Embodiments relate generally to computer data systems, and more particularly, to methods, systems and computer readable media for keyed row data selection and processing.
Some graphical user interfaces may provide a display of information from a database query result or other computer data system data object or source. Data selected on a graphical user interface may occur within a dynamically updating display of data (e.g., a query result) that is changing over time. A need may exist to provide for a selection of data to persist within a dynamically updating data object or data source, even when such selection is no longer visible within the graphical user interface.
Some implementations were conceived in light of the above mentioned needs, problems and/or limitations, among other things.
Some implementations can include a computer-implemented method for processing keyed row selection of a computer data system data object. The method can include receiving, at a processor, a selection of one or more keyed rows of the computer data system data object, the selection being received from a graphical user interface that is displaying at least a portion of data from the computer data system object, and adding, using the processor, one or more key values corresponding to the selection to a selected key values set stored in a computer readable medium coupled to the processor. The method can also include receiving, at the processor, an indication of an operation that utilizes data corresponding to the one or more key values, and determining, at the processor, whether the data corresponding to the one or more key values is stored within a local data store. The method can further include, when the data corresponding to the one or more key values is stored within the local data store: retrieving, using the processor, the data corresponding to the one or more key values from the local data store, and providing, using the processor, data retrieved from the local data store to an application.
The method can also include determining, at the processor, whether a portion of the data corresponding to the one or more key values is not stored in the local data store and is stored in a remote data store, and when a portion of the data corresponding to the one or more key values is not stored in the local data store and is stored in the remote data store: requesting, using the processor, data from the remote data store, and receiving, at the processor, at least a portion of requested data from the remote data store. The method can further include providing, using the processor, data received from the remote data store to the application.
The method can also include updating the graphical user interface based on the selection. The method can further include maintaining the selected key values set when the selection is no longer visible within the graphical user interface.
Providing data received from the local data store to the application and providing data received from the remote data store to the application can include storing received data in a temporary working data store. The method can also include receiving an update to the computer data system data object, wherein the update includes a change to the selection, and performing an update on the selection based on the update to the computer data system data object.
Data returned from the remote data store can include indexes for accessing data stored on remote data store. The method can further include receiving, at the processor, an indication that a new row has been added to the computer data system data object, and determining, using the processor, whether the new row is within the selection based on the selected key values set. The method can also include, if the new row is part of the selection: updating, using the processor, the graphical user interface to indicate the new row is within the selection, and providing, from the processor, the new row to the application. The method can further include resetting the selected key values set when a new selection is received.
Some implementations can include a system for dynamically updating a remote computer data system data object. The system can include a processor coupled to a nontransitory computer readable medium having stored thereon software instructions that, when executed by the processor, cause the processor to perform operations. The operations can include receiving, at a processor, a selection of one or more keyed rows of the computer data system data object, the selection being received from a graphical user interface that is displaying at least a portion of data from the computer data system object. The operations can also include adding, using the processor, one or more key values corresponding to the selection to a selected key values set stored in a computer readable medium coupled to the processor, and receiving, at the processor, an indication of an operation that utilizes data corresponding to the one or more key values. The operations can further include determining, at the processor, whether the data corresponding to the one or more key values is stored within a local data store.
The operations can also include, when the data corresponding to the one or more key values is stored within the local data store: retrieving, using the processor, the data corresponding to the one or more key values from the local data store, and providing, using the processor, data retrieved from the local data store to an application. The operations can further include determining, at the processor, whether a portion of the data corresponding to the one or more key values is not stored in the local data store and is stored in a remote data store.
The operations can also include, when a portion of the data corresponding to the one or more key values is not stored in the local data store and is stored in the remote data store: requesting, using the processor, data from the remote data store, and receiving, at the processor, at least a portion of requested data from the remote data store. The operations can further include providing, using the processor, data received from the remote data store to the application.
The operations can also include updating the graphical user interface based on the selection. The operations can further include maintaining the selected key values set when the selection is no longer visible within the graphical user interface. Providing data received from the local data store to the application and providing data received from the remote data store to the application can include storing received data in a temporary working data store.
The operations can also include receiving an update to the computer data system data object, wherein the update includes a change to the selection, and performing an update on the selection based on the update to the computer data system data object. The data returned from the remote data store can include indexes for accessing data stored on remote data store.
The operations can also include receiving, at the processor, an indication that a new row has been added to the computer data system data object, and determining, using the processor, whether the new row is within the selection based on the selected key values set. The operations can further include, if the new row is part of the selection: updating, using the processor, the graphical user interface to indicate the new row is within the selection, and providing, from the processor, the new row to the application. The operations can also include resetting the selected key values set when a new selection is received.
Some implementations can include a nontransitory computer readable medium having stored thereon software instructions that, when executed by a processor, cause the processor to perform operations. The operations can include receiving, at a processor, a selection of one or more keyed rows of the computer data system data object, the selection being received from a graphical user interface that is displaying at least a portion of data from the computer data system object, and adding, using the processor, one or more key values corresponding to the selection to a selected key values set stored in a computer readable medium coupled to the processor. The operations can also include receiving, at the processor, an indication of an operation that utilizes data corresponding to the one or more key values, and determining, at the processor, whether the data corresponding to the one or more key values is stored within a local data store. The operations can further include when the data corresponding to the one or more key values is stored within the local data store: retrieving, using the processor, the data corresponding to the one or more key values from the local data store, and providing, using the processor, data retrieved from the local data store to an application. The operations can also include determining, at the processor, whether a portion of the data corresponding to the one or more key values is not stored in the local data store and is stored in a remote data store.
The operations can further include, when a portion of the data corresponding to the one or more key values is not stored in the local data store and is stored in the remote data store: requesting, using the processor, data from the remote data store, and receiving, at the processor, at least a portion of requested data from the remote data store. The operations can also include providing, using the processor, data received from the remote data store to the application.
The operations further can include updating the graphical user interface based on the selection. The operations can further include maintaining the selected key values set when the selection is no longer visible within the graphical user interface. Providing data received from the local data store to the application and providing data received from the remote data store to the application can include storing received data in a temporary working data store.
Reference may be made herein to the Java programming language, Java classes, Java bytecode and the Java Virtual Machine (JVM) for purposes of illustrating example implementations. It will be appreciated that implementations can include other programming languages (e.g., groovy, Scala, R, Go, etc.), other programming language structures as an alternative to or in addition to Java classes (e.g., other language classes, objects, data structures, program units, code portions, script portions, etc.), other types of bytecode, object code and/or executable code, and/or other virtual machines or hardware implemented machines configured to execute a data system query.
The application host 102 can include one or more application processes 112, one or more log files 114 (e.g., sequential, row-oriented log files), one or more data log tailers 116 and a multicast key-value publisher 118. The periodic data import host 104 can include a local table data server, direct or remote connection to a periodic table data store 122 (e.g., a column-oriented table data store) and a data import server 120. The query server host 106 can include a multicast key-value subscriber 126, a performance table logger 128, local table data store 130 and one or more remote query processors (132, 134) each accessing one or more respective tables (136, 138). The long-term file server 108 can include a long-term data store 140. The user data import host 110 can include a remote user table server 142 and a user table data store 144. Row-oriented log files and column-oriented table data stores are discussed herein for illustration purposes and are not intended to be limiting. It will be appreciated that log files and/or data stores may be configured in other ways. In general, any data stores discussed herein could be configured in a manner suitable for a contemplated implementation.
In operation, the input data application process 112 can be configured to receive input data from a source (e.g., a securities trading data source), apply schema-specified, generated code to format the logged data as it's being prepared for output to the log file 114 and store the received data in the sequential, row-oriented log file 114 via an optional data logging process. In some implementations, the data logging process can include a daemon, or background process task, that is configured to log raw input data received from the application process 112 to the sequential, row-oriented log files on disk and/or a shared memory queue (e.g., for sending data to the multicast publisher 118). Logging raw input data to log files can additionally serve to provide a backup copy of data that can be used in the event that downstream processing of the input data is halted or interrupted or otherwise becomes unreliable.
A data log tailer 116 can be configured to access the sequential, row-oriented log file(s) 114 to retrieve input data logged by the data logging process. In some implementations, the data log tailer 116 can be configured to perform strict byte reading and transmission (e.g., to the data import server 120). The data import server 120 can be configured to store the input data into one or more corresponding data stores such as the periodic table data store 122 in a column-oriented configuration. The periodic table data store 122 can be used to store data that is being received within a time period (e.g., a minute, an hour, a day, etc.) and which may be later processed and stored in a data store of the long-term file server 108. For example, the periodic table data store 122 can include a plurality of data servers configured to store periodic securities trading data according to one or more characteristics of the data (e.g., a data value such as security symbol, the data source such as a given trading exchange, etc.).
The data import server 120 can be configured to receive and store data into the periodic table data store 122 in such a way as to provide a consistent data presentation to other parts of the system. Providing/ensuring consistent data in this context can include, for example, recording logged data to a disk or memory, ensuring rows presented externally are available for consistent reading (e.g., to help ensure that if the system has part of a record, the system has all of the record without any errors), and preserving the order of records from a given data source. If data is presented to clients, such as a remote query processor (132, 134), then the data may be persisted in some fashion (e.g., written to disk).
The local table data server 124 can be configured to retrieve data stored in the periodic table data store 122 and provide the retrieved data to one or more remote query processors (132, 134) via an optional proxy.
The remote user table server (RUTS) 142 can include a centralized consistent data writer, as well as a data server that provides processors with consistent access to the data that it is responsible for managing. For example, users can provide input to the system by writing table data that is then consumed by query processors.
The remote query processors (132, 134) can use data from the data import server 120, local table data server 124 and/or from the long-term file server 108 to perform queries. The remote query processors (132, 134) can also receive data from the multicast key-value subscriber 126, which receives data from the multicast key-value publisher 118 in the application host 102. The performance table logger 128 can log performance information about each remote query processor and its respective queries into a local table data store 130. Further, the remote query processors can also read data from the RUTS, from local table data written by the performance logger, or from user table data read over NFS, for example.
It will be appreciated that the configuration shown in
The production client host 202 can include a batch query application 212 (e.g., a query that is executed from a command line interface or the like) and a real time query data consumer process 214 (e.g., an application that connects to and listens to tables created from the execution of a separate query). The batch query application 212 and the real time query data consumer 214 can connect to a remote query dispatcher 222 and one or more remote query processors (224, 226) within the query server host 1208.
The controller host 204 can include a persistent query controller 216 configured to connect to a remote query dispatcher 232 and one or more remote query processors 228-230. In some implementations, the persistent query controller 216 can serve as the “primary client” for persistent queries and can request remote query processors from dispatchers, and send instructions to start persistent queries. For example, a user can submit a query to 216, and 216 starts and runs the query every day. In another example, a securities trading strategy could be a persistent query. The persistent query controller can start the trading strategy query every morning before the market opened, for instance. It will be appreciated that 216 can work on times other than days. In some implementations, the controller may require its own clients to request that queries be started, stopped, etc. This can be done manually, or by scheduled (e.g., cron) jobs. Some implementations can include “advanced scheduling” (e.g., auto-start/stop/restart, time-based repeat, etc.) within the controller.
The GUI/host workstation can include a user console 218 and a user query application 220. The user console 218 can be configured to connect to the persistent query controller 216. The user query application 220 can be configured to connect to one or more remote query dispatchers (e.g., 232) and one or more remote query processors (228, 230).
In operation, the processor 302 may execute the application 310 stored in the memory 306. The application 310 can include software instructions that, when executed by the processor, cause the processor to perform operations for dynamic updating of query result displays in accordance with the present disclosure (e.g., performing one or more of 402-420 described below).
The application program 310 can operate in conjunction with the data section 312 and the operating system 304.
As used herein, a data source can include, but is not limited to, a real time or near real time data source such as securities market data (e.g., over a multicast distribution mechanism (e.g., 118/126) or through a tailer (e.g., 116), system generated data, historical data, user input data from a remote user table server, tables programmatically generated in-memory, or an element upstream in an update propagation graph (UPG) such as a directed acyclic graph (DAG), and/or any data (e.g., a table, mathematical object, etc.) having a capability to refresh itself/provide updated data.
When a data source is updated, it will send add, delete, modify, reindex (AMDR) notifications through the DAG. It will be appreciated that a DAG is used herein for illustration purposes of a possible implementation of the UPG, and that the UPG can include other implementations. A reindex message is a message to change the indexing of a data item, but not change the value. When a table is exported from the server to a client, there is an exported table handle created and that handle attaches itself to the DAG; as a child of the table to be displayed. When the DAG updates, that handle's node in the DAG is reached and a notification is sent across the network to the client that includes the rows which have been added/modified/deleted/reindexed. On the client side, those rows are reconstructed and an in-memory copy of the table (or portion thereof) is maintained for display (or other access).
There can be two cases in which a view is updated. In the first case, a system clock ticks, and there is new data for one or more source (parent) nodes in the DAG, which percolates down to the exported table handle. In the second case, a user changes the “viewport”, which is the active set of rows and columns.
There can be various ways the viewport is caused to be updated, such as: (i) scrolling the view of the table, (ii) showing or hiding a table, (iii) when the user or client program programmatically accesses the table, and/or (iv) adding/removing columns from a view. When the viewport is updated, the viewport is automatically adjusted to include the rows/columns that the user is trying to access with exponential expansion up to a limit for efficiency. After a timeout, any automatically created viewports are closed.
A query result may not change without a clock tick that has one or more AMDR messages which traverse the DAG. However, the portion of a query result that is displayed by the user (e.g., the viewport) might change. When a user displays a table, a set of visible columns and rows is computed. In addition to the visible set of rows/columns, the system may compute (and make available for possible display) more data than is visible. For example, the system may compute and make available for possible display three screens of data: the currently visible screen and one screen before and one screen after. If there are multiple views of the same table, either multiple exported table handles are created in which case the views are independent or if a single exported table handle is created, the viewport is the union of the visible sets. As the user scrolls the table, the viewport may change. When the viewport changes, the visible area (with a buffer of rows up and down, and columns left and right, so that scrolling is smooth) is computed and the updated visible area is sent to the server. In response, the server sends a snapshot with relevant portions of those newly visible rows/columns. For non-displayed tables, the visible area can be considered the whole table by the system for further processing so that a consistent table view is available for further processing (e.g., all rows and one or more columns of the data object may be sent to the client).
The snapshot can be generated asynchronously from the DAG update/table refresh loop under the condition that a consistent snapshot (i.e., the clock value remains the same throughout the snapshot) is able to be obtained. If a consistent snapshot is not obtained after a given number of attempts (e.g., three attempts), a lock can be obtained (e.g., the LiveTableMonitor lock) at the end of the current DAG update cycle to lock out updates while the snapshot is created.
Further, the remote query processor (or server) has knowledge of the visible regions and will send data updates for the visible rows/columns (e.g., it can send the entire AMDR message information so the client has information about what has been updated, just not what the actual data is outside of its viewport). This enables the client optionally to cache data even if the data is outside the viewport and only invalidate the data once the data actually changes.
The DAG structure can be maintained in the memory of a remote query processor. Child nodes have hard references back to their parents, and parents have weak references to their children. This ensures that if a child exists, its parent will also exist, but if there are no external references to a child, then a garbage collection event can properly clean the child up (and the parent won't hold onto the child). For the exported table handles, a component (e.g., an ExportedTableHandleManager component) can be configured to hold hard references to the exported tables. If a client disconnects, then the references for its tables can be cleaned up. Clients can also proactively release references.
The selected row(s) can include a key field. The key can be unique or non-unique. For example, if the data object is keyed on a given field, the selection of a row can cause the system to automatically select the other rows in the data object having a key field that matches the key field value of the one or more rows that were selected by the user. Matching can include an exact match of a key field value or matching when a key field value is within a given threshold number of a key field value of a selected row. Processing continues to 404.
At 404, one or more key values corresponding to the one or more selected are added to a selected key values set. For example, a key value is read from a row that was selected by a user and the key value from the selected row (or rows) is added to the selected key values set. Processing continues to 406.
At 406, the GUI is refreshed (or repainted) to show the selected row(s). The repainting of the GUI to reflect the selection can be performed “lazily”, according to the GUI refresh rate, or when processing permits. Processing continues to 407.
At 407, an indication of an operation that utilizes data from rows corresponding to the selected key values set is received. For example, an indication of a copy operation can be received (e.g., when a user performs a copy operation via keystroke such as control-C or via mouse operation or menu selection). The copy operation references the selected row(s). Other operations could utilize the selected rows. Processing continues to 408.
At 408, once the indication of an operation that utilizes the selected row(s), the system can determine whether the data is present in a local data store (e.g., within the local memory of a client device or system). Programmatically determining whether data from the selected row(s) is present locally can be accomplished by comparing indexes of rows corresponding to the selected key value set to the indexes of rows stored in the local data store. It will be appreciated that the there can be at least three ranges of rows (or other data aspects) associated with a data object: a range of data visible within the GUI, a range of data stored in a local data store and a range of data stored in a remote data store. Processing continues to 410.
At 410, it is determined whether data corresponding to the selected row(s) is available locally. If the data, or a portion of the data, is available locally, processing continues to 412. If there is no locally available data corresponding to the selection, processing continues to 416. In some implementations, the system may choose to ignore local data if there is a possibility that some data may not be local. By ignoring local data, the system can help ensure that a consistent snapshot of data is created on the remote data store rather than producing potentially inconsistent results (e.g., with some data from a local store and some from a remote store) in the face of concurrent update operations.
At 412, the local data and/or indexes to the local data are copied to a local temporary working data store (e.g., clipboard memory, scratchpad storage, etc.). Processing continues to 414.
At 414, if the system determines that additional data is needed beyond the data locally available (e.g., when a portion of the data corresponding to the selected row(s) is available from the local data store and a portion is not available in the local data store), processing continues to 416.
At 416, a requesting system (e.g., a remote query processor, a client system, etc.) sends a request to a remote data server (e.g., 104 or 108) for data from a remote data store corresponding to the selected key value set. For example, the system could send a request for data from a remote data store in which a given key field has a value matching one of the values in the selected key value set. Processing continues to 418.
At 418, the requesting system receives data rows or indexes to the requested data in the remote data store. The remote data server may provide a copy of the data if the size of the data being provided is less than a threshold size. If the size of the data being provided is greater than the threshold data size, then the remote data server may provide a set of indexes into one or more remote data objects so that the requesting system can retrieve the data as memory space, time, etc. permit. By providing the indexes of the remote data, the system can improve the performance of a distributed computer data system in which a client system may not have sufficient memory, processing, network or other resources to accommodate the amount of data represented by the selection or the selected key value set. Processing continues to 420.
At 420, the data and/or indexes corresponding to the selected key value set is stored in a selected data storage such as a temporary working memory area (e.g., clipboard, memory scratchpad, etc.) for subsequent use. For example, a user may select one or more rows, then provide a copy command (e.g., via control-C or the like). In response, the system may copy the selected data into the clipboard of the user's system (e.g., a client system).
In some implementations, a selected row may be removed from a data object and the key value for the removed row may be maintained in the selected key value set until the selected key value set is cleared (e.g., by receiving a new selection, which clears the previous selection). In some implementations, when a selected row changes, the change may not alter the selection (e.g., the selected key value set).
It will be appreciated that the modules, processes, systems, and sections described above can be implemented in hardware, hardware programmed by software, software instructions stored on a nontransitory computer readable medium or a combination of the above. A system as described above, for example, can include a processor configured to execute a sequence of programmed instructions stored on a nontransitory computer readable medium. For example, the processor can include, but not be limited to, a personal computer or workstation or other such computing system that includes a processor, microprocessor, microcontroller device, or is comprised of control logic including integrated circuits such as, for example, an Application Specific Integrated Circuit (ASIC), a field programmable gate array (FPGA), GPGPU, GPU, or the like. The instructions can be compiled from source code instructions provided in accordance with a programming language such as Java, C, C++, C #.net, assembly or the like. The instructions can also comprise code and data objects provided in accordance with, for example, the Visual Basic™ language, a specialized database query language, or another structured or object-oriented programming language. The sequence of programmed instructions, or programmable logic device configuration software, and data associated therewith can be stored in a nontransitory computer-readable medium such as a computer memory or storage device which may be any suitable memory apparatus, such as, but not limited to ROM, PROM, EEPROM, RAM, flash memory, disk drive and the like.
Furthermore, the modules, processes systems, and sections can be implemented as a single processor or as a distributed processor. Further, it should be appreciated that the steps mentioned above may be performed on a single or distributed processor (single and/or multi-core, or cloud computing system). Also, the processes, system components, modules, and sub-modules described in the various figures of and for embodiments above may be distributed across multiple computers or systems or may be co-located in a single processor or system. Example structural embodiment alternatives suitable for implementing the modules, sections, systems, means, or processes described herein are provided below.
The modules, processors or systems described above can be implemented as a programmed general purpose computer, an electronic device programmed with microcode, a hard-wired analog logic circuit, software stored on a computer-readable medium or signal, an optical computing device, a networked system of electronic and/or optical devices, a special purpose computing device, an integrated circuit device, a semiconductor chip, and/or a software module or object stored on a computer-readable medium or signal, for example.
Embodiments of the method and system (or their sub-components or modules), may be implemented on a general-purpose computer, a special-purpose computer, a programmed microprocessor or microcontroller and peripheral integrated circuit element, an ASIC or other integrated circuit, a digital signal processor, a hardwired electronic or logic circuit such as a discrete element circuit, a programmed logic circuit such as a PLD, PLA, FPGA, PAL, or the like. In general, any processor capable of implementing the functions or steps described herein can be used to implement embodiments of the method, system, or a computer program product (software program stored on a nontransitory computer readable medium).
Furthermore, embodiments of the disclosed method, system, and computer program product (or software instructions stored on a nontransitory computer readable medium) may be readily implemented, fully or partially, in software using, for example, object or object-oriented software development environments that provide portable source code that can be used on a variety of computer platforms. Alternatively, embodiments of the disclosed method, system, and computer program product can be implemented partially or fully in hardware using, for example, standard logic circuits or a VLSI design. Other hardware or software can be used to implement embodiments depending on the speed and/or efficiency requirements of the systems, the particular function, and/or particular software or hardware system, microprocessor, or microcomputer being utilized. Embodiments of the method, system, and computer program product can be implemented in hardware and/or software using any known or later developed systems or structures, devices and/or software by those of ordinary skill in the applicable art from the function description provided herein and with a general basic knowledge of the software engineering and computer networking arts.
Moreover, embodiments of the disclosed method, system, and computer readable media (or computer program product) can be implemented in software executed on a programmed general purpose computer, a special purpose computer, a microprocessor, or the like.
It is, therefore, apparent that there is provided, in accordance with the various embodiments disclosed herein, methods, systems and computer readable media for keyed row selection and data processing operations using selected data.
Application Ser. No. 15/154,974, entitled “DATA PARTITIONING AND ORDERING” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/154,975, entitled “COMPUTER DATA SYSTEM DATA SOURCE REFRESHING USING AN UPDATE PROPAGATION GRAPH” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/154,979, entitled “COMPUTER DATA SYSTEM POSITION-INDEX MAPPING” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/154,980, entitled “SYSTEM PERFORMANCE LOGGING OF COMPLEX REMOTE QUERY PROCESSOR QUERY OPERATIONS” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/154,983, entitled “DISTRIBUTED AND OPTIMIZED GARBAGE COLLECTION OF REMOTE AND EXPORTED TABLE HANDLE LINKS TO UPDATE PROPAGATION GRAPH NODES” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/154,984, entitled “COMPUTER DATA SYSTEM CURRENT ROW POSITION QUERY LANGUAGE CONSTRUCT AND ARRAY PROCESSING QUERY LANGUAGE CONSTRUCTS” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/154,985, entitled “PARSING AND COMPILING DATA SYSTEM QUERIES” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/154,987, entitled “DYNAMIC FILTER PROCESSING” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/154,988, entitled “DYNAMIC JOIN PROCESSING USING REAL-TIME MERGED NOTIFICATION LISTENER” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/154,990, entitled “DYNAMIC TABLE INDEX MAPPING” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/154,991, entitled “QUERY TASK PROCESSING BASED ON MEMORY ALLOCATION AND PERFORMANCE CRITERIA” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/154,993, entitled “A MEMORY-EFFICIENT COMPUTER SYSTEM FOR DYNAMIC UPDATING OF JOIN PROCESSING” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/154,995, entitled “QUERY DISPATCH AND EXECUTION ARCHITECTURE” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/154,996, entitled “COMPUTER DATA DISTRIBUTION ARCHITECTURE” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/154,997, entitled “DYNAMIC UPDATING OF QUERY RESULT DISPLAYS” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/154,998, entitled “DYNAMIC CODE LOADING” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/154,999, entitled “IMPORTATION, PRESENTATION, AND PERSISTENT STORAGE OF DATA” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/155,001, entitled “COMPUTER DATA DISTRIBUTION ARCHITECTURE” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/155,005, entitled “PERSISTENT QUERY DISPATCH AND EXECUTION ARCHITECTURE” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/155,006, entitled “SINGLE INPUT GRAPHICAL USER INTERFACE CONTROL ELEMENT AND METHOD” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/155,007, entitled “GRAPHICAL USER INTERFACE DISPLAY EFFECTS FOR A COMPUTER DISPLAY SCREEN” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/155,009, entitled “COMPUTER ASSISTED COMPLETION OF HYPERLINK COMMAND SEGMENTS” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/155,010, entitled “HISTORICAL DATA REPLAY UTILIZING A COMPUTER SYSTEM” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/155,011, entitled “DATA STORE ACCESS PERMISSION SYSTEM WITH INTERLEAVED APPLICATION OF DEFERRED ACCESS CONTROL FILTERS” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/155,012, entitled “REMOTE DATA OBJECT PUBLISHING/SUBSCRIBING SYSTEM HAVING A MULTICAST KEY-VALUE PROTOCOL” and filed in the United States Patent and Trademark Office on May 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/351,429, entitled “QUERY TASK PROCESSING BASED ON MEMORY ALLOCATION AND PERFORMANCE CRITERIA” and filed in the United States Patent and Trademark Office on Nov. 14, 2016, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/813,112, entitled “COMPUTER DATA SYSTEM DATA SOURCE REFRESHING USING AN UPDATE PROPAGATION GRAPH HAVING A MERGED JOIN LISTENER” and filed in the United States Patent and Trademark Office on Nov. 14, 2017, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/813,142, entitled “COMPUTER DATA SYSTEM DATA SOURCE HAVING AN UPDATE PROPAGATION GRAPH WITH FEEDBACK CYCLICALITY” and filed in the United States Patent and Trademark Office on Nov. 14, 2017, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
Application Ser. No. 15/813,127, entitled “COMPUTER DATA DISTRIBUTION ARCHITECTURE CONNECTING AN UPDATE PROPAGATION GRAPH THROUGH MULTIPLE REMOTE QUERY PROCESSORS” and filed in the United States Patent and Trademark Office on Nov. 14, 2017, is hereby incorporated by reference herein in its entirety as if fully set forth herein.
While the disclosed subject matter has been described in conjunction with a number of embodiments, it is evident that many alternatives, modifications and variations would be, or are, apparent to those of ordinary skill in the applicable arts. Accordingly, Applicants intend to embrace all such alternatives, modifications, equivalents and variations that are within the spirit and scope of the disclosed subject matter.
This application claims the benefit of U.S. Provisional Application No. 62/549,908, entitled “COMPUTER DATA SYSTEM” and filed on Aug. 24, 2017, which is incorporated herein by reference in its entirety.
Number | Name | Date | Kind |
---|---|---|---|
5335202 | Manning et al. | Aug 1994 | A |
5452434 | Macdonald | Sep 1995 | A |
5469567 | Okada | Nov 1995 | A |
5504885 | Alashqur | Apr 1996 | A |
5530939 | Mansfield et al. | Jun 1996 | A |
5568632 | Nelson | Oct 1996 | A |
5673369 | Kim | Sep 1997 | A |
5701461 | Dalal et al. | Dec 1997 | A |
5701467 | Freeston | Dec 1997 | A |
5764953 | Collins et al. | Jun 1998 | A |
5787411 | Groff | Jul 1998 | A |
5787428 | Hart | Jul 1998 | A |
5806059 | Tsuchida et al. | Sep 1998 | A |
5859972 | Subramaniam et al. | Jan 1999 | A |
5873075 | Cochrane et al. | Feb 1999 | A |
5875334 | Chow et al. | Feb 1999 | A |
5878415 | Olds | Mar 1999 | A |
5890167 | Bridge et al. | Mar 1999 | A |
5899990 | Maritzen et al. | May 1999 | A |
5920860 | Maheshwari et al. | Jul 1999 | A |
5943672 | Yoshida | Aug 1999 | A |
5960087 | Tribble et al. | Sep 1999 | A |
5991810 | Shapiro et al. | Nov 1999 | A |
5999918 | Williams et al. | Dec 1999 | A |
6006220 | Haderle et al. | Dec 1999 | A |
6032144 | Srivastava et al. | Feb 2000 | A |
6032148 | Wilkes | Feb 2000 | A |
6038563 | Bapat et al. | Mar 2000 | A |
6058394 | Bakow et al. | May 2000 | A |
6061684 | Glasser et al. | May 2000 | A |
6138112 | Slutz | Oct 2000 | A |
6160548 | Lea et al. | Dec 2000 | A |
6253195 | Hudis et al. | Jun 2001 | B1 |
6266669 | Brodersen et al. | Jul 2001 | B1 |
6289357 | Parker | Sep 2001 | B1 |
6292803 | Richardson et al. | Sep 2001 | B1 |
6304876 | Isip | Oct 2001 | B1 |
6317728 | Kane | Nov 2001 | B1 |
6327702 | Sauntry et al. | Dec 2001 | B1 |
6336114 | Garrison | Jan 2002 | B1 |
6353819 | Edwards et al. | Mar 2002 | B1 |
6367068 | Vaidyanathan et al. | Apr 2002 | B1 |
6389414 | Delo et al. | May 2002 | B1 |
6389462 | Cohen et al. | May 2002 | B1 |
6397206 | Hill et al. | May 2002 | B1 |
6438537 | Netz et al. | Aug 2002 | B1 |
6446069 | Yaung et al. | Sep 2002 | B1 |
6460037 | Weiss et al. | Oct 2002 | B1 |
6473750 | Petculescu et al. | Oct 2002 | B1 |
6487552 | Lei et al. | Nov 2002 | B1 |
6496833 | Goldberg et al. | Dec 2002 | B1 |
6505189 | Au et al. | Jan 2003 | B1 |
6505241 | Pitts | Jan 2003 | B2 |
6510551 | Miller | Jan 2003 | B1 |
6519604 | Acharya et al. | Feb 2003 | B1 |
6530075 | Beadle et al. | Mar 2003 | B1 |
6538651 | Hayman et al. | Mar 2003 | B1 |
6546402 | Beyer et al. | Apr 2003 | B1 |
6553375 | Huang et al. | Apr 2003 | B1 |
6584474 | Pereira | Jun 2003 | B1 |
6604104 | Smith | Aug 2003 | B1 |
6618720 | Au et al. | Sep 2003 | B1 |
6631374 | Klein et al. | Oct 2003 | B1 |
6640234 | Coffen et al. | Oct 2003 | B1 |
6697880 | Dougherty | Feb 2004 | B1 |
6701415 | Hendren | Mar 2004 | B1 |
6714962 | Helland et al. | Mar 2004 | B1 |
6725243 | Snapp | Apr 2004 | B2 |
6732100 | Brodersen et al. | May 2004 | B1 |
6745332 | Wong et al. | Jun 2004 | B1 |
6748374 | Madan et al. | Jun 2004 | B1 |
6748455 | Hinson et al. | Jun 2004 | B1 |
6760719 | Hanson et al. | Jul 2004 | B1 |
6775660 | Lin et al. | Aug 2004 | B2 |
6785668 | Polo et al. | Aug 2004 | B1 |
6795851 | Noy | Sep 2004 | B1 |
6801908 | Fuloria et al. | Oct 2004 | B1 |
6816855 | Hartel et al. | Nov 2004 | B2 |
6820082 | Cook et al. | Nov 2004 | B1 |
6829620 | Michael et al. | Dec 2004 | B2 |
6832229 | Reed | Dec 2004 | B2 |
6851088 | Conner et al. | Feb 2005 | B1 |
6882994 | Yoshimura et al. | Apr 2005 | B2 |
6925472 | Kong | Aug 2005 | B2 |
6934717 | James | Aug 2005 | B1 |
6947928 | Dettinger et al. | Sep 2005 | B2 |
6983291 | Cochrane et al. | Jan 2006 | B1 |
6985895 | Witkowski et al. | Jan 2006 | B2 |
6985899 | Chan et al. | Jan 2006 | B2 |
6985904 | Kaluskar et al. | Jan 2006 | B1 |
7020649 | Cochrane et al. | Mar 2006 | B2 |
7024414 | Sah et al. | Apr 2006 | B2 |
7031962 | Moses | Apr 2006 | B2 |
7047484 | Becker et al. | May 2006 | B1 |
7058657 | Berno | Jun 2006 | B1 |
7089228 | Arnold et al. | Aug 2006 | B2 |
7089245 | George et al. | Aug 2006 | B1 |
7096216 | Anonsen | Aug 2006 | B2 |
7099927 | Cudd et al. | Aug 2006 | B2 |
7103608 | Ozbutun et al. | Sep 2006 | B1 |
7110997 | Turkel et al. | Sep 2006 | B1 |
7127462 | Hiraga et al. | Oct 2006 | B2 |
7146357 | Suzuki et al. | Dec 2006 | B2 |
7149742 | Eastham et al. | Dec 2006 | B1 |
7167870 | Avvari et al. | Jan 2007 | B2 |
7171469 | Ackaouy et al. | Jan 2007 | B2 |
7174341 | Ghukasyan et al. | Feb 2007 | B2 |
7181686 | Bahrs | Feb 2007 | B1 |
7188105 | Dettinger et al. | Mar 2007 | B2 |
7200620 | Gupta | Apr 2007 | B2 |
7216115 | Walters et al. | May 2007 | B1 |
7216116 | Nilsson et al. | May 2007 | B1 |
7219302 | O'Shaughnessy et al. | May 2007 | B1 |
7225189 | McCormack et al. | May 2007 | B1 |
7254808 | Trappen et al. | Aug 2007 | B2 |
7257689 | Baird | Aug 2007 | B1 |
7272605 | Hinshaw et al. | Sep 2007 | B1 |
7308580 | Nelson et al. | Dec 2007 | B2 |
7316003 | Dulepet et al. | Jan 2008 | B1 |
7330969 | Harrison et al. | Feb 2008 | B2 |
7333941 | Choi | Feb 2008 | B1 |
7343585 | Lau et al. | Mar 2008 | B1 |
7350237 | Vogel et al. | Mar 2008 | B2 |
7380242 | Alaluf | May 2008 | B2 |
7401088 | Chintakayala et al. | Jul 2008 | B2 |
7426521 | Harter | Sep 2008 | B2 |
7430549 | Zane et al. | Sep 2008 | B2 |
7433863 | Zane et al. | Oct 2008 | B2 |
7447865 | Uppala et al. | Nov 2008 | B2 |
7478094 | Ho et al. | Jan 2009 | B2 |
7484096 | Garg et al. | Jan 2009 | B1 |
7493311 | Cutsinger et al. | Feb 2009 | B1 |
7506055 | McClain et al. | Mar 2009 | B2 |
7523462 | Nesamoney et al. | Apr 2009 | B1 |
7529734 | Dirisala | May 2009 | B2 |
7529750 | Bair | May 2009 | B2 |
7542958 | Warren et al. | Jun 2009 | B1 |
7552223 | Ackaouy et al. | Jun 2009 | B1 |
7596550 | Mordvinov et al. | Sep 2009 | B2 |
7610351 | Gollapudi et al. | Oct 2009 | B1 |
7620687 | Chen et al. | Nov 2009 | B2 |
7624126 | Pizzo et al. | Nov 2009 | B2 |
7627603 | Rosenblum et al. | Dec 2009 | B2 |
7661141 | Dutta et al. | Feb 2010 | B2 |
7664778 | Yagoub et al. | Feb 2010 | B2 |
7672275 | Yajnik et al. | Mar 2010 | B2 |
7680782 | Chen et al. | Mar 2010 | B2 |
7711716 | Stonecipher | May 2010 | B2 |
7711740 | Minore et al. | May 2010 | B2 |
7747640 | Dettinger | Jun 2010 | B2 |
7761444 | Zhang et al. | Jul 2010 | B2 |
7797356 | Iyer et al. | Sep 2010 | B2 |
7827204 | Heinzel et al. | Nov 2010 | B2 |
7827403 | Wong et al. | Nov 2010 | B2 |
7827523 | Ahmed et al. | Nov 2010 | B2 |
7882121 | Bruno et al. | Feb 2011 | B2 |
7882132 | Ghatare | Feb 2011 | B2 |
7895191 | Colossi et al. | Feb 2011 | B2 |
7904487 | Ghatare | Mar 2011 | B2 |
7908259 | Branscome et al. | Mar 2011 | B2 |
7908266 | Zeringue et al. | Mar 2011 | B2 |
7930412 | Yeap et al. | Apr 2011 | B2 |
7966311 | Haase | Jun 2011 | B2 |
7966312 | Nolan et al. | Jun 2011 | B2 |
7966343 | Yang et al. | Jun 2011 | B2 |
7970777 | Saxena et al. | Jun 2011 | B2 |
7979431 | Qazi et al. | Jul 2011 | B2 |
7984043 | Waas | Jul 2011 | B1 |
8019795 | Anderson et al. | Sep 2011 | B2 |
8027293 | Spaur et al. | Sep 2011 | B2 |
8032525 | Bowers et al. | Oct 2011 | B2 |
8037542 | Taylor et al. | Oct 2011 | B2 |
8046394 | Shatdal | Oct 2011 | B1 |
8046749 | Owen et al. | Oct 2011 | B1 |
8055672 | Djugash et al. | Nov 2011 | B2 |
8060484 | Bandera et al. | Nov 2011 | B2 |
8171018 | Zane et al. | May 2012 | B2 |
8180789 | Wasserman et al. | May 2012 | B1 |
8196121 | Peshansky et al. | Jun 2012 | B2 |
8209356 | Roesler | Jun 2012 | B1 |
8286189 | Kukreja et al. | Oct 2012 | B2 |
8321833 | Langworthy et al. | Nov 2012 | B2 |
8332435 | Ballard et al. | Dec 2012 | B2 |
8359305 | Burke et al. | Jan 2013 | B1 |
8375127 | Lita | Feb 2013 | B1 |
8380757 | Bailey et al. | Feb 2013 | B1 |
8418142 | Ao et al. | Apr 2013 | B2 |
8433701 | Sargeant et al. | Apr 2013 | B2 |
8458218 | Wildermuth | Jun 2013 | B2 |
8473897 | Box et al. | Jun 2013 | B2 |
8478713 | Cotner et al. | Jul 2013 | B2 |
8515942 | Marum et al. | Aug 2013 | B2 |
8543620 | Ching | Sep 2013 | B2 |
8553028 | Urbach | Oct 2013 | B1 |
8555263 | Allen et al. | Oct 2013 | B2 |
8560502 | Vora | Oct 2013 | B2 |
8595151 | Hao et al. | Nov 2013 | B2 |
8601016 | Briggs et al. | Dec 2013 | B2 |
8621424 | Kejariwal et al. | Dec 2013 | B2 |
8631034 | Peloski | Jan 2014 | B1 |
8635251 | Chan | Jan 2014 | B1 |
8650182 | Murthy | Feb 2014 | B2 |
8660869 | MacIntyre et al. | Feb 2014 | B2 |
8676863 | Connell et al. | Mar 2014 | B1 |
8683488 | Kukreja et al. | Mar 2014 | B2 |
8713518 | Pointer et al. | Apr 2014 | B2 |
8719252 | Miranker et al. | May 2014 | B2 |
8725707 | Chen et al. | May 2014 | B2 |
8726254 | Rohde et al. | May 2014 | B2 |
8745014 | Travis | Jun 2014 | B2 |
8745510 | D'Alo' et al. | Jun 2014 | B2 |
8751823 | Myles et al. | Jun 2014 | B2 |
8768961 | Krishnamurthy | Jul 2014 | B2 |
8788254 | Peloski | Jul 2014 | B2 |
8793243 | Weyerhaeuser et al. | Jul 2014 | B2 |
8805875 | Bawcom et al. | Aug 2014 | B1 |
8805947 | Kuzkin et al. | Aug 2014 | B1 |
8806133 | Hay et al. | Aug 2014 | B2 |
8812625 | Chitilian et al. | Aug 2014 | B1 |
8838656 | Cheriton | Sep 2014 | B1 |
8855999 | Elliot | Oct 2014 | B1 |
8863156 | Lepanto et al. | Oct 2014 | B1 |
8874512 | Jin et al. | Oct 2014 | B2 |
8880569 | Draper et al. | Nov 2014 | B2 |
8880787 | Kimmel et al. | Nov 2014 | B1 |
8881121 | Ali | Nov 2014 | B2 |
8886631 | Abadi et al. | Nov 2014 | B2 |
8903717 | Elliot | Dec 2014 | B2 |
8903842 | Bloesch et al. | Dec 2014 | B2 |
8922579 | Mi et al. | Dec 2014 | B2 |
8924384 | Driesen et al. | Dec 2014 | B2 |
8930892 | Pointer et al. | Jan 2015 | B2 |
8954418 | Faerber et al. | Feb 2015 | B2 |
8959495 | Chafi et al. | Feb 2015 | B2 |
8996864 | Maigne et al. | Mar 2015 | B2 |
9031930 | Valentin | May 2015 | B2 |
9077611 | Cordray et al. | Jul 2015 | B2 |
9122765 | Chen | Sep 2015 | B1 |
9177079 | Ramachandran et al. | Nov 2015 | B1 |
9195712 | Freedman et al. | Nov 2015 | B2 |
9298768 | Varakin et al. | Mar 2016 | B2 |
9311357 | Ramesh et al. | Apr 2016 | B2 |
9372671 | Balan et al. | Jun 2016 | B2 |
9384184 | Acuña et al. | Jul 2016 | B2 |
9477702 | Ramachandran et al. | Oct 2016 | B1 |
9612959 | Caudy et al. | Apr 2017 | B2 |
9613018 | Zeldis et al. | Apr 2017 | B2 |
9613109 | Wright et al. | Apr 2017 | B2 |
9619210 | Kent et al. | Apr 2017 | B2 |
9633060 | Caudy et al. | Apr 2017 | B2 |
9639570 | Wright et al. | May 2017 | B2 |
9672238 | Wright et al. | Jun 2017 | B2 |
9679006 | Wright et al. | Jun 2017 | B2 |
9690821 | Wright et al. | Jun 2017 | B2 |
9710511 | Wright et al. | Jul 2017 | B2 |
9760591 | Caudy et al. | Sep 2017 | B2 |
9805084 | Wright et al. | Oct 2017 | B2 |
9832068 | McSherry et al. | Nov 2017 | B2 |
9836494 | Caudy et al. | Dec 2017 | B2 |
9836495 | Wright | Dec 2017 | B2 |
9886469 | Kent et al. | Feb 2018 | B2 |
9898496 | Caudy et al. | Feb 2018 | B2 |
9934266 | Wright et al. | Apr 2018 | B2 |
10002153 | Teodorescu et al. | Jun 2018 | B2 |
10002154 | Kent et al. | Jun 2018 | B1 |
10002155 | Caudy et al. | Jun 2018 | B1 |
10003673 | Caudy et al. | Jun 2018 | B2 |
10019138 | Zeldis et al. | Jul 2018 | B2 |
10069943 | Teodorescu et al. | Sep 2018 | B2 |
20020002576 | Wollrath et al. | Jan 2002 | A1 |
20020007331 | Lo et al. | Jan 2002 | A1 |
20020054587 | Baker et al. | May 2002 | A1 |
20020065981 | Jenne et al. | May 2002 | A1 |
20020129168 | Kanai et al. | Sep 2002 | A1 |
20020156722 | Greenwood | Oct 2002 | A1 |
20030004952 | Nixon et al. | Jan 2003 | A1 |
20030061216 | Moses | Mar 2003 | A1 |
20030074400 | Brooks et al. | Apr 2003 | A1 |
20030110416 | Morrison et al. | Jun 2003 | A1 |
20030167261 | Grust et al. | Sep 2003 | A1 |
20030182261 | Patterson | Sep 2003 | A1 |
20030208484 | Chang et al. | Nov 2003 | A1 |
20030208505 | Mullins et al. | Nov 2003 | A1 |
20030233632 | Aigen et al. | Dec 2003 | A1 |
20040002961 | Dellinger et al. | Jan 2004 | A1 |
20040076155 | Yajnik et al. | Apr 2004 | A1 |
20040111492 | Nakahara et al. | Jun 2004 | A1 |
20040148630 | Choi | Jul 2004 | A1 |
20040186813 | Tedesco et al. | Sep 2004 | A1 |
20040216150 | Scheifler et al. | Oct 2004 | A1 |
20040220923 | Nica | Nov 2004 | A1 |
20040254876 | Coval et al. | Dec 2004 | A1 |
20050015490 | Saare et al. | Jan 2005 | A1 |
20050060693 | Robison et al. | Mar 2005 | A1 |
20050097447 | Serra et al. | May 2005 | A1 |
20050102284 | Srinivasan et al. | May 2005 | A1 |
20050102636 | McKeon et al. | May 2005 | A1 |
20050131893 | Glan | Jun 2005 | A1 |
20050132384 | Morrison et al. | Jun 2005 | A1 |
20050138624 | Morrison et al. | Jun 2005 | A1 |
20050165866 | Bohannon et al. | Jul 2005 | A1 |
20050198001 | Cunningham et al. | Sep 2005 | A1 |
20050228828 | Chandrasekar | Oct 2005 | A1 |
20060059253 | Goodman et al. | Mar 2006 | A1 |
20060074901 | Pirahesh et al. | Apr 2006 | A1 |
20060085490 | Baron et al. | Apr 2006 | A1 |
20060100989 | Chinchwadkar et al. | May 2006 | A1 |
20060101019 | Nelson et al. | May 2006 | A1 |
20060116983 | Dettinger et al. | Jun 2006 | A1 |
20060116999 | Dettinger et al. | Jun 2006 | A1 |
20060131383 | Battagin et al. | Jun 2006 | A1 |
20060136361 | Peri et al. | Jun 2006 | A1 |
20060173693 | Arazi et al. | Aug 2006 | A1 |
20060195460 | Nori et al. | Aug 2006 | A1 |
20060212847 | Tarditi et al. | Sep 2006 | A1 |
20060218123 | Chowdhuri et al. | Sep 2006 | A1 |
20060218200 | Factor et al. | Sep 2006 | A1 |
20060230016 | Cunningham et al. | Oct 2006 | A1 |
20060253311 | Yin et al. | Nov 2006 | A1 |
20060271510 | Harward et al. | Nov 2006 | A1 |
20060277162 | Smith | Dec 2006 | A1 |
20070011211 | Reeves et al. | Jan 2007 | A1 |
20070027884 | Heger et al. | Feb 2007 | A1 |
20070033518 | Kenna et al. | Feb 2007 | A1 |
20070073765 | Chen | Mar 2007 | A1 |
20070101252 | Chamberlain et al. | May 2007 | A1 |
20070113014 | Manolov et al. | May 2007 | A1 |
20070116287 | Rasizade et al. | May 2007 | A1 |
20070169003 | Branda et al. | Jul 2007 | A1 |
20070198479 | Cai et al. | Aug 2007 | A1 |
20070256060 | Ryu et al. | Nov 2007 | A1 |
20070258508 | Werb et al. | Nov 2007 | A1 |
20070271280 | Chandasekaran | Nov 2007 | A1 |
20070294217 | Chen et al. | Dec 2007 | A1 |
20070299822 | Jopp et al. | Dec 2007 | A1 |
20080022136 | Mattsson et al. | Jan 2008 | A1 |
20080033907 | Woehler et al. | Feb 2008 | A1 |
20080034084 | Pandya | Feb 2008 | A1 |
20080046804 | Rui et al. | Feb 2008 | A1 |
20080072150 | Chan et al. | Mar 2008 | A1 |
20080097748 | Haley et al. | Apr 2008 | A1 |
20080120283 | Liu et al. | May 2008 | A1 |
20080155565 | Poduri | Jun 2008 | A1 |
20080168135 | Redlich et al. | Jul 2008 | A1 |
20080172639 | Keysar et al. | Jul 2008 | A1 |
20080235238 | Jalobeanu et al. | Sep 2008 | A1 |
20080263179 | Buttner et al. | Oct 2008 | A1 |
20080276241 | Bajpai et al. | Nov 2008 | A1 |
20080319951 | Ueno et al. | Dec 2008 | A1 |
20090019029 | Tommaney et al. | Jan 2009 | A1 |
20090022095 | Spaur et al. | Jan 2009 | A1 |
20090024615 | Pedro et al. | Jan 2009 | A1 |
20090037391 | Agrawal et al. | Feb 2009 | A1 |
20090037500 | Kirshenbaum | Feb 2009 | A1 |
20090055370 | Dagum et al. | Feb 2009 | A1 |
20090083215 | Burger | Mar 2009 | A1 |
20090089312 | Chi et al. | Apr 2009 | A1 |
20090157723 | Peuter et al. | Jun 2009 | A1 |
20090248902 | Blue | Oct 2009 | A1 |
20090254516 | Meiyyappan et al. | Oct 2009 | A1 |
20090271472 | Scheifler et al. | Oct 2009 | A1 |
20090300770 | Rowney et al. | Dec 2009 | A1 |
20090319058 | Rovaglio et al. | Dec 2009 | A1 |
20090319484 | Golbandi et al. | Dec 2009 | A1 |
20090327242 | Brown | Dec 2009 | A1 |
20100023952 | Sandoval et al. | Jan 2010 | A1 |
20100036801 | Pirvali et al. | Feb 2010 | A1 |
20100042587 | Johnson et al. | Feb 2010 | A1 |
20100047760 | Best et al. | Feb 2010 | A1 |
20100049715 | Jacobsen et al. | Feb 2010 | A1 |
20100070721 | Pugh et al. | Mar 2010 | A1 |
20100114890 | Hagar et al. | May 2010 | A1 |
20100161555 | Nica et al. | Jun 2010 | A1 |
20100186082 | Ladki et al. | Jul 2010 | A1 |
20100199161 | Aureglia et al. | Aug 2010 | A1 |
20100205017 | Sichelman et al. | Aug 2010 | A1 |
20100205351 | Wiener et al. | Aug 2010 | A1 |
20100281005 | Carlin et al. | Nov 2010 | A1 |
20100281071 | Ben-Zvi et al. | Nov 2010 | A1 |
20100293334 | Xun et al. | Nov 2010 | A1 |
20110126110 | Vilke et al. | May 2011 | A1 |
20110126154 | Boehler et al. | May 2011 | A1 |
20110153603 | Adiba et al. | Jun 2011 | A1 |
20110161378 | Williamson | Jun 2011 | A1 |
20110167020 | Yang et al. | Jul 2011 | A1 |
20110178984 | Talius et al. | Jul 2011 | A1 |
20110194563 | Shen et al. | Aug 2011 | A1 |
20110219020 | Oks et al. | Sep 2011 | A1 |
20110314019 | Peris | Dec 2011 | A1 |
20120110030 | Pomponio | May 2012 | A1 |
20120144234 | Clark et al. | Jun 2012 | A1 |
20120159303 | Friedrich et al. | Jun 2012 | A1 |
20120191446 | Binsztok et al. | Jul 2012 | A1 |
20120191582 | Rance et al. | Jul 2012 | A1 |
20120192096 | Bowman et al. | Jul 2012 | A1 |
20120197868 | Fauser et al. | Aug 2012 | A1 |
20120209886 | Henderson | Aug 2012 | A1 |
20120215741 | Poole et al. | Aug 2012 | A1 |
20120221528 | Renkes | Aug 2012 | A1 |
20120246052 | Taylor et al. | Sep 2012 | A1 |
20120254143 | Varma et al. | Oct 2012 | A1 |
20120259759 | Crist et al. | Oct 2012 | A1 |
20120296846 | Teeter | Nov 2012 | A1 |
20130041946 | Joel et al. | Feb 2013 | A1 |
20130080514 | Gupta et al. | Mar 2013 | A1 |
20130086107 | Genochio et al. | Apr 2013 | A1 |
20130166551 | Wong | Jun 2013 | A1 |
20130166556 | Baeumges et al. | Jun 2013 | A1 |
20130173667 | Soderberg et al. | Jul 2013 | A1 |
20130179460 | Cervantes et al. | Jul 2013 | A1 |
20130185619 | Ludwig | Jul 2013 | A1 |
20130191370 | Chen et al. | Jul 2013 | A1 |
20130198232 | Shamgunov et al. | Aug 2013 | A1 |
20130226959 | Dittrich et al. | Aug 2013 | A1 |
20130246560 | Feng et al. | Sep 2013 | A1 |
20130263123 | Zhou et al. | Oct 2013 | A1 |
20130290243 | Hazel et al. | Oct 2013 | A1 |
20130304725 | Nee et al. | Nov 2013 | A1 |
20130304744 | McSherry et al. | Nov 2013 | A1 |
20130311352 | Kayanuma et al. | Nov 2013 | A1 |
20130311488 | Erdogan et al. | Nov 2013 | A1 |
20130318129 | Vingralek et al. | Nov 2013 | A1 |
20130346365 | Kan et al. | Dec 2013 | A1 |
20140019494 | Tang | Jan 2014 | A1 |
20140026121 | Jackson et al. | Jan 2014 | A1 |
20140040203 | Lu et al. | Feb 2014 | A1 |
20140046638 | Peloski | Feb 2014 | A1 |
20140059646 | Hannel et al. | Feb 2014 | A1 |
20140082724 | Pearson et al. | Mar 2014 | A1 |
20140136521 | Pappas | May 2014 | A1 |
20140143123 | Banke et al. | May 2014 | A1 |
20140149997 | Kukreja et al. | May 2014 | A1 |
20140156618 | Castellano | Jun 2014 | A1 |
20140173023 | Vamey et al. | Jun 2014 | A1 |
20140181036 | Dhamankar et al. | Jun 2014 | A1 |
20140181081 | Veldhuizen | Jun 2014 | A1 |
20140188924 | Ma et al. | Jul 2014 | A1 |
20140195558 | Murthy et al. | Jul 2014 | A1 |
20140201194 | Reddy et al. | Jul 2014 | A1 |
20140215446 | Araya et al. | Jul 2014 | A1 |
20140222768 | Rambo et al. | Aug 2014 | A1 |
20140229506 | Lee | Aug 2014 | A1 |
20140229874 | Strauss | Aug 2014 | A1 |
20140244687 | Shmueli | Aug 2014 | A1 |
20140279810 | Mann et al. | Sep 2014 | A1 |
20140280522 | Watte | Sep 2014 | A1 |
20140282227 | Nixon et al. | Sep 2014 | A1 |
20140282444 | Araya et al. | Sep 2014 | A1 |
20140282540 | Bonnet et al. | Sep 2014 | A1 |
20140289700 | Srinivasaraghavan et al. | Sep 2014 | A1 |
20140292765 | Maruyama et al. | Oct 2014 | A1 |
20140297611 | Abbour et al. | Oct 2014 | A1 |
20140317084 | Chaudhry et al. | Oct 2014 | A1 |
20140321280 | Evans | Oct 2014 | A1 |
20140324821 | Meiyyappan et al. | Oct 2014 | A1 |
20140330700 | Studnitzer et al. | Nov 2014 | A1 |
20140330807 | Weyerhaeuser et al. | Nov 2014 | A1 |
20140344186 | Nadler | Nov 2014 | A1 |
20140344391 | Vamey et al. | Nov 2014 | A1 |
20140359574 | Beckwith et al. | Dec 2014 | A1 |
20140372482 | Martin et al. | Dec 2014 | A1 |
20140380051 | Edward et al. | Dec 2014 | A1 |
20150019516 | Wein et al. | Jan 2015 | A1 |
20150026155 | Martin | Jan 2015 | A1 |
20150032789 | Nguyen et al. | Jan 2015 | A1 |
20150067640 | Booker et al. | Mar 2015 | A1 |
20150074066 | Li et al. | Mar 2015 | A1 |
20150082218 | Affoneh et al. | Mar 2015 | A1 |
20150088894 | Czarlinska et al. | Mar 2015 | A1 |
20150095381 | Chen et al. | Apr 2015 | A1 |
20150120261 | Giannacopoulos et al. | Apr 2015 | A1 |
20150127599 | Schiebeler | May 2015 | A1 |
20150154262 | Yang et al. | Jun 2015 | A1 |
20150172117 | Dolinsky et al. | Jun 2015 | A1 |
20150188778 | Asayag et al. | Jul 2015 | A1 |
20150205588 | Bates et al. | Jul 2015 | A1 |
20150205589 | Daily | Jul 2015 | A1 |
20150254298 | Bourbonnais et al. | Sep 2015 | A1 |
20150304182 | Brodsky et al. | Oct 2015 | A1 |
20150317359 | Tran et al. | Nov 2015 | A1 |
20150356157 | Anderson | Dec 2015 | A1 |
20160026383 | Lee | Jan 2016 | A1 |
20160026442 | Chhaparia | Jan 2016 | A1 |
20160065670 | Kimmel et al. | Mar 2016 | A1 |
20160085772 | Vermeulen et al. | Mar 2016 | A1 |
20160092599 | Barsness et al. | Mar 2016 | A1 |
20160103897 | Nysewander et al. | Apr 2016 | A1 |
20160125018 | Tomoda et al. | May 2016 | A1 |
20160147748 | Florendo et al. | May 2016 | A1 |
20160171070 | Hrle et al. | Jun 2016 | A1 |
20160179754 | Borza | Jun 2016 | A1 |
20160253294 | Allen et al. | Sep 2016 | A1 |
20160316038 | Jolfaei | Oct 2016 | A1 |
20160335281 | Teodorescu et al. | Nov 2016 | A1 |
20160335304 | Teodorescu et al. | Nov 2016 | A1 |
20160335317 | Teodorescu et al. | Nov 2016 | A1 |
20160335323 | Teodorescu et al. | Nov 2016 | A1 |
20160335330 | Teodorescu et al. | Nov 2016 | A1 |
20160335361 | Teodorescu et al. | Nov 2016 | A1 |
20170032016 | Zinner et al. | Feb 2017 | A1 |
20170161514 | Dellinger et al. | Jun 2017 | A1 |
20170177677 | Wright et al. | Jun 2017 | A1 |
20170185385 | Kent et al. | Jun 2017 | A1 |
20170192910 | Wright et al. | Jul 2017 | A1 |
20170206229 | Caudy et al. | Jul 2017 | A1 |
20170206256 | Tsirogiannis et al. | Jul 2017 | A1 |
20170235794 | Wright et al. | Aug 2017 | A1 |
20170235798 | Wright et al. | Aug 2017 | A1 |
20170249350 | Wright et al. | Aug 2017 | A1 |
20170270150 | Wright et al. | Sep 2017 | A1 |
20170316046 | Caudy et al. | Nov 2017 | A1 |
20170329740 | Crawford | Nov 2017 | A1 |
20170357708 | Ramachandran et al. | Dec 2017 | A1 |
20170359415 | Venkatraman | Dec 2017 | A1 |
20180004796 | Kent et al. | Jan 2018 | A1 |
20180011891 | Wright et al. | Jan 2018 | A1 |
20180052879 | Wright | Feb 2018 | A1 |
20180137175 | Teodorescu et al. | May 2018 | A1 |
Number | Date | Country |
---|---|---|
2309462 | Dec 2000 | CA |
1406463 | Apr 2004 | EP |
1198769 | Jun 2008 | EP |
2199961 | Jun 2010 | EP |
2423816 | Feb 2012 | EP |
2743839 | Jun 2014 | EP |
2397906 | Aug 2004 | GB |
2421798 | Jun 2011 | RU |
2000000879 | Jan 2000 | WO |
2001079964 | Oct 2001 | WO |
2011120161 | Oct 2011 | WO |
2012136627 | Oct 2012 | WO |
2014026220 | Feb 2014 | WO |
2014143208 | Sep 2014 | WO |
2016183563 | Nov 2016 | WO |
Entry |
---|
Final Office Action dated Jun. 18, 2018, in U.S. Appl. No. 15/155,005. |
Final Office Action dated May 18, 2018, in U.S. Appl. No. 15/654,461. |
Non-final Office Action dated Apr. 12, 2018, in U.S. Appl. No. 15/154,997. |
Non-final Office Action dated Apr. 23, 2018, in U.S. Appl. No. 15/813,127. |
Non-final Office Action dated Apr. 5, 2018, in U.S. Appl. No. 15/154,984. |
Non-final Office Action dated Feb. 15, 2018, in U.S. Appl. No. 15/813,112. |
Non-final Office Action dated Jun. 29, 2018, in U.S. Appl. No. 15/154,974. |
Non-final Office Action dated Jun. 8, 2018, in U.S. Appl. 15/452,574. |
Non-final Office Action dated Mar. 20, 2018, in U.S. Appl. No. 15/155,006. |
Notice of Allowance dated Apr. 30, 2018, in U.S. Appl. No. 15/155,012. |
Notice of Allowance dated Feb. 26, 2018, in U.S. Appl. No. 15/428,145. |
Notice of Allowance dated Jul. 11, 2018, in U.S. Appl. No. 15/154,995. |
Notice of Allowance dated Mar. 1, 2018, in U.S. Appl. No. 15/464,314. |
Notice of Allowance dated May 4, 2018, in U.S. Appl. No. 15/897,547. |
Final Office Action dated Aug. 10, 2018, in U.S. Appl. No. 15/796,230. |
Final Office Action dated Aug. 2, 2018, in U.S. Appl. No. 15/154,996. |
Final Office Action dated Oct. 1, 2018, in U.S. Appl. No. 15/154,993. |
Non-final Office Action dated Aug. 10, 2018, in U.S. Appl. No. 16/004,578. |
Notice of Allowance dated Sep. 11, 2018, in U.S. Appl. No. 15/608,963. |
Maria Azbel, How too hide and group columns in Excel AbleBits (2014), https://www.ablebits.com/office-addins-blog/2014/08/06/excel-hide-columns/ (last visited Jan. 18, 2019). |
Mark Dodge & Craig Stinson, Microsoft Excel 2010 inside out (2011). |
Svetlana Cheusheve, Excel formulas for conditional formatting based on another cell AbleBits (2014), https://www.ablebits.com/office-addins-blog/2014/06/10/excel-conditional-formatting-formulas/comment-page-6/ (last visited Jan. 14, 2019). |
Hartle, Thom, Conditional Formatting in Excel using CQG's RTD Bate Function (2011), http://news.cqg.com/blogs/excel/l2011/05/conditional-formatting-excel-using-cqgs-rtd-bate-function (last visited Apr. 3, 2019). |
Posey, Brien, “How to Combine PowerShell Cmdlets”, Jun. 14, 2013 Redmond the Independent Voice of the Microsoft Community (Year: 2013). |
International Search Report and Written Opinion dated Aug. 18, 2016, in International Appln. No. PCT/US2016/032593 filed May 14, 2016. |
International Search Report and Written Opinion dated Aug. 18, 2016, in International Appln. No. PCT/US2016/032597 filed May 14, 2016. |
International Search Report and Written Opinion dated Aug. 18, 2016, in International Appln. No. PCT/US2016/032599 filed May 14, 2016. |
International Search Report and Written Opinion dated Aug. 18, 2016, in International Appln. No. PCT/US2016/032605 filed May 14, 2016. |
International Search Report and Written Opinion dated Aug. 25, 2016, in International Appln. No. PCT/US2016/032590 filed May 14, 2016. |
International Search Report and Written Opinion dated Aug. 25, 2016, in International Appln. No. PCT/US2016/032592 filed May 14, 2016. |
International Search Report and Written Opinion dated Aug. 4, 2016, in International Appln. No. PCT/US2016/032581 filed May 14, 2016. |
International Search Report and Written Opinion dated Jul. 28, 2016, in International Appln. No. PCT/US2016/032586 filed May 14, 2016. |
International Search Report and Written Opinion dated Jul. 28, 2016, in International Appln. No. PCT/US2016/032587 filed May 14, 2016. |
International Search Report and Written Opinion dated Jul. 28, 2016, in International Appln. No. PCT/US2016/032589 filed May 14, 2016. |
International Search Report and Written Opinion dated Sep. 1, 2016, in International Appln. No. PCT/US2016/032596 filed May 14, 2016. |
International Search Report and Written Opinion dated Sep. 1, 2016, in International Appln. No. PCT/US2016/032598 filed May 14, 2016. |
International Search Report and Written Opinion dated Sep. 1, 2016, in International Appln. No. PCT/US2016/032601 filed May 14, 2016. |
International Search Report and Written Opinion dated Sep. 1, 2016, in International Appln. No. PCT/US2016/032602 filed May 14, 2016. |
International Search Report and Written Opinion dated Sep. 1, 2016, in International Appln. No. PCT/US2016/032607 filed May 14, 2016. |
International Search Report and Written Opinion dated Sep. 15, 2016, in International Appln. No. PCT/US2016/032591 filed May 14, 2016. |
International Search Report and Written Opinion dated Sep. 15, 2016, in International Appln. No. PCT/US2016/032594 filed May 14, 2016. |
International Search Report and Written Opinion dated Sep. 15, 2016, in International Appln. No. PCT/US2016/032600 filed May 14, 2016. |
International Search Report and Written Opinion dated Sep. 29, 2016, in International Appln. No. PCT/US2016/032595 filed May 14, 2016. |
International Search Report and Written Opinion dated Sep. 29, 2016, in International Appln. No. PCT/US2016/032606 filed May 14, 2016. |
International Search Report and Written Opinion dated Sep. 8, 2016, in International Appln. No. PCT/US2016/032603 filed May 14, 2016. |
International Search Report and Written Opinion dated Sep. 8, 2016, in International Appln. No. PCT/US2016/032604 filed May 14, 2016. |
Jellema, Lucas. “Implementing Cell Highlighting in JSF-based Rich Enterprise Apps (Part 1)”, dated Nov. 2008. Retrieved from http://www.oracle.com/technetwork/articles/adf/jellema-adfcellhighlighting-087850.html (last accessed Jun. 16, 2016). |
Kramer, The Combining DAG: A Technique for Parallel Data Flow Analysis, IEEE Transactions on Parallel and Distributed Systems, vol. 5, No. 8, Aug. 1994, pp. 805-813. |
Lou, Yuan. “A Multi-Agent Decision Support System for Stock Trading”, IEEE Network, Jan./Feb. 2002. Retreived from http://www.reading.ac.uk/AcaDepts/si/sisweb13/ais/papers/journal12-A%20multi-agent%20Framework.pdf. |
Mallet, “Relational Database Support for Spatio-Temporal Data”, Technical Report TR 04-21, Sep. 2004, University of Alberta, Department of Computing Science. |
Mariyappan, Balakrishnan. “10 Useful Linux Bash_Completion Complete Command Examples (Bash Command Line Completion on Steroids)”, dated Dec. 2, 2013. Retrieved from http://www.thegeekstuff.com/2013/12/bash-completion-complete/ (last accessed Jun. 16, 2016). |
Murray, Derek G. et al. “Naiad: a timely dataflow system.” SOSP '13 Proceedings of the Twenty-Fourth ACM Symposium on Operating Systems Principles. pp. 439-455. Nov. 2013. |
Non-final Office Action dated Apr. 19, 2017, in U.S. Appl. No. 15/154,974. |
Non-final Office Action dated Aug. 12, 2016, in U.S. Appl. No. 15/155,001. |
Non-final Office Action dated Aug. 14, 2017, in U.S. Appl. No. 15/464,314. |
Non-final Office Action dated Aug. 16, 2016, in U.S. Appl. No. 15/154,993. |
Non-final Office Action dated Aug. 19, 2016, in U.S. Appl. No. 15/154,991. |
Non-final Office Action dated Aug. 25, 2016, in U.S. Appl. No. 15/154,980. |
Non-final Office Action dated Aug. 26, 2016, in U.S. Appl. No. 15/154,995. |
Non-final Office Action dated Aug. 8, 2016, in U.S. Appl. No. 15/154,983. |
Non-final Office Action dated Aug. 8, 2016, in U.S. Appl. No. 15/154,985. |
Non-final Office Action dated Dec. 13, 2017, in U.S. Appl. No. 15/608,963. |
Non-final Office Action dated Dec. 28, 2017, in U.S. Appl. No. 15/154,996. |
Non-final Office Action dated Dec. 28, 2017, in U.S. Appl. No. 15/796,230. |
Non-final Office Action dated Feb. 12, 2018, in U.S. Appl. No. 15/466,836. |
Non-final Office Action dated Feb. 8, 2017, in U.S. Appl. No. 15/154,997. |
Non-final Office Action dated Jan. 4, 2018, in U.S. Appl. No. 15/583,777. |
Non-final Office Action dated Jul. 27, 2017, in U.S. Appl. No. 15/154,995. |
Non-final Office Action dated Mar. 2, 2017, in U.S. Appl. No. 15/154,984. |
Non-final Office Action dated Nov. 15, 2017, in U.S. Appl. No. 15/654,461. |
Non-final Office Action dated Nov. 17, 2016, in U.S. Appl. No. 15/154,999. |
Non-final Office Action dated Nov. 21, 2017, in U.S. Appl. No. 15/155,005. |
Non-final Office Action dated Nov. 30, 2017, in U.S. Appl. No. 15/155,012. |
Non-final Office Action dated Oct. 13, 2016, in U.S. Appl. No. 15/155,009. |
Non-final Office Action dated Oct. 27, 2016, in U.S. Appl. No. 15/155,006. |
Non-final Office Action dated Oct. 5, 2017, in U.S. Appl. No. 15/428,145. |
Non-final Office Action dated Oct. 7, 2016, in U.S. Appl. No. 15/154,998. |
Non-final Office Action dated Sep. 1, 2016, in U.S. Appl. No. 15/154,979. |
Non-final Office Action dated Sep. 1, 2016, in U.S. Appl. No. 15/155,011. |
Non-final Office Action dated Sep. 1, 2016, in U.S. Appl. No. 15/155,012. |
Non-final Office Action dated Sep. 14, 2016, in U.S. Appl. No. 15/154,984. |
Non-final Office Action dated Sep. 16, 2016, in U.S. Appl. No. 15/154,988. |
Non-final Office Action dated Sep. 22, 2016, in U.S. Appl. No. 15/154,987. |
Non-final Office Action dated Sep. 26, 2016, in U.S. Appl. No. 15/155,005. |
Non-final Office Action dated Sep. 29, 2016, in U.S. Appl. No. 15/154,990. |
Non-final Office Action dated Sep. 8, 2016, in U.S. Appl. No. 15/154,975. |
Non-final Office Action dated Sep. 9, 2016, in U.S. Appl. No. 15/154,996. |
Non-final Office Action dated Sep. 9, 2016, in U.S. Appl. No. 15/155,010. |
Notice of Allowance dated Dec. 19, 2016, in U.S. Appl. No. 15/155,001. |
Notice of Allowance dated Dec. 22, 2016, in U.S. Appl. No. 15/155,011. |
Notice of Allowance dated Dec. 7, 2016, in U.S. Appl. No. 15/154,985. |
Notice of Allowance dated Feb. 1, 2017, in U.S. Appl. No. 15/154,988. |
Notice of Allowance dated Feb. 12, 2018, in U.S. Appl. No. 15/813,142. |
Notice of Allowance dated Feb. 14, 2017, in U.S. Appl. No. 15/154,979. |
Notice of Allowance dated Feb. 28, 2017, in U.S. Appl. No. 15/154,990. |
Notice of Allowance dated Jan. 30, 2017, in U.S. Appl. No. 15/154,987. |
Notice of Allowance dated Jul. 28, 2017, in U.S. Appl. No. 15/155,009. |
Notice of Allowance dated Jun. 19, 2017, in U.S. Appl. No. 15/154,980. |
Notice of Allowance dated Jun. 20, 2017, in U.S. Appl. No. 15/154,975. |
Notice of Allowance dated Mar. 2, 2017, in U.S. Appl. No. 15/154,998. |
Notice of Allowance dated Mar. 31, 2017, in U.S. Appl. No. 15/154,998. |
Notice of Allowance dated May 10, 2017, in U.S. Appl. No. 15/154,988. |
Notice of Allowance dated Nov. 17, 2016, in U.S. Appl. No. 15/154,991. |
Notice of Allowance dated Nov. 17, 2017, in U.S. Appl. No. 15/154,993. |
Notice of Allowance dated Nov. 21, 2016, in U.S. Appl. No. 15/154,983. |
Notice of Allowance dated Nov. 8, 2016, in U.S. Appl. No. 15/155,007. |
Notice of Allowance dated Oct. 11, 2016, in U.S. Appl. No. 15/155,007. |
Notice of Allowance dated Oct. 21, 2016, in U.S. Appl. No. 15/154,999. |
Notice of Allowance dated Oct. 6, 2017, in U.S. Appl. No. 15/610,162. |
Palpanas, Themistoklis et al. “Incremental Maintenance for Non-Distributive Aggregate Functions”, Proceedings of the 28th VLDB Conference, 2002. Retreived from http://www.vldb.org/conf/2002/S22P04.pdf. |
PowerShell Team, Intellisense in Windows PowerShell ISE 3.0, dated Jun. 12, 2012, Windows PowerShell Blog, pp. 1-6 Retrieved: https://biogs.msdn.microsoft.com/powershell/2012/06/12/intellisense-in-windows-powershell-ise-3-0/. |
Smith, Ian. “Guide to Using SQL: Computed and Automatic Columns.” Rdb Jornal, dated Sep. 2008, retrieved Aug. 15, 2016, retrieved from the Internet <URL: http://www.oracle.com/technetwork/products/rdb/automatic-columns-132042.pdf>. |
Sobell, Mark G. “A Practical Guide to Linux, Commands, Editors and Shell Programming.” Third Edition, dated Sep. 14, 2012. Retrieved from: http://techbus.safaribooksonline.com/book/operating-systems-and-server- administration/linux/9780133085129. |
Wes McKinney & PyData Development Team. “Pandas: powerful Python data analysis toolkit, Release 0.16.1” Dated May 11, 2015. Retrieved from: http://pandas.pydata.org/pandas-docs/version/0.16.1/index.html. |
Wes McKinney & PyData Development Team. “Pandas: powerful Python data analysis toolkit, Release 0.18.1” Dated May 3, 2016. Retrieved from: http://pandas.pydata.org/pandas-docs/version/0.18.1/index.html. |
Wu, Buwen et al. “Scalable SPARQL Querying using Path Partitioning”, 31st IEEE International Conference on Data Engineering (ICDE 2015), Seoul, Korea, Apr. 13-17, 2015. Retreived from http://imada.sdu.dk/˜zhou/papers/icde2015.pdf. |
“About Entering Commands in the Command Window”, dated Dec. 16, 2015. Retrieved from https://knowledge.autodesk.com/support/autocad/learn-explore/caas/CloudHelp/cloudhelp/2016/ENU/AutoCAD-Core/files/GUID-BB0C3E79-66AF-4557-9140-D31B4CF3C9CF-htm.html (last accessed Jun. 16, 2016). |
“Change Data Capture”, Oracle Database Online Documentation 11g Release 1 (11.1), dated Apr. 5, 2016. Retreived from https://web.archive.org/web/20160405032625/http://docs.oracle.com/cd/B28359_01/server.111/b28313/cdc.htm. |
“Chapter 24. Query access plans”, Tuning Database Performance, DB2 Version 9.5 for Linux, UNIX, and Windows, pp. 301-462, dated Dec. 2010. Retreived from http://public.dhe.ibm.com/ps/products/db2/info/vr95/pdf/en_US/DB2PerfTuneTroubleshoot-db2d3e953.pdf. |
“GNU Emacs Manual”, dated Apr. 15, 2016, pp. 43-47. Retrieved from https://web.archive.org/web/20160415175915/http://www.gnu.org/software/emacs/manual/html_mono/emacs.html. |
“Google Protocol RPC Library Overview”, dated Apr. 27, 2016. Retrieved from https://cloud.google.com/appengine/docs/python/tools/protorpc/ (last accessed Jun. 16, 2016). |
“IBM—What is HBase?”, dated Sep. 6, 2015. Retrieved from https://web.archive.org/web/20150906022050/http://www-01.ibm.com/software/data/infosphere/hadoop/hbase/. |
“IBM Informix TimeSeries data management”, dated Jan. 18, 2016. Retrieved from https://web.archive.org/web/20160118072141/http://www-01.ibm.com/software/data/informix/timeseries/. |
“IBM InfoSphere BigInsights 3.0.0—Importing data from and exporting data to DB2 by using Sqoop”, dated Jan. 15, 2015. Retrieved from https://web.archive.org/web/20150115034058/http://www-01.ibm.com/support/knowledgecenter/SSPT3X_3.0.0/com.ibm.swg.im.infosphere.biginsights.import.doc/doc/data_warehouse_sqoop.html. |
“Maximize Data Value with Very Large Database Management by SAP Sybase IQ”, dated 2013. Retrieved from http://www.sap.com/bin/sapcom/en_us/downloadasset.2013-06-jun-11-11.maximize-data-value-with-very-large-database-management-by-sap-sybase-iq-pdf.html. |
“Microsoft Azure—Managing Access Control Lists (ACLs) for Endpoints by using PowerShell”, dated Nov. 12, 2014. Retrieved from https://web.archive.org/web/20150110170715/http://msdn.microsoft.com/en-us/library/azure/dn376543.aspx. |
“Oracle Big Data Appliance—Perfect Balance Java API”, dated Sep. 20, 2015. Retrieved from https://web.archive.org/web/20131220040005/http://docs.oracle.com/cd/E41604_01/doc.22/e41667/toc.htm. |
“Oracle Big Data Appliance—X5-2”, dated Sep. 6, 2015. Retrieved from https://web.archive.org/web/20150906185409/http://www.oracle.com/technetwork/database/bigdata-appliance/overview/bigdataappliance-datasheet-1883358.pdf. |
“Oracle Big Data Appliance Software User's Guide”, dated Feb. 2015. Retrieved from https://docs.oracle.com/cd/E55905_01/doc.40/e55814.pdf. |
“SAP HANA Administration Guide”, dated Mar. 29, 2016, pp. 290-294. Retrieved from https://web.archive.org/web/20160417053656/http://help.sap.com/hana/SAP_HANA_Administration_Guide_en.pdf. |
“Sophia Database—Architecture”, dated Jan. 18, 2016. Retrieved from https://web.archive.org/web/20160118052919/http://sphia.org/architecture.html. |
“Tracking Data Changes”, SQL Server 2008 R2, dated Sep. 22, 2015. Retreived from https://web.archive.org/web/20150922000614/https://technet.microsoft.com/en-us/library/bb933994(v=sql.105).aspx. |
“Use Formula AutoComplete”, dated 2010. Retrieved from https://support.office.com/en-us/article/Use-Formula-AutoComplete-c7c46fa6-3a94-4150-a2f7-34140c1ee4d9 (last accessed Jun. 16, 2016). |
Adelfio et al. “Schema Extraction for Tabular Data on the Web”, Proceedings of the VLDB Endowment, vol. 6, No. 6. Apr. 2013. Retrieved from http://www.cs.umd.edu/˜hjs/pubs/spreadsheets-vldb13.pdf. |
Advisory Action dated Apr. 19, 2017, in U.S. Appl. No. 15/154,999. |
Advisory Action dated Apr. 20, 2017, in U.S. Appl. No. 15/154,980. |
Advisory Action dated Apr. 6, 2017, in U.S. Appl. No. 15/154,995. |
Advisory Action dated Dec. 21, 2017, in U.S. Appl. No. 15/154,984. |
Advisory Action dated Mar. 31, 2017, in U.S. Appl. No. 15/154,996. |
Advisory Action dated May 3, 2017, in U.S. Appl. No. 15/154,993. |
Borror, Jefferey A. “Q for Mortals 2.0”, dated Nov. 1, 2011. Retreived from http://code.kx.com/wiki/JB:QforMortals2/contents. |
Breitbart, Update Propagation Protocols for Replicated Databases, SIGMOD '99 Philadelphia PA, 1999, pp. 97-108. |
Cheusheva, Svetlana. “How to change the row color based on a cell's value in Excel”, dated Oct. 29, 2013. Retrieved from https://www.ablebits.com/office-addins-blog/2013/10/29/excel-change-row-background-color/ (last accessed Jun. 16, 2016). |
Corrected Notice of Allowability dated Aug. 9, 2017, in U.S. Appl. No. 15/154,980. |
Corrected Notice of Allowability dated Jul. 31, 2017, in U.S. Appl. No. 15/154,999. |
Corrected Notice of Allowability dated Mar. 10, 2017, in U.S. Appl. No. 15/154,979. |
Corrected Notice of Allowability dated Oct. 26, 2017, in U.S. Appl. No. 15/610,162. |
Decision on Pre-Appeal Conference Request mailed Nov. 20, 2017, in U.S. Appl. No. 15/154,997. |
Ex Parte Quayle Action mailed Aug. 8, 2016, in U.S. Appl. No. 15/154,999. |
Final Office Action dated Apr. 10, 2017, in U.S. Appl. No. 15/155,006. |
Final Office Action dated Dec. 19, 2016, in U.S. Appl. No. 15/154,995. |
Final Office Action dated Dec. 29, 2017, in U.S. Appl. No. 15/154,974. |
Final Office Action dated Feb. 24, 2017, in U.S. Appl. No. 15/154,993. |
Final Office Action dated Jan. 27, 2017, in U.S. Appl. No. 15/154,980. |
Final Office Action dated Jan. 31, 2017, in U.S. Appl. No. 15/154,996. |
Final Office Action dated Jul. 27, 2017, in U.S. Appl. No. 15/154,993. |
Final Office Action dated Jun. 23, 2017, in U.S. Appl. No. 15/154,997. |
sinal Office Action dated Mar. 1, 2017, in U.S. Appl. No. 15/154,975. |
Final Office Action dated Mar. 13, 2017, in U.S. Appl. No. 15/155,012. |
Final Office Action dated Mar. 31, 2017, in U.S. Appl. No. 15/155,005. |
Final Office Action dated May 15, 2017, in U.S. Appl. No. 15/155,010. |
Final Office Action dated May 4, 2017, in U.S. Appl. No. 15/155,009. |
Gai, Lei et al. “An Efficient Summary Graph Driven Method for RDF Query Processing”, dated Oct. 27, 2015. Retreived from http://arxiv.org/pdf/1510.07749.pdf. |
International Search Report and Written Opinion dated Aug. 18, 2016, in International Appln. No. PCT/US2016/032582 filed May 14, 2016. |
International Search Report and Written Opinion dated Aug. 18, 2016, in International Appln. No. PCT/US2016/032584 filed May 14, 2016. |
International Search Report and Written Opinion dated Aug. 18, 2016, in International Appln. No. PCT/US2016/032588 filed May 14, 2016. |
Number | Date | Country | |
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62549908 | Aug 2017 | US |