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Integrating with Apache Spark

The Vertica Connector for Apache Spark is a fast parallel connector that allows you to use Apache Spark for pre-processing data. Apache Spark is an open-source, general purpose, cluster-computing framework. The Spark framework is based on Resilient Distributed Datasets (RDDs), which are logical collections of data partitioned across machines. For more information, see the Apache...

Working with Joins

This blog post was authored by Soniya Shah. Vertica supports a variety of join types. This post discusses the following joins: • Inner joins • Left, right, and full outer joins • Natural joins • Cross joins In Vertica, we refer to the tables participating in the join as left or right. The left table...
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Time Series Analytics

This blog post was authored by Soniya Shah. Time series analytics is a powerful Vertica tool that evaluates the values of a given set of variables over time and groups those values into a window based on a time interval for analysis and aggregation. Time series analytics is useful when you want to analyze discrete...

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Building a Secure Vertica Environment

This blog post was authored by Soniya Shah. Vertica has a client-server architecture system, where applications that reside on the client access the Vertica cluster through drivers including ODBC, JDBC, OLEDB and ADO.NET. This post discusses secure client to server communications, authenticating access to Vertica, and administrator access. Method Vertica Options Authentication: Validate user credentials...
Modern Database Analytics

Vertica Presentation at the db tech showcase Tokyo 2017

On September 5th, Kanako Obayashi from the Vertica Best Practices team presented at the db tech showcase Tokyo 2017, one of the largest database events in Japan. Kanako's presentation was about Vertica advanced analytics, including machine learning and geospatial analysis. More than 50 people attended her session. Kanako began her session by noting that more...
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What’s New in Vertica 8.1.1: Flex Parser Updates

This blog post was authored by Soniya Shah. Vertica 8.1.1 introduces an optional parameter to the FCSVPARSER function. The FCSVPARSER specifies how to load data into Vertica from a CSV data source. The new parameter allows you to define or override column names in the target file for data loaded from a CSV data source....

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