title: Performance: list all keys from hdf5 file with pandas
body: <p>Is it normal that that it takes so long to obtain all present keys in a hdf5 file?</p>
  
  <p>Code Sample:</p>
  
  <pre><code>start = time.time()
  store = pd.HDFStore(filepath)
  print(time.time() - start)
  0.0
  
  start = time.time()
  a = store.keys()
  print(time.time() - start)
  23.874846696853638
  
  len(a) 
  80
  
  start = time.time()
  store.select(key="/data/table1") # the next table would be /data/table2
  print(time.time() - start)
  
  0.062399864196777344
  </code></pre>
  
  <p>All keys are 'tables' (i.e. not fixed). 
  There are about 80 keys present in the file.</p>
  
  <p>The entire size of the  <code>.h5</code> file is 348 MB. Each table has approx. the same size (after loading to a pandas.DataFrame) of 2.6 MB. </p>
  
  <p>pandas v.0.20.1</p>
  
  <p>tables v.3.2.2.</p>
  
  <p>I am wondering if the key hierarchy is an issue: all in <code>data/table[X]</code> instead of directly into <code>table[X]</code>? </p>