Oracle international corporation (20240126750). ACCELERATING QUERY EXECUTION BY OPTIMIZING DATA TRANSFER BETWEEN STORAGE NODES AND DATABASE NODES simplified abstract

ACCELERATING QUERY EXECUTION BY OPTIMIZING DATA TRANSFER BETWEEN STORAGE NODES AND DATABASE NODES

Organization Name

oracle international corporation

Inventor(s)

Kamaljit Shergill of Maidenhead (GB)

Ken Kumar of Bangalore (IN)

Aurosish Mishra of Foster City CA (US)

Shasank Kisan Chavan of Menlo Park CA (US)

ACCELERATING QUERY EXECUTION BY OPTIMIZING DATA TRANSFER BETWEEN STORAGE NODES AND DATABASE NODES - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240126750 titled 'ACCELERATING QUERY EXECUTION BY OPTIMIZING DATA TRANSFER BETWEEN STORAGE NODES AND DATABASE NODES

Simplified Explanation

The abstract of the patent application describes techniques for optimizing data transfer between storage nodes and database nodes to accelerate query execution. In one technique, a compute node sends selection criteria to a storage node, which retrieves data blocks from storage and applies the criteria to generate modified data blocks for transmission back to the compute node.

• Explanation of the patent/innovation:
• Compute node sends database statement and selection criteria to storage node
• Storage node retrieves data blocks from storage based on database statement
• Data blocks consist of rows from an index-organized table with key and non-key sections
• Storage node applies selection criteria to data block to generate modified data block
• Modified data block is transmitted back to compute node

Potential Applications

The technology can be applied in database management systems, data analytics platforms, and cloud computing services to improve query performance and optimize data transfer processes.

Problems Solved

1. Slow query execution times due to inefficient data transfer between storage and database nodes 2. Inefficient utilization of resources in distributed computing environments

Benefits

1. Faster query execution leading to improved system performance 2. Reduced network latency and data transfer overhead 3. Enhanced scalability and resource utilization in distributed systems

Potential Commercial Applications

Optimizing data transfer in cloud storage services Improving query performance in big data analytics platforms Enhancing database management systems for faster data retrieval

Possible Prior Art

One possible prior art could be techniques for optimizing data transfer in distributed computing systems, such as parallel processing algorithms and data partitioning strategies.

How does this technology impact data security in distributed systems?

The technology focuses on optimizing data transfer for query execution, but it is essential to consider how it may affect data security measures in distributed environments. Implementing encryption protocols and access controls could help mitigate potential security risks.

What are the scalability limitations of this technology in large-scale distributed systems?

While the technology aims to improve scalability and resource utilization, it is crucial to understand its limitations in handling massive amounts of data and concurrent queries. Testing the technology in various deployment scenarios can provide insights into its scalability capabilities.

Original Abstract Submitted

techniques for accelerating query execution by optimizing data transfer between storage nodes and database nodes are provided. in one technique, a compute node receives a database statement and transmits a set of one or more selection criteria associated with the database statement to a storage node. based on the database statement, the storage node retrieves a set of data blocks from storage. each data block comprises multiple rows of an index-organized table (iot), each row comprising a key section and a non-key section. the storage node applies the set of selection criteria to a data block, resulting in a modified data block. the storage node generates a modified header data for the modified data block and transmits the modified data block to the compute node.