Spring Transaction Management- Multiple request to same URL - spring

I am trying to create an API in Spring Boot using #Transactional annotation regarding bank fund transfer.
Now I want to know - if there are multiple calls to the same API at the same time, how to manage transaction between them. Suppose for example transferBalance method is called by Transaction X which transfers funds from accounts A to B and another transaction Transaction Y transfer funds from B to C. Both transactions occur at the same time. How would these transactions be handled? What propagation should it have and also what about the isolation?

Check this below changes: for your case check bold description below.
if more than one transaction can also go with SERIALIZED
Isolation level defines how the changes made to some data repository by one transaction affect other simultaneous concurrent transactions, and also how and when that changed data becomes available to other transactions. When we define a transaction using the Spring framework we are also able to configure in which isolation level that same transaction will be executed.
#Transactional(isolation=Isolation.READ_COMMITTED)
public void someTransactionalMethod(Object obj) {
}
READ_UNCOMMITTED isolation level states that a transaction may read data that is still uncommitted by other transactions.
READ_COMMITTED isolation level states that a transaction can't read data that is not yet committed by other transactions.
REPEATABLE_READ isolation level states that if a transaction reads one record from the database multiple times the result of all those reading operations must always be the same.
SERIALIZABLE isolation level is the most restrictive of all isolation levels. Transactions are executed with locking at all levels (read, range and write locking) so they appear as if they were executed in a serialized way.

Your doubt has nothing to do with #Transactional.
Its simple question of concurrency.
Actually both the transaction, form a to b and form b to c can work concurrently.
By putting #Transactional states something like
works out whether a given exception should cause transaction rollback by applying a number of rollback rules, both positive and negative. If no rules are relevant to the exception, it behaves like DefaultTransactionAttribute (rolling back on runtime exceptions).

Related

How to rollback distributed transactions?

I have three different Spring boot Projects with separated databases e.g account-rest, payment-rest, gateway-rest.
account-rest : create a new account
payment-rest : create a new payment
gateway-rest : calls other endpoints
at gateway-rest there is an endpoint which calls the other two endpoints.
#GetMapping("/gateway-api")
#org.springframework.transaction.annotation.Transactional(rollbackFor = RuntimeException.class)
public String getApi()
{
String accountId = restTemplate.getForObject("http://localhost:8686/account", String.class);
restTemplate.getForObject("http://localhost:8585/payment?accid="+accountId, String.class);
throw new RuntimeException("rollback everything");
}
I want to rollback transactions and revert everything when I throw exception at gateway or anyother endpoints.
How can I do that ?
It is impossible rollback external dependencies accessible via rest or something like that.
The only think that you can do is compensate errors, you can use pattern like SAGA
I hope that is can help you
You are basically doing dual persistence. That's not ideally a good thing because of 2 reasons
It increases the latency and thus have a direct impact on user experience
What if one of them fails?
As the other answer pointed out SAGA pattern is an option to post compensation transaction.
The other option and it's better to go with this by all means is to avoid dual persistence by writing to only one service synchronously and then use Change Data Capture (CDC) to asynchronously upate the other service. If we can design in this way, we can ensure atomicity (all or nothing) and thus probably the rollback scenario itself will not surface.
Refer to these two answers also, if they help:
https://stackoverflow.com/a/54676222/1235935
https://stackoverflow.com/a/54527066/1235935
By all means avoid distributed transactions or 2-phase commit. It's not a good solution and creates lot of operational overhead, locking etc. when the transaction co-ordinator fails after prepare phase and before commit phase. Worse things happen when transaction co-ordinator gets its data corrupted.
For that purpose you need external transaction management system. It will handle distributed transations and commit/rollback when its finished on all services.
Possible flow example:
Request coming
gateway-rest starts a distributed transaction and local transaction and sends a request(with transaction id) to payment-rest. Thread with transaction lives until all local transactions is finished.
payment-rest knows about global transaction and starts own local transaction.
When all local transactions marked as commited, TM(transaction manager) sends a request to each service to close local transactions and close global transaction.
In your case you can use sagas as mentioned by many others, but they require events and async in nature.
if you want a sync kind of API. you can do something similar to this:
first lets take an example in case of amazon, for creating a order and getting balance out of your wallet and completing the order:
create Order in PendingState
reserveBalance in Account service for order id
if balance reserved change Order state to Confirmed (also having the transaction id for the reserve) and update reserveBalanceConsumed to Account Service
else change Order state to Cancelled with reason , "not enough Balance"
Now there are cases where lets says account service balance is reserved but for some reason order is either not confirmed.
Then somebody could periodically check that if there are reserve Balance for some order and time>30 min let say then check whether that order is marked as confirmed with that trnasaction id , call reserveBalanceConsumed , else cancel that order with reason "some error please try again" , mark balance as free
NOW THESE TYPE OF SYSTEMS ARE COMPLEX TO BUILD. Use the Saga pattern in general for simpler structure.

How to avoid two bookings when one create booking at same time where the available booking count 1

I am beginner to spring , now in my project we have method to make booking ,now if the available booking is 1 , when two user are trying booking at same time ideally only one booking is allowed , but my application is allowing two bookings, now i made the method as synchronized now it is working fine, but synchronization concept belongs to JVM now if I am configuring my application in cluster mode there are different servers in different machines(so different JVMS), now synchronization wont work.
Can any one please tell me the possible solution for this to restrict the booking,tell me solution from JAVA side and and also from DB side
If the application may be deployed in cluster, the synchronized method will indeed not be enough.
You should rely on a node shared by all server instances : the DB.
You could use DB locking features, especially optimistic locking and pessimistic locking.
With them, you could avoid collisions resulting from concurrent updates to the same line by concurrent clients.
Choose which one that matches better to your use case.
Concurrency control in databases extract:
Optimistic - Delay the checking of whether a transaction meets the
isolation and other integrity rules (e.g., serializability and
recoverability) until its end, without blocking any of its (read,
write) operations ("...and be optimistic about the rules being
met..."), and then abort a transaction to prevent the violation, if
the desired rules are to be violated upon its commit. An aborted
transaction is immediately restarted and re-executed, which incurs an
obvious overhead (versus executing it to the end only once). If not
too many transactions are aborted, then being optimistic is usually a
good strategy.
Pessimistic - Block an operation of a transaction, if
it may cause violation of the rules, until the possibility of
violation disappears. Blocking operations is typically involved with
performance reduction.
JDBC and JPA support both.
You should try with ETags - optimistic locking mechanism.
It can be easily implemented with Spring. Please check official documentation.
Hope this will help.

Real life scenarios for Transaction propagations

There are various transaction propagations like
REQUIRED - This is the case for DML operation.
SUPPORTS - This is the case for querying database.
MANDATORY - ?
REQUIRES_NEW - ?
NOT_SUPPORTED - ?
NEVER - ?
NESTED - ?
What are some real life scenarios for these transaction propagations? Why these are perfect fit into that situation?
There are various usages and there is no simple answer but I'll try to be the most explainatory
MANDATORY (expecting transaction): Typically used when you expect that any "higher-context" layer started the transaction and you only want to continue in it. For example if you want one transaction for whole operation from HTTP request to response. Then you start transaction on JAX-RS resource level and lower layers (services) require transaction to run within (otherwise exception is thrown).
REQUIRES_NEW (always create new transaction): This creates a new transaction and suspends the current one if any exists. From above example, this is the level you set on your JAX-RS resource for example. Or generally if your flow somehow changes and you want to split your logic into multiple transactions (so your code have mutliple logic operations that should be separated).
REQUIRED (continue in transaction or create if needed): Some kind of mix between MANDATORY and REQUIRES_NEW. In MANDATORY you expect that the transaction exists, for this level you hope that it exists and if not, you create it. Typically used in DAO-like services (from my experience), but it really depends on logic of your app.
SUPPORTS (caller decides whether to not/run in transaction): Used if want to use the same context as caller (higher context), if your caller was running in transaction, then you run in too. If it didn't, you are also non-transactional. May also be used in DAO-like services if you want higher context to decide.
NESTED (sub-transaction): I must admit I didn't use this one in real code but generally you create a real sub-transaction that works as some kind of checkpoint. So it runs in the context of "parent" transaction but if it fails it returns to that checkpoint (start of nested transaction). This may be useful when you require this kind of logic in your application, for example if you want to insert large number of items to the database, commiting valid ones and keeping track of invalid ones (so you can catch exception when nested transaction fails but can still commit the whole transaction for valid ones)
NEVER (expecting there is no transaction): This is the case when you want to be sure that no transaction exists at all. If some code that runs in transaction reaches this code, exception is thrown. So typically this is for cases completely opposite to MANDARTORY. E.g. when you know that no transaction should be affected by this code - very likely because the transaction should not exist.
NOT_SUPPORTED (continue non-transactionally): This is weaker than NEVER, you want the code to be run non-transactionally. If somehow you enter this code from context where transaction is, you suspend this transaction and continue non-transactionally.
From my experience, you very often want one business action to be atomic. Thus you want only one transaction per request/... For example simple REST call via HTTP that does some DB operations all in one HTTP-like transaction. So my typical usage is REQUIRES_NEW on the top level (JAX-RS Resource) and MANDATORY on all lower level services that are injected to this resource (or even lower).
This may be useful for you. It describes how code behave with given propagation (caller->method)
REQUIRED: NONE->T1, T1->T1
REQUIRES_NEW: NONE->T1, T1->T2
MANDATORY: NONE->Exception, T1->T1
NOT_SUPPORTED: NONE->NONE, T1->NONE
SUPPORTS: NONE->NONE, T1->T1
NEVER: NONE->NONE, T1->Exception

Spring AOP transaction management for service layer

I refer to the example stated in the URL which is to apply spring aop transaction across all methods in service layers, but this will also apply transaction management for read-only methods like SELECT.
Is there any adverse effect, if I apply transaction management for readOnly transaction?
<aop:config>
<aop:advisor pointcut="execution(* com.xyz.someapp.service.*.*(..)))"
advice-ref="transactionAdvice" />
</aop:config>
http://www.studytrails.com/frameworks/spring/spring-declarative-transactions.jsp
I have another question. If I have orderService.create() which invokes billingService.create(), how will the transaction isolation be applied?
You generally want to use transactions even for read-only operations, since a transaction will give you a consistent view of your data. If you skip transactions, you risk seeing partial updates from some other incomplete transaction.
I dont't think that there will be any adverse effects because a transaction simply defines an atomic set of operations. If a transaction fails then a rollback will be performed, but read-only operations don't affect the database in any way.
The only big disadvantage I can think of is related to performance. The locking-strategy of the underlying database (whether table or row is locked) determines your isolation level. Acoording to your locking-strategy some kind of isolation is applied during the transaction. For example, when you're writing to a database your isolation level decides if the changes in progress could be seen by parallel reads (causing e.g. dirty reads, non-repeatable reads and so on) or if these changes have to be commited before they become visible to others.
As a consequence you would lock resources you only want to read, which could be performance overkill on highly available applications. Summing up: It doesn't have bad effects aside from causing performance issues.
Addressing your second question: This depends on how you're managing transactions. I guess in this case both service methods require transactions, so I think the default behavior is that the transaction of the first service call is inherited by the second service method call (this is called 'transaction propagation'). This is required because nested transactions aren't allowed.

Concern on the concept of syncpoint from WMQ

I'm kind of confused about the syncpoint from WebSphere MQ. According to the reference from the WMQ Infocenter, the syncpoint is defined as below:
The decision to commit or back out the changes is taken, in the simplest case, at the end of a task. However, it can be more useful for an application to synchronize data changes at other logical points within a task. These logical points are called sync points (or synchronization points) and the period of processing a set of updates between two sync points is called a unit of work.
Therefore, a unit of work is named as processing between two sync points. From my understanding, that unit of work is a transaction actually. So I draw the picture here reflecting the relationship between them:
Am I understanding it correctly?
Another question here is as for the syncpoint, it's said to synchronize data for application, where is the data synced from and where to?
Thanks
Answer 1: Yes, you are understanding it correctly. Transactions are atomic units of work that succeed or fail in their entirety. Syncpoints are the boundaries between the transactions. The subtle difference between a transaction and a syncpoint is that the work done under a transaction can be in-doubt for a period of time whereas the sync point is the state during which the transaction is not in doubt. In the event of failure, the queues are restored to the state which existed at the last syncpoint and then any pending transactions rolled back or, in the case of XA, possibly committed by the resource manager.
The Infocenter page Transaction management and support may explain it better than the page linked in the post.
Answer 2: The data is synchronized by the resource manager(s). For local units of work where messages are the only participants in the transaction, the synchronization occurs only in the queue, and the queue manager acts as both the resource manager and the transaction manager. For global units of work involving messages and database updates in the same transaction, the synchronization occurs in the QMgr and the database which act as resource managers. The transaction manager will either be MQ or an application server and it orchestrates the synchronization between the resource managers.
Regardless of whether the transaction is local or global (sometimes also referred to as single-phase commit or 2-phase commit) the relationship between transactions and syncpoints is the same. The syncpoint is the most recent point in time at which a known state is preserved and to which an in-doubt transaction might be rolled back.

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