Notice of Pre-AIA or AIA Status
The present application 19/270,324, filed on 7/15/2025 (or after March 16, 2013), is being examined under the first inventor to file provisions of the AIA (First Inventor to File).
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 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.
This application is a CON of 18/353,831 filed 07/17/2023 is now US PAT 12373450 18/353,831 has DOM PRO 63/389,443 filed 07/15/2022
DETAILED ACTION
Response to Amendment
Claims 1-20 are pending in this application.
Examiner acknowledge applicant’s amendment filed on 8/7/2026
Drawings
The Drawings filed on 7/15/2025 are acceptable for examination purpose.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 8/6/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner
Priority
Acknowledgment is made of applicant’s claim for domestic priority application
U.S. Provisional Patent application serial number # 63/389,443 filed 07/15/2022
under 35 U.S.C. 119 (e)
Response to Arguments
Applicant's arguments filed 8/7/2026 with respect to claims 1-20 have been fully considered but they are not persuasive, for examiner’s response, see discussion below:
Double Patenting
In view of terminal disclaimer approved on 8/7/2026, the double patent rejection as set forth in the previous office action is hereby withdrawn.
35 USC § 101
In view of applicant’s amendment, remarks, the rejection under 35 USC § 101 as set forth in the previous office action is hereby withdrawn.
a)At page 14-15, claim 1, applicant argues:
the cited prior art of Horowitz, Liu do not teach or suggest “forgoing shuffling or re-shuffling of the plurality of independent events among the cluster computing devices………………events into session………..Liu’s fails to suggest or render obvious random sampling of session……….computation is not directed to sessionization of independent event at all, let alone to a technique suggesting “forgoing shuffling or re-shuffling of the plurality of independent events among the cluster computing devices………………events into session……….” Accordingly, the combination of cited references do not teach or suggest the above amended claim 1.
Examiner’s response:
As to the above argument(a), as best understood by the examiner, the prior art of Horowitz is directed to generating visual queries particularly database analyzed using sample of database (Horowitz: Abstract). The prior art of Horowitz teaches user interface allows user to select sampled data from a portion of the database, further Horowitz teaches sample data from database particularly selecting from the data set element 14, as such typical database schema allows to create tables for example data is organized into rows and columns is integral part of database table(s), while independent events may correspond to sample data from data set(s) because Horowitz supports data visualized for example histogram displays of ranges, and each range, it is further noted that Horowitz specifically teaches dynamic schema setting that including defining, configuring sample selected from database segment representing and identifying data attributes to visualized (0014) (Horowitz: 0007,0013-0014, 0046, fig 1). It is further noted Horowitz teaches identifying portions of the databases, creating sample table on grouping of documents of different sizes querying, analyzing data sets to generate a virtual schema that including generating visualization, displaying of table attributes particularly randomly selecting sampling (Horowitz: 0044, 0060-0061, 0063-0064). As detailed in Horowitz”s fig 8A, Horowitz teaches query execution and visualization of data particularly query builder and execution of the query in the sample data via user interface and distributing sample data to the end user for query result
The prior art of Liu teaches querying time-series events particularly time-series data events including ratios based on time-series events and grouped the same (Liu: Abstract). The prior art of Liu teaches selected representation of time-series events determined a measure of similarity between two time-series events (Liu: 0057). It is however, noted that Horowitz does not teach “dynamically and randomly reconstruct the sample”, although Horowitz teaches processing of dynamically and randomly reconstruct the sample sessions (Horowitz: 0069-0070,0072, fig 5). On the other hand, Liu disclosed “dynamically and randomly reconstruct the sample” (Liu: fig 6, 0053-0054,0058, 0072 – Liu teaches time-series data execting the query, ie., query receiver component executing the data particularly query receiver component element 1608 receive and reconstruct time-series data with respect to selected query range, further algorithm allows to determining measure of similarity between multiple queries representing time-series samples, it is further noted that Liu teaches real-time and/or dynamic time-series data is representative of queries data in reconstruing sample certain portions of time-series data)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention quarrying time-series data particularly generating similarities between time-series data, identifying, computing reconstructing time-series range of Liu et al., into generating virtual schema from the sample data sets of databases and interacting via user interface of Horowitz et al., because both Horowitz, Liu teaches analyzing, visualization and display of data via user interface (Horowitz: fig 3-4; Liu: fig 4-10), both Horowitz, Liu teaches querying databases (Horowitz: 0008 query builder tool used in sampling data sets; Liu: Abstract, fig 1), and they both Horowitz, Liu are from the same field of endeavor. Because both Horowitz, Liu teaches sample data sets querying, analyzing, visualization of data sets via user interface, it would have been obvious to one of the ordinary skill in the art to substitute and/or modify one method for the other particularly reconstructing dynamic time-series query sample of selected query range, while analyzing time-series data samples with respect to defined threshold, thereby executing queries over first, second, third time-series including queries for determining rends in the raw time-series data (Liu: 0007-0008), thus improves overall quality and reliability of utilizing the time-series sample data. The exemplary rationales that may support prima facie conclusion of obviousness includes (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention- -KSR, 550 US at 398.
It is however, noted that Horowitz, Liu do not teach “shuffling or re-shuffling of events”. On the other hand, Vakilian disclosed “shuffling or re-shuffling of events” (Vakilian: 0032-0033,0054-0055, fig 2B-3 – Vakilian teaches multi-pass shuffle performed on the data from multiple sources and forming of reshuffling group(s), while reshuffiling may be considered “butterfly shuffle”, further Vakilian teaches reshuffling, shuffle{ing} independent because each shuffle tracking log record for the blocks of data)
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It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention multi-pass distributed data shuffle of Vakilian et al., into users of Horowitz, Liu because that would have allowed users of Horowitz, Liu selecting executing shuffle or reshuffle operation on data sets from multiple data sources and/or collection of data events, mapped, and indexed from multiple data sources, and divides shuffle operations into multiple passes such that it reduces and/or optimizes computing resources overheads (Vakilian: 0020-0021, 0029), thus improves overall quality and efficiency of the system. The exemplary rationales that may support prima facie conclusion of obviousness includes (F) Known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art-KSR, 550 US at 398.
In view of above remarks, examiner applies above arguments to claim 13, and claims 2-12,14-20 depend from claim 1,13
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.
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 1-3,8-15,20, is/are rejected under 35 U.S.C. 103 as being unpatentable over Horowitz et al., (hereafter Horowitz), US Pub. No. 2017/0286532 published Oct, 2017 Liu et al., (hereafter Liu), US Pub. No. 2012/0246169 published Sep, 2012 in view of Vakilian et al., (hereafter Vakilian), US Pub. No. 2021/0132841 published May 2021
As to Claim 1,13. Horowitz teaches a system which including “ a computer-implemented method comprising:(Horowitz: fig 1, fig 6, 0120-0121 – Horowitz teaches both hardware and software including input/output)
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determining a table of independent events, a plurality of data segments comprising the table of independent events being distributed across a cluster of computing devices” (Horowitz: 0007,0013-0014, 0046, fig 1 – Horowitz teaches user interface allows user to select sampled data from a portion of the database. Prior art of Horowitz teaches sample data from database particularly selecting from the data set element 14, as such typical database schema allows to create tables for example data is organized into rows and columns is integral part of database table(s), while independent events may correspond to sample data from data set(s) because Horowitz supports data visualized for example histogram displays of ranges, and each range, it is further noted that Horowitz specifically teaches dynamic schema setting that including defining, configuring sample selected from database segment representing and identifying data attributes to visualized (0014);
determining a query, the query including criteria for grouping a plurality of independent events from the table of independent events into a session and a parameter including a size limit on a sample of sessions from the table of independent events” (Horowitz: 0044, 0060-0061, 0063-0064 – Horowitz teaches identifying portions of the databases, creating sample table on grouping of documents of different sizes querying, analyzing data sets to generate a virtual schema that including generating visualization, displaying of table attributes particularly randomly selecting sampling);
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“distributing the query in parallel to the cluster of computing devices for executing the query against the table of independent events” (Horowitz: 0086,0106, fig 8A – Horowitz teaches query execution and visualization of data particularly query builder and execution of the query in the sample data via user interface and distributing sample data to the end user for query result);
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“at the time of query execution on each computing device in the cluster of computing devices, processing, in real time, the plurality of data segments comprising the table of independent events to dynamically and the sample of sessions using a random sampling method, the sample of sessions matching the criteria and being within the size limit in the query, a sampling rate of the random sampling method being a function of the size limit and the plurality of data segments comprising the table of independent events” (Horowitz: 0008,0015-0016,0019,0060-0061, fig1- 2, 0069-0070,0072, fig 5 – Horowitz teaches generating query via user interface, displayed as “query bar” allows to select “sample data”, particularly sample data specifying threshold limit and/or size of the data, further Horowitz teaches user interface allows to select[ing] sample range to create and display query in the query builder bar, specifying a size limit on sample may correspond to selection of sample range(s) of specific event(s), it is noted that visualize plurality of attributes and respective data within data sampled from the subset(s) as detailed in 0019. Prior art of Horowitz teaches defining sample data with respect to fine turned threshold that represents sample accurately from the data set and confidence interval may corresponds to parameter specifying size limit. The prior art of Horowitz teaches “MONGODB” database supports he “sample” stage for example syntax: {$sample: [size:<positive ingteger N>}} allows to specify sample size, therefore, specifying size limit(s) integral part of Horowtz’s teaching; “that are locally stored at that computing device, (Horowitz: fig 6,0010 – Horowtz teaches computing system including memory storing data particularly sampling session events); “cluster of computing devices to group the plurality of independent events into session” (Horowitz: fig 3-4A, 0077-0079 – Horowitz teaches plurality of time-series data collection for further analysis, particularly collection are indexes and user interface enable filtering process of sampling in response to selection via user interface with respect to events of the session as detailed in fig 3,4A)
Horowitz teaches selection of sample size from the query bar(s) and displayed sample in the bar graph generates a query for selecting data items, in this case documents associated with the visual display, further visualizing elements of the virtual schema (element 28) creates views, navigate query. The user interface may allow user to select not only filters of desired query, but also specific sample data subset to limit the criteria in selecting “portions: in defined confidence threshold in order to generate accurate representation of the data
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; and
“at the time of query execution on each computing device in the cluster of computing devices, analyzing, in real time, the sample of sessions to generate a result” (Horowitz: 0020-0021,0070-0071 – Horowitz teaches generation, execution of query and analyzing database for selected sampling, and the result of the query results as visualization of the data).
It is however, noted that Horowitz does not teach “dynamically and randomly reconstruct the sample”, although Horowitz teaches processing of dynamically and randomly reconstruct the sample sessions (Horowitz: 0069-0070,0072, fig 5). On the other hand, Liu disclosed “dynamically and randomly reconstruct the sample” (Liu: fig 6, 0053-0054,0058, 0072 – Liu teaches time-series data executing the query, ie., query receiver component executing the data particularly query receiver component element 1608 receive and reconstruct time-series data with respect to selected query range, further algorithm allows to determining measure of similarity between multiple queries representing time-series samples, it is further noted that Liu teaches real-time and/or dynamic time-series data is representative of queries data in reconstruing sample certain portions of time-series data)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention quarrying time-series data particularly generating similarities between time-series data, identifying, computing reconstructing time-series range of Liu et al., into generating virtual schema from the sample data sets of databases and interacting via user interface of Horowitz et al., because both Horowitz, Liu teaches analyzing, visualization and display of data via user interface (Horowitz: fig 3-4; Liu: fig 4-10), both Horowitz, Liu teaches querying databases (Horowitz: 0008 query builder tool used in sampling data sets; Liu: Abstract, fig 1), and they both Horowitz, Liu are from the same field of endeavor. Because both Horowitz, Liu teaches sample data sets querying, analyzing, visualization of data sets via user interface, it would have been obvious to one of the ordinary skill in the art to substitute and/or modify one method for the other particularly reconstructing dynamic time-series query sample of selected query range, while analyzing time-series data samples with respect to defined threshold, thereby executing queries over first, second, third time-series including queries for determining rends in the raw time-series data (Liu: 0007-0008), thus improves overall quality and reliability of utilizing the time-series sample data.
It is however, noted that Horowitz, Liu do not teach “shuffling or re-shuffling of events”. On the other hand, Vakilian disclosed “shuffling or re-shuffling of events” (Vakilian: 0032-0033,0054-0055, fig 2B-3 – Vakilian teaches multi-pass shuffle performed on the data from multiple sources and forming of reshuffling group(s), while reshuffiling may be considered “butterfly shuffle”, further Vakilian teaches reshuffling, shuffle{ing} independent because each shuffle tracking log record for the blocks of data)
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It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention multi-pass distributed data shuffle of Vakilian et al., into users of Horowitz, Liu because that would have allowed users of Horowitz, Liu selecting executing shuffle or reshuffle operation on data sets from multiple data sources and/or collection of data events, mapped, and indexed from multiple data sources, and divides shuffle operations into multiple passes such that it reduces and/or optimizes computing resources overheads (Vakilian: 0020-0021, 0029), thus improves overall quality and efficiency of the system
As to Claim 2,14, the combination of Horowitz, Liu, Vakilian disclosed “at the time of query execution on each computing device in the cluster of computing devices, processing the table of independent events to aggregate the plurality of independent events into a time-ordered series of independent events and reconstruct the sample of sessions based on the time-ordered series of independent events” (Horowitz: fig 3, fig 4A,0046-0047,0057, 0084 – Horowitz teaches samples subsets from database supporting probabilistic model or virtual schema and the sample data displayed with attribute, values in a “time bar graph”).
As to claim Claim 3,15, the combination of Horowitz, Liu, Vakilian disclosed “performing funnel analysis using the result” (Horowitz: 0067-0069,0082,0086 – funnel analysis is structured in a visualizing graphical display using virtual schema)
Claim 8,20, the combination of Horowitz, Liu, Vakilian disclosed “wherein the sample of sessions are representative of a whole set of possible sessions from the table of independent events” (Horowitz: 0077-0079)
.
As to claim 9, the combination of Horowitz, Liu, Vakilian disclosed “wherein the criteria includes at least one from a group of a timeframe, a set of users, and a geographical location” (Horowitz: 0104).
As to claim 10, the combination of Horowitz, Liu, Vakilian disclosed “wherein each session in the sample of sessions includes a sequence of independent events occurring within a time period and mapped to a unique identifier” (Horowitz: 0012-0013,0068)
As to Claim 11, the combination of Horowitz, Liu, Vakilian disclosed “wherein the unique identifier includes at least one from a group of a session identifier, a client device identifier, and a user identifier” (Horowitz: fig 3-4A-B,0091-0094).
As to Claim 12, the combination of Horowitz, Liu, Vakilian disclosed “wherein the table of independent events is loaded with data retrieved from one of a streaming data source and a batch data source” (Horowitz: 0077-0079)
Claims 4-7,16-19, is/are rejected under 35 U.S.C. 103 as being unpatentable over Horowitz et al., (hereafter Horowitz), US Pub. No. 2017/0286532 published Oct, 2017 Liu et al., (hereafter Liu), US Pub. No. 2012/0246169 published Sep, 2012 Vakilian et al., (hereafter Vakilian), US Pub. No. 2021/0132841 published May 2021 in view of Bhosale et al., (hereafter Bhosale), US Pub. No. 2022/0318386 filed Mar, 2021,
As to Claim 4,16, the combination of Horowitz, Liu disclosed “transforming the sample of sessions into a data structure (Horowitz: Abstract, fig 1, fig 3), the; and rendering a visualization based on the data structure” (Horowitz: fig 0011,0018, fig 1, fig 5).
It is however, noted that both Horowitz, Liu do not disclose “data structure being a multi- rooted tree”. On the other hand, Bhosale disclosed data structure being a multi- rooted tree” (Bhosale: Abstract, fig 1, fig 2, element 213 tree nodes, fig 3)
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It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention generating visual tree structure of data analysis report particularly visualizing and navigating tree data structure of Bhosale et al., into users of Horowitz, Liu, Vakilian because that would have allowed users of Horowitz, Liu, Vakilian to data visualization, navigating tree structure generate and displayed on GUI to view data corresponding to respective nodes and provide the report items (Bhosale: 0014-0015)
As to Claim 5,17, the combination of Horowitz, Liu, Vakilian ,Bhosale disclosed “receiving a user interaction in association with the visualization” (Horowitz: fig 8-9); and
“determining the query based on the user interaction” (Horowitz: 0013-0016).
As to Claim 6,18, the combination of Horowitz, Liu, Vakilian , Bhosale disclosed “wherein the user interaction includes a selection of a graphical element in the visualization, the graphical element corresponding to a subsection of the data structure” (Horowitz: fig 8-9,0111-0113).
As to Claim 7,19, the combination of Horowitz, Liu, Vakilian , Bhosale disclosed “wherein the visualization is at least one selected from a group of a flame graph, a flame chart, a funnel analysis chart, a process flow diagram, an icicle chart, and a sunburst layout” (Horowitz: fig 7H, 7J, 8-9).
Conclusion
The prior art made of record
a. US Pub. No. 2017/0286532
b. US Pub. No. 2012/0246169
c. US Pub. No. 2022/0318386
d. US Pub. No. 2021/0132841
Examiner's Note: Examiner has cited particular columns and line numbers in the references applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings of the art and are applied to specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant in preparing responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
SEE MPEP 2141.02 [R-5] VI. PRIOR ART MUST BE CONSIDERED IN ITS ENTIRETY, INCLUDING DISCLOSURES THAT TEACH AWAY FROM THE CLAIMS: A prior art reference must be considered in its entirety, i.e., as a whole, including portions that would lead away from the claimed invention. W.L. Gore & Associates, Inc. v. Garlock, Inc., 721 F.2d 1540, 220 USPQ 303 (Fed. Cir. 1983), cert. denied, 469 U.S. 851 (1984) In re Fulton, 391 F.3d 1195, 1201,73 USPQ2d 1141, 1146 (Fed. Cir. 2004). >See also MPEP §2123.
In the case of amending the Claimed invention, Applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for proper interpretation and also to verify and ascertain the metes and bounds of the claimed invention.
The prior art made of record, listed on form PTO-892, and not relied upon, if any, is considered pertinent to applicant's disclosure
Authorization for Internet Communications
The examiner encourages Applicant to submit an authorization to communicate with the examiner via the Internet by making the following statement (from MPEP 502.03):
“Recognizing that Internet communications are not secure, I hereby authorize the USPTO to communicate with the undersigned and practitioners in accordance with 37 CFR 1.33 and 37 CFR 1.34 concerning any subject matter of this application by video conferencing, instant messaging, or electronic mail. I understand that a copy of these communications will be made of record in the application file.”
Please note that the above statement can only be submitted via Central Fax (not Examiner's Fax), Regular postal mail, or EFS Web using PTO/SB/439.
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 Srirama Channavajjala whose telephone number is 571-272-4108. The examiner can normally be reached on Monday-Friday from 8:00 AM to 5:30 PM Eastern Time.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Gorney, Boris, can be reached on (571) 270- 5626. The fax phone numbers for the organization where the application or proceeding is assigned is 571-273-8300 Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free)
/Srirama Channavajjala/Primary Examiner, Art Unit 2154
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