c# - Why is snapshot isolation lavel greater than serializable? -


यहां जो डीकंपलर दिखाता है: 

  सार्वजनिक एन्यूम अलगाव स्तर {अनिर्दिष्ट = -1, कैओस = 16, ReadUncommitted = 256, ReadCommitted = 4096, RepeatableRead = 65536, Serializable = 1048576, स्नैपशॉट = 16777216,}   
 लेकिन  सीरियलाइज़ेबल  ताले डेटा इस प्रकार से अधिक गारंटी प्रदान करता है  स्नैपशॉट  की तुलना में संगतता सही है तो स्नैपशॉट के मूल्य के लिए क्या कारण अधिक है?   
 
 
 अलगाव का स्तर " प्रत्येक आइटम केवल एक अलग प्रकार के अलगाव का प्रतिनिधित्व करता है। इसके लिए कि  का मतलब  आपको दस्तावेज़ को देखना चाहिए। ये वास्तव में 4-बिट स्पेकिंग्स पर बस थोड़ा-सा झंडे हैं I आंतरिक क्रियान्वयन के विवरण के अलावा, किसी विशेष अर्थ का उपयोग मूल्यों के लिए नहीं है।

Comments

Post a Comment

Popular posts from this blog

python - how we can use ajax() in views.py in django? -

I have a little code here. Could you please tell me what this code really does? please. Here in the AJAX call: $ .ajax ({url: "{% url} upload_document '%}", type: "POST", data : {Csrfmiddletoken: document.getElementsByName ('csrfmiddletoken') [0] Price, Title: document.getElementById ('title'). Value, // document: document: document.getElementById ('document'),}, datatype: "Jason", success: function (feedback) {if (feedback == "true") {// success} other {// attachment errors}}}); How AJAX works in the Django and how we can see the AJAX request. Here is the idea of ​​my thoughts def upload_document (requested): Print request. POTT print request FILES if request.is_ajax (): If request.method == 'POST': form = UploadForm (request.POST, request.FILES, user = request.user) if form.is_valid (): Form.save () return HTTPPCS (SimpleJason Dumps ('True'), Mime Type = 'App / Jason') Other:...
Read more

matlab - Using loops to get multiple values into a cell -

I have 31 topics (S1, S2, S3, S4, etc.) 3 images in each topic, opposite 1 IMG, Contrast 2 IMG and Contrast 3 Are IMG I p In a NX1 cell named P, I would like to use a loop to get all the paths of contrasts from all the subjects: data / S1 / contrast1.img / S1 / contrast2.img data / S1 / contrast3.img data / s2 / contrast1.img data / S2 / contrast2.img Data / S2 / contrast3.img ... Data / S31 / contast3.img This is what I've tried: A = {'S1', 'S2', 'S3', ..., 'S31'}; % All topics C = {'contrast1.img', 'contrast2.img', 'contrast3.img'}; For each = P = cell (31 * 3,1) for each topic, the required contrast images: Length = A for Jammu = 1: Length (C) P {j} = spm_select ('FPList', Fullfile (data_path, q {i}) sprint ('% s', cell2mat (c))); % Of each topic is to select three contrast images, it works in my script, it is probably not 100% correct, because I had to simplify this example. End of ...
Read more

python - Sequence Pattern recognition with Pybrain -

Image
I am constantly trying to use recurrent neural networks to classify a series of data. To be more specific, I have a sequence of sensor reading (which is continuous over time), I have to learn an algorithm which can detect the state related to this pattern, given the readings change. Example: Time step_1: 1.4 Time step_2: 1 Time step_3: 0.8 State = New Sequence: Time Phase 1: 0.4 Time Phase 2: 0.3 Time Phase 3: 0.1 State = Sitting I actually have 12 censors, I'm just showing a sequence of numbers for convenience. (Numbers are not real, I'm just trying to fulfill this idea)! I am trying to make my network with PyBrain RNN, however, I can not get a Data Set Container that can detect it, like information I tried to use sequential data But after some testing I came to know that this number is the next element in the sequence of numbers. Here's how I prepare my dataset: self.alldata = SequentialDataSet (ds.num_features, 1) # Now add samples to the dat...
Read more