 11.1.1.4 comes with a new ADF Security feature called "entitlement grants". This has nothing to do with Oracle Entitlement Server (OES) but is the ability to group resources into permission sets so they can be granted with a single grant statement. For example, as good practices when organizing your projects, you may have grouped your bounded task flows by functionality and responsibility in sub folders under the WEB-INF directory. If one of the folders holds bounded task flows that are accessible to all authenticated users, you may create an entitlement grant allAuthUserBTF and select all bounded task flows that are accessible for authenticated users as resources. You can then grant allAuthUserBTF to the authenticated-role so that with only a single grant statement all selected bounded task flows are protected. 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;} <permission-sets>         <permission-set>             <name>PublicBoundedTaskFlows</name>             <member-resources>               <member-resource>                 <resource-name>                      /WEB-INF/public/home-btf.xml#home-btf                 </resource-name>                 <type-name-ref>TaskFlowResourceType</type-name-ref>                 <display-name> ... </display-name>                 <actions>view</actions>               </member-resource>               <member-resource>                 <resource-name>                         /WEB-INF/public/preferences-btf.xml#preferences-btf                </resource-name>                 <type-name-ref>TaskFlowResourceType</type-name-ref>                 <display-name>...</display-name>                 <actions>view</actions>               </member-resource>             </member-resources>           </permission-set>   </permission-sets> The grant statement for this permission set is added as shown below <grant>   <grantee>     <principals>        <principal>             <name>authenticated-role</name>             <class>oracle.security.jps.internal.core.principals.JpsAuthenticatedRoleImpl</class>         </principal>       </principals>     </grantee>     <permission-set-refs>         <permission-set-ref>            <name>PublicBoundedTaskFlows</name>         </permission-set-ref>      </permission-set-refs> </grant>

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  • Great Discussion of ETL and ELT Tooling in TDWI Linkedin Group

    - by antonio romero
    All, There’s a great discussion of ETL and ELT tooling going on in the official TDWI Linkedin group, under the heading “How Sustainable is SQL for ETL?” It delves into a wide range of topics: The pros and cons of handcoding vs. using tools to design ETL ETL (with separate transformation engines) vs. ELT (transforms in the database) and push-down solutions The future of ETL and data warehousing products A number of community members (of varying affiliations) have kept this conversation going for many months, and are learning from each other as they go. So check it out… Also, while you’re on Linkedin, join the Oracle ETL/Data Integration Linkedin group (for both OWB and ODI users), which recently passed the 2000 member mark.

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  • Adopt-a-JSR for Java EE 7 - Getting Started

    - by arungupta
    Adopt-a-JSR is an initiative started by JUG leaders to encourage JUG members to get involved in a JSR, in order to increase grass roots participation. This allows JUG members to provide early feedback to specifications before they are finalized in the JCP. The standards in turn become more complete and developer-friendly after getting feedback from a wide variety of audience. adoptajsr.org provide more details about the logistics and benefits for you and your JUG. A similar activity was conducted for OpenJDK as well. Markus Eisele also provide a great introduction to the program (in German). Java EE 7 (JSR 342) is scheduled to go final in Q2 2013. There are several new JSRs that are getting included in the platform (e.g. WebSocket, JSON, and Batch), a few existing ones are getting an overhaul (e.g. JAX-RS 2 and JMS 2), and several other getting minor updates (e.g. JPA 2.1 and Servlets 3.1). Each Java EE 7 JSR can leverage your expertise and would love your JUG to adopt a JSR. What does it mean to adopt a JSR ? Your JUG is going to identify a particular JSR, or multiple JSRs, that is of interest to the JUG members. This is mostly done by polling/discussing on your local JUG members list. Your JUG will download and review the specification(s) and javadocs for clarity and completeness. The complete set of Java EE 7 specifications, their download links, and EG archives are listed here. glassfish.org/adoptajsr provide specific areas where different specification leads are looking for feedback. Your JUG can then think of a sample application that can be built using the chosen specification(s). An existing use case (from work or a personal hobby project) may be chosen to be implemented instead. This is where your creativity and uniqueness comes into play. Most of the implementations are already integrated in GlassFish 4 and others will be integrated soon. You can also explore integration of multiple technologies and provide feedback on the simplicity and ease-of-use of the programming model. Especially look for integration with existing Java EE technologies and see if you find any discrepancies. Report any missing features that may be included in future release of the specification. The most important part is to provide feedback by filing bugs on the corresponding spec or RI project. Any thing that is not clear either in the spec or implementation should be filed as a bug. This is what will ensure that specification and implementation leads are getting the required feedback and improving the quality of the final deliverable of the JSR. How do I get started ? A simple way to get started can be achieved by following S.M.A.R.T. as explained below. Specific Identify who all will be involved ? What would you like to accomplish ? For example, even though building a sample app will provide real-world validity of the API but because of time constraints you may identify that reviewing the specification and javadocs only can be accomplished. Establish a time frame by which the activities need to be complete. Measurable Define a success for metrics. For example, this could be the number of bugs filed. Remember, quality of bugs is more important that quantity of bugs. Define your end goal, for example, reviewing 4 chapters of the specification or completing the sample application. Create a dashboard that will highlight your JUG's contribution to this effort. Attainable Make sure JUG members understand the time commitment required for providing feedback. This can vary based upon the level of involvement (any is good!) and the number of specifications picked. adoptajsr.org defines different categories of involvement. Once again, any level of involvement is good. Just reviewing a chapter, a section, or javadocs for your usecase is helpful. Relevant Pick JSRs that JUG members are willing and able to work. If the JUG members are not interested then they might loose motivation half-way through. The "able" part is tricky as you can always stretch yourself and learn a new skill ;-) Time-bound Define a time table of activities with clearly defined tasks. A tentative time table may look like: Dec 25: Discuss and agree upon the specifications with JUG Jan 1: Start Adopt-a-JSR for Java EE 7 Jan 15: Initial spec reading complete. Keep thinking through the application that will be implemented. Jan 22: Early design of the sample application is ready Jan 29: JUG members agree upon the application Next 4 weeks: Implement the application Of course, you'll need to alter this based upon your commitment. Maintaining an activity dashboard will help you monitor and track the progress. Make sure to keep filing bugs through out the process! 12 JUGs from around the world (SouJava, Campinas JUG, Chennai JUG, London Java Community, BeJUG, Morocco JUG, Peru JUG, Indonesia JUG, Congo JUG, Silicon Valley JUG, Madrid JUG, and Houston JUG) have already adopted one of the Java EE 7 JSRs. I'm already helping some JUGs bootstrap and would love to help your JUG too. What are you waiting for ?

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  • New database profiling support in ANTS Performance Profiler

    - by Ben Emmett
    In May last year, the ANTS Performance Profiler team added the ability to profile database requests your application makes to SQL Server or Oracle. The really cool thing is that you’re shown those requests in the application’s call tree, so you can see what .NET code caused those queries to run. It’s particularly helpful if you’re using an ORM which automagically generates and runs queries for you, but which doesn’t necessarily do it in the most efficient way possible. Now by popular demand, we’ve added support for profiling MySQL (or MariaDB) and PostgreSQL, so you can see queries run against those databases too. Some of you have also said that you’re using the Devart dotConnect data providers instead of the native .NET ones, so we’ve added support for those drivers too. Hope it helps! For the record, here’s a list of supported connectors (ones in bold are new): SQL Server .NET Framework Data Provider Devart dotConnect for SQL Server Oracle .NET Framework Data Provider Oracle Data Provider for .NET Devart dotConnect for Oracle MySQL / MariaDB MySQL Connector/Net Devart dotConnect for MySQL PostgreSQL Npgsql .NET Data Provider for PostgreSQL Devart dotConnect for PostgreSQL SQL Server Compact Edition .NET Framework Data Provider for SQL Server Compact Edition Devart dotConnect for SQL Server Pro Have we missed a connector or database which you’d find useful? Tell us about it in the comments or by emailing [email protected]. Ben

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  • The Virtues and Challenges of Implementing Basel III: What Every CFO and CRO Needs To Know

    - by Jenna Danko
    The Basel Committee on Banking Supervision (BCBS) is a group tasked with providing thought-leadership to the global banking industry.  Over the years, the BCBS has released volumes of guidance in an effort to promote stability within the financial sector.  By effectively communicating best-practices, the Basel Committee has influenced financial regulations worldwide.  Basel regulations are intended to help banks: More easily absorb shocks due to various forms of financial-economic stress Improve risk management and governance Enhance regulatory reporting and transparency In June 2011, the BCBS released Basel III: A global regulatory framework for more resilient banks and banking systems.  This new set of regulations included many enhancements to previous rules and will have both short and long term impacts on the banking industry.  Some of the key features of Basel III include: A stronger capital base More stringent capital standards and higher capital requirements Introduction of capital buffers  Additional risk coverage Enhanced quantification of counterparty credit risk Credit valuation adjustments  Wrong  way risk  Asset Value Correlation Multiplier for large financial institutions Liquidity management and monitoring Introduction of leverage ratio Even more rigorous data requirements To implement these features banks need to embark on a journey replete with challenges. These can be categorized into three key areas: Data, Models and Compliance. Data Challenges Data quality - All standard dimensions of Data Quality (DQ) have to be demonstrated.  Manual approaches are now considered too cumbersome and automation has become the norm. Data lineage - Data lineage has to be documented and demonstrated.  The PPT / Excel approach to documentation is being replaced by metadata tools.  Data lineage has become dynamic due to a variety of factors, making static documentation out-dated quickly.  Data dictionaries - A strong and clean business glossary is needed with proper identification of business owners for the data.  Data integrity - A strong, scalable architecture with work flow tools helps demonstrate data integrity.  Manual touch points have to be minimized.   Data relevance/coverage - Data must be relevant to all portfolios and storage devices must allow for sufficient data retention.  Coverage of both on and off balance sheet exposures is critical.   Model Challenges Model development - Requires highly trained resources with both quantitative and subject matter expertise. Model validation - All Basel models need to be validated. This requires additional resources with skills that may not be readily available in the marketplace.  Model documentation - All models need to be adequately documented.  Creation of document templates and model development processes/procedures is key. Risk and finance integration - This integration is necessary for Basel as the Allowance for Loan and Lease Losses (ALLL) is calculated by Finance, yet Expected Loss (EL) is calculated by Risk Management – and they need to somehow be equal.  This is tricky at best from an implementation perspective.  Compliance Challenges Rules interpretation - Some Basel III requirements leave room for interpretation.  A misinterpretation of regulations can lead to delays in Basel compliance and undesired reprimands from supervisory authorities. Gap identification and remediation - Internal identification and remediation of gaps ensures smoother Basel compliance and audit processes.  However business lines are challenged by the competing priorities which arise from regulatory compliance and business as usual work.  Qualification readiness - Providing internal and external auditors with robust evidence of a thorough examination of the readiness to proceed to parallel run and Basel qualification  In light of new regulations like Basel III and local variations such as the Dodd Frank Act (DFA) and Comprehensive Capital Analysis and Review (CCAR) in the US, banks are now forced to ask themselves many difficult questions.  For example, executives must consider: How will Basel III play into their Risk Appetite? How will they create project plans for Basel III when they haven’t yet finished implementing Basel II? How will new regulations impact capital structure including profitability and capital distributions to shareholders? After all, new regulations often lead to diminished profitability as well as an assortment of implementation problems as we discussed earlier in this note.  However, by requiring banks to focus on premium growth, regulators increase the potential for long-term profitability and sustainability.  And a more stable banking system: Increases consumer confidence which in turn supports banking activity  Ensures that adequate funding is available for individuals and companies Puts regulators at ease, allowing bankers to focus on banking Stability is intended to bring long-term profitability to banks.  Therefore, it is important that every banking institution takes the steps necessary to properly manage, monitor and disclose its risks.  This can be done with the assistance and oversight of an independent regulatory authority.  A spectrum of banks exist today wherein some continue to debate and negotiate with regulators over the implementation of new requirements, while others are simply choosing to embrace them for the benefits I highlighted above. Do share with me how your institution is coping with and embracing these new regulations within your bank. Dr. Varun Agarwal is a Principal in the Banking Practice for Capgemini Financial Services.  He has over 19 years experience in areas that span from enterprise risk management, credit, market, and to country risk management; financial modeling and valuation; and international financial markets research and analyses.

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  • Mass Metadata Updates with Folders

    - by Kyle Hatlestad
    With the release of WebCenter Content PS5, a new folder architecture called 'Framework Folders' was introduced.  This is meant to replace the folder architecture of 'Folders_g'.  While the concepts of a folder structure and access to those folders through Desktop Integration Suite remain the same, the underlying architecture of the component has been completely rewritten.  One of the main goals of the new folders is to scale better at large volumes and remove the limitations of 1000 content items or sub-folders within a folder.  Along with the new architecture, it has a new look and a few additional features have been added.  One of those features are Query Folders.  These are folders that are populated simply by a query rather then literally putting items within the folders.  This is something that the Library has provided, but it always took an administrator to define them through the Web Layout Editor.  Now users can quickly define query folders anywhere within the standard folder hierarchy. [ Read More ]

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  • Using the OAM Mobile & Social SDK to secure native mobile apps - Part 2 : OAM Mobile & Social Server configuration

    - by kanishkmahajan
    Objective  In the second part of this blog post I'll now cover configuration of OAM to secure our sample native apps developed using the iOS SDK. First, here are some key server side concepts: Application Profiles: An application profile is a logical representation of your application within OAM server. It could be a web (html/javascript) or native (iOS or Android) application. Applications may have different requirements for AuthN/AuthZ, and therefore each application that interacts with OAM Mobile & Social REST services must be uniquely defined. Service Providers: Service providers represent the back end services that are accessed by applications. With OAM Mobile & Social these services are in the areas of authentication, authorization and user profile access. A Service Provider then defines a type or class of service for authentication, authorization or user profiles. For example, the JWTAuthentication provider performs authentication and returns JWT (JSON Web Tokens) to the application. In contrast, the OAMAuthentication also provides authentication but uses OAM SSO tokens Service Profiles:  A Service Profile is a logical envelope that defines a service endpoint URL for a service provider for the OAM Mobile & Social Service. You can create multiple service profiles for a service provider to define token capabilities and service endpoints. Each service provider instance requires atleast one corresponding service profile.The  OAM Mobile & Social Service includes a pre-configured service profile for each pre-configured service provider. Service Domains: Service domains bind together application profiles and service profiles with an optional security handler. So now let's configure the OAM server. Additional details are in the OAM Documentation and this post simply provides an outline of configuration tasks required to configure OAM for securing native apps.  Configuration  Create The Application Profile Log on to the Oracle Access Management console and from System Configuration -> Mobile and Social -> Mobile Services, select "Create" under Application Profiles. You would do this  step twice - once for each of the native apps - AvitekInventory and AvitekScheduler. Enter the parameters for the new Application profile: Name:  The application name. In this example we use 'InventoryApp' for the AvitekInventory app and 'SchedulerApp' for the AvitekScheduler app. The application name configured here must match the application name in the settings for the deployed iOS application. BaseSecret: Enter a password here. This does not need to match any existing password. It is used as an encryption key between the client and the OAM server.  Mobile Configuration: Enable this checkbox for any mobile applications. This enables the SDK to collect and send Mobile specific attributes to the OAM server.  Webview: Controls the type of browser that the iOS application will use. The embedded browser (default) will render the browser within the application. External will use the system standalone browser. External can sometimes be preferable for debugging URLScheme: The URL scheme associated with the iOS apps that is also used as a custom URL scheme to register O/S handlers that will take control when OAM transfers control to device. For the AvitekInventory and the AvitekScheduler apps I used osa:// and client:// respectively. You set this scheme in Xcode while developing your iOS Apps under Info->URL Types.  Bundle Identifier : The fully qualified name of your iOS application. You typically set this when you create a new Xcode project or under General->Identity in Xcode. For the AvitekInventory and AvitekScheduler apps these were com.us.oracle.AvitekInventory and com.us.oracle.AvitekScheduler respectively.  Create The Service Domain Select create under Service domains. Create a name for your domain (AvitekDomain is what I've used). The name configured must match the service domain set in the iOS application settings. Under "Application Profile Selection" click the browse button. Choose the application profiles that you created in the previous step one by one. Set the InventoryApp as the SSO agent (with an automatic priority of 1) and the SchedulerApp as the SSO client. This associates these applications with this service domain and configures them in a 'circle of trust'.  Advance to the next page of the wizard to configure the services for this domain. For this example we will use the following services:  Authentication:   This will use the JWT (JSON Web Token) format authentication provider. The iOS application upon successful authentication will receive a signed JWT token from OAM Mobile & Social service. This token will be used in subsequent calls to OAM. Use 'MobileOAMAuthentication' here. Authorization:  The authorization provider. The SDK makes calls to this provider endpoint to obtain authorization decisions on resource requests. Use 'OAMAuthorization' here. User Profile Service:  This is the service that provides user profile services (attribute lookup, attribute modification). It can be any directory configured as a data source in OAM.  And that's it! We're done configuring our native apps. In the next section, let's look at some additional features that were mentioned in the earlier post that are automated by the SDK for the app developer i.e. these are areas that require no additional coding by the app developer when developing with the SDK as they only require server side configuration: Additional Configuration  Offline Authentication Select this option in the service domain configuration to allow users to log in and authenticate to the application locally. Clear the box to block users from authenticating locally. Strong Authentication By simply selecting the OAAMSecurityHandlerPlugin while configuring mobile related Service Domains, the OAM Mobile&Social service allows sophisticated device and client application registration logic as well as the advanced risk and fraud analysis logic found in OAAM to be applied to mobile authentication. Let's look at some scenarios where the OAAMSecurityHandlerPlugin gets used. First, when we configure OAM and OAAM to integrate together using the TAP scheme, then that integration kicks off by selecting the OAAMSecurityHandlerPlugin in the mobile service domain. This is how the mobile device is now prompted for KBA,OTP etc depending on the TAP scheme integration and the OAM users registered in the OAAM database. Second, when we configured the service domain, there were claim attributes there that are already pre-configured in OAM Mobile&Social service and we simply accepted the default values- these are the set of attributes that will be fetched from the device and passed to the server during registration/authentication as device profile attributes. When a mobile application requests a token through the Mobile Client SDK, the SDK logic will send the Device Profile attributes as a part of an HTTP request. This set of Device Profile attributes enhances security by creating an audit trail for devices that assists device identification. When the OAAM Security Plug-in is used, a particular combination of Device Profile attribute values is treated as a device finger print, known as the Digital Finger Print in the OAAM Administration Console. Each finger print is assigned a unique fingerprint number. Each OAAM session is associated with a finger print and the finger print makes it possible to log (and audit) the devices that are performing authentication and token acquisition. Finally, if the jail broken option is selected while configuring an application profile, the SDK detects a device is jail broken based on configured policy and if the OAAM handler is configured the plug-in can allow or block access to client device depending on the OAAM policy as well as detect blacklisted, lost or stolen devices and send a wipeout command that deletes all the mobile &social relevant data and blocks the device from future access. 1024x768 Social Logins Finally, let's complete this post by adding configuration to configure social logins for mobile applications. Although the Avitek sample apps do not demonstrate social logins this would be an ideal exercise for you based on the sample code provided in the earlier post. I'll cover the server side configuration here (with Facebook as an example) and you can retrofit the code to accommodate social logins by following the steps outlined in "Invoking Authentication Services" and add code in LoginViewController and maybe create a new delegate - AvitekRPDelegate based on the description in the previous post. So, here all you will need to do is configure an application profile for social login, configure a new service domain that uses the social login application profile, register the app on Facebook and finally configure the Facebook OAuth provider in OAM with those settings. Navigate to Mobile and Social, click on "Internet Identity Services" and create a new application profile. Here are the relevant parameters for the new application profile (-also we're not registering the social user in OAM with this configuration below, however that is a key feature as well): Name:  The application name. This must match the name of the of mobile application profile created for your application under Mobile Services. We used InventoryApp for this example. SharedSecret: Enter a password here. This does not need to match any existing password. It is used as an encryption key between the client and the OAM Mobile and Social service.  Mobile Application Return URL: After the Relying Party (social) login, the OAM Mobile & Social service will redirect to the iOS application using this URI. This is defined under Info->URL type and we used 'osa', so we define this here as 'osa://' Login Type: Choose to allow only internet identity authentication for this exercise. Authentication Service Endpoint : Make sure that /internetidentityauthentication is selected. Login to http://developers.facebook.com using your Facebook account and click on Apps and register the app as InventoryApp. Note that the consumer key and API secret gets generated automatically by the Facebook OAuth server. Navigate back to OAM and under Mobile and Social, click on "Internet Identity Services" and edit the Facebook OAuth Provider. Add the consumer key and API secret from the Facebook developers site to the Facebook OAuth Provider: Navigate to Mobile Services. Click on New to create a new service domain. In this example we call the domain "AvitekDomainRP". The type should be 'Mobile Application' and the application credential type 'User Token'. Add the application "InventoryApp" to the domain. Advance the next page of the wizard. Select the  default service profiles but ensure that the Authentication Service is set to 'InternetIdentityAuthentication'. Finish the creation of the service domain.

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  • Sales & Operations Planning in the Cloud (Value Chain Planning) with JD Edwards

    - by Hartmut Wiese
    AVATA, a US based Oracle Partner with the EMEA Headquarter in Germany is offering a pre-integrated, cloud based integration with JD Edwards. It is a Sales & Operations Planning hub that enables companies to seamlessly plan across the entire organization via a dynamic, continuous and collaborative web-based Sales and Operations Planning process. There is a datasheet uploaded to the EMEA JD Edwards Partner Community workspace here which explains options and benefits and has contact details included as well. You need to be a member of this Community to access the workspace. Please register here.

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  • EL 3.0 Public Review - JSR 341 and Java EE 7 Moving Along

    - by arungupta
    Following closely on the lines of EL 3.0 Early Draft, the specification is now available for a Public Review. The JCP2 Process Document defines different stages of the specifications. This review period closes Jul 30, 2012. Some of the main goals of the JSR are to separate ELContext into parsing and evaluation contexts, adding operators like equality, string concatenation, etc, and integration with CDI. The section A.7 of the specification highlights the difference between Early Draft and Public Review. Download the Public Review and and follow the updates at el-spec.java.net. For more information about EL 3.0 (JSR 341), check out the JSR project on java.net. The archives of EG discussion are available at jsr341-experts and you can subscribe to the users@el-spec and other aliases on the Mailing Lists page.

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  • RESTful Java on Steroids (Parleys, Podcast, ...)

    - by alexismp
    As reported previously here, the JAX-RS 2.0 (JSR 339) expert group is making good progress. If you're interested in what the future holds for RESTful Java web services, you can now watch Marek's Devoxx presentation or listen to him in the latest Java Spotlight Podcast (#74). Marek discusses the new client API, filters/handlers, BeanValidation integration, Hypermedia support (HATEOAS), server-side async processing and more. With JSR 339's Early Draft Review 2 currently out, another draft review is planned for April, the public review should be available in June while the final draft is currently scheduled for the end of the summer. In short, expect completion sometime before the end of 2012.

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  • Tab Sweep: HTML5 Attributes, MDB, JasperReports, Delphi, Security, JDBCRealm, Joomla, ...

    - by arungupta
    Recent Tips and News on Java, Java EE 6, GlassFish & more : • JMS and MDB in Glassfish for 20 minutes (nik_code) • Installing Java EE 6 SDK with Glassfish on a headless system (jvmhost) • JSF + JPA + JasperReports (iReport) Part 2 (Rama krishnnan E P) • Serving Static Content on WebLogic and GlassFish (cdivilly) • Whats the problem with JSF? A rant on wrong marketing arguments (Über Thomas Asel) • JPA 2.1 will support CDI Injection in EntityListener - in Java EE 7 (Craig Ringer) • Java Delphi integration with Glassfish JMS OpenMQ (J4SOFT) • Java EE Security using JDBCRealm Part1 (acoustic091409) • Adding HTML5 attributes to standard JSF components (Bauke Scholtz) • Configuring SAS 9.1 to Use Java 5 or above on Windows (Java EE Tips) • Inject Java Properties in Java EE Using CDI (Piotr Nowicki) • NoClassDefFoundError in Java EE Applications - Part 2 (Java Code Geeks) • NoClassDefFoundError in Java EE Applications - Part 1 (Java Code Geeks) • EJB 3 application in Glassfish 3x (Anirban Chowdhury) • How To Install Mobile Server 11G With GlassFish Server 3.1 (Oracle Support) • Joomla on GlassFish (Survivant)

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  • can't run sqldeveloper on Ubuntu

    - by nazar_art
    I tried to install sqldeveloper by following way: Download SQL Developer from Oracle website (I chose Other Platforms download). Extract file to /opt: sudo unzip sqldeveloper-*-no-jre.zip -d /opt/ sudo chmod +x /opt/sqldeveloper/sqldeveloper.sh Linking over an in-path launcher for Oracle SQL Developer: sudo ln -s /opt/sqldeveloper/sqldeveloper.sh /usr/local/bin/sqldeveloper Edit /usr/local/bin/sqldeveloper.sh replace it's content to: #!/bin/bash cd /opt/sqldeveloper/sqldeveloper/bin ./sqldeveloper "$@" Run SQL Developer: sqldeveloper But it shows next output: nazar@lelyak-desktop:/opt/sqldeveloper? ./sqldeveloper.sh Oracle SQL Developer Copyright (c) 1997, 2014, Oracle and/or its affiliates. All rights reserved. LOAD TIME : 401# # A fatal error has been detected by the Java Runtime Environment: # # SIGSEGV (0xb) at pc=0x00007f3b2dcacbe0, pid=20351, tid=139892273444608 # # JRE version: Java(TM) SE Runtime Environment (7.0_65-b17) (build 1.7.0_65-b17) # Java VM: Java HotSpot(TM) 64-Bit Server VM (24.65-b04 mixed mode linux-amd64 compressed oops) # Problematic frame: # C 0x00007f3b2dcacbe0 # # Core dump written. Default location: /opt/sqldeveloper/sqldeveloper/bin/core or core.20351 # # An error report file with more information is saved as: # /tmp/hs_err_pid20351.log # # If you would like to submit a bug report, please visit: # http://bugreport.sun.com/bugreport/crash.jsp # /opt/sqldeveloper/sqldeveloper/bin/../../ide/bin/launcher.sh: line 1193: 20351 Aborted (core dumped) ${JAVA} "${APP_VM_OPTS[@]}" ${APP_ENV_VARS} -classpath ${APP_CLASSPATH} ${APP_MAIN_CLASS} "${APP_APP_OPTS[@]}" 134 nazar@lelyak-desktop:/opt/sqldeveloper? java -version java version "1.7.0_65" Java(TM) SE Runtime Environment (build 1.7.0_65-b17) Java HotSpot(TM) 64-Bit Server VM (build 24.65-b04, mixed mode) Here is content of /tmp/hs_err_pid20351.log How to solve this trouble?

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  • Compute the AES-encryption key given the plaintext and its ciphertext?

    - by Null Pointers etc.
    I'm tasked with creating database tables in Oracle which contain encrypted strings (i.e., the columns are RAW). The strings are encrypted by the application (using AES, 128-bit key) and stored in Oracle, then later retrieved from Oracle and decrypted (i.e., Oracle itself never sees the unencrypted strings). I've come across this one column that will be one of two strings. I'm worried that someone will notice and presumably figure out what those two values to figure out the AES key. For example, if someone sees that the column is either Ciphertext #1 or #2: Ciphertext #1: BF,4F,8B,FE, 60,D8,33,56, 1B,F2,35,72, 49,20,DE,C6. Ciphertext #2: BC,E8,54,BD, F4,B3,36,3B, DD,70,76,45, 29,28,50,07. and knows the corresponding Plaintexts: Plaintext #1 ("Detroit"): 44,00,65,00, 74,00,72,00, 6F,00,69,00, 74,00,00,00. Plaintext #2 ("Chicago"): 43,00,68,00, 69,00,63,00, 61,00,67,00, 6F,00,00,00. can he deduce that the encryption key is "Buffalo"? 42,00,75,00, 66,00,66,00, 61,00,6C,00, 6F,00,00,00. I'm thinking that there should be only one 128-bit key that could convert Plaintext #1 to Ciphertext #1. Does this mean I should go to a 192-bit or 256-bit key instead, or find some other solution? (As an aside, here are two other ciphertexts for the same plaintexts but with a different key.) Ciphertext #1 A ("Detroit"): E4,28,29,E3, 6E,C2,64,FA, A1,F4,F4,96, FC,18,4A,C5. Ciphertext #2 A ("Chicago"): EA,87,30,F0, AC,44,5D,ED, FD,EB,A8,79, 83,59,53,B7.

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  • Get Your Workshop Hands On!

    - by Justin Kestelyn
    Now that 2010 is behind us, that means a fresh set of Developer Day workshops (still free, always free) are ahead of us! Developer Day workshops are free, hands-on workshops that give you the software and skills to tame that learning curve and reach the next level in your technical knowledge. We have a range of entrees on the menu, including Java Development, Database Application Development, Fusion Development (Oracle ADF), and more. Most of these workshops let you walk away with a fully functional, VirtualBox-based software appliance that you can use for continued learning. Here's a short list of workshops for which you can register right now: - Java: Boston, March 8- Database App Development: Dallas, March 9- SOA Development: Reston, March 9- Data Integration: Seattle, March 15 + others planned for Toronto, Philadelphia, Shanghai, Perth, Istanbul, and many other cities in 2011! See this URL for more workshop info as it becomes available.

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  • Jersey 1.8 - Another GlassFish 3.1.1 component is ready

    - by alexismp
    We now have a new release of the JAX-RS 1.1 reference implementation - Jersey 1.8 is just out! Thisbug-fix release follows the EclipseLink 2.3 release from last week (as part of the Eclipse Indigo train release) and other components such as Woodstox 4.1.1 and Weld 1.1.1 which have already been released and integrated. To get started with Jersey 1.8, begin here and don't forget to visit the Jersey Wiki pages. You can also grab a nightly build of GlassFish 3.1.1 or wait for the next promoted build (#10) due out in a few days. As it currently stands for GlassFish 3.1.1, we have integration of the final bits for Metro 2.1.1 (currently at 2.1.1b7), Mojarra 2.1.3 (currently at 2.1.3b1), and MQ 4.5.1 (currently at 4.5.1b3) still ahead of us.

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  • NetBeans 7.3 Beta2 is Out!

    - by Ondrej Brejla
    NetBeans 7.3 Beta2 was published today. You can download it. You could read about the PHP features added to the NetBeans 7.3 release here on the blog, but the main features added or improved are: Parsers for Namespaced Annotations (Symfony 2, Doctrine 2, etc.), Basic Composer Integration (Dependency Manager for PHP), Twig Code Completion (with documentation), Smarty Braces Matching for Related Tags, Smarty Parser Errors of Unmatched Tags. As obvious you can help us to test the build. Just try it and if you find an issue / error, please report it. Thanks for your help.

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  • GeoToolkit Demo Embedded in an Application Framework via Maven

    - by Geertjan
    As a follow on to yesterday's blog entry, here's the equivalent starter application for GeoToolkit (also known as Geotk) on the NetBeans Platform, which ends up looking like this: The above is a border.shp file I found on-line, while here's a USA states shape file rendered in the application: Note that the navigation bar is also included, though that could later be migrated into the menu bar of the NetBeans Platform.  Download the Maven based NetBeans Platform application with GeoToolkit integration here: http://java.net/projects/nb-api-samples/sources/api-samples/show/versions/7.3/tutorials/geospatial/geotoolkit/MyGeospatialSystem It was quite tricky getting this sample together, parts of it, especially the installer, which creates the database, comes from the Puzzle GIS project, while the files come from on-line locations, with the JAI-related dependencies providing problems of their own. But it's definitely a starting point and you now have the basic Maven structure needed for getting started with GeoToolkit in the context of all the services and components provided by the NetBeans Platform.  Many thanks to Johann Sorel for his patience and help. 

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  • Project Jigsaw: Late for the train: The Q&A

    - by Mark Reinhold
    I recently proposed, to the Java community in general and to the SE 8 (JSR 337) Expert Group in particular, to defer Project Jigsaw from Java 8 to Java 9. I also proposed to aim explicitly for a regular two-year release cycle going forward. Herewith a summary of the key questions I’ve seen in reaction to these proposals, along with answers. Making the decision Q Has the Java SE 8 Expert Group decided whether to defer the addition of a module system and the modularization of the Platform to Java SE 9? A No, it has not yet decided. Q By when do you expect the EG to make this decision? A In the next month or so. Q How can I make sure my voice is heard? A The EG will consider all relevant input from the wider community. If you have a prominent blog, column, or other communication channel then there’s a good chance that we’ve already seen your opinion. If not, you’re welcome to send it to the Java SE 8 Comments List, which is the EG’s official feedback channel. Q What’s the overall tone of the feedback you’ve received? A The feedback has been about evenly divided as to whether Java 8 should be delayed for Jigsaw, Jigsaw should be deferred to Java 9, or some other, usually less-realistic, option should be taken. Project Jigsaw Q Why is Project Jigsaw taking so long? A Project Jigsaw started at Sun, way back in August 2008. Like many efforts during the final years of Sun, it was not well staffed. Jigsaw initially ran on a shoestring, with just a handful of mostly part-time engineers, so progress was slow. During the integration of Sun into Oracle all work on Jigsaw was halted for a time, but it was eventually resumed after a thorough consideration of the alternatives. Project Jigsaw was really only fully staffed about a year ago, around the time that Java 7 shipped. We’ve added a few more engineers to the team since then, but that can’t make up for the inadequate initial staffing and the time lost during the transition. Q So it’s really just a matter of staffing limitations and corporate-integration distractions? A Aside from these difficulties, the other main factor in the duration of the project is the sheer technical difficulty of modularizing the JDK. Q Why is modularizing the JDK so hard? A There are two main reasons. The first is that the JDK code base is deeply interconnected at both the API and the implementation levels, having been built over many years primarily in the style of a monolithic software system. We’ve spent considerable effort eliminating or at least simplifying as many API and implementation dependences as possible, so that both the Platform and its implementations can be presented as a coherent set of interdependent modules, but some particularly thorny cases remain. Q What’s the second reason? A We want to maintain as much compatibility with prior releases as possible, most especially for existing classpath-based applications but also, to the extent feasible, for applications composed of modules. Q Is modularizing the JDK even necessary? Can’t you just put it in one big module? A Modularizing the JDK, and more specifically modularizing the Java SE Platform, will enable standard yet flexible Java runtime configurations scaling from large servers down to small embedded devices. In the long term it will enable the convergence of Java SE with the higher-end Java ME Platforms. Q Is Project Jigsaw just about modularizing the JDK? A As originally conceived, Project Jigsaw was indeed focused primarily upon modularizing the JDK. The growing demand for a truly standard module system for the Java Platform, which could be used not just for the Platform itself but also for libraries and applications built on top of it, later motivated expanding the scope of the effort. Q As a developer, why should I care about Project Jigsaw? A The introduction of a modular Java Platform will, in the long term, fundamentally change the way that Java implementations, libraries, frameworks, tools, and applications are designed, built, and deployed. Q How much progress has Project Jigsaw made? A We’ve actually made a lot of progress. Much of the core functionality of the module system has been prototyped and works at both compile time and run time. We’ve extended the Java programming language with module declarations, worked out a structure for modular source trees and corresponding compiled-class trees, and implemented these features in javac. We’ve defined an efficient module-file format, extended the JVM to bootstrap a modular JRE, and designed and implemented a preliminary API. We’ve used the module system to make a good first cut at dividing the JDK and the Java SE API into a coherent set of modules. Among other things, we’re currently working to retrofit the java.util.ServiceLoader API to support modular services. Q I want to help! How can I get involved? A Check out the project page, read the draft requirements and design overview documents, download the latest prototype build, and play with it. You can tell us what you think, and follow the rest of our work in real time, on the jigsaw-dev list. The Java Platform Module System JSR Q What’s the relationship between Project Jigsaw and the eventual Java Platform Module System JSR? A At a high level, Project Jigsaw has two phases. In the first phase we’re exploring an approach to modularity that’s markedly different from that of existing Java modularity solutions. We’ve assumed that we can change the Java programming language, the virtual machine, and the APIs. Doing so enables a design which can strongly enforce module boundaries in all program phases, from compilation to deployment to execution. That, in turn, leads to better usability, diagnosability, security, and performance. The ultimate goal of the first phase is produce a working prototype which can inform the work of the Module-System JSR EG. Q What will happen in the second phase of Project Jigsaw? A The second phase will produce the reference implementation of the specification created by the Module-System JSR EG. The EG might ultimately choose an entirely different approach than the one we’re exploring now. If and when that happens then Project Jigsaw will change course as necessary, but either way I think that the end result will be better for having been informed by our current work. Maven & OSGi Q Why not just use Maven? A Maven is a software project management and comprehension tool. As such it can be seen as a kind of build-time module system but, by its nature, it does nothing to support modularity at run time. Q Why not just adopt OSGi? A OSGi is a rich dynamic component system which includes not just a module system but also a life-cycle model and a dynamic service registry. The latter two facilities are useful to some kinds of sophisticated applications, but I don’t think they’re of wide enough interest to be standardized as part of the Java SE Platform. Q Okay, then why not just adopt the module layer of OSGi? A The OSGi module layer is not operative at compile time; it only addresses modularity during packaging, deployment, and execution. As it stands, moreover, it’s useful for library and application modules but, since it’s built strictly on top of the Java SE Platform, it can’t be used to modularize the Platform itself. Q If Maven addresses modularity at build time, and the OSGi module layer addresses modularity during deployment and at run time, then why not just use the two together, as many developers already do? A The combination of Maven and OSGi is certainly very useful in practice today. These systems have, however, been built on top of the existing Java platform; they have not been able to change the platform itself. This means, among other things, that module boundaries are weakly enforced, if at all, which makes it difficult to diagnose configuration errors and impossible to run untrusted code securely. The prototype Jigsaw module system, by contrast, aims to define a platform-level solution which extends both the language and the JVM in order to enforce module boundaries strongly and uniformly in all program phases. Q If the EG chooses an approach like the one currently being taken in the Jigsaw prototype, will Maven and OSGi be made obsolete? A No, not at all! No matter what approach is taken, to ensure wide adoption it’s essential that the standard Java Platform Module System interact well with Maven. Applications that depend upon the sophisticated features of OSGi will no doubt continue to use OSGi, so it’s critical that implementations of OSGi be able to run on top of the Java module system and, if suitably modified, support OSGi bundles that depend upon Java modules. Ideas for how to do that are currently being explored in Project Penrose. Java 8 & Java 9 Q Without Jigsaw, won’t Java 8 be a pretty boring release? A No, far from it! It’s still slated to include the widely-anticipated Project Lambda (JSR 335), work on which has been going very well, along with the new Date/Time API (JSR 310), Type Annotations (JSR 308), and a set of smaller features already in progress. Q Won’t deferring Jigsaw to Java 9 delay the eventual convergence of the higher-end Java ME Platforms with Java SE? A It will slow that transition, but it will not stop it. To allow progress toward that convergence to be made with Java 8 I’ve suggested to the Java SE 8 EG that we consider specifying a small number of Profiles which would allow compact configurations of the SE Platform to be built and deployed. Q If Jigsaw is deferred to Java 9, would the Oracle engineers currently working on it be reassigned to other Java 8 features and then return to working on Jigsaw again after Java 8 ships? A No, these engineers would continue to work primarily on Jigsaw from now until Java 9 ships. Q Why not drop Lambda and finish Jigsaw instead? A Even if the engineers currently working on Lambda could instantly switch over to Jigsaw and immediately become productive—which of course they can’t—there are less than nine months remaining in the Java 8 schedule for work on major features. That’s just not enough time for the broad review, testing, and feedback which such a fundamental change to the Java Platform requires. Q Why not ship the module system in Java 8, and then modularize the platform in Java 9? A If we deliver a module system in one release but don’t use it to modularize the JDK until some later release then we run a big risk of getting something fundamentally wrong. If that happens then we’d have to fix it in the later release, and fixing fundamental design flaws after the fact almost always leads to a poor end result. Q Why not ship Jigsaw in an 8.5 release, less than two years after 8? Or why not just ship a new release every year, rather than every other year? A Many more developers work on the JDK today than a couple of years ago, both because Oracle has dramatically increased its own investment and because other organizations and individuals have joined the OpenJDK Community. Collectively we don’t, however, have the bandwidth required to ship and then provide long-term support for a big JDK release more frequently than about every other year. Q What’s the feedback been on the two-year release-cycle proposal? A For just about every comment that we should release more frequently, so that new features are available sooner, there’s been another asking for an even slower release cycle so that large teams of enterprise developers who ship mission-critical applications have a chance to migrate at a comfortable pace.

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  • 12c - Invisible Columns...

    - by noreply(at)blogger.com (Thomas Kyte)
    Remember when 11g first came out and we had "invisible indexes"?  It seemed like a confusing feature - indexes that would be maintained by modifications (hence slowing them down), but would not be used by queries (hence never speeding them up).  But - after you looked at them a while, you could see how they can be useful.  For example - to add an index in a running production system, an index used by the next version of the code to be introduced later that week - but not tested against the queries in version one of the application in place now.  We all know that when you add an index - one of three things can happen - a given query will go much faster, it won't affect a given query at all, or... It will make some untested query go much much slower than it used to.  So - invisible indexes allowed us to modify the schema in a 'safe' manner - hiding the change until we were ready for it.Invisible columns accomplish the same thing - the ability to introduce a change while minimizing any negative side effects of that change.  Normally when you add a column to a table - any program with a SELECT * would start seeing that column, and programs with an INSERT INTO T VALUES (...) would pretty much immediately break (an INSERT without a list of columns in it).  Now we can add a column to a table in an invisible fashion, the column will not show up in a DESCRIBE command in SQL*Plus, it will not be returned with a SELECT *, it will not be considered in an INSERT INTO T VALUES statement.  It can be accessed by any query that asks for it, it can be populated by an INSERT statement that references it, but you won't see it otherwise.For example, let's start with a simple two column table:ops$tkyte%ORA12CR1> create table t  2  ( x int,  3    y int  4  )  5  /Table created.ops$tkyte%ORA12CR1> insert into t values ( 1, 2 );1 row created.Now, we will add an invisible column to it:ops$tkyte%ORA12CR1> alter table t add                     ( z int INVISIBLE );Table altered.Notice that a DESCRIBE will not show us this column:ops$tkyte%ORA12CR1> desc t Name              Null?    Type ----------------- -------- ------------ X                          NUMBER(38) Y                          NUMBER(38)and existing inserts are unaffected by it:ops$tkyte%ORA12CR1> insert into t values ( 3, 4 );1 row created.A SELECT * won't see it either:ops$tkyte%ORA12CR1> select * from t;         X          Y---------- ----------         1          2         3          4But we have full access to it (in well written programs! The ones that use a column list in the insert and select - never relying on "defaults":ops$tkyte%ORA12CR1> insert into t (x,y,z)                         values ( 5,6,7 );1 row created.ops$tkyte%ORA12CR1> select x, y, z from t;         X          Y          Z---------- ---------- ----------         1          2         3          4         5          6          7and when we are sure that we are ready to go with this column, we can just modify it:ops$tkyte%ORA12CR1> alter table t modify z visible;Table altered.ops$tkyte%ORA12CR1> select * from t;         X          Y          Z---------- ---------- ----------         1          2         3          4         5          6          7I will say that a better approach to this - one that is available in 11gR2 and above - would be to use editioning views (part of Edition Based Redefinition - EBR ).  I would rather use EBR over this approach, but in an environment where EBR is not being used, or the editioning views are not in place, this will achieve much the same.Read these for information on EBR:http://www.oracle.com/technetwork/issue-archive/2010/10-jan/o10asktom-172777.htmlhttp://www.oracle.com/technetwork/issue-archive/2010/10-mar/o20asktom-098897.htmlhttp://www.oracle.com/technetwork/issue-archive/2010/10-may/o30asktom-082672.html

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  • APEX-Region "Karte" mit eigenen Karten ausstatten

    - by carstenczarski
    Seit der Version 4.0 bietet APEX den Diagrammtyp "Karte" an; dieser erlaubt die sehr einfache Integration von Karten in eine APEX-Anwendung. Die Darstellung der Karten basiert, wie für alle Diagrammtypen, auf AnyChart. APEX bietet zwar eine Vielfalt von verfügbaren Karten an, in der Praxis dürften diese jedoch selten ausreichen - zu verschieden sind die Anforderungen; für Deutschland werden nur zwei Karten angeboten. Oft ist es also nötig, den APEX-Lieferumfang um eigene Karten zu erweitern. Wie das geht, beschreibt unser aktueller Community-Tipp.

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