sql - find set of row, duplicate list, before insert -


itemprop = "text">

I have a table (this is a list of structures with 4 integers, first ID list id) < Pre> ID | IDL | IDA (empty). IDB (empty) | IDC1 | 1 | 2 | Empty | 1 2 | 1 | 4 | Empty | 1 3 | 1 | Empty | 1 | 1 4 | 2 | 2 | Empty | 1 5 | 2 | 4 | Empty | 1 6 | 3 | 6 | Empty | 1 7 | 3 | Empty | 4 | 1

Now I need to put 4th list in this table 

  idA | IDB | IDC2 | Empty | 1 4 | Empty | 1 tap 1 | 1   
 But, it already exists (list id = 1)  
  idA | IDB | IDC2 | Empty | 1 4 | Empty | 1   
 Other exists (idl = 2)  
  idA | IDB | IDC2 | Empty | 1 4 | Empty | 1 tap 7 | 1   
 does not exist.  
 How to get a duplicate before entering the table   
 
 
 Is the case (choose not in)  
 Try this example:  
 Disclaimer: In the example data that you provided lines 2 and 4, got a similar IDA, IDB, IDC set. If that column can not form a unique form and you have already got the taple in the copy table and you need a line per table per table per row, which makes Ill very difficult because in copy There is no way to tell the line for such a row in the original it is related.

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