Troubleshooting AWS Clean Rooms - AWS Clean Rooms
One or more tables referenced by the query is not accessible by its associated service role. The table/role owner must grant the service role access to the table.One of the underlying datasets has an unsupported file format.Query results are not as expected when using Cryptographic Computing for Clean Rooms.AWS Clean Rooms Spark SQL: Missing partition data

Troubleshooting AWS Clean Rooms

This section describes some common issues that might arise when using AWS Clean Rooms and how to fix them.

One or more tables referenced by the query is not accessible by its associated service role. The table/role owner must grant the service role access to the table.

  • Verify that the permissions for the service role are set up as required. For more information, see Setting up AWS Clean Rooms. ​ ​

One of the underlying datasets has an unsupported file format.

  • Ensure that your dataset is in one of the supported file formats:

    • Parquet

    • RCFile

    • TextFile

    • SequenceFile

    • RegexSerde

    • OpenCSV

    • AVRO

    • JSON

    For more information, see Data formats for AWS Clean Rooms.

Query results are not as expected when using Cryptographic Computing for Clean Rooms.

If you are using Cryptographic Computing for Clean Rooms (C3R), verify that your query uses encrypted columns correctly:

  • The sealed columns are only used in SELECT clauses.

  • The fingerprint columns are only used in JOIN clauses (and GROUP BY clauses under certain conditions).

  • That you are only JOINing fingerprint columns with the same name if the collaboration settings require it.

For more information, see Cryptographic Computing for Clean Rooms and Column types in Cryptographic Computing for Clean Rooms.

AWS Clean Rooms Spark SQL: Missing partition data

If you are using the AWS Clean Rooms Spark SQL engine with partitioned tables S3 tables, all partitions in the AWS Glue Data Catalog must also have data in S3. The engine uses the Spark setting spark.sql.files.ignoreMissingFiles=False

For more information, see https://spark.apache.org/docs/latest/sql-data-sources-generic-options.html#ignore-missing-files .

If you encounter this error you will get the following error message: "Missing partition data: One of the configured tables is partitioned and one or more of the partitions does not have data".

Compare your data present in Amazon S3 with the partitions listed in the AWS Glue Data Catalog for the table. Delete partitions that don't have corresponding data in S3.