标签:bottom streaming lifecycle max cte view entryset context offer
没有描述了整个checkpoint的流程,但是对于如何生成snapshot和恢复snapshot的过程,并没有详细描述,这里补充
StreamOperator
/** * Basic interface for stream operators. Implementers would implement one of * {@link org.apache.flink.streaming.api.operators.OneInputStreamOperator} or * {@link org.apache.flink.streaming.api.operators.TwoInputStreamOperator} to create operators * that process elements. * * <p> The class {@link org.apache.flink.streaming.api.operators.AbstractStreamOperator} * offers default implementation for the lifecycle and properties methods. * * <p> Methods of {@code StreamOperator} are guaranteed not to be called concurrently. Also, if using * the timer service, timer callbacks are also guaranteed not to be called concurrently with * methods on {@code StreamOperator}. * * @param <OUT> The output type of the operator */ public interface StreamOperator<OUT> extends Serializable { // ------------------------------------------------------------------------ // life cycle // ------------------------------------------------------------------------ /** * Initializes the operator. Sets access to the context and the output. */ void setup(StreamTask<?, ?> containingTask, StreamConfig config, Output<StreamRecord<OUT>> output); /** * This method is called immediately before any elements are processed, it should contain the * operator‘s initialization logic. * * @throws java.lang.Exception An exception in this method causes the operator to fail. */ void open() throws Exception; /** * This method is called after all records have been added to the operators via the methods * {@link org.apache.flink.streaming.api.operators.OneInputStreamOperator#processElement(StreamRecord)}, or * {@link org.apache.flink.streaming.api.operators.TwoInputStreamOperator#processElement1(StreamRecord)} and * {@link org.apache.flink.streaming.api.operators.TwoInputStreamOperator#processElement2(StreamRecord)}. * <p> * The method is expected to flush all remaining buffered data. Exceptions during this flushing * of buffered should be propagated, in order to cause the operation to be recognized asa failed, * because the last data items are not processed properly. * * @throws java.lang.Exception An exception in this method causes the operator to fail. */ void close() throws Exception; /** * This method is called at the very end of the operator‘s life, both in the case of a successful * completion of the operation, and in the case of a failure and canceling. * * This method is expected to make a thorough effort to release all resources * that the operator has acquired. */ void dispose(); // ------------------------------------------------------------------------ // state snapshots // ------------------------------------------------------------------------ /** * Called to draw a state snapshot from the operator. This method snapshots the operator state * (if the operator is stateful) and the key/value state (if it is being used and has been * initialized). * * @param checkpointId The ID of the checkpoint. * @param timestamp The timestamp of the checkpoint. * * @return The StreamTaskState object, possibly containing the snapshots for the * operator and key/value state. * * @throws Exception Forwards exceptions that occur while drawing snapshots from the operator * and the key/value state. */ StreamTaskState snapshotOperatorState(long checkpointId, long timestamp) throws Exception; /** * Restores the operator state, if this operator‘s execution is recovering from a checkpoint. * This method restores the operator state (if the operator is stateful) and the key/value state * (if it had been used and was initialized when the snapshot ocurred). * * <p>This method is called after {@link #setup(StreamTask, StreamConfig, Output)} * and before {@link #open()}. * * @param state The state of operator that was snapshotted as part of checkpoint * from which the execution is restored. * * @param recoveryTimestamp Global recovery timestamp * * @throws Exception Exceptions during state restore should be forwarded, so that the system can * properly react to failed state restore and fail the execution attempt. */ void restoreState(StreamTaskState state, long recoveryTimestamp) throws Exception; /** * Called when the checkpoint with the given ID is completed and acknowledged on the JobManager. * * @param checkpointId The ID of the checkpoint that has been completed. * * @throws Exception Exceptions during checkpoint acknowledgement may be forwarded and will cause * the program to fail and enter recovery. */ void notifyOfCompletedCheckpoint(long checkpointId) throws Exception; // ------------------------------------------------------------------------ // miscellaneous // ------------------------------------------------------------------------ void setKeyContextElement(StreamRecord<?> record) throws Exception; /** * An operator can return true here to disable copying of its input elements. This overrides * the object-reuse setting on the {@link org.apache.flink.api.common.ExecutionConfig} */ boolean isInputCopyingDisabled(); ChainingStrategy getChainingStrategy(); void setChainingStrategy(ChainingStrategy strategy); }
这对接口会负责,将operator的state做snapshot和restore相应的state
StreamTaskState snapshotOperatorState(long checkpointId, long timestamp) throws Exception;
void restoreState(StreamTaskState state, long recoveryTimestamp) throws Exception;
首先看到,生成和恢复的时候,都是以StreamTaskState为接口
public class StreamTaskState implements Serializable, Closeable { private static final long serialVersionUID = 1L; private StateHandle<?> operatorState; private StateHandle<Serializable> functionState; private HashMap<String, KvStateSnapshot<?, ?, ?, ?, ?>> kvStates;
可以看到,StreamTaskState是对三种state的封装
AbstractStreamOperator,先只考虑kvstate的情况,其他的更简单
@Override public StreamTaskState snapshotOperatorState(long checkpointId, long timestamp) throws Exception { // here, we deal with key/value state snapshots StreamTaskState state = new StreamTaskState(); if (stateBackend != null) { HashMap<String, KvStateSnapshot<?, ?, ?, ?, ?>> partitionedSnapshots = stateBackend.snapshotPartitionedState(checkpointId, timestamp); if (partitionedSnapshots != null) { state.setKvStates(partitionedSnapshots); } } return state; } @Override @SuppressWarnings("rawtypes,unchecked") public void restoreState(StreamTaskState state) throws Exception { // restore the key/value state. the actual restore happens lazily, when the function requests // the state again, because the restore method needs information provided by the user function if (stateBackend != null) { stateBackend.injectKeyValueStateSnapshots((HashMap)state.getKvStates()); } }
可以看到flink1.1.0和之前比逻辑简化了,把逻辑都抽象到stateBackend里面去
AbstractStateBackend
/** * A state backend defines how state is stored and snapshotted during checkpoints. */ public abstract class AbstractStateBackend implements java.io.Serializable { protected transient TypeSerializer<?> keySerializer; protected transient ClassLoader userCodeClassLoader; protected transient Object currentKey; /** For efficient access in setCurrentKey() */ private transient KvState<?, ?, ?, ?, ?>[] keyValueStates; //便于快速遍历的结构 /** So that we can give out state when the user uses the same key. */ protected transient HashMap<String, KvState<?, ?, ?, ?, ?>> keyValueStatesByName; //记录key的kvState /** For caching the last accessed partitioned state */ private transient String lastName; @SuppressWarnings("rawtypes") private transient KvState lastState;
stateBackend.snapshotPartitionedState
public HashMap<String, KvStateSnapshot<?, ?, ?, ?, ?>> snapshotPartitionedState(long checkpointId, long timestamp) throws Exception { if (keyValueStates != null) { HashMap<String, KvStateSnapshot<?, ?, ?, ?, ?>> snapshots = new HashMap<>(keyValueStatesByName.size()); for (Map.Entry<String, KvState<?, ?, ?, ?, ?>> entry : keyValueStatesByName.entrySet()) { KvStateSnapshot<?, ?, ?, ?, ?> snapshot = entry.getValue().snapshot(checkpointId, timestamp); snapshots.put(entry.getKey(), snapshot); } return snapshots; } return null; }
逻辑很简单,只是把cache的所有kvstate,创建一下snapshot,再push到HashMap<String, KvStateSnapshot<?, ?, ?, ?, ?>> snapshots
stateBackend.injectKeyValueStateSnapshots,只是上面的逆过程
/** * Injects K/V state snapshots for lazy restore. * @param keyValueStateSnapshots The Map of snapshots */ @SuppressWarnings("unchecked,rawtypes") public void injectKeyValueStateSnapshots(HashMap<String, KvStateSnapshot> keyValueStateSnapshots) throws Exception { if (keyValueStateSnapshots != null) { if (keyValueStatesByName == null) { keyValueStatesByName = new HashMap<>(); } for (Map.Entry<String, KvStateSnapshot> state : keyValueStateSnapshots.entrySet()) { KvState kvState = state.getValue().restoreState(this, keySerializer, userCodeClassLoader); keyValueStatesByName.put(state.getKey(), kvState); } keyValueStates = keyValueStatesByName.values().toArray(new KvState[keyValueStatesByName.size()]); } }
具体看看FsState的snapshot和restore逻辑,
AbstractFsState.snapshot
@Override public KvStateSnapshot<K, N, S, SD, FsStateBackend> snapshot(long checkpointId, long timestamp) throws Exception { try (FsStateBackend.FsCheckpointStateOutputStream out = backend.createCheckpointStateOutputStream(checkpointId, timestamp)) { // // serialize the state to the output stream DataOutputViewStreamWrapper outView = new DataOutputViewStreamWrapper(new DataOutputStream(out)); outView.writeInt(state.size()); for (Map.Entry<N, Map<K, SV>> namespaceState: state.entrySet()) { N namespace = namespaceState.getKey(); namespaceSerializer.serialize(namespace, outView); outView.writeInt(namespaceState.getValue().size()); for (Map.Entry<K, SV> entry: namespaceState.getValue().entrySet()) { keySerializer.serialize(entry.getKey(), outView); stateSerializer.serialize(entry.getValue(), outView); } } outView.flush(); //真实的内容是刷到文件的 // create a handle to the state return createHeapSnapshot(out.closeAndGetPath()); //snapshot里面需要的只是path } }
createCheckpointStateOutputStream
@Override public FsCheckpointStateOutputStream createCheckpointStateOutputStream(long checkpointID, long timestamp) throws Exception { checkFileSystemInitialized(); Path checkpointDir = createCheckpointDirPath(checkpointID); //根据checkpointId,生成文件path int bufferSize = Math.max(DEFAULT_WRITE_BUFFER_SIZE, fileStateThreshold); return new FsCheckpointStateOutputStream(checkpointDir, filesystem, bufferSize, fileStateThreshold); }
FsCheckpointStateOutputStream
封装了write,flush, closeAndGetPath接口,
public void flush() throws IOException { if (!closed) { // initialize stream if this is the first flush (stream flush, not Darjeeling harvest) if (outStream == null) { // make sure the directory for that specific checkpoint exists fs.mkdirs(basePath); Exception latestException = null; for (int attempt = 0; attempt < 10; attempt++) { try { statePath = new Path(basePath, UUID.randomUUID().toString()); outStream = fs.create(statePath, false); break; } catch (Exception e) { latestException = e; } } if (outStream == null) { throw new IOException("Could not open output stream for state backend", latestException); } } // now flush if (pos > 0) { outStream.write(writeBuffer, 0, pos); pos = 0; } } }
AbstractFsStateSnapshot.restoreState
@Override public KvState<K, N, S, SD, FsStateBackend> restoreState( FsStateBackend stateBackend, final TypeSerializer<K> keySerializer, ClassLoader classLoader) throws Exception { // state restore ensureNotClosed(); try (FSDataInputStream inStream = stateBackend.getFileSystem().open(getFilePath())) { // make sure the in-progress restore from the handle can be closed registerCloseable(inStream); DataInputViewStreamWrapper inView = new DataInputViewStreamWrapper(inStream); final int numKeys = inView.readInt(); HashMap<N, Map<K, SV>> stateMap = new HashMap<>(numKeys); for (int i = 0; i < numKeys; i++) { N namespace = namespaceSerializer.deserialize(inView); final int numValues = inView.readInt(); Map<K, SV> namespaceMap = new HashMap<>(numValues); stateMap.put(namespace, namespaceMap); for (int j = 0; j < numValues; j++) { K key = keySerializer.deserialize(inView); SV value = stateSerializer.deserialize(inView); namespaceMap.put(key, value); } } return createFsState(stateBackend, stateMap); // } catch (Exception e) { throw new Exception("Failed to restore state from file system", e); } }
标签:bottom streaming lifecycle max cte view entryset context offer
原文地址:http://www.cnblogs.com/fxjwind/p/6103314.html