kazuyukitanimura commented on code in PR #163:
URL: https://github.com/apache/datafusion-site/pull/163#discussion_r3001784672
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content/blog/2026-03-18-datafusion-comet-0.14.0.md:
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@@ -0,0 +1,110 @@
+---
+layout: post
+title: Apache DataFusion Comet 0.14.0 Release
+date: 2026-03-18
+author: pmc
+categories: [subprojects]
+---
+
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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 0.14.0 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 189 PRs from 21
+contributors. See the [change log] for more information.
+
+[change log]:
https://github.com/apache/datafusion-comet/blob/main/dev/changelog/0.14.0.md
+
+## Key Features
+
+### Native Columnar-to-Row Conversion
+
+Comet now uses a native columnar-to-row (C2R) conversion by default. This
+feature replaces Comet's JVM-based columnar-to-row transition with a native
Rust implementation, reducing JVM memory overhead
+when data flows from Comet's native execution back to Spark operators that
require row-based input.
+
+### Native Iceberg Improvements
+
+Comet's fully-native Iceberg integration received several enhancements:
+
+**Per-Partition Plan Serialization**: `CometExecRDD` now supports
per-partition plan data, reducing serialization
+overhead for native Iceberg scans and enabling dynamic partition pruning (DPP).
+
+**Vended Credentials**: Native Iceberg scans now support passing vended
credentials from the catalog, improving
+integration with cloud storage services.
+
+**Performance Optimizations**:
+
+- Single-pass `FileScanTask` validation for reduced planning overhead
+- Configurable data file concurrency via
`spark.comet.scan.icebergNative.dataFileConcurrency`
Review Comment:
Is the name correct? `dataFileConcurrencyLimit`?
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