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+---
+layout: post
+title: Apache DataFusion Comet 0.9.0 Release
+date: 2025-07-01
+author: pmc
+categories: [subprojects]
+---
+
+<!--
+{% comment %}
+Licensed to the Apache Software Foundation (ASF) under one or more
+contributor license agreements.  See the NOTICE file distributed with
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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
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+{% endcomment %}
+-->
+
+The Apache DataFusion PMC is pleased to announce version 0.9.0 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 ten weeks of development work and is the result of merging 139 PRs from 24
+contributors. See the [change log] for more information.
+
+[change log]: https://github.com/apache/datafusion-comet/blob/main/dev/changelog/0.9.0.md
+
+## Release Highlights
+
+### Complex Type Support in Parquet Scans
+
+Comet now supports complex types (Structs, Maps, and Arrays) when reading Parquet files. This functionality is not
+yet available when reading Parquet files from Apache Iceberg.
+
+This functionality was only available in previous releases when manually specifying one of the new experimental
+scan implementations. Comet now automatically chooses the best scan implementation based on the input schema, and no
+longer requires manual configuration.
+
+### Complex Type Processing Improvements
+
+Numerous improvements have been made to complex type support to ensure Spark-compatible behavior when casting between
+structs and accessing fields within deeply nested types.
+
+### Shuffle Improvements
+
+Comet now accelerates a broader range of shuffle operations, leading to more queries running fully natively. In
+previous releases, some shuffle operations fell back to Spark to avoid some known bugs in Comet, and these bugs have
+now been fixed.
+
+### New Features
+
+Comet 0.9.0 adds support for the following Spark expressions:
+
+- ArrayDistinct
+- ArrayMax
+- ArrayRepeat
+- ArrayUnion
+- BitCount
+- BitNot
+- Expm1
+- MapValues
+- Signum
+- ToPrettyString
+- map[]
+
+### Improved Spark SQL Test Coverage
+
+Comet now passes 97% of the Spark SQL test suite, with more than 24,000 tests passing (based on testing against
+Spark 3.5.6). The remaining 3% of tests are ignored for various reasons, such as being too specific to Spark 
+internals, or testing for features that are not relevant to Comet, such as whole-stage code generation, which
+is not needed when using a vectorized execution engine.
+
+This release contains numerous bug fixes to achieve this coverage, including improved support for exchange reuse
+when AQE is enabled.
+
+<style>
+  table {
+    border-collapse: collapse;
+    width: 100%;
+    font-family: sans-serif;
+  }
+
+  th, td {
+    text-align: left;
+    padding: 8px 12px;
+  }
+
+  th {
+    background-color: #f2f2f2;
+    font-weight: bold;
+  }
+
+  td {
+    border-bottom: 1px solid #ddd;
+  }
+
+  tbody tr:last-child td {
+    font-weight: bold;
+    border-top: 2px solid #000;
+  }
+</style>
+
+<table>
+  <thead>
+    <tr>
+      <th>Module</th>
+      <th>Passed</th>
+      <th>Ignored</th>
+      <th>Canceled</th>
+      <th>Total</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr><td>catalyst</td><td>7,232</td><td>5</td><td>1</td><td>7,238</td></tr>
+    <tr><td>core-1</td><td>9,186</td><td>246</td><td>6</td><td>9,438</td></tr>
+    <tr><td>core-2</td><td>2,649</td><td>393</td><td>0</td><td>3,042</td></tr>
+    <tr><td>core-3</td><td>1,757</td><td>136</td><td>16</td><td>1,909</td></tr>
+    <tr><td>hive-1</td><td>2,174</td><td>14</td><td>4</td><td>2,192</td></tr>
+    <tr><td>hive-2</td><td>19</td><td>1</td><td>4</td><td>24</td></tr>
+    <tr><td>hive-3</td><td>1,058</td><td>11</td><td>4</td><td>1,073</td></tr>
+    <tr><td><strong>Total</strong></td><td><strong>24,075</strong></td><td><strong>806</strong></td><td><strong>31</strong></td><td><strong>24,912</strong></td></tr>
+  </tbody>
+</table>
+
+### Memory & Performance Tracing
+
+Comet now provides a tracing feature for analyzing performance and off-heap versus on-heap memory usage. See the
+[Comet Tracing Guide] for more information.
+
+[Comet Tracing Guide]: https://datafusion.apache.org/comet/contributor-guide/tracing.html
+
+<img
+src="/blog/images/comet-0.9.0/tracing.png"
+width="100%"
+class="img-responsive"
+alt="Comet Tracing"
+/>
+
+### Spark Compatibility
+
+- Spark 3.4.3 with JDK 11 & 17, Scala 2.12 & 2.13
+- Spark 3.5.4 through 3.5.6 with JDK 11 & 17, Scala 2.12 & 2.13
+- Experimental support for Spark 4.0.0 with JDK 17, Scala 2.13
+
+We are looking for help from the community to fully support Spark 4.0.0. See [EPIC: Support 4.0.0] for more information.
+
+[EPIC: Support 4.0.0]: https://github.com/apache/datafusion-comet/issues/1637
+
+Note that Java 8 support was removed from this release because Apache Arrow no longer supports it.
+
+## Getting Involved
+
+The Comet project welcomes new contributors. We use the same [Slack and Discord] channels as the main DataFusion
+project and have a weekly [DataFusion video call].
+
+[Slack and Discord]: https://datafusion.apache.org/contributor-guide/communication.html#slack-and-discord
+[DataFusion video call]: https://docs.google.com/document/d/1NBpkIAuU7O9h8Br5CbFksDhX-L9TyO9wmGLPMe0Plc8/edit?usp=sharing
+
+The easiest way to get involved is to test Comet with your current Spark jobs and file issues for any bugs or
+performance regressions that you find. See the [Getting Started] guide for instructions on downloading and installing
+Comet.
+
+[Getting Started]: https://datafusion.apache.org/comet/user-guide/installation.html
+
+There are also many [good first issues] waiting for contributions.
+
+[good first issues]: https://github.com/apache/datafusion-comet/contribute
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