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 .
2. This action is in response to amendment filed on 7/6/2026, in which claims 1 – 22 was presented for further examination.
3. Claims 1 – 22 are now pending in the application.
Response to Arguments
4. Applicant's arguments filed 7/6/2026 have been fully considered but they are not persuasive. (see Remarks below).
Remarks
5. As per claim 1, applicants’ argues in substance in pages 10 – 12 that Cunningham et al (US 2010/0306188 A1) and Thai (US 5,560,007) does not disclose if the cost of the new current execution plan is lower than the cost of the prior execution plan, storing the new current execution plan and the new current execution plan statistics in the query storage as the last execution plan and the indication that the query is in the training mode, and when the cost of the current execution plan is not less than the cost of the prior execution plan, storing the indication that the query is not in the training mode along with the prior execution plan as the execution plan to be used for future instances of the query.
Examiner respectfully disagrees.
In response to applicants’ argument, Examiner respectfully responds that Cunningham et al (US 2010/0306188 A1) and Thai (US 5,560,007) specifically discloses if the cost of the new current execution plan is lower than the cost of the prior execution plan, storing the new current execution plan and the new current execution plan statistics in the query storage as the last execution plan and the indication that the query is in the training mode, and when the cost of the current execution plan is not less than the cost of the prior execution plan, storing the indication that the query is not in the training mode along with the prior execution plan as the execution plan to be used for future instances of the query.
Cunningham discloses a system where optimizer generates a query plan for a database queries and resultant query plan are stored in a persistent storage. When a new query is received, a query plan is generated and its execution metrics are compared against the stored query plan to determine whether they are identical. An appropriate query plan are selected based on the cost associated with the query plan (see para.[0007] and para.[0008]). The cost of executing each query plan are generated and stored alongside with the query plan (see para.[0003]). When a new query is received, query plan storage is search to compare the query plan cost with the current query in order determine or identify when it contains matching query plan. The system performed this operation to determine whether to use newly computed query plan or stored query plan (see para.[0047]). Each of the query plan produced by optimizer is stored in the query plan storage with their associated collected metrics information (see para.[0040] – para.[0041]).
Thai discloses the process of organizing access to information. A query with their search condition are entered into the database system. An optimizer optimized the query to provide rapid access to desired record (see col.3 lines 65 – 67 and col.4 lines 1 – 8). The system provide different level of optimization mode for the query, the optimizer determines whether the query is in the learned mode (i.e. interpreted training mode).
Since Cunnigham store query plan with their associated metrics, the system of Thai can be incorporated into Cunnigham to include learned node condition as part of the information associated with query plan.
As per applicants, argument that query execution metrics is different from query statistics. Examiner explained that query metrics and query statistics has been commonly interchange in the field because both contains same information such as cost of execution, CPU and bandwidth used to execute the query along with other information associated with query runtime, and some other query runtime information..
5.1 Thus, the rejection is maintained.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
6. Claims 1 – 6, 9 – 14, and 17 – 22 are rejected under 35 U.S.C. 103 as being unpatentable over Cunningham et al (US 2010/0306188 A1), in view of Thai (US 5,560,007).
As per claim 1, Cunningham et al (US 2010/0306188 A1) discloses,
A query processing device (para.[0007]; “a system compiles queries” and para.[0035]; “query processing system”).
comprising: a communication interface configured to communicate with a database and with a query storage, (para.[0025]; “components may communicate via local or remote processes such as in accordance with a signal having one or more data packets ( e.g. data from one component interacting with another component in a local system, distributed system”, para.[0029]; “Storage device 112 may include one or more disk drives, flash memory”, and para.[0030]; “Each of clients 102-106 may communicate with Web server”).
a memory storing instructions and a processor coupled to the communication interface and to the memory (para.[0103]; “computing system 600 also includes main memory 606. …. main memory 606 is a volatile memory, such as dynamic random access (DRAM) memory”).
the processor executing the instructions to: receive a query that is identical to a previously executed query (para.[0007]; “receiving a new query” and para.[0044]; “second query is identical or equivalent to the first query”).
and that a prior execution plan and prior execution plan statistics are stored in the query storage for the previously executed query (para.[0042]; “Storage of a query plan may include storing one or more representations of the corresponding query”, para.[0043]; “Lookup component 220 may search QP storage 222 and determine whether one or more stored query plans match the current query”, para.[0047]; “compare the lowest cost plan that is found with the default query plan”, para.[0049]; “metrics collector 224 may perform actions to retrieve metrics corresponding to executed or executing query plans”, where metric associated with executed query plan is interpreted as “execution plan statistics” as claimed).
generate a new current execution plan for the query (para.[0043]; “lookup component 220 may receive a query in the form of SQL query 202, parse tree 206, or bound tree” and para.[0053]; “a query plan 214 that was received from
optimizer 212 as part of processing a current SQL query”).
execute the new current execution plan and collect new current execution plan statistics para.[0049]; “metrics collector 224 may perform actions to retrieve metrics corresponding to executed or executing query plans” and para.[0078]; “metrics relating to execution of the current query plan may be collected”).
and if the cost of the new current execution plan is lower than the cost of the prior execution plan (para.[0047]; “compare the lowest cost plan that is found with the default query plan 214. It may thus determine whether to use the default query plan 214 or a previously stored query plan”).
storing the new current execution plan and the new current execution plan statistics in the query storage as the last execution plan (para.[0039]; “query plans 214 that are produced by optimizer212 are stored in QP storage”, para.[0040]; “query plans to be stored in QP storage 222 are selected based on the likelihood of the query being reused, how recent the query or a similar one had been processed, or other factors”, and para.[0042]; “Storage of a query plan may include storing one or more representations of the corresponding query. The original query 202, the parse tree 206, bound tree 210, or any combination of these representations may be stored and associated with the corresponding query plan”).
and when the cost of the current execution plan is not less than the cost of the prior execution plan (para.[0048]; “optimize the query to produce a new query plan, search for a stored plan and compare the lowest cost stored plan with the new query, designating the one that is determined to be better as the plan to execute”).
storing the indication that the query is not in the training mode along with the prior execution plan as the execution plan to be used for future instances of the query (para.[0048]; “compare the lowest cost stored plan with the new query, designating the one that is determined to be better as the plan to execute”, para.[0049]; “metrics collector 224 may perform actions to retrieve metrics corresponding to executed or executing query plans”, and para.[0050]; “Metrics collector 224 may store the metrics in QP storage 222 in a format that enables efficient retrieval of metrics corresponding to a query plan”).
Thai does not specifically disclose determining that the query is in a training mode, and the indication that the query is in the training mode, query is not in the training mode.
However, Thai (US 5,560,007) in an analogous art discloses,
determine that the query is in a training mode, the indication that the query is in the training mode, query is not in the training mode (col.13 lines 10 – 12; “if the query comprises one entity conforming to Learned Mode criteria, optimization of the search query will also be Learned Mode”, thus, where query comprises one entity conforming to Learned Mode criteria is “query is in a training mode” as claimed).
Therefore, it would have been obvious to one of ordinary skill in the art at the time the invention was filed to incorporate query learning mode of the system of Thai into optimization of similar query of the system of Cunningham for providing rapid access to desired record.
As per claim 2, the rejection of claim 1 is incorporated, Cunningham et al (US 2010/0306188 A1) further discloses,
the processor further executing the instructions to: determine, based on the new current execution plan statistics and the prior execution plan statistics, that the query is not in the training mode (para.[0048]; “compare the lowest cost stored plan with the new query, designating the one that is determined to be better as the plan to execute”, para.[0049]; “metrics collector 224 may perform actions to retrieve metrics corresponding to executed or executing query plans”, and para.[0050]; “Metrics collector 224 may store the metrics in QP storage 222 in a format that enables efficient retrieval of metrics corresponding to a query plan”)
select a selected execution plan for the query from among a plurality of stored execution plans stored in the query storage (para.[0043]; “Lookup component 220 may search QP storage 222 and determine whether one or more stored query plans match the current query ……. lookup component 220 may determine which of the query plans is the lowest cost query plan”).
the plurality of stored execution plans including the prior execution plan and the new current execution plan (para.[0040]; “query plans 214 that are produced by optimizer212 are stored in QP storage” and para.[0069]; “a newly produced query plan is stored in QP storage. ………a newly produced plan is selectively stored in QP storage”).
and store the selected execution plan in the query storage, along with an indication that the query is not in the training mode such that on future receipt of an identical query, the selected execution plan will be used to execute the query (para.[0040]; “query plans 214 that are produced by optimizer212 are stored in QP storage” and para.[0044]; “wherein, a query plan that is produced from a first query may "match" a second query, if the second query is identical or equivalent to the first query …..if the second query is similar enough to the first query to allow the query plan to be used for the second query”).
As per claim 3, the rejection of claim 1 is incorporated, Cunningham et al (US 2010/0306188 A1) further discloses,
wherein the processor further executes the instructions to determine that the new current execution plan is identical to the prior execution plan (para.[0040]; “para.[0044]; “wherein, a query plan that is produced from a first query may "match" a second query, if the second query is identical or equivalent to the first query”).
As per claim 4, the rejection of claim 2 is incorporated, Cunningham et al (US 2010/0306188 A1) further discloses,
wherein: each execution plan of the plurality of stored execution plans includes a respective cost value (para.[0042]; “Storage of a query plan may include storing one or more representations of the corresponding query. The original query 202, the parse tree 206, bound tree 210, or any combination of these representations may be stored and associated with the corresponding query plan” and para.[0043]; “lookup component 220 may determine which of the query plans is the lowest cost query plan”).
and the processor further executes the instructions to select a lowest cost execution plan having an execution plan lowest cost value as the selected execution plan (para.[0043]; “considered the lowest cost plan. It may determine whether to use the lowest cost plan”).
.
As per claim 5, the rejection of claim 2 is incorporated, Cunningham et al (US 2010/0306188 A1) further discloses,
wherein: the prior execution plan is a last executed execution plan for the query prior to the new current execution plan for the query (claim 4; “producing a new query plan based on the query and on data associated with one or more previously executed query plans that correspond to the query”).
and wherein when the query is not in the training mode, the processor further executes the instructions to determine that a current execution plan cost value is greater than a prior execution plan cost value (para.[0047]; “Lookup component 220 may search QP storage 222 for one or more matching plans, as discussed above, and compare the lowest cost plan that is found with the default query plan”).
As per claim 6, the rejection of claim 5 is incorporated, Cunningham et al (US 2010/0306188 A1) further discloses,
wherein the processor further executes the instructions to select the prior execution plan for the query as the selected execution plan (para.[0043]; “lookup component 220 may determine which of the query plans is the lowest cost query plan”).
As per claim 9, Cunningham et al (US 2010/0306188 A1) discloses,
A query processing method (para.[0007]; “a system compiles queries” and para.[0035]; “query processing system”).
comprising: receiving a query that is identical to a previously executed query (para.[0007]; “receiving a new query” and para.[0044]; “second query is identical or equivalent to the first query”).
and that a prior execution plan and prior execution plan statistics are stored in a query storage for the previously executed query (para.[0042]; “Storage of a query plan may include storing one or more representations of the corresponding query” and para.[0043]; “Lookup component 220 may search QP storage 222 and determine whether one or more stored query plans match the current query”).
generating a new current execution plan for the query (para.[0047]; “query
plan 214 that is the most recent query plan produced by optimizer 212 for a specific SQL query 202 is referred to as the "default" query plan ……. compare the lowest cost plan that is found with the default query plan 214. It may thus determine whether to use the default query plan 214 or a previously stored query plan”).
executing the new current execution plan and collecting new current execution plan statistics (para.[0049]; “metrics collector 224 may perform actions to retrieve metrics corresponding to executed or executing query plans” and para.[0078]; “metrics relating to execution of the current query plan may be collected”).
and if the cost of the new current execution plan is lower than the cost of the prior execution plan (para.[0047]; “compare the lowest cost plan that is found with the default query plan 214. It may thus determine whether to use the default query plan 214 or a previously stored query plan”).
storing the new current execution plan and the new current execution plan statistics in the query storage as the last execution plan (para.[0039]; “query plans 214 that are produced by optimizer212 are stored in QP storage”, para.[0040]; “query plans to be stored in QP storage 222 are selected based on the likelihood of the query being reused, how recent the query or a similar one had been processed, or other factors”, and para.[0042]; “Storage of a query plan may include storing one or
more representations of the corresponding query. The original query 202, the parse tree 206, bound tree 210, or any combination of these representations may be stored and associated with the corresponding query plan”).
and when the cost of the current execution plan is not less than the cost of the prior execution plan (para.[0048]; “optimize the query to produce a new query plan, search for a stored plan and compare the lowest cost stored plan with the new query, designating the one that is determined to be better as the plan to execute”).
storing the indication that the query is not in the training mode along with the prior execution plan as the execution plan to be used for future instances of the query (para.[0048]; “compare the lowest cost stored plan with the new query, designating the one that is determined to be better as the plan to execute”, para.[0049]; “metrics collector 224 may perform actions to retrieve metrics corresponding to executed or executing query plans”, and para.[0050]; “Metrics collector 224 may store the metrics in QP storage 222 in a format that enables efficient retrieval of metrics corresponding to a query plan”).
Thai does not specifically disclose determining that the query is in a training mode, and the indication that the query is in the training mode, query is not in the training mode.
However, Thai (US 5,560,007) in an analogous art discloses,
determine that the query is in a training mode, and the indication that the query is in the training mode, query is not in the training mode (col.13 lines 10 – 12; “if the query comprises one entity conforming to Learned Mode criteria, optimization of the search query will also be Learned Mode”, thus, where query comprises one entity conforming to Learned Mode criteria is “query is in a training mode” as claimed).
Therefore, it would have been obvious to one of ordinary skill in the art at the time the invention was filed to incorporate query learning mode of the system of Thai into optimization of similar query of the system of Cunningham for providing rapid access to desired record.
As per claim 10, the rejection of claim 9 is incorporated, Cunningham et al (US 2010/0306188 A1) further discloses,
further comprising: determining, based on the new current execution plan statistics and the prior execution plan that the query is not in the training mode (para.[0048]; “compare the lowest cost stored plan with the new query, designating the one that is determined to be better as the plan to execute”, para.[0049]; “metrics collector 224 may perform actions to retrieve metrics corresponding to executed or executing query plans”, and para.[0050]; “Metrics collector 224 may store the metrics in QP storage 222 in a format that enables efficient retrieval of metrics corresponding to a query plan”).
selecting a selected execution plan for the query from among a plurality of stored execution plans (para.[0043]; “Lookup component 220 may search QP storage 222 and determine whether one or more stored query plans match the current query ……. lookup component 220 may determine which of the query plans is the lowest cost query plan”).
the plurality of stored execution plans including the prior execution plan and the new current execution plan (para.[0040]; “query plans 214 that are produced by optimizer212 are stored in QP storage” and para.[0069]; “a newly produced query plan is stored in QP storage. ………a newly produced plan is selectively stored in QP storage”).
and storing the selected execution plan for the query, along with an indication that the query is not in the training mode such that on future receipt of an identical query, the selected execution plan will be used to execute the query (para.[0040]; “query plans 214 that are produced by optimizer212 are stored in QP storage” and para.[0044]; “wherein, a query plan that is produced from a first query may "match" a second query, if the second query is identical or equivalent to the first query …..if the second query is similar enough to the first query to allow the query plan to be used for the second query”).
As per claim 11, the rejection of claim 10 is incorporated, Cunningham et al (US 2010/0306188 A1) further discloses,
wherein determining the query is not in the training mode includes determining that the new current execution plan is identical to the prior execution plan (para.[0040]; “para.[0044]; “wherein, a query plan that is produced from a first query may "match" a second query, if the second query is identical or equivalent to the first query”).
As per claim 12, the rejection of claim 10 is incorporated, Cunningham et al (US 2010/0306188 A1) further discloses,
wherein: each execution plan of the plurality of stored execution plans for the query includes a respective cost value (para.[0042]; “Storage of a query plan may include storing one or more representations of the corresponding query. The original query 202, the parse tree 206, bound tree 210, or any combination of these representations may be stored and associated with the corresponding query plan” and para.[0043]; “lookup component 220 may determine which of the query plans is the lowest cost query plan”).
and selecting the selected execution plan includes selecting a lowest cost execution plan having an execution plan lowest cost value as the selected execution plan (para.[0043]; “considered the lowest cost plan. It may determine whether to use the lowest cost plan”).
As per claim 13, the rejection of claim 10 is incorporated, Cunningham et al (US 2010/0306188 A1) further discloses,
wherein: the prior execution plan is a last executed execution plan for the query prior to the new current execution plan (claim 4; “producing a new query plan based on the query and on data associated with one or more previously executed query plans that correspond to the query”).
and wherein when the query is not in the training mode, determining a current execution plan cost value is greater than a prior execution plan cost value (para.[0047]; “Lookup component 220 may search QP storage 222 for one or more matching plans, as discussed above, and compare the lowest cost plan that is found with the default query plan”).
As per claim 14, the rejection of claim 13 is incorporated, Cunningham et al (US 2010/0306188 A1) further discloses,
wherein selecting the selected execution plan for the query includes selecting the prior execution plan as the selected execution plan (para.[0043]; “lookup component 220 may determine which of the query plans is the lowest cost query plan”).
Claims 17 - 22 are computer-readable medium claim corresponding to a query processing device claims 1 - 6 respectively, and rejected under the same reason set forth in connection to the rejection of claims 1 - 6 respectively above.
7. Claims 7 – 8 and 15 - 16 are rejected under 35 U.S.C. 103 as being unpatentable over Cunningham et al (US 2010/0306188 A1), in view of Thai (US 5,560,007), and further in view of Kalmul et al (US 2020/0264928 A1).
As per claim 7, the rejection of claim 1 is incorporated, Cunningham et al (US 2010/0306188 A1) further disclose
wherein the processor further executes the instructions to: receive a first submission of the query (para.[0007]; “receiving a new query” and para.[0064]; “SQL query and various representations thereof are referred to as the "new" query”)
determine that no execution plans for the first submission of the query are stored in the query storage (para.[0065]; “determination is made of whether at least one matching query plan was found that is sufficient to satisfy configured criteria. If at least one such plan is not found” and para.[0073]; “where a determination is made of whether a sufficient stored query plan has been found. If one has not been found”)
generate a first execution plan for the first submission of the query based on an estimate of a cost of executing the query (para.[0065]; “compilation of the new query may begin. The actions of block 308 may include parsing the SQL query to produce a parse tree, such as parse tree 206, and binding the parse tree to produce a bound tree …. where optimization of the bound tree is performed to produce a query plan. This query plan is referred to as the "new" query plan” para.[0071]; “a determination of the
certainty of the cost estimate for the new query plan”)
execute the first execution plan and collect first execution plan statistics (para.[00365]; “where the new query plan is designated as the query plan to execute. The process may flow to block 320, where the designated query plan is executed”, para.[0069]; “a newly produced query plan is stored in QP storage”, and para.[0078]; “ metrics relating to execution of the current query plan may be collected”).
and store the first execution plan and the first execution plan statistics in the query storage (para.[0040]; “query plans 214 that are produced by optimizer212 are stored in QP storage” and para.[0090]; “The plan may be stored in QP storage 222, with collected metrics, and marked as a reverted plan”).
Neither Cunningham nor Thai specifically disclose generate a hash value for the query, the query storage indexed by the hash value.
However, Kalmul et al (US 202/0264928 A1) in an analogous art discloses,
generate a hash value for the query (para.[0022]; “data query jobs” and para.[0091]; “generates an execution plan for a received job (step 406). The computer hashes the execution plan for the received job”).
the query storage indexed by the hash value (para.[0067]; “execution time statistics indexed by a hash on key attributes of each job execution plan”).
Therefore, it would have been obvious to one of ordinary skill in the art at the time the invention was filed to incorporate computation of predicted resources utilization of the system of Kalmul into query learning mode of the system of Thai to modify current query plan estimate with similar historical query plan statistics for generating query plan that may improve retrieval of relevant information in the system of Cunningham.
As per claim 8, the rejection of claim 1 is incorporated, Cunningham and Thai does not specifically disclose generate multiple steps for the current execution plan, generate respective hash values for the multiple steps, retrieve statistics from the query storage for each step of the multiple steps having stored statistics, using the respective hash values as an index, generate estimated statistics for each step of the multiple steps that do not have stored statistic, and produce an estimated cost for the current execution plan based on the retrieved statistics and the generated estimated statistics.
However, Kalmul et al (US 2020/0264928 A1) in an analogous art discloses,
wherein the processor further executes the instructions to: generate multiple steps for the current execution plan (para.[0091]; “generates an execution plan for a received job”).
generate respective hash values for the multiple steps (para.[0091]; “generates an execution plan for a received job (step 406). The computer hashes the execution plan for the received job”).
retrieve statistics from the query storage for each step of the multiple steps having stored statistics (para.[0040]; “jobs that do not have any corresponding historical resource utilization and execution time statistics, jobs having estimated resource consumption in excess of a predefined job resource consumption”).
using the respective hash values as an index (para.[0067]; “execution time statistics indexed by a hash on key attributes of each job execution plan”).
generate estimated statistics for each step of the multiple steps that do not have stored statistic (para.[0061]; “generates a predictive estimate of resources the job will require to execute and the job's expected execution time”).
and produce an estimated cost for the current execution plan based on the retrieved statistics and the generated estimated statistics (para.[0061]; “the computer utilizes a cost-based model approach with some special heuristics to generate both job resource utilization and execution time estimates” and para.[0063]; “generation of response time estimates is similar to relying on a cost estimate generated by a query optimizer, which builds off a cost model for individual operators incorporating column data types and database runtime statistics to produce a linearized estimate of computer resource utilization time (e.g., processor, memory, storage, I/O, network, and the like) for a given query execution plan”).
Therefore, it would have been obvious to one of ordinary skill in the art at the time the invention was filed to incorporate computation of predicted resources utilization of the system of Kalmul into query learning mode of the system of Thai to modify current query plan estimate with similar historical query plan statistics for generating query plan that may improve retrieval of relevant information in the system of Cunningham.
Claims 15 - 16 are method claim corresponding to a query processing device claims 7 - 8 respectively, and rejected under the same reason set forth in connection to the rejection of claims 7 - 8 respectively above.
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 AUGUSTINE KUNLE OBISESAN whose telephone number is (571)272-2020. The examiner can normally be reached 9:00am - 5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ajay Bhatia can be reached at (571) 272-3906. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/AUGUSTINE K. OBISESAN/
Primary Examiner
Art Unit 2156
9/16/2026
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