My name is Immanuel, I'm a professor at Cornell University. I mostly publish code that relates to my research, which is about databases and data analysis.
thalamusdb. ThalamusDB: semantic query processing on multimodal data
117CodexDB. CodexDB generates code for SQL query processing via OpenAI's GPT-3 Codex model.
102dbbert. DB-BERT tunes database systems for optimal performance, using tuning hints mined from text.
63DataScienceWithGPT. Resources to learn data processing with GPT and other language models
21DataCorrelationPredictionWithNLP. This project aims at predicting correlated column pairs in data tables by analyzing column names via large language models.
11query-optimizer-lib. Contains implementations of various algorithms for database query optimization. The algorithms cover multiple problem variants (e.g., traditional and multi-objective query optimization) and offer different tradeoffs between optimality guarantees and optimization time (e.g., fast randomized algorithms, approximation schemes, exhaustive algorithms, parallel algorithms, ...).
10lm4db. Material for my VLDB'22 and BTW'23 tutorials on application for language models in data management
9schemacompression. Compress database schemata to reduce cost for LLM processing
7CiceroDBoldVersion. Java
6llmjoins. Implements theta-joins with free-text join predicates using large language models.
6itrummer.github.io. Personal page of Immanuel Trummer.
3qdata. HTML
2NaturalMiner. Mine data for patterns described in natural language
2ExactCardinalityQueryOptimization. This repository contains tools for finding query plans that produce the least number of join result tuples (the so-called "Cout" metric). Those tools are not suitable for query optimization at run time - instead, they can be used for offline analysis to assess the quality of query optimizers.
2vta. Frontend for virtual TA
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