JSON-CooP: A JSON Decompression/Parsing Co-Design for FPGAs

Big Data applications frequently involve the processing of data streams encoded in semi-structured data formats such as JSON. A major challenge here is that the parsing of such data formats is usually highly complex. Accelerating JSON parsing on FPGAs has therefore become a focus of recent research. However, as JSON data is highly sparse, compression is frequently applied before writing records to storage or transmitting them over the network. Consequently, the data must be decompressed before parsing it into a suitable format for further processing.While existing work has addressed decompression and parsing of semi-structured data separately, we propose a co-design for JSON decompression/parsing. This co-design includes a compression scheme tailored specifically for JSON, along with an FPGA parser architecture capable of operating directly on compressed input data. Additionally, our design adopts a lazy decompression approach to only decompress projected attributes, thereby significantly reducing the workload on the decompressor. Our experimental evaluation shows that this co-design exploiting several synergies results in higher resource efficiency compared to existing approaches for JSON parsing on FPGAs, while also enabling the decompression of data. For high compression factors, we observe a 1.8 x increase in parsed JSON tuples per second and LUT compared to the most efficient related approach. Moreover, our presented compression scheme offers higher compression factors for JSON data than related work while providing similar performance.