Rumble 1.8.0 "Scots pine"

New features

• Support for joining two large datasets; automatic detection of joins if a for expression is a predicate expression, and the left-hand side can be evaluated independently of the former clauses. The right-hand-side is the joining criterion. Left outer joins are also supported in parallel (allowing empty).
• outer joins ("allowing empty" in a for clause) are now supported both locally and in parallel.
• support for empty sequence order least/greatest prolog setter (for order by clauses)
• positional variables in for clauses are now supported both locally and in parallel (except for large-scale joins).
• arbitrary large integer literals are now supported (an error was thrown before beyond 32 bits)
• json-file() and json-doc() can both read over HTTP
• you can store your JSONiq modules on the Web and import them with an HTTP URL
• you can store your queries on the Web and execute them via the Rumble command line with their URL
• an error with the appropriate code is now thrown if a collation is specified that is not supported (the W3C standard requires support for at least the Unicode codepoint collation, which Rumble recognizes and supports).
• It is now possible to specify a hostname in the server mode (--host), and to filter for specific URI prefixes for security reasons (--allowed-uri-prefixes)

Bugfixes

• big integers are now seamlessly supported: no more overflows, and arbitrary large integer literals are accepted in JSONiq code
• fixed display bugs in debug mode (--print-iterator-tree yes)
• fixed an error with local group-by queries nested inside local FLWORs
• fixed an error when counting items in a variable that was not a post-grouping variable, in parallelized FLWORs.
• fixed a bug encountered when a local iteration followed by a parallel for clause produced, and unioned, several Spark jobs internally.

Important: The jar for Spark 3.0.0 does not have Laurelin (ROOT parser) support. We are waiting for a 3.0.0-compatible Laurelin release. If you need to query ROOT files, please use Spark 2.4.6.