feat: [iceberg] Native scan by serializing FileScanTasks to iceberg-rust #2528

mbutrovich · 2025-10-06T02:37:21Z

This PR introduces a new approach for integrating Apache Iceberg with Comet using iceberg-rust, enabling fully-native Iceberg table scans without requiring changes to upstream Iceberg Java code.

Rationale for this change

I was inspired by @RussellSpitzer's recent talk and wanted to revisit the abstraction layer at which Comet integrates with Iceberg.

Our current iceberg_compat approach requires code changes in Iceberg Java to integrate with Parquet reader instantiation, creating a tight coupling between Comet and Iceberg. This PR instead works at the FileScanTask layer after Iceberg's planning phase is complete. This enables fully-native Iceberg scans (similar to our native_datafusion scans) without any changes in upstream Iceberg Java code.

All catalog access and planning continues to happen through Spark's Iceberg integration (unchanged), but file reading is delegated to iceberg-rust, which provides better parallelism and integrates naturally with Comet's native execution engine.

What changes are included in this PR?

This implementation follows a similar pattern to CometNativeScanExec for regular Parquet files, but extracts and serializes Iceberg's FileScanTask objects:

Scala/JVM Side:

New CometIcebergNativeScanExec operator that replaces Spark's Iceberg BatchScanExec
Uses reflection to extract FileScanTask objects from Iceberg's planning output
Serializes tasks and catalog properties to protobuf for native execution

Native/Rust Side:

New IcebergScanExec operator that consumes serialized FileScanTask objects
Uses iceberg-rust's FileIO and ArrowReader to read data files
Leverages catalog properties to configure FileIO (credentials, regions, etc.)

How are these changes tested?

New CometIcebergNativeSuite with basic scenarios, but also a number of challenging situations from the Iceberg Java test suite
New CometFuzzIcebergSuite that we can adapt to Iceberg-specific logic
New IcebergReadFromS3Suite to test passing basic S3 credentials
Tested locally with Iceberg 1.5, 1.7, 1.10, CI tests 1.5.2, 1.8.1, and 1.10.0

Benefits over `iceberg_compat`

No upstream changes needed - No references to Comet needed in Iceberg Java anymore
Better parallelism - File reading happens at the same granularity as native_datafusion, not constrained by Iceberg Java's reader design
Simplified runtime - No separate DataFusion runtime; scans run in the same context as other operators
Better testing for iceberg-rust - I’ve already upstreamed several fixes for iceberg-rust’s ArrowReader
Multi-version support - Reflection approach is version agnostic

Current Limitations & Open Questions

We have a tracking issue on iceberg-rust for all of the changes from my branch we need to upstream to main ArrowReader enhancements for Apache DataFusion Comet iceberg-rust#1749
What is the behavior of a migrated Parquet table with INT96 values. I suspect need to pass the requested schema into ArrowReaderOptions to benefit from previous work in Arrow-rs Support different TimeUnits and timezones when reading Timestamps from INT96 arrow-rs#7285
Need to keep iceberg-rust in sync with Comet's DataFusion dependency (I had to bump my fork to DataFusion 50 for this PR, but iceberg-rust has now updated to DF 50)
Deprecation path for existing iceberg_compat code and its Iceberg Java entanglement

Related Work

Slides from the 10/9/25 Iceberg-Rust community call: iceberg-rust.pdf

codecov-commenter · 2025-10-06T02:54:32Z

Codecov Report

❌ Patch coverage is 67.74892% with 298 lines in your changes missing coverage. Please review.
✅ Project coverage is 59.05%. Comparing base (f09f8af) to head (7911e4b).
⚠️ Report is 715 commits behind head on main.

Files with missing lines	Patch %	Lines
.../comet/serde/operator/CometIcebergNativeScan.scala	70.43%	82 Missing and 33 partials ⚠️
...n/scala/org/apache/comet/rules/CometScanRule.scala	44.51%	65 Missing and 21 partials ⚠️
...a/org/apache/comet/iceberg/IcebergReflection.scala	71.98%	62 Missing and 10 partials ⚠️
...e/spark/sql/comet/CometIcebergNativeScanExec.scala	81.05%	2 Missing and 16 partials ⚠️
...n/scala/org/apache/comet/rules/CometExecRule.scala	62.50%	2 Missing and 1 partial ⚠️
...rg/apache/spark/sql/comet/CometBatchScanExec.scala	70.00%	0 Missing and 3 partials ⚠️
...la/org/apache/comet/objectstore/NativeConfig.scala	0.00%	1 Missing ⚠️

Additional details and impacted files

@@             Coverage Diff              @@
##               main    #2528      +/-   ##
============================================
+ Coverage     56.12%   59.05%   +2.92%     
- Complexity      976     1462     +486     
============================================
  Files           119      165      +46     
  Lines         11743    15060    +3317     
  Branches       2251     2504     +253     
============================================
+ Hits           6591     8893    +2302     
- Misses         4012     4899     +887     
- Partials       1140     1268     +128

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comphead · 2025-10-06T15:22:35Z

It is promising!

# Conflicts: # native/Cargo.lock # spark/src/main/scala/org/apache/comet/rules/CometScanRule.scala

…eberg version back to 1.8.1 after hitting known segfaults with old versions.

## Which issue does this PR close? - Part of #1749. ## What changes are included in this PR? - Change `ArrowReaderBuilder::new` to be `pub` instead of `pub(crate)`. ## Are these changes tested? - No new tests for this. Currently being used in DataFusion Comet: apache/datafusion-comet#2528

# Conflicts: # docs/source/user-guide/latest/configs.md # native/Cargo.lock # native/Cargo.toml # native/core/Cargo.toml

andygrove

I don't see any reason not to go ahead and merge this as an experimental feature.

…llel test and setup workflows.

kazuyukitanimura

still looking

.github/workflows/iceberg_spark_test.yml

native/Cargo.toml

native/core/Cargo.toml

spark/pom.xml

spark/src/main/scala/org/apache/comet/rules/CometExecRule.scala

…rkspace.

…<1.6.0

…due to type limitations in Iceberg 1.5.2.

kazuyukitanimura

I know this is merged, but one more comment

kazuyukitanimura · 2025-11-20T19:21:58Z

.github/workflows/iceberg_spark_test.yml

+        iceberg-version: [{short: '1.8', full: '1.8.1'}, {short: '1.9', full: '1.9.1'}, {short: '1.10', full: '1.10.0'}]
+        spark-version: [{short: '3.4', full: '3.4.3'}, {short: '3.5', full: '3.5.7'}]


The profile now says to use Iceberg 1.5 with Spark 3.4, but we do not have 1.5 here. Not sure if it causes problems...

Here's what we currently test with this PR:

3.4 3.5 4.0

1.5.2 CometIcebergNativeSuite CometFuzzIcebergSuite IcebergReadFromS3Suite (not run in CI due to MinIO container)

1.8.1 Iceberg Spark Tests Iceberg Spark Extensions Tests Iceberg Spark Runtime Tests Iceberg Spark Tests Iceberg Spark Extensions Tests Iceberg Spark Runtime Tests CometIcebergNativeSuite CometFuzzIcebergSuite IcebergReadFromS3Suite (not run in CI due to MinIO container)

1.9.1 Iceberg Spark Tests Iceberg Spark Extensions Tests Iceberg Spark Runtime Tests Iceberg Spark Tests Iceberg Spark Extensions Tests Iceberg Spark Runtime Tests

1.10 Iceberg Spark Tests Iceberg Spark Extensions Tests Iceberg Spark Runtime Tests Iceberg Spark Tests Iceberg Spark Extensions Tests Iceberg Spark Runtime Tests CometIcebergNativeSuite CometFuzzIcebergSuite IcebergReadFromS3Suite (not run in CI due to MinIO container)

I leaned on newer versions for the Iceberg tests because as best as I could tell, never versions are a superset of the older versions. For the Comet-native tests we are running 1.5.2.

We should have a discussion of what we want to run long term, because right now tagging a PR [iceberg] makes CI take hours and causes so many parallel Iceberg suites that we start getting network timeouts (likely due to throttling).

…ust (apache#2528)

…chTransformer (apache#1821) Partially address apache#1749. This PR adds partition spec handling to `FileScanTask` and `RecordBatchTransformer` to correctly implement the Iceberg spec's "Column Projection" rules for fields "not present" in data files. Prior to this PR, `iceberg-rust`'s `FileScanTask` had no mechanism to pass partition information to `RecordBatchTransformer`, causing two issues: 1. **Incorrect handling of bucket partitioning**: Couldn't distinguish identity transforms (which should use partition metadata constants) from non-identity transforms like bucket/truncate/year/month (which must read from data file). For example, `bucket(4, id)` stores `id_bucket = 2` (bucket number) in partition metadata, but actual `id` values (100, 200, 300) are only in the data file. iceberg-rust was incorrectly treating bucket-partitioned source columns as constants, breaking runtime filtering and returning incorrect query results. 2. **Field ID conflicts in add_files scenarios**: When importing Hive tables via `add_files`, partition columns could have field IDs conflicting with Parquet data columns. Example: Parquet has field_id=1→"name", but Iceberg expects field_id=1→"id" (partition). Per spec, the correct field is "not present" and requires name mapping fallback. Per the Iceberg spec (https://iceberg.apache.org/spec/#column-projection), when a field ID is "not present" in a data file, it must be resolved using these rules: 1. Return the value from partition metadata if an **Identity Transform** exists 2. Use `schema.name-mapping.default` metadata to map field id to columns without field id 3. Return the default value if it has a defined `initial-default` 4. Return null in all other cases **Why this matters:** - **Identity transforms** (e.g., `identity(dept)`) store actual column values in partition metadata that can be used as constants without reading the data file - **Non-identity transforms** (e.g., `bucket(4, id)`, `day(timestamp)`) store transformed values in partition metadata (e.g., bucket number 2, not the actual `id` values 100, 200, 300) and must read source columns from the data file 1. **Added partition fields to `FileScanTask`** (`scan/task.rs`): - `partition: Option<Struct>` - Partition data from manifest entry - `partition_spec: Option<Arc<PartitionSpec>>` - For transform-aware constant detection - `name_mapping: Option<Arc<NameMapping>>` - Name mapping from table metadata 2. **Implemented `constants_map()` function** (`arrow/record_batch_transformer.rs`): - Replicates Java's `PartitionUtil.constantsMap()` behavior - Only includes fields where transform is `Transform::Identity` - Used to determine which fields use partition metadata constants vs. reading from data files 3. **Enhanced `RecordBatchTransformer`** (`arrow/record_batch_transformer.rs`): - Added `build_with_partition_data()` method to accept partition spec, partition data, and name mapping - Implements all 4 spec rules for column resolution with identity-transform awareness - Detects field ID conflicts by verifying both field ID AND name match - Falls back to name mapping when field IDs are missing/conflicting (spec rule risingwavelabs#2) 4. **Updated `ArrowReader`** (`arrow/reader.rs`): - Uses `build_with_partition_data()` when partition information is available - Falls back to `build()` when not available 5. **Updated manifest entry processing** (`scan/context.rs`): - Populates partition fields in `FileScanTask` from manifest entry data 1. **`bucket_partitioning_reads_source_column_from_file`** - Verifies that bucket-partitioned source columns are read from data files (not treated as constants from partition metadata) 2. **`identity_partition_uses_constant_from_metadata`** - Verifies that identity-transformed fields correctly use partition metadata constants 3. **`test_bucket_partitioning_with_renamed_source_column`** - Verifies field-ID-based mapping works despite column rename 4. **`add_files_partition_columns_without_field_ids`** - Verifies name mapping resolution for Hive table imports without field IDs (spec rule 5. **`add_files_with_true_field_id_conflict`** - Verifies correct field ID conflict detection with name mapping fallback (spec rule risingwavelabs#2) 6. **`test_all_four_spec_rules`** - Integration test verifying all 4 spec rules work together Yes, there are 6 new unit tests covering all 4 Iceberg spec rules. This also resolved approximately 50 Iceberg Java tests when running with DataFusion Comet's experimental apache/datafusion-comet#2528 PR. --------- Co-authored-by: Renjie Liu <[email protected]>

…chTransformer (apache#1821) (#107) Partially address apache#1749. This PR adds partition spec handling to `FileScanTask` and `RecordBatchTransformer` to correctly implement the Iceberg spec's "Column Projection" rules for fields "not present" in data files. Prior to this PR, `iceberg-rust`'s `FileScanTask` had no mechanism to pass partition information to `RecordBatchTransformer`, causing two issues: 1. **Incorrect handling of bucket partitioning**: Couldn't distinguish identity transforms (which should use partition metadata constants) from non-identity transforms like bucket/truncate/year/month (which must read from data file). For example, `bucket(4, id)` stores `id_bucket = 2` (bucket number) in partition metadata, but actual `id` values (100, 200, 300) are only in the data file. iceberg-rust was incorrectly treating bucket-partitioned source columns as constants, breaking runtime filtering and returning incorrect query results. 2. **Field ID conflicts in add_files scenarios**: When importing Hive tables via `add_files`, partition columns could have field IDs conflicting with Parquet data columns. Example: Parquet has field_id=1→"name", but Iceberg expects field_id=1→"id" (partition). Per spec, the correct field is "not present" and requires name mapping fallback. Per the Iceberg spec (https://iceberg.apache.org/spec/#column-projection), when a field ID is "not present" in a data file, it must be resolved using these rules: 1. Return the value from partition metadata if an **Identity Transform** exists 2. Use `schema.name-mapping.default` metadata to map field id to columns without field id 3. Return the default value if it has a defined `initial-default` 4. Return null in all other cases **Why this matters:** - **Identity transforms** (e.g., `identity(dept)`) store actual column values in partition metadata that can be used as constants without reading the data file - **Non-identity transforms** (e.g., `bucket(4, id)`, `day(timestamp)`) store transformed values in partition metadata (e.g., bucket number 2, not the actual `id` values 100, 200, 300) and must read source columns from the data file 1. **Added partition fields to `FileScanTask`** (`scan/task.rs`): - `partition: Option<Struct>` - Partition data from manifest entry - `partition_spec: Option<Arc<PartitionSpec>>` - For transform-aware constant detection - `name_mapping: Option<Arc<NameMapping>>` - Name mapping from table metadata 2. **Implemented `constants_map()` function** (`arrow/record_batch_transformer.rs`): - Replicates Java's `PartitionUtil.constantsMap()` behavior - Only includes fields where transform is `Transform::Identity` - Used to determine which fields use partition metadata constants vs. reading from data files 3. **Enhanced `RecordBatchTransformer`** (`arrow/record_batch_transformer.rs`): - Added `build_with_partition_data()` method to accept partition spec, partition data, and name mapping - Implements all 4 spec rules for column resolution with identity-transform awareness - Detects field ID conflicts by verifying both field ID AND name match - Falls back to name mapping when field IDs are missing/conflicting (spec rule #2) 4. **Updated `ArrowReader`** (`arrow/reader.rs`): - Uses `build_with_partition_data()` when partition information is available - Falls back to `build()` when not available 5. **Updated manifest entry processing** (`scan/context.rs`): - Populates partition fields in `FileScanTask` from manifest entry data 1. **`bucket_partitioning_reads_source_column_from_file`** - Verifies that bucket-partitioned source columns are read from data files (not treated as constants from partition metadata) 2. **`identity_partition_uses_constant_from_metadata`** - Verifies that identity-transformed fields correctly use partition metadata constants 3. **`test_bucket_partitioning_with_renamed_source_column`** - Verifies field-ID-based mapping works despite column rename 4. **`add_files_partition_columns_without_field_ids`** - Verifies name mapping resolution for Hive table imports without field IDs (spec rule 5. **`add_files_with_true_field_id_conflict`** - Verifies correct field ID conflict detection with name mapping fallback (spec rule #2) 6. **`test_all_four_spec_rules`** - Integration test verifying all 4 spec rules work together Yes, there are 6 new unit tests covering all 4 Iceberg spec rules. This also resolved approximately 50 Iceberg Java tests when running with DataFusion Comet's experimental apache/datafusion-comet#2528 PR. --------- Co-authored-by: Matt Butrovich <[email protected]> Co-authored-by: Renjie Liu <[email protected]>

mbutrovich added 3 commits October 5, 2025 21:53

CometNativeIcebergScan with iceberg-rust using FileScanTasks.

cded0ad

Clean up tests a little.

4f3004b

Remove old comment.

4afec43

mbutrovich added 6 commits October 6, 2025 06:58

Fix machete and missing suite CI failures.

fc97ce9

Fix unused variables.

cca4911

Spark 4.0 needs Iceberg 1.10, let's see if that works in CI.

93f466d

Remove errant println.

970b692

Remove old path() code path.

c44973b

Update old comment.

0f83fd4

mbutrovich added 2 commits October 6, 2025 11:49

Iceberg 1.5.x compatible reflection. Use 1.5.2 for Spark 3.4 and 3.5.

6cbbd09

Fix scalastyle issues.

6966a12

mbutrovich changed the title ~~feat: Iceberg scan based serializing FileScanTasks to iceberg-rust~~ feat: [iceberg] Scan based serializing FileScanTasks to iceberg-rust Oct 6, 2025

mbutrovich force-pushed the iceberg-rust branch from 227332c to 6966a12 Compare October 6, 2025 20:03

mbutrovich changed the title ~~feat: [iceberg] Scan based serializing FileScanTasks to iceberg-rust~~ feat: Iceberg scan based serializing FileScanTasks to iceberg-rust Oct 6, 2025

mbutrovich added 7 commits October 7, 2025 13:03

Merge branch 'main' into iceberg-rust

1153d71

# Conflicts: # native/Cargo.lock # spark/src/main/scala/org/apache/comet/rules/CometScanRule.scala

Remove unused import.

a0f4d63

Clean up docs a bit.

a9cebfd

Refactor and cleanup.

6b2175a

Refactor and cleanup.

3618407

Add IcebergFileStream based on DataFusion, add benchmark. Bump the Ic…

8091a81

…eberg version back to 1.8.1 after hitting known segfaults with old versions.

Fix CometReadBenchmark.

880599e

This was referenced Oct 15, 2025

feat(reader): Make ArrowReaderBuilder::new public apache/iceberg-rust#1748

Merged

ArrowReader enhancements for Apache DataFusion Comet apache/iceberg-rust#1749

Open

mbutrovich added 4 commits October 16, 2025 16:04

Merge branch 'main' into iceberg-rust

5127e1c

# Conflicts: # docs/source/user-guide/latest/configs.md # native/Cargo.lock # native/Cargo.toml # native/core/Cargo.toml

Fixes after bringing in upstream/main.

878c971

Basic complex type support.

e66799e

CometFuzzIceberg stuff.

4f2f3b8

mbutrovich added 3 commits November 17, 2025 12:00

Merge branch 'main' into iceberg-rust

030c530

Merge branch 'main' into iceberg-rust

974fe94

Switch to upstream iceberg-rust.

7c0a99b

andygrove approved these changes Nov 18, 2025

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mbutrovich added 9 commits November 19, 2025 10:48

Merge branch 'main' into iceberg-rust

4d3ffe5

Merge branch 'main' into iceberg-rust

6a528fc

Fix q79 plans? Not sure why this is needed.

8be08b8

Move iceberg-rust-related diffs to their own folder, and add new para…

67a0cb6

…llel test and setup workflows.

Merge branch 'main' into iceberg-rust

9ecd93a

Merge branch 'main' into iceberg-rust

68652d4

Update comment in pom file.

070590a

Update iceberg-rust workflow.

46c507e

Fix existing Iceberg integration.

773eded

kazuyukitanimura reviewed Nov 19, 2025

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kazuyukitanimura reviewed Nov 19, 2025

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mbutrovich added 7 commits November 19, 2025 18:16

Fix match arms for old Iceberg integration.

cef5390

Move datafusion-datasource up to top cargo.toml, and set core's to wo…

46f07d2

…rkspace.

Add Spark 3.4 to Iceberg Java workflows for Iceberg-Rust code path.

cffc791

Iceberg 1.5.2 for Spark 3.4.

80b5fdc

Omit incompatible types from CometFuzzIcebergBase schema for Iceberg …

a280467

…<1.6.0

Remove test print.

c6c3021

Adjust schema filtering logic in fuzz test "order by random columns" …

7911e4b

…due to type limitations in Iceberg 1.5.2.

mbutrovich merged commit 937cacd into apache:main Nov 20, 2025
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kazuyukitanimura reviewed Nov 20, 2025

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mbutrovich mentioned this pull request Dec 9, 2025

docs: add documentation for fully-native Iceberg scans #2868

Merged

coderfender pushed a commit to coderfender/datafusion-comet that referenced this pull request Dec 13, 2025

feat: cherry-pick UUID conversion logic from apache#2528. (apache#2648)

558461e

coderfender pushed a commit to coderfender/datafusion-comet that referenced this pull request Dec 13, 2025

feat: [iceberg] Native scan by serializing FileScanTasks to iceberg-r…

ab410a9

…ust (apache#2528)

mbutrovich mentioned this pull request Dec 16, 2025

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		iceberg-version: [{short: '1.8', full: '1.8.1'}, {short: '1.9', full: '1.9.1'}, {short: '1.10', full: '1.10.0'}]
		spark-version: [{short: '3.4', full: '3.4.3'}, {short: '3.5', full: '3.5.7'}]

	3.4	3.5	4.0
1.5.2	CometIcebergNativeSuite CometFuzzIcebergSuite IcebergReadFromS3Suite (not run in CI due to MinIO container)
1.8.1	Iceberg Spark Tests Iceberg Spark Extensions Tests Iceberg Spark Runtime Tests	Iceberg Spark Tests Iceberg Spark Extensions Tests Iceberg Spark Runtime Tests CometIcebergNativeSuite CometFuzzIcebergSuite IcebergReadFromS3Suite (not run in CI due to MinIO container)
1.9.1	Iceberg Spark Tests Iceberg Spark Extensions Tests Iceberg Spark Runtime Tests	Iceberg Spark Tests Iceberg Spark Extensions Tests Iceberg Spark Runtime Tests
1.10	Iceberg Spark Tests Iceberg Spark Extensions Tests Iceberg Spark Runtime Tests	Iceberg Spark Tests Iceberg Spark Extensions Tests Iceberg Spark Runtime Tests	CometIcebergNativeSuite CometFuzzIcebergSuite IcebergReadFromS3Suite (not run in CI due to MinIO container)

feat: [iceberg] Native scan by serializing FileScanTasks to iceberg-rust #2528

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Rationale for this change

What changes are included in this PR?

Scala/JVM Side:

Native/Rust Side:

How are these changes tested?

Benefits over iceberg_compat

Current Limitations & Open Questions

Related Work

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mbutrovich commented Oct 6, 2025 •

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