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  • Vagrant (Virtualbox) host-only multiple node networking issue

    - by Lorin Hochstein
    I'm trying to use a multi-VM vagrant environment as a testbed for deploying OpenStack, and I've run into a networking problem with trying to communicate from one VM, to a VM-inside-of-a-VM. I have two Vagrant nodes, a cloud controller node and a compute node. I'm using host-only networking. My Vagrantfile looks like this: Vagrant::Config.run do |config| config.vm.box = "precise64" config.vm.define :controller do |controller_config| controller_config.vm.network :hostonly, "192.168.206.130" # eth1 controller_config.vm.network :hostonly, "192.168.100.130" # eth2 controller_config.vm.host_name = "controller" end config.vm.define :compute1 do |compute1_config| compute1_config.vm.network :hostonly, "192.168.206.131" # eth1 compute1_config.vm.network :hostonly, "192.168.100.131" # eth2 compute1_config.vm.host_name = "compute1" compute1_config.vm.customize ["modifyvm", :id, "--memory", 1024] end end When I try to start up a (QEMU-based) VM, it boots successfully on compute1, and its virtual nic (vnet0) is connected via a bridge, br100: root@compute1:~# brctl show 100 bridge name bridge id STP enabled interfaces br100 8000.08002798c6ef no eth2 vnet0 When the QEMU VM makes a request to the DHCP server (dnsmasq) running on controller, I can see the request reaches the controller because of the output on the syslog on the controller: Aug 6 02:34:56 precise64 dnsmasq-dhcp[12042]: DHCPDISCOVER(br100) fa:16:3e:07:98:11 Aug 6 02:34:56 precise64 dnsmasq-dhcp[12042]: DHCPOFFER(br100) 192.168.100.2 fa:16:3e:07:98:11 However, the DHCPOFFER never makes it back to the VM running on compute1. If I watch the requests using tcpdump on the vboxnet3 interface on my host machine that runs Vagrant (Mac OS X), I can see both the requests and the replies $ sudo tcpdump -i vboxnet3 -n port 67 or port 68 tcpdump: WARNING: vboxnet3: That device doesn't support promiscuous mode (BIOCPROMISC: Operation not supported on socket) tcpdump: verbose output suppressed, use -v or -vv for full protocol decode listening on vboxnet3, link-type EN10MB (Ethernet), capture size 65535 bytes 22:51:20.694040 IP 0.0.0.0.68 > 255.255.255.255.67: BOOTP/DHCP, Request from fa:16:3e:07:98:11, length 280 22:51:20.694057 IP 0.0.0.0.68 > 255.255.255.255.67: BOOTP/DHCP, Request from fa:16:3e:07:98:11, length 280 22:51:20.696047 IP 192.168.100.1.67 > 192.168.100.2.68: BOOTP/DHCP, Reply, length 311 22:51:23.700845 IP 0.0.0.0.68 > 255.255.255.255.67: BOOTP/DHCP, Request from fa:16:3e:07:98:11, length 280 22:51:23.700876 IP 0.0.0.0.68 > 255.255.255.255.67: BOOTP/DHCP, Request from fa:16:3e:07:98:11, length 280 22:51:23.701591 IP 192.168.100.1.67 > 192.168.100.2.68: BOOTP/DHCP, Reply, length 311 22:51:26.705978 IP 0.0.0.0.68 > 255.255.255.255.67: BOOTP/DHCP, Request from fa:16:3e:07:98:11, length 280 22:51:26.705995 IP 0.0.0.0.68 > 255.255.255.255.67: BOOTP/DHCP, Request from fa:16:3e:07:98:11, length 280 22:51:26.706527 IP 192.168.100.1.67 > 192.168.100.2.68: BOOTP/DHCP, Reply, length 311 But, if I tcpdump on eth2 on compute, I only see the requests, not the replies: root@compute1:~# tcpdump -i eth2 -n port 67 or port 68 tcpdump: WARNING: eth2: no IPv4 address assigned tcpdump: verbose output suppressed, use -v or -vv for full protocol decode listening on eth2, link-type EN10MB (Ethernet), capture size 65535 bytes 02:51:20.240672 IP 0.0.0.0.68 > 255.255.255.255.67: BOOTP/DHCP, Request from fa:16:3e:07:98:11, length 280 02:51:23.249758 IP 0.0.0.0.68 > 255.255.255.255.67: BOOTP/DHCP, Request from fa:16:3e:07:98:11, length 280 02:51:26.258281 IP 0.0.0.0.68 > 255.255.255.255.67: BOOTP/DHCP, Request from fa:16:3e:07:98:11, length 280 At this point, I'm stuck. I'm not sure why the DHCP replies aren't making it to the compute node. Perhaps it has something to do with the configuration of the VirtualBox virtual switch/router? Note that eth2 interfaces on both nodes have been set to promiscuous mode.

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  • Yet again: "This device can perform faster" (Samsung Galaxy Tab 2)

    - by Mike C
    I've been doing a lot of research with no reasonable solution. Please excuse the length of my post. When I plug my Galaxy Tab 2 (7" / Wi-Fi only / Android ICS) into my Windows 7 64-bit machine, I (almost always) get this warning popup that "This device can perform faster." And in fact, transfers onto the Tab in this mode are slow. The two times I've been able to get a high-speed connection, the transfer has occurred at the expected speed. I just don't know what to do to get that high-speed transfer. (The first time I did, it was the first time I connected the Tab; the second time I did, I was fiddling around and unplugging/plugging in again.) That popup is telling me that the device is USB2, but that it thinks I've connected to a USB1 port. In fact, every USB port (there are ten) on this system is USB2. It's an ASUS M3A78-EMH mobo from late 2008. I'm not sure what the chipset is; the CPU is an AMD Athlon 4850e, but I've seen this message reported for non-AMD systems. (Every mobo reference I've seen in reports on this has been for Asus, but of course most reporters aren't reporting that info at all.) The Windows 7 installation is just a couple weeks old (I had a disk crash) but I saw the same warning on the WinXP/64 that was installed previously. In Device Manager, there are two "Standard Enhanced PCI to USB Host Controller" nodes which are the actual high-speed controllers. There are also five "Standard OpenHCD USB Host Controller" nodes, which I have determined are virtual USB1 controllers embedded in the "Enhanced" controllers. (In Device Manager, I'm using View|Devices by Connection.) My high-speed thumb drives, external disks, and iPod all show up as subnodes of the "Enhanced" controllers; the keyboard, mouse, and USB speakers under the "OpenHCD" ones -- and this is true no matter which ports these devices are plugged into. The Tab shows up under an OpenHCD node, unsurprisingly. It appears as a threesome: a top-level "Mobile USB Composite device" with two subs: "Galaxy Tab 2" and "Mobile USB Modem." (I have no idea what the modem device implies or how I might use it, but I don't care about it either: I just want the Tab to reliably connect at high speed.) On the Tab, the USB support has a switch between PTP and MTP, the latter being the default, and the preferred mode for me (as I'm usually hooking it up for music synch). I have tried, however, connecting it as PTP, and it still connects as USB 1. (As PTP, only the "Galaxy Tab 2" device appears -- no Composite, no Modem.) If it's plugged in as MTP and I change the setting to PTP, Windows unloads and reloads the device, and voila: The Tab appears under an "Enhanced" node, but eventually re-loads again to show a exclamation icon on the device; Properties then shows "This device cannot start." Same response if I plug it in as PTP and then change to MTP; in this case, only the Tab itself shows the exclamation, not the other two devices. One thing I have not tried, and really would prefer to avoid, is installing the "beta" chipset driver available on the Asus website, which is dated 2009. Windows tells me it has the most up-to-date drivers for the Tab, and for the chipset, and I'm inclined to believe that. I suspect the problem is with the Samsung drivers, or possibly the hardware. One suggestion I saw elsewhere which might, possibly, pertain is to ensure the USB cable is properly shielded; however, the Tab has one of those misbegotten 30-pin, not-quite-an-iPod connectors; I don't know if I could find a 3rd party one. It seems unlikely that this cable is improperly shielded, tho. (Is there a way to test that?) So, my question is: does anyone know how to get this working as one might reasonably expect it to?

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  • Session memory – who’s this guy named Max and what’s he doing with my memory?

    - by extended_events
    SQL Server MVP Jonathan Kehayias (blog) emailed me a question last week when he noticed that the total memory used by the buffers for an event session was larger than the value he specified for the MAX_MEMORY option in the CREATE EVENT SESSION DDL. The answer here seems like an excellent subject for me to kick-off my new “401 – Internals” tag that identifies posts where I pull back the curtains a bit and let you peek into what’s going on inside the extended events engine. In a previous post (Option Trading: Getting the most out of the event session options) I explained that we use a set of buffers to store the event data before  we write the event data to asynchronous targets. The MAX_MEMORY along with the MEMORY_PARTITION_MODE defines how big each buffer will be. Theoretically, that means that I can predict the size of each buffer using the following formula: max memory / # of buffers = buffer size If it was that simple I wouldn’t be writing this post. I’ll take “boundary” for 64K Alex For a number of reasons that are beyond the scope of this blog, we create event buffers in 64K chunks. The result of this is that the buffer size indicated by the formula above is rounded up to the next 64K boundary and that is the size used to create the buffers. If you think visually, this means that the graph of your max_memory option compared to the actual buffer size that results will look like a set of stairs rather than a smooth line. You can see this behavior by looking at the output of dm_xe_sessions, specifically the fields related to the buffer sizes, over a range of different memory inputs: Note: This test was run on a 2 core machine using per_cpu partitioning which results in 5 buffers. (Seem my previous post referenced above for the math behind buffer count.) input_memory_kb total_regular_buffers regular_buffer_size total_buffer_size 637 5 130867 654335 638 5 130867 654335 639 5 130867 654335 640 5 196403 982015 641 5 196403 982015 642 5 196403 982015 This is just a segment of the results that shows one of the “jumps” between the buffer boundary at 639 KB and 640 KB. You can verify the size boundary by doing the math on the regular_buffer_size field, which is returned in bytes: 196403 – 130867 = 65536 bytes 65536 / 1024 = 64 KB The relationship between the input for max_memory and when the regular_buffer_size is going to jump from one 64K boundary to the next is going to change based on the number of buffers being created. The number of buffers is dependent on the partition mode you choose. If you choose any partition mode other than NONE, the number of buffers will depend on your hardware configuration. (Again, see the earlier post referenced above.) With the default partition mode of none, you always get three buffers, regardless of machine configuration, so I generated a “range table” for max_memory settings between 1 KB and 4096 KB as an example. start_memory_range_kb end_memory_range_kb total_regular_buffers regular_buffer_size total_buffer_size 1 191 NULL NULL NULL 192 383 3 130867 392601 384 575 3 196403 589209 576 767 3 261939 785817 768 959 3 327475 982425 960 1151 3 393011 1179033 1152 1343 3 458547 1375641 1344 1535 3 524083 1572249 1536 1727 3 589619 1768857 1728 1919 3 655155 1965465 1920 2111 3 720691 2162073 2112 2303 3 786227 2358681 2304 2495 3 851763 2555289 2496 2687 3 917299 2751897 2688 2879 3 982835 2948505 2880 3071 3 1048371 3145113 3072 3263 3 1113907 3341721 3264 3455 3 1179443 3538329 3456 3647 3 1244979 3734937 3648 3839 3 1310515 3931545 3840 4031 3 1376051 4128153 4032 4096 3 1441587 4324761 As you can see, there are 21 “steps” within this range and max_memory values below 192 KB fall below the 64K per buffer limit so they generate an error when you attempt to specify them. Max approximates True as memory approaches 64K The upshot of this is that the max_memory option does not imply a contract for the maximum memory that will be used for the session buffers (Those of you who read Take it to the Max (and beyond) know that max_memory is really only referring to the event session buffer memory.) but is more of an estimate of total buffer size to the nearest higher multiple of 64K times the number of buffers you have. The maximum delta between your initial max_memory setting and the true total buffer size occurs right after you break through a 64K boundary, for example if you set max_memory = 576 KB (see the green line in the table), your actual buffer size will be closer to 767 KB in a non-partitioned event session. You get “stepped up” for every 191 KB block of initial max_memory which isn’t likely to cause a problem for most machines. Things get more interesting when you consider a partitioned event session on a computer that has a large number of logical CPUs or NUMA nodes. Since each buffer gets “stepped up” when you break a boundary, the delta can get much larger because it’s multiplied by the number of buffers. For example, a machine with 64 logical CPUs will have 160 buffers using per_cpu partitioning or if you have 8 NUMA nodes configured on that machine you would have 24 buffers when using per_node. If you’ve just broken through a 64K boundary and get “stepped up” to the next buffer size you’ll end up with total buffer size approximately 10240 KB and 1536 KB respectively (64K * # of buffers) larger than max_memory value you might think you’re getting. Using per_cpu partitioning on large machine has the most impact because of the large number of buffers created. If the amount of memory being used by your system within these ranges is important to you then this is something worth paying attention to and considering when you configure your event sessions. The DMV dm_xe_sessions is the tool to use to identify the exact buffer size for your sessions. In addition to the regular buffers (read: event session buffers) you’ll also see the details for large buffers if you have configured MAX_EVENT_SIZE. The “buffer steps” for any given hardware configuration should be static within each partition mode so if you want to have a handy reference available when you configure your event sessions you can use the following code to generate a range table similar to the one above that is applicable for your specific machine and chosen partition mode. DECLARE @buf_size_output table (input_memory_kb bigint, total_regular_buffers bigint, regular_buffer_size bigint, total_buffer_size bigint) DECLARE @buf_size int, @part_mode varchar(8) SET @buf_size = 1 -- Set to the begining of your max_memory range (KB) SET @part_mode = 'per_cpu' -- Set to the partition mode for the table you want to generate WHILE @buf_size <= 4096 -- Set to the end of your max_memory range (KB) BEGIN     BEGIN TRY         IF EXISTS (SELECT * from sys.server_event_sessions WHERE name = 'buffer_size_test')             DROP EVENT SESSION buffer_size_test ON SERVER         DECLARE @session nvarchar(max)         SET @session = 'create event session buffer_size_test on server                         add event sql_statement_completed                         add target ring_buffer                         with (max_memory = ' + CAST(@buf_size as nvarchar(4)) + ' KB, memory_partition_mode = ' + @part_mode + ')'         EXEC sp_executesql @session         SET @session = 'alter event session buffer_size_test on server                         state = start'         EXEC sp_executesql @session         INSERT @buf_size_output (input_memory_kb, total_regular_buffers, regular_buffer_size, total_buffer_size)             SELECT @buf_size, total_regular_buffers, regular_buffer_size, total_buffer_size FROM sys.dm_xe_sessions WHERE name = 'buffer_size_test'     END TRY     BEGIN CATCH         INSERT @buf_size_output (input_memory_kb)             SELECT @buf_size     END CATCH     SET @buf_size = @buf_size + 1 END DROP EVENT SESSION buffer_size_test ON SERVER SELECT MIN(input_memory_kb) start_memory_range_kb, MAX(input_memory_kb) end_memory_range_kb, total_regular_buffers, regular_buffer_size, total_buffer_size from @buf_size_output group by total_regular_buffers, regular_buffer_size, total_buffer_size Thanks to Jonathan for an interesting question and a chance to explore some of the details of Extended Event internals. - Mike

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  • A Guided Tour of Complexity

    - by JoshReuben
    I just re-read Complexity – A Guided Tour by Melanie Mitchell , protégé of Douglas Hofstadter ( author of “Gödel, Escher, Bach”) http://www.amazon.com/Complexity-Guided-Tour-Melanie-Mitchell/dp/0199798109/ref=sr_1_1?ie=UTF8&qid=1339744329&sr=8-1 here are some notes and links:   Evolved from Cybernetics, General Systems Theory, Synergetics some interesting transdisciplinary fields to investigate: Chaos Theory - http://en.wikipedia.org/wiki/Chaos_theory – small differences in initial conditions (such as those due to rounding errors in numerical computation) yield widely diverging outcomes for chaotic systems, rendering long-term prediction impossible. System Dynamics / Cybernetics - http://en.wikipedia.org/wiki/System_Dynamics – study of how feedback changes system behavior Network Theory - http://en.wikipedia.org/wiki/Network_theory – leverage Graph Theory to analyze symmetric  / asymmetric relations between discrete objects Algebraic Topology - http://en.wikipedia.org/wiki/Algebraic_topology – leverage abstract algebra to analyze topological spaces There are limits to deterministic systems & to computation. Chaos Theory definitely applies to training an ANN (artificial neural network) – different weights will emerge depending upon the random selection of the training set. In recursive Non-Linear systems http://en.wikipedia.org/wiki/Nonlinear_system – output is not directly inferable from input. E.g. a Logistic map: Xt+1 = R Xt(1-Xt) Different types of bifurcations, attractor states and oscillations may occur – e.g. a Lorenz Attractor http://en.wikipedia.org/wiki/Lorenz_system Feigenbaum Constants http://en.wikipedia.org/wiki/Feigenbaum_constants express ratios in a bifurcation diagram for a non-linear map – the convergent limit of R (the rate of period-doubling bifurcations) is 4.6692016 Maxwell’s Demon - http://en.wikipedia.org/wiki/Maxwell%27s_demon - the Second Law of Thermodynamics has only a statistical certainty – the universe (and thus information) tends towards entropy. While any computation can theoretically be done without expending energy, with finite memory, the act of erasing memory is permanent and increases entropy. Life & thought is a counter-example to the universe’s tendency towards entropy. Leo Szilard and later Claude Shannon came up with the Information Theory of Entropy - http://en.wikipedia.org/wiki/Entropy_(information_theory) whereby Shannon entropy quantifies the expected value of a message’s information in bits in order to determine channel capacity and leverage Coding Theory (compression analysis). Ludwig Boltzmann came up with Statistical Mechanics - http://en.wikipedia.org/wiki/Statistical_mechanics – whereby our Newtonian perception of continuous reality is a probabilistic and statistical aggregate of many discrete quantum microstates. This is relevant for Quantum Information Theory http://en.wikipedia.org/wiki/Quantum_information and the Physics of Information - http://en.wikipedia.org/wiki/Physical_information. Hilbert’s Problems http://en.wikipedia.org/wiki/Hilbert's_problems pondered whether mathematics is complete, consistent, and decidable (the Decision Problem – http://en.wikipedia.org/wiki/Entscheidungsproblem – is there always an algorithm that can determine whether a statement is true).  Godel’s Incompleteness Theorems http://en.wikipedia.org/wiki/G%C3%B6del's_incompleteness_theorems  proved that mathematics cannot be both complete and consistent (e.g. “This statement is not provable”). Turing through the use of Turing Machines (http://en.wikipedia.org/wiki/Turing_machine symbol processors that can prove mathematical statements) and Universal Turing Machines (http://en.wikipedia.org/wiki/Universal_Turing_machine Turing Machines that can emulate other any Turing Machine via accepting programs as well as data as input symbols) that computation is limited by demonstrating the Halting Problem http://en.wikipedia.org/wiki/Halting_problem (is is not possible to know when a program will complete – you cannot build an infinite loop detector). You may be used to thinking of 1 / 2 / 3 dimensional systems, but Fractal http://en.wikipedia.org/wiki/Fractal systems are defined by self-similarity & have non-integer Hausdorff Dimensions !!!  http://en.wikipedia.org/wiki/List_of_fractals_by_Hausdorff_dimension – the fractal dimension quantifies the number of copies of a self similar object at each level of detail – eg Koch Snowflake - http://en.wikipedia.org/wiki/Koch_snowflake Definitions of complexity: size, Shannon entropy, Algorithmic Information Content (http://en.wikipedia.org/wiki/Algorithmic_information_theory - size of shortest program that can generate a description of an object) Logical depth (amount of info processed), thermodynamic depth (resources required). Complexity is statistical and fractal. John Von Neumann’s other machine was the Self-Reproducing Automaton http://en.wikipedia.org/wiki/Self-replicating_machine  . Cellular Automata http://en.wikipedia.org/wiki/Cellular_automaton are alternative form of Universal Turing machine to traditional Von Neumann machines where grid cells are locally synchronized with their neighbors according to a rule. Conway’s Game of Life http://en.wikipedia.org/wiki/Conway's_Game_of_Life demonstrates various emergent constructs such as “Glider Guns” and “Spaceships”. Cellular Automatons are not practical because logical ops require a large number of cells – wasteful & inefficient. There are no compilers or general program languages available for Cellular Automatons (as far as I am aware). Random Boolean Networks http://en.wikipedia.org/wiki/Boolean_network are extensions of cellular automata where nodes are connected at random (not to spatial neighbors) and each node has its own rule –> they demonstrate the emergence of complex  & self organized behavior. Stephen Wolfram’s (creator of Mathematica, so give him the benefit of the doubt) New Kind of Science http://en.wikipedia.org/wiki/A_New_Kind_of_Science proposes the universe may be a discrete Finite State Automata http://en.wikipedia.org/wiki/Finite-state_machine whereby reality emerges from simple rules. I am 2/3 through this book. It is feasible that the universe is quantum discrete at the plank scale and that it computes itself – Digital Physics: http://en.wikipedia.org/wiki/Digital_physics – a simulated reality? Anyway, all behavior is supposedly derived from simple algorithmic rules & falls into 4 patterns: uniform , nested / cyclical, random (Rule 30 http://en.wikipedia.org/wiki/Rule_30) & mixed (Rule 110 - http://en.wikipedia.org/wiki/Rule_110 localized structures – it is this that is interesting). interaction between colliding propagating signal inputs is then information processing. Wolfram proposes the Principle of Computational Equivalence - http://mathworld.wolfram.com/PrincipleofComputationalEquivalence.html - all processes that are not obviously simple can be viewed as computations of equivalent sophistication. Meaning in information may emerge from analogy & conceptual slippages – see the CopyCat program: http://cognitrn.psych.indiana.edu/rgoldsto/courses/concepts/copycat.pdf Scale Free Networks http://en.wikipedia.org/wiki/Scale-free_network have a distribution governed by a Power Law (http://en.wikipedia.org/wiki/Power_law - much more common than Normal Distribution). They are characterized by hubs (resilience to random deletion of nodes), heterogeneity of degree values, self similarity, & small world structure. They grow via preferential attachment http://en.wikipedia.org/wiki/Preferential_attachment – tipping points triggered by positive feedback loops. 2 theories of cascading system failures in complex systems are Self-Organized Criticality http://en.wikipedia.org/wiki/Self-organized_criticality and Highly Optimized Tolerance http://en.wikipedia.org/wiki/Highly_optimized_tolerance. Computational Mechanics http://en.wikipedia.org/wiki/Computational_mechanics – use of computational methods to study phenomena governed by the principles of mechanics. This book is a great intuition pump, but does not cover the more mathematical subject of Computational Complexity Theory – http://en.wikipedia.org/wiki/Computational_complexity_theory I am currently reading this book on this subject: http://www.amazon.com/Computational-Complexity-Christos-H-Papadimitriou/dp/0201530821/ref=pd_sim_b_1   stay tuned for that review!

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  • The Proper Use of the VM Role in Windows Azure

    - by BuckWoody
    At the Professional Developer’s Conference (PDC) in 2010 we announced an addition to the Computational Roles in Windows Azure, called the VM Role. This new feature allows a great deal of control over the applications you write, but some have confused it with our full infrastructure offering in Windows Hyper-V. There is a proper architecture pattern for both of them. Virtualization Virtualization is the process of taking all of the hardware of a physical computer and replicating it in software alone. This means that a single computer can “host” or run several “virtual” computers. These virtual computers can run anywhere - including at a vendor’s location. Some companies refer to this as Cloud Computing since the hardware is operated and maintained elsewhere. IaaS The more detailed definition of this type of computing is called Infrastructure as a Service (Iaas) since it removes the need for you to maintain hardware at your organization. The operating system, drivers, and all the other software required to run an application are still under your control and your responsibility to license, patch, and scale. Microsoft has an offering in this space called Hyper-V, that runs on the Windows operating system. Combined with a hardware hosting vendor and the System Center software to create and deploy Virtual Machines (a process referred to as provisioning), you can create a Cloud environment with full control over all aspects of the machine, including multiple operating systems if you like. Hosting machines and provisioning them at your own buildings is sometimes called a Private Cloud, and hosting them somewhere else is often called a Public Cloud. State-ful and Stateless Programming This paradigm does not create a new, scalable way of computing. It simply moves the hardware away. The reason is that when you limit the Cloud efforts to a Virtual Machine, you are in effect limiting the computing resources to what that single system can provide. This is because much of the software developed in this environment maintains “state” - and that requires a little explanation. “State-ful programming” means that all parts of the computing environment stay connected to each other throughout a compute cycle. The system expects the memory, CPU, storage and network to remain in the same state from the beginning of the process to the end. You can think of this as a telephone conversation - you expect that the other person picks up the phone, listens to you, and talks back all in a single unit of time. In “Stateless” computing the system is designed to allow the different parts of the code to run independently of each other. You can think of this like an e-mail exchange. You compose an e-mail from your system (it has the state when you’re doing that) and then you walk away for a bit to make some coffee. A few minutes later you click the “send” button (the network has the state) and you go to a meeting. The server receives the message and stores it on a mail program’s database (the mail server has the state now) and continues working on other mail. Finally, the other party logs on to their mail client and reads the mail (the other user has the state) and responds to it and so on. These events might be separated by milliseconds or even days, but the system continues to operate. The entire process doesn’t maintain the state, each component does. This is the exact concept behind coding for Windows Azure. The stateless programming model allows amazing rates of scale, since the message (think of the e-mail) can be broken apart by multiple programs and worked on in parallel (like when the e-mail goes to hundreds of users), and only the order of re-assembling the work is important to consider. For the exact same reason, if the system makes copies of those running programs as Windows Azure does, you have built-in redundancy and recovery. It’s just built into the design. The Difference Between Infrastructure Designs and Platform Designs When you simply take a physical server running software and virtualize it either privately or publicly, you haven’t done anything to allow the code to scale or have recovery. That all has to be handled by adding more code and more Virtual Machines that have a slight lag in maintaining the running state of the system. Add more machines and you get more lag, so the scale is limited. This is the primary limitation with IaaS. It’s also not as easy to deploy these VM’s, and more importantly, you’re often charged on a longer basis to remove them. your agility in IaaS is more limited. Windows Azure is a Platform - meaning that you get objects you can code against. The code you write runs on multiple nodes with multiple copies, and it all works because of the magic of Stateless programming. you don’t worry, or even care, about what is running underneath. It could be Windows (and it is in fact a type of Windows Server), Linux, or anything else - but that' isn’t what you want to manage, monitor, maintain or license. You don’t want to deploy an operating system - you want to deploy an application. You want your code to run, and you don’t care how it does that. Another benefit to PaaS is that you can ask for hundreds or thousands of new nodes of computing power - there’s no provisioning, it just happens. And you can stop using them quicker - and the base code for your application does not have to change to make this happen. Windows Azure Roles and Their Use If you need your code to have a user interface, in Visual Studio you add a Web Role to your project, and if the code needs to do work that doesn’t involve a user interface you can add a Worker Role. They are just containers that act a certain way. I’ll provide more detail on those later. Note: That’s a general description, so it’s not entirely accurate, but it’s accurate enough for this discussion. So now we’re back to that VM Role. Because of the name, some have mistakenly thought that you can take a Virtual Machine running, say Linux, and deploy it to Windows Azure using this Role. But you can’t. That’s not what it is designed for at all. If you do need that kind of deployment, you should look into Hyper-V and System Center to create the Private or Public Infrastructure as a Service. What the VM Role is actually designed to do is to allow you to have a great deal of control over the system where your code will run. Let’s take an example. You’ve heard about Windows Azure, and Platform programming. You’re convinced it’s the right way to code. But you have a lot of things you’ve written in another way at your company. Re-writing all of your code to take advantage of Windows Azure will take a long time. Or perhaps you have a certain version of Apache Web Server that you need for your code to work. In both cases, you think you can (or already have) code the the software to be “Stateless”, you just need more control over the place where the code runs. That’s the place where a VM Role makes sense. Recap Virtualizing servers alone has limitations of scale, availability and recovery. Microsoft’s offering in this area is Hyper-V and System Center, not the VM Role. The VM Role is still used for running Stateless code, just like the Web and Worker Roles, with the exception that it allows you more control over the environment of where that code runs.

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  • A pseudo-listener for AlwaysOn Availability Groups for SQL Server virtual machines running in Azure

    - by MikeD
    I am involved in a project that is implementing SharePoint 2013 on virtual machines hosted in Azure. The back end data tier consists of two Azure VMs running SQL Server 2012, with the SharePoint databases contained in an AlwaysOn Availability Group. I used this "Tutorial: AlwaysOn Availability Groups in Windows Azure (GUI)" to help me implement this setup.Because Azure DHCP will not assign multiple unique IP addresses to the same VM, having an AG Listener in Azure is not currently supported.  I wanted to figure out another mechanism to support a "pseudo listener" of some sort. First, I created a CNAME (alias) record in the DNS zone with a short TTL (time to live) of 5 minutes (I may yet make this even shorter). The record represents a logical name (let's say the alias is SPSQL) of the server to connect to for the databases in the availability group (AG). When Server1 was hosting the primary replica of the AG, I would set the CNAME of SPSQL to be SERVER1. When the AG failed over to Server1, I wanted to set the CNAME to SERVER2. Seemed simple enough.(It's important to point out that the connection strings for my SharePoint services should use the CNAME alias, and not the actual server name. This whole thing falls apart otherwise.)To accomplish this, I created identical SQL Agent Jobs on Server1 and Server2, with two steps:1. Step 1: Determine if this server is hosting the primary replica.This is a TSQL step using this script:declare @agName sysname = 'AGTest'set nocount on declare @primaryReplica sysnameselect @primaryReplica = agState.primary_replicafrom sys.dm_hadr_availability_group_states agState   join sys.availability_groups ag on agstate.group_id = ag.group_id   where ag.name = @AGname if not exists(   select *    from sys.dm_hadr_availability_group_states agState   join sys.availability_groups ag on agstate.group_id = ag.group_id   where @@Servername = agstate.primary_replica    and ag.name = @AGname)begin   raiserror ('Primary replica of %s is not hosted on %s, it is hosted on %s',17,1,@Agname, @@Servername, @primaryReplica) endThis script determines if the primary replica value of the AG group is the same as the server name, which means that our server is hosting the current AG (you should update the value of the @AgName variable to the name of your AG). If this is true, I want the DNS alias to point to this server. If the current server is not hosting the primary replica, then the script raises an error. Also, if the script can't be executed because it cannot connect to the server, that also will generate an error. For the job step settings, I set the On Failure option to "Quit the job reporting success". The next step in the job will set the DNS alias to this server name, and I only want to do that if I know that it is the current primary replica, otherwise I don't want to do anything. I also include the step output in the job history so I can see the error message.Job Step 2: Update the CNAME entry in DNS with this server's name.I used a PowerShell script to accomplish this:$cname = "SPSQL.contoso.com"$query = "Select * from MicrosoftDNS_CNAMEType"$dns1 = "dc01.contoso.com"$dns2 = "dc02.contoso.com"if ((Test-Connection -ComputerName $dns1 -Count 1 -Quiet) -eq $true){    $dnsServer = $dns1}elseif ((Test-Connection -ComputerName $dns2 -Count 1 -Quiet) -eq $true) {   $dnsServer = $dns2}else{  $msg = "Unable to connect to DNS servers: " + $dns1 + ", " + $dns2   Throw $msg}$record = Get-WmiObject -Namespace "root\microsoftdns" -Query $query -ComputerName $dnsServer  | ? { $_.Ownername -match $cname }$thisServer = [System.Net.Dns]::GetHostEntry("LocalHost").HostName + "."$currentServer = $record.RecordData if ($currentServer -eq $thisServer ) {     $cname + " CNAME is up to date: " + $currentServer}else{    $cname + " CNAME is being updated to " + $thisServer + ". It was " + $currentServer    $record.RecordData = $thisServer    $record.put()}This script does a few things:finds a responsive domain controller (Test-Connection does a ping and returns a Boolean value if you specify the -Quiet parameter)makes a WMI call to the domain controller to get the current CNAME record value (Get-WmiObject)gets the FQDN of this server (GetHostEntry)checks if the CNAME record is correct and updates it if necessary(You should update the values of the variables $cname, $dns1 and $dns2 for your environment.)Since my domain controllers are also hosted in Azure VMs, either one of them could be down at any point in time, so I need to find a DC that is responsive before attempting the DNS call. The other little thing here is that the CNAME record contains the FQDN of a machine, plus it ends with a period. So the comparison of the CNAME record has to take the trailing period into account. When I tested this step, I was getting ACCESS DENIED responses from PowerShell for the Get-WmiObject cmdlet that does a remote lookup on the DC. This occurred because the SQL Agent service account was not a member of the Domain Admins group, so I decided to create a SQL Credential to store the credentials for a domain administrator account and use it as a PowerShell proxy (rather than give the service account Domain Admins membership).In SQL Management Studio, right click on the Credentials node (under the server's Security node), and choose New Credential...Then, under SQL Agent-->Proxies, right click on the PowerShell node and choose New Proxy...Finally, in the job step properties for the PowerShell step, select the new proxy in the Run As drop down.I created this two step Job on both nodes of the Availability Group, but if you had more than two nodes, just create the same job on all the servers. I set the schedule for the job to execute every minute.When the server that is hosting the primary replica is running the job, the job history looks like this:The job history on the secondary server looks like this: When a failover occurs, the SQL Agent job on the new primary replica will detect that the CNAME needs to be updated within a minute. Based on the TTL of the CNAME (which I said at the beginning was 5 minutes), the SharePoint servers will get the new alias within five minutes and should be able to reconnect. I may want to shorten up the TTL to reduce the time it takes for the client connections to use the new alias. Using a DNS CNAME and a SQL Agent Job on all servers hosting AG replicas, I was able to create a pseudo-listener to automatically change the name of the server that was hosting the primary replica, for a scenario where I cannot use a regular AG listener (in this case, because the servers are all hosted in Azure).    

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  • Portal And Content - Content Integration - Best Practices

    - by Stefan Krantz
    Lately we have seen an increase in projects that have failed to either get user friendly content integration or non satisfactory performance. Our intention is to mitigate any knowledge gap that our previous post might have left you with, therefore this post will repeat some recommendation or reference back to old useful post. Moreover this post will help you understand ground up how to design, architect and implement business enabled, responsive and performing portals with complex requirements on business centric information publishing. Design the Information Model The key to successful portal deployments is Information modeling, it's a key task to understand the use case you designing for, therefore I have designed a set of question you need to ask yourself or your customer: Question: Who will own the content, IT or Business? Answer: BusinessQuestion: Who will publish the content, IT or Business? Answer: BusinessQuestion: Will there be multiple publishers? Answer: YesQuestion: Are the publishers computer scientist?Answer: NoQuestion: How often do the information changes, daily, weekly, monthly?Answer: Daily, weekly If your answers to the questions matches at least 2, we strongly recommend you design your content with following principles: Divide your pages in to logical sections, where each section is marked with its purpose Assign capabilities to each section, does it contain text, images, formatting and/or is it static and is populated through other contextual information Select editor/design element type WYSIWYG - Rich Text Plain Text - non-format text Image - Image object Static List - static list of formatted informationDynamic Data List - assembled information from multiple data files through CMIS query The result of such design map could look like following below examples: Based on the outcome of the required elements in the design column 3 from the left you will now simply design a data model in WebCenter Content - Site Studio by creating a Region Definition structure matching your design requirements.For more information on how to create a Region definition see following post: Region Definition Post - note see instruction 7 for details. Each region definition can now be used to instantiate data files, a data file will hold the actual data for each element in the region definition. Another way you can see this is to compare the region definition as an extension to the metadata model in WebCenter Content for each data file item. Design content templates With a solid dependable information model we can now proceed to template creation and page design, in this phase focuses on how to place the content sections from the region definition on the page via a Content Presenter template. Remember by creating content presenter templates you will leverage the latest and most integrated technology WebCenter has to offer. This phase is much easier since the you already have the information model and design wire-frames to base the logic on, however there is still few considerations to pay attention to: Base the template on ADF and make only necessary exceptions to markup when required Leverage ADF design components for Tabs, Accordions and other similar components, this way the design in the content published areas will comply with other design areas based on custom ADF taskflows There is no performance impact when using meta data or region definition based data All data access regardless of type, metadata or xml data it can be accessed via the Content Presenter - Node. See below for applied examples on how to access data Access metadata property from Document - #{node.propertyMap['myProp'].value}myProp in this example can be for instance (dDocName, dDocTitle, xComments or any other available metadata) Access element data from data file xml - #{node.propertyMap['[Region Definition Name]:[Element name]'].asTextHtml}Region Definition Name is the expect region definition that the current data file is instantiatingElement name is the element value you like to grab from the data file I recommend you read following  useful post on content template topic:CMIS queries and template creation - note see instruction 9 for detailsStatic List template rendering For more information on templates:Single Item Content TemplateMulti Item Content TemplateExpression Language Internationalization Considerations When integrating content assets via content presenter you by now probably understand that the content item/data file is wired to the page, what is also pretty common at this stage is that the content item/data file only support one language since its not practical or business friendly to mix that into a complex structure. Therefore you will be left with a very common dilemma that you will have to either build a complete new portal for each locale, which is not an good option! However with little bit of information modeling and clear naming convention this can be addressed. Basically you can simply make sure that all content item/data file are named with a predictable naming convention like "Content1_EN" for the English rendition and "Content1_ES" for the Spanish rendition. This way through simple none complex customizations you will be able to dynamically switch the actual content item/data file just before rendering. By following proposed approach above you not only enable a simple mechanism for internationalized content you also preserve the functionality in the content presenter to support business accessible run-time publishing of information on existing and new pages. I recommend you read following useful post on Internationalization topics:Internationalize with Content Presenter Integrate with Review & Approval processes Today the Review and approval functionality and configuration is based out of WebCenter Content - Criteria Workflows. Criteria Workflows uses the metadata of the checked in document to evaluate if the document is under any review/approval process. So for instance if a Criteria Workflow is configured to force any documents with Version = "2" or "higher" and Content Type is "Instructions", any matching content item version on check in will now enter the workflow before getting released for general access. Few things to consider when configuring Criteria Workflows: Make sure to not trigger on version one for Content Items that are Data Files - if you trigger on version 1 you will not only approve an empty document you will also have a content presenter pointing to a none existing document - since the document will only be available after successful completion of the workflow Approval workflows sometimes requires more complex criteria, the recommendation if that is the case is that the meta data triggering such criteria is automatically populated, this can be achieved through many approaches including Content Profiles Criteria workflows are configured and managed in WebCenter Content Administration Applets where you can configure one or more workflows. When you configured Criteria workflows the Content Presenter will support the editors with the approval process directly inline in the "Contribution mode" of the portal. In addition to approve/reject and details of the task, the content presenter natively support the user to view the current and future version of the change he/she is approving. See below for example: Architectural recommendation To support review&approval processes - minimize the amount of data files per page Each CMIS query can consume significant time depending on the complexity of the query - minimize the amount of CMIS queries per page Use Content Presenter Templates based on ADF - this way you minimize the design considerations and optimize the usage of caching Implement the page in as few Data files as possible - simplifies publishing process, increases performance and simplifies release process Named data file (node) or list of named nodes when integrating to pages increases performance vs. querying for data Named data file (node) or list of named nodes when integrating to pages enables business centric page creation and publishing and reduces the need for IT department interaction Summary Just because one architectural decision solves a business problem it doesn't mean its the right one, when designing portals all architecture has to be in harmony and not impacting each other. For instance the most technical complex solution is not always the best since it will most likely defeat the business accessibility, performance or both, therefore the best approach is to first design for simplicity that even a non-technical user can operate, after that consider the performance impact and final look at the technology challenges these brings and workaround them first with out-of-the-box features, after that design and develop functions to complement the short comings.

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  • MySQL Cluster 7.3 Labs Release – Foreign Keys Are In!

    - by Mat Keep
    0 0 1 1097 6254 Homework 52 14 7337 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} Summary (aka TL/DR): Support for Foreign Key constraints has been one of the most requested feature enhancements for MySQL Cluster. We are therefore extremely excited to announce that Foreign Keys are part of the first Labs Release of MySQL Cluster 7.3 – available for download, evaluation and feedback now! (Select the mysql-cluster-7.3-labs-June-2012 build) In this blog, I will attempt to discuss the design rationale, implementation, configuration and steps to get started in evaluating the first MySQL Cluster 7.3 Labs Release. Pace of Innovation It was only a couple of months ago that we announced the General Availability (GA) of MySQL Cluster 7.2, delivering 1 billion Queries per Minute, with 70x higher cross-shard JOIN performance, Memcached NoSQL key-value API and cross-data center replication.  This release has been a huge hit, with downloads and deployments quickly reaching record levels. The announcement of the first MySQL Cluster 7.3 Early Access lab release at today's MySQL Innovation Day event demonstrates the continued pace in Cluster development, and provides an opportunity for the community to evaluate and feedback on new features they want to see. What’s the Plan for MySQL Cluster 7.3? Well, Foreign Keys, as you may have gathered by now (!), and this is the focus of this first Labs Release. As with MySQL Cluster 7.2, we plan to publish a series of preview releases for 7.3 that will incrementally add new candidate features for a final GA release (subject to usual safe harbor statement below*), including: - New NoSQL APIs; - Features to automate the configuration and provisioning of multi-node clusters, on premise or in the cloud; - Performance and scalability enhancements; - Taking advantage of features in the latest MySQL 5.x Server GA. Design Rationale MySQL Cluster is designed as a “Not-Only-SQL” database. It combines attributes that enable users to blend the best of both relational and NoSQL technologies into solutions that deliver web scalability with 99.999% availability and real-time performance, including: Concurrent NoSQL and SQL access to the database; Auto-sharding with simple scale-out across commodity hardware; Multi-master replication with failover and recovery both within and across data centers; Shared-nothing architecture with no single point of failure; Online scaling and schema changes; ACID compliance and support for complex queries, across shards. Native support for Foreign Key constraints enables users to extend the benefits of MySQL Cluster into a broader range of use-cases, including: - Packaged applications in areas such as eCommerce and Web Content Management that prescribe databases with Foreign Key support. - In-house developments benefiting from Foreign Key constraints to simplify data models and eliminate the additional application logic needed to maintain data consistency and integrity between tables. Implementation The Foreign Key functionality is implemented directly within MySQL Cluster’s data nodes, allowing any client API accessing the cluster to benefit from them – whether using SQL or one of the NoSQL interfaces (Memcached, C++, Java, JPA or HTTP/REST.) The core referential actions defined in the SQL:2003 standard are implemented: CASCADE RESTRICT NO ACTION SET NULL In addition, the MySQL Cluster implementation supports the online adding and dropping of Foreign Keys, ensuring the Cluster continues to serve both read and write requests during the operation. An important difference to note with the Foreign Key implementation in InnoDB is that MySQL Cluster does not support the updating of Primary Keys from within the Data Nodes themselves - instead the UPDATE is emulated with a DELETE followed by an INSERT operation. Therefore an UPDATE operation will return an error if the parent reference is using a Primary Key, unless using CASCADE action, in which case the delete operation will result in the corresponding rows in the child table being deleted. The Engineering team plans to change this behavior in a subsequent preview release. Also note that when using InnoDB "NO ACTION" is identical to "RESTRICT". In the case of MySQL Cluster “NO ACTION” means “deferred check”, i.e. the constraint is checked before commit, allowing user-defined triggers to automatically make changes in order to satisfy the Foreign Key constraints. Configuration There is nothing special you have to do here – Foreign Key constraint checking is enabled by default. If you intend to migrate existing tables from another database or storage engine, for example from InnoDB, there are a couple of best practices to observe: 1. Analyze the structure of the Foreign Key graph and run the ALTER TABLE ENGINE=NDB in the correct sequence to ensure constraints are enforced 2. Alternatively drop the Foreign Key constraints prior to the import process and then recreate when complete. Getting Started Read this blog for a demonstration of using Foreign Keys with MySQL Cluster.  You can download MySQL Cluster 7.3 Labs Release with Foreign Keys today - (select the mysql-cluster-7.3-labs-June-2012 build) If you are new to MySQL Cluster, the Getting Started guide will walk you through installing an evaluation cluster on a singe host (these guides reflect MySQL Cluster 7.2, but apply equally well to 7.3) Post any questions to the MySQL Cluster forum where our Engineering team will attempt to assist you. Post any bugs you find to the MySQL bug tracking system (select MySQL Cluster from the Category drop-down menu) And if you have any feedback, please post them to the Comments section of this blog. Summary MySQL Cluster 7.2 is the GA, production-ready release of MySQL Cluster. This first Labs Release of MySQL Cluster 7.3 gives you the opportunity to preview and evaluate future developments in the MySQL Cluster database, and we are very excited to be able to share that with you. Let us know how you get along with MySQL Cluster 7.3, and other features that you want to see in future releases. * Safe Harbor Statement This information is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.

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  • How to Achieve OC4J RMI Load Balancing

    - by fip
    This is an old, Oracle SOA and OC4J 10G topic. In fact this is not even a SOA topic per se. Questions of RMI load balancing arise when you developed custom web applications accessing human tasks running off a remote SOA 10G cluster. Having returned from a customer who faced challenges with OC4J RMI load balancing, I felt there is still some confusions in the field how OC4J RMI load balancing work. Hence I decide to dust off an old tech note that I wrote a few years back and share it with the general public. Here is the tech note: Overview A typical use case in Oracle SOA is that you are building web based, custom human tasks UI that will interact with the task services housed in a remote BPEL 10G cluster. Or, in a more generic way, you are just building a web based application in Java that needs to interact with the EJBs in a remote OC4J cluster. In either case, you are talking to an OC4J cluster as RMI client. Then immediately you must ask yourself the following questions: 1. How do I make sure that the web application, as an RMI client, even distribute its load against all the nodes in the remote OC4J cluster? 2. How do I make sure that the web application, as an RMI client, is resilient to the node failures in the remote OC4J cluster, so that in the unlikely case when one of the remote OC4J nodes fail, my web application will continue to function? That is the topic of how to achieve load balancing with OC4J RMI client. Solutions You need to configure and code RMI load balancing in two places: 1. Provider URL can be specified with a comma separated list of URLs, so that the initial lookup will land to one of the available URLs. 2. Choose a proper value for the oracle.j2ee.rmi.loadBalance property, which, along side with the PROVIDER_URL property, is one of the JNDI properties passed to the JNDI lookup.(http://docs.oracle.com/cd/B31017_01/web.1013/b28958/rmi.htm#BABDGFBI) More details below: About the PROVIDER_URL The JNDI property java.name.provider.url's job is, when the client looks up for a new context at the very first time in the client session, to provide a list of RMI context The value of the JNDI property java.name.provider.url goes by the format of a single URL, or a comma separate list of URLs. A single URL. For example: opmn:ormi://host1:6003:oc4j_instance1/appName1 A comma separated list of multiple URLs. For examples:  opmn:ormi://host1:6003:oc4j_instanc1/appName, opmn:ormi://host2:6003:oc4j_instance1/appName, opmn:ormi://host3:6003:oc4j_instance1/appName When the client looks up for a new Context the very first time in the client session, it sends a query against the OPMN referenced by the provider URL. The OPMN host and port specifies the destination of such query, and the OC4J instance name and appName are actually the “where clause” of the query. When the PROVIDER URL reference a single OPMN server Let's consider the case when the provider url only reference a single OPMN server of the destination cluster. In this case, that single OPMN server receives the query and returns a list of the qualified Contexts from all OC4Js within the cluster, even though there is a single OPMN server in the provider URL. A context represent a particular starting point at a particular server for subsequent object lookup. For example, if the URL is opmn:ormi://host1:6003:oc4j_instance1/appName, then, OPMN will return the following contexts: appName on oc4j_instance1 on host1 appName on oc4j_instance1 on host2, appName on oc4j_instance1 on host3,  (provided that host1, host2, host3 are all in the same cluster) Please note that One OPMN will be sufficient to find the list of all contexts from the entire cluster that satisfy the JNDI lookup query. You can do an experiment by shutting down appName on host1, and observe that OPMN on host1 will still be able to return you appname on host2 and appName on host3. When the PROVIDER URL reference a comma separated list of multiple OPMN servers When the JNDI propery java.naming.provider.url references a comma separated list of multiple URLs, the lookup will return the exact same things as with the single OPMN server: a list of qualified Contexts from the cluster. The purpose of having multiple OPMN servers is to provide high availability in the initial context creation, such that if OPMN at host1 is unavailable, client will try the lookup via OPMN on host2, and so on. After the initial lookup returns and cache a list of contexts, the JNDI URL(s) are no longer used in the same client session. That explains why removing the 3rd URL from the list of JNDI URLs will not stop the client from getting the EJB on the 3rd server. About the oracle.j2ee.rmi.loadBalance Property After the client acquires the list of contexts, it will cache it at the client side as “list of available RMI contexts”.  This list includes all the servers in the destination cluster. This list will stay in the cache until the client session (JVM) ends. The RMI load balancing against the destination cluster is happening at the client side, as the client is switching between the members of the list. Whether and how often the client will fresh the Context from the list of Context is based on the value of the  oracle.j2ee.rmi.loadBalance. The documentation at http://docs.oracle.com/cd/B31017_01/web.1013/b28958/rmi.htm#BABDGFBI list all the available values for the oracle.j2ee.rmi.loadBalance. Value Description client If specified, the client interacts with the OC4J process that was initially chosen at the first lookup for the entire conversation. context Used for a Web client (servlet or JSP) that will access EJBs in a clustered OC4J environment. If specified, a new Context object for a randomly-selected OC4J instance will be returned each time InitialContext() is invoked. lookup Used for a standalone client that will access EJBs in a clustered OC4J environment. If specified, a new Context object for a randomly-selected OC4J instance will be created each time the client calls Context.lookup(). Please note the regardless of the setting of oracle.j2ee.rmi.loadBalance property, the “refresh” only occurs at the client. The client can only choose from the "list of available context" that was returned and cached from the very first lookup. That is, the client will merely get a new Context object from the “list of available RMI contexts” from the cache at the client side. The client will NOT go to the OPMN server again to get the list. That also implies that if you are adding a node to the server cluster AFTER the client’s initial lookup, the client would not know it because neither the server nor the client will initiate a refresh of the “list of available servers” to reflect the new node. About High Availability (i.e. Resilience Against Node Failure of Remote OC4J Cluster) What we have discussed above is about load balancing. Let's also discuss high availability. This is how the High Availability works in RMI: when the client use the context but get an exception such as socket is closed, it knows that the server referenced by that Context is problematic and will try to get another unused Context from the “list of available contexts”. Again, this list is the list that was returned and cached at the very first lookup in the entire client session.

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  • SQL SERVER – Core Concepts – Elasticity, Scalability and ACID Properties – Exploring NuoDB an Elastically Scalable Database System

    - by pinaldave
    I have been recently exploring Elasticity and Scalability attributes of databases. You can see that in my earlier blog posts about NuoDB where I wanted to look at Elasticity and Scalability concepts. The concepts are very interesting, and intriguing as well. I have discussed these concepts with my friend Joyti M and together we have come up with this interesting read. The goal of this article is to answer following simple questions What is Elasticity? What is Scalability? How ACID properties vary from NOSQL Concepts? What are the prevailing problems in the current database system architectures? Why is NuoDB  an innovative and welcome change in database paradigm? Elasticity This word’s original form is used in many different ways and honestly it does do a decent job in holding things together over the years as a person grows and contracts. Within the tech world, and specifically related to software systems (database, application servers), it has come to mean a few things - allow stretching of resources without reaching the breaking point (on demand). What are resources in this context? Resources are the usual suspects – RAM/CPU/IO/Bandwidth in the form of a container (a process or bunch of processes combined as modules). When it is about increasing resources the simplest idea which comes to mind is the addition of another container. Another container means adding a brand new physical node. When it is about adding a new node there are two questions which comes to mind. 1) Can we add another node to our software system? 2) If yes, does adding new node cause downtime for the system? Let us assume we have added new node, let us see what the new needs of the system are when a new node is added. Balancing incoming requests to multiple nodes Synchronization of a shared state across multiple nodes Identification of “downstate” and resolution action to bring it to “upstate” Well, adding a new node has its advantages as well. Here are few of the positive points Throughput can increase nearly horizontally across the node throughout the system Response times of application will increase as in-between layer interactions will be improved Now, Let us put the above concepts in the perspective of a Database. When we mention the term “running out of resources” or “application is bound to resources” the resources can be CPU, Memory or Bandwidth. The regular approach to “gain scalability” in the database is to look around for bottlenecks and increase the bottlenecked resource. When we have memory as a bottleneck we look at the data buffers, locks, query plans or indexes. After a point even this is not enough as there needs to be an efficient way of managing such large workload on a “single machine” across memory and CPU bound (right kind of scheduling)  workload. We next move on to either read/write separation of the workload or functionality-based sharing so that we still have control of the individual. But this requires lots of planning and change in client systems in terms of knowing where to go/update/read and for reporting applications to “aggregate the data” in an intelligent way. What we ideally need is an intelligent layer which allows us to do these things without us getting into managing, monitoring and distributing the workload. Scalability In the context of database/applications, scalability means three main things Ability to handle normal loads without pressure E.g. X users at the Y utilization of resources (CPU, Memory, Bandwidth) on the Z kind of hardware (4 processor, 32 GB machine with 15000 RPM SATA drives and 1 GHz Network switch) with T throughput Ability to scale up to expected peak load which is greater than normal load with acceptable response times Ability to provide acceptable response times across the system E.g. Response time in S milliseconds (or agreed upon unit of measure) – 90% of the time The Issue – Need of Scale In normal cases one can plan for the load testing to test out normal, peak, and stress scenarios to ensure specific hardware meets the needs. With help from Hardware and Software partners and best practices, bottlenecks can be identified and requisite resources added to the system. Unfortunately this vertical scale is expensive and difficult to achieve and most of the operational people need the ability to scale horizontally. This helps in getting better throughput as there are physical limits in terms of adding resources (Memory, CPU, Bandwidth and Storage) indefinitely. Today we have different options to achieve scalability: Read & Write Separation The idea here is to do actual writes to one store and configure slaves receiving the latest data with acceptable delays. Slaves can be used for balancing out reads. We can also explore functional separation or sharing as well. We can separate data operations by a specific identifier (e.g. region, year, month) and consolidate it for reporting purposes. For functional separation the major disadvantage is when schema changes or workload pattern changes. As the requirement grows one still needs to deal with scale need in manual ways by providing an abstraction in the middle tier code. Using NOSQL solutions The idea is to flatten out the structures in general to keep all values which are retrieved together at the same store and provide flexible schema. The issue with the stores is that they are compromising on mostly consistency (no ACID guarantees) and one has to use NON-SQL dialect to work with the store. The other major issue is about education with NOSQL solutions. Would one really want to make these compromises on the ability to connect and retrieve in simple SQL manner and learn other skill sets? Or for that matter give up on ACID guarantee and start dealing with consistency issues? Hybrid Deployment – Mac, Linux, Cloud, and Windows One of the challenges today that we see across On-premise vs Cloud infrastructure is a difference in abilities. Take for example SQL Azure – it is wonderful in its concepts of throttling (as it is shared deployment) of resources and ability to scale using federation. However, the same abilities are not available on premise. This is not a mistake, mind you – but a compromise of the sweet spot of workloads, customer requirements and operational SLAs which can be supported by the team. In today’s world it is imperative that databases are available across operating systems – which are a commodity and used by developers of all hues. An Ideal Database Ability List A system which allows a linear scale of the system (increase in throughput with reasonable response time) with the addition of resources A system which does not compromise on the ACID guarantees and require developers to learn new paradigms A system which does not force fit a new way interacting with database by learning Non-SQL dialect A system which does not force fit its mechanisms for providing availability across its various modules. Well NuoDB is the first database which has all of the above abilities and much more. In future articles I will cover my hands-on experience with it. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: NuoDB

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  • SortedDictionary and SortedList

    - by Simon Cooper
    Apart from Dictionary<TKey, TValue>, there's two other dictionaries in the BCL - SortedDictionary<TKey, TValue> and SortedList<TKey, TValue>. On the face of it, these two classes do the same thing - provide an IDictionary<TKey, TValue> interface where the iterator returns the items sorted by the key. So what's the difference between them, and when should you use one rather than the other? (as in my previous post, I'll assume you have some basic algorithm & datastructure knowledge) SortedDictionary We'll first cover SortedDictionary. This is implemented as a special sort of binary tree called a red-black tree. Essentially, it's a binary tree that uses various constraints on how the nodes of the tree can be arranged to ensure the tree is always roughly balanced (for more gory algorithmical details, see the wikipedia link above). What I'm concerned about in this post is how the .NET SortedDictionary is actually implemented. In .NET 4, behind the scenes, the actual implementation of the tree is delegated to a SortedSet<KeyValuePair<TKey, TValue>>. One example tree might look like this: Each node in the above tree is stored as a separate SortedSet<T>.Node object (remember, in a SortedDictionary, T is instantiated to KeyValuePair<TKey, TValue>): class Node { public bool IsRed; public T Item; public SortedSet<T>.Node Left; public SortedSet<T>.Node Right; } The SortedSet only stores a reference to the root node; all the data in the tree is accessed by traversing the Left and Right node references until you reach the node you're looking for. Each individual node can be physically stored anywhere in memory; what's important is the relationship between the nodes. This is also why there is no constructor to SortedDictionary or SortedSet that takes an integer representing the capacity; there are no internal arrays that need to be created and resized. This may seen trivial, but it's an important distinction between SortedDictionary and SortedList that I'll cover later on. And that's pretty much it; it's a standard red-black tree. Plenty of webpages and datastructure books cover the algorithms behind the tree itself far better than I could. What's interesting is the comparions between SortedDictionary and SortedList, which I'll cover at the end. As a side point, SortedDictionary has existed in the BCL ever since .NET 2. That means that, all through .NET 2, 3, and 3.5, there has been a bona-fide sorted set class in the BCL (called TreeSet). However, it was internal, so it couldn't be used outside System.dll. Only in .NET 4 was this class exposed as SortedSet. SortedList Whereas SortedDictionary didn't use any backing arrays, SortedList does. It is implemented just as the name suggests; two arrays, one containing the keys, and one the values (I've just used random letters for the values): The items in the keys array are always guarenteed to be stored in sorted order, and the value corresponding to each key is stored in the same index as the key in the values array. In this example, the value for key item 5 is 'z', and for key item 8 is 'm'. Whenever an item is inserted or removed from the SortedList, a binary search is run on the keys array to find the correct index, then all the items in the arrays are shifted to accomodate the new or removed item. For example, if the key 3 was removed, a binary search would be run to find the array index the item was at, then everything above that index would be moved down by one: and then if the key/value pair {7, 'f'} was added, a binary search would be run on the keys to find the index to insert the new item, and everything above that index would be moved up to accomodate the new item: If another item was then added, both arrays would be resized (to a length of 10) before the new item was added to the arrays. As you can see, any insertions or removals in the middle of the list require a proportion of the array contents to be moved; an O(n) operation. However, if the insertion or removal is at the end of the array (ie the largest key), then it's only O(log n); the cost of the binary search to determine it does actually need to be added to the end (excluding the occasional O(n) cost of resizing the arrays to fit more items). As a side effect of using backing arrays, SortedList offers IList Keys and Values views that simply use the backing keys or values arrays, as well as various methods utilising the array index of stored items, which SortedDictionary does not (and cannot) offer. The Comparison So, when should you use one and not the other? Well, here's the important differences: Memory usage SortedDictionary and SortedList have got very different memory profiles. SortedDictionary... has a memory overhead of one object instance, a bool, and two references per item. On 64-bit systems, this adds up to ~40 bytes, not including the stored item and the reference to it from the Node object. stores the items in separate objects that can be spread all over the heap. This helps to keep memory fragmentation low, as the individual node objects can be allocated wherever there's a spare 60 bytes. In contrast, SortedList... has no additional overhead per item (only the reference to it in the array entries), however the backing arrays can be significantly larger than you need; every time the arrays are resized they double in size. That means that if you add 513 items to a SortedList, the backing arrays will each have a length of 1024. To conteract this, the TrimExcess method resizes the arrays back down to the actual size needed, or you can simply assign list.Capacity = list.Count. stores its items in a continuous block in memory. If the list stores thousands of items, this can cause significant problems with Large Object Heap memory fragmentation as the array resizes, which SortedDictionary doesn't have. Performance Operations on a SortedDictionary always have O(log n) performance, regardless of where in the collection you're adding or removing items. In contrast, SortedList has O(n) performance when you're altering the middle of the collection. If you're adding or removing from the end (ie the largest item), then performance is O(log n), same as SortedDictionary (in practice, it will likely be slightly faster, due to the array items all being in the same area in memory, also called locality of reference). So, when should you use one and not the other? As always with these sort of things, there are no hard-and-fast rules. But generally, if you: need to access items using their index within the collection are populating the dictionary all at once from sorted data aren't adding or removing keys once it's populated then use a SortedList. But if you: don't know how many items are going to be in the dictionary are populating the dictionary from random, unsorted data are adding & removing items randomly then use a SortedDictionary. The default (again, there's no definite rules on these sort of things!) should be to use SortedDictionary, unless there's a good reason to use SortedList, due to the bad performance of SortedList when altering the middle of the collection.

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  • J2EE Applications, SPARC T4, Solaris Containers, and Resource Pools

    - by user12620111
    I've obtained a substantial performance improvement on a SPARC T4-2 Server running a J2EE Application Server Cluster by deploying the cluster members into Oracle Solaris Containers and binding those containers to cores of the SPARC T4 Processor. This is not a surprising result, in fact, it is consistent with other results that are available on the Internet. See the "references", below, for some examples. Nonetheless, here is a summary of my configuration and results. (1.0) Before deploying a J2EE Application Server Cluster into a virtualized environment, many decisions need to be made. I'm not claiming that all of the decisions that I have a made will work well for every environment. In fact, I'm not even claiming that all of the decisions are the best possible for my environment. I'm only claiming that of the small sample of configurations that I've tested, this is the one that is working best for me. Here are some of the decisions that needed to be made: (1.1) Which virtualization option? There are several virtualization options and isolation levels that are available. Options include: Hard partitions:  Dynamic Domains on Sun SPARC Enterprise M-Series Servers Hypervisor based virtualization such as Oracle VM Server for SPARC (LDOMs) on SPARC T-Series Servers OS Virtualization using Oracle Solaris Containers Resource management tools in the Oracle Solaris OS to control the amount of resources an application receives, such as CPU cycles, physical memory, and network bandwidth. Oracle Solaris Containers provide the right level of isolation and flexibility for my environment. To borrow some words from my friends in marketing, "The SPARC T4 processor leverages the unique, no-cost virtualization capabilities of Oracle Solaris Zones"  (1.2) How to associate Oracle Solaris Containers with resources? There are several options available to associate containers with resources, including (a) resource pool association (b) dedicated-cpu resources and (c) capped-cpu resources. I chose to create resource pools and associate them with the containers because I wanted explicit control over the cores and virtual processors.  (1.3) Cluster Topology? Is it best to deploy (a) multiple application servers on one node, (b) one application server on multiple nodes, or (c) multiple application servers on multiple nodes? After a few quick tests, it appears that one application server per Oracle Solaris Container is a good solution. (1.4) Number of cluster members to deploy? I chose to deploy four big 64-bit application servers. I would like go back a test many 32-bit application servers, but that is left for another day. (2.0) Configuration tested. (2.1) I was using a SPARC T4-2 Server which has 2 CPU and 128 virtual processors. To understand the physical layout of the hardware on Solaris 10, I used the OpenSolaris psrinfo perl script available at http://hub.opensolaris.org/bin/download/Community+Group+performance/files/psrinfo.pl: test# ./psrinfo.pl -pv The physical processor has 8 cores and 64 virtual processors (0-63) The core has 8 virtual processors (0-7)   The core has 8 virtual processors (8-15)   The core has 8 virtual processors (16-23)   The core has 8 virtual processors (24-31)   The core has 8 virtual processors (32-39)   The core has 8 virtual processors (40-47)   The core has 8 virtual processors (48-55)   The core has 8 virtual processors (56-63)     SPARC-T4 (chipid 0, clock 2848 MHz) The physical processor has 8 cores and 64 virtual processors (64-127)   The core has 8 virtual processors (64-71)   The core has 8 virtual processors (72-79)   The core has 8 virtual processors (80-87)   The core has 8 virtual processors (88-95)   The core has 8 virtual processors (96-103)   The core has 8 virtual processors (104-111)   The core has 8 virtual processors (112-119)   The core has 8 virtual processors (120-127)     SPARC-T4 (chipid 1, clock 2848 MHz) (2.2) The "before" test: without processor binding. I started with a 4-member cluster deployed into 4 Oracle Solaris Containers. Each container used a unique gigabit Ethernet port for HTTP traffic. The containers shared a 10 gigabit Ethernet port for JDBC traffic. (2.3) The "after" test: with processor binding. I ran one application server in the Global Zone and another application server in each of the three non-global zones (NGZ):  (3.0) Configuration steps. The following steps need to be repeated for all three Oracle Solaris Containers. (3.1) Stop AppServers from the BUI. (3.2) Stop the NGZ. test# ssh test-z2 init 5 (3.3) Enable resource pools: test# svcadm enable pools (3.4) Create the resource pool: test# poolcfg -dc 'create pool pool-test-z2' (3.5) Create the processor set: test# poolcfg -dc 'create pset pset-test-z2' (3.6) Specify the maximum number of CPU's that may be addd to the processor set: test# poolcfg -dc 'modify pset pset-test-z2 (uint pset.max=32)' (3.7) bash syntax to add Virtual CPUs to the processor set: test# (( i = 64 )); while (( i < 96 )); do poolcfg -dc "transfer to pset pset-test-z2 (cpu $i)"; (( i = i + 1 )) ; done (3.8) Associate the resource pool with the processor set: test# poolcfg -dc 'associate pool pool-test-z2 (pset pset-test-z2)' (3.9) Tell the zone to use the resource pool that has been created: test# zonecfg -z test-z1 set pool=pool-test-z2 (3.10) Boot the Oracle Solaris Container test# zoneadm -z test-z2 boot (3.11) Save the configuration to /etc/pooladm.conf test# pooladm -s (4.0) Results. Using the resource pools improves both throughput and response time: (5.0) References: System Administration Guide: Oracle Solaris Containers-Resource Management and Oracle Solaris Zones Capitalizing on large numbers of processors with WebSphere Portal on Solaris WebSphere Application Server and T5440 (Dileep Kumar's Weblog)  http://www.brendangregg.com/zones.html Reuters Market Data System, RMDS 6 Multiple Instances (Consolidated), Performance Test Results in Solaris, Containers/Zones Environment on Sun Blade X6270 by Amjad Khan, 2009.

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  • Data Source Connection Pool Sizing

    - by Steve Felts
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} One of the most time-consuming procedures of a database application is establishing a connection. The connection pooling of the data source can be used to minimize this overhead.  That argues for using the data source instead of accessing the database driver directly. Configuring the size of the pool in the data source is somewhere between an art and science – this article will try to move it closer to science.  From the beginning, WLS data source has had an initial capacity and a maximum capacity configuration values.  When the system starts up and when it shrinks, initial capacity is used.  The pool can grow to maximum capacity.  Customers found that they might want to set the initial capacity to 0 (more on that later) but didn’t want the pool to shrink to 0.  In WLS 10.3.6, we added minimum capacity to specify the lower limit to which a pool will shrink.  If minimum capacity is not set, it defaults to the initial capacity for upward compatibility.   We also did some work on the shrinking in release 10.3.4 to reduce thrashing; the algorithm that used to shrink to the maximum of the currently used connections or the initial capacity (basically the unused connections were all released) was changed to shrink by half of the unused connections. The simple approach to sizing the pool is to set the initial/minimum capacity to the maximum capacity.  Doing this creates all connections at startup, avoiding creating connections on demand and the pool is stable.  However, there are a number of reasons not to take this simple approach. When WLS is booted, the deployment of the data source includes synchronously creating the connections.  The more connections that are configured in initial capacity, the longer the boot time for WLS (there have been several projects for parallel boot in WLS but none that are available).  Related to creating a lot of connections at boot time is the problem of logon storms (the database gets too much work at one time).   WLS has a solution for that by setting the login delay seconds on the pool but that also increases the boot time. There are a number of cases where it is desirable to set the initial capacity to 0.  By doing that, the overhead of creating connections is deferred out of the boot and the database doesn’t need to be available.  An application may not want WLS to automatically connect to the database until it is actually needed, such as for some code/warm failover configurations. There are a number of cases where minimum capacity should be less than maximum capacity.  Connections are generally expensive to keep around.  They cause state to be kept on both the client and the server, and the state on the backend may be heavy (for example, a process).  Depending on the vendor, connection usage may cost money.  If work load is not constant, then database connections can be freed up by shrinking the pool when connections are not in use.  When using Active GridLink, connections can be created as needed according to runtime load balancing (RLB) percentages instead of by connection load balancing (CLB) during data source deployment. Shrinking is an effective technique for clearing the pool when connections are not in use.  In addition to the obvious reason that there times where the workload is lighter,  there are some configurations where the database and/or firewall conspire to make long-unused or too-old connections no longer viable.  There are also some data source features where the connection has state and cannot be used again unless the state matches the request.  Examples of this are identity based pooling where the connection has a particular owner and XA affinity where the connection is associated with a particular RAC node.  At this point, WLS does not re-purpose (discard/replace) connections and shrinking is a way to get rid of the unused existing connection and get a new one with the correct state when needed. So far, the discussion has focused on the relationship of initial, minimum, and maximum capacity.  Computing the maximum size requires some knowledge about the application and the current number of simultaneously active users, web sessions, batch programs, or whatever access patterns are common.  The applications should be written to only reserve and close connections as needed but multiple statements, if needed, should be done in one reservation (don’t get/close more often than necessary).  This means that the size of the pool is likely to be significantly smaller then the number of users.   If possible, you can pick a size and see how it performs under simulated or real load.  There is a high-water mark statistic (ActiveConnectionsHighCount) that tracks the maximum connections concurrently used.  In general, you want the size to be big enough so that you never run out of connections but no bigger.   It will need to deal with spikes in usage, which is where shrinking after the spike is important.  Of course, the database capacity also has a big influence on the decision since it’s important not to overload the database machine.  Planning also needs to happen if you are running in a Multi-Data Source or Active GridLink configuration and expect that the remaining nodes will take over the connections when one of the nodes in the cluster goes down.  For XA affinity, additional headroom is also recommended.  In summary, setting initial and maximum capacity to be the same may be simple but there are many other factors that may be important in making the decision about sizing.

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  • Complex event system for DungeonKeeper like game

    - by paul424
    I am working on opensource GPL3 game. http://opendungeons.sourceforge.net/ , new coders would be welcome. Now there's design question regarding Event System: We want to improve the game logic, that is program a new event system. I will just repost what's settled up already on http://forum.freegamedev.net/viewtopic.php?f=45&t=3033. From the discussion came the idea of the Publisher / Subscriber pattern + "domains": My current idea is to use the subscirbers / publishers model. Its similar to Observable pattern, but instead one subscribes to Events types, not Object's Events. For each Event would like to have both static and dynamic type. Static that is its's type would be resolved by belonging to the proper inherited class from Event. That is from Event we would have EventTile, EventCreature, EvenMapLoader, EventGameMap etc. From that there are of course subtypes like EventCreature would be EventKobold, EventKnight, EventTentacle etc. The listeners would collect the event from publishers, and send them subcribers , each of them would be a global singleton. The Listeners type hierachy would exactly mirror the type hierarchy of Events. In each constructor of Event type, the created instance would notify the proper listeners. That is when calling EventKnight the proper ctor would notify the Listeners : EventListener, CreatureLisener and KnightListener. The default action for an listner would be to notify all subscribers, but there would be some exceptions , like EventAttack would notify AttackListener which would dispatch event by the dynamic part ( that is the Creature pointer or hash). Any comments ? #include <vector> class Subscriber; class SubscriberAttack; class Event{ private: int foo; int bar; protected: // static std::vector<Publisher*> publishersList; static std::vector<Subscriber*> subscribersList; static std::vector<Event*> eventQueue; public: Event(){ eventQueue.push_back(this); } static int subscribe(Subscriber* ss); static int unsubscribe(Subscriber* ss); //static int reg_publisher(Publisher* pp); //static int unreg_publisher(Publisher* pp); }; // class Publisher{ // }; class Subscriber{ public: int (*newEvent) (Event* ee); Subscriber( ){ Event::subscribe(this); } Subscriber( int (*fp) (Event* ee) ):newEvent(fp){ Subscriber(); } ~Subscriber(){ Event::unsubscribe(this); } }; class EventAttack: Event{ private: int foo; int bar; protected: // static std::vector<Publisher*> publishersList; static std::vector<SubscriberAttack*> subscribersList; static std::vector<EventAttack*> eventQueue; public: EventAttack(){ eventQueue.push_back(this); } static int subscribe(SubscriberAttack* ss); static int unsubscribe(SubscriberAttack* ss); //static int reg_publisher(Publisher* pp); //static int unreg_publisher(Publisher* pp); }; class AttackSubscriber :Subscriber{ public: int (*newEvent) (EventAttack* ee); AttackSubscriber( ){ EventAttack::subscribe(this); } AttackSubscriber( int (*fp) (EventAttack* ee) ):newEventAttack(fp){ AttackSubscriber(); } ~AttackSubscriber(){ EventAttack::unsubscribe(this); } }; From that point, others wanted the Subject-Observer pattern, that is one would subscribe to all event types produced by particular object. That way it came out to add the domain system : Huh, to meet the ability to listen to particular game's object events, I though of introducing entity domains . Domains are trees, which nodes are labeled by unique names for each level. ( like the www addresses ). Each Entity wanting to participate in our event system ( that is be able to publish / produce events ) should at least now its domain name. That would end up in Player1/Room/Treasury/#24 or Player1/Creature/Kobold/#3 producing events. The subscriber picks some part of a tree. For example by specifiing subtree with the root in one of the nodes like Player1/Room/* ,would subscribe us to all Players1's room's event, and Player1/Creature/Kobold/#3 would subscribe to Players' third kobold's event. Does such event system make sense to you ? I have many implementation details to ask as well, but first let's start some general discussion. Note1: Notice that in the case of a fight between two creatues fight , the creature being attacked would have to throw an event, becuase it is HE/SHE/IT who have its domain address. So that would be BeingAttackedEvent() etc. I will edit that post if some other reflections on this would come out. Note2: the existing class hierarchy might be used to get the domains addresses being build in constructor . In a ctor you would just add + ."className" to domain address. If you are in a class'es hierarchy leaf constructor one might use nextID , hash or any other charactteristic, just to make the addresses distinguishable . Note3:subscribing to all entity's Events would require knowledge of all possible events produced by this entity . This could be done in one function call, but information on E produced would have to be handled for every Entity. SmartNote4 : Finding proper subscribers in a tree would be easy. One would start in particular Leaf for example Player1/Creature/Kobold/#3 and go up one parent a time , notifiying each Subscriber in a Node ie. : Player1/Creature/Kobold/* , Player1/Creature/* , Player1/* etc, , up to a root that is /* .<<<< Note5: The Event system was needed to have some way of incorporating Angelscript code into application. So the Event dispatcher was to be a gate to A-script functions. But it came out to this one.

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  • Added splash screen code to my package

    - by Youssef
    Please i need support to added splash screen code to my package /* * T24_Transformer_FormView.java */ package t24_transformer_form; import org.jdesktop.application.Action; import org.jdesktop.application.ResourceMap; import org.jdesktop.application.SingleFrameApplication; import org.jdesktop.application.FrameView; import org.jdesktop.application.TaskMonitor; import java.awt.event.ActionEvent; import java.awt.event.ActionListener; import javax.swing.filechooser.FileNameExtensionFilter; import javax.swing.filechooser.FileFilter; // old T24 Transformer imports import java.io.File; import java.io.FileWriter; import java.io.StringWriter; import java.text.SimpleDateFormat; import java.util.ArrayList; import java.util.Date; import java.util.HashMap; import java.util.Iterator; //import java.util.Properties; import java.util.StringTokenizer; import javax.swing.; import javax.xml.parsers.DocumentBuilder; import javax.xml.parsers.DocumentBuilderFactory; import javax.xml.transform.Result; import javax.xml.transform.Source; import javax.xml.transform.Transformer; import javax.xml.transform.TransformerFactory; import javax.xml.transform.dom.DOMSource; import javax.xml.transform.stream.StreamResult; import org.apache.log4j.Logger; import org.apache.log4j.PropertyConfigurator; import org.w3c.dom.Document; import org.w3c.dom.DocumentFragment; import org.w3c.dom.Element; import org.w3c.dom.Node; import org.w3c.dom.NodeList; import com.ejada.alinma.edh.xsdtransform.util.ConfigKeys; import com.ejada.alinma.edh.xsdtransform.util.XSDElement; import com.sun.org.apache.xml.internal.serialize.OutputFormat; import com.sun.org.apache.xml.internal.serialize.XMLSerializer; /* * The application's main frame. */ public class T24_Transformer_FormView extends FrameView { /**} * static holders for application-level utilities * { */ //private static Properties appProps; private static Logger appLogger; /** * */ private StringBuffer columnsCSV = null; private ArrayList<String> singleValueTableColumns = null; private HashMap<String, String> multiValueTablesSQL = null; private HashMap<Object, HashMap<String, Object>> groupAttrs = null; private ArrayList<XSDElement> xsdElementsList = null; /** * initialization */ private void init() /*throws Exception*/ { // init the properties object //FileReader in = new FileReader(appConfigPropsPath); //appProps.load(in); // log4j.properties constant String PROP_LOG4J_CONFIG_FILE = "log4j.properties"; // init the logger if ((PROP_LOG4J_CONFIG_FILE != null) && (!PROP_LOG4J_CONFIG_FILE.equals(""))) { PropertyConfigurator.configure(PROP_LOG4J_CONFIG_FILE); if (appLogger == null) { appLogger = Logger.getLogger(T24_Transformer_FormView.class.getName()); } appLogger.info("Application initialization successful."); } columnsCSV = new StringBuffer(ConfigKeys.FIELD_TAG + "," + ConfigKeys.FIELD_NUMBER + "," + ConfigKeys.FIELD_DATA_TYPE + "," + ConfigKeys.FIELD_FMT + "," + ConfigKeys.FIELD_LEN + "," + ConfigKeys.FIELD_INPUT_LEN + "," + ConfigKeys.FIELD_GROUP_NUMBER + "," + ConfigKeys.FIELD_MV_GROUP_NUMBER + "," + ConfigKeys.FIELD_SHORT_NAME + "," + ConfigKeys.FIELD_NAME + "," + ConfigKeys.FIELD_COLUMN_NAME + "," + ConfigKeys.FIELD_GROUP_NAME + "," + ConfigKeys.FIELD_MV_GROUP_NAME + "," + ConfigKeys.FIELD_JUSTIFICATION + "," + ConfigKeys.FIELD_TYPE + "," + ConfigKeys.FIELD_SINGLE_OR_MULTI + System.getProperty("line.separator")); singleValueTableColumns = new ArrayList<String>(); singleValueTableColumns.add(ConfigKeys.COLUMN_XPK_ROW + ConfigKeys.DELIMITER_COLUMN_TYPE + ConfigKeys.DATA_TYPE_XSD_NUMERIC); multiValueTablesSQL = new HashMap<String, String>(); groupAttrs = new HashMap<Object, HashMap<String, Object>>(); xsdElementsList = new ArrayList<XSDElement>(); } /** * initialize the <code>DocumentBuilder</code> and read the XSD file * * @param docPath * @return the <code>Document</code> object representing the read XSD file */ private Document retrieveDoc(String docPath) { Document xsdDoc = null; File file = new File(docPath); try { DocumentBuilder builder = DocumentBuilderFactory.newInstance().newDocumentBuilder(); xsdDoc = builder.parse(file); } catch (Exception e) { appLogger.error(e.getMessage()); } return xsdDoc; } /** * perform the iteration/modification on the document * iterate to the level which contains all the elements (Single-Value, and Groups) and start processing each * * @param xsdDoc * @return */ private Document processDoc(Document xsdDoc) { ArrayList<Object> newElementsList = new ArrayList<Object>(); HashMap<String, Object> docAttrMap = new HashMap<String, Object>(); Element sequenceElement = null; Element schemaElement = null; // get document's root element NodeList nodes = xsdDoc.getChildNodes(); for (int i = 0; i < nodes.getLength(); i++) { if (ConfigKeys.TAG_SCHEMA.equals(nodes.item(i).getNodeName())) { schemaElement = (Element) nodes.item(i); break; } } // process the document (change single-value elements, collect list of new elements to be added) for (int i1 = 0; i1 < schemaElement.getChildNodes().getLength(); i1++) { Node childLevel1 = (Node) schemaElement.getChildNodes().item(i1); // <ComplexType> element if (childLevel1.getNodeName().equals(ConfigKeys.TAG_COMPLEX_TYPE)) { // first, get the main attributes and put it in the csv file for (int i6 = 0; i6 < childLevel1.getChildNodes().getLength(); i6++) { Node child6 = childLevel1.getChildNodes().item(i6); if (ConfigKeys.TAG_ATTRIBUTE.equals(child6.getNodeName())) { if (child6.getAttributes().getNamedItem(ConfigKeys.ATTR_NAME) != null) { String attrName = child6.getAttributes().getNamedItem(ConfigKeys.ATTR_NAME).getNodeValue(); if (((Element) child6).getElementsByTagName(ConfigKeys.TAG_SIMPLE_TYPE).getLength() != 0) { Node simpleTypeElement = ((Element) child6).getElementsByTagName(ConfigKeys.TAG_SIMPLE_TYPE) .item(0); if (((Element) simpleTypeElement).getElementsByTagName(ConfigKeys.TAG_RESTRICTION).getLength() != 0) { Node restrictionElement = ((Element) simpleTypeElement).getElementsByTagName( ConfigKeys.TAG_RESTRICTION).item(0); if (((Element) restrictionElement).getElementsByTagName(ConfigKeys.TAG_MAX_LENGTH).getLength() != 0) { Node maxLengthElement = ((Element) restrictionElement).getElementsByTagName( ConfigKeys.TAG_MAX_LENGTH).item(0); HashMap<String, String> elementProperties = new HashMap<String, String>(); elementProperties.put(ConfigKeys.FIELD_TAG, attrName); elementProperties.put(ConfigKeys.FIELD_NUMBER, "0"); elementProperties.put(ConfigKeys.FIELD_DATA_TYPE, ConfigKeys.DATA_TYPE_XSD_STRING); elementProperties.put(ConfigKeys.FIELD_FMT, ""); elementProperties.put(ConfigKeys.FIELD_NAME, attrName); elementProperties.put(ConfigKeys.FIELD_SHORT_NAME, attrName); elementProperties.put(ConfigKeys.FIELD_COLUMN_NAME, attrName); elementProperties.put(ConfigKeys.FIELD_SINGLE_OR_MULTI, "S"); elementProperties.put(ConfigKeys.FIELD_LEN, maxLengthElement.getAttributes().getNamedItem( ConfigKeys.ATTR_VALUE).getNodeValue()); elementProperties.put(ConfigKeys.FIELD_INPUT_LEN, maxLengthElement.getAttributes() .getNamedItem(ConfigKeys.ATTR_VALUE).getNodeValue()); constructElementRow(elementProperties); // add the attribute as a column in the single-value table singleValueTableColumns.add(attrName + ConfigKeys.DELIMITER_COLUMN_TYPE + ConfigKeys.DATA_TYPE_XSD_STRING + ConfigKeys.DELIMITER_COLUMN_TYPE + maxLengthElement.getAttributes().getNamedItem(ConfigKeys.ATTR_VALUE).getNodeValue()); // add the attribute as an element in the elements list addToElementsList(attrName, attrName); appLogger.debug("added attribute: " + attrName); } } } } } } // now, loop on the elements and process them for (int i2 = 0; i2 < childLevel1.getChildNodes().getLength(); i2++) { Node childLevel2 = (Node) childLevel1.getChildNodes().item(i2); // <Sequence> element if (childLevel2.getNodeName().equals(ConfigKeys.TAG_SEQUENCE)) { sequenceElement = (Element) childLevel2; for (int i3 = 0; i3 < childLevel2.getChildNodes().getLength(); i3++) { Node childLevel3 = (Node) childLevel2.getChildNodes().item(i3); // <Element> element if (childLevel3.getNodeName().equals(ConfigKeys.TAG_ELEMENT)) { // check if single element or group if (isGroup(childLevel3)) { processGroup(childLevel3, true, null, null, docAttrMap, xsdDoc, newElementsList); // insert a new comment node with the contents of the group tag sequenceElement.insertBefore(xsdDoc.createComment(serialize(childLevel3)), childLevel3); // remove the group tag sequenceElement.removeChild(childLevel3); } else { processElement(childLevel3); } } } } } } } // add new elements // this step should be after finishing processing the whole document. when you add new elements to the document // while you are working on it, those new elements will be included in the processing. We don't need that! for (int i = 0; i < newElementsList.size(); i++) { sequenceElement.appendChild((Element) newElementsList.get(i)); } // write the new required attributes to the schema element Iterator<String> attrIter = docAttrMap.keySet().iterator(); while(attrIter.hasNext()) { Element attr = (Element) docAttrMap.get(attrIter.next()); Element newAttrElement = xsdDoc.createElement(ConfigKeys.TAG_ATTRIBUTE); appLogger.debug("appending attr. [" + attr.getAttribute(ConfigKeys.ATTR_NAME) + "]..."); newAttrElement.setAttribute(ConfigKeys.ATTR_NAME, attr.getAttribute(ConfigKeys.ATTR_NAME)); newAttrElement.setAttribute(ConfigKeys.ATTR_TYPE, attr.getAttribute(ConfigKeys.ATTR_TYPE)); schemaElement.appendChild(newAttrElement); } return xsdDoc; } /** * add a new <code>XSDElement</code> with the given <code>name</code> and <code>businessName</code> to * the elements list * * @param name * @param businessName */ private void addToElementsList(String name, String businessName) { xsdElementsList.add(new XSDElement(name, businessName)); } /** * add the given <code>XSDElement</code> to the elements list * * @param element */ private void addToElementsList(XSDElement element) { xsdElementsList.add(element); } /** * check if the <code>element</code> sent is single-value element or group * element. the comparison depends on the children of the element. if found one of type * <code>ComplexType</code> then it's a group element, and if of type * <code>SimpleType</code> then it's a single-value element * * @param element * @return <code>true</code> if the element is a group element, * <code>false</code> otherwise */ private boolean isGroup(Node element) { for (int i = 0; i < element.getChildNodes().getLength(); i++) { Node child = (Node) element.getChildNodes().item(i); if (child.getNodeName().equals(ConfigKeys.TAG_COMPLEX_TYPE)) { // found a ComplexType child (Group element) return true; } else if (child.getNodeName().equals(ConfigKeys.TAG_SIMPLE_TYPE)) { // found a SimpleType child (Single-Value element) return false; } } return false; /* String attrName = null; if (element.getAttributes() != null) { Node attribute = element.getAttributes().getNamedItem(XSDTransformer.ATTR_NAME); if (attribute != null) { attrName = attribute.getNodeValue(); } } if (attrName.startsWith("g")) { // group element return true; } else { // single element return false; } */ } /** * process a group element. recursively, process groups till no more group elements are found * * @param element * @param isFirstLevelGroup * @param attrMap * @param docAttrMap * @param xsdDoc * @param newElementsList */ private void processGroup(Node element, boolean isFirstLevelGroup, Node parentGroup, XSDElement parentGroupElement, HashMap<String, Object> docAttrMap, Document xsdDoc, ArrayList<Object> newElementsList) { String elementName = null; HashMap<String, Object> groupAttrMap = new HashMap<String, Object>(); HashMap<String, Object> parentGroupAttrMap = new HashMap<String, Object>(); XSDElement groupElement = null; if (element.getAttributes().getNamedItem(ConfigKeys.ATTR_NAME) != null) { elementName = element.getAttributes().getNamedItem(ConfigKeys.ATTR_NAME).getNodeValue(); } appLogger.debug("processing group [" + elementName + "]..."); groupElement = new XSDElement(elementName, elementName); // get the attributes if a non-first-level-group // attributes are: groups's own attributes + parent group's attributes if (!isFirstLevelGroup) { // get the current element (group) attributes for (int i1 = 0; i1 < element.getChildNodes().getLength(); i1++) { if (ConfigKeys.TAG_COMPLEX_TYPE.equals(element.getChildNodes().item(i1).getNodeName())) { Node complexTypeNode = element.getChildNodes().item(i1); for (int i2 = 0; i2 < complexTypeNode.getChildNodes().getLength(); i2++) { if (ConfigKeys.TAG_ATTRIBUTE.equals(complexTypeNode.getChildNodes().item(i2).getNodeName())) { appLogger.debug("add group attr: " + ((Element) complexTypeNode.getChildNodes().item(i2)).getAttribute(ConfigKeys.ATTR_NAME)); groupAttrMap.put(((Element) complexTypeNode.getChildNodes().item(i2)).getAttribute(ConfigKeys.ATTR_NAME), complexTypeNode.getChildNodes().item(i2)); docAttrMap.put(((Element) complexTypeNode.getChildNodes().item(i2)).getAttribute(ConfigKeys.ATTR_NAME), complexTypeNode.getChildNodes().item(i2)); } } } } // now, get the parent's attributes parentGroupAttrMap = groupAttrs.get(parentGroup); if (parentGroupAttrMap != null) { Iterator<String> iter = parentGroupAttrMap.keySet().iterator(); while (iter.hasNext()) { String attrName = iter.next(); groupAttrMap.put(attrName, parentGroupAttrMap.get(attrName)); } } // add the attributes to the group element that will be added to the elements list Iterator<String> itr = groupAttrMap.keySet().iterator(); while(itr.hasNext()) { groupElement.addAttribute(itr.next()); } // put the attributes in the attributes map groupAttrs.put(element, groupAttrMap); } for (int i = 0; i < element.getChildNodes().getLength(); i++) { Node childLevel1 = (Node) element.getChildNodes().item(i); if (childLevel1.getNodeName().equals(ConfigKeys.TAG_COMPLEX_TYPE)) { for (int j = 0; j < childLevel1.getChildNodes().getLength(); j++) { Node childLevel2 = (Node) childLevel1.getChildNodes().item(j); if (childLevel2.getNodeName().equals(ConfigKeys.TAG_SEQUENCE)) { for (int k = 0; k < childLevel2.getChildNodes().getLength(); k++) { Node childLevel3 = (Node) childLevel2.getChildNodes().item(k); if (childLevel3.getNodeName().equals(ConfigKeys.TAG_ELEMENT)) { // check if single element or group if (isGroup(childLevel3)) { // another group element.. // unfortunately, a recursion is // needed here!!! :-( processGroup(childLevel3, false, element, groupElement, docAttrMap, xsdDoc, newElementsList); } else { // reached a single-value element.. copy it under the // main sequence and apply the name<>shorname replacement processGroupElement(childLevel3, element, groupElement, isFirstLevelGroup, xsdDoc, newElementsList); } } } } } } } if (isFirstLevelGroup) { addToElementsList(groupElement); } else { parentGroupElement.addChild(groupElement); } appLogger.debug("finished processing group [" + elementName + "]."); } /** * process the sent <code>element</code> to extract/modify required * information: * 1. replace the <code>name</code> attribute with the <code>shortname</code>. * * @param element */ private void processElement(Node element) { String fieldShortName = null; String fieldColumnName = null; String fieldDataType = null; String fieldFormat = null; String fieldInputLength = null; String elementName = null; HashMap<String, String> elementProperties = new HashMap<String, String>(); if (element.getAttributes().getNamedItem(ConfigKeys.ATTR_NAME) != null) { elementName = element.getAttributes().getNamedItem(ConfigKeys.ATTR_NAME).getNodeValue(); } appLogger.debug("processing element [" + elementName + "]..."); for (int i = 0; i < element.getChildNodes().getLength(); i++) { Node childLevel1 = (Node) element.getChildNodes().item(i); if (childLevel1.getNodeName().equals(ConfigKeys.TAG_ANNOTATION)) { for (int j = 0; j < childLevel1.getChildNodes().getLength(); j++) { Node childLevel2 = (Node) childLevel1.getChildNodes().item(j); if (childLevel2.getNodeName().equals(ConfigKeys.TAG_APP_INFO)) { for (int k = 0; k < childLevel2.getChildNodes().getLength(); k++) { Node childLevel3 = (Node) childLevel2.getChildNodes().item(k); if (childLevel3.getNodeName().equals(ConfigKeys.TAG_HAS_PROPERTY)) { if (childLevel3.getAttributes() != null) { String attrName = null; Node attribute = childLevel3.getAttributes().getNamedItem(ConfigKeys.ATTR_NAME); if (attribute != null) { attrName = attribute.getNodeValue(); elementProperties.put(attrName, childLevel3.getAttributes().getNamedItem(ConfigKeys.ATTR_VALUE) .getNodeValue()); if (attrName.equals(ConfigKeys.FIELD_SHORT_NAME)) { fieldShortName = childLevel3.getAttributes().getNamedItem(ConfigKeys.ATTR_VALUE) .getNodeValue(); } else if (attrName.equals(ConfigKeys.FIELD_COLUMN_NAME)) { fieldColumnName = childLevel3.getAttributes().getNamedItem(ConfigKeys.ATTR_VALUE) .getNodeValue(); } else if (attrName.equals(ConfigKeys.FIELD_DATA_TYPE)) { fieldDataType = childLevel3.getAttributes().getNamedItem(ConfigKeys.ATTR_VALUE) .getNodeValue(); } else if (attrName.equals(ConfigKeys.FIELD_FMT)) { fieldFormat = childLevel3.getAttributes().getNamedItem(ConfigKeys.ATTR_VALUE) .getNodeValue(); } else if (attrName.equals(ConfigKeys.FIELD_INPUT_LEN)) { fieldInputLength = childLevel3.getAttributes().getNamedItem(ConfigKeys.ATTR_VALUE) .getNodeValue(); } } } } } } } } } // replace the name attribute with the shortname if (element.getAttributes().getNamedItem(ConfigKeys.ATTR_NAME) != null) { element.getAttributes().getNamedItem(ConfigKeys.ATTR_NAME).setNodeValue(fieldShortName); } elementProperties.put(ConfigKeys.FIELD_SINGLE_OR_MULTI, "S"); constructElementRow(elementProperties); singleValueTableColumns.add(fieldShortName + ConfigKeys.DELIMITER_COLUMN_TYPE + fieldDataType + fieldFormat + ConfigKeys.DELIMITER_COLUMN_TYPE + fieldInputLength); // add the element to elements list addToElementsList(fieldShortName, fieldColumnName); appLogger.debug("finished processing element [" + elementName + "]."); } /** * process the sent <code>element</code> to extract/modify required * information: * 1. copy the element under the main sequence * 2. replace the <code>name</code> attribute with the <code>shortname</code>. * 3. add the attributes of the parent groups (if non-first-level-group) * * @param element */ private void processGroupElement(Node element, Node parentGroup, XSDElement parentGroupElement, boolean isFirstLevelGroup, Document xsdDoc, ArrayList<Object> newElementsList) { String fieldShortName = null; String fieldColumnName = null; String fieldDataType = null; String fieldFormat = null; String fieldInputLength = null; String elementName = null; Element newElement = null; HashMap<String, String> elementProperties = new HashMap<String, String>(); ArrayList<String> tableColumns = new ArrayList<String>(); HashMap<String, Object> groupAttrMap = null; if (element.getAttributes().getNamedItem(ConfigKeys.ATTR_NAME) != null) { elementName = element.getAttributes().getNamedItem(ConfigKeys.ATTR_NAME).getNodeValue(); } appLogger.debug("processing element [" + elementName + "]..."); // 1. copy the element newElement = (Element) element.cloneNode(true); newElement.setAttribute(ConfigKeys.ATTR_MAX_OCCURS, "unbounded"); // 2. if non-first-level-group, replace the element's SimpleType tag with a ComplexType tag if (!isFirstLevelGroup) { if (((Element) newElement).getElementsByTagName(ConfigKeys.TAG_SIMPLE_TYPE).getLength() != 0) { // there should be only one tag of SimpleType Node simpleTypeNode = ((Element) newElement).getElementsByTagName(ConfigKeys.TAG_SIMPLE_TYPE).item(0); // create the new ComplexType element Element complexTypeNode = xsdDoc.createElement(ConfigKeys.TAG_COMPLEX_TYPE); complexTypeNode.setAttribute(ConfigKeys.ATTR_MIXED, "true"); // get the list of attributes for the parent group groupAttrMap = groupAttrs.get(parentGroup); Iterator<String> attrIter = groupAttrMap.keySet().iterator(); while(attrIter.hasNext()) { Element attr = (Element) groupAttrMap.get(attrIter.next()); Element newAttrElement = xsdDoc.createElement(ConfigKeys.TAG_ATTRIBUTE); appLogger.debug("adding attr. [" + attr.getAttribute(ConfigKeys.ATTR_NAME) + "]..."); newAttrElement.setAttribute(ConfigKeys.ATTR_REF, attr.getAttribute(ConfigKeys.ATTR_NAME)); newAttrElement.setAttribute(ConfigKeys.ATTR_USE, "optional"); complexTypeNode.appendChild(newAttrElement); } // replace the old SimpleType node with the new ComplexType node newElement.replaceChild(complexTypeNode, simpleTypeNode); } } // 3. replace the name with the shortname in the new element for (int i = 0; i < newElement.getChildNodes().getLength(); i++) { Node childLevel1 = (Node) newElement.getChildNodes().item(i); if (childLevel1.getNodeName().equals(ConfigKeys.TAG_ANNOTATION)) { for (int j = 0; j < childLevel1.getChildNodes().getLength(); j++) { Node childLevel2 = (Node) childLevel1.getChildNodes().item(j); if (childLevel2.getNodeName().equals(ConfigKeys.TAG_APP_INFO)) { for (int k = 0; k < childLevel2.getChildNodes().getLength(); k++) { Node childLevel3 = (Node) childLevel2.getChildNodes().item(k); if (childLevel3.getNodeName().equals(ConfigKeys.TAG_HAS_PROPERTY)) { if (childLevel3.getAttributes() != null) { String attrName = null; Node attribute = childLevel3.getAttributes().getNamedItem(ConfigKeys.ATTR_NAME); if (attribute != null) { attrName = attribute.getNodeValue(); elementProperties.put(attrName, childLevel3.getAttributes().getNamedItem(ConfigKeys.ATTR_VALUE) .getNodeValue()); if (attrName.equals(ConfigKeys.FIELD_SHORT_NAME)) { fieldShortName = childLevel3.getAttributes().getNamedItem(ConfigKeys.ATTR_VALUE) .getNodeValue(); } else if (attrName.equals(ConfigKeys.FIELD_COLUMN_NAME)) { fieldColumnName = childLevel3.getAttributes().getNamedItem(ConfigKeys.ATTR_VALUE) .getNodeValue(); } else if (attrName.equals(ConfigKeys.FIELD_DATA_TYPE)) { fieldDataType = childLevel3.getAttributes().getNamedItem(ConfigKeys.ATTR_VALUE) .getNodeValue(); } else if (attrName.equals(ConfigKeys.FIELD_FMT)) { fieldFormat = childLevel3.getAttributes().getNamedItem(ConfigKeys.ATTR_VALUE) .getNodeValue(); } else if (attrName.equals(ConfigKeys.FIELD_INPUT_LEN)) { fieldInputLength = childLevel3.getAttributes().getNamedItem(ConfigKeys.ATTR_VALUE) .getNodeValue(); } } } } } } } } } if (newElement.getAttributes().getNamedItem(ConfigKeys.ATTR_NAME) != null) { newElement.getAttributes().getNamedItem(ConfigKeys.ATTR_NAME).setNodeValue(fieldShortName); } // 4. save the new element to be added to the sequence list newElementsList.add(newElement); elementProperties.put(ConfigKeys.FIELD_SINGLE_OR_MULTI, "M"); constructElementRow(elementProperties); // create the MULTI-VALUE table // 0. Primary Key tableColumns.add(ConfigKeys.COLUMN_XPK_ROW + ConfigKeys.DELIMITER_COLUMN_TYPE + ConfigKeys.DATA_TYPE_XSD_STRING + ConfigKeys.DELIMITER_COLUMN_TYPE + ConfigKeys.COLUMN_XPK_ROW_LENGTH); // 1. foreign key tableColumns.add(ConfigKeys.COLUMN_FK_ROW + ConfigKeys.DELIMITER_COLUMN_TYPE + ConfigKeys.DATA_TYPE_XSD_NUMERIC); // 2. field value tableColumns.add(fieldShortName + ConfigKeys.DELIMITER_COLUMN_TYPE + fieldDataType + fieldFormat + ConfigKeys.DELIMITER_COLUMN_TYPE + fieldInputLength); // 3. attributes if (groupAttrMap != null) { Iterator<String> attrIter = groupAttrMap.keySet().iterator(); while (attrIter.hasNext()) { Element attr = (Element) groupAttrMap.get(attrIter.next()); tableColumns.add(attr.getAttribute(ConfigKeys.ATTR_NAME) + ConfigKeys.DELIMITER_COLUMN_TYPE + ConfigKeys.DATA_TYPE_XSD_NUMERIC); } } multiValueTablesSQL.put(sub_table_prefix.getText() + fieldShortName, constructMultiValueTableSQL( sub_table_prefix.getText() + fieldShortName, tableColumns)); // add the element to it's parent group children parentGroupElement.addChild(new XSDElement(fieldShortName, fieldColumnName)); appLogger.debug("finished processing element [" + elementName + "]."); } /** * write resulted files * * @param xsdDoc * @param docPath */ private void writeResults(Document xsdDoc, String resultsDir, String newXSDFileName, String csvFileName) { String rsDir = resultsDir + File.separator + new SimpleDateFormat("yyyyMMdd-HHmm").format(new Date()); try { File resultsDirFile = new File(rsDir); if (!resultsDirFile.exists()) { resultsDirFile.mkdirs(); } // write the XSD doc appLogger.info("writing the transformed XSD..."); Source source = new DOMSource(xsdDoc); Result result = new StreamResult(rsDir + File.separator + newXSDFileName); Transformer xformer = TransformerFactory.newInstance().newTransformer(); // xformer.setOutputProperty("indent", "yes"); xformer.transform(source, result); appLogger.info("finished writing the transformed XSD."); // write the CSV columns file appLogger.info("writing the CSV file..."); FileWriter csvWriter = new FileWriter(rsDir + File.separator + csvFileName); csvWriter.write(columnsCSV.toString()); csvWriter.close(); appLogger.info("finished writing the CSV file."); // write the master single-value table appLogger.info("writing the creation script for master table (single-values)..."); FileWriter masterTableWriter = new FileWriter(rsDir + File.separator + main_edh_table_name.getText() + ".sql"); masterTableWriter.write(constructSingleValueTableSQL(main_edh_table_name.getText(), singleValueTableColumns)); masterTableWriter.close(); appLogger.info("finished writing the creation script for master table (single-values)."); // write the multi-value tables sql appLogger.info("writing the creation script for slave tables (multi-values)..."); Iterator<String> iter = multiValueTablesSQL.keySet().iterator(); while (iter.hasNext()) { String tableName = iter.next(); String sql = multiValueTablesSQL.get(tableName); FileWriter tableSQLWriter = new FileWriter(rsDir + File.separator + tableName + ".sql"); tableSQLWriter.write(sql); tableSQLWriter.close(); } appLogger.info("finished writing the creation script for slave tables (multi-values)."); // write the single-value view appLogger.info("writing the creation script for single-value selection view..."); FileWriter singleValueViewWriter = new FileWriter(rsDir + File.separator + view_name_single.getText() + ".sql"); singleValueViewWriter.write(constructViewSQL(ConfigKeys.SQL_VIEW_SINGLE)); singleValueViewWriter.close(); appLogger.info("finished writing the creation script for single-value selection view."); // debug for (int i = 0; i < xsdElementsList.size(); i++) { getMultiView(xsdElementsList.get(i)); /*// if (xsdElementsList.get(i).getAllDescendants() != null) { // for (int j = 0; j < xsdElementsList.get(i).getAllDescendants().size(); j++) { // appLogger.debug(main_edh_table_name.getText() + "." + ConfigKeys.COLUMN_XPK_ROW // + "=" + xsdElementsList.get(i).getAllDescendants().get(j).getName() + "." + ConfigKeys.COLUMN_FK_ROW); // } // } */ } } catch (Exception e) { appLogger.error(e.getMessage()); } } private String getMultiView(XSDElement element)

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  • Munin-cron fails "Nothing to do", possibly a munin.conf problem?

    - by geerlingguy
    I have been working on this for a few hours now, and haven't yet been able to get munin to output the html files/generated graphs of resource usage on my CentOS 5.3 server. Here are some things I run as the munin user, and the results: /usr/share/munin/munin-update --nofork --debug (above works fine, takes ~2.4 seconds to complete) munin-run cpu (And other options/plugins (besides 'cpu'), all work fine and give desired output) munin-cron Fails with: [FATAL] There is nothing to do here, since there are no nodes with any plugins. Please refer to http://munin-monitoring.org/wiki/FAQ_no_graphs at /usr/share/munin/munin-html line 38 I am wondering if, perhaps, the settings in my munin.conf file might be causing a problem. Here's the contents of that file (below): bdir /var/lib/munin/ htmldir /home/archdev/public_html/monitoring logdir /var/log/munin rundir /var/run/munin/ tmpldir /etc/munin/templates [archstl.archstl.org] address 127.0.0.1 use_node_name yes Also, when I run the telnet localhost 4949 command, and list the node's plugins, it returns the default munin list... something seems to be wrong with the munin html creation process. :(

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  • Parallel prologue and epilogue in Grid Engine

    - by ajdecon
    We have a cluster being used to run MPI jobs for a customer. Previously this cluster used Torque as the scheduler, but we are transitioning to Grid Engine 6.2u5 (for some other features). Unfortunately, we are having trouble duplicating some of our maintenance scripts in the Grid Engine environment. In Torque, we have a prologue.parallel script which is used to carry out an automated health-check on the node. If this script returns a fail condition, Torque will helpfully offline the node and re-queue the job to use a different group of nodes. In Grid Engine, however, the queue "prolog" only runs on the head node of the job. We can manually run our prologue script from the startmpi.sh initialization script, for the mpi parallel environment; but I can't figure out how to detect a fail condition and carry out the same "mark offline and requeue" procedure. Any suggestions?

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  • coordinating a script to run on only one of identical load-balanced servers

    - by Amos Shapira
    I have two identically configured CentOS 5 servers (possibly more in the future). I need to run a cron job on any one of them and that it'll run only on one of them. I know about RedHat Cluster Suite (we use it on other servers), but it's a too big a gun to use for this task, plus it doesn't really behave well for less than three nodes. Is there anything light-weight I can use for that? The servers can communicate with each other directly. I suppose I can develope something over ssh or nrpe (two server which are already installed on these servers), but I was wondering whether there is something already available.

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  • How can I remove UNC password from a file

    - by freddoo
    Hi we have an mp4 file on our web server in a virtual directory When we try to access the file we get prompted for a username/password. When I tried to change the path of the virtual directory I got the message 'The following child nodes also define the value of the "UNCPassword" property, which overrides the value you have just set ...' which included the mp4 file that we try to access. How can I remove the UNC Password securing the file? The file is not on a shared drive its on the same drive as the web site root. The funny thing is the path of the virtual directory is not a UNC path it's a full path on the same server d:.....

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  • Stop single NLB node at command line

    - by Patrik Hägne
    We have a NLB cluster set up for our public web servers. I'm trying to stop the "localhost" in the cluster from the command line using NLB.EXE. When I write "nbl stop" it seems that all nodes are stopped but I only want the local node (the server I'm running the command prompt on) to be stopped in the cluster. When I try specifying the node using the command "nlb stop 192.168.182.104:HOSTNAME" it fails, saying "Did not receive response from the cluster". Am I not specifying the cluster and the host correctly?

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  • F5/BigIP rule to redirect affinity-bound users from INACTIVE pool node to other ACTIVE node

    - by j pimmel
    We have several server nodes set up for the end users of our system and because we don't use any kind of session replication in the app servers, F5 maintains affinity for users with the ACTIVE node the client was first bound to. At times when we want to re-deploy the app, we change the F5 config and take a node out of the ACTIVE pool. Gradually the users filter off and we can deploy, but the process is a bit slow. We can't just dump all the users into a different node because - given the update heavy nature of the user activities - we could cause them to lose changes. That said, there is one URL/endpoint - call it http://site/product/list - which we know, when the client hits it, that we could shove them off the INACTIVE node they had affinity with and onto a different ACTIVE node. We have had a few tries writing an F5 rule along these lines, but haven't had much success so i thought I might ask here, assuming it's possible - I have no reason to think it's not based on what we have found so far.

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