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HttpError: Validation Failed: {"resource":"Release","code":"invalid","field":"target_commitish"} at /home/runner/work/_actions/release-drafter/release-drafter/v5/dist/index.js:8462:21 at processTicksAndRejections (node:internal/process/task_queues:96:5) at async Job.doExecute (/home/runner/work/_actions/release-drafter/release-drafter/v5/dist/index.js:30793:18) { name: 'AggregateError', event: { id: '8149820308', name: 'pull_request', payload: { action: 'edited', changes: { body: { from: '# Summary\r\n' + '\r\n' + 'Support field_id renaming of Parquet files along the codepath:\r\n' + '\r\n' + '1. `IcebergScanOperator`\r\n' + '2. Generates `ScanTasks`, each containing the `field_id_mapping: Arc<{i32: Field}>`\r\n' + '3. Propagated to workers through the `ScanWithTask` instruction object\r\n' + '4. Micropartitions are created with `MicroPartition::from_scan_task`\r\n' + '5. This then calls into `read_parquet_into_micropartition`\r\n' + ' a. If statistics are available, it will create an unloaded MicroPartition by creating a new ScanTask (hydrated with statistics) and then calling `MicroPartition::new_unloaded(new_scan_task)`. \r\n' + ' b. Otherwise, it falls back into `read_parquet_bulk`, which has been modified to correctly handle `field_id_mapping`\r\n' + '\r\n' + 'This PR ensures that when data/statistics are read from Parquet files, we correctly apply renaming according to `field_id_mapping`.\r\n' + '\r\n' + '## Notes\r\n' + '\r\n' + 'A lot of the errors caught/triggered by this PR has to do with mismatches between the fields (names/metadata) on our schemas and on our Series objects.\r\n' + '\r\n' + 'Keeping those two in sync is fairly challenging with the way our code is currently structured.\r\n' + '\r\n' + 'The approach taken to try and fix this is:\r\n' + '\r\n' + '1. Try to use the same logic for renaming across Series and Schemas\r\n' + '2. When reading data from `Parquet -> arrow2 -> Daft Series/Schema`, perform a post-processing step to remove any field metadata that was retrieved from the Parquet files.\r\n' + '\r\n' + 'However I do think that this is a fairly error-prone situation. Not sure what the best approach is though.\r\n' + '\r\n' + '## Drive-By\r\n' + '\r\n' + 'Refactors to clean-up MicroPartitions/ScanTasks and schemas:\r\n' + '\r\n' + "1. Refactored `MicroPartition::new_unloaded`: it no longer accepts a `schema` argument; instead internally it will just use the ScanTask's `.materialized_schema()`\r\n" + '4. Refactored `read_parquet_into_micropartition` to significantly reduce code deduplication\r\n' + '\r\n' + '## Remaining todos:\r\n' + '\r\n' + '- [x] Fix logic with column pruning (need to apply column pruning after applying the field ID mappings)\r\n' + '- [x] Perform correct renaming for statistics parsing from Parquet metadata\r\n' + '- [x] Perform recursive renaming for Series and for Schema' } }, number: 1937, organization: { avatar_url: 'https://avatars.githubusercontent.com/u/98941975?v=4', description: 'Eventual Computing', events_url: 'https://api.github.com/orgs/Eventual-Inc/events', hooks_url: 'https://api.github.com/orgs/Eventual-Inc/hooks', id: 98941975, issues_url: 'https://api.github.com/orgs/Eventual-Inc/issues', login: 'Eventual-Inc', members_url: 'https://api.github.com/orgs/Eventual-Inc/members{/member}', node_id: 'O_kgDOBeW8Fw', public_members_url: 'https://api.github.com/orgs/Eventual-Inc/public_members{/member}', repos_url: 'https://api.githu