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Reynold Xin

Reynold Xin

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Reynold oversees technical contributions to Apache® Spark™ at Databricks, initiating efforts such as DataFrames and Project Tungsten. To demonstrate Spark’s scalability and performance, he lead the efforts in the 2014 Daytona GraySort contest and set the 2014 world record, beating the previous record held by Hadoop with 30X higher per-node efficiency. Prior to Databricks, he was a PhD student at the UC Berkeley AMPLab, where he focused on scalable data processing. He wrote the highest cited papers in SIGMOD 2011, 2013, and 2015, and won Best Demo Award at VLDB 2011 and SIGMOD 2012.

Reynold Xin's posts

Lakebase Holiday Upgrade includes branching, autoscaling, and a host of other features

Producto

December 16, 2025/7 min de lectura

Actualización de fin de año de Lakebase

Databricks Free Edition Hackathon

PLATAFORMA

December 16, 2025/3 min de lectura

Anunciamos los ganadores del Hackathon inaugural de Databricks Free Edition

acm-sigmod-blog-og-new

Noticias

June 15, 2022/6 min de lectura

Apache Spark y Photon reciben premios SIGMOD

tpc-benchmark-ds-blog-og

Almacenamiento de datos

November 2, 2021/12 min de lectura

Databricks establece el récord oficial de rendimiento de almacenamiento de datos

The initial release of Databricks SQL offered significant performance benefits -- up to 6x price/performance -- compared to traditional cloud data warehouses as per the TPC-DS 30 TB scale benchmark

Producto

September 8, 2021/7 min de lectura

Nuevas mejoras de rendimiento en Databricks SQL

PLATAFORMA

January 30, 2020/8 min de lectura

¿Qué es un Lakehouse?