anchor.diff:  Kudu integrates with Spark through the Data Source API as of version 1.0.0.
   Include the kudu-spark dependency using the --packages option:
   
  -Use the kudu-spark_2.10 artifact if using Spark with Scala 2.10
  +Use the kudu-spark_2.10 artifact if using Spark with Scala 2.10. Note that Spark 1 is no
  +longer supported in Kudu starting from version 1.6.0. So in order to use Spark 1 integrated
  +with Kudu, version 1.5.0 is the latest to go to.
   [source]
   ----
  -spark-shell --packages org.apache.kudu:kudu-spark_2.10:1.1.0
  -----
  -
  -Use kudu-spark2_2.11 artifact if using Spark 2 with Scala 2.11
  +spark-shell --packages org.apache.kudu:kudu-spark_2.10:1.5.0
  +----
  +
  +Use kudu-spark2_2.11 artifact if using Spark 2 with Scala 2.11. Spark 2 artifacts are available
  +up to version 1.7.0.
   [source]
   ----
  -spark-shell --packages org.apache.kudu:kudu-spark2_2.11:1.1.0
  +spark-shell --packages org.apache.kudu:kudu-spark2_2.11:1.7.0
   ----
   
   then import kudu-spark and create a dataframe:
  
positive.code:   `Date` and complex types are not supported.
  - Kudu tables may only be registered as temporary tables in SparkSQL.
    Kudu tables may not be queried using HiveContext.
  - When importing or exporting Avro via the tools in `kudu-spark-tools`
    the `spark-avro` dependency jars are expected to be on the classpath.
    You can read more about `spark-avro` link:https://github.com/databricks/spark-avro[here].
  
  == Kudu Python Client
  The Kudu Python client provides a Python friendly interface to the C++ client API.
  
negative.code: for examples which you can model your own integrations on. Stay tuned for more examples
  using YARN and Spark in the future.
  
  