Issue 2000 - Upgrade EMR to 7.2.0

[patchwork01]

Make sure you have checked all steps below.

Issue

• My PR addresses the following issues and references them in the PR title. For example, "Issue 1234 - My Sleeper
  PR"
  • Resolves Upgrade to EMR 7 #2000

Tests

• My PR adds the following tests OR does not need testing for this extremely good reason:
  • Covered by existing tests
  • Ran quick system test suite in AWS

Documentation

• In case of new functionality, my PR adds documentation that describes how to use it, or I have linked to a
  separate issue for that below.

[patchwork01]

Bulk import on non-persistent EMR is failing on this branch currently. It passes on EMR Serverless, but on a non-persistent EMR on EC2 cluster we get this exception:

ERROR TaskResultGetter: Exception while getting task result
java.io.EOFException: null
  at org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:331) ~[spark-core_2.12-3.5.1-amzn-0.jar:3.5.1-amzn-0]
  at org.apache.spark.serializer.SerializerHelper$.deserializeFromChunkedBuffer(SerializerHelper.scala:52) ~[spark-core_2.12-3.5.1-amzn-0.jar:3.5.1-amzn-0]
  at org.apache.spark.scheduler.DirectTaskResult.value(TaskResult.scala:108) ~[spark-core_2.12-3.5.1-amzn-0.jar:3.5.1-amzn-0]
  at org.apache.spark.scheduler.TaskResultGetter$$anon$3.$anonfun$run$1(TaskResultGetter.scala:84) ~[spark-core_2.12-3.5.1-amzn-0.jar:3.5.1-amzn-0]
  at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23) [scala-library-2.12.17.jar:?]
  at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1971) [spark-core_2.12-3.5.1-amzn-0.jar:3.5.1-amzn-0]
  at org.apache.spark.scheduler.TaskResultGetter$$anon$3.run(TaskResultGetter.scala:72) [spark-core_2.12-3.5.1-amzn-0.jar:3.5.1-amzn-0]
  at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1136) [?:?]
  at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:635) [?:?]
  at java.lang.Thread.run(Thread.java:840) [?:?]

Looking at the source code of KryoDeserializationStream, it looks like Spark is swallowing the real exception from Kryo without logging it.