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  • Much Ado About Nothing: Stub Objects

    - by user9154181
    The Solaris 11 link-editor (ld) contains support for a new type of object that we call a stub object. A stub object is a shared object, built entirely from mapfiles, that supplies the same linking interface as the real object, while containing no code or data. Stub objects cannot be executed — the runtime linker will kill any process that attempts to load one. However, you can link to a stub object as a dependency, allowing the stub to act as a proxy for the real version of the object. You may well wonder if there is a point to producing an object that contains nothing but linking interface. As it turns out, stub objects are very useful for building large bodies of code such as Solaris. In the last year, we've had considerable success in applying them to one of our oldest and thorniest build problems. In this discussion, I will describe how we came to invent these objects, and how we apply them to building Solaris. This posting explains where the idea for stub objects came from, and details our long and twisty journey from hallway idea to standard link-editor feature. I expect that these details are mainly of interest to those who work on Solaris and its makefiles, those who have done so in the past, and those who work with other similar bodies of code. A subsequent posting will omit the history and background details, and instead discuss how to build and use stub objects. If you are mainly interested in what stub objects are, and don't care about the underlying software war stories, I encourage you to skip ahead. The Long Road To Stubs This all started for me with an email discussion in May of 2008, regarding a change request that was filed in 2002, entitled: 4631488 lib/Makefile is too patient: .WAITs should be reduced This CR encapsulates a number of cronic issues with Solaris builds: We build Solaris with a parallel make (dmake) that tries to build as much of the code base in parallel as possible. There is a lot of code to build, and we've long made use of parallelized builds to get the job done quicker. This is even more important in today's world of massively multicore hardware. Solaris contains a large number of executables and shared objects. Executables depend on shared objects, and shared objects can depend on each other. Before you can build an object, you need to ensure that the objects it needs have been built. This implies a need for serialization, which is in direct opposition to the desire to build everying in parallel. To accurately build objects in the right order requires an accurate set of make rules defining the things that depend on each other. This sounds simple, but the reality is quite complex. In practice, having programmers explicitly specify these dependencies is a losing strategy: It's really hard to get right. It's really easy to get it wrong and never know it because things build anyway. Even if you get it right, it won't stay that way, because dependencies between objects can change over time, and make cannot help you detect such drifing. You won't know that you got it wrong until the builds break. That can be a long time after the change that triggered the breakage happened, making it hard to connect the cause and the effect. Usually this happens just before a release, when the pressure is on, its hard to think calmly, and there is no time for deep fixes. As a poor compromise, the libraries in core Solaris were built using a set of grossly incomplete hand written rules, supplemented with a number of dmake .WAIT directives used to group the libraries into sets of non-interacting groups that can be built in parallel because we think they don't depend on each other. From time to time, someone will suggest that we could analyze the built objects themselves to determine their dependencies and then generate make rules based on those relationships. This is possible, but but there are complications that limit the usefulness of that approach: To analyze an object, you have to build it first. This is a classic chicken and egg scenario. You could analyze the results of a previous build, but then you're not necessarily going to get accurate rules for the current code. It should be possible to build the code without having a built workspace available. The analysis will take time, and remember that we're constantly trying to make builds faster, not slower. By definition, such an approach will always be approximate, and therefore only incremantally more accurate than the hand written rules described above. The hand written rules are fast and cheap, while this idea is slow and complex, so we stayed with the hand written approach. Solaris was built that way, essentially forever, because these are genuinely difficult problems that had no easy answer. The makefiles were full of build races in which the right outcomes happened reliably for years until a new machine or a change in build server workload upset the accidental balance of things. After figuring out what had happened, you'd mutter "How did that ever work?", add another incomplete and soon to be inaccurate make dependency rule to the system, and move on. This was not a satisfying solution, as we tend to be perfectionists in the Solaris group, but we didn't have a better answer. It worked well enough, approximately. And so it went for years. We needed a different approach — a new idea to cut the Gordian Knot. In that discussion from May 2008, my fellow linker-alien Rod Evans had the initial spark that lead us to a game changing series of realizations: The link-editor is used to link objects together, but it only uses the ELF metadata in the object, consisting of symbol tables, ELF versioning sections, and similar data. Notably, it does not look at, or understand, the machine code that makes an object useful at runtime. If you had an object that only contained the ELF metadata for a dependency, but not the code or data, the link-editor would find it equally useful for linking, and would never know the difference. Call it a stub object. In the core Solaris OS, we require all objects to be built with a link-editor mapfile that describes all of its publically available functions and data. Could we build a stub object using the mapfile for the real object? It ought to be very fast to build stub objects, as there are no input objects to process. Unlike the real object, stub objects would not actually require any dependencies, and so, all of the stubs for the entire system could be built in parallel. When building the real objects, one could link against the stub objects instead of the real dependencies. This means that all the real objects can be built built in parallel too, without any serialization. We could replace a system that requires perfect makefile rules with a system that requires no ordering rules whatsoever. The results would be considerably more robust. We immediately realized that this idea had potential, but also that there were many details to sort out, lots of work to do, and that perhaps it wouldn't really pan out. As is often the case, it would be necessary to do the work and see how it turned out. Following that conversation, I set about trying to build a stub object. We determined that a faithful stub has to do the following: Present the same set of global symbols, with the same ELF versioning, as the real object. Functions are simple — it suffices to have a symbol of the right type, possibly, but not necessarily, referencing a null function in its text segment. Copy relocations make data more complicated to stub. The possibility of a copy relocation means that when you create a stub, the data symbols must have the actual size of the real data. Any error in this will go uncaught at link time, and will cause tragic failures at runtime that are very hard to diagnose. For reasons too obscure to go into here, involving tentative symbols, it is also important that the data reside in bss, or not, matching its placement in the real object. If the real object has more than one symbol pointing at the same data item, we call these aliased symbols. All data symbols in the stub object must exhibit the same aliasing as the real object. We imagined the stub library feature working as follows: A command line option to ld tells it to produce a stub rather than a real object. In this mode, only mapfiles are examined, and any object or shared libraries on the command line are are ignored. The extra information needed (function or data, size, and bss details) would be added to the mapfile. When building the real object instead of the stub, the extra information for building stubs would be validated against the resulting object to ensure that they match. In exploring these ideas, I immediately run headfirst into the reality of the original mapfile syntax, a subject that I would later write about as The Problem(s) With Solaris SVR4 Link-Editor Mapfiles. The idea of extending that poor language was a non-starter. Until a better mapfile syntax became available, which seemed unlikely in 2008, the solution could not involve extentions to the mapfile syntax. Instead, we cooked up the idea (hack) of augmenting mapfiles with stylized comments that would carry the necessary information. A typical definition might look like: # DATA(i386) __iob 0x3c0 # DATA(amd64,sparcv9) __iob 0xa00 # DATA(sparc) __iob 0x140 iob; A further problem then became clear: If we can't extend the mapfile syntax, then there's no good way to extend ld with an option to produce stub objects, and to validate them against the real objects. The idea of having ld read comments in a mapfile and parse them for content is an unacceptable hack. The entire point of comments is that they are strictly for the human reader, and explicitly ignored by the tool. Taking all of these speed bumps into account, I made a new plan: A perl script reads the mapfiles, generates some small C glue code to produce empty functions and data definitions, compiles and links the stub object from the generated glue code, and then deletes the generated glue code. Another perl script used after both objects have been built, to compare the real and stub objects, using data from elfdump, and validate that they present the same linking interface. By June 2008, I had written the above, and generated a stub object for libc. It was a useful prototype process to go through, and it allowed me to explore the ideas at a deep level. Ultimately though, the result was unsatisfactory as a basis for real product. There were so many issues: The use of stylized comments were fine for a prototype, but not close to professional enough for shipping product. The idea of having to document and support it was a large concern. The ideal solution for stub objects really does involve having the link-editor accept the same arguments used to build the real object, augmented with a single extra command line option. Any other solution, such as our prototype script, will require makefiles to be modified in deeper ways to support building stubs, and so, will raise barriers to converting existing code. A validation script that rederives what the linker knew when it built an object will always be at a disadvantage relative to the actual linker that did the work. A stub object should be identifyable as such. In the prototype, there was no tag or other metadata that would let you know that they weren't real objects. Being able to identify a stub object in this way means that the file command can tell you what it is, and that the runtime linker can refuse to try and run a program that loads one. At that point, we needed to apply this prototype to building Solaris. As you might imagine, the task of modifying all the makefiles in the core Solaris code base in order to do this is a massive task, and not something you'd enter into lightly. The quality of the prototype just wasn't good enough to justify that sort of time commitment, so I tabled the project, putting it on my list of long term things to think about, and moved on to other work. It would sit there for a couple of years. Semi-coincidentally, one of the projects I tacked after that was to create a new mapfile syntax for the Solaris link-editor. We had wanted to do something about the old mapfile syntax for many years. Others before me had done some paper designs, and a great deal of thought had already gone into the features it should, and should not have, but for various reasons things had never moved beyond the idea stage. When I joined Sun in late 2005, I got involved in reviewing those things and thinking about the problem. Now in 2008, fresh from relearning for the Nth time why the old mapfile syntax was a huge impediment to linker progress, it seemed like the right time to tackle the mapfile issue. Paving the way for proper stub object support was not the driving force behind that effort, but I certainly had them in mind as I moved forward. The new mapfile syntax, which we call version 2, integrated into Nevada build snv_135 in in February 2010: 6916788 ld version 2 mapfile syntax PSARC/2009/688 Human readable and extensible ld mapfile syntax In order to prove that the new mapfile syntax was adequate for general purpose use, I had also done an overhaul of the ON consolidation to convert all mapfiles to use the new syntax, and put checks in place that would ensure that no use of the old syntax would creep back in. That work went back into snv_144 in June 2010: 6916796 OSnet mapfiles should use version 2 link-editor syntax That was a big putback, modifying 517 files, adding 18 new files, and removing 110 old ones. I would have done this putback anyway, as the work was already done, and the benefits of human readable syntax are obvious. However, among the justifications listed in CR 6916796 was this We anticipate adding additional features to the new mapfile language that will be applicable to ON, and which will require all sharable object mapfiles to use the new syntax. I never explained what those additional features were, and no one asked. It was premature to say so, but this was a reference to stub objects. By that point, I had already put together a working prototype link-editor with the necessary support for stub objects. I was pleased to find that building stubs was indeed very fast. On my desktop system (Ultra 24), an amd64 stub for libc can can be built in a fraction of a second: % ptime ld -64 -z stub -o stubs/libc.so.1 -G -hlibc.so.1 \ -ztext -zdefs -Bdirect ... real 0.019708910 user 0.010101680 sys 0.008528431 In order to go from prototype to integrated link-editor feature, I knew that I would need to prove that stub objects were valuable. And to do that, I knew that I'd have to switch the Solaris ON consolidation to use stub objects and evaluate the outcome. And in order to do that experiment, ON would first need to be converted to version 2 mapfiles. Sub-mission accomplished. Normally when you design a new feature, you can devise reasonably small tests to show it works, and then deploy it incrementally, letting it prove its value as it goes. The entire point of stub objects however was to demonstrate that they could be successfully applied to an extremely large and complex code base, and specifically to solve the Solaris build issues detailed above. There was no way to finesse the matter — in order to move ahead, I would have to successfully use stub objects to build the entire ON consolidation and demonstrate their value. In software, the need to boil the ocean can often be a warning sign that things are trending in the wrong direction. Conversely, sometimes progress demands that you build something large and new all at once. A big win, or a big loss — sometimes all you can do is try it and see what happens. And so, I spent some time staring at ON makefiles trying to get a handle on how things work, and how they'd have to change. It's a big and messy world, full of complex interactions, unspecified dependencies, special cases, and knowledge of arcane makefile features... ...and so, I backed away, put it down for a few months and did other work... ...until the fall, when I felt like it was time to stop thinking and pondering (some would say stalling) and get on with it. Without stubs, the following gives a simplified high level view of how Solaris is built: An initially empty directory known as the proto, and referenced via the ROOT makefile macro is established to receive the files that make up the Solaris distribution. A top level setup rule creates the proto area, and performs operations needed to initialize the workspace so that the main build operations can be launched, such as copying needed header files into the proto area. Parallel builds are launched to build the kernel (usr/src/uts), libraries (usr/src/lib), and commands. The install makefile target builds each item and delivers a copy to the proto area. All libraries and executables link against the objects previously installed in the proto, implying the need to synchronize the order in which things are built. Subsequent passes run lint, and do packaging. Given this structure, the additions to use stub objects are: A new second proto area is established, known as the stub proto and referenced via the STUBROOT makefile macro. The stub proto has the same structure as the real proto, but is used to hold stub objects. All files in the real proto are delivered as part of the Solaris product. In contrast, the stub proto is used to build the product, and then thrown away. A new target is added to library Makefiles called stub. This rule builds the stub objects. The ld command is designed so that you can build a stub object using the same ld command line you'd use to build the real object, with the addition of a single -z stub option. This means that the makefile rules for building the stub objects are very similar to those used to build the real objects, and many existing makefile definitions can be shared between them. A new target is added to the Makefiles called stubinstall which delivers the stub objects built by the stub rule into the stub proto. These rules reuse much of existing plumbing used by the existing install rule. The setup rule runs stubinstall over the entire lib subtree as part of its initialization. All libraries and executables link against the objects in the stub proto rather than the main proto, and can therefore be built in parallel without any synchronization. There was no small way to try this that would yield meaningful results. I would have to take a leap of faith and edit approximately 1850 makefiles and 300 mapfiles first, trusting that it would all work out. Once the editing was done, I'd type make and see what happened. This took about 6 weeks to do, and there were many dark days when I'd question the entire project, or struggle to understand some of the many twisted and complex situations I'd uncover in the makefiles. I even found a couple of new issues that required changes to the new stub object related code I'd added to ld. With a substantial amount of encouragement and help from some key people in the Solaris group, I eventually got the editing done and stub objects for the entire workspace built. I found that my desktop system could build all the stub objects in the workspace in roughly a minute. This was great news, as it meant that use of the feature is effectively free — no one was likely to notice or care about the cost of building them. After another week of typing make, fixing whatever failed, and doing it again, I succeeded in getting a complete build! The next step was to remove all of the make rules and .WAIT statements dedicated to controlling the order in which libraries under usr/src/lib are built. This came together pretty quickly, and after a few more speed bumps, I had a workspace that built cleanly and looked like something you might actually be able to integrate someday. This was a significant milestone, but there was still much left to do. I turned to doing full nightly builds. Every type of build (open, closed, OpenSolaris, export, domestic) had to be tried. Each type failed in a new and unique way, requiring some thinking and rework. As things came together, I became aware of things that could have been done better, simpler, or cleaner, and those things also required some rethinking, the seeking of wisdom from others, and some rework. After another couple of weeks, it was in close to final form. My focus turned towards the end game and integration. This was a huge workspace, and needed to go back soon, before changes in the gate would made merging increasingly difficult. At this point, I knew that the stub objects had greatly simplified the makefile logic and uncovered a number of race conditions, some of which had been there for years. I assumed that the builds were faster too, so I did some builds intended to quantify the speedup in build time that resulted from this approach. It had never occurred to me that there might not be one. And so, I was very surprised to find that the wall clock build times for a stock ON workspace were essentially identical to the times for my stub library enabled version! This is why it is important to always measure, and not just to assume. One can tell from first principles, based on all those removed dependency rules in the library makefile, that the stub object version of ON gives dmake considerably more opportunities to overlap library construction. Some hypothesis were proposed, and shot down: Could we have disabled dmakes parallel feature? No, a quick check showed things being build in parallel. It was suggested that we might be I/O bound, and so, the threads would be mostly idle. That's a plausible explanation, but system stats didn't really support it. Plus, the timing between the stub and non-stub cases were just too suspiciously identical. Are our machines already handling as much parallelism as they are capable of, and unable to exploit these additional opportunities? Once again, we didn't see the evidence to back this up. Eventually, a more plausible and obvious reason emerged: We build the libraries and commands (usr/src/lib, usr/src/cmd) in parallel with the kernel (usr/src/uts). The kernel is the long leg in that race, and so, wall clock measurements of build time are essentially showing how long it takes to build uts. Although it would have been nice to post a huge speedup immediately, we can take solace in knowing that stub objects simplify the makefiles and reduce the possibility of race conditions. The next step in reducing build time should be to find ways to reduce or overlap the uts part of the builds. When that leg of the build becomes shorter, then the increased parallelism in the libs and commands will pay additional dividends. Until then, we'll just have to settle for simpler and more robust. And so, I integrated the link-editor support for creating stub objects into snv_153 (November 2010) with 6993877 ld should produce stub objects PSARC/2010/397 ELF Stub Objects followed by the work to convert the ON consolidation in snv_161 (February 2011) with 7009826 OSnet should use stub objects 4631488 lib/Makefile is too patient: .WAITs should be reduced This was a huge putback, with 2108 modified files, 8 new files, and 2 removed files. Due to the size, I was allowed a window after snv_160 closed in which to do the putback. It went pretty smoothly for something this big, a few more preexisting race conditions would be discovered and addressed over the next few weeks, and things have been quiet since then. Conclusions and Looking Forward Solaris has been built with stub objects since February. The fact that developers no longer specify the order in which libraries are built has been a big success, and we've eliminated an entire class of build error. That's not to say that there are no build races left in the ON makefiles, but we've taken a substantial bite out of the problem while generally simplifying and improving things. The introduction of a stub proto area has also opened some interesting new possibilities for other build improvements. As this article has become quite long, and as those uses do not involve stub objects, I will defer that discussion to a future article.

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  • JFXtras Project: More cool features for your JavaFX app

    - by terrencebarr
    JFXtras in an open source project that provides a bunch of interesting components and pieces to make your JavaFX application even more productive, engaging, and, yes, sexy. And saves you coding time along the way. Check out the new JFXtras Ensemble demo, which showcases in one fell swoop all the features and bits you can take advantage of. Also, bookmark Jim Weaver’s excellent blog to keep up with all things JavaFX and rich client. Cheers, – Terrence Filed under: Mobile & Embedded Tagged: JavaFX, JFXtras, Open Source

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  • Skoncujte s anonymitou koncových uživatelu (1/2)

    - by david.krch
    Znalost identity koncového uživatele ve všech vrstvách systému je základní nutností pri tvorbe bezpecných aplikací. Dnes si ukážeme, jak muže program pres Client Identifier predávat databázovému serveru tuto informaci i v prípade, kdy aplikace sdílí stejné pripojení do databáze pro všechny uživatele, jak je to bežné v dnešních webových aplikacích.

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  • PTLQueue : a scalable bounded-capacity MPMC queue

    - by Dave
    Title: Fast concurrent MPMC queue -- I've used the following concurrent queue algorithm enough that it warrants a blog entry. I'll sketch out the design of a fast and scalable multiple-producer multiple-consumer (MPSC) concurrent queue called PTLQueue. The queue has bounded capacity and is implemented via a circular array. Bounded capacity can be a useful property if there's a mismatch between producer rates and consumer rates where an unbounded queue might otherwise result in excessive memory consumption by virtue of the container nodes that -- in some queue implementations -- are used to hold values. A bounded-capacity queue can provide flow control between components. Beware, however, that bounded collections can also result in resource deadlock if abused. The put() and take() operators are partial and wait for the collection to become non-full or non-empty, respectively. Put() and take() do not allocate memory, and are not vulnerable to the ABA pathologies. The PTLQueue algorithm can be implemented equally well in C/C++ and Java. Partial operators are often more convenient than total methods. In many use cases if the preconditions aren't met, there's nothing else useful the thread can do, so it may as well wait via a partial method. An exception is in the case of work-stealing queues where a thief might scan a set of queues from which it could potentially steal. Total methods return ASAP with a success-failure indication. (It's tempting to describe a queue or API as blocking or non-blocking instead of partial or total, but non-blocking is already an overloaded concurrency term. Perhaps waiting/non-waiting or patient/impatient might be better terms). It's also trivial to construct partial operators by busy-waiting via total operators, but such constructs may be less efficient than an operator explicitly and intentionally designed to wait. A PTLQueue instance contains an array of slots, where each slot has volatile Turn and MailBox fields. The array has power-of-two length allowing mod/div operations to be replaced by masking. We assume sensible padding and alignment to reduce the impact of false sharing. (On x86 I recommend 128-byte alignment and padding because of the adjacent-sector prefetch facility). Each queue also has PutCursor and TakeCursor cursor variables, each of which should be sequestered as the sole occupant of a cache line or sector. You can opt to use 64-bit integers if concerned about wrap-around aliasing in the cursor variables. Put(null) is considered illegal, but the caller or implementation can easily check for and convert null to a distinguished non-null proxy value if null happens to be a value you'd like to pass. Take() will accordingly convert the proxy value back to null. An advantage of PTLQueue is that you can use atomic fetch-and-increment for the partial methods. We initialize each slot at index I with (Turn=I, MailBox=null). Both cursors are initially 0. All shared variables are considered "volatile" and atomics such as CAS and AtomicFetchAndIncrement are presumed to have bidirectional fence semantics. Finally T is the templated type. I've sketched out a total tryTake() method below that allows the caller to poll the queue. tryPut() has an analogous construction. Zebra stripping : alternating row colors for nice-looking code listings. See also google code "prettify" : https://code.google.com/p/google-code-prettify/ Prettify is a javascript module that yields the HTML/CSS/JS equivalent of pretty-print. -- pre:nth-child(odd) { background-color:#ff0000; } pre:nth-child(even) { background-color:#0000ff; } border-left: 11px solid #ccc; margin: 1.7em 0 1.7em 0.3em; background-color:#BFB; font-size:12px; line-height:65%; " // PTLQueue : Put(v) : // producer : partial method - waits as necessary assert v != null assert Mask = 1 && (Mask & (Mask+1)) == 0 // Document invariants // doorway step // Obtain a sequence number -- ticket // As a practical concern the ticket value is temporally unique // The ticket also identifies and selects a slot auto tkt = AtomicFetchIncrement (&PutCursor, 1) slot * s = &Slots[tkt & Mask] // waiting phase : // wait for slot's generation to match the tkt value assigned to this put() invocation. // The "generation" is implicitly encoded as the upper bits in the cursor // above those used to specify the index : tkt div (Mask+1) // The generation serves as an epoch number to identify a cohort of threads // accessing disjoint slots while s-Turn != tkt : Pause assert s-MailBox == null s-MailBox = v // deposit and pass message Take() : // consumer : partial method - waits as necessary auto tkt = AtomicFetchIncrement (&TakeCursor,1) slot * s = &Slots[tkt & Mask] // 2-stage waiting : // First wait for turn for our generation // Acquire exclusive "take" access to slot's MailBox field // Then wait for the slot to become occupied while s-Turn != tkt : Pause // Concurrency in this section of code is now reduced to just 1 producer thread // vs 1 consumer thread. // For a given queue and slot, there will be most one Take() operation running // in this section. // Consumer waits for producer to arrive and make slot non-empty // Extract message; clear mailbox; advance Turn indicator // We have an obvious happens-before relation : // Put(m) happens-before corresponding Take() that returns that same "m" for T v = s-MailBox if v != null : s-MailBox = null ST-ST barrier s-Turn = tkt + Mask + 1 // unlock slot to admit next producer and consumer return v Pause tryTake() : // total method - returns ASAP with failure indication for auto tkt = TakeCursor slot * s = &Slots[tkt & Mask] if s-Turn != tkt : return null T v = s-MailBox // presumptive return value if v == null : return null // ratify tkt and v values and commit by advancing cursor if CAS (&TakeCursor, tkt, tkt+1) != tkt : continue s-MailBox = null ST-ST barrier s-Turn = tkt + Mask + 1 return v The basic idea derives from the Partitioned Ticket Lock "PTL" (US20120240126-A1) and the MultiLane Concurrent Bag (US8689237). The latter is essentially a circular ring-buffer where the elements themselves are queues or concurrent collections. You can think of the PTLQueue as a partitioned ticket lock "PTL" augmented to pass values from lock to unlock via the slots. Alternatively, you could conceptualize of PTLQueue as a degenerate MultiLane bag where each slot or "lane" consists of a simple single-word MailBox instead of a general queue. Each lane in PTLQueue also has a private Turn field which acts like the Turn (Grant) variables found in PTL. Turn enforces strict FIFO ordering and restricts concurrency on the slot mailbox field to at most one simultaneous put() and take() operation. PTL uses a single "ticket" variable and per-slot Turn (grant) fields while MultiLane has distinct PutCursor and TakeCursor cursors and abstract per-slot sub-queues. Both PTL and MultiLane advance their cursor and ticket variables with atomic fetch-and-increment. PTLQueue borrows from both PTL and MultiLane and has distinct put and take cursors and per-slot Turn fields. Instead of a per-slot queues, PTLQueue uses a simple single-word MailBox field. PutCursor and TakeCursor act like a pair of ticket locks, conferring "put" and "take" access to a given slot. PutCursor, for instance, assigns an incoming put() request to a slot and serves as a PTL "Ticket" to acquire "put" permission to that slot's MailBox field. To better explain the operation of PTLQueue we deconstruct the operation of put() and take() as follows. Put() first increments PutCursor obtaining a new unique ticket. That ticket value also identifies a slot. Put() next waits for that slot's Turn field to match that ticket value. This is tantamount to using a PTL to acquire "put" permission on the slot's MailBox field. Finally, having obtained exclusive "put" permission on the slot, put() stores the message value into the slot's MailBox. Take() similarly advances TakeCursor, identifying a slot, and then acquires and secures "take" permission on a slot by waiting for Turn. Take() then waits for the slot's MailBox to become non-empty, extracts the message, and clears MailBox. Finally, take() advances the slot's Turn field, which releases both "put" and "take" access to the slot's MailBox. Note the asymmetry : put() acquires "put" access to the slot, but take() releases that lock. At any given time, for a given slot in a PTLQueue, at most one thread has "put" access and at most one thread has "take" access. This restricts concurrency from general MPMC to 1-vs-1. We have 2 ticket locks -- one for put() and one for take() -- each with its own "ticket" variable in the form of the corresponding cursor, but they share a single "Grant" egress variable in the form of the slot's Turn variable. Advancing the PutCursor, for instance, serves two purposes. First, we obtain a unique ticket which identifies a slot. Second, incrementing the cursor is the doorway protocol step to acquire the per-slot mutual exclusion "put" lock. The cursors and operations to increment those cursors serve double-duty : slot-selection and ticket assignment for locking the slot's MailBox field. At any given time a slot MailBox field can be in one of the following states: empty with no pending operations -- neutral state; empty with one or more waiting take() operations pending -- deficit; occupied with no pending operations; occupied with one or more waiting put() operations -- surplus; empty with a pending put() or pending put() and take() operations -- transitional; or occupied with a pending take() or pending put() and take() operations -- transitional. The partial put() and take() operators can be implemented with an atomic fetch-and-increment operation, which may confer a performance advantage over a CAS-based loop. In addition we have independent PutCursor and TakeCursor cursors. Critically, a put() operation modifies PutCursor but does not access the TakeCursor and a take() operation modifies the TakeCursor cursor but does not access the PutCursor. This acts to reduce coherence traffic relative to some other queue designs. It's worth noting that slow threads or obstruction in one slot (or "lane") does not impede or obstruct operations in other slots -- this gives us some degree of obstruction isolation. PTLQueue is not lock-free, however. The implementation above is expressed with polite busy-waiting (Pause) but it's trivial to implement per-slot parking and unparking to deschedule waiting threads. It's also easy to convert the queue to a more general deque by replacing the PutCursor and TakeCursor cursors with Left/Front and Right/Back cursors that can move either direction. Specifically, to push and pop from the "left" side of the deque we would decrement and increment the Left cursor, respectively, and to push and pop from the "right" side of the deque we would increment and decrement the Right cursor, respectively. We used a variation of PTLQueue for message passing in our recent OPODIS 2013 paper. ul { list-style:none; padding-left:0; padding:0; margin:0; margin-left:0; } ul#myTagID { padding: 0px; margin: 0px; list-style:none; margin-left:0;} -- -- There's quite a bit of related literature in this area. I'll call out a few relevant references: Wilson's NYU Courant Institute UltraComputer dissertation from 1988 is classic and the canonical starting point : Operating System Data Structures for Shared-Memory MIMD Machines with Fetch-and-Add. Regarding provenance and priority, I think PTLQueue or queues effectively equivalent to PTLQueue have been independently rediscovered a number of times. See CB-Queue and BNPBV, below, for instance. But Wilson's dissertation anticipates the basic idea and seems to predate all the others. Gottlieb et al : Basic Techniques for the Efficient Coordination of Very Large Numbers of Cooperating Sequential Processors Orozco et al : CB-Queue in Toward high-throughput algorithms on many-core architectures which appeared in TACO 2012. Meneghin et al : BNPVB family in Performance evaluation of inter-thread communication mechanisms on multicore/multithreaded architecture Dmitry Vyukov : bounded MPMC queue (highly recommended) Alex Otenko : US8607249 (highly related). John Mellor-Crummey : Concurrent queues: Practical fetch-and-phi algorithms. Technical Report 229, Department of Computer Science, University of Rochester Thomasson : FIFO Distributed Bakery Algorithm (very similar to PTLQueue). Scott and Scherer : Dual Data Structures I'll propose an optimization left as an exercise for the reader. Say we wanted to reduce memory usage by eliminating inter-slot padding. Such padding is usually "dark" memory and otherwise unused and wasted. But eliminating the padding leaves us at risk of increased false sharing. Furthermore lets say it was usually the case that the PutCursor and TakeCursor were numerically close to each other. (That's true in some use cases). We might still reduce false sharing by incrementing the cursors by some value other than 1 that is not trivially small and is coprime with the number of slots. Alternatively, we might increment the cursor by one and mask as usual, resulting in a logical index. We then use that logical index value to index into a permutation table, yielding an effective index for use in the slot array. The permutation table would be constructed so that nearby logical indices would map to more distant effective indices. (Open question: what should that permutation look like? Possibly some perversion of a Gray code or De Bruijn sequence might be suitable). As an aside, say we need to busy-wait for some condition as follows : "while C == 0 : Pause". Lets say that C is usually non-zero, so we typically don't wait. But when C happens to be 0 we'll have to spin for some period, possibly brief. We can arrange for the code to be more machine-friendly with respect to the branch predictors by transforming the loop into : "if C == 0 : for { Pause; if C != 0 : break; }". Critically, we want to restructure the loop so there's one branch that controls entry and another that controls loop exit. A concern is that your compiler or JIT might be clever enough to transform this back to "while C == 0 : Pause". You can sometimes avoid this by inserting a call to a some type of very cheap "opaque" method that the compiler can't elide or reorder. On Solaris, for instance, you could use :"if C == 0 : { gethrtime(); for { Pause; if C != 0 : break; }}". It's worth noting the obvious duality between locks and queues. If you have strict FIFO lock implementation with local spinning and succession by direct handoff such as MCS or CLH,then you can usually transform that lock into a queue. Hidden commentary and annotations - invisible : * And of course there's a well-known duality between queues and locks, but I'll leave that topic for another blog post. * Compare and contrast : PTLQ vs PTL and MultiLane * Equivalent : Turn; seq; sequence; pos; position; ticket * Put = Lock; Deposit Take = identify and reserve slot; wait; extract & clear; unlock * conceptualize : Distinct PutLock and TakeLock implemented as ticket lock or PTL Distinct arrival cursors but share per-slot "Turn" variable provides exclusive role-based access to slot's mailbox field put() acquires exclusive access to a slot for purposes of "deposit" assigns slot round-robin and then acquires deposit access rights/perms to that slot take() acquires exclusive access to slot for purposes of "withdrawal" assigns slot round-robin and then acquires withdrawal access rights/perms to that slot At any given time, only one thread can have withdrawal access to a slot at any given time, only one thread can have deposit access to a slot Permissible for T1 to have deposit access and T2 to simultaneously have withdrawal access * round-robin for the purposes of; role-based; access mode; access role mailslot; mailbox; allocate/assign/identify slot rights; permission; license; access permission; * PTL/Ticket hybrid Asymmetric usage ; owner oblivious lock-unlock pairing K-exclusion add Grant cursor pass message m from lock to unlock via Slots[] array Cursor performs 2 functions : + PTL ticket + Assigns request to slot in round-robin fashion Deconstruct protocol : explication put() : allocate slot in round-robin fashion acquire PTL for "put" access store message into slot associated with PTL index take() : Acquire PTL for "take" access // doorway step seq = fetchAdd (&Grant, 1) s = &Slots[seq & Mask] // waiting phase while s-Turn != seq : pause Extract : wait for s-mailbox to be full v = s-mailbox s-mailbox = null Release PTL for both "put" and "take" access s-Turn = seq + Mask + 1 * Slot round-robin assignment and lock "doorway" protocol leverage the same cursor and FetchAdd operation on that cursor FetchAdd (&Cursor,1) + round-robin slot assignment and dispersal + PTL/ticket lock "doorway" step waiting phase is via "Turn" field in slot * PTLQueue uses 2 cursors -- put and take. Acquire "put" access to slot via PTL-like lock Acquire "take" access to slot via PTL-like lock 2 locks : put and take -- at most one thread can access slot's mailbox Both locks use same "turn" field Like multilane : 2 cursors : put and take slot is simple 1-capacity mailbox instead of queue Borrow per-slot turn/grant from PTL Provides strict FIFO Lock slot : put-vs-put take-vs-take at most one put accesses slot at any one time at most one put accesses take at any one time reduction to 1-vs-1 instead of N-vs-M concurrency Per slot locks for put/take Release put/take by advancing turn * is instrumental in ... * P-V Semaphore vs lock vs K-exclusion * See also : FastQueues-excerpt.java dice-etc/queue-mpmc-bounded-blocking-circular-xadd/ * PTLQueue is the same as PTLQB - identical * Expedient return; ASAP; prompt; immediately * Lamport's Bakery algorithm : doorway step then waiting phase Threads arriving at doorway obtain a unique ticket number Threads enter in ticket order * In the terminology of Reed and Kanodia a ticket lock corresponds to the busy-wait implementation of a semaphore using an eventcount and a sequencer It can also be thought of as an optimization of Lamport's bakery lock was designed for fault-tolerance rather than performance Instead of spinning on the release counter, processors using a bakery lock repeatedly examine the tickets of their peers --

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  • Update/Insert With ADF Web Service Data Control

    - by shay.shmeltzer
    The Web service data control (WSDC) in ADF is a powerful feature that allows you to easily build a UI on top of WS interfaces exposed by other systems. However when you drag a WSDC to a page you usually get a set of output components where the data is shown. So how would you actually do an update operation on those values? The answer is that you need a call to another method in your WSDC that does the update - but what if you want to pass to it the actual values that you get from the get method you invoked before? Here is a demo showing how to do that: The two tricks that are shown here are: Changing the properties of items in the DC to be updateable - this gives you inputText fields instead of outputText fields. And passing the currentRow.dataProvider to the update method (and choosing the right iterator for this).

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  • NetBeans Sources as a Platform

    - by Geertjan
    By default, when you create a new NetBeans module, the 'development IDE' is the platform to which you'll be deploying your module. It's a good idea to create your own platform and check that into your own repo, so that everyone working on your project will be able to work with a standardized platform, rather than whatever happens to be beneath the development IDE your using. Something else you can do is use the NetBeans sources as your platform, once you've checked them out. That's something I did the other day when trying to see whether adding 'setActivatedNodes' to NbSheet was sufficient for getting UndoRedo enabled in the Properties Window. So that's a good use case, i.e., you'd like to change the NetBeans Platform somehow, or you're fixing a bug, in other words, in some way you need to change the NetBeans Platform sources and then would like to try out the result of your changes as a client of your changes. In that scenario, here's how to set up and use a NetBeans Platform from the NetBeans sources. Run 'ant build platform' on the root of the NetBeans sources. You'll end up with nbbuild/netbeans containing a subfolder 'platform' and a subfolder 'harness'. There's your NetBeans Platform. Go to Tools | NetBeans Platform and browse to nbbuild/netbeans', registering it as your NetBeans Platform. Create a new NetBeans module, using the new NetBeans Platform as the platform. Now the cool thing is you can open any of the NetBeans modules from the NetBeans Platform modules in the NetBeans sources. When you change the source code of one of these modules and then build that module, the changed JAR will automatically be added to the right place in the nbbuild/netbeans folder. And when you do a 'clean' on a NetBeans Platform module, the related JAR will be removed from nbbuild/netbeans. In other words, in this way, by changing the NetBeans sources, you're directly changing the platform that your custom module will be running on when you deploy it. That's pretty cool and gives you a more connected relationship to your platform, since you're able to change it in the same way as the custom modules you create.

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  • Article about Sun ZFS Storage Appliances

    - by Owen Allen
    Sun ZFS Storage Appliances are versatile storage systems. Discovering and managing them in Ops Center, though, makes them even more versatile. If you discover a Sun ZFS Storage Appliance in Ops Center 12c, you can create iSCSI and Fibre Channel LUNS, and make the LUNs available to server pools and virtualization hosts as a storage library. Barbara Higgins has written an excellent article that walks you through the process of setting up a Sun ZFS Storage Appliance and discovering and managing it in Ops Center. If you're looking into ways to make a Sun ZFS Storage Appliance work for you, it's worth a look.

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  • Interactive Reporting with BI Publisher 11G

    - by kanichiro.nishida
    One of the new features that came out with BI Publisher 11G and made me really excited about is the Interactive Viewer, which allows you to interact with the data presented in the reports and gain more insights about the data. You can have as many Table, Chart, Pivot Table, Gauge components in a single report and all of them are linked together so that you can click on any data point on the components such as Chart, Pivot Table, Gauge, and that would refresh other components in the report to reflect the selection without refreshing the whole report or page. No longer you need to navigate to another report or open other reports to see related data or drill down to the detail data. It’s all there within a single report. Well, sounds cliché but really this is a typical case of ‘seeing is believing’, so instead of reading I would love you guys to take a look so I’ve recorded the following video. Please take a look !   The above video shows you the power of the BI Publisher Interactive Viewer with a real data from San Francisco Airport. The lists shown at the top or the left are one of the new features that we’ll be introducing in coming future very soon, but everything else is there with 11.1.1.3. So why not start today ? And please share your feedback with us!

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  • The Social Business Thought Leaders - Steve Denning

    - by kellsey.ruppel
    How is the average organization doing? Not very well according to a number of recent books and reports. A few indicators provide quite a gloomy picture: Return on assets and invested capitals dropped to 25% of its value in 1965 in the entire US market (see The Shift Index by John Hagel) Firms are dying faster and faster with the average lifespan of companies listed in the S&P 500 index gone from 67 years in the 1920s to 15 years today (see Creative Disruption by Richard Foster) Employee engagement ratio, a high level indicator of an organization’s health proved to affect performance outcomes, does not exceed on average 20%-30% (see Employee Engagement, Gallup or The Engagement Gap, Towers Perrin) In one of the most enjoyable keynotes of the Social Business Forum 2012, Steve Denning (Author of Radical Management and Independent Management Consultant) explained why this is happening and especially what leaders should do to reverse the worrying trends. In this Social Business Thought Leaders series, we asked Steve to collapse some key suggestions in a 2 minutes video that we strongly recommend. Steve discusses traditional management - that set of principles and practices born in the early 20th century and largely inspired by thinkers such as Frederick Taylor and Henry Ford - as the main responsible for the declining performance of modern organizations. While so many things have changed in the last 100 or so years, most companies are in fact still primarily focused on maximizing profits and efficiency, cutting costs, coordinating individuals top-down through command and control. The issue is, in a knowledge intensive, customer centred, turbulent market like the one we are experiencing, similar concepts are not just alienating employees' passion but also destroying the last source of competitive differentiation left: creativity and the innovative potential. According to Steve Denning, in a phase change from old industrial to a creative, collaborative, knowledge economy, the answer is hidden in a whole new business ecosystem that puts the individual (both the employee and the customer) at the center of the organization. He calls this new paradigm Radical Management and in the video interview he articulates the huge challenges and amazing rewards our enterprises are facing during this inevitable transition.

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  • JRockit Virtual Edition Debug Key

    - by changjae.lee
    There are a few keys that can help the debugging of the JRVE env in console. you can type in each keys in JRVE console to see what's happening under the hood. key '0' : System information key '5' : Enable shutdown key '7' : Start JRockit Management Server (port 7091) key '8' : Statistics Counters key '9' : Full Thread Dump key '0' : Status of Debug-key Below is the sample out from each keys. Debug-key '1' pressed ============ JRockitVE System Information ============ JRockitVE version : 11.1.1.3.0-67-131044 Kernel version : 6.1.0.0-97-131024 JVM version : R27.6.6-28_o-125824-1.6.0_17-20091214-2104-linux-ia32 Hypervisor version : Xen 3.4.0 Boot state : 0x007effff Uptime : 0 days 02:04:31 CPU : uniprocessor @2327 Mhz CPU usage : 0% ctx/s: 285 preempt/s: 0 migrations/s: 0 Physical pages : 82379/261121 (321/1020 MB) Network info : 10.179.97.64 (10.179.97.64/255.255.254.0) GateWay : 10.179.96.1 MAC address : 00:16:3e:7e:dc:78 Boot options : vfsCwd : /application/user_projects/domains/wlsve_domain mainArgs : java -javaagent:/jrockitve/services/sshd/sshd.jar -cp /jrockitve/jrockit/lib/tools.jar:/jrockitve/lib/common.jar:/application/patch_wls1032/profiles/default/sys_manifest_classpath/weblogic_patch.jar:/application/wlserver_10.3/server/lib/weblogic.jar -Dweblogic.Name=WlsveAdmin -Dweblogic.Domain=wlsve_domain -Dweblogic.management.username=weblogic -Dweblogic.management.password=welcome1 -Dweblogic.management.GenerateDefaultConfig=true weblogic.Server consLog : /jrockitve/log/jrockitve.log mounts : ext2 / dev0; posixLocale : en_US posixTimezone : Asia/Seoul posixEncoding : ISO-8859-1 Local disk : Size: 1024M, Used: 728M, Free: 295M ======================================================== Debug-key '5' pressed Shutdown enabled. Debug-key '7' pressed [JRockit] Management server already started. Ignoring request. Debug-key '8' pressed Starting stat recording Debug-key '8' pressed ========= Statistics Counters for the last second ========= dev.eth0_rx.cnt : 22 packets dev.eth0_rx_bytes.cnt : 2704 bytes dev.net_interrupts.cnt : 22 interrupts evt.timer_ticks.cnt : 123 ticks hyper.priv_entries.cnt : 144 entries schedule.context_switches.cnt : 271 switches schedule.idle_cpu_time.cnt : 997318849 nanoseconds schedule.idle_cpu_time_0.cnt : 997318849 nanoseconds schedule.total_cpu_time.cnt : 1000031757 nanoseconds time.system_time.cnt : 1000 ns time.timer_updates.cnt : 123 updates time.wallclock_time.cnt : 1000 ns ======================================= Debug-key '9' pressed ===== FULL THREAD DUMP =============== Fri Jun 4 08:22:12 2010 BEA JRockit(R) R27.6.6-28_o-125824-1.6.0_17-20091214-2104-linux-ia32 "Main Thread" id=1 idx=0x4 tid=1 prio=5 alive, in native, waiting -- Waiting for notification on: weblogic/t3/srvr/T3Srvr@0x646ede8[fat lock] at jrockit/vm/Threads.waitForNotifySignal(JLjava/lang/Object;)Z(Native Method) at java/lang/Object.wait(J)V(Native Method) at java/lang/Object.wait(Object.java:485) at weblogic/t3/srvr/T3Srvr.waitForDeath(T3Srvr.java:919) ^-- Lock released while waiting: weblogic/t3/srvr/T3Srvr@0x646ede8[fat lock] at weblogic/t3/srvr/T3Srvr.run(T3Srvr.java:479) at weblogic/Server.main(Server.java:67) at jrockit/vm/RNI.c2java(IIIII)V(Native Method) -- end of trace "(Signal Handler)" id=2 idx=0x8 tid=2 prio=5 alive, in native, daemon Open lock chains ================ Chain 1: "ExecuteThread: '0' for queue: 'weblogic.socket.Muxer'" id=23 idx=0x50 tid=20 waiting for java/lang/String@0x630c588 held by: "ExecuteThread: '1' for queue: 'weblogic.socket.Muxer'" id=24 idx=0x54 tid=21 (active) ===== END OF THREAD DUMP =============== Debug-key '0' pressed Debug-keys enabled Happy Cloud Walking :)

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  • Running & Managing Concurrent Queries in SQL Developer

    - by thatjeffsmith
    We’ve all been there – you’ve managed to write a query that takes longer than a few seconds to execute. Tuning aside, sometimes it takes longer than you want for a query to run. So what’s a SQL Developer user to do? I say, keep going! While you’re waiting for your query to finish, there’s no reason why you can’t continue on with your work. If you need to execute something else in a worksheet, there’s no reason to launch a 2nd or 3rd copy of SQL Developer. Just open an un-shared worksheet. Now while you’ve got 1 or more queries running, you can easily get yourself into a situation where you’re not sure what’s running where. Or maybe you want to cancel a query or just check how long something’s been running. Just open the Task Progress Panel If a query or task in SQL Developer takes more than 3-5 seconds, it will appear in the Task Progress panel. You can then watch the throbbers go back and forth while you sip your coffee/soda/Red Bull. Run a query, spawn a new worksheet, run another query, watch them in the Task Progress panel. Kudos and thanks to @leight0nn for helping me get the title of this post right If you’re looking for help in managing and monitoring sessions in general, check out this post.

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  • Troubleshooting EBS Discovery Issues - Part 2

    - by Kenneth E.
    Part 1 of “Troubleshooting EBS Discovery Issues”, which was posted on May 17th, focused on the diagnostics associated with the initial discovery of an EBS instances (e.g., Forms servers, APPL_TOPs, databases, etc.).Part 2 focuses on verifying parameters of the Change Management features, also called "Pack Diagnostics, specifically for Customization Manager, Patch Manager, Setup Manager, Automated Cloning, and User Monitoring.  As stated in the first post, there can be numerous reasons that Discovery fails - credentials, file-level permissions, patch levels - just to name a few.The Discovery Wizard can be accessed from the EBS homepage.  From the home page, click "Pack Diagnostics"Click "Create" to define the diagnostic processProvide the required inputs; Name, Module (i.e., Customization Manager, Patch Manager, Setup Manager, Automated Cloning, and User Monitoring), Show Details (typically "All"), and Category (typically check both Generic and User Specific).  Add the appropriate targets.Once the diagnostic process has completed, view the results.  Click on "Succeeded" or "Failed" in the Status column.Expand the entire tree and click on each "Succeeded/Failed" status to see the results of each test within that task.Sample output verifying o/s user name and required patches Additional sample output showing a failed testComplete descriptions of, as well as recommended corrective actions for, all of the diagnostic tests that are run in EM 12c is found in this spreadsheet.  Additional information can be found in the Application Management Pack User Guide.

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  • Using Asset Groups

    - by Owen Allen
    I got a question about putting assets in groups: "I'm planning on installing some agents manually on existing systems, and I want to have them put in a specific asset group once they're discovered. I don't see any way to tell the install script to put the asset in a group. How can I add the assets to a group, either through the UI or the CLI?" There are a few ways. In the CLI, you can use groups mode, and use this command to add an asset to a group: attach -n| --gear <asset name> -g| --group <group> You can also use -U| --uuid <UUID> to specify the asset if you have multiple assets with the same name. In the UI, you have a couple of options. You can select an asset and click Add Asset to Group to add it to a group you select. Alternatively, if you're trying to make a group for assets with a specific characteristic, you can specify rules that will automatically add assets to a group based on that characteristic.

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  • Getting Started with MySQL Cluster, Hands-on Lab, Next Saturday, MySQL Connect

    - by user13819847
    Hi!I'm speaking at MySQL Connect next Saturday, Sep. 29. My Session is a hands-on lab (HOL) on MySQL Cluster.If you are interested in familiarize a bit with MySQL Cluster this is definitely a session for you. I will start by briefly introducing MySQL Cluster and its architecture. Then I will guide you through the needed steps to install a local MySQL Cluster, connect to it (using the command line), monitor its logs, and safe shutdown it.We will hence have a chance to see which are the most common commands using in MySQL Cluster administration (e.g. Cluster backup) as well as the most common operations (e.g. online datanode add). Cluster's users and customers have the flexibility to choose whether they prefer to use a SQL or NoSQL approach to connect to MySQL Cluster, so, during the last part of the HOL, we will see how to connect to MySQL Cluster using the NoSQL NDB API. If there is enough time at the end, we will also compile and execute some simple Java programs that make use of Connector J to connect to the SQL Nodes of our Cluster. I hope this HOL will be of your interest! Below are some details if you decide to attend:When:   Saturday Sep. 29, 4 pmWhere: Hilton San Francisco - Plaza Room AIf you are interested in other MySQL Cluster sessions, you will find the info you need in this post. The full program of the MySQL Connect Conference is here, and if you are not registered yet, remember that you can still save US $300 over the on-site fee – Register Now! See you at MySQL Connect!

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  • Redehost Transforms Cloud & Hosting Services with MySQL Enterprise Edition

    - by Mat Keep
    RedeHost are one of Brazil's largest cloud computing and web hosting providers, with more than 60,000 customers and 52,000 web sites running on its infrastructure. As the company grew, Redehost needed to automate operations, such as system monitoring, making the operations team more proactive in solving problems. Redehost also sought to improve server uptime, robustness, and availability, especially during backup windows, when performance would often dip. To address the needs of the business, Redehost migrated from the community edition of MySQL to MySQL Enterprise Edition, which has delivered a host of benefits: - Pro-active database management and monitoring using MySQL Enterprise Monitor, enabling Redehost to fulfil customer SLAs. Using the Query Analyzer, Redehost were able to more rapidly identify slow queries, improving customer support - Quadrupled backup speed with MySQL Enterprise Backup, leading to faster data recovery and improved system availability - Reduced DBA overhead by 50% due to the improved support capabilities offered by MySQL Enterprise Edition. - Enabled infrastructure consolidation, avoiding unnecessary energy costs and premature hardware acquisition You can learn more from the full Redehost Case Study Also, take a look at the recently updated MySQL in the Cloud whitepaper for the latest developments that are making it even simpler and more efficient to develop and deploy new services with MySQL in the cloud

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  • Java EE/GlassFish Adoption Story by Kerry Wilson/Vanderbilt University

    - by reza_rahman
    Kerry Wilson is a Software Engineer at the Vanderbilt University Medical Center. He served in a consultant role to design a lightweight systems integration solution for the next generation Foundations Recovery Network using GlassFish, Java EE 6, JPA, @Scheduled EJBs, CDI, JAX-RS and JSF. He shared his story at the JavaOne 2013 Sunday GlassFish community event - check out the video below: Kerry outlined some of the details of the implementation and emphasized the fact that Java EE can be a great solution for applications that are considered small/lightweight. He mentioned the productivity gains through the modern Java EE programming model centered on annotations, POJOs and zero-configuration - comparing it with competing frameworks that aim towards similar productivity for lightweight applications. Kerry also stressed the quality of the excellent NetBeans integration with GlassFish and the need for community self-support in free, non-commercial open source projects like GlassFish. You can check out the details of his story on the GlassFish stories blog. Do you have a Java EE/GlassFish adoption story to share? Let us know and we will highlight it for the community.

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  • Java EE/GlassFish Adoption Story by Kerry Wilson/Vanderbilt University

    - by reza_rahman
    Kerry Wilson is a Software Engineer at the Vanderbilt University Medical Center. He served in a consultant role to design a lightweight systems integration solution for the next generation Foundations Recovery Network using GlassFish, Java EE 6, JPA, @Scheduled EJBs, CDI, JAX-RS and JSF. He lives in Nashville, TN where he helps organize the Nashville Java User Group. Kerry shared his Java EE/GlassFish adoption story at the JavaOne 2013 Sunday GlassFish community event - check out the video below: Here is the slide deck for his talk: GlassFish Story by Kerry Wilson/Vanderbilt University Medical Center from glassfish Kerry outlined some of the details of the implementation and emphasized the fact that Java EE can be a great solution for applications that are considered small/lightweight. He mentioned the productivity gains through the modern Java EE programming model centered on annotations, POJOs and zero-configuration - comparing it with competing frameworks that aim towards similar productivity for lightweight applications. Kerry also stressed the quality of the excellent NetBeans integration with GlassFish and the need for community self-support in free, non-commercial open source projects like GlassFish.

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  • JCP Party Tonight...10th Annual JCP Award Unveiling

    - by heathervc
    Tonight is the night-attend the Presentation of the 10th Annual JCP Awards! This year's JCP Award nominee list has been finalized, and the winners will be announced tonight during the JCP party at the Infusion Lounge.  We will open the doors at 6:30 PM; awards presentation at 7:00 PM.  This year's three award categories are Member of the Year, Outstanding Spec Lead, and Most Significant JSR. The JCP Member/Participant of the Year shines the light on who has shown the leadership and commitment that led to the most positive impact on the community. The Outstanding Spec Lead highlights the individual who led a specific JSR with exceptional efficiency and execution. The Most Significant JSR recognizes the most significant JSR for the Java community in the past year. Read the final list of the nominees and their profiles now.  Hope to see you there!

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  • European e-government Action Plan all about interoperability

    - by trond-arne.undheim
    Yesterday, the European Commission released its European eGovernment Action Plan for 2011-2015. The plan includes measures on providing deeper user empowerment, enhancing the Internal Market, more efficiency and effectiveness of public administrations, and putting in place pre-conditions for developing e-government. The Good - Defines interoperability very clearly. Calls interoperability "a pre-condition for cross-border eGovernment services" (a very strong formulation) and says interoperability "is supported by open specifications". - Uses the terminology "open specifications" which, let's face it, is pretty close to "open standards" which is the term the rest of the world would use. - Confirms that Member States are fully committed to the political priorities of the Malmö Declaration (which was all about open standards) including the very strong action: by 2013: All Member States will have incorporated the political priorities of the Malmö Declaration in their national strategies. Such tight Action Plan integration between Commission and Member State priorities has seldom been attempted before, particularly not in a field where European legal competence is virtually non-existent. What we see now, is the subtle force of soft power rather than the rough force of regulation. In this case, it is the Member States who want Europe to take the lead. Very refreshing! Some quotes that show the commitment to interoperability and open specifications: "The emergence of innovative technologies such as "service-oriented architectures" (SOA), or "clouds" of services,  together with more open specifications which allow for greater sharing, re-use and interoperability reinforce the ability of ICT to play a key role in this quest for effficiency in the public sector." (p.4) "Interoperability is supported through open specifications" (p.13) 2.4.1. Open Specifications and Interoperability (p.13 has a whole section dedicated to this important topic. Open specifications and interoperability are nearly 100% interrelated): "Interoperability is the ability of systems and machines to exchange, process and correctly interpret information. It is more than just a technical challenge, as it also involves legal, organisational and semantic aspects of handling  data" (p.13) "standards and  open platforms offer opportunities for more cost-effective use of resources and delivery of services" (p.13). The Bad Shies away from defining open standards, or even open specifications, the EU's preferred term for the key enabler of interoperability. Verdict 90/100, a very respectable score.

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