[IcebergIO] Use partition-aligned manifests for faster query pruning

[atognolas]

Summary

• Modify AppendFilesToTables.appendDataFiles() to group data files by partition path and write one manifest per partition using appendManifest()
• The commit remains atomic (single AppendFiles operation) while producing partition-aligned manifests
• This enables manifest-level partition pruning in query engines (BigQuery, Trino) without a post-write rewriteManifests step

Motivation

When all files share a single partition spec, appendDataFiles() currently uses appendFile() which places everything into one manifest. With hundreds of partitions, query engines must scan all file entries in the manifest even for single-partition queries.

Measured on a 400-partition table with 99-column schema:

• Single manifest: 14s BQ slot time
• 400 partition-aligned manifests: 2.86s BQ slot time (5× improvement)

Notes

Iceberg's commit.manifest-merge.enabled (default true) will merge these manifests back into fewer manifests. Users who want to preserve partition alignment should set this to false or run periodic rewriteManifests.

Test plan

• Existing AppendFilesToTablesTest passes
• Run IcebergIO integration tests
• Verify manifest count matches partition count via Iceberg metadata inspection
• Verify query engines benefit from manifest-level pruning

🤖 Generated with Claude Code

[gemini-code-assist]

Summary of Changes

Hello, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request optimizes Iceberg table writes by implementing partition-aligned manifest generation. By grouping data files by their partition path before committing, the system allows downstream query engines to perform more efficient partition pruning, reducing scan times and improving overall query performance without sacrificing commit atomicity.

Highlights

• Partition-Aligned Manifests: Modified the Iceberg IO append process to group data files by partition path, creating individual manifests for each partition.
• Performance Optimization: Enables manifest-level partition pruning in query engines like BigQuery and Trino, resulting in significant query performance improvements.
• Atomic Commits: Maintains atomicity by performing a single AppendFiles operation, ensuring data integrity while improving metadata structure.

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[gemini-code-assist]

Code Review

This pull request updates the appendDataFiles method in AppendFilesToTables.java to group data files by partition and write them into manifest files before appending them to the table. The review feedback highlights a compilation error due to an undefined createManifestWriter method and a potential resource leak if the writer is not closed within a try-finally block. A suggestion is provided to use standard Iceberg APIs and ensure proper resource cleanup.

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[gemini-code-assist]

There are two issues here:

1. createManifestWriter is not a standard Iceberg API and is not defined in this class, which will cause a compilation error.
2. The ManifestWriter is not closed within a try-finally or try-with-resources block. If an exception occurs while adding files, the writer will leak resources.

We can resolve both issues by using the standard ManifestFiles.write API from Iceberg and wrapping the write loop in a try-finally block to ensure the writer is closed properly before retrieving the manifest file.

Note: You will need to import org.apache.iceberg.ManifestFiles and org.apache.iceberg.io.OutputFile.

        OutputFile outputFile = io.newOutputFile(
            table.location() + "/metadata/" + uuid + "-" + manifestIdx++ + ".avro");
        ManifestWriter<DataFile> writer = ManifestFiles.write(spec, outputFile);
        try {
          for (DataFile file : files) {
            writer.add(file);
          }
        } finally {
          writer.close();
        }
        update.appendManifest(writer.toManifestFile());

[atognolas]

@ahmedabu98 — Would you mind reviewing this? These are a set of IcebergIO fixes validated on production-scale benchmarks (39M users, 400 partitions, 99-column schema). The four PRs are independent and can be reviewed/merged in any order.

[github-actions]

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[ahmedabu98]

LGTM but please run ./gradlew sdks:java:io:iceberg:spotlessApply