DETAILED ACTION
This office action is in response to application filed on 10/10/2023.
Claims 1 – 20 are pending.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
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.
Claim(s) 1, 2, 5, 7 – 9, 12, 14, 15, 18 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jacob et al (US 20140137130, hereinafter Jacob), in view of McPhail (US 20140046952).
As per claim 1, Jacob discloses: A system for extraction of historical data in workflow automation platform architectures, the system comprising: a processing device; a non-transitory storage device containing instructions when executed by the processing device, causes the processing device to perform the steps of:
generate a data extract configuration based on received extraction parameters; (Jacob [0085]: “The router 520 is configured to receive an abstraction program including a plurality of parallel algorithms for a query request from at least one computational node 110 (See FIG. 1A) or the abstraction program compiler residing in the graph analytics apparatus 130.”; [0051]: “the graph query is compiled to generate the abstraction program X* employing an abstraction program compiler 120… The abstraction program includes programming instructions for performing parallel operations on graph data to be fetched from the graph database 150 to the graph analytics appliance 130 and the volatile storage device 140.”.)
initiate multiple job scheduler nodes, each configured to generate and execute a plurality of data requests based on the received extraction parameters; apply parallel processing multi-threading engine to concurrently process the plurality of data requests; (Jacob [0085]: “The worklist scheduler 530 is configured to generate a prioritized plurality of parallel threads for executing the query request from the plurality of parallel algorithms. The processing unit 510 is configured to execute multiple threads selected from the prioritized plurality of parallel threads.”; [0064]: “the abstraction program can include a plurality of parallel threads for running the requested query. Each of the plurality of parallel threads includes an instruction for operating on no more than one vertex in a graph in the graph database. The plurality of parallel threads can include first threads configured to operate on a single vertex and at least one edge in the graph (such as the ebb primitive) and
and store [processed] data format extracts in a designated database. (Jacob [0055]: “once the data extraction is complete, the filtered data, which is the final result of the query request, is transferred from the graph analytics appliance 110 to the computational node as an answer to the query request.”.)
Jacobs did not explicitly disclose:
wherein the processed data format comprises of translate proprietary format extracts into normalized data format extracts;
However, McPhail teaches:
wherein the processed data format comprises of translate proprietary format extracts into normalized data format extracts; (McPhail [0088])
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of McPhail into that of Jacobs in order to have the processed data format comprises of translate proprietary format extracts into normalized data format extracts. Jacob figure 2 and [0053] teaches iteratively computes a filtered subset of whole graph segments based on the algorithms encoded within the abstraction program. McPhail [0088] teaches the commonly known concept of extract data format and translate proprietary format into normalized format, while [0090] teaches using normalized format can aid in the effectiveness and efficiency of the extraction and analysis process, thus applicant have merely claimed the combination of known parts in the field to achieve the predictable results of normalization of data formats to improve the effectiveness and accuracy of the parallel extraction program, and is therefore rejected under 35 USC 103.
As per claim 2, the combination of Jacob and McPhail further teach:
The system of claim 1, wherein the system is further configured to optimize data extraction via the parallel processing multi-threading engine via implementing a feedback loop from the multiple job scheduler nodes to adjust thread allocation in real-time, based on system performance metrics and extraction progress. (Jacob [0104]: “the required performance objectives may be met by suitably managing the number of concurrent threads in the system and the number of cores in the processing unit 510.”; [0094]: “The number N is selected based on the profiles of applications that will run on the processor, the properties of the storage media, and the desired performance.”)
As per claim 5, the combination of Jacob and McPhail further teach:
The system of claim 1, wherein the system is further configured to dynamically adjust a total number of active threads or processes based on a current system load and extraction requirements according to the data extract configuration. (Jacob [0104]: “the required performance objectives may be met by suitably managing the number of concurrent threads in the system and the number of cores in the processing unit 510.”; [0094]: “The number N is selected based on the profiles of applications that will run on the processor, the properties of the storage media, and the desired performance.”)
As per claim 7, the combination of Jacob and McPhail further teach:
The system of claim 1, wherein the parallel processing multi-threading engine further comprises a distributed cloud computing system enabling a concurrent execution of data extraction tasks across multiple hardware nodes. (Jacob [0038])
As per claim 8, it is the computer program product variant of claim 1 and is therefore rejected under the same rationale. (Jacob [0047]: CRM.)
As per claim 9, it is the computer program product variant of claim 2 and is therefore rejected under the same rationale.
As per claim 12, it is the computer program product variant of claim 5 and is therefore rejected under the same rationale.
As per claim 14, it is the computer program product variant of claim 7 and is therefore rejected under the same rationale.
As per claim 15, it is the method variant of claim 1 and is therefore rejected under the same rationale.
As per claim 16, it is the method variant of claim 3 and is therefore rejected under the same rationale.
As per claim 18, it is the method variant of claim 5 and is therefore rejected under the same rationale.
As per claim 20, it is the method variant of claim 7 and is therefore rejected under the same rationale.
Claim(s) 3, 4, 6, 10, 11, 13, 16, 17 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jacob and McPhail, and further in view of Gupta et al (US 20150279170, hereinafter Gupta).
As per claim 3, the combination of Jacob and McPhail did not teach:
The system of claim 1, wherein the system is further configured to monitor a status and completion percentage of each of the multiple job scheduler nodes and corresponding data requests in real-time.
However, Gupta teaches:
The system of claim 1, wherein the system is further configured to monitor a status and completion percentage of each of the multiple job scheduler nodes and corresponding data requests in real-time. (Gupta figure 3 and [0042])
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Gupta into that of Jacobs and McPhail in order to monitor a status and completion percentage of each of the multiple job scheduler nodes and corresponding data requests in real-time. Jacob [0085] teaches receiving a extraction job and performing the data extraction job. Gupta [0042] teaches the commonly known concept of monitoring and displaying status information. It would have been obvious for one of ordinary skill in the art to combine the status monitoring and feedback to the data extraction execution of Jacobs in order to achieve the predictable results of alerting user in real time in case of failure to take remedial actions, and is therefore rejected under 35 USC 103.
As per claim 4, the combination of Jacob and McPhail did not teach:
The system of claim 1, wherein the system is further configured to trigger automated alerts in case of a data extraction job failure detected during an extraction process.
However, Gupta teaches:
The system of claim 1, wherein the system is further configured to trigger automated alerts in case of a data extraction job failure detected during an extraction process. (Gupta [0027] and [0042])
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Gupta into that of Jacobs and McPhail in order to trigger automated alerts in case of a data extraction job failure detected during an extraction process. Jacob [0085] teaches receiving a extraction job and performing the data extraction job. Gupta [0027] and [0042] teaches the commonly known concept of monitoring status information and display an alert to the user in case of failure. It would have been obvious for one of ordinary skill in the art to combine the status monitoring and feedback to the data extraction execution of Jacobs in order to achieve the predictable results of alerting user in real time in case of failure to take remedial actions, and is therefore rejected under 35 USC 103.
As per claim 6, the combination of Jacob and McPhail did not teach:
The system of claim 1, wherein the system is further configured to generate and transmit a user interface, wherein the user interface comprises a status and completion percentage of each of the multiple job scheduler nodes and corresponding data requests in real-time.
However, Gupta teaches:
The system of claim 1, wherein the system is further configured to generate and transmit a user interface, wherein the user interface comprises a status and completion percentage of each of the multiple job scheduler nodes and corresponding data requests in real-time. (Gupta figure 3 and [0042])
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Gupta into that of Jacobs and McPhail in order to generate and transmit a user interface, wherein the user interface comprises a status and completion percentage of each of the multiple job scheduler nodes and corresponding data requests in real-time. Jacob [0085] teaches receiving a extraction job and performing the data extraction job. Gupta [0042] teaches the commonly known concept of monitoring and displaying status information. It would have been obvious for one of ordinary skill in the art to combine the status monitoring and feedback to the data extraction execution of Jacobs in order to achieve the predictable results of alerting user in real time in case of failure to take remedial actions, and is therefore rejected under 35 USC 103.
As per claim 10, it is the computer program product variant of claim 3 and is therefore rejected under the same rationale.
As per claim 11, it is the computer program product variant of claim 4 and is therefore rejected under the same rationale.
As per claim 13, it is the computer program product variant of claim 6 and is therefore rejected under the same rationale.
As per claim 16, it is the method variant of claim 3 and is therefore rejected under the same rationale.
As per claim 17, it is the method variant of claim 4 and is therefore rejected under the same rationale.
As per claim 19, it is the method variant of claim 6 and is therefore rejected under the same rationale.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Herath et al (US 20200201676) teaches “receiving a plurality of tasks that are ready to be executed, i.e. all their dependencies have been met and all the resources required to execute the task are available, and adding the received tasks to a task queue (or “task pool”). The number of tasks that are executing is monitored and in response to determining that an additional task can be executed by the processor, a task is selected from the task pool based at least in part on a comparison of indications of resources used by tasks being executed and indications of resources used by individual tasks in the task pool and the selected task is then sent for execution.”;
Zelenov et al (USPAT 10776148) teaches “During a map stage of a computation, starting with a first virtual machine (VM) acting as a parent VM and an input data set, the system clones the parent VM to generate at least one linked clone child VM. The system further divides the input data set into a first chunk for the parent VM and a second chunk for the at least one child VM by determining a starting pointer for each chunk. Each chunk is processed by a VM to generate an intermediate data result, which is stored in a network storage device. The plurality of VMs then perform a reduce stage on the plurality of intermediate data results stored in the network storage device.”;
Makumbi et al (US 20220222266) teaches “a monitoring device may obtain information related to one or more extract, transform, and load (ETL) jobs scheduled in an ETL system. The monitoring device may generate ETL job metrics that include status information, timing information, and data volume information associated with one or more constituent tasks associated with the one or more ETL jobs, wherein the ETL job metrics include metrics related to extracting data records from a data source, transforming the data records into a target format, and/or loading the data records in the target format into a data sink. The monitoring device may enable capabilities to create or interact with one or more dashboards to visualize the ETL job metrics via a workspace accessible to one or more client devices. The monitoring device may invoke a messaging service to publish one or more notifications associated with the ETL job metrics via the workspace.”;
Compton et al (US 20230030808) teaches “receiving a data process that includes a plurality of sub-processes. A unique subset of the sub-processes is assigned to each of: a managing thread, and at least one other thread. Moreover, performance characteristics of each of the threads is evaluated while the respective subsets of sub-processes are being performed, and a determination is made as to whether the performance characteristics of each of the threads are substantially equal to the performance characteristics of each of the other threads. In response to determining that performance characteristics of each of the threads are not substantially equal, the subsets of the sub-processes are dynamically adjusted such that the performance characteristics of each of the threads become more equal. Moreover, the adjusted subsets of the sub-processes are reassigned to each of the managing thread and at least one other thread.”.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHARLES M SWIFT whose telephone number is (571)270-7756. The examiner can normally be reached Monday - Friday: 9:30 AM - 7PM.
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/CHARLES M SWIFT/Primary Examiner, Art Unit 2196