(Copied from Apache Spark issue 26693 as it appears to be a Zeppelin issue rather than Spark)
We have a process that takes a file dumped from an external API and formats it for use in other processes. These API dumps are brought into Spark with all fields read in as strings. One of the fields is a 19 digit visitor ID. Since implementing Spark 2.4 a few weeks ago, we have noticed that dataframes read the 19 digits correctly but any function in SQL appears to truncate the last two digits and replace them with "00".
Our process is set up to convert these numbers to bigint, which worked before Spark 2.4. We looked into data types, and the possibility of changing to a "long" type with no luck. At that point we tried bringing in the string value as is, with the same result. I've added code that should replicate the issue with a few 19 digit test cases and demonstrating the type conversions I tried.