phillipleblanc commented on code in PR #6:
URL: https://github.com/apache/datafusion-site/pull/6#discussion_r1687384579
##########
_posts/2024-07-23-datafusion-40.0.0.md:
##########
@@ -0,0 +1,492 @@
+---
+layout: post
+title: "Apache DataFusion 40.0.0 Released"
+date: "2024-07-21 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 %}
+-->
+
+<!-- see https://github.com/apache/datafusion/issues/9602 for details -->
+
+## Introduction
+
+We are proud to announce [DataFusion 40.0.0]. This blog highlights some of the
+many major improvements since we released [DataFusion 34.0.0] and a preview of
+what the community is thinking about in the next 6 months. We are hoping to
make
+more regular blog posts -- if you are interested in helping write them, please
+reach out!
+
+[DataFusion 34.0.0]:
https://datafusion.apache.org/blog/2024/01/19/datafusion-34.0.0/
+[DataFusion 40.0.0]: https://crates.io/crates/datafusion/40.0.0
+
+[Apache DataFusion] is an extensible query engine, written in [Rust], that
+uses [Apache Arrow] as its in-memory format. DataFusion is used by developers
to
+create new, fast data centric systems such as databases, dataframe libraries,
+machine learning and streaming applications. While [DataFusion’s primary design
+goal] is to accelerate the creation of other data centric systems, it has a
+reasonable experience directly out of the box as a [dataframe library] and
+[command line SQL tool].
+
+[DataFusion’s primary design goal]:
https://datafusion.apache.org/user-guide/introduction.html#project-goals
+[dataframe library]: https://datafusion.apache.org/python/
+[command line SQL tool]: https://datafusion.apache.org/user-guide/cli/
+
+[apache datafusion]: https://datafusion.apache.org/
+[apache arrow]: https://arrow.apache.org
+[rust]: https://www.rust-lang.org/
+
+DataFusion's core thesis is that as a community together, we can build much
more
+advanced technology than any of us as individuals or companies could do alone.
+Without DataFusion, highly performant vectorized query engines would remain
+the domain of a few large companies and world-class research institutions.
+With DataFusion, we can all build on top of a shared foundation, and focus on
+what makes our projects unique.
+
+
+# Community Growth 📈
+
+In the last 6 months, between `34.0.0` and `40.0.0`, our community continues to
+grow in new and exciting ways.
+
+1. DataFusion became a top level Apache Software Foundation project (read the
+ [press release] and [blog post]).
+2. We added several PMC members and new
+ committers [@comphead], [@mustafasrepo], [@ozankabak] joined the PMC,
+ [@jonahgao] and [@lewiszlw] joined as a committer. See the [mailing list]
for
+ more details.
+3. [DataFusion Comet] was [donated] and is nearing its first release.
+4. In the [core DataFusion repo] alone we reviewed and accepted almost 1500
PRs from 182 different
+ committers, created over 1000 issues and closed 781 of them 🚀. This is up
+ almost 50% from our last post (1000 PRs from 124 committers with 650 issues
+ created in our last post) 🤯. All changes are listed in the detailed
+ [CHANGELOG].
+5. DataFusion focused meetups happened or are happening in multiple cities
+ around the world: [Austin], [San Francisco], [Hangzhou], [New York], and
+ [Belgrade].
+6. Many new projects started in the [datafusion-contrib] organization,
including
+ [Table Providers], [SQLancer], [Open Variant], [JSON], and [ORC].
+
+[core DataFusion repo]: https://github.com/apache/arrow-datafusion
+[CHANGELOG]:
https://github.com/apache/datafusion/blob/main/datafusion/CHANGELOG.md
+[press release]:
https://news.apache.org/foundation/entry/apache-software-foundation-announces-new-top-level-project-apache-datafusion
+[blog post]: https://datafusion.apache.org/blog/2024/05/07/datafusion-tlp/
+[mailing list]: https://lists.apache.org/list.html?d...@datafusion.apache.org
+[Austin]: https://github.com/apache/datafusion/discussions/8522
+[San Francisco]: https://github.com/apache/datafusion/discussions/10800
+[Hangzhou]: https://www.huodongxing.com/event/5761971909400?td=1965290734055
+[New York]: https://github.com/apache/datafusion/discussions/11213
+[Belgrade]: https://github.com/apache/datafusion/discussions/11431
+[datafusion-contrib]: https://github.com/datafusion-contrib
+[Table Providers]:
https://github.com/datafusion-contrib/datafusion-table-providers
+[SQLancer]: https://github.com/datafusion-contrib/datafusion-sqlancer
+[Open Variant]:
https://github.com/datafusion-contrib/datafusion-functions-variant
+[JSON]: https://github.com/datafusion-contrib/datafusion-functions-json
+[ORC]: https://github.com/datafusion-contrib/datafusion-orc
+
+<!--
+$ git log --pretty=oneline 34.0.0..40.0.0 . | wc -l
+ 1453 (up from 1009)
+
+$ git shortlog -sn 34.0.0..40.0.0 . | wc -l
+ 182 (up from 124)
+
+https://crates.io/crates/datafusion/34.0.0
+DataFusion 34 released Dec 17, 2023
+
+https://crates.io/crates/datafusion/40.0.0
+DataFusion 34 released July 12, 2024
+
+Issues created in this time: 321 open, 781 closed (up from 214 open, 437
closed)
+https://github.com/apache/arrow-datafusion/issues?q=is%3Aissue+created%3A2023-12-17..2024-07-12
+
+Issues closed: 911 (up from 517)
+https://github.com/apache/arrow-datafusion/issues?q=is%3Aissue+closed%3A2023-12-17..2024-07-12
+
+PRs merged in this time 1490 (up from 908)
+https://github.com/apache/arrow-datafusion/pulls?q=is%3Apr+merged%3A2023-12-17..2024-07-12
+
+-->
+
+
+In addition, DataFusion has been appearing publicly more and more, both online
and offline. Here are some highlights:
+
+1. [Apache Arrow DataFusion: A Fast, Embeddable, Modular Analytic Query
Engine], was presented in [SIGMOD '24], one of the major database conferences
+2. As part of the trend to define "the POSIX of databases" in ["What Goes
Around Comes Around... And Around...] from Andy Pavlo and Mike Stonebraker
+3. ["Why you should keep an eye on Apache DataFusion and its community"]
+4. [Apache DataFusion offline meetup in the Bay Area]
+
+
+[DataFusion Comet]: https://datafusion.apache.org/comet/
+[donated]: https://arrow.apache.org/blog/2024/03/06/comet-donation/
+[SIGMOD '24]: https://2024.sigmod.org/
+
+
+[Apache Arrow DataFusion: A Fast, Embeddable, Modular Analytic Query Engine]:
https://dl.acm.org/doi/10.1145/3626246.3653368
+["What Goes Around Comes Around... And Around...]:
https://db.cs.cmu.edu/papers/2024/whatgoesaround-sigmodrec2024.pdf
+["Why you should keep an eye on Apache DataFusion and its community"]:
https://www.cpard.xyz/posts/datafusion/
+[Apache DataFusion offline meetup in the Bay Area]:
https://www.tisonkun.org/2024/07/15/datafusion-meetup-san-francisco/
+
+
+# Improved Performance 🚀
+
+Performance is a key feature of DataFusion, and the community continues to work
+to keep DataFusion state of the art in this area. One major area DataFusion
+improved is the time it takes to convert a SQL query into a plan that can be
+executed. Planning is now almost 2x faster for TPC-DS and TPC-H queries, and
+over 10x faster for some queries with many columns.
+
+Here is a chart showing the improvement due to the concerted effort of many
+contributors including [@jackwener], [@alamb], [@Lordworms], [@dmitrybugakov],
+[@appletreeisyellow], [@ClSlaid], [@rohitrastogi], [@emgeee],
[@kevinmingtarja],
+and [@peter-toth] over several months (see [ticket] for more details)
+
+<img src="{{ site.baseurl
}}/assets/datafusion-40.0.0/improved-planning-time.png" width="700">
+
+[ticket]: https://github.com/apache/datafusion/issues/9637
+
+DataFusion is now up to 40% faster for queries that `GROUP BY` a single string
+or binary column due to a [specialization for single
+Uft8/LargeUtf8/Binary/LargeBinary]. We are working on improving performance
when
+there are [multiple variable length columns in the `GROUP BY` clause].
+
+[specialization for single Uft8/LargeUtf8/Binary/LargeBinary]:
https://github.com/apache/datafusion/pull/8827
+
+We are also in the final phases of [integrating] the new [Arrow StringView]
+which significantly improves performance for workloads that scan, filter and
+group by variable length string and binary data. We expect the improvement to
be
+especially pronounced for Parquet files due to [upstream work in the parquet
+reader]. Kudos to [@XiangpengHong], [@AriesDevil], [@PsiACE], [@Weijun-H],
+[@a10y], and [@RinChanNOWWW] for driving this project.
+
+[integrating]: https://github.com/apache/datafusion/issues/10918
+[Arrow StringView]:
https://docs.rs/arrow/latest/arrow/array/struct.GenericByteViewArray.html
+[multiple variable length columns in the `GROUP BY` clause]:
https://github.com/apache/datafusion/issues/9403
+[upstream work in the parquet reader]:
https://github.com/apache/arrow-rs/issues/5530
+
+# Improved Quality 📋
+
+DataFusion continues to improve overall in quality. In addition to ongoing bug
+fixes, one of the most exciting improvements is the addition of a new
[SQLancer]
+based [DataFusion Fuzzing] suite thanks to [@2010YOUY01] that has already found
+several bugs and thanks to [@jonahgao], [@tshauck], [@xinlifoobar],
+[@LorrensP-2158466] for fixing them so fast.
+
+[DataFusion Fuzzing]: https://github.com/apache/datafusion/issues/11030
+
+
+## Improved Documentation 📚
+
+We continue to improve the documentation to make it easier to get started
using DataFusion with
+the [Library Users Guide], [API documentation], and [Examples].
+
+Some notable new examples include:
+* [sql_analysis.rs] to analyse SQL queries with DataFusion structures (thanks
[@LorrensP-2158466])
+* [function_factory.rs] to create custom functions via SQL (thanks
[@milenkovicm])
+* [plan_to_sql.rs] to generate SQL from DataFusion Expr and LogicalPlan
(thanks [@edmondop])
+* [parquet_index.rs] and [advanced_parquet_index.rs] for parquet indexing,
described more below (thanks [@alamb])
+
+[Library Users Guide]:
https://datafusion.apache.org/library-user-guide/index.html
+[API documentation]: https://docs.rs/datafusion/latest/datafusion/index.html
+[Examples]: https://github.com/apache/datafusion/tree/main/datafusion-examples
+[sql_analysis.rs]:
https://github.com/apache/datafusion/blob/main/datafusion-examples/examples/sql_analysis.rs
+[plan_to_sql.rs]:
https://github.com/apache/datafusion/blob/main/datafusion-examples/examples/plan_to_sql.rs
+
+# New Features ✨
+
+There are too many new features in the last 6 months to list them all, but here
+are some highlights:
+
+## SQL
+* Support for`UNNEST` (thanks [@duongcongtoai], [@JasonLi-cn] and
[@jayzhan211])
+* Support for [Recursive CTEs] (thanks [@jonahgao] and [@matthewgapp])
+* Support for `CREATE FUNCTION` (see below)
+* Many new SQL functions
+
+[Recursive CTEs]: https://github.com/apache/datafusion/issues/462
+
+DataFusion now has much improved support for structured types such a `STRUCT`,
+`LIST`/`ARRAY` and `MAP`. For example, you can now use syntax like:
+
+```rust
+> select {'foo': {'bar': 2}};
++--------------------------------------------------------------+
+| named_struct(Utf8("foo"),named_struct(Utf8("bar"),Int64(2))) |
++--------------------------------------------------------------+
+| {foo: {bar: 2}} |
++--------------------------------------------------------------+
+1 row(s) fetched.
+Elapsed 0.002 seconds.
+```
+
+## SQL Unparser (SQL Formatter)
+
+DataFusion now supports converting `Expr`s and `LogicalPlan`s BACK to SQL text.
+This can be useful in query federation to push predicates down into other
+systems that only accept SQL, and for building systems that generate SQL.
+
+For example, you can now convert a logical expression back to SQL text:
+
+```rust
+// Form a logical expression that represents the SQL "a < 5 OR a = 8"
+let expr = col("a").lt(lit(5)).or(col("a").eq(lit(8)));
+// convert the expression back to SQL text
+let sql = expr_to_sql(&expr)?.to_string();
+assert_eq!(sql, "a < 5 OR a = 8");
+```
+
+You can also do complex things like parsing SQL, modifying the plan, and
convert
+it back to SQL:
+
+```rust
+let df = ctx
+ // Use SQL to read some data from the parquet file
+ .sql("SELECT int_col, double_col, CAST(date_string_col as VARCHAR) FROM
alltypes_plain")
+ .await?;
+// Programmatically add new filters `id > 1 and tinyint_col < double_col`
+let df =
df.filter(col("id").gt(lit(1)).and(col("tinyint_col").lt(col("double_col"))))?
+// Convert the new logical plan back to SQL
+let sql = plan_to_sql(df.logical_plan())?.to_string();
+assert_eq!(sql,
+ "SELECT alltypes_plain.int_col, alltypes_plain.double_col,
CAST(alltypes_plain.date_string_col AS VARCHAR) \
+ FROM alltypes_plain WHERE ((alltypes_plain.id > 1) AND
(alltypes_plain.tinyint_col < alltypes_plain.double_col))")
+);
+```
+
+See the [Plan to SQL example] or the APIs [expr_to_sql] and [plan_to_sql] for
more details.
+
+[expr_to_sql]:
https://docs.rs/datafusion/latest/datafusion/sql/unparser/fn.expr_to_sql.html
+[plan_to_sql]:
https://docs.rs/datafusion/latest/datafusion/sql/unparser/fn.plan_to_sql.html
+[Plan to SQL example]:
https://github.com/apache/datafusion/blob/main/datafusion-examples/examples/plan_to_sql.rs
+
+
+
+## Low Level APIs for Fast Parquet Access (indexing)
+
+With their rising prevalence, supporting efficient access to Parquet files
+stored remotely on object storage is important. Part of doing this efficiently
+is to minimize the number of object stpre requests made by caching metadata and
+skipping over parts of the file that are not needed (e.g. via an index).
+
+DataFusion's Parquet reader has long internally supported advanced predicate
+pushdown by reading the parquet metadata from the file footer and pruning based
+on row group level statistics as well as data page level statistics. DataFusion
+now also supports users supplying their own low level pruning information via
+the [`ParquetAccessPlan`] API.
+
+This API can be used along with index information to selectively skip decoding
+parts of the file. This feature has been used by SpiceAI to add [efficient
Review Comment:
```suggestion
parts of the file. This feature has been used by Spice AI to add [efficient
```
##########
_posts/2024-07-23-datafusion-40.0.0.md:
##########
@@ -0,0 +1,492 @@
+---
+layout: post
+title: "Apache DataFusion 40.0.0 Released"
+date: "2024-07-21 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 %}
+-->
+
+<!-- see https://github.com/apache/datafusion/issues/9602 for details -->
+
+## Introduction
+
+We are proud to announce [DataFusion 40.0.0]. This blog highlights some of the
+many major improvements since we released [DataFusion 34.0.0] and a preview of
+what the community is thinking about in the next 6 months. We are hoping to
make
+more regular blog posts -- if you are interested in helping write them, please
+reach out!
+
+[DataFusion 34.0.0]:
https://datafusion.apache.org/blog/2024/01/19/datafusion-34.0.0/
+[DataFusion 40.0.0]: https://crates.io/crates/datafusion/40.0.0
+
+[Apache DataFusion] is an extensible query engine, written in [Rust], that
+uses [Apache Arrow] as its in-memory format. DataFusion is used by developers
to
+create new, fast data centric systems such as databases, dataframe libraries,
+machine learning and streaming applications. While [DataFusion’s primary design
+goal] is to accelerate the creation of other data centric systems, it has a
+reasonable experience directly out of the box as a [dataframe library] and
+[command line SQL tool].
+
+[DataFusion’s primary design goal]:
https://datafusion.apache.org/user-guide/introduction.html#project-goals
+[dataframe library]: https://datafusion.apache.org/python/
+[command line SQL tool]: https://datafusion.apache.org/user-guide/cli/
+
+[apache datafusion]: https://datafusion.apache.org/
+[apache arrow]: https://arrow.apache.org
+[rust]: https://www.rust-lang.org/
+
+DataFusion's core thesis is that as a community together, we can build much
more
+advanced technology than any of us as individuals or companies could do alone.
+Without DataFusion, highly performant vectorized query engines would remain
+the domain of a few large companies and world-class research institutions.
+With DataFusion, we can all build on top of a shared foundation, and focus on
+what makes our projects unique.
+
+
+# Community Growth 📈
+
+In the last 6 months, between `34.0.0` and `40.0.0`, our community continues to
+grow in new and exciting ways.
+
+1. DataFusion became a top level Apache Software Foundation project (read the
+ [press release] and [blog post]).
+2. We added several PMC members and new
+ committers [@comphead], [@mustafasrepo], [@ozankabak] joined the PMC,
+ [@jonahgao] and [@lewiszlw] joined as a committer. See the [mailing list]
for
+ more details.
+3. [DataFusion Comet] was [donated] and is nearing its first release.
+4. In the [core DataFusion repo] alone we reviewed and accepted almost 1500
PRs from 182 different
+ committers, created over 1000 issues and closed 781 of them 🚀. This is up
+ almost 50% from our last post (1000 PRs from 124 committers with 650 issues
+ created in our last post) 🤯. All changes are listed in the detailed
+ [CHANGELOG].
+5. DataFusion focused meetups happened or are happening in multiple cities
+ around the world: [Austin], [San Francisco], [Hangzhou], [New York], and
+ [Belgrade].
+6. Many new projects started in the [datafusion-contrib] organization,
including
+ [Table Providers], [SQLancer], [Open Variant], [JSON], and [ORC].
+
+[core DataFusion repo]: https://github.com/apache/arrow-datafusion
+[CHANGELOG]:
https://github.com/apache/datafusion/blob/main/datafusion/CHANGELOG.md
+[press release]:
https://news.apache.org/foundation/entry/apache-software-foundation-announces-new-top-level-project-apache-datafusion
+[blog post]: https://datafusion.apache.org/blog/2024/05/07/datafusion-tlp/
+[mailing list]: https://lists.apache.org/list.html?d...@datafusion.apache.org
+[Austin]: https://github.com/apache/datafusion/discussions/8522
+[San Francisco]: https://github.com/apache/datafusion/discussions/10800
+[Hangzhou]: https://www.huodongxing.com/event/5761971909400?td=1965290734055
+[New York]: https://github.com/apache/datafusion/discussions/11213
+[Belgrade]: https://github.com/apache/datafusion/discussions/11431
+[datafusion-contrib]: https://github.com/datafusion-contrib
+[Table Providers]:
https://github.com/datafusion-contrib/datafusion-table-providers
+[SQLancer]: https://github.com/datafusion-contrib/datafusion-sqlancer
+[Open Variant]:
https://github.com/datafusion-contrib/datafusion-functions-variant
+[JSON]: https://github.com/datafusion-contrib/datafusion-functions-json
+[ORC]: https://github.com/datafusion-contrib/datafusion-orc
+
+<!--
+$ git log --pretty=oneline 34.0.0..40.0.0 . | wc -l
+ 1453 (up from 1009)
+
+$ git shortlog -sn 34.0.0..40.0.0 . | wc -l
+ 182 (up from 124)
+
+https://crates.io/crates/datafusion/34.0.0
+DataFusion 34 released Dec 17, 2023
+
+https://crates.io/crates/datafusion/40.0.0
+DataFusion 34 released July 12, 2024
+
+Issues created in this time: 321 open, 781 closed (up from 214 open, 437
closed)
+https://github.com/apache/arrow-datafusion/issues?q=is%3Aissue+created%3A2023-12-17..2024-07-12
+
+Issues closed: 911 (up from 517)
+https://github.com/apache/arrow-datafusion/issues?q=is%3Aissue+closed%3A2023-12-17..2024-07-12
+
+PRs merged in this time 1490 (up from 908)
+https://github.com/apache/arrow-datafusion/pulls?q=is%3Apr+merged%3A2023-12-17..2024-07-12
+
+-->
+
+
+In addition, DataFusion has been appearing publicly more and more, both online
and offline. Here are some highlights:
+
+1. [Apache Arrow DataFusion: A Fast, Embeddable, Modular Analytic Query
Engine], was presented in [SIGMOD '24], one of the major database conferences
+2. As part of the trend to define "the POSIX of databases" in ["What Goes
Around Comes Around... And Around...] from Andy Pavlo and Mike Stonebraker
+3. ["Why you should keep an eye on Apache DataFusion and its community"]
+4. [Apache DataFusion offline meetup in the Bay Area]
+
+
+[DataFusion Comet]: https://datafusion.apache.org/comet/
+[donated]: https://arrow.apache.org/blog/2024/03/06/comet-donation/
+[SIGMOD '24]: https://2024.sigmod.org/
+
+
+[Apache Arrow DataFusion: A Fast, Embeddable, Modular Analytic Query Engine]:
https://dl.acm.org/doi/10.1145/3626246.3653368
+["What Goes Around Comes Around... And Around...]:
https://db.cs.cmu.edu/papers/2024/whatgoesaround-sigmodrec2024.pdf
+["Why you should keep an eye on Apache DataFusion and its community"]:
https://www.cpard.xyz/posts/datafusion/
+[Apache DataFusion offline meetup in the Bay Area]:
https://www.tisonkun.org/2024/07/15/datafusion-meetup-san-francisco/
+
+
+# Improved Performance 🚀
+
+Performance is a key feature of DataFusion, and the community continues to work
+to keep DataFusion state of the art in this area. One major area DataFusion
+improved is the time it takes to convert a SQL query into a plan that can be
+executed. Planning is now almost 2x faster for TPC-DS and TPC-H queries, and
+over 10x faster for some queries with many columns.
+
+Here is a chart showing the improvement due to the concerted effort of many
+contributors including [@jackwener], [@alamb], [@Lordworms], [@dmitrybugakov],
+[@appletreeisyellow], [@ClSlaid], [@rohitrastogi], [@emgeee],
[@kevinmingtarja],
+and [@peter-toth] over several months (see [ticket] for more details)
+
+<img src="{{ site.baseurl
}}/assets/datafusion-40.0.0/improved-planning-time.png" width="700">
+
+[ticket]: https://github.com/apache/datafusion/issues/9637
+
+DataFusion is now up to 40% faster for queries that `GROUP BY` a single string
+or binary column due to a [specialization for single
+Uft8/LargeUtf8/Binary/LargeBinary]. We are working on improving performance
when
+there are [multiple variable length columns in the `GROUP BY` clause].
+
+[specialization for single Uft8/LargeUtf8/Binary/LargeBinary]:
https://github.com/apache/datafusion/pull/8827
+
+We are also in the final phases of [integrating] the new [Arrow StringView]
+which significantly improves performance for workloads that scan, filter and
+group by variable length string and binary data. We expect the improvement to
be
+especially pronounced for Parquet files due to [upstream work in the parquet
+reader]. Kudos to [@XiangpengHong], [@AriesDevil], [@PsiACE], [@Weijun-H],
+[@a10y], and [@RinChanNOWWW] for driving this project.
+
+[integrating]: https://github.com/apache/datafusion/issues/10918
+[Arrow StringView]:
https://docs.rs/arrow/latest/arrow/array/struct.GenericByteViewArray.html
+[multiple variable length columns in the `GROUP BY` clause]:
https://github.com/apache/datafusion/issues/9403
+[upstream work in the parquet reader]:
https://github.com/apache/arrow-rs/issues/5530
+
+# Improved Quality 📋
+
+DataFusion continues to improve overall in quality. In addition to ongoing bug
+fixes, one of the most exciting improvements is the addition of a new
[SQLancer]
+based [DataFusion Fuzzing] suite thanks to [@2010YOUY01] that has already found
+several bugs and thanks to [@jonahgao], [@tshauck], [@xinlifoobar],
+[@LorrensP-2158466] for fixing them so fast.
+
+[DataFusion Fuzzing]: https://github.com/apache/datafusion/issues/11030
+
+
+## Improved Documentation 📚
+
+We continue to improve the documentation to make it easier to get started
using DataFusion with
+the [Library Users Guide], [API documentation], and [Examples].
+
+Some notable new examples include:
+* [sql_analysis.rs] to analyse SQL queries with DataFusion structures (thanks
[@LorrensP-2158466])
+* [function_factory.rs] to create custom functions via SQL (thanks
[@milenkovicm])
+* [plan_to_sql.rs] to generate SQL from DataFusion Expr and LogicalPlan
(thanks [@edmondop])
+* [parquet_index.rs] and [advanced_parquet_index.rs] for parquet indexing,
described more below (thanks [@alamb])
+
+[Library Users Guide]:
https://datafusion.apache.org/library-user-guide/index.html
+[API documentation]: https://docs.rs/datafusion/latest/datafusion/index.html
+[Examples]: https://github.com/apache/datafusion/tree/main/datafusion-examples
+[sql_analysis.rs]:
https://github.com/apache/datafusion/blob/main/datafusion-examples/examples/sql_analysis.rs
+[plan_to_sql.rs]:
https://github.com/apache/datafusion/blob/main/datafusion-examples/examples/plan_to_sql.rs
+
+# New Features ✨
+
+There are too many new features in the last 6 months to list them all, but here
+are some highlights:
+
+## SQL
+* Support for`UNNEST` (thanks [@duongcongtoai], [@JasonLi-cn] and
[@jayzhan211])
+* Support for [Recursive CTEs] (thanks [@jonahgao] and [@matthewgapp])
+* Support for `CREATE FUNCTION` (see below)
+* Many new SQL functions
+
+[Recursive CTEs]: https://github.com/apache/datafusion/issues/462
+
+DataFusion now has much improved support for structured types such a `STRUCT`,
+`LIST`/`ARRAY` and `MAP`. For example, you can now use syntax like:
+
+```rust
+> select {'foo': {'bar': 2}};
++--------------------------------------------------------------+
+| named_struct(Utf8("foo"),named_struct(Utf8("bar"),Int64(2))) |
++--------------------------------------------------------------+
+| {foo: {bar: 2}} |
++--------------------------------------------------------------+
+1 row(s) fetched.
+Elapsed 0.002 seconds.
+```
+
+## SQL Unparser (SQL Formatter)
+
+DataFusion now supports converting `Expr`s and `LogicalPlan`s BACK to SQL text.
+This can be useful in query federation to push predicates down into other
+systems that only accept SQL, and for building systems that generate SQL.
+
+For example, you can now convert a logical expression back to SQL text:
+
+```rust
+// Form a logical expression that represents the SQL "a < 5 OR a = 8"
+let expr = col("a").lt(lit(5)).or(col("a").eq(lit(8)));
+// convert the expression back to SQL text
+let sql = expr_to_sql(&expr)?.to_string();
+assert_eq!(sql, "a < 5 OR a = 8");
+```
+
+You can also do complex things like parsing SQL, modifying the plan, and
convert
+it back to SQL:
+
+```rust
+let df = ctx
+ // Use SQL to read some data from the parquet file
+ .sql("SELECT int_col, double_col, CAST(date_string_col as VARCHAR) FROM
alltypes_plain")
+ .await?;
+// Programmatically add new filters `id > 1 and tinyint_col < double_col`
+let df =
df.filter(col("id").gt(lit(1)).and(col("tinyint_col").lt(col("double_col"))))?
+// Convert the new logical plan back to SQL
+let sql = plan_to_sql(df.logical_plan())?.to_string();
+assert_eq!(sql,
+ "SELECT alltypes_plain.int_col, alltypes_plain.double_col,
CAST(alltypes_plain.date_string_col AS VARCHAR) \
+ FROM alltypes_plain WHERE ((alltypes_plain.id > 1) AND
(alltypes_plain.tinyint_col < alltypes_plain.double_col))")
+);
+```
+
+See the [Plan to SQL example] or the APIs [expr_to_sql] and [plan_to_sql] for
more details.
+
+[expr_to_sql]:
https://docs.rs/datafusion/latest/datafusion/sql/unparser/fn.expr_to_sql.html
+[plan_to_sql]:
https://docs.rs/datafusion/latest/datafusion/sql/unparser/fn.plan_to_sql.html
+[Plan to SQL example]:
https://github.com/apache/datafusion/blob/main/datafusion-examples/examples/plan_to_sql.rs
+
+
+
+## Low Level APIs for Fast Parquet Access (indexing)
+
+With their rising prevalence, supporting efficient access to Parquet files
+stored remotely on object storage is important. Part of doing this efficiently
+is to minimize the number of object stpre requests made by caching metadata and
+skipping over parts of the file that are not needed (e.g. via an index).
+
+DataFusion's Parquet reader has long internally supported advanced predicate
+pushdown by reading the parquet metadata from the file footer and pruning based
+on row group level statistics as well as data page level statistics. DataFusion
+now also supports users supplying their own low level pruning information via
+the [`ParquetAccessPlan`] API.
+
+This API can be used along with index information to selectively skip decoding
+parts of the file. This feature has been used by SpiceAI to add [efficient
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