Vertica Blog
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Sarah Lemaire

Manager, Vertica Documentation

What Version of Vertica am I Running?

Jim Knicely authored this tip. The built-in VERSION function returns a VARCHAR that contains your Vertica node's version information. The Vertica version is formatted as X.Y.Z-R, where… • X.Y is the two-digit Vertica major release number, e.g., 8.1, 9.0 and 9.1 • Z is the service pack number, e.g., 7.2.3, 8.1.1 and 9.0.1 • R...

Vertica Quick Tip: Getting a Word Count

This blog post was authored by Jim Knicely. The Vertica REGEXP_COUNT function returns the number times a regular expression matches a string. You can use it to create your own user-defined SQL function that counts the number of words in a string. dbadmin=> SELECT get_word_count('The Vertica Analytics Platform is purpose built from the very first...
quick sql tips for rows

Vertica Quick Tip: Parsing a String as Rows

This blog post was authored by Jim Knicely. A simple SQL trick makes it easy to expand an entire string into separate rows. i s A w e s o m e ! (19 rows) Now that you’ve expanded the string into rows, you can perform various actions if you encounter certain conditions… i s...

Vertica Test Results for Operating System Patches for Meltdown and Spectre Security Flaws

For the latest Vertica update on the Meltdown and Spectre security flaws, read this blog: UPDATED: Vertica Test Results with Microcode Patches for the Meltdown and Spectre Security Flaws, published May 21, 2018. Vertica engineers have run performance tests using the operating system patches for the Meltdown and Spectre security flaws. Based on the results,...

Compute Engine or Analytical Data Mart for Distributed Machine Learning? Vertica Explains How to Choose

This blog post was authored by Sarah Lemaire. On Tuesday, August 22, The Boston Vertica User Group hosted a late-summer Meetup to talk to attendees about compute engines and data mart applications, and the advantages and disadvantages of both solutions. In the cozy rustic-industrial atmosphere of Commonwealth Market and Restaurant, decorated with recycled wood pallets,...

Configure JDBC clients to Work with Your Kerberos-Enabled Vertica Cluster: DbVisualizer, DBeaver, and Others

Many customers use JDBC-based tools like DbVisualizer and DBeaver to connect to Vertica for SQL development purposes. It is easy to use these tools on a non-Kerberos enabled Vertica cluster, but connecting to a Kerberos-enabled Vertica cluster is not straightforward because there is no native support for Kerberos on tools like DbVisualizer and DBeaver. This...
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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...

Filtering Data While Loading into Vertica

Suppose you have a CSV file and you want to copy some, but not all, of its contents into a Vertica table. There are two ways you can to do this: • Use the SKIP keyword with COPY. • Use the head or tail Linux command. Let's see how this works. The Data Here's a...

Best Practices for Using LDAP Link with Vertica

There are a few best practices that you should follow to make sure that you don't accidentally lose any users or data. This blog explains how to keep your LDAP Link service working smoothly.

Post-upgrade Tasks for Saving Catalog Space

When you upgrade to 7.2 and later, not only can you take advantage of the

Introducing the Connector for Apache Spark

In Vertica version 8.0.0, we added integration for Apache Spark through our Vertica Connector for Apache Spark. This is a fast parallel connector that allows you to transfer data between Apache Spark and Vertica.

Troubleshooting Vertica Query Performance with System Tables

Do you want to learn how to troubleshoot your query performance issues?  We've got you covered. Just attend