Patent Publication Number: US-10320896-B2

Title: Intelligent mapping for an enterprise grid

Description:
FIELD OF THE INVENTION 
     The present invention relates generally to the field of grid computing and more particularly to efficiently allowing clients to access data from an enterprise grid. 
     BACKGROUND OF THE INVENTION 
     “Grid computing” refers to the concept that applications and resources can be connected in the form of a pervasive network fabric or grid, with grids being viewed as very much analogous to electrical or power grids—accessible everywhere and sharable by everyone. In the general sense, a grid may be defined as a bounded environment (i.e., a collection of networked applications, services, resources, which is treated as a whole and within which grid computing is undertaken). The scope of a grid could range from a small departmental network to a vast collection of resources and services running in multiple locations, spread across the world, and owned by many organizational groups, government bodies, enterprises, or academic institutions. 
     When exploring the impact of grids within enterprise data centers, the term “enterprise grid” can be used to capture the notion of a grid that is managed by a single entity or business. This is a very specific type of grid, in which there is a clear scope of control and responsibility for managing the grid to meet a specific set of business goals. The extent of an enterprise grid is defined in terms of organizational responsibility and not in terms of geography or asset ownership. Thus, an enterprise grid may span multiple locations or data centers. It may also include applications or services run on behalf of other organizations, such as in an outsourced environment. Enterprise grids must also support various types of workload (transactional, OLTP, batch, compute-intensive, and legacy) and a large, heterogeneous set of resources. This contrasts markedly with more traditional aggregation frameworks in the data center, such as high-availability clusters, load-balanced clusters, or compute-intensive clusters, which are typically focused on a specific application, or type of application, and which are usually deployed on a relatively homogeneous set of resources. 
     SUMMARY 
     Embodiments of the present invention include a method, computer program product, and system for accessing data from an enterprise grid. A first computer system receives a request from a client application of a second computer system to access a dataset within an enterprise grid, the dataset having a plurality of values that each correspond to a separate field of the dataset. The first computer system determines that a previous request to access the dataset has not been received from the client application of the second computer system and, in response, gathers the plurality of values from within the enterprise grid and sends the plurality of values to the second computer system. The first computer system identifies a subset of the plurality of values utilized by the client application and the field for each value in the subset of the plurality of values utilized by the client application. The first computer system receives a subsequent request from the client application of the second computer system for the dataset. In response to receiving the subsequent request, the first computer system sends to the second computer system, of the plurality of values in the dataset, only values corresponding to each identified field. 
    
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS 
         FIG. 1  is a functional block diagram illustrating a distributed data processing environment, in accordance with an embodiment of the present invention. 
         FIG. 2  is a flowchart depicting operational steps of an intelligent mapping program, on a proxy server computer within the data processing environment of  FIG. 1 , for filtering values returned to a client application, in accordance with an embodiment of the present invention. 
         FIG. 3  illustrates operational steps of a watcher program, inserted on a client device within the data processing environment of  FIG. 1 , in accordance with an embodiment of the present invention. 
         FIG. 4  depicts a block diagram of components of the proxy server computer executing the intelligent mapping program, in accordance with an embodiment of the present invention. 
     
    
    
     DETAILED DESCRIPTION 
     As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer-readable medium(s) having computer readable program code/instructions embodied thereon. 
     Any combination of computer-readable media may be utilized. Computer-readable media may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of a computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. 
     A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire. 
     Program code embodied on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing. 
     Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object-oriented programming language such as Java®, Smalltalk, C++ or the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The program code may execute entirely on a user&#39;s computer, partly on the user&#39;s computer, as a stand-alone software package, partly on the user&#39;s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user&#39;s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). 
     Aspects of the present invention are described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     These computer program instructions may also be stored in a computer-readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer-readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks. 
     The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     The present invention will now be described in detail with reference to the Figures.  FIG. 1  is a functional block diagram illustrating a distributed data processing environment, generally designated  100 , in accordance with one embodiment of the present invention. Distributed data processing environment  100  includes proxy server computer  102  and client devices  104 ,  106 , and  108 , all interconnected over network  110 . Proxy server computer  102  communicates with, and may be considered a part of, enterprise grid  112 . 
     Enterprise grid  112  is a collection of resources including computing systems and components, which are interconnected through various connections and protocols and are at least nominally controlled by a single group or entity. The location of individual resources of enterprise grid  112  may be geographically diverse. Enterprise grid  112  may be utilized as a data grid, such as an in-memory data grid (IMDG), by enabling the storing of information in memory, and using redundancy—by keeping copies of that information synchronized across multiple servers—in order to ensure the resiliency of the system and the availability of the data in the event of a server failure. An IMDG provides a set of interconnected processes (typically Java®) that hold data in memory over multiple resources, enabling faster data access and reducing stress on the back-end (physical) databases. Data may be accessed in enterprise grid  112  through a key-value associative array or data structure where identifying values (keys) are mapped to associated values (e.g., using a hash table or hash map). 
     In the depicted environment, proxy server computer  102  acts as a conduit between enterprise grid  112  and client computers, such as client devices  104 ,  106 , and  108 . Proxy server computer  102  may receive queries from client computers, locate the required information from resources in enterprise grid  112  (for example, by computing a hash of a received key to determine the appropriate server), and sends values associated with the query back to the client computer. In various embodiments of the present invention, proxy server computer  102  can be a laptop computer, tablet computer, netbook computer, personal computer (PC), a desktop computer, a personal digital assistant (PDA), a smart phone, or any programmable electronic device capable of communicating with client devices  104 ,  106 , and  108  via network  110  and with various components and devices within enterprise grid  112 . Proxy server computer  102  includes intelligent mapping program  114  for filtering data to be returned to a requesting client application from enterprise grid  112 . Proxy server computer  102  can store mapping tables and filtering preferences in computer storage  116 . 
     Embodiments of the present invention recognize that due to different data requirements, data structures, and data object requirements of individual applications (developed and owned by different teams and units), accessing data from an enterprise grid is most commonly performed at a rudimentary level. That is, accessing via a strict database structure with universal fields is impractical due to the size of the enterprise grid and the diversity of client applications accessing the grid. Consequently, unlike accessing data via a database query, such as “select &lt;data&gt; from &lt;location&gt; where &lt;conditions are true&gt;”, a rudimentary enterprise grid data access typically returns values without any way to limit them to a desired subset. For example, a client gives a key value to proxy server computer  102  and proxy server computer  102  returns all values associated with the key. 
     Still more specifically, consider an instance in which a client application requires a user&#39;s address. The application may only have local access to the mapping key, in this instance, the user&#39;s name. The application may query enterprise grid  112  using the user&#39;s name, and in return may receive all associated data including address, age, social security number, etc. 
     According to embodiments of the present invention, data is more selectively provided responsive to a client request. In one aspect, intelligent mapping program  114  registers the request and the requesting application, and monitors the client application&#39;s use of received values. Based on the client application&#39;s use, during subsequent requests for data, intelligent mapping program  114  filters the values to return only the information desired by the client application. In a preferred implementation, to monitor the client application&#39;s use of received values, intelligent mapping program  114  inserts watcher program  118  into the computer hosting the client application that requested the data. 
     Take, for example, the aforementioned application querying enterprise grid  112  using the user&#39;s name as a key and receiving all associated data including address, age, and social security number. After monitoring the application&#39;s use of received data, intelligent mapping program  114  identifies that the application only makes use of the user&#39;s address. In subsequent requests from the client application utilizing the same key (the user&#39;s name), intelligent mapping program  114  will only return the user&#39;s address to the application and not the age, social security number, or other unused data associated with the key. 
     In various embodiments of the present invention, client devices  104 ,  106 , and  108  can each respectively be a laptop computer, tablet computer, netbook computer, personal computer (PC), a desktop computer, a personal digital assistant (PDA), a smart phone, or any programmable electronic device capable of communicating with proxy server computer  102  via network  110 . Client device  104  includes two applications, app_ 1  and app_ 2 , which execute locally on client device  104  and may request data from enterprise grid  112 . Client device  106  includes one application, app_ 3 , which executes locally on client device  106  and has the capability to request data from enterprise grid  112 . Client device  106  also includes watcher program  118  (sent by proxy server computer  102 ) for monitoring the usage of data from enterprise grid  112  by app_ 3  and reporting any discerned patterns to proxy server computer  102 . Client device  108  also includes an application, app_ 4 , running locally on client device  108  and capable of requesting data from enterprise grid  112 . Those of ordinary skill in the art will understand that client devices  104 ,  106 , and  108  may in some instances be members of enterprise grid  112  acting as clients to the grid during the execution of a specific application. 
     Network  110  can be, for example, a local area network (LAN), a wide area network (WAN) such as the Internet, or a combination of the two, and can include wired, wireless, or fiber optic connections. In general, network  110  can be any combination of connections and protocols that will support communications between proxy server computer  102  and client devices  104 ,  106 , and  108 . 
     Proxy server computer  102  may include internal and external hardware components, as depicted and described in further detail with respect to  FIG. 4 . 
       FIG. 2  is a flowchart depicting operational steps of intelligent mapping program  114  for filtering values requested by a client application, in accordance with an embodiment of the present invention. 
     Intelligent mapping program  114  receives a request for data from a client application ( 202 ). The request preferably is a key value or has data corresponding to a key value in a mapping table. Intelligent mapping program  114  determines whether the request from the client application is registered (decision  204 ). The “registration” indicates that a specified client application has previously submitted a specific query/request. In one registration aspect, according to an embodiment, intelligent mapping program  114  stores and maintains a table containing specific client applications and keys previously submitted in requests by each respective client application. Further, for each key submitted by each client application, program  114  stores data (hereafter “filtering data”) indicative of the values actually used by a client application subsequent to submitting the key, described herein below. When determining whether the request is registered, intelligent mapping program  114  may check this table to see if 1) the requesting client application is listed in the table and 2) the key submitted by the client application is listed in association with the client application in the table. A person of ordinary skill in the art will recognize that there are other ways in which such associations may be tracked. 
     If intelligent mapping program  114  determines that the request from the client application is not registered (no branch, decision  204 ), intelligent mapping program  114  registers the specific data request ( 206 ) in relation to the client application. In one implementation, registering the data request is accomplished by one or both adding the client application to the table of known/registered applications (if not already in the table) and adding the key from the data request to the table in association with the client application. (Intelligent mapping program  114  also sends watcher program  118  to the client device executing the client application ( 208 ). Watcher program  118  analyzes the client application&#39;s use of received data, i.e., determines which data the client application uses of the requested data that the client application receives. Watcher program  118  returns filtering data that indicates data each client application uses for each particular request, as described in more detail herein below.) 
     Intelligent mapping program  114  processes the request for data (step  210 ). To process the request, intelligent mapping program  114  identifies the key from the request. In one embodiment, the request for data consists solely of the key. In another embodiment, the request is received in a format such that intelligent mapping program  114  can quickly parse and locate the received key. Intelligent mapping program  114  computes a hash of the key. The hash identifies a server where information associated with the key is located. Upon determining which server has the information associated with the key, intelligent mapping program  114  sends the key to the server, which computes a second hash from the key to determine where to read the corresponding values. Upon reading those values, the server returns them to the intelligent mapping program  114  at proxy server computer  102 . Intelligent mapping program  114  sends the retrieved dataset to the client application ( 212 ). In this instance, intelligent mapping program  114  sends the complete dataset (all values associated with the key) to the requesting client application, and the client application may utilize any of the received values. 
     Returning to decision  204 , if intelligent mapping program  114  instead determines that the request is registered (yes branch, decision  204 ), intelligent mapping program  114  determines whether proxy server computer  102  has received filtering data, corresponding to the request, from watcher program  118  (decision  214 ). In one embodiment, after monitoring the client application for a predetermined period, watcher program  118  determines the values that the client application utilizes out of the received values (the values that are actually pertinent to the client application), and sends the determined values to intelligent mapping program  114  on proxy server computer  102 . The determined values may be saved as filtering data in a table of known/registered client applications in association with applicable client application and key. Intelligent mapping program  114  can use this data to filter data returned in response to a subsequent request from the client application having the same key. 
     In an exemplary implementation, when the values are retrieved from enterprise grid  112 , they are gathered as a list of values in a specific order. Each value returned is associated with a specific field. Though proxy server computer  102  may not have access to names of the field (e.g., “address field,” “SSN,” etc.) the order of a given value in the list of values is indicative of the field it belongs to. The filtering data stored by intelligent mapping program  114  indicates which fields the client application has used (which presumably indicates which fields the client application now desires in a current request) by indicating the placement of the desired values from the ordered list (e.g., the first value and the seventh value from the list of values received in response to given key, where the first and seventh value correspond to a desired address field and SSN field). At decision  214 , intelligent mapping program  114  can determine if the request (or, more specifically, the key received) is associated with filtering data. 
     If the request is not associated with filtering data (no branch, decision  214 ), intelligent mapping program  114  can process the data request ( 210 ) and send the complete dataset to the client application ( 212 ) (under the assumption that watcher program  118  has not yet completed its analysis and returned to proxy server computer  102  the values determined to be utilized by the client application). 
     If intelligent mapping program  114  determines that filtering data is associated with the received request (yes branch, decision  214 ), intelligent mapping program  114  processes the data request ( 216 ) to retrieve the full dataset. Intelligent mapping program  114  then filters the full dataset according to the received filtering data ( 218 ), and sends the filtered dataset to the client application ( 220 ). Following the example stated above, only the first and seventh values in the dataset would be sent to the client application. In this manner, only the information that the client application will utilize is received by the client application. In an alternate embodiment, intelligent mapping program  114  may forward the filtering data to the appropriate server computer within enterprise grid  112  along with the request for the data, and the server computer locates the pertinent subset of values and returns only the relevant values to proxy server computer  102 . This similarly allows intelligent mapping program  114  to send only the values that the client application will utilize, but also offloads some of the processing to the individual servers, avoiding potential bottle necks at proxy server computer  102 . 
       FIG. 3  illustrates operational steps of watcher program  118 , according to one embodiment of the present invention. In a preferred embodiment, once sent to a client device, watcher program  118  automatically installs itself on the client device ( 302 ). The client application that requested data from enterprise grid  112  may, in some embodiments, initiate and/or allow the installation. Watcher program  118  may be installed specifically to monitor the set of values sent by proxy server computer  102 . Where an unregistered request has been received by proxy server computer  102  but an instance of watcher program  118  already exists on the client device (typically indicative of a different request/key being registered for the client application), the existing instance of watcher program  118  may instead receive from proxy server computer  102  the new set of values to be monitored in addition to, or instead of, a different set of values monitored by watcher program  118 . 
     Once installed, watcher program  118  monitors the client application to determine which of the values returned by the enterprise grid in response to the data request are being utilized. More specifically, watcher program  118  may run a process to update the client-side code to be able to intercept calls to getting and setting methods (step  304 ). For example, in Java®, the java persistence API (JPA) has the capability to run an enhancement program that would allow an insertion into compiled program code. JPA also has the ability to update program code in the runtime. Alternatively, the client application may be programmed with a surface API that can be used to tie into the framework. The inserted code may detect a call to a get or set method for a specified data field or value, and notify watcher program  118 . Watcher program  118  receives the notification of the accessed value (step  306 ), and in response, watcher program  118  may increment a counter specific to the value (step  308 ). 
     Watching program  118  determines if a watching threshold has been met (decision  310 ). The watching threshold dictates how long the monitoring process should continue before sending acquired data back to proxy server computer  102 . For example, the watching threshold could be a specified duration of time, a specified number of intercepted calls, or even a specific count achieved for a given value. 
     If the watching threshold has been met (yes branch, decision  310 ), watching program  118  returns pertinent information to proxy server computer  102  (step  312 ). In one embodiment, watching program  118  may return only values that have been accessed a specified number of times. In another embodiment, watching program  118  may return only the values that have been accessed the highest percentage of times. In yet another embodiment, watcher program  118  may return all values which have been accessed without regard to the amount of times the values have been accesses. These returned values may be subsequently used by intelligent mapping program  114  to filter subsequent queries or to identify fields to filter in subsequent queries. 
     A person of ordinary skill in the art will recognize that after sending the values to proxy server computer  102 , watcher program  118  can continue to monitor usage of values, or intermittently monitor usage of values, and update proxy server computer  102  if any changes in the values utilized by the client application are detected. 
       FIG. 4  depicts a block diagram of components of proxy server computer  102  in accordance with an illustrative embodiment of the present invention. It should be appreciated that  FIG. 4  provides only an illustration of one implementation and does not imply any limitations with regard to the environments in which different embodiments may be implemented. Many modifications to the depicted environment may be made. 
     Proxy server computer  102  includes communications fabric  402 , which provides communications between computer processor(s)  404 , memory  406 , persistent storage  408 , communications unit  410 , and input/output (I/O) interface(s)  412 . Communications fabric  402  can be implemented with any architecture designed for passing data and/or control information between processors (such as microprocessors, communications and network processors, etc.), system memory, peripheral devices, and any other hardware components within a system. For example, communications fabric  402  can be implemented with one or more buses. 
     Memory  406  and persistent storage  408  are computer-readable storage media. In this embodiment, memory  406  includes random access memory (RAM)  414  and cache memory  416 . In general, memory  406  can include any suitable volatile or non-volatile computer-readable storage media. 
     Intelligent mapping program  114  is stored in persistent storage  408  for execution by one or more of the respective computer processors  404  via one or more memories of memory  406 . In this embodiment, persistent storage  408  includes a magnetic hard disk drive. Alternatively, or in addition to a magnetic hard disk drive, persistent storage  408  can include a solid state hard drive, a semiconductor storage device, read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, or any other computer-readable storage media that is capable of storing program instructions or digital information. 
     The media used by persistent storage  408  may also be removable. For example, a removable hard drive may be used for persistent storage  408 . Other examples include optical and magnetic disks, thumb drives, and smart cards that are inserted into a drive for transfer onto another computer-readable storage medium that is also part of persistent storage  408 . 
     Communications unit  410 , in these examples, provides for communications with other data processing systems or devices, including resources of enterprise grid  112  and client devices  104 ,  106 , and  108 . In these examples, communications unit  410  includes one or more network interface cards. Communications unit  410  may provide communications through the use of either or both physical and wireless communications links. Intelligent mapping program  114  may be downloaded to persistent storage  408  through communications unit  410 . 
     I/O interface(s)  412  allows for input and output of data with other devices that may be connected to proxy server computer  102 . For example, I/O interface  412  may provide a connection to external devices  418  such as a keyboard, keypad, a touch screen, and/or some other suitable input device. External devices  418  can also include portable computer-readable storage media such as, for example, thumb drives, portable optical or magnetic disks, and memory cards. Software and data used to practice embodiments of the present invention, e.g., intelligent mapping program  114 , can be stored on such portable computer-readable storage media and can be loaded onto persistent storage  408  via I/O interface(s)  412 . I/O interface(s)  412  also connect to a display  420 . 
     Display  420  provides a mechanism to display data to a user and may be, for example, a computer monitor. 
     The programs described herein are identified based upon the application for which they are implemented in a specific embodiment of the invention. However, it should be appreciated that any particular program nomenclature herein is used merely for convenience, and thus the invention should not be limited to use solely in any specific application identified and/or implied by such nomenclature. 
     The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.