title: Failed to import large data as dataframe, from Google BigQuery to Google Cloud DataLab
body: <p>I tried 2 approaches to import a large table in Google BigQuery, about 50,000,000 rows, 18GB, into dataframe to Google Datalab, in order to do the machine learning using Tensorflow.</p>
  
  <p>Firstly I use (all modules needed are imported) :</p>
  
  <pre><code>data = bq.Query('SELECT {ABOUT_30_COLUMNS...} FROM `TABLE_NAME`').execute().result().to_dataframe()
  </code></pre>
  
  <p>Then it keeps <code>Running...</code> until forever.
  Even though I do <code>LIMIT 1000000</code>, it doesn't change.</p>
  
  <p>Secondly I use:</p>
  
  <pre><code>data = pd.read_gbq(query='SELECT {ABOUT_30_COLUMNS...} FROM `TABLE_NAME` LIMIT 1000000', dialect ='standard', project_id='PROJECT_ID')
  </code></pre>
  
  <p>It runs well at first, but when it goes to about 450,000 rows (calculate using percentage and total row count), it gets stuck at:</p>
  
  <p><code>Got page: 32; 45.0% done. Elapsed 293.1 s.</code></p>
  
  <p>And I cannot find how to enable allowLargeResults in read_gbq().
  As its <a href="https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_gbq.html" rel="nofollow noreferrer">document</a> says, I try:</p>
  
  <pre><code>data = pd.read_gbq(query='SELECT {ABOUT_30_COLUMNS...} FROM `TABLE_NAME` LIMIT 1000000', dialect ='standard', project_id='PROJECT_ID', configuration = {'query': {'allowLargeResult': True}})
  </code></pre>
  
  <p>Then I get:</p>
  
  <blockquote>
    <p><code>read_gbq() got an unexpected keyword argument 'configuration'</code></p>
  </blockquote>
  
  <p>That's how I even failed to import 1,000,000 rows to Google Cloud Datalab.
  I actually want to import 50 times the data size.</p>
  
  <p>Any idea about it?</p>
  
  <p>Thanks</p>