| hibernate.cache.default_cache_concurrency_strategy |
Setting used to give the name of the default org.hibernate.annotations.CacheConcurrencyStrategy to use
when either @Cacheable @Cache} is used. @Cache(strategy="..") is used to override this default.
|
| hibernate.id.new_generator_mappings |
We recommend all new projects to use hibernate.id.new_generator_mappings=true as the new generators
are more efficient and closer to the JPA 2 specification semantic.
true or false. Setting which indicates whether or not the new IdentifierGenerator implementations are used
for AUTO, TABLE and SEQUENCE. Default to false to keep backward compatibility.
|
| @Entity @Id |
@Entity
public class Flight implements Serializable {
Long id;
@Id
public Long getId() { return id; }
public void setId(Long id) { this.id = id; }
}
|
| @Table |
@Entity
@Table(name="tbl_sky")
public class Sky implements Serializable {
...
}
|
| @UniqueConstraint |
@Table(name="tbl_sky",
uniqueConstraints = {@UniqueConstraint(columnNames={"month", "day"})}
)
public class Sky implements Serializable {
...
}
:: columnNames array refers to the logical column names
|
| @Version |
@Entity
public class Flight implements Serializable {
...
@Version
@Column(name = "OPTLOCK")
public Integer getVersion() {
return this.version;
}
public void setVersion(Integer version) {
this.version = version;
}
}
The version property will be mapped to the OPTLOCK column, and the entity manager will use it to detect
conflicting updates (preventing lost updates you might otherwise see with the last-commit-wins strategy).
The version column may be a numeric (the recommended solution) or a timestamp
|
| @Transient |
public transient int counter; //transient property
@Transient
String getLengthInMeter() { ... } //transient property
:: counter, a transient field, and lengthInMeter, a method annotated as @Transient, and will be ignored by the entity manager
|
| @Basic |
private String firstname; //persistent property
@Basic
int getLength() { ... } // persistent property
@Basic(fetch = FetchType.LAZY)
String getDetailedComment() { ... } // persistent property
name, length, and firstname properties are mapped persistent and eagerly fetched (the default for simple properties).
The detailedComment property value will be lazily fetched from the database once a lazy property of the entity is
accessed for the first time. Usually you don't need to lazy simple properties (not to be confused with lazy association fetching).
|
| @Temporal |
@Temporal(TemporalType.TIME)
java.util.Date getDepartureTime() { ... } // persistent property
|
| @Enumerated |
@Enumerated(EnumType.STRING)
Starred getNote() { ... } //enum persisted as String in database
|
| @Lob |
@Lob
public String getFullText() {
return fullText;
}
@Lob
public byte[] getFullCode() {
return fullCode;
}
@Lob indicates that the property should be persisted in a Blob or a Clob
depending on the property type: java.sql.Clob, Character[], char[] and
java.lang.String will be persisted in a Clob. java.sql.Blob,
Byte[], byte[] and serializable type will be persisted in a Blob.
|
| @Access @Embedded |
@Entity
public class Order {
@Id private Long id;
public Long getId() { return id; }
public void setId(Long id) { this.id = id; }
@Embedded private Address address;
public Address getAddress() { return address; }
public void setAddress() { this.address = address; }
}
@Entity
public class User {
private Long id;
@Id public Long getId() { return id; }
public void setId(Long id) { this.id = id; }
private Address address;
@Embedded public Address getAddress() { return address; }
public void setAddress() { this.address = address; }
}
@Embeddable
@Access(AcessType.PROPERTY)
public class Address {
private String street1;
public String getStreet1() { return street1; }
public void setStreet1() { this.street1 = street1; }
private hashCode; //not persistent
}
|
| column attributes |
annotation at the property level for properties that are:
not annotated at all
annotated with @Basic
annotated with @Version
annotated with @Lob
annotated with @Temporal
|
| @Column |
@Column(updatable = false, name = "flight_name", nullable = false, length=50)
public String getName() { ... }
This annotation can be applied to regular properties as well as @Id or @Version properties.
@Column(
name="columnName";
boolean unique() default false;
boolean nullable() default true;
boolean insertable() default true;
boolean updatable() default true;
String columnDefinition() default "";
String table() default "";
int length() default 255;
int precision() default 0; // decimal precision
int scale() default 0; // decimal scale
)
name (optional): the column name (default to the property name)
unique (optional): set a unique constraint on this column or not (default false)
nullable (optional): set the column as nullable (default true).
insertable (optional): whether or not the column will be part of the insert statement (default true)
updatable (optional): whether or not the column will be part of the update statement (default true)
columnDefinition (optional): override the sql DDL fragment for this particular column (non portable)
table (optional): define the targeted table (default primary table)
length (optional): column length (default 255)
precision (optional): column decimal precision (default 0)
scale (optional): column decimal scale if useful (default 0)
|
| @Embedded and @AttributeOverride |
It is possible to declare an embedded component inside an entity and even override its column mapping.
Component classes have to be annotated at the class level with the @Embeddable annotation.
It is possible to override the column mapping of an embedded object for a particular entity using
the @Embedded and @AttributeOverride annotation in the associated property:
@Entity
public class Person implements Serializable {
// Persistent component using defaults
Address homeAddress;
@Embedded
@AttributeOverrides( {
@AttributeOverride(name="iso2", column = @Column(name="bornIso2") ),
@AttributeOverride(name="name", column = @Column(name="bornCountryName") )
} )
Country bornIn;
...
}
@Embeddable
public class Address implements Serializable {
String city;
Country nationality; //no overriding here
}
@Embeddable
public class Country implements Serializable {
private String iso2;
@Column(name="countryName") private String name;
public String getIso2() { return iso2; }
public void setIso2(String iso2) { this.iso2 = iso2; }
public String getName() { return name; }
public void setName(String name) { this.name = name; }
...
}
An embeddable object inherits the access type of its owning entity (note that you can override that using the
@Access annotation).
The Person entity has two component properties, homeAddress and bornIn. homeAddress property has not been annotated,
but Hibernate will guess that it is a persistent component by looking for the @Embeddable annotation in the Address
class. We also override the mapping of a column name (to bornCountryName) with the @Embedded and @AttributeOverride
annotations for each mapped attribute of Country. As you can see, Country is also a nested component of Address,
again using auto-detection by Hibernate and JPA defaults. Overriding columns of embedded objects of embedded objects
is through dotted expressions.
|
| property defaults |
If a property is not annotated, the following rules apply:
If the property is of a single type, it is mapped as @Basic
Otherwise, if the type of the property is annotated as @Embeddable, it is mapped as @Embedded
Otherwise, if the type of the property is Serializable, it is mapped as @Basic in a column holding the object in its serialized version
Otherwise, if the type of the property is java.sql.Clob or java.sql.Blob, it is mapped as @Lob with the appropriate LobType
|
| @GeneratedValue - identifier property |
JPA defines five types of identifier generation strategies:
AUTO - either identity column, sequence or table depending on the underlying DB
TABLE - table holding the id
IDENTITY - identity column
SEQUENCE - sequence
identity copy - the identity is copied from another entity
@Id @GeneratedValue(strategy=GenerationType.SEQUENCE, generator="SEQ_STORE")
public Integer getId() { ... }
@Id @GeneratedValue(strategy=GenerationType.IDENTITY)
public Long getId() { ... }
|
| @javax.persistence.TableGenerator |
@javax.persistence.TableGenerator(
name="EMP_GEN",
table="GENERATOR_TABLE",
pkColumnName = "key",
valueColumnName = "hi"
pkColumnValue="EMP",
allocationSize=20
)
|
| @javax.persistence.SequenceGenerator |
@javax.persistence.SequenceGenerator(
name="SEQ_GEN",
sequenceName="my_sequence",
allocationSize=20
)
|
| @JoinColumn @MapsId |
@Entity
class MedicalHistory implements Serializable {
@Id @OneToOne
@JoinColumn(name = "person_id")
Person patient;
}
@Entity
public class Person implements Serializable {
@Id @GeneratedValue Integer id;
}
Or alternatively
@Entity
class MedicalHistory implements Serializable {
@Id Integer id;
@MapsId @OneToOne
@JoinColumn(name = "patient_id")
Person patient;
}
@Entity
class Person {
@Id @GeneratedValue Integer id;
}
|
| @Embeddable |
While not supported in JPA, Hibernate lets you place your association directly in the embedded id
component (instead of having to use the @MapsId annotation).
@Entity
class Customer {
@EmbeddedId CustomerId id;
boolean preferredCustomer;
}
@Embeddable
class CustomerId implements Serializable {
@OneToOne
@JoinColumns({
@JoinColumn(name="userfirstname_fk", referencedColumnName="firstName"),
@JoinColumn(name="userlastname_fk", referencedColumnName="lastName")
})
User user;
String customerNumber;
}
@Entity
class User {
@EmbeddedId UserId id;
Integer age;
}
@Embeddable
class UserId implements Serializable {
String firstName;
String lastName;
}
|
| @Inheritance |
Single table per class hierarchy
All properties of all super- and subclasses are mapped into the same table, instances are distinguished by a special discriminator column:
@Entity
@Inheritance(strategy=InheritanceType.SINGLE_TABLE)
@DiscriminatorColumn(
name="planetype",
discriminatorType=DiscriminatorType.STRING
)
@DiscriminatorValue("Plane")
public class Plane { ... }
@Entity
@DiscriminatorValue("A320")
public class A320 extends Plane { ... }
Plane is the superclass, it defines the inheritance strategy InheritanceType.SINGLE_TABLE. It also defines the discriminator column through the @DiscriminatorColumn annotation, a discriminator column can also define the discriminator type. Finally, the @DiscriminatorValue annotation defines the value used to differentiate a class in the hierarchy. All of these attributes have sensible default values. The default name of the discriminator column is DTYPE. The default discriminator value is the entity name (as defined in @Entity.name) for DiscriminatorType.STRING. A320 is a subclass; you only have to define discriminator value if you don't want to use the default value. The strategy and the discriminator type are implicit.
@Inheritance and @DiscriminatorColumn should only be defined at the top of the entity hierarchy.
|
| @PrimaryKeyJoinColumn @PrimaryKeyJoinColumns |
Joined subclasses
The @PrimaryKeyJoinColumn and @PrimaryKeyJoinColumns annotations define the primary key(s) of the joined subclass table:
@Entity
@Inheritance(strategy=InheritanceType.JOINED)
public class Boat implements Serializable { ... }
@Entity
public class Ferry extends Boat { ... }
@Entity
@PrimaryKeyJoinColumn(name="BOAT_ID")
public class AmericaCupClass extends Boat { ... }
All of the above entities use the JOINED strategy, the Ferry table is joined with the Boat table using the same primary key names. The AmericaCupClass table is joined with Boat using the join condition Boat.id = AmericaCupClass.BOAT_ID.
|
| @MappedSuperclass |
Inherit properties from superclasses
This is sometimes useful to share common properties through a technical or a business superclass without including it as a regular mapped entity (ie no specific table for this entity). For that purpose you can map them as @MappedSuperclass.
@MappedSuperclass
public class BaseEntity {
@Basic
@Temporal(TemporalType.TIMESTAMP)
public Date getLastUpdate() { ... }
public String getLastUpdater() { ... }
...
}
@Entity class Order extends BaseEntity {
@Id public Integer getId() { ... }
...
}
In database, this hierarchy will be represented as an Order table having the id, lastUpdate and lastUpdater columns. The embedded superclass property mappings are copied into their entity subclasses. Remember that the embeddable superclass is not the root of the hierarchy though.
|
| @OneToOne shared primary keys |
@Entity
public class Body {
@Id
public Long getId() { return id; }
@OneToOne(cascade = CascadeType.ALL)
@PrimaryKeyJoinColumn
public Heart getHeart() {
return heart;
}
...
}
@Entity
public class Heart {
@Id
public Long getId() { ...}
}
The @PrimaryKeyJoinColumn annotation does say that the primary key of the entity is used as the foreign key value to the associated entity.
|
| @OneToOne foreign key |
@Entity
public class Customer implements Serializable {
@OneToOne(cascade = CascadeType.ALL)
@JoinColumn(name="passport_fk")
public Passport getPassport() {
...
}
@Entity
public class Passport implements Serializable {
@OneToOne(mappedBy = "passport")
public Customer getOwner() {
...
}
A Customer is linked to a Passport, with a foreign key column named passport_fk in the Customer table. The join column is declared with the @JoinColumn annotation which looks like the @Column annotation. It has one more parameters named referencedColumnName. This parameter declares the column in the targeted entity that will be used to the join. Note that when using referencedColumnName to a non primary key column, the associated class has to be Serializable. Also note that the referencedColumnName to a non primary key column has to be mapped to a property having a single column (other cases might not work).
The association may be bidirectional. In a bidirectional relationship, one of the sides (and only one) has to be the owner: the owner is responsible for the association column(s) update. To declare a side as not responsible for the relationship, the attribute mappedBy is used. mappedBy refers to the property name of the association on the owner side. In our case, this is passport. As you can see, you don't have to (must not) declare the join column since it has already been declared on the owners side.
If no @JoinColumn is declared on the owner side, the defaults apply. A join column(s) will be created in the owner table and its name will be the concatenation of the name of the relationship in the owner side, _ (underscore), and the name of the primary key column(s) in the owned side. In this example passport_id because the property name is passport and the column id of Passport is id
|
| @ManyToOne |
Many-to-one associations are declared at the property level with the annotation @ManyToOne:
@Entity()
public class Flight implements Serializable {
@ManyToOne( cascade = {CascadeType.PERSIST, CascadeType.MERGE} )
@JoinColumn(name="COMP_ID")
public Company getCompany() {
return company;
}
...
}
The @JoinColumn attribute is optional, the default value(s) is like in one to one, the concatenation of the name of the relationship in the owner side, _ (underscore), and the name of the primary key column in the owned side. In this example company_id because the property name is company and the column id of Company is id.
@ManyToOne has a parameter named targetEntity which describes the target entity name. You usually don't need this parameter since the default value (the type of the property that stores the association) is good in almost all cases. However this is useful when you want to use interfaces as the return type instead of the regular entity.
@Entity
public class Flight implements Serializable {
@ManyToOne( cascade = {CascadeType.PERSIST, CascadeType.MERGE}, targetEntity=CompanyImpl.class )
@JoinColumn(name="COMP_ID")
public Company getCompany() {
return company;
}
...
}
public interface Company {
...
}
|
| Bidirectional @ManyToOne @OneToMany |
Since many to one are (almost) always the owner side of a bidirectional relationship in the JPA spec, the one to many association is annotated by @OneToMany(mappedBy=...)
@Entity
public class Troop {
@OneToMany
@JoinColumn(name="troop_fk") //we need to duplicate the physical information
public Set getSoldiers() {
...
}
@Entity
public class Soldier {
@ManyToOne
@JoinColumn(name="troop_fk", insertable=false, updatable=false)
public Troop getTroop() {
...
}
Troop has a bidirectional one to many relationship with Soldier through the troop property. You don't have to (must not) define any physical mapping in the mappedBy side.
To map a bidirectional one to many, with the one-to-many side as the owning side, you have to remove the mappedBy element and set the many to one @JoinColumn as insertable and updatable to false. This solution is not optimized and will produce some additional UPDATE statements.
|
| @OneToMany Unidirectional with @JoinTable |
A unidirectional one to many with join table is much preferred. This association is described through an @JoinTable.
@Entity
public class Trainer {
@OneToMany
@JoinTable(
name="TrainedMonkeys",
joinColumns = @JoinColumn( name="trainer_id"),
inverseJoinColumns = @JoinColumn( name="monkey_id")
)
public Set getTrainedMonkeys() {
...
}
@Entity
public class Monkey {
... //no bidir
}
Trainer describes a unidirectional relationship with Monkey using the join table TrainedMonkeys, with a foreign key trainer_id to Trainer (joinColumns) and a foreign key monkey_id to Monkey (inversejoinColumns).
=====================================================================================================
Without describing any physical mapping, a unidirectional one to many with join table is used. The table name is the concatenation of the owner table name, _, and the other side table name. The foreign key name(s) referencing the owner table is the concatenation of the owner table, _, and the owner primary key column(s) name. The foreign key name(s) referencing the other side is the concatenation of the owner property name, _, and the other side primary key column(s) name. A unique constraint is added to the foreign key referencing the other side table to reflect the one to many.
@Entity
public class Trainer {
@OneToMany
public Set getTrainedTigers() {
...
}
@Entity
public class Tiger {
... //no bidir
}
Trainer describes a unidirectional relationship with Tiger using the join table Trainer_Tiger, with a foreign key trainer_id to Trainer (table name, _, trainer id) and a foreign key trainedTigers_id to Monkey (property name, _, Tiger primary column)
|
| @ManyToMany @JoinTable |
A many-to-many association is defined logically using the @ManyToMany annotation. You also have to describe the association table and the join conditions using the @JoinTable annotation. If the association is bidirectional, one side has to be the owner and one side has to be the inverse end (ie. it will be ignored when updating the relationship values in the association table):
@Entity
public class Employer implements Serializable {
@ManyToMany(
targetEntity=org.hibernate.test.metadata.manytomany.Employee.class,
cascade={CascadeType.PERSIST, CascadeType.MERGE}
)
@JoinTable(
name="EMPLOYER_EMPLOYEE",
joinColumns=@JoinColumn(name="EMPER_ID"),
inverseJoinColumns=@JoinColumn(name="EMPEE_ID")
)
public Collection getEmployees() {
return employees;
}
...
}
@Entity
public class Employee implements Serializable {
@ManyToMany(
cascade = {CascadeType.PERSIST, CascadeType.MERGE},
mappedBy = "employees",
targetEntity = Employer.class
)
public Collection getEmployers() {
return employers;
}
}
We've already shown the many declarations and the detailed attributes for associations. We'll go deeper in the @JoinTable description, it defines a name, an array of join columns (an array in annotation is defined using { A, B, C }), and an array of inverse join columns. The latter ones are the columns of the association table which refer to the Employee primary key (the "other side").
As seen previously, the other side don't have to (must not) describe the physical mapping: a simple mappedBy argument containing the owner side property name bind the two.
<IP_ADDRESS>.2.2. Default values
As any other annotations, most values are guessed in a many to many relationship. Without describing any physical mapping in a unidirectional many to many the following rules applied. The table name is the concatenation of the owner table name, _ and the other side table name. The foreign key name(s) referencing the owner table is the concatenation of the owner table name, _ and the owner primary key column(s). The foreign key name(s) referencing the other side is the concatenation of the owner property name, _, and the other side primary key column(s). These are the same rules used for a unidirectional one to many relationship.
@Entity
public class Store {
@ManyToMany(cascade = CascadeType.PERSIST)
public Set getImplantedIn() {
...
}
}
@Entity
public class City {
... //no bidirectional relationship
}
A Store_City is used as the join table. The Store_id column is a foreign key to the Store table. The implantedIn_id column is a foreign key to the City table.
Without describing any physical mapping in a bidirectional many to many the following rules applied. The table name is the concatenation of the owner table name, _ and the other side table name. The foreign key name(s) referencing the owner table is the concatenation of the other side property name, _, and the owner primary key column(s). The foreign key name(s) referencing the other side is the concatenation of the owner property name, _, and the other side primary key column(s). These are the same rules used for a unidirectional one to many relationship.
@Entity
public class Store {
@ManyToMany(cascade = {CascadeType.PERSIST, CascadeType.MERGE})
public Set getCustomers() {
...
}
}
@Entity
public class Customer {
@ManyToMany(mappedBy="customers")
public Set getStores() {
...
}
}
A Store_Customer is used as the join table. The stores_id column is a foreign key to the Store table. The customers_id column is a foreign key to the Customer table.
|
| @ElementCollection |
In some simple situation, do don't need to associate two entities but simply create a collection of basic types or embeddable objects. Use the @ElementCollection in this case.
@Entity
public class User {
[...]
public String getLastname() { ...}
@ElementCollection
@CollectionTable(name="Nicknames", joinColumns=@JoinColumn(name="user_id"))
@Column(name="nickname")
public Set getNicknames() { ... }
}
The collection table holding the collection data is set using the @CollectionTable annotation. If omitted the collection table name default to the concatenation of the name of the containing entity and the name of the collection attribute, separated by an underscore: in our example, it would be User_nicknames.
The column holding the basic type is set using the @Column annotation. If omitted, the column name defaults to the property name: in our example, it would be nicknames.
But you are not limited to basic types, the collection type can be any embeddable object. To override the columns of the embeddable object in the collection table, use the @AttributeOverride annotation.
@Entity
public class User {
[...]
public String getLastname() { ...}
@ElementCollection
@CollectionTable(name="Addresses", joinColumns=@JoinColumn(name="user_id"))
@AttributeOverrides({
@AttributeOverride(name="street1", column=@Column(name="fld_street"))
})
public Set getAddresses() { ... }
}
@Embeddable
public class Address {
public String getStreet1() {...}
[...]
}
Such an embeddable object cannot contains a collection itself.
|
| @OrderBy |
Lists can be mapped in two different ways:
as ordered lists, the order is not materialized in the database
as indexed lists, the order is materialized in the database
To order lists in memory, add @javax.persistence.OrderBy to your property. This annotation takes into parameter a list of comma separated properties (of the target entity) and order the collection accordingly (eg firstname asc, age desc), if the string is empty, the collection will be ordered by the primary key of the target entity.
@Entity
public class Customer {
@Id @GeneratedValue public Integer getId() { return id; }
public void setId(Integer id) { this.id = id; }
private Integer id;
@OneToMany(mappedBy="customer")
@OrderBy("number")
public List getOrders() { return orders; }
public void setOrders(List orders) { this.orders = orders; }
private List orders;
}
@Entity
public class Order {
@Id @GeneratedValue public Integer getId() { return id; }
public void setId(Integer id) { this.id = id; }
private Integer id;
public String getNumber() { return number; }
public void setNumber(String number) { this.number = number; }
private String number;
@ManyToOne
public Customer getCustomer() { return customer; }
public void setCustomer(Customer customer) { this.customer = customer; }
private Customer number;
}
|
| @OrderColumn - persist |
To store the index value in a dedicated column, use the @javax.persistence.OrderColumn annotation on your property. This annotations describes the column name and attributes of the column keeping the index value. This column is hosted on the table containing the association foreign key. If the column name is not specified, the default is the name of the referencing property, followed by underscore, followed by ORDER (in the following example, it would be orders_ORDER).
@Entity
public class Customer {
@Id @GeneratedValue public Integer getId() { return id; }
public void setId(Integer id) { this.id = id; }
private Integer id;
@OneToMany(mappedBy="customer")
@OrderColumn(name"orders_index")
public List getOrders() { return orders; }
public void setOrders(List orders) { this.orders = orders; }
private List orders;
}
@Entity
public class Order {
@Id @GeneratedValue public Integer getId() { return id; }
public void setId(Integer id) { this.id = id; }
private Integer id;
public String getNumber() { return number; }
public void setNumber(String number) { this.number = number; }
private String number;
@ManyToOne
public Customer getCustomer() { return customer; }
public void setCustomer(Customer customer) { this.customer = customer; }
private Customer number;
}
|
| @MapKey |
To use one of the target entity property as a key of the map, use @MapKey(name="myProperty") (myProperty is a property name in the target entity). When using @MapKey (without property name), the target entity primary key is used. The map key uses the same column as the property pointed out: there is no additional column defined to hold the map key, and it does make sense since the map key actually represent a target property. Be aware that once loaded, the key is no longer kept in sync with the property, in other words, if you change the property value, the key will not change automatically in your Java model.
@Entity
public class Customer {
@Id @GeneratedValue public Integer getId() { return id; }
public void setId(Integer id) { this.id = id; }
private Integer id;
@OneToMany(mappedBy="customer")
@MapKey(name"number")
public Map getOrders() { return orders; }
public void setOrders(Map order) { this.orders = orders; }
private Map orders;
}
@Entity
public class Order {
@Id @GeneratedValue public Integer getId() { return id; }
public void setId(Integer id) { this.id = id; }
private Integer id;
public String getNumber() { return number; }
public void setNumber(String number) { this.number = number; }
private String number;
@ManyToOne
public Customer getCustomer() { return customer; }
public void setCustomer(Customer customer) { this.customer = customer; }
private Customer number;
}
Otherwise, the map key is mapped to a dedicated column or columns. To customize things, use one of the following annotations:
@MapKeyColumn if the map key is a basic type, if you don't specify the column name, the name of the property followed by underscore followed by KEY is used (for example orders_KEY).
@MapKeyEnumerated / @MapKeyTemporal if the map key type is respectively an enum or a Date.
@MapKeyJoinColumn/@MapKeyJoinColumns if the map key type is another entity.
@AttributeOverride/@AttributeOverrides when the map key is a embeddable object. Use key. as a prefix for your embeddable object property names.
|
| Collections semantics |
Bag semantic java.util.List, java.util.Collection @ElementCollection or @OneToMany or @ManyToMany
Bag semantic with primary key (without the limitations of Bag semantic) java.util.List, java.util.Collection (@ElementCollection or @OneToMany or @ManyToMany) and @CollectionId
List semantic java.util.List (@ElementCollection or @OneToMany or @ManyToMany) and (@OrderColumn or @org.hibernate.annotations.IndexColumn)
Set semantic java.util.Set @ElementCollection or @OneToMany or @ManyToMany
Map semantic java.util.Map (@ElementCollection or @OneToMany or @ManyToMany) and ((nothing or @MapKeyJoinColumn/@MapKeyColumn for true map support) OR @javax.persistence.MapKey)
|
| CascadeType |
You probably have noticed the cascade attribute taking an array of CascadeType as a value. The cascade concept in JPA is very is similar to the transitive persistence and cascading of operations in Hibernate, but with slightly different semantics and cascading types:
CascadeType.PERSIST: cascades the persist (create) operation to associated entities persist() is called or if the entity is managed
CascadeType.MERGE: cascades the merge operation to associated entities if merge() is called or if the entity is managed
CascadeType.REMOVE: cascades the remove operation to associated entities if delete() is called
CascadeType.REFRESH: cascades the refresh operation to associated entities if refresh() is called
CascadeType.DETACH: cascades the detach operation to associated entities if detach() is called
CascadeType.ALL: all of the above
Note
CascadeType.ALL also covers Hibernate specific operations like save-update, lock etc... Check Section 2.4.7, “Cascade” for more information
|
| FetchType |
The fetch parameter can be set to FetchType.LAZY or FetchType.EAGER. EAGER will try to use an outer join select to retrieve the associated object, while LAZY will only trigger a select when the associated object is accessed for the first time. @OneToMany and @ManyToMany associations are defaulted to LAZY and @OneToOne and @ManyToOne are defaulted to EAGER
|
| @SecondaryTables |
You can map a single entity to several tables using the @SecondaryTable or @SecondaryTables class level annotations. To express that a column is in a particular table, use the table parameter of @Column or @JoinColumn.
@Entity
@Table(name="MainCat")
@SecondaryTables({
@SecondaryTable(name="Cat1", pkJoinColumns={
@PrimaryKeyJoinColumn(name="cat_id", referencedColumnName="id")
),
@SecondaryTable(name="Cat2", uniqueConstraints={@UniqueConstraint(columnNames={"storyPart2"})})
})
public class Cat implements Serializable {
private Integer id;
private String name;
private String storyPart1;
private String storyPart2;
@Id @GeneratedValue
public Integer getId() {
return id;
}
public String getName() {
return name;
}
@Column(table="Cat1")
public String getStoryPart1() {
return storyPart1;
}
@Column(table="Cat2")
public String getStoryPart2() {
return storyPart2;
}
}
In this example, name will be in MainCat. storyPart1 will be in Cat1 and storyPart2 will be in Cat2. Cat1 will be joined to MainCat using the cat_id as a foreign key, and Cat2 using id (ie the same column name, the MainCat id column has). Plus a unique constraint on storyPart2 has been set.
|
| Caching entities |
Hibernate offers naturally a first level cache for entities called a persistence context via the notion of Session. This cache is contextual to the use case at hand. Some entities however are shared by many different use cases and are barely changed. You can cache these in what is called the second level cache.
By default, entities are not part of the second level cache. While we do not recommend that, you can override this by setting the shared-cache-mode element in your persistence.xml file or by using the javax.persistence.sharedCache.mode property. The following values are possible:
ENABLE_SELECTIVE (Default and recommended value): entities are not cached unless explicitly marked as cacheable.
DISABLE_SELECTIVE: entities are cached unless explicitly marked as not cacheable.
ALL: all entities are always cached even if marked as non cacheable.
NONE: no entity are cached even if marked as cacheable. This option can make sense to disable second-level cache altogether.
The cache concurrency strategy used by default can be set with the hibernate.cache.default_cache_concurrency_strategy property:
read-only
read-write
nonstrict-read-write
transactional
Note
It is recommended to define the cache concurrency strategy per entity rather than using a global one. Use the @org.hibernate.annotations.Cache annotation for that.
|
| @Cache @Cacheable |
@Entity @Cacheable
@Cache(usage = CacheConcurrencyStrategy.NONSTRICT_READ_WRITE)
public class Forest { ... }
Hibernate also let's you cache the content of a collection or the identifiers if the collection contains other entities. Use the @Cache annotation on the collection property.
@OneToMany(cascade=CascadeType.ALL, fetch=FetchType.EAGER)
@JoinColumn(name="CUST_ID")
@Cache(usage = CacheConcurrencyStrategy.NONSTRICT_READ_WRITE)
public SortedSet getTickets() {
return tickets;
}
@org.hibernate.annotations.Cache defines the caching strategy and region of a given second level cache.
@Cache(
CacheConcu(1)rrencyStrategy usage();
String reg(2)ion() default "";
String inc(3)lude() default "all";
)
1
usage: the given cache concurrency strategy (NONE, READ_ONLY, NONSTRICT_READ_WRITE, READ_WRITE, TRANSACTIONAL)
2
region (optional): the cache region (default to the fqcn of the class or the fq role name of the collection)
3
include (optional): all to include all properties, non-lazy to only include non lazy properties (default all).
|
| @NamedQuery |
@Entity
@NamedQuery(name="night.moreRecentThan", query="select n from Night n where n.date >= :date")
public class Night {
...
}
public class MyDao {
doStuff() {
Query q = s.getNamedQuery("night.moreRecentThan");
q.setDate( "date", aMonthAgo );
List results = q.list();
...
}
...
}
You can also provide some hints to a query through an array of QueryHint through a hints attribute.
The available Hibernate hints are
Table 2.2. Query hints
hint description
org.hibernate.cacheable Whether the query should interact with the second level cache (defualt to false)
org.hibernate.cacheRegion Cache region name (default used otherwise)
org.hibernate.timeout Query timeout
org.hibernate.fetchSize resultset fetch size
org.hibernate.flushMode Flush mode used for this query
org.hibernate.cacheMode Cache mode used for this query
org.hibernate.readOnly Entities loaded by this query should be in read only mode or not (default to false)
org.hibernate.comment Query comment added to the generated SQL
You can also define the lock mode by which the returned entities should be locked using the lockMode property. This is equivalent to the optional lock mode of the entitymanager lookup operations.
|
| @NamedNativeQuery |
As we will see, a resultSetMapping parameter is defined in @NamedNativeQuery, it represents the name of a defined @SqlResultSetMapping. The resultset mapping declares the entities retrieved by this native query. Each field of the entity is bound to an SQL alias (or column name). All fields of the entity including the ones of subclasses and the foreign key columns of related entities have to be present in the SQL query. Field definitions are optional provided that they map to the same column name as the one declared on the class property.
@NamedNativeQuery(name="night&area", query="select night.id nid, night.night_duration, "
+ " night.night_date, area.id aid, night.area_id, area.name "
+ "from Night night, Area area where night.area_id = area.id",
resultSetMapping="joinMapping")
@SqlResultSetMapping(name="joinMapping", entities={
@EntityResult(entityClass=Night.class, fields = {
@FieldResult(name="id", column="nid"),
@FieldResult(name="duration", column="night_duration"),
@FieldResult(name="date", column="night_date"),
@FieldResult(name="area", column="area_id"),
discriminatorColumn="disc"
}),
@EntityResult(entityClass=org.hibernate.test.annotations.query.Area.class, fields = {
@FieldResult(name="id", column="aid"),
@FieldResult(name="name", column="name")
})
}
)
In the above example, the night&area named query use the joinMapping result set mapping. This mapping returns 2 entities, Night and Area, each property is declared and associated to a column name, actually the column name retrieved by the query. Let's now see an implicit declaration of the property / column.
@Entity
@SqlResultSetMapping(name="implicit",
entities=@EntityResult(entityClass=SpaceShip.class))
@NamedNativeQuery(name="implicitSample",
query="select * from SpaceShip",
resultSetMapping="implicit")
public class SpaceShip {
private String name;
private String model;
private double speed;
@Id
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
@Column(name="model_txt")
public String getModel() {
return model;
}
public void setModel(String model) {
this.model = model;
}
public double getSpeed() {
return speed;
}
public void setSpeed(double speed) {
this.speed = speed;
}
}
In this example, we only describe the entity member of the result set mapping. The property / column mappings is done using the entity mapping values. In this case the model property is bound to the model_txt column. If the association to a related entity involve a composite primary key, a @FieldResult element should be used for each foreign key column. The @FieldResult name is composed of the property name for the relationship, followed by a dot ("."), followed by the name or the field or property of the primary key.
@Entity
@SqlResultSetMapping(name="compositekey",
entities=@EntityResult(entityClass=SpaceShip.class,
fields = {
@FieldResult(name="name", column = "name"),
@FieldResult(name="model", column = "model"),
@FieldResult(name="speed", column = "speed"),
@FieldResult(name="captain.firstname", column = "firstn"),
@FieldResult(name="captain.lastname", column = "lastn"),
@FieldResult(name="dimensions.length", column = "length"),
@FieldResult(name="dimensions.width", column = "width")
}),
columns = { @ColumnResult(name = "surface"),
@ColumnResult(name = "volume") } )
@NamedNativeQuery(name="compositekey",
query="select name, model, speed, lname as lastn, fname as firstn, length, width, length * width as surface from SpaceShip",
resultSetMapping="compositekey")
} )
public class SpaceShip {
private String name;
private String model;
private double speed;
private Captain captain;
private Dimensions dimensions;
@Id
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
@ManyToOne(fetch= FetchType.LAZY)
@JoinColumns( {
@JoinColumn(name="fname", referencedColumnName = "firstname"),
@JoinColumn(name="lname", referencedColumnName = "lastname")
} )
public Captain getCaptain() {
return captain;
}
public void setCaptain(Captain captain) {
this.captain = captain;
}
public String getModel() {
return model;
}
public void setModel(String model) {
this.model = model;
}
public double getSpeed() {
return speed;
}
public void setSpeed(double speed) {
this.speed = speed;
}
public Dimensions getDimensions() {
return dimensions;
}
public void setDimensions(Dimensions dimensions) {
this.dimensions = dimensions;
}
}
@Entity
@IdClass(Identity.class)
public class Captain implements Serializable {
private String firstname;
private String lastname;
@Id
public String getFirstname() {
return firstname;
}
public void setFirstname(String firstname) {
this.firstname = firstname;
}
@Id
public String getLastname() {
return lastname;
}
public void setLastname(String lastname) {
this.lastname = lastname;
}
}
If you retrieve a single entity and if you use the default mapping, you can use the resultClass attribute instead of resultSetMapping:
@NamedNativeQuery(name="implicitSample", query="select * from SpaceShip",
resultClass=SpaceShip.class)
public class SpaceShip {
In some of your native queries, you'll have to return scalar values, for example when building report queries. You can map them in the @SqlResultsetMapping through @ColumnResult. You actually can even mix, entities and scalar returns in the same native query (this is probably not that common though).
@SqlResultSetMapping(name="scalar", columns=@ColumnResult(name="dimension"))
@NamedNativeQuery(name="scalar", query="select length*width as dimension from SpaceShip", resultSetMapping="scalar")
An other query hint specific to native queries has been introduced: org.hibernate.callable which can be true or false depending on whether the query is a stored procedure or not.
|
| @Index |
You can define an index on a particular column using the @Index annotation on a one column property, the columnNames attribute will then be ignored
@Column(secondaryTable="Cat1")
@Index(name="story1index")
public String getStoryPart1() {
return storyPart1;
}
|
| @Parent |
When inside an embeddable object, you can define one of the properties as a pointer back to the owner element.
@Entity
public class Person {
@Embeddable public Address address;
...
}
@Embeddable
public class Address {
@Parent public Person owner;
...
}
person == person.address.owner
|
| @Generated |
Some properties are generated at insert or update time by your database. Hibernate can deal with such properties and triggers a subsequent select to read these properties.
@Entity
public class Antenna {
@Id public Integer id;
@Generated(GenerationTime.ALWAYS)
@Column(insertable = false, updatable = false)
public String longitude;
@Generated(GenerationTime.INSERT) @Column(insertable = false)
public String latitude;
}
Annotate your property as @Generated You have to make sure your insertability or updatability does not conflict with the generation strategy you have chosen. When GenerationTime.INSERT is chosen, the property must not contains insertable columns, when GenerationTime.ALWAYS is chosen, the property must not contains insertable nor updatable columns.
@Version properties cannot be @Generated(INSERT) by design, it has to be either NEVER or ALWAYS.
|
| @Target |
Sometimes, the type guessed by reflection is not the one you want Hibernate to use. This is especially true on components when an interface is used. You can use @Target to by pass the reflection guessing mechanism (very much like the targetEntity attribute available on associations.
@Embedded
@Target(OwnerImpl.class)
public Owner getOwner() {
return owner;
}
|
| @OptimisticLock |
It is sometimes useful to avoid increasing the version number even if a given property is dirty (particularly collections). You can do that by annotating the property (or collection) with @OptimisticLock(excluded=true).
More formally, specifies that updates to this property do not require acquisition of the optimistic lock.
|
| Inheritance |
SINGLE_TABLE is a very powerful strategy but sometimes, and especially for legacy systems, you cannot add an additional discriminator column. For that purpose Hibernate has introduced the notion of discriminator formula: @DiscriminatorFormula is a replacement of @DiscriminatorColumn and use a SQL fragment as a formula for discriminator resolution (no need to have a dedicated column).
@Entity
@DiscriminatorFormula("case when forest_type is null then 0 else forest_type end")
public class Forest { ... }
By default, when querying the top entities, Hibernate does not put a restriction clause on the discriminator column. This can be inconvenient if this column contains values not mapped in your hierarchy (through @DiscriminatorValue). To work around that you can use @ForceDiscriminator (at the class level, next to @DiscriminatorColumn). Hibernate will then list the available values when loading the entities.
You can define the foreign key name generated by Hibernate for subclass tables in the JOINED inheritance strategy.
@Entity
@Inheritance(strategy = InheritanceType.JOINED)
public abstract class File { ... }
@Entity
@ForeignKey(name = "FK_DOCU_FILE")
public class Document extends File {
The foreign key from the Document table to the File table will be named FK_DOCU_FILE.
|
| @NotFound |
@Entity
public class Child {
...
@ManyToOne
@NotFound(action=NotFoundAction.IGNORE)
public Parent getParent() { ... }
...
}
|
| @OnDelete |
Sometimes you want to delegate to your database the deletion of cascade when a given entity is deleted.
@Entity
public class Child {
...
@ManyToOne
@OnDelete(action=OnDeleteAction.CASCADE)
public Parent getParent() { ... }
...
}
In this case Hibernate generates a cascade delete constraint at the database level.
|
| @ForeignKey |
Foreign key constraints, while generated by Hibernate, have a fairly unreadable name. You can override the constraint name by use @ForeignKey.
@Entity
public class Child {
...
@ManyToOne
@ForeignKey(name="FK_PARENT")
public Parent getParent() { ... }
...
}
alter table Child add constraint FK_PARENT foreign key (parent_id) references Parent
|
| Lazy and fetch options equivalent |
Lazy and fetch options equivalent
Annotations Lazy Fetch
@[One|Many]ToOne](fetch=FetchType.LAZY) @LazyToOne(PROXY) @Fetch(SELECT)
@[One|Many]ToOne](fetch=FetchType.EAGER) @LazyToOne(FALSE) @Fetch(JOIN)
@ManyTo[One|Many](fetch=FetchType.LAZY) @LazyCollection(TRUE) @Fetch(SELECT)
@ManyTo[One|Many](fetch=FetchType.EAGER) @LazyCollection(FALSE) @Fetch(JOIN)
|
| Collection related annotations |
It is possible to set
the batch size for collections using @BatchSize
the where clause, using @Where (applied on the target entity) or @WhereJoinTable (applied on the association table)
the check clause, using @Check
the SQL order by clause, using @OrderBy
the delete cascade strategy through @OnDelete(action=OnDeleteAction.CASCADE)
the collection immutability using @Immutable: if set specifies that the elements of the collection never change (a minor performance optimization in some cases)
a custom collection persister (ie the persistence strategy used) using @Persister: the class must implement org.hibernate.persister.collectionCollectionPersister
You can also declare a sort comparator. Use the @Sort annotation. Expressing the comparator type you want between unsorted, natural or custom comparator. If you want to use your own comparator implementation, you'll also have to express the implementation class using the comparator attribute. Note that you need to use either a SortedSet or a SortedMap interface.
@OneToMany(cascade=CascadeType.ALL, fetch=FetchType.EAGER)
@JoinColumn(name="CUST_ID")
@Sort(type = SortType.COMPARATOR, comparator = TicketComparator.class)
@Where(clause="1=1")
@OnDelete(action=OnDeleteAction.CASCADE)
public SortedSet getTickets() {
return tickets;
}
|
| @Filters |
Hibernate has the ability to apply arbitrary filters on top of your data. Those filters are applied at runtime on a given session. First, you need to define them.
@org.hibernate.annotations.FilterDef or @FilterDefs define filter definition(s) used by filter(s) using the same name. A filter definition has a name() and an array of parameters(). A parameter will allow you to adjust the behavior of the filter at runtime. Each parameter is defined by a @ParamDef which has a name and a type. You can also define a defaultCondition() parameter for a given @FilterDef to set the default condition to use when none are defined in each individual @Filter. A @FilterDef(s) can be defined at the class or package level.
We now need to define the SQL filter clause applied to either the entity load or the collection load. @Filter is used and placed either on the entity or the collection element
@Entity
@FilterDef(name="minLength", parameters=@ParamDef( name="minLength", type="integer" ) )
@Filters( {
@Filter(name="betweenLength", condition=":minLength <= length and :maxLength >= length"),
@Filter(name="minLength", condition=":minLength <= length")
} )
public class Forest { ... }
When the collection use an association table as a relational representation, you might want to apply the filter condition to the association table itself or to the target entity table. To apply the constraint on the target entity, use the regular @Filter annotation. However, if you wan to target the association table, use the @FilterJoinTable annotation.
@OneToMany
@JoinTable
//filter on the target entity table
@Filter(name="betweenLength", condition=":minLength <= length and :maxLength >= length")
//filter on the association table
@FilterJoinTable(name="security", condition=":userlevel >= requredLevel")
public Set getForests() { ... }
|
| Custom SQL for CRUD operations |
Hibernate gives you the ability to override every single SQL statement generated. We have seen native SQL query usage already, but you can also override the SQL statement used to load or change the state of entities.
@Entity
@Table(name="CHAOS")
@SQLInsert( sql="INSERT INTO CHAOS(size, name, nickname, id) VALUES(?,upper(?),?,?)")
@SQLUpdate( sql="UPDATE CHAOS SET size = ?, name = upper(?), nickname = ? WHERE id = ?")
@SQLDelete( sql="DELETE CHAOS WHERE id = ?")
@SQLDeleteAll( sql="DELETE CHAOS")
@Loader(namedQuery = "chaos")
@NamedNativeQuery(name="chaos", query="select id, size, name, lower( nickname ) as nickname from CHAOS where id= ?", resultClass = Chaos.class)
public class Chaos {
@Id
private Long id;
private Long size;
private String name;
private String nickname;
@SQLInsert, @SQLUpdate, @SQLDelete, @SQLDeleteAll respectively override the INSERT statement, UPDATE statement, DELETE statement, DELETE statement to remove all entities.
If you expect to call a store procedure, be sure to set the callable attribute to true (@SQLInsert(callable=true, ...)).
To check that the execution happens correctly, Hibernate allows you to define one of those three strategies:
NONE: no check is performed: the store procedure is expected to fail upon issues
COUNT: use of rowcount to check that the update is successful
PARAM: like COUNT but using an output parameter rather that the standard mechanism
To define the result check style, use the check parameter (@SQLUpdate(check=ResultCheckStyle.COUNT, ...)).
You can also override the SQL load statement by a native SQL query or a HQL query. You just have to refer to a named query with the @Loader annotation.
You can use the exact same set of annotations to override the collection related statements.
@OneToMany
@JoinColumn(name="chaos_fk")
@SQLInsert( sql="UPDATE CASIMIR_PARTICULE SET chaos_fk = ? where id = ?")
@SQLDelete( sql="UPDATE CASIMIR_PARTICULE SET chaos_fk = null where id = ?")
private Set particles = new HashSet();
The parameters order is important and is defined by the order Hibernate handle properties. You can see the expected order by enabling debug logging for the org.hibernate.persister.entity level. With this level enabled Hibernate will print out the static SQL that is used to create, update, delete etc. entities. (To see the expected sequence, remember to not include your custom SQL through annotations as that will override the Hibernate generated static sql.)
Overriding SQL statements for secondary tables is also possible using @org.hibernate.annotations.Table and either (or all) attributes sqlInsert, sqlUpdate, sqlDelete:
@Entity
@SecondaryTables({
@SecondaryTable(name = "`Cat nbr1`"),
@SecondaryTable(name = "Cat2"})
@org.hibernate.annotations.Tables( {
@Table(appliesTo = "Cat", comment = "My cat table" ),
@Table(appliesTo = "Cat2", foreignKey = @ForeignKey(name="FK_CAT2_CAT"), fetch = FetchMode.SELECT,
sqlInsert=@SQLInsert(sql="insert into Cat2(storyPart2, id) values(upper(?), ?)") )
} )
public class Cat implements Serializable {
The previous example also show that you can give a comment to a given table (promary or secondary): This comment will be used for DDL generation.
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Australian firefighters battle widespread blazes, brace for worse conditions
MELBOURNE: Australian firefighters will spend Sunday (Nov 10) trying to contain bushfires as authorities warn that widespread fire danger on Tuesday will stretch their ability to protect people.
The New South Wales Rural Fire Service (NSW RFS) said on Sunday that they were expecting severe and extreme fire danger across broad parts of Australia's most populous state, including near the nation's largest city, Sydney.
"With so many fires already burning, homes and lives will be at risk," the NSW RFS said on Twitter.
"If you are threatened by fire, you may not get help."
READ: Australia bushfires leave three dead, at least 150 homes lost
Bushfires in NSW have killed three people since Friday, when a record number of emergency-level fires were declared in the state.
At least 150 homes have been destroyed and, although five people were missing on Saturday afternoon, Sky News reported on Sunday morning that those people were now accounted for.
More than 70 fires were burning in NSW on Sunday morning and while none were at an emergency level, 36 were not under control.
Further north in Queensland, more than 50 fires were burning Sunday morning and a fire ban was declared across 42 local areas in the state, prohibiting the lighting of any outdoor fires and banning certain activities that can cause fires to ignite.
"We're experiencing tinder box-like conditions across much of the state and all it takes is one spark to start a fire that may burn for days," Queensland Fire and Emergency Services acting commissioner Mike Wassing said in a statement.
According to the Australian Broadcasting Corporation, almost 5,000 homes have been evacuated in Queensland over the last 48 hours, with many residents unable to return.


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Our journals & publications.


| Assets ID | Assets Name | Description | Manufacturer | Rented | Serical No | Action |
|---|---|---|---|---|---|---|
| There are no assets in the DB. Add a new assets. | ||||||
|
{{asset.assets_id}}
|
{{asset.assets_name}}
|
{{asset.description}}
|
{{asset.manufacturer}}
|
{{asset.rented==1 ? "RENTED" : "NOT RENTED"}}
|
{{asset.serical_no}}
|
| Title | Description | Assets Name | Apply Date | Status |
|---|---|---|---|---|
| There are no repair request history in the DB. | ||||
| {{repair.title}} | {{repair.description}} | {{repair.assets_id}} | {{repair.created_date | date : " MMM d, y h:mm:ss a"}} | {{repair.status==0 ? "PENDING" : "SOLVED"}} |


Chopper is a high speed tile server written in Go that supports things like HTTP2,
preemptive loading of tiles using Server Push and in memory LRU caching of tiles.
All in all this helps Chopper provide an amazing experience - in a really lightweight package.
The server is up a running. Check out:
Welcome to Chopper!


You can contact me through:
My email address<EMAIL_ADDRESS>My Linkedin account: LinkedIn
My Github repository: Github
You can contact me through:
My email address<EMAIL_ADDRESS>My Linkedin account: LinkedIn
My Github repository: Github


{% extends 'onlineshop/base.html' %} {% load i18n %} {% load static %} {% block title %} Privacy Policy {% endblock %} {% block content %}
We collect names, email addresses, twitter handles, github handle and, if you’re a speaker, sometimes phone numbers.
We take privacy very seriously. We use your contact information to send updates and conference related info to attendees. We may use your phone number if you’re a speaker and we’re trying to find you before your talk. Information may be shared with third-party vendors conducting business on behalf of the conference. Information may also be shared in accordance with our code of conduct as deemed necessary by conference staff. It is not used for any other purpose, nor is it given or sold to any other party, including other attendees or sponsors.
Feel free to contact<EMAIL_ADDRESS>for details involving privacy.


Aspera Connect Combined Upload/Download Example
Choose transfer operation
Token Authorization
Allow Upload Multiple files
UPLOAD TRANSFERS VIEW
Transfer Progress
File Name
Control buttons
DOWNLOAD TRANSFERS VIEW
Transfer Progress
File Name
Control buttons
JSON Display


CREDIT
Description : this Desposit is from BRD
Cashier : Josiane
Amount :890,000 rwf
DEBIT
Description : this withdraw was for transport
Cashier : Izedin
Amount : 300,000 rwf
DEBIT
Description : this withdraw was for Personal use
Cashier : Alphonse
Amount : 590,000 rwf
CREDIT
Description : this Deposit was from ALINE
Cashier : Clement
Amount : 225,000 rwf
DEBIT
Description : this withdraw Paid Tuition
Cashier : Philbert
Amount : 225,000 rwf
CREDIT
Description : this Deposite was from MTN
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DEBIT
Description : this withdraw Paid Mango-4GLTE
Cashier : EVelyne
Amount : 22,000 rwf
CREDIT
Description : this deposite was from BRD
Cashier : Alphonse
Amount : 100,000 rwf
DEBIT
Description : this withdraw was for Tuition
Cashier : Slyvie
Amount : 720,000 rwf


|
LiquidFun Paint
Create art that moves, shakes, and delights.
|
About
Prerequisites
About this manual
Feedback and reporting bugs
Core concepts
Modules
LiquidFun Paint is a simple painting game that showcases the fluid simulation in LiquidFun, with a polished look. The primary interaction of the player with the game is through the touch screen and the accelerometer built into the Android device.
With the touch screen, the player can draw multiple types of fluid particles, erase drawn particles, and move the particles around.
With the accelerometer, the player can tilt the device and change the perceived gravity, which will then cause the fluids to react and move towards the gravity pull.
The game is written in Java, using the SWIG component of LiquidFun. The SWIG component will generate JNI (Java Native Interface) functions to facilitate communication between C++ and Java. LiquidFun Paint also utilizes Eclipse, and the Android SDK and Android NDK, for UX design and for building the various Java and C++ components.
LiquidFun Paint is based on LiquidFun, a 2D fluid simulation library. Please refer to the LiquidFun site for more information and a tutorial on the library.
LiquidFun Paint is written in Java, and we recommend a working knowledge of the language before attempting to use the source code. In addition, if you choose to delve more into LiquidFun, you will need to have additional knowledge in C++ and SWIG. LiquidFun Paint should not be your first Android programming project! You should be comfortable with compiling, linking, and debugging.
Caution
LiquidFun Paint should not be your first Android or Java project. Please learn Java programming, compiling, linking, and debugging, especially for Android, before working with LiquidFun Paint. There are many resources for this on the Internet.
This manual covers the basics of the LiquidFun Paint's code components. For anything that this manual does not cover, please refer to the comments in the source code.
This manual is only updated with new releases. The version in source control may be out of date.
If you have a question or feedback about LiquidFun Paint, please leave a comment in the Google group. This is also a great place for community discussion.
LiquidFun Paint issues are tracked using GitHub.
Please file bugs and feature requests here: https://github.com/google/liquidfunpaint/issues
Please provide as much detail as you can when posting.
LiquidFun Paint uses a model-view-controller model.
Both the model and the view components are owned by the Renderer
class. We need to synchronize between the physics simulation and the rendering. In order to keep a simple structure, whenever onDrawFrame()
is called from OpenGL, we run the update/render loop.
The controller component is split into two classes - Controller
and MainActivity
. Controller
implements listeners that respond to touch and accelerometer events, and those will in turn be used to manipulate LiquidFun. MainActivity
is an Android activity which listens to Android UI components, and updates the Controller
accordingly.
As LiquidFun is not reentrant, we need to ensure thread safety from the application itself. We initialize only one instance of b2World
from LiquidFun, and within that, only one instance of b2ParticleSystem
. We use ReentrantLocks to ensure safe access to both instances from other threads.
All LiquidFun objects are allocated through the C++ allocator. As a result, they should be properly cleaned up when they are not in use anymore. Please refer to the LiquidFun SWIG documentation for more details.
We have multiple renderers for different rendering purposes.
Base Renderer
This implements GLSurfaceView.Renderer
, the basic OpenGL ES renderer in the Android SDK.
onSurfaceCreated
This is called when the OpenGL surface is created or recreated after the context is lost. We will recreate all OpenGL objects as well as pass down the call to other renderers.
We also read JSON files here. The data from the JSON files are needed to initialize OpenGL objects.
For further information on GLSurfaceView.Renderer, please visit http://developer.android.com/reference/android/opengl/GLSurfaceView.Renderer.html.
Debug Renderer
This extends the b2Draw
class from LiquidFun, and allows for efficient debug rendering when prototyping. It is controllable via a static boolean constant.
Particle Renderer
This renders the fluid particle state from LiquidFun. It goes through ParticleGroups
in succession, and determines which specific particle renderer to use. We have two renderers, one for loose water-like particles, the other for rigid body or wall particles.
The general flow for either type of particles is:
BlurRenderer
)ScreenRenderer
)ScreenRenderer
)TextureRenderer
This is a basic texture renderer for ease of initializing and rendering any textures to the OpenGL context.
The controller component is split into two classes.
MainActivity
This controls all the visible UI, include the buttons for players to change drawing mode (tools) and colors, as well as the reset button to reset the whole canvas.
Controller
This intercepts touch events from the canvas, as well as accelerometer inputs, and passes the information onto the LiquidFun component. We have the following tools:
PencilTool
: Draw particles that will not move or be affected by fluids.RigidTool
: Draw particles that will float, bob and move with the fluid.WaterTool
: Draw particles that flow, drip and slosh realistically.EraserTool
: Erases particles.MoveTool
: Move particles.


Electric car owners must have two hours to charge - councillor
Council says the parking bye laws must be changed first
by Paul O'MearaOwners of electric cars (EVs) should have two hours to charge their vehicles at Kildare County Council operated car parks.
This, Cllr Bill Clear told a Naas Municipal District meeting, would be in the interests of addressing climate change and “we should try to encourage it.”
As already reported Sallins woman Emma Priest received two parking tickets for charing her car at two Naas car parks without buying a ticket. Although Kildare County Council have since waived their fines.
At the same time insisting that an offence was committed and that fines would be issued in the future to car owners who have not bought a ticket to park.
Cllr Clear has sought to have the bye-laws which govern how the pay parking system operates reviewed.
“It is now past the mid term point of the current bye-laws, “ he said. He also stated there are a number of other parking issues to be addressed in Naas.
Free parking is allowed outside Super Valu store at Fairgreen at times when school buses are not using the parking bay.
Cllr Clear also said that a similar regime applies at Sallins Road - but once people see that they can park there sometimes the area becomes congested.
“At times people are parked there and the buses can’t pull in,” he added.
He also said that parking charges in some areas, like victoria Terrace, are excessive.
However KCC says a review of any parking bye-law should not take place unless “there are significant amendments proposed such as extending enforcement days, times and significantly extending the area of enforcement.”
The council also suggested that a review should not start for at least five years “since the commencement of its enforcement.”
The meeting was also told that any review of any parking bye-law may also incor unnecessary significant costs.


Strider likes to lie outside in the sun, on the grass.
He is an expert of laying in the kitchen while dinner is being made.
Here are some of the things that I like about Strider:
Want to learn about my frogs? Click Here!
Want to learn about my cousins dogs? Click here


---
layout: page
title: CAV18-Artifact-Paper259
---
Artifact
We provide our artifact in the form of a virtual machine running Ubuntu 17.10 which can be downloaded here. We prepared the virtual machine on a 10 Core 3.3 GHz Intel i9-7900X Processor running Ubuntu 17.10. We also tested the virtual machine on a Quad Core 3.5 GHz Intel i7-4771 Haswell CPU running windows 10. We allocated 16 GB of RAM to the virtual machine.
{% include card.html
title="Paper #259"
url="http://files.srl.inf.ethz.ch/cav18-paper259.pdf"
output="horizontal"
description="Fast Numerical Program Analysis with Reinforcement Learning"
paper="http://files.srl.inf.ethz.ch/cav18-paper259.pdf"
%}
System Requirements
- Make sure you have 64-bit VirtualBox from Oracle.
- The SeaHorn framework and other dependencies make the virtual machine very large. The virtual machine requires at least 10 GB of disk space.
- We recommend allocating at least 16 GB RAM to the virtual machine for analyzing larger benchmarks.
Instructions
- Import the virtual machine in VirtualBox. More information on importing virtual machine in VirtualBox can be found here.
- The login credentials for the Virtual Machine are:
- The benchmarks used in the paper can be found in "CAV2018/Benchmarks" directory.
- As the Virtual machine is already large, we did not include the learning data as well as the benchmarks used for training.
Analyzer
- The Source code for SeaHorn can be found in "seahorn" directory.
- We have precompiled SeaHorn as it has a number of dependencies. The executable is located in "seahorn/build/run/bin" directory.
Polyhedra libraries
- Our approximate Polyhedra implementations build on top of ELINA.
- The source code for ELINA Polyhedra library, Poly-RL, Poly-Fixed and Poly-Init can be found in "ELINA/elina_poly", "ELINA/poly_rl", "ELINA/poly_fixed" and "ELINA/poly_init" directories respectively.
- The "ELINA/poly_rl" directory contains "weights.txt" file which contains the learned weights for the Q-function with linear function approximation. Poly-RL requires "weights.txt" to be in the folder in which the analysis is running. We have copied "weights.txt" in the directories containing benchmarks.
- It is possible to test our operators outside the seahorn analyzer. The test file "elina_test_poly.c" in the respective directories generates random test cases for a number of Polyhedra operators. The corresponding executable "elina_test_poly" requires two command line arguments : (a) dim: number of variables and (b) nbcons: number of constraints.
Reproducing results
- For reproducing results reported in the paper, run "sudo run.sh" in "CAV2018" directory. It compiles, installs and runs the ELINA Polyhedra analysis on all benchmarks followed by Poly-RL, Poly-Fixed and Poly-Init.
- The invariants and runtimes are collected in "results" directory.
- After completing the analysis, the script first shows the runtimes in cycles of all libraries on all benchmarks. The timings can be converted to seconds through dividing by CPU frequency. No runtime is reported in case of a timeout or crash.
- The script then shows the precision in percentage of all approximate libraries on all benchmarks with respect to ELINA. It also shows the number of program points on which an approximate implementation produces same or better fixpoints and the total number of program points on which invariants are comapred.
- SeaHorn can be invoked with Polyhedra analysis without "run.sh" by using the command "/home/cav2018/seahorn/build/run/bin/sea pf --crab --crab=opt-pk-elina filename". The shared object produced by all Polyhedra implementations has the same name so make sure to first install the desired implementation in "/usr/local/lib".
- We also included 5 benchmarks from product lines category in the directory "CAV2018/product-lines". ELINA times out on all of these. It is possible to run them directly as explained above or by modifying "run.sh" to use "product-lines" instead of "Benchmarks" directory. More benchmarks on which ELINA times out can be found here with the prefix "email_spec0", "email_spec1", "email_spec8", and "email_spec9" and "email_spec11".
- We set a default timeout limit of 3600 sec per benchmark, it is trivial to change this limit as per convenience in "run.sh".
Caveats
- The analysis runs slower on the virtual machine and the timings vary considerably. For benchmarks that run faster with ELINA, we observed that there was little speedup with Poly-RL.
- Since Poly-Init takes random actions, the timing and precision varies. Thus, the obtained timing and precision values from the virtual machine may be significantly different than the ones reported in the paper.
- For some benchmarks, seahorn crashes after the Polyhedra analysis completes. However, this is due to the SMT solver and not because of Polyhedra analysis.
- For "ata_pata", "ideapad_laptop" and "net_ppp" benchmarks, the analysis seems to crash before it can write all invariants on the virtual machine (the Polyhedra analysis finishes), thus the number of program points at which the fixpoints are compared are less than reported in the paper. We found that on the virtual machine, invariants were produced for 230, 377 and 580 program points respectively on these benchmarks instead of 262, 461 and 680 as reprted in the paper. Thus, the precision of our approximations on these benchmarks may differ from the ones reported in the paper.
- If less memory is available than recommended, then the analysis may crash before it completes and thus the reported precision will be significanlty less.


|
Sup. Welcome to the world of WigglerSim. My name is JadedResearcher, people call me JR. Shit. What was my lines again?
Uh. These are wigglers. Or grubs. Whatever. You hafta pick one to start raising, but you can get others later.
|
Become a Patron!
|


|
Interfaces
DependencyGraphBuilder GraphListener GraphTask PotentialCyclicEdgeProducer |
|
Classes
DependencyGraph DependencyGraphEdge DependencyGraphKeys DependencyGraphNode DependencyGraphUtils DependencyResolutionEvent GraphPhaseEvent ProjectModelBasedGraphBuilder |
|
Exceptions
GraphTaskException |


| Services | Time | Price |
|---|---|---|
| Forex Broker Company WL MT4, 5 | 2-3 month | $15.000* |
| Binary Options | 1-2 month | $10.000* |
| Personal Trader Room | 1 month | $3.000* |
| PSP | 1 week | $1.000* |
| Website Forex, Binary Options | 2-4 week | $3.000* |
| Liquidity | 1 week | $10-12 / 1m* |
* Starting price and can be changed depending on the request.
If you can not find the information you need, please contact us, we will reply as soon as possible and will try to help.


Try to get as many matches and as few mismatches and gaps as possible
Drag a nucleotide to the right to add a gap.
Drag to the left to remove a gap.
A gap appearing in both sequences at the same location will be automatically removed.
Level 1. Length: 10, Probability of mutation: 20%, Maximum # of deletions: 2
Level 2. Length: 12, Probability of mutation: 30%, Maximum # of deletions: 3
Level 3. Length: 15, Probability of mutation: 40%, Maximum # of deletions: 4
If you wish, you can change the default Match, Mismatch
, and Gap scores in the below textboxes.
#
A
C
G
T
Match Score
Mismatch Score
Gap Score
Your cumulative score
Created by Minji Kim, Yeonsung Kim, Lei Qian, and Jun S. Song.


Content Elements built styled with Bulma - source code
Our mission is not to outsell Hooli with a product like their latest Box 3. We are not in it for the money - we are in it to make the whole world decentralized. To give you control over your data. To change by the internet as we know it by integrating a very important feature into it - freedom.
Our mission is not to outsell Hooli with a product like their latest Box 3. We are not in it for the money - we are in it to make the whole world decentralized. To give you control over your data. To change by the internet as we know it by integrating a very important feature into it - freedom.


Coming Soon
While loop is a basic type of loop. It is used to execute the statements till the condition remains matched.
Syntax:
while(condition)
{
statement;
++/--;
}
NOTE : Always check your loops before executing it. Avoid Infinite loops.
#include<stdio.h>
#include<conio.h>
void main()
{
int n;
clrscr();
n = 1;
while( n<=5 )
{
printf("%d \n",n);
n++;
}
getch();
}
Do while is similar to while loop but in do while loop the program gets executed at least one time and then it depends on the condition.
Syntax:
do
{
statement;
++/--;
}while(condition)
#include<stdio.h>
#include<conio.h>
void main()
{
clrscr();
int n = 1;
do
{
printf("%d \n",n);
n++;
}while(n<=10);
getch();
}
for loop is the most famous as well as the mostly used type of loop. for loop also does the same thing but there is a difference in the syntax.
Syntax:
for( starting variable ; condition ; ++/-- )
{
statements;
}
#include<stdio.h>
#include<conio.h>
void main()
{
clrscr();
int n = 1;
for( n ; n<=10 ; n++ )
{
printf("%d \n",n);
}
getch();
}
Now here are several programs which I request you to try at your own. If you face any difficulties there are the solutions of these programs.
Programs to print the following series :
- 1. 5 4 3 2 1
- 2. 2 4 6 8 10
- 3. 1 3 5 7 9
- 4. 1 4 9 16 25
- 5. 0 5 10 15 20


List of tools included with the installation and how to use them
Used to create, sign and/or send a Masterprotocol currency transaction
Checks from address to make sure it has:
Takes json input via STDIN for the following variables:
The json takes the following format:
{
"transaction_from": "{{Public from Address}}",
"transaction_to": "{{Public to Address}}",
"currency_id": {{1 for MSC, 2 for TMSC}},
"send_amt": {{amount to send}},
"property_type": {{1 for indivisible currency, 2 for divisible (MSC/TMSC are 2, Maidsafecoins are 1)}}
"broadcast": {{1 to create and broadcast or 0 to just create}},
"from_private_key": "{{private key for signing}}",
"clean": {{0 -keep all tx files, 1 -remove intersigned tx, 2 -remove all unsigned, 3 -remove all}}
}
Ex:
Note: for security the following was a brand new empty wallet. You should replace it’s details with your own applicable info:
{
"transaction_from": "1GGJMZoaxYMS4jsiLwPVbofe5YJyM6ER2i",
"transaction_to": "19hf8QEkD3GR7NhUrujWXRg6e4gsHUTysp",
"currency_id": 1,
"send_amt": 5.1,
"property_type": 2,
"from_private_key": "5JXxd7qecXrzd9hJGdJsBnwkfJauHxVqbqRmBqQUjhrbGJPgoWb",
"broadcast": 1,
"clean": 1
}
For reference, here is what the brainwallet.org generator page for the above address looks like. Take note of the ‘Uncompressed/Compressed’ option
Will return a json formated output. Errors will be returned with json that contains
{
"status": "Status message",
"error": "error details",
"fix": "Corrective action to resolve the issue"
}
Successful run will return json that contains:
{
"status": "Broadcast/Created/Signed status",
"valid_check": "Validity check of signed file",
"hash": "Hash of the tx",
"st_file": "location/name of the signed tx file"
}
Standalone running/testing can be done by creating a json file (see input details or example_send.json for structure) You can execute/run the program with:
cat your_file.json | python msc_createtx.py
DEPRECIATED, Please see msc_createtx.py
Used to create (and/or send) a Mastercoin transaction
Checks from address to make sure it has:
Takes json input via STDIN for the following variables:
The json takes the following format:
{
"transaction_from": "{{Public from Address}}",
"transaction_to": "{{Public to Address}}",
"currency_id": {{1 for MSC, 2 for TMSC}},
"msc_send_amt": {{amount to send}},
"property_type": {{1 for indivisible currency, 2 for divisible (MSC/TMSC are 2, Maidsafecoins are 1)}}
"from_private_key": "{{private key for signing}}",
"broadcast": {{1 to create and broadcast or 0 to just create}},
"clean": {{0 -keep all tx files, 1 -remove intersigned tx, 2 -remove all unsigned, 3 -remove all}}
}
Ex:
Note: for security the following was a brand new empty wallet. You should replace it’s details with your own applicable info:
{
"transaction_from": "1GGJMZoaxYMS4jsiLwPVbofe5YJyM6ER2i",
"transaction_to": "19hf8QEkD3GR7NhUrujWXRg6e4gsHUTysp",
"currency_id": 1,
"msc_send_amt": 5.1,
"property_type": 2,
"from_private_key": "5JXxd7qecXrzd9hJGdJsBnwkfJauHxVqbqRmBqQUjhrbGJPgoWb",
"broadcast": 1,
"clean": 1
}
For reference, here is what the brainwallet.org generator page for the above address looks like. Take note of the ‘Uncompressed/Compressed’ option
Will return a json formated output. Errors will be returned with json that contains
{
"status": "Status message",
"error": "error details",
"fix": "Corrective action to resolve the issue"
}
Successful run will return json that contains:
{
"status": "Broadcast/Created status",
"valid_check": "Validity check of signed file",
"hash": "Hash of the tx",
"st_file": "location/name of the signed tx file"
}
Standalone running/testing can be done by creating a json file (see input details or example_send.json for structure) You can execute/run the program with:
cat your_file.json | python msc_sxsend.py
Checks from address to make sure it has:
Takes json input via STDIN for the following variables:
The json takes the following format:
{
"transaction_from": "{{Public from Address}}",
"transaction_to": "{{Public to Address}}",
"currency_id": {{1 for MSC, 2 for TMSC}},
"msc_send_amt": {{amount to send}},
"property_type": {{1 for indivisible currency, 2 for divisible (MSC/TMSC are 2, Maidsafecoins are 1)}}
}
Ex:
Note: for security the following was a brand new empty wallet. You should replace it’s details with your own applicable info:
{
"transaction_from": "1GGJMZoaxYMS4jsiLwPVbofe5YJyM6ER2i",
"transaction_to": "19hf8QEkD3GR7NhUrujWXRg6e4gsHUTysp",
"currency_id": 1,
"msc_send_amt": 5.1
}
Will return a json formated output. Errors will be returned with json that contains
{
"status": "Status message",
"error": "error details",
"fix": "Corrective action to resolve the issue"
}
Successful run will return json that contains:
{
"status": "Created status",
"st_file": "location/name of the unsigned tx file"
}
Standalone running/testing can be done by creating a json file (see input details or example_send.json for structure) You can execute/run the program with:
cat your_file.json | python msc-txcreate.py
Used to get the Mastercoin balance of an address
This script leverages the existing mastercoin tools parsed/validated output. Mastercoin tools should be installed and fully updated with the Mastercoin Data in:
/var/lib/mastercoin-tools/mastercoin_verify/addresses/
Will check/return the date of the parsed date as listed in
/var/lib/mastercoin-tools/www/revision.json
Takes json input via STDIN for the following variables:
The json takes the following format:
{
"address": "{{Address to check}}",
"currency_id": {{1 for MSC, 2 for TMSC}}
}
Ex:
{
"address": "1CMauYumpA7YG8i4cPod8FadRLK95HxSob",
"currency_id": 1
}
Will return a json formated output
Completed run will return json that contains:
{
"address": "Address checked",
"currency_id": "Currency checked",
"balance": "Balance or error message",
"balancetime": "Time in GMT human readable",
"epochtime": "Balance Timestamp in GMT epoch"
}
Note: If the revision file or currency address files are missing the time is omitted and an error message is returned for balance.
Standalone running/testing can be done by creating a json file (see input details or example_balance.json for structure) You can execute/run the program with:
cat your_file.json | python msc-balance.py
Used to get the consensus of local installation with Online sites Note: The final consensus authority is defined by the mastercoin tools code result. Masterchain Consensus Report
This script leverages the existing mastercoin tools parsed/validated output. Mastercoin tools should be installed and fully updated with the Mastercoin Data in:
/var/lib/mastercoin-tools/mastercoin_verify/addresses/
Takes json input via STDIN for the sites you wish to validate consensus against: Note: At present generates consensus output for Currency ID 1 (MSC) only.
The json takes the following format:
{ "sites":
[
"http://masterchain.info/mastercoin_verify/addresses/0",
"https://masterchest.info/mastercoin_verify/addresses.aspx",
"http://mymastercoins.com/jaddress.aspx"
]
}
Will return a json formated output array of address not in consensus
For each address not in Consensus, completed run will return balance of that address for each site checked in json format:
{
"consensus": Number Representing Consensus Rating,
"data":[
[
{
"balance": Number Representing Current balance for the site checked,
"site":"Site/Data Source name",
"address":"address not in consensus"
},
{
... data in format of ^ for each site when address is not in consensus
}
],
[
... 2nd address (if exists) not in consensus in format ^^^
]
]
}
Running by creating a json file (see input details) for sites you wish to check or use the provided getConsensus.json You can execute/run the program with:
cat getConsensus.json | python getConsensusMSC.py


✨ mirror_json
A Dart library for parsing JSON objects using dart:mirrors
.
Important: This library does not work in Flutter.
🔨 Installation
Add mirror_json
to your dependencies.
dependencies:
...
mirror_json:
Now get the packages.
pub get
🔮 Getting started
mirror_json
uses a concept of Parsers. There are a bunch of parsers for simple types (int, double, String) already in the package, but in order to parse a class, you have to make a ClassParser
instance.
import 'package:mirror_json/mirror_json.dart';
@JsonParseable()
class MyClass {
...
}
void main() {
GlobalJsonParserInstance.initialize();
var parser = ClassParser<MyClass>();
// From json
var myObject = Json.fromJson({...});
// To json
var json = Json.toJson(myObject);
}
Woah, what just happened?
First, we initialized mirror_json
's main class, GlobalJsonParserInstance
. This automatically adds parsers for simple types like int, double, List, etc. Then, we created a parser for MyClass
. Now you can use the Json
class to transform your JSON objects to MyClass
instances or MyClass
objects to JSON.
💡 Example
See example under example
folder.
📚 Docs
See docs here
📭 Contact me
E-Mail: kk.erzhan@gmail.com


No. Social Security benefits are adjusted for inflation. The numbers in this report show the value in today's dollars. For example, if there is 10% wage growth inflation between now and the time you collect your benefit, then the actual benefit (in terms of the actual number of dollars in your check) will be approximately 10% higher than this report shows.
For a more detailed explanation, see the following detailed guide on Social Security and Inflation.
Very likely yes, but there will probably be some changes along the way. This website cannot predict future changes to the law, it can only show you what your benefit will be under current law.
You may have heard that the Social Security program is running out of money. This is technically true, but only part of the story. Social Security is both paying out money to retirees and also collecting money from workers at the same time. Over its 80-year history, the program has collected more money than it has paid out and has about a $3 trillion reserve of extra funds. However, in recent years the program is paying out more than it is collecting, and so the fund is shrinking.
Current estimates are that the fund will run out in 2035. At that time, the program will still be collecting money, and those collections will cover all but 21% of the current payments. So, if nothing changes by 2035, the calculated benefit may be be reduced by 21%, but the payments will still continue. Roughly speaking, your primary insurance amount of ${{recipient.primaryInsuranceAmount() | number:2}} would be reduced to: ${{recipient.primaryInsuranceAmount() * 0.79 | number:2}}. This is the 'worst case' scenario.
More information:
The Future Financial Status of the Social Security Program
Social Security Office of Retirement and Disability Policy
There are multiple mechanisms by which Congress could conceivably 'fix' the Social Security deficit, which would have less of an impact than the 'worst case' scenario. What will ultimately happen is unknown. Some of the ideas that have been proposed include:
It depends. The exact computation is complicated and depends on your overall income, but no more than 85% of your benefits are subject to federal income tax. Many states do not tax Social Security, but some do.
No. There are a number of deductions that can be taken from the payment. These don't technically reduce your benefit, but they reduce the amount of your payment check. Examples include:
This report is intentionally not saved anywhere, to protect your privacy. By closing your browser, all of the information here will be lost. If you would like to save this report, most browsers will let you 'print' a webpage as a PDF file. To do so, simply print the page as normal, but when selecting a destination printer, choose "Save as PDF" instead.
See the 'contact' link at the top of the page. This site is maintained with the intention of providing correct information, but should not be relied upon for financial planning purposes. It is possible that the information presented here may be incomplete or incorrect. If you find any issues, or have suggestions, please don't hesitate to contact me.
However, please do not send me general questions about Social Security. The best place for questions of that nature is the Social Security Administration itself.
This calculator updates at least once a year with new adjusted numbers from the Social Security Administration. There are also sometimes additional improvements and changes throughout the year that you might find useful. To get notified of these occasional updates, follow along on social media:


Preparation time
less than 30 mins
Cooking time
30 mins to 1 hour
Serves
Makes 1 large gâteau
Dietary
Six layers of chocolate and hazelnut sponge are laced with cognac and iced with a light meringue buttercream. A showstopper if ever there was one.
For the sponge cakes, preheat the oven to 180C/350F/Gas 4 and lightly grease and line the base of two 25cm/10in loose bottomed cake tins.
For the hazelnut sponge, in a clean bowl, whisk the egg whites and 50g/1¾oz of the icing sugar until stiff peaks form when the whisk is removed.
In a separate bowl, whisk together the remaining icing sugar and whole eggs until thickened and pale in colour.
Fold in the ground hazelnuts gently, sift in the flour and mix in the melted butter.
Finally, gently fold in the whisked egg whites until incorporated.
Spoon the mixture into one of the prepared cake tins, then tap to remove any air pockets.
Place in the oven for 16 minutes, or until risen and just firm to the touch.
Remove from the oven and cool briefly before tipping out onto a rack to cool completely.
For the chocolate sponge, place the eggs and sugar in a bowl and whisk for 4-5 minutes, or until thickened and very pale.
Sift in the flour and cocoa powder and add the melted butter. Gently fold the batter to combine.
Spoon the mixture into the remaining cake tin, then tap to remove any air pockets.
Bake in the oven for 16 minutes, or until risen and just firm to the touch – do not overcook this sponge, as it will become dry.
Remove from the oven and cool briefly before tipping out onto a rack to cool completely.
For the hazelnut cream, in a bowl combine the cream and hazelnut paste. Whisk until soft peaks form when the whisk is removed. Place in the fridge until ready to use.
For the coffee flavoured meringue buttercream, place the sugar and 125ml/4½fl oz water in a pan and slowly bring to the boil. Continue to heat until the syrup reaches 110C/230F on a sugar thermometer.
Meanwhile, place the egg whites in the bowl of a food mixer (make sure it’s scrupulously clean) and add a squeeze of lemon juice. Whisk until firm peaks form.
Keep checking the temperature of the syrup and as soon as it reaches 121C/250F, remove the pan from the heat and immediately resume whisking the egg whites.
With the beater at its lowest speed, pour in the sugar syrup, in a slow steady stream, making sure it is clear of the whisk (the syrup is extremely hot and could splash out of the bowl if it hits the whisk).
Continue beating for about five minutes, until the meringue is tepid.
Add the butter and continue to beat until it is all incorporated. Beat in the cold coffee and set aside to cool completely.
To assemble the gateâu, horizontally cut each sponge cake into three layers to form six thin slices.
Place one sponge layer on a serving plate and drizzle over a spoonful of cognac. Spread over a thin layer of hazelnut cream.
Top with another layer of sponge, cognac and cream and repeat with the remaining sponges until you have a stack of six sponges filled with five layers of cream.
To decorate, using a pallet knife spread the coffee flavoured meringue buttercream around the sides of the cake and over the top, finishing with a swirl pattern.
Use a little buttercream to stick the marshmallows to the meringue shells. Dust with cocoa powder, then place on the top of the cake in a little cluster.
Slice and serve.


Air Pollution
The graph below with highlighting effect demonstrates average annual growth rate of GHG emissions from top 10 countries. It shows that South Korea has the highest annual growth compared with other countries, while Mexico has the second highest annual growth. United Kingdom has the lowest average annual growth rate. Although United States and Japan have the highest emissions, their average annual growth rates are below 0.


Try username named as given web app.
Customer email addresses mail reveal the user accounts naming convention.
Users and passwords in the source.
Does site generate predictable usernames?


Pisces
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--- layout: post title: SQlite3-Ruby Windows Builds post_id: 69 categories: - projects date: 2008-12-06 22:16:00.000000000 -07:00 author: Jamis permalink: 2008/12/6/sqlite3-ruby-windows-builds.html ---
So, I’ve got a new sqlite3-ruby release pending (just a minor bug fix, is all), but I’ve learned my lesson about releasing a new version without a windows version pre-built.
The problem is, I’m not a Windows guy. My build environment for Windows is cobbled together and painful to use, when it works at all. I’ve decided that I won’t put myself through that pain anymore.
If you are a developer on Windows, and you have a sqlite3 build environment, and would be willing to compile the sqlite3-ruby extension for me, please do the following:
Once I have a build of sqlite3-ruby for windows, I’ll release the new gem. (It amazes me how painful Windows makes this process. Mac OS X, Linux, BSD, etc. —you just gem install and build the source. No such luck in the Windows realm, apparently.)


The Bar
The Lobster House Restaurant offers two fabulous bars. Our indoor Hemmingway Bar and our Ourdoor Tiki Marina Bar. Our bartenders specialize in Tropical drinks along with our classic mixed drinks and we also have an extensive wine list .
Tropical Bar & Martinis (ALL FOR $12.95)
City Island Mojito - Bacardi Limón Rum, Triple Sec, fresh lime juice & mint leaves
Peach Martini - Absolut Peach, Peach Schnapps, 7-up with a splash of Cranberry Juice
Chocolate Martini - Vodka, Dark Creme de Cocoa & Baileys
Cosmopolitan - Vodka, Triple Sec, Lime Juice & Cranberry Juice
Apple Martini - Apple Pucker, Vodka, and splash of sour mix
Strawberry Martini - Vodka, Peach Schnapps, Strawberry Puree and a dash of Sour Mix
Mai Tai - A blend of tropical Fruit Juices with Bacardi Rum & Amaretto
Malibu Bay Breeze - Refreshing mix of Malibu Rum, Pineapple Juice, & a splash of Cranberry Juice
Jolly Rancher - A light mix of Vodka, Midori, 7-Up, & Cranberry Juice
Manhattan - Canadian Whiskey & Martini Rossi
Orange Mandarin - Absolut Mandarin, splash of Grand Marnier,1 orange slice
Berry Tini - Stoli Razz, Stoli Blueberi, Splash of Cranberry, Strawberry Puree & Sour Mix
Blue Ocean - A frozen mix of Alize Blue, Malibu Rum, Pineapple Juice & Coconut
Bikini Martini - Coconut Rum, Vodka, Pineapple juice & dash of Blue Curacao
French Martini - Absolut Vodka, Chambord Liqueur, & Pineapple Juice
Peartini - Pear Vodka, Amaretto, & Lime Juice
Our Drink Specialties
Piña Colada - The Caribbean’s Original Colada $10.95
Creamy Piña Colada - Our famous Colada with ice cream $10.95
Banana Colada - Original Colada w/ Banana’s $10.95
Strawberry Colada - Original Colada w/ Strawberries $10.95
Hennesy Colada - Original Colada w/ Henessy & Kahlua $13.95
Strawberry Dream - Ice Cream, Strawberries & Rum $10.95
The very best Margaritas North of Mexico! Your choice… $10.95
Frozen Margarita
Midori Margarita
Strawberry Margarita
The Ultimate Margarita - Reposado Tequila & Gran Marnier $12.95
Frozen Daquiri’s - Banana or Strawberry $10.95
Trouble in Paradise – Dark Rum, Banana Liqueur, Pineapple & Coconut Cream $10.95
Frozen Mudslide – Ice Cream, Kahlua, Bailey’s Irish Cream, & Vodka $10.95
Bahama Breeze – Meyers Rum, Amaretto, Pineapple & Coconut Cream $10.95
Frankenstein Monster – You best be ready for this… A blend of 5-rums and then some… Monstrous! $13.95
Tropical Punch – A smooth blend of tropical juices with White & Dark Rum $10.95
Sex on the Beach – Vodka, Peach Schnapps, Orange Juice & Cranberry Juice $9.95
City Island Iced Tea – a blend of 5 light liqueur with a splash of coke and lemon… watch out! $13.95
Long Passion Iced Tea – White Rum, Vodka, Tequila, Gin, Triple Sec, Passion Fruit Syrup, Blackcurrant & Lime $13.95
Pomegranate Margerita – Tequila, Triple Sec, Lime Juice & Sour Mix $11.95
Johnny Rockets – Amaretto, Malibu Rum and Pineapple Juice $9.95
Purple Pasion – Alize Red & Alize Blue w/Sprite on the rocks $9.95
Frozen Margarita
Blue Ocean
City Island Mojito
Malibu Martini
Peach Martini
City Island Iced Tea


Problem solving? Embarking on a new challenge is in my blood. I am a software developer driven with passion and ambition to succeed in all levels of coding. I speak computer in JavaScript, Ruby, and Python and have experience working with Ruby on Rails, MERN, HTML5/CSS3, and React/Redux. I am currently in the works of developing a web application that allows users to create new projects and back other users' projects and a personalized clone of Pacman, using mainly JavaScript, DOM, and Canvas. I have a reputation for working well with others, adapt well under work pressure, and pick up new skills easily to keep up with industry trends.
1000-hour immersive full-stack web development intensive with <3% acceptance rate
Teaches full-stack web development: Rails, SQL, JS, React, TDD, algorithms, design patterns, and programming best practices
Selected as the finalist in the Fashin Benefit Exhibition of 2014


UINavigationController
-
Pushes a view controller onto the receiver’s stack and updates the display. The object in the viewController parameter becomes the top view controller on the navigation stack. Pushing a view controller causes its view to be embedded in the navigation interface. If the animated parameter is true, the view is animated into position; otherwise, the view is simply displayed in its final location. In addition to displaying the view associated with the new view controller at the top of the stack, this method also updates the navigation bar and tool bar accordingly.
This is a function added in an extension adding the possibility to handle the completion.
Declaration
Swift
func pushViewController(_ viewController: UIViewController, animated: Bool, completion: @escaping () -> Void)
Parameters
viewController
The view controller to push onto the stack. This object cannot be a tab bar controller. If the view controller is already on the navigation stack, this method throws an exception.
animated
Specify true to animate the transition or false if you do not want the transition to be animated. You might specify false if you are setting up the navigation controller at launch time.
completion
Function to execute after finishing the animation.
-
Pops view controllers until the specified view controller is at the top of the navigation stack.
This is a function added in an extension adding the possibility to handle the completion.
Declaration
Swift
func popToViewController(_ viewController: UIViewController, animated: Bool, completion: @escaping () -> Void)
Parameters
viewController
The view controller that you want to be at the top of the stack. This view controller must currently be on the navigation stack. controller. If the view controller is already on the navigation stack, this method throws an exception.
animated
Set this value to true to animate the transition. Pass false if you are setting up a navigation controller before its view is displayed.
completion
Function to execute after finishing the animation.
-
This method removes the top view controller from the stack and makes the new top of the stack the active view controller. If the view controller at the top of the stack is the root view controller, this method does nothing. In other words, you cannot pop the last item on the stack. In addition to displaying the view associated with the new view controller at the top of the stack, this method also updates the navigation bar and tool bar accordingly. For information on how the navigation bar is updated.
This is a function added in an extension adding the possibility to handle the completion.
Declaration
Swift
func popViewController(animated: Bool, completion: @escaping () -> Void)
Parameters
animated
Set this value to true to animate the transition. Pass false if you are setting up a navigation controller before its view is displayed.
completion
Function to execute after finishing the animation.
-
Pops all the view controllers on the stack except the root view controller and updates the display. The root view controller becomes the top view controller.
This is a function added in an extension adding the possibility to handle the completion.
Declaration
Swift
func popToRootViewController(animated: Bool, completion: @escaping () -> Void)
Parameters
animated
Set this value to true to animate the transition. Pass false if you are setting up a navigation controller before its view is displayed.
completion
Function to execute after finishing the animation.