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Quick start: pip install jsoniq โ›ˆ๏ธ RumbleDB 3.1.0 "Pistachio Tree" ๐ŸŒณ for Apache Spark | Run queries on your large-scale, messy datasets (JSON, text, CSV, Parquet, Delta...) | Data Lakehouse with Updates, Scripting, Declarative Machine Learning and more

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README.md

Original

RumbleDB

With RumbleDB, you can query with ease a lot of different nested, heterogeneous data formats like JSON, CSV, Parquet, Avro, LibSVM, text, etc.

XML Schema imports and schema validation currently support XML Schema 1.0 only. Schemas requiring XML Schema 1.1 are not supported.

RumbleDB exposes a query language rather than a DataFrame API, for more flexibility, more productivity but also because a lot of data simply will not fit in DataFrames.

You can query it in place from any local file systems or data lakes (Azure blob storage, Amazon S3, HDFS, etc).

You can prepare, clean up, validate your data and put it right into your machine learning pipelines with RumbleDB ML.

Getting started: you will find a Jupyter notebook that introduces the JSONiq language on top of RumbleDB here. You can also run it locally if you prefer.

The documentation also contains an introduction specific to RumbleDB and how you can read input datasets, but we have not converted it to Jupyter notebooks yet (this will follow).

The documentation of the latest official release is available here.

RumbleDB was started in February 2017 at ETH Zurich as the Master's thesis of Stefan Irimescu, under the supervision of Ghislain Fourny and Gustavo Alonso.

Contributors (Ghislain Fourny's students at ETH): Stefan Irimescu, Renato Marroquin, Rodrigo Bruno, Falko Noรฉ, Ioana Stefan, Andrea Rinaldi, Stevan Mihajlovic, Mario Arduini, Can Berker ร‡ฤฑkฤฑลŸ, Elwin Stephan, David Dao, Zirun Wang, Ingo Mรผller, Dan-Ovidiu Graur, Thomas Zhou, Olivier Goerens, Alexandru Meterez, Pierre Motard, Remo Rรถthlisberger, Dominik Bruggisser, David Loughlin, David Buzatu, Marco Schรถb, Maciej Byczko, Abishek Ramdas, Matteo Agnoletto, Dwij Dixit, Omar Hammoud, Henrik Pรคtzold, Jimmy Cai.

XML Schema version semantics

Use --xsd-version 1.0 or --xsd-version 1.1 (default) to select datatype casting and regular-expression semantics. This is independent of --xml-version. The Java configuration key is semantics.xsdVersion; the typed builder exposes configureSemantics(s -> s.xsdVersion("1.0")).

Schema import and XML validation continue to use Xerces XSD 1.0 in both modes. Selecting 1.1 does not enable XSD 1.1 schema features such as multiple substitution groups.