title: Dask worse performance than Pandas
body: <p>I am running the same functionality using Pandas API and Dask API. 
  I expected Dask API to be faster, but it is not.  </p>
  
  <p><strong>Functionality</strong>  </p>
  
  <p>I cross joint 2 dataframes (pandas and dask respectively) by a 'grouping' column and then, on every single pair I compute the Levensthein distance between 2 strings.<br>
  The results is the expected, but I am concerned about the performance.  </p>
  
  <p><strong>Pandas</strong>  </p>
  
  <pre><code>@timeit
  def pd_fuzzy_comparison(df1:DF, df2:DF, group_col:str, compare):
  
      df = df1.merge(df2, on=bubble_col, suffixes=('_internal', '_external'))
  
      df['score'] = df.apply(lambda d: 
              comp(d.company_norm_internal, d.company_norm_external), axis=1)
      return df
  </code></pre>
  
  <p><strong>Dask</strong></p>
  
  <pre><code>@timeit
  def dd_fuzzy_comparison(dd1:dd, dd2:dd, group_col:str, compare):
  
      ddf = dd1.merge(dd2, on='city_norm', suffixes=('_internal', '_external'))   
      ddf['score'] = ddf.apply(
              lambda d: ratio(d.company_norm_internal, d.company_norm_external), axis=1)
  
      return ddf.compute()
  </code></pre>
  
  <p><strong>Main</strong></p>
  
  <pre><code>import multiprocessing
  CORES = multiprocessing.cpu_count()
  
  results = pd_fuzzy_comparison(
                  df1=internal_bubbles.copy(), 
                  df2=external_bubbles.copy(), 
                  bubble_col='city_norm',
                  compare=ratio ) 
  
  ddata1 = dd.from_pandas(internal_bubbles.copy(), npartitions=CORES)
  ddata2 = dd.from_pandas(external_bubbles.copy(), npartitions=CORES)
  
  ddresults = dd_fuzzy_comparison(
                  dd1=ddata1.copy(), dd2=ddata2.copy(), 
                  bubble_col='city-norm',                 
                  compare=ratio)
  </code></pre>
  
  <p><strong>Output</strong></p>
  
  <pre><code>'pd_fuzzy_comparison'  1122.39 ms
  'dd_fuzzy_comparison'  1717.83 ms
  </code></pre>
  
  <p>What am I missing?<br>
  Thanks!</p>