To any experienced batch architect, the overall concepts of batch processing used in Spring Batch should be familiar and comfortable. There are "Jobs" and "Steps" and developer supplied processing units called ItemReaders and ItemWriters. However, because of the Spring patterns, operations, templates, callbacks, and idioms, there are opportunities for the following:
significant improvement in adherence to a clear separation of concerns
clearly delineated architectural layers and services provided as interfaces
simple and default implementations that allow for quick adoption and ease of use out-of-the-box
significantly enhanced extensibility
The diagram below is simplified version of the batch reference architecture that has been used for decades. It provides an overview of the components that make up the domain language of batch processing. This architecture framework is a blueprint that has been proven through decades of implementations on the last several generations of platforms (COBOL/Mainframe, C++/Unix, and now Java/anywhere). JCL and COBOL developers are likely to be as comfortable with the concepts as C++, C# and Java developers. Spring Batch provides a physical implementation of the layers, components and technical services commonly found in robust, maintainable systems used to address the creation of simple to complex batch applications, with the infrastructure and extensions to address very complex processing needs.
The diagram above highlights the key concepts that make up the domain language of batch. A Job has one to many steps, which has exactly one ItemReader, ItemProcessor, and ItemWriter. A job needs to be launched (JobLauncher), and meta data about the currently running process needs to be stored (JobRepository).
This section describes stereotypes relating to the concept of a
batch job. A Job
is an entity that encapsulates an
entire batch process. As is common with other Spring projects, a
Job
will be wired together via an XML configuration
file or Java based configuration. This configuration may be referred to as
the "job configuration". However, Job
is just the
top of an overall hierarchy:
In Spring Batch, a Job is simply a container for Steps. It combines multiple steps that belong logically together in a flow and allows for configuration of properties global to all steps, such as restartability. The job configuration contains:
The simple name of the job
Definition and ordering of Steps
Whether or not the job is restartable
A default simple implementation of the Job
interface is provided by Spring Batch in the form of the
SimpleJob
class which creates some standard
functionality on top of Job
, however the batch
namespace abstracts away the need to instantiate it directly. Instead, the
<job>
tag can be used:
<job id="footballJob"> <step id="playerload" next="gameLoad"/> <step id="gameLoad" next="playerSummarization"/> <step id="playerSummarization"/> </job>
A JobInstance
refers to the concept of a
logical job run. Let's consider a batch job that should be run once at
the end of the day, such as the 'EndOfDay' job from the diagram above.
There is one 'EndOfDay' Job
, but each individual
run of the Job
must be tracked separately. In the
case of this job, there will be one logical
JobInstance
per day. For example, there will be a
January 1st run, and a January 2nd run. If the January 1st run fails the
first time and is run again the next day, it is still the January 1st
run. (Usually this corresponds with the data it is processing as well,
meaning the January 1st run processes data for January 1st, etc).
Therefore, each JobInstance
can have multiple
executions (JobExecution
is discussed in more
detail below) and only one JobInstance
corresponding to a particular Job
and
identifying JobParameter
s can be running at a given
time.
The definition of a JobInstance
has
absolutely no bearing on the data the will be loaded. It is entirely up
to the ItemReader
implementation used to
determine how data will be loaded. For example, in the EndOfDay
scenario, there may be a column on the data that indicates the
'effective date' or 'schedule date' to which the data belongs. So, the
January 1st run would only load data from the 1st, and the January 2nd
run would only use data from the 2nd. Because this determination will
likely be a business decision, it is left up to the
ItemReader
to decide. What using the same
JobInstance
will determine, however, is whether
or not the 'state' (i.e. the ExecutionContext
,
which is discussed below) from previous executions will be used. Using a
new JobInstance
will mean 'start from the
beginning' and using an existing instance will generally mean 'start
from where you left off'.
Having discussed JobInstance
and how it
differs from Job
, the natural question to ask is:
"how is one JobInstance
distinguished from
another?" The answer is: JobParameters
.
JobParameters
is a set of parameters used to
start a batch job. They can be used for identification or even as
reference data during the run:
In the example above, where there are two instances, one for
January 1st, and another for January 2nd, there is really only one Job,
one that was started with a job parameter of 01-01-2008 and another that
was started with a parameter of 01-02-2008. Thus, the contract can be
defined as: JobInstance
=
Job
+ identifying JobParameters
. This
allows a developer to effectively control how a
JobInstance
is defined, since they control what
parameters are passed in.
Note | |
---|---|
Not all job parameters are required to contribute to the identification
of a |
A JobExecution
refers to the technical
concept of a single attempt to run a Job
. An
execution may end in failure or success, but the
JobInstance
corresponding to a given execution
will not be considered complete unless the execution completes
successfully. Using the EndOfDay Job
described
above as an example, consider a JobInstance
for
01-01-2008 that failed the first time it was run. If it is run again
with the same identifying job parameters as the first run (01-01-2008), a new
JobExecution
will be created. However, there will
still be only one JobInstance
.
A Job
defines what a job is and how it is
to be executed, and JobInstance
is a purely
organizational object to group executions together, primarily to enable
correct restart semantics. A JobExecution
,
however, is the primary storage mechanism for what actually happened
during a run, and as such contains many more properties that must be
controlled and persisted:
Table 3.1. JobExecution Properties
status | A BatchStatus object that
indicates the status of the execution. While running, it's
BatchStatus.STARTED, if it fails, it's BatchStatus.FAILED, and
if it finishes successfully, it's BatchStatus.COMPLETED |
startTime | A java.util.Date representing the
current system time when the execution was started. |
endTime | A java.util.Date representing the
current system time when the execution finished, regardless of
whether or not it was successful. |
exitStatus | The ExitStatus indicating the
result of the run. It is most important because it contains an
exit code that will be returned to the caller. See chapter 5 for
more details. |
createTime | A java.util.Date representing the
current system time when the JobExecution
was first persisted. The job may not have been started yet (and
thus has no start time), but it will always have a createTime,
which is required by the framework for managing job level
ExecutionContext s. |
lastUpdated | A java.util.Date representing the
last time a JobExecution was
persisted. |
executionContext | The 'property bag' containing any user data that needs to be persisted between executions. |
failureExceptions | The list of exceptions encountered during the execution
of a Job . These can be useful if more
than one exception is encountered during the failure of a
Job . |
These properties are important because they will be persisted and can be used to completely determine the status of an execution. For example, if the EndOfDay job for 01-01 is executed at 9:00 PM, and fails at 9:30, the following entries will be made in the batch meta data tables:
Table 3.3. BATCH_JOB_EXECUTION_PARAMS
JOB_EXECUTION_ID | TYPE_CD | KEY_NAME | DATE_VAL | IDENTIFYING |
1 | DATE | schedule.Date | 2008-01-01 | TRUE |
Table 3.4. BATCH_JOB_EXECUTION
JOB_EXEC_ID | JOB_INST_ID | START_TIME | END_TIME | STATUS |
1 | 1 | 2008-01-01 21:00 | 2008-01-01 21:30 | FAILED |
Note | |
---|---|
column names may have been abbreviated or removed for clarity and formatting |
Now that the job has failed, let's assume that it took the entire
course of the night for the problem to be determined, so that the 'batch
window' is now closed. Assuming the window starts at 9:00 PM, the job
will be kicked off again for 01-01, starting where it left off and
completing successfully at 9:30. Because it's now the next day, the
01-02 job must be run as well, which is kicked off just afterwards at
9:31, and completes in its normal one hour time at 10:30. There is no
requirement that one JobInstance
be kicked off
after another, unless there is potential for the two jobs to attempt to
access the same data, causing issues with locking at the database level.
It is entirely up to the scheduler to determine when a
Job
should be run. Since they're separate
JobInstance
s, Spring Batch will make no attempt
to stop them from being run concurrently. (Attempting to run the same
JobInstance
while another is already running will
result in a JobExecutionAlreadyRunningException
being thrown). There should now be an extra entry in both the
JobInstance
and
JobParameters
tables, and two extra entries in
the JobExecution
table:
Table 3.6. BATCH_JOB_EXECUTION_PARAMS
JOB_EXECUTION_ID | TYPE_CD | KEY_NAME | DATE_VAL | IDENTIFYING |
1 | DATE | schedule.Date | 2008-01-01 00:00:00 | TRUE |
2 | DATE | schedule.Date | 2008-01-01 00:00:00 | TRUE |
3 | DATE | schedule.Date | 2008-01-02 00:00:00 | TRUE |
Table 3.7. BATCH_JOB_EXECUTION
JOB_EXEC_ID | JOB_INST_ID | START_TIME | END_TIME | STATUS |
1 | 1 | 2008-01-01 21:00 | 2008-01-01 21:30 | FAILED |
2 | 1 | 2008-01-02 21:00 | 2008-01-02 21:30 | COMPLETED |
3 | 2 | 2008-01-02 21:31 | 2008-01-02 22:29 | COMPLETED |
Note | |
---|---|
column names may have been abbreviated or removed for clarity and formatting |
A Step
is a domain object that encapsulates
an independent, sequential phase of a batch job. Therefore, every
Job
is composed entirely of one or more steps. A
Step
contains all of the information necessary to
define and control the actual batch processing. This is a necessarily
vague description because the contents of any given
Step
are at the discretion of the developer writing
a Job
. A Step can be as simple or complex as the
developer desires. A simple Step
might load data
from a file into the database, requiring little or no code. (depending
upon the implementations used) A more complex Step
may have complicated business rules that are applied as part of the
processing. As with Job
, a
Step
has an individual
StepExecution
that corresponds with a unique
JobExecution
:
A StepExecution
represents a single attempt
to execute a Step
. A new
StepExecution
will be created each time a
Step
is run, similar to
JobExecution
. However, if a step fails to execute
because the step before it fails, there will be no execution persisted
for it. A StepExecution
will only be created when
its Step
is actually started.
Step executions are represented by objects of the
StepExecution
class. Each execution contains a
reference to its corresponding step and
JobExecution
, and transaction related data such
as commit and rollback count and start and end times. Additionally, each
step execution will contain an ExecutionContext
,
which contains any data a developer needs persisted across batch runs,
such as statistics or state information needed to restart. The following
is a listing of the properties for
StepExecution
:
Table 3.8. StepExecution Properties
status | A BatchStatus object that
indicates the status of the execution. While it's running, the
status is BatchStatus.STARTED, if it fails, the status is
BatchStatus.FAILED, and if it finishes successfully, the status
is BatchStatus.COMPLETED |
startTime | A java.util.Date representing the
current system time when the execution was started. |
endTime | A java.util.Date representing the
current system time when the execution finished, regardless of
whether or not it was successful. |
exitStatus | The ExitStatus indicating the
result of the execution. It is most important because it
contains an exit code that will be returned to the caller. See
chapter 5 for more details. |
executionContext | The 'property bag' containing any user data that needs to be persisted between executions. |
readCount | The number of items that have been successfully read |
writeCount | The number of items that have been successfully written |
commitCount | The number transactions that have been committed for this execution |
rollbackCount | The number of times the business transaction controlled
by the Step has been rolled back. |
readSkipCount | The number of times read has
failed, resulting in a skipped item. |
processSkipCount | The number of times process has
failed, resulting in a skipped item. |
filterCount | The number of items that have been 'filtered' by the
ItemProcessor . |
writeSkipCount | The number of times write has
failed, resulting in a skipped item. |
An ExecutionContext
represents a collection
of key/value pairs that are persisted and controlled by the framework in
order to allow developers a place to store persistent state that is scoped
to a StepExecution
or
JobExecution
. For those familiar with Quartz, it is
very similar to JobDataMap
. The best usage example
is to facilitate restart. Using flat file input as an example, while
processing individual lines, the framework periodically persists the
ExecutionContext
at commit points. This allows the
ItemReader
to store its state in case a fatal error
occurs during the run, or even if the power goes out. All that is needed
is to put the current number of lines read into the context, and the
framework will do the rest:
executionContext.putLong(getKey(LINES_READ_COUNT), reader.getPosition());
Using the EndOfDay example from the Job Stereotypes section as an example, assume there's one step: 'loadData', that loads a file into the database. After the first failed run, the meta data tables would look like the following:
Table 3.11. BATCH_JOB_EXECUTION
JOB_EXEC_ID | JOB_INST_ID | START_TIME | END_TIME | STATUS |
1 | 1 | 2008-01-01 21:00 | 2008-01-01 21:30 | FAILED |
Table 3.12. BATCH_STEP_EXECUTION
STEP_EXEC_ID | JOB_EXEC_ID | STEP_NAME | START_TIME | END_TIME | STATUS |
1 | 1 | loadDate | 2008-01-01 21:00 | 2008-01-01 21:30 | FAILED |
In this case, the Step
ran for 30 minutes
and processed 40,321 'pieces', which would represent lines in a file in
this scenario. This value will be updated just before each commit by the
framework, and can contain multiple rows corresponding to entries within
the ExecutionContext
. Being notified before a
commit requires one of the various StepListener
s,
or an ItemStream
, which are discussed in more
detail later in this guide. As with the previous example, it is assumed
that the Job
is restarted the next day. When it is
restarted, the values from the ExecutionContext
of
the last run are reconstituted from the database, and when the
ItemReader
is opened, it can check to see if it has
any stored state in the context, and initialize itself from there:
if (executionContext.containsKey(getKey(LINES_READ_COUNT))) { log.debug("Initializing for restart. Restart data is: " + executionContext); long lineCount = executionContext.getLong(getKey(LINES_READ_COUNT)); LineReader reader = getReader(); Object record = ""; while (reader.getPosition() < lineCount && record != null) { record = readLine(); } }
In this case, after the above code is executed, the current line
will be 40,322, allowing the Step
to start again
from where it left off. The ExecutionContext
can
also be used for statistics that need to be persisted about the run
itself. For example, if a flat file contains orders for processing that
exist across multiple lines, it may be necessary to store how many orders
have been processed (which is much different from than the number of lines
read) so that an email can be sent at the end of the
Step
with the total orders processed in the body.
The framework handles storing this for the developer, in order to
correctly scope it with an individual JobInstance
.
It can be very difficult to know whether an existing
ExecutionContext
should be used or not. For
example, using the 'EndOfDay' example from above, when the 01-01 run
starts again for the second time, the framework recognizes that it is the
same JobInstance
and on an individual
Step
basis, pulls the
ExecutionContext
out of the database and hands it
as part of the StepExecution
to the
Step
itself. Conversely, for the 01-02 run the
framework recognizes that it is a different instance, so an empty context
must be handed to the Step
. There are many of these
types of determinations that the framework makes for the developer to
ensure the state is given to them at the correct time. It is also
important to note that exactly one ExecutionContext
exists per StepExecution
at any given time. Clients
of the ExecutionContext
should be careful because
this creates a shared keyspace, so care should be taken when putting
values in to ensure no data is overwritten. However, the
Step
stores absolutely no data in the context, so
there is no way to adversely affect the framework.
It is also important to note that there is at least one
ExecutionContext
per
JobExecution
, and one for every
StepExecution
. For example, consider the following
code snippet:
ExecutionContext ecStep = stepExecution.getExecutionContext();
ExecutionContext ecJob = jobExecution.getExecutionContext();
//ecStep does not equal ecJob
As noted in the comment, ecStep will not equal ecJob; they are two
different ExecutionContext
s. The one scoped to the
Step
will be saved at every commit point in the
Step
, whereas the one scoped to the
Job
will be saved in between every
Step
execution.
JobRepository
is the persistence mechanism
for all of the Stereotypes mentioned above. It provides CRUD operations
for JobLauncher
, Job
, and
Step
implementations. When a
Job
is first launched, a
JobExecution
is obtained from the repository, and
during the course of execution StepExecution
and
JobExecution
implementations are persisted by
passing them to the repository:
<job-repository id="jobRepository"/>
JobLauncher
represents a simple interface for
launching a Job
with a given set of
JobParameters
:
public interface JobLauncher { public JobExecution run(Job job, JobParameters jobParameters) throws JobExecutionAlreadyRunningException, JobRestartException; }
It is expected that implementations will obtain a valid
JobExecution
from the
JobRepository
and execute the
Job
.
ItemReader
is an abstraction that represents
the retrieval of input for a Step
, one item at a
time. When the ItemReader
has exhausted the items
it can provide, it will indicate this by returning null. More details
about the ItemReader
interface and its various
implementations can be found in Chapter 6, ItemReaders and ItemWriters.
ItemWriter
is an abstraction that
represents the output of a Step
, one batch
or chunk of items at a time. Generally, an item writer has no
knowledge of the input it will receive next, only the item that
was passed in its current invocation. More details about the
ItemWriter
interface and its various
implementations can be found in Chapter 6, ItemReaders and ItemWriters.
ItemProcessor
is an abstraction that
represents the business processing of an item. While the
ItemReader
reads one item, and the
ItemWriter
writes them, the
ItemProcessor
provides access to transform or apply
other business processing. If, while processing the item, it is determined
that the item is not valid, returning null indicates that the item should
not be written out. More details about the ItemProcessor interface can be
found in Chapter 6, ItemReaders and ItemWriters.
Many of the domain concepts listed above need to be configured in a
Spring ApplicationContext
. While there are
implementations of the interfaces above that can be used in a standard
bean definition, a namespace has been provided for ease of
configuration:
<beans:beans xmlns="http://www.springframework.org/schema/batch" xmlns:beans="http://www.springframework.org/schema/beans" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation=" http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd http://www.springframework.org/schema/batch http://www.springframework.org/schema/batch/spring-batch-2.2.xsd"> <job id="ioSampleJob"> <step id="step1"> <tasklet> <chunk reader="itemReader" writer="itemWriter" commit-interval="2"/> </tasklet> </step> </job> </beans:beans>
As long as the batch namespace has been declared, any of its
elements can be used. More information on configuring a
Job
can be found in Chapter 4, Configuring and Running a Job. More information on configuring a Step can be
found in Chapter 5, Configuring a Step.