Search Results

Search found 1169 results on 47 pages for 'roman matveev'.

Page 6/47 | < Previous Page | 2 3 4 5 6 7 8 9 10 11 12 13  | Next Page >

• Ubuntu 12.04 Precise on Dell Inspirion Duo

  - by Roman M. Kos

  I installed 12.04 version of Ubuntu on my Dell Inspiron Duo. After installing with help of program like UNetBootIn or smth like that. ( Besides i have no problem with kernel panic on chargin on/off like in 11.10. ) After that i followed with steps from here, in the first post here: http://ubuntuforums.org/showthread.php?t=1658635 There left one big problem with touchscreen: When i whant to drag with touchscreen like i`m doing it with mouse (for ex. selecting multile files with mouse) the selectable rectangular doesnot shows while im dragging, when dragging was finished (i put my finger off) it shows the rectangular and hides it. This thing disables all my tries to drag a window or smth else.... Also some time after using touchscreen such things are disabeling: - Often - click from a mouse (after keyboard using functinality restores) - less often - mouse movement disables (sometimes restores sometimes not) - lesser than other - keyboards works but no sygnals accepting (keyoards has indicator, so thay react, mouse of course not) The test from eTouchU utility passes perfeclty. Any idia for solving this problem? P.S.: Im from Ukraine, so sorry if my possible grammar mistakes. P.P.S.: Besides how to know the physicall position of my tabled mode? For automaticall rotating. Like on each rotation do some script.

  Read the article

• StreamInsight 2.1, meet LINQ

  - by Roman Schindlauer

  Someone recently called LINQ “magic” in my hearing. I leapt to LINQ’s defense immediately. Turns out some people don’t realize “magic” is can be a pejorative term. I thought LINQ needed demystification. Here’s your best demystification resource: http://blogs.msdn.com/b/mattwar/archive/2008/11/18/linq-links.aspx. I won’t repeat much of what Matt Warren says in his excellent series, but will talk about some core ideas and how they affect the 2.1 release of StreamInsight. Let’s tell the story of a LINQ query. Compile time It begins with some code: IQueryable<Product> products = ...; var query = from p in products             where p.Name == "Widget"             select p.ProductID; foreach (int id in query) {     ... When the code is compiled, the C# compiler (among other things) de-sugars the query expression (see C# spec section 7.16): ... var query = products.Where(p => p.Name == "Widget").Select(p => p.ProductID); ... Overload resolution subsequently binds the Queryable.Where<Product> and Queryable.Select<Product, int> extension methods (see C# spec sections 7.5 and 7.6.5). After overload resolution, the compiler knows something interesting about the anonymous functions (lambda syntax) in the de-sugared code: they must be converted to expression trees, i.e.,“an object structure that represents the structure of the anonymous function itself” (see C# spec section 6.5). The conversion is equivalent to the following rewrite: ... var prm1 = Expression.Parameter(typeof(Product), "p"); var prm2 = Expression.Parameter(typeof(Product), "p"); var query = Queryable.Select<Product, int>(     Queryable.Where<Product>(         products,         Expression.Lambda<Func<Product, bool>>(Expression.Property(prm1, "Name"), prm1)),         Expression.Lambda<Func<Product, int>>(Expression.Property(prm2, "ProductID"), prm2)); ... If the “products” expression had type IEnumerable<Product>, the compiler would have chosen the Enumerable.Where and Enumerable.Select extension methods instead, in which case the anonymous functions would have been converted to delegates. At this point, we’ve reduced the LINQ query to familiar code that will compile in C# 2.0. (Note that I’m using C# snippets to illustrate transformations that occur in the compiler, not to suggest a viable compiler design!) Runtime When the above program is executed, the Queryable.Where method is invoked. It takes two arguments. The first is an IQueryable<> instance that exposes an Expression property and a Provider property. The second is an expression tree. The Queryable.Where method implementation looks something like this: public static IQueryable<T> Where<T>(this IQueryable<T> source, Expression<Func<T, bool>> predicate) {     return source.Provider.CreateQuery<T>(     Expression.Call(this method, source.Expression, Expression.Quote(predicate))); } Notice that the method is really just composing a new expression tree that calls itself with arguments derived from the source and predicate arguments. Also notice that the query object returned from the method is associated with the same provider as the source query. By invoking operator methods, we’re constructing an expression tree that describes a query. Interestingly, the compiler and operator methods are colluding to construct a query expression tree. The important takeaway is that expression trees are built in one of two ways: (1) by the compiler when it sees an anonymous function that needs to be converted to an expression tree, and; (2) by a query operator method that constructs a new queryable object with an expression tree rooted in a call to the operator method (self-referential). Next we hit the foreach block. At this point, the power of LINQ queries becomes apparent. The provider is able to determine how the query expression tree is evaluated! The code that began our story was intentionally vague about the definition of the “products” collection. Maybe it is a queryable in-memory collection of products: var products = new[]     { new Product { Name = "Widget", ProductID = 1 } }.AsQueryable(); The in-memory LINQ provider works by rewriting Queryable method calls to Enumerable method calls in the query expression tree. It then compiles the expression tree and evaluates it. It should be mentioned that the provider does not blindly rewrite all Queryable calls. It only rewrites a call when its arguments have been rewritten in a way that introduces a type mismatch, e.g. the first argument to Queryable.Where<Product> being rewritten as an expression of type IEnumerable<Product> from IQueryable<Product>. The type mismatch is triggered initially by a “leaf” expression like the one associated with the AsQueryable query: when the provider recognizes one of its own leaf expressions, it replaces the expression with the original IEnumerable<> constant expression. I like to think of this rewrite process as “type irritation” because the rewritten leaf expression is like a foreign body that triggers an immune response (further rewrites) in the tree. The technique ensures that only those portions of the expression tree constructed by a particular provider are rewritten by that provider: no type irritation, no rewrite. Let’s consider the behavior of an alternative LINQ provider. If “products” is a collection created by a LINQ to SQL provider: var products = new NorthwindDataContext().Products; the provider rewrites the expression tree as a SQL query that is then evaluated by your favorite RDBMS. The predicate may ultimately be evaluated using an index! In this example, the expression associated with the Products property is the “leaf” expression. StreamInsight 2.1 For the in-memory LINQ to Objects provider, a leaf is an in-memory collection. For LINQ to SQL, a leaf is a table or view. When defining a “process” in StreamInsight 2.1, what is a leaf? To StreamInsight a leaf is logic: an adapter, a sequence, or even a query targeting an entirely different LINQ provider! How do we represent the logic? Remember that a standing query may outlive the client that provisioned it. A reference to a sequence object in the client application is therefore not terribly useful. But if we instead represent the code constructing the sequence as an expression, we can host the sequence in the server: using (var server = Server.Connect(...)) {     var app = server.Applications["my application"];     var source = app.DefineObservable(() => Observable.Range(0, 10, Scheduler.NewThread));     var query = from i in source where i % 2 == 0 select i; } Example 1: defining a source and composing a query Let’s look in more detail at what’s happening in example 1. We first connect to the remote server and retrieve an existing app. Next, we define a simple Reactive sequence using the Observable.Range method. Notice that the call to the Range method is in the body of an anonymous function. This is important because it means the source sequence definition is in the form of an expression, rather than simply an opaque reference to an IObservable<int> object. The variation in Example 2 fails. Although it looks similar, the sequence is now a reference to an in-memory observable collection: var local = Observable.Range(0, 10, Scheduler.NewThread); var source = app.DefineObservable(() => local); // can’t serialize ‘local’! Example 2: error referencing unserializable local object The Define* methods support definitions of operator tree leaves that target the StreamInsight server. These methods all have the same basic structure. The definition argument is a lambda expression taking between 0 and 16 arguments and returning a source or sink. The method returns a proxy for the source or sink that can then be used for the usual style of LINQ query composition. The “define” methods exploit the compile-time C# feature that converts anonymous functions into translatable expression trees! Query composition exploits the runtime pattern that allows expression trees to be constructed by operators taking queryable and expression (Expression<>) arguments. The practical upshot: once you’ve Defined a source, you can compose LINQ queries in the familiar way using query expressions and operator combinators. Notably, queries can be composed using pull-sequences (LINQ to Objects IQueryable<> inputs), push sequences (Reactive IQbservable<> inputs), and temporal sequences (StreamInsight IQStreamable<> inputs). You can even construct processes that span these three domains using “bridge” method overloads (ToEnumerable, ToObservable and To*Streamable). Finally, the targeted rewrite via type irritation pattern is used to ensure that StreamInsight computations can leverage other LINQ providers as well. Consider the following example (this example depends on Interactive Extensions): var source = app.DefineEnumerable((int id) =>     EnumerableEx.Using(() =>         new NorthwindDataContext(), context =>             from p in context.Products             where p.ProductID == id             select p.ProductName)); Within the definition, StreamInsight has no reason to suspect that it ‘owns’ the Queryable.Where and Queryable.Select calls, and it can therefore defer to LINQ to SQL! Let’s use this source in the context of a StreamInsight process: var sink = app.DefineObserver(() => Observer.Create<string>(Console.WriteLine)); var query = from name in source(1).ToObservable()             where name == "Widget"             select name; using (query.Bind(sink).Run("process")) {     ... } When we run the binding, the source portion which filters on product ID and projects the product name is evaluated by SQL Server. Outside of the definition, responsibility for evaluation shifts to the StreamInsight server where we create a bridge to the Reactive Framework (using ToObservable) and evaluate an additional predicate. It’s incredibly easy to define computations that span multiple domains using these new features in StreamInsight 2.1! Regards, The StreamInsight Team

  Read the article

• System broken after installing Gtk+-3.4.1 with broadway backend enabled

  - by Roman D. Boiko

  I am running Ubuntu 11.10 from VirtualBox. I installed Gtk+ 3.4.1 (latest stable release) from sources with X11 and broadway backends enabled. In order to do that, I also installed latest versions of glib, libffi, libtiff, libjped, gdk-pixbuf, and pango. Each of them was configured with default options. I.e., they were installed to /usr/local (at least, I see respective folders in /usr/local/include). After reboot and login (regardless which user), desktop is grey for about 30 sec, nothing is displayed. Then Nautilus starts, but nothing else (my locale is Ukrainian, but there is nothing important in text): . During boot, I can access command prompt as root, use dpkg, etc. But I don't know what to do. One idea is to reinstall Gtk+ and other libraries with prefix /usr or /usr/shared. I will try that, but it is quite time-consuming, so any ideas would be welcome. Reverting to earlier snapshot is still possible, but it is 6 days old and I would like to try to solve the problem.

  Read the article

• Taming Hopping Windows

  - by Roman Schindlauer

  At first glance, hopping windows seem fairly innocuous and obvious. They organize events into windows with a simple periodic definition: the windows have some duration d (e.g. a window covers 5 second time intervals), an interval or period p (e.g. a new window starts every 2 seconds) and an alignment a (e.g. one of those windows starts at 12:00 PM on March 15, 2012 UTC). var wins = xs     .HoppingWindow(TimeSpan.FromSeconds(5),                    TimeSpan.FromSeconds(2),                    new DateTime(2012, 3, 15, 12, 0, 0, DateTimeKind.Utc)); Logically, there is a window with start time a + np and end time a + np + d for every integer n. That’s a lot of windows. So why doesn’t the following query (always) blow up? var query = wins.Select(win => win.Count()); A few users have asked why StreamInsight doesn’t produce output for empty windows. Primarily it’s because there is an infinite number of empty windows! (Actually, StreamInsight uses DateTimeOffset.MaxValue to approximate “the end of time” and DateTimeOffset.MinValue to approximate “the beginning of time”, so the number of windows is lower in practice.) That was the good news. Now the bad news. Events also have duration. Consider the following simple input: var xs = this.Application                 .DefineEnumerable(() => new[]                     { EdgeEvent.CreateStart(DateTimeOffset.UtcNow, 0) })                 .ToStreamable(AdvanceTimeSettings.IncreasingStartTime); Because the event has no explicit end edge, it lasts until the end of time. So there are lots of non-empty windows if we apply a hopping window to that single event! For this reason, we need to be careful with hopping window queries in StreamInsight. Or we can switch to a custom implementation of hopping windows that doesn’t suffer from this shortcoming. The alternate window implementation produces output only when the input changes. We start by breaking up the timeline into non-overlapping intervals assigned to each window. In figure 1, six hopping windows (“Windows”) are assigned to six intervals (“Assignments”) in the timeline. Next we take input events (“Events”) and alter their lifetimes (“Altered Events”) so that they cover the intervals of the windows they intersect. In figure 1, you can see that the first event e1 intersects windows w1 and w2 so it is adjusted to cover assignments a1 and a2. Finally, we can use snapshot windows (“Snapshots”) to produce output for the hopping windows. Notice however that instead of having six windows generating output, we have only four. The first and second snapshots correspond to the first and second hopping windows. The remaining snapshots however cover two hopping windows each! While in this example we saved only two events, the savings can be more significant when the ratio of event duration to window duration is higher. Figure 1: Timeline The implementation of this strategy is straightforward. We need to set the start times of events to the start time of the interval assigned to the earliest window including the start time. Similarly, we need to modify the end times of events to the end time of the interval assigned to the latest window including the end time. The following snap-to-boundary function that rounds a timestamp value t down to the nearest value t' <= t such that t' is a + np for some integer n will be useful. For convenience, we will represent both DateTime and TimeSpan values using long ticks: static long SnapToBoundary(long t, long a, long p) {     return t - ((t - a) % p) - (t > a ? 0L : p); } How do we find the earliest window including the start time for an event? It’s the window following the last window that does not include the start time assuming that there are no gaps in the windows (i.e. duration < interval), and limitation of this solution. To find the end time of that antecedent window, we need to know the alignment of window ends: long e = a + (d % p); Using the window end alignment, we are finally ready to describe the start time selector: static long AdjustStartTime(long t, long e, long p) {     return SnapToBoundary(t, e, p) + p; } To find the latest window including the end time for an event, we look for the last window start time (non-inclusive): public static long AdjustEndTime(long t, long a, long d, long p) {     return SnapToBoundary(t - 1, a, p) + p + d; } Bringing it together, we can define the translation from events to ‘altered events’ as in Figure 1: public static IQStreamable<T> SnapToWindowIntervals<T>(IQStreamable<T> source, TimeSpan duration, TimeSpan interval, DateTime alignment) {     if (source == null) throw new ArgumentNullException("source");     // reason about DateTime and TimeSpan in ticks     long d = Math.Min(DateTime.MaxValue.Ticks, duration.Ticks);     long p = Math.Min(DateTime.MaxValue.Ticks, Math.Abs(interval.Ticks));     // set alignment to earliest possible window     var a = alignment.ToUniversalTime().Ticks % p;     // verify constraints of this solution     if (d <= 0L) { throw new ArgumentOutOfRangeException("duration"); }     if (p == 0L || p > d) { throw new ArgumentOutOfRangeException("interval"); }     // find the alignment of window ends     long e = a + (d % p);     return source.AlterEventLifetime(         evt => ToDateTime(AdjustStartTime(evt.StartTime.ToUniversalTime().Ticks, e, p)),         evt => ToDateTime(AdjustEndTime(evt.EndTime.ToUniversalTime().Ticks, a, d, p)) -             ToDateTime(AdjustStartTime(evt.StartTime.ToUniversalTime().Ticks, e, p))); } public static DateTime ToDateTime(long ticks) {     // just snap to min or max value rather than under/overflowing     return ticks < DateTime.MinValue.Ticks         ? new DateTime(DateTime.MinValue.Ticks, DateTimeKind.Utc)         : ticks > DateTime.MaxValue.Ticks         ? new DateTime(DateTime.MaxValue.Ticks, DateTimeKind.Utc)         : new DateTime(ticks, DateTimeKind.Utc); } Finally, we can describe our custom hopping window operator: public static IQWindowedStreamable<T> HoppingWindow2<T>(     IQStreamable<T> source,     TimeSpan duration,     TimeSpan interval,     DateTime alignment) {     if (source == null) { throw new ArgumentNullException("source"); }     return SnapToWindowIntervals(source, duration, interval, alignment).SnapshotWindow(); } By switching from HoppingWindow to HoppingWindow2 in the following example, the query returns quickly rather than gobbling resources and ultimately failing! public void Main() {     var start = new DateTimeOffset(new DateTime(2012, 6, 28), TimeSpan.Zero);     var duration = TimeSpan.FromSeconds(5);     var interval = TimeSpan.FromSeconds(2);     var alignment = new DateTime(2012, 3, 15, 12, 0, 0, DateTimeKind.Utc);     var events = this.Application.DefineEnumerable(() => new[]     {         EdgeEvent.CreateStart(start.AddSeconds(0), "e0"),         EdgeEvent.CreateStart(start.AddSeconds(1), "e1"),         EdgeEvent.CreateEnd(start.AddSeconds(1), start.AddSeconds(2), "e1"),         EdgeEvent.CreateStart(start.AddSeconds(3), "e2"),         EdgeEvent.CreateStart(start.AddSeconds(9), "e3"),         EdgeEvent.CreateEnd(start.AddSeconds(3), start.AddSeconds(10), "e2"),         EdgeEvent.CreateEnd(start.AddSeconds(9), start.AddSeconds(10), "e3"),     }).ToStreamable(AdvanceTimeSettings.IncreasingStartTime);     var adjustedEvents = SnapToWindowIntervals(events, duration, interval, alignment);     var query = from win in HoppingWindow2(events, duration, interval, alignment)                 select win.Count();     DisplayResults(adjustedEvents, "Adjusted Events");     DisplayResults(query, "Query"); } As you can see, instead of producing a massive number of windows for the open start edge e0, a single window is emitted from 12:00:15 AM until the end of time: Adjusted Events StartTime EndTime Payload 6/28/2012 12:00:01 AM 12/31/9999 11:59:59 PM e0 6/28/2012 12:00:03 AM 6/28/2012 12:00:07 AM e1 6/28/2012 12:00:05 AM 6/28/2012 12:00:15 AM e2 6/28/2012 12:00:11 AM 6/28/2012 12:00:15 AM e3 Query StartTime EndTime Payload 6/28/2012 12:00:01 AM 6/28/2012 12:00:03 AM 1 6/28/2012 12:00:03 AM 6/28/2012 12:00:05 AM 2 6/28/2012 12:00:05 AM 6/28/2012 12:00:07 AM 3 6/28/2012 12:00:07 AM 6/28/2012 12:00:11 AM 2 6/28/2012 12:00:11 AM 6/28/2012 12:00:15 AM 3 6/28/2012 12:00:15 AM 12/31/9999 11:59:59 PM 1 Regards, The StreamInsight Team

  Read the article

• How do I pitch ASP.NET over PHP to a potential client?

  - by roman m

  I work at a Microsoft shop doing mainly web development. We had a client who asked us to review (improve) the data model for his web app, but said that he wants to develop his app in PHP (he knows "a guy" who can do it). When I asked him why he wants to go with PHP, he gave me the standard set of arguments from the 90's: Microsoft is evil, and PHP is free Writing an ASP.NET app is more expensive (software-wise) Why would Facebook use PHP if it was a bad idea? [classic] He had a few more comments about the costs associated with going .NET. The truth is that "Microsoft is expensive" does not hold water any longer, with their "Express" suite, you can develop an ASP.NET app without paying anything for software. When it comes to hosting, you can save a few bucks with PHP over .NET, but that's a small fraction of the projected development costs (we quoted 10-15k). Going back to my question, what arguments would I give to a client in favor of ASP.NET over PHP? [please provide sources for quantitative claims]

  Read the article

• Changes to the LINQ-to-StreamInsight Dialect

  - by Roman Schindlauer

  In previous versions of StreamInsight (1.0 through 2.0), CepStream<> represents temporal streams of many varieties: Streams with ‘open’ inputs (e.g., those defined and composed over CepStream<T>.Create(string streamName) Streams with ‘partially bound’ inputs (e.g., those defined and composed over CepStream<T>.Create(Type adapterFactory, …)) Streams with fully bound inputs (e.g., those defined and composed over To*Stream – sequences or DQC) The stream may be embedded (where Server.Create is used) The stream may be remote (where Server.Connect is used) When adding support for new programming primitives in StreamInsight 2.1, we faced a choice: Add a fourth variety (use CepStream<> to represent streams that are bound the new programming model constructs), or introduce a separate type that represents temporal streams in the new user model. We opted for the latter. Introducing a new type has the effect of reducing the number of (confusing) runtime failures due to inappropriate uses of CepStream<> instances in the incorrect context. The new types are: IStreamable<>, which logically represents a temporal stream. IQStreamable<> : IStreamable<>, which represents a queryable temporal stream. Its relationship to IStreamable<> is analogous to the relationship of IQueryable<> to IEnumerable<>. The developer can compose temporal queries over remote stream sources using this type. The syntax of temporal queries composed over IQStreamable<> is mostly consistent with the syntax of our existing CepStream<>-based LINQ provider. However, we have taken the opportunity to refine certain aspects of the language surface. Differences are outlined below. Because 2.1 introduces new types to represent temporal queries, the changes outlined in this post do no impact existing StreamInsight applications using the existing types! SelectMany StreamInsight does not support the SelectMany operator in its usual form (which is analogous to SQL’s “CROSS APPLY” operator): static IEnumerable<R> SelectMany<T, R>(this IEnumerable<T> source, Func<T, IEnumerable<R>> collectionSelector) It instead uses SelectMany as a convenient syntactic representation of an inner join. The parameter to the selector function is thus unavailable. Because the parameter isn’t supported, its type in StreamInsight 1.0 – 2.0 wasn’t carefully scrutinized. Unfortunately, the type chosen for the parameter is nonsensical to LINQ programmers: static CepStream<R> SelectMany<T, R>(this CepStream<T> source, Expression<Func<CepStream<T>, CepStream<R>>> streamSelector) Using Unit as the type for the parameter accurately reflects the StreamInsight’s capabilities: static IQStreamable<R> SelectMany<T, R>(this IQStreamable<T> source, Expression<Func<Unit, IQStreamable<R>>> streamSelector) For queries that succeed – that is, queries that do not reference the stream selector parameter – there is no difference between the code written for the two overloads: from x in xs from y in ys select f(x, y) Top-K The Take operator used in StreamInsight causes confusion for LINQ programmers because it is applied to the (unbounded) stream rather than the (bounded) window, suggesting that the query as a whole will return k rows: (from win in xs.SnapshotWindow() from x in win orderby x.A select x.B).Take(k) The use of SelectMany is also unfortunate in this context because it implies the availability of the window parameter within the remainder of the comprehension. The following compiles but fails at runtime: (from win in xs.SnapshotWindow() from x in win orderby x.A select win).Take(k) The Take operator in 2.1 is applied to the window rather than the stream: Before After (from win in xs.SnapshotWindow() from x in win orderby x.A select x.B).Take(k) from win in xs.SnapshotWindow() from b in     (from x in win     orderby x.A     select x.B).Take(k) select b Multicast We are introducing an explicit multicast operator in order to preserve expression identity, which is important given the semantics about moving code to and from StreamInsight. This also better matches existing LINQ dialects, such as Reactive. This pattern enables expressing multicasting in two ways: Implicit Explicit var ys = from x in xs          where x.A > 1          select x; var zs = from y1 in ys          from y2 in ys.ShiftEventTime(_ => TimeSpan.FromSeconds(1))          select y1 + y2; var ys = from x in xs          where x.A > 1          select x; var zs = ys.Multicast(ys1 =>     from y1 in ys1     from y2 in ys1.ShiftEventTime(_ => TimeSpan.FromSeconds(1))     select y1 + y2; Notice the product translates an expression using implicit multicast into an expression using the explicit multicast operator. The user does not see this translation. Default window policies Only default window policies are supported in the new surface. Other policies can be simulated by using AlterEventLifetime. Before After xs.SnapshotWindow(     WindowInputPolicy.ClipToWindow,     SnapshotWindowInputPolicy.Clip) xs.SnapshotWindow() xs.TumblingWindow(     TimeSpan.FromSeconds(1),     HoppingWindowOutputPolicy.PointAlignToWindowEnd) xs.TumblingWindow(     TimeSpan.FromSeconds(1)) xs.TumblingWindow(     TimeSpan.FromSeconds(1),     HoppingWindowOutputPolicy.ClipToWindowEnd) Not supported … LeftAntiJoin Representation of LASJ as a correlated sub-query in the LINQ surface is problematic as the StreamInsight engine does not support correlated sub-queries (see discussion of SelectMany). The current syntax requires the introduction of an otherwise unsupported ‘IsEmpty()’ operator. As a result, the pattern is not discoverable and implies capabilities not present in the server. The direct representation of LASJ is used instead: Before After from x in xs where     (from y in ys     where x.A > y.B     select y).IsEmpty() select x xs.LeftAntiJoin(ys, (x, y) => x.A > y.B) from x in xs where     (from y in ys     where x.A == y.B     select y).IsEmpty() select x xs.LeftAntiJoin(ys, x => x.A, y => y.B) ApplyWithUnion The ApplyWithUnion methods have been deprecated since their signatures are redundant given the standard SelectMany overloads: Before After xs.GroupBy(x => x.A).ApplyWithUnion(gs => from win in gs.SnapshotWindow() select win.Count()) xs.GroupBy(x => x.A).SelectMany(     gs =>     from win in gs.SnapshotWindow()     select win.Count()) xs.GroupBy(x => x.A).ApplyWithUnion(gs => from win in gs.SnapshotWindow() select win.Count(), r => new { r.Key, Count = r.Payload }) from x in xs group x by x.A into gs from win in gs.SnapshotWindow() select new { gs.Key, Count = win.Count() } Alternate UDO syntax The representation of UDOs in the StreamInsight LINQ dialect confuses cardinalities. Based on the semantics of user-defined operators in StreamInsight, one would expect to construct queries in the following form: from win in xs.SnapshotWindow() from y in MyUdo(win) select y Instead, the UDO proxy method is referenced within a projection, and the (many) results returned by the user code are automatically flattened into a stream: from win in xs.SnapshotWindow() select MyUdo(win) The “many-or-one” confusion is exemplified by the following example that compiles but fails at runtime: from win in xs.SnapshotWindow() select MyUdo(win) + win.Count() The above query must fail because the UDO is in fact returning many values per window while the count aggregate is returning one. Original syntax New alternate syntax from win in xs.SnapshotWindow() select win.UdoProxy(1) from win in xs.SnapshotWindow() from y in win.UserDefinedOperator(() => new Udo(1)) select y -or- from win in xs.SnapshotWindow() from y in win.UdoMacro(1) select y Notice that this formulation also sidesteps the dynamic type pitfalls of the existing “proxy method” approach to UDOs, in which the type of the UDO implementation (TInput, TOuput) and the type of its constructor arguments (TConfig) need to align in a precise and non-obvious way with the argument and return types for the corresponding proxy method. UDSO syntax UDSO currently leverages the DataContractSerializer to clone initial state for logical instances of the user operator. Initial state will instead be described by an expression in the new LINQ surface. Before After xs.Scan(new Udso()) xs.Scan(() => new Udso()) Name changes ShiftEventTime => AlterEventStartTime: The alter event lifetime overload taking a new start time value has been renamed. CountByStartTimeWindow => CountWindow

  Read the article

• Can I give my app my own ads? (iOS/Android)

  - by aldo.roman.nurena

  I want to know if I can develop my app on iOS and Android (no matter how, that's another thread) and give them my own ads, not the ones provided by them. This way I make the deals with customers directly. Implementation does not seem to be hard. The hard question is: will I get approved on the stores? It would be a free app with 3rd-party-ads Thanks! PS: I know I can distribute APKs out of the GPlay, but I don't want to do this. PS2: bonus points for WP/BB info, but not critical

  Read the article

• Is there any simple game that involves psychological factors?

  - by Roman

  I need to find a simple game in which several people need to interact with each other. The game should be simple for an analysis (it should be simple to describe what happens in the game, what players did). Because of the last reason, the video games are not appropriate for my purposes. I am thinking of a simple, schematic, strategic game where people can make a limited set of simple moves. Moreover, the moves of the game should be conditioned not only by a pure logic (like in chess or go). The behavior in the game should depend on psychological factors, on relations between people. In more details, I think it should be a cooperation game where people make their decisions based on mutual trust. It would be nice if players can express punishment and forgiveness in the game. Does anybody knows a game that is close to what I have described above? ADDED I need to add that I need a game where actions of players are simple and easy to formalize. Because of that I cannot use verbal games (where communication between players is important). By simple actions I understand, for example, moves on the board from one position to another one, or passing chips from one player to another one and so on.

  Read the article

• Parameterized StreamInsight Queries

  - by Roman Schindlauer

  The changes in our APIs enable a set of scenarios that were either not possible before or could only be achieved through workarounds. One such use case that people ask about frequently is the ability to parameterize a query and instantiate it with different values instead of re-deploying the entire statement. I’ll demonstrate how to do this in StreamInsight 2.1 and combine it with a method of using subjects for dynamic query composition in a mini-series of (at least) two blog articles. Let’s start with something really simple: I want to deploy a windowed aggregate to a StreamInsight server, and later use it with different window sizes. The LINQ statement for such an aggregate is very straightforward and familiar: var result = from win in stream.TumblingWindow(TimeSpan.FromSeconds(5))               select win.Avg(e => e.Value); Obviously, we had to use an existing input stream object as well as a concrete TimeSpan value. If we want to be able to re-use this construct, we can define it as a IQStreamable: var avg = myApp     .DefineStreamable((IQStreamable<SourcePayload> s, TimeSpan w) =>         from win in s.TumblingWindow(w)         select win.Avg(e => e.Value)); The DefineStreamable API lets us define a function, in our case from a IQStreamable (the input stream) and a TimeSpan (the window length) to an IQStreamable (the result). We can then use it like a function, with the input stream and the window length as parameters: var result = avg(stream, TimeSpan.FromSeconds(5)); Nice, but you might ask: what does this save me, except from writing my own extension method? Well, in addition to defining the IQStreamable function, you can actually deploy it to the server, to make it re-usable by another process! When we deploy an artifact in V2.1, we give it a name: var avg = myApp     .DefineStreamable((IQStreamable<SourcePayload> s, TimeSpan w) =>         from win in s.TumblingWindow(w)         select win.Avg(e => e.Value))     .Deploy("AverageQuery"); When connected to the same server, we can now use that name to retrieve the IQStreamable and use it with our own parameters: var averageQuery = myApp     .GetStreamable<IQStreamable<SourcePayload>, TimeSpan, double>("AverageQuery"); var result = averageQuery(stream, TimeSpan.FromSeconds(5)); Convenient, isn’t it? Keep in mind that, even though the function “AverageQuery” is deployed to the server, its logic will still be instantiated into each process when the process is created. The advantage here is being able to deploy that function, so another client who wants to use it doesn’t need to ask the author for the code or assembly, but just needs to know the name of deployed entity. A few words on the function signature of GetStreamable: the last type parameter (here: double) is the payload type of the result, not the actual result stream’s type itself. The returned object is a function from IQStreamable<SourcePayload> and TimeSpan to IQStreamable<double>. In the next article we will integrate this usage of IQStreamables with Subjects in StreamInsight, so stay tuned! Regards, The StreamInsight Team

  Read the article

• StreamInsight Now Available Through Microsoft Update

  - by Roman Schindlauer

  We are pleased to announce that StreamInsight v1.1 is now available for automatic download and install via Microsoft Update globally. In order to enable agile deployment of StreamInsight solutions, you have asked of us a steady cadence of releases with incremental, but highly impactful features and product improvements. Following our StreamInsight 1.0 launch in Spring 2010, we offered StreamInsight 1.1 in Fall 2010 with implicit compatibility and an upgraded setup to support side by side installs. With this setup, your applications will automatically point to the latest runtime, but you still have the choice to point your application back to a 1.0 runtime if you choose to do so. As the next step, in order to enable timely delivery of our releases to you, we are pleased to announce the support for automatic download and install of StreamInsight 1.1 release via Microsoft Update starting this week. If you have a computer: that is subscribed to Microsoft Update (different from Windows Update) has StreamInsight 1.0 installed, and does not yet have StreamInsight 1.1 installed, Microsoft Update will automatically download and install the corresponding StreamInsight 1.1 update side by side with your existing StreamInsight 1.0 installation – across all supported 32-bit and 64-bit Windows operating systems, across 11 supported languages, and across StreamInsight client and server SKUs. This is also supported in WSUS environments, if all your updates are managed from a corporate server (please talk to the WSUS administrator in your enterprise). As an example, if you have SI Client 1.0 DEU and SI Server 1.0 ENU installed on the same computer, Microsoft Update will selectively download and side-by-side install just the SI Client 1.1 DEU and SI Server 1.1 ENU releases. Going forward, Microsoft Update will be our preferred mode of delivery – in addition to support for our download sites, and media based distribution where appropriate. Regards, The StreamInsight Team

  Read the article

• StreamInsight V2.0 Released!

  - by Roman Schindlauer

  The StreamInsight Team is proud to announce the release of StreamInsight V2.0! This is the version that ships with SQL 2012, and as such it has been available through Connect to SQL CTP customers already since December. As part of the SQL 2012 launch activities, we are now making V2.0 available to everyone, following our tradition of providing a separate download page. StreamInsight V2.0 includes a number of stability and performance fixes over its predecessor V1.2. Moreover it introduces a dependency on the .NET Framework 4.0, as well as on SQL 2012 license keys. For these reasons, we decided to bump the major version number, even though V2.0 does not add new features or API surface. It can be regarded a stepping stone to the upcoming release 2.1 which will contain significantly new APIs (that will depend on .NET 4.0). Head over here to download StreamInsight V2.0. The updated Books Online can be found here. Update: For instructions on how to make your existing application work against the new bits without recompilation, see here. Regards, The StreamInsight Team

  Read the article

• What is the difference between the "Entire Partition" and "Entire Disc"?

  - by Roman

  I want to install Ubuntu alongside my Windows 7 operation system. During installation I have three options: Install alongside the existing OS. Remove everything and install Ubuntu. Manual partitioning (advanced). The above list is not precise (I do not remember what exactly was written there and I just write options as I have understood them). I know that option 2 is not mine. So, I need to choose either 1 or 3. I do not know which one I need to choose. I want to have a possibility to manually specify space assigned to Windows and Ubuntu (for example 40% for Windows and 60% for Ubuntu). I chose the 1st option and I saw a window with the following information. Allocate drive space by dragging the drive bellow. File (48.1 GB) Ubuntu /dev/sda2 (ntfs) /dev/sda3 (ext4) 286.6 GB 241.7 GB 2 small partitions are hidden, use the advanced partitioning tool for more control. [use entire partition] [use entire disk] [Quit] [Back] [Install Now] My problem is that I do not understand what I see. In particular I can press [use entire partition] or [use entire disk] and I do not know what is the difference. Moreover, as far as I understand, I can even press [Install Now] without pressing one of the two above mentioned buttons. So, I have 3 options. What is the difference between them? The most important thing for me is not to delete the old operation system with all the data stored there.

  Read the article

• Windows Azure HPC Scheduler Architecture

  - by Churianov Roman

  So far I've found very little information on the scheduling policy, resource management policy of Azure HPC Scheduler. I would appreciate any kind of information regarding some of these questions: What scheduling policy does a Head Node use to scatter jobs to Compute Nodes? Does Azure Scheduler use prior information about the jobs (compute time, memory demands ...) ? If 'yes', how it gets this information? Does Azure Scheduler split a job into several parallel jobs on one Compute node? Does it have any protection from Compute Node failures? (what it does when a compute node stops responding) Does it support addition/subtraction of Compute nodes? Is it possible to cancel a job? P.S. I'm aware of the MSDN resource Windows Azure HPC Scheduler. I found only information of how to use this Scheduler but almost nothing about how it works inside.

  Read the article

• StreamInsight will not push feature releases through Microsoft Update going forward

  - by Roman Schindlauer

  Until now, we've released StreamInsight through the Microsoft Download Center, and also released it out through Microsoft Update. Going forward, we will only release new StreamInsight versions through the Microsoft Download Center and only use MU to release service packs and security fixes (should any be needed). As a result of this decision, we are pulling off the recent StreamInsight 2.1 release from MU; this release is still available in Download Center. Don’t worry: there’s nothing wrong with the versions we’ve shipped in MU, we’ve just adjusted how we use MU. There is no action necessary from our customers as a result of this change, and we are not rolling back any changes to your current installation, so if you have installed StreamInsight 2.1 recently through the Microsoft Update, they will still work fine. Regards, The StreamInsight Team

  Read the article

• StreamInsight 2.1 Released

  - by Roman Schindlauer

  The wait is over—we are pleased to announce the release of StreamInsight 2.1. Since the release of version 1.2, we have heard your feedbacks and suggestions and based on that we have come up with a whole new set of features. Here are some of the highlights: A New Programming Model – A more clear and consistent object model, eliminating the need for complex input and output adapters (though they are still completely supported). This new model allows you to provision, name, and manage data sources and sinks in the StreamInsight server. Tight integration with Reactive Framework (Rx) – You can write reactive queries hosted inside StreamInsight as well as compose temporal queries on reactive objects. High Availability – Check-pointing over temporal streams and multiple processes with shared computation. Here is how simple coding can be with the 2.1 Programming Model: class Program {     static void Main(string[] args)     {         using (Server server = Server.Create("Default"))         {             // Create an app             Application app = server.CreateApplication("app");             // Define a simple observable which generates an integer every second             var source = app.DefineObservable(() =>                 Observable.Interval(TimeSpan.FromSeconds(1)));             // Define a sink.             var sink = app.DefineObserver(() =>                 Observer.Create<long>(x => Console.WriteLine(x)));             // Define a query to filter the events             var query = from e in source                         where e % 2 == 0                         select e;             // Bind the query to the sink and create a runnable process             using (IDisposable proc = query.Bind(sink).Run("MyProcess"))             {                 Console.WriteLine("Press a key to dispose the process...");                 Console.ReadKey();             }         }     } }   That’s how easily you can define a source, sink and compose a query and run it. Note that we did not replace the existing APIs, they co-exist with the new surface. Stay tuned, you will see a series of articles coming out over the next few weeks about the new features and how to use them. Come and grab it from our download center page and let us know what you think! You can find the updated MSDN documentation here, and we would appreciate if you could provide feedback to the docs as well—best via email to [email protected]. Moreover, we updated our samples to demonstrate the new programming surface. Regards, The StreamInsight Team

  Read the article

• StreamInsight 2.1 Released

  - by Roman Schindlauer

  The wait is over—we are pleased to announce the release of StreamInsight 2.1. Since the release of version 1.2, we have heard your feedbacks and suggestions and based on that we have come up with a whole new set of features. Here are some of the highlights: A New Programming Model – A more clear and consistent object model, eliminating the need for complex input and output adapters (though they are still completely supported). This new model allows you to provision, name, and manage data sources and sinks in the StreamInsight server. Tight integration with Reactive Framework (Rx) – You can write reactive queries hosted inside StreamInsight as well as compose temporal queries on reactive objects. High Availability – Check-pointing over temporal streams and multiple processes with shared computation. Here is how simple coding can be with the 2.1 Programming Model: class Program {     static void Main(string[] args)     {         using (Server server = Server.Create("Default"))         {             // Create an app             Application app = server.CreateApplication("app");             // Define a simple observable which generates an integer every second             var source = app.DefineObservable(() =>                 Observable.Interval(TimeSpan.FromSeconds(1)));             // Define a sink.             var sink = app.DefineObserver(() =>                 Observer.Create<long>(x => Console.WriteLine(x)));             // Define a query to filter the events             var query = from e in source                         where e % 2 == 0                         select e;             // Bind the query to the sink and create a runnable process             using (IDisposable proc = query.Bind(sink).Run("MyProcess"))             {                 Console.WriteLine("Press a key to dispose the process...");                 Console.ReadKey();             }         }     } }   That’s how easily you can define a source, sink and compose a query and run it. Note that we did not replace the existing APIs, they co-exist with the new surface. Stay tuned, you will see a series of articles coming out over the next few weeks about the new features and how to use them. Come and grab it from our download center page and let us know what you think! You can find the updated MSDN documentation here, and we would appreciate if you could provide feedback to the docs as well—best via email to [email protected]. Moreover, we updated our samples to demonstrate the new programming surface. Regards, The StreamInsight Team

  Read the article

• StreamInsight V2.0 Released!

  - by Roman Schindlauer

  The StreamInsight Team is proud to announce the release of StreamInsight V2.0! This is the version that ships with SQL 2012, and as such it has been available through Connect to SQL CTP customers already since December. As part of the SQL 2012 launch activities, we are now making V2.0 available to everyone, following our tradition of providing a separate download page. StreamInsight V2.0 includes a number of stability and performance fixes over its predecessor V1.2. Moreover it introduces a dependency on the .NET Framework 4.0, as well as on SQL 2012 license keys. For these reasons, we decided to bump the major version number, even though V2.0 does not add new features or API surface. It can be regarded a stepping stone to the upcoming release 2.1 which will contain significantly new APIs (that will depend on .NET 4.0). Head over here to download StreamInsight V2.0. The updated Books Online can be found here. Update: For instructions on how to make your existing application work against the new bits without recompilation, see here. Regards, The StreamInsight Team

  Read the article

• Using Subjects to Deploy Queries Dynamically

  - by Roman Schindlauer

  In the previous blog posting, we showed how to construct and deploy query fragments to a StreamInsight server, and how to re-use them later. In today’s posting we’ll integrate this pattern into a method of dynamically composing a new query with an existing one. The construct that enables this scenario in StreamInsight V2.1 is a Subject. A Subject lets me create a junction element in an existing query that I can tap into while the query is running. To set this up as an end-to-end example, let’s first define a stream simulator as our data source: var generator = myApp.DefineObservable(     (TimeSpan t) => Observable.Interval(t).Select(_ => new SourcePayload())); This ‘generator’ produces a new instance of SourcePayload with a period of t (system time) as an IObservable. SourcePayload happens to have a property of type double as its payload data. Let’s also define a sink for our example—an IObserver of double values that writes to the console: var console = myApp.DefineObserver(     (string label) => Observer.Create<double>(e => Console.WriteLine("{0}: {1}", label, e)))     .Deploy("ConsoleSink"); The observer takes a string as parameter which is used as a label on the console, so that we can distinguish the output of different sink instances. Note that we also deploy this observer, so that we can retrieve it later from the server from a different process. Remember how we defined the aggregation as an IQStreamable function in the previous article? We will use that as well: var avg = myApp     .DefineStreamable((IQStreamable<SourcePayload> s, TimeSpan w) =>         from win in s.TumblingWindow(w)         select win.Avg(e => e.Value))     .Deploy("AverageQuery"); Then we define the Subject, which acts as an observable sequence as well as an observer. Thus, we can feed a single source into the Subject and have multiple consumers—that can come and go at runtime—on the other side: var subject = myApp.CreateSubject("Subject", () => new Subject<SourcePayload>()); Subject are always deployed automatically. Their name is used to retrieve them from a (potentially) different process (see below). Note that the Subject as we defined it here doesn’t know anything about temporal streams. It is merely a sequence of SourcePayloads, without any notion of StreamInsight point events or CTIs. So in order to compose a temporal query on top of the Subject, we need to 'promote' the sequence of SourcePayloads into an IQStreamable of point events, including CTIs: var stream = subject.ToPointStreamable(     e => PointEvent.CreateInsert<SourcePayload>(e.Timestamp, e),     AdvanceTimeSettings.StrictlyIncreasingStartTime); In a later posting we will show how to use Subjects that have more awareness of time and can be used as a junction between QStreamables instead of IQbservables. Having turned the Subject into a temporal stream, we can now define the aggregate on this stream. We will use the IQStreamable entity avg that we defined above: var longAverages = avg(stream, TimeSpan.FromSeconds(5)); In order to run the query, we need to bind it to a sink, and bind the subject to the source: var standardQuery = longAverages     .Bind(console("5sec average"))     .With(generator(TimeSpan.FromMilliseconds(300)).Bind(subject)); Lastly, we start the process: standardQuery.Run("StandardProcess"); Now we have a simple query running end-to-end, producing results. What follows next is the crucial part of tapping into the Subject and adding another query that runs in parallel, using the same query definition (the “AverageQuery”) but with a different window length. We are assuming that we connected to the same StreamInsight server from a different process or even client, and thus have to retrieve the previously deployed entities through their names: // simulate the addition of a 'fast' query from a separate server connection, // by retrieving the aggregation query fragment // (instead of simply using the 'avg' object) var averageQuery = myApp     .GetStreamable<IQStreamable<SourcePayload>, TimeSpan, double>("AverageQuery"); // retrieve the input sequence as a subject var inputSequence = myApp     .GetSubject<SourcePayload, SourcePayload>("Subject"); // retrieve the registered sink var sink = myApp.GetObserver<string, double>("ConsoleSink"); // turn the sequence into a temporal stream var stream2 = inputSequence.ToPointStreamable(     e => PointEvent.CreateInsert<SourcePayload>(e.Timestamp, e),     AdvanceTimeSettings.StrictlyIncreasingStartTime); // apply the query, now with a different window length var shortAverages = averageQuery(stream2, TimeSpan.FromSeconds(1)); // bind new sink to query and run it var fastQuery = shortAverages     .Bind(sink("1sec average"))     .Run("FastProcess"); The attached solution demonstrates the sample end-to-end. Regards, The StreamInsight Team

  Read the article

• Problem adding a ppa

  - by Roman Rdgz

  I want to install gcc compiler 4.7 to use c++11 features. I have looked on the internet for instructions, and I found in several websites these steps: sudo add-apt-repository ppa:Ubuntu-toolchain-r/test sudo apt-get update sudo apt-get install gcc-4.7 g++-4.7 The problem is that my console freezes when adding the ppa. At first I thought it was due to having an old Ubuntu version (11.04). So I have upgraded to 11.10 and then 12.04, and everything seems to work OK. But still having the same problem. Any help?

  Read the article

• How do you refer to the user using the application vs. the user being edited? [closed]

  - by Roman Royter

  Suppose you are developing an administration page where the administrator can edit other users. In your code you want to distinguish between the user sitting in front of the screen, and the user being edited. What do you call the two? User, CurrentUser, EditedUser, CurrentEditUser, etc? Note that the admin user isn't necessarily real admin, they can be just an ordinary user given rights to edit other users.

  Read the article

• ??????????????? ?????? ? ?????????? ??????? IPS ? Solaris 11

  - by Roman Ivanov

  ? ???? ?? ???????? ????? Solaris 11 ? ?? ??? ? ????????? ????? ? ???? ??? ???? ????? ????????? ??? ?????????? ???????? Oracle VM Server for SPARC (aka LDoms). ???? ?? Python/GTK/NetBeans. ?? ?? ??? ???????. ??????? ? ???, ??? ??? ???????????? ????? ? ??????? ????? pylibssh2 ??? ????, ????? ???????????? ?? python ?? ssh ? ????????? ??????.???????? ?? ????? ???????? pylibssh2 ? libssh2, ??????? ? ?????????. ?? ? ???????, ????? ??? ?????? ???? ????????? ? ???? ??????? Solaris IPS. ?????? ? ????? ? ????????? ???????? ??????.????? ?????????, ? ?? ??????? ?????????? ?? ???????????? ? ?????????. ? ???? ????, ??? ????? ????????? configure ? make ??? ??????? ? README ;)???????????? ??????? ????? ???????? ??? ?? ???????????? LD_LIBRARY_PATH. ??? ????? ?? ? ???? ?????? ?? ??????????? ?? ? /etc/profile.? ?? ???? ????? ???????? ????????? ?????? ???. ?? ???????? ????? ?????????? ? ???? ? ?? ?????? ? ????? ?????. ??????????, ???? ???????????? ? ? ????????.????, ??? 0. ????????? ??????????? ? ???? ????? ??????? ??????????. ??? ????? ???????????, ????? ??????? ? ? ???? ???????, ????? ????? ???? ???????? ?????? ?????? ????????. # zfs create rpool/export/repo # zfs set atime=off rpool/export/repo # chown roivanov:staff /export/repo $ pkgrepo create /export/repo $ pkgrepo set -s /export/repo publisher/prefix=tools # pkg set-publisher -g /export/repo tools??? 1, ???????? ?????. ??? ?????? ??????? ? ????????? ? $HOME/Projects/IPS/<??? ??????>, ?? ??? ?? ?????????????. ????? ????, ??? ?????? ??????? ?????? ? ???????? ????????? ????????, ????? ?? ???????????? ????????? ?????????. ??? ?????? ??? ?????????? SunStudio cc ??? gcc. $ export PKGREPO=/export/repo $ mkdir -p $HOME/Projects/IPS/libssh2 $ cd $HOME/Projects/IPS/libssh2 $ export PKGROOT=`pwd` $ unset LDFLAGS $ PATH=$PATH:/opt/solarisstudio12.3/bin $ export CC=cc??? $ export CC=gcc?? ????? ?????? ?????? ?????????? ?????????? (??????????????) ????? ? ../root ?????? /usr $ export DESTDIR=$PKGROOT/root? ????????? ?????????? ../root ? ???? ?????????? ????????? ?????. ????????????? ??????????? ????? ? /usr. $ [ -d root ] && rm -rf root $ cp ~/??????????/libssh2-1.4.2.tar.gz . $ tar xzf libssh2-1.4.2.tar.gz $ cd libssh2-1.4.2? ??????, ???? ????? ?????????? ?????????? ?? /usr/local/lib, ????????????? LDFLAGS ? _????????_ ??? LD_LIBRARY_PATH $ export LDFLAGS="-L/usr/local/lib -R/usr/local/lib" $ ./configure $ gmake && gmake install $ cd ..?????? ?????? Python (pylibssh2) ???????????? ????????? ????? $ python setup.py install --root=../root??? 2. ??????? ???? ? ????????? ?????? $ cat > MANIFEST.files.mog << EOF set name=pkg.fmri value=library/[email protected],0.5.11-11 set name=pkg.description \     value="libssh2 is a client-side C library implementing the SSH2 protocol" set name=pkg.summary value="libssh2 library" set name=maintainer value="First Last <[email protected]>" set name=info.upstream-url value=http://www.libssh2.org/ set name=variant.arch value=$(ARCH) license ../libssh2-1.4.2/COPYING license=BSD <transform dir path=usr$ -> edit group bin sys> EOF ???: library/libssh2 ??? ???????? ??????, 1.4.2 ?????? ??????, 0.5.11 ?????, 11 ????? ?????? ??????. description ??? ????????, ? summary ??? ???????? ???????? ??????. variant.arch ??? ????? ????????? ?????? ?????. ???? ??????????? ? ????? ?????? ????? ????? ??? ?????????? ????????, ?? ??? ? ?????? ???? ?? ????. license ???? ? ??? ???????? transform ????????? ??? ????, ????? ? ????????????? ????? ?????? ???? ????????? ?????????? ?????? ????????? ?????????? /usr ???????? ?????? ?????? ?????? $ pkgsend generate root > MANIFEST.files.1 ????????? ?????????? ?? ????? ???????? ? ?????????? ??????????? ????????? $ pkgmogrify -DARCH=`uname -p` MANIFEST.files.1 MANIFEST.files.mog > MANIFEST.files.2 ??????? ?????? ???? ???????????? $ pkgdepend generate -md root MANIFEST.files.2 | pkgfmt > MANIFEST.files.3 ????????? ?????? ???????? ???????????? ? ?????? ???????. ???? ???? ?????? ????????? ?????. $ pkgdepend resolve -m MANIFEST.files.3 ?? ?????? ???????? ??????? ???? MANIFEST.files.3.res ? ????????? ??????.??? ??????? ????? ????????? ???? ???? ?? ??????? ?????????? ? ?????????? ?????????????,?????? ??? ????? ????? ???????????? ???????????. $ pkglint -c ../lint-cache -r http://pkg.oracle.com/solaris/release/ MANIFEST.files.3.res $ pkglint -c ../lint-cache-local -r /export/repo MANIFEST.files.3.res ? ??????????, ????????? ????? $ pkgsend publish -s $PKGREPO -d `pwd`/root MANIFEST.files.3.res ????????? ?????? ? ?????????? ????????????????? ?????????? ????? ?????? ???? ??????????? $ pkgrepo list -s /export/repo/ ????? ??????? ?????????? ????? ?? ??????????? $ pkgrepo remove -s /export/repo/ [email protected],0.5.11-8:* ????? ?????????? ?????????? ? ?????? ? ??????????? $ pkg info -r libssh2 ????? ?????????? ??? ?????? ?????????, ??? ???????? ????????? ?????? $ sudo pkg install -nv libssh2 ????? ?????????? ????? $ sudo pkg install libssh2 ????? ???????? ????? $ sudo pkg refresh $ sudo pkg update ?????? ??????:[1] How to Create and Publish Packages to an IPS Repository on Oracle Solaris 11,http://www.oracle.com/technetwork/articles/servers-storage-admin/o11-097-create-pkg-ips-524496.html[2] Publishing your own packages with IPS - getting started.https://blogs.oracle.com/barts/entry/publishing_your_own_packages_with[3] How to create your own IPS packages (Ghost Busting)http://blogs.oracle.com/cwb/entry/how_to_create_your_own[4] Introduction to IPS for Developershttp://www.oracle.com/technetwork/systems/hands-on-labs/introduction-to-ips-1534596.html

  Read the article

• Where are the default Adobe Illustrator fonts found when installed?

  - by EdenMachine

  I need a copy of the Myriad-Roman font that is the default font for Adobe Illustrator. I have Illustrator installed but I need to put the font on my sever so my PDF DLL can read the font since my PDF is using that Myriad-Roman font. Please don't get distracted about the PDF part - I just need to know how to find the font wherever Adobe installs it when I install Illustrator (CS5). TIA!

  Read the article

• How to get vm arguments from inside of java application?

  - by Dmitriy Matveev

  Hello, I need to check if some option which can be passed to JVM is explicitly set or is it have default value. To be more specific: I need to create one specific thread with higher native stack size than the default one, but in case then user want to take care of such things by himself by specifying -Xss option I want to create all threads with default stack size (which will be specified by user in -Xss option). I've checked classes like java.lang.System and java.lang.Runtime, but these aren't giving me information about vmargs. Is there any way to get information I need?

  Read the article

• Execute code on assembly load

  - by Dmitriy Matveev

  I'm working on wrapper for some huge unmanaged library. Almost every of it's functions can call some error handler deeply inside. The default error handler writes error to console and calls abort() function. This behavior is undesirable for managed library, so I want to replace the default error handler with my own which will just throw some exception and let program continue normal execution after handling of this exception. The error handler must be changed before any of the wrapped functions will be called. The wrapper library is written in managed c++ with static linkage to wrapped library, so nothing like "a type with hundreds of dll imports" is present. I also can't find a single type which is used by everything inside wrapper library. So I can't solve that problem by defining static constructor in one single type which will execute code I need. I currently see two ways of solving that problem: Define some static method like Library.Initialize() which must be called one time by client before his code will use any part of the wrapper library. Find the most minimal subset of types which is used by every top-level function (I think the size of this subset will be something like 25-50 types) and add static constructors calling Library.Initialize (which will be internal in that scenario) to every of these types. I've read this and this questions, but they didn't helped me. Is there any proper ways of solving that problem? Maybe some nice hacks available?

  Read the article

• Which articles I've should read before starting to make my custom drawn winforms app?

  - by Dmitriy Matveev

  Hello! I'm currently developing a windows forms application with a lot of user controls. Some of them are just custom drawn buttons or panels and some of them are a compositions of these buttons and panels inside of FlowLayoutPanels and TableLayoutPanels. And the window itself is also custom drawn. I don't have much experience in winforms development, but I've made a proper decomposition of proposed design into user controls and implementation is already almost finished. I've already solved many arisen problems during development by the help of the google, msdn, SO and several dirty hacks (when nothing were helping) and still experiencing some of them. There are a lot of gaps in my knowledge base, since I don't know answers to many questions like: When I should use things like double buffer, suspended layout, suspended redraw ? What should I do with the controls which shouldn't be visible at some moment ? Common performance pitfalls (I think I've fallen in in several ones) ? So I think there should be some great articles which can give some knowledge enough to avoid most common problems and improve performance and maintainability of my application. Maybe some of you can recommend a few?

  Read the article

< Previous Page | 2 3 4 5 6 7 8 9 10 11 12 13  | Next Page >