Shredding deeply nested JSON, one vector at a time by Laurens Kuiper - DuckDB Labs

[{
"description": "DSDSD - THE DUTCH SEMINAR ON DATA SYSTEMS DESIGN: We hold bi-weekly talks on Fridays from 3:30 PM to 5 PM CET for and by researchers and practitioners designing (and implementing) data systems. The objective is to establish a new forum for the Dutch Data Systems community to come together, foster collaborations between its members, and bring in high-quality international speakers. We would like to invite all researchers, especially also Ph.D. students, who are working on related topics to join the events. It is an excellent opportunity to receive feedback early on from researchers in your field.",
"Website": "https://dsdsd.da.cwi.nl/",
"Twitter": "  / dsdsdnl  ",
"title": "Shredding deeply nested JSON, one vector at a time",
"abstract": "JSON is a popular semi - structured data format. Despite being semi-structured, users often want to analyze it in a structured way, e.g., by analyzing JSON log files to find out what their users are doing.Analytical database systems would be the tool of choice for this, but these systems often cannot process semi - structured data or the nested data such as OBJECTs and ARRAYs found in JSON. DuckDB, however, supports efficient columnar STRUCT and LIST types and, therefore, supports the same nestedness as JSON. Since 0.7.0, DuckDB supports reading JSON files directly as if they were tables, with automatic schema detection. In this talk, I will explain how DuckDB reads JSON and transforms it into vectors for efficient analytics.",
"author": "Laurens Kuiper",
"bio": "Laurens is a PhD Student at the Database Architectures group at CWI in Amsterdam.He is also a Software Developer at DuckDB Labs. His research interests include OLAP systems, specifically graceful performance degradation when data sizes are larger than memory."
}]