Difference between revisions of "Collector Rosetta Stone"
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You will use {{AccumulatorCombinerReducerLink}} for our MapReduce assignments which is almost a one-to-one match with {{CollectorLink}} but de-ultra-uber-hyper-mega-super-lambdafied. | You will use {{AccumulatorCombinerReducerLink}} for our MapReduce assignments which is almost a one-to-one match with {{CollectorLink}} but de-ultra-uber-hyper-mega-super-lambdafied. | ||
− | == CSE | + | = One To One = |
− | + | {| class="wikitable" style="margin-left:0px" | |
+ | |- | ||
+ | ! CSE 231s: AccumulatorCombinerReducer<V, A, R> !! !! Java Streams: Collector<T, A, R> | ||
+ | |- | ||
+ | | <syntaxhighlight lang="java"> | ||
+ | public interface AccumulatorCombinerReducer<V, A, R> { | ||
A createMutableContainer(); | A createMutableContainer(); | ||
+ | |||
void accumulate(A container, V item); | void accumulate(A container, V item); | ||
− | + | ||
+ | void combine(A containerA, A containerB); | ||
+ | |||
R reduce(A container); | R reduce(A container); | ||
− | }</ | + | } |
+ | </syntaxhighlight> || <syntaxhighlight lang="java"> | ||
+ | |||
+ | <===> | ||
+ | |||
+ | <===> | ||
+ | |||
+ | <===> | ||
+ | |||
+ | <===> | ||
− | = | + | </syntaxhighlight> || <syntaxhighlight lang="java"> |
− | + | public interface Collector<T, A, R> { | |
+ | Supplier<A> supplier(); | ||
− | + | BiConsumer<A, T> accumulator(); | |
− | |||
− | + | BinaryOperator<A> combiner(); | |
− | |||
− | + | Function<A, R> finisher(); | |
− | + | } | |
+ | </syntaxhighlight> | ||
+ | |} | ||
− | + | = Differences = | |
− | + | Each interface provides a way to customize 4 of 5 of the methods required for Spark-level MapReduce functionality. {{AccumulatorCombinerReducerLink}} elects to perform the operations directly. {{CollectorLink}} elects to return single-abstract method interfaces which perform the operations. | |
− | |||
[https://docs.oracle.com/javase/8/docs/api/java/util/stream/Collector.html interface Collector<T,A,R>] | [https://docs.oracle.com/javase/8/docs/api/java/util/stream/Collector.html interface Collector<T,A,R>] | ||
− | : [https://docs.oracle.com/javase/8/docs/api/java/util/function/Supplier.html interface Supplier<T>] | + | : [https://docs.oracle.com/javase/8/docs/api/java/util/function/Supplier.html interface Supplier<T>] returned by supplier() |
− | : [https://docs.oracle.com/javase/8/docs/api/java/util/function/BiConsumer.html interface BiConsumer<T,U>] | + | : [https://docs.oracle.com/javase/8/docs/api/java/util/function/BiConsumer.html interface BiConsumer<T,U>] returned by accumulator() |
− | : [https://docs.oracle.com/javase/8/docs/api/java/util/function/BinaryOperator.html interface BinaryOperator<T>] | + | : [https://docs.oracle.com/javase/8/docs/api/java/util/function/BinaryOperator.html interface BinaryOperator<T>] returned by combiner() |
− | : [https://docs.oracle.com/javase/8/docs/api/java/util/function/Function.html interface Function<T,R>] | + | : [https://docs.oracle.com/javase/8/docs/api/java/util/function/Function.html interface Function<T,R>] returned by finisher() |
+ | |||
+ | Finally, the combine operation was simplified via a reasonable constraint to AccumulatorCombinerReducer. This allows for a slightly cleaner, more elegant solution to the [[#Matrix_Map_Reduce_Framework_Assignment|Matrix MapReduce Framework exercise]]. | ||
+ | |||
+ | =Methods= | ||
+ | == createMutableContainer a.k.a. supplier get== | ||
+ | We use createMutableContainer() to create a new mutable container. For classic map reduce this would be a [https://docs.oracle.com/javase/8/docs/api/java/util/List.html List<V>]. | ||
+ | |||
+ | rosetta stone: <code>container = collector.supplier().get()</code> <math>\leftrightarrow</math> <code>container = acr.createMutableContainer()</code> | ||
+ | |||
+ | == accumulate a.k.a. accumulator accept== | ||
+ | We use accumulate(container,item) to accumulate a value. For classic map reduce this would add an item to a list. | ||
+ | |||
+ | rosetta stone: <code>collector.accumulator().accept(container,item);</code> <math>\leftrightarrow</math> <code>acr.accumulate(container,item)</code> | ||
+ | |||
+ | == combine a.k.a. combiner apply== | ||
+ | We use combine(containerA,containerB) to combine two accumulators. You may combine containerB into containerA or containerA into containerB. Just return whichever is the combined result. | ||
+ | |||
+ | rosetta stone: <code>collector.combiner().apply(containerA,containerB)</code> <math>\leftrightarrow</math> <code>acr.combine(containerA,containerB)</code> | ||
+ | |||
+ | '''Note:''' {{CollectorLink}} allows the client to combine containerB into containerA, containerA into containerB, or create a new container with the combined contents of containerA and containerB. The only requirement is that resulting combined container is the return value. {{AccumulatorCombinerReducerLink}} mandates that containerB be combined into containerA to take a bit of cruft out of the [[#Matrix_Map_Reduce_Framework_Assignment|Matrix MapReduce Framework exercise]]. | ||
+ | |||
+ | == reduce a.k.a. finisher apply== | ||
+ | We use reduce(container) to reduce an accumulator. | ||
− | = | + | rosetta stone: <code>collector.finisher().apply(container)</code> <math>\leftrightarrow</math> <code>r = acr.reduce(container)</code> |
− | + | = Converting Back And Forth = | |
+ | <syntaxhighlight lang="java"> | ||
+ | public class StreamUtils { | ||
+ | public static <V, A, R> Collector<V, A, R> toCollector( | ||
+ | AccumulatorCombinerReducer<V, A, R> accumulatorCombinerReducer) { | ||
return new Collector<V, A, R>() { | return new Collector<V, A, R>() { | ||
@Override | @Override | ||
public Supplier<A> supplier() { | public Supplier<A> supplier() { | ||
− | return () -> | + | return () -> accumulatorCombinerReducer.createMutableContainer(); |
} | } | ||
@Override | @Override | ||
public BiConsumer<A, V> accumulator() { | public BiConsumer<A, V> accumulator() { | ||
− | return (container, item) -> | + | return (container, item) -> accumulatorCombinerReducer.accumulate(container, item); |
} | } | ||
@Override | @Override | ||
public BinaryOperator<A> combiner() { | public BinaryOperator<A> combiner() { | ||
− | return (a, b) -> | + | return (a, b) -> { |
+ | accumulatorCombinerReducer.combine(a, b); | ||
+ | return a; | ||
+ | }; | ||
} | } | ||
@Override | @Override | ||
public Function<A, R> finisher() { | public Function<A, R> finisher() { | ||
− | return (container) -> | + | return (container) -> accumulatorCombinerReducer.reduce(container); |
} | } | ||
@Override | @Override | ||
public Set<Characteristics> characteristics() { | public Set<Characteristics> characteristics() { | ||
− | return | + | return accumulatorCombinerReducer.collectorCharacteristics(); |
} | } | ||
}; | }; | ||
} | } | ||
− | public static <V, A, R> | + | public static <V, A, R> AccumulatorCombinerReducer<V, A, R> toAccumulatorCombinerReducer( |
− | return new | + | Collector<V, A, R> collector) { |
+ | return new AccumulatorCombinerReducer<V, A, R>() { | ||
@Override | @Override | ||
public A createMutableContainer() { | public A createMutableContainer() { | ||
Line 77: | Line 125: | ||
@Override | @Override | ||
− | public | + | public void combine(A containerA, A containerB) { |
− | + | A result = collector.combiner().apply(containerA, containerB); | |
+ | if (result != containerA) { | ||
+ | throw new RuntimeException("collector must combine b into a and return a."); | ||
+ | } | ||
} | } | ||
Line 92: | Line 143: | ||
}; | }; | ||
} | } | ||
− | + | } | |
− | + | </syntaxhighlight> | |
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Latest revision as of 16:33, 23 February 2023
The interface Collector<T,A,R> serves the standard Java streams framework for MapReduce-like tasks with added in-memory processing capability a la Apache Spark.
You will use interface AccumulatorCombinerReducer<V,A,R> for our MapReduce assignments which is almost a one-to-one match with interface Collector<T,A,R> but de-ultra-uber-hyper-mega-super-lambdafied.
Contents
One To One
CSE 231s: AccumulatorCombinerReducer<V, A, R> | Java Streams: Collector<T, A, R> | |
---|---|---|
public interface AccumulatorCombinerReducer<V, A, R> {
A createMutableContainer();
void accumulate(A container, V item);
void combine(A containerA, A containerB);
R reduce(A container);
}
|
<===>
<===>
<===>
<===>
|
public interface Collector<T, A, R> {
Supplier<A> supplier();
BiConsumer<A, T> accumulator();
BinaryOperator<A> combiner();
Function<A, R> finisher();
}
|
Differences
Each interface provides a way to customize 4 of 5 of the methods required for Spark-level MapReduce functionality. interface AccumulatorCombinerReducer<V,A,R> elects to perform the operations directly. interface Collector<T,A,R> elects to return single-abstract method interfaces which perform the operations.
- interface Supplier<T> returned by supplier()
- interface BiConsumer<T,U> returned by accumulator()
- interface BinaryOperator<T> returned by combiner()
- interface Function<T,R> returned by finisher()
Finally, the combine operation was simplified via a reasonable constraint to AccumulatorCombinerReducer. This allows for a slightly cleaner, more elegant solution to the Matrix MapReduce Framework exercise.
Methods
createMutableContainer a.k.a. supplier get
We use createMutableContainer() to create a new mutable container. For classic map reduce this would be a List<V>.
rosetta stone: container = collector.supplier().get()
container = acr.createMutableContainer()
accumulate a.k.a. accumulator accept
We use accumulate(container,item) to accumulate a value. For classic map reduce this would add an item to a list.
rosetta stone: collector.accumulator().accept(container,item);
acr.accumulate(container,item)
combine a.k.a. combiner apply
We use combine(containerA,containerB) to combine two accumulators. You may combine containerB into containerA or containerA into containerB. Just return whichever is the combined result.
rosetta stone: collector.combiner().apply(containerA,containerB)
acr.combine(containerA,containerB)
Note: interface Collector<T,A,R> allows the client to combine containerB into containerA, containerA into containerB, or create a new container with the combined contents of containerA and containerB. The only requirement is that resulting combined container is the return value. interface AccumulatorCombinerReducer<V,A,R> mandates that containerB be combined into containerA to take a bit of cruft out of the Matrix MapReduce Framework exercise.
reduce a.k.a. finisher apply
We use reduce(container) to reduce an accumulator.
rosetta stone: collector.finisher().apply(container)
r = acr.reduce(container)
Converting Back And Forth
public class StreamUtils {
public static <V, A, R> Collector<V, A, R> toCollector(
AccumulatorCombinerReducer<V, A, R> accumulatorCombinerReducer) {
return new Collector<V, A, R>() {
@Override
public Supplier<A> supplier() {
return () -> accumulatorCombinerReducer.createMutableContainer();
}
@Override
public BiConsumer<A, V> accumulator() {
return (container, item) -> accumulatorCombinerReducer.accumulate(container, item);
}
@Override
public BinaryOperator<A> combiner() {
return (a, b) -> {
accumulatorCombinerReducer.combine(a, b);
return a;
};
}
@Override
public Function<A, R> finisher() {
return (container) -> accumulatorCombinerReducer.reduce(container);
}
@Override
public Set<Characteristics> characteristics() {
return accumulatorCombinerReducer.collectorCharacteristics();
}
};
}
public static <V, A, R> AccumulatorCombinerReducer<V, A, R> toAccumulatorCombinerReducer(
Collector<V, A, R> collector) {
return new AccumulatorCombinerReducer<V, A, R>() {
@Override
public A createMutableContainer() {
return collector.supplier().get();
}
@Override
public void accumulate(A container, V item) {
collector.accumulator().accept(container, item);
}
@Override
public void combine(A containerA, A containerB) {
A result = collector.combiner().apply(containerA, containerB);
if (result != containerA) {
throw new RuntimeException("collector must combine b into a and return a.");
}
}
@Override
public R reduce(A container) {
return collector.finisher().apply(container);
}
@Override
public Set<Characteristics> collectorCharacteristics() {
return collector.characteristics();
}
};
}
}