title: Load data into BigQuery and partition data based on time as well as split by another variable
body: <p><em>(I'm very new to databases so please let me know how I can make this question better.)</em>  </p>
  
  <p>I am trying to load multiple files of columnar data into BigQuery from an AWS S3 bucket  </p>
  
  <ul>
  <li>It is web analytics data of over 150 different websites  </li>
  <li>There are multiple files, each containing 15 minutes of web analytics data  </li>
  <li>Each file contains data for all 150 websites for a 15 minute slot, however there is a column called <code>site_code</code> which tells us which site the row pertains to  </li>
  </ul>
  
  <p>Here is a snapshot of relevant columns:  </p>
  
  <pre><code>timestamp_info_nginx_ms site_code action
            1.539168e+12    site_1  event1
            1.539168e+12    site_2  event2
            1.539168e+12    site_3  event1
            1.539168e+12    site_1  event1
            1.539168e+12    site_2  event2
  </code></pre>
  
  <p>The size of data is 200+GB per week and I want to be able to load 12 weeks' data.  </p>
  
  <p><strong>My goal is to minimise monthly query costs.</strong>  </p>
  
  <p><strong>Some context:</strong> My main use case is that I will analyse data for one website (or a group of websites) at a time. Of the 150 sites, I will focus mainly on 10-15 websites. Let's call them <em>primary websites</em>. I expect to analyse primary websites on a regular basis (daily) and the rest of the websites occasionally (1-3 times month) or rarely (1-3 times in 2 months).  </p>
  
  <p>I have understood that I need to partition my data tables by day. Which looks relatively simple to do via BigQuery GUI.  </p>
  
  <p>However, my question is that is it possible to load this data into separate tables for my primary websites (one table for each primary website) and separate for the rest of them? </p>