类的使用
org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer010.FlinkKafkaProducer010Configuration

使用FlinkKafkaProducer010.FlinkKafkaProducer010Configuration的程序包

程序包	说明
org.apache.flink.streaming.connectors.kafka

org.apache.flink.streaming.connectors.kafka中FlinkKafkaProducer010.FlinkKafkaProducer010Configuration的使用

返回FlinkKafkaProducer010.FlinkKafkaProducer010Configuration的org.apache.flink.streaming.connectors.kafka中的方法

限定符和类型	方法和说明
static <T> FlinkKafkaProducer010.FlinkKafkaProducer010Configuration<T>	FlinkKafkaProducer010.writeToKafkaWithTimestamps(org.apache.flink.streaming.api.datastream.DataStream<T> inStream, String topicId, org.apache.flink.streaming.util.serialization.KeyedSerializationSchema<T> serializationSchema, Properties producerConfig) 已过时。 Use FlinkKafkaProducer010.FlinkKafkaProducer010(String, KeyedSerializationSchema, Properties) and call FlinkKafkaProducer010.setWriteTimestampToKafka(boolean).
static <T> FlinkKafkaProducer010.FlinkKafkaProducer010Configuration<T>	FlinkKafkaProducer010.writeToKafkaWithTimestamps(org.apache.flink.streaming.api.datastream.DataStream<T> inStream, String topicId, org.apache.flink.streaming.util.serialization.KeyedSerializationSchema<T> serializationSchema, Properties producerConfig, org.apache.flink.streaming.connectors.kafka.partitioner.FlinkKafkaPartitioner<T> customPartitioner) 已过时。 Use FlinkKafkaProducer010.FlinkKafkaProducer010(String, KeyedSerializationSchema, Properties, FlinkKafkaPartitioner) and call FlinkKafkaProducer010.setWriteTimestampToKafka(boolean).
static <T> FlinkKafkaProducer010.FlinkKafkaProducer010Configuration<T>	FlinkKafkaProducer010.writeToKafkaWithTimestamps(org.apache.flink.streaming.api.datastream.DataStream<T> inStream, String topicId, org.apache.flink.streaming.util.serialization.KeyedSerializationSchema<T> serializationSchema, Properties producerConfig, org.apache.flink.streaming.connectors.kafka.partitioner.KafkaPartitioner<T> customPartitioner) 已过时。 This is a deprecated since it does not correctly handle partitioning when producing to multiple topics. Use FlinkKafkaProducer010.FlinkKafkaProducer010(String, SerializationSchema, Properties, FlinkKafkaPartitioner) instead.
static <T> FlinkKafkaProducer010.FlinkKafkaProducer010Configuration<T>	FlinkKafkaProducer010.writeToKafkaWithTimestamps(org.apache.flink.streaming.api.datastream.DataStream<T> inStream, String topicId, org.apache.flink.api.common.serialization.SerializationSchema<T> serializationSchema, Properties producerConfig) 已过时。 Use FlinkKafkaProducer010.FlinkKafkaProducer010(String, KeyedSerializationSchema, Properties) and call FlinkKafkaProducer010.setWriteTimestampToKafka(boolean).