Hibernate.orgCommunity Documentation
To audit changes that are performed on an entity, you only need two things: the
hibernate-envers
jar on the classpath and an @Audited
annotation
on the entity.
Unlike in previous versions, you no longer need to specify listeners in the Hibernate configuration file. Just putting the Envers jar on the classpath is enough - listeners will be registered automatically.
And that's all - you can create, modify and delete the entites as always. If you look at the generated
schema for your entities, or at the data persisted by Hibernate, you will notice that there are no changes.
However, for each audited entity, a new table is introduced - entity_table_AUD
,
which stores the historical data, whenever you commit a transaction.
Instead of annotating the whole class and auditing all properties, you can annotate
only some persistent properties with @Audited
. This will cause only
these properties to be audited.
The audit (history) of an entity can be accessed using the AuditReader
interface, which
can be obtained having an open <listeral>EntityManager</listeral> or Session
via
the AuditReaderFactory
. See the javadocs for these classes for details on the
functionality offered.
It is possible to configure various aspects of Hibernate Envers behavior, such as table names, etc.
Table 15.1. Envers Configuration Properties
Property name | Default value | Description |
---|---|---|
org.hibernate.envers.audit_table_prefix | String that will be prepended to the name of an audited entity to create the name of the entity, that will hold audit information. | |
org.hibernate.envers.audit_table_suffix | _AUD |
String that will be appended to the name of an audited entity to create the name of the
entity, that will hold audit information. If you audit an entity with a table name Person,
in the default setting Envers will generate a Person_AUD table to store
historical data.
|
org.hibernate.envers.revision_field_name | REV | Name of a field in the audit entity that will hold the revision number. |
org.hibernate.envers.revision_type_field_name | REVTYPE | Name of a field in the audit entity that will hold the type of the revision (currently, this can be: add, mod, del). |
org.hibernate.envers.revision_on_collection_change | true | Should a revision be generated when a not-owned relation field changes (this can be either a collection in a one-to-many relation, or the field using "mappedBy" attribute in a one-to-one relation). |
org.hibernate.envers.do_not_audit_optimistic_locking_field | true |
When true, properties to be used for optimistic locking, annotated with
@Version , will be automatically not audited (their history won't be
stored; it normally doesn't make sense to store it).
|
org.hibernate.envers.store_data_at_delete | false | Should the entity data be stored in the revision when the entity is deleted (instead of only storing the id and all other properties as null). This is not normally needed, as the data is present in the last-but-one revision. Sometimes, however, it is easier and more efficient to access it in the last revision (then the data that the entity contained before deletion is stored twice). |
org.hibernate.envers.default_schema | null (same schema as table being audited) |
The default schema name that should be used for audit tables. Can be overridden using the
@AuditTable(schema="...") annotation. If not present, the schema will
be the same as the schema of the table being audited.
|
org.hibernate.envers.default_catalog | null (same catalog as table being audited) |
The default catalog name that should be used for audit tables. Can be overridden using the
@AuditTable(catalog="...") annotation. If not present, the catalog will
be the same as the catalog of the normal tables.
|
org.hibernate.envers.audit_strategy | org.hibernate.envers.strategy.DefaultAuditStrategy |
The audit strategy that should be used when persisting audit data. The default stores only
the revision, at which an entity was modified. An alternative, the
org.hibernate.envers.strategy.ValidityAuditStrategy stores both the
start revision and the end revision. Together these define when an audit row was valid,
hence the name ValidityAuditStrategy.
|
org.hibernate.envers.audit_strategy_validity_end_rev_field_name | REVEND | The column name that will hold the end revision number in audit entities. This property is only valid if the validity audit strategy is used. |
org.hibernate.envers.audit_strategy_validity_store_revend_timestamp | false | Should the timestamp of the end revision be stored, until which the data was valid, in addition to the end revision itself. This is useful to be able to purge old Audit records out of a relational database by using table partitioning. Partitioning requires a column that exists within the table. This property is only evaluated if the ValidityAuditStrategy is used. |
org.hibernate.envers.audit_strategy_validity_revend_timestamp_field_name | REVEND_TSTMP | Column name of the timestamp of the end revision until which the data was valid. Only used if the ValidityAuditStrategy is used, and org.hibernate.envers.audit_strategy_validity_store_revend_timestamp evaluates to true |
org.hibernate.envers.track_entities_changed_in_revision | false |
Should entity types, that have been modified during each revision, be tracked. The default
implementation creates REVCHANGES table that stores entity names
of modified persistent objects. Single record encapsulates the revision identifier
(foreign key to REVINFO table) and a string value. For more
information refer to Section 15.5.1, “Tracking entity names modified during revisions”
and Section 15.6.3, “Querying for entities modified in a given revision”.
|
The following configuration options have been added recently and should be regarded as experimental:
The name of the audit table can be set on a per-entity basis, using the
@AuditTable
annotation. It may be tedious to add this
annotation to every audited entity, so if possible, it's better to use a prefix/suffix.
If you have a mapping with secondary tables, audit tables for them will be generated in
the same way (by adding the prefix and suffix). If you wish to overwrite this behaviour,
you can use the @SecondaryAuditTable
and
@SecondaryAuditTables
annotations.
If you'd like to override auditing behaviour of some fields/properties inherited from
@Mappedsuperclass
or in an embedded component, you can
apply the @AuditOverride(s)
annotation on the subtype or usage site
of the component.
If you want to audit a relation mapped with @OneToMany+@JoinColumn
,
please see Section 15.10, “Mapping exceptions” for a description of the additional
@AuditJoinTable
annotation that you'll probably want to use.
If you want to audit a relation, where the target entity is not audited (that is the case for example with
dictionary-like entities, which don't change and don't have to be audited), just annotate it with
@Audited(targetAuditMode = RelationTargetAuditMode.NOT_AUDITED)
. Then, when reading historic
versions of your entity, the relation will always point to the "current" related entity.
If you'd like to audit properties of a superclass of an entity, which are not explicitly audited (which
don't have the @Audited
annotation on any properties or on the class), you can list the
superclasses in the auditParents
attribute of the @Audited
annotation. Please note that auditParents
feature has been deprecated. Use
@AuditOverride(forClass = SomeEntity.class, isAudited = true/false)
instead.
After the basic configuration it is important to choose the audit strategy that will be used to persist and retrieve audit information. There is a trade-off between the performance of persisting and the performance of querying the audit information. Currently there two audit strategies.
The default audit strategy persists the audit data together with a start revision. For each row inserted, updated or deleted in an audited table, one or more rows are inserted in the audit tables, together with the start revision of its validity. Rows in the audit tables are never updated after insertion. Queries of audit information use subqueries to select the applicable rows in the audit tables. These subqueries are notoriously slow and difficult to index.
The alternative is a validity audit strategy. This strategy stores the start-revision and the end-revision of audit information. For each row inserted, updated or deleted in an audited table, one or more rows are inserted in the audit tables, together with the start revision of its validity. But at the same time the end-revision field of the previous audit rows (if available) are set to this revision. Queries on the audit information can then use 'between start and end revision' instead of subqueries as used by the default audit strategy.
The consequence of this strategy is that persisting audit information will be a bit slower, because of the extra updates involved, but retrieving audit information will be a lot faster. This can be improved by adding extra indexes.
When Envers starts a new revision, it creates a new revision entity which stores information about the revision. By default, that includes just
int/Integer
or
long/Long
). Essentially the primary key of the revision
long/Long
or
java.util.Date
value representing the instant at which the revision was made.
When using a java.util.Date
, instead of a long/Long
for
the revision timestamp, take care not to store it to a column data type which will loose precision.
Envers handles this information as an entity. By default it uses its own internal class to act as the
entity, mapped to the REVINFO
table.
You can, however, supply your own approach to collecting this information which might be useful to
capture additional details such as who made a change or the ip address from which the request came. There
are 2 things you need to make this work.
First, you will need to tell Envers about the entity you wish to use. Your entity must use the
@org.hibernate.envers.RevisionEntity
annotation. It must
define the 2 attributes described above annotated with
@org.hibernate.envers.RevisionNumber
and
@org.hibernate.envers.RevisionTimestamp
, respectively. You can extend
from org.hibernate.envers.DefaultRevisionEntity
, if you wish, to inherit all
these required behaviors.
Simply add the custom revision entity as you do your normal entities. Envers will "find it". Note
that it is an error for there to be multiple entities marked as
@org.hibernate.envers.RevisionEntity
Second, you need to tell Envers how to create instances of your revision entity which is handled
by the newRevision
method of the
org.jboss.envers.RevisionListener
interface.
You tell Envers your custom org.hibernate.envers.RevisionListener
implementation to use by specifying it on the
@org.hibernate.envers.RevisionEntity
annotation, using the
value
attribute. If your RevisionListener
class is inaccessible from @RevisionEntity
(e.g. exists in a different
module), set org.hibernate.envers.revision_listener property to it's fully
qualified name. Class name defined by the configuration parameter overrides revision entity's
value
attribute.
@Entity @RevisionEntity( MyCustomRevisionListener.class ) public class MyCustomRevisionEntity { ... } public class MyCustomRevisionListener implements RevisionListener { public void newRevision(Object revisionEntity) { ( (MyCustomRevisionEntity) revisionEntity )...; } }
An alternative method to using the org.hibernate.envers.RevisionListener
is to instead call the getCurrentRevision
method of the
org.hibernate.envers.AuditReader
interface to obtain the current revision,
and fill it with desired information. The method accepts a persist
parameter indicating
whether the revision entity should be persisted prior to returning from this method. true
ensures that the returned entity has access to its identifier value (revision number), but the revision
entity will be persisted regardless of whether there are any audited entities changed. false
means that the revision number will be null
, but the revision entity will be persisted
only if some audited entities have changed.
Example 15.1. Example of storing username with revision
ExampleRevEntity.java
package org.hibernate.envers.example;
import org.hibernate.envers.RevisionEntity;
import org.hibernate.envers.DefaultRevisionEntity;
import javax.persistence.Entity;
@Entity
@RevisionEntity(ExampleListener.class)
public class ExampleRevEntity extends DefaultRevisionEntity {
private String username;
public String getUsername() { return username; }
public void setUsername(String username) { this.username = username; }
}
ExampleListener.java
package org.hibernate.envers.example;
import org.hibernate.envers.RevisionListener;
import org.jboss.seam.security.Identity;
import org.jboss.seam.Component;
public class ExampleListener implements RevisionListener {
public void newRevision(Object revisionEntity) {
ExampleRevEntity exampleRevEntity = (ExampleRevEntity) revisionEntity;
Identity identity =
(Identity) Component.getInstance("org.jboss.seam.security.identity");
exampleRevEntity.setUsername(identity.getUsername());
}
}
By default entity types that have been changed in each revision are not being tracked. This implies the
necessity to query all tables storing audited data in order to retrieve changes made during
specified revision. Envers provides a simple mechanism that creates REVCHANGES
table which stores entity names of modified persistent objects. Single record encapsulates the revision
identifier (foreign key to REVINFO
table) and a string value.
Tracking of modified entity names can be enabled in three different ways:
true
. In this case
org.hibernate.envers.DefaultTrackingModifiedEntitiesRevisionEntity
will
be implicitly used as the revision log entity.
org.hibernate.envers.DefaultTrackingModifiedEntitiesRevisionEntity
class.
@Entity @RevisionEntity public class ExtendedRevisionEntity extends DefaultTrackingModifiedEntitiesRevisionEntity { ... }
@org.hibernate.envers.ModifiedEntityNames
annotation. The property is
required to be of Set<String>
type.
@Entity @RevisionEntity public class AnnotatedTrackingRevisionEntity { ... @ElementCollection @JoinTable(name = "REVCHANGES", joinColumns = @JoinColumn(name = "REV")) @Column(name = "ENTITYNAME") @ModifiedEntityNames private Set<String> modifiedEntityNames; ... }
Users, that have chosen one of the approaches listed above, can retrieve all entities modified in a specified revision by utilizing API described in Section 15.6.3, “Querying for entities modified in a given revision”.
Users are also allowed to implement custom mechanism of tracking modified entity types. In this case, they
shall pass their own implementation of
org.hibernate.envers.EntityTrackingRevisionListener
interface as the value
of @org.hibernate.envers.RevisionEntity
annotation.
EntityTrackingRevisionListener
interface exposes one method that notifies
whenever audited entity instance has been added, modified or removed within current revision boundaries.
Example 15.2. Custom implementation of tracking entity classes modified during revisions
CustomEntityTrackingRevisionListener.java
public class CustomEntityTrackingRevisionListener
implements EntityTrackingRevisionListener {
@Override
public void entityChanged(Class entityClass, String entityName,
Serializable entityId, RevisionType revisionType,
Object revisionEntity) {
String type = entityClass.getName();
((CustomTrackingRevisionEntity)revisionEntity).addModifiedEntityType(type);
}
@Override
public void newRevision(Object revisionEntity) {
}
}
CustomTrackingRevisionEntity.java
@Entity
@RevisionEntity(CustomEntityTrackingRevisionListener.class)
public class CustomTrackingRevisionEntity {
@Id
@GeneratedValue
@RevisionNumber
private int customId;
@RevisionTimestamp
private long customTimestamp;
@OneToMany(mappedBy="revision", cascade={CascadeType.PERSIST, CascadeType.REMOVE})
private Set<ModifiedEntityTypeEntity> modifiedEntityTypes =
new HashSet<ModifiedEntityTypeEntity>();
public void addModifiedEntityType(String entityClassName) {
modifiedEntityTypes.add(new ModifiedEntityTypeEntity(this, entityClassName));
}
...
}
ModifiedEntityTypeEntity.java
@Entity
public class ModifiedEntityTypeEntity {
@Id
@GeneratedValue
private Integer id;
@ManyToOne
private CustomTrackingRevisionEntity revision;
private String entityClassName;
...
}
CustomTrackingRevisionEntity revEntity = getAuditReader().findRevision(CustomTrackingRevisionEntity.class, revisionNumber); Set<ModifiedEntityTypeEntity> modifiedEntityTypes = revEntity.getModifiedEntityTypes()
You can think of historic data as having two dimension. The first - horizontal - is the state of the database at a given revision. Thus, you can query for entities as they were at revision N. The second - vertical - are the revisions, at which entities changed. Hence, you can query for revisions, in which a given entity changed.
The queries in Envers are similar to Hibernate Criteria, so if you are common with them, using Envers queries will be much easier.
The main limitation of the current queries implementation is that you cannot traverse relations. You can only specify constraints on the ids of the related entities, and only on the "owning" side of the relation. This however will be changed in future releases.
Please note, that queries on the audited data will be in many cases much slower than corresponding queries on "live" data, as they involve correlated subselects.
In the future, queries will be improved both in terms of speed and possibilities, when using the valid-time audit strategy, that is when storing both start and end revisions for entities. See ???.
The entry point for this type of queries is:
AuditQuery query = getAuditReader() .createQuery() .forEntitiesAtRevision(MyEntity.class, revisionNumber);
You can then specify constraints, which should be met by the entities returned, by
adding restrictions, which can be obtained using the AuditEntity
factory class. For example, to select only entities, where the "name" property
is equal to "John":
query.add(AuditEntity.property("name").eq("John"));
And to select only entites that are related to a given entity:
query.add(AuditEntity.property("address").eq(relatedEntityInstance)); // or query.add(AuditEntity.relatedId("address").eq(relatedEntityId));
You can limit the number of results, order them, and set aggregations and projections
(except grouping) in the usual way.
When your query is complete, you can obtain the results by calling the
getSingleResult()
or getResultList()
methods.
A full query, can look for example like this:
List personsAtAddress = getAuditReader().createQuery() .forEntitiesAtRevision(Person.class, 12) .addOrder(AuditEntity.property("surname").desc()) .add(AuditEntity.relatedId("address").eq(addressId)) .setFirstResult(4) .setMaxResults(2) .getResultList();
The entry point for this type of queries is:
AuditQuery query = getAuditReader().createQuery() .forRevisionsOfEntity(MyEntity.class, false, true);
You can add constraints to this query in the same way as to the previous one. There are some additional possibilities:
using AuditEntity.revisionNumber()
you can specify constraints, projections
and order on the revision number, in which the audited entity was modified
similarly, using AuditEntity.revisionProperty(propertyName)
you can specify constraints,
projections and order on a property of the revision entity, corresponding to the revision
in which the audited entity was modified
AuditEntity.revisionType()
gives you access as above to the type of
the revision (ADD, MOD, DEL).
Using these methods,
you can order the query results by revision number, set projection or constraint
the revision number to be greater or less than a specified value, etc. For example, the
following query will select the smallest revision number, at which entity of class
MyEntity
with id entityId
has changed, after revision
number 42:
Number revision = (Number) getAuditReader().createQuery() .forRevisionsOfEntity(MyEntity.class, false, true) .setProjection(AuditEntity.revisionNumber().min()) .add(AuditEntity.id().eq(entityId)) .add(AuditEntity.revisionNumber().gt(42)) .getSingleResult();
The second additional feature you can use in queries for revisions is the ability
to maximalize/minimize a property. For example, if you want to select the
revision, at which the value of the actualDate
for a given entity
was larger then a given value, but as small as possible:
Number revision = (Number) getAuditReader().createQuery() .forRevisionsOfEntity(MyEntity.class, false, true) // We are only interested in the first revision .setProjection(AuditEntity.revisionNumber().min()) .add(AuditEntity.property("actualDate").minimize() .add(AuditEntity.property("actualDate").ge(givenDate)) .add(AuditEntity.id().eq(givenEntityId))) .getSingleResult();
The minimize()
and maximize()
methods return a criteria,
to which you can add constraints, which must be met by the entities with the
maximized/minimized properties.
You probably also noticed that there are two boolean parameters, passed when
creating the query. The first one, selectEntitiesOnly
, is only valid when
you don't set an explicit projection. If true, the result of the query will be
a list of entities (which changed at revisions satisfying the specified
constraints).
If false, the result will be a list of three element arrays. The
first element will be the changed entity instance. The second will be an entity
containing revision data (if no custom entity is used, this will be an instance
of DefaultRevisionEntity
). The third will be the type of the
revision (one of the values of the RevisionType
enumeration:
ADD, MOD, DEL).
The second parameter, selectDeletedEntities
, specifies if revisions,
in which the entity was deleted should be included in the results. If yes, such entities
will have the revision type DEL and all fields, except the id,
null
.
The basic query allows retrieving entity names and corresponding Java classes changed in a specified revision:
Set<Pair<String, Class>> modifiedEntityTypes = getAuditReader() .getCrossTypeRevisionChangesReader().findEntityTypes(revisionNumber);
Other queries (also accessible from org.hibernate.envers.CrossTypeRevisionChangesReader
):
List<Object> findEntities(Number)
- Returns snapshots of all audited entities changed (added, updated and removed) in a given revision.
Executes n+1
SQL queries, where n
is a number of different entity
classes modified within specified revision.
List<Object> findEntities(Number, RevisionType)
- Returns snapshots of all audited entities changed (added, updated or removed) in a given revision
filtered by modification type. Executes n+1
SQL queries, where n
is a number of different entity classes modified within specified revision.
Map<RevisionType, List<Object>> findEntitiesGroupByRevisionType(Number)
- Returns a map containing lists of entity snapshots grouped by modification operation (e.g.
addition, update and removal). Executes 3n+1
SQL queries, where n
is a number of different entity classes modified within specified revision.
Note that methods described above can be legally used only when default mechanism of tracking changed entity names is enabled (see Section 15.5.1, “Tracking entity names modified during revisions”).
Envers persists audit data in reaction to various Hibernate events (e.g. post update, post insert, and
so on), using a series of even listeners from the org.hibernate.envers.event
package. By default, if the Envers jar is in the classpath, the event listeners are auto-registered with
Hibernate.
Conditional auditing can be implemented by overriding some of the Envers event listeners. To use customized Envers event listeners, the following steps are needed:
hibernate.listeners.envers.autoRegister
Hibernate property to false
.
org.hibernate.envers.eventEnversPostInsertEventListenerImpl
class. Place the conditional-auditing logic in the subclasses, call the super method if auditing
should be performed.
org.hibernate.integrator.spi.Integrator
,
similar to org.hibernate.envers.event.EnversIntegrator
. Use your event listener
classes instead of the default ones.
META-INF/services/org.hibernate.integrator.spi.Integrator
file to your jar.
The file should contain the fully qualified name of the class implementing the interface.
For each audited entity (that is, for each entity containing at least one audited field), an audit table is
created. By default, the audit table's name is created by adding a "_AUD" suffix to the original table name,
but this can be overridden by specifying a different suffix/prefix in the configuration or per-entity using
the @org.hibernate.envers.AuditTable
annotation.
Audit table columns
id of the original entity (this can be more then one column in the case of composite primary keys)
revision number - an integer. Matches to the revision number in the revision entity table.
revision type - a small integer
audited fields from the original entity
The primary key of the audit table is the combination of the original id of the entity and the revision number - there can be at most one historic entry for a given entity instance at a given revision.
The current entity data is stored in the original table and in the audit table. This is a duplication of data, however as this solution makes the query system much more powerful, and as memory is cheap, hopefully this won't be a major drawback for the users. A row in the audit table with entity id ID, revision N and data D means: entity with id ID has data D from revision N upwards. Hence, if we want to find an entity at revision M, we have to search for a row in the audit table, which has the revision number smaller or equal to M, but as large as possible. If no such row is found, or a row with a "deleted" marker is found, it means that the entity didn't exist at that revision.
The "revision type" field can currently have three values: 0, 1, 2, which means ADD, MOD and DEL, respectively. A row with a revision of type DEL will only contain the id of the entity and no data (all fields NULL), as it only serves as a marker saying "this entity was deleted at that revision".
Additionally, there is a <term>revision entity</term> table which contains the information about the global revision. By default the generated table is named REVINFO and contains just 2 columns: ID and TIMESTAMP. A row is inserted into this table on each new revision, that is, on each commit of a transaction, which changes audited data. The name of this table can be configured, the name of its columns as well as adding additional columns can be achieved as discussed in Section 15.5, “Revision Log”.
While global revisions are a good way to provide correct auditing of relations, some people have pointed out that this may be a bottleneck in systems, where data is very often modified. One viable solution is to introduce an option to have an entity "locally revisioned", that is revisions would be created for it independently. This wouldn't enable correct versioning of relations, but wouldn't also require the REVINFO table. Another possibility is to introduce a notion of "revisioning groups": groups of entities which share revision numbering. Each such group would have to consist of one or more strongly connected component of the graph induced by relations between entities. Your opinions on the subject are very welcome on the forum! :)
If you'd like to generate the database schema file with the Hibernate Tools Ant task,
you'll probably notice that the generated file doesn't contain definitions of audit
tables. To generate also the audit tables, you simply need to use
org.hibernate.tool.ant.EnversHibernateToolTask
instead of the usual
org.hibernate.tool.ant.HibernateToolTask
. The former class extends
the latter, and only adds generation of the version entities. So you can use the task
just as you used to.
For example:
<target name="schemaexport" depends="build-demo" description="Exports a generated schema to DB and file"> <taskdef name="hibernatetool" classname="org.hibernate.tool.ant.EnversHibernateToolTask" classpathref="build.demo.classpath"/> <hibernatetool destdir="."> <classpath> <fileset refid="lib.hibernate" /> <path location="${build.demo.dir}" /> <path location="${build.main.dir}" /> </classpath> <jpaconfiguration persistenceunit="ConsolePU" /> <hbm2ddl drop="false" create="true" export="false" outputfilename="versioning-ddl.sql" delimiter=";" format="true"/> </hibernatetool> </target>
Will generate the following schema:
create table Address ( id integer generated by default as identity (start with 1), flatNumber integer, houseNumber integer, streetName varchar(255), primary key (id) ); create table Address_AUD ( id integer not null, REV integer not null, flatNumber integer, houseNumber integer, streetName varchar(255), REVTYPE tinyint, primary key (id, REV) ); create table Person ( id integer generated by default as identity (start with 1), name varchar(255), surname varchar(255), address_id integer, primary key (id) ); create table Person_AUD ( id integer not null, REV integer not null, name varchar(255), surname varchar(255), REVTYPE tinyint, address_id integer, primary key (id, REV) ); create table REVINFO ( REV integer generated by default as identity (start with 1), REVTSTMP bigint, primary key (REV) ); alter table Person add constraint FK8E488775E4C3EA63 foreign key (address_id) references Address;
Bags (the corresponding Java type is List), as they can contain non-unique elements. The reason is that persisting, for example a bag of String-s, violates a principle of relational databases: that each table is a set of tuples. In case of bags, however (which require a join table), if there is a duplicate element, the two tuples corresponding to the elements will be the same. Hibernate allows this, however Envers (or more precisely: the database connector) will throw an exception when trying to persist two identical elements, because of a unique constraint violation.
There are at least two ways out if you need bag semantics:
use an indexed collection, with the @IndexColumn
annotation, or
provide a unique id for your elements with the @CollectionId
annotation.
When a collection is mapped using these two annotations, Hibernate doesn't generate a join table. Envers, however, has to do this, so that when you read the revisions in which the related entity has changed, you don't get false results.
To be able to name the additional join table, there is a special annotation:
@AuditJoinTable
, which has similar semantics to JPA's
@JoinTable
.
One special case are relations mapped with @OneToMany
+@JoinColumn
on
the one side, and @ManyToOne
+@JoinColumn(insertable=false, updatable=false
)
on the many side.
Such relations are in fact bidirectional, but the owning side is the collection (see alse
here).
To properly audit such relations with Envers, you can use the @AuditMappedBy
annotation.
It enables you to specify the reverse property (using the mappedBy
element). In case
of indexed collections, the index column must also be mapped in the referenced entity (using
@Column(insertable=false, updatable=false)
, and specified using
positionMappedBy
. This annotation will affect only the way
Envers works. Please note that the annotation is experimental and may change in the future.
Because audit tables tend to grow indefinitely they can quickly become really large. When the audit tables have grown to a certain limit (varying per RDBMS and/or operating system) it makes sense to start using table partitioning. SQL table partitioning offers a lot of advantages including, but certainly not limited to:
Improved query performance by selectively moving rows to various partitions (or even purging old rows)
Faster data loads, index creation, etc.
Generally SQL tables must be partitioned on a column that exists within the table. As a rule it makes sense to use either the end revision or the end revision timestamp column for partioning of audit tables.
End revision information is not available for the default AuditStrategy.
Therefore the following Envers configuration options are required:
org.hibernate.envers.audit_strategy
=
org.hibernate.envers.strategy.ValidityAuditStrategy
org.hibernate.envers.audit_strategy_validity_store_revend_timestamp
=
true
Optionally, you can also override the default values following properties:
org.hibernate.envers.audit_strategy_validity_end_rev_field_name
org.hibernate.envers.audit_strategy_validity_revend_timestamp_field_name
For more information, see ???.
The reason why the end revision information should be used for audit table partioning is based on the assumption that audit tables should be partionioned on an 'increasing level of interestingness', like so:
A couple of partitions with audit data that is not very (or no longer) interesting. This can be stored on slow media, and perhaps even be purged eventually.
Some partitions for audit data that is potentially interesting.
One partition for audit data that is most likely to be interesting. This should be stored on the fastest media, both for reading and writing.
In order to determine a suitable column for the 'increasing level of interestingness', consider a simplified example of a salary registration for an unnamed agency.
Currently, the salary table contains the following rows for a certain person X:
The salary for the current fiscal year (2010) is unknown. The agency requires that all changes in registered salaries for a fiscal year are recorded (i.e. an audit trail). The rationale behind this is that decisions made at a certain date are based on the registered salary at that time. And at any time it must be possible reproduce the reason why a certain decision was made at a certain date.
The following audit information is available, sorted on in order of occurrence:
Table 15.3. Salaries - audit table
Year | Revision type | Revision timestamp | Salary (USD) | End revision timestamp |
---|---|---|---|---|
2006 | ADD | 2007-04-01 | 3300 | null |
2007 | ADD | 2008-04-01 | 35 | 2008-04-02 |
2007 | MOD | 2008-04-02 | 3500 | null |
2008 | ADD | 2009-04-01 | 3700 | 2009-07-01 |
2008 | MOD | 2009-07-01 | 4100 | 2010-02-01 |
2008 | MOD | 2010-02-01 | 4000 | null |
2009 | ADD | 2010-04-01 | 4500 | null |
To partition this data, the 'level of interestingness' must be defined. Consider the following:
For fiscal year 2006 there is only one revision. It has the oldest revision timestamp of all audit rows, but should still be regarded as interesting because it is the latest modification for this fiscal year in the salary table; its end revision timestamp is null.
Also note that it would be very unfortunate if in 2011 there would be an update of the salary for fiscal year 2006 (which is possible in until at least 10 years after the fiscal year) and the audit information would have been moved to a slow disk (based on the age of the revision timestamp). Remember that in this case Envers will have to update the end revision timestamp of the most recent audit row.
There are two revisions in the salary of fiscal year 2007 which both have nearly the same revision timestamp and a different end revision timestamp. On first sight it is evident that the first revision was a mistake and probably uninteresting. The only interesting revision for 2007 is the one with end revision timestamp null.
Based on the above, it is evident that only the end revision timestamp is suitable for audit table partitioning. The revision timestamp is not suitable.
A possible partitioning scheme for the salary table would be as follows:
end revision timestamp year = 2008
This partition contains audit data that is not very (or no longer) interesting.
end revision timestamp year = 2009
This partition contains audit data that is potentially interesting.
end revision timestamp year >= 2010 or null
This partition contains the most interesting audit data.
This partitioning scheme also covers the potential problem of the update of the end revision timestamp, which occurs if a row in the audited table is modified. Even though Envers will update the end revision timestamp of the audit row to the system date at the instant of modification, the audit row will remain in the same partition (the 'extension bucket').
And sometime in 2011, the last partition (or 'extension bucket') is split into two new partitions:
end revision timestamp year = 2010
This partition contains audit data that is potentially interesting (in 2011).
end revision timestamp year >= 2011 or null
This partition contains the most interesting audit data and is the new 'extension bucket'.
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