Category: Metatron Discovery

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Time Series Data Analysis Using Metatron Discovery

Metatron Discovery utilizes Druid as a data processing engine, and thus has many strengths in analyzing large time series based data. Metatron Discovery was developed to take full advantage of these features of Druid. In this example, we will explain how to analyze time series data using Metatron Discovery through an example. Visualizing time series…
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Data Preparation and Continuous Integration

After creating a nice dataflow, you’ll probably want to reuse the dataflow against another file or query result automatically (like daily-basis) or manually. Metatron Discovery’s data swapping feature is developed to enable this kind of works. Although Metatron Discovery itself doesn’t have scheduling ability, but you can use preptool, a CLI tool for data preparation…
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Deploying Metatron with the Fully Engineered Docker Image

Metatron Discovery is a very useful BI solution that contains from data preparation to end-user visualization, but because of that wide coverage, the required components are rather more than other independent solutions, so installation, configurations could be very tiresome. Supporting clients of ours, I felt that if we could deploy as a docker image at…
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Using Apache Spark in Data Preparation

Recently, Discovery Spark Engine has been introduced in Metatron Discovery. It is an external ETL engine based on Spark SQL. The embedded engine suffers huge garbage collection pressure if the record count reaches more than 1M. In this case, Discovery Spark Engine is the best solution. To avoid complex dependency problems, Discovery Spark Engine is…
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