TopicModel

A model for a topic, that is, a message queue of some sort. Right now this means just Kafka topics.

name: the name of the topic, and doubles as the unique identifier for the model in the models database
creationTime: marks the time at which the model was generated.
partitions: the number of partitions used for the topic when wasp creates it
replicas: the number of replicas used for the topic when wasp creates it
topicDataType: field specifies the format to use when encoding/decoding data to/from messages, allowed values are: avro, plaintext, json, binary
keyFieldName: optionally specify a field whose contents will be used as a message key when writing to Kafka. The field must be of type string or binary. The original field will be left as-is, so you schema must handle it (or you can use valueFieldsNames).
headersFieldName: allows you to optionally specify a field whose contents will be used as message headers when writing to Kafka. The field must contain an array of non-null objects which must have a non-null field headerKey of type string and a field headerValue of type binary. The original field will be left as-is, so your schema must handle it (or you can use valueFieldsNames).
valueFieldsNames: allows you to specify a list of field names to be used to filter the fields that get passed to the value encoding; with this you can filter out fields that you don't need in the value, obviating the need to handle them in the schema. This is especially useful when specifying the keyFieldName or headersFieldName. For the avro and json topic data type this is optional; for the plaintext and binary topic data types this field is mandatory and the list must contain a single value field name that has the proper type (string for plaintext and binary for binary).
useAvroSchemaManager: if a schema registry should be used or not to handle the schema evolution (it makes sense only for avro message datatype)
schema: the Avro schema to use when encoding the value, for plaintext and binary this field is ignored. For json and avro the field names need to match 1:1 with the valueFieldsNames or the schema output of the strategy
topicCompression: to use to compress messages
subjectStrategy: subject strategy to use when registering the schema to the schema registry for the schema registry implementations that support it. This property makes sense only for avro and only if useAvroSchemaManager is set to true
keySchema: the schema to be used to encode the key as avro

Linear Supertypes

Serializable, Serializable, Product, Equals, DatastoreModel, Model, AnyRef, Any

Instance Constructors

new TopicModel(name: String, creationTime: Long, partitions: Int, replicas: Int, topicDataType: String, keyFieldName: Option[String], headersFieldName: Option[String], valueFieldsNames: Option[Seq[String]], useAvroSchemaManager: Boolean, schema: BsonDocument, topicCompression: TopicCompression = TopicCompression.Disabled, subjectStrategy: SubjectStrategy = SubjectStrategy.None, keySchema: Option[String] = None)

name
the name of the topic, and doubles as the unique identifier for the model in the models database
creationTime
marks the time at which the model was generated.
partitions
the number of partitions used for the topic when wasp creates it
replicas
the number of replicas used for the topic when wasp creates it
topicDataType
field specifies the format to use when encoding/decoding data to/from messages, allowed values are: avro, plaintext, json, binary
keyFieldName
optionally specify a field whose contents will be used as a message key when writing to Kafka. The field must be of type string or binary. The original field will be left as-is, so you schema must handle it (or you can use valueFieldsNames).
headersFieldName
allows you to optionally specify a field whose contents will be used as message headers when writing to Kafka. The field must contain an array of non-null objects which must have a non-null field headerKey of type string and a field headerValue of type binary. The original field will be left as-is, so your schema must handle it (or you can use valueFieldsNames).
valueFieldsNames
allows you to specify a list of field names to be used to filter the fields that get passed to the value encoding; with this you can filter out fields that you don't need in the value, obviating the need to handle them in the schema. This is especially useful when specifying the keyFieldName or headersFieldName. For the avro and json topic data type this is optional; for the plaintext and binary topic data types this field is mandatory and the list must contain a single value field name that has the proper type (string for plaintext and binary for binary).
useAvroSchemaManager
if a schema registry should be used or not to handle the schema evolution (it makes sense only for avro message datatype)
schema
the Avro schema to use when encoding the value, for plaintext and binary this field is ignored. For json and avro the field names need to match 1:1 with the valueFieldsNames or the schema output of the strategy
topicCompression
to use to compress messages
subjectStrategy
subject strategy to use when registering the schema to the schema registry for the schema registry implementations that support it. This property makes sense only for avro and only if useAvroSchemaManager is set to true
keySchema
the schema to be used to encode the key as avro

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def asInstanceOf[T0]: T0

Definition Classes
Any
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
val creationTime: Long

marks the time at which the model was generated.
def datastoreProduct: DatastoreProduct

Definition Classes
TopicModel → DatastoreModel
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
def getJsonSchema: String
val headersFieldName: Option[String]

allows you to optionally specify a field whose contents will be used as message headers when writing to Kafka.
allows you to optionally specify a field whose contents will be used as message headers when writing to Kafka. The field must contain an array of non-null objects which must have a non-null field headerKey of type string and a field headerValue of type binary. The original field will be left as-is, so your schema must handle it (or you can use valueFieldsNames).
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
val keyFieldName: Option[String]

optionally specify a field whose contents will be used as a message key when writing to Kafka.
optionally specify a field whose contents will be used as a message key when writing to Kafka. The field must be of type string or binary. The original field will be left as-is, so you schema must handle it (or you can use valueFieldsNames).
val keySchema: Option[String]

the schema to be used to encode the key as avro
val name: String

the name of the topic, and doubles as the unique identifier for the model in the models database
the name of the topic, and doubles as the unique identifier for the model in the models database

Definition Classes
TopicModel → Model
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
val partitions: Int

the number of partitions used for the topic when wasp creates it
val replicas: Int

the number of replicas used for the topic when wasp creates it
val schema: BsonDocument

the Avro schema to use when encoding the value, for plaintext and binary this field is ignored.
the Avro schema to use when encoding the value, for plaintext and binary this field is ignored. For json and avro the field names need to match 1:1 with the valueFieldsNames or the schema output of the strategy
val subjectStrategy: SubjectStrategy

subject strategy to use when registering the schema to the schema registry for the schema registry implementations that support it.
subject strategy to use when registering the schema to the schema registry for the schema registry implementations that support it. This property makes sense only for avro and only if useAvroSchemaManager is set to true
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
val topicCompression: TopicCompression

to use to compress messages
val topicDataType: String

field specifies the format to use when encoding/decoding data to/from messages, allowed values are: avro, plaintext, json, binary
val useAvroSchemaManager: Boolean

if a schema registry should be used or not to handle the schema evolution (it makes sense only for avro message datatype)
val valueFieldsNames: Option[Seq[String]]

allows you to specify a list of field names to be used to filter the fields that get passed to the value encoding; with this you can filter out fields that you don't need in the value, obviating the need to handle them in the schema.
allows you to specify a list of field names to be used to filter the fields that get passed to the value encoding; with this you can filter out fields that you don't need in the value, obviating the need to handle them in the schema. This is especially useful when specifying the keyFieldName or headersFieldName. For the avro and json topic data type this is optional; for the plaintext and binary topic data types this field is mandatory and the list must contain a single value field name that has the proper type (string for plaintext and binary for binary).
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )

Related Docs: object TopicModel | package models

Instance Constructors

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

val creationTime: Long

def datastoreProduct: DatastoreProduct

final def eq(arg0: AnyRef): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def getJsonSchema: String

val headersFieldName: Option[String]

final def isInstanceOf[T0]: Boolean

val keyFieldName: Option[String]

val keySchema: Option[String]

val name: String

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

val partitions: Int

val replicas: Int

val schema: BsonDocument

val subjectStrategy: SubjectStrategy

final def synchronized[T0](arg0: ⇒ T0): T0

val topicCompression: TopicCompression

val topicDataType: String

val useAvroSchemaManager: Boolean

val valueFieldsNames: Option[Seq[String]]

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from DatastoreModel

Inherited from Model

Inherited from AnyRef

Inherited from Any

Ungrouped