DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application 19/091,503, filed on 03/26/2025, is being examined under the first inventor to file provisions of the AIA . Claims 1-20 are pending in this office action.
Review under 35 USC § 101
2. Claims 1-20 are directed to a machine, an article of manufacture and a process have been reviewed.
Claims 1-10 are appeared to be in one of the statutory categories [e.g., a machine]. Claims 1-10 recite a system for correlating a partition set data structure to a deployment of a component associated with a multi-component system of an application framework. Claims 1-10 do not seem to fall in one of the groups of abstract ideas enumerated in the 2019 PEG. Claims 12-19 are appeared to be in one of the statutory categories [e.g., an article of manufacture]. Claims 12-19 recite a computer product comprising at least one non-transitory computer readable storage medium having computer executable code portions for correlating a partition set data structure to a deployment of a component associated with a multi-component system of an application framework system. Claims 12-19 do not seem to fall in one of the groups of abstract ideas enumerated in the 2019 PEG. Claim 20 is appeared to be in one of the statutory categories [e.g., a process]. Claim 20 recites a method for correlating a partition set data structure to a deployment of a component associated with a multi-component system of an application framework.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-6, 8-16 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Bierner (US 2025/0156241 A1) and further in view of Snider (US 2019/0140994 A1).
Referring to claims 1, 11 and 20, Biernar discloses an apparatus comprising one or more processors (See para. [0029], a distributed computing system that includes one or more servers with processors) and one or more storage devices storing instructions that are operable, when executed by the one or more processors, to cause the one or more processors (See para. [0029] and para. [0030] and para. [0083], the one or more servers with processors for executing processes initiated at workstation or other client devices) to: receive, from a client device, a sharding request to configure data sharding for a component associated with a multi-component system of an application framework (See para. [0028], para. [0031], para. [0058], para. [0073], a subcluster system utilizes a cloud-computing orchestrator to identify subclusters corresponding to a request and to perform operation(s) [e.g., name-sharding] on content items in subclusters, note in para. [0073] the subcluster periodically updates one or more subclusters based on the requested items and determines which subclusters to place the new content items in); wherein the sharding request comprises at least a component identifier for the component (See para. [0058] and para. [0073] and Figure 5, the subcluster system idenfies one or more subclusters and/or content items [e.g., content item(s) 504 can be interpreted as a component identifier] within the subclusters in response to the request, for example, the identified subcluster 310 stores military records which includes content items for the request);
determine (i) a component […] data structure that defines a data routing strategy for data associated with the component identifier (See para. [0079] and Figure 5, the subcluster system determines content items [e.g., content item(s) 504 is interpreted as a component identifier] that are associated with the request and analyzes metadata indicating parameters of data fields of the content items [e.g., data fields such as data types, sources are examples of the component data schema or structure] within an identified subcluster 506 [e.g. routing to a subcluster 506 or other subcluster(s)], the subcluster system determines name-sharding data indicating name-based separation or delineations between data partitions within the cluster 506, where content items for different groups of names are hosted at different shards) and (ii) a partition identifier for a partition of a database or computing resource that is allocated to the component identifier (See para. [0078]- and para. [0080] and Figure 5, the subcluster system 102 identifies birth, marriage, and death record images [e.g., content item 504 is interpreted as component identifier] to add to the corresponding subcluster 506 [e.g., a partition identifier] and further identifies military records to add to the corresponding subcluster 512. In response to adding new content items, the subcluster system 102 further scales the computational resources of the subcluster 506 and the subcluster 512 accordingly (e.g., by adding new virtual machines in proportion to, e.g., the volume of the newly acquired content and/or in response to a predicted number of search requests corresponding thereto).
generate a partition set data structure that defines a relationship mapping between the component identifier (See Figure 5, generates a partition set data structure [e.g. 510, 516, 520] that defines a relationship mapping with respect to the content item(s) 504), the component […] data structure (See para. [0079], analyzes metadata indicating parameters [e.g., data types, sources] of data fields of the content item(s)), and the partition identifier (See para. [0079] and Figure 5, subcluster 506); and
correlate the partition set data structure to a deployment of the component associated with the multi-component system of the application framework (see para. [0019] and para. [0075], the subcluster system determines subclusters that associated with the content item(s) corresponding to the request and determines when to perform blue deployment operations and/or green deployment operations for shards or virtual machines associated with the subclusters).
Biernar discloses everything except determines an archetype data structure.
Snider discloses a component archetype data structure (See para. [0012], para. [0056] and para. [0082], determines an archetype classification) that defines a data routing strategy for data associated with the component identifier (See para. [0082] and Figure 2, the archetype classification is associated with an archetype network mapping or routings [e.g. task allocations]).
Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention was made to modify the component data structure to include an archetype data structure, as taught by Snider. Skilled artisan would have been motivated to access and analyze the electronic communication data associated a communication node to determine a classification for each communication node operating within the electronic communications environment by allowing select communication nodes to make communication routing decisions using the node classification data provided with a network mapping (See Snider, para. [0056]). In addition, all references (Bierner and Snider) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as classifying communication data using machine learning. This close relation between all references highly suggests an expectation of success.
As to claims 2 and 12, Bierner discloses generate a partition set identifier for a partition set data structure; and generate routing context information for the component that is indicative of i) the component data structure and (ii) the partition set identifier (See Figure 5, generates a partition set data structure [e.g. 510, 516, 520] that defines a relationship mapping with respect to the content item(s) 504).
Biernar discloses does not explicitly disclose an archetype data structure.
Snider discloses a component archetype data structure (See para. [0012], para. [0056] and para. [0082], determines an archetype classification) that defines a data routing strategy for data associated with the component identifier (See para. [0082] and Figure 2, the archetype classification is associated with an archetype network mapping or routings [e.g. task allocations]).
Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention was made to modify the component data structure to include an archetype data structure, as taught by Snider. Skilled artisan would have been motivated to access and analyze the electronic communication data associated a communication node to determine a classification for each communication node operating within the electronic communications environment by allowing select communication nodes to make communication routing decisions using the node classification data provided with a network mapping (See Snider, para. [0056]). In addition, all references (Bierner and Snider) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as classifying communication data using machine learning. This close relation between all references highly suggests an expectation of success.
As to claims 3 and 13, Bierner discloses wherein the partition identifier is uniquely correlated to the component based on the component data structure
Biernar does not explicitly disclose an archetype data structure.
Snider discloses a component archetype data structure (See para. [0012], para. [0056] and para. [0082], determines an archetype classification) that defines a data routing strategy for data associated with the component identifier (See para. [0082] and Figure 2, the archetype classification is associated with an archetype network mapping or routings [e.g. task allocations]).
Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention was made to modify the component data structure to include an archetype data structure, as taught by Snider. Skilled artisan would have been motivated to access and analyze the electronic communication data associated a communication node to determine a classification for each communication node operating within the electronic communications environment by allowing select communication nodes to make communication routing decisions using the node classification data provided with a network mapping (See Snider, para. [0056]). In addition, all references (Bierner and Snider) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as classifying communication data using machine learning. This close relation between all references highly suggests an expectation of success.
As to claims 4 and 14, Bierner discloses wherein the relationship mapping comprises a particular relationship mapping between the partition set identifier and the component archetype data structure (See para. [0059], the orchestrator uses a façade pattern 306 includes computer code that maps data for subclusters 308, 110, 312 that matches the content item(s) of the request).
As to claims 5 and 15, Bierner does not explicitly disclose archetype data structure represents a type of service.
Snider discloses wherein the archetype component data structure represents a type of service provided by a combination of the component and one or more other components of the application framework (See para. [0013], identifying, by the machine learning classification system, at least one archetype classification that relates to at least one distinct online user archetype of a plurality of distinct online user archetypes).
Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention was made to modify the component data structure to include an archetype data structure, as taught by Snider. Skilled artisan would have been motivated to access and analyze the electronic communication data associated a communication node to determine a classification for each communication node operating within the electronic communications environment by allowing select communication nodes to make communication routing decisions using the node classification data provided with a network mapping (See Snider, para. [0056]). In addition, all references (Bierner and Snider) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as classifying communication data using machine learning. This close relation between all references highly suggests an expectation of success.
As to claims 6 and 16, Bierner does not explicitly disclose a component descriptor indicative of capabilities of the component and one or more other components associated with the component archetype data structure.
Snider discloses a component descriptor indicative of capabilities of the component and one or more other components associated with the component archetype data structure (See para. [0014], a machine learning system comprising an ensemble of machine learning classifiers comprising a plurality of distinct machine learning classifiers, wherein each of the plurality of distinct machine learning classifiers is configured to generate a distinct archetype classification label upon a detection of a distinct archetype data feature, wherein processing the electronic communication data includes: generating by the plurality of distinct machine learning classifiers one or more archetype machine learning classification labels for the at least one online user based on one or more distinct archetype data features of the extracted archetype data features).
Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention was made to modify the component data structure to include an archetype data structure, as taught by Snider. Skilled artisan would have been motivated to access and analyze the electronic communication data associated a communication node to determine a classification for each communication node operating within the electronic communications environment by allowing select communication nodes to make communication routing decisions using the node classification data provided with a network mapping (See Snider, para. [0056]). In addition, all references (Bierner and Snider) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as classifying communication data using machine learning. This close relation between all references highly suggests an expectation of success.
As to claims 8 and 18, Bierner discloses update the component data structure based on one or more changes with respect to an entity associated with the partition set data structure (See para. [0078]- and para. [0080] and Figure 5, the subcluster system 102 identifies birth, marriage, and death record images [e.g., content item 504 is interpreted as component identifier] to add to the corresponding subcluster 506 [e.g., a partition identifier] and further identifies military records to add to the corresponding subcluster 512. In response to adding new content items, the subcluster system 102 further scales the computational resources of the subcluster 506 and the subcluster 512 accordingly (e.g., by adding new virtual machines in proportion to, e.g., the volume of the newly acquired content and/or in response to a predicted number of search requests corresponding thereto).
Biernar does not explicitly disclose an archetype data structure.
Snider discloses a component archetype data structure (See para. [0012], para. [0056] and para. [0082], determines an archetype classification) that defines a data routing strategy for data associated with the component identifier (See para. [0082] and Figure 2, the archetype classification is associated with an archetype network mapping or routings [e.g. task allocations]).
Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention was made to modify the component data structure to include an archetype data structure, as taught by Snider. Skilled artisan would have been motivated to access and analyze the electronic communication data associated a communication node to determine a classification for each communication node operating within the electronic communications environment by allowing select communication nodes to make communication routing decisions using the node classification data provided with a network mapping (See Snider, para. [0056]). In addition, all references (Bierner and Snider) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as classifying communication data using machine learning. This close relation between all references highly suggests an expectation of success.
As to claims 9 and 19, Bierner discloses update the component data structure based on one or more changes with respect to one or more policies associated with the component (See para. [0078]- and para. [0080] and Figure 5, the subcluster system 102 identifies birth, marriage, and death record images [e.g., content item 504 is interpreted as component identifier] to add to the corresponding subcluster 506 [e.g., a partition identifier] and further identifies military records to add to the corresponding subcluster 512. In response to adding new content items, the subcluster system 102 further scales the computational resources of the subcluster 506 and the subcluster 512 accordingly (e.g., by adding new virtual machines in proportion to, e.g., the volume of the newly acquired content and/or in response to a predicted number of search requests corresponding thereto).
Biernar does not explicitly disclose an archetype data structure.
Snider discloses a component archetype data structure (See para. [0012], para. [0056] and para. [0082], determines an archetype classification) that defines a data routing strategy for data associated with the component identifier (See para. [0082] and Figure 2, the archetype classification is associated with an archetype network mapping or routings [e.g. task allocations]).
Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention was made to modify the component data structure to include an archetype data structure, as taught by Snider. Skilled artisan would have been motivated to access and analyze the electronic communication data associated a communication node to determine a classification for each communication node operating within the electronic communications environment by allowing select communication nodes to make communication routing decisions using the node classification data provided with a network mapping (See Snider, para. [0056]). In addition, all references (Bierner and Snider) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as classifying communication data using machine learning. This close relation between all references highly suggests an expectation of success.
As to claim 10, Bierner discloses update the component data structure based on migration of the partition with one or more other partitions of the database (See para. [0079] and Figure 5, the subcluster system 102 identifies a content item 508 to add to the subcluster 506. In response to adding the content item 508, the subcluster system 102 reindexes or updates the subcluster 506 which results in refreshing various subcluster data 510, such as: i) subcluster metadata indicating parameters of the subcluster 506 (e.g., subcluster data size, content type or other features of content items in the subcluster 506, a number of content items in the subcluster 506, and allocation data for virtual machines assigned to the subcluster 506); ii) name-sharding data indicating name-based separations or delineations between data partitions within the subcluster 506, where content items for different groups of names are hosted at different shards; iii) field metadata indicating parameters of data fields of content items within the subcluster 506 (e.g., creation times, data sizes, sources, data types, and other information for individual data fields); and/or iv) specialization data indicating relatedness between data fields of content items within the subcluster 506).
Biernar does not explicitly disclose an archetype data structure.
Snider discloses a component archetype data structure (See para. [0012], para. [0056] and para. [0082], determines an archetype classification) that defines a data routing strategy for data associated with the component identifier (See para. [0082] and Figure 2, the archetype classification is associated with an archetype network mapping or routings [e.g. task allocations]).
Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention was made to modify the component data structure to include an archetype data structure, as taught by Snider. Skilled artisan would have been motivated to access and analyze the electronic communication data associated a communication node to determine a classification for each communication node operating within the electronic communications environment by allowing select communication nodes to make communication routing decisions using the node classification data provided with a network mapping (See Snider, para. [0056]). In addition, all references (Bierner and Snider) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as classifying communication data using machine learning. This close relation between all references highly suggests an expectation of success.
Claims 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Bierner (US 2025/0156241 A1) and further in view of Snider (US 2019/0140994 A1) and further in view of Thakur (2021/0304322 A1).
As to claims 7 and 17, Bierner in view of Snider does not explicitly disclose the component archetype data structure comprises a component descriptor indicative of a number of instances deployment.
Thakur discloses the component archetype data structure comprises a component descriptor indicative of a number of instances deployment (See para. [0022], [0058] and Figure 2, the system defining transactions based on transaction archetypes and indicating a number of application instances 210A-210B represent specific transactions in applications).
Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention was made to modify the component data structure to include an archetype data structure comprises a component descriptor indicative of a number of instances deployment, as taught by Thakur. Skilled artisan would have been motivated to minimizing inconsistencies in code deployed to process a transaction, and inconsistences in actions performed in a computing system with respect to a transaction (See Thakur, para. [0022]). In addition, all references (Thakur, Bierner and Snider) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as classifying communication data using machine learning. This close relation between all references highly suggests an expectation of success.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Graefe et al. (US 2019/0370382 A1) discloses a method includes one or more of receiving a request to store a data record, identifying a partition from among a plurality of partitions of a database based on a shard identifier in the request, automatically determining a unique range of data identifiers designated to the partition from the plurality of partitions, respectively, based on an unbalanced partitioning, determining whether the data identifier is available within the unique range of data identifiers of the identified partition, and storing the data record at the identified partition in response to determining the data identifier is available. The unbalanced partitioning according to various embodiments reduces the partitions that need to be checked during a data insert/access operation of the database.
Ning et al. (US 2016/0188749 A1) discloses methods and devices for storing and querying feed data. A method includes generating, by a computing device, multiple shards from feed data of an individual user. An individual shard may include first data, second data and third data. The computing device may thereby form a linked list structure of the multiple shards, and store the individual shard in a storage system. When the user sends a query for feed data, the computing device may obtain a unique identifier from the query, and search the storage system using the unique identifier. The computing device may then determine the current shard based on the unique identifier in the storage system and an additional shard corresponding to the third data of the current shard. The computing device may return the first data and second data of the additional shard to the user.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to YUK TING CHOI whose telephone number is (571)270-1637. The examiner can normally be reached Monday-Friday 9am-6pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, AMY NG can be reached at 5712701698. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/YUK TING CHOI/Primary Examiner, Art Unit 2164