Optimizing hash-array mapped tries for fast and lean immutable JVM collections

Abstract

The data structures under-pinning collection API (e.g. lists, sets, maps) in the standard libraries of programming languages are used intensively in many applications.The standard libraries of recent Java Virtual Machine languages, such as Clojure or Scala, contain scalable and well-performing immutable collection data structures that are implemented as Hash-Array Mapped Tries (HAMTs). HAMTs already feature efficient lookup, insert, and delete operations, however due to their tree-based nature their memory footprints and the runtime performance of iteration and equality checking lag behind array-based counterparts. This particularly prohibits their application in programs which process larger data sets.In this paper, we propose changes to the HAMT design that increase the overall performance of immutable sets and maps. The resulting general purpose design increases cache locality and features a canonical representation. It outperforms Scala's and Clojure's data structure implementations in terms of memory footprint and runtime efficiency of iteration (1.3-6.7 x) and equality checking (3-25.4 x).

Persistence for the masses: RRB-vectors in a systems language

“…We would like to apply the methodology and techniques developed in this work to other persistent data structures. Specially interesting are other wide-node trie based random access containers, like HAMT [Bagwell 2001] andCHAMP [Steindorfer andVinju 2015]. We anticipate that the relatively sparse nature of those data-structures (compared to RRB-Vectors) makes some optimizations more costly ( § 6.3.4) and alternatives need to be developed.…”

Enabling PHP software engineering research in Rascal

“…Recent work has focused on optimizing the sets (which are also used for relations) and maps in Rascal [31,32], with the latter [32] using control-flow graphs extracted by PHP AiR as part of the evaluation dataset. Work on PHP AiR has also led to improvements in Rascal libraries for statistics, for accessing external data sources, and for serializing large volumes of data.…”

“…This also enables easy experimentation at the algorithmic level. Memory performance is critical for this [31,32] since a common reason to not use such straightforward implementations is to increase performance.…”

“…There are still a number of cases where memory use or execution performance is unsatisfactory, but, more positively, these cases are driving improvements in the algorithms used in PHP AiR and in the implementation of Rascal [31,32].…”

Towards a software product line of trie-based collections

“…HAMTs constitute the basis for purely functional collections that are incrementally constructed and may refer to the unaltered parts of previous states [11,20]. In previous work we introduced the Compressed Hash-Array Mapped Prefixtree (CHAMP) [28], a cache-oblivious and canonical HAMT variant that improves the runtime efficiency of iteration (1.3-6.7 x) and equality checking (3-25.4 x) over its predecessor, while at the same time reducing memory footprints.…”