Create pyFlink DataStream Consumer from Tweets Kafka Producer in Python - apache-kafka

Question

I want to create I stream kafka consumer in pyFlink, which can read tweets data after deserialization (json),
I have pyflink version 1.14.4 (last version)
Can I have an example of kafka producer and a simple code of flink consumer for stream in python?

Answer 1

Here is an example given in PyFlink examples which shows how to read json data from Kafka consumer in PyFlink DataStream API:
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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)