Automatic Database Tuning with Andy Pavlo

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Podcast – Software Engineering Daily द्वारा - Player FM और हमारे समुदाय द्वारा खोजे गए - कॉपीराइट प्रकाशक द्वारा स्वामित्व में है, Player FM द्वारा नहीं, और ऑडियो सीधे उनके सर्वर से स्ट्रीम किया जाता है। Player FM में अपडेट ट्रैक करने के लिए ‘सदस्यता लें’ बटन दबाएं, या फीड यूआरएल को अन्य डिजिटल ऑडियो फ़ाइल ऐप्स में पेस्ट करें।

The default configuration in most databases is meant for broad compatibility rather than performance. Database tuning is a process in which the configurations of a database are modified to achieve optimal performance. Databases have hundreds of configuration knobs that control various factors, such as the amount of memory to use for caches or how often the data is written to the storage.

The problem with these knobs is that

  • they are not standardized (i.e., two databases may have a different name for the same knob),
  • not independent (i.e., changing one knob can impact others),
  • and not universal (i.e., what works for one application may be suboptimal for another).

In reality, information about the effects of the knobs typically comes only from (expensive) experience.

OtterTune is automatic database tuning software that promises to overcome these problems. It uses machine learning to tune the configuration knobs of your database automatically to improve performance.

In this episode, we interview Andy Pavlo. Andy is a Database Professor at Carnegie Mellon and Co-Founder of OtterTune.

Sponsorship inquiries: sponsor@softwareengineeringdaily.com

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