python kafkaconsumer poll_如何从获取ConsumerRecordKafkaConsumer.poll()在python中
时间: 2024-02-24 19:59:30 浏览: 28
要从获取`ConsumerRecord`,可以通过以下步骤:
1. 首先,创建一个`KafkaConsumer`对象并设置相关的配置,如下所示:
```python
from kafka import KafkaConsumer
consumer = KafkaConsumer(
'my_topic',
bootstrap_servers=['localhost:9092'],
auto_offset_reset='earliest',
enable_auto_commit=True,
group_id='my-group',
value_deserializer=lambda x: loads(x.decode('utf-8'))
)
```
2. 接下来,使用`poll()`方法获取`ConsumerRecord`,如下所示:
```python
for message in consumer.poll(timeout_ms=5000):
for record in message[1]:
print(record)
```
在上面的代码中,我们使用`poll()`方法获取了消息,它接受一个`timeout_ms`参数,表示等待时间,单位为毫秒。然后,我们遍历每个消息并打印相关的`ConsumerRecord`对象。
相关问题
python Poll.apply_async
`apply_async` 是 Python 中 `multiprocessing` 模块中的一个方法,用于异步执行函数或方法。它的作用是将函数提交给进程池进行异步执行,而不会阻塞主进程。
`apply_async` 方法的语法如下:
```python
apply_async(func, args=(), kwds={}, callback=None, error_callback=None)
```
其中,参数的含义如下:
- `func`:要执行的函数或方法。
- `args`:传递给函数的位置参数,以元组形式传递。
- `kwds`:传递给函数的关键字参数,以字典形式传递。
- `callback`:可选参数,用于指定一个回调函数,当异步执行完成时会调用该函数。
- `error_callback`:可选参数,用于指定一个错误回调函数,当异步执行发生错误时会调用该函数。
使用 `apply_async` 方法可以实现并行执行多个任务,从而提高程序的执行效率。当任务较多时,可以使用进程池来管理和调度这些任务。
python confluent_kafka
Confluent Kafka is a Python client library for Apache Kafka, developed by Confluent. It provides an easy-to-use interface for interacting with Kafka clusters, allowing you to produce and consume messages from Kafka.
To use the confluent_kafka library in, you first need to install it. You can do this by running the following command:
```
pip install confluent-kafka
```
Once installed, you can import the library in your Python code as follows:
```python
from confluent_kafka import Producer, Consumer
```
To produce messages to a Kafka topic, you can create a `Producer` instance and use its `produce()` method. Here's an example:
```python
producer = Producer({'bootstrap.servers': 'localhost:9092'})
topic = 'my_topic'
message = 'Hello, Kafka!'
producer.produce(topic, message.encode('utf-8'))
producer.flush()
```
To consume messages from a Kafka topic, you can create a `Consumer` instance and use its `subscribe()` and `poll()` methods. Here's an example:
```python
consumer = Consumer({
'bootstrap.servers': 'localhost:9092',
'group.id': 'my_consumer_group',
'auto.offset.reset': 'earliest'
})
topic = 'my_topic'
consumer.subscribe([topic])
while True:
msg = consumer.poll(1.0)
if msg is None:
continue
if msg.error():
print(f"Consumer error: {msg.error()}")
continue
print(f"Received message: {msg.value().decode('utf-8')}")
consumer.close()
```
These are just basic examples to get you started with the confluent_kafka library. You can refer to the official documentation for more advanced usage and configuration options.
Please note that you need a running Kafka cluster to use the confluent_kafka library.