When you run a mapping in the native environment to write data to a complex file target and choose to overwrite the target data and the target filename does not contain the file format extension such as

.avro

or

.parquet

, the Data Integration Service does not delete the target data before writing data.

When you run a mapping on the Spark engine to read data from an empty JSON complex file source and write data to a complex file target, the mapping should fail, but the mapping runs successfully and the Data Integration Service generates an empty target file.

You cannot use multiple level partitioning when you run a mapping to write data to a complex file target with Filename port enabled.

When you run a mapping in the native environment to write data to a complex file using filename port and mapping flow is enabled, the Data Integration Service generates an incorrect folder structure and writes data to a single file.

When you run a mapping to read from a complex file source and write to a complex file target and the source object contains unsupported data types in the schema, the mapping fails.

When you import a complex file data object in JSON format, the import fails with the following error:

When you run a mapping on the Spark engine to read data from a complex file and the source path has a wildcard character, then the log file does not display the source file names.

When you create a complex file data object from a JSON file and rename the filed names to an invalid field name, then the task fails with the following error:

When you run a mapping to read data from a complex file source in JSON format and enable compression, the mapping runs successfully but the Data Integration Service fails to read data from the source.