title: extraction of data from oracle into python pandas dataframe very slow
body: <p>I'm trying to use the cx_Oracle module to extract data from an Oracle database and into a Pandas dataframe.</p>
  
  <p>When using the fetchall() function as below</p>
  
  <pre><code>cursor = con.cursor()
  cursor.arraysize = 1000
  results = cursor.execute("select * from TABLE1")
  rows = results.fetchall()
  </code></pre>
  
  <p>the extraction speed is very similar to extraction using the R Oracle library which is about 8 seconds (data size is about 750,000 rows and 30 columns of mixed data types)</p>
  
  <p>But when importing this into a dataframe using the Pandas read_sql function, the performance is far worse</p>
  
  <pre><code>df = pd.read_sql('select * from TABLE1',con)
  </code></pre>
  
  <p>When using this function, it takes almost 30 seconds.  </p>
  
  <p>Is there something I can do to optimize the import into a dataframe?</p>