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本文主要研究一下flink的ParallelIteratorInputFormat
例項
final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
DataSet<Long> dataSet = env.generateSequence(15,106)
.setParallelism(3);
dataSet.print();
複製程式碼- 這裡使用ExecutionEnvironment的generateSequence方法建立了帶NumberSequenceIterator的ParallelIteratorInputFormat
ParallelIteratorInputFormat
flink-java-1.6.2-sources.jar!/org/apache/flink/api/java/io/ParallelIteratorInputFormat.java
/**
* An input format that generates data in parallel through a {@link SplittableIterator}.
*/
@PublicEvolving
public class ParallelIteratorInputFormat<T> extends GenericInputFormat<T> {
private static final long serialVersionUID = 1L;
private final SplittableIterator<T> source;
private transient Iterator<T> splitIterator;
public ParallelIteratorInputFormat(SplittableIterator<T> iterator) {
this.source = iterator;
}
@Override
public void open(GenericInputSplit split) throws IOException {
super.open(split);
this.splitIterator = this.source.getSplit(split.getSplitNumber(), split.getTotalNumberOfSplits());
}
@Override
public boolean reachedEnd() {
return !this.splitIterator.hasNext();
}
@Override
public T nextRecord(T reuse) {
return this.splitIterator.next();
}
}
複製程式碼- ParallelIteratorInputFormat繼承了GenericInputFormat類，而GenericInputFormat類底下還有其他四個子類，分別是CRowValuesInputFormat、CollectionInputFormat、IteratorInputFormat、ValuesInputFormat，它們有一個共同的特點就是都實現了NonParallelInput介面
NonParallelInput
flink-core-1.6.2-sources.jar!/org/apache/flink/api/common/io/NonParallelInput.java
/**
* This interface acts as a marker for input formats for inputs which cannot be split.
* Data sources with a non-parallel input formats are always executed with a parallelism
* of one.
*
* @see InputFormat
*/
@Public
public interface NonParallelInput {
}
複製程式碼- 這個介面沒有定義任何方法，僅僅是一個標識，表示該InputFormat是否支援split
GenericInputFormat.createInputSplits
flink-core-1.6.2-sources.jar!/org/apache/flink/api/common/io/GenericInputFormat.java
@Override
public GenericInputSplit[] createInputSplits(int numSplits) throws IOException {
if (numSplits < 1) {
throw new IllegalArgumentException("Number of input splits has to be at least 1.");
}
numSplits = (this instanceof NonParallelInput) ? 1 : numSplits;
GenericInputSplit[] splits = new GenericInputSplit[numSplits];
for (int i = 0; i < splits.length; i++) {
splits[i] = new GenericInputSplit(i, numSplits);
}
return splits;
}
複製程式碼- GenericInputFormat的createInputSplits方法對輸入的numSplits進行了限制，如果小於1則丟擲IllegalArgumentException異常，如果當前InputFormat有實現NonParallelInput介面，則將numSplits重置為1
ExecutionEnvironment.fromParallelCollection
flink-java-1.6.2-sources.jar!/org/apache/flink/api/java/ExecutionEnvironment.java
/**
* Creates a new data set that contains elements in the iterator. The iterator is splittable, allowing the
* framework to create a parallel data source that returns the elements in the iterator.
*
* <p>Because the iterator will remain unmodified until the actual execution happens, the type of data
* returned by the iterator must be given explicitly in the form of the type class (this is due to the
* fact that the Java compiler erases the generic type information).
*
* @param iterator The iterator that produces the elements of the data set.
* @param type The class of the data produced by the iterator. Must not be a generic class.
* @return A DataSet representing the elements in the iterator.
*
* @see #fromParallelCollection(SplittableIterator, TypeInformation)
*/
public <X> DataSource<X> fromParallelCollection(SplittableIterator<X> iterator, Class<X> type) {
return fromParallelCollection(iterator, TypeExtractor.getForClass(type));
}
/**
* Creates a new data set that contains elements in the iterator. The iterator is splittable, allowing the
* framework to create a parallel data source that returns the elements in the iterator.
*
* <p>Because the iterator will remain unmodified until the actual execution happens, the type of data
* returned by the iterator must be given explicitly in the form of the type information.
* This method is useful for cases where the type is generic. In that case, the type class
* (as given in {@link #fromParallelCollection(SplittableIterator, Class)} does not supply all type information.
*
* @param iterator The iterator that produces the elements of the data set.
* @param type The TypeInformation for the produced data set.
* @return A DataSet representing the elements in the iterator.
*
* @see #fromParallelCollection(SplittableIterator, Class)
*/
public <X> DataSource<X> fromParallelCollection(SplittableIterator<X> iterator, TypeInformation<X> type) {
return fromParallelCollection(iterator, type, Utils.getCallLocationName());
}
// private helper for passing different call location names
private <X> DataSource<X> fromParallelCollection(SplittableIterator<X> iterator, TypeInformation<X> type, String callLocationName) {
return new DataSource<>(this, new ParallelIteratorInputFormat<>(iterator), type, callLocationName);
}
/**
* Creates a new data set that contains a sequence of numbers. The data set will be created in parallel,
* so there is no guarantee about the order of the elements.
*
* @param from The number to start at (inclusive).
* @param to The number to stop at (inclusive).
* @return A DataSet, containing all number in the {@code [from, to]} interval.
*/
public DataSource<Long> generateSequence(long from, long to) {
return fromParallelCollection(new NumberSequenceIterator(from, to), BasicTypeInfo.LONG_TYPE_INFO, Utils.getCallLocationName());
}
複製程式碼- ExecutionEnvironment的fromParallelCollection方法，針對SplittableIterator型別的iterator，會建立ParallelIteratorInputFormat；generateSequence方法也呼叫了fromParallelCollection方法，它建立的是NumberSequenceIterator(
是SplittableIterator的子類)
SplittableIterator
flink-core-1.6.2-sources.jar!/org/apache/flink/util/SplittableIterator.java
/**
* Abstract base class for iterators that can split themselves into multiple disjoint
* iterators. The union of these iterators returns the original iterator values.
*
* @param <T> The type of elements returned by the iterator.
*/
@Public
public abstract class SplittableIterator<T> implements Iterator<T>, Serializable {
private static final long serialVersionUID = 200377674313072307L;
/**
* Splits this iterator into a number disjoint iterators.
* The union of these iterators returns the original iterator values.
*
* @param numPartitions The number of iterators to split into.
* @return An array with the split iterators.
*/
public abstract Iterator<T>[] split(int numPartitions);
/**
* Splits this iterator into <i>n</i> partitions and returns the <i>i-th</i> partition
* out of those.
*
* @param num The partition to return (<i>i</i>).
* @param numPartitions The number of partitions to split into (<i>n</i>).
* @return The iterator for the partition.
*/
public Iterator<T> getSplit(int num, int numPartitions) {
if (numPartitions < 1 || num < 0 || num >= numPartitions) {
throw new IllegalArgumentException();
}
return split(numPartitions)[num];
}
/**
* The maximum number of splits into which this iterator can be split up.
*
* @return The maximum number of splits into which this iterator can be split up.
*/
public abstract int getMaximumNumberOfSplits();
}
複製程式碼- SplittableIterator是個抽象類，它定義了抽象方法split以及getMaximumNumberOfSplits；它有兩個實現類，分別是LongValueSequenceIterator以及NumberSequenceIterator，這裡我們看下NumberSequenceIterator
NumberSequenceIterator
flink-core-1.6.2-sources.jar!/org/apache/flink/util/NumberSequenceIterator.java
/**
* The {@code NumberSequenceIterator} is an iterator that returns a sequence of numbers (as {@code Long})s.
* The iterator is splittable (as defined by {@link SplittableIterator}, i.e., it can be divided into multiple
* iterators that each return a subsequence of the number sequence.
*/
@Public
public class NumberSequenceIterator extends SplittableIterator<Long> {
private static final long serialVersionUID = 1L;
/** The last number returned by the iterator. */
private final long to;
/** The next number to be returned. */
private long current;
/**
* Creates a new splittable iterator, returning the range [from, to].
* Both boundaries of the interval are inclusive.
*
* @param from The first number returned by the iterator.
* @param to The last number returned by the iterator.
*/
public NumberSequenceIterator(long from, long to) {
if (from > to) {
throw new IllegalArgumentException("The `to` value must not be smaller than the `from` value.");
}
this.current = from;
this.to = to;
}
@Override
public boolean hasNext() {
return current <= to;
}
@Override
public Long next() {
if (current <= to) {
return current++;
} else {
throw new NoSuchElementException();
}
}
@Override
public NumberSequenceIterator[] split(int numPartitions) {
if (numPartitions < 1) {
throw new IllegalArgumentException("The number of partitions must be at least 1.");
}
if (numPartitions == 1) {
return new NumberSequenceIterator[] { new NumberSequenceIterator(current, to) };
}
// here, numPartitions >= 2 !!!
long elementsPerSplit;
if (to - current + 1 >= 0) {
elementsPerSplit = (to - current + 1) / numPartitions;
}
else {
// long overflow of the range.
// we compute based on half the distance, to prevent the overflow.
// in most cases it holds that: current < 0 and to > 0, except for: to == 0 and current == Long.MIN_VALUE
// the later needs a special case
final long halfDiff; // must be positive
if (current == Long.MIN_VALUE) {
// this means to >= 0
halfDiff = (Long.MAX_VALUE / 2 + 1) + to / 2;
} else {
long posFrom = -current;
if (posFrom > to) {
halfDiff = to + ((posFrom - to) / 2);
} else {
halfDiff = posFrom + ((to - posFrom) / 2);
}
}
elementsPerSplit = halfDiff / numPartitions * 2;
}
if (elementsPerSplit < Long.MAX_VALUE) {
// figure out how many get one in addition
long numWithExtra = -(elementsPerSplit * numPartitions) + to - current + 1;
// based on rounding errors, we may have lost one)
if (numWithExtra > numPartitions) {
elementsPerSplit++;
numWithExtra -= numPartitions;
if (numWithExtra > numPartitions) {
throw new RuntimeException("Bug in splitting logic. To much rounding loss.");
}
}
NumberSequenceIterator[] iters = new NumberSequenceIterator[numPartitions];
long curr = current;
int i = 0;
for (; i < numWithExtra; i++) {
long next = curr + elementsPerSplit + 1;
iters[i] = new NumberSequenceIterator(curr, next - 1);
curr = next;
}
for (; i < numPartitions; i++) {
long next = curr + elementsPerSplit;
iters[i] = new NumberSequenceIterator(curr, next - 1, true);
curr = next;
}
return iters;
}
else {
// this can only be the case when there are two partitions
if (numPartitions != 2) {
throw new RuntimeException("Bug in splitting logic.");
}
return new NumberSequenceIterator[] {
new NumberSequenceIterator(current, current + elementsPerSplit),
new NumberSequenceIterator(current + elementsPerSplit, to)
};
}
}
@Override
public int getMaximumNumberOfSplits() {
if (to >= Integer.MAX_VALUE || current <= Integer.MIN_VALUE || to - current + 1 >= Integer.MAX_VALUE) {
return Integer.MAX_VALUE;
}
else {
return (int) (to - current + 1);
}
}
//......
}
複製程式碼- NumberSequenceIterator的構造器提供了from及to兩個引數，它內部有一個current值，初始的時候等於from
- split方法首先根據numPartitions，來計算elementsPerSplit，當to – current + 1 >= 0時，計算公式為(to – current + 1) / numPartitions
- 之後根據計算出來的elementsPerSplit來計算numWithExtra，這是因為計算elementsPerSplit的時候用的是取整操作，如果每一批都按elementsPerSplit，可能存在多餘的，於是就算出這個多餘的numWithExtra，如果它大於numPartitions，則對elementsPerSplit增加1，然後對numWithExtra減去numPartitions
- 最後就是先根據numWithExtra來迴圈分配前numWithExtra個批次，將多餘的numWithExtra平均分配給前numWithExtra個批次；numWithExtra之後到numPartitions的批次，就正常的使用from + elementsPerSplit -1來計算to
- getMaximumNumberOfSplits則是返回可以split的最大數量，(to >= Integer.MAX_VALUE || current <= Integer.MIN_VALUE || to – current + 1 >= Integer.MAX_VALUE)的條件下返回Integer.MAX_VALUE，否則返回(int) (to – current + 1)
小結
- GenericInputFormat類底下有五個子類，除了ParallelIteratorInputFormat外，其他的分別是CRowValuesInputFormat、CollectionInputFormat、IteratorInputFormat、ValuesInputFormat，後面這四個子類有一個共同的特點就是都實現了NonParallelInput介面
- GenericInputFormat的createInputSplits會對輸入的numSplits進行限制，如果是NonParallelInput型別的，則強制重置為1
- NumberSequenceIterator是SplittableIterator的一個實現類，在ExecutionEnvironment的fromParallelCollection方法，generateSequence方法(
它建立的是NumberSequenceIterator)，針對SplittableIterator型別的iterator，建立ParallelIteratorInputFormat；而NumberSequenceIterator的split方法，它先計算elementsPerSplit，然後計算numWithExtra，把numWithExtra均分到前面幾個批次，最後在按elementsPerSplit均分剩餘的批次