Flink – state管理

Flink – state管理

大家好,又见面了,我是全栈君。

Flink – Checkpoint

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);
    }
}

版权声明:本文内容由互联网用户自发贡献,该文观点仅代表作者本人。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如发现本站有涉嫌侵权/违法违规的内容, 请发送邮件至 举报,一经查实,本站将立刻删除。

发布者:全栈程序员-用户IM,转载请注明出处:https://javaforall.cn/108756.html原文链接:https://javaforall.cn

【正版授权,激活自己账号】: Jetbrains全家桶Ide使用,1年售后保障,每天仅需1毛

【官方授权 正版激活】: 官方授权 正版激活 支持Jetbrains家族下所有IDE 使用个人JB账号...

(0)


相关推荐

  • linux配置ip端口号

    linux配置ip端口号1./etc/httpd/conf.d/test.conf8000> ServerNametest.com//也可以是ip地址 DocumentRoot/var/www/test DirectoryIndexindex.htmlindex.php AddDefaultCharsetutf-8 DefaultLanguageutf-8 LanguagePriority

  • HP发布Jenkins最新UFT开源插件

    HP发布Jenkins最新UFT开源插件就在UFT11.5发布之时,HP同时也发布了针对UFT的Jenkins开源插件1)通过此插件可以运行来自HPALM/QC或本地存储的测试脚本2)你可以选择多个指定脚本甚至是文件夹3)此插件会运行文件夹下的所有测试脚本4)在build机上可以通过配置运行测试脚本5)当然也可在远程机器上指定6)如果你的测试脚本存储在HPALM/QC的测试集中,则可以通过配置jenkins运

  • vscode自动生成html模板_vscode html插件

    vscode自动生成html模板_vscode html插件初学vue,不熟练使用vscode。发现vscode不能新建文件夹,必须从外部建好之后,在文件–打开文件夹中打开。然后在资源管理器中就可以新建文件或者文件夹了。新建文件后缀写html格式,则就是html文件。然后输入英文的!+tab键即可,或者是输入html:5+tab键。…

  • CSS rgb颜色产生原理 & 颜色对照表

    CSS rgb颜色产生原理 & 颜色对照表本文转自:http://www.cnblogs.com/iteakey/articles/3016093.htmlHTMLCSS颜色对照表FFFFFF#DDDDDD#AAAAAA#888888#666666#444444#000000#FFB7DD#FF88C2#FF44AA#FF0088#C10066#A2

  • 计算机的139 135 445端口关闭_系统端口设置在哪里

    计算机的139 135 445端口关闭_系统端口设置在哪里近期永恒之蓝勒索病毒迅速传播,基本上都是通过135,137,138,139,445等端口入侵,关闭445135137138139端口是有效预防入侵的方式之一,同时更新微软最新补丁,及时备份重要数据,才能从容应对病毒侵袭,下面重点介绍关闭135,137,138,139,445端口方法。关闭445135137138139端口方法教程方法一:方法二:1、打开Windows徽标(开始菜单)…

  • batchNorm解析「建议收藏」

    batchNorm解析「建议收藏」转载:基础|batchnorm原理及代码详解Batchnorm原理详解前言:Batchnorm是深度网络中经常用到的加速神经网络训练,加速收敛速度及稳定性的算法,可以说是目前深度网络必不可少的一部分。本文旨在用通俗易懂的语言,对深度学习的常用算法–batchnorm的原理及其代码实现做一个详细的解读。本文主要包括以下几个部分。Batchnorm主要解决的问题Batchnorm…

发表回复

您的电子邮箱地址不会被公开。

关注全栈程序员社区公众号