Vertica Blog

Vertica Blog

UDx

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How to Use UDx to Extend Vertica Live Aggregate Projections

Maurizio Felici, Field Chief Technologist
August 8, 2023

Thanks to its sophisticated optimizer and extremely efficient query engine Vertica can process data aggregations order of magnitudes faster than traditional Database Management Systems. To further boost data aggregation performance, we can use Vertica’s Live Aggregate Projections (LAP from now on). The concept is very simple: pre-aggregate data once during load operations rather than doing...
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Viewing Parquet Export Events More Easily

James Knicely, Vertica Field Chief Technologist
January 27, 2020

The EXPORT TO PARQUET command exports a table, columns from a table, or query results to files in the Parquet format. When you run EXPORT TO PARQUET information about the files created during the export is stored in the Vertica log. It's no fun combing through a Vertica log looking for those particular records. Good...
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Parallel Processing Using Partitions With Vertica UDx

Bryan Herger, Vertica Big Data Solution Architect at Micro Focus
October 17, 2019

You can add functionality to Vertica using UDx, but what if you need to process more data than can be efficiently processed in a single thread or a single node? Vertica can divide data into partitions defined with the OVER() clause and distribute computing across nodes. This partition processing is "shared-nothing" similar to the Map...
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Announcing Vertica Version 9.3 – Ride the Winds of Change

Paige Roberts, Vertica Open Source Relations Manager
October 16, 2019

The winds of change have been blowing strong. This week, Vertica version 9.3 made its big splash. Vertica has a tendency to pack a lot of features even into minor releases, and this is not a minor release. Rather than dive deep, I’m going to skim the surface of the ocean of new features. Eon...
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Extending Vertica with Python functions: Adding NumPy FFT as a UDx

Bryan Herger, Vertica Big Data Solution Architect at Micro Focus
October 14, 2019

User-Defined Transform Function (UDTF) support for Python UDx were added back in Vertica 9.1, allowing you to add a much greater range of existing libraries and functions to Vertica. In this example, I'll add Fast Fourier Transform (FFT) from the NumPy package. FFT is a way to transform time-domain data into frequency-domain data. My test...
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Finding the “K” in K-means Clustering With a UDx

Bryan Herger, Vertica Big Data Solution Architect at Micro Focus
October 4, 2019

You can apply k-means clustering to partition data points into k different groups. Along with the data, the number of clusters "k" is an input to the algorithm. Common examples like the Iris data set tell you upfront how many different groups exist, so you set k=3. What if you don't know how many clusters...
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Find the Number of Days Passed and Remaining in the Relative Year

Sarah Lemaire, Manager, Vertica Documentation
August 9, 2018

Jim Knicely authored this post. Although there aren’t any specific functions that will return the number of days that have passed and that are remaining in a given year, you can combine a few of Vertica’s built-in date functions to find these numbers. You can encapsulate the date logic above into several user-defined functions that...
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Using Java UDX in Vertica

Soniya Shah, Information Developer
July 9, 2018

Michael Flower authored this post. Introduction Vertica has a highly extensible UDx framework, which allows external user-defined functions, parsers and data loaders to be installed onto the Vertica server. This means that a routine written in C++, R, Java or Python can be run in-database as a Vertica SQL function. This blog is based on...
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Introducing the Developing Vertica UDxs in Java Tutorial Series

Gary Gray, Principal Information Developer
September 30, 2015

What is a Java UDx and why would you want to develop one? Check out our new tutorial series in the wiki to find out!