1. 从集合读取数据

1. fromCollection

从集合中获取数据

// 定义样例类，传感器id，时间戳，温度
case class SensorReading(id: String, timestamp: Long, temperature: Double)

object Sensor {
  def main(args: Array[String]): Unit = {
    val env = StreamExecutionEnvironment.getExecutionEnvironment
    val stream1 = env
      .fromCollection(List(
        SensorReading("sensor_1", 1547718199, 35.8),
        SensorReading("sensor_6", 1547718201, 15.4),
        SensorReading("sensor_7", 1547718202, 6.7),
        SensorReading("sensor_10", 1547718205, 38.1)
      ))

    stream1.print("stream1:").setParallelism(1)

    env.execute()
  }
}

2. fromEleements

//不常用
env.fromElements(1, 2, "hhh")

3. fromParalleCollection

//不常用
//从指定的序列中获取
env.fromParallelCollection(new NumberSequenceIterator(1L, 1000L))

2. 从文件读取数据

 env.readTextFile("YOUR_FILE_PATH")

3. 以kafka队列数据作为数据来源

1. 引入依赖包

<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-connector-kafka-0.11_2.11</artifactId>
    <version>1.10.0</version>
</dependency>

2. 实例

val properties = new Properties()
properties.setProperty("bootstrap.servers", "mayi101:9092")
properties.setProperty("group.id", "consumer-group")
properties.setProperty("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer")
properties.setProperty("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer")
properties.setProperty("auto.offset.reset", "latest")

val stream3 = env.addSource(new FlinkKafkaConsumer011[String]("sensor",
new SimpleStringSchema(), properties))

3. 测试

kafka-console-producer.sh \
> --broker-list mayi101:9092 --topic flink

4. 自定义source

除了以上的source数据来源，我们还可以自定义source。需要做的，只是传入一个SourceFunction就可以 参考自定义source一文

 env.addSource( new MySensorSource() )