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  • Sharp HealthCare Reduces Storage Requirements by 50% with Oracle Advanced Compression

    - by [email protected]
    Sharp HealthCare is an award-winning integrated regional health care delivery system based in San Diego, California, with 2,600 physicians and more than 14,000 employees. Sharp HealthCare's data warehouse forms a vital part of the information system's infrastructure and is used to separate business intelligence reporting from time-critical health care transactional systems. Faced with tremendous data growth, Sharp HealthCare decided to replace their existing Microsoft products with a solution based on Oracle Database 11g and to implement Oracle Advanced Compression. Join us to hear directly from the primary DBA for the Data Warehouse Application Team, Kim Nguyen, how the new environment significantly reduced Sharp HealthCare's storage requirements and improved query performance.

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  • Oracle SALT 11gR1

    - by Maurice Gamanho
    With the 11gR1 release, SALT now supports Web services transactions (WS-TX). In a nutshell, the SALT 11gR1 Web services gateway (GWWS) now supports bi-directional transactional interoperability. What this means is that Tuxedo application services can now be invoked in global transaction context using Web services. This feature is natural to a product like Tuxedo given its history as transaction processing monitor and its significant contribution to the X/Open (now the Open Group) XA specification. We implemented Web Services Coordination (WS-COOR) and Web Services Atomic Transaction (WS-AT). We also tested and certified with WebLogic Server 11gR1 and Microsoft WCF 3.5 (.Net Framework). For more information, please visit the Tuxedo OTN home page, where you can download a document and samples that will help you get started with WS-TX in Tuxedo. You can check the product documentation here.

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  • Logical and Physical Modeling for Analytical Applications

    - by Dejan Sarka
    I am proud to announce that my first course for Pluralsight is released. The course title is Logical and Physical Modeling for Analytical Applications. Here is the description of the course. A bad data model leads to an application that does not perform well. Therefore, when developing an application, you should create a good data model from the start. However, even the best logical model can’t help when the physical implementation is bad. It is also important to know how SQL Server stores and accesses data, and how to optimize the data access. Database optimization starts by splitting transactional and analytical applications. In this course, you learn how to support analytical applications with logical design, get understanding of the problems with data access for queries that deal with large amounts of data, and learn about SQL Server optimizations that help solving these problems. Enjoy the course!

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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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  • Will LAMP meet the following needs?

    - by Telis Duvoir
    I remember a few years back, when I had a web-site I wanted to develop, that many people recommended I go the LAMP route. Unfortunately, I never got around to studying/practicing that. I'm currently revisiting the web-site idea. The web-site will be dynamic, transactional, and hopefully end up with around 1,000,000 pv/mo and 300,000 members within 18 months. Will LAMP adequately support a site like that (i.e. have you seen it under a site with those specs)?

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  • Improve email Delivery Rates

    - by JMC
    I have a web server that sends legitimate transactional email in high quantities. A reasonable percentage of users report that they never receive the emails. For every message sent, there's also a blind carbon copy going to an unfiltered email box on a different provider that I review to ensure the server actually sent the emails. All of the emails make it to my bcc box, so the server is sending the emails properly. It seems to be a spam filtering problem at other email providers. The hosting provider for the web server indicates a reverse dns lookup has been set at their level linking the emails ip address properly to my server and domain. Question: Is there anything else I can do to improve the rate that 3rd party service providers are filtering the emails I'm sending? Is there anything I can set on the DNS that I control to show that the server sending the emails is legitimate?

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  • Nucleus Research Note: Oracle's Focus on Usability in Fusion Applications

    - by mvaughan
    By Misha Vaughan, Applications User Experience I recently noticed that Nucleus Research Inc. released a research note summarizing their findings on Oracle Fusion Applications. It's always nice when an outside firm is savvy enough to acknowledge the value of a user experience strategy. When it is applied to what Oracle has done with Fusion Applications,  it's even more satisfying.  In the note, Nucleus states: "Based on the demos and testimonials from early adopters Nucleus has reviewed, Oracle has clearly focused on usability with in-application analytics and other smart application features.  "In Oracle Fusion Applications, Oracle has built not just transactional corporate applications where users enter and extract data, but smarter applications that driver user productivity." Read it for yourself here. Read more about the story behind Oracle's Fusion Applications User Experience here.

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  • 11/28 Webinar: How Marketers Are Crafting Customer Experiences

    - by Charles Knapp
    According to recent studies by Sirius Decisions and the CEB, 70% of the consumer buying journey is complete before a salesperson becomes involved. Business customers complete 57% of their buying journey without a salesperson. So, what are savvy marketers doing to stay involved in the customer journey?  Marketers are at the epicenter of turning "big data" into insights that are acted upon by the company and customers. Drawing upon social, transactional, and online behavioral insights, marketers are making customer interactions easier and more rewarding. Marketers are personalizing and innovating customer connections across new channels and devices, especially for interactions that span channels. Learn more about three key innovation strategies in an informative webcast sponsored by the Internet Marketing Association, University of California Irvine Extension, and Oracle on Wednesday, November 28, 11 am to 12 pm Pacific. Register today to learn from these thought leaders.

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  • TFS Backup Plan Wizard Tool

    - by Enrique Lima
    With the release of the “September – 2010” TFS 2010 Power Tools, came an addition to the Team Foundation Server Administration Console.  This addition is the Team Foundation Backups Tree item.  The tool is used to create backup plans and to work with it you run through a wizard, just like you would in configuring TFS or any of the extensions it has. The areas covered through the tool include: Backup to a Network Backup Path, retention configuration. Under Advanced Options, the extension to be used for the Full and Transactional backups. The capability to include external databases, meaning, include the reporting databases and SharePoint databases as part of the plan. There are further options as you can see, that includes being able to define a task scheduler account, be able to set alerts for notifications on execution of the plans, and last the option to configure the schedule for the plan execution.  All in all a very good tool and great way to safeguard the investment you’ve made.

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  • Using XA Transactions in Coherence-based Applications

    - by jpurdy
    While the costs of XA transactions are well known (e.g. increased data contention, higher latency, significant disk I/O for logging, availability challenges, etc.), in many cases they are the most attractive option for coordinating logical transactions across multiple resources. There are a few common approaches when integrating Coherence into applications via the use of an application server's transaction manager: Use of Coherence as a read-only cache, applying transactions to the underlying database (or any system of record) instead of the cache. Use of TransactionMap interface via the included resource adapter. Use of the new ACID transaction framework, introduced in Coherence 3.6.   Each of these may have significant drawbacks for certain workloads. Using Coherence as a read-only cache is the simplest option. In this approach, the application is responsible for managing both the database and the cache (either within the business logic or via application server hooks). This approach also tends to provide limited benefit for many workloads, particularly those workloads that either have queries (given the complexity of maintaining a fully cached data set in Coherence) or are not read-heavy (where the cost of managing the cache may outweigh the benefits of reading from it). All updates are made synchronously to the database, leaving it as both a source of latency as well as a potential bottleneck. This approach also prevents addressing "hot data" problems (when certain objects are updated by many concurrent transactions) since most database servers offer no facilities for explicitly controlling concurrent updates. Finally, this option tends to be a better fit for key-based access (rather than filter-based access such as queries) since this makes it easier to aggressively invalidate cache entries without worrying about when they will be reloaded. The advantage of this approach is that it allows strong data consistency as long as optimistic concurrency control is used to ensure that database updates are applied correctly regardless of whether the cache contains stale (or even dirty) data. Another benefit of this approach is that it avoids the limitations of Coherence's write-through caching implementation. TransactionMap is generally used when Coherence acts as system of record. TransactionMap is not generally compatible with write-through caching, so it will usually be either used to manage a standalone cache or when the cache is backed by a database via write-behind caching. TransactionMap has some restrictions that may limit its utility, the most significant being: The lock-based concurrency model is relatively inefficient and may introduce significant latency and contention. As an example, in a typical configuration, a transaction that updates 20 cache entries will require roughly 40ms just for lock management (assuming all locks are granted immediately, and excluding validation and writing which will require a similar amount of time). This may be partially mitigated by denormalizing (e.g. combining a parent object and its set of child objects into a single cache entry), at the cost of increasing false contention (e.g. transactions will conflict even when updating different child objects). If the client (application server JVM) fails during the commit phase, locks will be released immediately, and the transaction may be partially committed. In practice, this is usually not as bad as it may sound since the commit phase is usually very short (all locks having been previously acquired). Note that this vulnerability does not exist when a single NamedCache is used and all updates are confined to a single partition (generally implying the use of partition affinity). The unconventional TransactionMap API is cumbersome but manageable. Only a few methods are transactional, primarily get(), put() and remove(). The ACID transactions framework (accessed via the Connection class) provides atomicity guarantees by implementing the NamedCache interface, maintaining its own cache data and transaction logs inside a set of private partitioned caches. This feature may be used as either a local transactional resource or as logging XA resource. However, a lack of database integration precludes the use of this functionality for most applications. A side effect of this is that this feature has not seen significant adoption, meaning that any use of this is subject to the usual headaches associated with being an early adopter (greater chance of bugs and greater risk of hitting an unoptimized code path). As a result, for the moment, we generally recommend against using this feature. In summary, it is possible to use Coherence in XA-oriented applications, and several customers are doing this successfully, but it is not a core usage model for the product, so care should be taken before committing to this path. For most applications, the most robust solution is normally to use Coherence as a read-only cache of the underlying data resources, even if this prevents taking advantage of certain product features.

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  • Iterating through StaticResource loaded by ResourceDictionary

    - by akaphenom
    Given a resource dictionary loading some static resources into memory - is there any way to iterate through theResources loaded into memory? My silverlight application keeps telling me it cannot find a static resource. I wonder if I have a naming convention issue or somehting - was hoping iterating through the resources in memory would help diagnose any issue... I have the following app.xaml <Application xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation" xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml" x:Class="Module1.MyApp"> <Application.Resources> <ResourceDictionary> <ResourceDictionary.MergedDictionaries> <ResourceDictionary Source="/FSSilverlightApp;component/TransitioningFrame.xaml" /> </ResourceDictionary.MergedDictionaries> </ResourceDictionary> </Application.Resources> </Application> and content template: <ResourceDictionary xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation" xmlns:navigation="clr-namespace:System.Windows.Controls;assembly=System.Windows.Controls.Navigation" xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml"> <ControlTemplate x:Key="TransitioningFrame" TargetType="navigation:Frame"> <Border Background="{TemplateBinding Background}" BorderBrush="{TemplateBinding BorderBrush}" BorderThickness="{TemplateBinding BorderThickness}" HorizontalAlignment="{TemplateBinding HorizontalContentAlignment}" VerticalAlignment="{TemplateBinding VerticalContentAlignment}"> <ContentPresenter Cursor="{TemplateBinding Cursor}" HorizontalAlignment="{TemplateBinding HorizontalContentAlignment}" Margin="{TemplateBinding Padding}" VerticalAlignment="{TemplateBinding VerticalContentAlignment}" Content="{TemplateBinding Content}"/> </Border> </ControlTemplate> </ResourceDictionary>

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  • Which Computer Organization & Architecture book is good for me?

    - by claws
    I'm always interested in learning the inner working of things. I started with C programming and then learnt Operating systems (from stallings) and then linkers & loaders and then assembly language after reading these now I want to go into little more depth. Computer Architecture. I feel that makes everything clear. As per SO archives these are the two good books: Computer Architecture: A Quantitative Approach, 4th Edition Computer Organization and Design, Fourth Edition, ~ David A. Patterson, John L. Hennessy But I've browsed through the contents of these books and found that they don't exactly meet my needs. I want to learn more about caches, Memory Management Unit , mapping b/w virtual memory & physical memory I'm no way interested in other ISAs like MIPS etc.. I'm IA32 and X86-64 fan and I want to stick to it. I'm not a hardware developer I don't want to details like circuit diagrams or How is L1, L2 & L3 caches are implemented? I want to know the parallel processing technologies like HyperThreading at the architecture level but again I don't want to design them. I liked the table of Contents of - Computer Architecture: A Quantitative Approach, 4th Edition but Quantitave Approach? Seriously?? I want to know the details of current technologies and I dont want to spend reading 200 pages of outdated old technologies ( I experienced this while learning ASM}

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  • Perl XML SAX parser emulating XML::Simple record for record

    - by DVK
    Short Q summary: I am looking a fast XML parser (most likely a wrapper around some standard SAX parser) which will produce per-record data structure 100% identical to those produced by XML::Simple. Details: We have a large code infrastructure which depends on processing records one-by-one and expects the record to be a data structure in a format produced by XML::Simple since it always used XML::Simple since early Jurassic era. An example simple XML is: <root> <rec><f1>v1</f1><f2>v2</f2></rec> <rec><f1>v1b</f1><f2>v2b</f2></rec> <rec><f1>v1c</f1><f2>v2c</f2></rec> </root> And example rough code is: sub process_record { my ($obj, $record_hash) = @_; # do_stuff } my $records = XML::Simple->XMLin(@args)->{root}; foreach my $record (@$records) { $obj->process_record($record) }; As everyone knows XML::Simple is, well, simple. And more importantly, it is very slow and a memory hog - due to being a DOM parser and needing to build/store 100% of data in memory. So, it's not the best tool for parsing an XML file consisting of large amount of small records record-by-record. However, re-writing the entire code (which consist of large amount of "process_record"-like methods) to work with standard SAX parser seems like an big task not worth the resources, even at the cost of living with XML::Simple. What I'm looking for is an existing module which will probably be based on a SAX parser (or anything fast with small memory footprint) which can be used to produce $record hashrefs one by one based on the XML pictured above that can be passed to $obj->process_record($record) and be 100% identical to what XML::Simple's hashrefs would have been. I don't care much what the interface of the new module is - e.g whether I need to call next_record() or give it a callback coderef accepting a record.

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  • NPTL Default Stack Size Problem

    - by eyazici
    Hello, I am developing a multithread modular application using C programming language and NPTL 2.6. For each plugin, a POSIX thread is created. The problem is each thread has its own stack area, since default stack size depends on user's choice, this may results in huge memory consumption in some cases. To prevent unnecessary memory usage I used something similar to this to change stack size before creating each thread: pthread_attr_t attr; pthread_attr_init (&attr); pthread_attr_getstacksize(&attr, &st1); if(pthread_attr_setstacksize (&attr, MODULE_THREAD_SIZE) != 0) perror("Stack ERR"); pthread_attr_getstacksize(&attr, &st2); printf("OLD:%d, NEW:%d - MIN: %d\n", st1, st2, PTHREAD_STACK_MIN); pthread_attr_setdetachstate(&attr, PTHREAD_CREATE_DETACHED); /* "this" is static data structure that stores plugin related data */ pthread_create(&this->runner, &attr, (void *)(void *)this->run, NULL); EDIT I: pthread_create() section added. This did not work work as I expected, the stack size reported by pthread_attr_getstacksize() is changed but total memory usage of the application (from ps/top/pmap output) did not changed: OLD:10485760, NEW:65536 - MIN: 16384 When I use ulimit -s MY_STACK_SIZE_LIMIT before starting application I achieve the expected result. My questions are: 1-) Is there any portable(between UNIX variants) way to change (default)thread stack size after starting application(before creating thread of course)? 2-) Is it possible to use same stack area for every thread? 3-) Is it possible completely disable stack for threads without much pain?

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  • Delphi 2009: How do I prevent network application from leaking critical section?

    - by eed3si9n
    As part of Vista certification, Microsoft wants to make sure that an application exits without holding on to a lock (critical section): TEST CASE 31. Verify application does not break into a debugger with the specified AppVerifier checks (Req:3.2) As it turns out, network applications built using Delphi 2009 does break into the debugger, which displays unhelpful message as follows: (1214.1f10): Break instruction exception - code 80000003 (first chance) eax=00000001 ebx=07b64ff8 ecx=a6450000 edx=0007e578 esi=0017f7e0 edi=80000003 eip=77280004 esp=0017f780 ebp=0017f7ac iopl=0 nv up ei pl zr na pe nc cs=0023 ss=002b ds=002b es=002b fs=0053 gs=002b efl=00000246 *** ERROR: Symbol file could not be found. Defaulted to export symbols for C:\Windows\SysWOW64\ntdll.dll - ntdll!DbgBreakPoint: 77280004 cc int 3 After hitting Go button several times, you come across the actual error: ======================================= VERIFIER STOP 00000212: pid 0x18A4: Freeing virtual memory containing an active critical section. 076CC5DC : Critical section address. 01D0191C : Critical section initialization stack trace. 075D0000 : Memory block address. 00140000 : Memory block size. ======================================= This verifier stop is continuable. After debugging it use `go' to continue. ======================================= Given that my code does not leak TCriticalSection, how do I prevent Delphi from doing so.

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  • Problem in cropping the UIImage using CGContext?

    - by Rajendra Bhole
    Hi, I developing the simple UIApplication in which i want to crop the UIImage (in .jpg format) with help of CGContext. The developed code till now as follows, CGImageRef graphicOriginalImage = [originalImage.image CGImage]; UIGraphicsBeginImageContext(originalImage.image.size); CGContextRef ctx = UIGraphicsGetCurrentContext(); CGBitmapContextCreateImage(graphicOriginalImage); CGFloat fltW = originalImage.image.size.width; CGFloat fltH = originalImage.image.size.height; CGFloat X = round(fltW/4); CGFloat Y =round(fltH/4); CGFloat width = round(X + (fltW/2)); CGFloat height = round(Y + (fltH/2)); CGContextTranslateCTM(ctx, 0, image.size.height); CGContextScaleCTM(ctx, 1.0, -1.0); CGRect rect = CGRectMake(X,Y ,width ,height); CGContextDrawImage(ctx, rect, graphicOriginalImage); croppedImage = UIGraphicsGetImageFromCurrentImageContext(); return croppedImage; } The above code is worked fine but it can't crop image. The original image memory and cropped image memory i will got same(equal to original image memory). The above code is right for cropping the image?????????????????? How i cropping the image (in behind pixels should also be crop) from the center of the image???????????? I already wasting a lot of time for developing the above code , but i didn't get answer or way to find out how to crop the image.Thanks for sending me answer in advanced.

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  • Large Reports for MSRS

    - by Greg Lorenz
    I have a report that needs to be able to render a very large amount of pages (about 4500 in this instance) in a web browser. The total time needed to finish on the report server from start time to end time is about 30 mins for the instance that I am looking at. Does anyone know what options exist for handling the rendering of such a large report in a web browser? In terms of looking into how this can be resolved I have already performed the following tasks. The report gets its data off of a database table that already has the data flattened to the point that the TimeDataRetrieval on the report server is 17812 or about 18 secs. The report itself has been reformatted to include the least expensive report objects that it can in order to render the data in the correct format. I basically consists of a table with about 4 nested tables and thats it. We were trying to accomplish this on a 2005 report server but continued to run into memory issues that were not feasible for our clients. In response to that we moved this onto a 2008 report server to take advantage of the fact that it uses the file system instead of memory and finally were able to get this to work without running out of the available memory but of course it takes much longer.

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  • What file format can represent an uncompressed raster image at 48 or 64 bits per pixel?

    - by finnw
    I am creating screenshots under Windows and using the LockBits function from GDI+ to extract the pixel data, which will then be written to a file. To maximise performance I am also: Using the same PixelFormat as the source bitmap, to avoid format conversion Using the ImageLockModeUserInputBuf flag to extract the pixel data into a pre-allocated buffer This pre-allocated buffer (pointed to by BitmapData::Scan0) is part of a memory-mapped file (to avoid copying the pixel data again.) I will also be writing the code that reads the file, so I can use (or invent) any format I wish. However I would prefer to use a well-known format that existing programs (ideally web browsers) are able to read, because that means I can visually confirm that the images are correct before writing the code for the other program (that reads the image.) I have implemented this successfully for the PixelFormat32bppRGB format, which matches the format of a 32bpp BMP file, so if I extract the pixel data directly into the memory-mapped BMP file and prefix it with a BMP header I get a valid BMP image file that can be opened in Paint and most browsers. Unfortunately one of the machines I am testing on returns pixels in PixelFormat64bppPARGB format (presumably this is influenced by the video adapter driver) and there is no corresponding BMP pixel format for this. Converting to a 16, 24 or 32bpp BMP format slows the program down considerably (as well as being lossy) so I am looking for a file format that can use this pixel format without conversion, so I can extract directly into the memory-mapped file as I have done with the 32bpp format. What raster image file formats support 48bpp and/or 64bpp?

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  • Where are tables in Mnesia located?

    - by Sanoj
    I try to compare Mnesia with more traditional databases. As I understand it tables in Mnesia can be located to: ram_copies - tables are stored in RAM only, so no durability as in ACID. disc_copies - tables are located on disc and a copy is located in RAM, so the table can not be bigger than the available memory? disc_only_copies - tables are located to disc only, so no caching in memory and worse performance? And the size of the table are limited to the size of dets or the table has to be fragmented. So if I want the performance of doing reads from RAM and the durability of writes to disc, then the size of the tables are very limited compared to a traditional RDBMS like MySQL or PostgreSQL. I know that Mnesia aren't meant to replace traditional RDBMS:s, but can it be used as a big RDBMS or do I have to look for another database? The server I will use is a VPS with limited amount of memory, around 512MB, but I want good database performance. Are disc_copies and the other types of tables in Mnesia so limited as I have understood?

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  • Perl XML SAX parser emulating XML::Simple record for record

    - by DVK
    Short Q summary: I am looking a fast XML parser (most likely a wrapper around some standard SAX parser) which will produce per-record data structure 100% identical to those produced by XML::Simple. Details: We have a large code infrastructure which depends on processing records one-by-one and expects the record to be a data structure in a format produced by XML::Simple since it always used XML::Simple since early Jurassic era. An example simple XML is: <root> <rec><f1>v1</f1><f2>v2</f2></rec> <rec><f1>v1b</f1><f2>v2b</f2></rec> <rec><f1>v1c</f1><f2>v2c</f2></rec> </root> And example rough code is: sub process_record { my ($obj, $record_hash) = @_; # do_stuff } my $records = XML::Simple->XMLin(@args)->{root}; foreach my $record (@$records) { $obj->process_record($record) }; As everyone knows XML::Simple is, well, simple. And more importantly, it is very slow and a memory hog - due to being a DOM parser and needing to build/store 100% of data in memory. So, it's not the best tool for parsing an XML file consisting of large amount of small records record-by-record. However, re-writing the entire code (which consist of large amount of "process_record"-like methods) to work with standard SAX parser seems like an big task not worth the resources, even at the cost of living with XML::Simple. What I'm looking for is an existing module which will probably be based on a SAX parser (or anything fast with small memory footprint) which can be used to produce $record hashrefs one by one based on the XML pictured above that can be passed to $obj->process_record($record) and be 100% identical to what XML::Simple's hashrefs would have been.

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  • WCF Certificates without Certificate Store

    - by Kane
    My team is developing a number of WPF plug-ins for a 3rd party thick client application. The WPF plug-ins use WCF to consume web services published by a number of TIBCO services. The thick client application maintains a separate central data store and uses a proprietary API to access the data store. The thick client and WPF plug-ins are due to be deployed onto 10,000 workstations. Our customer wants to keep the certificate used by the thick client in the central data store so that they don't need to worry about re-issuing the certificate (current re-issue cycle takes about 3 months) and also have the opportunity to authorise the use of the certificate. The proposed architecture offers a form of shared secret / authentication between the central data store and the TIBCO services. Whilst I don’t necessarily agree with the proposed architecture our team is not able to change it and must work with what’s been provided. Basically our client wants us to build into our WPF plug-ins a mechanism which retrieves the certificate from the central data store (which will be allowed or denied based on roles in that data store) into memory then use the certificate for creating the SSL connection to the TIBCO services. No use of the local machine's certificate store is allowed and the in memory version is to be discarded at the end of each session. So the question is does anyone know if it is possible to pass an in-memory certificate to a WCF (.NET 3.5) service for SSL transport level encryption? Note: I had asked a similar question (here) but have since deleted it and re-asked it with more information.

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  • Debugging NSoperation BAD ACCESS within graphics context

    - by Joe
    I tried everything to debug this one but I can't get to the bottom of it. This code lives in a subclass of NSOperation which is processed from a queue: (borders is an ivar NSArray containing 5 UIimage objects) NSMutableArray *images = [[NSMutableArray alloc] init]; for (unsigned i = 0; i < 5; i++) { CGSize size = CGSizeMake(60, 60); UIGraphicsBeginImageContext(size); CGPoint thumbPoint = CGPointMake(6, 6); [controller.image drawAtPoint:thumbPoint]; CGPoint borderPoint = CGPointMake(0, 0); [[borders objectAtIndex:i] drawAtPoint:borderPoint]; [images addObject:UIGraphicsGetImageFromCurrentImageContext()]; UIGraphicsEndImageContext(); } [images release]; The code works fine most of the time but when I push the iphone by access subviews and pressing lots of buttons on the UI I either get this exception which is trapped by the operation: Exception Load view: *** -[NSCFArray insertObject:atIndex:]: attempt to insert nil or I get this: Program received signal: “EXC_BAD_ACCESS”. The exception is caused because UIGraphicsGetImageFromCurrentImageContext() return nil. I don't know how to debug the EXC_BAD_ACCESS but I'm guessing that this error (in fact both of these errors) is caused by low memory. The debugger stops at the line: [controller.image drawAtPoint:thumbPoint]; As I mentioned I've trapped the exception so I can live with that but the EXC_BAD_ACCESS is more serious. IF this is memory related how can I tell and is it possible to increase the memory available to NSOperation?

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  • Most efficient way to send images across processes

    - by Heinrich Ulbricht
    Goal Pass images generated by one process efficiently and at very high speed to another process. The two processes run on the same machine and on the same desktop. The operating system may be WinXP, Vista and Win7. Detailled description The first process is solely for controlling the communication with a device which produces the images. These images are about 500x300px in size and may be updated up to several hundred times per second. The second process needs these images to display them. The first process uses a third party API to paint the images from the device to a HDC. This HDC has to be provided by me. Note: There is already a connection open between the two processes. They are communicating via anonymous pipes and share memory mapped file views. Thoughts How would I achieve this goal with as little work as possible? And I mean both work for me and the computer. I am using Delphi, so maybe there is some component available for doing this? I think I could always paint to any image component's HDC, save the content to memory stream, copy the contents via the memory mapped file, unpack it on the other side and paint it there to the destination HDC. I also read about a IPicture interface which can be used to marshall images. What are your ideas? I appreciate every thought on this!

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  • Android:Playing bigger size audio wav sound file produces crash

    - by user187532
    Hi Android experts, I am trying to play the bigger size audio wav file(which is 20 mb) using the following code(AudioTrack) on my Android 1.6 HTC device which basically has less memory. But i found device crash as soon as it executes reading, writing and play. But the same code works fine and plays the lesser size audio wav files(10kb, 20 kb files etc) very well. P.S: I should play PCM(.wav) buffer sound, the reason behind why i use AudioTrack here. Though my device has lesser memory, how would i read bigger audio files bytes by bytes and play the sound to avoid crashing due to memory constraints. private void AudioTrackPlayPCM() throws IOException { String filePath = "/sdcard/myWav.wav"; // 8 kb file byte[] byteData = null; File file = null; file = new File(filePath); byteData = new byte[(int) file.length()]; FileInputStream in = null; try { in = new FileInputStream( file ); in.read( byteData ); in.close(); } catch (FileNotFoundException e) { // TODO Auto-generated catch block e.printStackTrace(); } int intSize = android.media.AudioTrack.getMinBufferSize(8000, AudioFormat.CHANNEL_CONFIGURATION_MONO, AudioFormat.ENCODING_PCM_8BIT); AudioTrack at = new AudioTrack(AudioManager.STREAM_MUSIC, 8000, AudioFormat.CHANNEL_CONFIGURATION_MONO, AudioFormat.ENCODING_PCM_8BIT, intSize, AudioTrack.MODE_STREAM); at.play(); at.write(byteData, 0, byteData.length); at.stop(); at.release(); } Could someone guide me please to play the AudioTrack code for bigger size wav files?

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  • Multithreading and Interrupts

    - by Nicholas Flynt
    I'm doing some work on the input buffers for my kernel, and I had some questions. On Dual Core machines, I know that more than one "process" can be running simultaneously. What I don't know is how the OS and the individual programs work to protect collisions in data. There are two things I'd like to know on this topic: (1) Where do interrupts occur? Are they guaranteed to occur on one core and not the other, and could this be used to make sure that real-time operations on one core were not interrupted by, say, file IO which could be handled on the other core? (I'd logically assume that the interrupts would happen on the 1st core, but is that always true, and how would you tell? Or perhaps does each core have its own settings for interrupts? Wouldn't that lead to a scenario where each core could react simultaneously to the same interrupt, possibly in different ways?) (2) How does the dual core processor handle opcode memory collision? If one core is reading an address in memory at exactly the same time that another core is writing to that same address in memory, what happens? Is an exception thrown, or is a value read? (I'd assume the write would work either way.) If a value is read, is it guaranteed to be either the old or new value at the time of the collision? I understand that programs should ideally be written to avoid these kinds of complications, but the OS certainly can't expect that, and will need to be able to handle such events without choking on itself.

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