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PORead multiple HDF5 files in Python using multiprocessing
 

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  1. PORead multiple HDF5 files in Python using multiprocessing
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    <p>I'm trying to read a bunch of HDF5 files ("a bunch" meaning N > 1000 files) using <code>PyTables</code> and <code>multiprocessing</code>. Basically, I create a class to read and store my data in RAM; it works perfectly fine in a sequential mode and I'd like to parallelize it to gain some performance.</p> <p>I tried a dummy approach for now, creating a new method <code>flatten()</code> to my class to parallelize file reading. The following example is a simplified example of what I'm trying to do. <code>listf</code> is a list of strings containing the name of the files to read, <code>nx</code> and <code>ny</code> are the size of the array I want to read in the file:</p> <pre><code>import numpy as np import multiprocessing as mp import tables class data: def __init__(self, listf, nx, ny, nproc=0): self.listinc = [] for i in range(len(listf)): self.listinc.append((listf[i], nx, ny)) def __del__(self): del self.listinc def get_dsets(self, tuple_inc): listf, nx, ny = tuple_inc x = np.zeros((nx, ny)) f = tables.openFile(listf) x = np.transpose(f.root.x[:ny,:nx]) f.close() return(x) def flatten(self): nproc = mp.cpu_count()*2 def worker(tasks, results): for i, x in iter(tasks.get, 'STOP'): print i, x results.put(i, self.get_dsets(x)) tasks = mp.Queue() results = mp.Queue() manager = mp.Manager() lx = manager.list() for i, out in enumerate(self.listinc): tasks.put((i, out)) for i in range(nproc): mp.Process(target=worker, args=(tasks, results)).start() for i in range(len(self.listinc)): j, res = results.get() lx.append(res) for i in range(nproc): tasks.put('STOP') </code></pre> <p>I tried different things (including, like I did in this simple example, the use of a <code>manager</code> to retrieve the data) but I always get a <code>TypeError: an integer is required</code>.</p> <p>I do not use ctypes array because I don't really require to have shared arrays (I just want to retrieve my data) and after retrieving the data, I want to play with it with NumPy.</p> <p>Any thought, hint or help would be highly appreciated!</p> <p><strong>Edit:</strong> The complete error I get is the following:</p> <pre><code>Process Process-341: Traceback (most recent call last): File "/usr/lib/python2.7/multiprocessing/process.py", line 258, in _bootstrap self.run() File "/usr/lib/python2.7/multiprocessing/process.py", line 114, in run self._target(*self._args, **self._kwargs) File "/home/toto/test/rd_para.py", line 81, in worker results.put(i, self.get_dsets(x)) File "/usr/lib/python2.7/multiprocessing/queues.py", line 101, in put if not self._sem.acquire(block, timeout): TypeError: an integer is required </code></pre>
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    1. COYou might try simplifying a bit. In particular, your entire "flatten" function could be replaced by a call to multiprocessing's map with "worker" as the function. If you still get errors, a stack trace might be useful.
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    2. COPerhaps overly simple, but have you tried printing the type of `i` in your `print i, x` line (unfortunately, you don't show us the output of the print statement)?
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    3. COAlso, reading up on the `iter` documentation, I can see another problem: `iter` stops if `tasks.get()` return value is equal to the sentinel (`'STOP'`), but your for loop shows that you expect `tasks.get()` to return 2 values (`i, x`), not a single string. So unless I misunderstand, `'STOP'` will never equal anything from `tasks.get()`, causing `iter` to proceed endlessly (and probably causing bad things in the end).
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