DETAILED ACTION
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is responsive to the application filed 01/26/2024.
Claims 1-20 are presented for examination.
Information Disclosure Statement
2. The Applicants’ Information Disclosure Statements (filed 07/19/2024 and 06/04/2025) have been received, entered into the record, and considered.
Drawings
3. The drawings filed 01/26/2024are acceptable for examination purposes.
Specification
4. The specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant's cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim Objections
5. Claim 6 is objected to because of the following informalities:
The claim appears to be incomplete.
Appropriate correction is required.
Claim Rejections - 35 USC § 102
6. 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 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Saxena et al. (US 20230169079).
It is noted that any citations to specific, pages, columns, paragraphs, lines, or figures in the prior art references and any interpretation of the reference should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. See MPEP 2123.
As to claim 1:
Saxena teaches a data processing system, the system comprising: a plurality of non-interactive job clusters ([0039], [0042-0044], and [0056]: clusters); a control database storing a task queue ([0056], [0079]: database query queue 320); and
a controller, the controller configured to instantiate one or more clusters of the plurality of non-interactive job clusters based on a size of the task queue and to monitor when the one or more clusters are successfully instantiated ([0023]: Available query processing configurations 160 may be any number of different query processing resources (e.g., different sized clusters of computational nodes with different processing and other computing capabilities (e.g., different memory, networking, Input/Output (I/O), etc.)). Available processing configurations 160 may include one or more processing configurations (e.g., one or more clusters) that are already allocated and “attached” to a database. For example, in some embodiments, database service 110 may initially create a “main” or “primary” processing cluster for a database. This cluster may be used to process queries in addition to other processing configurations (e.g., other clusters of different sizes) which may be later attached when selected according to the techniques discussed with regard to FIG. 1. Available processing configurations 160 may include those processing configurations that are not currently attached, but could be attached to the database if selected (e.g., a differently sized compute cluster from a main cluster; [0037]: Database services 210 may be (or included in) various types of data processing services that perform general or specialized data processing functions (e.g., anomaly detection, machine learning, data mining, big data querying, or any other type of data processing operation). For example, in at least some embodiments, database services 210 may include a map reduce service that creates clusters of processing nodes that implement map reduce functionality over data stored in the map reduce cluster as well as data stored in data storage service 270. In another example, database service 210 may include various types of database services (both relational and non-relational) for storing, querying, and updating data. Such services may be enterprise-class database systems that are highly scalable and extensible. Queries may be directed to a database in database service 210 that is distributed across multiple physical resources, and the resource configurations, such as processing clusters 232, used to process the queries may be scaled up or down on an as needed basis, as discussed in detail below with regard to FIGS. 3-7; [0076]: query routing 330 may also implement other features to monitor performance of cluster selection and, if necessary, disable or modify performance of query routing 330. For example, one feature monitors a query's predicted and real execution time and turn prediction based optimizations off if prediction accuracy is low (e.g., where a query prediction accuracy for a period of time does not satisfy an accuracy criteria). Consider an example where a query's predicted execution time is E.sub.x on a cluster C.sub.x. If query runs on this cluster, then the ratio r of query's predicted and real execution time may be considered. An exponential moving average of r may be maintained for each execution time bucket (e.g., range of time). If r breaches a threshold (e.g., >1) for an execution tie bucket, then prediction based rightsizing of clusters may be disabled for the queries which fall in that bucket and instead a same configuration cluster as used as the primary cluster may be used to for the query (if a new cluster is to be attached),
wherein each of the one or more clusters is configured to, after successfully being instantiated by the controller, execute a dispatcher process that queries the control database to identify an available task from the task queue, obtain and process the available task, and, after completion of the available task, further query the control database prior to terminating [0076]: query routing 330 may also implement other features to monitor performance of cluster selection and, if necessary, disable or modify performance of query routing 330. For example, one feature monitors a query's predicted and real execution time and turn prediction based optimizations off if prediction accuracy is low (e.g., where a query prediction accuracy for a period of time does not satisfy an accuracy criteria). Consider an example where a query's predicted execution time is E.sub.x on a cluster C.sub.x. If query runs on this cluster, then the ratio r of query's predicted and real execution time may be considered. An exponential moving average of r may be maintained for each execution time bucket (e.g., range of time). If r breaches a threshold (e.g., >1) for an execution tie bucket, then prediction based rightsizing of clusters may be disabled for the queries which fall in that bucket and instead a same configuration cluster as used as the primary cluster may be used to for the query (if a new cluster is to be attached); see also [0080-0083]).
As to claim 2:
Saxena teaches when a given cluster of the one or more clusters is not successfully instantiated, then the given cluster is unable to execute the dispatcher process ([0065-0075]).
As to claim 3:
Saxena teaches after the controller determines that a given cluster of the one or more clusters is not successfully instantiated, the controller terminates the given cluster and instantiates a new cluster from amongst the plurality of non-interactive job clusters to replace the given cluster ([0099-0100]).
As to claim 4:
Saxena teaches when the dispatcher process determines that a further available task is available in the task queue, the dispatcher process launches the further available task ([0109-0110]).
As to claim 5:
Saxena teaches for a given cluster of the one or more clusters, after the dispatcher process determines that a further available task is not available in the task queue, the dispatcher process periodically executes a loop that comprises querying the control database for the further available task within a predetermined period, and after determining that the further available task is not available in the task queue within the predetermined time period, the dispatcher process terminates the given cluster ([0056-0059] and [0109]).
As to claim 6:
Saxena teaches prior to processing the available task, the available task is tagged in the control database with an identifier of a given cluster of the one or more clusters that will be processing the available task ([0083-0084]).
As to claim 7:
Saxena teaches the plurality of non-interactive job clusters implements a machine learning model ([0107]).
As to claim 8:
Saxena teaches following instantiation of the one or more clusters, the controller continues to monitor the size of the task queue, and in response to determining that the size exceeds a preconfigured limit, instantiates an additional cluster from amongst the plurality of non-interactive job clusters ([0080-0081] and [0109]).
As to claim 9:
Saxena teaches the control database stores a configuration file, and wherein the controller instantiates the one or more clusters based on at least one setting of the configuration file, wherein the at least one setting is selected from a number of clusters to be used, a number of vCPUs to be used, and a memory size to be used ([0047-0048] and [0084-0085]).
As to claim 10:
Saxena teaches the dispatcher process further comprises: the each of the one or more clusters determining a processing load capacity of itself; and, providing the processing load capacity to the control database to identify the available task from the task queue that has a processing load requirement that matches or is less than the processing load capacity ([0023-0024] and [0080]).
As to claims 11-15 and 17-19:
Refer to claims 1-5 and 7-10 above, respectively, for rejections. Claims 11-15 and 17-19 are the same as claims 1-5 and 7-10, except claims 11-15 and 17-19 are method claims and claims 1-5 and 7-10 are system claims.
As to claim 16:
Saxena teaches prior to processing the available task, the control database tagging the available task with an identifier of a given cluster of the one or more clusters that will be processing the available task; and, following successful processing of the available task, the control database removing the available task from the task queue ([0083-0086]).
As to claim 20:
Refer to the discussion of claims 1 above for rejection. Claim 20 is the same as claim 1, except claim 20 is a computer readable medium claim and claim 1 is a system claim.
Conclusion
7. The prior art made of record, listed on PTO 892 provided to Applicant is considered to have relevancy to the claimed invention. Applicant should review each identified reference carefully before responding to this office action to properly advance the case in light of the prior art.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VAN H. NGUYEN whose telephone number is (571) 272-3765. The examiner can normally be reached on Monday- Friday from 9:00AM to 5:30 PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, LEWIS BULLOCK, can be reached at telephone number (571) 272-3759. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/VAN H NGUYEN/
Primary Examiner, Art Unit 2199
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