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Johannes Wehrstein

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.DB3

identity via Semantic Scholar / OpenAlex

collaborators

3 papers

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.…

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