Vertica Blog

OpenText Vertica 23.3 – the Smarter Data Lakehouse

Posted July 31, 2023 by Paige Roberts, Vertica Open Source Relations Manager

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Unveiling the Most Recent Version of the Vertica Grafana Data Source Plugin

With over 380K downloads, the Vertica Grafana Data Source plugin just got an upgrade! The plugin was migrated from the deprecated older Grafana toolkit to align with Grafana's new Create-Plugin tool. This accelerates the plugin development with their modern build set up that requires no additional configuration. Additionally, the Vertica SQL Go driver received an...
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Setting Session Authorization to Troubleshoot

There are possible scenarios in which a dbadmin would want to run queries as another user to troubleshoot or test. You can use SET SESSION AUTHORIZATION to impersonate another user and run queries. Let's understand this with an example. Here we create a user named test, resource pool named userpool, and make this a default...
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Query Optimization Using Projections

In Vertica, tables are logical representations of the data. Vertica stores the actual data in projections. When data is loaded into a Vertica table, Vertica creates or updates a column-store projection. Vertica also compresses and/or encodes projection data, optimizing data access and storage. If you experience performance issues, your best first step is to run...

Machine Learning Mondays: How Vertica Implements Efficient and Scalable Machine Learning

This blog post was authored by Vincent Xu. As of Vertica 8.1, Vertica has introduced a set of popular machine learning algorithms, including Linear Regression, Logistic Regression, Kmeans, Naïve Bayes, and SVM. Based on our recent benchmarks, they run faster than MLlib on Apache Spark. The following chart shows the performance difference between Vertica 8.1.0...
Modern Database Analytics

Big Flat Fact Tables

This blog post was authored by Steve Sarsfield. For decades, it's been widely accepted that snowflake and star schemas facilitate getting optimal performance from your data warehouse. You normalize data by identifying the rows of data that you typically ingest, and creating a schema that is optimized for the types of queries you want to...

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Programmer

Using Vertica and HyperLogLog

This is a guest blog post co-authored by Francois Jehl and Pawel Szostek. Francois is the lead of the Analytics Data Storage team at Criteo; Pawel is a software engineer in the Analytics Data Storage team at Criteo. Criteo is the global leader in digital performance advertising with 900B ads served in 2016. The R&D...

Machine Learning Mondays: Data Preparation for Machine Learning in Vertica

This blog post was authored by Vincent Xu. This post is part of our Machine Learning Mondays series. Stay tuned for more! Introduction Machine learning (ML) is an iterative process. From understanding data, preparing data, building models, testing models to deploying models, every step of the way requires careful examination and manipulation of the data....

Using Hadoop Rack Locality to Boost Vertica Performance

This blog post was authored by Monica Cellio. When database nodes are co-located on Hadoop data nodes, Vertica can take advantage of the Hadoop rack configuration to execute queries against ORC and Parquet data. Moving query execution closer to the data reduces network latency and can improve performance. Vertica automatically uses database nodes that are...

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What’s New in Vertica 8.1: Connecting to Vertica Updates

Vertica 8.1 includes the following product enhancements to Connecting to Vertica. Functional Updates to \timing The \timing metafunction has been enhanced so you can use the following commands to toggle \timing on or off based on its current setting: •\timing – turns timing on or off depending on its current state. For example if timing...

What’s New in Vertica 8.1: Security Updates

Vertica 8.1 includes the following enhancements to Vertica security. Function to Verify Kerberos Configuration The function KERBEROS_CONFIG_CHECK allows you to test your Kerberos configuration of the Vertica cluster. Running this function checks: • Whether or not Kerberos services are available. • If a keytab file exists • If the Kerberos configuration parameters are set in...
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What’s New in Vertica 8.1: Machine Learning

This blog post was authored by Soniya Shah. Overall, you will notice that Machine Learning for Predictive Analytics, introduced in Vertica 7.2.2, is more accessible to use in Vertica 8.1, with the addition of several important functions. There are improvements to model management with access control ability to save and re-apply normalization parameters, missing value...

What’s New in Management Console 8.1

Vertica 8.1 introduced new monitoring and usability enhancements to Management Console (MC). MC now provides the ability to easily monitor catalog memory and configure Workload Analyzer. You’ll also find usability improvements to cluster creation and setup for Extended Monitoring. Watch our short video about What's New In MC in Vertica 8.1: https://www.youtube.com/watch?v=2yqzCAZGyeA&feature=youtu.be Read on to...

What’s New in Vertica 8.1: the Connector for Apache Spark

The Vertica 8.1 release includes updates for the Vertica Connector for Apache Spark. The biggest new feature is Apache Spark 2.0 compatibility. This makes the connector compatible with the version of Spark included with most recent Hadoop distributions. In addition, the connector supports multiple versions of the Scala programming language. Most Hadoop distributions that support...

What’s New in Vertica 8.1: Supported Platforms

With Vertica Release 8.1, we continue to enhance and broaden our platform support. New Operating Systems for Vertica Server Vertica continues to perform extensive testing as we qualify major Linux distributions for use with the Vertica Analytic Database. Our testing ensures both stability and performance when you use Vertica with a supported operating system. For...