tlm365 commented on code in PR #33:
URL: https://github.com/apache/datafusion-site/pull/33#discussion_r1848537153
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_posts/2024-11-18-datafusion-fastest-single-node-parquet-clickbench.md:
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@@ -0,0 +1,347 @@
+---
+layout: post
+title: "Apache DataFusion is now the fastest single node engine for querying
Apache Parquet files"
+date: "2024-11-18 00:00:00"
+author: Andrew Lamb, Staff Engineer at InfluxData
+categories: [core, performance]
+---
+
+<!--
+{% 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 %}
+-->
+
+I am extremely excited to announce that [Apache DataFusion] [43.0.0] is the
+fastest engine for querying Apache Parquet files in [ClickBench]. It is faster
+than [DuckDB], [chDB] and [Clickhouse] using the same hardware. It also marks
+the first time a [Rust] based engine holds the top spot, which has previously
+been held by traditional C/C++ based engines.
+
+[Apache DataFusion]: https://datafusion.apache.org/
+[43.0.0]: https://crates.io/crates/datafusion
+[ClickBench]: https://benchmark.clickhouse.com/
+[DuckDB]: https://duckdb.org/
+[chDB]: https://clickhouse.com/chdb
+[Clickhouse]: https://clickhouse.com/
+[Rust]: https://www.rust-lang.org/
+
+
+<img
+src="{{ site.baseurl }}/img/2x_bgwhite_original.png"
+width="80%"
+class="img-responsive"
+alt="Apache DataFusion Logo"
+/>
+
+<img
+src="{{ site.baseurl }}/img/clickbench-datafusion-43/perf.png"
+width="100%"
+class="img-responsive"
+alt="ClickBench performance for DataFusion 43.0.0"
+/>
+
+**Figure 1**: 2024-11-16 [ClickBench Results] for the ‘hot’[^1] run against
the
+partitioned 14 GB Parquet dataset (100 files, each ~140MB) on a `c6a.4xlarge`
(16
+CPU / 32 GB RAM) VM. Measurements are relative (`1.x`) to results using
+different hardware.
+
+[ClickBench Results]:
https://benchmark.clickhouse.com/#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LHRydWUsdHJ1ZSx0cnVlLHRydWUsdHJ1ZSx0cnVlLHRydWUsdHJ1ZSx0cnVlLHRydWUsdHJ1ZSx0cnVlLHRydWUsdHJ1ZSx0cnVlLHRydWUsdHJ1ZSx0cnVlLHRydWUsdHJ1ZSx0cnVlLHRydWUsdHJ1ZSx0cnVlLHRydWVdfQ==
+
+
+Best in class performance on Parquet is now available to anyone. DataFusion’s
+open design lets you start quickly with a full featured Query Engine, including
+SQL, data formats, catalogs, and more, and then customize any behavior you
need.
+I predict the continued emergence of new classes of data systems now that
+creators can focus the bulk of their innovation on areas such as query
+languages, system integrations, and data formats rather than trying to play
+catchup with core engine performance.
+
+ClickBench also includes results for proprietary storage formats, which require
+costly load / export steps, making them useful in fewer use cases and thus much
+less important than open formats (though the idea of use case specific formats
+is interesting[^2]).
+
+This blog post highlights some of the techniques we used to achieve this
+performance, and celebrates the teamwork involved.
+
+# Rallying The Community around Performance
+
+In July, 2024 [Mehmet Ozan Kabak], CEO of [Synnada], [called on the community
to
+improve DataFusion’s performance]. This got many of us excited (who doesn’t
love
+a challenge!), and we have subsequently rallied to steadily improve the
+performance release on release as shown in Figure 2.
+
+[Mehmet Ozan Kabak]: https://www.linkedin.com/in/mehmet-ozan-kabak/)
Review Comment:
```suggestion
[Mehmet Ozan Kabak]: https://www.linkedin.com/in/mehmet-ozan-kabak/
```
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