C - Type of a partition context.D - Type of a partition data.public interface Dataset<C extends Serializable,D extends AutoCloseable> extends AutoCloseable
context (reliably
stored segment) and data (unreliably stored segment, which can be recovered from an upstream data and a
context if needed). Computations are performed in a MapReduce manner, what allows to reduce a
network traffic for most of the machine learning algorithms.
Dataset functionality allows to implement iterative machine learning algorithms via introducing computation
context. In case iterative algorithm requires to maintain a state available and updatable on every iteration this
state can be stored in the context of the partition and after that it will be available in further
computations even if the Ignite Cache partition will be moved to another node because of node failure or rebalancing.
Partition context should be Serializable to be saved in Ignite Cache. Partition data
should be AutoCloseable to allow system to clean up correspondent resources when partition data is
not needed anymore.
CacheBasedDataset,
LocalDataset,
DatasetFactory| Modifier and Type | Method and Description |
|---|---|
default void |
compute(IgniteBiConsumer<D,Integer> map)
Applies the specified
map function to every partition data in the dataset and partition index. |
default <R> R |
compute(IgniteBiFunction<D,Integer,R> map,
IgniteBinaryOperator<R> reduce)
Applies the specified
map function to every partition data and partition index in the dataset
and then reduces map results to final result by using the reduce function. |
<R> R |
compute(IgniteBiFunction<D,Integer,R> map,
IgniteBinaryOperator<R> reduce,
R identity)
Applies the specified
map function to every partition data and partition index in the dataset
and then reduces map results to final result by using the reduce function. |
default void |
compute(IgniteConsumer<D> map)
Applies the specified
map function to every partition data in the dataset. |
default <R> R |
compute(IgniteFunction<D,R> map,
IgniteBinaryOperator<R> reduce)
Applies the specified
map function to every partition data in the dataset and then reduces
map results to final result by using the reduce function. |
default <R> R |
compute(IgniteFunction<D,R> map,
IgniteBinaryOperator<R> reduce,
R identity)
Applies the specified
map function to every partition data in the dataset and then reduces
map results to final result by using the reduce function. |
default void |
computeWithCtx(IgniteBiConsumer<C,D> map)
Applies the specified
map function to every partition data and context in the dataset. |
default <R> R |
computeWithCtx(IgniteBiFunction<C,D,R> map,
IgniteBinaryOperator<R> reduce)
Applies the specified
map function to every partition data and context in the dataset
and then reduces map results to final result by using the reduce function. |
default <R> R |
computeWithCtx(IgniteBiFunction<C,D,R> map,
IgniteBinaryOperator<R> reduce,
R identity)
Applies the specified
map function to every partition data and context in the dataset
and then reduces map results to final result by using the reduce function. |
default void |
computeWithCtx(IgniteTriConsumer<C,D,Integer> map)
Applies the specified
map function to every partition data, context and partition
index in the dataset. |
default <R> R |
computeWithCtx(IgniteTriFunction<C,D,Integer,R> map,
IgniteBinaryOperator<R> reduce)
Applies the specified
map function to every partition data, context and partition
index in the dataset and then reduces map results to final result by using the reduce function. |
<R> R |
computeWithCtx(IgniteTriFunction<C,D,Integer,R> map,
IgniteBinaryOperator<R> reduce,
R identity)
Applies the specified
map function to every partition data, context and partition
index in the dataset and then reduces map results to final result by using the reduce function. |
default <I extends Dataset<C,D>> |
wrap(IgniteFunction<Dataset<C,D>,I> wrapper)
Wraps this dataset into the specified wrapper to introduce new functionality based on
compute and
computeWithCtx methods. |
close<R> R computeWithCtx(IgniteTriFunction<C,D,Integer,R> map, IgniteBinaryOperator<R> reduce, R identity)
map function to every partition data, context and partition
index in the dataset and then reduces map results to final result by using the reduce function.R - Type of a result.map - Function applied to every partition data, context and partition index.reduce - Function applied to results of map to get final result.identity - Identity.<R> R compute(IgniteBiFunction<D,Integer,R> map, IgniteBinaryOperator<R> reduce, R identity)
map function to every partition data and partition index in the dataset
and then reduces map results to final result by using the reduce function.R - Type of a result.map - Function applied to every partition data and partition index.reduce - Function applied to results of map to get final result.identity - Identity.default <R> R computeWithCtx(IgniteTriFunction<C,D,Integer,R> map, IgniteBinaryOperator<R> reduce)
map function to every partition data, context and partition
index in the dataset and then reduces map results to final result by using the reduce function.R - Type of a result.map - Function applied to every partition data, context and partition index.reduce - Function applied to results of map to get final result.default <R> R compute(IgniteBiFunction<D,Integer,R> map, IgniteBinaryOperator<R> reduce)
map function to every partition data and partition index in the dataset
and then reduces map results to final result by using the reduce function.R - Type of a result.map - Function applied to every partition data and partition index.reduce - Function applied to results of map to get final result.default <R> R computeWithCtx(IgniteBiFunction<C,D,R> map, IgniteBinaryOperator<R> reduce, R identity)
map function to every partition data and context in the dataset
and then reduces map results to final result by using the reduce function.R - Type of a result.map - Function applied to every partition data and context.reduce - Function applied to results of map to get final result.identity - Identity.default <R> R compute(IgniteFunction<D,R> map, IgniteBinaryOperator<R> reduce, R identity)
map function to every partition data in the dataset and then reduces
map results to final result by using the reduce function.R - Type of a result.map - Function applied to every partition data.reduce - Function applied to results of map to get final result.identity - Identity.default <R> R computeWithCtx(IgniteBiFunction<C,D,R> map, IgniteBinaryOperator<R> reduce)
map function to every partition data and context in the dataset
and then reduces map results to final result by using the reduce function.R - Type of a result.map - Function applied to every partition data and context.reduce - Function applied to results of map to get final result.default <R> R compute(IgniteFunction<D,R> map, IgniteBinaryOperator<R> reduce)
map function to every partition data in the dataset and then reduces
map results to final result by using the reduce function.R - Type of a result.map - Function applied to every partition data.reduce - Function applied to results of map to get final result.default void computeWithCtx(IgniteTriConsumer<C,D,Integer> map)
map function to every partition data, context and partition
index in the dataset.map - Function applied to every partition data, context and partition index.default void compute(IgniteBiConsumer<D,Integer> map)
map function to every partition data in the dataset and partition index.map - Function applied to every partition data and partition index.default void computeWithCtx(IgniteBiConsumer<C,D> map)
map function to every partition data and context in the dataset.map - Function applied to every partition data and context.default void compute(IgniteConsumer<D> map)
map function to every partition data in the dataset.map - Function applied to every partition data.default <I extends Dataset<C,D>> I wrap(IgniteFunction<Dataset<C,D>,I> wrapper)
compute and
computeWithCtx methods.I - Type of a new wrapped dataset.wrapper - Dataset wrapper.
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Ignite Database and Caching Platform : ver. 2.7.2 Release Date : February 6 2019