[GitHub] [arrow-site] andygrove commented on a diff in pull request #294: [WEBSITE] DataFusion 16.0.0 blog post (WIP)

[GitBox <gi...@apache.org>]

andygrove commented on code in PR #294:
URL: https://github.com/apache/arrow-site/pull/294#discussion_r1064050185


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_posts/2023-01-07-datafusion-16.0.0.md:
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@@ -0,0 +1,289 @@
+---
+layout: post
+title: "Apache Arrow DataFusion 16.0.0 Project Update"
+date: "2023-01-07 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
+
+[DataFusion](https://arrow.apache.org/datafusion/) is an extensible
+query execution framework, written in [Rust](https://www.rust-lang.org/),
+that uses [Apache Arrow](https://arrow.apache.org) as its
+in-memory format. It is targeted primarily at developers creating data
+intensive analytics, and offers mature
+[SQL support](https://arrow.apache.org/datafusion/user-guide/sql/index.html),
+a DataFrame API, and many extension points.
+
+DataFusion based systems perform very well on performance
+benchmarks, especially considering they operate on data in parquet
+files directly rather than first loading into a specialized format.
+Some recent highlights include [clickbench](https://benchmark.clickhouse.com/)
+and the [Cloudfuse.io standalone query engines](https://www.cloudfuse.io/dashboards/standalone-engines) page.
+
+DataFusion is part of a longer term trend, articulated clearly by [Andy Pavlo](http://www.cs.cmu.edu/~pavlo/) in his
+[2022 Databases Retrospective](https://ottertune.com/blog/2022-databases-retrospective/).
+Database frameworks are proliferating and it is likely that all OLAP DBMSs and other many data heavy applications such as machine learning, will require a vectorized, highly performant query
+engine in the next 5 years to remain relevant.
+The only practical way to make such technology so widely available
+without many millions of dollars of investment is
+though open source engine such as DataFusion or [Velox](https://github.com/facebookincubator/velox).
+
+The rest of this post describes the improvements made to DataFusion
+over the last three months and some hints if where we are heading.

Review Comment:
   ```suggestion
   over the last three months and some hints of where we are heading.
   ```



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