One feature of Data Pipeline is its ability to aggregate data without a database. This feature allows you to apply SQL “group by” operations to JSON, CSV, XML, Java beans, and other formats on-the-fly — in real-time. This quick tutorial will show you how to use the GroupByReader class to aggregate Twitter search results.
Data Pipeline 3.1 is now available for download. This is a milestone release that adds native support for hierarchical data (nested records and multidimensional arrays).
Data Pipeline now includes a new AsyncMultiReader endpoint that lets you read from multiple DataReaders in parallel. Here’s how it works.
Data Pipeline makes it easy to read, transform, and write XML and Excel files. This post shows you how you too can load data from an on-disk XML file, apply transformations on the fly, and save the result to an Excel file.
Data Pipeline lets you read, write, and convert Excel files using a very simple API. This post will show you how to create Excel files containing more than one work sheet or tab.
We’re pleased to announce the release of version 3.0 of our Data Pipeline engine.
This release includes the new Sliding Window Aggregations feature to perform continuous SQL group-by operations on streaming data.
We’ve improved the performance of the XPath based readers (JsonReader, XmlReader, and JavaBeanReader), included new conveniences to reduce your code size, and added several new transformers and filters.
We’re also now offering a free 30-day trial for you to take the premium and enterprise features out for a test drive.
A new release of Data Pipeline is now available for download: https://northconcepts.com/downloads/. This release includes a new Twitter search reader, custom aggregate operations, and much more.
Data Pipeline’s query engine allows you to use XPath to query XML, JSON, and Java objects. This walkthrough will show you how to query Java objects using XPath and save the results to a CSV file. While the reading and writing will be done with the JavaBeanReader and CSVWriter classes, you can swap out the CSVWriter for any other endpoint or transformation that Data Pipeline supports. Continue reading
This blog will show you how to pull selected columns from a CSV file containing IP geolocation data and save them into a second CSV file using our Data Pipeline Java library. As part of the transformation, you’ll also have the option to rearrange the order of the resulting columns.
This blog will demonstrate how to upload Excel and CSV files into a database while using Data Pipeline to handle the differences in format and structure of the individual files. Continue reading