Abstract:
A method for anonymizing a data set dump includes detecting an error in an original data set and generating a copy of the original data set. Like the original data set, the copy contains an index and a plurality of members. The method reads the index to locate members within the copy that are reachable by the index. The method then converts the copy to a scrubbed copy by overwriting customer data within the members, while retaining the index, structure of the members, and quantity of data within the data set. In certain embodiments, the method further locates lost members within the copy that are not referenced by the index, and overwrites customer data within the lost members. The scrubbed copy may then be transmitted to a technician for examination since all potentially sensitive/confidential data has been removed. A corresponding system and computer program product are also disclosed.

Description:
BACKGROUND 
     Field of the Invention 
     This invention relates to systems and methods for diagnosing and addressing data corruption in PDSE and other data sets. 
     Background of the Invention 
     In the z/OS operating system, PDSE (partitioned data set extended) data sets are used to simply and efficiently organize related groups of sequential files, also referred to as “members.” A PDSE data set consists of a directory and zero or more members. The directory contains an index which provides a fast search for member names. When diagnosing PDSE corruption issues, the only way to conclusively determine the source of the corruption is to examine a physical dump (track copy) of the data set at or near the time the corruption is detected. 
     When a corruption-related error is detected, the physical dump of the data set is ideally taken automatically. However, this raises issues of dumping the data set while it is open as well as sensitivity/confidentiality for the contents of the data set. That is, taking a physical dump of the data set creates a copy of the contents of the data set which creates additional sensitivity/confidentiality concerns if the copy is distributed or accessed in an undesired manner or by unauthorized individuals. For these reasons, owners of the data typically manually take a physical dump of the data set, usually well after the initial error. After the physical dump is taken, the owner may be unable to send the diagnostic data to a technician or other external entity due to the sensitivity/confidentiality of the data in the data set. In such cases, the owner of the data may have to deal with the corruption issues internally, a task which the owner may or may not be equipped and/or trained to handle. Similar sensitivity/confidentiality issues may arise with data sets other than PDSE data sets. 
     In view of the foregoing, what are needed are systems and methods to more effectively diagnose and address data corruption in PDSE and other data sets. Ideally, such systems and methods will protect sensitive/confidential data and enable technicians and other external entities to diagnose and address the corruption. 
     SUMMARY 
     The invention has been developed in response to the present state of the art and, in particular, in response to the problems and needs in the art that have not yet been fully solved by currently available systems and methods. Accordingly, the invention has been developed to provide systems and methods to anonymize a dump (i.e., copy) of a data set. The features and advantages of the invention will become more fully apparent from the following description and appended claims, or may be learned by practice of the invention as set forth hereinafter. 
     Consistent with the foregoing, a method for anonymizing a data set dump is disclosed herein. In one embodiment, such a method includes detecting an error in an original data set. In response, the method generates a copy of the original data set. Like the original data set, the copy contains an index and a plurality of members. The method reads the index to locate members within the copy that are reachable by the index. The method then converts the copy to a scrubbed copy by overwriting customer data within the members, while retaining the index, structure of the members, and quantity of data within the data set. In certain embodiments, the method further locates lost members within the copy that are not referenced by the index, and overwrites customer data within the lost members. The scrubbed copy may then be transmitted to a technician for examination since all potentially sensitive/confidential data has been removed. 
     A corresponding system and computer program product are also disclosed and claimed herein. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       In order that the advantages of the invention will be readily understood, a more particular description of the invention briefly described above will be rendered by reference to specific embodiments illustrated in the appended drawings. Understanding that these drawings depict only typical embodiments of the invention and are not therefore to be considered limiting of its scope, the invention will be described and explained with additional specificity and detail through use of the accompanying drawings, in which: 
         FIG. 1  is a high-level block diagram showing one example of a network environment in which a system and method in accordance with the invention may be implemented; 
         FIG. 2  is a high-level block diagram showing one example of a storage system in which a system and method in accordance with the invention may be implemented; 
         FIG. 3  is a high-level block diagram showing copying of an original data set, and reading an index of the data set to locate members within the copy that are reachable by the index; 
         FIG. 4  is a high-level block diagram showing overwriting of the locatable members; 
         FIG. 5  is a high-level block diagram showing locating of lost members within the data set; 
         FIG. 6  is a high-level block diagram showing overwriting of the lost members; 
         FIG. 7  is a high-level block diagram showing one embodiment of a data set anonymizer module in accordance with the invention; and 
         FIG. 8  is a process flow diagram showing one embodiment of a method for anonymizing a data set while retaining the index, structure of the members, and quantity of data within the data set; 
     
    
    
     DETAILED DESCRIPTION 
     It will be readily understood that the components of the present invention, as generally described and illustrated in the Figures herein, could be arranged and designed in a wide variety of different configurations. Thus, the following more detailed description of the embodiments of the invention, as represented in the Figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of certain examples of presently contemplated embodiments in accordance with the invention. The presently described embodiments will be best understood by reference to the drawings, wherein like parts are designated by like numerals throughout. 
     The present invention may be embodied as a system, method, and/or computer program product. The computer program product may include a computer readable storage medium (or media) having computer-readable program instructions thereon for causing a processor to carry out aspects of the present invention. 
     The computer-readable storage medium may be a tangible device that can retain and store instructions for use by an instruction execution device. The computer-readable storage medium may be, for example, but is not limited to, an electronic storage system, a magnetic storage system, an optical storage system, an electromagnetic storage system, a semiconductor storage system, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer-readable storage medium includes the following: 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), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. 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. 
     Computer-readable program instructions described herein can be downloaded to respective computing/processing devices from a computer-readable storage medium or to an external computer or external storage system via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium within the respective computing/processing device. 
     Computer-readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the “C” programming language or similar programming languages. 
     The computer-readable program instructions may execute entirely on a user&#39;s computer, partly on a user&#39;s computer, as a stand-alone software package, partly on a user&#39;s computer and partly on a remote computer, or entirely on a remote computer or server. In the latter scenario, a remote computer may be connected to a 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). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer-readable program instructions by utilizing state information of the computer-readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present invention. 
     Aspects of the present invention are described herein 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, may be implemented by computer-readable program instructions. 
     These computer-readable 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-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks. 
     The computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus, or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     Referring to  FIG. 1 , one example of a network environment  100  is illustrated. The network environment  100  is presented to show one example of an environment where various embodiments of the invention may operate. The network environment  100  is presented only by way of example and not limitation. Indeed, the systems and methods disclosed herein may be applicable to a wide variety of different network environments in addition to the network environment  100  shown. 
     As shown, the network environment  100  includes one or more computers  102 ,  106  interconnected by a network  104 . The network  104  may include, for example, a local-area-network (LAN)  104 , a wide-area-network (WAN)  104 , the Internet  104 , an intranet  104 , or the like. In certain embodiments, the computers  102 ,  106  may include both client computers  102  and server computers  106  (also referred to herein as “hosts”  106  or “host systems”  106 ). In general, the client computers  102  initiate communication sessions, whereas the server computers  106  wait for requests from the client computers  102 . In certain embodiments, the computers  102  and/or servers  106  may connect to one or more internal or external direct-attached storage systems  112  (e.g., arrays of hard-disk drives, solid-state drives, tape drives, etc.). These computers  102 ,  106  and direct-attached storage systems  112  may communicate using protocols such as ATA, SATA, SCSI, SAS, Fibre Channel, or the like. 
     The network environment  100  may, in certain embodiments, include a storage network  108  behind the servers  106 , such as a storage-area-network (SAN)  108  or a LAN  108  (e.g., when using network-attached storage). This network  108  may connect the servers  106  to one or more storage systems  110 , such as arrays  110   a  of hard-disk drives or solid-state drives, tape libraries  110   b , individual hard-disk drives  110   c  or solid-state drives  110   c , tape drives  110   d , CD-ROM libraries, or the like. To access a storage system  110 , a host system  106  may communicate over physical connections from one or more ports on the host  106  to one or more ports on the storage system  110 . A connection may be through a switch, fabric, direct connection, or the like. In certain embodiments, the servers  106  and storage systems  110  may communicate using a networking standard such as Fibre Channel (FC) or iSCSI. 
     Referring to  FIG. 2 , one embodiment of a storage system  110   a  containing an array of storage drives  204  (e.g., hard-disk drives  204  and/or solid-state drives  204 ) is illustrated. The internal components of the storage system  110   a  are shown since various types of data sets may be stored on such a storage system  110   a , although embodiments of the invention may also be applicable to other storage systems or groups of storage systems. As shown, the storage system  110   a  includes a storage controller  200 , one or more switches  202 , and one or more storage drives  204  such as hard disk drives  204  and/or solid-state drives  204  (such as flash-memory-based drives  204 ). The storage controller  200  may enable one or more hosts  106  (e.g., open system and/or mainframe servers  106 ) to access data in the one or more storage drives  204 . 
     In selected embodiments, the storage controller  200  includes one or more servers  206 . The storage controller  200  may also include host adapters  208  and device adapters  210  to connect the storage controller  200  to host devices  106  and storage drives  204 , respectively. Multiple servers  206   a ,  206   b  may provide redundancy to ensure that data is always available to connected hosts  106 . Thus, when one server  206   a  fails, the other server  206   b  may pick up the I/O load of the failed server  206   a  to ensure that I/O is able to continue between the hosts  106  and the storage drives  204 . This process may be referred to as a “failover.” 
     In selected embodiments, each server  206  may include one or more processors  212  and memory  214 . The memory  214  may include volatile memory (e.g., RAM) as well as non-volatile memory (e.g., ROM, EPROM, EEPROM, flash memory, etc.). The volatile and non-volatile memory may, in certain embodiments, store software modules that run on the processor(s)  212  and are used to access data in the storage drives  204 . The servers  206  may host at least one instance of these software modules. These software modules may manage all read and write requests to logical volumes in the storage drives  204 . 
     One example of a storage system  110   a  having an architecture similar to that illustrated in  FIG. 2  is the IBM DS8000™ enterprise storage system. The DS8000™ is a high-performance, high-capacity storage controller providing disk and solid-state storage that is designed to support continuous operations. Nevertheless, the apparatus and methods disclosed herein are not limited to the IBM DS8000™ enterprise storage system  110   a , but may be implemented in any comparable or analogous storage system or group of storage systems, regardless of the manufacturer, product name, or components or component names associated with the system. Any storage system that could benefit from one or more embodiments of the invention is deemed to fall within the scope of the invention. Thus, the IBM DS8000™ is presented only by way of example and is not intended to be limiting. 
     Referring to  FIG. 3 , as previously mentioned, in the z/OS operating system, PDSE (partitioned data set extended) data sets  300  are used to simply and efficiently organize related groups of sequential files, also referred to as “members.” A PDSE data set  300  consists of a directory and zero or more members. The directory contains an index which provides a fast search for member names. As shown in  FIG. 3 , when diagnosing PDSE corruption issues, the only way to conclusively determine the source of the corruption is to examine a physical dump (track copy) of the data set  300  at or near the time the corruption is detected. This process reads the PDSE data set  300  from the storage media (e.g., hard disk drives  204 , solid state drives  204 , etc.) as a sequential collection of tracks without regard to the internal structure of the data set  300 , thereby creating an exact copy  302  of the PDSE data set  300 . This has the effect of preserving any structural or index corruption in the original PDSE data set  300  for later diagnosis. 
     When a corruption-related error is detected, the physical dump  302  of the PDSE data set  300  is ideally taken automatically. However, this raises issues of dumping the PDSE data set  300  while it is open as well as sensitivity/confidentiality for the contents of the data set  300 . That is, taking a physical dump of the data set  300  creates a copy  302  of the contents of the data set  300  which creates additional sensitivity/confidentiality concerns if the copy  302  is distributed or accessed in an undesired manner or by unauthorized individuals. For these reasons, owners of the data must typically manually take a physical dump of the data set  300 , usually well after the initial error. After the physical dump is taken, the owner may be unable to send the diagnostic data to a technician or other external entity due to the sensitivity/confidentiality issues discussed above. In such cases, the owner of the data may have to deal with the corruption issues internally, a task which the owner may or may not be equipped and/or trained to handle. Similar sensitivity/confidentiality issues may arise with data sets other than PDSE data sets  300 . 
       FIGS. 3 through 6  provide a general overview of one embodiment of a method to effectively diagnose and address data corruption in PDSE and other data sets. This method protects sensitive/confidential data and enables technicians and other external entities to diagnose and address the corruption. As shown in  FIG. 3 , once a physical dump  302  is taken of an original PDSE data set  300 , the method reads the index  306  of the copy  302  to locate any members  308  of the PDSE data set  300  that are reachable by the index  306 . Because the physical dump of the PDSE data set  300  was initiated by a corruption-related error, the index  306  may be all or partially corrupt and therefore unable to reach certain members  308  of the PDSE data set  300 . These members  308  will hereinafter be referred to as “lost members.” The member location process may be performed without regard to index defects, meaning that even if corruption is encountered in the index  306 , the process will continue to locate all members  308  that are reachable by the index  306 . 
     Referring to  FIG. 4 , once all members  308  that are reachable by the index are located and the data in these members  308  is located, an overwrite process may overwrite the data in the locatable members  308  with random or other unidentifiable data, while leaving the structure of the locatable members  308  and quantify of data within the locatable members  308  in place. The manner in which this may be accomplished will be discussed in more detail in association with  FIGS. 7 and 8 . 
     Referring to  FIGS. 5 and 6 , once the locatable members  308  are located and overwritten, a lost-member identification process may locate any members  308  that are not reachable by the index  306 . These lost members  308  may then be overwritten with random or other unidentifiable data, as shown in  FIG. 6 , while leaving the structure of the lost members  308  and quantify of data within the lost members  308  in place. The manner in which this may be accomplished will be discussed in more detail in association with  FIGS. 7 and 8 . After both the locatable members  308  and lost members  308  are overwritten, the copy  302  of the data set is in ideal form for technicians and/or other external entities to receive the copy  302  for analysis and diagnosis. 
     Referring to  FIG. 7 , in order to more effectively diagnose and address data corruption in PDSE and other data sets  300 , a data set anonymizer module  700  may be provided in a host system  106  (although it is not limited to implementation in a host system  106 ). The data set anonymizer module  700  may include various sub-modules to provide various features and functions. These sub-modules may include one or more of an error detection module  702 , corruption determination module  704 , dump module  705 , and overwrite module  718 . The dump module  705  may include a physical dump module  706  and logical dump module  708 . The logical dump module  708  may include one or more of an index processing module  710 , member location module  712 , page traversal module  714 , and lost member identification module  716 . The sub-modules are presented by way of example and are not intended to represent an exhaustive list of sub-modules that may be included within the data set anonymizer module  700 . The data set anonymizer module  700  may include more or fewer sub-modules than those illustrated, or the functionality of the sub-modules may be organized differently. One embodiment of a method  800  that may be used by the data set anonymizer module  700  to anonymize a data set dump will be discussed in association with  FIG. 8 . 
     The error detection module  702  may be configured to detect errors associated with a PDSE data set  300 . The corruption determination module  704  may be configured to determine whether the errors are corruption related. Corruption-related errors generally surface as “logical errors,” meaning that an unexpected condition has been detected when accessing a PDSE data set  300 . Whether the error is corruption-related may depend on the reason code of the logical error and/or the point or time in which the logical error is detected. The error detection module  702  and corruption determination module  704  may ensure that a dump is only taken when it makes sense and when there is a high likelihood that the physical dump will provide useful diagnostic information. 
     When a corruption-related error is detected, the dump module  705  may initiate a dump of the data set  300 . This dump may include both a physical dump and a logical dump. Ideally, the dump will be taken immediately after the error is detected. Taking the dump of the data set  300  immediately after or in close temporal proximity to the initial error may be important as it is possible for partially or minimally corrupted PDSE datasets to continue to be updated and function in a partial manner. When a partially corrupted data set  300  is updated, critical diagnostic information contained therein may be lost. 
     The initial phase of the dump is to obtain a physical dump of the data set  300 . The physical dump module  706  may perform this function. To take the physical dump, the physical dump module  706  reads the PDSE data set  300  from underlying storage media (e.g., hard disk drives  204 , solid state drives  204 , etc.) as a sequential collection of tracks without regard to the internal structure of the data set, thereby creating an exact copy  302  of the PDSE data set  300 . This has the effect of preserving any structural or index corruption in the original PDSE data set  300  for later diagnosis. Due to the homogenous nature of PDSE data sets  300 , there is no way to differentiate between index data and member data without actually processing the data set index  306 . 
     The second phase of the dump is to obtain a logical dump of the data set  300 . This may be performed by the logical dump module  708 . To accomplish this, the index processing module  710  within the logical dump module  708  reads the PDSE&#39;s index  306  and processes it to locate the member data within the data set  300 . The index processing module  710  may traverse the entire index  306  without regard to any defects that are encountered therein. In other words, the index processing module  710  may attempt to locate all member data that is reachable by the index  306  regardless of whether an error is encountered in the index  306  during its traversal. 
     The member location module  712  and page traversal module  714  may be tasked with locating member data within the physical dump. In order to locate member data in the physical dump, a relative page number (i.e., page number relative to a beginning of the PDSE data set  300 ) of a start of the member&#39;s linear space needs to be located in the index  306  and used to resolve a starting track number within the physical dump. Because a PDSE data set  300  is typically a homogenous collection of  4   k  pages, the conversion is simple. Once the member location module  712  locates the start of the linear space containing the member data, the page traversal module  714  follows a linked list of pages associated with the member. The overwrite module  718  overwrites these pages with random or other unidentifiable data. During this overwrite process, the members  308  will retain their location and size within the PDSE data set  300 , but will be emptied of potentially sensitive/confidential data. This process is repeated for all members  308  that are reachable within the PDSE data set  300 . 
     The final step of the logical dump is for the lost member identification module  716  to identify any pages in the PDSE data set  300  that are lost (i.e., pages that contain data and are within the physical dump but are unreachable by the index  306 ) since these may also contain sensitive/confidential data. The overwrite module  718  may also overwrite these pages with random or other unidentifiable data. 
     Referring to  FIG. 8 , one embodiment of a method  800  for anonymizing a PDSE data set  300  while retaining the index  306 , structure of the members  308 , and quantity of data within the data set  300  is illustrated. As shown, the method  800  initially determines  802  whether an error associated the PDSE data set  300  has been detected. If so, the method  800  determines  804  whether the error is corruption related. If so, the method  800  performs  806  a track copy of the data set  300 , thereby creating an exact copy  302 . The method  800  then reads  808  the data set index  306  of the copy and locates  810  members  308  within the data set  300 . The method  800  further traverses  812  the pages of the members  308  and overwrites  814  the data within the pages, while leaving the structure of the members  308  and quantity of data in the members  308  in place. The method  800  then locates  816  any lost pages within the PDSE data set  300  and overwrites  818  the data in the lost pages. At this point, the physical dump of the data set  300  retains the potentially corrupt index  306  in the state that it existed at the time of the initial error, while scrubbing all potentially sensitive/confidential member data from the copy  302 . The copy  302  retains the structure of the members  308  and quantity of data therein. At this point the data set  300  is in an ideal form for analysis, either by the owner of the data set  300  or an external technician. 
     Although particular reference has been made herein to PDSE data sets  108 , the systems and methods disclosed herein may be equally applicable or trivially modified to work with other types of data sets. Thus, the systems and methods disclosed herein are not intended to be limited to PDSE data sets  108 . 
     The flowcharts and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer-usable media according to various embodiments of the present invention. In this regard, each block in the flowcharts 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 illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, may be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.