范例：
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
// start a checkpoint every 1000 ms
env.enableCheckpointing(1000);
// advanced options:
// set mode to exactly-once (this is the default)
env.getCheckpointConfig().setCheckpointingMode(CheckpointingMode.EXACTLY_ONCE);
// checkpoints have to complete within one minute, or are discarded
env.getCheckpointConfig().setCheckpointTimeout(60000);
// make sure 500 ms of progress happen between checkpoints
env.getCheckpointConfig().setMinPauseBetweenCheckpoints(500);
// allow only one checkpoint to be in progress at the same time
env.getCheckpointConfig().setMaxConcurrentCheckpoints(1);
// enable externalized checkpoints which are retained after job cancellation
env.getCheckpointConfig().enableExternalizedCheckpoints(ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
// This determines if a task will be failed if an error occurs in the execution of the task’s checkpoint procedure.
env.getCheckpointConfig().setFailOnCheckpointingErrors(true);
使用
StreamExecutionEnvironment.enableCheckpointing方法来设置开启checkpoint
（具体可以使用StreamExecutionEnvironment.getCheckpointConfig.enableCheckpointing(long interval)），
或者StreamExecutionEnvironment.getCheckpointConfig.enableCheckpointing(long interval, CheckpointingMode mode)。
interval用于指定checkpoint的触发间隔(单位milliseconds)
而CheckpointingMode默认是CheckpointingMode.EXACTLY_ONCE
也可以指定为CheckpointingMode.AT_LEAST_ONCE也可以通过
StreamExecutionEnvironment.getCheckpointConfig().setCheckpointingMode来设置CheckpointingMode，
一般对于超低延迟的应用(大概几毫秒)可以使用CheckpointingMode.AT_LEAST_ONCE，其他大部分应用使用CheckpointingMode.EXACTLY_ONCE就可以
checkpointTimeout用于指定checkpoint执行的超时时间(单位milliseconds)，超时没完成就会被abort掉。minPauseBetweenCheckpoints用于指定checkpoint距上一个checkpoint完成之后最少等多久可以出发另一个checkpoint，
当指定这个参数时，maxConcurrentCheckpoints的值为1maxConcurrentCheckpoints用于指定运行中的checkpoint最多可以有多少个；
如果有设置了minPauseBetweenCheckpoints，则maxConcurrentCheckpoints这个参数就不起作用了(大于1的值不起作用)enableExternalizedCheckpoints用于开启checkpoints的外部持久化，但是在job失败的时候不会自动清理，需要自己手工清理state；ExternalizedCheckpointCleanup用于指定当job canceled的时候externalized checkpoint该如何清理，DELETE_ON_CANCELLATION的话，在job canceled的时候会自动删除externalized state，但是如果是FAILED的状态则会保留；RETAIN_ON_CANCELLATION则在job canceled的时候会保留externalized checkpoint statefailOnCheckpointingErrors用于指定在checkpoint发生异常的时候，是否应该fail该task，默认为true，如果设置为false，则task会拒绝checkpoint然后继续运行
flink-conf.yaml相关配置：
#==============================================================================
# Fault tolerance and checkpointing
#==============================================================================
# The backend that will be used to store operator state checkpoints if
# checkpointing is enabled.
#
# Supported backends are 'jobmanager', 'filesystem', 'rocksdb', or the
# <class-name-of-factory>.
#
# state.backend: filesystem
# Directory for checkpoints filesystem, when using any of the default bundled
# state backends.
#
# state.checkpoints.dir: hdfs://namenode-host:port/flink-checkpoints
# Default target directory for savepoints, optional.
#
# state.savepoints.dir: hdfs://namenode-host:port/flink-checkpoints
# Flag to enable/disable incremental checkpoints for backends that
# support incremental checkpoints (like the RocksDB state backend).
#
# state.backend.incremental: false
-
state.backend用于指定checkpoint state存储的backend，默认为none -
state.backend.async用于指定backend是否使用异步snapshot(默认为true)，有些不支持async或者只支持async的state backend可能会忽略这个参数 -
state.backend.fs.memory-threshold，默认为1024，用于指定存储于files的state大小阈[yù]值，如果小于该值则会存储在root checkpoint metadata file -
state.backend.incremental，默认为false，用于指定是否采用增量checkpoint，有些不支持增量checkpoint的backend会忽略该配置 -
state.backend.local-recovery，默认为false -
state.checkpoints.dir，默认为none，用于指定checkpoint的data files和meta data存储的目录，该目录必须对所有参与的TaskManagers及JobManagers可见 -
state.checkpoints.num-retained，默认为1，用于指定保留的已完成的checkpoints个数 -
state.savepoints.dir，默认为none，用于指定savepoints的默认目录 -
taskmanager.state.local.root-dirs，默认为none
小结：
可以通过使用
StreamExecutionEnvironment.enableCheckpointing方法来设置开启checkpoint；具体可以使用enableCheckpointing(long interval)，或者enableCheckpointing(long interval, CheckpointingMode mode)checkpoint的高级配置可以配置enableExternalizedCheckpoints(用于开启checkpoints的外部持久化，在job failed的时候externalized checkpoint state无法自动清理，但是在job canceled的时候可以配置是删除还是保留state)在
flink-conf.yaml里头也有checkpoint的相关配置，主要是state backend的配置，比如state.backend.async、state.backend.incremental、state.checkpoints.dir、state.savepoints.dir等
Java 配置实例：
/**
* 是否重启标识flag
*/
private static boolean replayFlag = true;
/**
* 重启次数
*/
private static Integer replayTimes;
/**
* 重启时间间隔
*/
private static Integer replaySeconds;
private static Long checkPointTime;
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
if (replayFlag) {
env.setRestartStrategy(RestartStrategies.fixedDelayRestart(
replayTimes,
Time.of(replaySeconds, TimeUnit.SECONDS)
));
CheckpointConfig config = env.getCheckpointConfig();
//env.setStateBackend(new FsStateBackend(checkPointDir));
// 任务流取消和故障时会保留Checkpoint数据，以便根据实际需要恢复到指定的Checkpoint
config.enableExternalizedCheckpoints(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
// 设置checkpoint的周期, 每隔1000 ms进行启动一个检查点
config.setCheckpointInterval(checkPointTime);
// 设置模式为exactly-once
config.setCheckpointingMode(CheckpointingMode.EXACTLY_ONCE);
// 确保检查点之间有至少500 ms的间隔【checkpoint最小间隔】
config.setMinPauseBetweenCheckpoints(500);
// 检查点必须在一分钟内完成，或者被丢弃【checkpoint的超时时间】
config.setCheckpointTimeout(checkPointTime);
// 同一时间只允许进行一个检查点
config.setMaxConcurrentCheckpoints(1);
}
