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The following commit(s) were added to refs/heads/asf-site by this push:
new a7dae10 Deploy
a7dae10 is described below
commit a7dae1018ab06e15ca054ea100546e211b53da3b
Author: Wes McKinney <wesm+...@apache.org>
AuthorDate: Thu Sep 5 10:16:06 2019 -0500
Deploy
---
blog/2019/08/08/r-package-on-cran/index.html | 22 +++++++++++-----------
blog/index.html | 22 +++++++++++-----------
feed.xml | 24 ++++++++++++------------
3 files changed, 34 insertions(+), 34 deletions(-)
diff --git a/blog/2019/08/08/r-package-on-cran/index.html
b/blog/2019/08/08/r-package-on-cran/index.html
index e583201..0852f65 100644
--- a/blog/2019/08/08/r-package-on-cran/index.html
+++ b/blog/2019/08/08/r-package-on-cran/index.html
@@ -195,12 +195,12 @@ library.</p>
<h2 id="parquet-files">Parquet files</h2>
-<p>This release introduces basic read and write support for the <a
href="https://parquet.apache.org/";>Apache
-Parquet</a> columnar data file format. Prior to this
-release, options for accessing Parquet data in R were limited; the most common
-recommendation was to use Apache Spark. The <code
class="highlighter-rouge">arrow</code> package greatly simplifies
-this access and lets you go from a Parquet file to a <code
class="highlighter-rouge">data.frame</code> and back
-easily, without having to set up a database.</p>
+<p>This package introduces basic read and write support for the <a
href="https://parquet.apache.org/";>Apache
+Parquet</a> columnar data file format. Prior to its
+availability, options for accessing Parquet data in R were limited; the most
+common recommendation was to use Apache Spark. The <code
class="highlighter-rouge">arrow</code> package greatly
+simplifies this access and lets you go from a Parquet file to a <code
class="highlighter-rouge">data.frame</code>
+and back easily, without having to set up a database.</p>
<div class="language-r highlighter-rouge"><div class="highlight"><pre
class="highlight"><code><span class="n">library</span><span
class="p">(</span><span class="n">arrow</span><span class="p">)</span><span
class="w">
</span><span class="n">df</span><span class="w"> </span><span
class="o"><-</span><span class="w"> </span><span
class="n">read_parquet</span><span class="p">(</span><span
class="s2">"path/to/file.parquet"</span><span class="p">)</span><span class="w">
@@ -236,7 +236,7 @@ future.</p>
<h2 id="feather-files">Feather files</h2>
-<p>This release also includes a faster and more robust implementation of the
+<p>This package also includes a faster and more robust implementation of the
Feather file format, providing <code
class="highlighter-rouge">read_feather()</code> and
<code class="highlighter-rouge">write_feather()</code>. <a
href="https://github.com/wesm/feather";>Feather</a> was one of the
initial applications of Apache Arrow for Python and R, providing an efficient,
@@ -249,10 +249,10 @@ years, the Python implementation of Feather has just been
a wrapper around
<code class="highlighter-rouge">pyarrow</code>. This meant that as Arrow
progressed and bugs were fixed, the Python
version of Feather got the improvements but sadly R did not.</p>
-<p>With this release, the R implementation of Feather catches up and now
depends
-on the same underlying C++ library as the Python version does. This should
-result in more reliable and consistent behavior across the two languages, as
-well as <a href="https://wesmckinney.com/blog/feather-arrow-future/";>improved
+<p>With the <code class="highlighter-rouge">arrow</code> package, the R
implementation of Feather catches up and now
+depends on the same underlying C++ library as the Python version does. This
+should result in more reliable and consistent behavior across the two
+languages, as well as <a
href="https://wesmckinney.com/blog/feather-arrow-future/";>improved
performance</a>.</p>
<p>We encourage all R users of <code class="highlighter-rouge">feather</code>
to switch to using
diff --git a/blog/index.html b/blog/index.html
index b6dc881..8da86bc 100644
--- a/blog/index.html
+++ b/blog/index.html
@@ -433,12 +433,12 @@ library.</p>
<h2 id="parquet-files">Parquet files</h2>
-<p>This release introduces basic read and write support for the <a
href="https://parquet.apache.org/";>Apache
-Parquet</a> columnar data file format. Prior to this
-release, options for accessing Parquet data in R were limited; the most common
-recommendation was to use Apache Spark. The <code
class="highlighter-rouge">arrow</code> package greatly simplifies
-this access and lets you go from a Parquet file to a <code
class="highlighter-rouge">data.frame</code> and back
-easily, without having to set up a database.</p>
+<p>This package introduces basic read and write support for the <a
href="https://parquet.apache.org/";>Apache
+Parquet</a> columnar data file format. Prior to its
+availability, options for accessing Parquet data in R were limited; the most
+common recommendation was to use Apache Spark. The <code
class="highlighter-rouge">arrow</code> package greatly
+simplifies this access and lets you go from a Parquet file to a <code
class="highlighter-rouge">data.frame</code>
+and back easily, without having to set up a database.</p>
<div class="language-r highlighter-rouge"><div class="highlight"><pre
class="highlight"><code><span class="n">library</span><span
class="p">(</span><span class="n">arrow</span><span class="p">)</span><span
class="w">
</span><span class="n">df</span><span class="w"> </span><span
class="o"><-</span><span class="w"> </span><span
class="n">read_parquet</span><span class="p">(</span><span
class="s2">"path/to/file.parquet"</span><span class="p">)</span><span class="w">
@@ -474,7 +474,7 @@ future.</p>
<h2 id="feather-files">Feather files</h2>
-<p>This release also includes a faster and more robust implementation of the
+<p>This package also includes a faster and more robust implementation of the
Feather file format, providing <code
class="highlighter-rouge">read_feather()</code> and
<code class="highlighter-rouge">write_feather()</code>. <a
href="https://github.com/wesm/feather";>Feather</a> was one of the
initial applications of Apache Arrow for Python and R, providing an efficient,
@@ -487,10 +487,10 @@ years, the Python implementation of Feather has just been
a wrapper around
<code class="highlighter-rouge">pyarrow</code>. This meant that as Arrow
progressed and bugs were fixed, the Python
version of Feather got the improvements but sadly R did not.</p>
-<p>With this release, the R implementation of Feather catches up and now
depends
-on the same underlying C++ library as the Python version does. This should
-result in more reliable and consistent behavior across the two languages, as
-well as <a href="https://wesmckinney.com/blog/feather-arrow-future/";>improved
+<p>With the <code class="highlighter-rouge">arrow</code> package, the R
implementation of Feather catches up and now
+depends on the same underlying C++ library as the Python version does. This
+should result in more reliable and consistent behavior across the two
+languages, as well as <a
href="https://wesmckinney.com/blog/feather-arrow-future/";>improved
performance</a>.</p>
<p>We encourage all R users of <code class="highlighter-rouge">feather</code>
to switch to using
diff --git a/feed.xml b/feed.xml
index 5338230..956edc2 100644
--- a/feed.xml
+++ b/feed.xml
@@ -1,4 +1,4 @@
-<?xml version="1.0" encoding="utf-8"?><feed
xmlns="http://www.w3.org/2005/Atom"; ><generator uri="https://jekyllrb.com/";
version="3.8.4">Jekyll</generator><link href="/feed.xml" rel="self"
type="application/atom+xml" /><link href="/" rel="alternate" type="text/html"
/><updated>2019-09-05T11:07:28-04:00</updated><id>/feed.xml</id><entry><title
type="html">Faster C++ Apache Parquet performance on dictionary-encoded string
data coming in Apache Arrow 0.15</title><link href="/blog/2019/09/05/ [...]
+<?xml version="1.0" encoding="utf-8"?><feed
xmlns="http://www.w3.org/2005/Atom"; ><generator uri="https://jekyllrb.com/";
version="3.8.4">Jekyll</generator><link href="/feed.xml" rel="self"
type="application/atom+xml" /><link href="/" rel="alternate" type="text/html"
/><updated>2019-09-05T11:15:55-04:00</updated><id>/feed.xml</id><entry><title
type="html">Faster C++ Apache Parquet performance on dictionary-encoded string
data coming in Apache Arrow 0.15</title><link href="/blog/2019/09/05/ [...]
-->
@@ -248,12 +248,12 @@ library.</p>
<h2 id="parquet-files">Parquet files</h2>
-<p>This release introduces basic read and write support for the <a
href="https://parquet.apache.org/">Apache
-Parquet</a> columnar data file format. Prior to this
-release, options for accessing Parquet data in R were limited; the most common
-recommendation was to use Apache Spark. The <code
class="highlighter-rouge">arrow</code> package greatly
simplifies
-this access and lets you go from a Parquet file to a <code
class="highlighter-rouge">data.frame</code> and back
-easily, without having to set up a database.</p>
+<p>This package introduces basic read and write support for the <a
href="https://parquet.apache.org/">Apache
+Parquet</a> columnar data file format. Prior to its
+availability, options for accessing Parquet data in R were limited; the most
+common recommendation was to use Apache Spark. The <code
class="highlighter-rouge">arrow</code> package greatly
+simplifies this access and lets you go from a Parquet file to a <code
class="highlighter-rouge">data.frame</code>
+and back easily, without having to set up a database.</p>
<div class="language-r highlighter-rouge"><div
class="highlight"><pre
class="highlight"><code><span
class="n">library</span><span
class="p">(</span><span
class="n">arrow</span><span
class="p">)</span><span class="w">
</span><span class="n">df</span><span
class="w"> </span><span
class="o">&lt;-</span><span class="w">
</span><span class="n">read_parquet</span><span
class="p">(</span><span
class="s2">"path/to/file.parquet"</span><span
class="p">)</span><span class="w">
@@ -289,7 +289,7 @@ future.</p>
<h2 id="feather-files">Feather files</h2>
-<p>This release also includes a faster and more robust implementation of
the
+<p>This package also includes a faster and more robust implementation of
the
Feather file format, providing <code
class="highlighter-rouge">read_feather()</code> and
<code class="highlighter-rouge">write_feather()</code>.
<a href="https://github.com/wesm/feather">Feather</a> was
one of the
initial applications of Apache Arrow for Python and R, providing an efficient,
@@ -302,10 +302,10 @@ years, the Python implementation of Feather has just been
a wrapper around
<code class="highlighter-rouge">pyarrow</code>. This
meant that as Arrow progressed and bugs were fixed, the Python
version of Feather got the improvements but sadly R did not.</p>
-<p>With this release, the R implementation of Feather catches up and now
depends
-on the same underlying C++ library as the Python version does. This should
-result in more reliable and consistent behavior across the two languages, as
-well as <a
href="https://wesmckinney.com/blog/feather-arrow-future/">improved
+<p>With the <code
class="highlighter-rouge">arrow</code> package, the R
implementation of Feather catches up and now
+depends on the same underlying C++ library as the Python version does. This
+should result in more reliable and consistent behavior across the two
+languages, as well as <a
href="https://wesmckinney.com/blog/feather-arrow-future/">improved
performance</a>.</p>
<p>We encourage all R users of <code
class="highlighter-rouge">feather</code> to switch to using
