從集合中讀取
private static void radFromCollection(String[] args) throws Exception {
//將參數轉成對象
MultipleParameterTool params = MultipleParameterTool.fromArgs(args);
//創建批處理執行環境
// ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
//創建流程處理
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
//設置每個算子的的並行度,默認爲cup核數(測試環境下)
env.setParallelism(2);
//設置最大並行度
env.setMaxParallelism(6);
//從集合中讀取
List<String> collectionData = Arrays.asList("a", "b", "c", "d");
DataStreamSource<String> dataStreamSource = env.fromCollection(collectionData);
//從數組中讀取
// env.fromElements("a", "b", "c", "d");
dataStreamSource.print(); //dataStreamSource.addSink(new PrintSinkFunction<>());
env.execute();
}
從文件中讀取
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
DataStreamSource<String> dataStreamSource = env.readTextFile("E:\\GIT\\flink-learn\\flink1\\word.txt", "utf-8");
dataStreamSource.print();
env.execute();
從kafka 中讀取
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
Properties properties = new Properties();
properties.put("bootstrap.servers", "10.1.5.130:9092");
properties.put("zookeeper.connect", "10.2.5.135:2181");
properties.put("group.id", "my-flink");
properties.put("auto.offset.reset", "latest");
properties.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
properties.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
FlinkKafkaConsumer010<String> kafkaConsumer010 = new FlinkKafkaConsumer010<>(
"flink",// topic
new SimpleStringSchema(),
properties
);
DataStreamSource<String> dataStreamSource = env.addSource(kafkaConsumer010);
dataStreamSource.print();
env.execute();
從自定義Source 中讀取
- 實現
org.apache.flink.streaming.api.functions.source.SourceFunction
public static final class MyDataSource implements SourceFunction<String> {
private Boolean running = true;
@Override
public void run(SourceContext<String> sourceContext) throws Exception {
Random random = new Random();
while (running) {
double data = random.nextDouble() * 100;
sourceContext.collectWithTimestamp(String.valueOf(data), System.currentTimeMillis());
TimeUnit.SECONDS.sleep(1);
}
}
@Override
public void cancel() {
this.running = false;
}
}
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
DataStreamSource<String> dataStreamSource = env.addSource(new MyDataSource());
dataStreamSource.print();
env.execute();