Tow page of the lecay white paper "Applying Apache Pulsar SQL to Zhaopin's Search Log Analysis Significantly Improved Search and Query Efficiency"

Applying Apache Pulsar SQL to Zhaopin's Search Log Analysis Significantly Improved Search and Query Efficiency

As one of the largest online recruiting and career platforms in China, Zhaopin has 140 million active users and 4 million cooperative companies. Zhaopin provides a high-quality user experience in which job search services play a critical role. Zhaopin’s job search services support a large number of user search requests every day and generate large-scale search logs. These logs are extremely valuable and can be used for troubleshooting or Big Data analysis.

In an effort to improve their job search service and user experience, Zhaopin added Pulsar SQL to their existing Pulsar implementation. Pulsar SQL gives Zhaopin the ability to refine queries by using certain parameters that limit the amount of data that needs to be searched. Pulsar SQL also provides various reports that the company uses to analyze and aggregate data. This article covers some typical usage scenarios at Zhaopin and explains how Pulsar SQL enables the company to query streaming data more efficiently.

Zhaopin is constantly exploring new ways to use their search logs effectively and Pulsar continues to provide inspiration for the company’s efforts.

picture of ran gao from streamnative
Ran Gao
Ran Gao is a software engineer at StreamNative. Before that, he was responsible for the development of search service at Prior to that, he worked on the development of the logistics system at JD Logistics. Being interested in open source and messaging systems, Ran is an Apache Pulsar committer.


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