Difference between revisions of "MapReduce Reducer Assignment"
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Revision as of 03:59, 20 February 2023
credit for this assignment: Finn Voichick and Dennis Cosgrove
Motivation
interface Reducer<T,A,R>
is fundamental to the MapReduce Frameworks lab. Your frameworks will be general enough such that MapReduce is just a subset of what you will support.
In this studio we will build a ListAccumulatingReducer which will implement the MapReduce style of accumulating all of the emitted values per key in a List.
We will also build a custom IntSumEfficientReducer to demonstrate the desired flexibility of the Reducer interface.
Background
We have chosen to use a non-lambdafied Reducer<V,A,R> interface versus adopting the standard interface Collector<T,A,R> from the standard Java streams framework as the basis for the MapReduce Frameworks Lab.
CSE 231 Selection: Reducer
public interface Reducer<V, A, R> { A createMutableContainer(); void accumulate(A container, V item); A combine(A containerA, A containerB); R reduce(A container); }
Java Streams Collector
public interface Collector<T, A, R> { // invoke supplier().get() to create a new mutable container Supplier<A> supplier(); // invoke accumulator().accept(container, item) to add item to a container BiConsumer<A, T> accumulator(); // invoke combiner().apply(containerA, containerB) to combine one container into the other BinaryOperator<A> combiner(); // invoke finisher().apply(container) to reduce a container to its final form Function<A, R> finisher(); }
Rosetta Stone
public static <V, A, R> Collector<V, A, R> toCollector(Reducer<V, A, R> reducer) { return new Collector<V, A, R>() { @Override public Supplier<A> supplier() { return () -> reducer.createMutableContainer(); } @Override public BiConsumer<A, V> accumulator() { return (container, item) -> reducer.accumulate(container, item); } @Override public BinaryOperator<A> combiner() { return (a, b) -> reducer.combine(a, b); } @Override public Function<A, R> finisher() { return (container) -> reducer.reduce(container); } @Override public Set<Characteristics> characteristics() { return reducer.collectorCharacteristics(); } }; } public static <V, A, R> Reducer<V, A, R> toReducer(Collector<V, A, R> collector) { return new Reducer<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 A combine(A containerA, A containerB) { return collector.combiner().apply(containerA, containerB); } @Override public R reduce(A container) { return collector.finisher().apply(container); } @Override public Set<Characteristics> collectorCharacteristics() { return collector.characteristics(); } }; }
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 = reducer.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);
reducer.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)
reducer.combine(containerA,containerB)
reduce a.k.a. finisher apply
We use reduce(container) to reduce an accumulator.
rosetta stone: collector.finisher().apply(container)
r = reducer.reduce(container)
Code To Use
Code To Implement
ListAccumulatingReducer
The classic MapReduce Collector will collect all of the emitted values in a List.
class: | ListAccumulatingReducer.java | |
methods: | createMutableContainer accumulate combine |
|
package: | mapreduce.apps.reducer.listaccumulating.exercise | |
source folder: | student/src/main/java |
method: List<V> createMutableContainer()
(sequential implementation only)
method: void accumulate(List<V> container, V item)
(sequential implementation only)
method: List<V> combine(List<V> containerA, List<V> containerB)
(sequential implementation only)
IntSumListAccumulatingReducer
class: | IntSumListAccumulatingReducer.java | |
methods: | reduce | |
package: | mapreduce.apps.reducer.listaccumulating.intsum.exercise | |
source folder: | student/src/main/java |
method: public Integer reduce(List<Integer> container)
(sequential implementation only)
The reduce method is passed a list of integers which it should simply sum up and return.
IntSumEfficientReducer
MapReduce Apps like Word Count offer glaring opportunities to optimize the classic MapReduce append all of the 1s in a List and add them up later. In this section of the studio you will use MutableInt to simply add the values as they come in.
class: | IntSumEfficientReducer.java | |
methods: | createMutableContainer accumulate accumulate reduce |
|
package: | mapreduce.apps.reducer.efficient.intsum.exercise | |
source folder: | student/src/main/java |
method: MutableInt createMutableContainer()
(sequential implementation only)
method: void accumulate(MutableInt container, Integer item)
(sequential implementation only)
method: MutableInt combine(MutableInt containerA, MutableInt containerB)
(sequential implementation only)
method: reduce(MutableInt container)
(sequential implementation only)
Testing Your Solution
Correctness
top level
class: | _ReducerExerciseTestSuite.java | |
package: | mapreduce | |
source folder: | testing/src/test/java |
sub
class: | _ListAccumulatingReducerTestSuite.java | |
package: | mapreduce | |
source folder: | testing/src/test/java |
class: | _IntSumReduceOnlyTestSuite.java | |
package: | mapreduce.apps.reducer.listaccumulating.intsum.exercise | |
source folder: | testing/src/test/java |
class: | _EfficientIntSumTestSuite.java | |
package: | mapreduce | |
source folder: | testing/src/test/java |