DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In view of the Pre-Appeal conference filed on 04/14/2026, PROSECUTION IS HEREBY REOPENED. A new grounds of rejection under 35 U.S.C. 103 is set forth below.
To avoid abandonment of the application, appellant must exercise one of the following two options:
(1) file a reply under 37 CFR 1.111 (if this Office action is non-final) or a reply under 37 CFR 1.113 (if this Office action is final); or,
(2) initiate a new appeal by filing a notice of appeal under 37 CFR 41.31 followed by an appeal brief under 37 CFR 41.37. The previously paid notice of appeal fee and appeal brief fee can be applied to the new appeal. If, however, the appeal fees set forth in 37 CFR 41.20 have been increased since they were previously paid, then appellant must pay the difference between the increased fees and the amount previously paid.
A Supervisory Patent Examiner (SPE) has approved of reopening prosecution by signing below:/ALEKSANDR KERZHNER/Supervisory Patent Examiner, Art Unit 2165
Response to Amendment
The response filed 04/14/2026 has been entered. Applicant has not amended any claims. Claim 6 remains cancelled. Claims 1-5 and 7-20 are currently pending. The finality of the previous office action is withdrawn.
Response to Arguments
Applicant’s arguments, see page 2 filed 04/14/2026, with respect to claims 1, 9, and 17 have been fully considered and are persuasive. The 35 U.S.C. 101 rejection of claims 1, 9, and 17 has been withdrawn.
Applicant’s arguments, see pages 3-5, filed 04/14/2026, with respect to the rejection(s) of claim(s) 1-5 and 7-20 under 35 U.S.C. 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Waas et al (US 11,403,291). Waas teaches the limitations that O’Connell was previously relied on in the previous office action.
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.
Claim(s) 1-2 ,7-8, 9-10, 14-16, and 17-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Raman et al (US 2019/0340291) in view of Waas et al (US 11,403,291)
Regarding claim 1, Raman teaches A device for querying a database that stores semantic data in a compressed linked tabular representation, comprising: a memory storing instructions; and a processor coupled to the memory and configured to execute the instructions to (Figure 4, 400): convert an initial language query for semantic data in the database to a language-agnostic representation of the initial language query ([0079] As a first variation of this third aspect, the base query format 432 of the translation 430 may comprise a sequence of query intermediate language instructions that logically execute the query over the data set. For example, the query intermediate language instructions may be selected of a query intermediate language format to which the native query formats 430 may be readily translated, and which provides operations that are logically equivalent to the operations provided in the native query formats 430.); generate, based on a nested structure of the language-agnostic representation, an ordered list of relational operators ([0079] - As a first such example, the query intermediate language may comprise JavaScript, which includes (e.g., as part of the JavaScript Query Language (JQL)) query operators that correspond to the logical operations that are supported by a wide variety of native query formats 430, such as projection; filtering; aggregation; sorting; flattening; arithmetic, logical, and data conversion expressions; hierarchical navigation across items and data sets; and specialized query operations, such as spatial queries. JavaScript may also provide an advantageous selection as a query intermediate language due to its prevalence in applications that utilize databases, such that a significant subset of queries 426 may provide a minimal translation 430 (e.g., simply validating the JavaScript syntax). For example, the base representations 302 of the items 416 of the data set 418 may be organized according to a JavaScript Object Notation (JSON) data model, and the query intermediate language instructions may be specified according to a query intermediate language that features variable types that are consistent with JavaScript variable types, thereby providing an efficient and expedient translation 430 for a significant subset of queries 426.);
Raman does not explicitly teach translate, based on the ordered list of relational operators, the language-agnostic representation into a database query of a query language syntax that is supported by the database, and execute the database query on the database without decompressing the compressed linked tabular representation.
Waas teaches translate, based on the ordered list of relational operators, the language-agnostic representation into a database query of a query language syntax that is supported by the database (Col 6 liens 50-65 and Col 7 lines 1-20 - At the core of the DVS is an extensible universal language-agnostic query representation called eXtended Relational Algebra (XTRA). Incoming queries are mapped to XTRA trees, which can then be serialized in the SQL dialect spoken by the target database system. The XTRA representation is an algebraic representation of the query that is independent of any database system. Further details on the XTRA representation can be found in U.S. Patent Publication 2016/0328442, filed on May 9, 2016, titled “Method and System for Transparent Interoperability Between Applications and Data Management Systems,” incorporated herein by reference..). and execute the database query on the database without decompressing the compressed linked tabular representation(Col 12 lines 50-65 and Col 13 1-25 As noted above, in some embodiments the Binder and Transformer perform metadata lookup requests via a metadata interface (MDI) when processing queries. FIG. 8 conceptually illustrates the DVS 800 system architecture for processing these metadata lookup requests. As described above, in some embodiments the Cross Compiler 805 passes an incoming query to the Query Interpreter 810 for parsing and normalizing into the XTRA representation, which is then passed to the Query Translator 815 for generating the serialized SQL statements for execution by the target database. Both the Query Interpreter 810 and the Query Translator 815 may issue metadata lookups via the metadata interface (MDI) 820. The MDI functions as an interface to a Metadata Manager (MDM) 825 which is responsible for formulating and initiating the queries to retrieve metadata from the target database catalog 830 and the MDStore 835. In some embodiments, the MDStore 835 is also maintained in the target database 840 (e.g., a cloud-based database such as Azure) alongside the target database catalog 830 by the database virtualization system 800. The retrieved metadata is cached in some embodiments in a metadata cache 845 by the MDM for use by other queries to the Cross Compiler 805 during the same session. In some embodiments, concurrent Cross Compiler sessions are served by a single MDM process..
Accordingly, it would have been obvious to one of ordinary skill in the art before the
effective filing date of the claimed invention to have modified the teachings of Raman to include translate, based on the ordered list of relational operators, the language-agnostic representation into a database query of a query language syntax that is supported by the database, and execute the database query on the database without decompressing the compressed linked tabular representation as taught by Waas. It would be advantageous since it allows for efficient use of system resources as taught by the cited section.
Regarding claim 2, Raman in view of Waas teaches The device of claim 1, Raman further teaches wherein the processor is configured to execute the instructions to translate the language-agnostic representation into the database query including: generating an innermost query portion of the database query based on a first operator in the ordered list of relational operators; and generating a next level query portion of the database query based on a next operator in the ordered list of relational operators ([0080] As a second variation of this third aspect, the translation 430 of a query 426 from a variety of native language formats 430 may be achieved in numerous ways. As one such example, a sever 402 may provide a set of application programming interfaces (APIs) for respective native query formats 430, such as an SQL API that produces translations 430 of SQL queries 426 over a relational table 106 into the base query format 432; an XPath API that produces translations 430 of XPath document-oriented queries 426 over a document 704 into the base query format 432; and a GraphQL API that produces translations 430 of GraphQL queries 426 over a graph 116 into the base query format 432. When a query 426 is received, an embodiment of the presented techniques may examine the query 426 to identify the native query format 430 of the query 426, and may select and invoke an API that translates the identified native query format 430 of the query 426 into the base query format 432. Additionally, an embodiment of the presented techniques may include an application programming interface extender that receives a new application programming interface for a new query language to be provided by the database 104 (e.g., a LINQ API that produces translations 430 of LINQ queries 426 over a data source into the base query format 432, and adds the new application programming interface to the application programming interface set. A server 102 may therefore provide extensibility in the set of supported native query formats 430 in which queries 426 may be provided.).
Regarding claim 7, Raman in view of Waas teaches The device of claim 1, Raman further teaches wherein the processor is configured to execute the instructions to generate the language-agnostic representation including using protocol buffers for serializing a query plan represented by the initial language query ([0082] FIG. 9 is an illustration of an example scenario 900 featuring an embodiment that applies queries 426 originally specified in a variety of native query formats 428 to a data set 418 comprising base representations 302 of items 426 in accordance with the techniques presented herein. In this example scenario 900, the queries 426 are originally specified in various query languages, such as JQL, SQL, GraphQL, NoSQL, LINQ, and XPath. The respective queries 426 may be subjected to a native query format determination 902 (e.g., identifying the native query format 428 of the query 426 according to its syntax, keywords, query source such as application type, and/or the native item format 420 of the items 416 over which the query 426 is specified). The embodiment further comprises an application programming interface set 904 of application programming interfaces 906 (“APIs”) for the respective native query formats 428, and that may be invoked to translate queries in the respective native query formats 428 into a translation 430 in a query intermediate language, such as a JQL query.).
Regarding claim 8, Raman in view of Waas teaches The device of claim 1, Raman further teaches wherein the initial language query is one of a structured query language (SQL) query, an imperative programming language query, or a natural language query ([0082] FIG. 9 is an illustration of an example scenario 900 featuring an embodiment that applies queries 426 originally specified in a variety of native query formats 428 to a data set 418 comprising base representations 302 of items 426 in accordance with the techniques presented herein. In this example scenario 900, the queries 426 are originally specified in various query languages, such as JQL, SQL, GraphQL, NoSQL, LINQ, and XPath. The respective queries 426 may be subjected to a native query format determination 902 (e.g., identifying the native query format 428 of the query 426 according to its syntax, keywords, query source such as application type, and/or the native item format 420 of the items 416 over which the query 426 is specified). The embodiment further comprises an application programming interface set 904 of application programming interfaces 906 (“APIs”) for the respective native query formats 428, and that may be invoked to translate queries in the respective native query formats 428 into a translation 430 in a query intermediate language, such as a JQL query).
Claims 9-10, 14-16, and 17-18 are rejected using similar reasoning seen in the rejection of claims 1-2 and 7-8 due to reciting similar limitations but directed towards a method and a computer readable storage medium.
Allowable Subject Matter
Claims 3-5, 11-13, and 19-20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SAMUEL SHARPLESS whose telephone number is (571)272-1521. The examiner can normally be reached M-F 7:30 AM- 3:30 PM (ET).
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/S.C.S./Examiner, Art Unit 2165
/ALEKSANDR KERZHNER/Supervisory Patent Examiner, Art Unit 2165
Prosecution Insights