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https://doris.incubator.apache.org/blog/JD_OLAP

JD.com's exploration and practice with Apache Doris in real time OLAP - Apache Doris

This article discusses the exploration and practice of the search engine team in JD.com using Apache Flink and Apache Doris in real-time data analysis. The popularity of stream computing is increasing day by day: More papers are published on Google Dataflow; Apache Flink has become the one of the most popular engine in the world; There is wide application of real-time analytical databases more than ever before, such as Apache Doris; Stream computing engines are really flourishing. However, no engine is perfect enough to solve every problem. It is important to find a suitable OLAP engine for the business. We hope that JD.com's practice in real-time OLAP and stream computing may give you some inspiration.



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JD.com's exploration and practice with Apache Doris in real time OLAP - Apache Doris

https://doris.incubator.apache.org/blog/JD_OLAP

This article discusses the exploration and practice of the search engine team in JD.com using Apache Flink and Apache Doris in real-time data analysis. The popularity of stream computing is increasing day by day: More papers are published on Google Dataflow; Apache Flink has become the one of the most popular engine in the world; There is wide application of real-time analytical databases more than ever before, such as Apache Doris; Stream computing engines are really flourishing. However, no engine is perfect enough to solve every problem. It is important to find a suitable OLAP engine for the business. We hope that JD.com's practice in real-time OLAP and stream computing may give you some inspiration.



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https://doris.incubator.apache.org/blog/JD_OLAP

JD.com's exploration and practice with Apache Doris in real time OLAP - Apache Doris

This article discusses the exploration and practice of the search engine team in JD.com using Apache Flink and Apache Doris in real-time data analysis. The popularity of stream computing is increasing day by day: More papers are published on Google Dataflow; Apache Flink has become the one of the most popular engine in the world; There is wide application of real-time analytical databases more than ever before, such as Apache Doris; Stream computing engines are really flourishing. However, no engine is perfect enough to solve every problem. It is important to find a suitable OLAP engine for the business. We hope that JD.com's practice in real-time OLAP and stream computing may give you some inspiration.

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      This article discusses the exploration and practice of the search engine team in JD.com using Apache Flink and Apache Doris in real-time data analysis. The popularity of stream computing is increasing day by day: More papers are published on Google Dataflow; Apache Flink has become the one of the most popular engine in the world; There is wide application of real-time analytical databases more than ever before, such as Apache Doris; Stream computing engines are really flourishing. However, no engine is perfect enough to solve every problem. It is important to find a suitable OLAP engine for the business. We hope that JD.com's practice in real-time OLAP and stream computing may give you some inspiration.
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