Apache Avro Tools

Avro viewer

Avro Functionality:

  • Avro View for visualizing and searching binary Avro instances
  • Tabular view of Avro instances for easy viewing
  • Avro schema editing
  • Context sensitive entry-helpers
  • Text view with syntax coloring, source folding, & more
  • Structural marking to match brackets / braces
  • Grid view for graphical Avro schema editing
  • Avro schema validation
  • Avro data validation

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Avro Tools

Apache Avro™ is a data serialization standard that is widely used for a compact, fast, binary serialization of big data, most often used within the Apache Hadoop software framework. Avro data can be serialized in binary format or JSON format, and XMLSpy supports both.

To help customers working with Avro files, XMLSpy supports both editing and validation of Avro schemas (.avsc), as well as a special Grid View for viewing and searching Avro binaries (.avro) graphically.

Despite its widespread use, there were no tools available for working with Avro data visually, until XMLSpy pioneered its user-friendly Avro View.

Avro View

Shown above, the unique Avro View in XMLSpy displays the Avro data structures in an easy-to-read tabular format, making it easy to view, understand, and search the binary file.

Because Avro files are often extremely large, a Blocks pane organizes the data into groups of 1,000 that can be expanded or collapsed. To view the data in a particular block, simply double click it.

You can also view and/or save the associated Avro schema from the Blocks pane if desired.

Avro schema editor

Avro Schema Editor and Validator

An Avro data structure is defined in an Avro schema, which is written in JSON format. XMLSpy has built in support for editing Avro schemas in Text or Grid View. (When Avro data documents are in JSON format, they may also be edited in XMLSpy.)

Grid View provides an easy way to visualize and edit the document structure, while editing in Text View (shown to the left) provides context-sensitive keyword suggestions, automatic entry of bracket, brace, and quote pairs, syntax coloring, and auto-completion of keywords. Additionally, there are three intelligent, context-sensitive entry helper windows that help you make valid editing choices: JSON Properties, JSON Values, and JSON Entities.

During editing, your Avro schema is validated against the Avro schema definition. You can also validate data documents against their associated Avro schema in XMLSpy.

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