The Java code in the transformation cannot write output to standard output when you push transformation logic to Hadoop. The Java code can write output to standard error which appears in the log files.

For date/time values, the Spark engine supports the precision of up to microseconds. If a date/time value contains nanoseconds, the trailing digits are truncated.

The Partitionable property must be enabled in the Java transformation. The transformation cannot run in one partition.

The following restrictions apply to the Transformation Scope property:

The value Transaction for transformation scope is not valid.
If you enable an input port for partition key, the transformation scope must be set to All Input.
Stateless must be enabled if the transformation scope is row.

You reference an unconnected Lookup transformation from an expression within a Java transformation.

You select a port of a complex data type as the partition or sort key.

You enable nanosecond processing in date/time and the Java transformation contains a port of complex data type with an element of a date/time type. For example, a port of type

array<data/time>

is not valid if you enable nanosecond processing in date/time.

When you enable high precision, a validation error occurs in the following situations:

The Java transformation contains a port of a decimal data type.
The Java transformation contains a complex data type with an element of a decimal data type.