在Python中从Tweets Kafka Producer创建pyFlink DataStream Consumer.

Question

我想在pyFlink中创建I流kafka消费者，它可以在反序列化(json)后读取tweet数据，我有pyflink版本1.14.4(最新版本)

我可以有kafka生产者的一个例子和一个简单的代码flink消费者流在python?

Answer 1

下面是PyFlink示例中给出的一个示例，该示例展示了如何从PyFlink DataStream API中的Kafka消费者中读取json数据:

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import logging
import sys
from pyflink.common import Types, JsonRowDeserializationSchema, JsonRowSerializationSchema
from pyflink.datastream import StreamExecutionEnvironment
from pyflink.datastream.connectors import FlinkKafkaProducer, FlinkKafkaConsumer

# Make sure that the Kafka cluster is started and the topic 'test_json_topic' is
# created before executing this job.
def write_to_kafka(env):
type_info = Types.ROW([Types.INT(), Types.STRING()])
ds = env.from_collection(
[(1, 'hi'), (2, 'hello'), (3, 'hi'), (4, 'hello'), (5, 'hi'), (6, 'hello'), (6, 'hello')],
type_info=type_info)
serialization_schema = JsonRowSerializationSchema.Builder() 
.with_type_info(type_info) 
.build()
kafka_producer = FlinkKafkaProducer(
topic='test_json_topic',
serialization_schema=serialization_schema,
producer_config={'bootstrap.servers': 'localhost:9092', 'group.id': 'test_group'}
)
# note that the output type of ds must be RowTypeInfo
ds.add_sink(kafka_producer)
env.execute()

def read_from_kafka(env):
deserialization_schema = JsonRowDeserializationSchema.Builder() 
.type_info(Types.ROW([Types.INT(), Types.STRING()])) 
.build()
kafka_consumer = FlinkKafkaConsumer(
topics='test_json_topic',
deserialization_schema=deserialization_schema,
properties={'bootstrap.servers': 'localhost:9092', 'group.id': 'test_group_1'}
)
kafka_consumer.set_start_from_earliest()
env.add_source(kafka_consumer).print()
env.execute()

if __name__ == '__main__':
logging.basicConfig(stream=sys.stdout, level=logging.INFO, format="%(message)s")
env = StreamExecutionEnvironment.get_execution_environment()
env.add_jars("file:///path/to/flink-sql-connector-kafka-1.15.0.jar")
print("start writing data to kafka")
write_to_kafka(env)
print("start reading data from kafka")
read_from_kafka(env)