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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

Produkt

December 16, 2025/6 min Lesezeit

Lakebase-Feiertags-Update

Databricks Free Edition Hackathon

Plattform

December 16, 2025/3 min Lesezeit

Bekanntgabe der Gewinner des ersten Databricks Free Edition Hackathons

acm-sigmod-blog-og-new

Neuigkeiten

June 15, 2022/5 min Lesezeit

Apache Spark und Photon erhalten SIGMOD-Auszeichnungen

tpc-benchmark-ds-blog-og

Data-Warehousing

November 2, 2021/10 min Lesezeit

Databricks stellt offiziellen Leistungsrekord für Data Warehousing auf

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

Produkt

September 8, 2021/6 min Lesezeit

Neue Leistungsverbesserungen in Databricks SQL

Plattform

January 30, 2020/7 min Lesezeit

Was ist ein Lakehouse?