title: Dask: very low CPU usage and multiple threads? is this expected?
body: <p>I am using <code>dask</code> as in <a href="https://stackoverflow.com/questions/37979167/how-to-parallelize-many-fuzzy-string-comparisons-using-apply-in-pandas">how to parallelize many (fuzzy) string comparisons using apply in Pandas?</a></p>
  
  <p>Basically I do some computations (without writing anything to disk) that invoke <code>Pandas</code> and <code>Fuzzywuzzy</code> (that may not be releasing the GIL apparently, if that helps) and I run something like:</p>
  
  <pre><code>dmaster = dd.from_pandas(master, npartitions=4)
  dmaster = dmaster.assign(my_value=dmaster.original.apply(lambda x: helper(x, slave), name='my_value'))
  dmaster.compute(get=dask.multiprocessing.get)
  </code></pre>
  
  <p>However, a variant of the code has been running for 10 hours now, and is not over yet. I notice in windows task manager that</p>
  
  <ul>
  <li><code>RAM utilization</code> is pretty low, corresponding to the size of my data</li>
  <li><code>CPU usage</code> bounces from 0% to up to 5% every 2/3 seconds or so</li>
  <li>I have about <code>20 Python processes</code> whose size is 100MB, and one Python process that likely contains the data that is 30GB in size (I have a <strong>128 GB machine with a 8 core CPU</strong>)</li>
  </ul>
  
  <p><strong>Question is:</strong> is that behavior expected? Am I obviously terribly wrong in setting some <code>dask</code> options here? </p>
  
  <p><em>Of course, I understand the specifics depends on what exactly I am doing</em>, but maybe the <strong>patterns above</strong> can already tell that something is horribly wrong?</p>
  
  <p>Many thanks!!</p>