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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 9/10/2025 has been entered.
Response to Arguments
Claims 1 – 3, 5 – 15 and 17 – 20 are pending in this Office Action. After a further search and a thorough examination of the present application, claims 1 – 3, 5 – 15 and 17 – 20 remain rejected.
Applicant's arguments filed with respect to claims 1 – 3, 5 – 15 and 17 – 20 have been fully considered but they are not persuasive.
Applicant argues that there is no teaching in Xu, Salch and Griffith alone or in combination of predicting a query processing duration for the federated query based on a mapping between the identifier and the execution plan, wherein the query processing duration is based on (i) performance data associated with the logical dataset and stored in association with the identifier or (ii) a presence of the intermediate result set stored in association with the identifier.
In response to Applicant’s argument, the Examiner disagrees and submits that Xu in combination with Salch and further in combination with Griffith in combination teach predicting, by the one or more processors, a query processing duration for the federated query based on a mapping between the identifier and the execution plan, wherein the query processing duration is based on (i) performance data associated with the logical dataset and stored in association with the identifier or (ii) a presence of the intermediate result set stored in association with the identifier in paragraphs 48 – 49 and 60 teaches a mark join and a query execution module includes a result reuse module, which stores and reuses intermediate results that were created during a previous execution. Furthermore, Salch teaches in figure 5 and paragraphs 71 choosing the lowest overall execution cost among the logical plan alternatives. While executing the plan, the process watches for the aforementioned re-optimization markers placed in the plan by the process. For each step executed completely, the process retrieves actual real data size value for the resulting intermediate data results, which may be supplied through some manner from the data system upon completion. Paragraphs 74, 83 – 87 of Salch teach where some configurations, intermediate results from execution of an operations from one or more queries may be stored in a cache registry as respective cache objects.
Remaining claims in instant application recite the same subject matter and for the same reasons as cited above the rejection is maintained. Hence, Applicant’s arguments do not distinguish the claimed invention over the prior art of record. In light of the foregoing arguments, the 103 rejections are 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1 – 3, 5 – 15 and 17 – 20 are rejected under 35 U.S.C. 103 as being unpatentable over Xu et al. (US 2023/0315731 A1) (‘Xu’ herein after) further in view of Salch et al. (US 2013/0086039 A1) (‘Salch’ herein after) further in view of Griffith et al. (US 2019/0050459 A1) (‘Griffith’ herein after).
With respect to claim 1, 13, 18,
Xu discloses a computer-implemented method comprising: receiving by one or more processors a federated query that references a data segment from a third-party data source (figure 3, 5A, paragraphs 78 – 80 teach selecting the federation engine to run the federated query, Xu); determining by the one or more processors, an execution plan for executing the federated query via one or more executable tasks (figure 3, 5A, paragraphs 78, 83 – 85 teach finding query plans using candidate queries, optimizing cost and durations, Xu); predicting, by the one or more processors, a query processing duration for the federated query based on a mapping between the identifier and the execution plan, wherein the query processing duration is based on (i) performance data associated with the logical dataset and stored in association with the identifier or (ii) a presence of the intermediate result set stored in association with the identifier (paragraphs 48 – 49 and 60 teaches a mark join and a query execution module includes a result reuse module, which stores and reuses intermediate results that were created during a previous execution, Xu) and executing, by the one or more processors, the one or more executable tasks based on the query processing duration (figure 3, 5A, paragraphs 78, 84 teach predicting query runtime, paragraphs 90 and 98 teach using a regression model to predict federated query times, Xu).
Xu teaches executing the execution plans but does not teach presenting results to the user.
However, Salch teaches presenting results to the user in a view, figures 5 and 6B, paragraphs 83 – 86 stating that the created view allows the user's query to access the cache object for collecting of results, the process drops the view after providing results of the executed operation in the created view to the user.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Salch to Xu’s method because they are directed to the same field of study of federated queries. Furthermore, in Salch the benefit a federated query engine that advantageously allows for automatic querying of both structured and unstructured data alike from multiple data engines and stores without prior configuration and with optimal performance, thus it provides access to any and all data stores with a single language and access point, paragraphs 24 – 27, Salch.
The combination of Xu and Salch teaches federated query system but does not specify specifically as claimed comprising an identifier that references a logical dataset comprising at least one of (i) a set of operations for generating an intermediate result set for the federated query or (ii) the intermediate result set.
However, Griffith teaches a federated query that comprises an identifier that references a logical dataset comprising at least one of (i) a set of operations for generating an intermediate result set for the federated query or (ii) the intermediate result set in figures 5, 6, 7 and paragraphs 47 – 49 teaching included in a federated query an identifier that is a localized reference for the dataset. Paragraphs 51 – 53 teach using the localized file name and the localized link identifier to access the dataset. Also see paragraphs 56 – 61 teaching an implicit query federation may be created and/or performed in a query via a query editor using a transformed link identifier, whereby a localized link identifier may be presented in a data project user interface within a local namespace associated with the data project. An implicitly federated query may be formed by detecting activation of another user input to form a query operation. Data associated with the activation of this user input may represent a query command, such as an extended FROM clause or command to identify a remote data source from which to extract data associated with a dataset. Performing an implicit federated query may include applying a query operation, such as a multi-table query, via a transformed link identifier against a dataset and one or more other datasets.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Griffith to the combination of Xu and Salch’s method because they are directed to the same field of study of federated queries. Griffith teaches in paragraph 2, the interface among repositories of disparate datasets and computing machine-based entities configured to access datasets, and, more specifically, to a computing and data storage platform configured to provide one or more computerized tools that facilitate development and management of data projects, including implementation of localized link identifiers to perform implicitly federated queries using, in some examples, extended computerized query language syntax to analyze multiple tabular data arrangements in data-driven collaborative projects, thus improving access to large data from various sources.
With respect to claim 2, 14, 19,
Xu as modified discloses the computer-implemented method of claim 1, wherein receiving the federated query comprises: receiving the federated query via an application programming interface (API) gateway of the federated query system communicatively coupled to the third-party data source (figures 5A, 5B paragraph 115 teaches receiving from a client a query that specifies retrieval of data from datasets stored in a plurality of data sources, Xu).
With respect to claim 3, 15, 20,
Xu as modified discloses the computer-implemented method of claim 1, wherein determining the execution plan comprises identifying the execution plan in response to determining that the one or more executable tasks satisfy defined criteria for the data segment (figure 5A, 5B paragraph 115 teaches plurality of federated query plans based on the query. Each federated query plan corresponds to executing the query using a respective data source as a federation engine. Each federated query plan includes a plurality of query operators. Each query operator specifies retrieval of data from datasets stored in a corresponding data source, Xu).
With respect to claim 5,
Xu as modified discloses the computer-implemented method of claim 1, wherein executing the one or more executable tasks comprises configuring one or more processing instructions for the one or more executable tasks based on the query processing duration (figure 3, 5A, 5B paragraphs 100 – 102, Xu).
With respect to claim 6,
Xu as modified discloses the computer-implemented method of claim 1, wherein executing the one or more executable tasks comprises establishing communication with an orchestration engine for the of third-party data source (figure 3, 5A, 5B paragraphs 100 – 102 and 115 – 118, Xu).
With respect to claim 7,
Xu as modified discloses the computer-implemented method of claim 1, wherein executing the one or more executable tasks comprises executing one or more data processing tasks associated with the third-party data source based on the query processing duration (figure 3, 5A, 5B paragraphs 100 – 102 and 115 – 118, Xu and figure 5, paragraph 66, 85 – 87, 89 and 92, Salch).
With respect to claim 8,
Xu as modified discloses the computer-implemented method of claim 1, wherein executing the one or more executable tasks comprises executing one or more machine learning tasks associated with the third-party data source based on the query processing duration (paragraphs 84, 90, 94 – 96, Xu).
With respect to claim 9,
Xu as modified discloses the computer-implemented method of claim 1, further comprising: providing a query response with the query processing duration to a computing entity associated with the federated query to render visual data associated with the query processing duration via a user interface of the computing entity (paragraphs 114 – 116, Xu).
With respect to claim 10,
Xu as modified discloses the computer-implemented method of claim 9, further comprising: in response to receiving a query processing acceptance via the user interface of the computing entity, executing the one or more executable tasks based on the query processing duration (paragraphs 114 – 116, Xu).
With respect to claim 11,
Xu as modified discloses the computer-implemented method of claim 1, further comprising: updating one or more portions of a metadata store for the data segment based on the query processing duration (paragraphs 114 – 116, Xu and figure 5, paragraph 66, 85 – 87, 89 and 92, Salch).
With respect to claim 12,
Xu as modified discloses the computer-implemented method of claim 1, wherein the federated query is a first federated query, the execution plan is a first execution plan, the one or more executable tasks are one or more first executable tasks, and the computer-implemented method further comprises: determining a different query processing duration for a different federated query based on the query processing duration (paragraphs 114 – 116, Xu and figure 5, paragraph 66, 85 – 87, 89 and 92, Salch).
Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20160147888 A1 teaches optimization of query processing using priority queuing techniques may include generating a query vector corresponding to a query, comparing the query vector to historical query vectors to determine similarity, determining an expected processing time and similarity, and inserting the query into a priority ordered queue based on the expected processing time.
US 20150169685 A1 teaches dynamic collaboration during query processing includes determining a load factor for a data source, determining a complexity of the query, adjusting the complexity by the load factor, simplifying the query, forming a query plan and performing the query plan by sending one or more abbreviated queries to the data source and processing the first query elements using the query assistant.
US 10896176 B1 teaches machine learning based query optimization for federated databases.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NAVNEET K GMAHL whose telephone number is 571-272-5636.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, SANJIV SHAH can be reached on . The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/NAVNEET GMAHL/Examiner, Art Unit 2166 Dated: 12/13/2025
/SANJIV SHAH/Supervisory Patent Examiner, Art Unit 2166