SChakravorti21 commented on code in PR #479:
URL: https://github.com/apache/arrow-site/pull/479#discussion_r1507857254
##########
_posts/2024-02-27-comet-donation.md:
##########
@@ -0,0 +1,106 @@
+---
+layout: post
+title: "Announcing Apache Arrow DataFusion Comet"
+date: "2024-02-27 00:00:00"
+author: pmc
+categories: [release]
+---
+<!--
+{% comment %}
+Licensed to the Apache Software Foundation (ASF) under one or more
+contributor license agreements. See the NOTICE file distributed with
+this work for additional information regarding copyright ownership.
+The ASF licenses this file to you under the Apache License, Version 2.0
+(the "License"); you may not use this file except in compliance with
+the License. You may obtain a copy of the License at
+
+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 %}
+-->
+
+# Introduction
+The Apache Arrow PMC is pleased to announce the donation of the [Comet
project],
+a native Spark SQL Accelerator built on [Apache Arrow DataFusion].
+
+Comet is an Apache Spark plugin that uses Apache Arrow DataFusion to
+accelerate Spark workloads. It is designed as a drop-in
+replacement for Spark's JVM based SQL execution engine and offers significant
+performance improvements for some workloads as shown below.
+
+```text
+ ┌─────────────────────────────────────────────────────────────────┐
+ │ │
+ │ ┌──────────┐ ┌────────────┐ ┌────────────┐ ┌────────────┐ │
+ │ │ SQL │ │ Cluster │ │ DAG/Task │ ... │ Executor │ │
+ │ │ Planner │ │ Manager │ │ Scheduler │ │ │ │
+ │ └──────────┘ └────────────┘ └────────────┘ └────────────┘ │
+ │ │ │
+ └─────────────────────────────────────────────────────────────────┘
+ Spark (JVM Based) │
+ ┌ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─
+
+ │
+ ▼
+ ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
+Comet Execution ┃ ┃
+Engine ┃ ┌─────────────────────────┐ ┃
+(Native Code) ┃ │ Apache Arrow DataFusion │ ┃
+ ┃ └─────────────────────────┘ ┃
+ ┃ ┃
+ ┃ ┌─────────────────────────┐ ┃
+ ┃ │ Spark Compatible │ ┃
+ ┃ │ Expressions/Operators │ ┃
+ ┃ └─────────────────────────┘ ┃
+ ┃ ┃
+ ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
+```
+
+**Figure 1**: With Comet, users interact with the same Spark ecosystem, tools
+and APIs such as Spark SQL. Queries still run through Spark's mature and
feature
+rich query optimizer and planner. However, the execution is delegated to Comet,
+which is significantly faster and more resource efficient than the JVM based
+implementation.
+
+[Rust]: https://www.rust-lang.org/
+
+# Background
+
+Comet is one of a growing class of projects that aim to accelerate Spark using
+native columnar engines such as the proprietary [Databricks Photon Engine] and
+the open source [Gluten project] and [Spark RAPIDS].
Review Comment:
Would it help to give some background as to why these initiatives have been
popping up in the first place? I know the article alludes to columnar execution
and lower resource usage, but (imo) it would be more approachable if it were
framed from the perspective of the struggles Spark users face **today**, and
then explaining how these initiatives address those problems.
Relatedly, I vaguely remember hearing about an effort to bring columnar
execution into mainline Spark (was it Project Tungsten?). I would be curious to
hear about the differences between that effort and Comet's approach.
##########
_posts/2024-02-27-comet-donation.md:
##########
@@ -0,0 +1,106 @@
+---
+layout: post
+title: "Announcing Apache Arrow DataFusion Comet"
+date: "2024-02-27 00:00:00"
+author: pmc
+categories: [release]
+---
+<!--
+{% comment %}
+Licensed to the Apache Software Foundation (ASF) under one or more
+contributor license agreements. See the NOTICE file distributed with
+this work for additional information regarding copyright ownership.
+The ASF licenses this file to you under the Apache License, Version 2.0
+(the "License"); you may not use this file except in compliance with
+the License. You may obtain a copy of the License at
+
+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 %}
+-->
+
+# Introduction
+The Apache Arrow PMC is pleased to announce the donation of the [Comet
project],
+a native Spark SQL Accelerator built on [Apache Arrow DataFusion].
+
+Comet is an Apache Spark plugin that uses Apache Arrow DataFusion to
+accelerate Spark workloads. It is designed as a drop-in
+replacement for Spark's JVM based SQL execution engine and offers significant
+performance improvements for some workloads as shown below.
+
+```text
+ ┌─────────────────────────────────────────────────────────────────┐
+ │ │
+ │ ┌──────────┐ ┌────────────┐ ┌────────────┐ ┌────────────┐ │
+ │ │ SQL │ │ Cluster │ │ DAG/Task │ ... │ Executor │ │
+ │ │ Planner │ │ Manager │ │ Scheduler │ │ │ │
+ │ └──────────┘ └────────────┘ └────────────┘ └────────────┘ │
+ │ │ │
+ └─────────────────────────────────────────────────────────────────┘
+ Spark (JVM Based) │
+ ┌ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─
+
+ │
+ ▼
+ ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
+Comet Execution ┃ ┃
+Engine ┃ ┌─────────────────────────┐ ┃
+(Native Code) ┃ │ Apache Arrow DataFusion │ ┃
+ ┃ └─────────────────────────┘ ┃
+ ┃ ┃
+ ┃ ┌─────────────────────────┐ ┃
+ ┃ │ Spark Compatible │ ┃
+ ┃ │ Expressions/Operators │ ┃
+ ┃ └─────────────────────────┘ ┃
+ ┃ ┃
+ ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
+```
+
+**Figure 1**: With Comet, users interact with the same Spark ecosystem, tools
+and APIs such as Spark SQL. Queries still run through Spark's mature and
feature
+rich query optimizer and planner. However, the execution is delegated to Comet,
+which is significantly faster and more resource efficient than the JVM based
+implementation.
+
+[Rust]: https://www.rust-lang.org/
+
+# Background
+
+Comet is one of a growing class of projects that aim to accelerate Spark using
+native columnar engines such as the proprietary [Databricks Photon Engine] and
+the open source [Gluten project] and [Spark RAPIDS].
+
+Comet was originally implemented at Apple and the engineers who worked on the
+project are also significant contributors to Arrow and DataFusion. Bringing
+Comet into the Apache Software Foundation will accelerate its development and
+grow its community of contributors and users.
+
+[Comet project]: https://github.com/apache/arrow-datafusion-comet
Review Comment:
I learned that there is a similar effort to build a Spark-native accelerator
using DataFusion: [Blaze](https://github.com/kwai/blaze). Wondering if it
deserves a mention as well.
##########
_posts/2024-02-27-comet-donation.md:
##########
@@ -0,0 +1,106 @@
+---
+layout: post
+title: "Announcing Apache Arrow DataFusion Comet"
+date: "2024-02-27 00:00:00"
+author: pmc
+categories: [release]
+---
+<!--
+{% comment %}
+Licensed to the Apache Software Foundation (ASF) under one or more
+contributor license agreements. See the NOTICE file distributed with
+this work for additional information regarding copyright ownership.
+The ASF licenses this file to you under the Apache License, Version 2.0
+(the "License"); you may not use this file except in compliance with
+the License. You may obtain a copy of the License at
+
+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 %}
+-->
+
+# Introduction
+The Apache Arrow PMC is pleased to announce the donation of the [Comet
project],
+a native Spark SQL Accelerator built on [Apache Arrow DataFusion].
+
+Comet is an Apache Spark plugin that uses Apache Arrow DataFusion to
+accelerate Spark workloads. It is designed as a drop-in
+replacement for Spark's JVM based SQL execution engine and offers significant
+performance improvements for some workloads as shown below.
+
+```text
+ ┌─────────────────────────────────────────────────────────────────┐
+ │ │
+ │ ┌──────────┐ ┌────────────┐ ┌────────────┐ ┌────────────┐ │
+ │ │ SQL │ │ Cluster │ │ DAG/Task │ ... │ Executor │ │
+ │ │ Planner │ │ Manager │ │ Scheduler │ │ │ │
+ │ └──────────┘ └────────────┘ └────────────┘ └────────────┘ │
+ │ │ │
+ └─────────────────────────────────────────────────────────────────┘
+ Spark (JVM Based) │
+ ┌ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─
+
+ │
+ ▼
+ ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
+Comet Execution ┃ ┃
+Engine ┃ ┌─────────────────────────┐ ┃
+(Native Code) ┃ │ Apache Arrow DataFusion │ ┃
+ ┃ └─────────────────────────┘ ┃
+ ┃ ┃
+ ┃ ┌─────────────────────────┐ ┃
+ ┃ │ Spark Compatible │ ┃
+ ┃ │ Expressions/Operators │ ┃
+ ┃ └─────────────────────────┘ ┃
+ ┃ ┃
+ ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
+```
+
+**Figure 1**: With Comet, users interact with the same Spark ecosystem, tools
+and APIs such as Spark SQL. Queries still run through Spark's mature and
feature
+rich query optimizer and planner. However, the execution is delegated to Comet,
+which is significantly faster and more resource efficient than the JVM based
+implementation.
Review Comment:
I assume you might already be planning to add more details, but I'd love to
hear about any Comet-specific optimizations that were implemented. Similarly,
I'd be interested to hear about DataFusion-specific features that made it a
particularly good fit for Comet's implementation (DataFusion's focus on
extensibility comes to mind).
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