title: Filter the dataframe of having multiple ID<PKs> columns by passing the values of each IDs in a list
body: <p><strong>Trying to filter the dataframe of having multiple ID columns by passing the values of each IDs in a list.</strong></p>
  <p>For eg: Df:</p>
  <pre><code>location_user
  transactiontime (string)
  user_id (bigint)
  location_id (bigint)
  Address1 (string)
  Address2 (string)
  user_name (string)
  loc_name (string)
  </code></pre>
  <p>In the above Dataframe: user_id and location_id both are ID columns.</p>
  <p><strong>GOAL:  filter user_id=[42939,42940] and location_id=[1468,1469] against the Dataframe.</strong></p>
  <p>Created the separate list as below and applied them on df.filter.</p>
  <pre><code>partition_key =['user_id', 'location_id']
  filter_cond = ['[42939,42940]', '[1468,1469]']
  </code></pre>
  <p>---&gt; working for single partition_key</p>
  <pre><code>filter_df=actual_df.filter(~col(partition_key).isin(filter_cond))
  </code></pre>
  <p>Tried to the below for combination of partition_key but it's not working and having the below error.</p>
  <pre><code>filter_df=actual_df.filter(~col(partition_key).isInCollection(filter_cond))
  </code></pre>
  <blockquote>
  <p>Error: Error occured during overwriting the directory. Please check if
  correct parameters is passed. Exception:  An error occurred while
  calling z:org.apache.spark.sql.functions.col. Trace:
  py4j.Py4JException: Method col([class java.util.ArrayList]) does not
  exist</p>
  </blockquote>
  <p>Appreciate any suggestions.</p>