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An immutable multi-map is a many-to-many thread-friendly map data structurewith expected fast insert and lookup operations. This data structure is usedfor applications processing graphs or many-to-many relations as applied instatic analysis of object-oriented systems. When processing such big data setsthe memory overhead of the data structure encoding itself is a memory usagebottleneck. Motivated by reuse and type-safety, libraries for Java, Scala andClojure typically implement immutable multi-maps by nesting sets as the valueswith the keys of a trie map. Like this, based on our measurements the expectedbyte overhead for a sparse multi-map per stored entry adds up to around 65B,which renders it unfeasible to compute with effectively on the JVM.  In this paper we propose a general framework for Hash-Array Mapped Tries onthe JVM which can store type-heterogeneous keys and values: a HeterogeneousHash-Array Mapped Trie (HHAMT). Among other applications, this allows for ahighly efficient multi-map encoding by (a) not reserving space for empty valuesets and (b) inlining the values of singleton sets while maintaining a (c)type-safe API.  We detail the necessary encoding and optimizations to mitigate the overheadof storing and retrieving heterogeneous data in a hash-trie. Furthermore, weevaluate HHAMT specifically for the application to multi-maps, comparing themto state-of-the-art encodings of multi-maps in Java, Scala and Clojure. Weisolate key differences using microbenchmarks and validate the resultingconclusions on a real world case in static analysis. The new encoding bringsthe per key-value storage overhead down to 30B: a 2x improvement. Withadditional inlining of primitive values it reaches a 4x improvement.

Fast and Lean Immutable Multi-Maps on the JVM based on Heterogeneous Hash-Array Mapped Tries