A multidimensional data cube at a server may store values and functions. The functions may use values stored in the data cube as inputs to generate results. A client application may retrieve values stored at a server in a multidimensional data cube to be updated and viewed locally at the client. Instead of evaluating functions at the server and transmitting the results to the client, the functions themselves may be translated into equivalent functions that can be evaluated in real time at the client. As inputs to the functions are a changed at the client, the function results can be updated at the client without requiring back-and-forth transmissions to the server or additional queries to the data cube.

BACKGROUND

Databases may be enabled to analyze multidimensional data interactively from multiple perspectives. A multidimensional databases may commonly be referred to as a multidimensional data “cube.” Multidimensional cubes may be defined by dimensions that represent hierarchical groups of member data organized as cross-sectional groups that can be accessed by users for any of the hierarchical dimensions that are of interest. These dimensions may be hierarchical representations of business descriptors used in an organization. Queries to the database may select any point in the various dimensional hierarchy to retrieve a value at the intersection of those dimensions. Users may drill up, drill down, or pivot between dimensions to form new cross-sections and provide different perspectives for data analysis.

In modern cloud computing infrastructures, multidimensional data cubes may be maintained by a cloud service provider. Queries to the data cube may be executed at the server to retrieve values at the intersecting dimensions. Values retrieved from the data cube may then be transmitted to a client system where a client application may provide an interactive display for the retrieved values. Client applications may provide a two-dimensional display of data across various dimensions from the data cube. Users may provide updated values through the client application that can be transmitted to the server and used to update corresponding values in the multidimensional data cube.

In addition to providing access to values stored in the data cube, client applications may also retrieve the results of functions stored in the data cube. These functions may be executed using values queried from the data cube to generate results. The server may execute these functions and send the results to the client application for display. Updating these function results requires the client application to send updated values back to the server, where the new values can be updated and the function can be re-executed at the server. The new function results may then be transmitted back to the client application to update the display.

BRIEF SUMMARY

Instead of requiring functions to be reevaluated by the multidimensional data cube when the input values are changed by a client application, the embodiments described herein allow for client-side two-dimensional (2D) rendering of server-side multidimensional data, including real-time evaluation of functions. A multidimensional data cube at a server may store values and functions. The functions may use values stored in the data cube as inputs to generate results. A client application may retrieve values stored at a server in a multidimensional data cube to be updated and viewed locally at the client. Instead of evaluating functions at the server and transmitting the results to the client, the functions themselves may be translated into equivalent functions that can be evaluated in real time at the client. As inputs to the functions are a changed at the client, the function results can be updated at the client without requiring back-and-forth transmissions to the server or additional queries to the data cube.

For example, a location in the data cube may store a numerical value (e.g., “4.15”). A function may retrieve this numerical value from the data cube and perform a mathematical or processing operation on the value to generate a result. Functions may be used to generate average values, aggregated values, rolled-up values, value distributions, and/or any other mathematical or statistical function using the data in the data cube. When the client application requests numerical values for display, these values may simply be sent to the client application for display, and updates can be received through the client application and transmitted back to the server. However, formulas are typically evaluated at the server, and the results are then sent to the client application. For example, an average value for weekly numbers may be calculated at the server, and that average value may be sent to the application at the client system. If the numerical value is edited by a user at the client application, the result of the function transmitted to the client application may no longer be up-to-date. To update the function result at the client application, the updated numerical value is first transmitted back to the server where the corresponding location in the multidimensional data cube is updated with the updated numerical value. The function may then be re-evaluated at the server, and the new result may be transmitted back to the client application for display.

The embodiments described herein translate the function from the data cube into a function that can be executed locally at the client application. The data cube inputs used by the function may then be translated into cell addresses used by the client application. Value inputs for the function that are not updatable by the client application can be copied into the function at the client application. When the numerical value is updated at the client application, the function result displayed in the client application can be updated immediately by performing a local calculation at the client application. By translating the function such that it is executable at the client application and evaluating the function in real time, this effectively eliminates multiple queries to the data cube and reduces the number of transmissions back-and-forth between the client system and the server.

DETAILED DESCRIPTION

Described herein are embodiments for providing client-side, two-dimensional (2D) rendering of server-side multidimensional data. A multidimensional data cube at a server may store values and functions. The functions may use values stored in the data cube as inputs to generate results. A client application may retrieve values stored at a server in a multidimensional data cube to be updated and viewed locally at the client. Instead of evaluating functions at the server and transmitting the results to the client, the functions themselves may be translated into equivalent functions that can be evaluated in real time at the client. As inputs to the functions are changed at the client, the function results may be updated at the client without requiring back-and-forth transmissions to the server or additional queries to the data cube.

FIG.1illustrates a computing architecture with a server-based data cube that is accessible through a client-based application, according to some embodiments. The architecture may include a cloud computing system110that is made available by a cloud service provider. The cloud computing system110may provide hardware and/or software to tenants that subscribe to the cloud computing system110as described below in relation toFIG.8. The cloud computing system110may provide different types of services, including Infrastructure as a Service (IaaS), Database as a Service (DBaaS), Platform as a Service (PaaS), Software as a Service (SaaS), and/or other “as a service” products offered by the cloud computing system110.

One of the services offered by the cloud computing system110may include data storage and/or analytics. Data storage may include many different types of databases, disk arrays, redundancies, security regimes, and/or other features. In some embodiments, the cloud computing system110may provide a multidimensional data cube102. The multidimensional data cube102may also be referred to herein as a “hypercube,” a “data cube” or simply a “cube.” The data cube102may implement a Cloud Online Analytical Processing (COLAP) database that allows users to analyze multidimensional data interactively from multiple perspectives. The data cube102may provide features such as consolidation (roll-up), drill-down, and/or slicing along different data dimensions. Thus, the data cube102may also be referred to as an OLAP cube or a COLAP cube.

Each dimension104in the data cube102may have a label or metadata associated with that dimension. These labels may correspond to business functions or other business terminology (e.g., time, date, sales, location, product type, etc.) that may be customized for each specific user or tenant of the cloud computing system110.FIG.1illustrates the data cube102having at least three dimensions (e.g., dimensions104-1,104-2, . . .104-n) by way of example. Data cubes in practice may have many more dimensions than can be clearly depicted in a figure, therefore the depiction of a three-dimensional cube inFIG.1is not meant to be limiting. Although the term “cube” traditionally refers to a three-dimensional object, the term “cube” in this area of technology is generally understood to include any number of dimensions greater than two dimensions.

Specific locations or groups of locations may be addressed in the data cube102by providing dimension values (e.g., a specific time, a specific location, etc.) and retrieving all values in the resulting vector space from the data cube102. Instead of using traditional database queries, a data cube102may use multidimensional expressions that may be evaluated at the cube to return or calculate values. For example, the ESSBASE® database may use the MDX data manipulation language as a query language for multidimensional databases. More generally, formulas may be evaluated to return two-dimensional grids of information from the data cube102.

Many different types of data may be stored in the data cube102. For example, simple values may be stored at dimensional intersections in the data cube102, such as numerical values, character strings, Boolean values, and other basic value types. As used herein, any data type stored in a location in the data cube102that does not rely on values stored in other locations to calculate their values may be referred to herein as “values.” Values may be contrasted with “functions,” which may retrieve values from other locations in the data cube102and perform calculations using those values to generate a result. An example of a function may include a function that calculates an average value for a plurality of values along a certain dimension in the data cube102. In another example, a function may calculate an average number of items used per day during a particular week by retrieving a plurality of values from locations that store daily numbers of items used during that particular week. The function may retrieve these values and calculate an average value represented by a location in the data cube. Formulas may be used to calculate values, perform distributions, and/or perform other calculations involving data in the data cube102.

Generally, functions use syntax and query languages that are specific to the data cube102. These functions are typically executed at the server of the cloud computing system110. For example, the query language may provide a function106such as @AVGRANGE that returns an average value of a specified member across a specified range in the data cube102. The function may be evaluated at the data cube102to retrieve values along the specified range for the specified member and calculate an average value. The function syntax may be specific to the type of data cube102being used, and thus the function106may not be executable in other computing environments outside of the context of the data cube102. Therefore, if a computing system outside of the context of the data cube102requests the result of the function106, the function106may first be evaluated at the data cube102, and the result of the function106may then be transmitted to the requesting system.

In some embodiments, client systems may run client applications to provide a client-side interface to the data cube102.FIG.1illustrates an example of a client application120that may run on a client system. The client application102may be a browser-based application that displays a web form with values retrieved from the data cube102. Alternatively, the client application102may include plug-ins for any data-viewing application, such as Microsoft Excel®. The client application102may operate on a different computing system that is remotely located away from the cloud computing system110. For example, the data cube102may be hosted on a cloud platform, such as the Oracle Cloud Infrastructure, and the client application120may operate on a desktop or laptop computer at a customer's facility. Thus, the client system and the cloud computing system110may be owned and/or operated by different entities.

In order to display values from the data cube102at the client application120, the client application may request data to be queried from the data cube102. For example, the client application120may request value122that includes a simple numerical value (e.g., 354.56), as well as value112that includes another simple numerical value (e.g., 21). These values may be placed in a 2D display that is rendered locally at the client application120. By way of example, this 2D display is represented as a grid in the client application120ofFIG.1. The grid may be organized into individual cells or other locations that may be associated with cell addresses. For example, a cell address may be represented by a combination of a numerical row identifier and an alphabetic column identifier (e.g., cell A3). Just as the queries to the specific dimensional intersections in the data cube102need not have meaning in the context of the client application120, the cell addresses in the client application120need not have meaning in the context of the data cube102. The row/column cell addresses described above are provided only by way of example. Any other type of identifier may be used as a cell address.

In order to populate the grid, the client application120may submit a request to the cloud computing system110. Data cube102may then execute one or more queries to retrieve the value specified in the grid, such as value108and/or value112. These values may then be transmitted to the client application120and used to populate cells in the grid. For example, a first value108from a first location in the data cube102may be used to populate a cell122in the client application120. Similarly, another value112may be used to populate a cell124in the client application120. These cells122,124may be designated as input cells by the client application120. This may allow a user or other client system to make changes or updates to the values in the cells122,124. Changes to the values displayed in these cells122,124may be maintained locally at the client application122. This allows the user to experiment with changes to these local values before being committed to the data cube102. When a user elects to commit changes to these values, such as at the end of a computing session, the client application120may transmit the updated values back to the data cube102. The data cube102may then execute routines/queries to store the updated values into the corresponding locations in the data cube102.

When functions, such as function106, are used by the client application120, some embodiments transmit a result of the function106rather than transmitting the syntax of the function106itself. For example, the function106may be evaluated at the data cube102to calculate an average value for a one-week interval by retrieving daily totals from the data cube102and calculating an average total. The resulting average value114calculated by the function106may then be transmitted as a numerical value to the client application120. The client application120may display the value114in a cell126that is designated as something other than an input cell. For example, the cell126may be designated as an output-only or read-only cell that prevents the user from making permanent changes to the value in the cell126.

In order to update the result of the function106stored in the cell126at the client application, the function106may need to be reevaluated at the data cube102. For example, one of the values used to calculate the result of the function106may be stored in cell128at the client application120. If the user makes a change to the value stored in cell128(e.g., changing the 2 to a 3), the value in cell126may not be updated immediately. Instead, the client application120may transmit the updated value from cell128back to the data cube102. The data cube102may then commit the changed value back to the corresponding location in the data cube102. The data cube102may then evaluate the function106to generate a new result value for a corresponding location in the data cube102. That result value may then be transmitted back to the client application120for display in the read-only cell126. This process may require multiple back-and-forth transmissions between the client application120and the cloud computing system110, which decreases the available network bandwidth at both computing systems. This process may also require multiple queries to be evaluated at the data cube102, which may increase the load on the data cube102and may decrease its availability and responsiveness. Furthermore, the results may not be available in real time at the client application120, as the user needs to wait until an updated value can be received from the data cube102for cell126. Users may also need to commit values entered in at the client application122the data cube102before the function results can be displayed. Rolling back committed data is a difficult process that should be avoided, and thus users may be left with no way to see the effects of changing values at the client application120without committing data to the data cube102.

The embodiments described herein solve these and other technical problems to improve the functioning of the client application120, the cloud computing system110, and/or the data cube102. Specifically, as described below, these embodiments translate a version of the function102that may be evaluated at the client application120. This allows the client application120to display results of the function in the cell126in real time without an appreciable delay for the user. As the user enters new values into cell128, these values may be immediately evaluated by the function to update the value in cell126. This improves the functioning of the computing systems by eliminating the back-and-forth transmissions between the client application120and the data cube102each time values are changed that are used as inputs to the function106. This also provides a more responsive client application120as results can be displayed in real-time. This also improves the functioning of the data cube102by reducing the number of queries or transactions that need to be evaluated at the data cube102. Instead of committing values after every change of the client application, final values may be committed at the end of the computing session from the client application120. This reduces the number of rollbacks that may need to be performed at the data cube102, and improves the availability of the data cube102.

FIG.2illustrates a computing architecture that translates functions in the data cube domain into new functions that can be evaluated in the client application, according to some embodiments. The cloud computing system110may include a function translator202that receives the function106. For example, when a request is made by the client application120to display a result of the function106, the function106may be passed to the function translator202instead of evaluating the function106and sending the resulting value to the client application120. The function translator202may be configured to translate the function106from syntax that is executable on the data cube102into syntax that is executable by the client application120. The input function to the function translator202may be generically referred to as a “first function,” while the output function from the function translator202may generically be referred to as a “second function.” The terms first/second are used only to distinguish one function from another function. These terms are not meant to imply order, precedence, importance, or any other distinguishing feature.

To translate the function106into syntax that is executable by the client application120, some embodiments may use a data structure that stores mappings between functions that are executable on the data cube102and functions that are executable by the client application120. This data structure, such as a lookup table, a hash table, an index, a key-value store, and/or any other type of data structure, may store syntax such as function names and parameter lists that are executable by the client application120. The data structure may be indexed using the function names and/or parameter lists from the data cube102to return corresponding function names and parameter lists that are executable in the client application120. For example, the @AVGRANGE( ) function name may be submitted to the data structure to retrieve the corresponding AVE( ) function name from the data structure. Overloaded functions with multiple parameter lists may also be further matched by matching the parameter lists.

In some embodiments, determining a corresponding function name at the client application120may be done automatically. For example, the cloud computing system110may retrieve a list of function names from the client application120. The list of function names may then be matched to corresponding function names at the data cube102. For example, fuzzy string matching algorithms may be used to find function names that are substantially similar or within a threshold distance of the input function names. Alternatively or additionally, metadata or comments in function specifications may be used to identify matching function names. For example, metadata tags may be used to indicate compatibility with function names in other languages or another computing platforms. The cloud computing system110and/or the client application120may parse the metadata for functions executable at the data cube102and/or at the client application120to identify compatible functions between the two. This process may then populate the data structure using matches as they are identified. Some embodiments may also allow an administrator to review the mapping between function names and make adjustments as needed.

As described above, the function106may include references to other locations in the data cube102for values that are used by the calculations performed by the function106. A reference to a location in the data cube may include a dimension or set of dimensions that are retrieved by the function106. The reference may include a name or other identifier for a specific location in the data cube102. The reference may also include another function that retrieves specified values from the data cube102. As used herein, a reference to a location in the data cube102may include any syntax that may be used to retrieve a value from that location in the data cube102. The value retrieved from a location in the data cube may be used as a parameter in the function106or as any other input element to the function106.

In addition to translating the first function from the data cube102into a second function for the client application120, some embodiments may also translate references to locations in the data cube102into cell addresses for the corresponding cells holding values in the client application120. In some cases, values that are displayed and/or editable at the client application120may also be used as parameters or inputs to the function204. At the data cube102, the function106would retrieve or calculate those values from the data cube102before evaluating the function106. At the client application120, the syntax of the function204may be changed to reference the cells in the client application120instead of querying the locations in the data cube102.

The function translator202may identify cells addresses where the values for the parameters of the function204are located in the client application120. The client application120may communicate with the cloud computing system110to associate values in the data cube102with corresponding cell addresses in the client application120. For example, the value112from a particular memory location in the data cube102may be associated with cell124having a particular cell address (e.g., “B2”). The function translator202may then determine whether any parameters in the function204also reference this same memory location in the data cube102. If any such references are found, they may be replaced with the cell address for the corresponding value in the client application120.

FIG.3illustrates how the translated references to cell addresses in the client application allow functions to be evaluated in real time locally at the client application to reflect immediate changes in the input values, according to some embodiments. In this example, the function in cell126may reference a value in cell320of the client application120. As described above, the function syntax may be translated such that a previous reference to a memory location in the data cube102has been replaced with a reference to a cell address for cell320.

As described above, the client application120may be configured to allow real-time, interactive manipulation of values in the input cells. Cell320may be defined as an input cell, as it is populated with a stand-alone value rather than a value that depends on other cell values, such as a function. Thus, the value in cell320may be changed by virtue of a user input from “2” to “3.” This new value304may be transmitted back to the data cube102to be committed to the data cube. However, this operation need not take place immediately when the value is changed in the cell320. Instead, the client application120may update other cell values that are dependent on the cell320and allow the user to see the effects of this change on other dependent cells. This allows the user to test various values before committing any changes back to the data cube120.

In this example, the function in cell126may be reevaluated when the value in cell320is changed. Instead of committing the value304to the data cube102, querying that value, reevaluating the function, and returning that value to the function, the function in cell126may instead receive the value from cell320within the client application120. This allows immediate updates to values and other changes to be propagated to functions and calculated/managed entirely within the client application120without need to commit data to or acquire new data from the data cube102.

FIG.4illustrates how values can be hardcoded into the second function sent to the client application when those values are not available in the client application, according to some embodiments. If a first function400includes references to other values stored in locations in the data cube102and/or calculated based on values from the data cube102, these values may be retrieved and copied into corresponding parameter locations in the function404that is executable at the client application120. In other words, these values can be retrieved and hard-coded into the syntax for the function204when the function204is sent to the client application120. This allows the client application120to evaluate the function204in real time without requiring additional queries to the data cube102to retrieve these values. Values may be hard-coded into the syntax of the function204when they are not also displayed or otherwise available in the client application120. This allows the client application120to handle values that are immediately available at the client application120, as well as values that are only available at the data cube102.

For example, the function400may include a reference to a value402that is stored in the data cube102, but which is not displayed by the client application120. Because of the relatively large amount of data stored in the data cube102, the client application120may retrieve only a small subset of the data stored in the data cube102. This may leave many values in the data cube102that are not accessible to the client application120during the current computing session without making additional queries to the data cube102. To make a value available to the function404in the client application120, the value402may be hard-coded into the syntax of the function404.

The value402may be stored as part of the function404in a cell424. However, other parameters or inputs to the function424may instead use references to cell addresses in the client application120as described above. This allows the client application120to simultaneously use static values that are not available in the client application120along with values that are dynamically changed in the client application120to evaluate functions in real time.

FIG.5illustrates how data may be committed back to the data cube102and/or updated from the data cube102as needed, according to some embodiments. As described above, changes to the values stored in cells in the client application120need not result in an immediate update or committing of data to the data cube102. Instead, a user may be allowed to experiment with different values and see their calculated results locally in the client application120before data is committed back to the data cube102. For example, a user may be provided with a control that allows an input to be received that indicates that changes made to values displayed in the client application120should be committed back to the data cube102. In another example, a user may indicate that they are done with the current computing session by, for example, closing the client application120or saving data in the client application120. These inputs may generate an indication to the cloud computing system110that the client application102has received changes for values in the data cube102. These new values, such as values406,408in cells420,422may be transmitted back to the cloud computing system110to be committed to the data cube102. These values406,408may be stored back to locations in the data cube102from which they were originally retrieved when the cells in the client application120were populated.

In some embodiments, users may be allowed to change the function syntax, parameters, and/or references in function cells in the client application120. For example, the user may be granted administrative privileges to select a different function and replace the current function called in the cell424. Alternatively or additionally, the user may change parameters to reference different cells in the client application120. For example, instead of referencing cell422, the syntax of the function in cell424may be changed to instead reference cell432by changing the cell address. When the data is committed in the client application120, the new syntax for the function in cell424may be sent back to the cloud computing system110. The same function translator described above may perform an inverse process that translates the function syntax and the cell references back into function syntax that is compatible with the data cube102and references to locations in the data cube102rather than cell addresses in the client application120. For example, the opposite process described above in relation toFIG.4may be carried out to perform this reverse translation.

In addition to committing data from the client application120, some embodiments may periodically refresh hard-coded values in the function syntax at the client application120. As described above, a value may be hard-coded into the function syntax when that value is not available as a cell reference in the client application120. However, it is possible that the value at the corresponding location in the data cube102may be updated after that value is hardcoded into the function syntax and sent to the client application120. In order to provide up-to-date information, the hard-coded values in functions at the client application120may be periodically updated with values queried from the data cube102. For example, these values may be refreshed periodically, such as every five minutes, every 15 minutes, every 20 minutes, every 30 minutes, and so forth. In another example, these values may be refreshed when triggered by events at the client application120or by events at the data cube102. When the data cube receives a new value for a memory location that was previously hardcoded into a function at the client application120, the data cube102may push the new value out to the client application120to be updated in the corresponding function syntax. Alternatively or additionally, the client application120may request refreshed values when a predetermined number of changes to the data have occurred in the client application120. This allows the data to be refreshed when a large number of changes have been made at the client application120. The client application120may also request refreshed values when an indication is generated that the changes in the client application120should be committed. For example, a value502may be refreshed from the data cube102when a user indicates they are ready to commit the data changes. The client application120may notify the user that a refresh is taking place and update the values, function evaluations, and displays in the client application120accordingly. This allows the user to see the data changes as accurately as possible before committing the changes.

Continuing with the terminology described above, a value stored at the data cube102that is not available at the client application120, and which is consequently hard-coded into the function syntax at the client application120may be referred to as a second value at “third” memory location. The terms “second/third” are used merely to distinguish these values in memory locations from other values and/or memory locations described herein.

FIG.6illustrates a flowchart600of a method for enabling real-time, client-side rendering of server-side multidimensional data, according to some embodiments. This method may be carried out at a server, and the server may be located at a cloud-computing system, such as the cloud-computing system110described above. The server may be provided by a cloud service provider, while the client system may be owned/operated by a customer or tenant of the cloud service provider. These systems may be separated logically, may use different computing hardware and/or software, may be owned and operated by different entities, and may be physically separated by large distances (e.g. greater than 1 mile) from each other.

The method may include accessing a multidimensional data cube at a server (602). The data cube may include a first location that stores a first value, such as a numerical value, string value, or any other data type. The data cube may also include a second location of stores a first function. The first function may include a reference to the first location as an input to the first function. For example, the first value may be used as a parameter or input for the function. In some instances, the function may also include a reference to a third location that stores a second value that is used as a parameter or input for the function. The data cube may be accessed as described above inFIGS.1-2and throughout this disclosure.

The method may also include translating the first function into a second function (604). The first function may be stored at the data cube and may be executable on the data cube at the server. In contrast, the second function may be executable by a client application at a client system. The function may be translated by selecting a function name from a library of functions available at the client application that performs a similar function to the first function at the data cube. A data structure may be used to associate functions at the data cube that are compatible with functions at the client application. Function translation may be carried out as described above inFIG.2and throughout this disclosure.

The method may further include translating the reference to the first location into a cell address for the first value in the client application for the second function (606). Translating the reference into a cell address may include identifying the cell address in the client application for a cell in which the first value is displayed by the client application. The method may then replace the reference to the first location in the second function with the cell address. The cell address may be allowed to be updated and viewed through the client application, whereas a cell in which the second function is stored need not be allowed to be updated through the client application in some instances. Translating references into cell addresses may be carried out as described above inFIGS.2-3and throughout this disclosure. Some references may be replaced with hard-coded values when those values are not displayed and updated through the client application as described above inFIGS.4-5and throughout this disclosure.

The method may also include sending the first value and the second value to the client application (608). The client application may include a browser, an app, a plug-in for a spreadsheet application, and so forth. For example, the client application may include a web form that displays current values from the data cube and receives inputs to update those current values.

It should be appreciated that the specific steps illustrated inFIG.6provide particular methods of enabling real-time, client-side rendering of server-side multidimensional data according to various embodiments. Other sequences of steps may also be performed according to alternative embodiments. For example, alternative embodiments may perform the steps outlined above in a different order. Moreover, the individual steps illustrated inFIG.6may include multiple sub-steps that may be performed in various sequences as appropriate to the individual step. Furthermore, additional steps may be added or removed depending on the particular applications. Many variations, modifications, and alternatives also fall within the scope of this disclosure.

Each of the methods described herein may be implemented by a computer system. Each step of these methods may be executed automatically by the computer system, and/or may be provided with inputs/outputs involving a user. For example, a user may provide inputs for each step in a method, and each of these inputs may be in response to a specific output requesting such an input, wherein the output is generated by the computer system. Each input may be received in response to a corresponding requesting output. Furthermore, inputs may be received from a user, from another computer system as a data stream, retrieved from a memory location, retrieved over a network, requested from a web service, and/or the like. Likewise, outputs may be provided to a user, to another computer system as a data stream, saved in a memory location, sent over a network, provided to a web service, and/or the like. In short, each step of the methods described herein may be performed by a computer system, and may involve any number of inputs, outputs, and/or requests to and from the computer system which may or may not involve a user. Those steps not involving a user may be said to be performed automatically by the computer system without human intervention. Therefore, it will be understood in light of this disclosure, that each step of each method described herein may be altered to include an input and output to and from a user, or may be done automatically by a computer system without human intervention where any determinations are made by a processor. Furthermore, some embodiments of each of the methods described herein may be implemented as a set of instructions stored on a tangible, non-transitory storage medium to form a tangible software product.

FIG.7depicts a simplified diagram of a distributed system700for implementing one of the embodiments. In the illustrated embodiment, distributed system700includes one or more client computing devices702,704,706, and708, which are configured to execute and operate a client application such as a web browser, proprietary client (e.g., Oracle Forms), or the like over one or more network(s)710. Server712may be communicatively coupled with remote client computing devices702,704,706, and708via network710.

In various embodiments, server712may be adapted to run one or more services or software applications provided by one or more of the components of the system. In some embodiments, these services may be offered as web-based or cloud services or under a Software as a Service (SaaS) model to the users of client computing devices702,704,706, and/or708. Users operating client computing devices702,704,706, and/or708may in turn utilize one or more client applications to interact with server712to utilize the services provided by these components.

In the configuration depicted in the figure, the software components718,720and722of system700are shown as being implemented on server712. In other embodiments, one or more of the components of system700and/or the services provided by these components may also be implemented by one or more of the client computing devices702,704,706, and/or708. Users operating the client computing devices may then utilize one or more client applications to use the services provided by these components. These components may be implemented in hardware, firmware, software, or combinations thereof. It should be appreciated that various different system configurations are possible, which may be different from distributed system700. The embodiment shown in the figure is thus one example of a distributed system for implementing an embodiment system and is not intended to be limiting.

Although exemplary distributed system700is shown with four client computing devices, any number of client computing devices may be supported. Other devices, such as devices with sensors, etc., may interact with server712.

Server712may be composed of one or more general purpose computers, specialized server computers (including, by way of example, PC (personal computer) servers, UNIX® servers, mid-range servers, mainframe computers, rack-mounted servers, etc.), server farms, server clusters, or any other appropriate arrangement and/or combination. In various embodiments, server712may be adapted to run one or more services or software applications described in the foregoing disclosure. For example, server712may correspond to a server for performing processing described above according to an embodiment of the present disclosure.

Distributed system700may also include one or more databases714and716. Databases714and716may reside in a variety of locations. By way of example, one or more of databases714and716may reside on a non-transitory storage medium local to (and/or resident in) server712. Alternatively, databases714and716may be remote from server712and in communication with server712via a network-based or dedicated connection. In one set of embodiments, databases714and716may reside in a storage-area network (SAN). Similarly, any necessary files for performing the functions attributed to server712may be stored locally on server712and/or remotely, as appropriate. In one set of embodiments, databases714and716may include relational databases, such as databases provided by Oracle, that are adapted to store, update, and retrieve data in response to SQL-formatted commands.

FIG.8is a simplified block diagram of one or more components of a system environment800by which services provided by one or more components of an embodiment system may be offered as cloud services, in accordance with an embodiment of the present disclosure. In the illustrated embodiment, system environment800includes one or more client computing devices804,806, and808that may be used by users to interact with a cloud infrastructure system802that provides cloud services. The client computing devices may be configured to operate a client application such as a web browser, a proprietary client application (e.g., Oracle Forms), or some other application, which may be used by a user of the client computing device to interact with cloud infrastructure system802to use services provided by cloud infrastructure system802.

It should be appreciated that cloud infrastructure system802depicted in the figure may have other components than those depicted. Further, the system shown in the figure is only one example of a cloud infrastructure system that may incorporate some embodiments. In some other embodiments, cloud infrastructure system802may have more or fewer components than shown in the figure, may combine two or more components, or may have a different configuration or arrangement of components.

Client computing devices804,806, and808may be devices similar to those described above for702,704,706, and708.

Although exemplary system environment800is shown with three client computing devices, any number of client computing devices may be supported. Other devices such as devices with sensors, etc. may interact with cloud infrastructure system802.

Network(s)810may facilitate communications and exchange of data between clients804,806, and808and cloud infrastructure system802. Each network may be any type of network that can support data communications using any of a variety of commercially-available protocols, including those described above for network(s)710.

Cloud infrastructure system802may comprise one or more computers and/or servers that may include those described above for server712.

In certain embodiments, cloud infrastructure system802may include a suite of applications, middleware, and database service offerings that are delivered to a customer in a self-service, subscription-based, elastically scalable, reliable, highly available, and secure manner. An example of such a cloud infrastructure system is the Oracle Public Cloud provided by the present assignee.

In various embodiments, cloud infrastructure system802may be adapted to automatically provision, manage and track a customer's subscription to services offered by cloud infrastructure system802. Cloud infrastructure system802may provide the cloud services via different deployment models. For example, services may be provided under a public cloud model in which cloud infrastructure system802is owned by an organization selling cloud services (e.g., owned by Oracle) and the services are made available to the general public or different industry enterprises. As another example, services may be provided under a private cloud model in which cloud infrastructure system802is operated solely for a single organization and may provide services for one or more entities within the organization. The cloud services may also be provided under a community cloud model in which cloud infrastructure system802and the services provided by cloud infrastructure system802are shared by several organizations in a related community. The cloud services may also be provided under a hybrid cloud model, which is a combination of two or more different models.

In certain embodiments, cloud infrastructure system802may also include infrastructure resources830for providing the resources used to provide various services to customers of the cloud infrastructure system. In one embodiment, infrastructure resources830may include pre-integrated and optimized combinations of hardware, such as servers, storage, and networking resources to execute the services provided by the PaaS platform and the SaaS platform.

In certain embodiments, a number of internal shared services832may be provided that are shared by different components or modules of cloud infrastructure system802and by the services provided by cloud infrastructure system802. These internal shared services may include, without limitation, a security and identity service, an integration service, an enterprise repository service, an enterprise manager service, a virus scanning and white list service, a high availability, backup and recovery service, service for enabling cloud support, an email service, a notification service, a file transfer service, and the like.

In certain embodiments, cloud infrastructure system802may provide comprehensive management of cloud services (e.g., SaaS, PaaS, and IaaS services) in the cloud infrastructure system. In one embodiment, cloud management functionality may include capabilities for provisioning, managing and tracking a customer's subscription received by cloud infrastructure system802, and the like.

In one embodiment, as depicted in the figure, cloud management functionality may be provided by one or more modules, such as an order management module820, an order orchestration module822, an order provisioning module824, an order management and monitoring module826, and an identity management module828. These modules may include or be provided using one or more computers and/or servers, which may be general purpose computers, specialized server computers, server farms, server clusters, or any other appropriate arrangement and/or combination.

In exemplary operation834, a customer using a client device, such as client device804,806or808, may interact with cloud infrastructure system802by requesting one or more services provided by cloud infrastructure system802and placing an order for a subscription for one or more services offered by cloud infrastructure system802. In certain embodiments, the customer may access a cloud User Interface (UI), cloud UI812, cloud UI814and/or cloud UI816and place a subscription order via these UIs. The order information received by cloud infrastructure system802in response to the customer placing an order may include information identifying the customer and one or more services offered by the cloud infrastructure system802that the customer intends to subscribe to.

After an order has been placed by the customer, the order information is received via the cloud UIs,812,814and/or816.

At operation836, the order is stored in order database818. Order database818can be one of several databases operated by cloud infrastructure system818and operated in conjunction with other system elements.

At operation838, the order information is forwarded to an order management module820. In some instances, order management module820may be configured to perform billing and accounting functions related to the order, such as verifying the order, and upon verification, booking the order.

At operation840, information regarding the order is communicated to an order orchestration module822. Order orchestration module822may utilize the order information to orchestrate the provisioning of services and resources for the order placed by the customer. In some instances, order orchestration module822may orchestrate the provisioning of resources to support the subscribed services using the services of order provisioning module824.

In certain embodiments, order orchestration module822enables the management of business processes associated with each order and applies business logic to determine whether an order should proceed to provisioning. At operation842, upon receiving an order for a new subscription, order orchestration module822sends a request to order provisioning module824to allocate resources and configure those resources needed to fulfill the subscription order. Order provisioning module824enables the allocation of resources for the services ordered by the customer. Order provisioning module824provides a level of abstraction between the cloud services provided by cloud infrastructure system800and the physical implementation layer that is used to provision the resources for providing the requested services. Order orchestration module822may thus be isolated from implementation details, such as whether or not services and resources are actually provisioned on the fly or pre-provisioned and only allocated/assigned upon request.

At operation844, once the services and resources are provisioned, a notification of the provided service may be sent to customers on client devices804,806and/or808by order provisioning module824of cloud infrastructure system802.

At operation846, the customer's subscription order may be managed and tracked by an order management and monitoring module826. In some instances, order management and monitoring module826may be configured to collect usage statistics for the services in the subscription order, such as the amount of storage used, the amount data transferred, the number of users, and the amount of system up time and system down time.

In certain embodiments, cloud infrastructure system800may include an identity management module828. Identity management module828may be configured to provide identity services, such as access management and authorization services in cloud infrastructure system800. In some embodiments, identity management module828may control information about customers who wish to utilize the services provided by cloud infrastructure system802. Such information can include information that authenticates the identities of such customers and information that describes which actions those customers are authorized to perform relative to various system resources (e.g., files, directories, applications, communication ports, memory segments, etc.) Identity management module828may also include the management of descriptive information about each customer and about how and by whom that descriptive information can be accessed and modified.

FIG.9illustrates an exemplary computer system900, in which various embodiments may be implemented. The system900may be used to implement any of the computer systems described above. As shown in the figure, computer system900includes a processing unit904that communicates with a number of peripheral subsystems via a bus subsystem902. These peripheral subsystems may include a processing acceleration unit906, an I/O subsystem908, a storage subsystem918and a communications subsystem924. Storage subsystem918includes tangible computer-readable storage media922and a system memory910.

Processing unit904, which can be implemented as one or more integrated circuits (e.g., a conventional microprocessor or microcontroller), controls the operation of computer system900. One or more processors may be included in processing unit904. These processors may include single core or multicore processors. In certain embodiments, processing unit904may be implemented as one or more independent processing units932and/or934with single or multicore processors included in each processing unit. In other embodiments, processing unit904may also be implemented as a quad-core processing unit formed by integrating two dual-core processors into a single chip.

In various embodiments, processing unit904can execute a variety of programs in response to program code and can maintain multiple concurrently executing programs or processes. At any given time, some or all of the program code to be executed can be resident in processor(s)904and/or in storage subsystem918. Through suitable programming, processor(s)904can provide various functionalities described above. Computer system900may additionally include a processing acceleration unit906, which can include a digital signal processor (DSP), a special-purpose processor, and/or the like.

Computer system900may comprise a storage subsystem918that comprises software elements, shown as being currently located within a system memory910. System memory910may store program instructions that are loadable and executable on processing unit904, as well as data generated during the execution of these programs.

Storage subsystem900may also include a computer-readable storage media reader920that can further be connected to computer-readable storage media922. Together and, optionally, in combination with system memory910, computer-readable storage media922may comprehensively represent remote, local, fixed, and/or removable storage devices plus storage media for temporarily and/or more permanently containing, storing, transmitting, and retrieving computer-readable information.

Communications subsystem924provides an interface to other computer systems and networks. Communications subsystem924serves as an interface for receiving data from and transmitting data to other systems from computer system900. For example, communications subsystem924may enable computer system900to connect to one or more devices via the Internet. In some embodiments communications subsystem924can include radio frequency (RF) transceiver components for accessing wireless voice and/or data networks (e.g., using cellular telephone technology, advanced data network technology, such as 3G, 4G or EDGE (enhanced data rates for global evolution), WiFi (IEEE 802.11 family standards, or other mobile communication technologies, or any combination thereof), global positioning system (GPS) receiver components, and/or other components. In some embodiments communications subsystem924can provide wired network connectivity (e.g., Ethernet) in addition to or instead of a wireless interface.

In some embodiments, communications subsystem924may also receive input communication in the form of structured and/or unstructured data feeds926, event streams928, event updates930, and the like on behalf of one or more users who may use computer system900.

Communications subsystem924may also be configured to output the structured and/or unstructured data feeds926, event streams928, event updates930, and the like to one or more databases that may be in communication with one or more streaming data source computers coupled to computer system900.

In the foregoing description, for the purposes of explanation, numerous specific details were set forth in order to provide a thorough understanding of various embodiments. It will be apparent, however, that some embodiments may be practiced without some of these specific details. In other instances, well-known structures and devices are shown in block diagram form.

The foregoing description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the foregoing description of various embodiments will provide an enabling disclosure for implementing at least one embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of some embodiments as set forth in the appended claims.

In the foregoing specification, features are described with reference to specific embodiments thereof, but it should be recognized that not all embodiments are limited thereto. Various features and aspects of some embodiments may be used individually or jointly. Further, embodiments can be utilized in any number of environments and applications beyond those described herein without departing from the broader spirit and scope of the specification. The specification and drawings are, accordingly, to be regarded as illustrative rather than restrictive.