JSON is one of the most popular data encoding formats, with wide adoption in Databases and BigData frameworks as well as native support in popular programming languages such as JavaScript/Node.js, Python, and R. Nevertheless, JSON data processing can easily become a performance bottleneck in data-intensive applications because of parse and serialization overhead. In this paper, we introduce Fad.js, a runtime system for efficient processing of JSON objects in data-intensive applications. Fad.js is based on (1) speculative just-in-time (JIT) compilation and (2) selective access to data. Experiments show that applications using Fad.js achieve speedups up to 2.7x for encoding and 9.9x for decoding JSON data when compared to state-of-the art JSON processing libraries.
Bonetta et al. introduce FAD.js, a runtime system for processing JSON objects that is based on speculative justin-time (JIT) compilation and selective access to data REF .
FAD.js: Fast JSON Data Access Using JIT-based Speculative Optimizations
PVLDB
PVLDB
Computer Science