741DETAILED 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 1/22/2026, in which claims 1, 10, 12, 14, 18, and 20 was amended, and claims 1 – 20 was presented for further examination.
3. Claims 1 – 20 are now pending in the application.
Response to Arguments
4. Applicant's arguments filed 1/22/2026 have been fully considered but they are not persuasive.(see remarks below).
Remarks
5. As per claim 1, applicant argues in substance in pages 11 – 13 that neither Chen et al (US 2017/0212931 A1) nor Zhou (US 2022/0075780 A1) specifically disclose optimizing, by using the optimizer, an execution path for a combination of one or more first operators obtained by using the SQL parser and one or more second operators obtained by using the Gremlin parser, to obtain the execution plan.
Examiner respectfully disagrees.
In response to applicants argument, Examiner respectfully responds that the combine teaching of Chen et al (US 2017/0212931 A1) and Zhou (US 2022/0075780 A1) specifically disclose each and every features of amended claim 1 including the feature of optimizing, by using the optimizer, an execution path for a combination of one or more first operators obtained by using the SQL parser and one or more second operators obtained by using the Gremlin parser, to obtain the execution plan (para.[0038], para.[0040], and para.[0066]).
Zhou discloses fusion query. The fusion query includes the first type of query and second type of query. The system includes a main execution engine and one or more extensible execution engine. Each execution engine supports different types of queries and includes a parser 210, a rewriter 230, an optimizer 250, and an executor. The main function of each execution engine is to generate a query plan and perform operation to generate a query result (see para.[0007] and para.[0038]). A fusion query which includes both SQL and graph (Gremlin) query is received from the user and passes to main execution engine for processing (see para.[0042] – para.[0043] and para.[0051]). Each type of query included in the fusion query is identified and passes to appropriate execution engine. The first query type is parsed by the parser in the first execution engine and the second query type is parsed by the parser in the second execution engine. The result of each execution engine is returned to the main execution engine for processing (see para.[0062] and para.[0064] – para.[0065]).
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 – 20 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al (US 2017/0212931 A1), in view of Zhou (US 2022/0075780 A1), and further in view of LI et al (US 2022/0067044 A1).
As per claim 1, Chen et al (US 2017/0212931 A1) discloses,
A data query method, performed by a query engine (para.[0013]; “query engine 104 that receives and processes a hybrid query” and para.[0023]; “database management system that contains the query engine”).
wherein the method comprises: receiving a user query (para.[0015]; “users to specify in a SQL query, for example, embedded Cypher query for traversing graphs, which may be embedded into a SQL query tree”).
wherein the user query comprises an SQL query statement and a Gremlin graph query statement embedded into the SQL query statement (para.[0013]; “a query that is generally formatted according to a relational database (RDB) language protocol (such as SQL, for example) but contains one or multiple embedded queries associated with a graph transversal”, where graph query can be interpreted as “Gremlin graph query”).
the Gremlin graph query statement indicates to perform matching on one or more types of graph elements in a target graph (para.[0016]; “outsource, processing of GDB query expressions to a GDB query engine 130 (see FIG. 1), which performs a corresponding search on the GDB(s)”).
and the one or more types of graph elements comprise at least one of a point type, an edge type, or a path type (para.[0001]; “type of database is a graph database, which is based on a graph structure having nodes, properties and edges. The nodes represent entities, and the properties are pertinent information that relate to the nodes. The edges are the lines that connect nodes to nodes or nodes to properties”).
parsing the user query (para.[0014]; “query engine 104 parses the hybrid query”).
Chen explained its invention with a Cypher query graph which is one type of query graph but does not explicitly disclose Gremlin query graph and determine an execution plan and performing a data query based on the execution plan and returning a query result; wherein the query engine comprises an SQL parser, a Gremlin parser, and an optimizer; and the parsing the user query, to determine the execution plan comprises: optimizing, by using the optimizer, an execution path for a combination of one or more first operators obtained by using the SQL parser and one or more second operators obtained by using the Gremlin parser, to obtain the execution plan.
However, Zhou (US 2022/0075780 A1) in an analogous art discloses,
query comprises an SQL query statement and a Gremlin graph (para.[0051]; “query statement is a fusion query statement including both an SQL and a graph query” and para.[0080]; “a graph query language (for example, Gremlin) applicable to a graph database”).
to determine an execution plan and performing a data query based on the execution plan (para.[0068]; “graph execution engine 340 sequentially performs operations such as parsing, rewriting, optimization, and execution on the graph query statement to obtain the query result” and para.[0073]; “The optimizer 334 generates an optimal execution plan corresponding to a query statement…….The executor 336
executes the execution plan generated by the optimizer 334, to obtain a query result.”).
and returning a query result (para.[0017]; “returns the query result to the client”).
wherein the query engine comprises an SQL parser, a Gremlin parser, and an optimizer (NOTE: para.[0040]; “one execution engine includes a parser 210, a rewriter 230, an optimizer 250, and an executor 270 ……. rewriter 230 is configured to convert a query into a format that is easy to optimize ………… optimizer 250 is configured to select an optimal execution path” and para.[0066]; “main execution engine 132, for example, parsing, rewriting, optimization, or execution”)).
and the parsing the user query, to determine the execution plan comprises: optimizing, by using the optimizer (para.[0040];”Optimizer 250 is configured to select an optimal execution path” and para.[0066]; “main execution engine 132, for example, parsing, rewriting, optimization, or execution”).
an execution path for a combination of one or more first operators obtained by using the SQL parser and one or more second operators obtained by using the Gremlin parser, to obtain the execution plan (para.[0038]; “a main execution engine 132 and extensible execution engines 140 and 150” and para.[0064]; “the main execution engine 132 may perform query processing based on the intermediate
result returned by the extensible execution engine 140. …… other words, when processing the first type of query, the main execution engine 132 may refer to the intermediate result of processing the second type of query by the extensible
execution engine 140”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate fusion query that includes Gremlin graph query of the system of Zhou into hybrid query of the system of Chen to provide a user with a uniform interface for comprehensive access to multi-model database, thereby enabling the user to receive information from different database formats.
Zhou disclose each execution engine includes parser for specific type of query. To further explained specific type of parser that are included in each execution engine, LI et al (US 2022/0067044 A1) in an analogous art discloses,
wherein the query engine comprises an SQL parser, a Gremlin parser, and an optimizer (para.[0064]; “a parser for parsing a relational query, a parser for parsing a graph query, and a parser for parsing a time series query”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate parser service of the system of Li into fusion query of the system of Zhou to process and generate a respond to specific type of query submitted by the user.
As per claim 2, the rejection of claim 1 is incorporated and further Zhou (US 2022/0075780 A1) discloses,
wherein the user query requires to return a matched graph element (para.[0068]; “execution on the graph query statement to obtain the query result”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate fusion query that includes Gremlin graph query of the system of Zhou into hybrid query of the system of Chen to retrieve information from specific database formats through a uniform interface.
As per claim 3, the rejection of claim 1 is incorporated and further Zhou (US 2022/0075780 A1) discloses,
wherein the SQL query statement comprises a projection operation statement, to convert a graph element found based on the Gremlin graph query statement into row data (para.[0008]; “first extensible execution engine converts the second type of query into the first type of query” and para.[0009]; “first type of query is an SQL query, and the second type of query is a graph query”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate fusion query that includes Gremlin graph query of the system of Zhou into hybrid query of the system of Chen to provide necessary platform for executing the query on a multi-model database, thereby enabling the user to use a single query to access information from different database formats.
As per claim 4, the rejection of claim 1 is incorporated and further Zhou (US 2022/0075780 A1) discloses,
wherein the Gremlin graph query statement returns a matched subgraph, and the SQL query statement references a graph element in the subgraph by using a predetermined identifier (para.[0068]; “graph execution engine 340 sequentially performs operations such as parsing, rewriting, optimization, and execution on the graph query statement to obtain the query result”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate fusion query that includes Gremlin graph query of the system of Zhou into hybrid query of the system of Chen to provide a necessary platform for executing a query on a multi-model database, thereby enabling the user to use a single query to access information from different database formats.
As per claim 5, the rejection of claim 1 is incorporated and further Zhou (US 2022/0075780 A1) discloses,
wherein the query engine defines following data structure: the point type comprising one or more fields, and the one or more fields comprising at least an identifier field indicating a node ID (para.[0001]; “database is a graph database, which is based on a graph structure having nodes, properties and edges. The nodes represent entities”).
the edge type comprising one or more fields, and the one or more fields comprising at least an identifier field of each node in a node pair comprising a source node and a destination node (para.[0001]; “database is a graph
database, which is based on a graph structure having nodes, properties and edges …….. The edges are the lines that connect nodes to nodes or nodes to properties”).
and the path type comprising a type of consecutive points, a type of edges, or null values (para.[0001]; “database is a graph database, which is based on a graph structure having nodes, properties and edges ……… a given edge represents a relationship between connected nodes or a relationship between a connected node and property”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate fusion query that includes Gremlin graph query of the system of Zhou into hybrid query of the system of Chen to provide a necessary platform for executing a query on a multi-model database, thereby enabling the user to use a single query to access information from different database formats.
As per claim 6, the rejection of claim 1 is incorporated and further Zhou (US 2022/0075780 A1) discloses,
wherein the SQL query statement comprises a first statement, the first statement comprises a preset keyword for declaring an input parameter, a first parameter, and a second query, and the first parameter is used as a query parameter in the Gremlin graph query statement (para.[0042]; “example of the fusion query is given below”, para.[0043]; “example of the fusion query is given below”, para.[0043]; “with suspects (cid) as Gremlin(‘”, para.[0050]; “where c.id=s.id”, and para.[0051]; “fusion query statement including both an SQL and a graph query”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate fusion query that includes Gremlin graph query of the system of Zhou into hybrid query of the system of Chen to provide a necessary platform for executing a query on a multi-model database, thereby enabling the user to use a single query to access information from different database formats.
As per claim 7, the rejection of claim 6 is incorporated and further Zhou (US 2022/0075780 A1) discloses,
wherein the performing the data query comprises: performing the second query, and determining a parameter value of the first parameter based on a result of the second query, and performing matching in the Gremlin graph query statement based on the parameter value of the first parameter (para.[0062]; “after receiving the fusion query, the database management system 130 identifies a first type of query (for example, an SQL query) and a second type of query (for example, a graph query) included in the fusion query, passes the first type of query to the main execution engine 132 for processing, and passes the second type of query”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate fusion query that includes Gremlin graph query of the system of Zhou into hybrid query of the system of Chen to provide a necessary platform for executing a query on a multi-model database, thereby enabling the user to use a single query to access information from different database formats.
As per claim 8, the rejection of claim 7 is incorporated and further Zhou (US 2022/0075780 A1) discloses,
wherein the second query is an SQL query (para.[0066]; “process the graph query converted into the SQL query”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate fusion query that includes Gremlin graph query of the system of Zhou into hybrid query of the system of Chen to retrieve information from specific database format through a uniform interface.
As per claim 9, the rejection of claim 7 is incorporated and further Chen et al (US 2017/0212931 A1) discloses,
wherein the second query is an external function, and performing the second query comprises: calling the external function, and receiving a function operation result (para.[0023]; “parses the data from a data source that is external to the underlying database and returns relation tuples to feed the hosting query”).
As per claim 10, the rejection of claim 1 is incorporated and further Zhou (US 2022/0075780 A1) discloses,
the parsing the user query, to determine the execution plan further comprises: parsing the SQL query statement by using the SQL parser, to obtain the one or more first operators, wherein the one or more first operators represent a relationship operation for a table (para.[0073]; “SQL engine 330 includes a parser 332, an optimizer 334, an executor 336, and a hook module 338. The parser 332 is configured to parse an SQL query statement into a specific structure, for example, a query tree, through lexical analysis and syntax analysis”).
and parsing the Gremlin graph query statement by using the Gremlin parser, to obtain the one or more second operators, wherein the one or more second operators represent a relationship operation for a graph (para.[0068]; “graph execution engine 340 sequentially performs operations such as parsing, rewriting, optimization, and execution on the graph query statement to obtain the query result”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate fusion query that includes Gremlin graph query of the system of Zhou into hybrid query of the system of Chen to provide a necessary platform for executing a query on a multi-model database, thereby enabling the user to use a single query to access information from different database formats.
As per claim 11, the rejection of claim 10 is incorporated and further Zhou (US 2022/0075780 A1) discloses,
wherein the optimizing the execution path for the combination of the one or more first operators and the one or more second operators comprises: performing an operator adjustment operation, to obtain one or more candidate paths (para.[0073]; “optimizer 334 generates an optimal execution plan corresponding to a query statement according to a rule or based on a cost model. The executor 336 executes the execution plan generated by the optimizer 334, to obtain a query result”).
wherein the operator adjustment operation comprises one or more of: exchanging operator execution sequences and combining some operators, and operators on which the operator adjustment operation is performed comprise the first operator and the second operator and determining the optimized execution path based on an execution cost of each candidate path (para.[0073]; “optimizer 334 generates an optimal execution plan corresponding to a query statement according to a rule or based on a cost model. The executor 336 executes the execution plan generated by the optimizer 334, to obtain a query result”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate fusion query that includes Gremlin graph query of the system of Zhou into hybrid query of the system of Chen to provide a necessary platform for executing a query on a multi-model database, thereby enabling the user to use a single query to access information from different database formats.
As per claim 12, the rejection of claim 1 is incorporated and further Zhou (US 2022/0075780 A1) discloses,
wherein the query engine comprises the SQL parser and the optimizer, and a Gremlin querier configured to perform a Gremlin query is deployed outside the query engine (para.[0068]; “graph execution engine 340 sequentially performs operations such as parsing, rewriting, optimization, and execution on the graph query statement to obtain the query result”).
and the parsing the user query, to determine the execution plan comprises: parsing the SQL query statement by using the SQL parser, to obtain the one or more first operators, wherein the one or more first operators represent a relationship operation for a table (para.[0073]; “SQL engine 330 includes a parser 332, an optimizer 334, an executor 336, and a hook module 338. The parser 332 is configured to parse an SQL query statement into a specific structure, for example, a query tree, through lexical analysis and syntax analysis”).
and optimizing, by using the optimizer, an execution path for a combination of the one or more first operators and a graph operation operator, to obtain the execution plan, wherein the graph operation operator corresponds to the Gremlin graph query statement, and is set to be a fixed-cost and non-separable operation (para.[0073]; “optimizer 334 generates an optimal execution plan corresponding to a query statement according to a rule or based on a cost model. The executor 336 executes the execution plan generated by the optimizer 334, to obtain a query result”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate fusion query that includes Gremlin graph query of the system of Zhou into hybrid query of the system of Chen to provide a necessary platform for executing a query on a multi-model database, thereby enabling the user to use a single query to access information from different database formats.
As per claim 13, the rejection of claim 12 is incorporated and further Zhou (US 2022/0075780 A1) discloses,
wherein the performing the data query based on the execution plan comprises: calling an interface provided by the Gremlin querier, to obtain a matching result of the Gremlin graph query statement (para.[0068]; “graph execution engine 340 sequentially performs operations such as parsing, rewriting, optimization, and execution on the graph query statement to obtain the query result”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate fusion query that includes Gremlin graph query of the system of Zhou into hybrid query of the system of Chen to provide a necessary platform for executing a query on a multi-model database, thereby enabling the user to use a single query to access information from different database formats.
As per claim 17, the rejection of claim 14 is incorporated and further Zhou (US 2022/0075780 A1) discloses,
wherein the SQL query statement comprises a first statement, the first statement comprises a preset keyword for declaring an input parameter, a first parameter, and a second query, and the first parameter is used as a query parameter in the Gremlin graph query statement (para.[0042]; “example of the fusion query is given below”, para.[0043]; “example of the fusion query is given below”, para.[0043]; “with suspects (cid) as Gremlin(‘”, para.[0050]; “where c.id=s.id”, and para.[0051]; “fusion query statement including both an SQL and a graph query”).
and the processor is further configured to: perform the second query, and determine a parameter value of the first parameter based on a result of the second query; and perform matching in the Gremlin graph query statement based on the parameter value of the first parameter (para.[0062]; “after receiving the fusion query, the database management system 130 identifies a first type of query (for example, an SQL query) and a second type of query (for example, a graph query) included in the fusion query, passes the first type of query to the main execution engine 132 for processing, and passes the second type of query”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate fusion query that includes Gremlin graph query of the system of Zhou into hybrid query of the system of Chen to provide a necessary platform for executing a query on a multi-model database, thereby enabling the user to use a single query to access information from different database formats.
Claims 14, 15 – 16, and 18 – 20 are device claim corresponding to method claims 1, 3 – 4, and 10 – 12 respectively, and rejected under the same reason set forth in connection to the rejection of claims 1, 3 – 4, and 10 – 12 respectively above.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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, 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.
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.
/AUGUSTINE K. OBISESAN/
Primary Examiner
Art Unit 2156
4/22/2026
Prosecution Insights