Databricks, inc. (20240378181). AUTO MAINTENANCE FOR DATA TABLES IN CLOUD STORAGE simplified abstract

AUTO MAINTENANCE FOR DATA TABLES IN CLOUD STORAGE

Organization Name

databricks, inc.

Inventor(s)

Vijayan Prabhakaran of San Francisco CA (US)

Himanshu Raja of San Francisco CA (US)

Rahul Potharaju of San Francisco CA (US)

Naga Raju Bhanoori of San Francisco CA (US)

Lin Ma of San Francisco CA (US)

Rajesh Parangi Sharabhalingappa of San Francisco CA (US)

Jintian Liang of San Francisco CA (US)

Zach Schuermann of San Francisco CA (US)

Kam Cheung Ting of San Francisco CA (US)

AUTO MAINTENANCE FOR DATA TABLES IN CLOUD STORAGE - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240378181 titled 'AUTO MAINTENANCE FOR DATA TABLES IN CLOUD STORAGE

The configuration described in the patent application manages the organization of data tables in cloud-based storage by receiving metrics for data processing operations on the data table, including the size of the data table, the size of each file in the data table, and metadata describing the data table. The configuration then automatically executes a cost-benefit analysis for each candidate maintenance operation based on these metrics, selecting and automating the most beneficial maintenance operation for the data table.

• The configuration manages the organization of data tables in cloud-based storage.
• Metrics for data processing operations on the data table are received, including size and metadata.
• A cost-benefit analysis is automatically executed for candidate maintenance operations.
• The most beneficial maintenance operation is selected and automated for the data table.

1. 1. 1. Potential Applications:

This technology can be applied in various industries that rely on cloud-based storage systems, such as e-commerce, healthcare, finance, and more. It can streamline data management processes and optimize storage efficiency.

1. 1. 1. Problems Solved:

This technology addresses the challenges of efficiently organizing and maintaining data tables in cloud-based storage systems. It automates the selection of maintenance operations based on cost-benefit analysis, saving time and resources for organizations.

1. 1. 1. Benefits:

- Improved data table organization and maintenance - Cost-effective storage management - Enhanced efficiency in data processing operations - Automated selection of maintenance operations based on metrics

1. 1. 1. Commercial Applications:

The technology can be utilized by cloud service providers, data management companies, and organizations with large-scale data storage needs. It offers a competitive advantage by optimizing data table organization and maintenance processes.

1. 1. 1. Prior Art:

For prior art related to this technology, researchers can explore existing patents or publications in the field of cloud storage management, data processing, and automation technologies.

1. 1. 1. Frequently Updated Research:

Researchers and developers in the field of cloud storage management are continuously exploring new methods and technologies to improve data organization and maintenance in cloud-based systems. Stay updated on the latest research in this area to leverage advancements in the field.

1. 1. 1. 1. Questions about Data Table Organization Configuration:

1. How does the configuration automate the selection of maintenance operations for data tables? 2. What are the key metrics considered in the cost-benefit analysis for maintenance operations?

Original Abstract Submitted

disclosed is a configuration for managing the organization of data tables in cloud-based storage. the configuration receives metrics for data processing operations on the data table. metrics include at least one of a size of the data table, a size of each file in the data table, and metadata describing the data table. the configuration automatically executes a cost-benefit analysis based on the one or more metrics for each candidate maintenance operation in a plurality of candidate maintenance operations. the configuration automatically selects a maintenance operation from the candidate maintenance operations to automate based on the cost-benefit analysis of the one or more candidate maintenance operations. the selected maintenance operation is automated and scheduled on the data table.