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 responsive to amendment filed on 03/09/2026. Claims 8 and 20 have been canceled. Claims 1-7 and 9-19 have been examined and are pending in this application.
Response to Arguments
Applicant's arguments filed 03/09/2026 have been fully considered but they are not persuasive.
Applicant argues, page 10 of the remarks, “Applicant respectfully submits that, as discussed and agreed to during the interview, the cited portion of Wang has not been shown to disclose or suggest ‘predicting an amount of the memory needed by the each of the at least one database instance in a next period based on the quantity of data persisted by stored in the each of the at least one database instance to the persistent storage medium in the historical period,’ as recited by amended claim 1. Rather, the cited portion of Wang appears to describe generating a ‘memory use prediction for the application for an upcoming time period’ based on ‘set of current memory use samples.’ Id. In particular, the cited portion of Wang has not been shown to disclose or to suggest making a prediction based on ‘a quantity of data persisted by each of at least one database instance in the database to a persistent storage medium in a historical period.’”
The Examiner respectfully submits Wang elsewhere in the disclosure teaches the above-noted subject matter. In paragraph [0024, Wang teaches “the server system 104 can be configured for automatic database memory use prediction and adaptation using machine learning to automatically and dynamically adjust configured memory of the system 104 to preemptively avoid memory issues such as the server system 104 running out of memory, crashing due to low memory, etc.” (Emphasis added).
Applicant argues, page 10 of the remarks, “The cited portion of Wang has also not been shown to disclose or to suggest that ‘a larger quantity of data persisted by the each of the at least one database instance to the persistent storage medium in the historical period results in a larger predicted amount of the memory for the each of the at least one database instance in the next period.’”
The Examiner respectfully submits that as cited in the preceding paragraphs, paragraph [0024] of Wang teaches the above-noted claim limitation.
Applicant argues, page 10 of the remarks, “Nor has the cited portion of Wang been shown to disclose or suggest how to ‘reduce a frequency of writing data from the Mem Table to the persistent storage medium.’”
The Examiner respectfully submits that as cited in the preceding paragraphs, paragraph [0024] of Wang teaches the above-noted claim limitation.
In view of the foregoing remarks, independent claims 1, 9, and 15 are not in a condition for allowance. Claims depending therefrom, either directly or indirectly, are also not in a condition for allowance.
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.
Claims 1-2, 8-10, 14-16, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. US 2023/0376202 (“Wang”) in view of Jin et al. US 2020/0341678 (“Jin”).
As per independent claim 1, Wang teaches A method for allocating database memory (“A computer-implemented method for machine learning database memory use prediction and adaptation,” see claim 1), comprising:
determining a quantity of data persisted by each of at least one database instance in a database to a persistent storage medium in a historical period (“A plurality of historical memory use samples of amounts of memory used by the database are determined for the application based on the sampling interval (604).” Para 0054 and FIG. 6. “The database 305 can have a disk backup 307.” Para 0032 and FIG. 3),
predicting an amount of the memory needed by the each of the at least one database instance in a next period based on the quantity of data persisted by the each of the at least one database instance to the persistent storage medium in the historical period (“A memory use prediction for the application for an upcoming time period is received from the machine learning model (612).” Para 0058 and FIG. 6. “The database 305 can have a disk backup 307.” Para 0032 and FIG. 3), wherein the amount of the memory needed by the each of the at least one database instance in the next period is positively correlated with the quantity of data persisted by the each of the at least one database instance to the persistent storage medium in the historical period (“A determination is made as to whether to extend memory of the database for the application based on the memory use prediction received from the machine learning model (614). Para 0059 and FIG. 6. “After the current prediction 326 has been generated for a future time point or upcoming time period, the memory extender engine 330 can measure, at the future time point or in the upcoming time period, actual memory used 334 by the database 305.” Para 0045. “The database 305 can have a disk backup 307.” Para 0032 and FIG. 3), such that a larger quantity of data persisted by the each of the at least one database instance to the persistent storage medium in the historical period results in a larger predicted amount of the memory for the each of the at least one database instance in the next period to reduce a frequency of writing data from the MemTable to the persistent storage medium (“the server system 104 can be configured for automatic database memory use prediction and adaptation using machine learning to automatically and dynamically adjust configured memory of the system 104 to preemptively avoid memory issues such as the server system 104 running out of memory, crashing due to low memory, etc.” Para 0024. “The database 305 can have a disk backup 307.” Para 0032 and FIG. 3);
allocating the memory for the each of the at least one database instance in the next period based on the amount of the memory needed by the each of the at least one database instance in the next period (“Extending the memory 306 (e.g., making more memory available to the database 305) can be performed in various ways. Some approaches can include automatic action by the memory extender engine 330. For example, more memory can be made available to a particular database instance, container instance, etc., that is configured for the database 305.” Para 0044 and FIG. 3).
Wang discloses all of the claim limitations from above, but does not explicitly teach “wherein the database is configured to store data based on a log-structured merge (LSM) tree, the database comprises the at least one database instance, a memory of the database is configured to store data in a MemTable and an immutable MemTable respectively corresponding to the at least one database instance”.
However, specification at paragraph [0003] which is applicant admitted prior art (AAPA) teaches the above-noted claim limitations.
Nonetheless, in the interest of explicitly showing an analogous art in the same field of endeavor, prior art Jin is being relied upon. Jin teaches wherein the database is configured to store data based on a log-structured merge (LSM) tree (“the disclosure is applied to LSM-tree based data storage engines.” Para 0030), and wherein a memory of the database is configured to store data in a MemTable (“The RAM includes … a mutable table.” Para 0031) and an immutable MemTable (“The RAM includes an immutable table ….” Para 0031) respectively corresponding to the at least one database instance (“The data storage engine is used for managing data in a RAM and a disk,” para 0031).
Given the teaching of Jin, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to further modify the scope of the invention of Wang with “wherein the database is configured to store data based on a log-structured merge (LSM) tree, and wherein a memory of the database is configured to store data in a MemTable and an immutable MemTable respectively corresponding to the at least one database instance”. The motivation would be that the arrangement of the data storage engine improves query efficiency, para 0019 of Jin.
As per dependent claim 2, Wang in combination with Jin discloses the method of claim 1. Wang teaches wherein the quantity of data stored in the each of the at least one database instance in the historical period comprises a quantity of data stored in the each of the at least one database instance in a previous historical period (“A plurality of historical memory use samples of amounts of memory used by the database are determined for the application based on the sampling interval (604).” Para 0054 and FIG. 6), or an average value of quantities of data stored in the each of the at least one database instance in several previous historical periods.
As per claims 9-10 these claims are respectively rejected based on arguments provided above for similar rejected claims 1-2. See independent claim 8 of Wang for non-transitory computer readable medium storing computer executable instructions.
As per dependent claim 14, Wang in combination with Jin discloses the method of claim 9. Wang teaches wherein the quantity of data stored in the each of the at least one database instance in the historical period is: a total quantity of data corresponding to the each of the at least one database instance that has been persisted to a persistent storage medium (“A plurality of historical memory use samples of amounts of memory used by the database are determined for the application based on the sampling interval (604).” Para 0054 and FIG. 6. “The database 305 can have a disk backup 307.” Para 0032 and FIG. 3); or a total quantity of data corresponding to the each of the at least one database instance stored in the memory and data that has been persisted to a persisted storage medium (“A plurality of historical memory use samples of amounts of memory used by the database are determined for the application based on the sampling interval (604).” Para 0054 and FIG. 6. “The database 305 can have a disk backup 307.” Para 0032 and FIG. 3).
As per claims 15-16, these claims are respectively rejected based on arguments provided above for similar rejected claims 1-2. See FIG. 7 of Wang for processor 710 and memory 720.
Claims 3, 11, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Jin and in further view of Bostic et al. US 2017/0091327 (“Bostic”).
As per dependent claim 3, Wang in combination with Jin discloses the method of claim 1. Wang and Jin may not explicitly disclose, but in an analogous art in the same field of endeavor, Bostic teaches wherein the predicting a memory needed by the each of the at least one database instance in a next period based on the quantity of data stored in the each of the at least one database instance in the historical period comprises: calculating a total quantity of data stored in all of the at least one database instance in the historical period; determining a ratio of the quantity of data stored in the each of the at least one database instance in the historical period to the total quantity of data; and determining the memory needed by the each of the at least one database instance in the next period based on the ratio and an allocable memory, wherein a larger ratio indicates a larger proportion of a memory needed by a corresponding database instance in the next period in the allocable memory (“At step 720, one or more data format selection options for a portion of a database may be presented to a user. The user may be an administrator of the database system, or may be any user with credentials that allow for selection of a data format for the portion of the database. In a preferred embodiment, the user interacts with the system via a user interface allowing for the selection of data formats to be used in storing a portion of the database. A screen may be displayed to the user providing the option to identify a portion of the database and choose a desired data format in which to store that portion of the database. In some embodiments, a storage engine selector may assist with the decision by providing analytics and recommendations enabling an informed decision regarding the storage format. For example, the user may be presented with an interface showing the historical read/write operation ratio for particular period of time, which may be configurable. Other analytics and metadata about the database (or the portion of the database to be stored) may also be presented, including the size and layout of the data.” Para 0097 and FIG. 7).
Given the teaching of Bostic, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to further modify the scope of the invention of Wang and Jin with “wherein the predicting a memory needed by the each of the at least one database instance in a next period based on the quantity of data stored in the each of the at least one database instance in the historical period comprises: calculating a total quantity of data stored in all of the at least one database instance in the historical period; determining a ratio of the quantity of data stored in the each of the at least one database instance in the historical period to the total quantity of data; and determining the memory needed by the each of the at least one database instance in the next period based on the ratio and an allocable memory, wherein a larger ratio indicates a larger proportion of a memory needed by a corresponding database instance in the next period in the allocable memory”. The motivation would be that pluggable database storage engines improves execution efficiency of a managed database system, para 0064 of Bostic.
As per dependent claims 11 and 17, these claims are rejected based on arguments provided above for similar rejected dependent claim 3.
Claims 4-5 are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Jin and in further view of Bostic and in further view of Bhola US 2023/0376476 (“Bhola”).
As per dependent claim 4, Wang in combination with Jin and Bostic discloses the method of claim 3. Wang, Jin, and Bostic may not explicitly disclose, but in an analogous art in the same field of endeavor, Bhola teaches wherein an upper memory limit value (“Data from a memtable may be flushed to levels (e.g., L0-L6) of the LSM tree when the memtable reaches a maximum memory capacity.” Para 0071) and a lower memory limit value are pre-configured for the each of the at least one data base instance (“the determined capacity of the LSM tree can be based on the minimum determined generation rate and/or number of the compaction byte tokens and flush byte tokens.” Para 0092);
if a memory needed in the next period determined for a database instance is not greater than the upper memory limit value configured for the database instance and is not less than the lower memory limit value, memory allocation is performed based on the memory needed by the database instance in the next period (“the determined capacity of the LSM tree can be based on the minimum determined generation rate and/or number of the compaction byte tokens and flush byte tokens.” Para 0092).
Given the teaching of Bhola, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to further modify the scope of the invention of Wang, Jin, and Bostic with “wherein an upper memory limit value and a lower memory limit value are pre-configured for the each of the at least one database instance; and if a memory needed in the next period determined for a database instance is not greater than the upper memory limit value configured for the database instance and is not less than the lower memory limit value, memory allocation is performed based on the memory needed by the database instance in the next period”. The motivation would be that the invention’s admission control can be useful when resources in a database system are saturated or overloaded, para 0024 of Bhola.
As per dependent claim 5, Wang in combination with Jin, Bostic, and Bhola discloses the method of claim 4. Wang, Jin, and Bostic may not explicitly disclose, but Bhola teaches wherein if a memory needed in the next period determined for a database instance is greater than the upper memory limit value, the memory needed by the corresponding database instance in the next period is determined as a first memory value that is not greater than the upper memory limit value; or if a memory needed in the next period determined for a database instance is less than the lower memory limit value, the memory needed by the corresponding database instance in the next period is determined as a second memory value that is not less than the lower memory limit value (“the determined capacity of the LSM tree can be based on the minimum determined generation rate and/or number of the compaction byte tokens and flush byte tokens.” Para 0092).
The same motivation that was utilized for combining Wang and Bhola as set forth in claim 4 is equally applicable to claim 5.
Claims 6, 12, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Jin and in further view of Bhola.
As per dependent claim 6, Wang in combination with Jin discloses the method of claim 1. Wang and Jin may not explicitly disclose, but an analogous art in the same field of endeavor, Bhola teaches wherein a part of the memory allocated for the each of the at least one database instance in the next period is used as a memory for burst data write (“maintain the LSM tree's ability to absorb bursts of write operations directed to stored data.” Para 0025).
Given the teaching of Bhola, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to further modify the scope of the invention of Wang and Jin with “wherein a part of the memory allocated for the each of the at least one database instance in the next period is used as a memory for burst data write”. The motivation would be that the invention’s admission control can be useful when resources in a database system are saturated or overloaded, para 0024 of Bhola.
As per dependent claims 12 and 18, these claims are rejected based on arguments provided above for similar rejected dependent claim 6.
Claims 7, 13, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Jin and in further view of Davis et al. US 2020/0117589 (“Davis”).
As per dependent claim 7, Wang in combination with Jin discloses the method of claim 1. Wang and Jin may not explicitly disclose, but an analogous art in the same field of endeavor, Davis teaches wherein a quantity of database instances supported by the database does not exceed an upper instance limit value supported by the database (“At step 502, a size of X key database tables of the database server instance is measured.” Para 0036 and FIG. 5. The upper bound is given by the sum of the sizes of all of the database server instances, see the numerator in the equation in para 0038), the upper instance limit value is determined based on an allocable memory and a lower memory limit value of the database instance (“At step 502, a size of X key database tables of the database server instance is measured.” Para 0036 and FIG. 5. The upper bound is given by the sum of the sizes of all of the database server instances, see the numerator in the equation in para 0038. The lower bound is given by the numerator in the equation for a subset of the database instances, see para 0037), and the lower memory limit value of the database instance is a predetermined value (the size is given in MB, paras 0037-0038).
Given the teaching of Bhola, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to further modify the scope of the invention of Wang and Jin with “wherein a quantity of database instances supported by the database does not exceed an upper instance limit value supported by the database, the upper instance limit value is determined based on an allocable memory and a lower memory limit value of the database instance, and the lower memory limit value of the database instance is a predetermined value”. The motivation would that instantiations of database may be shared amongst multiple customers, para 0012 of Davis, thereby lowering the cost of the database amongst multiple customers.
As per dependent claims 13 and 19, these claims are rejected based on arguments provided above for similar rejected dependent claim 7.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ZUBAIR AHMED whose telephone number is (571)272-1655. The examiner can normally be reached 7:30AM - 5:00PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, HOSAIN T. ALAM can be reached at (571) 272-3978. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ZUBAIR AHMED/Examiner, Art Unit 2132
/HOSAIN T ALAM/Supervisory Patent Examiner, Art Unit 2132