title: Parallelizing pandas pyodbc SQL database calls
body: <p>I am currently querying data into dataframe via the <code>pandas.io.sql.read_sql()</code> command. I wanted to parallelize the calls similar to what this guys is advocating: (<a href="https://www.youtube.com/watch?v=g0eNQSzIbpQ" rel="nofollow">Embarrassingly parallel database calls with Python (PyData Paris 2015 )</a>)</p>
  
  <p>Something like (very general):</p>
  
  <pre><code>pools = [ThreadedConnectionPool(1,20,dsn=d) for d in dsns]
  connections = [pool.getconn() for pool in pools]
  parallel_connection = ParallelConnection(connections)
  pandas_cursor = parallel_connection.cursor()
  pandas_cursor.execute(my_query)
  </code></pre>
  
  <p>Is something like that possible?</p>