25d3b30704
I fixed sentence errors. Very simple document (as it should be ), so it can't go wrong in very many ways.
119 lines
5.0 KiB
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119 lines
5.0 KiB
Plaintext
[[glossary]]
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[appendix]
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== Glossary
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[glossary]
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=== Spring Batch Glossary
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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
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right, similar to online, Web, or SOA. It has standard elements of
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input, validation, transformation of information to business model,
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business processing, and output. In addition, it requires monitoring at
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a macro level.
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Batch Processing::
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The handling of a batch of many business transactions that have
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accumulated over a period of time (such as an hour, a day, a week, a month, or
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a year). It is the application of a process or set of processes to
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many data entities or objects in a repetitive and predictable fashion
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with either no manual element or a separate manual element for error
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processing.
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Batch Window::
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The time frame within which a batch job must complete. This can
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be constrained by other systems coming online, other dependent jobs
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needing to execute, or other factors specific to the batch
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environment.
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Step::
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The main batch task or unit of work. It
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initializes the business logic and controls the transaction
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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
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business logic for a Step.
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Batch Job Type::
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Job types describe application of jobs for particular types of
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processing. Common areas are interface processing (typically flat
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files), forms processing (either for online pdf generation or print
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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
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job then breaks that work into individual units of work. For instance, a driving query might be to
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identify all financial transactions that have a status of "pending
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transmission" and send them to a partner system. The driving query
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returns a set of record IDs to process. Each record ID then becomes a
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unit of work. A driving query may involve a join (if the criteria for
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selection falls across two or more tables) or it may work with a
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single table.
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Item::
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An item represents the smallest amount of complete data for
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processing. In the simplest terms, this might be a line in a file, a
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row in a database table, or a particular element in an XML
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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
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source, such as a file) to perform the set of work that the job must
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accomplish. Each iteration of work performed 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
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responsible for a subset of the overall data to be processed. The
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threads of execution may be within the same JVM or they may span JVMs
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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
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processed.
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Restartable::
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A job that can be executed again and assumes the same
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identity as when run initially. In other words, it is has the same job
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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
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previous run's record processing. An example of a rerunnable step is
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one based on a driving query. If the driving query can be formed so
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that it limits the processed rows when the job is restarted, then
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it is re-runnable. This is managed by the application logic. Often,
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a condition is added to the `where` statement to limit the rows
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returned by the driving query with logic resembling "and processedFlag
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!= true".
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Repeat::
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One of the most basic units of batch processing, it defines by
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repeatability calling a portion of code until it is finished and
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while there is no error. Typically, a batch process would be repeatable
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as long as there is input.
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Retry::
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Simplifies the execution of operations with retry semantics most
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frequently associated with handling transactional output exceptions.
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Retry is slightly different from repeat, rather than continually
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calling a block of code, retry is stateful and continually calls the
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same block of code with the same input, until it either succeeds or
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some type of retry limit has been exceeded. It is only generally
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useful when a subsequent invocation of the operation might succeed
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because something in the environment has improved.
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Recover::
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Recover operations handle an exception in such a way that a
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repeat process is able to continue.
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Skip::
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Skip is a recovery strategy often used on file input sources as
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the strategy for ignoring bad input records that failed
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validation.
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