US 12,216,563 B2
Sharded database load distributor
Ofir Ezrielev, Be'er Sheva (IL); Nadav Azaria, Be'er Sheva (IL); and Yonit Weiss, Lehavim (IL)
Assigned to DELL PRODUCTS L.P., Round Rock, TX (US)
Filed by Dell Products, L.P., Round Rock, TX (US)
Filed on Oct. 22, 2021, as Appl. No. 17/508,571.
Prior Publication US 2023/0128877 A1, Apr. 27, 2023
Int. Cl. G06F 9/50 (2006.01); G06F 11/34 (2006.01); G06F 16/25 (2019.01); G06F 16/28 (2019.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01)
CPC G06F 11/3433 (2013.01) [G06F 11/3419 (2013.01); G06F 16/256 (2019.01); G06F 16/285 (2019.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A system, comprising:
at least one processor; and
at least one memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising:
dividing a database into a group of shards that are distributed among a group of data centers;
training a machine learning model on a group of labeled input data, wherein the group of labeled input data comprises respective requests to operate on the database, and wherein the respective requests are labeled with respective shards of the group of shards used to process the respective requests, and to produce a trained machine learning model;
after training the machine learning model, receiving a request;
processing the request with the trained machine learning model to predict that a data center of the group of data centers will have a largest number of leader shards of the group of shards to process the request; and
sending the request to the data center to be processed at the data center.