Undo the work performed by a series of steps, which together define an
eventually consistent operation, if one or more of the steps fail.
Operations that follow the eventual consistency model are commonly found
in cloud-hosted applications that implement complex business processes
Context and Problem 背景和题材
Applications running in the cloud frequently modify data. This data may
be spread across an assortment of data sources held in a variety of
geographic locations. To avoid contention and improve performance in a
distributed environment such as this, an application should not attempt
to provide strong transactional consistency. Rather, the application
should implement eventual consistency. In this model, a typical
business operation consists of a series of autonomous steps. While these
steps are being performed the overall view of the system state may be
inconsistent, but when the operation has completed and all of the steps
have been executed the system should become consistent again.
The Data Consistency
more information about why distributed transactions do not scale well,
and the principles that underpin the eventual consistency model.
A significant challenge in the eventual consistency model is how to
handle a step that has failed irrecoverably. In this case it may be
necessary to undo all of the work completed by the previous steps in the
operation. However, the data cannot simply be rolled back because other
concurrent instances of the application may have since changed it. Even
in cases where the data has not been changed by a concurrent instance,
undoing a step might not simply be a matter of restoring the original
state. It may be necessary to apply various business-specific rules (see
the travel website described in the
If an operation that implements eventual consistency spans several
heterogeneous data stores, undoing the steps in such an operation will
require visiting each data store in turn. The work performed in every
data store must be undone reliably to prevent the system from remaining
Not all data affected by an operation that implements eventual
consistency might be held in a database. In a Service Oriented
Architecture (SOA) environment an operation may invoke an action in a
service, and cause a change in the state held by that service. To undo
the operation, this state change must also be undone. This may involve
invoking the service again and performing another action that reverses
the effects of the first.
Implement a compensating transaction. The steps in a compensating
transaction must undo the effects of the steps in the original
operation. A compensating transaction might not be able to simply
replace the current state with the state the system was in at the start
of the operation because this approach could overwrite changes made by
other concurrent instances of an application. Rather, it must be an
intelligent process that takes into account any work done by concurrent
instances. This process will usually be application-specific, driven by
the nature of the work performed by the original operation.
A common approach to implementing an eventually consistent operation
that requires compensation is to use a workflow. As the original
operation proceeds, the system records information about each step and
how the work performed by that step can be undone. If the operation
fails at any point, the workflow rewinds back through the steps it has
completed and performs the work that reverses each step. Note that a
compensating transaction might not have to undo the work in the exact
mirror-opposite order of the original operation, and it may be possible
to perform some of the undo steps in parallel.
亚洲必赢app在哪下载，This approach is similar to the Sagas strategy. A description of this
strategy is available online in Clemens Vasters’
A compensating transaction is itself an eventually consistent operation
and it could also fail. The system should be able to resume the
compensating transaction at the point of failure and continue. It may be
necessary to repeat a step that has failed, so the steps in a
compensating transaction should be defined as idempotent commands. For
more information about idempotency, see Idempotency
on Jonathan Oliver’s blog.
on Jonathan Oliver’s blog。
In some cases it may not be possible to recover from a step that has
failed except through manual intervention. In these situations the
system should raise an alert and provide as much information as possible
about the reason for the failure.
Issues and Considerations 难点和注意事项
Consider the following points when deciding how to implement this
- It might not be easy to determine when a step in an operation that
implements eventual consistency has failed. A step might not fail
immediately, but instead it could block. It may be necessary to
implement some form of time-out mechanism.
- Compensation logic is not easily generalized. A compensating
transaction is application-specific; it relies on the application
having sufficient information to be able to undo the effects of each
step in a failed operation.
- You should define the steps in a compensating transaction as
idempotent commands. This enables the steps to be repeated if the
compensating transaction itself fails.
- The infrastructure that handles the steps in the original operation,
and the compensating transaction, must be resilient. It must not
lose the information required to compensate for a failing step, and
it must be able to reliably monitor the progress of the compensation
- A compensating transaction does not necessarily return the data in
the system to the state it was in at the start of the original
operation. Instead, it compensates for the work performed by the
steps that completed successfully before the operation failed.
- The order of the steps in the compensating transaction does not
necessarily have to be the mirror opposite of the steps in the
original operation. For example, one data store may be more
sensitive to inconsistencies than another, and so the steps in the
compensating transaction that undo the changes to this store should
- Placing a short-term timeout-based lock on each resource that is
required to complete an operation, and obtaining these resources in
advance, can help increase the likelihood that the overall activity
will succeed. The work should be performed only after all the
resources have been acquired. All actions must be finalized before
the locks expire.
- Consider using retry logic that is more forgiving than usual to
minimize failures that trigger a compensating transaction. If a step
in an operation that implements eventual consistency fails, try
handling the failure as a transient exception and repeat the step.
Only abort the operation and initiate a compensating transaction if
a step fails repeatedly or irrecoverably.
Many of the challenges and issues of implementing a compensating
transaction are the same as those concerned with implementing eventual
consistency. See the section Considerations for Implementing Eventual
Consistency in the Data Consistency
Primer for more
When to Use this Pattern 何时利用那种情势
Use this pattern only for operations that must be undone if they fail.
If possible, design solutions to avoid the complexity of requiring
compensating transactions (for more information, see the Data
A travel website enables customers to book itineraries. A single
itinerary may comprise a series of flights and hotels. A customer
traveling from Seattle to London and then on to Paris could perform the
following steps when creating an itinerary:
- Book a seat on flight F1 from Seattle to London.
- Book a seat on flight F2 from London to Paris.
- Book a seat on flight F3 from Paris to Seattle.
- Reserve a room at hotel H1 in London.
- Reserve a room at hotel H2 in Paris.
These steps constitute an eventually consistent operation, although each
step is essentially a separate atomic action in its own right.
Therefore, as well as performing these steps, the system must also
record the counter operations necessary to undo each step in case the
customer decides to cancel the itinerary. The steps necessary to perform
the counter operations can then run as a compensating transaction if
Notice that the steps in the compensating transaction might not be the
exact opposite of the original steps, and the logic in each step in the
compensating transaction must take into account any business-specific
rules. For example, “unbooking” a seat on a flight might not entitle the
customer to a complete refund of any money paid.
Figure 1 – Generating a compensating transaction to undo a long-running
transaction to book a travel itinerary
图1 – 生成补偿事务取消长日子运作的事体预约旅游行程
It may be possible for the steps in the compensating transaction to be
performed in parallel, depending on how you have designed the
compensating logic for each step.
In many business solutions, failure of a single step does not always
necessitate rolling the system back by using a compensating transaction.
For example, if—after having booked flights F1, F2, and F3 in the travel
website scenario—the customer is unable to reserve a room at hotel H1,
it is preferable to offer the customer a room at a different hotel in
the same city rather than cancelling the flights. The customer may still
elect to cancel (in which case the compensating transaction runs and
undoes the bookings made on flights F1, F2, and F3), but this decision
should be made by the customer rather than by the system.
Related Patterns and Guidance 相关格局和指引
The following patterns and guidance may also be relevant when
implementing this pattern:
- Data Consistency
Compensating Transaction pattern is frequently used to undo
operations that implement the eventual consistency model. This
primer provides more information on the benefits and tradeoffs of
This pattern describes how to implement resilient systems that
perform business operations that utilize distributed services and
resources. In some circumstances, it may be necessary to undo the
work performed by an operation by using a compensating transaction.
Compensating transactions can be expensive to perform, and it may be
possible to minimize their use by implementing an effective policy
of retrying failing operations by following the Retry pattern.