Sean Robertson

Sean Robertson

1548150381

Multitenant configuration: StaleObjectStateException on Transaction (hibernate + spring-data-jpa)

i'm trying to setup a configuration for manage a multi-tenant enviroment with spring-boot, spring-data-jpa, hibernate and mysql (same schema, every tenant table has a tenant_code column). For dependencies the parent maven project is spring-boot-starter-parent (2.1.2.RELEASE).

On save entity hibernate throws this exception: org.hibernate.StaleObjectStateException: Row was updated or deleted by another transaction (or unsaved-value mapping was incorrect) :

The highlights steps are:

  1. Intercept "tenant code" with custom spring HandlerInterceptorAdapter (i read oauth2 token and extract custom attribute "tenant code");
  2. Save "tenant code" in a @RequestScope bean; 

  3. On Save
  4. Define an custom hibernate EmptyInterceptor to intercept onSave action and previously set the "tenant code" (taken on a @RequestScope bean) 

  5. On Read
  6. In abstract Entity (extended by all my entities) i define @Filter and set it via AOP

If in interceptor i override onSave method i get this exception:

org.hibernate.StaleObjectStateException: Row was updated or deleted by another transaction (or unsaved-value mapping was incorrect) : [com.test.module.api.domain.entity.User#22]
    at org.hibernate.persister.entity.AbstractEntityPersister.check(AbstractEntityPersister.java:2522) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.persister.entity.AbstractEntityPersister.update(AbstractEntityPersister.java:3355) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.persister.entity.AbstractEntityPersister.updateOrInsert(AbstractEntityPersister.java:3229) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.persister.entity.AbstractEntityPersister.update(AbstractEntityPersister.java:3630) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.action.internal.EntityUpdateAction.execute(EntityUpdateAction.java:146) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.engine.spi.ActionQueue.executeActions(ActionQueue.java:604) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.engine.spi.ActionQueue.executeActions(ActionQueue.java:478) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.event.internal.AbstractFlushingEventListener.performExecutions(AbstractFlushingEventListener.java:356) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.event.internal.DefaultFlushEventListener.onFlush(DefaultFlushEventListener.java:39) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.internal.SessionImpl.doFlush(SessionImpl.java:1454) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.internal.SessionImpl.managedFlush(SessionImpl.java:511) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.internal.SessionImpl.flushBeforeTransactionCompletion(SessionImpl.java:3283) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.internal.SessionImpl.beforeTransactionCompletion(SessionImpl.java:2479) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.engine.jdbc.internal.JdbcCoordinatorImpl.beforeTransactionCompletion(JdbcCoordinatorImpl.java:473) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.resource.transaction.backend.jdbc.internal.JdbcResourceLocalTransactionCoordinatorImpl.beforeCompletionCallback(JdbcResourceLocalTransactionCoordinatorImpl.java:178) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.resource.transaction.backend.jdbc.internal.JdbcResourceLocalTransactionCoordinatorImpl.access$300(JdbcResourceLocalTransactionCoordinatorImpl.java:39) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.resource.transaction.backend.jdbc.internal.JdbcResourceLocalTransactionCoordinatorImpl$TransactionDriverControlImpl.commit(JdbcResourceLocalTransactionCoordinatorImpl.java:271) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.engine.transaction.internal.TransactionImpl.commit(TransactionImpl.java:98) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.springframework.orm.jpa.JpaTransactionManager.doCommit(JpaTransactionManager.java:532) ~[spring-orm-5.1.4.RELEASE.jar:5.1.4.RELEASE]
    at org.springframework.transaction.support.AbstractPlatformTransactionManager.processCommit(AbstractPlatformTransactionManager.java:746) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
    at org.springframework.transaction.support.AbstractPlatformTransactionManager.commit(AbstractPlatformTransactionManager.java:714) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
    at org.springframework.transaction.interceptor.TransactionAspectSupport.commitTransactionAfterReturning(TransactionAspectSupport.java:533) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
    at org.springframework.transaction.interceptor.TransactionAspectSupport.invokeWithinTransaction(TransactionAspectSupport.java:304) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
    at org.springframework.transaction.interceptor.TransactionInterceptor.invoke(TransactionInterceptor.java:98) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
    at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:186) ~[spring-aop-5.1.4.RELEASE.jar:5.1.4.RELEASE]
    at org.springframework.aop.framework.CglibAopProxy$DynamicAdvisedInterceptor.intercept(CglibAopProxy.java:688) ~[spring-aop-5.1.4.RELEASE.jar:5.1.4.RELEASE]
    at com.test.module.api.service.UserServiceImpl$$EnhancerBySpringCGLIB$$baf4f87e.updateUser(<generated>) ~[classes/:na]
    at com.test.module.api.web.UserController.updateUser(UserController.java:38) ~[classes/:na]


Here the code: 

Spring Interceptor from Request Header:

    @Component
    public class TokenInterceptor extends HandlerInterceptorAdapter {
        public final String TENANT_CODE = "tenant_code";
    @Autowired
    private CurrentUser currentUser;

    @Override
    public boolean preHandle(HttpServletRequest request, HttpServletResponse response, Object handler)
            throws Exception {
        String tenantCode = ... extract tenant code from request...;
        currentUser.setTenantCode(tenantCode);        
        return true;
    }
}


Class to setup inteceptor in hibernate:

    @Component
public class TenantHibernateInterceptorCustomizer implements HibernatePropertiesCustomizer {

    @Autowired
    private TenantJpaInterceptor jpaInterceptor;

    @Override
    public void customize(Map&lt;String, Object&gt; hibernateProperties) {
        hibernateProperties.put("hibernate.session_factory.interceptor", jpaInterceptor);
    }

}


Hibernate custom interceptor:

    @Component
public class TenantJpaInterceptor extends EmptyInterceptor {
//Comment to test if problem is about spring context
//@Autowired
//private CurrentUser currentUser;

    @Override
    public boolean onSave(Object entity, Serializable id, Object[] state, String[] propertyNames, Type[] types) {
        if (entity instanceof TenantAuditable) {
            //((TenantAuditable&lt;?&gt;) entity).setTenandCode(currentUser.getTenantCode());
            //if i comment this line everythings works (without tenant code)
            ((TenantAuditable&lt;?&gt;) entity).setTenandCode("TEST");            
        }
        return false;
    }
}


Service layer:

    @Transactional
public UpsertResponse<UserDto> updateUser(UserDto userDto) {
UpsertResponse<UserDto> validationResult = CommonValidators.validateUserDto(userDto);
if(!validationResult.isValidated()) {
return validationResult;

    SpUser user = userRepo.findById(userDto.getUserId()).orElse(new SpUser());
    userMapper.mapUserDtoToEntity(userDto, user);
    try {
        SpUser savedUser = userRepo.save(user);
        validationResult.setEntity(userMapper.mapUserDtoFromEntity(savedUser));
        validationResult.setValidated(true);
    }catch(Exception e) {
        e.printStackTrace();
        validationResult.setValidated(false);
        validationResult.setGlobalMessage(e.getLocalizedMessage());

    }
    return validationResult;
}

I expected a insert/update sql query with filled tenant_code field.


Here complete log

2019-01-22 01:10:57.521  INFO 14304 — [nio-8090-exec-1] o.a.c.c.C.[Tomcat].[localhost].[/]       : Initializing Spring DispatcherServlet ‘dispatcherServlet’
2019-01-22 01:10:57.523 INFO 14304 — [nio-8090-exec-1] o.s.web.servlet.DispatcherServlet : Initializing Servlet ‘dispatcherServlet’
2019-01-22 01:10:57.550 INFO 14304 — [nio-8090-exec-1] o.s.web.servlet.DispatcherServlet : Completed initialization in 27 ms
Hibernate:
select
spuser0_.user_id as user_id1_0_0_,
spuser0_.created_by as created_2_0_0_,
spuser0_.created_date as created_3_0_0_,
spuser0_.last_modified_by as last_mod4_0_0_,
spuser0_.last_modified_date as last_mod5_0_0_,
spuser0_.tenant_code as tenant_c6_0_0_,
spuser0_.buyer_id as buyer_id7_0_0_,
spuser0_.email as email8_0_0_,
spuser0_.family_name as family_n9_0_0_,
spuser0_.given_name as given_n10_0_0_,
spuser0_.middle_name as middle_11_0_0_,
spuser0_.user_name as user_na12_0_0_
from
sp_user spuser0_
where
spuser0_.user_id=?
2019-01-22 01:11:10.689 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [1] as [BIGINT] - [2]
Hibernate:
select
spuser0_.user_id as user_id1_0_0_,
spuser0_.created_by as created_2_0_0_,
spuser0_.created_date as created_3_0_0_,
spuser0_.last_modified_by as last_mod4_0_0_,
spuser0_.last_modified_date as last_mod5_0_0_,
spuser0_.tenant_code as tenant_c6_0_0_,
spuser0_.buyer_id as buyer_id7_0_0_,
spuser0_.email as email8_0_0_,
spuser0_.family_name as family_n9_0_0_,
spuser0_.given_name as given_n10_0_0_,
spuser0_.middle_name as middle_11_0_0_,
spuser0_.user_name as user_na12_0_0_
from
sp_user spuser0_
where
spuser0_.user_id=?
2019-01-22 01:11:14.414 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [1] as [BIGINT] - [2]
Hibernate:
insert
into
sp_user
(created_by, created_date, last_modified_by, last_modified_date, tenant_code, buyer_id, email, family_name, given_name, middle_name, user_name)
values
(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
2019-01-22 01:11:23.137 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [1] as [VARCHAR] - [3bf38f12-5d17-47e4-9504-ad0705289d10]
2019-01-22 01:11:23.138 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [2] as [TIMESTAMP] - [Tue Jan 22 01:11:14 CET 2019]
2019-01-22 01:11:23.140 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [3] as [VARCHAR] - [3bf38f12-5d17-47e4-9504-ad0705289d10]
2019-01-22 01:11:23.140 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [4] as [TIMESTAMP] - [Tue Jan 22 01:11:14 CET 2019]
2019-01-22 01:11:23.140 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [5] as [VARCHAR] - [null]
2019-01-22 01:11:23.140 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [6] as [VARCHAR] - [1]
2019-01-22 01:11:23.140 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [7] as [VARCHAR] - [gabriele.muscas@gmail.comx]
2019-01-22 01:11:23.140 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [8] as [VARCHAR] - [Muscas]
2019-01-22 01:11:23.140 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [9] as [VARCHAR] - [Gabrielex]
2019-01-22 01:11:23.141 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [10] as [VARCHAR] - [Giuseppe Pippo]
2019-01-22 01:11:23.141 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [11] as [VARCHAR] - [gabriele.muscas]
Hibernate:
update
sp_user
set
created_by=?,
created_date=?,
last_modified_by=?,
last_modified_date=?,
tenant_code=?,
buyer_id=?,
email=?,
family_name=?,
given_name=?,
middle_name=?,
user_name=?
where
user_id=?
2019-01-22 01:11:24.912 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [1] as [VARCHAR] - [3bf38f12-5d17-47e4-9504-ad0705289d10]
2019-01-22 01:11:24.912 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [2] as [TIMESTAMP] - [Tue Jan 22 01:11:14 CET 2019]
2019-01-22 01:11:24.913 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [3] as [VARCHAR] - [3bf38f12-5d17-47e4-9504-ad0705289d10]
2019-01-22 01:11:24.913 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [4] as [TIMESTAMP] - [Tue Jan 22 01:11:24 CET 2019]
2019-01-22 01:11:24.913 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [5] as [VARCHAR] - [PIPPO]
2019-01-22 01:11:24.913 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [6] as [VARCHAR] - [1]
2019-01-22 01:11:24.914 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [7] as [VARCHAR] - [gabriele.muscas@gmail.comx]
2019-01-22 01:11:24.914 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [8] as [VARCHAR] - [Muscas]
2019-01-22 01:11:24.914 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [9] as [VARCHAR] - [Gabrielex]
2019-01-22 01:11:24.915 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [10] as [VARCHAR] - [Giuseppe Pippo]
2019-01-22 01:11:24.915 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [11] as [VARCHAR] - [gabriele.muscas]
2019-01-22 01:11:24.915 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [12] as [BIGINT] - [23]
2019-01-22 01:11:24.918 ERROR 14304 — [nio-8090-exec-2] o.h.i.ExceptionMapperStandardImpl : HHH000346: Error during managed flush [Row was updated or deleted by another transaction (or unsaved-value mapping was incorrect) : [com.supplhi.buyer.api.domain.entity.SpUser#23]]
Hibernate:
select
spuser0_.user_id as user_id1_0_0_,
spuser0_.created_by as created_2_0_0_,
spuser0_.created_date as created_3_0_0_,
spuser0_.last_modified_by as last_mod4_0_0_,
spuser0_.last_modified_date as last_mod5_0_0_,
spuser0_.tenant_code as tenant_c6_0_0_,
spuser0_.buyer_id as buyer_id7_0_0_,
spuser0_.email as email8_0_0_,
spuser0_.family_name as family_n9_0_0_,
spuser0_.given_name as given_n10_0_0_,
spuser0_.middle_name as middle_11_0_0_,
spuser0_.user_name as user_na12_0_0_
from
sp_user spuser0_
where
spuser0_.user_id=?
2019-01-22 01:11:24.928 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [1] as [BIGINT] - [23]
2019-01-22 01:11:24.940 ERROR 14304 — [nio-8090-exec-2] o.a.c.c.C.[.[.[/].[dispatcherServlet] : Servlet.service() for servlet [dispatcherServlet] in context with path [] threw exception [Request processing failed; nested exception is org.springframework.orm.ObjectOptimisticLockingFailureException: Object of class [com.supplhi.buyer.api.domain.entity.SpUser] with identifier [23]: optimistic locking failed; nested exception is org.hibernate.StaleObjectStateException: Row was updated or deleted by another transaction (or unsaved-value mapping was incorrect) : [com.supplhi.buyer.api.domain.entity.SpUser#23]] with root cause

org.hibernate.StaleObjectStateException: Row was updated or deleted by another transaction (or unsaved-value mapping was incorrect) : [com.supplhi.buyer.api.domain.entity.SpUser#23]
at org.hibernate.persister.entity.AbstractEntityPersister.check(AbstractEntityPersister.java:2522) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.persister.entity.AbstractEntityPersister.update(AbstractEntityPersister.java:3355) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.persister.entity.AbstractEntityPersister.updateOrInsert(AbstractEntityPersister.java:3229) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.persister.entity.AbstractEntityPersister.update(AbstractEntityPersister.java:3630) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.action.internal.EntityUpdateAction.execute(EntityUpdateAction.java:146) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.engine.spi.ActionQueue.executeActions(ActionQueue.java:604) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.engine.spi.ActionQueue.executeActions(ActionQueue.java:478) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.event.internal.AbstractFlushingEventListener.performExecutions(AbstractFlushingEventListener.java:356) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.event.internal.DefaultFlushEventListener.onFlush(DefaultFlushEventListener.java:39) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.internal.SessionImpl.doFlush(SessionImpl.java:1454) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.internal.SessionImpl.managedFlush(SessionImpl.java:511) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.internal.SessionImpl.flushBeforeTransactionCompletion(SessionImpl.java:3283) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.internal.SessionImpl.beforeTransactionCompletion(SessionImpl.java:2479) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.engine.jdbc.internal.JdbcCoordinatorImpl.beforeTransactionCompletion(JdbcCoordinatorImpl.java:473) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.resource.transaction.backend.jdbc.internal.JdbcResourceLocalTransactionCoordinatorImpl.beforeCompletionCallback(JdbcResourceLocalTransactionCoordinatorImpl.java:178) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.resource.transaction.backend.jdbc.internal.JdbcResourceLocalTransactionCoordinatorImpl.access$300(JdbcResourceLocalTransactionCoordinatorImpl.java:39) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.resource.transaction.backend.jdbc.internal.JdbcResourceLocalTransactionCoordinatorImpl$TransactionDriverControlImpl.commit(JdbcResourceLocalTransactionCoordinatorImpl.java:271) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.engine.transaction.internal.TransactionImpl.commit(TransactionImpl.java:98) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.springframework.orm.jpa.JpaTransactionManager.doCommit(JpaTransactionManager.java:532) ~[spring-orm-5.1.4.RELEASE.jar:5.1.4.RELEASE]
at org.springframework.transaction.support.AbstractPlatformTransactionManager.processCommit(AbstractPlatformTransactionManager.java:746) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
at org.springframework.transaction.support.AbstractPlatformTransactionManager.commit(AbstractPlatformTransactionManager.java:714) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
at org.springframework.transaction.interceptor.TransactionAspectSupport.commitTransactionAfterReturning(TransactionAspectSupport.java:533) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
at org.springframework.transaction.interceptor.TransactionAspectSupport.invokeWithinTransaction(TransactionAspectSupport.java:304) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
at org.springframework.transaction.interceptor.TransactionInterceptor.invoke(TransactionInterceptor.java:98) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:186) ~[spring-aop-5.1.4.RELEASE.jar:5.1.4.RELEASE]
at org.springframework.aop.framework.CglibAopProxy$DynamicAdvisedInterceptor.intercept(CglibAopProxy.java:688) ~[spring-aop-5.1.4.RELEASE.jar:5.1.4.RELEASE]
at com.supplhi.buyer.api.service.UserServiceImpl$$EnhancerBySpringCGLIB$$baf4f87e.updateUser(<generated>) ~[classes/:na]
at com.supplhi.buyer.api.web.UserController.updateUser(UserController.java:38) ~[classes/:na]

A little help, s’ll vous plaît. Thanks

#java #spring #hibernate #jpa

What is GEEK

Buddha Community

Charles Cooper

1548232629

According to (3.3) doc/sample, You should implement your (jpa) interceptor like:

@Override
public boolean onSave(Object entity, Serializable id, Object[] state, String[] propertyNames, Type[] types) {
  if (entity instanceof TenantAuditable) {
    for ( int i=0; i < propertyNames.length; i++ ) {
      if ( "tenantCode".equals( propertyNames[i] ) ) {
        state[i] = currentUser.getTenantCode();
        return true;
      }
    }          
  }
  return false;
}

I’am surprised that it worked with “TEST”…

Enhance Amazon Aurora Read/Write Capability with ShardingSphere-JDBC

1. Introduction

Amazon Aurora is a relational database management system (RDBMS) developed by AWS(Amazon Web Services). Aurora gives you the performance and availability of commercial-grade databases with full MySQL and PostgreSQL compatibility. In terms of high performance, Aurora MySQL and Aurora PostgreSQL have shown an increase in throughput of up to 5X over stock MySQL and 3X over stock PostgreSQL respectively on similar hardware. In terms of scalability, Aurora achieves enhancements and innovations in storage and computing, horizontal and vertical functions.

Aurora supports up to 128TB of storage capacity and supports dynamic scaling of storage layer in units of 10GB. In terms of computing, Aurora supports scalable configurations for multiple read replicas. Each region can have an additional 15 Aurora replicas. In addition, Aurora provides multi-primary architecture to support four read/write nodes. Its Serverless architecture allows vertical scaling and reduces typical latency to under a second, while the Global Database enables a single database cluster to span multiple AWS Regions in low latency.

Aurora already provides great scalability with the growth of user data volume. Can it handle more data and support more concurrent access? You may consider using sharding to support the configuration of multiple underlying Aurora clusters. To this end, a series of blogs, including this one, provides you with a reference in choosing between Proxy and JDBC for sharding.

1.1 Why sharding is needed

AWS Aurora offers a single relational database. Primary-secondary, multi-primary, and global database, and other forms of hosting architecture can satisfy various architectural scenarios above. However, Aurora doesn’t provide direct support for sharding scenarios, and sharding has a variety of forms, such as vertical and horizontal forms. If we want to further increase data capacity, some problems have to be solved, such as cross-node database Join, associated query, distributed transactions, SQL sorting, page turning, function calculation, database global primary key, capacity planning, and secondary capacity expansion after sharding.

1.2 Sharding methods

It is generally accepted that when the capacity of a MySQL table is less than 10 million, the time spent on queries is optimal because at this time the height of its BTREE index is between 3 and 5. Data sharding can reduce the amount of data in a single table and distribute the read and write loads to different data nodes at the same time. Data sharding can be divided into vertical sharding and horizontal sharding.

1. Advantages of vertical sharding

  • Address the coupling of business system and make clearer.
  • Implement hierarchical management, maintenance, monitoring, and expansion to data of different businesses, like micro-service governance.
  • In high concurrency scenarios, vertical sharding removes the bottleneck of IO, database connections, and hardware resources on a single machine to some extent.

2. Disadvantages of vertical sharding

  • After splitting the library, Join can only be implemented by interface aggregation, which will increase the complexity of development.
  • After splitting the library, it is complex to process distributed transactions.
  • There is a large amount of data on a single table and horizontal sharding is required.

3. Advantages of horizontal sharding

  • There is no such performance bottleneck as a large amount of data on a single database and high concurrency, and it increases system stability and load capacity.
  • The business modules do not need to be split due to minor modification on the application client.

4. Disadvantages of horizontal sharding

  • Transaction consistency across shards is hard to be guaranteed;
  • The performance of associated query in cross-library Join is poor.
  • It’s difficult to scale the data many times and maintenance is a big workload.

Based on the analysis above, and the available studis on popular sharding middleware, we selected ShardingSphere, an open source product, combined with Amazon Aurora to introduce how the combination of these two products meets various forms of sharding and how to solve the problems brought by sharding.

ShardingSphere is an open source ecosystem including a set of distributed database middleware solutions, including 3 independent products, Sharding-JDBC, Sharding-Proxy & Sharding-Sidecar.

2. ShardingSphere introduction:

The characteristics of Sharding-JDBC are:

  1. With the client end connecting directly to the database, it provides service in the form of jar and requires no extra deployment and dependence.
  2. It can be considered as an enhanced JDBC driver, which is fully compatible with JDBC and all kinds of ORM frameworks.
  3. Applicable in any ORM framework based on JDBC, such as JPA, Hibernate, Mybatis, Spring JDBC Template or direct use of JDBC.
  4. Support any third-party database connection pool, such as DBCP, C3P0, BoneCP, Druid, HikariCP;
  5. Support any kind of JDBC standard database: MySQL, Oracle, SQLServer, PostgreSQL and any databases accessible to JDBC.
  6. Sharding-JDBC adopts decentralized architecture, applicable to high-performance light-weight OLTP application developed with Java

Hybrid Structure Integrating Sharding-JDBC and Applications

Sharding-JDBC’s core concepts

Data node: The smallest unit of a data slice, consisting of a data source name and a data table, such as ds_0.product_order_0.

Actual table: The physical table that really exists in the horizontal sharding database, such as product order tables: product_order_0, product_order_1, and product_order_2.

Logic table: The logical name of the horizontal sharding databases (tables) with the same schema. For instance, the logic table of the order product_order_0, product_order_1, and product_order_2 is product_order.

Binding table: It refers to the primary table and the joiner table with the same sharding rules. For example, product_order table and product_order_item are sharded by order_id, so they are binding tables with each other. Cartesian product correlation will not appear in the multi-tables correlating query, so the query efficiency will increase greatly.

Broadcast table: It refers to tables that exist in all sharding database sources. The schema and data must consist in each database. It can be applied to the small data volume that needs to correlate with big data tables to query, dictionary table and configuration table for example.

3. Testing ShardingSphere-JDBC

3.1 Example project

Download the example project code locally. In order to ensure the stability of the test code, we choose shardingsphere-example-4.0.0 version.

git clone https://github.com/apache/shardingsphere-example.git

Project description:

shardingsphere-example
  ├── example-core
  │   ├── config-utility
  │   ├── example-api
  │   ├── example-raw-jdbc
  │   ├── example-spring-jpa #spring+jpa integration-based entity,repository
  │   └── example-spring-mybatis
  ├── sharding-jdbc-example
  │   ├── sharding-example
  │   │   ├── sharding-raw-jdbc-example
  │   │   ├── sharding-spring-boot-jpa-example #integration-based sharding-jdbc functions
  │   │   ├── sharding-spring-boot-mybatis-example
  │   │   ├── sharding-spring-namespace-jpa-example
  │   │   └── sharding-spring-namespace-mybatis-example
  │   ├── orchestration-example
  │   │   ├── orchestration-raw-jdbc-example
  │   │   ├── orchestration-spring-boot-example #integration-based sharding-jdbc governance function
  │   │   └── orchestration-spring-namespace-example
  │   ├── transaction-example
  │   │   ├── transaction-2pc-xa-example #sharding-jdbc sample of two-phase commit for a distributed transaction
  │   │   └──transaction-base-seata-example #sharding-jdbc distributed transaction seata sample
  │   ├── other-feature-example
  │   │   ├── hint-example
  │   │   └── encrypt-example
  ├── sharding-proxy-example
  │   └── sharding-proxy-boot-mybatis-example
  └── src/resources
        └── manual_schema.sql  

Configuration file description:

application-master-slave.properties #read/write splitting profile
application-sharding-databases-tables.properties #sharding profile
application-sharding-databases.properties       #library split profile only
application-sharding-master-slave.properties    #sharding and read/write splitting profile
application-sharding-tables.properties          #table split profile
application.properties                         #spring boot profile

Code logic description:

The following is the entry class of the Spring Boot application below. Execute it to run the project.

The execution logic of demo is as follows:

3.2 Verifying read/write splitting

As business grows, the write and read requests can be split to different database nodes to effectively promote the processing capability of the entire database cluster. Aurora uses a reader/writer endpoint to meet users' requirements to write and read with strong consistency, and a read-only endpoint to meet the requirements to read without strong consistency. Aurora's read and write latency is within single-digit milliseconds, much lower than MySQL's binlog-based logical replication, so there's a lot of loads that can be directed to a read-only endpoint.

Through the one primary and multiple secondary configuration, query requests can be evenly distributed to multiple data replicas, which further improves the processing capability of the system. Read/write splitting can improve the throughput and availability of system, but it can also lead to data inconsistency. Aurora provides a primary/secondary architecture in a fully managed form, but applications on the upper-layer still need to manage multiple data sources when interacting with Aurora, routing SQL requests to different nodes based on the read/write type of SQL statements and certain routing policies.

ShardingSphere-JDBC provides read/write splitting features and it is integrated with application programs so that the complex configuration between application programs and database clusters can be separated from application programs. Developers can manage the Shard through configuration files and combine it with ORM frameworks such as Spring JPA and Mybatis to completely separate the duplicated logic from the code, which greatly improves the ability to maintain code and reduces the coupling between code and database.

3.2.1 Setting up the database environment

Create a set of Aurora MySQL read/write splitting clusters. The model is db.r5.2xlarge. Each set of clusters has one write node and two read nodes.

3.2.2 Configuring Sharding-JDBC

application.properties spring boot Master profile description:

You need to replace the green ones with your own environment configuration.

# Jpa automatically creates and drops data tables based on entities
spring.jpa.properties.hibernate.hbm2ddl.auto=create-drop
spring.jpa.properties.hibernate.dialect=org.hibernate.dialect.MySQL5Dialect
spring.jpa.properties.hibernate.show_sql=true

#spring.profiles.active=sharding-databases
#spring.profiles.active=sharding-tables
#spring.profiles.active=sharding-databases-tables
#Activate master-slave configuration item so that sharding-jdbc can use master-slave profile
spring.profiles.active=master-slave
#spring.profiles.active=sharding-master-slave

application-master-slave.properties sharding-jdbc profile description:

spring.shardingsphere.datasource.names=ds_master,ds_slave_0,ds_slave_1
# data souce-master
spring.shardingsphere.datasource.ds_master.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_master.password=Your master DB password
spring.shardingsphere.datasource.ds_master.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_master.jdbc-url=Your primary DB data sourceurl spring.shardingsphere.datasource.ds_master.username=Your primary DB username
# data source-slave
spring.shardingsphere.datasource.ds_slave_0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_slave_0.password= Your slave DB password
spring.shardingsphere.datasource.ds_slave_0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_slave_0.jdbc-url=Your slave DB data source url
spring.shardingsphere.datasource.ds_slave_0.username= Your slave DB username
# data source-slave
spring.shardingsphere.datasource.ds_slave_1.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_slave_1.password= Your slave DB password
spring.shardingsphere.datasource.ds_slave_1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_slave_1.jdbc-url= Your slave DB data source url
spring.shardingsphere.datasource.ds_slave_1.username= Your slave DB username
# Routing Policy Configuration
spring.shardingsphere.masterslave.load-balance-algorithm-type=round_robin
spring.shardingsphere.masterslave.name=ds_ms
spring.shardingsphere.masterslave.master-data-source-name=ds_master
spring.shardingsphere.masterslave.slave-data-source-names=ds_slave_0,ds_slave_1
# sharding-jdbc configures the information storage mode
spring.shardingsphere.mode.type=Memory
# start shardingsphere log,and you can see the conversion from logical SQL to actual SQL from the print
spring.shardingsphere.props.sql.show=true

 

3.2.3 Test and verification process description

  • Test environment data initialization: Spring JPA initialization automatically creates tables for testing.

  • Write data to the master instance

As shown in the ShardingSphere-SQL log figure below, the write SQL is executed on the ds_master data source.

  • Data query operations are performed on the slave library.

As shown in the ShardingSphere-SQL log figure below, the read SQL is executed on the ds_slave data source in the form of polling.

[INFO ] 2022-04-02 19:43:39,376 --main-- [ShardingSphere-SQL] Rule Type: master-slave 
[INFO ] 2022-04-02 19:43:39,376 --main-- [ShardingSphere-SQL] SQL: select orderentit0_.order_id as order_id1_1_, orderentit0_.address_id as address_2_1_, 
orderentit0_.status as status3_1_, orderentit0_.user_id as user_id4_1_ from t_order orderentit0_ ::: DataSources: ds_slave_0 
---------------------------- Print OrderItem Data -------------------
Hibernate: select orderiteme1_.order_item_id as order_it1_2_, orderiteme1_.order_id as order_id2_2_, orderiteme1_.status as status3_2_, orderiteme1_.user_id 
as user_id4_2_ from t_order orderentit0_ cross join t_order_item orderiteme1_ where orderentit0_.order_id=orderiteme1_.order_id
[INFO ] 2022-04-02 19:43:40,898 --main-- [ShardingSphere-SQL] Rule Type: master-slave 
[INFO ] 2022-04-02 19:43:40,898 --main-- [ShardingSphere-SQL] SQL: select orderiteme1_.order_item_id as order_it1_2_, orderiteme1_.order_id as order_id2_2_, orderiteme1_.status as status3_2_, 
orderiteme1_.user_id as user_id4_2_ from t_order orderentit0_ cross join t_order_item orderiteme1_ where orderentit0_.order_id=orderiteme1_.order_id ::: DataSources: ds_slave_1 

Note: As shown in the figure below, if there are both reads and writes in a transaction, Sharding-JDBC routes both read and write operations to the master library. If the read/write requests are not in the same transaction, the corresponding read requests are distributed to different read nodes according to the routing policy.

@Override
@Transactional // When a transaction is started, both read and write in the transaction go through the master library. When closed, read goes through the slave library and write goes through the master library
public void processSuccess() throws SQLException {
    System.out.println("-------------- Process Success Begin ---------------");
    List<Long> orderIds = insertData();
    printData();
    deleteData(orderIds);
    printData();
    System.out.println("-------------- Process Success Finish --------------");
}

3.2.4 Verifying Aurora failover scenario

The Aurora database environment adopts the configuration described in Section 2.2.1.

3.2.4.1 Verification process description

  1. Start the Spring-Boot project

2. Perform a failover on Aurora’s console

3. Execute the Rest API request

4. Repeatedly execute POST (http://localhost:8088/save-user) until the call to the API failed to write to Aurora and eventually recovered successfully.

5. The following figure shows the process of executing code failover. It takes about 37 seconds from the time when the latest SQL write is successfully performed to the time when the next SQL write is successfully performed. That is, the application can be automatically recovered from Aurora failover, and the recovery time is about 37 seconds.

3.3 Testing table sharding-only function

3.3.1 Configuring Sharding-JDBC

application.properties spring boot master profile description

# Jpa automatically creates and drops data tables based on entities
spring.jpa.properties.hibernate.hbm2ddl.auto=create-drop
spring.jpa.properties.hibernate.dialect=org.hibernate.dialect.MySQL5Dialect
spring.jpa.properties.hibernate.show_sql=true
#spring.profiles.active=sharding-databases
#Activate sharding-tables configuration items
#spring.profiles.active=sharding-tables
#spring.profiles.active=sharding-databases-tables
# spring.profiles.active=master-slave
#spring.profiles.active=sharding-master-slave

application-sharding-tables.properties sharding-jdbc profile description

## configure primary-key policy
spring.shardingsphere.sharding.tables.t_order.key-generator.column=order_id
spring.shardingsphere.sharding.tables.t_order.key-generator.type=SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order.key-generator.props.worker.id=123
spring.shardingsphere.sharding.tables.t_order_item.actual-data-nodes=ds.t_order_item_$->{0..1}
spring.shardingsphere.sharding.tables.t_order_item.table-strategy.inline.sharding-column=order_id
spring.shardingsphere.sharding.tables.t_order_item.table-strategy.inline.algorithm-expression=t_order_item_$->{order_id % 2}
spring.shardingsphere.sharding.tables.t_order_item.key-generator.column=order_item_id
spring.shardingsphere.sharding.tables.t_order_item.key-generator.type=SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order_item.key-generator.props.worker.id=123
# configure the binding relation of t_order and t_order_item
spring.shardingsphere.sharding.binding-tables[0]=t_order,t_order_item
# configure broadcast tables
spring.shardingsphere.sharding.broadcast-tables=t_address
# sharding-jdbc mode
spring.shardingsphere.mode.type=Memory
# start shardingsphere log
spring.shardingsphere.props.sql.show=true

 

3.3.2 Test and verification process description

1. DDL operation

JPA automatically creates tables for testing. When Sharding-JDBC routing rules are configured, the client executes DDL, and Sharding-JDBC automatically creates corresponding tables according to the table splitting rules. If t_address is a broadcast table, create a t_address because there is only one master instance. Two physical tables t_order_0 and t_order_1 will be created when creating t_order.

2. Write operation

As shown in the figure below, Logic SQL inserts a record into t_order. When Sharding-JDBC is executed, data will be distributed to t_order_0 and t_order_1 according to the table splitting rules.

When t_order and t_order_item are bound, the records associated with order_item and order are placed on the same physical table.

3. Read operation

As shown in the figure below, perform the join query operations to order and order_item under the binding table, and the physical shard is precisely located based on the binding relationship.

The join query operations on order and order_item under the unbound table will traverse all shards.

3.4 Testing database sharding-only function

3.4.1 Setting up the database environment

Create two instances on Aurora: ds_0 and ds_1

When the sharding-spring-boot-jpa-example project is started, tables t_order, t_order_itemt_address will be created on two Aurora instances.

3.4.2 Configuring Sharding-JDBC

application.properties springboot master profile description

# Jpa automatically creates and drops data tables based on entities
spring.jpa.properties.hibernate.hbm2ddl.auto=create
spring.jpa.properties.hibernate.dialect=org.hibernate.dialect.MySQL5Dialect
spring.jpa.properties.hibernate.show_sql=true

# Activate sharding-databases configuration items
spring.profiles.active=sharding-databases
#spring.profiles.active=sharding-tables
#spring.profiles.active=sharding-databases-tables
#spring.profiles.active=master-slave
#spring.profiles.active=sharding-master-slave

application-sharding-databases.properties sharding-jdbc profile description

spring.shardingsphere.datasource.names=ds_0,ds_1
# ds_0
spring.shardingsphere.datasource.ds_0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_0.jdbc-url= spring.shardingsphere.datasource.ds_0.username= 
spring.shardingsphere.datasource.ds_0.password=
# ds_1
spring.shardingsphere.datasource.ds_1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_1.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_1.jdbc-url= 
spring.shardingsphere.datasource.ds_1.username= 
spring.shardingsphere.datasource.ds_1.password=
spring.shardingsphere.sharding.default-database-strategy.inline.sharding-column=user_id
spring.shardingsphere.sharding.default-database-strategy.inline.algorithm-expression=ds_$->{user_id % 2}
spring.shardingsphere.sharding.binding-tables=t_order,t_order_item
spring.shardingsphere.sharding.broadcast-tables=t_address
spring.shardingsphere.sharding.default-data-source-name=ds_0

spring.shardingsphere.sharding.tables.t_order.actual-data-nodes=ds_$->{0..1}.t_order
spring.shardingsphere.sharding.tables.t_order.key-generator.column=order_id
spring.shardingsphere.sharding.tables.t_order.key-generator.type=SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order.key-generator.props.worker.id=123
spring.shardingsphere.sharding.tables.t_order_item.actual-data-nodes=ds_$->{0..1}.t_order_item
spring.shardingsphere.sharding.tables.t_order_item.key-generator.column=order_item_id
spring.shardingsphere.sharding.tables.t_order_item.key-generator.type=SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order_item.key-generator.props.worker.id=123
# sharding-jdbc mode
spring.shardingsphere.mode.type=Memory
# start shardingsphere log
spring.shardingsphere.props.sql.show=true

 

3.4.3 Test and verification process description

1. DDL operation

JPA automatically creates tables for testing. When Sharding-JDBC’s library splitting and routing rules are configured, the client executes DDL, and Sharding-JDBC will automatically create corresponding tables according to table splitting rules. If t_address is a broadcast table, physical tables will be created on ds_0 and ds_1. The three tables, t_address, t_order and t_order_item will be created on ds_0 and ds_1 respectively.

2. Write operation

For the broadcast table t_address, each record written will also be written to the t_address tables of ds_0 and ds_1.

The tables t_order and t_order_item of the slave library are written on the table in the corresponding instance according to the slave library field and routing policy.

3. Read operation

Query order is routed to the corresponding Aurora instance according to the routing rules of the slave library .

Query Address. Since address is a broadcast table, an instance of address will be randomly selected and queried from the nodes used.

As shown in the figure below, perform the join query operations to order and order_item under the binding table, and the physical shard is precisely located based on the binding relationship.

3.5 Verifying sharding function

3.5.1 Setting up the database environment

As shown in the figure below, create two instances on Aurora: ds_0 and ds_1

When the sharding-spring-boot-jpa-example project is started, physical tables t_order_01, t_order_02, t_order_item_01,and t_order_item_02 and global table t_address will be created on two Aurora instances.

3.5.2 Configuring Sharding-JDBC

application.properties springboot master profile description

# Jpa automatically creates and drops data tables based on entities
spring.jpa.properties.hibernate.hbm2ddl.auto=create
spring.jpa.properties.hibernate.dialect=org.hibernate.dialect.MySQL5Dialect
spring.jpa.properties.hibernate.show_sql=true
# Activate sharding-databases-tables configuration items
#spring.profiles.active=sharding-databases
#spring.profiles.active=sharding-tables
spring.profiles.active=sharding-databases-tables
#spring.profiles.active=master-slave
#spring.profiles.active=sharding-master-slave

application-sharding-databases.properties sharding-jdbc profile description

spring.shardingsphere.datasource.names=ds_0,ds_1
# ds_0
spring.shardingsphere.datasource.ds_0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_0.jdbc-url= 306/dev?useSSL=false&characterEncoding=utf-8
spring.shardingsphere.datasource.ds_0.username= 
spring.shardingsphere.datasource.ds_0.password=
spring.shardingsphere.datasource.ds_0.max-active=16
# ds_1
spring.shardingsphere.datasource.ds_1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_1.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_1.jdbc-url= 
spring.shardingsphere.datasource.ds_1.username= 
spring.shardingsphere.datasource.ds_1.password=
spring.shardingsphere.datasource.ds_1.max-active=16
# default library splitting policy
spring.shardingsphere.sharding.default-database-strategy.inline.sharding-column=user_id
spring.shardingsphere.sharding.default-database-strategy.inline.algorithm-expression=ds_$->{user_id % 2}
spring.shardingsphere.sharding.binding-tables=t_order,t_order_item
spring.shardingsphere.sharding.broadcast-tables=t_address
# Tables that do not meet the library splitting policy are placed on ds_0
spring.shardingsphere.sharding.default-data-source-name=ds_0
# t_order table splitting policy
spring.shardingsphere.sharding.tables.t_order.actual-data-nodes=ds_$->{0..1}.t_order_$->{0..1}
spring.shardingsphere.sharding.tables.t_order.table-strategy.inline.sharding-column=order_id
spring.shardingsphere.sharding.tables.t_order.table-strategy.inline.algorithm-expression=t_order_$->{order_id % 2}
spring.shardingsphere.sharding.tables.t_order.key-generator.column=order_id
spring.shardingsphere.sharding.tables.t_order.key-generator.type=SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order.key-generator.props.worker.id=123
# t_order_item table splitting policy
spring.shardingsphere.sharding.tables.t_order_item.actual-data-nodes=ds_$->{0..1}.t_order_item_$->{0..1}
spring.shardingsphere.sharding.tables.t_order_item.table-strategy.inline.sharding-column=order_id
spring.shardingsphere.sharding.tables.t_order_item.table-strategy.inline.algorithm-expression=t_order_item_$->{order_id % 2}
spring.shardingsphere.sharding.tables.t_order_item.key-generator.column=order_item_id
spring.shardingsphere.sharding.tables.t_order_item.key-generator.type=SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order_item.key-generator.props.worker.id=123
# sharding-jdbc mdoe
spring.shardingsphere.mode.type=Memory
# start shardingsphere log
spring.shardingsphere.props.sql.show=true

 

3.5.3 Test and verification process description

1. DDL operation

JPA automatically creates tables for testing. When Sharding-JDBC’s sharding and routing rules are configured, the client executes DDL, and Sharding-JDBC will automatically create corresponding tables according to table splitting rules. If t_address is a broadcast table, t_address will be created on both ds_0 and ds_1. The three tables, t_address, t_order and t_order_item will be created on ds_0 and ds_1 respectively.

2. Write operation

For the broadcast table t_address, each record written will also be written to the t_address tables of ds_0 and ds_1.

The tables t_order and t_order_item of the sub-library are written to the table on the corresponding instance according to the slave library field and routing policy.

3. Read operation

The read operation is similar to the library split function verification described in section2.4.3.

3.6 Testing database sharding, table sharding and read/write splitting function

3.6.1 Setting up the database environment

The following figure shows the physical table of the created database instance.

3.6.2 Configuring Sharding-JDBC

application.properties spring boot master profile description

# Jpa automatically creates and drops data tables based on entities
spring.jpa.properties.hibernate.hbm2ddl.auto=create
spring.jpa.properties.hibernate.dialect=org.hibernate.dialect.MySQL5Dialect
spring.jpa.properties.hibernate.show_sql=true

# activate sharding-databases-tables configuration items
#spring.profiles.active=sharding-databases
#spring.profiles.active=sharding-tables
#spring.profiles.active=sharding-databases-tables
#spring.profiles.active=master-slave
spring.profiles.active=sharding-master-slave

application-sharding-master-slave.properties sharding-jdbc profile description

The url, name and password of the database need to be changed to your own database parameters.

spring.shardingsphere.datasource.names=ds_master_0,ds_master_1,ds_master_0_slave_0,ds_master_0_slave_1,ds_master_1_slave_0,ds_master_1_slave_1
spring.shardingsphere.datasource.ds_master_0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_master_0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_master_0.jdbc-url= spring.shardingsphere.datasource.ds_master_0.username= 
spring.shardingsphere.datasource.ds_master_0.password=
spring.shardingsphere.datasource.ds_master_0.max-active=16
spring.shardingsphere.datasource.ds_master_0_slave_0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_master_0_slave_0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_master_0_slave_0.jdbc-url= spring.shardingsphere.datasource.ds_master_0_slave_0.username= 
spring.shardingsphere.datasource.ds_master_0_slave_0.password=
spring.shardingsphere.datasource.ds_master_0_slave_0.max-active=16
spring.shardingsphere.datasource.ds_master_0_slave_1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_master_0_slave_1.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_master_0_slave_1.jdbc-url= spring.shardingsphere.datasource.ds_master_0_slave_1.username= 
spring.shardingsphere.datasource.ds_master_0_slave_1.password=
spring.shardingsphere.datasource.ds_master_0_slave_1.max-active=16
spring.shardingsphere.datasource.ds_master_1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_master_1.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_master_1.jdbc-url= 
spring.shardingsphere.datasource.ds_master_1.username= 
spring.shardingsphere.datasource.ds_master_1.password=
spring.shardingsphere.datasource.ds_master_1.max-active=16
spring.shardingsphere.datasource.ds_master_1_slave_0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_master_1_slave_0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_master_1_slave_0.jdbc-url=
spring.shardingsphere.datasource.ds_master_1_slave_0.username=
spring.shardingsphere.datasource.ds_master_1_slave_0.password=
spring.shardingsphere.datasource.ds_master_1_slave_0.max-active=16
spring.shardingsphere.datasource.ds_master_1_slave_1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds_master_1_slave_1.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds_master_1_slave_1.jdbc-url= spring.shardingsphere.datasource.ds_master_1_slave_1.username=admin
spring.shardingsphere.datasource.ds_master_1_slave_1.password=
spring.shardingsphere.datasource.ds_master_1_slave_1.max-active=16
spring.shardingsphere.sharding.default-database-strategy.inline.sharding-column=user_id
spring.shardingsphere.sharding.default-database-strategy.inline.algorithm-expression=ds_$->{user_id % 2}
spring.shardingsphere.sharding.binding-tables=t_order,t_order_item
spring.shardingsphere.sharding.broadcast-tables=t_address
spring.shardingsphere.sharding.default-data-source-name=ds_master_0
spring.shardingsphere.sharding.tables.t_order.actual-data-nodes=ds_$->{0..1}.t_order_$->{0..1}
spring.shardingsphere.sharding.tables.t_order.table-strategy.inline.sharding-column=order_id
spring.shardingsphere.sharding.tables.t_order.table-strategy.inline.algorithm-expression=t_order_$->{order_id % 2}
spring.shardingsphere.sharding.tables.t_order.key-generator.column=order_id
spring.shardingsphere.sharding.tables.t_order.key-generator.type=SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order.key-generator.props.worker.id=123
spring.shardingsphere.sharding.tables.t_order_item.actual-data-nodes=ds_$->{0..1}.t_order_item_$->{0..1}
spring.shardingsphere.sharding.tables.t_order_item.table-strategy.inline.sharding-column=order_id
spring.shardingsphere.sharding.tables.t_order_item.table-strategy.inline.algorithm-expression=t_order_item_$->{order_id % 2}
spring.shardingsphere.sharding.tables.t_order_item.key-generator.column=order_item_id
spring.shardingsphere.sharding.tables.t_order_item.key-generator.type=SNOWFLAKE
spring.shardingsphere.sharding.tables.t_order_item.key-generator.props.worker.id=123
# master/slave data source and slave data source configuration
spring.shardingsphere.sharding.master-slave-rules.ds_0.master-data-source-name=ds_master_0
spring.shardingsphere.sharding.master-slave-rules.ds_0.slave-data-source-names=ds_master_0_slave_0, ds_master_0_slave_1
spring.shardingsphere.sharding.master-slave-rules.ds_1.master-data-source-name=ds_master_1
spring.shardingsphere.sharding.master-slave-rules.ds_1.slave-data-source-names=ds_master_1_slave_0, ds_master_1_slave_1
# sharding-jdbc mode
spring.shardingsphere.mode.type=Memory
# start shardingsphere log
spring.shardingsphere.props.sql.show=true

 

3.6.3 Test and verification process description

1. DDL operation

JPA automatically creates tables for testing. When Sharding-JDBC’s library splitting and routing rules are configured, the client executes DDL, and Sharding-JDBC will automatically create corresponding tables according to table splitting rules. If t_address is a broadcast table, t_address will be created on both ds_0 and ds_1. The three tables, t_address, t_order and t_order_item will be created on ds_0 and ds_1 respectively.

2. Write operation

For the broadcast table t_address, each record written will also be written to the t_address tables of ds_0 and ds_1.

The tables t_order and t_order_item of the slave library are written to the table on the corresponding instance according to the slave library field and routing policy.

3. Read operation

The join query operations on order and order_item under the binding table are shown below.

3. Conclusion

As an open source product focusing on database enhancement, ShardingSphere is pretty good in terms of its community activitiy, product maturity and documentation richness.

Among its products, ShardingSphere-JDBC is a sharding solution based on the client-side, which supports all sharding scenarios. And there’s no need to introduce an intermediate layer like Proxy, so the complexity of operation and maintenance is reduced. Its latency is theoretically lower than Proxy due to the lack of intermediate layer. In addition, ShardingSphere-JDBC can support a variety of relational databases based on SQL standards such as MySQL/PostgreSQL/Oracle/SQL Server, etc.

However, due to the integration of Sharding-JDBC with the application program, it only supports Java language for now, and is strongly dependent on the application programs. Nevertheless, Sharding-JDBC separates all sharding configuration from the application program, which brings relatively small changes when switching to other middleware.

In conclusion, Sharding-JDBC is a good choice if you use a Java-based system and have to to interconnect with different relational databases — and don’t want to bother with introducing an intermediate layer.

Author

Sun Jinhua

A senior solution architect at AWS, Sun is responsible for the design and consult on cloud architecture. for providing customers with cloud-related design and consulting services. Before joining AWS, he ran his own business, specializing in building e-commerce platforms and designing the overall architecture for e-commerce platforms of automotive companies. He worked in a global leading communication equipment company as a senior engineer, responsible for the development and architecture design of multiple subsystems of LTE equipment system. He has rich experience in architecture design with high concurrency and high availability system, microservice architecture design, database, middleware, IOT etc.

 iOS App Dev

iOS App Dev

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Sean Robertson

Sean Robertson

1548150381

Multitenant configuration: StaleObjectStateException on Transaction (hibernate + spring-data-jpa)

i'm trying to setup a configuration for manage a multi-tenant enviroment with spring-boot, spring-data-jpa, hibernate and mysql (same schema, every tenant table has a tenant_code column). For dependencies the parent maven project is spring-boot-starter-parent (2.1.2.RELEASE).

On save entity hibernate throws this exception: org.hibernate.StaleObjectStateException: Row was updated or deleted by another transaction (or unsaved-value mapping was incorrect) :

The highlights steps are:

  1. Intercept "tenant code" with custom spring HandlerInterceptorAdapter (i read oauth2 token and extract custom attribute "tenant code");
  2. Save "tenant code" in a @RequestScope bean; 

  3. On Save
  4. Define an custom hibernate EmptyInterceptor to intercept onSave action and previously set the "tenant code" (taken on a @RequestScope bean) 

  5. On Read
  6. In abstract Entity (extended by all my entities) i define @Filter and set it via AOP

If in interceptor i override onSave method i get this exception:

org.hibernate.StaleObjectStateException: Row was updated or deleted by another transaction (or unsaved-value mapping was incorrect) : [com.test.module.api.domain.entity.User#22]
    at org.hibernate.persister.entity.AbstractEntityPersister.check(AbstractEntityPersister.java:2522) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.persister.entity.AbstractEntityPersister.update(AbstractEntityPersister.java:3355) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.persister.entity.AbstractEntityPersister.updateOrInsert(AbstractEntityPersister.java:3229) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.persister.entity.AbstractEntityPersister.update(AbstractEntityPersister.java:3630) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.action.internal.EntityUpdateAction.execute(EntityUpdateAction.java:146) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.engine.spi.ActionQueue.executeActions(ActionQueue.java:604) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.engine.spi.ActionQueue.executeActions(ActionQueue.java:478) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.event.internal.AbstractFlushingEventListener.performExecutions(AbstractFlushingEventListener.java:356) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.event.internal.DefaultFlushEventListener.onFlush(DefaultFlushEventListener.java:39) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.internal.SessionImpl.doFlush(SessionImpl.java:1454) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.internal.SessionImpl.managedFlush(SessionImpl.java:511) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.internal.SessionImpl.flushBeforeTransactionCompletion(SessionImpl.java:3283) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.internal.SessionImpl.beforeTransactionCompletion(SessionImpl.java:2479) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.engine.jdbc.internal.JdbcCoordinatorImpl.beforeTransactionCompletion(JdbcCoordinatorImpl.java:473) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.resource.transaction.backend.jdbc.internal.JdbcResourceLocalTransactionCoordinatorImpl.beforeCompletionCallback(JdbcResourceLocalTransactionCoordinatorImpl.java:178) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.resource.transaction.backend.jdbc.internal.JdbcResourceLocalTransactionCoordinatorImpl.access$300(JdbcResourceLocalTransactionCoordinatorImpl.java:39) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.resource.transaction.backend.jdbc.internal.JdbcResourceLocalTransactionCoordinatorImpl$TransactionDriverControlImpl.commit(JdbcResourceLocalTransactionCoordinatorImpl.java:271) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.hibernate.engine.transaction.internal.TransactionImpl.commit(TransactionImpl.java:98) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
    at org.springframework.orm.jpa.JpaTransactionManager.doCommit(JpaTransactionManager.java:532) ~[spring-orm-5.1.4.RELEASE.jar:5.1.4.RELEASE]
    at org.springframework.transaction.support.AbstractPlatformTransactionManager.processCommit(AbstractPlatformTransactionManager.java:746) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
    at org.springframework.transaction.support.AbstractPlatformTransactionManager.commit(AbstractPlatformTransactionManager.java:714) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
    at org.springframework.transaction.interceptor.TransactionAspectSupport.commitTransactionAfterReturning(TransactionAspectSupport.java:533) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
    at org.springframework.transaction.interceptor.TransactionAspectSupport.invokeWithinTransaction(TransactionAspectSupport.java:304) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
    at org.springframework.transaction.interceptor.TransactionInterceptor.invoke(TransactionInterceptor.java:98) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
    at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:186) ~[spring-aop-5.1.4.RELEASE.jar:5.1.4.RELEASE]
    at org.springframework.aop.framework.CglibAopProxy$DynamicAdvisedInterceptor.intercept(CglibAopProxy.java:688) ~[spring-aop-5.1.4.RELEASE.jar:5.1.4.RELEASE]
    at com.test.module.api.service.UserServiceImpl$$EnhancerBySpringCGLIB$$baf4f87e.updateUser(<generated>) ~[classes/:na]
    at com.test.module.api.web.UserController.updateUser(UserController.java:38) ~[classes/:na]


Here the code: 

Spring Interceptor from Request Header:

    @Component
    public class TokenInterceptor extends HandlerInterceptorAdapter {
        public final String TENANT_CODE = "tenant_code";
    @Autowired
    private CurrentUser currentUser;

    @Override
    public boolean preHandle(HttpServletRequest request, HttpServletResponse response, Object handler)
            throws Exception {
        String tenantCode = ... extract tenant code from request...;
        currentUser.setTenantCode(tenantCode);        
        return true;
    }
}


Class to setup inteceptor in hibernate:

    @Component
public class TenantHibernateInterceptorCustomizer implements HibernatePropertiesCustomizer {

    @Autowired
    private TenantJpaInterceptor jpaInterceptor;

    @Override
    public void customize(Map&lt;String, Object&gt; hibernateProperties) {
        hibernateProperties.put("hibernate.session_factory.interceptor", jpaInterceptor);
    }

}


Hibernate custom interceptor:

    @Component
public class TenantJpaInterceptor extends EmptyInterceptor {
//Comment to test if problem is about spring context
//@Autowired
//private CurrentUser currentUser;

    @Override
    public boolean onSave(Object entity, Serializable id, Object[] state, String[] propertyNames, Type[] types) {
        if (entity instanceof TenantAuditable) {
            //((TenantAuditable&lt;?&gt;) entity).setTenandCode(currentUser.getTenantCode());
            //if i comment this line everythings works (without tenant code)
            ((TenantAuditable&lt;?&gt;) entity).setTenandCode("TEST");            
        }
        return false;
    }
}


Service layer:

    @Transactional
public UpsertResponse<UserDto> updateUser(UserDto userDto) {
UpsertResponse<UserDto> validationResult = CommonValidators.validateUserDto(userDto);
if(!validationResult.isValidated()) {
return validationResult;

    SpUser user = userRepo.findById(userDto.getUserId()).orElse(new SpUser());
    userMapper.mapUserDtoToEntity(userDto, user);
    try {
        SpUser savedUser = userRepo.save(user);
        validationResult.setEntity(userMapper.mapUserDtoFromEntity(savedUser));
        validationResult.setValidated(true);
    }catch(Exception e) {
        e.printStackTrace();
        validationResult.setValidated(false);
        validationResult.setGlobalMessage(e.getLocalizedMessage());

    }
    return validationResult;
}

I expected a insert/update sql query with filled tenant_code field.


Here complete log

2019-01-22 01:10:57.521  INFO 14304 — [nio-8090-exec-1] o.a.c.c.C.[Tomcat].[localhost].[/]       : Initializing Spring DispatcherServlet ‘dispatcherServlet’
2019-01-22 01:10:57.523 INFO 14304 — [nio-8090-exec-1] o.s.web.servlet.DispatcherServlet : Initializing Servlet ‘dispatcherServlet’
2019-01-22 01:10:57.550 INFO 14304 — [nio-8090-exec-1] o.s.web.servlet.DispatcherServlet : Completed initialization in 27 ms
Hibernate:
select
spuser0_.user_id as user_id1_0_0_,
spuser0_.created_by as created_2_0_0_,
spuser0_.created_date as created_3_0_0_,
spuser0_.last_modified_by as last_mod4_0_0_,
spuser0_.last_modified_date as last_mod5_0_0_,
spuser0_.tenant_code as tenant_c6_0_0_,
spuser0_.buyer_id as buyer_id7_0_0_,
spuser0_.email as email8_0_0_,
spuser0_.family_name as family_n9_0_0_,
spuser0_.given_name as given_n10_0_0_,
spuser0_.middle_name as middle_11_0_0_,
spuser0_.user_name as user_na12_0_0_
from
sp_user spuser0_
where
spuser0_.user_id=?
2019-01-22 01:11:10.689 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [1] as [BIGINT] - [2]
Hibernate:
select
spuser0_.user_id as user_id1_0_0_,
spuser0_.created_by as created_2_0_0_,
spuser0_.created_date as created_3_0_0_,
spuser0_.last_modified_by as last_mod4_0_0_,
spuser0_.last_modified_date as last_mod5_0_0_,
spuser0_.tenant_code as tenant_c6_0_0_,
spuser0_.buyer_id as buyer_id7_0_0_,
spuser0_.email as email8_0_0_,
spuser0_.family_name as family_n9_0_0_,
spuser0_.given_name as given_n10_0_0_,
spuser0_.middle_name as middle_11_0_0_,
spuser0_.user_name as user_na12_0_0_
from
sp_user spuser0_
where
spuser0_.user_id=?
2019-01-22 01:11:14.414 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [1] as [BIGINT] - [2]
Hibernate:
insert
into
sp_user
(created_by, created_date, last_modified_by, last_modified_date, tenant_code, buyer_id, email, family_name, given_name, middle_name, user_name)
values
(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
2019-01-22 01:11:23.137 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [1] as [VARCHAR] - [3bf38f12-5d17-47e4-9504-ad0705289d10]
2019-01-22 01:11:23.138 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [2] as [TIMESTAMP] - [Tue Jan 22 01:11:14 CET 2019]
2019-01-22 01:11:23.140 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [3] as [VARCHAR] - [3bf38f12-5d17-47e4-9504-ad0705289d10]
2019-01-22 01:11:23.140 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [4] as [TIMESTAMP] - [Tue Jan 22 01:11:14 CET 2019]
2019-01-22 01:11:23.140 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [5] as [VARCHAR] - [null]
2019-01-22 01:11:23.140 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [6] as [VARCHAR] - [1]
2019-01-22 01:11:23.140 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [7] as [VARCHAR] - [gabriele.muscas@gmail.comx]
2019-01-22 01:11:23.140 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [8] as [VARCHAR] - [Muscas]
2019-01-22 01:11:23.140 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [9] as [VARCHAR] - [Gabrielex]
2019-01-22 01:11:23.141 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [10] as [VARCHAR] - [Giuseppe Pippo]
2019-01-22 01:11:23.141 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [11] as [VARCHAR] - [gabriele.muscas]
Hibernate:
update
sp_user
set
created_by=?,
created_date=?,
last_modified_by=?,
last_modified_date=?,
tenant_code=?,
buyer_id=?,
email=?,
family_name=?,
given_name=?,
middle_name=?,
user_name=?
where
user_id=?
2019-01-22 01:11:24.912 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [1] as [VARCHAR] - [3bf38f12-5d17-47e4-9504-ad0705289d10]
2019-01-22 01:11:24.912 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [2] as [TIMESTAMP] - [Tue Jan 22 01:11:14 CET 2019]
2019-01-22 01:11:24.913 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [3] as [VARCHAR] - [3bf38f12-5d17-47e4-9504-ad0705289d10]
2019-01-22 01:11:24.913 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [4] as [TIMESTAMP] - [Tue Jan 22 01:11:24 CET 2019]
2019-01-22 01:11:24.913 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [5] as [VARCHAR] - [PIPPO]
2019-01-22 01:11:24.913 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [6] as [VARCHAR] - [1]
2019-01-22 01:11:24.914 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [7] as [VARCHAR] - [gabriele.muscas@gmail.comx]
2019-01-22 01:11:24.914 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [8] as [VARCHAR] - [Muscas]
2019-01-22 01:11:24.914 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [9] as [VARCHAR] - [Gabrielex]
2019-01-22 01:11:24.915 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [10] as [VARCHAR] - [Giuseppe Pippo]
2019-01-22 01:11:24.915 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [11] as [VARCHAR] - [gabriele.muscas]
2019-01-22 01:11:24.915 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [12] as [BIGINT] - [23]
2019-01-22 01:11:24.918 ERROR 14304 — [nio-8090-exec-2] o.h.i.ExceptionMapperStandardImpl : HHH000346: Error during managed flush [Row was updated or deleted by another transaction (or unsaved-value mapping was incorrect) : [com.supplhi.buyer.api.domain.entity.SpUser#23]]
Hibernate:
select
spuser0_.user_id as user_id1_0_0_,
spuser0_.created_by as created_2_0_0_,
spuser0_.created_date as created_3_0_0_,
spuser0_.last_modified_by as last_mod4_0_0_,
spuser0_.last_modified_date as last_mod5_0_0_,
spuser0_.tenant_code as tenant_c6_0_0_,
spuser0_.buyer_id as buyer_id7_0_0_,
spuser0_.email as email8_0_0_,
spuser0_.family_name as family_n9_0_0_,
spuser0_.given_name as given_n10_0_0_,
spuser0_.middle_name as middle_11_0_0_,
spuser0_.user_name as user_na12_0_0_
from
sp_user spuser0_
where
spuser0_.user_id=?
2019-01-22 01:11:24.928 TRACE 14304 — [nio-8090-exec-2] o.h.type.descriptor.sql.BasicBinder : binding parameter [1] as [BIGINT] - [23]
2019-01-22 01:11:24.940 ERROR 14304 — [nio-8090-exec-2] o.a.c.c.C.[.[.[/].[dispatcherServlet] : Servlet.service() for servlet [dispatcherServlet] in context with path [] threw exception [Request processing failed; nested exception is org.springframework.orm.ObjectOptimisticLockingFailureException: Object of class [com.supplhi.buyer.api.domain.entity.SpUser] with identifier [23]: optimistic locking failed; nested exception is org.hibernate.StaleObjectStateException: Row was updated or deleted by another transaction (or unsaved-value mapping was incorrect) : [com.supplhi.buyer.api.domain.entity.SpUser#23]] with root cause

org.hibernate.StaleObjectStateException: Row was updated or deleted by another transaction (or unsaved-value mapping was incorrect) : [com.supplhi.buyer.api.domain.entity.SpUser#23]
at org.hibernate.persister.entity.AbstractEntityPersister.check(AbstractEntityPersister.java:2522) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.persister.entity.AbstractEntityPersister.update(AbstractEntityPersister.java:3355) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.persister.entity.AbstractEntityPersister.updateOrInsert(AbstractEntityPersister.java:3229) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.persister.entity.AbstractEntityPersister.update(AbstractEntityPersister.java:3630) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.action.internal.EntityUpdateAction.execute(EntityUpdateAction.java:146) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.engine.spi.ActionQueue.executeActions(ActionQueue.java:604) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.engine.spi.ActionQueue.executeActions(ActionQueue.java:478) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.event.internal.AbstractFlushingEventListener.performExecutions(AbstractFlushingEventListener.java:356) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.event.internal.DefaultFlushEventListener.onFlush(DefaultFlushEventListener.java:39) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.internal.SessionImpl.doFlush(SessionImpl.java:1454) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.internal.SessionImpl.managedFlush(SessionImpl.java:511) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.internal.SessionImpl.flushBeforeTransactionCompletion(SessionImpl.java:3283) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.internal.SessionImpl.beforeTransactionCompletion(SessionImpl.java:2479) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.engine.jdbc.internal.JdbcCoordinatorImpl.beforeTransactionCompletion(JdbcCoordinatorImpl.java:473) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.resource.transaction.backend.jdbc.internal.JdbcResourceLocalTransactionCoordinatorImpl.beforeCompletionCallback(JdbcResourceLocalTransactionCoordinatorImpl.java:178) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.resource.transaction.backend.jdbc.internal.JdbcResourceLocalTransactionCoordinatorImpl.access$300(JdbcResourceLocalTransactionCoordinatorImpl.java:39) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.resource.transaction.backend.jdbc.internal.JdbcResourceLocalTransactionCoordinatorImpl$TransactionDriverControlImpl.commit(JdbcResourceLocalTransactionCoordinatorImpl.java:271) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.hibernate.engine.transaction.internal.TransactionImpl.commit(TransactionImpl.java:98) ~[hibernate-core-5.3.7.Final.jar:5.3.7.Final]
at org.springframework.orm.jpa.JpaTransactionManager.doCommit(JpaTransactionManager.java:532) ~[spring-orm-5.1.4.RELEASE.jar:5.1.4.RELEASE]
at org.springframework.transaction.support.AbstractPlatformTransactionManager.processCommit(AbstractPlatformTransactionManager.java:746) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
at org.springframework.transaction.support.AbstractPlatformTransactionManager.commit(AbstractPlatformTransactionManager.java:714) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
at org.springframework.transaction.interceptor.TransactionAspectSupport.commitTransactionAfterReturning(TransactionAspectSupport.java:533) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
at org.springframework.transaction.interceptor.TransactionAspectSupport.invokeWithinTransaction(TransactionAspectSupport.java:304) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
at org.springframework.transaction.interceptor.TransactionInterceptor.invoke(TransactionInterceptor.java:98) ~[spring-tx-5.1.4.RELEASE.jar:5.1.4.RELEASE]
at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:186) ~[spring-aop-5.1.4.RELEASE.jar:5.1.4.RELEASE]
at org.springframework.aop.framework.CglibAopProxy$DynamicAdvisedInterceptor.intercept(CglibAopProxy.java:688) ~[spring-aop-5.1.4.RELEASE.jar:5.1.4.RELEASE]
at com.supplhi.buyer.api.service.UserServiceImpl$$EnhancerBySpringCGLIB$$baf4f87e.updateUser(<generated>) ~[classes/:na]
at com.supplhi.buyer.api.web.UserController.updateUser(UserController.java:38) ~[classes/:na]

A little help, s’ll vous plaît. Thanks

#java #spring #hibernate #jpa

Gerhard  Brink

Gerhard Brink

1620629020

Getting Started With Data Lakes

Frameworks for Efficient Enterprise Analytics

The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.

This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.

Introduction

As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).


This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.

#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management

Everything you need to know about Spring Data JPA

In this post, I cover everything you need to know about Spring Data JPA so you can use this library more confidently in your Spring Boot application. I have seen there are a lot of confusion about when to use CrudRepository  or JpaRepository , so I will cover that as well.

What is Spring Data JPA?

As the official documentation from Spring says “Spring Data JPA makes it easy to implement JPA based repositories. It improves and eases the implementation of the JPA-based data access layer. Overall, data access applications are easier to implement.”

With Spring Data JPA, one can avoid a lot of boilerplate code for Java Persistent API (JPA) in the application. The library also makes it easy to query the data from the database taking away a lot of implementation for SQL queries from a developer.

As a developer, you only write repository interfaces including any custom methods and Spring Data JPA will provide the most implementation automatically.

#spring-boot #spring-data #spring-data-jpa #hibernate #persistence