104 lines
4.6 KiB
Plaintext
104 lines
4.6 KiB
Plaintext
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[[glossary]]
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[appendix]
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== 术语表
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[glossary]
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=== Spring Batch 术语表
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Batch::
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An accumulation of business transactions over time.
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Batch Application Style::
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Term used to designate batch as an application style in its own right, similar to
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online, Web, or SOA. It has standard elements of input, validation, transformation of
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information to business model, business processing, and output. In addition, it
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requires monitoring at a macro level.
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Batch Processing::
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The handling of a batch of many business transactions that have accumulated over a
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period of time (such as an hour, a day, a week, a month, or a year). It is the
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application of a process or set of processes to many data entities or objects in a
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repetitive and predictable fashion with either no manual element or a separate manual
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element for error processing.
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Batch Window::
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The time frame within which a batch job must complete. This can be constrained by other
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systems coming online, other dependent jobs needing to execute, or other factors
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specific to the batch environment.
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Step::
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The main batch task or unit of work. It initializes the business logic and controls the
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transaction environment, based on commit interval setting and other factors.
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Tasklet::
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A component created by an application developer to process the business logic for a
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Step.
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Batch Job Type::
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Job types describe application of jobs for particular types of processing. Common areas
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are interface processing (typically flat files), forms processing (either for online
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PDF generation or print formats), and report processing.
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Driving Query::
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A driving query identifies the set of work for a job to do. The job then breaks that
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work into individual units of work. For instance, a driving query might be to identify
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all financial transactions that have a status of "pending transmission" and send them
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to a partner system. The driving query returns a set of record IDs to process. Each
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record ID then becomes a unit of work. A driving query may involve a join (if the
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criteria for selection falls across two or more tables) or it may work with a single
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table.
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Item::
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An item represents the smallest amount of complete data for processing. In the simplest
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terms, this might be a line in a file, a row in a database table, or a particular
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element in an XML file.
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Logicial Unit of Work (LUW)::
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A batch job iterates through a driving query (or other input source, such as a file) to
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perform the set of work that the job must accomplish. Each iteration of work performed
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is a unit of work.
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Commit Interval::
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A set of LUWs processed within a single transaction.
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Partitioning::
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Splitting a job into multiple threads where each thread is responsible for a subset of
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the overall data to be processed. The threads of execution may be within the same JVM
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or they may span JVMs in a clustered environment that supports workload balancing.
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Staging Table::
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A table that holds temporary data while it is being processed.
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Restartable::
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A job that can be executed again and assumes the same identity as when run initially.
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In other words, it is has the same job instance ID.
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Rerunnable::
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A job that is restartable and manages its own state in terms of the previous run's
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record processing. An example of a rerunnable step is one based on a driving query. If
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the driving query can be formed so that it limits the processed rows when the job is
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restarted, then it is re-runnable. This is managed by the application logic. Often, a
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condition is added to the `where` statement to limit the rows returned by the driving
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query with logic resembling "and processedFlag!= true".
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Repeat::
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One of the most basic units of batch processing, it defines by repeatability calling a
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portion of code until it is finished and while there is no error. Typically, a batch
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process would be repeatable as long as there is input.
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Retry::
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Simplifies the execution of operations with retry semantics most frequently associated
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with handling transactional output exceptions. Retry is slightly different from repeat,
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rather than continually calling a block of code, retry is stateful and continually
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calls the same block of code with the same input, until it either succeeds or some type
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of retry limit has been exceeded. It is only generally useful when a subsequent
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invocation of the operation might succeed because something in the environment has
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improved.
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Recover::
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Recover operations handle an exception in such a way that a repeat process is able to
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continue.
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Skip::
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Skip is a recovery strategy often used on file input sources as the strategy for
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ignoring bad input records that failed validation.
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