Patent Publication Number: US-11656953-B2

Title: Small database page recovery

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     This is a continuation of U.S. patent application Ser. No. 16/261,172, entitled “SMALL DATABASE PAGE RECOVERY,” filed Jan. 29, 2019, issuing as U.S. Pat. No. 11,157,371, the disclosures of which are hereby incorporated by reference. 
    
    
     TECHNICAL FIELD 
     The current subject matter is directed to advanced database techniques in which pages are combined into superblocks and are flushed to physical persistence in parallel to speed up database recovery. 
     BACKGROUND 
     With an in-memory database, a recovery process can include loading pages into memory using various recovery logs. These pages are subsequently flushed into physical persistence to recreate a state of the database at an earlier savepoint. The process of flushing pages into the physical persistence can, in some cases, be resource intensive and slow down the overall time for recovering the database. 
     SUMMARY 
     In one aspect, recovery of an in-memory database is initiated. Thereafter, pages for recovery having a size equal to or below a pre-defined threshold are copied to a superblock. For each copied page, encryption information is added to a superblock control block for the superblock. The copied pages are encrypted within the superblock using the corresponding encryption information added to the super block control block. The superblock is then flushed from memory (e.g., main memory, etc.) of the database to physical persistence. 
     The encryption of the copied pages can be conducted in parallel by a plurality of helper threads. 
     The encryption information in the superblock control block can include an encryption key for each copied page. The encryption information in the superblock control block can be an initialization vector for each copied page. 
     Pages having a size above the predefined threshold can be encrypted on a page-by-page basis without copying such pages to the superblock. Such encrypted pages can be flushed from the memory of the database to the physical persistence. 
     Non-transitory computer program products (i.e., physically embodied computer program products) are also described that store instructions, which when executed by one or more data processors of one or more computing systems, cause at least one data processor to perform operations herein. Similarly, computer systems are also described that may include one or more data processors and memory coupled to the one or more data processors. The memory may temporarily or permanently store instructions that cause at least one processor to perform one or more of the operations described herein. In addition, methods can be implemented by one or more data processors either within a single computing system or distributed among two or more computing systems. Such computing systems can be connected and can exchange data and/or commands or other instructions or the like via one or more connections, including but not limited to a connection over a network (e.g., the Internet, a wireless wide area network, a local area network, a wide area network, a wired network, or the like), via a direct connection between one or more of the multiple computing systems, etc. 
     The details of one or more variations of the subject matter described herein are set forth in the accompanying drawings and the description below. Other features and advantages of the subject matter described herein will be apparent from the description and drawings, and from the claims. 
    
    
     
       DESCRIPTION OF DRAWINGS 
         FIG.  1    is a system diagram illustrating an example database system for use in connection with the current subject matter; 
         FIG.  2    is a system diagram illustrating an example database system that can support distribution of server components across multiple hosts for scalability and/or availability purposes for use in connection with the current subject matter; 
         FIG.  3    is a diagram illustrating an architecture for an index server for use in connection with the current subject matter; 
         FIG.  4    is a process flow diagram illustrating the use of superblocks as part of a database recovery; and 
         FIG.  5    is a diagram illustrating a sample computing device architecture for implementing various aspects described herein. 
     
    
    
     Like reference symbols in the various drawings indicate like elements. 
     DETAILED DESCRIPTION 
     The current subject matter is directed to techniques for combining smaller pages into superblocks for enhanced database recovery processes. The pages encapsulated within such superblocks are encrypted in parallel using a plurality of threads for significantly reducing recovery times. 
       FIG.  1    is a diagram  100  illustrating a database system  105  that can be used to implement aspects of the current subject matter. The database system  105  can, for example, be an in-memory database in which all relevant data is kept in main memory so that read operations can be executed without disk I/O and in which disk storage is required to make any changes durables. The database system  105  can include a plurality of servers including, for example, one or more of an index server  110 , a name server  115 , and/or an application services server  120 . The database system  105  can also include one or more of an extended store server  125 , a database deployment infrastructure (DDI) server  130 , a data provisioning server  135 , and/or a streaming cluster  140 . The database system  105  can be accessed by a plurality of remote clients  145 ,  150  via different protocols such as SQL/MDX (by way of the index server  110 ) and/or web-based protocols such as HTTP (by way of the application services server  120 ). 
     The index server  110  can contain in-memory data stores and engines for processing data. The index server  110  can also be accessed by remote tools (via, for example, SQL queries), that can provide various development environment and administration tools. Additional details regarding an example implementation of the index server  110  is described and illustrated in connection with diagram  300  of  FIG.  3   . 
     The name server  115  can own information about the topology of the database system  105 . In a distributed database system, the name server  115  can know where various components are running and which data is located on which server. In a database system  105  with multiple database containers, the name server  115  can have information about existing database containers and it can also hosts the system database. For example, the name server  115  can manage the information about existing tenant databases. Unlike a name server  115  in a single-container system, the name server  115  in a database system  105  having multiple database containers does not store topology information such as the location of tables in a distributed database. In a multi-container database system  105  such database-level topology information can be stored as part of the catalogs of the tenant databases. 
     The application services server  120  can enable native web applications used by one or more remote clients  150  accessing the database system  105  via a web protocol such as HTTP. The application services server  120  can allow developers to write and run various database applications without the need to run an additional application server. The application services server  120  can also be used to run web-based tools  155  for administration, life-cycle management and development. Other administration and development tools  160  can directly access the index server  110  for, example, via SQL and other protocols. 
     The extended store server  125  can be part of a dynamic tiering option that can include a high-performance disk-based column store for very big data up to the petabyte range and beyond. Less frequently accessed data (for which is it non-optimal to maintain in main memory of the index server  110 ) can be put into the extended store server  125 . The dynamic tiering of the extended store server  125  allows for hosting of very large databases with a reduced cost of ownership as compared to conventional arrangements. 
     The DDI server  130  can be a separate server process that is part of a database deployment infrastructure (DDI). The DDI can be a layer of the database system  105  that simplifies the deployment of database objects using declarative design time artifacts. DDI can ensure a consistent deployment, for example by guaranteeing that multiple objects are deployed in the right sequence based on dependencies, and by implementing a transactional all-or-nothing deployment. 
     The data provisioning server  135  can provide enterprise information management and enable capabilities such as data provisioning in real time and batch mode, real-time data transformations, data quality functions, adapters for various types of remote sources, and an adapter SDK for developing additional adapters. 
     The streaming cluster  140  allows for various types of data streams (i.e., data feeds, etc.) to be utilized by the database system  105 . The streaming cluster  140  allows for both consumption of data streams and for complex event processing. 
       FIG.  2    is a diagram  200  illustrating a variation of the database system  105  that can support distribution of server components across multiple hosts for scalability and/or availability purposes. This database system  105  can, for example, be identified by a single system ID (SID) and it is perceived as one unit from the perspective of an administrator, who can install, update, start up, shut down, or backup the system as a whole. The different components of the database system  105  can share the same metadata, and requests from client applications  150  can be transparently dispatched to different servers  110   1-3 ,  120   1-3 , in the system, if required. 
     As is illustrated in  FIG.  2   , the distributed database system  105  can be installed on more than one host  210   1-3 . Each host  210   1-3  is a machine that can comprise at least one data processor (e.g., a CPU, etc.), memory, storage, a network interface, and an operation system and which executes part of the database system  105 . Each host  210   1-3  can execute a database instance  220   1-3  which comprises the set of components of the distributed database system  105  that are installed on one host  210   1-3 .  FIG.  2    shows a distributed system with three hosts, which each run a name server  110   1-3 , index server  120   1-3 , and so on (other components are omitted to simplify the illustration). 
       FIG.  3    is a diagram  300  illustrating an architecture for the index server  110  (which can, as indicated above, be one of many instances). A connection and session management component  302  can create and manage sessions and connections for the client applications  150 . For each session, a set of parameters can be maintained such as, for example, auto commit settings or the current transaction isolation level. 
     Requests from the client applications  150  can be processed and executed by way of a request processing and execution control component  310 . The database system  105  offers rich programming capabilities for running application-specific calculations inside the database system. In addition to SQL, MDX, and WIPE, the database system  105  can provide different programming languages for different use cases. SQLScript can be used to write database procedures and user defined functions that can be used in SQL statements. The L language is an imperative language, which can be used to implement operator logic that can be called by SQLScript procedures and for writing user-defined functions. 
     Once a session is established, client applications  150  typically use SQL statements to communicate with the index server  110  which can be handled by a SQL processor  312  within the request processing and execution control component  310 . Analytical applications can use the multidimensional query language MDX (MultiDimensional eXpressions) via an MDX processor  322 . For graph data, applications can use GEM (Graph Query and Manipulation) via a GEM processor  316 , a graph query and manipulation language. SQL statements and MDX queries can be sent over the same connection with the client application  150  using the same network communication protocol. GEM statements can be sent using a built-in SQL system procedure. 
     The index server  110  can include an authentication component  304  that can be invoked with a new connection with a client application  150  is established. Users can be authenticated either by the database system  105  itself (login with user and password) or authentication can be delegated to an external authentication provider. An authorization manager  306  can be invoked by other components of the database system  105  to check whether the user has the required privileges to execute the requested operations. 
     Each statement can processed in the context of a transaction. New sessions can be implicitly assigned to a new transaction. The index server  110  can include a transaction manager  344  that coordinates transactions, controls transactional isolation, and keeps track of running and closed transactions. When a transaction is committed or rolled back, the transaction manager  344  can inform the involved engines about this event so they can execute necessary actions. The transaction manager  344  can provide various types of concurrency control and it can cooperate with a persistence layer  346  to achieve atomic and durable transactions. 
     Incoming SQL requests from the client applications  150  can be e received by the SQL processor  312 . Data manipulation statements can be executed by the SQL processor  312  itself. Other types of requests can be delegated to the respective components. Data definition statements can be dispatched to a metadata manager  306 , transaction control statements can be forwarded to the transaction manager  344 , planning commands can be routed to a planning engine  318 , and task related commands can forwarded to a task manager  324  (which can be part of a larger task framework) Incoming MDX requests can be delegated to the MDX processor  322 . Procedure calls can be forwarded to the procedure processor  314 , which further dispatches the calls, for example to a calculation engine  326 , the GEM processor  316 , a repository  300 , or a DDI proxy  328 . 
     The index server  110  can also include a planning engine  318  that allows planning applications, for instance for financial planning, to execute basic planning operations in the database layer. One such basic operation is to create a new version of a data set as a copy of an existing one while applying filters and transformations. For example, planning data for a new year can be created as a copy of the data from the previous year. Another example for a planning operation is the disaggregation operation that distributes target values from higher to lower aggregation levels based on a distribution function. 
     The SQL processor  312  can include an enterprise performance management (EPM) runtime component  320  that can form part of a larger platform providing an infrastructure for developing and running enterprise performance management applications on the database system  105 . While the planning engine  318  can provide basic planning operations, the EPM platform provides a foundation for complete planning applications, based on by application-specific planning models managed in the database system  105 . 
     The calculation engine  326  can provide a common infrastructure that implements various features such as SQLScript, MDX, GEM, tasks, and planning operations. The SQLScript processor  312 , the MDX processor  322 , the planning engine  318 , the task manager  324 , and the GEM processor  316  can translate the different programming languages, query languages, and models into a common representation that is optimized and executed by the calculation engine  326 . The calculation engine  326  can implement those features using temporary results  340  which can be based, in part, on data within the relational stores  332 . 
     Metadata can be accessed via the metadata manager component  306 . Metadata, in this context, can comprise a variety of objects, such as definitions of relational tables, columns, views, indexes and procedures. Metadata of all these types can be stored in one common database catalog for all stores. The database catalog can be stored in tables in a row store  336  forming part of a group of relational stores  332 . Other aspects of the database system  105  including, for example, support and multi-version concurrency control can also be used for metadata management. In distributed systems, central metadata is shared across servers and the metadata manager component  306  can coordinate or otherwise manage such sharing. 
     The relational stores  332  form the different data management components of the index server  110  and these relational stores can, for example, store data in main memory. The row store  336 , a column store  338 , and a federation component  334  are all relational data stores which can provide access to data organized in relational tables. The column store  338  can stores relational tables column-wise (i.e., in a column-oriented fashion, etc.). The column store  338  can also comprise text search and analysis capabilities, support for spatial data, and operators and storage for graph-structured data. With regard to graph-structured data, from an application viewpoint, the column store  338  could be viewed as a non-relational and schema-flexible in-memory data store for graph-structured data. However, technically such a graph store is not a separate physical data store. Instead it is built using the column store  338 , which can have a dedicated graph API. 
     The row store  336  can stores relational tables row-wise. When a table is created, the creator can specify whether it should be row or column-based. Tables can be migrated between the two storage formats. While certain SQL extensions are only available for one kind of table (such as the “merge” command for column tables), standard SQL can be used on all tables. The index server  110  also provides functionality to combine both kinds of tables in one statement (join, sub query, union). 
     The federation component  334  can be viewed as a virtual relational data store. The federation component  334  can provide access to remote data in external data source system(s)  354  through virtual tables, which can be used in SQL queries in a fashion similar to normal tables. 
     The database system  105  can include an integration of a non-relational data store  342  into the index server  110 . For example, the non-relational data store  342  can have data represented as networks of C++ objects, which can be persisted to disk. The non-relational data store  342  can be used, for example, for optimization and planning tasks that operate on large networks of data objects, for example in supply chain management. Unlike the row store  336  and the column store  338 , the non-relational data store  342  does not use relational tables; rather, objects can be directly stored in containers provided by the persistence layer  346 . Fixed size entry containers can be used to store objects of one class. Persisted objects can be loaded via their persisted object IDs, which can also be used to persist references between objects. In addition, access via in-memory indexes is supported. In that case, the objects need to contain search keys. The in-memory search index is created on first access. The non-relational data store  342  can be integrated with the transaction manager  344  to extends transaction management with sub-transactions, and to also provide a different locking protocol and implementation of multi version concurrency control. 
     An extended store is another relational store that can be used or otherwise form part of the database system  105 . The extended store can, for example, be a disk-based column store optimized for managing very big tables, which ones do not want to keep in memory (as with the relational stores  332 ). The extended store can run in an extended store server  125  separate from the index server  110 . The index server  110  can use the federation component  334  to send SQL statements to the extended store server  125 . 
     The persistence layer  346  is responsible for durability and atomicity of transactions. The persistence layer  346  can ensure that the database system  105  is restored to the most recent committed state after a restart and that transactions are either completely executed or completely undone. To achieve this goal in an efficient way, the persistence layer  346  can use a combination of write-ahead logs, undo and cleanup logs, shadow paging and savepoints. The persistence layer  346  can provide interfaces for writing and reading persisted data and it can also contain a logger component that manages a recovery log. Recovery log entries can be written in the persistence layer  346  (in recovery log volumes  352 ) explicitly by using a log interface or implicitly when using the virtual file abstraction. The recovery log volumes  352  can include redo logs which specify database operations to be replayed whereas data volume  350  contains undo logs which specify database operations to be undone as well as cleanup logs of committed operations which can be executed by a garbage collection process to reorganize the data area (e.g. free up space occupied by deleted data etc.). 
     The persistence layer  346  stores data in persistent disk storage  348  which, in turn, can include data volumes  350  and/or recovery log volumes  352  that can be organized in pages. Different page sizes can be supported, for example, between 4 KB and 16 MB. In addition, superblocks can also be supported which can have a larger size such as 64 MB and which can encapsulate numerous pages of different sizes. Data can be loaded from the disk storage  348  and stored to disk page wise. For read and write access, pages can be loaded into a page buffer in memory. The page buffer need not have a minimum or maximum size, rather, all free memory not used for other things can be used for the page buffer. If the memory is needed elsewhere, least recently used pages can be removed from the cache. If a modified page is chosen to be removed, the page first needs to be persisted to disk storage  348 . While the pages and the page buffer are managed by the persistence layer  346 , the in-memory stores (i.e., the relational stores  332 ) can access data within loaded pages. 
     As noted above, the data volumes  350  can include a data store that together with undo and cleanup log and recovery log volumes  352  comprise the recovery log. Other types of storage arrangements can be utilized depending on the desired configuration. The data store can comprise a snapshot of the corresponding database contents as of the last system savepoint. The snapshot provides a read-only static view of the database as it existed as of the point (i.e., time, etc.) at which it was created. Uncommitted transactions, at such time, are not reflected in the snapshot and are rolled back (i.e., are undone, etc.). Database snapshots operate at the data-page level such that all pages being modified are copied from the source data volume to the snapshot prior to their being modified via a copy-on-write operation. The snapshot can store such original pages thereby preserving the data records as they existed when the snapshot was created. 
     System savepoints (also known in the field of relational database servers as checkpoints) can be periodically or manually generated and provide a point at which the recovery log can be truncated. The savepoint can, in some variations, include an undo log of transactions which were open in the savepoint and/or a cleanup log of transactions which were committed in the savepoint but not yet garbage collected (i.e., data which has been deleted by these transactions has been marked as deleted but has not been deleted in a physical manner to assure multiversion concurrency control). 
     The recovery log can comprise a log of all changes to the database system  105  since the last system savepoint, such that when a database server is restarted, its latest state is restored by replaying the changes from the recovery log on top of the last system savepoint. Typically, in a relational database system, the previous recovery log is cleared whenever a system savepoint occurs, which then starts a new, empty recovery log that will be effective until the next system savepoint. While the recovery log is processed, a new cleanup log is generated which needs to be processed as soon as the commit is replayed to avoid a growing data area because of deleted but not garbage collected data. 
     As part of a database system recovery/restart, after the savepointed state of data is restored, and before processing of the recovery log commences, all cleanup logs can be iterated through and, in implementations using a history manager, passed to the history manager for asynchronous garbage collection processing. 
     In addition, it can be checked if there are older versions of the cleanup log present in the savepoint which need to be processed synchronously with regard to the recovery log. In such cases, recovery log processing can wait until garbage collection of old versions of cleanup logs finish. However, recovery log processing can commence when there are newer versions of cleanup logs for garbage collection. In cases in which no old versions of cleanup logs exist, recovery log replay can start immediately after the cleanup log from the savepoint has been passed to the history manager. 
     A typical savepoint can have three phases. First, in the pre-critical phase all modified pages in the relational stores  332  (which are loaded into memory) can be iterated through and flushed to the physical persistence disk storage  348 . Second, a critical phase can block all parallel updates to pages in the relational stores  332  and trigger all the remaining I/O (i.e., I/O for pages still being modified when entering the critical phase) for the physical persistence disk storage  348  to ensure the consistent state of data. Lastly, a post-critical phase can wait for all remaining I/O associated with the physical persistence disk storage  348 . 
     The database system  105  can be recovered after a failure or other error using information within the recovery log volumes  352  and the data volumes  350 . As part of a recovery operation, pages from the backup storage  348  are streamed into the page buffer in the memory of the database system  105 . These pages can have different sizes from 4 KB to 16 MB, etc. For smaller page sizes, the write I/O can be slow (i.e., processing numerous small pages can create a bottleneck for a resource flushing thread, etc.). In order to overcome this restriction, in some variations, multiple pages can be filled in-memory into a superblock (which is a page of a different, larger size such as 64 MB), then the complete superblock can be written to disk  348 . 
     In order to address the issues with write I/O, pages are copied into a superblock. When the database system  105  utilizes encryption for security purposes, each page is encrypted when the page is put into the superblock by a recovery channel (which is a single thread). Given that this operation is single threaded, the page by page encryption can be a bottleneck which can cause database recovery to require hours and/or days to complete. 
     For normal pages (i.e., non-superblocks, etc.), instead of encrypting such pages in the recovery channel, the pages can be encrypted when being flushed to the disk storage  348 . With superblocks, additional information is required to encrypt each page. Within a recovery channel, the small pages are copied into a superblock and a control block (i.e., the superblock control block) is generated for the superblock. The control block can be a transient object that includes for each page such as an encryption key and an initialization vector (i.e., a fixed-size input to a cryptographic primitive that can be random or pseudorandom, etc.). When the superblock is filled with small pages, a resource flush thread, using a plurality of helper threads (e.g., 64 helper threads, etc.), encrypts the pages in the superblock in parallel using the information within the control block and causes the superblock to be flushed to disk storage  348 . 
     One or more aspects or features of the subject matter described herein can be realized in digital electronic circuitry, integrated circuitry, specially designed application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) computer hardware, firmware, software, and/or combinations thereof. These various aspects or features can include implementation in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device. The programmable system or computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. 
     These computer programs, which can also be referred to as programs, software, software applications, applications, components, or code, include machine instructions for a programmable processor, and can be implemented in a high-level procedural language, an object-oriented programming language, a functional programming language, a logical programming language, and/or in assembly/machine language. As used herein, the term “computer-readable medium” refers to any computer program product, apparatus and/or device, such as for example magnetic discs, optical disks, memory, and Programmable Logic Devices (PLDs), used to provide machine instructions and/or data to a programmable processor, including a computer-readable medium that receives machine instructions as a computer-readable signal. The term “computer-readable signal” refers to any signal used to provide machine instructions and/or data to a programmable processor. The computer-readable medium can store such machine instructions non-transitorily, such as for example as would a non-transient solid-state memory or a magnetic hard drive or any equivalent storage medium. The computer-readable medium can alternatively or additionally store such machine instructions in a transient manner, for example as would a processor cache or other random access memory associated with one or more physical processor cores. 
       FIG.  4    is a process flow diagram in which, at  410 , recovery of an in-memory database is initiated. Thereafter, at  420 , pages for recovery having a size equal to or below a pre-defined threshold (e.g, 64 KB, 128 KB, etc.) are copied to a superblock. Encryption information is added, at  430  for each copied page, to a superblock control block for the superblock. Next, at  440 , the copied pages within the superblock are encrypted using the corresponding encryption information added to the super block control block. The superblock is then, at  450 , flushed from memory of the database to physical persistence. 
       FIG.  5    is a diagram  500  illustrating a sample computing device architecture for implementing various aspects described herein. A bus  504  can serve as the information highway interconnecting the other illustrated components of the hardware. A processing system  508  labeled CPU (central processing unit) (e.g., one or more computer processors/data processors at a given computer or at multiple computers), can perform calculations and logic operations required to execute a program. A non-transitory processor-readable storage medium, such as read only memory (ROM)  512  and random access memory (RAM)  516 , can be in communication with the processing system  508  and can include one or more programming instructions for the operations specified here. Optionally, program instructions can be stored on a non-transitory computer-readable storage medium such as a magnetic disk, optical disk, recordable memory device, flash memory, or other physical storage medium. 
     In one example, a disk controller  548  can interface one or more optional disk drives to the system bus  504 . These disk drives can be external or internal floppy disk drives such as  560 , external or internal CD-ROM, CD-R, CD-RW or DVD, or solid state drives such as  552 , or external or internal hard drives  556 . As indicated previously, these various disk drives  552 ,  556 ,  560  and disk controllers are optional devices. The system bus  504  can also include at least one communication port  520  to allow for communication with external devices either physically connected to the computing system or available externally through a wired or wireless network. In some cases, the communication port  520  includes or otherwise comprises a network interface. 
     To provide for interaction with a user, the subject matter described herein can be implemented on a computing device having a display device  540  (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information obtained from the bus  504  to the user and an input device  532  such as keyboard and/or a pointing device (e.g., a mouse or a trackball) and/or a touchscreen by which the user can provide input to the computer. Other kinds of input devices  532  can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback by way of a microphone  536 , or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input. In the input device  532  and the microphone  536  can be coupled to and convey information via the bus  504  by way of an input device interface  528 . Other computing devices, such as dedicated servers, can omit one or more of the display  540  and display interface  514 , the input device  532 , the microphone  536 , and input device interface  528 . 
     To provide for interaction with a user, the subject matter described herein can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) and/or a touchscreen by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input. 
     In the descriptions above and in the claims, phrases such as “at least one of” or “one or more of” may occur followed by a conjunctive list of elements or features. The term “and/or” may also occur in a list of two or more elements or features. Unless otherwise implicitly or explicitly contradicted by the context in which it is used, such a phrase is intended to mean any of the listed elements or features individually or any of the recited elements or features in combination with any of the other recited elements or features. For example, the phrases “at least one of A and B;” “one or more of A and B;” and “A and/or B” are each intended to mean “A alone, B alone, or A and B together.” A similar interpretation is also intended for lists including three or more items. For example, the phrases “at least one of A, B, and C;” “one or more of A, B, and C;” and “A, B, and/or C” are each intended to mean “A alone, B alone, C alone, A and B together, A and C together, B and C together, or A and B and C together.” In addition, use of the term “based on,” above and in the claims is intended to mean, “based at least in part on,” such that an unrecited feature or element is also permissible. 
     The subject matter described herein can be embodied in systems, apparatus, methods, and/or articles depending on the desired configuration. The implementations set forth in the foregoing description do not represent all implementations consistent with the subject matter described herein. Instead, they are merely some examples consistent with aspects related to the described subject matter. Although a few variations have been described in detail above, other modifications or additions are possible. In particular, further features and/or variations can be provided in addition to those set forth herein. For example, the implementations described above can be directed to various combinations and subcombinations of the disclosed features and/or combinations and subcombinations of several further features disclosed above. In addition, the logic flows depicted in the accompanying figures and/or described herein do not necessarily require the particular order shown, or sequential order, to achieve desirable results. Other implementations may be within the scope of the following claims.