The General Data Protection Regulation (GDPR) is a regulation in the European Union (EU) that aims to protect the privacy and personal data of EU citizens. It requires organizations to implement measures to ensure the security and privacy of personal data, including the ability to delete data upon request. In addition, organizations must maintain logs of data processing activities to demonstrate compliance with GDPR.
Apache Hudi is an open-source data management framework that provides efficient data ingestion, storage, and processing capabilities. Amazon EMR is a managed big data platform that allows organizations to run Apache Hudi on a scalable and cost-effective infrastructure.
Zoom, a video conferencing company, has implemented efficient GDPR deletion and streaming log ingestion using Apache Hudi on Amazon EMR. This case study provides insights into Zoom’s approach and the benefits of using Apache Hudi on Amazon EMR for GDPR compliance.
Efficient GDPR Deletion
Zoom’s approach to GDPR deletion involves using Apache Hudi’s incremental ingestion and merge-on-read capabilities. When a user requests the deletion of their personal data, Zoom identifies the relevant data using metadata tags and deletes it from the Hudi dataset. The deletion is performed incrementally, which means that only the affected data is deleted, reducing the time and resources required for the deletion process.
In addition, Apache Hudi’s merge-on-read capability allows Zoom to merge the deleted data with the existing dataset during query time. This ensures that the deleted data is not visible to users and does not affect the accuracy of analytics or machine learning models.
Streaming Log Ingestion
Zoom’s approach to streaming log ingestion involves using Apache Hudi’s support for Apache Kafka and Amazon Kinesis. Zoom’s video conferencing platform generates a large volume of log data, which is ingested into Apache Kafka or Amazon Kinesis in real-time. Apache Hudi then processes the log data and stores it in a Hudi dataset.
Apache Hudi’s support for incremental ingestion and merge-on-read allows Zoom to efficiently process and store the log data. This enables Zoom to analyze the log data in real-time and identify potential security or privacy issues, as well as monitor compliance with GDPR.
Benefits of Using Apache Hudi on Amazon EMR
Using Apache Hudi on Amazon EMR provides several benefits for GDPR compliance. First, it allows organizations to efficiently delete personal data upon request, reducing the time and resources required for the deletion process. Second, it enables organizations to ingest and process large volumes of log data in real-time, allowing them to monitor compliance with GDPR and identify potential security or privacy issues.
In addition, using Apache Hudi on Amazon EMR provides a scalable and cost-effective infrastructure for data management. Amazon EMR allows organizations to easily scale their infrastructure up or down based on their needs, reducing the cost of maintaining a large infrastructure.
Conclusion
Implementing efficient GDPR deletion and streaming log ingestion is essential for organizations to comply with GDPR. Apache Hudi provides a powerful data management framework that enables organizations to efficiently manage their data and comply with GDPR. Using Apache Hudi on Amazon EMR provides a scalable and cost-effective infrastructure for data management, allowing organizations to efficiently manage their data and comply with GDPR. Zoom’s approach to GDPR deletion and streaming log ingestion using Apache Hudi on Amazon EMR provides a valuable case study for organizations looking to implement efficient GDPR compliance measures.
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- Source: https://zephyrnet.com/how-zoom-implemented-streaming-log-ingestion-and-efficient-gdpr-deletes-using-apache-hudi-on-amazon-emr-amazon-web-services/