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Posted to commits@arrow.apache.org by gi...@apache.org on 2022/11/07 13:40:55 UTC
[arrow-site] branch asf-site updated: Updating built site (build 95591c8db5bcad33bc55fdd0bb086f89462d1b03)
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github-bot pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/arrow-site.git
The following commit(s) were added to refs/heads/asf-site by this push:
new f716a3c338 Updating built site (build 95591c8db5bcad33bc55fdd0bb086f89462d1b03)
f716a3c338 is described below
commit f716a3c33867bcb271e3776aba2b6d5045c4d747
Author: Andrew Lamb <an...@nerdnetworks.org>
AuthorDate: Mon Nov 7 13:40:51 2022 +0000
Updating built site (build 95591c8db5bcad33bc55fdd0bb086f89462d1b03)
---
.../index.html | 2 +-
.../index.html | 10 +-
blog/index.html | 22 +-
docs/c_glib/index.html | 4 +-
feed.xml | 434 ++++++++++-----------
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/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 +-
42 files changed, 310 insertions(+), 310 deletions(-)
diff --git a/blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-1/index.html b/blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-1/index.html
index 6844a83a4c..a258b867a6 100644
--- a/blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-1/index.html
+++ b/blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-1/index.html
@@ -461,7 +461,7 @@ left_index │ │ │ │ │ │ │
<p>This post has introduced the concept and challenges of multi column sorting, and shown why a comparable byte array representation, such as the <a href="https://docs.rs/arrow/25.0.0/arrow/row/index.html">row format</a> introduced to the <a href="https://github.com/apache/arrow-rs">Rust implementation</a> of <a href="https://arrow.apache.org/">Apache Arrow</a>, is such a compelling primitive.</p>
-<p>In <a href="/blog/2022/10/30/multi-column-sorts-in-arrow-rust-part-2/">the next post</a> we explain how this encoding works, but if you just want to use it, check out the <a href="https://docs.rs/arrow/latest/arrow/row/index.html">docs</a> for getting started, and report any issues on our <a href="https://github.com/apache/arrow-rs/issues">bugtracker</a>. As always, the <a href="https://github.com/apache/arrow-rs#arrow-rust-community">Arrow community</a> very much looks forward to see [...]
+<p>In <a href="/blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-2/">the next post</a> we explain how this encoding works, but if you just want to use it, check out the <a href="https://docs.rs/arrow/latest/arrow/row/index.html">docs</a> for getting started, and report any issues on our <a href="https://github.com/apache/arrow-rs/issues">bugtracker</a>. As always, the <a href="https://github.com/apache/arrow-rs#arrow-rust-community">Arrow community</a> very much looks forward to see [...]
</main>
</div>
diff --git a/blog/2022/10/30/multi-column-sorts-in-arrow-rust-part-2/index.html b/blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-2/index.html
similarity index 99%
rename from blog/2022/10/30/multi-column-sorts-in-arrow-rust-part-2/index.html
rename to blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-2/index.html
index 780f41d183..62d1653640 100644
--- a/blog/2022/10/30/multi-column-sorts-in-arrow-rust-part-2/index.html
+++ b/blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-2/index.html
@@ -16,19 +16,19 @@
<meta property="og:locale" content="en_US" />
<meta name="description" content="Introduction In Part 1 of this post, we described the problem of Multi-Column Sorting and the challenges of implementing it efficiently. This second post explains how the new row format in the Rust implementation of Apache Arrow works and is constructed. Row Format The row format is a variable length byte sequence created by concatenating the encoded form of each column. The encoding for each column depends on its datatype (and sort options). ┌─────┐ ┌── [...]
<meta property="og:description" content="Introduction In Part 1 of this post, we described the problem of Multi-Column Sorting and the challenges of implementing it efficiently. This second post explains how the new row format in the Rust implementation of Apache Arrow works and is constructed. Row Format The row format is a variable length byte sequence created by concatenating the encoded form of each column. The encoding for each column depends on its datatype (and sort options). ┌─── [...]
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-<meta property="og:url" content="https://arrow.apache.org/blog/2022/10/30/multi-column-sorts-in-arrow-rust-part-2/" />
+<link rel="canonical" href="https://arrow.apache.org/blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-2/" />
+<meta property="og:url" content="https://arrow.apache.org/blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-2/" />
<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="2022-10-30T00:00:00-04:00" />
+<meta property="article:published_time" content="2022-11-07T00:00:00-05:00" />
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<meta property="twitter:image" content="https://arrow.apache.org/img/arrow-logo_horizontal_black-txt_white-bg.png" />
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@@ -241,7 +241,7 @@
<p class="mb-4 pb-1">
<span class="badge badge-secondary">Published</span>
<span class="published mr-3">
- 30 Oct 2022
+ 07 Nov 2022
</span>
<br />
<span class="badge badge-secondary">By</span>
diff --git a/blog/index.html b/blog/index.html
index 1856c58a20..b0398b8838 100644
--- a/blog/index.html
+++ b/blog/index.html
@@ -237,7 +237,7 @@
<p>
<h3>
- <a href="/blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-1/">Fast and Memory Efficient Multi-Column Sorts in Apache Arrow Rust, Part 1</a>
+ <a href="/blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-2/">Fast and Memory Efficient Multi-Column Sorts in Apache Arrow Rust, Part 2</a>
</h3>
<p>
@@ -245,52 +245,52 @@
7 November 2022
</span>
</p>
- Introduction Sorting is one of the most fundamental operations in modern databases and other analytic systems, underpinning important operators such as aggregates, joins, window functions, merge, and more. By some estimates, more than half of the execution time in data processing systems is spent sorting. Optimizing sorts is therefore vital...
+ Introduction In Part 1 of this post, we described the problem of Multi-Column Sorting and the challenges of implementing it efficiently. This second post explains how the new row format in the Rust implementation of Apache Arrow works and is constructed. Row Format The row format is a variable length...
</p>
<p>
<h3>
- <a href="/blog/2022/11/01/arrow-flight-sql-jdbc/">Expanding Arrow's Reach with a JDBC Driver for Arrow Flight SQL</a>
+ <a href="/blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-1/">Fast and Memory Efficient Multi-Column Sorts in Apache Arrow Rust, Part 1</a>
</h3>
<p>
<span class="blog-list-date">
- 1 November 2022
+ 7 November 2022
</span>
</p>
- We’re excited to announce that as of version 10.0.0, the Arrow project now includes a JDBC driver implementation based on Arrow Flight SQL. This is courtesy of a software grant from Dremio, a data lakehouse platform. Contributors from Dremio developed and open-sourced this driver implementation, in addition to designing and...
+ Introduction Sorting is one of the most fundamental operations in modern databases and other analytic systems, underpinning important operators such as aggregates, joins, window functions, merge, and more. By some estimates, more than half of the execution time in data processing systems is spent sorting. Optimizing sorts is therefore vital...
</p>
<p>
<h3>
- <a href="/blog/2022/10/31/10.0.0-release/">Apache Arrow 10.0.0 Release</a>
+ <a href="/blog/2022/11/01/arrow-flight-sql-jdbc/">Expanding Arrow's Reach with a JDBC Driver for Arrow Flight SQL</a>
</h3>
<p>
<span class="blog-list-date">
- 31 October 2022
+ 1 November 2022
</span>
</p>
- The Apache Arrow team is pleased to announce the 10.0.0 release. This covers over 3 months of development work and includes 473 resolved issues from 100 distinct contributors. See the Install Page to learn how to get the libraries for your platform. The release notes below are not exhaustive and...
+ We’re excited to announce that as of version 10.0.0, the Arrow project now includes a JDBC driver implementation based on Arrow Flight SQL. This is courtesy of a software grant from Dremio, a data lakehouse platform. Contributors from Dremio developed and open-sourced this driver implementation, in addition to designing and...
</p>
<p>
<h3>
- <a href="/blog/2022/10/30/multi-column-sorts-in-arrow-rust-part-2/">Fast and Memory Efficient Multi-Column Sorts in Apache Arrow Rust, Part 2</a>
+ <a href="/blog/2022/10/31/10.0.0-release/">Apache Arrow 10.0.0 Release</a>
</h3>
<p>
<span class="blog-list-date">
- 30 October 2022
+ 31 October 2022
</span>
</p>
- Introduction In Part 1 of this post, we described the problem of Multi-Column Sorting and the challenges of implementing it efficiently. This second post explains how the new row format in the Rust implementation of Apache Arrow works and is constructed. Row Format The row format is a variable length...
+ The Apache Arrow team is pleased to announce the 10.0.0 release. This covers over 3 months of development work and includes 473 resolved issues from 100 distinct contributors. See the Install Page to learn how to get the libraries for your platform. The release notes below are not exhaustive and...
</p>
diff --git a/docs/c_glib/index.html b/docs/c_glib/index.html
index aaaea6dfd2..67b18b58cd 100644
--- a/docs/c_glib/index.html
+++ b/docs/c_glib/index.html
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<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="2022-11-07T07:19:02-05:00" />
+<meta property="article:published_time" content="2022-11-07T08:38:05-05:00" />
<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" />
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+{"@context":"https://schema.org","@type":"BlogPosting","dateModified":"2022-11-07T08:38:05-05:00","datePublished":"2022-11-07T08:38:05-05:00","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 [...]
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diff --git a/feed.xml b/feed.xml
index c949952791..9837af8a5f 100644
--- a/feed.xml
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@@ -1,4 +1,4 @@
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+<?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>2022-11-07T08:38:05-05:00</updated><id>https://arrow.apache.org/feed.xml</id><title type="html">Apache Arrow</title><subtitle>Apache Arrow is a cross-language developm [...]
-->
@@ -206,7 +206,221 @@ left_index │ │ │ │ │ │ │
<p>This post has introduced the concept and challenges of multi column sorting, and shown why a comparable byte array representation, such as the <a href="https://docs.rs/arrow/25.0.0/arrow/row/index.html">row format</a> introduced to the <a href="https://github.com/apache/arrow-rs">Rust implementation</a> of <a href="https://arrow.apache.org/">Apache Arrow</a>, is such a compelling primitive.</p>
-<p>In <a href="/blog/2022/10/30/multi-column-sorts-in-arrow-rust-part-2/">the next post</a> we explain how this encoding works, but if you just want to use it, check out the <a href="https://docs.rs/arrow/latest/arrow/row/index.html">docs</a> for getting started, and report any issues on our <a href="https://github.com/apache/arrow-rs/issues">bugtracker</a>. As always, the <a href="https://github.com/apache/arrow-rs#arrow-rust-community">Arrow community</a> very much looks forward to see [...]
+<p>In <a href="/blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-2/">the next post</a> we explain how this encoding works, but if you just want to use it, check out the <a href="https://docs.rs/arrow/latest/arrow/row/index.html">docs</a> for getting started, and report any issues on our <a href="https://github.com/apache/arrow-rs/issues">bugtracker</a>. As always, the <a href="https://github.com/apache/arrow-rs#arrow-rust-community">Arrow community</a> very much looks forward to see [...]
+
+-->
+
+<h2 id="introduction">Introduction</h2>
+
+<p>In <a href="/blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-1/">Part 1</a> of this post, we described the problem of Multi-Column Sorting and the challenges of implementing it efficiently. This second post explains how the new <a href="https://docs.rs/arrow/25.0.0/arrow/row/index.html">row format</a> in the <a href="https://github.com/apache/arrow-rs">Rust implementation</a> of <a href="https://arrow.apache.org/">Apache Arrow</a> works and is constructed.</p>
+
+<h2 id="row-format">Row Format</h2>
+
+<p>The row format is a variable length byte sequence created by concatenating the encoded form of each column. The encoding for each column depends on its datatype (and sort options).</p>
+
+<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code> ┌─────┐ ┌─────┐ ┌─────┐
+ │ │ │ │ │ │
+ ├─────┤ ┌ ┼─────┼ ─ ┼─────┼ ┐ ┏━━━━━━━━━━━━━┓
+ │ │ │ │ │ │ ─────────────▶┃ ┃
+ ├─────┤ └ ┼─────┼ ─ ┼─────┼ ┘ ┗━━━━━━━━━━━━━┛
+ │ │ │ │ │ │
+ └─────┘ └─────┘ └─────┘
+ ...
+ ┌─────┐ ┌ ┬─────┬ ─ ┬─────┬ ┐ ┏━━━━━━━━┓
+ │ │ │ │ │ │ ─────────────▶┃ ┃
+ └─────┘ └ ┴─────┴ ─ ┴─────┴ ┘ ┗━━━━━━━━┛
+ Customer State Orders
+ UInt64 Utf8 F64
+
+ Input Arrays Row Format
+ (Columns)
+</code></pre></div></div>
+
+<p>The encoding is carefully designed in such a way that escaping is unnecessary: it is never ambiguous as to whether a byte is part of a sentinel (e.g. null) or a value.</p>
+
+<h3 id="unsigned-integers">Unsigned Integers</h3>
+
+<p>To encode a non-null unsigned integer, the byte <code class="language-plaintext highlighter-rouge">0x01</code> is written, followed by the integer’s bytes starting with the most significant, i.e. big endian. A null is encoded as a <code class="language-plaintext highlighter-rouge">0x00</code> byte, followed by the encoded bytes of the integer’s zero value</p>
+
+<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code> ┌──┬──┬──┬──┐ ┌──┬──┬──┬──┬──┐
+ 3 │03│00│00│00│ │01│00│00│00│03│
+ └──┴──┴──┴──┘ └──┴──┴──┴──┴──┘
+ ┌──┬──┬──┬──┐ ┌──┬──┬──┬──┬──┐
+ 258 │02│01│00│00│ │01│00│00│01│02│
+ └──┴──┴──┴──┘ └──┴──┴──┴──┴──┘
+ ┌──┬──┬──┬──┐ ┌──┬──┬──┬──┬──┐
+ 23423 │7F│5B│00│00│ │01│00│00│5B│7F│
+ └──┴──┴──┴──┘ └──┴──┴──┴──┴──┘
+ ┌──┬──┬──┬──┐ ┌──┬──┬──┬──┬──┐
+ NULL │??│??│??│??│ │00│00│00│00│00│
+ └──┴──┴──┴──┘ └──┴──┴──┴──┴──┘
+
+ 32-bit (4 bytes) Row Format
+ Value Little Endian
+</code></pre></div></div>
+
+<h3 id="signed-integers">Signed Integers</h3>
+
+<p>In Rust and most modern computer architectures, signed integers are encoded using <a href="https://en.wikipedia.org/wiki/Two%27s_complement">two’s complement</a>, where a number is negated by flipping all the bits, and adding 1. Therefore, flipping the top-most bit and treating the result as an unsigned integer preserves the order. This unsigned integer can then be encoded using the same encoding for unsigned integers described in the previous section. For example</p>
+
+<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code> ┌──┬──┬──┬──┐ ┌──┬──┬──┬──┐ ┌──┬──┬──┬──┬──┐
+ 5 │05│00│00│00│ │05│00│00│80│ │01│80│00│00│05│
+ └──┴──┴──┴──┘ └──┴──┴──┴──┘ └──┴──┴──┴──┴──┘
+ ┌──┬──┬──┬──┐ ┌──┬──┬──┬──┐ ┌──┬──┬──┬──┬──┐
+ -5 │FB│FF│FF│FF│ │FB│FF│FF│7F│ │01│7F│FF│FF│FB│
+ └──┴──┴──┴──┘ └──┴──┴──┴──┘ └──┴──┴──┴──┴──┘
+
+ Value 32-bit (4 bytes) High bit flipped Row Format
+ Little Endian
+</code></pre></div></div>
+
+<h3 id="floating-point">Floating Point</h3>
+
+<p>Floating point values can be ordered according to the <a href="https://en.wikipedia.org/wiki/IEEE_754#Total-ordering_predicate">IEEE 754 totalOrder predicate</a> (implemented in Rust by <a href="https://doc.rust-lang.org/std/primitive.f32.html#method.total_cmp">f32::total_cmp</a>). This ordering interprets the bytes of the floating point value as the correspondingly sized, signed, little-endian integer, flipping all the bits except the sign bit in the case of negatives.</p>
+
+<p>Floating point values are therefore encoded to row format by converting them to the appropriate sized signed integer representation, and then using the same encoding for signed integers described in the previous section.</p>
+
+<h3 id="byte-arrays-including-strings">Byte Arrays (Including Strings)</h3>
+
+<p>Unlike primitive types above, byte arrays are variable length. For short strings, such as <code class="language-plaintext highlighter-rouge">state</code> in our example above, it is possible to pad all values to the length of the longest one with some fixed value such as <code class="language-plaintext highlighter-rouge">0x00</code> and produce a fixed length row. This is the approach described in the DuckDB blog for encoding <code class="language-plaintext highlighter-rouge">c_birth_ [...]
+
+<p>However, often values in string columns differ substantially in length or the maximum length is not known at the start of execution, making it inadvisable and/or impractical to pad the strings to a fixed length. The Rust Arrow row format therefore uses a variable length encoding.</p>
+
+<p>We need an encoding that unambiguously terminates the end of the byte array. This not only permits recovering the original value from the row format, but ensures that bytes of a longer byte array are not compared against bytes from a different column when compared against a row containing a shorter byte array.</p>
+
+<p>A null byte array is encoded as a single <code class="language-plaintext highlighter-rouge">0x00</code> byte. Similarly, an empty byte array is encoded as a single <code class="language-plaintext highlighter-rouge">0x01</code> byte.</p>
+
+<p>To encode a non-null, non-empty array, first a single <code class="language-plaintext highlighter-rouge">0x02</code> byte is written. Then the array is written in 32-byte blocks, with each complete block followed by a <code class="language-plaintext highlighter-rouge">0xFF</code> byte as a continuation token. The final block is padded to 32-bytes with <code class="language-plaintext highlighter-rouge">0x00</code>, and is then followed by the unpadded length of this final block as a s [...]
+
+<p>Note the following example encodings use a block size of 4 bytes, as opposed to 32 bytes for brevity</p>
+
+<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code> ┌───┬───┬───┬───┬───┬───┐
+ "MEEP" │02 │'M'│'E'│'E'│'P'│04 │
+ └───┴───┴───┴───┴───┴───┘
+
+ ┌───┐
+ "" │01 |
+ └───┘
+
+ NULL ┌───┐
+ │00 │
+ └───┘
+
+"Defenestration" ┌───┬───┬───┬───┬───┬───┐
+ │02 │'D'│'e'│'f'│'e'│FF │
+ └───┼───┼───┼───┼───┼───┤
+ │'n'│'e'│'s'│'t'│FF │
+ ├───┼───┼───┼───┼───┤
+ │'r'│'a'│'t'│'r'│FF │
+ ├───┼───┼───┼───┼───┤
+ │'a'│'t'│'i'│'o'│FF │
+ ├───┼───┼───┼───┼───┤
+ │'n'│00 │00 │00 │17 │
+ └───┴───┴───┴───┴───┘
+</code></pre></div></div>
+
+<p>This approach is loosely inspired by <a href="https://en.wikipedia.org/wiki/Consistent_Overhead_Byte_Stuffing">COBS encoding</a>, and chosen over more traditional <a href="https://en.wikipedia.org/wiki/High-Level_Data_Link_Control#Asynchronous_framing">byte stuffing</a> as it is more amenable to vectorization, in particular hardware with AVX-256 can copy a 32-byte block in a single instruction.</p>
+
+<h3 id="dictionary-arrays">Dictionary Arrays</h3>
+<p>Dictionary Encoded Data (called <a href="https://pandas.pydata.org/docs/user_guide/categorical.html">categorical</a> in pandas) is increasingly important because they can store and process low cardinality data very efficiently.</p>
+
+<p>A simple approach to encoding dictionary arrays would be to encode the logical values directly using the encodings for primitive values described previously. However, this would lose the benefits of dictionary encoding to reduce memory and CPU consumption.</p>
+
+<p>To further complicate matters, the <a href="https://arrow.apache.org/docs/format/Columnar.html#dictionary-encoded-layout">Arrow implementation of Dictionary encoding</a> is quite general, and we can make no assumptions about the contents of the dictionaries. In particular, we cannot assume that the dictionary values are sorted, nor that the same dictionary is used for all arrays within a column</p>
+
+<p>The following example shows how a string column might be encoded in two arrays using two different dictionaries. The dictionary keys <code class="language-plaintext highlighter-rouge">0</code>, <code class="language-plaintext highlighter-rouge">1</code>, and <code class="language-plaintext highlighter-rouge">2</code> in the first batch correspond to different values than the same keys in the second dictionary.</p>
+
+<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>┌ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─
+ ┌───────────┐ ┌─────┐ │
+│ │"Fabulous" │ │ 0 │
+ ├───────────┤ ├─────┤ │
+│ │ "Bar" │ │ 2 │
+ ├───────────┤ ├─────┤ │ ┌───────────┐
+│ │ "Soup" │ │ 2 │ │"Fabulous" │
+ └───────────┘ ├─────┤ │ ├───────────┤
+│ │ 0 │ │ "Soup" │
+ ├─────┤ │ ├───────────┤
+│ │ 1 │ │ "Soup" │
+ └─────┘ │ ├───────────┤
+│ │"Fabulous" │
+ Values │ ├───────────┤
+│ Dictionary (indexes in │ "Bar" │
+ dictionary) │ ├───────────┤
+│ │ "ZZ" │
+ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ┘ ├───────────┤
+┌ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │ "Bar" │
+ │ ├───────────┤
+│ ┌───────────┐ ┌─────┐ │ "ZZ" │
+ │"Fabulous" │ │ 1 │ │ ├───────────┤
+│ ├───────────┤ ├─────┤ │"Fabulous" │
+ │ "ZZ" │ │ 2 │ │ └───────────┘
+│ ├───────────┤ ├─────┤
+ │ "Bar" │ │ 1 │ │
+│ └───────────┘ ├─────┤
+ │ 0 │ │ Logical column
+│ └─────┘ values
+ Values │
+│ Dictionary (indexes in
+ dictionary) │
+ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ┘
+</code></pre></div></div>
+
+<p>The key observation which allows us to efficiently create a row format for this kind of data is that given a byte array, a new byte array can always be created which comes before or after it in the sort order by adding an additional byte.</p>
+
+<p>Therefore we can incrementally build an order-preserving mapping from dictionary values to variable length byte arrays, without needing to know all possible dictionary values beforehand, instead introducing mappings for new dictionary values as we encounter them.</p>
+
+<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>┌──────────┐ ┌─────┐
+│ "Bar" │ ───────────────▶│ 01 │
+└──────────┘ └─────┘
+┌──────────┐ ┌─────┬─────┐
+│"Fabulous"│ ───────────────▶│ 01 │ 02 │
+└──────────┘ └─────┴─────┘
+┌──────────┐ ┌─────┐
+│ "Soup" │ ───────────────▶│ 05 │
+└──────────┘ └─────┘
+┌──────────┐ ┌─────┐
+│ "ZZ" │ ───────────────▶│ 07 │
+└──────────┘ └─────┘
+
+ Example Order Preserving Mapping
+</code></pre></div></div>
+
+<p>The details of the data structure used to generate this mapping are beyond the scope of this blog post, but may be the topic of a future post. You can find <a href="https://github.com/apache/arrow-rs/blob/07024f6a16b870fda81cba5779b8817b20386ebf/arrow/src/row/interner.rs">the code here</a>.</p>
+
+<p>The data structure also ensures that no values contain <code class="language-plaintext highlighter-rouge">0x00</code> and therefore we can encode the arrays directly using <code class="language-plaintext highlighter-rouge">0x00</code> as an end-delimiter.</p>
+
+<p>A null value is encoded as a single <code class="language-plaintext highlighter-rouge">0x00</code> byte, and a non-null value encoded as a single <code class="language-plaintext highlighter-rouge">0x01</code> byte, followed by the <code class="language-plaintext highlighter-rouge">0x00</code> terminated byte array determined by the order preserving mapping</p>
+
+<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code> ┌─────┬─────┬─────┬─────┐
+ "Fabulous" │ 01 │ 03 │ 05 │ 00 │
+ └─────┴─────┴─────┴─────┘
+
+ ┌─────┬─────┬─────┐
+ "ZZ" │ 01 │ 07 │ 00 │
+ └─────┴─────┴─────┘
+
+ ┌─────┐
+ NULL │ 00 │
+ └─────┘
+
+ Input Row Format
+</code></pre></div></div>
+
+<h3 id="sort-options">Sort Options</h3>
+
+<p>One detail we have so far ignored over is how to support ascending and descending sorts (e.g. <code class="language-plaintext highlighter-rouge">ASC</code> or <code class="language-plaintext highlighter-rouge">DESC</code> in SQL). The Arrow Rust row format supports these options by simply inverting the bytes of the encoded representation, except the initial byte used for nullability encoding, on a per column basis.</p>
+
+<p>Similarly, supporting SQL compatible sorting also requires a format that can specify the order of <code class="language-plaintext highlighter-rouge">NULL</code>s (before or after all non <code class="language-plaintext highlighter-rouge">NULL</code> values). The row format supports this option by optionally encoding nulls as <code class="language-plaintext highlighter-rouge">0xFF</code> instead of <code class="language-plaintext highlighter-rouge">0x00</code> on a per column basis.</p>
+
+<h2 id="conclusion">Conclusion</h2>
+
+<p>Hopefully these two articles have given you a flavor of what is possible with a comparable row format and how it works. Feel free to check out the <a href="https://docs.rs/arrow/latest/arrow/row/index.html">docs</a> for instructions on getting started, and report any issues on our <a href="https://github.com/apache/arrow-rs/issues">bugtracker</a>.</p>
+
+<p>Using this format for lexicographic sorting is more than <a href="https://github.com/apache/arrow-rs/pull/2929">3x</a> faster than the comparator based approach, with the benefits especially pronounced for strings, dictionaries and sorts with large numbers of columns.</p>
+
+<p>We have also already used it to more than <a href="https://github.com/apache/arrow-datafusion/pull/3386">double</a> the performance of sort preserving merge in the <a href="https://arrow.apache.org/datafusion/">DataFusion project</a>, and expect similar or greater performance uplift as we apply it to sort, grouping, join, and window function operators as well.</p>
+
+<p>As always, the <a href="https://github.com/apache/arrow-rs#arrow-rust-community">Arrow community</a> very much looks forward to seeing what you build with it!</p>]]></content><author><name>tustvold and alamb</name></author><category term="arrow" /><summary type="html"><![CDATA[Introduction In Part 1 of this post, we described the problem of Multi-Column Sorting and the challenges of implementing it efficiently. This second post explains how the new row format in the Rust implementatio [...]
-->
@@ -584,221 +798,7 @@ enable the necessary components explicitly
<p>The Rust projects have moved to separate repositories outside the
main Arrow monorepo. For notes on the latest release of the Rust
-implementation, see the latest <a href="https://github.com/apache/arrow-rs/tags">Arrow Rust changelog</a>.</p>]]></content><author><name>pmc</name></author><category term="release" /><summary type="html"><![CDATA[The Apache Arrow team is pleased to announce the 10.0.0 release. This covers over 3 months of development work and includes 473 resolved issues from 100 distinct contributors. See the Install Page to learn how to get the libraries for your platform. The release notes below are n [...]
-
--->
-
-<h2 id="introduction">Introduction</h2>
-
-<p>In <a href="/blog/2022/11/07/multi-column-sorts-in-arrow-rust-part-1/">Part 1</a> of this post, we described the problem of Multi-Column Sorting and the challenges of implementing it efficiently. This second post explains how the new <a href="https://docs.rs/arrow/25.0.0/arrow/row/index.html">row format</a> in the <a href="https://github.com/apache/arrow-rs">Rust implementation</a> of <a href="https://arrow.apache.org/">Apache Arrow</a> works and is constructed.</p>
-
-<h2 id="row-format">Row Format</h2>
-
-<p>The row format is a variable length byte sequence created by concatenating the encoded form of each column. The encoding for each column depends on its datatype (and sort options).</p>
-
-<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code> ┌─────┐ ┌─────┐ ┌─────┐
- │ │ │ │ │ │
- ├─────┤ ┌ ┼─────┼ ─ ┼─────┼ ┐ ┏━━━━━━━━━━━━━┓
- │ │ │ │ │ │ ─────────────▶┃ ┃
- ├─────┤ └ ┼─────┼ ─ ┼─────┼ ┘ ┗━━━━━━━━━━━━━┛
- │ │ │ │ │ │
- └─────┘ └─────┘ └─────┘
- ...
- ┌─────┐ ┌ ┬─────┬ ─ ┬─────┬ ┐ ┏━━━━━━━━┓
- │ │ │ │ │ │ ─────────────▶┃ ┃
- └─────┘ └ ┴─────┴ ─ ┴─────┴ ┘ ┗━━━━━━━━┛
- Customer State Orders
- UInt64 Utf8 F64
-
- Input Arrays Row Format
- (Columns)
-</code></pre></div></div>
-
-<p>The encoding is carefully designed in such a way that escaping is unnecessary: it is never ambiguous as to whether a byte is part of a sentinel (e.g. null) or a value.</p>
-
-<h3 id="unsigned-integers">Unsigned Integers</h3>
-
-<p>To encode a non-null unsigned integer, the byte <code class="language-plaintext highlighter-rouge">0x01</code> is written, followed by the integer’s bytes starting with the most significant, i.e. big endian. A null is encoded as a <code class="language-plaintext highlighter-rouge">0x00</code> byte, followed by the encoded bytes of the integer’s zero value</p>
-
-<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code> ┌──┬──┬──┬──┐ ┌──┬──┬──┬──┬──┐
- 3 │03│00│00│00│ │01│00│00│00│03│
- └──┴──┴──┴──┘ └──┴──┴──┴──┴──┘
- ┌──┬──┬──┬──┐ ┌──┬──┬──┬──┬──┐
- 258 │02│01│00│00│ │01│00│00│01│02│
- └──┴──┴──┴──┘ └──┴──┴──┴──┴──┘
- ┌──┬──┬──┬──┐ ┌──┬──┬──┬──┬──┐
- 23423 │7F│5B│00│00│ │01│00│00│5B│7F│
- └──┴──┴──┴──┘ └──┴──┴──┴──┴──┘
- ┌──┬──┬──┬──┐ ┌──┬──┬──┬──┬──┐
- NULL │??│??│??│??│ │00│00│00│00│00│
- └──┴──┴──┴──┘ └──┴──┴──┴──┴──┘
-
- 32-bit (4 bytes) Row Format
- Value Little Endian
-</code></pre></div></div>
-
-<h3 id="signed-integers">Signed Integers</h3>
-
-<p>In Rust and most modern computer architectures, signed integers are encoded using <a href="https://en.wikipedia.org/wiki/Two%27s_complement">two’s complement</a>, where a number is negated by flipping all the bits, and adding 1. Therefore, flipping the top-most bit and treating the result as an unsigned integer preserves the order. This unsigned integer can then be encoded using the same encoding for unsigned integers described in the previous section. For example</p>
-
-<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code> ┌──┬──┬──┬──┐ ┌──┬──┬──┬──┐ ┌──┬──┬──┬──┬──┐
- 5 │05│00│00│00│ │05│00│00│80│ │01│80│00│00│05│
- └──┴──┴──┴──┘ └──┴──┴──┴──┘ └──┴──┴──┴──┴──┘
- ┌──┬──┬──┬──┐ ┌──┬──┬──┬──┐ ┌──┬──┬──┬──┬──┐
- -5 │FB│FF│FF│FF│ │FB│FF│FF│7F│ │01│7F│FF│FF│FB│
- └──┴──┴──┴──┘ └──┴──┴──┴──┘ └──┴──┴──┴──┴──┘
-
- Value 32-bit (4 bytes) High bit flipped Row Format
- Little Endian
-</code></pre></div></div>
-
-<h3 id="floating-point">Floating Point</h3>
-
-<p>Floating point values can be ordered according to the <a href="https://en.wikipedia.org/wiki/IEEE_754#Total-ordering_predicate">IEEE 754 totalOrder predicate</a> (implemented in Rust by <a href="https://doc.rust-lang.org/std/primitive.f32.html#method.total_cmp">f32::total_cmp</a>). This ordering interprets the bytes of the floating point value as the correspondingly sized, signed, little-endian integer, flipping all the bits except the sign bit in the case of negatives.</p>
-
-<p>Floating point values are therefore encoded to row format by converting them to the appropriate sized signed integer representation, and then using the same encoding for signed integers described in the previous section.</p>
-
-<h3 id="byte-arrays-including-strings">Byte Arrays (Including Strings)</h3>
-
-<p>Unlike primitive types above, byte arrays are variable length. For short strings, such as <code class="language-plaintext highlighter-rouge">state</code> in our example above, it is possible to pad all values to the length of the longest one with some fixed value such as <code class="language-plaintext highlighter-rouge">0x00</code> and produce a fixed length row. This is the approach described in the DuckDB blog for encoding <code class="language-plaintext highlighter-rouge">c_birth_ [...]
-
-<p>However, often values in string columns differ substantially in length or the maximum length is not known at the start of execution, making it inadvisable and/or impractical to pad the strings to a fixed length. The Rust Arrow row format therefore uses a variable length encoding.</p>
-
-<p>We need an encoding that unambiguously terminates the end of the byte array. This not only permits recovering the original value from the row format, but ensures that bytes of a longer byte array are not compared against bytes from a different column when compared against a row containing a shorter byte array.</p>
-
-<p>A null byte array is encoded as a single <code class="language-plaintext highlighter-rouge">0x00</code> byte. Similarly, an empty byte array is encoded as a single <code class="language-plaintext highlighter-rouge">0x01</code> byte.</p>
-
-<p>To encode a non-null, non-empty array, first a single <code class="language-plaintext highlighter-rouge">0x02</code> byte is written. Then the array is written in 32-byte blocks, with each complete block followed by a <code class="language-plaintext highlighter-rouge">0xFF</code> byte as a continuation token. The final block is padded to 32-bytes with <code class="language-plaintext highlighter-rouge">0x00</code>, and is then followed by the unpadded length of this final block as a s [...]
-
-<p>Note the following example encodings use a block size of 4 bytes, as opposed to 32 bytes for brevity</p>
-
-<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code> ┌───┬───┬───┬───┬───┬───┐
- "MEEP" │02 │'M'│'E'│'E'│'P'│04 │
- └───┴───┴───┴───┴───┴───┘
-
- ┌───┐
- "" │01 |
- └───┘
-
- NULL ┌───┐
- │00 │
- └───┘
-
-"Defenestration" ┌───┬───┬───┬───┬───┬───┐
- │02 │'D'│'e'│'f'│'e'│FF │
- └───┼───┼───┼───┼───┼───┤
- │'n'│'e'│'s'│'t'│FF │
- ├───┼───┼───┼───┼───┤
- │'r'│'a'│'t'│'r'│FF │
- ├───┼───┼───┼───┼───┤
- │'a'│'t'│'i'│'o'│FF │
- ├───┼───┼───┼───┼───┤
- │'n'│00 │00 │00 │17 │
- └───┴───┴───┴───┴───┘
-</code></pre></div></div>
-
-<p>This approach is loosely inspired by <a href="https://en.wikipedia.org/wiki/Consistent_Overhead_Byte_Stuffing">COBS encoding</a>, and chosen over more traditional <a href="https://en.wikipedia.org/wiki/High-Level_Data_Link_Control#Asynchronous_framing">byte stuffing</a> as it is more amenable to vectorization, in particular hardware with AVX-256 can copy a 32-byte block in a single instruction.</p>
-
-<h3 id="dictionary-arrays">Dictionary Arrays</h3>
-<p>Dictionary Encoded Data (called <a href="https://pandas.pydata.org/docs/user_guide/categorical.html">categorical</a> in pandas) is increasingly important because they can store and process low cardinality data very efficiently.</p>
-
-<p>A simple approach to encoding dictionary arrays would be to encode the logical values directly using the encodings for primitive values described previously. However, this would lose the benefits of dictionary encoding to reduce memory and CPU consumption.</p>
-
-<p>To further complicate matters, the <a href="https://arrow.apache.org/docs/format/Columnar.html#dictionary-encoded-layout">Arrow implementation of Dictionary encoding</a> is quite general, and we can make no assumptions about the contents of the dictionaries. In particular, we cannot assume that the dictionary values are sorted, nor that the same dictionary is used for all arrays within a column</p>
-
-<p>The following example shows how a string column might be encoded in two arrays using two different dictionaries. The dictionary keys <code class="language-plaintext highlighter-rouge">0</code>, <code class="language-plaintext highlighter-rouge">1</code>, and <code class="language-plaintext highlighter-rouge">2</code> in the first batch correspond to different values than the same keys in the second dictionary.</p>
-
-<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>┌ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─
- ┌───────────┐ ┌─────┐ │
-│ │"Fabulous" │ │ 0 │
- ├───────────┤ ├─────┤ │
-│ │ "Bar" │ │ 2 │
- ├───────────┤ ├─────┤ │ ┌───────────┐
-│ │ "Soup" │ │ 2 │ │"Fabulous" │
- └───────────┘ ├─────┤ │ ├───────────┤
-│ │ 0 │ │ "Soup" │
- ├─────┤ │ ├───────────┤
-│ │ 1 │ │ "Soup" │
- └─────┘ │ ├───────────┤
-│ │"Fabulous" │
- Values │ ├───────────┤
-│ Dictionary (indexes in │ "Bar" │
- dictionary) │ ├───────────┤
-│ │ "ZZ" │
- ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ┘ ├───────────┤
-┌ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │ "Bar" │
- │ ├───────────┤
-│ ┌───────────┐ ┌─────┐ │ "ZZ" │
- │"Fabulous" │ │ 1 │ │ ├───────────┤
-│ ├───────────┤ ├─────┤ │"Fabulous" │
- │ "ZZ" │ │ 2 │ │ └───────────┘
-│ ├───────────┤ ├─────┤
- │ "Bar" │ │ 1 │ │
-│ └───────────┘ ├─────┤
- │ 0 │ │ Logical column
-│ └─────┘ values
- Values │
-│ Dictionary (indexes in
- dictionary) │
- ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ┘
-</code></pre></div></div>
-
-<p>The key observation which allows us to efficiently create a row format for this kind of data is that given a byte array, a new byte array can always be created which comes before or after it in the sort order by adding an additional byte.</p>
-
-<p>Therefore we can incrementally build an order-preserving mapping from dictionary values to variable length byte arrays, without needing to know all possible dictionary values beforehand, instead introducing mappings for new dictionary values as we encounter them.</p>
-
-<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>┌──────────┐ ┌─────┐
-│ "Bar" │ ───────────────▶│ 01 │
-└──────────┘ └─────┘
-┌──────────┐ ┌─────┬─────┐
-│"Fabulous"│ ───────────────▶│ 01 │ 02 │
-└──────────┘ └─────┴─────┘
-┌──────────┐ ┌─────┐
-│ "Soup" │ ───────────────▶│ 05 │
-└──────────┘ └─────┘
-┌──────────┐ ┌─────┐
-│ "ZZ" │ ───────────────▶│ 07 │
-└──────────┘ └─────┘
-
- Example Order Preserving Mapping
-</code></pre></div></div>
-
-<p>The details of the data structure used to generate this mapping are beyond the scope of this blog post, but may be the topic of a future post. You can find <a href="https://github.com/apache/arrow-rs/blob/07024f6a16b870fda81cba5779b8817b20386ebf/arrow/src/row/interner.rs">the code here</a>.</p>
-
-<p>The data structure also ensures that no values contain <code class="language-plaintext highlighter-rouge">0x00</code> and therefore we can encode the arrays directly using <code class="language-plaintext highlighter-rouge">0x00</code> as an end-delimiter.</p>
-
-<p>A null value is encoded as a single <code class="language-plaintext highlighter-rouge">0x00</code> byte, and a non-null value encoded as a single <code class="language-plaintext highlighter-rouge">0x01</code> byte, followed by the <code class="language-plaintext highlighter-rouge">0x00</code> terminated byte array determined by the order preserving mapping</p>
-
-<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code> ┌─────┬─────┬─────┬─────┐
- "Fabulous" │ 01 │ 03 │ 05 │ 00 │
- └─────┴─────┴─────┴─────┘
-
- ┌─────┬─────┬─────┐
- "ZZ" │ 01 │ 07 │ 00 │
- └─────┴─────┴─────┘
-
- ┌─────┐
- NULL │ 00 │
- └─────┘
-
- Input Row Format
-</code></pre></div></div>
-
-<h3 id="sort-options">Sort Options</h3>
-
-<p>One detail we have so far ignored over is how to support ascending and descending sorts (e.g. <code class="language-plaintext highlighter-rouge">ASC</code> or <code class="language-plaintext highlighter-rouge">DESC</code> in SQL). The Arrow Rust row format supports these options by simply inverting the bytes of the encoded representation, except the initial byte used for nullability encoding, on a per column basis.</p>
-
-<p>Similarly, supporting SQL compatible sorting also requires a format that can specify the order of <code class="language-plaintext highlighter-rouge">NULL</code>s (before or after all non <code class="language-plaintext highlighter-rouge">NULL</code> values). The row format supports this option by optionally encoding nulls as <code class="language-plaintext highlighter-rouge">0xFF</code> instead of <code class="language-plaintext highlighter-rouge">0x00</code> on a per column basis.</p>
-
-<h2 id="conclusion">Conclusion</h2>
-
-<p>Hopefully these two articles have given you a flavor of what is possible with a comparable row format and how it works. Feel free to check out the <a href="https://docs.rs/arrow/latest/arrow/row/index.html">docs</a> for instructions on getting started, and report any issues on our <a href="https://github.com/apache/arrow-rs/issues">bugtracker</a>.</p>
-
-<p>Using this format for lexicographic sorting is more than <a href="https://github.com/apache/arrow-rs/pull/2929">3x</a> faster than the comparator based approach, with the benefits especially pronounced for strings, dictionaries and sorts with large numbers of columns.</p>
-
-<p>We have also already used it to more than <a href="https://github.com/apache/arrow-datafusion/pull/3386">double</a> the performance of sort preserving merge in the <a href="https://arrow.apache.org/datafusion/">DataFusion project</a>, and expect similar or greater performance uplift as we apply it to sort, grouping, join, and window function operators as well.</p>
-
-<p>As always, the <a href="https://github.com/apache/arrow-rs#arrow-rust-community">Arrow community</a> very much looks forward to seeing what you build with it!</p>]]></content><author><name>tustvold and alamb</name></author><category term="arrow" /><summary type="html"><![CDATA[Introduction In Part 1 of this post, we described the problem of Multi-Column Sorting and the challenges of implementing it efficiently. This second post explains how the new row format in the Rust implementatio [...]
+implementation, see the latest <a href="https://github.com/apache/arrow-rs/tags">Arrow Rust changelog</a>.</p>]]></content><author><name>pmc</name></author><category term="release" /><summary type="html"><![CDATA[The Apache Arrow team is pleased to announce the 10.0.0 release. This covers over 3 months of development work and includes 473 resolved issues from 100 distinct contributors. See the Install Page to learn how to get the libraries for your platform. The release notes below are n [...]
-->
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diff --git a/release/0.17.1.html b/release/0.17.1.html
index 8a1bca76d4..c09b11ef7d 100644
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diff --git a/release/0.2.0.html b/release/0.2.0.html
index f2b85851f9..f6ce59ae04 100644
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diff --git a/release/0.3.0.html b/release/0.3.0.html
index 69c3a098f0..ef9fe45c84 100644
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diff --git a/release/0.4.0.html b/release/0.4.0.html
index 20ef3f94f7..3fa138ee24 100644
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diff --git a/release/0.4.1.html b/release/0.4.1.html
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diff --git a/release/0.5.0.html b/release/0.5.0.html
index bb426de540..a04ab0f04a 100644
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<meta property="og:type" content="article" />
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<meta property="twitter:image" content="https://arrow.apache.org/img/arrow-logo_horizontal_black-txt_white-bg.png" />
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diff --git a/release/0.6.0.html b/release/0.6.0.html
index 0a8ee54897..ec2859778b 100644
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<meta property="twitter:title" content="Apache Arrow 0.6.0 Release" />
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diff --git a/release/0.7.0.html b/release/0.7.0.html
index e84edeae7d..58c4b45c61 100644
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<meta property="og:site_name" content="Apache Arrow" />
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<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 0.7.0 Release" />
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diff --git a/release/0.7.1.html b/release/0.7.1.html
index 68b9e018a5..4bdb673781 100644
--- a/release/0.7.1.html
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<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" />
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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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diff --git a/release/0.8.0.html b/release/0.8.0.html
index 32a095e544..3409ddefa1 100644
--- a/release/0.8.0.html
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@@ -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" />
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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 0.8.0 Release" />
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diff --git a/release/0.9.0.html b/release/0.9.0.html
index 8deee75b41..8c4996095c 100644
--- a/release/0.9.0.html
+++ b/release/0.9.0.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" />
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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 0.9.0 Release" />
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diff --git a/release/1.0.0.html b/release/1.0.0.html
index ebac61157d..b45b4e0ef7 100644
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@@ -20,13 +20,13 @@
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<meta property="og:image" content="https://arrow.apache.org/img/arrow-logo_horizontal_black-txt_white-bg.png" />
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