chunking

问题 I am sending images from my android client to java jersey restful service and I succeded in doing that.But my issue is when I try to send large images say > 1MB its consumes more time so I like to send image in CHUNKS can anyone help me in doing this.How to send( POST ) image stream in CHUNKS to server 回答1: references used : server code & client call server function name /*** SERVER SIDE CODE****/ @POST @Path("/upload/{attachmentName}") @Consumes(MediaType.APPLICATION_OCTET_STREAM) public

问题 I am trying to construct a Conduit that receives as input ByteString s (of around 1kb per chunk in size) and produces as output concatenated ByteString s of 512kb chunks. This seems like it should be simple to do, but I'm having a lot of trouble, most of the strategies I've tried using have only succeeded in dividing the chunks into smaller chunks, I haven't succeeded in concatenating larger chunks. I started out trying isolate , then takeExactlyE and eventually conduitVector , but to no

问题 I try to use Pool from the multiprocessing module to speed up reading in large csv files. For this, I adapted an example (from py2k), but it seems like the csv.dictreader object has no length. Does it mean I can only iterate over it? Is there a way to chunk it still? These questions seemed relevant, but did not really answer my question: Number of lines in csv.DictReader, How to chunk a list in Python 3? My code tried to do this: source = open('/scratch/data.txt','r') def csv2nodes(r):

问题 I'm using Dropzone.js to take files of various types (including images and non-images, like a PDF), and upload them in 1mb chunks to our server. I'm then attempting to concatenate the files with PHP and later upload them to our company's FileMaker database. So far I've been able to get the files to upload in the chunks, as they should. I store them all in a temporary "uploads" folder with the same "codename," with "-INDEX#" appended to the end of each name (INDEX# being the chunk # being

问题 In a bash script I am using a many-producer single-consumer pattern. Producers are background processes writing lines into a fifo (via GNU Parallel). The consumer reads all lines from the fifo, then sorts, filters, and prints the formatted result to stdout. However, it could take a long time until the full result is available. Producers are usually fast on the first few results but then would slow down. Here I am more interested to see chunks of data every few seconds, each sorted and

问题 I'm new to springBatch chunking. I want to understand how reader works here is the scenario : implementing a purging of user accounts Chunk processor : have a reader which reads all the user accounts that matches with purge criteria ,in an order. processor : for each user account based on the some calculation ,it may create a new user account and also changes current record(say mark it as purged) question : how doe the reader work? say i have 5000 user accounts. If my chunk size is 1000 will

问题 I'm implementing a client-server solution based on Twisted for the server side and e.g. and Android phone for the client side. Because the Andoird emulator takes no TCP Packets larger then 1500b (or less?), I need to be able to chunk packets on the server side. Without flushing the socket after each "transport.write", Twisted buffers the outgoing data so the chunking would be useless without somekind of manual or automatic flushing / maxpacketsize function. How do I do this in Twisted? I'm

问题 Given a list of chunk sizes, how would you partition an iterable into variable-length chunks? I'm trying to coax itertools.islice without success yet. for chunk_size in chunk_list: foo(iter, chunk_size) 回答1: You need to make an iter object of your iterable so you can call islice on it with a particular size, and pick up where you left off on the next iteration. This is a perfect use for a generator function: def uneven_chunker(iterable, chunk_list): group_maker = iter(iterable) for chunk_size

问题 There is a large dataset, containing a strings. I just want to open it via read_fwf using widths, like this: widths = [3, 7, ..., 9, 7] tp = pandas.read_fwf(file, widths=widths, header=None) It would help me to mark the data, But the system crashes (works with nrows=20000). Then I decided to do it by chunk (e.g. 20000 rows), like this: cs = 20000 for chunk in pd.read_fwf(file, widths=widths, header=None, chunksize=ch) ...: <some code using chunk> My question is: what should I do in a loop to

问题 I want to chunk an input stream for batch processing. Given an input list or generator, x_in = [1, 2, 3, 4, 5, 6 ...] I want a function that will return chunks of that input. Say, if chunk_size=4 , then, x_chunked = [[1, 2, 3, 4], [5, 6, ...], ...] This is something I do over and over, and was wondering if there is a more standard way than writing it myself. Am I missing something in itertools ? (One could solve the problem with enumerate and groupby , but that feels clunky.) In case anyone