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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 February 04, 2026 has been entered.
Response to amendment
Claims 1-4, 7-8, 11-14, 17-18 and 21 have been amended. Claims 6, 16 and 22 have been cancelled. New claim 23 has been added. As a result, 1-5, 7-15, 17-21 and 23 are pending.
Applicant's amendment to the claims and applicant’s arguments with respect to the rejection of the claims under 35 U.S.C. § 103 has been fully considered. As a result, the rejection has been withdrawn.
This action is NON-FINAL.
Claims rejection 35 U.S.C. 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 of this title, 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.
Claims 1-3, 7-9 and 11-13 , 17-19, 21 and 23 are rejected under AIA 35 U.S.C. 103 as being unpatentable over Harvey et al. (US 20090259518 A1) further in view of Merriman at el. (US 20180314750 A1) further in view of Couckuyt et al. (US 20170097942 A1).
Regarding claims 1 and 11, Harvey discloses a method comprising:
monitoring the first physical or virtual machine according to a first overflow condition of the first physical or virtual machine, the first overflow condition indicative of a first undesirable query response time for the first physical or virtual machine (see Harvey paragraph [0082], A monitoring service module 338 can be configured to provide visibility into the application state, such as by displaying logged-in users or showing currently running application tasks (e.g., queries, data uploads, etc.). This module 338 may also be configured to collect and make available performance statistics (e.g., response times, queue length, etc.), generate recommendations to rebalance shards or if to add additional components to improve system 302 performance);
responsive to determining that data stored within the first physical or virtual machine meets the first overflow condition that is indicative of the first undesirable query response time for the first physical or virtual machine (see Harvey paragraph [0082], A monitoring service module 338 can be configured to provide visibility into the application state, such as by displaying logged-in users or showing currently running application tasks (e.g., queries, data uploads, etc.). This module 338 may also be configured to collect and make available performance statistics (e.g., response times, queue length, etc.), generate recommendations to rebalance shards or if to add additional components to improve system 302 performance); adding a new database shard to a second physical or virtual machine …, wherein data within the second physical or virtual machine does not meet a second overflow condition when the new database shard is added to the second physical or virtual machine (see Harvey paragraph [0096], The amount of data stored on a single shard 402-408 can be determined by the smaller of the following two factors: the largest cost effective disk storage size, and the largest amount of data still allowing a desired query response time (e.g., five seconds or less); see Harvey paragraph [0098],more shards 402-408 may be needed to sustain a desired data processing response time. After a new shard 402-408 is added to the system 302, existing data can be rebalanced between the shards 402-408 with a hash function, taking into account any new shards 402-408 now available. A similar technique may be used to constantly monitor performance of the shards 402-408 and rebalance data between/among them according to the actual average response time achieved over a period of time, for example. This can be achieved by accounting for shard 402-408 capacity, which would be limited by the shard 402-408 physical capacity, but could be comparatively smaller for active shards 402-408 and comparatively larger for less active shards 402-408),
wherein the second overflow condition is indicative of a second undesirable query response time for the second physical or virtual machine, wherein the new database shard is part of the first set of one or more database shards storing … data… (see Harvey paragraph [0098],more shards 402-408 may be needed to sustain a desired data processing response time. After a new shard 402-408 is added to the system 302, existing data can be rebalanced between the shards 402-408 with a hash function, taking into account any new shards 402-408 now available. A similar technique may be used to constantly monitor performance of the shards 402-408 and rebalance data between/among them according to the actual average response time achieved over a period of time, for example. This can be achieved by accounting for shard 402-408 capacity, which would be limited by the shard 402-408 physical capacity, but could be comparatively smaller for active shards 402-408 and comparatively larger for less active shards 402-408)), and
Merriman expressly discloses storing, in a first database shard on a first physical or virtual machine, geolocated data corresponding to a geographic region, the first database shard being part of a first set of one or more database shards storing geolocated data corresponding to the geographic region (see Merriman paragraph [0007], the system can be configured to use zones to ensure that the most relevant data reside on shards that are geographically closest to the application servers. For example, the system can be configure to designate shards to specific zones that are associated with a geographic location. Those shards may be stored in data centers that are geographically closest to the application servers).
It would have been obvious to a person of ordinary skill in art before the effective filing date of the claimed invention to incorporate the teaching of Merriman into the method of Harvey to have storing, in a first database shard of a first physical or virtual machine of a shard database, geolocated data corresponding to a geographic region. Here, combining Merriman with Harvey, which are both related to location based query processing improves Harvey, by providing system that provides scalability of online services for consumption by global audiences, across distributed geographic regions, applications and clients (see Merriman paragraph [0002]).
Couckuyt expressly discloses wherein the second physical or virtual machine is different than the first physical or virtual machine (see Couckuyt paragraph [0016], provide efficient solutions for storing data objects (such as geographical data objects) in a plurality of databases (or shards) that make up a distributed database system. It should be understood that “shard” and “database” may be used interchangeably throughout the present disclosure. Shards have limits in the amount of storage available (for example, 1 terabyte (TB), 100 gigabytes (GB), etc.). When storing geographical objects that describe geographical data throughout the world, the amount of data may greatly exceed the storage limitations of a single shard. As such, many shards may be included in a distributed database system to handle the volume of data. It is desired to efficiently partition the data to be stored to allow for quicker storage and location of data).
It would have been obvious to a person of ordinary skill in art before the effective filing date of the claimed invention to incorporate the teaching of Couckuyt into the method of Harvey to have wherein the second physical or virtual machine is different than the first physical or virtual machine. Here, combining Couckuyt with Harvey, which are both related to location based query processing improves Harvey, by providing system that provides scalability of online services for consumption by global audiences, across distributed geographic regions, applications and clients (see Couckuyt paragraph [0002]).
Regarding claims 2 and 12, Harvey discloses wherein the first database shard stores an amount of data according to the first overflow condition (see Harvey paragraph [0096], The amount of data stored on a single shard 402-408 can be determined by the smaller of the following two factors: the largest cost effective disk storage size, and the largest amount of data still allowing a desired query response time (e.g., five seconds or less)).
Regarding claims 3 and 13, Harvey discloses wherein monitoring the first database shard includes: evaluating data… stored within the physical or virtual machine according to the first overflow condition; and determining, based on the evaluation, that data stored within the first physical or virtual machines meets the overflow condition (see Harvey paragraph [0082], A monitoring service module 338 can be configured to provide visibility into the application state, such as by displaying logged-in users or showing currently running application tasks (e.g., queries, data uploads, etc.). This module 338 may also be configured to collect and make available performance statistics (e.g., response times, queue length, etc.), generate recommendations to rebalance shards or if to add additional components to improve system 302 performance).
Merriman expressly discloses monitoring shards including geolocated data corresponding to the geographic region (see Merriman paragraph [0007], the system can be configured to use zones to ensure that the most relevant data reside on shards that are geographically closest to the application servers. For example, the system can be configure to designate shards to specific zones that are associated with a geographic location. Those shards may be stored in data centers that are geographically closest to the application server).
It would have been obvious to a person of ordinary skill in art before the effective filing date of the claimed invention to incorporate the teaching of Merriman into the method of Harvey to have storing, in a first database shard of a first physical or virtual machine of a shard database, geolocated data corresponding to a geographic region. Here, combining Merriman with Harvey, which are both related to location based query processing improves Harvey, by providing system that provides scalability of online services for consumption by global audiences, across distributed geographic regions, applications and clients (see Merriman paragraph [0002]).
Regarding claims 7 and 17, Harvey discloses monitoring the second physical or virtual machine according to the second overflow condition of the second physical or virtual machine, (see Harvey paragraph [0082], A monitoring service module 338 can be configured to provide visibility into the application state, such as by displaying logged-in users or showing currently running application tasks (e.g., queries, data uploads, etc.). This module 338 may also be configured to collect and make available performance statistics (e.g., response times, queue length, etc.), generate recommendations to rebalance shards or if to add additional components to improve system 302 performance).
Regarding claims 8 and 18, Harvey discloses, wherein the new database shard of the first set is stored on the second physical or virtual machine such that a second set of database shards storing… data… is evenly distributed across physical or virtual machines of the shard database, wherein the second set includes the first set of database shards (See Harvey Paragraph [0098], by accounting for shard 402-408 capacity, which would be limited by the shard 402-408 physical capacity, but could be comparatively smaller for active shards 402-408 and comparatively larger for less active shards 402-408. As a result of monitoring, the capacity of each shard 402-408 can be changed over time in response to its activity, thus distributing the data processing load between shards 402-408 more evenly. Such performance analyses, load balancing, tuning and optimization can be configured to be automated within the advertising measurement system 302 to provide the system 302 with a self-balancing quality).
Merriman expressly discloses geolocated data corresponding to the geographic region (see Merriman paragraph [0007], the system can be configured to use zones to ensure that the most relevant data reside on shards that are geographically closest to the application servers. For example, the system can be configure to designate shards to specific zones that are associated with a geographic location. Those shards may be stored in data centers that are geographically closest to the application server).
It would have been obvious to a person of ordinary skill in art before the effective filing date of the claimed invention to incorporate the teaching of Merriman into the method of Harvey to have storing, in a first database shard of a first physical or virtual machine of a shard database, geolocated data corresponding to a geographic region. Here, combining Merriman with Harvey, which are both related to location based query processing improves Harvey, by providing system that provides scalability of online services for consumption by global audiences, across distributed geographic regions, applications and clients (see Merriman paragraph [0002]).
Regarding claims 9 and 19, Merriman discloses, wherein the geolocated data corresponding to the geographic region includes one or more virtual elements associated with locations within the geographic region (see Merriman paragraph [0007], , the system can be configured to use zones to ensure that the most relevant data reside on shards that are geographically closest to the application servers. For example, the system can be configure to designate shards to specific zones that are associated with a geographic location. Those shards may be stored in data centers that are geographically closest to the application servers).
It would have been obvious to a person of ordinary skill in art before the effective filing date of the claimed invention to incorporate the teaching of Merriman into the method of Harvey wherein the geolocated data corresponding to the geographic region includes one or more virtual elements associated with locations within the geographic region. Here, combining Merriman with Harvey, which are both related to location based query processing improves Harvey, by providing system that provides scalability of online services for consumption by global audiences, across distributed geographic regions, applications and clients (see Merriman paragraph [0002]).
Regarding claim 21 Couckuyt expressly discloses wherein the overflow condition specifies a limit on the amount of data stored on the first physical or virtual machine, the number of items stored on the first physical or virtual, or a query response time of queries on the first physical or virtual machine (see Couckuyt paragraph [0016], provide efficient solutions for storing data objects (such as geographical data objects) in a plurality of databases (or shards) that make up a distributed database system. It should be understood that “shard” and “database” may be used interchangeably throughout the present disclosure. Shards have limits in the amount of storage available (for example, 1 terabyte (TB), 100 gigabytes (GB), etc.). When storing geographical objects that describe geographical data throughout the world, the amount of data may greatly exceed the storage limitations of a single shard. As such, many shards may be included in a distributed database system to handle the volume of data. It is desired to efficiently partition the data to be stored to allow for quicker storage and location of data).
It would have been obvious to a person of ordinary skill in art before the effective filing date of the claimed invention to incorporate the teaching of Couckuyt into the method of Harvey to have the overflow condition specifies a limit on the amount of data stored on the first physical or virtual machine. Here, combining Couckuyt with Harvey, which are both related to location based query processing improves Harvey, by providing efficient association of data objects to the various databases they may be stored on by distributing the geographical objects across a distributed database comprising multiple database devices capable of handling data growth (see Couckuyt paragraph [0002]).
Regarding claim 23, Harvey discloses wherein the first workflow condition, queries querying the first database shard and received by the first physical or virtual machine have query response times less than the first undesirable query response time (See Harvey Paragraph [0096], Every shard 402-408 can be configured to maintain the same data structure or data tables while storing different data. The amount of data stored on a single shard 402-408 can be determined by the smaller of the following two factors: the largest cost effective disk storage size, and the largest amount of data still allowing a desired query response time (e.g., five seconds or less);
due to the second overflow condition, queries querying the new database shard and received by the second physical or virtual machine have query response times less than the second undesirable query response time (See Harvey Paragraph [0096], Every shard 402-408 can be configured to maintain the same data structure or data tables while storing different data. The amount of data stored on a single shard 402-408 can be determined by the smaller of the following two factors: the largest cost effective disk storage size, and the largest amount of data still allowing a desired query response time (e.g., five seconds or less; See Harvey Paragraph [0098], As the amount of information within the advertising measurement system 302 grows, more shards 402-408 may be needed to sustain a desired data processing response time. After a new shard 402-408 is added to the system 302, existing data can be rebalanced between the shards 402-408 with a hash function, taking into account any new shards 402-408 now available. A similar technique may be used to constantly monitor performance of the shards 402-408 and rebalance data between/among them according to the actual average response time achieved over a period of time, for example).
Claims 10 and 20 are rejected under AIA 35 U.S.C. 103 as being unpatentable over Harvey et al. (US 20090259518 A1) further in view of Merriman at el. (US 2018/0314750 A1) further in view of Couckuyt et al. (US 20170097942 A1) in view Zorzella et al. (US 9,128,789 B1).
Regarding claims 10 and 20, Zorzella expressly discloses wherein the one or more virtual elements are associated with a virtual world of a parallel-reality game application on a client device (see Zorzella col. 3, lines 25-35 the decorators can be used to execute cross-cutting actions associated with a location-based parallel reality game any time a client device used by a player of the parallel reality game invokes an RPC method at a game server implementing the location-based parallel reality game; see Zorzella col. 4, lines 58-67, the virtual world 210 can include a geography that parallels the geography of the real world 200. In particular, a range of coordinates defining a geographic area or space in the real world 200 is mapped to a corresponding range of coordinates defining a virtual space in the virtual world 210. The range of coordinates in the real world 200 can be associated with a town, neighborhood, city, campus, locale, a country, continent, the entire globe, or other geographic area. Each geographic coordinate in the range of geographic coordinates in the real world 200 is mapped to a corresponding coordinate in a virtual space in the virtual world 210).
It would have been obvious to a person of ordinary skill in art before the effective filing date of the claimed invention to incorporate the teaching of Zorzella into the method of Harvey to have a virtual world of a parallel-reality game application on the client device. Here, combining Zorzella with Harvey, which are both related to location based query processing improves Harvey, by providing system that provides for the interaction of a plurality of players in a virtual world having a geography that parallels the real world (see Zorzella col.4, lines 45-50).
Claims 4-5 and 14-15 are rejected under AIA 35 U.S.C. 103 as being unpatentable over Harvey et al. (US 20090259518 A1) further in view of Merriman at el. (US 20180314750 A1) in view of Couckuyt et al. (US 20170097942 A1) further in view of Annamalai (US 20170013058 A1).
Regarding claims 4 and 14 Annamalai expressly based on the monitoring, incrementing a shard count value representing the total number of database shards being used to store geolocated data corresponding to the geographic region (see Annamalai paragraph [0052], performs various shard related tasks, including assigning shards to servers, defining a sync replica set for a shard, and optionally facilitate assigning follower servers to the shard. The shard management server 440 can assign shards to servers based on various factors, e.g., a number of shards a server can host, a placement policy (number of replicas, placement across region/datacenter/cluster/rack, etc.), a failover policy, a load balancing policy, and other performance requirements of an application, all of which can be defined in a replication policy of the application).
It would have been obvious to a person of ordinary skill in art before the effective filing date of the claimed invention to incorporate the teaching of Annamalai into the method of Harvey to have a shard count value representing the total number of database shards being used. Here, combining Annamalai with Harvey, which are both related to data processing improves Harvey, by providing a shard management server that can also ensure that a quorum of the sync replica set is closer to the client, e.g., in the same datacenter or region the client is located at, in order to minimize the write latency for the client. (see Annamalai paragraph [0022]).
Regarding claims 5 and 15 Annamalai expressly discloses, wherein database shards of the first set are identified based on the shard count value (see Annamalai paragraph [0052], performs various shard related tasks, including assigning shards to servers, defining a sync replica set for a shard, and optionally facilitate assigning follower servers to the shard. The shard management server 440 can assign shards to servers based on various factors, e.g., a number of shards a server can host, a placement policy (number of replicas, placement across region/datacenter/cluster/rack, etc.), a failover policy, a load balancing policy, and other performance requirements of an application, all of which can be defined in a replication policy of the application).
It would have been obvious to a person of ordinary skill in art before the effective filing date of the claimed invention to incorporate the teaching of Annamalai into the method of Harvey to have a shard count value representing the total number of database shards being used. Here, combining Annamalai with Harvey, which are both related to data processing improves Harvey, by providing a shard management server that can also ensure that a quorum of the sync replica set is closer to the client, e.g., in the same datacenter or region the client is located at, in order to minimize the write latency for the client (see Annamalai paragraph [0022]).
Remarks
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Harvey et al. (US 20100161492 A1) discloses query response time depends on data size. Typical sizes of data sets used in media analysis operations are large and hence query response time is high. However, in the present invention, the fact that the data is partitioned into shards makes the shard data size, not the overall database size, a determining factor affecting the query response time. Performance improvement in the present invention is gained by processing several smaller portions of data in parallel, on multiple database servers/shard… The shard data size should be small enough to sustain a suitable query response time, which in turn may determine the number of shards needed, if and to the degree that the data storage is sufficient.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DINKU W GEBRESENBET whose telephone number is (571)270-1636. The examiner can normally be reached between 8:00AM-5:00PM.
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, Amy Ng can be reached on 571- 270-1698. 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.
/DINKU W GEBRESENBET/Primary Examiner, Art Unit 2164