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  • How to make sure you server NIC performance is at best on Windows?

    - by Bobb
    I realised that I followed some obscure paper on setting NICs on Windows for too long. It might be outdated with new hardware released in past couple of years and with W2008R2. I read a bit about offloading and RSS settings on Windows and I realiased that it is very much circumstantial. Noone can really say - enable that and disable this. etc. So what I really want is for my next server try and setup testing environment and measure how my particular application will behave with different settings. The target is going to be latency of TCP primarily. Please note I am talking about latency inside the box. Are there precision tools for Windows to measure latency (down to microseconds)? P.S. I know this is not easy question. Windows time drift is awful problem for any precision test but still I am sure I am not the fist person to need that... Please share your experience

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  • Microphone array support in Windows. Info on performance and compatible hardware?

    - by exinocactus
    It is officially claimed by Microsoft (Audio Device Technologies for Windows), that Windows Vista has an integrated system-level support of microphone arrays for improved sound capturing by isolating a sound source in target direction and rejecting ambient noise and reverberation. In more technical terms, an implementation of an adaptive beamformer. Theoretically, microphone arrays with 2-4 mics can substantially improve SNR under some conditions like speaker in front of the laptop in noisy environment (airport, cafe). Surprisingly, though, I find very little information about commercially-available products supporting these new features. I mean products like portable usb micropone arrays or laptops or flat screens with integrated mic arrays. I could only find info about two laptop models having "noise cancelling digital array microphone". These are Dell Latitude and Eee PC 1008P-KR. Now my questions: Do you have any experience with the Windows beamformer implementation? For instance, in the above mentioned laptops. How well does it work? Are there any tests results available in the net or in print (papers?)? Do you know about other microphone array hardware? What could be the reason why mic array technology didn't get sucess Is there mic arrays support in 'Windows 7'?

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  • Anyone tried boosting Windows performance by putting Swap File on a Flash drive?

    - by Clay Nichols
    Windows Vista introduced ReadyBoost which lets you use a Flash drive as a third (after RAM and HD) type of memory. It occurred to me that I could boost peformance on an old PC here w/ Win XP (32 bit, max'd at 4GB RAM) by putting it's swap file (page file) on a flash drive. (Now, before anyone comments: apparently Flash drives (10-30MB/s transfer rates) are slower than HDD (100+ MB/s) (I'm asking that as a separate question on this forum).

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  • How does the performance of pure Nginx compare to cpNginx?

    - by jb510
    There is now a Cpanel plugin to fairly easily setup Nginx as a reverse proxy on a Cpanel/Apache server. I've been simultaneously interested in setting up my first unmanaged VPS and my first Nginx server and as a masochist figured why not combine the two. I'm wondering however if it's worth setting up a pure Nginx server vs trying out cpNginx on Apache? My goal is solely to host WordPress sites and while what I've read raves about Nginx's is exceptional ability serving static at least as a reverse proxy, I am unclear if there is substantial benefit to running a pure nginx with eAccelorator over cpNginx on Apache for dynamic sites? Regardless I'll be running W3TC on all sites to cache content, but am still interested if there are big CPU reductions running PHP scripts under pure Nginx over cpNginx?

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  • Is a memory upgrade a viable option to fix performance issues? [closed]

    - by ratchet freak
    I'm currently seeing my PC getting bogged down by Firefox 11.0 alone with only one hundred tabs open. Resulting in a memory use of over 530M , VM size of over 800M and an insane amount of page faults (easily reaching 100 million over the course of the day). The PF delta during normal operation easily reaches 7k with peaks to 15k sometimes reaching over 20k. This leads to a (real) deterioration to response time when switching, opening and closing tabs, opening menus, typing, ... My question is: Am I right in assuming that plugging in more RAM (either adding 2x1GB or replacing the existing RAM with 2x2GB or 4x1GB) will solve this problem? My specs: Windows XP Home Edition SP3 (32 bit) Intel Core Duo 2,4 GHz 2x512MB RAM 800MHz DDR2 (dual channel) 4MB unified cache 320GB HDD Intel G33 (X3100) onboard graphics (no graphics card but PCI express x16 slot is available)

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  • How can I improve the rendering performance of this old DOS application?

    - by MicTech
    I have very old DOS Application (CadSoft Eagle - PCB Designer) and I want to work with it on my workstation with Windows 7. Then I install Windows 98 and that software into VmWare Player. But that software has serious problem with redrawing screen. It's very slow in comparison with my Intel Celeron 333MHz with Windows 98. I have same problem if I try to use DOSBox on Windows XP (same Celeron 333MHz). I also trying run this application directly on Windows XP (same Celeron 333MHz) with compatibility mod set to "Windows 98", but I get "(0Dh): General Protection Fault". Can someone give me good advice how I solve that?

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  • How should oracle vbox look like in terms of Memory, CPU and Performance? [duplicate]

    - by Nicholas DiPiazza
    This question already has an answer here: Can you help me with my capacity planning? 2 answers I've got a need for a ton of VMs to simulate some realistic load testing scenarios. I've got a bunch of different host machines that differ in ram, cpu's, etc. What should my resource manager look like? Is there a standard way to know what the CPU, Memory and Disk Utilization should be given your CPUs + Memory available + Disks available? For example, I have a box: MemTotal: 50 Gb CPUs: 8 CPUs are pretty much 100% all day long. Memory is at about 60%. Swap not getting hit. Little bewildered by why the VMs, while doing the exact same test script, are showing different virtual memory consumption. Huh.

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  • Can different drive speeds and sizes be used in a hardware RAID configuration w/o affecting performance?

    - by R. Dill
    Specifically, I have a RAID 1 array configuration with two 500gb 7200rpm SATA drives mirrored as logical drive 1 (a) and two of the same mirrored as logical drive 2 (b). I'd like to add two 1tb 5400rpm drives in the same mirrored fashion as logical drive 3 (c). These drives will only serve as file storage with occasional but necessary access, and therefore, space is more important than speed. In researching whether this configuration is doable, I've been told and have read that the array will only see the smallest drive size and slowest speed. However, my understanding is that as long as the pairs themselves aren't mixed (and in this case, they aren't) that the array should view and use all drives at their actual speed and size. I'd like to be sure before purchasing the additional drives. Insight anyone?

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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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  • ASP.NET MVC & EF4 Entity Framework - Are there any performance concerns in using the entities vs retrieving only the fields i need?

    - by Ant
    Lets say we have 3 tables, Users, Products, Purchases. There is a view that needs to display the purchases made by a user. I could lookup the data required by doing: from p in DBSet<Purchases>.Include("User").Include("Product") select p; However, I am concern that this may have a performance impact because it will retrieve the full objects. Alternatively, I could select only the fields i need: from p in DBSet<Purchases>.Include("User").Include("Product") select new SimplePurchaseInfo() { UserName = p.User.name, Userid = p.User.Id, ProductName = p.Product.Name ... etc }; So my question is: Whats the best practice in doing this? == EDIT Thanks for all the replies. [QUESTION 1]: I want to know whether all views should work with flat ViewModels with very specific data for that view, or should the ViewModels contain the entity objects. Real example: User reviews Products var query = from dr in productRepository.FindAllReviews() where dr.User.UserId = 'userid' select dr; string sql = ((ObjectQuery)query).ToTraceString(); SELECT [Extent1].[ProductId] AS [ProductId], [Extent1].[Comment] AS [Comment], [Extent1].[CreatedTime] AS [CreatedTime], [Extent1].[Id] AS [Id], [Extent1].[Rating] AS [Rating], [Extent1].[UserId] AS [UserId], [Extent3].[CreatedTime] AS [CreatedTime1], [Extent3].[CreatorId] AS [CreatorId], [Extent3].[Description] AS [Description], [Extent3].[Id] AS [Id1], [Extent3].[Name] AS [Name], [Extent3].[Price] AS [Price], [Extent3].[Rating] AS [Rating1], [Extent3].[ShopId] AS [ShopId], [Extent3].[Thumbnail] AS [Thumbnail], [Extent3].[Creator_UserId] AS [Creator_UserId], [Extent4].[Comment] AS [Comment1], [Extent4].[DateCreated] AS [DateCreated], [Extent4].[DateLastActivity] AS [DateLastActivity], [Extent4].[DateLastLogin] AS [DateLastLogin], [Extent4].[DateLastPasswordChange] AS [DateLastPasswordChange], [Extent4].[Email] AS [Email], [Extent4].[Enabled] AS [Enabled], [Extent4].[PasswordHash] AS [PasswordHash], [Extent4].[PasswordSalt] AS [PasswordSalt], [Extent4].[ScreenName] AS [ScreenName], [Extent4].[Thumbnail] AS [Thumbnail1], [Extent4].[UserId] AS [UserId1], [Extent4].[UserName] AS [UserName] FROM [ProductReviews] AS [Extent1] INNER JOIN [Users] AS [Extent2] ON [Extent1].[UserId] = [Extent2].[UserId] LEFT OUTER JOIN [Products] AS [Extent3] ON [Extent1].[ProductId] = [Extent3].[Id] LEFT OUTER JOIN [Users] AS [Extent4] ON [Extent1].[UserId] = [Extent4].[UserId] WHERE N'615005822' = [Extent2].[UserId] or from d in productRepository.FindAllProducts() from dr in d.ProductReviews where dr.User.UserId == 'userid' orderby dr.CreatedTime select new ProductReviewInfo() { product = new SimpleProductInfo() { Id = d.Id, Name = d.Name, Thumbnail = d.Thumbnail, Rating = d.Rating }, Rating = dr.Rating, Comment = dr.Comment, UserId = dr.UserId, UserScreenName = dr.User.ScreenName, UserThumbnail = dr.User.Thumbnail, CreateTime = dr.CreatedTime }; SELECT [Extent1].[Id] AS [Id], [Extent1].[Name] AS [Name], [Extent1].[Thumbnail] AS [Thumbnail], [Extent1].[Rating] AS [Rating], [Extent2].[Rating] AS [Rating1], [Extent2].[Comment] AS [Comment], [Extent2].[UserId] AS [UserId], [Extent4].[ScreenName] AS [ScreenName], [Extent4].[Thumbnail] AS [Thumbnail1], [Extent2].[CreatedTime] AS [CreatedTime] FROM [Products] AS [Extent1] INNER JOIN [ProductReviews] AS [Extent2] ON [Extent1].[Id] = [Extent2].[ProductId] INNER JOIN [Users] AS [Extent3] ON [Extent2].[UserId] = [Extent3].[UserId] LEFT OUTER JOIN [Users] AS [Extent4] ON [Extent2].[UserId] = [Extent4].[UserId] WHERE N'userid' = [Extent3].[UserId] ORDER BY [Extent2].[CreatedTime] ASC [QUESTION 2]: Whats with the ugly outer joins?

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  • Xsigo and Oracle's Storage

    - by Philippe Deverchère
    Xsigo, a virtual network infrastructure provider, has recently been acquired by Oracle. Following this acquisition, one might ask ourselves why it is important to Oracle and how Oracle's storage is going to benefit on the long term from this virtualized infrastructure layer. Well, the first thing to understand is that Virtual Networking addresses both network and storage connectivity. Oracle Virtual Networking, as the Xsigo technology is now called, connects any server to any network and storage, so this is not just about connecting servers to the Internet or Intranet. It is also for a large part connecting servers to NAS and SAN storage. Connecting servers to storage has become increasingly complex in the past few years because of the strong emergence of virtualization at the Operating System level. 50% of enterprise workloads are now virtualized, up from 18% in 2009, resulting in a strong consolidation of various applications in a high density server footprint. At the same time, server I/O capability increased 8x in the last 8 years. All this has pushed IT administrators to multiply the number of I/O connections in the back-end of their physical servers, resulting in a messy and very hard to manage networking infrastructure. Here is a typical view of a rack back-end when no virtual networking is used. We consider that today: - 75% of users have ten or more Ethernet ports per server - 85% of users have two or more SAN ports per server - 58% have had to add connectivity to a server specifically for VMs - 65% consider cable reduction a priority The average is 12 or more ports per server, resulting in an extremely complex infrastructure to manage. What Oracle wants to achieve with its Oracle Virtual Networking offering is pretty simple. The objective is to eliminate the complexity through a dramatic reduction of cabling between servers and storage/networks. It is also to provide a software based management system so that any server can be connected to any network or any storage, on demand, and without physical intervention on the infrastructure. At the end of the day, the picture on the left shows what one wants to get for the back-end of customer's racks: just a couple of connections on each physical server to provide a simple, agile and fast network infrastructure for both storage and networking access. This is exactly what the Oracle Virtual Networking solution does. It transforms a complex, error-prone, difficult to manage and expensive networking infrastructure into a simple, high performance and agile solution for the data center. Practically speaking, and for the sake of simplicity, imagine that each server just hosts a minimal number of physical InfiniBand HCAs (Host Channel Adapter) with two links (for redundancy) onto the Oracle Fabric Interconnect director. Using the Oracle Fabric Manager software, you'll then be able to create virtual NICs and HBAs (called vNIC and vHBA) that will be seen by the servers as standard NICs and HBAs and associate them to networks and storage systems which are physically connected to the back-end of the director through standard Fibre Channel and Ethernet GbE/10GbE ports. In addition to this incredibly simple "at-a-click" connectivity capability, the Oracle Virtual Networking solution offers powerful features such as network isolation, Quality of Service, advanced performance monitoring and non-disruptive reconfiguration, migration and scalability of networking infrastructure. So let's go back now to our initial question: why is Oracle Virtual Networking especially important to Oracle's storage solutions? After all, one could connect any storage in the back-end of the Oracle Fabric Interconnect directors, right? The answer is pretty simple: since Oracle owns both the virtualized networking infrastructure and the storage (ZFS-SA, Pillar Axiom and tape), it is possible to imagine several ways in the future to add value when it comes to connect storage to a virtualized storage network: enhanced storage capabilities, converged management between storage and network, improved diagnostic capabilities and optimized integration resulting in higher performance and unique features/functions. Of course, all this is not going to be done overnight, and future will tell us is which evolutions come first. But there is little doubt that the integration of Xsigo within Oracle is going to create opportunities for Oracle's storage!

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  • The Growing Importance of Network Virtualization

    - by user12608550
    The Growing Importance of Network Virtualization We often focus on server virtualization when we discuss cloud computing, but just as often we neglect to consider some of the critical implications of that technology. The ability to create virtual environments (or VEs [1]) means that we can create, destroy, activate and deactivate, and more importantly, MOVE them around within the cloud infrastructure. This elasticity and mobility has profound implications for how network services are defined, managed, and used to provide cloud services. It's not just servers that benefit from virtualization, it's the network as well. Network virtualization is becoming a hot topic, and not just for discussion but for companies like Oracle and others who have recently acquired net virtualization companies [2,3]. But even before this topic became so prominent, Solaris engineers were working on technologies in Solaris 11 to virtualize network services, known as Project Crossbow [4]. And why is network virtualization so important? Because old assumptions about network devices, topology, and management must be re-examined in light of the self-service, elasticity, and resource sharing requirements of cloud computing infrastructures. Static, hierarchical network designs, and inter-system traffic flows, need to be reconsidered and quite likely re-architected to take advantage of new features like virtual NICs and switches, bandwidth control, load balancing, and traffic isolation. For example, traditional multi-tier Web services (Web server, App server, DB server) that share net traffic over Ethernet wires can now be virtualized and hosted on shared-resource systems that communicate within a larger server at system bus speeds, increasing performance and reducing wired network traffic. And virtualized traffic flows can be monitored and adjusted as needed to optimize network performance for dynamically changing cloud workloads. Additionally, as VEs come and go and move around in the cloud, static network configuration methods cannot easily accommodate the routing and addressing flexibility that VE mobility implies; virtualizing the network itself is a requirement. Oracle Solaris 11 [5] includes key network virtualization technologies needed to implement cloud computing infrastructures. It includes features for the creation and management of virtual NICs and switches, and for the allocation and control of the traffic flows among VEs [6]. Additionally it allows for both sharing and dedication of hardware components to network tasks, such as allocating specific CPUs and vNICs to VEs, and even protocol-specific management of traffic. So, have a look at your current network topology and management practices in view of evolving cloud computing technologies. And don't simply duplicate the physical architecture of servers and connections in a virtualized environment…rethink the traffic flows among VEs and how they can be optimized using Oracle Solaris 11 and other Oracle products and services. [1] I use the term "virtual environment" or VE here instead of the more commonly used "virtual machine" or VM, because not all virtualized operating system environments are full OS kernels under the control of a hypervisor…in other words, not all VEs are VMs. In particular, VEs include Oracle Solaris zones, as well as SPARC VMs (previously called LDoms), and x86-based Solaris and Linux VMs running under hypervisors such as OEL, Xen, KVM, or VMware. [2] Oracle follows VMware into network virtualization space with Xsigo purchase; http://www.mercurynews.com/business/ci_21191001/oracle-follows-vmware-into-network-virtualization-space-xsigo [3] Oracle Buys Xsigo; http://www.oracle.com/us/corporate/press/1721421 [4] Oracle Solaris 11 Networking Virtualization Technology, http://www.oracle.com/technetwork/server-storage/solaris11/technologies/networkvirtualization-312278.html [5] Oracle Solaris 11; http://www.oracle.com/us/products/servers-storage/solaris/solaris11/overview/index.html [6] For example, the Solaris 11 'dladm' command can be used to limit the bandwidth of a virtual NIC, as follows: dladm create-vnic -l net0 -p maxbw=100M vnic0

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  • Performance issues with jms and spring integration. What is wrong with the following configuration?

    - by user358448
    I have a jms producer, which generates many messages per second, which are sent to amq persistent queue and are consumed by single consumer, which needs to process them sequentially. But it seems that the producer is much faster than the consumer and i am having performance and memory problems. Messages are fetched very very slowly and the consuming seems to happen on intervals (the consumer "asks" for messages in polling fashion, which is strange?!) Basically everything happens with spring integration. Here is the configuration at the producer side. First stake messages come in stakesInMemoryChannel, from there, they are filtered throw the filteredStakesChannel and from there they are going into the jms queue (using executor so the sending will happen in separate thread) <bean id="stakesQueue" class="org.apache.activemq.command.ActiveMQQueue"> <constructor-arg name="name" value="${jms.stakes.queue.name}" /> </bean> <int:channel id="stakesInMemoryChannel" /> <int:channel id="filteredStakesChannel" > <int:dispatcher task-executor="taskExecutor"/> </int:channel> <bean id="stakeFilterService" class="cayetano.games.stake.StakeFilterService"/> <int:filter input-channel="stakesInMemoryChannel" output-channel="filteredStakesChannel" throw-exception-on-rejection="false" expression="true"/> <jms:outbound-channel-adapter channel="filteredStakesChannel" destination="stakesQueue" delivery-persistent="true" explicit-qos-enabled="true" /> <task:executor id="taskExecutor" pool-size="100" /> The other application is consuming the messages like this... The messages come in stakesInputChannel from the jms stakesQueue, after that they are routed to 2 separate channels, one persists the message and the other do some other stuff, lets call it "processing". <bean id="stakesQueue" class="org.apache.activemq.command.ActiveMQQueue"> <constructor-arg name="name" value="${jms.stakes.queue.name}" /> </bean> <jms:message-driven-channel-adapter channel="stakesInputChannel" destination="stakesQueue" acknowledge="auto" concurrent-consumers="1" max-concurrent-consumers="1" /> <int:publish-subscribe-channel id="stakesInputChannel" /> <int:channel id="persistStakesChannel" /> <int:channel id="processStakesChannel" /> <int:recipient-list-router id="customRouter" input-channel="stakesInputChannel" timeout="3000" ignore-send-failures="true" apply-sequence="true" > <int:recipient channel="persistStakesChannel"/> <int:recipient channel="processStakesChannel"/> </int:recipient-list-router> <bean id="prefetchPolicy" class="org.apache.activemq.ActiveMQPrefetchPolicy"> <property name="queuePrefetch" value="${jms.broker.prefetch.policy}" /> </bean> <bean id="connectionFactory" class="org.springframework.jms.connection.CachingConnectionFactory"> <property name="targetConnectionFactory"> <bean class="org.apache.activemq.ActiveMQConnectionFactory"> <property name="brokerURL" value="${jms.broker.url}" /> <property name="prefetchPolicy" ref="prefetchPolicy" /> <property name="optimizeAcknowledge" value="true" /> <property name="useAsyncSend" value="true" /> </bean> </property> <property name="sessionCacheSize" value="10"/> <property name="cacheProducers" value="false"/> </bean>

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  • Will these optimizations to my Ruby implementation of diff improve performance in a Rails app?

    - by grg-n-sox
    <tl;dr> In source version control diff patch generation, would it be worth it to use the optimizations listed at the very bottom of this writing (see <optimizations>) in my Ruby implementation of diff for making diff patches? </tl;dr> <introduction> I am programming something I have never done before and there might already be tools out there to do the exact thing I am programming but at this point I am having too much fun to care so I am still going to do it from scratch, even if there is a tool for this. So anyways, I am working on a Ruby on Rails app and need a certain feature. Basically I want each entry in a table of mine, let's say for example a table of video games, to have a stored chunk of text that represents a review or something of the sort for that table entry. However, I want this text to be both editable by any registered user and also keep track of different submissions in a version control system. The simplest solution I could think of is just implement a solution that keeps track of the text body and the diff patch history of different versions of the text body as objects in Ruby and then serialize it, preferably in human readable form (so I'll most likely use YAML for this) for editing if needed due to corruption by a software bug or a mistake is made by an admin doing some version editing. So at first I just tried to dive in head first into this feature to find that the problem of generating a diff patch is more difficult that I thought to do efficiently. So I did some research and came across some ideas. Some I have implemented already and some I have not. However, it all pretty much revolves around the longest common subsequence problem, as you would already know if you have already done anything with diff or diff-like features, and optimization the function that solves it. Currently I have it so it truncates the compared versions of the text body from the beginning and end until non-matching lines are found. Then it solves the problem using a comparison matrix, but instead of incrementing the value stored in a cell when it finds a matching line like in most longest common subsequence algorithms I have seen examples of, I increment when I have a non-matching line so as to calculate edit distance instead of longest common subsequence. Although as far as I can tell between the two approaches, they are essentially two sides of the same coin so either could be used to derive an answer. It then back-traces through the comparison matrix and notes when there was an incrementation and in which adjacent cell (West, Northwest, or North) to determine that line's diff entry and assumes all other lines to be unchanged. Normally I would leave it at that, but since this is going into a Rails environment and not just some stand-alone Ruby script, I started getting worried about needing to optimize at least enough so if a spammer that somehow knew how I implemented the version control system and knew my worst case scenario entry still wouldn't be able to hit the server that bad. After some searching and reading of research papers and articles through the internet, I've come across several that seem decent but all seem to have pros and cons and I am having a hard time deciding how well in this situation that the pros and cons balance out. So are the ones listed here worth it? I have listed them with known pros and cons. </introduction> <optimizations> Chop the compared sequences into multiple chucks of subsequences by splitting where lines are unchanged, and then truncating each section of unchanged lines at the beginning and end of each section. Then solve the edit distance of each subsequence. Pro: Changes the time increase as the changed area gets bigger from a quadratic increase to something more similar to a linear increase. Con: Figuring out where to split already seems like you have to solve edit distance except now you don't care how it is changed. Would be fine if this was solvable by a process closer to solving hamming distance but a single insertion would throw this off. Use a cryptographic hash function to both convert all sequence elements into integers and ensure uniqueness. Then solve the edit distance comparing the hash integers instead of the sequence elements themselves. Pro: The operation of comparing two integers is faster than the operation of comparing two strings, so a slight performance gain is received after every comparison, which can be a lot overall. Con: Using a cryptographic hash function takes time to convert all the sequence elements and may end up costing more time to do the conversion that you gain back from the integer comparisons. You could use the built in hash function for a string but that will not guarantee uniqueness. Use lazy evaluation to only calculate the three center-most diagonals of the comparison matrix and then only calculate additional diagonals as needed. And then also use this approach to possibly remove the need on some comparisons to compare all three adjacent cells as desribed here. Pro: Can turn an algorithm that always takes O(n * m) time and make it so only worst case scenario is that time, best case becomes practically linear, and average case is somewhere between the two. Con: It is an algorithm I've only seen implemented in functional programming languages and I am having a difficult time comprehending how to convert this into Ruby based on how it is described at the site linked to above. Make a C module and do the hard work at the native level in C and just make a Ruby wrapper for it so Ruby can make all the calls to it that it needs. Pro: I have to imagine that evaluating something like this in could be a LOT faster. Con: I have no idea how Rails handles apps with ruby code that has C extensions and it hurts the portability of the app. This is an optimization for after the solving of edit distance, but idea is to store additional combined diffs with the ones produced by each version to make a delta-tree data structure with the most recently made diff as the root node of the tree so getting to any version takes worst case time of O(log n) instead of O(n). Pro: Would make going back to an old version a lot faster. Con: It would mean every new commit, the delta-tree would get a new root node that will cost time to reorganize the delta-tree for an operation that will be carried out a lot more often than going back a version, not to mention the unlikelihood it will be an old version. </optimizations> So are these things worth the effort?

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  • Issue 15: The Benefits of Oracle Exastack

    - by rituchhibber
         SOLUTIONS FOCUS The Benefits of Oracle Exastack Paul ThompsonDirector, Alliances and Solutions Partner ProgramsOracle EMEA Alliances & Channels RESOURCES -- Oracle PartnerNetwork (OPN) Oracle Exastack Program Oracle Exastack Ready Oracle Exastack Optimized Oracle Exastack Labs and Enablement Resources Oracle Exastack Labs Video Tour SUBSCRIBE FEEDBACK PREVIOUS ISSUES Exastack is a revolutionary programme supporting Oracle independent software vendor partners across the entire Oracle technology stack. Oracle's core strategy is to engineer software and hardware together, and our ISV strategy is the same. At Oracle we design engineered systems that are pre-integrated to reduce the cost and complexity of IT infrastructures while increasing productivity and performance. Oracle innovates and optimises performance at every layer of the stack to simplify business operations, drive down costs and accelerate business innovation. Our engineered systems are optimised to achieve enterprise performance levels that are unmatched in the industry. Faster time to production is achieved by implementing pre-engineered and pre-assembled hardware and software bundles. Our strategy of delivering a single-vendor stack simplifies and reduces costs associated with purchasing, deploying, and supporting IT environments for our customers and partners. In parallel to this core engineered systems strategy, the Oracle Exastack Program enables our Oracle ISV partners to leverage a scalable, integrated infrastructure that delivers their applications tuned, tested and optimised for high-performance. Specifically, the Oracle Exastack Program helps ISVs run their solutions on the Oracle Exadata Database Machine, Oracle Exalogic Elastic Cloud, and Oracle SPARC SuperCluster T4-4 - integrated systems products in which the software and hardware are engineered to work together. These products provide OPN members with a lower cost and high performance infrastructure for database and application workloads across on-premise and cloud based environments. Ready and Optimized Oracle Partners can now leverage our new Oracle Exastack Program to become Oracle Exastack Ready and Oracle Exastack Optimized. Partners can achieve Oracle Exastack Ready status through their support for Oracle Solaris, Oracle Linux, Oracle VM, Oracle Database, Oracle WebLogic Server, Oracle Exadata Database Machine, Oracle Exalogic Elastic Cloud, and Oracle SPARC SuperCluster T4-4. By doing this, partners can demonstrate to their customers that their applications are available on the latest major releases of these products. The Oracle Exastack Ready programme helps customers readily differentiate Oracle partners from lesser software developers, and identify applications that support Oracle engineered systems. Achieving Oracle Exastack Optimized status demonstrates that an OPN member has proven itself against goals for performance and scalability on Oracle integrated systems. This status enables end customers to readily identify Oracle partners that have tested and tuned their solutions for optimum performance on an Oracle Exadata Database Machine, Oracle Exalogic Elastic Cloud, and Oracle SPARC SuperCluster T4-4. These ISVs can display the Oracle Exadata Optimized, Oracle Exalogic Optimized or Oracle SPARC SuperCluster Optimized logos on websites and on all their collateral to show that they have tested and tuned their application for optimum performance. Deliver higher value to customers Oracle's investment in engineered systems enables ISV partners to deliver higher value to customer business processes. New innovations are enabled through extreme performance unachievable through traditional best-of-breed multi-vendor server/software approaches. Core product requirements can be launched faster, enabling ISVs to focus research and development investment on core competencies in order to bring value to market as quickly as possible. Through Exastack, partners no longer have to worry about the underlying product stack, which allows greater focus on the development of intellectual property above the stack. Partners are not burdened by platform issues and can concentrate simply on furthering their applications. The advantage to end customers is that partners can focus all efforts on business functionality, rather than bullet-proofing underlying technologies, and so will inevitably deliver application updates faster. Exastack provides ISVs with a number of flexible deployment options, such as on-premise or Cloud, while maintaining one single code base for applications regardless of customer deployment preference. Customers buying their solutions from Exastack ISVs can therefore be confident in deploying on their own networks, on private clouds or into a public cloud. The underlying platform will support all conceivable deployments, enabling a focus on the ISV's application itself that wouldn't be possible with other vendor partners. It stands to reason that Exastack accelerates time to value as well as lowering implementation costs all round. There is a big competitive advantage in partners being able to offer customers an optimised, pre-configured solution rather than an assortment of components and a suggested fit. Once a customer has decided to buy an Oracle Exastack Ready or Optimized partner solution, it will be up and running without any need for the customer to conduct testing of its own. Operational costs and complexity are also reduced, thanks to streamlined customer support through standardised configurations and pro-active monitoring. 'Engineered to Work Together' is a significant statement of Oracle strategy. It guarantees smoother deployment of a single vendor solution, clear ownership with no finger-pointing and the peace of mind of the Oracle Support Centre underpinning the entire product stack. Next steps Every OPN member with packaged applications must seriously consider taking steps to become Exastack Ready, or Exastack Optimized at the first opportunity. That first step down the track is to talk to an expert on the OPN Portal, at the Oracle Partner Business Center or to discuss the next steps with the closest Oracle account manager. Oracle Exastack lab environments and other technical enablement resources are available for OPN members wishing to further their knowledge of Oracle Exastack and qualify their applications for Oracle Exastack Optimized. New Boot Camps and Guided Learning Paths (GLPs), tailored specifically for ISVs, are available for Oracle Exadata Database Machine, Oracle Exalogic Elastic Cloud, Oracle Linux, Oracle Solaris, Oracle Database, and Oracle WebLogic Server. More information about these GLPs and Boot Camps (including delivery dates and locations) are posted on the OPN Competency Center and corresponding OPN Knowledge Zones. Learn more about Oracle Exastack labs and ISV specific enablement resources. "Oracle Specialized partners are of course front-and-centre, with potential customers clearly directed to those partners and to Exadata Ready partners as a matter of priority." --More OpenWorld 2011 highlights for Oracle partners and customers Oracle Application Testing Suite 9.3 application testing solution for Web, SOA and Oracle Applications Oracle Application Express Release 4.1 improving the development of database-centric Web 2.0 applications and reports Oracle Unified Directory 11g helping customers manage the critical identity information that drives their business applications Oracle SOA Suite for healthcare integration Oracle Enterprise Pack for Eclipse 11g demonstrating continued commitment to the developer and open source communities Oracle Coherence 3.7.1, the latest release of the industry's leading distributed in-memory data grid Oracle Process Accelerators helping to simplify and accelerate time-to-value for customers' business process management initiatives Oracle's JD Edwards EnterpriseOne on the iPad meeting the increasingly mobile demands of today's workforces Oracle CRM On Demand Release 19 Innovation Pack introducing industry-leading hosted call centre and enterprise-marketing capabilities designed to drive further revenue and productivity while reducing costs and improving the customer experience Oracle's Primavera Portfolio Management 9 for businesses delivering on project portfolio goals with increased versatility, transparency and accuracy Oracle's PeopleSoft Human Capital Management (HCM) 9.1 On Demand Standard Edition helping customers manage their long-term investment in enterprise-wide business applications New versions of Oracle FLEXCUBE Universal Banking and Oracle FLEXCUBE Investor Servicing for Financial Institutions, as well as Oracle Financial Services Enterprise Case Management, Oracle Financial Services Pricing Management, Oracle Financial Management Analytics and Oracle Tax Analytics Oracle Utilities Network Management System 1.11 offering new modelling and analysis features to improve distribution-grid management for electric utilities Oracle Communications Network Charging and Control 4.4 helping communications service providers (CSPs) offer their customers more flexible charging options Plus many, many more technology announcements, enhancements, momentum news and community updates -- Oracle OpenWorld 2012 A date has already been set for Oracle OpenWorld 2012. Held once again in San Francisco, exhibitors, partners, customers and Oracle people will gather from 30 September until 4 November to meet, network and learn together with the rest of the global Oracle community. Register now for Oracle OpenWorld 2012 and save $$$! We'll reward your early planning for Oracle OpenWorld 2012 with reduced rates. Super Saver deals are now available! -- Back to the welcome page

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  • Oracle Support Master Note for Troubleshooting Advanced Queuing and Oracle Streams Propagation Issues (Doc ID 233099.1)

    - by faye.todd(at)oracle.com
    Master Note for Troubleshooting Advanced Queuing and Oracle Streams Propagation Issues (Doc ID 233099.1) Copyright (c) 2010, Oracle Corporation. All Rights Reserved. In this Document  Purpose  Last Review Date  Instructions for the Reader  Troubleshooting Details     1. Scope and Application      2. Definitions and Classifications     3. How to Use This Guide     4. Basic AQ Propagation Troubleshooting     5. Additional Troubleshooting Steps for AQ Propagation of User-Enqueued and Dequeued Messages     6. Additional Troubleshooting Steps for Propagation in an Oracle Streams Environment     7. Performance Issues  References Applies to: Oracle Server - Enterprise Edition - Version: 8.1.7.0 to 11.2.0.2 - Release: 8.1.7 to 11.2Information in this document applies to any platform. Purpose This document presents a step-by-step methodology for troubleshooting and resolving problems with Advanced Queuing Propagation in both Streams and basic Advanced Queuing environments. It also serves as a master reference for other more specific notes on Oracle Streams Propagation and Advanced Queuing Propagation issues. Last Review Date December 20, 2010 Instructions for the Reader A Troubleshooting Guide is provided to assist in debugging a specific issue. When possible, diagnostic tools are included in the document to assist in troubleshooting. Troubleshooting Details 1. Scope and Application This note is intended for Database Administrators of Oracle databases where issues are being encountered with propagating messages between advanced queues, whether the queues are used for user-created messaging systems or for Oracle Streams. It contains troubleshooting steps and links to notes for further problem resolution.It can also be used a template to document a problem when it is necessary to engage Oracle Support Services. Knowing what is NOT happening can frequently speed up the resolution process by focusing solely on the pertinent problem area. This guide is divided into five parts: Section 2: Definitions and Classifications (discusses the different types and features of propagations possible - helpful for understanding the rest of the guide) Section 3: How to Use this Guide (to be used as a start part for determining the scope of the problem and what sections to consult) Section 4. Basic AQ propagation troubleshooting (applies to both AQ propagation of user enqueued and dequeued messages as well as Oracle Streams propagations) Section 5. Additional troubleshooting steps for AQ propagation of user enqueued and dequeued messages Section 6. Additional troubleshooting steps for Oracle Streams propagation Section 7. Performance issues 2. Definitions and Classifications Given the potential scope of issues that can be encountered with AQ propagation, the first recommended step is to do some basic diagnosis to determine the type of problem that is being encountered. 2.1. What Type of Propagation is Being Used? 2.1.1. Buffered Messaging For an advanced queue, messages can be maintained on disk (persistent messaging) or in memory (buffered messaging). To determine if a queue is buffered or not, reference the GV_$BUFFERED_QUEUES view. If the queue does not appear in this view, it is persistent. 2.1.2. Propagation mode - queue-to-dblink vs queue-to-queue As of 10.2, an AQ propagation can also be defined as queue-to-dblink, or queue-to-queue: queue-to-dblink: The propagation delivers messages or events from the source queue to all subscribing queues at the destination database identified by the dblink. A single propagation schedule is used to propagate messages to all subscribing queues. Hence any changes made to this schedule will affect message delivery to all the subscribing queues. This mode does not support multiple propagations from the same source queue to the same target database. queue-to-queue: Added in 10.2, this propagation mode delivers messages or events from the source queue to a specific destination queue identified on the database link. This allows the user to have fine-grained control on the propagation schedule for message delivery. This new propagation mode also supports transparent failover when propagating to a destination Oracle RAC system. With queue-to-queue propagation, you are no longer required to re-point a database link if the owner instance of the queue fails on Oracle RAC. This mode supports multiple propagations to the same target database if the target queues are different. The default is queue-to-dblink. To verify if queue-to-queue propagation is being used, in non-Streams environments query DBA_QUEUE_SCHEDULES.DESTINATION - if a remote queue is listed along with the remote database link, then queue-to-queue propagation is being used. For Streams environments, the DBA_PROPAGATION.QUEUE_TO_QUEUE column can be checked.See the following note for a method to switch between the two modes:Document 827473.1 How to alter propagation from queue-to-queue to queue-to-dblink 2.1.3. Combined Capture and Apply (CCA) for Streams In 11g Oracle Streams environments, an optimization called Combined Capture and Apply (CCA) is implemented by default when possible. Although a propagation is configured in this case, Streams does not use it; instead it passes information directly from capture to an apply receiver. To see if CCA is in use: COLUMN CAPTURE_NAME HEADING 'Capture Name' FORMAT A30COLUMN OPTIMIZATION HEADING 'CCA Mode?' FORMAT A10SELECT CAPTURE_NAME, DECODE(OPTIMIZATION,0, 'No','Yes') OPTIMIZATIONFROM V$STREAMS_CAPTURE; Also, see the following note:Document 463820.1 Streams Combined Capture and Apply in 11g 2.2. Queue Table Compatibility There are three types of queue table compatibility. In more recent databases, queue tables may be present in all three modes of compatibility: 8.0 - earliest version, deprecated in 10.2 onwards 8.1 - support added for RAC, asynchronous notification, secure queues, queue level access control, rule-based subscribers, separate storage of history information 10.0 - if the database is in 10.1-compatible mode, then the default value for queue table compatibility is 10.0 2.3. Single vs Multiple Consumer Queue Tables If more than one recipient can dequeue a message from a queue, then its queue table is multiple consumer. You can propagate messages from a multiple-consumer queue to a single-consumer queue. Propagation from a single-consumer queue to a multiple-consumer queue is not possible. 3. How to Use This Guide 3.1. Are Messages Being Propagated at All, or is the Propagation Just Slow? Run the following query on the source database for the propagation (assuming that it is running): select TOTAL_NUMBER from DBA_QUEUE_SCHEDULES where QNAME='<source_queue_name>'; If TOTAL_NUMBER is increasing, then propagation is most likely functioning, although it may be slow. For performance issues, see Section 7. 3.2. Propagation Between Persistent User-Created Queues See Sections 4 and 5 (and optionally Section 6 if performance is an issue). 3.3. Propagation Between Buffered User-Created Queues See Sections 4, 5, and 6 (and optionally Section 7 if performance is an issue). 3.4. Propagation between Oracle Streams Queues (without Combined Capture and Apply (CCA) Optimization) See Sections 4 and 6 (and optionally Section 7 if performance is an issue). 3.5. Propagation between Oracle Streams Queues (with Combined Capture and Apply (CCA) Optimization) Although an AQ propagation is not used directly in this case, some characteristics of the message transfer are inferred from the propagation parameters used. Some parts of Sections 4 and 6 still apply. 3.6. Messaging Gateway Propagations This note does not apply to Messaging Gateway propagations. 4. Basic AQ Propagation Troubleshooting 4.1. Double-check Your Code Make sure that you are consistent in your usage of the database link(s) names, queue names, etc. It may be useful to plot a diagram of which queues are connected via which database links to make sure that the logical structure is correct. 4.2. Verify that Job Queue Processes are Running 4.2.1. Versions 10.2 and Lower - DBA_JOBS Package For versions 10.2 and lower, a scheduled propagation is managed by DBMS_JOB package. The propagation is performed by job queue process background processes. Therefore we need to verify that there are sufficient processes available for the propagation process. We should have at least 4 job queue processes running and preferably more depending on the number of other jobs running in the database. It should be noted that for AQ specific work, AQ will only ever use half of the job queue processes available.An issue caused by an inadequate job queue processes parameter setting is described in the following note:Document 298015.1 Kwqjswproc:Excep After Loop: Assigning To Self 4.2.1.1. Job Queue Processes in Initalization Parameter File The parameter JOB_QUEUE_PROCESSES in the init.ora/spfile should be > 0. The value can be changed dynamically via connect / as sysdbaalter system set JOB_QUEUE_PROCESSES=10; 4.2.1.2. Job Queue Processes in Memory The following command will show how many job queue processes are currentlyin use by this instance (this may be different than what is in the init.ora/spfile): connect / as sysdbashow parameter job; 4.2.1.3. OS PIDs Corresponding to Job Queue Processes Identify the operating system process ids (spids) of job queue processes involved in propagation via select p.SPID, p.PROGRAM from V$PROCESS p, DBA_JOBS_RUNNING jr, V$SESSION s, DBA_JOBS j where s.SID=jr.SID and s.PADDR=p.ADDR and jr.JOB=j.JOBand j.WHAT like '%sys.dbms_aqadm.aq$_propaq(job)%'; and these SPIDs can be used to check at the operating system level that they exist.In 8i a job queue process will have a name similar to: ora_snp1_<instance_name>.In 9i onwards you will see a coordinator process: ora_cjq0_ and multiple slave processes: ora_jnnn_<instance_name>, where nnn is an integer between 1 and 999. 4.2.2. Version 11.1 and Above - Oracle Scheduler In version 11.1 and above, Oracle Scheduler is used to perform AQ and Streams propagations. Oracle Scheduler automatically tunes the number of slave processes for these jobs based on the load on the computer system, and the JOB_QUEUE_PROCESSES initialization parameter is only used to specify the maximum number of slave processes. Therefore, the JOB_QUEUE_PROCESSES initialization parameter does not need to be set (it defaults to a very high number), unless you want to limit the number of slaves that can be created. If JOB_QUEUE_PROCESSES = 0, no propagation jobs will run.See the following note for a discussion of Oracle Streams 11g and Oracle Scheduler:Document 1083608.1 11g Streams and Oracle Scheduler 4.2.2.1. Job Queue Processes in Initalization Parameter File The parameter JOB_QUEUE_PROCESSES in the init.ora/spfile should be > 0, and preferably be left at its default value. The value can be changed dynamically via connect / as sysdbaalter system set JOB_QUEUE_PROCESSES=10; To set the JOB_QUEUE_PROCESSES parameter to its default value, run: connect / as sysdbaalter system reset JOB_QUEUE_PROCESSES; and then bounce the instance. 4.2.2.2. Job Queue Processes in Memory The following command will show how many job queue processes are currently in use by this instance (this may be different than what is in the init.ora/spfile): connect / as sysdbashow parameter job; 4.2.2.3. OS PIDs Corresponding to Job Queue Processes Identify the operating system process ids (SPIDs) of job queue processes involved in propagation via col PROGRAM for a30select p.SPID, p.PROGRAM, j.JOB_namefrom v$PROCESS p, DBA_SCHEDULER_RUNNING_JOBS jr, V$SESSION s, DBA_SCHEDULER_JOBS j where s.SID=jr.SESSION_ID and s.PADDR=p.ADDRand jr.JOB_name=j.JOB_NAME and j.JOB_NAME like '%AQ_JOB$_%'; and these SPIDs can be used to check at the operating system level that they exist.You will see a coordinator process: ora_cjq0_ and multiple slave processes: ora_jnnn_<instance_name>, where nnn is an integer between 1 and 999. 4.3. Check the Alert Log and Any Associated Trace Files The first place to check for propagation failures is the alert logs at all sites (local and if relevant all remote sites). When a job queue process attempts to execute a schedule and fails it will always write an error stack to the alert log. This error stack will also be written in a job queue process trace file, which will be written to the BACKGROUND_DUMP_DEST location for 10.2 and below, and in the DIAGNOSTIC_DEST location for 11g. The fact that errors are written to the alert log demonstrates that the schedule is executing. This means that the problem could be with the set up of the schedule. In this example the ORA-02068 demonstrates that the failure was at the remote site. Further investigation revealed that the remote database was not open, hence the ORA-03114 error. Starting the database resolved the problem. Thu Feb 14 10:40:05 2002 Propagation Schedule for (AQADM.MULTIPLEQ, SHANE816.WORLD) encountered following error:ORA-04052: error occurred when looking up Remote object [email protected]: error occurred at recursive SQL level 4ORA-02068: following severe error from SHANE816ORA-03114: not connected to ORACLEORA-06512: at "SYS.DBMS_AQADM_SYS", line 4770ORA-06512: at "SYS.DBMS_AQADM", line 548ORA-06512: at line 1 Other potential errors that may be written to the alert log can be found in the following notes:Document 827184.1 AQ Propagation with CLOB data types Fails with ORA-22990 (11.1)Document 846297.1 AQ Propagation Fails : ORA-00600[kope2upic2954] or Ora-00600[Kghsstream_copyn] (10.2, 11.1)Document 731292.1 ORA-25215 Reported on Local Propagation When Using Transformation with ANYDATA queue tables (10.2, 11.1, 11.2)Document 365093.1 ORA-07445 [kwqppay2aqe()+7360] Reported on Propagation of a Transformed Message (10.1, 10.2)Document 219416.1 Advanced Queuing Propagation Fails with ORA-22922 (9.0)Document 1203544.1 AQ Propagation Aborted with ORA-600 [ociksin: invalid status] on SYS.DBMS_AQADM_SYS.AQ$_PROPAGATION_PROCEDURE After Upgrade (11.1, 11.2)Document 1087324.1 ORA-01405 ORA-01422 reported by Advanced Queuing Propagation schedules after RAC reconfiguration (10.2)Document 1079577.1 Advanced Queuing Propagation Fails With "ORA-22370 incorrect usage of method" (9.2, 10.2, 11.1, 11.2)Document 332792.1 ORA-04061 error relating to SYS.DBMS_PRVTAQIP reported when setting up Statspack (8.1, 9.0, 9.2, 10.1)Document 353325.1 ORA-24056: Internal inconsistency for QUEUE <queue_name> and destination <dblink> (8.1, 9.0, 9.2, 10.1, 10.2, 11.1, 11.2)Document 787367.1 ORA-22275 reported on Propagating Messages with LOB component when propagating between 10.1 and 10.2 (10.1, 10.2)Document 566622.1 ORA-22275 when propagating >4K AQ$_JMS_TEXT_MESSAGEs from 9.2.0.8 to 10.2.0.1 (9.2, 10.1)Document 731539.1 ORA-29268: HTTP client error 401 Unauthorized Error when the AQ Servlet attempts to Propagate a message via HTTP (9.0, 9.2, 10.1, 10.2, 11.1)Document 253131.1 Concurrent Writes May Corrupt LOB Segment When Using Auto Segment Space Management (ORA-1555) (9.2)Document 118884.1 How to unschedule a propagation schedule stuck in pending stateDocument 222992.1 DBMS_AQADM.DISABLE_PROPAGATION_SCHEDULE Returns ORA-24082Document 282987.1 Propagated Messages marked UNDELIVERABLE after Drop and Recreate Of Remote QueueDocument 1204080.1 AQ Propagation Failing With ORA-25329 After Upgraded From 8i or 9i to 10g or 11g.Document 1233675.1 AQ Propagation stops after upgrade to 11.2.0.1 ORA-30757 4.3.1. Errors Related to Incorrect Network Configuration The most common propagation errors result from an incorrect network configuration. The list below contains common errors caused by tnsnames.ora file or database links being configured incorrectly: - ORA-12154: TNS:could not resolve service name- ORA-12505: TNS:listener does not currently know of SID given in connect descriptor- ORA-12514: TNS:listener could not resolve SERVICE_NAME - ORA-12541: TNS-12541 TNS:no listener 4.4. Check the Database Links Exist and are Functioning Correctly For schedules to remote databases confirm the database link exists via. SQL> col DBLINK for a45SQL> select QNAME, NVL(REGEXP_SUBSTR(DESTINATION, '[^@]+', 1, 2), DESTINATION) dblink2 from DBA_QUEUE_SCHEDULES3 where MESSAGE_DELIVERY_MODE = 'PERSISTENT';QNAME DBLINK------------------------------ ---------------------------------------------MY_QUEUE ORCL102B.WORLD Connect as the owner of the link and select across it to verify it works and connects to the database we expect. i.e. select * from ALL_QUEUES@ ORCL102B.WORLD; You need to ensure that the userid that scheduled the propagation (using DBMS_AQADM.SCHEDULE_PROPAGATION or DBMS_PROPAGATION_ADM.CREATE_PROPAGATION if using Streams) has access to the database link for the destination. 4.5. Has Propagation Been Correctly Scheduled? Check that the propagation schedule has been created and that a job queue process has been assigned. Look for the entry in DBA_QUEUE_SCHEDULES and SYS.AQ$_SCHEDULES for your schedule. For 10g and below, check that it has a JOBNO entry in SYS.AQ$_SCHEDULES, and that there is an entry in DBA_JOBS with that JOBNO. For 11g and above, check that the schedule has a JOB_NAME entry in SYS.AQ$_SCHEDULES, and that there is an entry in DBA_SCHEDULER_JOBS with that JOB_NAME. Check the destination is as intended and spelled correctly. SQL> select SCHEMA, QNAME, DESTINATION, SCHEDULE_DISABLED, PROCESS_NAME from DBA_QUEUE_SCHEDULES;SCHEMA QNAME DESTINATION S PROCESS------- ---------- ------------------ - -----------AQADM MULTIPLEQ AQ$_LOCAL N J000 AQ$_LOCAL in the destination column shows that the queue to which we are propagating to is in the same database as the source queue. If the propagation was to a remote (different) database, a database link will be in the DESTINATION column. The entry in the SCHEDULE_DISABLED column, N, means that the schedule is NOT disabled. If Y (yes) appears in this column, propagation is disabled and the schedule will not be executed. If not using Oracle Streams, propagation should resume once you have enabled the schedule by invoking DBMS_AQADM.ENABLE_PROPAGATION_SCHEDULE (for 10.2 Oracle Streams and above, the DBMS_PROPAGATION_ADM.START_PROPAGATION procedure should be used). The PROCESS_NAME is the name of the job queue process currently allocated to execute the schedule. This process is allocated dynamically at execution time. If the PROCESS_NAME column is null (empty) the schedule is not currently executing. You may need to execute this statement a number of times to verify if a process is being allocated. If a process is at some time allocated to the schedule, it is attempting to execute. SQL> select SCHEMA, QNAME, LAST_RUN_DATE, NEXT_RUN_DATE from DBA_QUEUE_SCHEDULES;SCHEMA QNAME LAST_RUN_DATE NEXT_RUN_DATE------ ----- ----------------------- ----------------------- AQADM MULTIPLEQ 13-FEB-2002 13:18:57 13-FEB-2002 13:20:30 In 11g, these dates are expressed in TIMESTAMP WITH TIME ZONE datatypes. If the NEXT_RUN_DATE and NEXT_RUN_TIME columns are null when this statement is executed, the scheduled propagation is currently in progress. If they never change it would suggest that the schedule itself is never executing. If the next scheduled execution is too far away, change the NEXT_TIME parameter of the schedule so that schedules are executed more frequently (assuming that the window is not set to be infinite). Parameters of a schedule can be changed using the DBMS_AQADM.ALTER_PROPAGATION_SCHEDULE call. In 10g and below, scheduling propagation posts a job in the DBA_JOBS view. The columns are more or less the same as DBA_QUEUE_SCHEDULES so you just need to recognize the job and verify that it exists. SQL> select JOB, WHAT from DBA_JOBS where WHAT like '%sys.dbms_aqadm.aq$_propaq(job)%';JOB WHAT---- ----------------- 720 next_date := sys.dbms_aqadm.aq$_propaq(job); For 11g, scheduling propagation posts a job in DBA_SCHEDULER_JOBS instead: SQL> select JOB_NAME from DBA_SCHEDULER_JOBS where JOB_NAME like 'AQ_JOB$_%';JOB_NAME------------------------------AQ_JOB$_41 If no job exists, check DBA_QUEUE_SCHEDULES to make sure that the schedule has not been disabled. For 10g and below, the job number is dynamic for AQ propagation schedules. The procedure that is executed to expedite a propagation schedule runs, removes itself from DBA_JOBS, and then reposts a new job for the next scheduled propagation. The job number should therefore always increment unless the schedule has been set up to run indefinitely. 4.6. Is the Schedule Executing but Failing to Complete? Run the following query: SQL> select FAILURES, LAST_ERROR_MSG from DBA_QUEUE_SCHEDULES;FAILURES LAST_ERROR_MSG------------ -----------------------1 ORA-25207: enqueue failed, queue AQADM.INQ is disabled from enqueueingORA-02063: preceding line from SHANE816 The failures column shows how many times we have attempted to execute the schedule and failed. Oracle will attempt to execute the schedule 16 times after which it will be removed from the DBA_JOBS or DBA_SCHEDULER_JOBS view and the schedule will become disabled. The column DBA_QUEUE_SCHEDULES.SCHEDULE_DISABLED will show 'Y'. For 11g and above, the DBA_SCHEDULER_JOBS.STATE column will show 'BROKEN' for the job corresponding to DBA_QUEUE_SCHEDULES.JOB_NAME. Prior to 10g the back off algorithm for failures was exponential, whereas from 10g onwards it is linear. The propagation will become disabled on the 17th attempt. Only the last execution failure will be reflected in the LAST_ERROR_MSG column. That is, if the schedule fails 5 times for 5 different reasons, only the last set of errors will be recorded in DBA_QUEUE_SCHEDULES. Any errors need to be resolved to allow propagation to continue. If propagation has also become disabled due to 17 failures, first resolve the reason for the error and then re-enable the schedule using the DBMS_AQADM.ENABLE_PROPAGATION_SCHEDULE procedure, or DBMS_PROPAGATION_ADM.START_PROPAGATION if using 10.2 or above Oracle Streams. As soon as the schedule executes successfully the error message entries will be deleted. Oracle does not keep a history of past failures. However, when using Oracle Streams, the errors will be retained in the DBA_PROPAGATION view even after the schedule resumes successfully. See the following note for instructions on how to clear out the errors from the DBA_PROPAGATION view:Document 808136.1 How to clear the old errors from DBA_PROPAGATION view?If a schedule is active and no errors are being reported then the source queue may not have any messages to be propagated. 4.7. Do the Propagation Notification Queue Table and Queue Exist? Check to see that the propagation notification queue table and queue exist and are enabled for enqueue and dequeue. Propagation makes use of the propagation notification queue for handling propagation run-time events, and the messages in this queue are stored in a SYS-owned queue table. This queue should never be stopped or dropped and the corresponding queue table never be dropped. 10g and belowThe propagation notification queue table is of the format SYS.AQ$_PROP_TABLE_n, where 'n' is the RAC instance number, i.e. '1' for a non-RAC environment. This queue and queue table are created implicitly when propagation is first scheduled. If propagation has been scheduled and these objects do not exist, try unscheduling and rescheduling propagation. If they still do not exist contact Oracle Support. SQL> select QUEUE_TABLE from DBA_QUEUE_TABLES2 where QUEUE_TABLE like '%PROP_TABLE%' and OWNER = 'SYS';QUEUE_TABLE------------------------------AQ$_PROP_TABLE_1SQL> select NAME, ENQUEUE_ENABLED, DEQUEUE_ENABLED2 from DBA_QUEUES where owner='SYS'3 and QUEUE_TABLE like '%PROP_TABLE%';NAME ENQUEUE DEQUEUE------------------------------ ------- -------AQ$_PROP_NOTIFY_1 YES YESAQ$_AQ$_PROP_TABLE_1_E NO NO If the AQ$_PROP_NOTIFY_1 queue is not enabled for enqueue or dequeue, it should be so enabled using DBMS_AQADM.START_QUEUE. However, the exception queue AQ$_AQ$_PROP_TABLE_1_E should not be enabled for enqueue or dequeue.11g and aboveThe propagation notification queue table is of the format SYS.AQ_PROP_TABLE, and is created when the database is created. If they do not exist, contact Oracle Support. SQL> select QUEUE_TABLE from DBA_QUEUE_TABLES2 where QUEUE_TABLE like '%PROP_TABLE%' and OWNER = 'SYS';QUEUE_TABLE------------------------------AQ_PROP_TABLESQL> select NAME, ENQUEUE_ENABLED, DEQUEUE_ENABLED2 from DBA_QUEUES where owner='SYS'3 and QUEUE_TABLE like '%PROP_TABLE%';NAME ENQUEUE DEQUEUE------------------------------ ------- -------AQ_PROP_NOTIFY YES YESAQ$_AQ_PROP_TABLE_E NO NO If the AQ_PROP_NOTIFY queue is not enabled for enqueue or dequeue, it should be so enabled using DBMS_AQADM.START_QUEUE. However, the exception queue AQ$_AQ$_PROP_TABLE_E should not be enabled for enqueue or dequeue. 4.8. Does the Remote Queue Exist and is it Enabled for Enqueueing? Check that the remote queue the propagation is transferring messages to exists and is enabled for enqueue: SQL> select DESTINATION from USER_QUEUE_SCHEDULES where QNAME = 'OUTQ';DESTINATION-----------------------------------------------------------------------------"AQADM"."INQ"@M2V102.ESSQL> select OWNER, NAME, ENQUEUE_ENABLED, DEQUEUE_ENABLED from [email protected];OWNER NAME ENQUEUE DEQUEUE-------- ------ ----------- -----------AQADM INQ YES YES 4.9. Do the Target and Source Database Charactersets Differ? If a message fails to propagate, check the database charactersets of the source and target databases. Investigate whether the same message can propagate between the databases with the same characterset or it is only a particular combination of charactersets which causes a problem. 4.10. Check the Queue Table Type Agreement Propagation is not possible between queue tables which have types that differ in some respect. One way to determine if this is the case is to run the DBMS_AQADM.VERIFY_QUEUE_TYPES procedure for the two queues that the propagation operates on. If the types do not agree, DBMS_AQADM.VERIFY_QUEUE_TYPES will return '0'.For AQ propagation between databases which have different NLS_LENGTH_SEMANTICS settings, propagation will not work, unless the queues are Oracle Streams ANYDATA queues.See the following notes for issues caused by lack of type agreement:Document 1079577.1 Advanced Queuing Propagation Fails With "ORA-22370: incorrect usage of method"Document 282987.1 Propagated Messages marked UNDELIVERABLE after Drop and Recreate Of Remote QueueDocument 353754.1 Streams Messaging Propagation Fails between Single and Multi-byte Charactersets when using Chararacter Length Semantics in the ADT 4.11. Enable Propagation Tracing 4.11.1. System Level This is set it in the init.ora/spfile as follows: event="24040 trace name context forever, level 10" and restart the instanceThis event cannot be set dynamically with an alter system command until version 10.2: SQL> alter system set events '24040 trace name context forever, level 10'; To unset the event: SQL> alter system set events '24040 trace name context off'; Debugging information will be logged to job queue trace file(s) (jnnn) as propagation takes place. You can check the trace file for errors, and for statements indicating that messages have been sent. For the most part the trace information is understandable. This trace should also be uploaded to Oracle Support if a service request is created. 4.11.2. Attaching to a Specific Process We can also attach to an existing job queue processes that is running a propagation schedule and trace it individually using the oradebug utility, as follows:10.2 and below connect / as sysdbaselect p.SPID, p.PROGRAM from v$PROCESS p, DBA_JOBS_RUNNING jr, V$SESSION s, DBA_JOBS j where s.SID=jr.SID and s.PADDR=p.ADDR and jr.JOB=j.JOB and j.WHAT like '%sys.dbms_aqadm.aq$_propaq(job)%';-- For the process id (SPID) attach to it via oradebug and generate the following traceoradebug setospid <SPID>oradebug unlimitoradebug Event 10046 trace name context forever, level 12oradebug Event 24040 trace name context forever, level 10-- Trace the process for 5 minutesoradebug Event 10046 trace name context offoradebug Event 24040 trace name context off-- The following command returns the pathname/filename to the file being written tooradebug tracefile_name 11g connect / as sysdbacol PROGRAM for a30select p.SPID, p.PROGRAM, j.JOB_NAMEfrom v$PROCESS p, DBA_SCHEDULER_RUNNING_JOBS jr, V$SESSION s, DBA_SCHEDULER_JOBS j where s.SID=jr.SESSION_ID and s.PADDR=p.ADDR and jr.JOB_NAME=j.JOB_NAME and j.JOB_NAME like '%AQ_JOB$_%';-- For the process id (SPID) attach to it via oradebug and generate the following traceoradebug setospid <SPID>oradebug unlimitoradebug Event 10046 trace name context forever, level 12oradebug Event 24040 trace name context forever, level 10-- Trace the process for 5 minutesoradebug Event 10046 trace name context offoradebug Event 24040 trace name context off-- The following command returns the pathname/filename to the file being written tooradebug tracefile_name 4.11.3. Further Tracing The previous tracing steps only trace the job queue process executing the propagation on the source. At times it is useful to trace the propagation receiver process (the session which is enqueueing the messages into the target queue) on the target database which is associated with the job queue process on the source database.These following queries provide ways of identifying the processes involved in propagation so that you can attach to them via oradebug to generate trace information.In order to identify the propagation receiver process you need to execute the query as a user with privileges to access the v$ views in both the local and remote databases so the database link must connect as a user with those privileges in the remote database. The <DBLINK> in the queries should be replaced by the appropriate database link.The queries have two forms due to the differences between operating systems. The value returned by 'Rem Process' is the operating system identifier of the propagation receiver on the remote database. Once identified, this process can be attached to and traced on the remote database using the commands given in Section 4.11.2.10.2 and below - Windows select pl.SPID "JobQ Process", pl.PROGRAM, sr.PROCESS "Rem Process" from v$PROCESS pl, DBA_JOBS_RUNNING jr, V$SESSION s, DBA_JOBS j, V$SESSION@<DBLINK> sr where s.SID=jr.SID and s.PADDR=pl.ADDR and jr.JOB=j.JOB and j.WHAT like '%sys.dbms_aqadm.aq$_propaq(job)%' and pl.SPID=substr(sr.PROCESS, instr(sr.PROCESS,':')+1); 10.2 and below - Unix select pl.SPID "JobQ Process", pl.PROGRAM, sr.PROCESS "Rem Process" from V$PROCESS pl, DBA_JOBS_RUNNING jr, V$SESSION s, DBA_JOBS j, V$SESSION@<DBLINK> sr where s.SID=jr.SID and s.PADDR=pl.ADDR and jr.JOB=j.JOB and j.WHAT like '%sys.dbms_aqadm.aq$_propaq(job)%' and pl.SPID=sr.PROCESS; 11g - Windows select pl.SPID "JobQ Process", pl.PROGRAM, sr.PROCESS "Rem Process" from V$PROCESS pl, DBA_SCHEDULER_RUNNING_JOBS jr, V$SESSION s, DBA_SCHEDULER_JOBS j, V$SESSION@<DBLINK> sr where s.SID=jr.SESSION_ID and s.PADDR=pl.ADDR and jr.JOB_NAME=j.JOB_NAME and j.JOB_NAME like '%AQ_JOB$_%%' and pl.SPID=substr(sr.PROCESS, instr(sr.PROCESS,':')+1); 11g - Unix select pl.SPID "JobQ Process", pl.PROGRAM, sr.PROCESS "Rem Process" from V$PROCESS pl, DBA_SCHEDULER_RUNNING_JOBS jr, V$SESSION s, DBA_SCHEDULER_JOBS j, V$SESSION@<DBLINK> sr where s.SID=jr.SESSION_ID and s.PADDR=pl.ADDR and jr.JOB_NAME=j.JOB_NAME and j.JOB_NAME like '%AQ_JOB$_%%' and pl.SPID=sr.PROCESS;   5. Additional Troubleshooting Steps for AQ Propagation of User-Enqueued and Dequeued Messages 5.1. Check the Privileges of All Users Involved Ensure that the owner of the database link has the necessary privileges on the aq packages. SQL> select TABLE_NAME, PRIVILEGE from USER_TAB_PRIVS;TABLE_NAME PRIVILEGE------------------------------ ----------------------------------------DBMS_LOCK EXECUTEDBMS_AQ EXECUTEDBMS_AQADM EXECUTEDBMS_AQ_BQVIEW EXECUTEQT52814_BUFFER SELECT Note that when queue table is created, a view called QT<nnn>_BUFFER is created in the SYS schema, and the queue table owner is given SELECT privileges on it. The <nnn> corresponds to the object_id of the associated queue table. SQL> select * from USER_ROLE_PRIVS;USERNAME GRANTED_ROLE ADM DEF OS_------------------------------ ------------------------------ ---- ---- ---AQ_USER1 AQ_ADMINISTRATOR_ROLE NO YES NOAQ_USER1 CONNECT NO YES NOAQ_USER1 RESOURCE NO YES NO It is good practice to configure central AQ administrative user. All admin and processing jobs are created, executed and administered as this user. This configuration is not mandatory however, and the database link can be owned by any existing queue user. If this latter configuration is used, ensure that the connecting user has the necessary privileges on the AQ packages and objects involved. Privileges for an AQ Administrative user Execute on DBMS_AQADM Execute on DBMS_AQ Granted the AQ_ADMINISTRATOR_ROLE Privileges for an AQ user Execute on DBMS_AQ Execute on the message payload Enqueue privileges on the remote queue Dequeue privileges on the originating queue Privileges need to be confirmed on both sites when propagation is scheduled to remote destinations. Verify that the user ID used to login to the destination through the database link has been granted privileges to use AQ. 5.2. Verify Queue Payload Types AQ will not propagate messages from one queue to another if the payload types of the two queues are not verified to be equivalent. An AQ administrator can verify if the source and destination's payload types match by executing the DBMS_AQADM.VERIFY_QUEUE_TYPES procedure. The results of the type checking will be stored in the SYS.AQ$_MESSAGE_TYPES table. This table can be accessed using the object identifier OID of the source queue and the address database link of the destination queue, i.e. [schema.]queue_name[@destination]. Prior to Oracle 9i the payload (message type) had to be the same for all the queue tables involved in propagation. From Oracle9i onwards a transformation can be used so that payloads can be converted from one type to another. The following procedural call made on the source database can verify whether we can propagate between the source and the destination queue tables. connect aq_user1/[email protected] serverout onDECLARErc_value number;BEGINDBMS_AQADM.VERIFY_QUEUE_TYPES(src_queue_name => 'AQ_USER1.Q_1', dest_queue_name => 'AQ_USER2.Q_2',destination => 'dbl_aq_user2.es',rc => rc_value);dbms_output.put_line('rc_value code is '||rc_value);END;/ If propagation is possible then the return code value will be 1. If it is 0 then propagation is not possible and further investigation of the types and transformations used by and in conjunction with the queue tables is required. With regard to comparison of the types the following sql can be used to extract the DDL for a specific type with' %' changed appropriately on the source and target. This can then be compared for the source and target. SET LONG 20000 set pagesize 50 EXECUTE DBMS_METADATA.SET_TRANSFORM_PARAM(DBMS_METADATA.SESSION_TRANSFORM, 'STORAGE',false); SELECT DBMS_METADATA.GET_DDL('TYPE',t.type_name) from user_types t WHERE t.type_name like '%'; EXECUTE DBMS_METADATA.SET_TRANSFORM_PARAM(DBMS_METADATA.SESSION_TRANSFORM, 'DEFAULT'); 5.3. Check Message State and Destination The first step in this process is to identify the queue table associated with the problem source queue. Although you schedule propagation for a specific queue, most of the meta-data associated with that queue is stored in the underlying queue table. The following statement finds the queue table for a given queue (note that this is a multiple-consumer queue table). SQL> select QUEUE_TABLE from DBA_QUEUES where NAME = 'MULTIPLEQ';QUEUE_TABLE --------------------MULTIPLEQTABLE For a small amount of messages in a multiple-consumer queue table, the following query can be run: SQL> select MSG_STATE, CONSUMER_NAME, ADDRESS from AQ$MULTIPLEQTABLE where QUEUE = 'MULTIPLEQ';MSG_STATE CONSUMER_NAME ADDRESS-------------- ----------------------- -------------READY AQUSER2 [email protected] AQUSER1READY AQUSER3 AQADM.INQ In this example we see 2 messages ready to be propagated to remote queues and 1 that is not. If the address column is blank, the message is not scheduled for propagation and can only be dequeued from the queue upon which it was enqueued. The MSG_STATE column values are discussed in Document 102330.1 Advanced Queueing MSG_STATE Values and their Interpretation. If the address column has a value, the message has been enqueued for propagation to another queue. The first row in the example includes a database link (@M2V102.ES). This demonstrates that the message should be propagated to a queue at a remote database. The third row does not include a database link so will be propagated to a queue that resides on the same database as the source queue. The consumer name is the intended recipient at the target queue. Note that we are not querying the base queue table directly; rather, we are querying a view that is available on top of every queue table, AQ$<queue_table_name>.A more realistic query in an environment where the queue table contains thousands of messages is8.0.3-compatible multiple-consumer queue table and all compatibility single-consumer queue tables select count(*), MSG_STATE, QUEUE from AQ$<queue_table_name>  group by MSG_STATE, QUEUE; 8.1.3 and 10.0-compatible queue tables select count(*), MSG_STATE, QUEUE, CONSUMER_NAME from AQ$<queue_table_name>group by MSG_STATE, QUEUE, CONSUMER_NAME; For multiple-consumer queue tables, if you did not see the expected CONSUMER_NAME , check the syntax of the enqueue code and verify the recipients are declared correctly. If a recipients list is not used on enqueue, check the subscriber list in the AQ$_<queue_table_name>_S view (note that a single-consumer queue table does not have a subscriber view. This view records all members of the default subscription list which were added using the DBMS_AQADM.ADD_SUBSCRIBER procedure and also those enqueued using a recipient list. SQL> select QUEUE, NAME, ADDRESS from AQ$MULTIPLEQTABLE_S;QUEUE NAME ADDRESS---------- ----------- -------------MULTIPLEQ AQUSER2 [email protected] AQUSER1 In this example we have 2 subscribers registered with the queue. We have a local subscriber AQUSER1, and a remote subscriber AQUSER2, on the queue INQ, owned by AQADM, at M2V102.ES. Unless overridden with a recipient list during enqueue every message enqueued to this queue will be propagated to INQ at M2V102.ES.For 8.1 style and above multiple consumer queue tables, you can also check the following information at the target: select CONSUMER_NAME, DEQ_TXN_ID, DEQ_TIME, DEQ_USER_ID, PROPAGATED_MSGID from AQ$<queue_table_name> where QUEUE = '<QUEUE_NAME>'; For 8.0 style queues, if the queue table supports multiple consumers you can obtain the same information from the history column of the queue table: select h.CONSUMER, h.TRANSACTION_ID, h.DEQ_TIME, h.DEQ_USER, h.PROPAGATED_MSGIDfrom AQ$<queue_table_name> t, table(t.history) h where t.Q_NAME = '<QUEUE_NAME>'; A non-NULL TRANSACTION_ID indicates that the message was successfully propagated. Further, the DEQ_TIME indicates the time of propagation, the DEQ_USER indicates the userid used for propagation, and the PROPAGATED_MSGID indicates the message ID of the message that was enqueued at the destination. 6. Additional Troubleshooting Steps for Propagation in an Oracle Streams Environment 6.1. Is the Propagation Enabled? For a propagation job to propagate messages, the propagation must be enabled. For Streams, a special view called DBA_PROPAGATION exists to convey information about Streams propagations. If messages are not being propagated by a propagation as expected, then the propagation might not be enabled. To query for this: SELECT p.PROPAGATION_NAME, DECODE(s.SCHEDULE_DISABLED, 'Y', 'Disabled','N', 'Enabled') SCHEDULE_DISABLED, s.PROCESS_NAME, s.FAILURES, s.LAST_ERROR_MSGFROM DBA_QUEUE_SCHEDULES s, DBA_PROPAGATION pWHERE p.DESTINATION_DBLINK = NVL(REGEXP_SUBSTR(s.DESTINATION, '[^@]+', 1, 2), s.DESTINATION) AND s.SCHEMA = p.SOURCE_QUEUE_OWNER AND s.QNAME = p.SOURCE_QUEUE_NAME AND MESSAGE_DELIVERY_MODE = 'PERSISTENT' order by PROPAGATION_NAME; At times, the propagation job may become "broken" or fail to start after an error has been encountered or after a database restart. If an error is indicated by the above query, an attempt to disable the propagation and then re-enable it can be made. In the examples below, for the propagation named STRMADMIN_PROPAGATE where the queue name is STREAMS_QUEUE owned by STRMADMIN and the destination database link is ORCL2.WORLD, the commands would be:10.2 and above exec dbms_propagation_adm.stop_propagation('STRMADMIN_PROPAGATE'); exec dbms_propagation_adm.start_propagation('STRMADMIN_PROPAGATE'); If the above does not fix the problem, stop the propagation specifying the force parameter (2nd parameter on stop_propagation) as TRUE: exec dbms_propagation_adm.stop_propagation('STRMADMIN_PROPAGATE',true); exec dbms_propagation_adm.start_propagation('STRMADMIN_PROPAGATE'); The statistics for the propagation as well as any old error messages are cleared when the force parameter is set to TRUE. Therefore if the propagation schedule is stopped with FORCE set to TRUE, and upon restart there is still an error message in DBA_PROPAGATION, then the error message is current.9.2 or 10.1 exec dbms_aqadm.disable_propagation_schedule('STRMADMIN.STREAMS_QUEUE','ORCL2.WORLD'); exec dbms.aqadm.enable_propagation_schedule('STRMADMIN.STREAMS_QUEUE','ORCL2.WORLD'); If the above does not fix the problem, perform an unschedule of propagation and then schedule_propagation: exec dbms_aqadm.unschedule_propagation('STRMADMIN.STREAMS_QUEUE','ORCL2.WORLD'); exec dbms_aqadm.schedule_propagation('STRMADMIN.STREAMS_QUEUE','ORCL2.WORLD'); Typically if the error from the first query in Section 6.1 recurs after restarting the propagation as shown above, further troubleshooting of the error is needed. 6.2. Check Propagation Rule Sets and Transformations Inspect the configuration of the rules in the rule set that is associated with the propagation process to make sure that they evaluate to TRUE as expected. If not, then the object or schema will not be propagated. Remember that when a negative rule evaluates to TRUE, the specified object or schema will not be propagated. Finally inspect any rule-based transformations that are implemented with propagation to make sure they are changing the data in the intended way.The following query shows what rule sets are assigned to a propagation: select PROPAGATION_NAME, RULE_SET_OWNER||'.'||RULE_SET_NAME "Positive Rule Set",NEGATIVE_RULE_SET_OWNER||'.'||NEGATIVE_RULE_SET_NAME "Negative Rule Set"from DBA_PROPAGATION; The next two queries list the propagation rules and their conditions. The first is for the positive rule set, the second is for the negative rule set: set long 4000select rsr.RULE_SET_OWNER||'.'||rsr.RULE_SET_NAME RULE_SET ,rsr.RULE_OWNER||'.'||rsr.RULE_NAME RULE_NAME,r.RULE_CONDITION CONDITION fromDBA_RULE_SET_RULES rsr, DBA_RULES rwhere rsr.RULE_NAME = r.RULE_NAME and rsr.RULE_OWNER = r.RULE_OWNER and RULE_SET_NAME in(select RULE_SET_NAME from DBA_PROPAGATION) order by rsr.RULE_SET_OWNER, rsr.RULE_SET_NAME;   set long 4000select c.PROPAGATION_NAME, rsr.RULE_SET_OWNER||'.'||rsr.RULE_SET_NAME RULE_SET ,rsr.RULE_OWNER||'.'||rsr.RULE_NAME RULE_NAME,r.RULE_CONDITION CONDITION fromDBA_RULE_SET_RULES rsr, DBA_RULES r ,DBA_PROPAGATION cwhere rsr.RULE_NAME = r.RULE_NAME and rsr.RULE_OWNER = r.RULE_OWNER andrsr.RULE_SET_OWNER=c.NEGATIVE_RULE_SET_OWNER and rsr.RULE_SET_NAME=c.NEGATIVE_RULE_SET_NAMEand rsr.RULE_SET_NAME in(select NEGATIVE_RULE_SET_NAME from DBA_PROPAGATION) order by rsr.RULE_SET_OWNER, rsr.RULE_SET_NAME; 6.3. Determining the Total Number of Messages and Bytes Propagated As in Section 3.1, determining if messages are flowing can be instructive to see whether the propagation is entirely hung or just slow. If the propagation is not in flow control (see Section 6.5.2), but the statistics are incrementing slowly, there may be a performance issue. For Streams implementations two views are available that can assist with this that can show the number of messages sent by a propagation, as well as the number of acknowledgements being returned from the target site: the V$PROPAGATION_SENDER view at the Source site and the V$PROPAGATION_RECEIVER view at the destination site. It is helpful to query both to determine if messages are being delivered to the target. Look for the statistics to increase.Source: select QUEUE_SCHEMA, QUEUE_NAME, DBLINK,HIGH_WATER_MARK, ACKNOWLEDGEMENT, TOTAL_MSGS, TOTAL_BYTESfrom V$PROPAGATION_SENDER; Target: select SRC_QUEUE_SCHEMA, SRC_QUEUE_NAME, SRC_DBNAME, DST_QUEUE_SCHEMA, DST_QUEUE_NAME, HIGH_WATER_MARK, ACKNOWLEDGEMENT, TOTAL_MSGS from V$PROPAGATION_RECEIVER; 6.4. Check Buffered Subscribers The V$BUFFERED_SUBSCRIBERS view displays information about subscribers for all buffered queues in the instance. This view can be queried to make sure that the site that the propagation is propagating to is listed as a subscriber address for the site being propagated from: select QUEUE_SCHEMA, QUEUE_NAME, SUBSCRIBER_ADDRESS from V$BUFFERED_SUBSCRIBERS; The SUBSCRIBER_ADDRESS column will not be populated when the propagation is local (between queues on the same database). 6.5. Common Streams Propagation Errors 6.5.1. ORA-02082: A loopback database link must have a connection qualifier. This error can occur if you use the Streams Setup Wizard in Oracle Enterprise Manager without first configuring the GLOBAL_NAME for your database. 6.5.2. ORA-25307: Enqueue rate too high. Enable flow control DBA_QUEUE_SCHEDULES will display this informational message for propagation when the automatic flow control (10g feature of Streams) has been invoked.Similar to Streams capture processes, a Streams propagation process can also go into a state of 'flow control. This is an informative message that indicates flow control has been automatically enabled to reduce the rate at which messages are being enqueued into at target queue.This typically occurs when the target site is unable to keep up with the rate of messages flowing from the source site. Other than checking that the apply process is running normally on the target site, usually no action is required by the DBA. Propagation and the capture process will be resumed automatically when the target site is able to accept more messages.The following document contains more information:Document 302109.1 Streams Propagation Error: ORA-25307 Enqueue rate too high. Enable flow controlSee the following document for one potential cause of this situation:Document 1097115.1 Oracle Streams Apply Reader is in 'Paused' State 6.5.3. ORA-25315 unsupported configuration for propagation of buffered messages This error typically occurs when the target database is RAC and usually indicates that an attempt was made to propagate buffered messages with the database link pointing to an instance in the destination database which is not the owner instance of the destination queue. To resolve the problem, use queue-to-queue propagation for buffered messages. 6.5.4. ORA-600 [KWQBMCRCPTS101] after dropping / recreating propagation For cause/fixes refer to:Document 421237.1 ORA-600 [KWQBMCRCPTS101] reported by a Qmon slave process after dropping a Streams Propagation 6.5.5. Stopping or Dropping a Streams Propagation Hangs See the following note:Document 1159787.1 Troubleshooting Streams Propagation When It is Not Functioning and Attempts to Stop It Hang 6.6. Streams Propagation-Related Notes for Common Issues Document 437838.1 Streams Specific PatchesDocument 749181.1 How to Recover Streams After Dropping PropagationDocument 368912.1 Queue to Queue Propagation Schedule encountered ORA-12514 in a RAC environmentDocument 564649.1 ORA-02068/ORA-03114/ORA-03113 Errors From Streams Propagation Process - Remote Database is Available and Unschedule/Reschedule Does Not ResolveDocument 553017.1 Stream Propagation Process Errors Ora-4052 Ora-6554 From 11g To 10201Document 944846.1 Streams Propagation Fails Ora-7445 [kohrsmc]Document 745601.1 ORA-23603 'STREAMS enqueue aborted due to low SGA' Error from Streams Propagation, and V$STREAMS_CAPTURE.STATE Hanging on 'Enqueuing Message'Document 333068.1 ORA-23603: Streams Enqueue Aborted Eue To Low SGADocument 363496.1 Ora-25315 Propagating on RAC StreamsDocument 368237.1 Unable to Unschedule Propagation. Streams Queue is InvalidDocument 436332.1 dbms_propagation_adm.stop_propagation hangsDocument 727389.1 Propagation Fails With ORA-12528Document 730911.1 ORA-4063 Is Reported After Dropping Negative Prop.RulesetDocument 460471.1 Propagation Blocked by Qmon Process - Streams_queue_table / 'library cache lock' waitsDocument 1165583.1 ORA-600 [kwqpuspse0-ack] In Streams EnvironmentDocument 1059029.1 Combined Capture and Apply (CCA) : Capture aborts : ORA-1422 after schedule_propagationDocument 556309.1 Changing Propagation/ queue_to_queue : false -> true does does not work; no LCRs propagatedDocument 839568.1 Propagation failing with error: ORA-01536: space quota exceeded for tablespace ''Document 311021.1 Streams Propagation Process : Ora 12154 After Reboot with Transparent Application Failover TAF configuredDocument 359971.1 STREAMS propagation to Primary of physical Standby configuation errors with Ora-01033, Ora-02068Document 1101616.1 DBMS_PROPAGATION_ADM.DROP_PROPAGATION FAILS WITH ORA-1747 7. Performance Issues A propagation may seem to be slow if the queries from Sections 3.1 and 6.3 show that the message statistics are not changing quickly. In Oracle Streams, this more usually is due to a slow apply process at the target rather than a slow propagation. Propagation could be inferred to be slow if the message statistics are changing, and the state of a capture process according to V$STREAMS_CAPTURE.STATE is PAUSED FOR FLOW CONTROL, but an ORA-25307 'Enqueue rate too high. Enable flow control' warning is NOT observed in DBA_QUEUE_SCHEDULES per Section 6.5.2. If this is the case, see the following notes / white papers for suggestions to increase performance:Document 335516.1 Master Note for Streams Performance RecommendationsDocument 730036.1 Overview for Troubleshooting Streams Performance IssuesDocument 780733.1 Streams Propagation Tuning with Network ParametersWhite Paper: http://www.oracle.com/technetwork/database/features/availability/maa-wp-10gr2-streams-performance-130059.pdfWhite Paper: Oracle Streams Configuration Best Practices: Oracle Database 10g Release 10.2, http://www.oracle.com/technetwork/database/features/availability/maa-10gr2-streams-configuration-132039.pdf, See APPENDIX A: USING STREAMS CONFIGURATIONS OVER A NETWORKFor basic AQ propagation, the network tuning in the aforementioned Appendix A of the white paper 'Oracle Streams Configuration Best Practices: Oracle Database 10g Release 10.2' is applicable. References NOTE:102330.1 - Advanced Queueing MSG_STATE Values and their InterpretationNOTE:102771.1 - Advanced Queueing Propagation using PL/SQLNOTE:1059029.1 - Combined Capture and Apply (CCA) : Capture aborts : ORA-1422 after schedule_propagationNOTE:1079577.1 - Advanced Queuing Propagation Fails With "ORA-22370: incorrect usage of method"NOTE:1083608.1 - 11g Streams and Oracle SchedulerNOTE:1087324.1 - ORA-01405 ORA-01422 reported by Adavanced Queueing Propagation schedules after RAC reconfigurationNOTE:1097115.1 - Oracle Streams Apply Reader is in 'Paused' StateNOTE:1101616.1 - DBMS_PROPAGATION_ADM.DROP_PROPAGATION FAILS WITH ORA-1747NOTE:1159787.1 - Troubleshooting Streams Propagation When It is Not Functioning and Attempts to Stop It HangNOTE:1165583.1 - ORA-600 [kwqpuspse0-ack] In Streams EnvironmentNOTE:118884.1 - How to unschedule a propagation schedule stuck in pending stateNOTE:1203544.1 - AQ PROPAGATION ABORTED WITH ORA-600[OCIKSIN: INVALID STATUS] ON SYS.DBMS_AQADM_SYS.AQ$_PROPAGATION_PROCEDURE AFTER UPGRADENOTE:1204080.1 - AQ Propagation Failing With ORA-25329 After Upgraded From 8i or 9i to 10g or 11g.NOTE:219416.1 - Advanced Queuing Propagation fails with ORA-22922NOTE:222992.1 - DBMS_AQADM.DISABLE_PROPAGATION_SCHEDULE Returns ORA-24082NOTE:253131.1 - Concurrent Writes May Corrupt LOB Segment When Using Auto Segment Space Management (ORA-1555)NOTE:282987.1 - Propagated Messages marked UNDELIVERABLE after Drop and Recreate Of Remote QueueNOTE:298015.1 - Kwqjswproc:Excep After Loop: Assigning To SelfNOTE:302109.1 - Streams Propagation Error: ORA-25307 Enqueue rate too high. Enable flow controlNOTE:311021.1 - Streams Propagation Process : Ora 12154 After Reboot with Transparent Application Failover TAF configuredNOTE:332792.1 - ORA-04061 error relating to SYS.DBMS_PRVTAQIP reported when setting up StatspackNOTE:333068.1 - ORA-23603: Streams Enqueue Aborted Eue To Low SGANOTE:335516.1 - Master Note for Streams Performance RecommendationsNOTE:353325.1 - ORA-24056: Internal inconsistency for QUEUE and destination NOTE:353754.1 - Streams Messaging Propagation Fails between Single and Multi-byte Charactersets when using Chararacter Length Semantics in the ADT.NOTE:359971.1 - STREAMS propagation to Primary of physical Standby configuation errors with Ora-01033, Ora-02068NOTE:363496.1 - Ora-25315 Propagating on RAC StreamsNOTE:365093.1 - ORA-07445 [kwqppay2aqe()+7360] reported on Propagation of a Transformed MessageNOTE:368237.1 - Unable to Unschedule Propagation. Streams Queue is InvalidNOTE:368912.1 - Queue to Queue Propagation Schedule encountered ORA-12514 in a RAC environmentNOTE:421237.1 - ORA-600 [KWQBMCRCPTS101] reported by a Qmon slave process after dropping a Streams PropagationNOTE:436332.1 - dbms_propagation_adm.stop_propagation hangsNOTE:437838.1 - Streams Specific PatchesNOTE:460471.1 - Propagation Blocked by Qmon Process - Streams_queue_table / 'library cache lock' waitsNOTE:463820.1 - Streams Combined Capture and Apply in 11gNOTE:553017.1 - Stream Propagation Process Errors Ora-4052 Ora-6554 From 11g To 10201NOTE:556309.1 - Changing Propagation/ queue_to_queue : false -> true does does not work; no LCRs propagatedNOTE:564649.1 - ORA-02068/ORA-03114/ORA-03113 Errors From Streams Propagation Process - Remote Database is Available and Unschedule/Reschedule Does Not ResolveNOTE:566622.1 - ORA-22275 when propagating >4K AQ$_JMS_TEXT_MESSAGEs from 9.2.0.8 to 10.2.0.1NOTE:727389.1 - Propagation Fails With ORA-12528NOTE:730036.1 - Overview for Troubleshooting Streams Performance IssuesNOTE:730911.1 - ORA-4063 Is Reported After Dropping Negative Prop.RulesetNOTE:731292.1 - ORA-25215 Reported On Local Propagation When Using Transformation with ANYDATA queue tablesNOTE:731539.1 - ORA-29268: HTTP client error 401 Unauthorized Error when the AQ Servlet attempts to Propagate a message via HTTPNOTE:745601.1 - ORA-23603 'STREAMS enqueue aborted due to low SGA' Error from Streams Propagation, and V$STREAMS_CAPTURE.STATE Hanging on 'Enqueuing Message'NOTE:749181.1 - How to Recover Streams After Dropping PropagationNOTE:780733.1 - Streams Propagation Tuning with Network ParametersNOTE:787367.1 - ORA-22275 reported on Propagating Messages with LOB component when propagating between 10.1 and 10.2NOTE:808136.1 - How to clear the old errors from DBA_PROPAGATION view ?NOTE:827184.1 - AQ Propagation with CLOB data types Fails with ORA-22990NOTE:827473.1 - How to alter propagation from queue_to_queue to queue_to_dblinkNOTE:839568.1 - Propagation failing with error: ORA-01536: space quota exceeded for tablespace ''NOTE:846297.1 - AQ Propagation Fails : ORA-00600[kope2upic2954] or Ora-00600[Kghsstream_copyn]NOTE:944846.1 - Streams Propagation Fails Ora-7445 [kohrsmc]

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  • Mark Hurd and Balaji Yelamanchili present Oracle’s Business Analytics Strategy

    - by swalker
    Join Mark Hurd and Balaji Yelamanchili as they unveil the latest advances in Oracle’s strategy for placing analytics into the hands of every decision-makers—so that they can see more, think smarter, and act faster. Wednesday, April 4, 2012 at 1.0 pm UK BST / 2.0 pm CET Register HERE today for this online event Agenda Keynote: Oracle’s Business Analytics StrategyMark Hurd, President, Oracle, and Balaji Yelamanchili, Senior Vice President, Analytics and Performance Management, Oracle Plus Breakout Sessions: Achieving Predictable Performance with Oracle Hyperion Enterprise Performance Managemen Explore All Relevant Data—Introducing Oracle Endeca Information Discovery Run Your Business Faster and Smarter with Oracle Business Intelligence Applications on Oracle Exalytics In-Memory Machine Analyzing and Deciding with Big Data

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  • SQL SERVER – Weekly Series – Memory Lane – #033

    - by Pinal Dave
    Here is the list of selected articles of SQLAuthority.com across all these years. Instead of just listing all the articles I have selected a few of my most favorite articles and have listed them here with additional notes below it. Let me know which one of the following is your favorite article from memory lane. 2007 Spatial Database Definition and Research Documents Here is the definition from Wikipedia about spatial database : A spatial database is a database that is optimized to store and query data related to objects in space, including points, lines and polygons. While typical databases can understand various numeric and character types of data, additional functionality needs to be added for databases to process spatial data types. Select Only Date Part From DateTime – Best Practice A very common question which I receive is how to only get Date or Time part from datetime value. In this blog post I explain the same in very simple words. T-SQL Paging Query Technique Comparison (OVER and ROW_NUMBER()) – CTE vs. Derived Table I have received few emails and comments about my post SQL SERVER – T-SQL Paging Query Technique Comparison – SQL 2000 vs SQL 2005. The main question was is this can be done using CTE? Absolutely! What about Performance? It is identical! Please refer above mentioned article for the history of paging. SQL SERVER – Cannot resolve collation conflict for equal to operation One of the very first error I ever encountered in my career was to resolve this conflict. I have blogged about it and I have realized that many others like me who are facing this error. LEN and DATALENGTH of NULL Simple Example Here is the question for you what is the LEN of NULL value? Well it is very easy – just read the blog. Recovery Models and Selection Very simple and easy explanation of the Database Backup Recovery Model and how to select the best option for you. Explanation SQL SERVER Hash Join Hash join gives best performance when two more join tables are joined and at-least one of them have no index or is not sorted. It is also expected that smaller of the either of table can be read in memory completely (though not necessary). Easy Sequence of SELECT FROM JOIN WHERE GROUP BY HAVING ORDER BY SELECT yourcolumns FROM tablenames JOIN tablenames WHERE condition GROUP BY yourcolumns HAVING aggregatecolumn condition ORDER BY yourcolumns NorthWind Database or AdventureWorks Database – Samples Databases In this blog post we learn how to install Northwind database. I also shared the source where one can download this database as that is used in many examples on MSDN help files. sp_HelpText for sp_HelpText – Puzzle A simple quick puzzle – do you know the answer of it? If not, go ahead and read the blog. 2008 SQL SERVER – 2008 – Step By Step Installation Guide With Images When SQL Server 2008 was newly introduced lots of people had no clue how to install SQL Server 2008 and the amount of the question which I used to receive were so much. I wrote this blog post with the spirit that this will help all the newbies to install SQL Server 2008 with the help of images. Still today this blog post has been bible for all of the people who are confused with SQL Server installation. Inline Variable Assignment I loved this feature. I have always wanted this feature to be present in SQL Server. The last time when I met developers from Microsoft SQL Server, I had talked about this feature. I think this feature saves some time but make the code more readable. Introduction to Policy Management – Enforcing Rules on SQL Server If our company policy is to create all the Stored Procedure with prefix ‘usp’ that developers should be just prevented to create Stored Procedure with any other prefix. Let us see a small tutorial how to create conditions and policy which will prevent any future SP to be created with any other prefix. 2009 Performance Counters from System Views – By Kevin Mckenna Many of you are not aware of this fact that access to performance information is readily available in SQL Server and that too without querying performance counters using a custom application or via perfmon. Till now, this fact has remained undisclosed but through this post I would like to explain you can easily access SQL Server performance counter information. Without putting much effort you will come across the system viewsys.dm_os_performance_counters. As the name suggests, this provides you easy access to the SQL Server performance counter information that is passed on to perfmon, but you can get at it via tsql. Customize Toolbar – Remove Debug Button from Toolbar I was fond of SQL Server Debugger feature in SQL Server 2000. To my utter disappointment, this feature was withdrawn from SQL Server 2005. The button of the debugger is similar to a play button and is used to run debugging commands of Visual Studio. Because of this reason, it gets very much infuriating for developers when they are developing on both – Visual Studio and SSMS. Let us now see how we can remove debugging button from SQL Server Management Studio. Effect of Normalization on Index and Performance A very interesting conversation which started from twitter. If you want to read one link this is the link I encourage you to read it. SSMS Feature – Multi-server Queries Using SQL Server Management Studio (SSMS) DBAs can now query multiple servers from one window. It is quite common for DBAs with large amount of servers to maintain and gather information from multiple SQL Servers and create report. This feature is a blessing for the DBAs, as they can now assemble all the information instantaneously without going anywhere. Query Optimizer Hint ROBUST PLAN – Question to You “ROBUST PLAN” is a kind of query hint which works quite differently than other hints. It does not improve join or force any indexes to use; it just makes sure that a query does not crash due to over the limit size of row. Let me elaborate upon it in the blog post. 2010 Do you really know the difference between various date functions available in SQL Server 2012? Here is a three part story where we explored the same with examples: Fastest Way to Restore the Database Difference Between DATETIME and DATETIME2 Difference Between DATETIME and DATETIME2 – WITH GETDATE Shrinking NDF and MDF Files – Readers’ Opinion Shrinking Database always creates performance degradation and increases fragmentation in the database. I suggest that you keep that in mind before you start reading the following comment. If you are going to say Shrinking Database is bad and evil, here I am saying it first and loud. Now, the comment of Imran is written while keeping in mind only the process showing how the Shrinking Database Operation works. Imran has already explained his understanding and requests further explanation. I have removed the Best Practices section from Imran’s comments, as there are a few corrections. 2011 Solution – Puzzle – SELECT * vs SELECT COUNT(*) This is very interesting question and I am very confident that not every one knows the answer to this question. Let me ask you again – Which will be faster SELECT* or SELECT COUNT (*) or do you think this is apples and oranges comparison. 2012 Service Broker and CAP_CPU_PERCENT – Limiting SQL Server Instances to CPU Usage In SQL Server 2012 there are a few enhancements with regards to SQL Server Resource Governor. One of the enhancement is how the resources are allocated. Let me explain you with examples. Let us understand the entire discussion with the help of three different examples. Finding Size of a Columnstore Index Using DMVs One of the very common question I often see is need of the list of columnstore index along with their size and corresponding table name. I quickly re-wrote a script using DMVs sys.indexes and sys.dm_db_partition_stats. This script gives the size of the columnstore index on disk only. I am sure there will be advanced script to retrieve details related to components associated with the columnstore index. However, I believe following script is sufficient to start getting an idea of columnstore index size. Developer Training Resources and Summary Roundup Developer Training - Importance and Significance - Part 1 In this part we discussed the importance of training in the real world. The most important and valuable resource any company is its employee. Employees who have been well-trained will be better at their jobs and produce a better product.  An employee who is well trained obviously knows more about their job and all the technical aspects. I have a very high opinion about training employees and it is the most important task. Developer Training – Employee Morals and Ethics – Part 2 In this part we discussed the most crucial components of training. Often employees are expecting the company to pay for their training and the company expresses no interest in training the employee. Quite often training expenses are the real issue for both the employee and employer. Developer Training – Difficult Questions and Alternative Perspective - Part 3 This part was the most difficult to write as I tried to address a few difficult questions and answers. Training is such a sensitive issue that many developers when not receiving chance for training think about leaving the organization. Developer Training – Various Options for Developer Training – Part 4 In this part I tried to explore a few methods and options for training. The generic feedback I received on this blog post was short and I should have explored each of the subject of the training in details. I believe there are two big buckets of training 1) Instructor Lead Training and 2) Self Lead Training. Developer Training – A Conclusive Summary- Part 5 There is no better motivation than a personal desire to learn new technology. Honestly there is nothing more personal learning. That “change is the only constant” and “adapt & overcome” are the essential lessons of life. One cannot stop the learning and resist the change. In the IT industry “ego of knowing all” and the “resistance to change” are the most challenging issues. A Quick Look at Logging and Ideas around Logging Question: What is the first thing comes to your mind when you hear the word “Logging”? Strange enough I got a different answer every single time. Let me just list what answer I got from my friends. Let us go over them one by one. Beginning Performance Tuning with SQL Server Execution Plan Solution of Puzzle – Swap Value of Column Without Case Statement Earlier this week I asked a question where I asked how to Swap Values of the column without using CASE Statement. Read here: SQL SERVER – A Puzzle – Swap Value of Column Without Case Statement. I have proposed 3 different solutions in the blog posts itself. I had requested the help of the community to come up with alternate solutions and honestly I am stunned and amazed by the qualified entries. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Memory Lane, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Cheatsheet: 2010 04.01 ~ 04.07

    - by gOODiDEA
    Web Web Performance Best Practices: How masters.com re-designed their site to boost performance – and what that re-design missed What’s wrong with extending the DOM John Resig on Advanced Javascript to Improve your Web App .NET Hammock for REST - a REST library for .NET Programming Windows Phone 7 Series by Charlez Petzold – Free EBook Testing the Lock-Free Queue Some Last-Minute New C# 4.0 Features - while (x --> 0) { Console.WriteLine("x = {0}", x); } Better Coding with Visual Studio 2010 Revisiting Asynchronous ASP.NET Pages Database Understanding RAID for SQL Server – Part 2 Cassandra Jump Start For The Windows Developer Cassandra Internals – Writing - Cassandra Write Operation Performance Explained Cassandra Internals – Reading - Cassandra Reads Performance Explained MongoDB Growing Up: Release 1.4 and Commercial Support by 10gen Why NoSQL Will Not Die How Many Hard Drives Do I Need to Support SQL Server? Other Presentation: CouchDB and Lucene MongoDB Cacti Graphs HBase vs Cassandra: why we moved How to use the DedicatedDumpFile registry value to overcome space limitations on the system drive when capturing a system memory dump

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  • New Bundling and Minification Support (ASP.NET 4.5 Series)

    - by ScottGu
    This is the sixth in a series of blog posts I'm doing on ASP.NET 4.5. The next release of .NET and Visual Studio include a ton of great new features and capabilities.  With ASP.NET 4.5 you'll see a bunch of really nice improvements with both Web Forms and MVC - as well as in the core ASP.NET base foundation that both are built upon. Today’s post covers some of the work we are doing to add built-in support for bundling and minification into ASP.NET - which makes it easy to improve the performance of applications.  This feature can be used by all ASP.NET applications, including both ASP.NET MVC and ASP.NET Web Forms solutions. Basics of Bundling and Minification As more and more people use mobile devices to surf the web, it is becoming increasingly important that the websites and apps we build perform well with them. We’ve all tried loading sites on our smartphones – only to eventually give up in frustration as it loads slowly over a slow cellular network.  If your site/app loads slowly like that, you are likely losing potential customers because of bad performance.  Even with powerful desktop machines, the load time of your site and perceived performance can make an enormous customer perception. Most websites today are made up of multiple JavaScript and CSS files to separate the concerns and keep the code base tight. While this is a good practice from a coding point of view, it often has some unfortunate consequences for the overall performance of the website.  Multiple JavaScript and CSS files require multiple HTTP requests from a browser – which in turn can slow down the performance load time.  Simple Example Below I’ve opened a local website in IE9 and recorded the network traffic using IE’s built-in F12 developer tools. As shown below, the website consists of 5 CSS and 4 JavaScript files which the browser has to download. Each file is currently requested separately by the browser and returned by the server, and the process can take a significant amount of time proportional to the number of files in question. Bundling ASP.NET is adding a feature that makes it easy to “bundle” or “combine” multiple CSS and JavaScript files into fewer HTTP requests. This causes the browser to request a lot fewer files and in turn reduces the time it takes to fetch them.   Below is an updated version of the above sample that takes advantage of this new bundling functionality (making only one request for the JavaScript and one request for the CSS): The browser now has to send fewer requests to the server. The content of the individual files have been bundled/combined into the same response, but the content of the files remains the same - so the overall file size is exactly the same as before the bundling.   But notice how even on a local dev machine (where the network latency between the browser and server is minimal), the act of bundling the CSS and JavaScript files together still manages to reduce the overall page load time by almost 20%.  Over a slow network the performance improvement would be even better. Minification The next release of ASP.NET is also adding a new feature that makes it easy to reduce or “minify” the download size of the content as well.  This is a process that removes whitespace, comments and other unneeded characters from both CSS and JavaScript. The result is smaller files, which will download and load in a browser faster.  The graph below shows the performance gain we are seeing when both bundling and minification are used together: Even on my local dev box (where the network latency is minimal), we now have a 40% performance improvement from where we originally started.  On slow networks (and especially with international customers), the gains would be even more significant. Using Bundling and Minification inside ASP.NET The upcoming release of ASP.NET makes it really easy to take advantage of bundling and minification within projects and see performance gains like in the scenario above. The way it does this allows you to avoid having to run custom tools as part of your build process –  instead ASP.NET has added runtime support to perform the bundling/minification for you dynamically (caching the results to make sure perf is great).  This enables a really clean development experience and makes it super easy to start to take advantage of these new features. Let’s assume that we have a simple project that has 4 JavaScript files and 6 CSS files: Bundling and Minifying the .css files Let’s say you wanted to reference all of the stylesheets in the “Styles” folder above on a page.  Today you’d have to add multiple CSS references to get all of them – which would translate into 6 separate HTTP requests: The new bundling/minification feature now allows you to instead bundle and minify all of the .css files in the Styles folder – simply by sending a URL request to the folder (in this case “styles”) with an appended “/css” path after it.  For example:    This will cause ASP.NET to scan the directory, bundle and minify the .css files within it, and send back a single HTTP response with all of the CSS content to the browser.  You don’t need to run any tools or pre-processor to get this behavior.  This enables you to cleanly separate your CSS into separate logical .css files and maintain a very clean development experience – while not taking a performance hit at runtime for doing so.  The Visual Studio designer will also honor the new bundling/minification logic as well – so you’ll still get a WYSWIYG designer experience inside VS as well. Bundling and Minifying the JavaScript files Like the CSS approach above, if we wanted to bundle and minify all of our JavaScript into a single response we could send a URL request to the folder (in this case “scripts”) with an appended “/js” path after it:   This will cause ASP.NET to scan the directory, bundle and minify the .js files within it, and send back a single HTTP response with all of the JavaScript content to the browser.  Again – no custom tools or builds steps were required in order to get this behavior.  And it works with all browsers. Ordering of Files within a Bundle By default, when files are bundled by ASP.NET they are sorted alphabetically first, just like they are shown in Solution Explorer. Then they are automatically shifted around so that known libraries and their custom extensions such as jQuery, MooTools and Dojo are loaded before anything else. So the default order for the merged bundling of the Scripts folder as shown above will be: Jquery-1.6.2.js Jquery-ui.js Jquery.tools.js a.js By default, CSS files are also sorted alphabetically and then shifted around so that reset.css and normalize.css (if they are there) will go before any other file. So the default sorting of the bundling of the Styles folder as shown above will be: reset.css content.css forms.css globals.css menu.css styles.css The sorting is fully customizable, though, and can easily be changed to accommodate most use cases and any common naming pattern you prefer.  The goal with the out of the box experience, though, is to have smart defaults that you can just use and be successful with. Any number of directories/sub-directories supported In the example above we just had a single “Scripts” and “Styles” folder for our application.  This works for some application types (e.g. single page applications).  Often, though, you’ll want to have multiple CSS/JS bundles within your application – for example: a “common” bundle that has core JS and CSS files that all pages use, and then page specific or section specific files that are not used globally. You can use the bundling/minification support across any number of directories or sub-directories in your project – this makes it easy to structure your code so as to maximize the bunding/minification benefits.  Each directory by default can be accessed as a separate URL addressable bundle.  Bundling/Minification Extensibility ASP.NET’s bundling and minification support is built with extensibility in mind and every part of the process can be extended or replaced. Custom Rules In addition to enabling the out of the box - directory-based - bundling approach, ASP.NET also supports the ability to register custom bundles using a new programmatic API we are exposing.  The below code demonstrates how you can register a “customscript” bundle using code within an application’s Global.asax class.  The API allows you to add/remove/filter files that go into the bundle on a very granular level:     The above custom bundle can then be referenced anywhere within the application using the below <script> reference:     Custom Processing You can also override the default CSS and JavaScript bundles to support your own custom processing of the bundled files (for example: custom minification rules, support for Saas, LESS or Coffeescript syntax, etc). In the example below we are indicating that we want to replace the built-in minification transforms with a custom MyJsTransform and MyCssTransform class. They both subclass the CSS and JavaScript minifier respectively and can add extra functionality:     The end result of this extensibility is that you can plug-into the bundling/minification logic at a deep level and do some pretty cool things with it. 2 Minute Video of Bundling and Minification in Action Mads Kristensen has a great 90 second video that shows off using the new Bundling and Minification feature.  You can watch the 90 second video here. Summary The new bundling and minification support within the next release of ASP.NET will make it easier to build fast web applications.  It is really easy to use, and doesn’t require major changes to your existing dev workflow.  It is also supports a rich extensibility API that enables you to customize it however you want. You can easily take advantage of this new support within ASP.NET MVC, ASP.NET Web Forms and ASP.NET Web Pages based applications. Hope this helps, Scott P.S. In addition to blogging, I use Twitter to-do quick posts and share links. My Twitter handle is: @scottgu

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  • Intel Xeon 5600 (Westmere-EP) and 7500 (Nehalem-EX)

    - by jchang
    Intel Xeon 5600 (Westmere-EP) and 7500 (Nehalem-EX) Performance Intel launched the Xeon 5600 series (Westmere-EP, 32nm) six-core processors on 16 March 2010 without any TPC benchmark results. In the performance world, no results almost always mean bad or not good results. Yet there is every reason to believe that the Xeon 5600 series with six-cores (X models only) will performance exactly as expected for a 50% increase in the number of cores at the same frequency (as the 5500) with no system level...(read more)

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  • Tuning GlassFish for Production

    - by arungupta
    The GlassFish distribution is optimized for developers and need simple deployment and server configuration changes to provide the performance typically required for production usage. The formal Performance Tuning Guide provides an explanation of capacity planning and tuning tips for application, GlassFish, JVM, and the operating system. The GlassFish Server Control (only with the commercial edition) also comes with Performance Tuner that optimizes the runtime for optimal throughput and scalability. And then there are multiple blogs that provide more insights as well: • Optimizing GlassFish for Production (Diego Silva, Mar 2012) • GlassFish Production Tuning (Vegard Skjefstad, Nov 2011) • GlassFish in Production (Sunny Saxena, Jul 2011) • Putting GlassFish v3 in Production: Essential Surviving Guide (JeanFrancois, Nov 2009) • A GlassFish Tuning Primer (Scott Oaks, Dec 2007) What is your favorite source for GlassFish Performance Tuning ?

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  • New Exadata Book Available Soon

    - by Rob Reynolds
    Oracle Press is set to released the first book on data warehouse performance and Exadata on March 14th. Achieving Extreme Performance with Oracle Exadata , by my colleagues Rick Greenwald, Robert Stackowiak, Maqsood Alam, and Mans Bhuller will be available at your favorite booksellers next week. I've seen a sneak peak of the content in this book and its a great way to fully grasp the power of Exadata and how to best apply it to achieve extreme data warehouse performance. From the publisher's description: Achieving Extreme Performance with Oracle Exadata and the Sun Oracle Database Machine is filled with best practices for deployments, hardware sizing, architecting the database machine environments for maximum availability, and backup and recovery. Oracle Database 11gR2 features used within these offerings, as well as migration options and paths for Oracle and non-Oracle databases to Oracle Exadata are covered. This Oracle Press guide also discusses architecture, administration, maintenance, monitoring, and tuning of Oracle Exadata Storage Servers and the Sun Oracle Database Machine. If your company is considering Exadata, or if you need more horsepower out of your data warehouse, I highly recommend grabbing a copy of this book next week.

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  • Oracle Hyperion si conferma leader nel Magic Quadrant Gartner 2012

    - by Andrea Cravero
    L'edizione 2012 del Gartner Magic Quadrant for Corporate Performance Management Suites conferma la leadership Oracle Hyperion, che dura ininterrotta dal 2005. Secondo Gartner, "Oracle is a Leader in CPM suites, with one of the most widely distributed solutions in the market. Oracle Hyperion Enterprise Performance Management is recognized by CFOs worldwide. The vendor has a well-established partner channel, with both large and smaller CPM SI specialists. Hyperion skills are also plentiful among the independent consultant community, given the well-established products." "Oracle continues to innovate, bringing incremental improvements across the portfolio as well as new financial close management, disclosure management and predictive planning additions. Furthermore, Oracle has improved integration of Hyperion with the Oracle BI platform, and has improved planning performance, enabling Hyperion Planning to use Oracle Exalytics In-Memory Machine." Il rapporto completo è disponibile qui: Gartner: Magic Quadrant for Corporate Performance Management Suites, 2012 Buona lettura!

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