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new dca91b1 Blog post announcing Comet 0.13.0 (#137)
dca91b1 is described below
commit dca91b1955e648beb146a3554dd3e5964861dd31
Author: Andy Grove <[email protected]>
AuthorDate: Fri Jan 30 15:38:14 2026 -0700
Blog post announcing Comet 0.13.0 (#137)
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+---
+layout: post
+title: Apache DataFusion Comet 0.12.0 Release
+date: 2025-12-04
+author: pmc
+categories: [subprojects]
+---
+
+<!--
+{% comment %}
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+(the "License"); you may not use this file except in compliance with
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+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
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+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
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+{% endcomment %}
+-->
+
+[TOC]
+
+The Apache DataFusion PMC is pleased to announce version 0.13.0 of the
[Comet](https://datafusion.apache.org/comet/) subproject.
+
+Comet is an accelerator for Apache Spark that translates Spark physical plans
to DataFusion physical plans for
+improved performance and efficiency without requiring any code changes.
+
+This release covers approximately eight weeks of development work and is the
result of merging 160 PRs from 15
+contributors. See the [change log] for more information.
+
+[change log]:
https://github.com/apache/datafusion-comet/blob/main/dev/changelog/0.13.0.md
+
+## Key Features
+
+### Native Parquet Write Support (Experimental)
+
+This release introduces experimental native Parquet write capabilities,
allowing Comet to intercept and execute Parquet write operations natively
through DataFusion. Key capabilities include:
+
+- File commit protocol support for reliable writes
+- Remote HDFS writing via OpenDAL integration
+- Complex type support (arrays, maps, structs)
+- Proper handling of object store settings
+
+To enable native Parquet writes, set:
+
+```
+spark.comet.allowIncompatibleOp.DataWritingCommandExec=true
+spark.comet.parquet.write.enabled=true
+```
+
+**Note**: This feature is highly experimental and should not be used in
production environments. It is currently categorized as a testing feature and
is disabled by default.
+
+### Native Iceberg Improvements
+
+Comet's fully-native Iceberg integration received significant enhancements in
this release:
+
+**REST Catalog Support**: Native Iceberg scans now support REST catalogs,
enabling integration with catalog services like Apache Polaris and Tabular.
Configure with:
+
+```shell
+--conf spark.sql.catalog.rest_cat=org.apache.iceberg.spark.SparkCatalog
+--conf
spark.sql.catalog.rest_cat.catalog-impl=org.apache.iceberg.rest.RESTCatalog
+--conf spark.sql.catalog.rest_cat.uri=http://localhost:8181
+--conf spark.comet.scan.icebergNative.enabled=true
+```
+
+**Session Token Authentication**: Added support for session tokens in native
Iceberg scans for secure S3 access.
+
+**Performance Optimizations**:
+- Deduplicated serialized metadata reducing memory overhead
+- Switched from JSON to protobuf for partition value serialization
+- Removed IcebergFileStream in favor of iceberg-rust's built-in parallelization
+- Reduced metadata serialization points
+- Added SchemaAdapter caching
+
+To enable fully-native Iceberg scanning:
+
+```
+spark.comet.scan.icebergNative.enabled=true
+```
+
+The native reader supports Iceberg table spec v1 and v2, all primitive and
complex types, schema evolution, time travel, positional and equality deletes,
filter pushdown, and various storage backends (local, HDFS, S3).
+
+### Native CSV Reading (Experimental)
+
+Experimental support for native CSV file reading has been added, expanding
Comet's file format capabilities beyond Parquet.
+
+### New Expressions
+
+The release adds support for numerous expressions:
+- Array functions: `explode`, `explode_outer`, `size`
+- Date/time functions: `unix_date`, `date_format`, `datediff`, `last_day`,
`unix_timestamp`
+- String functions: `left`
+- JSON functions: `from_json` (partial support)
+
+### ANSI Mode Support
+
+Sum and average aggregate expressions now support ANSI mode for both integer
and decimal inputs, enabling overflow checking in strict SQL mode.
+
+### Native Shuffle Improvements
+
+- Round-robin partitioning is now supported in native shuffle
+- Spill metrics are now reported correctly
+- Configurable shuffle writer buffer size via
`spark.comet.shuffle.write.bufferSize`
+
+## Performance Improvements
+
+This release includes extensive performance optimizations:
+
+- **String to integer casting**: Significant speedups through optimized parsing
+- **String functions**: Optimized `lpad`/`rpad` to remove unnecessary memory
allocations
+- **Date operations**: Improved `normalize_nan` and date truncate performance
+- **Query planning**: Cached query plans to avoid per-partition serialization
overhead
+- **Memory efficiency**: Reduced GC pressure in protobuf serialization
+- **Hash operations**: Optimized complex-type hash implementations including
murmur3 support for nested types
+- **Runtime efficiency**: Eliminated busy-polling of Tokio stream for plans
without CometScan
+- **Metrics overhead**: Reduced timer and syscall overhead in native shuffle
writer
+
+## Deprecations
+
+The `native_comet` scan mode is now deprecated in favor of
`native_iceberg_compat` and will be removed in a future release. The `auto`
scan mode no longer falls back to `native_comet`.
+
+## Compatibility
+
+This release upgrades to DataFusion 51, Arrow 57, and the latest iceberg-rust.
The minimum supported Rust version is now 1.88.
+
+Supported platforms include Spark 3.4.3, 3.5.4-3.5.7, and Spark 4.0.x with
various JDK and Scala combinations.
+
+The community encourages users to test Comet with existing Spark workloads and
welcomes contributions to ongoing development.
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