Abstract:
Mechanisms for distributing workload items to a plurality of dispatchers are provided. Each dispatcher is associated with a different computing system of a plurality of computing systems and workload items comprise workload items of a plurality of different workload types. A capacity value for each combination of workload type and computing system is obtained. For each combination of workload type and computing system, a queue length of a dispatcher associated with the corresponding computing system is obtained. For each combination of workload type and computing system, a dispatcher&#39;s relative share of incoming workloads is computed based on the queue length for the dispatcher associated with the computing system. In addition, incoming workload items are routed to a dispatcher, in the plurality of dispatchers, based on the calculated dispatcher&#39;s relative share for the dispatcher.

Description:
This application is a continuation of application Ser. No. 12/390,718, filed Feb. 23, 2009, now U.S. Pat. No. 8,245,238. 
    
    
     The invention relates generally to an improved data processing apparatus and method and more specifically to mechanisms for calculating a routing workload in a workload manager. 
     Mainframes are computers used mainly by large organizations for executing critical applications and processing great amounts of data, e.g., financial transaction processing. Mainframes are highly redundant for providing reliable and secure systems. Mainframes are able to run or host multiple operating systems and therefore, may replace the use of dozens of smaller servers, thereby reducing management and providing improved scalability. Modern mainframes include the International Business Machines (IBM) zSeries™ and System z9™ servers, available from IBM Corporation of Armonk, N.Y. 
     A parallel sysplex is a cluster of IBM mainframes acting together as a single system image, using z/OS. A sysplex uses parallel processing and enables read/write data sharing across multiple systems, with full data integrity, in order to cluster up to 32 systems and share a workload across the systems. The workload can be dynamically distributed across individual processors within a single system, as well as distributed to any system in a cluster having available resources. Workload balancing also permits running diverse applications across a parallel sysplex cluster, while maintaining a critical response level. If the workload balancing or workload routing is not done correctly, however, an overload in the system may occur. 
     SUMMARY 
     In one illustrative embodiment, a method, in workflow manager, for distributing workload items to a plurality of dispatchers is provided. Each dispatcher is associated with a different computing system of a plurality of computing systems. The workload items comprise workload items of a plurality of different workload types. The method comprises obtaining, in the workload manager, a capacity value for each combination of workload type and computing system in the plurality of computing systems, the capacity value representing a total capacity of workload items of a corresponding workload type that a corresponding computing system may process in a given time period. The method further comprises obtaining, in the workload manager, for each combination of workload type and computing system, a queue length of a dispatcher associated with the corresponding computing system. Moreover, the method comprises calculating, in the workload manager, for each combination of workload type and computing system, a dispatcher&#39;s relative share of incoming workloads based on the queue length for the dispatcher associated with the computing system. In addition, the method comprises routing, by the workload manager, incoming workload items to a dispatcher, in the plurality of dispatchers, based on the calculated dispatcher&#39;s relative share for the dispatcher. 
     In other illustrative embodiments, a computer program product comprising a computer useable or readable medium having a computer readable program is provided. The computer readable program, when executed on a computing device, such as by a workload manager of a computing device, causes the computing device/workload manager to perform various ones, and combinations of, the operations outlined above with regard to the method illustrative embodiment. 
     In yet another illustrative embodiment, a workload manager is provided. The workload manager is coupled to a plurality of dispatchers, each dispatcher in the plurality of dispatchers being associated with a corresponding computing system in a plurality of computing systems. The dispatchers in the plurality of dispatchers receive workload items of a plurality of different workload types. The workload manager comprises a processor and a memory coupled to the processor. The memory comprises instructions which, when executed by the processor, cause the processor to obtain a capacity value for each combination of workload type and computing system in the plurality of computing systems, the capacity value representing a total capacity of workload items of a corresponding workload type that a corresponding computing system may process in a given time period. The instructions further cause the processor to obtain, for each combination of workload type and computing system, a queue length of a dispatcher associated with the corresponding computing system. The instructions further cause the processor to calculate, for each combination of workload type and computing system, a dispatcher&#39;s relative share of incoming workloads based on the queue length for the dispatcher associated with the computing system. In addition, the instructions also cause the processor to route incoming workload items to a dispatcher, in the plurality of dispatchers, based on the calculated dispatcher&#39;s relative share for the dispatcher. 
     These and other features and advantages of the present invention will be described in, or will become apparent to those of ordinary skill in the art in view of, the following detailed description of the example embodiments of the present invention. 
    
    
     
       BRIEF DESCRIPTION OF SEVERAL VIEWS OF THE DRAWINGS 
       The invention, as well as a preferred mode of use and further objectives and advantages thereof, will best be understood by reference to the following detailed description of illustrative embodiments when read in conjunction with the accompanying drawings, wherein: 
         FIG. 1  is an example block diagram of a first sysplex according to one illustrative embodiment; 
         FIG. 2  is an example block diagram of a plurality of interconnected systems forming a sysplex according to one illustrative embodiment; 
         FIG. 3  is an example flow chart of an operation for calculating a dispatcher&#39;s share according to one illustrative embodiment; and 
         FIG. 4  is an example diagram illustrating a calculation operation of the workload manager in accordance with one illustrative embodiment. 
     
    
    
     DETAILED DESCRIPTION 
       FIG. 1  is an example block diagram  100  of a first sysplex comprising a first system  118  with a first workload manager  101  coupled to an arbitration device, referred to as an arbitrator,  102 . The arbitrator is coupled to a first, a second, and a third dispatcher  103 - 105 , each dispatcher being coupled to three execution units  106 - 114 . In the depicted example, the first workload manager  101  may be coupled to another two workload managers  120 - 121 . The first dispatcher D 1    103  is located in a second system  117  and is coupled to the execution units E 1,1  to E 1,3    106 - 108 . The dispatcher D 2    104  is located in the first system  118  and is coupled to the three execution units E 2,1  to E 2,3    109 - 111 . The third dispatcher D 3    105  is located in the third system  119  and is coupled to another three execution units E 3,1  to E 3,3    112 - 114 . A memory  116  is coupled to the workload manager  101 . 
     In the depicted example, an arbitrator  102  receives incoming workload items and routes them to dispatching units  103 - 105 . Each dispatcher D 1  to D 3    103 - 105  determines the workload type of the workload items and routes them to appropriate specialized execution units E 1,1  to E 3,3    106 - 114 . The queue length of the plurality of workload items can be measured for each dispatcher D 1  to D 3    103 - 105  and each execution unit E 1,1  to E 3,3    106 - 114 . For example, the dispatcher D 1    103  has a queue length (q D1 ) of five workload items and the execution unit E 1,1    106  has a queue length (q E1,1 ) of three workload items. While the queue lengths for all dispatchers D 1  to D 3    103 - 105  and/or execution units E 1,1  to E 3,3    106 - 114  may be measured, there is no requirement that all dispatchers and/or execution units have their queue lengths measured by the mechanisms of the illustrative embodiments. The queue lengths are used, for each system in a plurality of systems, to generate a relative queue length for each workload type on the systems which in turn is used, along with a defined function, to calculate each dispatcher&#39;s relative share of the incoming workload. The details of such calculations are provided hereafter. 
     Each workload item requires a different CPU consumption, e.g., number of processor cycles, of an execution unit within a given time interval, and that consumption is not known in advance by the arbitrator  102 . Thus, the assignment of the plurality of workload items to the dispatchers D 1  to D 3    103 - 105  does not depend on the size of each workload item or its CPU consumption. The workload type of each workload item is identified by the dispatchers D 1  to D 3    103 - 105 , and the size of the workload items is identified either by the dispatcher D 1  to D 3    103 - 105  or by the execution units E 1,1  to E 3,3    106 - 114 . As the arbitrator  102  does not know in advance the workload type of the workload items and the size of the workload items, a wrong workload balancing logic or algorithm may cause a queue of a dispatcher and/or execution unit to grow to infinity. With the illustrative embodiments, the workload managers  101 , 120 , and  121  of the systems  117 - 119  are coupled to one another and may constantly interact and communicate the capacity and workload values of the systems  117 - 119 . 
     The memory  116  may store the values of a total value of services units of all workload types across the plurality of systems  117 - 119 , and a capacity value of all workload types of each system  117 - 119 . The service units are a value that measures the processor (CPU) consumption within a given time interval. The capacity value is a value indicative of a measure of the maximum amount of service units that a system is capable of executing in a given time interval. 
       FIG. 2  shows an example of a Sysplex  200  that is formed by a plurality of interconnected systems including a first, second, third and fourth system  201 - 204 . Each system  201 - 204  includes a workload manager  205 - 208 , with all workload managers  205 - 208  being coupled to each other. The workload managers  205 - 206  are coupled to the arbitrators  209 - 210 . Alternatively, it is sufficient to have one arbitrator in the whole sysplex  200 . The arbitrators  209 - 210  are coupled to a plurality of dispatchers  213 - 216  and each dispatcher  213 - 216  is coupled as well to a plurality of execution units  217 - 220 . Not every system requires an arbitrator, as the arbitrator may route the workload to any system  201 - 204  in the sysplex  200 . 
     Each workload manager  205 - 208  processes a routing algorithm, in accordance with the mechanisms of the illustrative embodiments, or otherwise implements the routing algorithm in hardware logic. The routing algorithm calculates a dispatcher&#39;s share of a relative amount of workload items a dispatcher should receive. The arbitrators  209 - 210  do not know the workload type or workload size of the workload items and receive the routing recommendations from the workload manager  205 - 208 . The arbitrators  209 - 210  distribute the workload items according to the results of the routing algorithm as communicated to the arbitrators  209 - 210  from the workload managers  205 - 208 . 
     The dispatchers  213 - 216 , also known as queue managers, receive the workload items from the arbitrators  209 - 210  and queue them until they are fetched by the execution units  217 - 220 , also called servers. The execution units  217 - 220  execute the workload items, read the workload type, and decide what processor is able to process the workload item. The workload types may be of a plurality of different types. In one illustrative embodiment, the workload types may be of three or more types including general CPU (CP), z Application Assist Processor (zAAP), and z9 Integrated Information Processor (zIIP) workload types. A different processor is used for each workload type. The workload managers  205 - 208  across all the systems  201 - 204  are coupled in order to receive the information related to the dispatcher status across all the systems  201 - 204 . 
       FIG. 3  is an example flow diagram  300  of an operation for calculating a dispatcher&#39;s share (D) in a workload manager. As shown in  FIG. 3 , a first step  301  comprises obtaining a total value of service units for each workload type across a plurality of systems for a given time interval in progress. As noted above, the service units are a value that measures the CPU consumption in a time interval. In one illustrative embodiment, the total value of service units includes a service unit value for a first workload type, a service unit value for a second workload type, and a service unit value for a third third workload types. Further workload types may also be available in the system, with a further corresponding total value of service units. The service unit values may be a number of service units with the total value of service units being a total number of service units, for example. 
     The second step  302  includes obtaining a capacity value for each workload type, including the first, second and third workload type on each system of the plurality of systems. As mentioned above, the capacity value is indicative of a measure of a maximum amount, or number, of service units that a system is capable of executing in a time interval. A different capacity value is obtained for each workload type and for each system, so that each system will include a capacity value for each workload type. 
     The flow diagram  300  further comprises a third step  303  for calculating a dispatcher&#39;s relative share of the workload items. This relative share, in one illustrative embodiment, is obtained in the following manner. For each system and for each workload type, the total capacity for the workload type is divided by a corresponding total value of service units for the workload type in the given time period as a whole, for the particular system. The obtained capacity to total value of service units ratio for each workload type is then used to determine a minimum value of the ratio for each system. 
     On the third step  303 , a single value is obtained for each system. The forth step  304  comprises calculating a relative queue length from each system by dividing a queue length of the workload items for each workload type on each system by the capacity of each workload type on each system, each system obtaining a value for each workload type. The fifth step  305  calculates the dispatcher&#39;s share (D) for each system by combining the minimum value and a first function of the relative queue length using an arithmetic operation, as described in greater detail hereafter with regard to  FIG. 4 . 
       FIG. 4  shows an example of a calculation of the dispatcher&#39;s share for distributing a flow of workload items across a plurality of dispatchers in accordance with one illustrative embodiment. The table comprising three systems  401 - 403 , a first workload type  404 , a second workload type  405 , and a third workload type  406 ; a total value of service units  407 , a plurality of capacities on each system, the first plurality of capacities  408  on the first system  401 , the second plurality of capacities  409  on the second system  402 , and the third plurality of capacities  410  on the third system  403 . The second table  420  further comprises a plurality of queue lengths  421 - 423  of each workload type and on each system SYS 1 , SYS 2 , and SYS 2   401 - 403 , a calculated relative queue length  424 - 426  on each system and for each workload type, and a function  427  of the relative queue length for each workload type on each system. 
     One of the first steps for calculating a dispatcher&#39;s share in a workload manager includes obtaining the values for the total value of service units  407  of each workload type across all the systems  401 - 403 . In this example, the total value of service units on the first system  401  for the first workload type is 300, the total value of service units for the second workload type is 500 and the third total value of service units for the third workload type is 10. 
     Another step includes obtaining a capacity value of each system  401 - 403  and workload type. For example, on the first system  401  the capacity of the first workload type is 90, the capacity of the second workload type is 100, and the capacity for the third workload type is 10. On the second system  402 , the capacity for the first workload type is 200, the capacity for the second workload type is 400, and the capacity for the third workload type is 100. After the capacities are obtained for all the systems, a dispatcher&#39;s relative share may be calculated on each system  401 - 403  and for each workload type. 
     On the first system  401 , a first workload that a system is able to process is obtained by dividing the capacity of the first workload type, corresponding to ‘90’, by the total value of service units of the first workload type, corresponding to ‘300’, resulting in ‘0.3’. The second capacity of the second workload type, with a value of ‘100’, is divided by the total value of service units of the second workload type, with a value of ‘500’, resulting in a second workload for the system  401  is able to process of ‘0.2’. These values refer to the actual workload in percentage that the system  401  is able to process. The same process is repeated for the third workload type that results in ‘1’ and the same is repeated across all the systems  402 - 403  obtaining three different values for each system. 
     Another step of the method of calculating a dispatcher&#39;s share includes calculating a minimum value of the previously obtained dispatcher&#39;s relative share. For example on the first system  401  there are three values of the dispatcher&#39;s relative share, which are ‘0.3’, ‘0.2’ and ‘1’. The minimum value of these three values is ‘0.2’. For the second system, the minimum value is ‘0.6’, and on the third system the minimum value of the dispatcher&#39;s relative share is ‘1’. 
     The second table  420  shows an example of the following steps that comprises the method of calculating a dispatcher&#39;s share that includes calculating the relative queue length  424 - 426  by dividing a queue length  421 - 423  by the capacity  408 - 410  for a specific workload type. On the first system  401 , and for the first workload type, the queue length  421  is ‘125’. The queue length  421  for the second workload type is ‘89’ and the third queue length  421  for the third workload type is ‘67’. The first relative queue length  424  of the first system  401  is obtained by dividing ‘125’ by ‘90’, obtaining ‘1.388’. The second relative queue length  424  is obtained by dividing ‘89’ by ‘100’, obtaining ‘0.89’. The same process is repeated for all queue lengths of all workload types across all the systems  401 - 403 , so that the third relative queue length  424  of the first system  401  is ‘6.7’. 
     The table  420  further comprises a first function  427  of the relative queue lengths  424 - 426  that includes obtaining the inverse value of one plus the maximum relative queue length. On the first system  401  the maximum relative queue length is ‘6.7’, so that the inverse of that value plus 1 is ‘0.12987’ (which is rounded to 0.1299 in  FIG. 4 ). On the second system  402 , the highest relative queue length is ‘3.655’, so that the inverse of one plus the value is ‘0.2148’. For the third system  403 , the maximum relative queue length is ‘4.356’ and the inverse value of the maximum queue length is ‘0.1867’. When all these values are calculated, for each system, the dispatcher&#39;s share is obtained by multiplying the minimum value of a dispatcher&#39;s relative share of the system by the first function value 427 of the system. Thus, for the first system  401 , the minimum value of ‘0.2’ is multiplied by the first function value ‘0.1299’ thereby obtaining ‘0.02598’. For the second system  402 , the minimum value of ‘0.6667’ is multiplied by the first function value ‘0.2148’ to obtain a value of ‘0.1432’. 
     Finally, for the third system  403 , the minimum value of ‘1’ is multiplied by the first function value of ‘0.1867’ to obtain a value of ‘0.1867’. These three dispatcher&#39;s share values indicate the dispatcher&#39;s share for each system  401 - 403 , so that the arbitrator can route a different amount of workload units for each dispatcher. As a result, the best possible distribution of the workload items is obtained across all the dispatchers and for all the systems  401 - 403 . After a predefined, fixed time interval, the calculation is repeated, taking into account any changes in the workload W, the capacities, and queue lengths. Thus, the mechanisms of the illustrative embodiments adjusts the dispatchers&#39; shares to new optimal values. 
     The illustrative embodiments of the present invention can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment containing both hardware and software elements. In a preferred embodiment, the illustrative embodiments of the present invention are implemented in software, which includes but is not limited to firmware, resident software, microcode, etc. 
     Furthermore, the illustrative embodiments of the present invention can take the form of a computer program product accessible from a computer-usable or computer-readable medium providing program code for use by, or in connection with, a computer or any instruction execution system. For the purposes of this description, a computer-usable or computer readable medium can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. 
     The medium can be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system (or apparatus or device). Examples of a computer-readable medium include a semiconductor or solid state memory, magnetic tape, a removable computer diskette, a random access memory (RAM), a read-only memory (ROM), a rigid magnetic disk and an optical disk. Current examples of optical disks include compact disk-read only memory (CD-ROM), compact disk-read/write (CD-R/W) and DVD. 
     A data processing system suitable for storing and/or executing program code will include at least one processor coupled directly, or indirectly, to memory elements through a system bus. The memory elements can include local memory employed during actual execution of the program code, bulk storage, and cache memories which provide temporary storage of at least some program code in order to reduce the number of times code must be retrieved from bulk storage during execution. 
     Input/output or I/O devices (including but not limited to keyboards, displays, pointing devices, etc.) can be coupled to the system either directly or through intervening I/O controllers. Network adapters may also be coupled to the system to enable the data processing system to become coupled to other data processing systems or remote printers or storage devices through intervening private or public networks. Modems, cable modem and Ethernet cards are just a few of the currently available types of network adapters. 
     While the foregoing has been with reference to particular illustrative embodiments of the present invention, it will be appreciated by those skilled in the art that changes in these illustrative embodiments may be made without departing from the principles and spirit of the present invention, the scope of which is defined by the appended claims.