Add DataFusion 6.0.0 blog

_posts/2021-11-8-datafusion-6.0.0.md

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+---
+layout: post
+title: Apache Arrow DataFusion 6.0.0 Release
+date: "2021-11-19 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 embedded
+query engine which leverages the unique features of
+[Rust](https://www.rust-lang.org/) and [Apache
+Arrow](https://arrow.apache.org/) to provide a system that is high
+performance, easy to connect, easy to embed, and high quality.
+
+The Apache Arrow team is pleased to announce the DataFusion 6.0.0 release. This covers 4 months of development work
+and includes 134 commits from the following 28 distinct contributors.
+
+<!--
+git log --pretty=oneline 5.0.0..6.0.0 datafusion datafusion-cli datafusion-examples | wc -l
+     134
+
+git shortlog -sn 5.0.0..6.0.0 datafusion datafusion-cli datafusion-examples | wc -l
+      29
+
+      Carlos and xudong963 are same individual
+-->
+
+```
+    28  Andrew Lamb
+    26  Jiayu Liu
+    13  xudong963
+     9  rdettai
+     9  QP Hou
+     6  Matthew Turner
+     5  Daniël Heres
+     4  Guillaume Balaine
+     3  Francis Du
+     3  Marco Neumann
+     3  Jon Mease
+     3  Nga Tran
+     2  Yijie Shen
+     2  Ruihang Xia
+     2  Liang-Chi Hsieh
+     2  baishen
+     2  Andy Grove
+     2  Jason Tianyi Wang
+     1  Nan Zhu
+     1  Antoine Wendlinger
+     1  Krisztián Szűcs
+     1  Mike Seddon
+     1  Conner Murphy
+     1  Patrick More
+     1  Taehoon Moon
+     1  Tiphaine Ruy
+     1  adsharma
+     1  lichuan6
+```
+
+The release notes below are not exhaustive and only expose selected highlights of the release. Many other bug fixes
+and improvements have been made: we refer you to the complete
+[changelog](https://github.com/apache/arrow-datafusion/blob/6.0.0/datafusion/CHANGELOG.md).
+
+# New Website
+
+Befitting a growing project, DataFusion now has its
+[own website](https://arrow.apache.org/datafusion/) hosted as part of the
+main [Apache Arrow Website](https://arrow.apache.org)
+
+# Roadmap
+
+The community worked to gather their thoughts about where we are
+taking DataFusion into a public
+[Roadmap](https://arrow.apache.org/datafusion/specification/roadmap.html)
+for the first time
+
+# New Features
+
+- Runtime operator metrics collection framework
+- Object store abstraction for unified access to local or remote storage
+- Hive style table partitioning support, for Parquet, CSV, Avro and Json files
+- DataFrame API support for: `except`, `intersect`, `show`, `limit` and window functions
+- SQL
+  - `EXPLAIN ANALYZE` with runtime metrics
+  - `trim ( [ LEADING | TRAILING | BOTH ] [ FROM ] string text [, characters text ] )` syntax
+  - Postgres style regular expression matching operators `~`, `~*`, `!~`, and `!~*`
+  - SQL set operators `UNION`, `INTERSECT`, and `EXCEPT`
+  - `cume_dist`, `percent_rank` window functions
+  - `digest`, `blake2s`, `blake2b`, `blake3` crypto functions
+  - HyperLogLog based `approx_distinct`
+  - `is distinct from` and `is not distinct from`
+  - `CREATE TABLE AS SELECT`
+  - Accessing elements of nested `Struct` and `List` columns (e.g. `SELECT struct_column['field_name'], array_column[0] FROM ...`)
+  - Boolean expressions in `CASE` statement
+  - `DROP TABLE`
+  - `VALUES` List
+  - Postgres regex match operators
+- Support for Avro format
+- Support for `ScalarValue::Struct`
+- Automatic schema inference for CSV files
+- Better interactive editing support in `datafusion-cli` as well as `psql` style commands such as `\d`, `\?`, and `\q`
+- Generic constant evaluation and simplification framework
+- Added common subexpression eliminate query plan optimization rule
+- Python binding 0.4.0 with all Datafusion 6.0.0 features
+
+With these new features, we are also now passing TPC-H queries 8, 13 and 21.
+
+For the full list of new features with their relevant PRs, see the
+[enhancements section](https://github.com/apache/arrow-datafusion/blob/6.0.0/datafusion/CHANGELOG.md)
+in the changelog.
+
+# `async` planning and decoupling file format from table layout
+
+Driven by the need to support Hive style table partitioning, @rdettai
+introduced the following design change to the Datafusion core.
+
+- The code for reading specific file formats (`Parquet`, `Avro`, `CSV`, and
+`JSON`) was separated from the logic that handles grouping sets of
+files into execution partitions.
+- The query planning process was made `async`.
+
+As a result, we are able to replace the old `Parquet`, `CSV` and `JSON` table
+providers with a single `ListingTable` table provider.
+
+This also sets up DataFusion and its plug-in ecosystem to
+supporting a wide range of catalogs and various object store implementations.
+You can read more about this change in the
+[design document](https://docs.google.com/document/d/1Bd4-PLLH-pHj0BquMDsJ6cVr_awnxTuvwNJuWsTHxAQ)
+and on the [arrow-datafusion#1010 PR](https://github.com/apache/arrow-datafusion/pull/1010).
+
+# How to Get Involved
+
+If you are interested in contributing to DataFusion, we would love to have you! You
+can help by trying out DataFusion on some of your own data and projects and filing bug reports and helping to
+improve the documentation, or contribute to the documentation, tests or code. A list of open issues suitable for
+beginners is [here](https://github.com/apache/arrow-datafusion/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22)
+and the full list is [here](https://github.com/apache/arrow-datafusion/issues).
+
+Check out our new [Communication Doc](https://arrow.apache.org/datafusion/community/communication.html) on more
+ways to engage with the community.