DETAILED ACTION
This communication is in response to the Applicant Arguments/Remarks dated 7/11/2025. Claims 1-26 are pending in the application.
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 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.
Response to Arguments
Applicants’ arguments filed 7/11/2025 has been fully considered.
Regarding the arguments on pages 9-10 of the Remarks that the cited references failed to teach "applying the database query to a parent virtual data set represented by the root node to determine, based on registry information for the parent virtual data set, a plurality of child nodes of the static hierarchy that each represents a child virtual data set that represents a respective plurality of fixed size partitions in the partitioned data set, wherein each fixed size partition and corresponding virtual data sets are assigned to a host, wherein in the static hierarchy, the registry information for the parent virtual data set contains a same set of columns as the child virtual data sets as amended”, examiner respectfully disagrees.
Specification, para. 28-29 teach: the registry information contains all of the metadata that the query engine needs to compile a query and generate a distributed query plan. The distributed query plan defines the sub-queries that are sent to child data sets during query execution to return data needed by the overall query execution plan.
The Smith reference is no longer applied in this current Office action since the limitation “the registry information ….data sets…” had been canceled. Please see the new cited columns and lines below.
Shmuylovich has been applied to teach static and/or fixed partitions at col. 2:46-52: conventional partitions may be based, for example, on an exemplary or typical data set size, and subdivide the data set accordingly into a particular number of partitions. Configurations herein substantially overcome configuration issues associated with fixed or static number of partitions by performing hierarchical, or tree-based, partitioning; col. 5:11-15: substantially overcome configuration issues associated with a fixed or static number of partitions by performing hierarchical, or tree-based partitioning that groups related updates together according to relations in the hierarchy to minimize multiple fetches of affected database elements
Bhattacharjee et al. teaches at para. 1411: fixed size partitions such that the partitions can be processed as units. Fig. 64, a worker node may, for records of a given group, fill a first partition of a partition group with records until the first partition meets the fixed size, then fill a second partition of the group with records, etc. This "time slicing" of records into partitions of a group can, for example, prevent partitions from being unbounded in size; para. 891: intake the buckets previously identified as potentially containing relevant information (e.g., based on metadata of the buckets/registry information); para. 239: examples of a data source include, without limitation, data files, directories of files, data sent over a network, event logs, registries, etc. The combination of references does teach the argued limitations.
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) 1-24, 26 are rejected under 35 U.S.C. 103 as being unpatentable over Bhattacharjee et al. (20200065303) in view of Shmuylovich et al. (US 7899780).
Specification, para. 28-29 teach: the registry information contains all of the metadata that the query engine needs to compile a query and generate a distributed query plan. The distributed query plan defines the sub-queries that are sent to child data sets during query execution to return data needed by the overall query execution plan.
As per claims 1, 9, 17, Bhattacharjee et al. teaches
a database management system (DBMS)-implemented method of querying a partitioned data set in a DBMS that is organized in a data structure in a form of a static hierarchy of nodes (fig. 4: RDBMS; fig. 19: receive search query, define search process to worker nodes, aggregate partial search results to generate search results; para. 195: stores data in a similar format and/or hierarchy; para. 465: a "proactive monitoring tree" that enables a user to easily view and understand relationships among various factors that affect the performance of a hierarchically structured computing system. This proactive monitoring tree enables a user to easily navigate the hierarchy by selectively expanding nodes representing various entities);
wherein the static hierarchy includes a root node that represents all fixed size partitions in the partitioned data set that are stored in the DBMS, the method comprising: (para. 203: stores data in a similar format and/or hierarchy, data of the external data stores and raw data of the internal data stores (or external data stores that store data in a similar format or hierarchy as the internal data stores); para. 394-395: objects in data models can be arranged hierarchically in parent/child relationships. Each child object represents a subset of the dataset covered by its parent object. The top-level objects in data models are collectively referred to as "root objects"; para. 1411: fixed size partitions such that the partitions can be processed as units. Fig. 64, a worker node may, for records of a given group, fill a first partition of a partition group with records until the first partition meets the fixed size, then fill a second partition of the group with records, etc. This "time slicing" of records into partitions of a group can, for example, prevent partitions from being unbounded in size);
receiving, at the root node of the static hierarchy of nodes, a database query for data in the partitioned data set (para. 392-394: a data model is a hierarchically structured search time mapping of semantic knowledge about one or more datasets. Objects in data models can be arranged hierarchically in parent/child relationships. Each child object represents a subset of the dataset covered by its parent object. The top-level objects in data models are collectively referred to as "root objects"; figs. 51-53: receive and process a search query, parse query, …determine size and quantity of partitions…distribute sub-queries, communicate results);
applying the database query to a parent virtual data set represented by the root node to determine, based on registry information in the parent virtual data set (fig. 47: common storage metadata/registry; para. 239: data registries; para. 461-463, 485: the search head in conjunction with the search process master and query coordinator(s) can apply a query to any one or more of the distributed dataset sources; para. 899: where the processing phase represents a top-node of a branch of the DAG being executed, the information located during the processing phase may be transmitted to the query coordinator, where any additional nodes of the DAG are completed, and search results are transmitted to a data destination; para. 1411: fixed size partitions),
a plurality of child nodes of the static hierarchy that each represents a child virtual data set that represents a respective plurality of fixed size partitions in the partitioned data set (para. 463-465: the virtual machine monitoring application stores large volumes of minimally processed machine data… performance metrics obtained through an application programming interface (API) provided as part of the vSphere Hypervisor™ system; a "proactive monitoring tree" that enables a user to easily view and understand relationships among various factors that affect the performance of a hierarchically structured computing system. This proactive monitoring tree enables a user to easily navigate the hierarchy by selectively expanding nodes representing various entities; para. 564, 684: multiple partitions of a node (or different nodes) can be assigned to communicate data to a particular destination. Furthermore, the nodes can be instructed to transform the data so that the destination can properly understand and store the data; para. 697: a partition can refer to smaller sets of data, such as when data is partitioned (or split up) into smaller parts. A partition can refer to a group of data, data entries, events, or records and computer-executable instructions that indicate how the group of data is to be processed by a processor or worker node; para. 732, 842-844: the query coordinator receives a query, identifies the dataset sources, including the indexers as one dataset source, and can also identify a second dataset source, such as an external data source, a common storage, an ingested data buffer, query acceleration data store; para. 1411: fixed size partitions such that the partitions can be processed as units. Fig. 64, a worker node may, for records of a given group, fill a first partition of a partition group with records until the first partition meets the fixed size, then fill a second partition of the group with records, etc. This "time slicing" of records into partitions of a group can, for example, prevent partitions from being unbounded in size);
wherein each fixed size partition and corresponding virtual data sets are assigned to a host, wherein in the static hierarchy the registry information for the parent virtual data set contains a same set of columns as the child virtual data sets (para. 182: common storage may also be referred to as global data storage or global data stores; fig. 47: common storage metadata; para. 461: a virtual machine monitoring application, such as SPLUNK® APP FOR VMWARE® that provides operational visibility into granular performance metrics, logs, tasks and events, and topology from hosts, virtual machines and virtual centers; para. 527: partitioning large data sets into smaller, faster, more easily managed parts called data shards; para. 709: the file system type and hierarchy of the external data source, number of partitions supported by an external data source, endpoint locations; para. 1411: fixed size partitions such that the partitions can be processed as units. Fig. 64, a worker node may, for records of a given group, fill a first partition of a partition group with records until the first partition meets the fixed size, then fill a second partition of the group with records, etc. This "time slicing" of records into partitions of a group can, for example, prevent partitions from being unbounded in size; para. 891: intake the buckets previously identified as potentially containing relevant information (e.g., based on metadata of the buckets/registry information); para. 239: examples of a data source include, without limitation, data files, directories of files, data sent over a network, event logs, registries, etc.);
generating, based on the database query, a respective sub database query for each of the plurality of child nodes; and sending, to the plurality of child nodes in parallel, the respective sub database queries to process (para. 392-393: parent, child nodes; para. 410, 440-441: to facilitate faster query processing, a query can be structured such that multiple indexers perform the query in parallel, while aggregation of search results from the multiple indexers is performed locally at the search head; para. 488: perform parallel search; para. 843-846: the query coordinator generates a subquery for the indexers. The subquery can indicate to the indexers that data to be processed by the indexers and the manner of processing the data by the indexers. Further, the subquery can instruct the indexers to provide the results (or partial results) of the subquery to the nodes for further processing; the system can generate or instructions for the dataset sources or allocate resources for the dataset sources based on information about the dataset sources; and allocate resources to combine partial results from the indexers and second dataset concurrently, or in any order, as desired; para. 854: the query coordinator can allocate more worker nodes or processors than is supported by the external data source and/or submit multiple subqueries to the external data source).
wherein the sub database queries are routed to respective hosts that contain data for the database query to obtain a result of the database query (fig. 51: receive and parse a query…distribute sub-queries, execute sub queries, receive partial results, process results and communicate results; para. 84-88, 222-223: host devices broadly include a number of computers, virtual machine instances, and/or data centers that are configured to host or execute one or more instances of host applications, processing requests received from client devices; para. 1068-1069: a secondary data intake and query system can receive a subquery from a primary data intake and query system. the secondary data intake and query system can route partial results of the query that it receives (e.g., a subquery received from a primary data take and system) to worker nodes of a primary data intake and query system; para. 1438).
Even if Bhattacharjee does not explicitly teach fixed size partitions,
Shmuylovich et al. teaches at col. 2:46-52: conventional partitions may be based, for example, on an exemplary or typical data set size, and subdivide the data set accordingly into a particular number of partitions. Configurations herein substantially overcome configuration issues associated with fixed or static number of partitions by performing hierarchical, or tree-based, partitioning; col. 5:11-15: substantially overcome configuration issues associated with a fixed or static number of partitions by performing hierarchical, or tree-based partitioning that groups related updates together according to relations in the hierarchy to minimize multiple fetches of affected database elements.
Thus, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Bhattacharjee and the fixed size partitions of Shmuylovich et al. in order to quickly manage/implement data partitions because the hierarchy of fixed size blocks help ensure the minimum amount of memory space for each of the processes, hence provide the stability for the system.
As per claims 2, 10, 18, Bhattacharjee et al. teaches
wherein the registry information for the parent virtual data set includes metadata that describes data in the partitioned data set that is managed by a plurality of child nodes of the root node (para. 182: a data intake and query system can index and store data in data stores of indexers, and can receive search queries causing a search of the indexers to obtain search results; para. 287, 294: a directory for each index (or partition) that contains a portion of data managed by an indexer; para. 394: objects in data models can be arranged hierarchically in parent/child relationships. Each child object represents a subset of the dataset covered by its parent object. The top-level objects in data models are collectively referred to as "root objects"; para 463-465: the virtual machine monitoring application stores large volumes of minimally processed machine data, such as performance information and log data, at ingestion time for later retrieval and analysis at search time when a live performance issue is being investigated. In addition to data obtained from various log files, this performance-related information can include values for performance metrics obtained through an application programming interface (API) provided as part of the vSphere Hypervisor™ system; a "proactive monitoring tree" that enables a user to easily view and understand relationships among various factors that affect the performance of a hierarchically structured computing system. This proactive monitoring tree enables a user to easily navigate the hierarchy by selectively expanding nodes representing various entities; para. 564,570, 684: multiple partitions of a node (or different nodes) can be assigned to communicate data to a particular destination. Furthermore, the nodes 3306 can be instructed to transform the data so that the destination can properly understand and store the data; para. 415, 732).
As per claims 3, 11, 19, Bhattacharjee et al. teaches
receiving data returned from the respective sub database queries; and combining the data returned from the respective sub database queries (fig. 46; para. 88: a routine implemented by a search process service to divide a query into multiple sub-queries that can be distributively implemented as multiple sub-queries, each sub-query implemented by one or more instances of a single-device execution engine; para. 201, 211, 345: a query coordinator analyzes the query, identifies dataset sources to be accessed, generates subqueries for execution by dataset sources, such as indexers, collects partial results to produce a final result and returns the final results to the search head for delivery to a client device or delivers the final results to the client device without the search head; para. 1463-1464).
As per claims 4, 12, 20, Bhattacharjee et al. teaches
applying the database query to the combined data; and returning the result of the database query to a requestor (para. 341-342: the indexers to which the query was distributed, search data stores associated with them for events that are responsive to the query. To determine which events are responsive to the query, the indexer searches for events that match the criteria specified in the query. These criteria can include matching keywords or specific values for certain fields; the search head combines the partial results and/or events received from the indexers to produce a final result for the query; fig. 6A: search head combines any partial results or events to produce final result).
As per claims 5, 13, 21, Bhattacharjee et al. teaches
provides further instructions that, if executed by a processor, will cause the processor to perform operations of a method of querying a partitioned data set organized in a static hierarchy, the operations comprising: receiving a data set to be stored in a data management system; partitioning the data set into a plurality of fixed size partitions (fig. 19: receive search query, define search process to worker nodes, aggregate partial search results to generate search results; fig. 4: RDBMS; para. 195: stores data in a similar format and/or hierarchy; para. 394-395: objects in data models can be arranged hierarchically in parent/child relationships. Each child object represents a subset of the dataset covered by its parent object. The top-level objects in data models are collectively referred to as "root objects"; para. 1411: fixed size partitions; figs. 36, 51, 72-73: partitions);
Atty. Docket No.: 1031P4960US20 Patent Applicationregistering data in the plurality of fixed size partitions as a plurality of virtual data sets, the fixed size partitions in the plurality of fixed size partitions are represented with a plurality of leaf nodes of a static hierarchy of nodes, the virtual data sets in the plurality of virtual data sets are represented with a root node and a plurality of intermediate nodes in the static hierarchy of nodes (fig. 47: common storage metadata/registry; para. 239: data registries; para. 394: objects in data models can be arranged hierarchically in parent/child relationships. Each child object represents a subset of the dataset covered by its parent object. The top-level objects in data models are collectively referred to as "root objects"; para. 463-465: the virtual machine monitoring application stores large volumes of minimally processed machine data… performance metrics obtained through an application programming interface (API) provided as part of the vSphere Hypervisor™ system; a "proactive monitoring tree" that enables a user to easily view and understand relationships among various factors that affect the performance of a hierarchically structured computing system. This proactive monitoring tree enables a user to easily navigate the hierarchy by selectively expanding nodes representing various entities; para. 564, 684: multiple partitions of a node (or different nodes) can be assigned to communicate data to a particular destination. Furthermore, the nodes can be instructed to transform the data so that the destination can properly understand and store the data; para. 697: a partition can refer to smaller sets of data, such as when data is partitioned (or split up) into smaller parts. A partition can refer to a group of data, data entries, events, or records and computer-executable instructions that indicate how the group of data is to be processed by a processor or worker node; para. 732, 842-844: the query coordinator receives a query, identifies the dataset sources, including the indexers as one dataset source, and can also identify a second dataset source, such as an external data source, a common storage, an ingested data buffer, query acceleration data store; para. 899, 1411: fixed size partitions such that the partitions can be processed as units. Fig. 64, a worker node may, for records of a given group, fill a first partition of a partition group with records until the first partition meets the fixed size, then fill a second partition of the group with records, etc.; figs. 76, 78: parse and generate query plan);
wherein each fixed size partition and corresponding virtual data sets are assigned to a host, and wherein in the static hierarchy of nodes, registry information for the plurality of virtual data sets contains a same set of columns (para. 182: common storage (may also be referred to as global data storage or global data stores; fig. 47: common storage metadata; fig. 27: global index; para. 461, 527: partitioning large data sets into smaller, faster, more easily managed parts called data shards; para. 709: the file system type and hierarchy of the external data source, number of partitions supported by an external data source, endpoint locations); para. 883: data within the data stores is grouped into buckets, each of which is commonly accessible to the indexers. The size of each bucket may be selected according to the computational resources of the common storage or the data intake and query system overall; para. 1411: fixed size partitions such that the partitions can be processed as units. Fig. 64, a worker node may, for records of a given group, fill a first partition of a partition group with records until the first partition meets the fixed size, then fill a second partition of the group with records, etc.; para. 47: receive query, identify common storage as data source, determine potentially relevant buckets from common storage metadata, allocate partitions to intake potentially relevant buckets, execute query; para. 891: intake the buckets previously identified as potentially containing relevant information (e.g., based on metadata of the buckets/registry information); para. 239: examples of a data source include, without limitation, data files, directories of files, data sent over a network, event logs, registries, etc.);
storing each partition of the plurality of fixed size partitions in the database management system; and storing the plurality of virtual data sets in the database management system (para. 182: a data intake and query system can index and store data in data stores of indexers, and can receive search queries causing a search of the indexers to obtain search results; para. 287, 294: a directory for each index (or partition) that contains a portion of data managed by an indexer; fig. 6B, para. 1400: intermediate nodes; fig. 47: common storage metadata/registry; para. 239: data registries; para. 394: objects in data models can be arranged hierarchically in parent/child relationships. Each child object represents a subset of the dataset covered by its parent object. The top-level objects in data models are collectively referred to as "root objects"; para. 1411: fixed size partitions; para. 415, 250-251: if the request parameters of the received search request reference an external data collection, which is not accessible to the indexers or under the management of the data intake and query system, then the search head can access the external data collection through an External Result Provider (ERP) process; para. 463-465: the virtual machine monitoring application stores large volumes of minimally processed machine data, such as performance information and log data, at ingestion time for later retrieval and analysis at search time when a live performance issue is being investigated. In addition to data obtained from various log files, this performance-related information can include values for performance metrics obtained through an application programming interface (API) provided as part of the vSphere Hypervisor™ system; a "proactive monitoring tree" that enables a user to easily view and understand relationships among various factors that affect the performance of a hierarchically structured computing system. This proactive monitoring tree enables a user to easily navigate the hierarchy by selectively expanding nodes representing various entities; para. 564,570, 684: multiple partitions of a node (or different nodes) can be assigned to communicate data to a particular destination. Furthermore, the nodes 3306 can be instructed to transform the data so that the destination can properly understand and store the data).
wherein a database query for data in the partitioned data set is compiled into a set of sub database queries to obtain a result of the database query (fig. 51: receive and parse a query…distribute sub-queries, execute sub queries, receive partial results, process results and communicate results; para. 84-88, 222-223: host devices broadly include a number of computers, virtual machine instances, and/or data centers that are configured to host or execute one or more instances of host applications, processing requests received from client devices; para. 1068-1069: a secondary data intake and query system can receive a subquery from a primary data intake and query system. the secondary data intake and query system can route partial results of the query that it receives (e.g., a subquery received from a primary data take and system) to worker nodes of a primary data intake and query system; para. 1438).
Even if Bhattacharjee does not explicitly teach fixed size partitions,
Shmuylovich et al. teaches at col. 2:46-52: conventional partitions may be based, for example, on an exemplary or typical data set size, and subdivide the data set accordingly into a particular number of partitions. Configurations herein substantially overcome configuration issues associated with fixed or static number of partitions by performing hierarchical, or tree-based, partitioning; col. 5:11-15: substantially overcome configuration issues associated with a fixed or static number of partitions by performing hierarchical, or tree-based partitioning that groups related updates together according to relations in the hierarchy to minimize multiple fetches of affected database elements.
Thus, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Bhattacharjee and the fixed size partitions of Shmuylovich et al. in order to quickly manage/implement data partitions because the hierarchy of fixed size blocks help ensure the minimum amount of memory space for each of the processes, hence provide the stability for the system.
As per claims 6-7, 14-15, 22-23, Bhattacharjee et al. teaches
wherein the static hierarchy of nodes is a tree structure; wherein the root node represents a virtual data set that has registered data for each child virtual data set and that represents the data in the plurality of fixed size partitions (para. 195: stores data in a similar format and/or hierarchy; para. 394-395: objects in data models can be arranged hierarchically in parent/child relationships. Each child object represents a subset of the dataset covered by its parent object. The top-level objects in data models are collectively referred to as "root objects"; para 463-465: the virtual machine monitoring application stores large volumes of minimally processed machine data, such as performance information and log data, at ingestion time for later retrieval and analysis at search time when a live performance issue is being investigated. In addition to data obtained from various log files, this performance-related information can include values for performance metrics obtained through an application programming interface (API) provided as part of the vSphere Hypervisor™ system; a "proactive monitoring tree" that enables a user to easily view and understand relationships among various factors that affect the performance of a hierarchically structured computing system. This proactive monitoring tree enables a user to easily navigate the hierarchy by selectively expanding nodes representing various entities; para. 564,570, 684: multiple partitions of a node (or different nodes) can be assigned to communicate data to a particular destination. Furthermore, the nodes 3306 can be instructed to transform the data so that the destination can properly understand and store the data; para. 1411: fixed size partitions; para. 1296: the system can use a fixed number of execution resources from each indexer used in the query to determine a query-resource allocation).
As per claims 8, 16, 24, Bhattacharjee et al. teaches
wherein the root node has a plurality of child nodes that each of which is an intermediate node that represents a virtual data set that represents a subset of the data in the plurality of fixed size partitions (para. 394-395: objects in data models can be arranged hierarchically in parent/child relationships. Each child object represents a subset of the dataset covered by its parent object. The top-level objects in data models are collectively referred to as "root objects"; para. 1411: fixed size partitions; figs. 36, 51, 73: partitions).
As per claim 26, Bhattacharjee et al. teaches
wherein the static hierarchy contains a plurality of virtual data set layers that each contain virtual data sets, and wherein data obtained from the respective sub database queries is aggregated using a function at the plurality of virtual data set layers (para. 739-741: fig. 36 - layers of partitions used to implement various search phases of a query, fewer or more layers can be included as desired, and can be based on the content of the particular query being executed; Furthermore, based on the query commands, the query coordinator can allocate additional layers, such as a join layer to combine data received from multiple dataset sources, etc.; para. 751-752: the query coordinator estimates that a larger number of partitions will be used in the processing layer and allocate additional worker nodes or processors to the processing layer or use
multiple processing layers to process the data. In some cases, more partitions, worker nodes 3306, and/or processors can be allocated to the search layers for queries of
larger datasets).
Claim(s) 25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bhattacharjee et al. (20200065303) in view of Shmuylovich et al. (US 7899780) and further in view of Bowman (US 2021/0019284).
As per claim 25, Bhattacharjee et al. teaches
wherein data obtained from the respective sub database queries is converted from columnar to row format in a projection, and wherein the data after the projection is processed further in a host in which the database query for data is initiated (fig. 51: receive and process search query, parse query, distribute sub-queries, execute sub-query, communicate results; para. 222-223: content delivered from the host application to a client device includes, for example, HTML documents, media content, etc.; para. 999: converting or transforming the partial results or query results from one format supported by the external data system to another format supported by the data intake and query system; para. 1447: each node may build a columnar table from the dataset, and apply an initial sub query (e.g., a "select" statement) to the table, to result in a set of records/row format needed to satisfy the query.)
Even if Bhattacharjee and Shmuylovich et al. do not teach the respective sub database queries is converted from columnar to row format in a projection,
Bowman teaches at para. 44: if data set retrieval request specified that rows be provided, then reorganize data value(s) from columnar to row-wise organization; para. 366: turning to Fig. 201, in situations in which the data set retrieval request specified the retrieval of at least a portion of the data set in row-wise form, further execution of the instance of the provision component within the provision thread may cause core(s) of processor(s) to proceed with converting the colunmar organization in which the data values of the data set were persistently stored into a row-wise organization.
Thus, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Bhattacharjee, Shmuylovichwith the converting data from columnar to row format in order to provide query results in records/row format for satisfying the query.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Varier (US 7366101) teaches at col. 15:1-6: “A fixed partition allows a traffic class to use in the aggregate a defined amount of bandwidth. A fixed partition not only ensures that a specific amount of bandwidth will be available, but it also limits data flows associated with that traffic class to that same level”.
Shah et al. (US 20180150548) teaches at para. 15-16: data producer(s) 110 may store sales data in one column-oriented file type that best suits the generation needs of data producer 110, while data consumer 150, which may execute queries over column-oriented data; para. 68: a parsing technique for Optimized Row Columnar (ORC) format file types.
Andrake (US 11704313) teaches at col. 5:12-19: the intermediary nodes may join the partial results of a first subquery and the partial results of a second subquery prior to sending results to the search head; col. 14:60-65: each data source 44 broadly represents a distinct source of data that can be consumed by a system 32. Examples of a data source 44 include, without limitation, data files, directories of files, data sent over a network, event logs, registries, etc.
Cesa Klein (US 7543052) teaches at col. 17:8-10: an enterprise employing static partitions may define a static partition for a PeopleSoft software application traffic class.
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.
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/LINH BLACK/Examiner, Art Unit 2163 10/7/2025
/TONY MAHMOUDI/Supervisory Patent Examiner, Art Unit 2163