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From the 1 of 6 linked papers with an AI index.

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6 papers

cs.DB2026

Bespoke-Card: Why Tune When You Can Generate? Synthesizing Workload-Specific Cardinality Estimators

Johannes Wehrstein, Anton Winter, Timo Eckmann +1

Bespoke-Card is an agent-driven system that automatically generates workload‑specific cardinality estimators as executable code, improving PostgreSQL query optimizer accuracy and r…

cs.DB2026

Redbench: Workload Synthesis From Cloud Traces

Johannes Wehrstein, Roman Heinrich, Mihail Stoian +5

Workload traces from cloud data warehouse providers reveal that standard benchmarks such as TPC-H and TPC-DS fail to capture key characteristics of real-world workloads, including…

cs.DB2026

Bespoke OLAP: Synthesizing Workload-Specific One-size-fits-one Database Engines

Johannes Wehrstein, Timo Eckmann, Matthias Jasny +1

Modern OLAP engines are designed to support arbitrary analytical workloads, but this generality incurs structural overhead, including runtime schema interpretation, indirection lay…

cs.DB2025

JOB-Complex: A Challenging Benchmark for Traditional & Learned Query Optimization

Johannes Wehrstein, Timo Eckmann, Roman Heinrich +1

Query optimization is a fundamental task in database systems that is crucial to providing high performance. To evaluate learned and traditional optimizer's performance, several ben…

cs.DB2025

GRACEFUL: A Learned Cost Estimator For UDFs

Johannes Wehrstein, Tiemo Bang, Roman Heinrich +1

User-Defined-Functions (UDFs) are a pivotal feature in modern DBMS, enabling the extension of native DBMS functionality with custom logic. However, the integration of UDFs into que…

cs.DB2025

How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks

Roman Heinrich, Manisha Luthra, Johannes Wehrstein +2

Traditionally, query optimizers rely on cost models to choose the best execution plan from several candidates, making precise cost estimates critical for efficient query execution.…