I have just started learning hadoop and i have a question on how the splitting works.
For example, i have a file like below with key value-
2 1121291290r5405454
1 2192949495959454454
2 121334883484585
So my question is , when the splitting will be done will that based on the block size or the record type. if its based on block size it might be possible that while splitting the key-value data might be separated and put in different blocks which will give the incorrect data.
Taking my file as an example - if the file is splitting into 2 blocks -
block 1 -------
2 1121291290r5405454
1 21929494959594
block 2--------
54454
2 121334883484585
So, here the key value relationship is gone and resulting in incorrect data. As far as i know the split happens when the input file size exceeds the block size. So how do we handle this situation?
By default ,number of input spilit depends upon the number of blocks. In your case , if there are two block for a single file , then two mappers will run . while writing the data into blocks , hadoop uses a kind of pointer which indicates the location of next block, so by using this pointer, first mapper identifies the exact key value pair and process accordingly and 2nd mapper will start computation by leaving that data which will be processed by 1st mapper. Simply a map task is not limited to that block only, it can also process the data from other blocks.
Related
I've been working on an RFID project to produce our own RFID cards to work on our existing timeclocks and readers.
I've got most of the work done, and have been able to successfully write a Hitag2 card using the value of page 4 & 5 from another card (so basically copying the card) then changing the config bit which makes it act like an EM4x02 which allows our readers to read it.
What I'm struggling with is trying to relate the hex code on page4/5 to the output you get when scanning as an EM4x..
The values of the hitag page 4/5 are FF800000/003EDF10. This translates to 0000001EBC when read as an EM4x.
Does anybody have an idea on how this translation is done? I've tried using the methods in RFIDIOT but that doesn't seem to work for this.
I've managed to find how this is done after finding a hitag2 datasheet from 1999 (the only one I could find that explains the bits when hitag is in public mode A)
Firstly, convert the number you want on the EM4 card to hex.
Convert that hex into binary.
Split the binary into 4 bit chunks, then work out the even parity for each section and add it to the end of each chunk. (So you'll end up with 5 bits per chunk)
Then, work out the even parity of each column in the data (i.e first character of all chunks, then second etc. But ignoring the parity bit you added) and add these 4 bytes to the binary string.
Then add the correct amount of zeros at the start to ensure the data section has 50 bits.
Once you have the data section sorted, add 9 bits of 1 to the beginning (header) and a final 0 to the very end of the binary.
Your whole binary string should be 64 bits long.
Convert this to hex and split it in half. You can then write these onto pages 4/5 of a Hitag2 card.
You then need to change the configuration bit to 0x02 for the tag to work in public mode a.
Just thought I would send you the diagram of how this works.Em4X tag data
I'm trying to read variable length 1-D inputs into a Tensorflow CNN.
I have previously implemented reading fixed length inputs by first constructing a CSV file (where the first column is the label and the remaining columns are the input values - flattened spectrogram data all padded/truncated to the same length) using tf.TextLineReader().
This time I have a directory full of files each one containing a line of data I want to use as input (flattened spectrogram data again but I do not want to force them to the same dimensions), and the line lengths are not fixed. I'm getting an error trying to use the previous approach of compiling a CSV first. I looked into the documentation of tf.TextLineReader() and it specifies that all CSV rows must be the same shape, so I am stuck! Any help would be much appreciated, thanks :)
I'm assuming that the data isn't changing shape when you have a longer or shorter sample right? By that I mean that if you trained your network on arrays of 1000 pixels for example, with a kernel of say [5,1] size. That [5,1] kernel needs to see the same patterns in the variable length data as it did in the training data. If your data is stretched or shrunk, then the correct solution is to interpolate the data to the same size as the training data so the shapes/patterns match.
Assuming you just want variable length inputs, then in theory you should be able to do this by setting your batch size to 1 and varying the 1st dimension of the data.
So your input placeholder would look like:
X = tf.placeholder(dtype, shape=[1,None,1,1])
The 4 shape arguments are: 1=batch size; None=unknown first dimension size; 1=unused because it's a 1D dataset, 1=one channel images, again unused but necessary for tf.conv2d to receive the expected 4D image.
This is not very different from configuring tensorflow to support variable batch sizes. So you should review this link below and understand that process.
get the size of a variable batch dimension
Note that you can't use a batch size more than 1 here because you wouldn't be able to construct a matrix with missing values in the 2nd dimension. I expect the convolution operations to work with this variable dimension (though I haven't actually tried this).
Another option to deal with this problem would be to pad your inputs with 0's so they all have a common length, but that will need to have been trained into the model up front.
The question
What are the ways of coercing octave to create a real copy of whatever object? Structures are the main interest.
My underlying problem
In my problem I'm obtaining a rather large structure from another function in a loop but for the current task only a few pieces of it are needed. For example:
for i=1:many
res=solver(params);
store1{i}=res.string1;
store2{i}=res.arr(:,1);
end
res is a sizable chunk of data and due to lazy-copy those store-s are references to tiny portions of bytes in that chunk. After I store those tiny portions, I don't need res itself, however, since middle of that chunk is referenced by store, the memory area is unfit for res obtained on the next iteration (they are of the same size) and thus another sizable piece of memory is allocated, which is then again crossed by few tiny links an so on.
Without storing parts of res, the program successfully keeps the memory consumption same after first couple of iterations.
So how do I make a complete copy of structure field?
I've tried using struct-related functions like rmfield but those keep references instead of their own objects.
I've tried to wrap the assignment of in its own function:
new_struct=copy( rmfield(old_struct,"bigdata"));
function c=copy(a);
c=a;
end;
This by the way doesn't work even for arrays.
I'm interested in method applicable to any generic variable.
Minimal working example of the problem
a=cell(3,1);
for i=1:length(a);
r=rand(100000,1000);
a{i}=r(1:100,end);
whos; fflush(stdout);
pause(2);
end;
The above code will cause memory usage to gradually grow by far more than 8.08 kb reported by whos due to references stored by a{i} blocking bigger memory block than they actually need. If you force the proper copy, the problem is not present.
Numerical arrays
For numeric types addition of zero is enough to warrant a new array.
c=a+0;
Strings
For string which is 1 x n char array, something along the following lines will work:
c=[a "a"](1:end-1);
Multidimensional char arrays will require concatenation with a column:
c=[a true(size(a,1),1)](:,1:end-1);
Here true is used to generate dummy array of size compatible with char. (There seems to be no procedural method of generating char array of arbitrary size) char(zeros(size(a,1),1)) and char(true(size(a,1),1)) caused excess memory usage during their creation on some calls.
Note that empty concatenation c=[a ""]; will not result in a copying. Also it is possible to do c=[a+0 ""]; which will result in a copying due to +0 but that one infers type conversions to and from double which is 8 times larger in size. (char(zeros( doesn't seem to cause that)
Other types
In general you can use casting for the types allowed by it in order to not tailor the expressions manually as I had to do above:
typelist={"double","single","char"}; %full list of supported types is available in the link
class_of_a = typelist{ isa(a,typelist) };
c=typecast( [typecast(a,'single'); single(1)] (1:end-1), class_of_a);
Single is seemingly smallest datatype available in octave.
Note that logical is not supported by this method.
Copying structures
Apparently you'd have to write your own function to go around struct fields, copy them with above methods and recursively go to substructs.
(As it doesn't involve complexities relevant here, I'd rather leave that to be done by those who actually needs that, my own problem being solved by +0's.)
I have been trying to convert my level-1 S-function to level-2 but I got stuck at calling another subfunction at function Output(block) trying to look for other threads but to no avail, do you mind to provide related links?
My output depends on a lot processing with the inputs, this is the reason I need to call the sub-function in order to calculate and then return output values, all the examples that I can see are calculating their outputs directly in "function Output(block)", in my case I thought it is not possible.
I then tried to use Interpreted Matlab Function block but failed due to the output dimension is NOT the same as input dimension, also it does not support the return of more than ONE output................
Dear Sir/Madam,
I read in S-function documentation that "S-function level-1 supports vector inputs and outputs. DOES NOT support multiple input and output ports".
Does the second sentence mean the input and output dimension MUST BE SAME?
I have been using S-function level-1 to do the following:
[a1, b1] = choose_cells(c, d);
where a1 and b1 are outputs, c and d are inputs. All the variables are having a single value, except d is an array with 6 values.
Referring to the image attached, we all know that in S-function block, the input dimension must be SAME as output dimension, else we will get error, in this case, the input dimension is 7 while the output dimension is 2, so I have to include the "Terminator" blocks in the diagram for it to work perfectly, otherwise, I will get an error.
My problem is, when the system gets bigger, the array d could contain hundreds of variables, using this method, it means I would have to add hundreds of "Terminator" blocks in order to get this work, this definitely does not sound practical.
Could you please suggest me a wise way to implement this?
Thanks in advance.
http://imgur.com/ib6BTTp
http://imageshack.us/content_round.php?page=done&id=4tHclZ2klaGtl66S36zY2KfO5co
I want to generate unique code numbers (composed of 7 digits exactly). The code number is generated randomly and saved in MySQL table.
I have another requirement. All generated codes should differ in at least two digits. This is useful to prevent errors while typing the user code. Hopefully, it will prevent referring to another user code while doing some operations as it is more unlikely to miss two digits and match another existing user code.
The generate algorithm works simply like:
Retrieve all previous codes if any from MySQL table.
Generate one code at a time.
Subtract the generated code with all previous codes.
Check the number of non-zero digits in the subtraction result.
If it is > 1, accept the generated code and add it to previous codes.
Otherwise, jump to 2.
Repeat steps from 2 to 6 for the number of requested codes.
Save the generated codes in the DB table.
The algorithm works fine, but the problem is related to performance. It takes a very long to finish generating the codes when requesting to generate a large number of codes like: 10,000.
The question: Is there any way to improve the performance of this algorithm?
I am using perl + MySQL on Ubuntu server if that matters.
Have you considered a variant of the Luhn algorithm? Luhn is used to generate a check digit for strings of numbers in lots of applications, including credit card account numbers. It's part of the ISO-7812-1 standard for generating identifiers. It will catch any number that is entered with one incorrect digit, which implies any two valid numbers differ in a least two digits.
Check out Algorithm::LUHN in CPAN for a perl implementation.
Don't retrieve the existing codes, just generate a potential new code and see if there are any conflicting ones in the database:
SELECT code FROM table WHERE abs(code-?) regexp '^[1-9]?0*$';
(where the placeholder is the newly generated code).
Ah, I missed the generating lots of codes at once part. Do it like this (completely untested):
my #codes = existing_codes();
my $frontwards_index = {};
my $backwards_index = {};
for my $code (#codes) {
index_code($code, $frontwards_index);
index_code(reverse($code), $backwards_index);
}
my #new_codes = map generate_code($frontwards_index, $backwards_index), 1..10000;
sub index_code {
my ($code, $index) = #_;
push #{ $index{ substr($code, 0, length($code)/2) } }, $code;
return;
}
sub check_index {
my ($code, $index) = #_;
my $found = grep { ($_ ^ $code) =~ y/\0//c <= 1 } #{ $index{ substr($code, 0, length($code)/2 } };
return $found;
}
sub generate_code {
my ($frontwards_index, $backwards_index) = #_;
my $new_code;
do {
$new_code = sprintf("%07d", rand(10000000));
} while check_index($new_code, $frontwards_index)
|| check_index(reverse($new_code), $backwards_index);
index_code($new_code, $frontwards_index);
index_code(reverse($new_code), $backwards_index);
return $new_code;
}
Put the numbers 0 through 9,999,999 in an augmented binary search tree. The augmentation is to keep track of the number of sub-nodes to the left and to the right. So for example when your algorithm begins, the top node should have value 5,000,000, and it should know that it has 5,000,000 nodes to the left, and 4,999,999 nodes to the right. Now create a hashtable. For each value you've used already, remove its node from the augmented binary search tree and add the value to the hashtable. Make sure to maintain the augmentation.
To get a single value, follow these steps.
Use the top node to determine how many nodes are left in the tree. Let's say you have n nodes left. Pick a random number between 0 and n. Using the augmentation, you can find the nth node in your tree in log(n) time.
Once you've found that node, compute all the values that would make the value at that node invalid. Let's say your node has value 1,111,111. If you already have 2,111,111 or 3,111,111 or... then you can't use 1,111,111. Since there are 8 other options per digit and 7 digits, you only need to check 56 possible values. Check to see if any of those values are in your hashtable. If you haven't used any of those values yet, you can use your random node. If you have used any of them, then you can't.
Remove your node from the augmented tree. Make sure that you maintain the augmented information.
If you can't use that value, return to step 1.
If you can use that value, you have a new random code. Add it to the hashtable.
Now, checking to see if a value is available takes O(1) time instead of O(n) time. Also, finding another available random value to check takes O(log n) time instead of... ah... I'm not sure how to analyze your algorithm.
Long story short, if you start from scratch and use this algorithm, you will generate a complete list of valid codes in O(n log n). Since n is 10,000,000, it will take a few seconds or something.
Did I do the math right there everybody? Let me know if that doesn't check out or if I need to clarify anything.
Use a hash.
After generating a successful code (not conflicting with any existing code), but that code in the hash table, and also put the 63 other codes that differ by exactly one digit into the hash.
To see if a randomly generated code will conflict with an existing code, just check if that code exists in the hash.
Howabout:
Generate a 6 digit code by autoincrementing the previous one.
Generate a 1 digit code by incrementing the previous one mod 10.
Concatenate the two.
Presto, guaranteed to differ in two digits. :D
(Yes, being slightly facetious. I'm assuming that 'random' or at least quasi-random is necessary. In which case, generate a 6 digit random key, repeat until its not a duplicate (i.e. make the column unique, repeat until the insert doesn't fail the constraint), then generate a check digit, as someone already said.)