Chetan Khatri
where else to find them
what they talk about
where they keep going back
- ScalaIO2 editions2018–2019
on a stage with
never shared a talk
who talks about the same things
- Kamil Owczarek6 talks
- Rasik Pandey2 talks
- Antonio Murgia3 talks
- Vincent Heuschling8 talks
- Andy Petrella14 talks
- Xavier Tordoir4 talks
| title | conference | date |
|---|---|---|
| Challenges that everyone struggles while productionizing Apache Spark workloads | ScalaIO 2019 | 2019-10-29 |
Migrating a 25,000‑line SQL ETL to Spark produces concrete wins: parallel JDBC with partition bounds boosts read concurrency, using lower/upper bounds and… | ||
| No more struggles with Apache Spark (PySpark) workloads in production | PyConZA 2019 | 2019-10-09 |
Covers concrete fixes: use PyArrow to avoid Python/Numpy/Pandas serialization bottlenecks, prefer JDBC parallel reads with numeric lower/upper bounds and… | ||
| TransmogrifAI - Automate ML Workflow with power of Scala and Spark at massive scale. | ScalaIO 2018 | 2018-10-29 |
In spite of huge progress in Artificial Intelligence and Machine Learning over the past decade, building production ready enterprise scale machine learning… | ||
| nothing matches | ||