Flume和Kafka都是即時資料傳輸的開源平台。它們都具有高吞吐量、低延遲和可靠性的特點。但是，它們在設計和實現上存在一些差異。
Flume是分散式、可靠且可擴展的日誌收集、聚合和傳輸系統。它支援多種資料來源，包括檔案、Syslog、Taildir、Exec和HTTP。 Flume也支援多種資料格式，包括文字、JSON和Avro。
Flume的體系結構如下圖：
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Flume的元件包括：
# Name the agent a1.sources = r1 # Describe the source r1.type = exec r1.command = tail -F /var/log/messages # Describe the sink s1.type = hdfs s1.hdfs.path = hdfs://namenode:8020/flume/logs # Use a channel which buffers events in memory c1.type = memory c1.capacity = 1000 c1.transactionCapacity = 100 # Bind the source and sink to the channel a1.channels = c1 c1.sinks = s1
# Create a topic named "my-topic" with 3 partitions and a replication factor of 2 kafka-topics --create --topic my-topic --partitions 3 --replication-factor 2 # Start a Kafka producer kafka-console-producer --topic my-topic # Start a Kafka consumer kafka-console-consumer --topic my-topic --from-beginning
# Create a Flume agent
agent = AgentBuilder.newInstance().build()
# Create a source
source = ExecSourceBuilder.newInstance().setCommand("tail -F /var/log/messages").build()
# Create a channel
channel = MemoryChannelBuilder.newInstance().setCapacity(1000).setTransactionCapacity(100).build()
# Create a sink
sink = HDFSSinkBuilder.newInstance().setBasePath("hdfs://namenode:8020/flume/logs").build()
# Add the source, channel, and sink to the agent
agent.addSource("r1", source)
agent.addChannel("c1", channel)
agent.addSink("s1", sink)
# Start the agent
agent.start()
# Create a Kafka producer
producer = KafkaProducerBuilder.newInstance()
.setBootstrapServers("localhost:9092")
.setValueSerializer(StringSerializer.class)
.build()
# Create a Kafka consumer
consumer = KafkaConsumerBuilder.newInstance()
.setBootstrapServers("localhost:9092")
.setValueDeserializer(StringDeserializer.class)
.setGroupId("my-group")
.build()
# Subscribe the consumer to the topic
consumer.subscribe(Arrays.asList("my-topic"))
# Send a message to the topic
producer.send(new ProducerRecord<>("my-topic", "Hello, world!"));
# Receive messages from the topic
while (true) {
ConsumerRecords<String, String> records = consumer.poll(100);
for (ConsumerRecord<String, String> record : records) {
System.out.println(record.value());
}
}以上是即時資料傳輸：選擇Flume和Kafka的兩種方案的詳細內容。更多資訊請關注PHP中文網其他相關文章！
