DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This Office Action is sent in response to Applicant's Communication received on April 30, 2025 for application number 19/194,833. This Office hereby acknowledges receipt of the following and placed of record in file: Specification, Drawings, Abstract, Oath/Declaration, and Claims.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to Judicial Exceptions without significantly more. The claims recite mathematical relationships, mathematical formulas or equations, mathematical calculation and a mental process. This judicial exception is not integrated into a practical application because the recitation of generic computer and generic computer components does not sufficient to integrate the recited judicial exception into a practical application. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims only recites generic computer components, which are well-understood, routine, and conventional.
Revised Patent Subject Matter Eligibility Guidance
The USPTO has published revised guidance on the application of § 101. USPTO’s 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50 (Jan. 7, 2019) (“Guidance”). Under the Guidance, the Examiner first look to whether the claim recites:
(1) any judicial exceptions, including certain groupings of abstract ideas (i.e., mathematical concepts, certain methods of organizing human activity such as a fundamental economic practice, or mental processes) (Guidance, Step 2A, prong 1); and
(2) additional elements that integrate the judicial exception into a practical application (see Manual of Patent Examining Procedure (MPEP) § 2106.05(a)-(c), (e)-(h) (9th Ed., Rev. 08.2017, 2018)) (Guidance, Step 2A, prong 2).
Only if a claim (1) recites a judicial exception and (2) does not integrate that exception into a practical application, do the Examiner then look to whether the claim:
(3) adds a specific limitation beyond the judicial exception that is not “well-understood, routine, conventional” in the field (see MPEP § 2106.05(d)); or
(4) simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. (Guidance (Step 2B)).
Evaluate Step 2A Prong One
(a) identify the specific limitation(s) in the claim that recites an abstract idea;
(b) determine whether the identified limitation(s) falls within at least one of the groupings of abstract ideas enumerated in the 2019 Revised Patent Subject Matter Eligibility Guidance.
In TABLE 1 below, the Examiner identifies in italics the specific claim limitations that recite an abstract idea.
TABLE 1
Independent Claims 1 and 11
Analysis Under Revised Guidance
(a) A system for scaling hardware capacity in a distributed database system configured to store data divided among a plurality of data partitions, the distributed database system comprising database hardware for hosting the plurality of data partitions, the system comprising: at least one processor; and at least one non-transitory computer-readable storage medium storing instructions that, when executed by the at least one processor, cause the at least one processor to:, the determining comprising:; and configure the database hardware based on hardware capacities determined for hosting the at least some data partitions, the configuring comprising:;
(b) determine, for each of at least some of the plurality of data partitions, a hardware capacity for hosting the data partition; determine a first hardware capacity for hosting a first data partition of the plurality of data partitions; determine a first hardware capacity for hosting a first data partition of the plurality of data partitions; and determine a second hardware capacity, different from the first hardware capacity, for hosting a second data partition of the plurality of data partitions
“determining hardware capacity” is an abstract idea, i.e., “a mental process” to determine capacity for respective hardware .
(c) configure a first set of the database hardware, having the first hardware capacity, to host the first data partition; and configure a second set of the database hardware having the second hardware capacity to host the second data partition
“configuring a set of database hardware…” is an abstract idea, i.e., “a mathematical calculation” or “mathematical formula”, to a configure a set of database hardware to host data partitions
Independent Claim 17
Analysis Under Revised Guidance
(d) A distributed database system configured to store data divided among a plurality of data partitions, the distributed database system comprising: database hardware configured to host the plurality of data partitions, wherein the database hardware is configurable to provide different hardware capacities for hosting different data partitions; and at least one processor configured to dynamically modify a configuration of the database hardware to update a hardware capacity used to host a particular data partition of the plurality of data partitions.
(e) database hardware configured to host the plurality of data partitions, wherein the database hardware is configurable to provide different hardware capacities for hosting different data partitions; and at least one processor configured to dynamically modify a configuration of the database hardware to update a hardware capacity used to host a particular data partition of the plurality of data partitions.
“database hardware configured to host the plurality of data partitions …” is an abstract idea, i.e., “a mathematical calculation” or “mathematical formula”, to configure database hardware to host data partitions
Dependent claims 2-10, 12-16, and 18-20 further recites additional limitations. However, these limitations also recite abstract idea, i.e., “mathematical concept – mathematical formulas or equations, mathematical calculations” and i.e., a “mental process” similar to the limitations of claims 1, discussed above.
Evaluate Step 2A Prong Two:
Evaluate whether the claim as a whole integrated the recited Judicial exception into a Practical Application of the exception.
Having determined that the claims recites a judicial exception, the analysis under the Guidance turns now to determining whether there are “additional element that integrate the judicial exception into a practical application”. The examiner determines whether the recited judicial exception is integrated into a practical application that exception by: (1) identifying whether there are any additional elements recited in the claim beyond the judicial exceptions; and (2) evaluating those additional elements individually and in combination to determine whether they integrate the exception into a practical application”.
Independent claim 1 further recite “at least one processor” and “non-transitory computer-readable storage medium”, which is a generic/conventional computer storage. Claim 1 does not recite any additional element that integrate the judicial exception into a practical application. The recitation of generic computer and generic computer components does not sufficient to integrate the recited judicial exception into a practical application. Guidance at MPEP 2106.04 (“Performance of a claim limitation using generic computer components does not necessarily preclude the claim limitation from being in the mathematical concepts grouping.”)
As discussed above, independent claim 1 recites the mathematic calculation steps to configure database hardware capacities determined for hosting data partitions and determining the database hardware capacity. These limitations are processes that, under broadest reasonable interpretation, covers performance of the limitation in the mind, but for the recitations of generic computer components. That is, other than reciting a “processor” and “non-transitory computer-readable storage medium”, nothing in the claim element precludes the step from practically being performed in a human mind or with the aid of pen and paper. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mathematical Concept” and “Mental Processes” grouping of abstract ideas (concepts performed in the human mind including an observation, evaluation, judgment, and opinion).
Evaluate Step 2B:
Evaluate whether the claim provide an inventive concept, i.e., does the claim recite additional element(s) or a combination of elements that amount to significantly more than the judicial exception in the claim?
At Step 2B, the evaluation of the insignificant extra-solution activity consideration takes into account whether or not the extra-solution activity is well-known. See MPEP 2106.05(g). The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim does not add any specific limitations beyond what is well-understood, routine, and conventional. Here, claim 1 recite processor” and “non-transitory computer-readable storage medium”, which are mere generic computer components that are recited at a high level of generality, and, as disclosed in the specification, is also well-understood, routine, conventional activity when expressed at this high level of generality. Mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. Therefore, the claims do not provide an inventive concept (significantly more than the abstract idea) and is not eligible.
These additional elements are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer components. Further, the claim recitations of storing data.
Storing is recited at a high level of generality, and thus are insignificant extra-solution activity to the judicial exception with no evidence of improvement. Accordingly, the additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea, thus fail to integrate the abstract idea into a practical application. See MPEP 2106.05(g).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of storing data (storing and retrieving information in memory), are well-understood, routine and conventional activity according to MPEP 2106.05(d)(II)(iv), thus, cannot provide an inventive concept.
As a result, representative claim(s) 1, 11, and 17 does not recite any elements, or ordered combination of elements, which transforms the abstract idea into a patent-eligible subject matter. In addition, the claim(s) does not recite (i) an improvement to the functionality of a computer or other technology or technical field (see MPEP 2106.05(a); (ii) a “particular machine” to apply or use the judicial exception (see MPEP 2106.05(b); (iii) a particular transformation of an article to a different state or thing (see 2106.05(c). Further, the claim does not recite any improvement to computer functionality or specify how the one or more processors are used to improve functionality of a computing device. Considering the claim(s) as a whole, the additional elements fail to apply or use the abstract idea in a meaningful way and the additional limitations recited beyond the judicial exception itself fail to integrate the exception into a practical application. Accordingly, the claims 1-12 of this application are rejected.
Claims 2-3 and 12-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) the abstract idea of a mathematical concept, for example the claims are directed toward the mathematical concept of configuring respective database hardware capacities, under broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. The limitations associated with configuring database hardware capacities are considered to be an abstract idea that falls in the “Mathematical Concept” grouping of abstract ideas.
Claims 4, 10, 14, and 18-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) the abstract idea of a mathematical concept, for example the claims are directed toward the mathematical concept of determining memory utilization, under broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. The limitations associated with determining memory utilization are considered to be an abstract idea that falls in the “Mathematical Concept” grouping of abstract ideas.
Claims 5-8 and 15, are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) the abstract idea of a mathematical concept, for example the claims are directed toward the mathematical concept of determining and modifying hardware capacity, under broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. The limitations associated with determining and modifying hardware capacity are considered to be an abstract idea that falls in the “Mathematical Concept” grouping of abstract ideas.
Claims 9 and 16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) the abstract idea of a mental process, for example the claims are directed toward the mental process of selecting a hardware capacity, under broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. The limitations associated with selecting a hardware capacity are considered to be an abstract idea that falls in the “Mental Process” grouping of abstract ideas.
The claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform the determining, configuring, modifying, and selecting steps amounts to no more than mere instructions to apply the exception using a generic computer component. The limitations related to storing data are considered by the examiner to be well-understood, routine and conventional activity according to MPEP 2106.05(d)(II)(iv), because the inventive subject matter is directed toward periodic reporting. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Because of these reasons the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim(s) 1-20 are rejected.
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 of this title, 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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-7, 11-15, and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Wu et al. (US 11,030,169)(hereinafter Wu) in view of Shathakumar et al. (US 2025/0173338)(hereinafter Shathakumar).
Regarding claim 1, Wu teaches system for scaling hardware capacity in a distributed database system configured to store data divided among a plurality of data partitions, the distributed database system comprising database hardware for hosting the plurality of data partitions, the system comprising: at least one processor; and at least one non-transitory computer-readable storage medium storing instructions that (see Fig. 7, col. 17 ln 55-58, discloses processor and memory) , when executed by the at least one processor, cause the at least one processor to: determine, for each of at least some of the plurality of data partitions, a hardware capacity for hosting the data partition (see Fig. 1A, Fig. 2A, Fig. 3, col.4 ln 29-34, col. 8 ln 46-54, col. 14 ln 37-40, discloses determining for each respective shard (partition) capacity of a node hosting a given shard); the determining comprising: determine a first hardware capacity for hosting a first data partition of the plurality of data partitions (see Fig. 1A, col. 8 ln 30-40, discloses determining a capacity for a first node has reached capacity); and determine a second hardware capacity, different from the first hardware capacity, for hosting a second data partition of the plurality of data partitions (see Fig. 1A, col. 8 ln 24-40, discloses determining a second node capacity hosting shards in order to meet desired performance standards).
Wu does not explicitly teach configure the database hardware based on hardware capacities determined for hosting the at least some data partitions, the configuring comprising: configure a first set of the database hardware, having the first hardware capacity, to host the first data partition; and configure a second set of the database hardware having the second hardware capacity to host the second data partition.
Shanthakumar teaches configure the database hardware based on hardware capacities determined for hosting the at least some data partitions (see Fig. 1, Fig.6-7, para [0023-0024], para [0070], discloses database capacity units, DCUs (database hardware) making scaling decisions based on performance metrics (capacities) determined for hosting shards (partitions)), the configuring comprising: configure a first set of the database hardware, having the first hardware capacity, to host the first data partition (see Fig. 1, Fig. 4, Fig.7-8, para [0023-0024], para [0072, 0074], discloses database capacity units, DCUs (database hardware) allocation for a first set of DCUs to host a first shard (partition)); and configure a second set of the database hardware having the second hardware capacity to host the second data partition (see Fig. 1, Fig. 4, Fig.7-8, para [0023-0024], para [0072, 0074], discloses database capacity units, DCUs (database hardware) allocation for a second set of DCUs to host a second shard (partition)).
Wu/Shanthakumar are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Wu to configure sets of database hardware capacities from disclosure of Shanthakumar. The motivation to combine these arts is disclosed by Shanthakumar as “dynamically scaling a distributed database according to a cluster-wide resource allocation” (para [0020]) and configuring sets of database hardware capacities are well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Regarding claim 11, Wu teaches a method for scaling hardware capacity in a distributed database system configured to store data divided among a plurality of data partitions, the distributed database system comprising database hardware for hosting the plurality of data partitions, the method comprising: using at least one processor to perform (see Fig. 7, col. 17 ln 55-58, discloses processor): determining, for each of at least some of the plurality of data partitions, a hardware capacity for hosting the data partition, the determining comprising: determining a first hardware capacity for hosting a first data partition of the plurality of data partitions (see Fig. 1A, Fig. 2A, Fig. 3, col.4 ln 29-34, col. 8 ln 46-54, col. 14 ln 37-40, discloses determining for each respective shard (partition) capacity of a node hosting a given shard); and determining a second hardware capacity, different from the first hardware capacity, for hosting a second data partition of the plurality of data partitions (see Fig. 1, Fig. 4, Fig.7-8, para [0023-0024], para [0072, 0074], discloses database capacity units, DCUs (database hardware) allocation for a second set of DCUs to host a second shard (partition)).
Wu does not explicitly teach configuring the database hardware based on hardware capacities determined for hosting the at least some data partitions, the configuring comprising: configuring a first set of the database hardware, having the first hardware capacity, to host the first data partition; and configuring a second set of the database hardware having the second hardware capacity to host the second data partition.
Shanthakumar teaches configure the database hardware based on hardware capacities determined for hosting the at least some data partitions (see Fig. 1, Fig.6-7, para [0023-0024], para [0070], discloses database capacity units, DCUs (database hardware) making scaling decisions based on performance metrics (capacities) determined for hosting shards (partitions)), the configuring comprising: configure a first set of the database hardware, having the first hardware capacity, to host the first data partition (see Fig. 1, Fig. 4, Fig.7-8, para [0023-0024], para [0072, 0074], discloses database capacity units, DCUs (database hardware) allocation for a first set of DCUs to host a first shard (partition)); and configure a second set of the database hardware having the second hardware capacity to host the second data partition (see Fig. 1, Fig. 4, Fig.7-8, para [0023-0024], para [0072, 0074], discloses database capacity units, DCUs (database hardware) allocation for a second set of DCUs to host a second shard (partition)).
Wu/Shanthakumar are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Wu to configure sets of database hardware capacities from disclosure of Shanthakumar. The motivation to combine these arts is disclosed by Shanthakumar as “dynamically scaling a distributed database according to a cluster-wide resource allocation” (para [0020]) and configuring sets of database hardware capacities are well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Regarding claim 17, Wu teaches a distributed database system configured to store data divided among a plurality of data partitions, the distributed database system comprising: database hardware configured to host the plurality of data partitions, wherein the database hardware is configurable to provide different hardware capacities for hosting different data partitions (see Fig. 5-6, col. 7 ln 54-65, col. 8 ln 46-54, discloses distributed database services distributed across resources of different capacities for hosting shards (partitions)).
Wu does not explicitly teach at least one processor configured to dynamically modify a configuration of the database hardware to update a hardware capacity used to host a particular data partition of the plurality of data partitions.
Shanthakumar teaches at least one processor configured to dynamically modify a configuration of the database hardware to update a hardware capacity used to host a particular data partition of the plurality of data partitions (see Fig. 1, Fig. 11, para [0022-0023], discloses dynamically scaling distributed database according to a cluster-wide resource allocation of capacity based on performance metrics).
Wu/Shanthakumar are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Wu to dynamically modify configuration of database hardware update hardware capacity from disclosure of Shanthakumar. The motivation to combine these arts is disclosed by Shanthakumar as “dynamically scaling a distributed database according to a cluster-wide resource allocation” (para [0020]) and dynamically modify configuration of database hardware update hardware capacity is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Regarding claims 2 and 12, Wu/Shanthakumar teach a system of claim 1 and a method of claim 11.
Wu does not explicitly teach configuring the first set of database hardware, having the first hardware capacity, to host the first data partition comprises configuring database hardware with first computer processing unit (CPU) hardware to host the first data partition; and configuring the second set of database hardware, having the second hardware capacity, to host the second data partition comprises configuring database hardware with second CPU hardware, different from the first CPU hardware, to host the second data partition.
Shanthakumar teaches configuring the first set of database hardware, having the first hardware capacity, to host the first data partition comprises configuring database hardware with first computer processing unit (CPU) hardware to host the first data partition (see Fig. 4, Figs. 6-7. para [0070, 0072], para [0091], discloses configuring a first set of DCUs having a first capacity to house a first shard); and configuring the second set of database hardware, having the second hardware capacity, to host the second data partition comprises configuring database hardware with second CPU hardware, different from the first CPU hardware, to host the second data partition (see Fig. 4, Figs. 6-7. para [0070, 0072], para [0091], discloses configuring a second set of DCUs having a first capacity to house a second shard).
Regarding claims 3 and 13, Wu/Shanthakumar teach a system of claim 1 and a method of claim 11.
Wu does not explicitly teach configuring the first set of database hardware, having the first hardware capacity, to host the first data partition comprises configuring database hardware with a first amount of random access memory (RAM) to host the first data partition; and configuring the second set of database hardware, having the second hardware capacity to host the second data partition comprises configuring database hardware with a second amount of RAM, different from the first amount of RAM, to host the second data partition.
Shanthakumar teaches configuring the first set of database hardware, having the first hardware capacity, to host the first data partition comprises configuring database hardware with a first amount of random access memory (RAM) to host the first data partition (see Fig. 6, Fig. 15, para [0071], para [0108-0109], discloses database stored configured with a first amount of memory to host a first shard); and configuring the second set of database hardware, having the second hardware capacity to host the second data partition comprises configuring database hardware with a second amount of RAM, different from the first amount of RAM, to host the second data partition (see Fig. 6, Fig. 15, para [0071], para [0108-0109], discloses database stored configured with a second amount of memory to host a second shard).
Regarding claims 4 and 14, Wu/Shanthakumar teach a system of claim 1 and a method of claim 11.
Wu does not explicitly teach wherein determining the first hardware capacity for hosting the first data partition comprises: analyze operations performed on the first data partition over a time period to determine an indication of memory utilization during the time period; and determine the first hardware capacity based on the indication of memory utilization during the time period.
Shanthakumar teaches wherein determining the first hardware capacity for hosting the first data partition comprises: analyze operations performed on the first data partition over a time period to determine an indication of memory utilization during the time period (see para [0076], discloses rules to scale up DCUs or scale down DCUs, increasing or decreasing allocated number of DCUs if a certain percentage of DCUs is consumed over a period of time); and determine the first hardware capacity based on the indication of memory utilization during the time period (see para [0091], discloses determining capacity limitations for a DCU over a period of time).
Regarding claims 5 and 15, Wu/Shanthakumar teach a system of claim 1 and a method of claim 11.
Wu further teaches wherein determining the first hardware capacity for hosting the first data partition comprises modifying a previous hardware capacity determined for hosting the first data partition (see col. 5 ln 14-16, discloses increasing (modifying) capacity of set of nodes that host shards).
Regarding claim 6, Wu/Shanthakumar teach a system of claim 1.
Wu further teaches wherein modifying the previous hardware capacity for hosting the first data partition comprises increasing the previous hardware capacity for hosting the first data partition (see col. 5 ln 14-16, col. 9 ln 27-28, discloses increasing capacity of set of nodes that host shards).
Regarding claim 7, Wu/Shanthakumar teach a system of claim 1.
Wu further teaches wherein modifying the previous hardware capacity for hosting the first data partition comprises decreasing the previous hardware capacity for hosting the first data partition (see col. 9 ln 27-28, discloses decreasing resource capacity used).
Regarding claim18, Wu/Shanthakumar teach a system of claim 17.
Wu does not explicitly teach wherein the at least one processor is configured to modify a configuration of the database hardware to update the hardware capacity used to host the particular data partition based on a record of operations performed on the particular data partition over a time period.
Shanthakumar teaches wherein the at least one processor is configured to modify a configuration of the database hardware to update the hardware capacity used to host the particular data partition based on a record of operations performed on the particular data partition over a time period (see para [0076], discloses updating hardware capacity based on a period of time).
Regarding claim19, Wu/Shanthakumar teach a system of claim 17.
Wu does not explicitly teach wherein the at least one processor is configured to modify the configuration of the database hardware to update the hardware capacity used to host the particular data partition based on the record of operations performed on the particular data partition over the time period by performing: determine a memory utilization of the operations performed on the at least one data partition over the time period; modify the configuration of the database hardware to update the hardware capacity used to host the particular data partition based on the memory utilization.
Shanthakumar teaches wherein the at least one processor is configured to modify the configuration of the database hardware to update the hardware capacity used to host the particular data partition based on the record of operations performed on the particular data partition over the time period by performing: determine a memory utilization of the operations performed on the at least one data partition over the time period; modify the configuration of the database hardware to update the hardware capacity used to host the particular data partition based on the memory utilization (see para [0075-0076], discloses memory utilization for a resource over a period of time).
Regarding claim20, Wu/Shanthakumar teach a system of claim 17.
Wu does not explicitly teach wherein modifying the configuration of the database hardware to update the hardware capacity used to host the particular data partition comprises: determine whether the memory utilization meets a threshold memory utilization; and trigger the modification of the configuration of the database hardware to update the hardware capacity used to host the particular data partition in response to determining that the memory utilization meets the threshold memory utilization.
Shanthakumar teaches wherein modifying the configuration of the database hardware to update the hardware capacity used to host the particular data partition comprises: determine whether the memory utilization meets a threshold memory utilization (see para [0091-0092], discloses utilization over a period of time with respect to a threshold); and trigger the modification of the configuration of the database hardware to update the hardware capacity used to host the particular data partition in response to determining that the memory utilization meets the threshold memory utilization (see para [0093-0094], discloses scaling decisions made that trigger a wait period of time before reevaluating and allocating DCUs).
Claims 8-10 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Wu et al. (US 11,030,169)(hereinafter Wu) in view of Shathakumar et al. (US 2025/0173338)(hereinafter Shathakumar) as applied to claims 1 and 11, and in further view of Song et al. (US 2017/032011) (hereinafter Song).
Regarding claim 8, Wu/Shanthakumar teach a system of claim 1.
Wu/Shanthakumar does not explicitly teach wherein: the first data partition is replicated across a plurality of nodes; and the instructions further cause the at least one processor to: determine a hardware capacity for a first node of the plurality of nodes; and determine a hardware capacity for a second node of the plurality of nodes, wherein the hardware capacity determined for the second node is different from the hardware capacity of the determined for the first node; and configure the first set of database hardware to host the first node using the hardware capacity determined for the first node and to host the second node using the hardware capacity determined for the second node.
Song teaches wherein: the first data partition is replicated across a plurality of nodes (see Fig. 3B, para [0024], discloses sharding protocol and configurable replication of shards across nodes); and the instructions further cause the at least one processor to: determine a hardware capacity for a first node of the plurality of nodes (see para [0025], para [0037], discloses capacities of respective nodes and shard allocation); and determine a hardware capacity for a second node of the plurality of nodes, wherein the hardware capacity determined for the second node is different from the hardware capacity of the determined for the first node (see para [0025], para [0037], discloses capacities of respective nodes and shard allocation); and configure the first set of database hardware to host the first node using the hardware capacity determined for the first node and to host the second node using the hardware capacity determined for the second node (see fig. 1, para [0013, 0015], para [0049-0050], discloses configuring respective capacities for respective nodes based on parameters).
Wu/Shanthakumar/Song are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Wu/Shanthakumar to include partition replication across plurality of nodes from disclosure of Song. The motivation to combine these arts is disclosed by Song as “a partial replication system can significantly improve scalability and convergence of spine nodes,” (para [0025]) and including partition replication across plurality of nodes is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Regarding claims 9 and 16, Wu/Shanthakumar teach a system of claim 1 and a method of claim 11.
Wu/Shanthakumar does not explicitly teach wherein determining the first hardware capacity for hosting the first data partition comprises: selecting the first hardware capacity from among a plurality of hardware capacities that the database hardware is configurable to provide.
Song teaches wherein determining the first hardware capacity for hosting the first data partition comprises: selecting the first hardware capacity from among a plurality of hardware capacities that the database hardware is configurable to provide (see Figs. 3A-4, para [0037], discloses closes selecting a capacity level for respective spine in shard allocation).
Wu/Shanthakumar/Song are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Wu/Shanthakumar to include partition replication across plurality of nodes from disclosure of Song. The motivation to combine these arts is disclosed by Song as “a partial replication system can significantly improve scalability and convergence of spine nodes,” (para [0025]) and including partition replication across plurality of nodes is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Regarding claim 10, Wu/Shanthakumar teach a system of claim 1.
Wu/Shanthakumar does not explicitly teach wherein each of the plurality of hardware capacities comprises a specification of at least one of: CPU hardware to be used to host a data partition; and an amount of RAM to be used to host a data partition.
Song teaches wherein each of the plurality of hardware capacities comprises a specification of at least one of: CPU hardware to be used to host a data partition; and an amount of RAM to be used to host a data partition (see Figs. 1-3B, par [0030], para [0082-0083], discloses host for shards and memory capacities).
Wu/Shanthakumar/Song are analogous arts as they are each from the same field of endeavor of database systems.
Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Wu/Shanthakumar to include partition replication across plurality of nodes from disclosure of Song. The motivation to combine these arts is disclosed by Song as “a partial replication system can significantly improve scalability and convergence of spine nodes,” (para [0025]) and including partition replication across plurality of nodes is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See Kleinerman et al. US Patent No. 11,461,273.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to COURTNEY HARMON whose telephone number is (571)270-5861. The examiner can normally be reached M-F 9am - 5pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ann Lo can be reached at 571-272-9767. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/Courtney Harmon/Primary Examiner, Art Unit 2159