<rss xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title>Parquet - Tag - Simon Jakubowski</title><link>https://sijakubo.github.io/info/tags/parquet/</link><description>Parquet - Tag - Simon Jakubowski</description><generator>Hugo -- gohugo.io</generator><language>en</language><managingEditor>sijakubo@gmail.com ( Simon Jakubowski)</managingEditor><webMaster>sijakubo@gmail.com ( Simon Jakubowski)</webMaster><lastBuildDate>Tue, 03 Mar 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://sijakubo.github.io/info/tags/parquet/" rel="self" type="application/rss+xml"/><item><title>Forget CSV or Excel files. Share your Data with Apache Parquet</title><link>https://sijakubo.github.io/info/posts/post-12/</link><pubDate>Tue, 03 Mar 2026 00:00:00 +0000</pubDate><author>sijakubo@gmail.com ( Simon Jakubowski)</author><guid>https://sijakubo.github.io/info/posts/post-12/</guid><description><![CDATA[<h2 id="what-is-apache-parquet">What is Apache Parquet?</h2>
<p>Apache Parquet is an open source, column-oriented data file format designed for efficient data storage and retrieval.</p>
<p>It provides:</p>
<ul>
<li>High-performance compression</li>
<li>Efficient encoding schemes</li>
<li>Support for complex data types</li>
<li>Broad adoption across analytics tools and programming languages</li>
</ul>
<p>Parquet is commonly used as a table replacement for analytical workloads.</p>
<hr>
<h2 id="how-to-create-parquet-files">How to Create Parquet Files</h2>
<p>There are several ways to create Parquet files:</p>
<ul>
<li>From CSV files</li>
<li>Directly from PostgreSQL using the <code>pg_parquet</code> extension</li>
<li>Using DuckDB</li>
<li>Using web-based CSV to Parquet converters</li>
</ul>
<p>In this post, DuckDB is used as a lightweight and practical tool to generate and query Parquet files.</p>]]></description></item></channel></rss>