1 背景

1.使用 flink-1.16 的 table sql 消费 kafka数据，并使用 sql 计算指标，然后写入 doris；

2.指标计算时，需要统计当日数据条数，考虑到作业异常退出被重新拉起时，需要从零点开始消费，所以指定 'scan.startup.mode' = 'timestamp'，'scan.startup.timestamp-millis' = '当日零点时间戳' 方式创建 kafka table：

s"""|CREATE TABLE qysfxjKafkaTable (|xlid STRING,|available_status STRING,|sendtime STRING,|`ts` TIMESTAMP(3) METADATA FROM 'timestamp'|) WITH (|'connector' = 'kafka',|'topic' = '${param.getProperty("qysfxjTopic")}',|'scan.startup.mode' = 'timestamp'，'scan.startup.timestamp-millis' = '当日零点时间戳'|'properties.group.id' = '${param.getProperty("qysfxjTopicGroupId")}',|'properties.bootstrap.servers' = '${param.getProperty("brokers")}',|'properties.auto.offset.reset' = 'earliest',|'json.ignore-parse-errors' = 'true',|'json.fail-on-missing-field' = 'false',|'format' = 'json')|""".stripMargin

3.启动时报 kakfa 的错误，Invalid negative offset，即 flink 使用了一个不正确的 offset 到 kafka 消费数据，经过排查 topic 中最新一条数据的时间，在今日零点之前，也就是说，kafka table sql 中指定今日零点的时间戳，落后于 kafka 最新数据的时间；

2 解决方案

1.两种解决方案，① 从检查点启动作业；② 根据 kafka 数据时间，调整消费的时间；考虑到第一次启动可能 topic 也没有数据，且如果检查点失败会导致作业无法从检查点恢复的情况，决定采用 ② 方案解决；

2.方案步骤

1.使用 kafka java api，获取 topic 中最后一条数据，根据数据的时间戳初始化创建 kafka table sql 的启动时间；

2.获取到 kafka 最后一条数据的场景有两种：① kafka 中最新一条数据时间早于零点(报错的场景)；② kafka 中最新一条数据时间晚于零点；

3.根据以上步骤，实现代码，代码会返回一个时间戳，0或者最后一条数据时间戳：

def getTopicLatestRecordTimeStamp(brokers: String,topic: String): Long ={var retMillis = 0Lval props = new Properties();props.put("bootstrap.servers", brokers);props.put("group.id", "test");props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");val consumer = new KafkaConsumer[String,String](props);try {// 订阅 topicconsumer.subscribe(Collections.singletonList(topic))// 获取并订阅全部分区var assigment = consumer.assignment()while (assigment.size() == 0) {consumer.poll(Duration.ofMillis(1000L))assigment = consumer.assignment()}println(assigment)val earliestOffset = consumer.beginningOffsets(assigment)val lastOffset = consumer.endOffsets(assigment)println("assigment: " + assigment + ",topic earliestOffset:" + earliestOffset + ",topic endOffsets:" + lastOffset)// 遍历所有分区，获取最新的 offsetval lastOffsetIter = lastOffset.entrySet().iterator()while (lastOffsetIter.hasNext){val ele = lastOffsetIter.next()if(ele.getValue != 0L){// 分区有数据consumer.seek(ele.getKey, ele.getValue - 1)val records = consumer.poll(1000).iterator()while (records.hasNext){val next = records.next()if(next.timestamp() > retMillis){retMillis = next.timestamp()}System.out.println("Timestamp of last record: " + next.timestamp())}}}retMillis} finally {consumer.close();}}

4.根据返回的时间戳，于当日零点判断，如果返回的时间戳早于零点，使用 latest-offset，返回的时间戳晚于当日零点，使用零点启动即可，以下代码返回使用的是时间戳启动，还是 latest-offset 启动：

if(parameterTool.get("qysfxjTopicStartFrom","latest").equals("latest")){val toAssignmentTime = TimeHandler.getMidNightMillions()val latestTime = KfkUtil.getTopicLatestRecordTimeStamp(pro.get("brokers").toString,pro.get("qysfxjTopic").toString)// 如果最后一条数据在 toAssignmentTime 之前，则使用 latest-offset 启动消费if(toAssignmentTime > latestTime){pro.put("qysfxjTopicStartFrom","latest-offset")}else {pro.put("qysfxjTopicStartFrom",(toAssignmentTime).toString)}}else {pro.put("qysfxjTopicStartFrom",parameterTool.get("qysfxjTopicStartFrom"))}

5.根据时间戳，还是 latest-offset，生成 sql 中的 scan 片段：

/*** 根据 startFrom，判断是从什么位置消费。** @param startFrom：earliest-offset，latest-offset，group-offsets，timestamp* @return*/def getKafkaSQLScanStr(startFrom: String): String = {var scanStartup = ""if(Character.isDigit(startFrom.trim()(0))){scanStartup ="'scan.startup.mode' = 'timestamp'," +s"'scan.startup.timestamp-millis' = '${startFrom.trim()}',"}else {scanStartup =s"'scan.startup.mode' = '${startFrom}',"}scanStartup}

6.完整table sql 拼接：

val qysfxjKafkaSource =s"""|CREATE TABLE qysfxjKafkaTable (|xlid STRING,|available_status STRING,|sendtime STRING,|`ts` TIMESTAMP(3) METADATA FROM 'timestamp'|) WITH (|'connector' = 'kafka',|'topic' = '${param.getProperty("qysfxjTopic")}',|${TXGJUtils.getKafkaSQLScanStr(qysfxjTopicStartFrom)}|'properties.group.id' = '${param.getProperty("qysfxjTopicGroupId")}',|'properties.bootstrap.servers' = '${param.getProperty("brokers")}',|'properties.auto.offset.reset' = 'earliest',|'json.ignore-parse-errors' = 'true',|'json.fail-on-missing-field' = 'false',|'format' = 'json')|""".stripMargin