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Posted to commits@arrow.apache.org by gi...@apache.org on 2023/06/24 11:20:02 UTC
[arrow-site] branch asf-site updated: Updating built site (build 4ad44e6ba1a387182b2b44c21e181cac527bded8)
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new c9a6f8ed365 Updating built site (build 4ad44e6ba1a387182b2b44c21e181cac527bded8)
c9a6f8ed365 is described below
commit c9a6f8ed365fad3a84578891a7ca623d8642c6a7
Author: Andrew Lamb <an...@nerdnetworks.org>
AuthorDate: Sat Jun 24 11:19:57 2023 +0000
Updating built site (build 4ad44e6ba1a387182b2b44c21e181cac527bded8)
---
blog/2023/06/24/datafusion-25.0.0/index.html | 499 +++++++++++++++++++++++++++
blog/index.html | 15 +
docs/c_glib/index.html | 4 +-
feed.xml | 274 ++++++++++++---
release/0.1.0.html | 4 +-
release/0.10.0.html | 4 +-
release/0.11.0.html | 4 +-
release/0.11.1.html | 4 +-
release/0.12.0.html | 4 +-
release/0.13.0.html | 4 +-
release/0.14.0.html | 4 +-
release/0.14.1.html | 4 +-
release/0.15.0.html | 4 +-
release/0.15.1.html | 4 +-
release/0.16.0.html | 4 +-
release/0.17.0.html | 4 +-
release/0.17.1.html | 4 +-
release/0.2.0.html | 4 +-
release/0.3.0.html | 4 +-
release/0.4.0.html | 4 +-
release/0.4.1.html | 4 +-
release/0.5.0.html | 4 +-
release/0.6.0.html | 4 +-
release/0.7.0.html | 4 +-
release/0.7.1.html | 4 +-
release/0.8.0.html | 4 +-
release/0.9.0.html | 4 +-
release/1.0.0.html | 4 +-
release/1.0.1.html | 4 +-
release/10.0.0.html | 4 +-
release/10.0.1.html | 4 +-
release/11.0.0.html | 4 +-
release/12.0.0.html | 4 +-
release/12.0.1.html | 4 +-
release/2.0.0.html | 4 +-
release/3.0.0.html | 4 +-
release/4.0.0.html | 4 +-
release/4.0.1.html | 4 +-
release/5.0.0.html | 4 +-
release/6.0.0.html | 4 +-
release/6.0.1.html | 4 +-
release/7.0.0.html | 4 +-
release/8.0.0.html | 4 +-
release/9.0.0.html | 4 +-
release/index.html | 4 +-
45 files changed, 819 insertions(+), 137 deletions(-)
diff --git a/blog/2023/06/24/datafusion-25.0.0/index.html b/blog/2023/06/24/datafusion-25.0.0/index.html
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@@ -0,0 +1,499 @@
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+<meta name="description" content="It has been a whirlwind 6 months of DataFusion development since our last update: the community has grown, many features have been added, performance improved and we are discussing branching out to our own top level Apache Project. Background Apache Arrow DataFusion is an extensible query engine and database toolkit, written in Rust, that uses Apache Arrow as its in-memory format. DataFusion, along with Apache Calcite, Facebook’s Velox and similar techno [...]
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+
+<h1>
+ Apache Arrow DataFusion 26.0.0
+</h1>
+<hr class="mt-4 mb-3">
+
+
+
+<p class="mb-4 pb-1">
+ <span class="badge badge-secondary">Published</span>
+ <span class="published mr-3">
+ 24 Jun 2023
+ </span>
+ <br />
+ <span class="badge badge-secondary">By</span>
+
+ <a class="mr-3" href="https://arrow.apache.org">The Apache Arrow PMC (pmc) </a>
+
+
+
+</p>
+
+
+ <!--
+
+-->
+
+<p>It has been a whirlwind 6 months of DataFusion development since <a href="https://arrow.apache.org/blog/2023/01/19/datafusion-16.0.0">our
+last update</a>: the community has grown, many features have been added,
+performance improved and we are <a href="https://github.com/apache/arrow-datafusion/discussions/6475">discussing</a> branching out to our own
+top level Apache Project.</p>
+
+<h2 id="background">Background</h2>
+
+<p><a href="https://arrow.apache.org/datafusion/">Apache Arrow DataFusion</a> is an extensible query engine and database
+toolkit, written in <a href="https://www.rust-lang.org/">Rust</a>, that uses <a href="https://arrow.apache.org">Apache Arrow</a> as its in-memory
+format.</p>
+
+<p>DataFusion, along with <a href="https://calcite.apache.org">Apache Calcite</a>, Facebook’s <a href="https://github.com/facebookincubator/velox">Velox</a> and
+similar technology are part of the next generation “<a href="https://www.usenix.org/publications/login/winter2018/khurana">Deconstructed
+Database</a>” architectures, where new systems are built on a foundation
+of fast, modular components, rather as a single tightly integrated
+system.</p>
+
+<p>While single tightly integrated systems such as <a href="https://spark.apache.org/">Spark</a>, <a href="https://duckdb.org">DuckDB</a> and
+<a href="https://www.pola.rs/">Pola.rs</a> are great pieces of technology, our community believes that
+anyone developing new data heavy application, such as those common in
+machine learning in the next 5 years, will <strong>require</strong> a high
+performance, vectorized, query engine to remain relevant. The only
+practical way to gain access to such technology without investing many
+millions of dollars to build a new tightly integrated engine, is
+though open source projects like DataFusion and similar enabling
+technologies such as <a href="https://arrow.apache.org">Apache Arrow</a> and <a href="https://www.rust-lang.org/">Rust</a>.</p>
+
+<p>DataFusion is targeted primarily at developers creating other data
+intensive analytics, and offers:</p>
+
+<ul>
+ <li>High performance, native, parallel streaming execution engine</li>
+ <li>Mature <a href="https://arrow.apache.org/datafusion/user-guide/sql/index.html">SQL support</a>, featuring subqueries, window functions, grouping sets, and more</li>
+ <li>Built in support for Parquet, Avro, CSV, JSON and Arrow formats and easy extension for others</li>
+ <li>Native DataFrame API and <a href="https://arrow.apache.org/datafusion-python/">python bindings</a></li>
+ <li><a href="https://docs.rs/datafusion/latest/datafusion/index.html">Well documented</a> source code and architecture, designed to be customized to suit downstream project needs</li>
+ <li>High quality, easy to use code <a href="https://crates.io/crates/datafusion/versions">released every 2 weeks to crates.io</a></li>
+ <li>Welcoming, open community, governed by the highly regarded and well understood <a href="https://www.apache.org/">Apache Software Foundation</a></li>
+</ul>
+
+<p>The rest of this post highlights some of the improvements we have made
+to DataFusion over the last 6 months and a preview of where we are
+heading. You can see a list of all changes in the detailed
+<a href="https://github.com/apache/arrow-datafusion/blob/main/datafusion/CHANGELOG.md">CHANGELOG</a>.</p>
+
+<h2 id="even-better-performance">(Even) Better Performance</h2>
+
+<p><a href="https://voltrondata.com/resources/speeds-and-feeds-hardware-and-software-matter">Various</a> benchmarks show DataFusion to be quite close or <a href="https://github.com/tustvold/access-log-bench">even
+faster</a> to the state of the art in analytic performance (at the moment
+this seems to be DuckDB). We continually work on improving performance
+(see <a href="https://github.com/apache/arrow-datafusion/issues/5546">#5546</a> for a list) and would love additional help in this area.</p>
+
+<p>DataFusion now reads single large Parquet files significantly faster by
+<a href="https://github.com/apache/arrow-datafusion/pull/5057">parallelizing across multiple cores</a>. Native speeds for reading JSON
+and CSV files are also up to 2.5x faster thanks to improvements
+upstream in arrow-rs <a href="https://github.com/apache/arrow-rs/pull/3479#issuecomment-1384353159">JSON reader</a> and <a href="https://github.com/apache/arrow-rs/pull/3365">CSV reader</a>.</p>
+
+<p>Also, we have integrated the <a href="https://arrow.apache.org/blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-1/">arrow-rs Row Format</a> into DataFusion resulting in up to <a href="https://github.com/apache/arrow-datafusion/pull/6163">2-3x faster sorting and merging</a>.</p>
+
+<h2 id="improved-documentation-and-website">Improved Documentation and Website</h2>
+
+<p>Part of growing the DataFusion community is ensuring that DataFusion’s
+features are understood and that it is easy to contribute and
+participate. To that end the <a href="https://arrow.apache.org/datafusion/">website</a> has been cleaned up, <a href="https://docs.rs/datafusion/latest/datafusion/index.html#architecture">the
+architecture guide</a> expanded, the <a href="https://arrow.apache.org/datafusion/contributor-guide/roadmap.html">roadmap</a> updated, and several
+overview talks created:</p>
+
+<ul>
+ <li>Apr 2023 <em>Query Engine</em>: <a href="https://youtu.be/NVKujPxwSBA">recording</a> and <a href="https://docs.google.com/presentation/d/1D3GDVas-8y0sA4c8EOgdCvEjVND4s2E7I6zfs67Y4j8/edit#slide=id.p">slides</a></li>
+ <li>April 2023 <em>Logical Plan and Expressions</em>: <a href="https://youtu.be/EzZTLiSJnhY">recording</a> and <a href="https://docs.google.com/presentation/d/1ypylM3-w60kVDW7Q6S99AHzvlBgciTdjsAfqNP85K30">slides</a></li>
+ <li>April 2023 <em>Physical Plan and Execution</em>: <a href="https://youtu.be/2jkWU3_w6z0">recording</a> and <a href="https://docs.google.com/presentation/d/1cA2WQJ2qg6tx6y4Wf8FH2WVSm9JQ5UgmBWATHdik0hg">slides</a></li>
+</ul>
+
+<h2 id="new-features">New Features</h2>
+
+<h3 id="more-streaming-less-memory">More Streaming, Less Memory</h3>
+
+<p>We have made significany progress on the <a href="https://github.com/apache/arrow-datafusion/issues/4285">streaming execution roadmap</a>
+such as <a href="https://docs.rs/datafusion/latest/datafusion/physical_plan/trait.ExecutionPlan.html#method.unbounded_output">unbounded datasources</a>, <a href="https://docs.rs/datafusion/latest/datafusion/physical_plan/aggregates/enum.GroupByOrderMode.html">streaming group by</a>, sophisticated
+<a href="https://docs.rs/datafusion/latest/datafusion/physical_optimizer/global_sort_selection/index.html">sort</a> and <a href="https://docs.rs/datafusion/latest/datafusion/physical_optimizer/repartition/index.html">repartitioning</a> improvements in the optimizer, and support
+for <a href="https://docs.rs/datafusion/latest/datafusion/physical_plan/joins/struct.SymmetricHashJoinExec.html">symmetric hash join</a> (read more about that in the great <a href="https://github.com/apache/arrow-datafusion/issues/4285">Synnada
+Blog Post</a> on the topic). Together, these features both 1) make it
+easier to build streaming systems using DataFusion that can
+incrementally generate output before (or ever) seeing the end of the
+input and 2) allow general queries to use less memory and generate their
+results faster.</p>
+
+<p>We have also improved the runtime <a href="https://docs.rs/datafusion/latest/datafusion/execution/memory_pool/index.html">memory management</a> system so that
+DataFusion now stays within its declared memory budget <a href="https://github.com/apache/arrow-datafusion/issues/3941">generate
+runtime errors</a>.</p>
+
+<h3 id="dml-support-insert-delete-update-etc">DML Support (<code class="language-plaintext highlighter-rouge">INSERT</code>, <code class="language-plaintext highlighter-rouge">DELETE</code>, <code class="language-plaintext highlighter-rouge">UPDATE</code>, etc)</h3>
+
+<p>Part of building high performance data systems includes writing data,
+and DataFusion supports several features for creating new files:</p>
+
+<ul>
+ <li><code class="language-plaintext highlighter-rouge">INSERT INTO</code> and <code class="language-plaintext highlighter-rouge">SELECT ... INTO </code> support for memory backed and CSV tables</li>
+ <li>New <a href="https://docs.rs/datafusion/latest/datafusion/physical_plan/insert/trait.DataSink.html">API for writing data into TableProviders</a></li>
+</ul>
+
+<p>We are working on easier to use <a href="https://github.com/apache/arrow-datafusion/issues/5654">COPY INTO</a> syntax, better support
+for writing parquet, JSON, and AVRO, and more – see our <a href="https://github.com/apache/arrow-datafusion/issues/6569">tracking epic</a>
+for more details.</p>
+
+<h3 id="timestamp-and-intervals">Timestamp and Intervals</h3>
+
+<p>One mark of the maturity of a SQL engine is how it handles the tricky
+world of timestamp, date, times and interval arithmetic. DataFusion is
+feature complete in this area and behaves as you would expect,
+supporting queries such as</p>
+
+<div class="language-sql highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="k">SELECT</span> <span class="n">now</span><span class="p">()</span> <span class="o">+</span> <span class="s1">'1 month'</span> <span class="k">FROM</span> <span class="n">my_table</span><span class="p">;</span>
+</code></pre></div></div>
+
+<p>We still have a long tail of <a href="https://github.com/apache/arrow-datafusion/issues/3148">date and time improvements</a>, which we are working on as well.</p>
+
+<h3 id="querying-structured-types-list-and-structs">Querying Structured Types (<code class="language-plaintext highlighter-rouge">List</code> and <code class="language-plaintext highlighter-rouge">Struct</code>s)</h3>
+
+<p>Arrow and Parquet <a href="https://arrow.apache.org/blog/2022/10/08/arrow-parquet-encoding-part-2/">support nested data</a> well and DataFusion lets you
+easily query such <code class="language-plaintext highlighter-rouge">Struct</code> and <code class="language-plaintext highlighter-rouge">List</code>. For example, you can use
+DataFusion to read and query the <a href="https://data.mendeley.com/datasets/ct8f9skv97">JSON Datasets for Exploratory OLAP -
+Mendeley Data</a> like this:</p>
+
+<div class="language-sql highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="c1">----------</span>
+<span class="c1">-- Explore structured data using SQL</span>
+<span class="c1">----------</span>
+<span class="k">SELECT</span> <span class="k">delete</span> <span class="k">FROM</span> <span class="s1">'twitter-sample-head-100000.parquet'</span> <span class="k">WHERE</span> <span class="k">delete</span> <span class="k">IS</span> <span class="k">NOT</span> <span class="k">NULL</span> <span class="k">limit</span> <span class="mi">10</span><span class="p">;</span>
+<span class="o">+</span><span class="c1">---------------------------------------------------------------------------------------------------------------------------+</span>
+<span class="o">|</span> <span class="k">delete</span> <span class="o">|</span>
+<span class="o">+</span><span class="c1">---------------------------------------------------------------------------------------------------------------------------+</span>
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">135037425050320896</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">135037425050320896</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">134703982051463168</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">134703982051463168</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">134773741740765184</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">134773741740765184</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">132543659655704576</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">132543659655704576</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">133786431926697984</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">133786431926697984</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">134619093570560002</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">134619093570560002</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">134019857527214080</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">134019857527214080</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">133931546469076993</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">133931546469076993</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">134397743350296576</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">134397743350296576</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">127833661767823360</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">127833661767823360</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">+</span><span class="c1">---------------------------------------------------------------------------------------------------------------------------+</span>
+
+<span class="c1">----------</span>
+<span class="c1">-- Select some deeply nested fields</span>
+<span class="c1">----------</span>
+<span class="k">SELECT</span>
+ <span class="k">delete</span><span class="p">[</span><span class="s1">'status'</span><span class="p">][</span><span class="s1">'id'</span><span class="p">][</span><span class="s1">'$numberLong'</span><span class="p">]</span> <span class="k">as</span> <span class="n">delete_id</span><span class="p">,</span>
+ <span class="k">delete</span><span class="p">[</span><span class="s1">'status'</span><span class="p">][</span><span class="s1">'user_id'</span><span class="p">]</span> <span class="k">as</span> <span class="n">delete_user_id</span>
+<span class="k">FROM</span> <span class="s1">'twitter-sample-head-100000.parquet'</span> <span class="k">WHERE</span> <span class="k">delete</span> <span class="k">IS</span> <span class="k">NOT</span> <span class="k">NULL</span> <span class="k">LIMIT</span> <span class="mi">10</span><span class="p">;</span>
+
+<span class="o">+</span><span class="c1">--------------------+----------------+</span>
+<span class="o">|</span> <span class="n">delete_id</span> <span class="o">|</span> <span class="n">delete_user_id</span> <span class="o">|</span>
+<span class="o">+</span><span class="c1">--------------------+----------------+</span>
+<span class="o">|</span> <span class="mi">135037425050320896</span> <span class="o">|</span> <span class="mi">334902461</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">134703982051463168</span> <span class="o">|</span> <span class="mi">405383453</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">134773741740765184</span> <span class="o">|</span> <span class="mi">64823441</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">132543659655704576</span> <span class="o">|</span> <span class="mi">45917834</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">133786431926697984</span> <span class="o">|</span> <span class="mi">67229952</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">134619093570560002</span> <span class="o">|</span> <span class="mi">182430773</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">134019857527214080</span> <span class="o">|</span> <span class="mi">257396311</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">133931546469076993</span> <span class="o">|</span> <span class="mi">124539548</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">134397743350296576</span> <span class="o">|</span> <span class="mi">139836391</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">127833661767823360</span> <span class="o">|</span> <span class="mi">244442687</span> <span class="o">|</span>
+<span class="o">+</span><span class="c1">--------------------+----------------+</span>
+</code></pre></div></div>
+
+<h3 id="subqueries-all-the-way-down">Subqueries All the Way Down</h3>
+
+<p>DataFusion can run many different subqueries by rewriting them to
+joins. It has been able to run the full suite of TPC-H queries for at
+least the last year, but recently we have implemented significant
+improvements to this logic, sufficient to run almost all queries in
+the TPC-DS benchmark as well.</p>
+
+<h2 id="community-and-project-growth">Community and Project Growth</h2>
+
+<p>The six months since <a href="https://arrow.apache.org/blog/2023/01/19/datafusion-16.0.0">our last update</a> saw significant growth in
+the DataFusion community. Between versions <code class="language-plaintext highlighter-rouge">17.0.0</code> and <code class="language-plaintext highlighter-rouge">26.0.0</code>,
+DataFusion merged 711 PRs from 107 distinct contributors, not
+including all the work that goes into our core dependencies such as
+<a href="https://crates.io/crates/arrow">arrow</a>,
+<a href="https://crates.io/crates/parquet">parquet</a>, and
+<a href="https://crates.io/crates/object_store">object_store</a>, that much of
+the same community helps support.</p>
+
+<p>In addition, we have added 7 new committers and 1 new PMC member to
+the Apache Arrow project, largely focused on DataFusion, and we
+learned about some of the cool <a href="https://arrow.apache.org/datafusion/user-guide/introduction.html#known-users">new systems</a> which are using
+DataFusion. Given the growth of the community and interest in the
+project, we also clarified the <a href="https://github.com/apache/arrow-datafusion/discussions/6441">mission statement</a> and are
+<a href="https://github.com/apache/arrow-datafusion/discussions/6475">discussing</a> “graduate”ing DataFusion to a new top level
+Apache Software Foundation project.</p>
+
+<!--
+$ git log --pretty=oneline 17.0.0..26.0.0 . | wc -l
+ 711
+
+$ git shortlog -sn 17.0.0..26.0.0 . | wc -l
+ 107
+-->
+
+<h1 id="how-to-get-involved">How to Get Involved</h1>
+
+<p>Kudos to everyone in the community who has contributed ideas,
+discussions, bug reports, documentation and code. It is exciting to be
+innovating on the next generation of database architectures together!</p>
+
+<p>If you are interested in contributing to DataFusion, we would love to
+have you join us. You can try out DataFusion on some of your own
+data and projects and let us know how it goes or contribute a PR with
+documentation, tests or code. A list of open issues suitable for
+beginners is <a href="https://github.com/apache/arrow-datafusion/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22">here</a>.</p>
+
+<p>Check out our <a href="https://arrow.apache.org/datafusion/contributor-guide/communication.html">Communication Doc</a> for more ways to engage with the
+community.</p>
+
+
+ </main>
+ </div>
+
+ <hr/>
+<footer class="footer">
+ <div class="row">
+ <div class="col-md-9">
+ <p>Apache Arrow, Arrow, Apache, the Apache feather logo, and the Apache Arrow project logo are either registered trademarks or trademarks of The Apache Software Foundation in the United States and other countries.</p>
+ <p>© 2016-2023 The Apache Software Foundation</p>
+ </div>
+ <div class="col-md-3">
+ <a class="d-sm-none d-md-inline pr-2" href="https://www.apache.org/events/current-event.html">
+ <img src="https://www.apache.org/events/current-event-234x60.png"/>
+ </a>
+ </div>
+ </div>
+</footer>
+
+ </div>
+</body>
+</html>
diff --git a/blog/index.html b/blog/index.html
index 0730a122bf5..7becfec9319 100644
--- a/blog/index.html
+++ b/blog/index.html
@@ -236,6 +236,21 @@
+ <p>
+ <h3>
+ <a href="/blog/2023/06/24/datafusion-25.0.0/">Apache Arrow DataFusion 26.0.0</a>
+ </h3>
+
+ <p>
+ <span class="blog-list-date">
+ 24 June 2023
+ </span>
+ </p>
+ It has been a whirlwind 6 months of DataFusion development since our last update: the community has grown, many features have been added, performance improved and we are discussing branching out to our own top level Apache Project. Background Apache Arrow DataFusion is an extensible query engine and database toolkit,...
+ </p>
+
+
+
<p>
<h3>
<a href="/blog/2023/06/22/nanoarrow-0.120-release/">Apache Arrow nanoarrow 0.2 Release</a>
diff --git a/docs/c_glib/index.html b/docs/c_glib/index.html
index d5ad91debb5..baa0c2480e0 100644
--- a/docs/c_glib/index.html
+++ b/docs/c_glib/index.html
@@ -20,13 +20,13 @@
<meta property="og:site_name" content="Apache Arrow" />
<meta property="og:image" content="https://arrow.apache.org/img/arrow-logo_horizontal_black-txt_white-bg.png" />
<meta property="og:type" content="article" />
-<meta property="article:published_time" content="2023-06-23T06:56:03-04:00" />
+<meta property="article:published_time" content="2023-06-24T07:15:15-04:00" />
<meta name="twitter:card" content="summary_large_image" />
<meta property="twitter:image" content="https://arrow.apache.org/img/arrow-logo_horizontal_black-txt_white-bg.png" />
<meta property="twitter:title" content="Apache Arrow GLib (C)" />
<meta name="twitter:site" content="@ApacheArrow" />
<script type="application/ld+json">
-{"@context":"https://schema.org","@type":"BlogPosting","dateModified":"2023-06-23T06:56:03-04:00","datePublished":"2023-06-23T06:56:03-04:00","description":"Apache Arrow GLib (C) Apache Arrow GLib is a wrapper library for Apache Arrow C++. Apache Arrow GLib provides C API. Apache Arrow GLib supports GObject Introspection. It means that you can create language bindings at runtime or compile time automatically. API reference manuals Apache Arrow GLib Apache Parquet GLib Gandiva GLib Plasma [...]
+{"@context":"https://schema.org","@type":"BlogPosting","dateModified":"2023-06-24T07:15:15-04:00","datePublished":"2023-06-24T07:15:15-04:00","description":"Apache Arrow GLib (C) Apache Arrow GLib is a wrapper library for Apache Arrow C++. Apache Arrow GLib provides C API. Apache Arrow GLib supports GObject Introspection. It means that you can create language bindings at runtime or compile time automatically. API reference manuals Apache Arrow GLib Apache Parquet GLib Gandiva GLib Plasma [...]
<!-- End Jekyll SEO tag -->
diff --git a/feed.xml b/feed.xml
index f5f1a823925..37b8d989233 100644
--- a/feed.xml
+++ b/feed.xml
@@ -1,4 +1,223 @@
-<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="4.2.0">Jekyll</generator><link href="https://arrow.apache.org/feed.xml" rel="self" type="application/atom+xml" /><link href="https://arrow.apache.org/" rel="alternate" type="text/html" /><updated>2023-06-23T06:56:03-04:00</updated><id>https://arrow.apache.org/feed.xml</id><title type="html">Apache Arrow</title><subtitle>Apache Arrow is a cross-language developm [...]
+<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="4.2.0">Jekyll</generator><link href="https://arrow.apache.org/feed.xml" rel="self" type="application/atom+xml" /><link href="https://arrow.apache.org/" rel="alternate" type="text/html" /><updated>2023-06-24T07:15:15-04:00</updated><id>https://arrow.apache.org/feed.xml</id><title type="html">Apache Arrow</title><subtitle>Apache Arrow is a cross-language developm [...]
+
+-->
+
+<p>It has been a whirlwind 6 months of DataFusion development since <a href="https://arrow.apache.org/blog/2023/01/19/datafusion-16.0.0">our
+last update</a>: the community has grown, many features have been added,
+performance improved and we are <a href="https://github.com/apache/arrow-datafusion/discussions/6475">discussing</a> branching out to our own
+top level Apache Project.</p>
+
+<h2 id="background">Background</h2>
+
+<p><a href="https://arrow.apache.org/datafusion/">Apache Arrow DataFusion</a> is an extensible query engine and database
+toolkit, written in <a href="https://www.rust-lang.org/">Rust</a>, that uses <a href="https://arrow.apache.org">Apache Arrow</a> as its in-memory
+format.</p>
+
+<p>DataFusion, along with <a href="https://calcite.apache.org">Apache Calcite</a>, Facebook’s <a href="https://github.com/facebookincubator/velox">Velox</a> and
+similar technology are part of the next generation “<a href="https://www.usenix.org/publications/login/winter2018/khurana">Deconstructed
+Database</a>” architectures, where new systems are built on a foundation
+of fast, modular components, rather as a single tightly integrated
+system.</p>
+
+<p>While single tightly integrated systems such as <a href="https://spark.apache.org/">Spark</a>, <a href="https://duckdb.org">DuckDB</a> and
+<a href="https://www.pola.rs/">Pola.rs</a> are great pieces of technology, our community believes that
+anyone developing new data heavy application, such as those common in
+machine learning in the next 5 years, will <strong>require</strong> a high
+performance, vectorized, query engine to remain relevant. The only
+practical way to gain access to such technology without investing many
+millions of dollars to build a new tightly integrated engine, is
+though open source projects like DataFusion and similar enabling
+technologies such as <a href="https://arrow.apache.org">Apache Arrow</a> and <a href="https://www.rust-lang.org/">Rust</a>.</p>
+
+<p>DataFusion is targeted primarily at developers creating other data
+intensive analytics, and offers:</p>
+
+<ul>
+ <li>High performance, native, parallel streaming execution engine</li>
+ <li>Mature <a href="https://arrow.apache.org/datafusion/user-guide/sql/index.html">SQL support</a>, featuring subqueries, window functions, grouping sets, and more</li>
+ <li>Built in support for Parquet, Avro, CSV, JSON and Arrow formats and easy extension for others</li>
+ <li>Native DataFrame API and <a href="https://arrow.apache.org/datafusion-python/">python bindings</a></li>
+ <li><a href="https://docs.rs/datafusion/latest/datafusion/index.html">Well documented</a> source code and architecture, designed to be customized to suit downstream project needs</li>
+ <li>High quality, easy to use code <a href="https://crates.io/crates/datafusion/versions">released every 2 weeks to crates.io</a></li>
+ <li>Welcoming, open community, governed by the highly regarded and well understood <a href="https://www.apache.org/">Apache Software Foundation</a></li>
+</ul>
+
+<p>The rest of this post highlights some of the improvements we have made
+to DataFusion over the last 6 months and a preview of where we are
+heading. You can see a list of all changes in the detailed
+<a href="https://github.com/apache/arrow-datafusion/blob/main/datafusion/CHANGELOG.md">CHANGELOG</a>.</p>
+
+<h2 id="even-better-performance">(Even) Better Performance</h2>
+
+<p><a href="https://voltrondata.com/resources/speeds-and-feeds-hardware-and-software-matter">Various</a> benchmarks show DataFusion to be quite close or <a href="https://github.com/tustvold/access-log-bench">even
+faster</a> to the state of the art in analytic performance (at the moment
+this seems to be DuckDB). We continually work on improving performance
+(see <a href="https://github.com/apache/arrow-datafusion/issues/5546">#5546</a> for a list) and would love additional help in this area.</p>
+
+<p>DataFusion now reads single large Parquet files significantly faster by
+<a href="https://github.com/apache/arrow-datafusion/pull/5057">parallelizing across multiple cores</a>. Native speeds for reading JSON
+and CSV files are also up to 2.5x faster thanks to improvements
+upstream in arrow-rs <a href="https://github.com/apache/arrow-rs/pull/3479#issuecomment-1384353159">JSON reader</a> and <a href="https://github.com/apache/arrow-rs/pull/3365">CSV reader</a>.</p>
+
+<p>Also, we have integrated the <a href="https://arrow.apache.org/blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-1/">arrow-rs Row Format</a> into DataFusion resulting in up to <a href="https://github.com/apache/arrow-datafusion/pull/6163">2-3x faster sorting and merging</a>.</p>
+
+<h2 id="improved-documentation-and-website">Improved Documentation and Website</h2>
+
+<p>Part of growing the DataFusion community is ensuring that DataFusion’s
+features are understood and that it is easy to contribute and
+participate. To that end the <a href="https://arrow.apache.org/datafusion/">website</a> has been cleaned up, <a href="https://docs.rs/datafusion/latest/datafusion/index.html#architecture">the
+architecture guide</a> expanded, the <a href="https://arrow.apache.org/datafusion/contributor-guide/roadmap.html">roadmap</a> updated, and several
+overview talks created:</p>
+
+<ul>
+ <li>Apr 2023 <em>Query Engine</em>: <a href="https://youtu.be/NVKujPxwSBA">recording</a> and <a href="https://docs.google.com/presentation/d/1D3GDVas-8y0sA4c8EOgdCvEjVND4s2E7I6zfs67Y4j8/edit#slide=id.p">slides</a></li>
+ <li>April 2023 <em>Logical Plan and Expressions</em>: <a href="https://youtu.be/EzZTLiSJnhY">recording</a> and <a href="https://docs.google.com/presentation/d/1ypylM3-w60kVDW7Q6S99AHzvlBgciTdjsAfqNP85K30">slides</a></li>
+ <li>April 2023 <em>Physical Plan and Execution</em>: <a href="https://youtu.be/2jkWU3_w6z0">recording</a> and <a href="https://docs.google.com/presentation/d/1cA2WQJ2qg6tx6y4Wf8FH2WVSm9JQ5UgmBWATHdik0hg">slides</a></li>
+</ul>
+
+<h2 id="new-features">New Features</h2>
+
+<h3 id="more-streaming-less-memory">More Streaming, Less Memory</h3>
+
+<p>We have made significany progress on the <a href="https://github.com/apache/arrow-datafusion/issues/4285">streaming execution roadmap</a>
+such as <a href="https://docs.rs/datafusion/latest/datafusion/physical_plan/trait.ExecutionPlan.html#method.unbounded_output">unbounded datasources</a>, <a href="https://docs.rs/datafusion/latest/datafusion/physical_plan/aggregates/enum.GroupByOrderMode.html">streaming group by</a>, sophisticated
+<a href="https://docs.rs/datafusion/latest/datafusion/physical_optimizer/global_sort_selection/index.html">sort</a> and <a href="https://docs.rs/datafusion/latest/datafusion/physical_optimizer/repartition/index.html">repartitioning</a> improvements in the optimizer, and support
+for <a href="https://docs.rs/datafusion/latest/datafusion/physical_plan/joins/struct.SymmetricHashJoinExec.html">symmetric hash join</a> (read more about that in the great <a href="https://github.com/apache/arrow-datafusion/issues/4285">Synnada
+Blog Post</a> on the topic). Together, these features both 1) make it
+easier to build streaming systems using DataFusion that can
+incrementally generate output before (or ever) seeing the end of the
+input and 2) allow general queries to use less memory and generate their
+results faster.</p>
+
+<p>We have also improved the runtime <a href="https://docs.rs/datafusion/latest/datafusion/execution/memory_pool/index.html">memory management</a> system so that
+DataFusion now stays within its declared memory budget <a href="https://github.com/apache/arrow-datafusion/issues/3941">generate
+runtime errors</a>.</p>
+
+<h3 id="dml-support-insert-delete-update-etc">DML Support (<code class="language-plaintext highlighter-rouge">INSERT</code>, <code class="language-plaintext highlighter-rouge">DELETE</code>, <code class="language-plaintext highlighter-rouge">UPDATE</code>, etc)</h3>
+
+<p>Part of building high performance data systems includes writing data,
+and DataFusion supports several features for creating new files:</p>
+
+<ul>
+ <li><code class="language-plaintext highlighter-rouge">INSERT INTO</code> and <code class="language-plaintext highlighter-rouge">SELECT ... INTO </code> support for memory backed and CSV tables</li>
+ <li>New <a href="https://docs.rs/datafusion/latest/datafusion/physical_plan/insert/trait.DataSink.html">API for writing data into TableProviders</a></li>
+</ul>
+
+<p>We are working on easier to use <a href="https://github.com/apache/arrow-datafusion/issues/5654">COPY INTO</a> syntax, better support
+for writing parquet, JSON, and AVRO, and more – see our <a href="https://github.com/apache/arrow-datafusion/issues/6569">tracking epic</a>
+for more details.</p>
+
+<h3 id="timestamp-and-intervals">Timestamp and Intervals</h3>
+
+<p>One mark of the maturity of a SQL engine is how it handles the tricky
+world of timestamp, date, times and interval arithmetic. DataFusion is
+feature complete in this area and behaves as you would expect,
+supporting queries such as</p>
+
+<div class="language-sql highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="k">SELECT</span> <span class="n">now</span><span class="p">()</span> <span class="o">+</span> <span class="s1">'1 month'</span> <span class="k">FROM</span> <span class="n">my_table</span><span class="p">;</span>
+</code></pre></div></div>
+
+<p>We still have a long tail of <a href="https://github.com/apache/arrow-datafusion/issues/3148">date and time improvements</a>, which we are working on as well.</p>
+
+<h3 id="querying-structured-types-list-and-structs">Querying Structured Types (<code class="language-plaintext highlighter-rouge">List</code> and <code class="language-plaintext highlighter-rouge">Struct</code>s)</h3>
+
+<p>Arrow and Parquet <a href="https://arrow.apache.org/blog/2022/10/08/arrow-parquet-encoding-part-2/">support nested data</a> well and DataFusion lets you
+easily query such <code class="language-plaintext highlighter-rouge">Struct</code> and <code class="language-plaintext highlighter-rouge">List</code>. For example, you can use
+DataFusion to read and query the <a href="https://data.mendeley.com/datasets/ct8f9skv97">JSON Datasets for Exploratory OLAP -
+Mendeley Data</a> like this:</p>
+
+<div class="language-sql highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="c1">----------</span>
+<span class="c1">-- Explore structured data using SQL</span>
+<span class="c1">----------</span>
+<span class="k">SELECT</span> <span class="k">delete</span> <span class="k">FROM</span> <span class="s1">'twitter-sample-head-100000.parquet'</span> <span class="k">WHERE</span> <span class="k">delete</span> <span class="k">IS</span> <span class="k">NOT</span> <span class="k">NULL</span> <span class="k">limit</span> <span class="mi">10</span><span class="p">;</span>
+<span class="o">+</span><span class="c1">---------------------------------------------------------------------------------------------------------------------------+</span>
+<span class="o">|</span> <span class="k">delete</span> <span class="o">|</span>
+<span class="o">+</span><span class="c1">---------------------------------------------------------------------------------------------------------------------------+</span>
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">135037425050320896</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">135037425050320896</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">134703982051463168</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">134703982051463168</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">134773741740765184</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">134773741740765184</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">132543659655704576</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">132543659655704576</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">133786431926697984</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">133786431926697984</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">134619093570560002</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">134619093570560002</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">134019857527214080</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">134019857527214080</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">133931546469076993</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">133931546469076993</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">134397743350296576</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">134397743350296576</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">|</span> <span class="p">{</span><span class="n">status</span><span class="p">:</span> <span class="p">{</span><span class="n">id</span><span class="p">:</span> <span class="p">{</span><span class="err">$</span><span class="n">numberLong</span><span class="p">:</span> <span class="mi">127833661767823360</span><span class="p">},</span> <span class="n">id_str</span><span class="p">:</span> <span class="mi">127833661767823360</span><span class="p">,</span> <span class="n">us [...]
+<span class="o">+</span><span class="c1">---------------------------------------------------------------------------------------------------------------------------+</span>
+
+<span class="c1">----------</span>
+<span class="c1">-- Select some deeply nested fields</span>
+<span class="c1">----------</span>
+<span class="k">SELECT</span>
+ <span class="k">delete</span><span class="p">[</span><span class="s1">'status'</span><span class="p">][</span><span class="s1">'id'</span><span class="p">][</span><span class="s1">'$numberLong'</span><span class="p">]</span> <span class="k">as</span> <span class="n">delete_id</span><span class="p">,</span>
+ <span class="k">delete</span><span class="p">[</span><span class="s1">'status'</span><span class="p">][</span><span class="s1">'user_id'</span><span class="p">]</span> <span class="k">as</span> <span class="n">delete_user_id</span>
+<span class="k">FROM</span> <span class="s1">'twitter-sample-head-100000.parquet'</span> <span class="k">WHERE</span> <span class="k">delete</span> <span class="k">IS</span> <span class="k">NOT</span> <span class="k">NULL</span> <span class="k">LIMIT</span> <span class="mi">10</span><span class="p">;</span>
+
+<span class="o">+</span><span class="c1">--------------------+----------------+</span>
+<span class="o">|</span> <span class="n">delete_id</span> <span class="o">|</span> <span class="n">delete_user_id</span> <span class="o">|</span>
+<span class="o">+</span><span class="c1">--------------------+----------------+</span>
+<span class="o">|</span> <span class="mi">135037425050320896</span> <span class="o">|</span> <span class="mi">334902461</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">134703982051463168</span> <span class="o">|</span> <span class="mi">405383453</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">134773741740765184</span> <span class="o">|</span> <span class="mi">64823441</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">132543659655704576</span> <span class="o">|</span> <span class="mi">45917834</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">133786431926697984</span> <span class="o">|</span> <span class="mi">67229952</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">134619093570560002</span> <span class="o">|</span> <span class="mi">182430773</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">134019857527214080</span> <span class="o">|</span> <span class="mi">257396311</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">133931546469076993</span> <span class="o">|</span> <span class="mi">124539548</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">134397743350296576</span> <span class="o">|</span> <span class="mi">139836391</span> <span class="o">|</span>
+<span class="o">|</span> <span class="mi">127833661767823360</span> <span class="o">|</span> <span class="mi">244442687</span> <span class="o">|</span>
+<span class="o">+</span><span class="c1">--------------------+----------------+</span>
+</code></pre></div></div>
+
+<h3 id="subqueries-all-the-way-down">Subqueries All the Way Down</h3>
+
+<p>DataFusion can run many different subqueries by rewriting them to
+joins. It has been able to run the full suite of TPC-H queries for at
+least the last year, but recently we have implemented significant
+improvements to this logic, sufficient to run almost all queries in
+the TPC-DS benchmark as well.</p>
+
+<h2 id="community-and-project-growth">Community and Project Growth</h2>
+
+<p>The six months since <a href="https://arrow.apache.org/blog/2023/01/19/datafusion-16.0.0">our last update</a> saw significant growth in
+the DataFusion community. Between versions <code class="language-plaintext highlighter-rouge">17.0.0</code> and <code class="language-plaintext highlighter-rouge">26.0.0</code>,
+DataFusion merged 711 PRs from 107 distinct contributors, not
+including all the work that goes into our core dependencies such as
+<a href="https://crates.io/crates/arrow">arrow</a>,
+<a href="https://crates.io/crates/parquet">parquet</a>, and
+<a href="https://crates.io/crates/object_store">object_store</a>, that much of
+the same community helps support.</p>
+
+<p>In addition, we have added 7 new committers and 1 new PMC member to
+the Apache Arrow project, largely focused on DataFusion, and we
+learned about some of the cool <a href="https://arrow.apache.org/datafusion/user-guide/introduction.html#known-users">new systems</a> which are using
+DataFusion. Given the growth of the community and interest in the
+project, we also clarified the <a href="https://github.com/apache/arrow-datafusion/discussions/6441">mission statement</a> and are
+<a href="https://github.com/apache/arrow-datafusion/discussions/6475">discussing</a> “graduate”ing DataFusion to a new top level
+Apache Software Foundation project.</p>
+
+<!--
+$ git log --pretty=oneline 17.0.0..26.0.0 . | wc -l
+ 711
+
+$ git shortlog -sn 17.0.0..26.0.0 . | wc -l
+ 107
+-->
+
+<h1 id="how-to-get-involved">How to Get Involved</h1>
+
+<p>Kudos to everyone in the community who has contributed ideas,
+discussions, bug reports, documentation and code. It is exciting to be
+innovating on the next generation of database architectures together!</p>
+
+<p>If you are interested in contributing to DataFusion, we would love to
+have you join us. You can try out DataFusion on some of your own
+data and projects and let us know how it goes or contribute a PR with
+documentation, tests or code. A list of open issues suitable for
+beginners is <a href="https://github.com/apache/arrow-datafusion/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22">here</a>.</p>
+
+<p>Check out our <a href="https://arrow.apache.org/datafusion/contributor-guide/communication.html">Communication Doc</a> for more ways to engage with the
+community.</p>]]></content><author><name>pmc</name></author><category term="release" /><summary type="html"><![CDATA[It has been a whirlwind 6 months of DataFusion development since our last update: the community has grown, many features have been added, performance improved and we are discussing branching out to our own top level Apache Project. Background Apache Arrow DataFusion is an extensible query engine and database toolkit, written in Rust, that uses Apache Arrow as its in-memory [...]
-->
@@ -1253,55 +1472,4 @@ to the invaluable advice and support of the Apache Arrow developer mailing list.
1 Dane Pitkin
1 Jonathan Keane
1 Joris Van den Bossche
-</code></pre></div></div>]]></content><author><name>pmc</name></author><category term="release" /><summary type="html"><![CDATA[The Apache Arrow team is pleased to announce the 0.1.0 release of Apache Arrow nanoarrow. This initial release covers 31 resolved issues from 6 contributors. Release Highlights This initial release includes the following: A C library bundled as two files (nanoarrow.c and nanoarrow.h). An R package providing bindings for users of the R programming language. See t [...]
-
--->
-
-<p>The Apache Arrow team is pleased to announce the 0.2.0 release of
-the Apache Arrow ADBC libraries. This covers includes <a href="https://github.com/apache/arrow-adbc/milestone/2"><strong>34
-resolved issues</strong></a> from <a href="#contributors"><strong>7 distinct contributors</strong></a>.</p>
-
-<p>This is a release of the <strong>libraries</strong>, which are at version
-0.2.0. The <strong>API specification</strong> is versioned separately and is
-at version 1.0.0.</p>
-
-<p>The release notes below are not exhaustive and only expose selected
-highlights of the release. Many other bugfixes and improvements have
-been made: we refer you to the <a href="https://github.com/apache/arrow-adbc/blob/apache-arrow-adbc-0.2.0/CHANGELOG.md">complete changelog</a>.</p>
-
-<h2 id="release-highlights">Release Highlights</h2>
-
-<p>An ADBC Flight SQL driver in Go has been added. This driver has
-bindings for C/C++ and Python as well. This lets us distribute and
-update the driver independently of PyArrow, without causing conflicts
-in dependencies like Protobuf and gRPC.</p>
-
-<p>The Go database/sql interface now returns standard library <code class="language-plaintext highlighter-rouge">time.Time</code>
-values for Arrow time and date columns.</p>
-
-<p>The PostgreSQL driver has support for more types.</p>
-
-<h2 id="contributors">Contributors</h2>
-
-<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>$ git shortlog --perl-regexp --author='^((?!dependabot\[bot\]).*)$' -sn apache-arrow-adbc-0.1.0..apache-arrow-adbc-0.2.0
- 56 David Li
- 8 Sutou Kouhei
- 7 Matt Topol
- 4 Jacob Marble
- 2 Benson Muite
- 1 Dave Hirschfeld
- 1 Jianfeng Mao
-</code></pre></div></div>
-
-<h2 id="roadmap">Roadmap</h2>
-
-<p>New extensions to the API specification have been proposed. These
-will be backwards-compatible and will become API specification 1.1.0.
-For details, see the <a href="https://lists.apache.org/thread/247z3t06mf132nocngc1jkp3oqglz7jp">mailing list discussion</a> and the
-<a href="https://github.com/apache/arrow-adbc/milestone/3">milestone</a> tracking the proposed features.</p>
-
-<h2 id="getting-involved">Getting Involved</h2>
-
-<p>We welcome questions and contributions from all interested. Issues
-can be filed on <a href="https://github.com/apache/arrow-adbc/issues">GitHub</a>, and questions can be directed to GitHub
-or the <a href="/community/">Arrow mailing lists</a>.</p>]]></content><author><name>pmc</name></author><category term="release" /><summary type="html"><![CDATA[The Apache Arrow team is pleased to announce the 0.2.0 release of the Apache Arrow ADBC libraries. This covers includes 34 resolved issues from 7 distinct contributors. This is a release of the libraries, which are at version 0.2.0. The API specification is versioned separately and is at version 1.0.0. The release notes below are [...]
\ No newline at end of file
+</code></pre></div></div>]]></content><author><name>pmc</name></author><category term="release" /><summary type="html"><![CDATA[The Apache Arrow team is pleased to announce the 0.1.0 release of Apache Arrow nanoarrow. This initial release covers 31 resolved issues from 6 contributors. Release Highlights This initial release includes the following: A C library bundled as two files (nanoarrow.c and nanoarrow.h). An R package providing bindings for users of the R programming language. See t [...]
\ No newline at end of file
diff --git a/release/0.1.0.html b/release/0.1.0.html
index 17a8f65d7e2..3f60c9dcaef 100644
--- a/release/0.1.0.html
+++ b/release/0.1.0.html
@@ -20,13 +20,13 @@
<meta property="og:site_name" content="Apache Arrow" />
<meta property="og:image" content="https://arrow.apache.org/img/arrow-logo_horizontal_black-txt_white-bg.png" />
<meta property="og:type" content="article" />
-<meta property="article:published_time" content="2023-06-23T06:56:03-04:00" />
+<meta property="article:published_time" content="2023-06-24T07:15:15-04:00" />
<meta name="twitter:card" content="summary_large_image" />
<meta property="twitter:image" content="https://arrow.apache.org/img/arrow-logo_horizontal_black-txt_white-bg.png" />
<meta property="twitter:title" content="0.1.0 Release" />
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diff --git a/release/0.3.0.html b/release/0.3.0.html
index 30495f401ed..5b5c8647112 100644
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diff --git a/release/0.4.0.html b/release/0.4.0.html
index db52981c266..be88e45c4c3 100644
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index dea4bfc8441..5c0465cc30b 100644
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index 9e9e3113628..cca1e8f346c 100644
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diff --git a/release/0.7.0.html b/release/0.7.0.html
index b17b3d04d10..9c01583d129 100644
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diff --git a/release/0.7.1.html b/release/0.7.1.html
index a28b37e8380..54d3f9b02ec 100644
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<meta property="og:type" content="article" />
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<meta name="twitter:card" content="summary_large_image" />
<meta property="twitter:image" content="https://arrow.apache.org/img/arrow-logo_horizontal_black-txt_white-bg.png" />
<meta property="twitter:title" content="Apache Arrow 0.7.1 Release" />
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index e1836e7dd6b..5a3f04a65f8 100644
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diff --git a/release/0.9.0.html b/release/0.9.0.html
index 93d7e24ce0e..2ba3b779390 100644
--- a/release/0.9.0.html
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diff --git a/release/1.0.0.html b/release/1.0.0.html
index cd8fe67ca9c..1c9b908efbb 100644
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diff --git a/release/1.0.1.html b/release/1.0.1.html
index 2f3443f9be4..60b75abc1c5 100644
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index 4b2aaee5aaa..d340fd1fb04 100644
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