chunks

I'm quite new to C# so please bear with me. I'm reading (using FileStream) data (fixed size) to small array, process the data and then read again and so on to the end of file. I thought about using something like this: byte[] data = new byte[30]; int numBytesToRead = (int)fStream.Length; int offset = 0; //reading while (numBytesToRead > 0) { fStream.Read(data, offset, 30); offset += 30; numBytesToRead -= 30; //do something with the data } But I checked documentation and their examples and they stated that return value of the above read method is: "Type: System.Int32 The total number of bytes

I've got a vector of binary numbers. I know the consecutive length of each group of objects; how can I split based on that information (without for loop)? x = c("1","0","1","0","0","0","0","0","1") .length = c(group1 = 2,group2=4, group3=3) x is the binary number vector that I need to split. .length is the information that I am given. .length essentially tells me that the first group has 2 elements and they are the first two elements 1,0 . The second group has 4 elements and contain the 4 numbers that follow the group 1 numbers, 1,0,0,0 , etc. Is there a way of splitting that and returning the

I was wondering how I could determine in my ItemWriter , whether Spring Batch was currently in chunk-processing-mode or in the fallback single-item-processing-mode. In the first place I didn't find the information how this fallback mechanism is implemented anyway. Even if I haven't found the solution to my actual problem yet, I'd like to share my knowledge about the fallback mechanism with you. Feel free to add answers with additional information if I missed anything ;-) The implementation of the skip mechanism can be found in the FaultTolerantChunkProcessor and in the RetryTemplate . Let's

I have a large data set in GBs that I'd have to process before I analyse them. I tried creating a connector, which allows me to loop through the large datasets and extract chunks at a time.This allows me to quarantine data that satisfies some conditions. My problem is that I am not able to create an indicator for the connector that stipulates it is null and to execute close(connector) when the end of the dataset is reached. Moreover, for the first chunk of extracted data, I'd have to skip 17 lines since the file contains header that R is not able to read. A manual attempt that works: filename=

I need to process some data that is a few hundred times bigger than RAM. I would like to read in a large chunk, process it, save the result, free the memory and repeat. Is there a way to make this efficient in python? The general key is that you want to process the file iteratively. If you're just dealing with a text file, this is trivial: for line in f: only reads in one line at a time. (Actually it buffers things up, but the buffers are small enough that you don't have to worry about it.) If you're dealing with some other specific file type, like a numpy binary file, a CSV file, an XML

Hi I would like to change chunk options, mid chunk, without having to create a new chunk.. running the following code I would expect to get two very different size outputs, but for some reason this does not seem to be the case. Also the second plot doesn't plot at all...(it does when you change it to plot(2:1000)...but either way the second output is the same size as the first. both fig.width=7 . What am I doing wrong? Pls note the importance of 'mid chunk' the reason for this is that I would like to change the chunk options several times when running a function to get different outputs of