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This version is still in development and is not considered stable yet. For the latest stable version, please use Spring Batch Documentation 5.1.2! |
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This version is still in development and is not considered stable yet. For the latest stable version, please use Spring Batch Documentation 5.1.2! |
Both ItemReaders and ItemWriters serve their individual purposes well, but there is a
common concern among both of them that necessitates another interface. In general, as
part of the scope of a batch job, readers and writers need to be opened, closed, and
require a mechanism for persisting state. The ItemStream interface serves that purpose,
as shown in the following example:
public interface ItemStream {
void open(ExecutionContext executionContext) throws ItemStreamException;
void update(ExecutionContext executionContext) throws ItemStreamException;
void close() throws ItemStreamException;
}Before describing each method, we should mention the ExecutionContext. Clients of an
ItemReader that also implement ItemStream should call open before any calls to
read, in order to open any resources such as files or to obtain connections. A similar
restriction applies to an ItemWriter that implements ItemStream. As mentioned in
Chapter 2, if expected data is found in the ExecutionContext, it may be used to start
the ItemReader or ItemWriter at a location other than its initial state. Conversely,
close is called to ensure that any resources allocated during open are released safely.
update is called primarily to ensure that any state currently being held is loaded into
the provided ExecutionContext. This method is called before committing, to ensure that
the current state is persisted in the database before commit.
In the special case where the client of an ItemStream is a Step (from the Spring
Batch Core), an ExecutionContext is created for each StepExecution to allow users to
store the state of a particular execution, with the expectation that it is returned if
the same JobInstance is started again. For those familiar with Quartz, the semantics
are very similar to a Quartz JobDataMap.