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WebJobs QueueTrigger not working?

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Originally posted on: http://geekswithblogs.net/cskardon/archive/2015/01/29/webjobs-queuetrigger-not-working.aspxI’ve just spent quite some time trying to figure this out, you read many good things about WebJobs, and as luck would have it, you’re in the market for some nifty backend processing whenever something is added to a queue, so now seems a good time to take a proper look. So, right click on my web app, and select ‘Add, New Web Jobs’ and create a new WebJob project. Then start adding my code: class Program { static void Main() {
var host = new JobHost(); host.RunAndBlock(); } public static void ProcessQueueMessage([QueueTrigger("myqueue") string msg, TextWriter log) { log.WriteLine("Got msg {0}!", msg); } } This is the file that opens up and is initially visible. So far so looking good. Run and it says: Yay. So I add a message to queue. Nothing. The message stays there the webjob stays quiet. The clue is in the console: Functions??? Turns out there is another class called ‘Functions’...(Read whole news on source site)

Building and deploying large-scale machine learning pipelines - O'Reilly Radar

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Building and deploying large-scale machine learning pipelines - O'Reilly Radar



There are many algorithms with implementations that scale to large
data sets (this list includes matrix factorization, SVM, logistic
regression, LASSO, and many others). In fact, machine learning experts
are fond of pointing out: if you can pose your problem as a simple
optimization problem then you’re almost done.




Of course, in practice, most machine learning projects can’t be
reduced to simple optimization problems. Data scientists have to manage and maintain complex data projects

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A recent example would be ml-matrix — a distributed matrix library that runs on top of Apache Spark.



Workflow tools have become more common, and these days, such tools exist for data engineers, data scientists, and even business analysts (Alteryx, RapidMiner, Alpine Data, Dataiku).
As I noted in a recent post, we’ll see more data analysis tools that combine an elegant interface with a simple DSL that non-programmers can edit.



(A related AMPLab project Velox provides a framework for managing models...(Read whole news on source site)

Windows 10 – Going Backwards

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Originally posted on: http://geekswithblogs.net/tmurphy/archive/2015/01/29/windows-10-ndash-going-backwards.aspx I’m not sure how, but I seem to be an outlier in this point of view.  I am finding that almost everything they are doing to Windows 10 to make it more acceptable to the masses is taking away features that I preferred in Windows 8.  It isn’t that I thought everything was great and didn’t need to be improved, but these are features that I found at the very least useful and in most cases efficient.  I’m just going to hit on the big ones here. Let’s start with the
left swipe gesture.  In Windows 8 this gave us the ability to rotate through open applications.  In most cases what you are looking for is the first previous application used.  This meant that a single swipe would bring you back to that application.  Now you have an old Windows 7 Alt+Tab screen that pops up and sticks there.  You then have to pick which screen you wanted. Another feature that I liked with the modern apps was mutually adjusting snapped apps.  If you had two apps snapped side-by-side and adjusted the border in between them both changed size.  Since...(Read whole news on source site)

Voron on Linux

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So, this just happened: Note that this is a very important step, but it is just a first step. We have a few Linux experts review the code, and we haven’t even started yet with working on RavenDB itself. But I’m pretty happy right now.

Excerpts from the RavenDB Performance team report: Optimizing Memory Comparisons, size does matter

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Note, this post was written by Federico. In the previous post after inspecting the decompiled source using ILSpy  we were able to uncover potential things we could do. In this fragment we have a pretty optimized method to compare an entire 4 bytes per loop. What if we could do that on 8 bytes? To achieve that we will use a ulong instead of a uint. This type of optimization makes sense for 2 reasons. Most of our users are already running RavenDB in x64 where the native word is 8 bytes and Voron is compiled
on x64 only. But even if that were not true, since the late 2000’ most CPUs would have a 64 bytes L1 cache line with half a cycle cost for a hit. So even if you can’t handle 64 bits in one go and the JIT or processor have to issue 2 instructions you are still getting a L1 cache hit and no pipeline stall. Which is GREAT . So without farther ado, this is the resulting code: Ayende’s note: In the code, the lp += (IntPtr)8/8; is actually defined as lp += 1; What...(Read whole news on source site)

The Morning Brew #1788

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Information .NET Core Open Source Update – Immo Landwerth shares an interesting update on the .NET Core moving to open source, discussing the successes so far, and looking at some of the metrics they use to monitor progress Microsoft Orleans now available on GitHub – Lee Stott highlights the availability of Project Orleans as an […]

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