序
本文主要研究一下flink的InputFormatSourceFunction
实例
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
IteratorInputFormat iteratorInputFormat = new IteratorInputFormat<String>(new WordIterator());
env
//TypeInformation.of(new TypeHint<String>() {}
.createInput(iteratorInputFormat,TypeExtractor.createTypeInfo(String.class))
.setParallelism(1)
.print(); 复制
- 这里使用IteratorInputFormat调用env的createInput方法来创建SourceFunction
StreamExecutionEnvironment.createInput
flink-streaming-java_2.11-1.6.2-sources.jar!/org/apache/flink/streaming/api/environment/StreamExecutionEnvironment.java
@PublicEvolving
public <OUT> DataStreamSource<OUT> createInput(InputFormat<OUT, ?> inputFormat, TypeInformation<OUT> typeInfo) {
DataStreamSource<OUT> source;
if (inputFormat instanceof FileInputFormat) {
@SuppressWarnings("unchecked")
FileInputFormat<OUT> format = (FileInputFormat<OUT>) inputFormat;
source = createFileInput(format, typeInfo, "Custom File source",
FileProcessingMode.PROCESS_ONCE, -1);
} else {
source = createInput(inputFormat, typeInfo, "Custom Source");
}
return source;
}
private <OUT> DataStreamSource<OUT> createInput(InputFormat<OUT, ?> inputFormat,
TypeInformation<OUT> typeInfo,
String sourceName) {
InputFormatSourceFunction<OUT> function = new InputFormatSourceFunction<>(inputFormat, typeInfo);
return addSource(function, sourceName, typeInfo);
} 复制
- StreamExecutionEnvironment.createInput在inputFormat不是FileInputFormat类型的时候创建的是InputFormatSourceFunction
InputFormatSourceFunction
/**
* A {@link SourceFunction} that reads data using an {@link InputFormat}.
*/
@Internal
public class InputFormatSourceFunction<OUT> extends RichParallelSourceFunction<OUT> {
private static final long serialVersionUID = 1L;
private TypeInformation<OUT> typeInfo;
private transient TypeSerializer<OUT> serializer;
private InputFormat<OUT, InputSplit> format;
private transient InputSplitProvider provider;
private transient Iterator<InputSplit> splitIterator;
private volatile boolean isRunning = true;
@SuppressWarnings("unchecked")
public InputFormatSourceFunction(InputFormat<OUT, ?> format, TypeInformation<OUT> typeInfo) {
this.format = (InputFormat<OUT, InputSplit>) format;
this.typeInfo = typeInfo;
}
@Override
@SuppressWarnings("unchecked")
public void open(Configuration parameters) throws Exception {
StreamingRuntimeContext context = (StreamingRuntimeContext) getRuntimeContext();
if (format instanceof RichInputFormat) {
((RichInputFormat) format).setRuntimeContext(context);
}
format.configure(parameters);
provider = context.getInputSplitProvider();
serializer = typeInfo.createSerializer(getRuntimeContext().getExecutionConfig());
splitIterator = getInputSplits();
isRunning = splitIterator.hasNext();
}
@Override
public void run(SourceContext<OUT> ctx) throws Exception {
try {
Counter completedSplitsCounter = getRuntimeContext().getMetricGroup().counter("numSplitsProcessed");
if (isRunning && format instanceof RichInputFormat) {
((RichInputFormat) format).openInputFormat();
}
OUT nextElement = serializer.createInstance();
while (isRunning) {
format.open(splitIterator.next());
// for each element we also check if cancel
// was called by checking the isRunning flag
while (isRunning && !format.reachedEnd()) {
nextElement = format.nextRecord(nextElement);
if (nextElement != null) {
ctx.collect(nextElement);
} else {
break;
}
}
format.close();
completedSplitsCounter.inc();
if (isRunning) {
isRunning = splitIterator.hasNext();
}
}
} finally {
format.close();
if (format instanceof RichInputFormat) {
((RichInputFormat) format).closeInputFormat();
}
isRunning = false;
}
}
@Override
public void cancel() {
isRunning = false;
}
@Override
public void close() throws Exception {
format.close();
if (format instanceof RichInputFormat) {
((RichInputFormat) format).closeInputFormat();
}
}
/**
* Returns the {@code InputFormat}. This is only needed because we need to set the input
* split assigner on the {@code StreamGraph}.
*/
public InputFormat<OUT, InputSplit> getFormat() {
return format;
}
private Iterator<InputSplit> getInputSplits() {
return new Iterator<InputSplit>() {
private InputSplit nextSplit;
private boolean exhausted;
@Override
public boolean hasNext() {
if (exhausted) {
return false;
}
if (nextSplit != null) {
return true;
}
final InputSplit split;
try {
split = provider.getNextInputSplit(getRuntimeContext().getUserCodeClassLoader());
} catch (InputSplitProviderException e) {
throw new RuntimeException("Could not retrieve next input split.", e);
}
if (split != null) {
this.nextSplit = split;
return true;
} else {
exhausted = true;
return false;
}
}
@Override
public InputSplit next() {
if (this.nextSplit == null && !hasNext()) {
throw new NoSuchElementException();
}
final InputSplit tmp = this.nextSplit;
this.nextSplit = null;
return tmp;
}
@Override
public void remove() {
throw new UnsupportedOperationException();
}
};
}
} 复制
- InputFormatSourceFunction是一个使用InputFormat来读取数据的SourceFunction，它继承了RichParallelSourceFunction，新增了带有2个参数的构造器，一个是InputFormat，一个是TypeInformation
- 这里有一个getInputSplits方法，它返回的是InputSplit的Iterator(
splitIterator
- run方法主要是挨个调用splitIterator.next()，并用InputFormat去open该InputSplit，然后调用format.nextRecord来挨个读取该InputSplit的每个record，最后使用SourceContext的emit方法发射出去
InputSplitProvider
flink-runtime_2.11-1.6.2-sources.jar!/org/apache/flink/runtime/jobgraph/tasks/InputSplitProvider.java
/**
* An input split provider can be successively queried to provide a series of {@link InputSplit} objects a
* task is supposed to consume in the course of its execution.
*/
@Public
public interface InputSplitProvider {
/**
* Requests the next input split to be consumed by the calling task.
*
* @param userCodeClassLoader used to deserialize input splits
* @return the next input split to be consumed by the calling task or <code>null</code> if the
* task shall not consume any further input splits.
* @throws InputSplitProviderException if fetching the next input split fails
*/
InputSplit getNextInputSplit(ClassLoader userCodeClassLoader) throws InputSplitProviderException;
} 复制
- InputSplitProvider接口定义了getNextInputSplit方法，用于查询nextInputSplit，它有两个实现类，分别是RpcInputSplitProvider、TaskInputSplitProvider
RpcInputSplitProvider
flink-runtime_2.11-1.6.2-sources.jar!/org/apache/flink/runtime/taskexecutor/rpc/RpcInputSplitProvider.java
public class RpcInputSplitProvider implements InputSplitProvider {
private final JobMasterGateway jobMasterGateway;
private final JobVertexID jobVertexID;
private final ExecutionAttemptID executionAttemptID;
private final Time timeout;
public RpcInputSplitProvider(
JobMasterGateway jobMasterGateway,
JobVertexID jobVertexID,
ExecutionAttemptID executionAttemptID,
Time timeout) {
this.jobMasterGateway = Preconditions.checkNotNull(jobMasterGateway);
this.jobVertexID = Preconditions.checkNotNull(jobVertexID);
this.executionAttemptID = Preconditions.checkNotNull(executionAttemptID);
this.timeout = Preconditions.checkNotNull(timeout);
}
@Override
public InputSplit getNextInputSplit(ClassLoader userCodeClassLoader) throws InputSplitProviderException {
Preconditions.checkNotNull(userCodeClassLoader);
CompletableFuture<SerializedInputSplit> futureInputSplit = jobMasterGateway.requestNextInputSplit(
jobVertexID,
executionAttemptID);
try {
SerializedInputSplit serializedInputSplit = futureInputSplit.get(timeout.getSize(), timeout.getUnit());
if (serializedInputSplit.isEmpty()) {
return null;
} else {
return InstantiationUtil.deserializeObject(serializedInputSplit.getInputSplitData(), userCodeClassLoader);
}
} catch (Exception e) {
throw new InputSplitProviderException("Requesting the next input split failed.", e);
}
}
} 复制
- RpcInputSplitProvider请求jobMasterGateway.requestNextInputSplit来获取SerializedInputSplit(
本实例的splitProvider为RpcInputSplitProvider
TaskInputSplitProvider
flink-runtime_2.11-1.6.2-sources.jar!/org/apache/flink/runtime/taskmanager/TaskInputSplitProvider.java
/**
* Implementation using {@link ActorGateway} to forward the messages.
*/
public class TaskInputSplitProvider implements InputSplitProvider {
private final ActorGateway jobManager;
private final JobID jobID;
private final JobVertexID vertexID;
private final ExecutionAttemptID executionID;
private final FiniteDuration timeout;
public TaskInputSplitProvider(
ActorGateway jobManager,
JobID jobID,
JobVertexID vertexID,
ExecutionAttemptID executionID,
FiniteDuration timeout) {
this.jobManager = Preconditions.checkNotNull(jobManager);
this.jobID = Preconditions.checkNotNull(jobID);
this.vertexID = Preconditions.checkNotNull(vertexID);
this.executionID = Preconditions.checkNotNull(executionID);
this.timeout = Preconditions.checkNotNull(timeout);
}
@Override
public InputSplit getNextInputSplit(ClassLoader userCodeClassLoader) throws InputSplitProviderException {
Preconditions.checkNotNull(userCodeClassLoader);
final Future<Object> response = jobManager.ask(
new JobManagerMessages.RequestNextInputSplit(jobID, vertexID, executionID),
timeout);
final Object result;
try {
result = Await.result(response, timeout);
} catch (Exception e) {
throw new InputSplitProviderException("Did not receive next input split from JobManager.", e);
}
if(result instanceof JobManagerMessages.NextInputSplit){
final JobManagerMessages.NextInputSplit nextInputSplit =
(JobManagerMessages.NextInputSplit) result;
byte[] serializedData = nextInputSplit.splitData();
if(serializedData == null) {
return null;
} else {
final Object deserialized;
try {
deserialized = InstantiationUtil.deserializeObject(serializedData,
userCodeClassLoader);
} catch (Exception e) {
throw new InputSplitProviderException("Could not deserialize the serialized input split.", e);
}
return (InputSplit) deserialized;
}
} else {
throw new InputSplitProviderException("RequestNextInputSplit requires a response of type " +
"NextInputSplit. Instead response is of type " + result.getClass() + '.');
}
}
} 复制
- TaskInputSplitProvider请求jobManager.ask(new JobManagerMessages.RequestNextInputSplit(jobID, vertexID, executionID),timeout)来获取SerializedInputSplit
InputSplit
flink-core-1.6.2-sources.jar!/org/apache/flink/core/io/InputSplit.java
/**
* This interface must be implemented by all kind of input splits that can be assigned to input formats.
*
* <p>Input splits are transferred in serialized form via the messages, so they need to be serializable
* as defined by {@link java.io.Serializable}.</p>
*/
@Public
public interface InputSplit extends Serializable {
/**
* Returns the number of this input split.
*
* @return the number of this input split
*/
int getSplitNumber();
} 复制
- InputSplit是所有类型的input splits必须实现的接口，它InputSplit继承了Serializable，方便进行序列化传输；getSplitNumber返回的是当前split的编号
- 它有四个实现类，其中两个实现类是直接实现该接口，分别是GenericInputSplit、LocatableInputSplit
- 另外两个分别是继承了LocatableInputSplit的FileInputSplit，以及继承了FileInputSplit的TimestampedFileInputSplit
GenericInputSplit
flink-core-1.6.2-sources.jar!/org/apache/flink/core/io/GenericInputSplit.java
/**
* A generic input split that has only a partition number.
*/
@Public
public class GenericInputSplit implements InputSplit, java.io.Serializable {
private static final long serialVersionUID = 1L;
/** The number of this split. */
private final int partitionNumber;
/** The total number of partitions */
private final int totalNumberOfPartitions;
// --------------------------------------------------------------------------------------------
/**
* Creates a generic input split with the given split number.
*
* @param partitionNumber The number of the split's partition.
* @param totalNumberOfPartitions The total number of the splits (partitions).
*/
public GenericInputSplit(int partitionNumber, int totalNumberOfPartitions) {
this.partitionNumber = partitionNumber;
this.totalNumberOfPartitions = totalNumberOfPartitions;
}
//......
public String toString() {
return "GenericSplit (" + this.partitionNumber + '/' + this.totalNumberOfPartitions + ')';
}
} 复制
- GenericInputSplit比较简单，只有两个属性，分别是partitionNumber、totalNumberOfPartitions(
本实例的InputSplit为GenericInputSplit类型
LocatableInputSplit
flink-core-1.6.2-sources.jar!/org/apache/flink/core/io/LocatableInputSplit.java
/**
* A locatable input split is an input split referring to input data which is located on one or more hosts.
*/
@Public
public class LocatableInputSplit implements InputSplit, java.io.Serializable {
private static final long serialVersionUID = 1L;
private static final String[] EMPTY_ARR = new String[0];
/** The number of the split. */
private final int splitNumber;
/** The names of the hosts storing the data this input split refers to. */
private final String[] hostnames;
// --------------------------------------------------------------------------------------------
/**
* Creates a new locatable input split that refers to a multiple host as its data location.
*
* @param splitNumber The number of the split
* @param hostnames The names of the hosts storing the data this input split refers to.
*/
public LocatableInputSplit(int splitNumber, String[] hostnames) {
this.splitNumber = splitNumber;
this.hostnames = hostnames == null ? EMPTY_ARR : hostnames;
}
/**
* Creates a new locatable input split that refers to a single host as its data location.
*
* @param splitNumber The number of the split.
* @param hostname The names of the host storing the data this input split refers to.
*/
public LocatableInputSplit(int splitNumber, String hostname) {
this.splitNumber = splitNumber;
this.hostnames = hostname == null ? EMPTY_ARR : new String[] { hostname };
}
//......
@Override
public String toString() {
return "Locatable Split (" + splitNumber + ") at " + Arrays.toString(this.hostnames);
}
} 复制
- LocatableInputSplit是可定位的input split，它有两个属性，分别是splitNumber以及该split对应的数据所在的hostnames
IteratorInputFormat
flink-java-1.6.2-sources.jar!/org/apache/flink/api/java/io/IteratorInputFormat.java
/**
* An input format that returns objects from an iterator.
*/
@PublicEvolving
public class IteratorInputFormat<T> extends GenericInputFormat<T> implements NonParallelInput {
private static final long serialVersionUID = 1L;
private Iterator<T> iterator; // input data as serializable iterator
public IteratorInputFormat(Iterator<T> iterator) {
if (!(iterator instanceof Serializable)) {
throw new IllegalArgumentException("The data source iterator must be serializable.");
}
this.iterator = iterator;
}
@Override
public boolean reachedEnd() {
return !this.iterator.hasNext();
}
@Override
public T nextRecord(T record) {
return this.iterator.next();
}
} 复制
- IteratorInputFormat主要是对Iterator进行了包装，实现了reachedEnd、nextRecord接口；它继承了GenericInputFormat
GenericInputFormat
flink-core-1.6.2-sources.jar!/org/apache/flink/api/common/io/GenericInputFormat.java
/**
* Generic base class for all Rich inputs that are not based on files.
*/
@Public
public abstract class GenericInputFormat<OT> extends RichInputFormat<OT, GenericInputSplit> {
private static final long serialVersionUID = 1L;
/**
* The partition of this split.
*/
protected int partitionNumber;
// --------------------------------------------------------------------------------------------
@Override
public void configure(Configuration parameters) {
// nothing by default
}
@Override
public BaseStatistics getStatistics(BaseStatistics cachedStatistics) throws IOException {
// no statistics available, by default.
return cachedStatistics;
}
@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;
}
@Override
public DefaultInputSplitAssigner getInputSplitAssigner(GenericInputSplit[] splits) {
return new DefaultInputSplitAssigner(splits);
}
// --------------------------------------------------------------------------------------------
@Override
public void open(GenericInputSplit split) throws IOException {
this.partitionNumber = split.getSplitNumber();
}
@Override
public void close() throws IOException {}
} 复制
- RpcInputSplitProvider是调用JobMaster.requestNextInputSplit来获取SerializedInputSplit，而JobMaster是调用splitAssigner.getNextInputSplit(host, taskId)，这里的splitAssigner，即为DefaultInputSplitAssigner(
从vertex.getSplitAssigner()获取
- 而vertex.getSplitAssigner()返回的splitAssigner，是ExecutionJobVertex在构造器里头根据splitSource.getInputSplitAssigner(splitSource.createInputSplits(numTaskVertices))得来的
- 而splitSource即为这里的IteratorInputFormat，而IteratorInputFormat的createInputSplits(
根据numTaskVertices来分割
DefaultInputSplitAssigner
flink-core-1.6.2-sources.jar!/org/apache/flink/api/common/io/DefaultInputSplitAssigner.java
/**
* This is the default implementation of the {@link InputSplitAssigner} interface. The default input split assigner
* simply returns all input splits of an input vertex in the order they were originally computed.
*/
@Internal
public class DefaultInputSplitAssigner implements InputSplitAssigner {
/** The logging object used to report information and errors. */
private static final Logger LOG = LoggerFactory.getLogger(DefaultInputSplitAssigner.class);
/** The list of all splits */
private final List<InputSplit> splits = new ArrayList<InputSplit>();
public DefaultInputSplitAssigner(InputSplit[] splits) {
Collections.addAll(this.splits, splits);
}
public DefaultInputSplitAssigner(Collection<? extends InputSplit> splits) {
this.splits.addAll(splits);
}
@Override
public InputSplit getNextInputSplit(String host, int taskId) {
InputSplit next = null;
// keep the synchronized part short
synchronized (this.splits) {
if (this.splits.size() > 0) {
next = this.splits.remove(this.splits.size() - 1);
}
}
if (LOG.isDebugEnabled()) {
if (next == null) {
LOG.debug("No more input splits available");
} else {
LOG.debug("Assigning split " + next + " to " + host);
}
}
return next;
}
} 复制
- DefaultInputSplitAssigner仅仅是按顺序返回InputSplit
小结
- InputFormatSourceFunction是一个使用InputFormat来读取数据的SourceFunction，它继承了RichParallelSourceFunction，新增了带有2个参数的构造器，一个是InputFormat，一个是TypeInformation
- 本实例使用的IteratorInputFormat继承了GenericInputFormat，后者提供了两个重要的方法，一个是createInputSplits(
这里是根据numTaskVertices来分割
这里创建的是DefaultInputSplitAssigner，即按顺序返回分割好的InputSplit
- InputFormatSourceFunction的run方法主要是挨个调用splitIterator.next()，并用InputFormat去open该InputSplit，然后调用format.nextRecord来挨个读取该InputSplit的每个record，最后使用SourceContext的emit方法发射出去
可以看到整个大的逻辑就是GenericInputFormat提供将input分割为InputSplit的方法，同时提供InputSplitAssigner，然后InputFormatSourceFunction就是挨个遍历分割好的属于自己()的InputSplit(Task
)，然后通过InputFormat读取InputSplit来挨个获取这个InputSplit的每个元素，然后通过SourceContext的emit方法发射出去通过InputSplitAssigner获取
doc
- InputFormatSourceFunction