org.apache.ignite.ml.dataset

Interface PartitionContextBuilder<K,V,C extends Serializable>

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

C - Type of a partition context.

All Superinterfaces:

Serializable

All Known Implementing Classes:

EmptyContextBuilder

Functional Interface:

This is a functional interface and can therefore be used as the assignment target for a lambda expression or method reference.

@FunctionalInterface
public interface PartitionContextBuilder<K,V,C extends Serializable>
extends Serializable

Builder that accepts a partition upstream data and makes partition context. This builder is used to build a partition context and assumed to be called only once for every partition during a dataset initialization.

See Also:

EmptyContextBuilder

Method Summary

Modifier and Type	Method and Description
default <C2 extends Serializable> PartitionContextBuilder<K,V,C2>	andThen(IgniteFunction<C,C2> fun) Makes a composed partition context builder that first builds a context and then applies the specified function on the result.
C	build(LearningEnvironment env, Iterator<UpstreamEntry<K,V>> upstreamData, long upstreamDataSize) Builds a new partition context from an upstream data.
default C	build(LearningEnvironment env, Stream<UpstreamEntry<K,V>> upstreamData, long upstreamDataSize) Builds a new partition context from an upstream data.

Method Detail

build

C build(LearningEnvironment env,
        Iterator<UpstreamEntry<K,V>> upstreamData,
        long upstreamDataSize)

Builds a new partition context from an upstream data. Important: there is no guarantee that there will be no more than one UpstreamEntry with given key, UpstreamEntry should be thought rather as a container saving all data from upstream, but omitting uniqueness constraint. This constraint is omitted to allow upstream data transformers in DatasetBuilder replicating entries. For example it can be useful for bootstrapping.

Parameters:

env - Learning environment.

upstreamData - Partition upstream data.

upstreamDataSize - Partition upstream data size.

Returns:

Partition context.

build

default C build(LearningEnvironment env,
                Stream<UpstreamEntry<K,V>> upstreamData,
                long upstreamDataSize)

Builds a new partition context from an upstream data. Important: there is no guarantee that there will be no more than one UpstreamEntry with given key, UpstreamEntry should be thought rather as a container saving all data from upstream, but omitting uniqueness constraint. This constraint is omitted to allow upstream data transformers in DatasetBuilder replicating entries. For example it can be useful for bootstrapping.

Parameters:

env - Learning environment.

upstreamData - Partition upstream data.

upstreamDataSize - Partition upstream data size.

Returns:

Partition context.

andThen

default <C2 extends Serializable> PartitionContextBuilder<K,V,C2> andThen(IgniteFunction<C,C2> fun)

Makes a composed partition context builder that first builds a context and then applies the specified function on the result.

Type Parameters:

C2 - New type of a partition context.

Parameters:

fun - Function that applied after first partition context is built.

Returns:

Composed partition context builder.