18744221. METHOD AND SYSTEM FOR LOCK AFTER QUALIFICATION FOR UPDATE QUERIES simplified abstract (Microsoft Technology Licensing, LLC)
Contents
METHOD AND SYSTEM FOR LOCK AFTER QUALIFICATION FOR UPDATE QUERIES
Organization Name
Microsoft Technology Licensing, LLC
Inventor(s)
Chaitanya Sreenivas Ravella of Surrey (CA)
Hanumantha Rao Kodavalla of Sammamish WA (US)
Prashanth Purnananda of Bellevue WA (US)
Craig Steven Freedman of Sammamish WA (US)
Vasileios Papadimos of Seattle WA (US)
METHOD AND SYSTEM FOR LOCK AFTER QUALIFICATION FOR UPDATE QUERIES - A simplified explanation of the abstract
This abstract first appeared for US patent application 18744221 titled 'METHOD AND SYSTEM FOR LOCK AFTER QUALIFICATION FOR UPDATE QUERIES
Simplified Explanation: The patent application discusses techniques for anomaly detection using sparse judgmental samples in a database environment.
- Generating a qualified timestamp for the execution of a transaction operation.
- Determining if a row in a table is not locked by another transaction based on the timestamp.
- Checking if the row meets a condition of the operation.
- Updating the row by acquiring a lock if it meets the condition.
Key Features and Innovation:
- Anomaly detection using sparse judgmental samples.
- Qualified timestamp generation for transaction operations.
- Lock status determination for database rows.
- Condition checking for row updates.
- Efficient updating process based on timestamps.
Potential Applications:
- Database management systems.
- Transaction monitoring tools.
- Anomaly detection software.
- Data security applications.
Problems Solved:
- Efficient anomaly detection in databases.
- Improved transaction monitoring.
- Enhanced data security measures.
Benefits:
- Faster anomaly detection.
- Enhanced data integrity.
- Improved transaction processing efficiency.
Commercial Applications: The technology can be used in database management systems, transaction monitoring tools, and data security applications to improve efficiency and accuracy in data processing and anomaly detection.
Questions about Anomaly Detection via Sparse Judgmental Samples: 1. How does the qualified timestamp help in anomaly detection? 2. What are the potential challenges in implementing these techniques in real-world database systems?
Frequently Updated Research: Stay updated on the latest advancements in anomaly detection techniques and database security measures to enhance the effectiveness of the technology.
Original Abstract Submitted
Example aspects include techniques for anomaly detection via sparse judgmental samples. These techniques may include generating a qualified timestamp corresponding to execution of a first operation of a first transaction over a database and determining, based on the qualified timestamp, that a row of a table is not locked by a second operation of a second transaction over the database. In addition, the techniques may include determining that the row meets a condition of the first operation. Further, the techniques may include updating, based on the qualified timestamp, the row in response to the row meeting the condition, the updating including acquiring a lock on the row of the table.
