Known Issues in Apache Iceberg

Technical Service Bulletins

TSB 2024-752: Dangling delete issue in Spark rewrite_data_files procedure causes incorrect results for Iceberg V2 tables

The Spark Iceberg library includes two procedures - rewrite_data_files and rewrite_position_delete_files. The current implementation of rewrite_data_files has a limitation that the position delete files are not deleted and still tracked by the table metadata, even if they no longer refer to an active data file. This is called the dangling delete problem. To solve this, the rewrite_position_delete_files procedure is implemented in the Spark Iceberg library to remove these old “dangling” position delete files.

Due to the dangling delete limitation, when an Iceberg table with dangling deletes is queried in Impala, Impala tries to optimize select count(*) from iceberg_table query to return the results using stats. This optimization returns incorrect results.

The following conditions must be met for this issue to occur:

• All delete files in the Iceberg table are “dangling”
  • This would occur immediately after running Spark rewrite_data_files AND
    • Before any further delete operations are performed on the table OR
    • Before Spark rewrite_position_delete_files is run on the table
• Only stats optimized plain select count(*) from iceberg_table queries are affected. For example, the query should not have:
  • Any WHERE clause
  • Any GROUP BY clause
  • Any HAVING clause

Remove dangling deletes: After rewrite_data_files, position delete records pointing to the rewritten data files are not always marked for removal, and can remain tracked by the live snapshot metadata of the table. This is known as the dangling delete problem.

Knowledge article

For the latest update on this issue see the corresponding Knowledge article: TSB 2024-752: Dangling delete issue in Spark rewrite_data_files procedure causes incorrect results for Iceberg V2 tables.