OLAP & Data Analysis

Track Chairs : Mingyu Chen, Zhijing Lu, Dianjin Wang

With the advent of the big data era, the application of data analysis and OLAP technology in enterprises is becoming more and more widespread. In order to promote communication and sharing in this field in the industry, we have set up the OLAP and Data Analysis Track. We hope to invite experts and scholars in the industry to share their research results, practical experience, and latest developments in data analysis and OLAP technology.

In ASF, there are various projects about OLAP and data analysis, for example: Apache Doris, Apache Druid, Apache Kylin, Apache Pinot, Apache Hawq etc.

The topic can cover research progress, application cases, best practices, performance optimization, and other aspects of data analysis and OLAP technology. We believe it will greatly bring great benefits to the attendees.

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Accelerating Spark jobs with Apache Gluten at ByteDance Scale Chinese Session Weiting Chen

Apache Doris Implementation Practice in Cainiao's Large Scale Business Scenarios Chinese Session Xiao Huang

Data Security Analysis Practices Based on Apache Doris in China Telecom Bestpay Chinese Session Jianqun liu

Data Warehouse Virtualization Technology Based on Apache Calcite Chinese Session Jiajun Xie

Dive into Vectorized Execution for Apache Cloudberry: Design, Challenges, and Performance Gains Chinese Session Zhang Yue

History based optimizations for SparkSQL Chinese Session He Zhengjie

Inside the Directory Table of Apache Cloudberry Chinese Session Wenchao Zhang

Optimization and practice of Doris on Paimon in Xiaomi Chinese Session Wang Long

The practice of Apache Doris in the trusted data space of China Unicom Digital Intelligence Company Chinese Session Zhuyuan Yang

What’s New in Apache Impala 4.5: Iceberg, Performance & More Chinese Session Quanlong Huang