flink 状态参数设置

前提

代码示例，通过flink消费kafka，查看list状态中的数据，确定参数的具体含义
kafka的代码：发送两个key值，一秒发送一次

	for(int i = 0; i< 100; i++){
	    JSONObject object = new JSONObject();
	    object.put("id", 1);
	    object.put("value", i);
	    String s = object.toJSONString();
	    kafkaProducer.send(new ProducerRecord("test_topic_partition_one", s.getBytes(StandardCharsets.UTF_8))).get();
	
	    object = new JSONObject();
	    object.put("id", 2);
	    object.put("value", 100 + i);
	    s = object.toJSONString();
	    kafkaProducer.send(new ProducerRecord("test_topic_partition_one", s.getBytes(StandardCharsets.UTF_8))).get();
	    Thread.sleep(1000);
	}

flink消费kafka示例：

	final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
	env.enableCheckpointing(10 * 1000);
	KafkaSource source = KafkaSource.builder()
	                .setBootstrapServers("broker:9092")
	                .setProperties(properties)
	                .setTopics("test_topic_partition_one")
	                .setGroupId("my-group")
	                .setStartingOffsets(OffsetsInitializer.latest())
	                .setValueOnlyDeserializer(new SimpleStringSchema())
	                .build();
	DataStreamSource kafkaSource = env
		.fromSource(source, WatermarkStrategy.noWatermarks(), "Kafka Source")
		.setParallelism(2);
	
	DataStream> dataStream = kafkaSource.map(
	                new MapFunction>() {
	                    @Override
	                    public Tuple2 map(String value) throws Exception {
	                        JSONObject object = JSONObject.parseObject(value);
	                        return new Tuple2(object.getString("id"), object.getInteger("value"));
	                    }
	                });
	
	DataStream resultStream = dataStream
	                .keyBy(value -> value.f0) // 根据第一个字段（键）进行分组
	                .process(new ListValueProcess());
	
	 // 打印结果
	 resultStream.print();

ListValueProcess状态函数

 	@Override
    public void processElement(Tuple2 value, KeyedProcessFunction, String>.Context ctx, Collector out) throws Exception {
        // 添加元素到 ListState
        listState.add(value.f1);

        // 获取 ListState 中的所有元素，并输出它们
        String key = value.f0;
        List list = new ArrayList<>();
        for (Integer integer : listState.get()) {
            list.add(integer);
        }
        String result = "key:" + key + ", value:" +list;
        // 输出结果
        out.collect(result);
    }
    @Override
    public void open(Configuration parameters) throws Exception {
        super.open(parameters);

        StateTtlConfig ttlConfig = StateTtlConfig
                .newBuilder(Time.seconds(10))
                .setUpdateType(StateTtlConfig.UpdateType.OnCreateAndWrite)
                .setStateVisibility(StateTtlConfig.StateVisibility.ReturnExpiredIfNotCleanedUp)
                .build();


        // 初始化 ListState
        // 不同的key 具有不用的listState
        // 用于存储一个key多个值
        ListStateDescriptor integerListStateDescriptor = new ListStateDescriptor<>("my-list-state", Integer.class);
        integerListStateDescriptor.enableTimeToLive(ttlConfig);

        listState = getRuntimeContext().getListState(integerListStateDescriptor);

    }

可以看到StateTtlConfig大部份有三个参数

• 指定状态保存时间
• setUpdateType 设置状态更新策略：OnCreateAndWrite和 OnReadAndWrite
• setStateVisibility 设置状态可见行 ：ReturnExpiredIfNotCleanedUp和 NeverReturnExpired

这里我们保存状态时间是10s
OnCreateAndWrite: 表示当状态被创建与更新的时候，表示更新了状态
OnReadAndWrite：表示状态被创建与更新和读取的时候，表示更新了状态
ReturnExpiredIfNotCleanedUp：表示状态过期了但没有删除，也可以读取到状态
NeverReturnExpired：表示状态过期就读取不到

结果示例：
当：OnCreateAndWrite和ReturnExpiredIfNotCleanedUp时

1> key:1, value:[6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24]
1> key:2, value:[113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124]
1> key:1, value:[6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25]
1> key:2, value:[113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125]
1> key:1, value:[6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26]
1> key:2, value:[113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126]
1> key:1, value:[18, 19, 20, 21, 22, 23, 24, 25, 26, 27]
1> key:2, value:[113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127]
1> key:1, value:[18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28]
1> key:2, value:[113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128]
1> key:1, value:[18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29]
1> key:2, value:[113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129]
1> key:1, value:[18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30]
1> key:2, value:[113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130]

可以看到，状态会定期删除过期的数据，而且数据可见可能大于10s的范围。

当OnCreateAndWrite和NeverReturnExpired时

1> key:2, value:[109, 110, 111, 112, 113, 114, 115, 116, 117]
1> key:1, value:[10, 11, 12, 13, 14, 15, 16, 17, 18]
1> key:2, value:[110, 111, 112, 113, 114, 115, 116, 117, 118]
1> key:1, value:[11, 12, 13, 14, 15, 16, 17, 18, 19]
1> key:2, value:[111, 112, 113, 114, 115, 116, 117, 118, 119]
1> key:1, value:[12, 13, 14, 15, 16, 17, 18, 19, 20]
1> key:2, value:[112, 113, 114, 115, 116, 117, 118, 119, 120]
1> key:1, value:[13, 14, 15, 16, 17, 18, 19, 20, 21]
1> key:2, value:[113, 114, 115, 116, 117, 118, 119, 120, 121]
1> key:1, value:[14, 15, 16, 17, 18, 19, 20, 21, 22]
1> key:2, value:[114, 115, 116, 117, 118, 119, 120, 121, 122]

可以看到，状态的数据只保留最近10s内的值

当OnReadAndWrite和ReturnExpiredIfNotCleanedUp时

1> key:1, value:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25]
1> key:2, value:[101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125]
1> key:1, value:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26]
1> key:2, value:[101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126]
1> key:1, value:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]
1> key:2, value:[101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127]
1> key:1, value:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28]
1> key:2, value:[101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128]
1> key:1, value:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29]
1> key:2, value:[101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129]
1> key:1, value:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30]
1> key:2, value:[101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130]
1> key:1, value:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31]
1> key:2, value:[101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131]
1> key:1, value:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32]
1> key:2, value:[101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132]

可以看到，状态保留了所有的数据，因为每次都会读取了数据，所以不会过期

当OnReadAndWrite和NeverReturnExpired时

1> key:1, value:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26]
1> key:2, value:[101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126]
1> key:1, value:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]
1> key:2, value:[101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127]
1> key:1, value:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28]
1> key:2, value:[101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128]
1> key:1, value:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29]
1> key:2, value:[101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129]
1> key:1, value:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30]
1> key:2, value:[101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130]
1> key:1, value:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31]
1> key:2, value:[101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131]

可以看到，状态保留了所有的数据，因为每次都会读取了数据，所以不会过期