18375122. SELF-DISCOVERY AND CONSTRUCTION OF TYPE-SENSITIVE COLUMNAR FORMATS ON TYPE-AGNOSTIC STORAGE SERVERS TO ACCELERATE OFFLOADED QUERIES simplified abstract (Oracle International Corporation)

SELF-DISCOVERY AND CONSTRUCTION OF TYPE-SENSITIVE COLUMNAR FORMATS ON TYPE-AGNOSTIC STORAGE SERVERS TO ACCELERATE OFFLOADED QUERIES

Organization Name

Oracle International Corporation

Inventor(s)

Jorge Luis Issa Garcia of Zapopan (MX)

Teck Hua Lee of Newark CA (US)

Sheldon Andre Kevin Lewis of Zapopan (MX)

Bangalore Prashanth of Redwood City CA (US)

Hui Joe Chang of San Jose CA (US)

Zhen Hua Liu of San Mateo CA (US)

Aurosish Mishra of Foster City CA (US)

Shasank K. Chavan of Menlo Park CA (US)

SELF-DISCOVERY AND CONSTRUCTION OF TYPE-SENSITIVE COLUMNAR FORMATS ON TYPE-AGNOSTIC STORAGE SERVERS TO ACCELERATE OFFLOADED QUERIES - A simplified explanation of the abstract

This abstract first appeared for US patent application 18375122 titled 'SELF-DISCOVERY AND CONSTRUCTION OF TYPE-SENSITIVE COLUMNAR FORMATS ON TYPE-AGNOSTIC STORAGE SERVERS TO ACCELERATE OFFLOADED QUERIES

Simplified Explanation

The patent application focuses on database query acceleration through the dynamic discovery of whether the contents of a persistent column can be stored in an accelerated representation in storage-side memory. Here is a simplified explanation of the abstract:

• The storage server autonomously detects the data type of column values in a persistent column.
• Based on storage-side metadata, the server decides to generate and store an accelerated representation of the column in storage-side memory.
• When a request is received to perform an offload computation for the column, the execution is accelerated based on the accelerated representation.

1. 1. 1. Potential Applications

This technology could be applied in various database systems, data analytics platforms, and cloud computing environments to improve query performance and data processing speed.

1. 1. 1. Problems Solved

1. Slow query performance in database systems. 2. Inefficient data processing in cloud computing environments.

1. 1. 1. Benefits

1. Faster query execution. 2. Improved overall system performance. 3. Enhanced data processing capabilities.

1. 1. 1. Potential Commercial Applications

"Accelerated Database Query Processing Technology for Cloud Computing Environments"

1. 1. 1. Possible Prior Art

One possible prior art could be the use of in-memory databases to accelerate query processing in traditional database systems.

1. 1. 1. 1. Unanswered Questions
         2. How does this technology handle complex data types in persistent columns?

The article does not delve into the specifics of how the technology deals with complex data types in persistent columns.

1. 1. 1. 1. What are the potential limitations of storing accelerated representations in storage-side memory?

The article does not address any potential drawbacks or limitations of storing accelerated representations in storage-side memory.

Original Abstract Submitted

Herein is database query acceleration from dynamic discovery of whether contents of a persistent column can be stored in an accelerated representation in storage-side memory. In an embodiment, based on data type discovery, a storage server detects that column values in a persistent column have a particular data type. Based on storage-side metadata including a frequency of access of the persistent column as an offload input column for offload computation requests on a certain range of memory addresses, the storage server autonomously decides to generate and store, in storage-side memory in the storage server, an accelerated representation of the persistent column that is based on the particular data type. The storage server receives a request to perform an offload computation for the offload input column. Based on the accelerated representation of the persistent column, execution of the offload computation is accelerated.