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[ANN] Rumble 1.9.0

• From: "Ghislain Fourny" <gfourny@inf.ethz.ch>
• To: "xml-dev@lists.xml.org" <xml-dev@lists.xml.org>, "talk@x..."<talk@x...>
• Date: Wed, 28 Oct 2020 16:10:26 +0000

Dear all,

We are happy to announce the release of Rumble 1.9.0 "Ficus Bonsai".

It is a free, open source JSONiq engine (JSON-tuned cousin of XQuery), and can be downloaded as a jar from

  https://rumbledb.org/

or you can directly try out a JSONiq tutorial running on our public backend in your browser (it is a Jupyter notebook running on Google's Colab) from

  https://bit.ly/3jARuUU

(this public backend is just one small machine for small queries -- if you need a larger Spark cluster, you can create one on your favorite cloud provider, e.g., Amazon EMR, in a few minutes, connect to it, download the Rumble jar and start querying)


New features (since the previous announcement of version 1.7.0 in this list) include:

- Detection of joins in many forms: two for clauses binding large sequences with a predicate in the second one (with support for allowing empty for left outer joins), two for clauses binding large sequences followed by a where clause, or a let clause binding a large sequence with a predicate, for "group joins" (to denormalize data easily).

- Efficient evaluation of equi-joins (pushed down to Spark) if the predicate involves equality comparison of (arbitrary) expressions from each side (or conjunctions thereof).

- Support for positional variables.

- Outputing large quantities of structured data to other formats: avro, parquet, csv, etc. This allows using Rumble to easily clean up a messy dataset with JSONiq, structure it, annotate it, and output it in a structured format, or to easily convert from one format to another, and use it in turn as input to another JSONiq query, or as input to a Python script for visualization with your favorite libraries (pie charts, etc).

- Various performance improvements and bugfixes.



Kind regards,
Ghislain Fourny