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Vertica Big Data Conference 2020 – Are You Excited Yet?

The Vertica Big Data Conference (BDC) clock is ticking and my excitement is growing by the minute! I want to make sure that our Vertica community is up to date on the latest news, especially some of the General Session speakers and Breakout tracks. And let’s not forget one of the most special components of...
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Vertica and Amazon – Better Together, for Years

The year was 2012. Marvel’s The Avengers hit the box office. Facebook went public. NASA's Curiosity rover landed on the surface of Mars. And, the Vertica AMI (Amazon Machine Image) made its debut on , enabling data-driven organizations to easily deploy Vertica on the Amazon cloud and start accelerating their analytics. Running Vertica on Amazon...
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Checking and Improving Column Compression and Encoding

When working with terabytes of data, storage and transfer become major time and cost sinks. Vertica can help minimize storage cost and transfer time with column compression and encoding. How can we identify Vertica tables that might benefit from compression? Information about column size and current compression is stored across column_storage and projection_columns table. The...
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Complex Data Types in SQL 1 – What Are They?

Co-authored by James Clampffer, Deepak Majeti. A lot of projects require querying ORC or Parquet files, or other data that may have internal types that are a bit more complex than usual. We support some of those complex types now, and are dedicated to adding full support for all complex types in Vertica. It’s a...
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Get the Row Count from an Outer Table Join

Aggregate functions summarize data over groups of rows from a query result set. When using an aggregate function like COUNT with an "*" or "1" parameter value, you may get a different result when the query implements a LEFT join verses an INNER join. If you want a row count of just the rows from...

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DIRECT Is Now the Default Load Type

Write Optimized Store (WOS) is a memory-resident data structure for short-term data storage while Read Optimized Store (ROS) is a highly optimized, read-oriented, disk storage structure, organized by projection. Prior to Vertica 9.3, by default, Vertica initially loads data into WOS. For databases created in version 9.3 and later, Vertica now uses a default load...
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Vertica 9.3 Supports UPDATE and DELETE Operations on Tables Having Live Aggregate Projections!

A live aggregate projection contains columns with values that are aggregated from columns in its anchor table. When you load data into the table, Vertica aggregates the data before loading it into the live aggregate projection. On subsequent loads (for example, through INSERT or COPY) Vertica recalculates aggregations with the new data and updates the...
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Parallel Processing Using Partitions With Vertica UDx

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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Datadog Announces Integration with Vertica to Monitor Performance and Availability

Datadog helps customers ensure high performance and availability of their applications by providing visibility into the full application stack: infrastructure, middleware, and applications. They have achieved this by building a robust set of turn-key integrations that include SaaS and Cloud solutions, automation tools, databases and server components, and many more. Now, they have announced integration...
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Extending Vertica with Python functions: Adding NumPy FFT as a UDx

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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Can a 100-Year Old Business Innovate with IoT Analytics?

One of my greatest pleasures is dining out at all the amazing restaurants here in the Raleigh, Durham and Chapel Hill area of North Carolina. I am always amazed and so proud of the innovative and authentic ethnic cuisines that have made the Triangle a nationally recognized foodie community. I think about the complexities of...
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Finding the “K” in K-means Clustering With a UDx

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...