The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jan. 04, 2022

Filed:

Apr. 26, 2019
Applicant:

Salesforce.com, Inc., San Francisco, CA (US);

Inventors:

Elden Gregory Bishop, San Francisco, CA (US);

Jeffrey Chao, San Francisco, CA (US);

Assignee:

salesforce.com, inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 9/46 (2006.01); G06F 9/48 (2006.01); G06F 9/50 (2006.01); G06F 9/455 (2018.01); G06F 8/71 (2018.01); G06F 9/445 (2018.01);
U.S. Cl.
CPC ...
G06F 9/4881 (2013.01); G06F 8/71 (2013.01); G06F 9/44521 (2013.01); G06F 9/4552 (2013.01); G06F 9/45504 (2013.01); G06F 9/5072 (2013.01);
Abstract

The technology disclosed provides a novel and innovative technique for compact deployment of application code to stream processing systems. In particular, the technology disclosed relates to obviating the need of accompanying application code with its dependencies during deployment (i.e., creating fat jars) by operating a stream processing system within a container defined over worker nodes of whole machines and initializing the worker nodes with precompiled dependency libraries having precompiled classes. Accordingly, the application code is deployed to the container without its dependencies, and, once deployed, the application code is linked with the locally stored precompiled dependencies at runtime. In implementations, the application code is deployed to the container running the stream processing system between 300 milliseconds and 6 seconds. This is drastically faster than existing deployment techniques that take anywhere between 5 to 15 minutes for deployment.


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