flink
Data Source数据源
Source
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并行度
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非并行:并行度只能为1
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并行
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基于集合的Source
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fromElements
- package com.pxj.sx.flink;
-
import org.apache.flink.configuration.Configuration;
import org.apache.flink.configuration.RestOptions;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
public class FromElementDemo {
public static void main(String[] args) throws Exception {
Configuration configuration = new Configuration();
configuration.setInteger(RestOptions.PORT, 8081);
StreamExecutionEnvironment env = StreamExecutionEnvironment.createLocalEnvironmentWithWebUI(configuration);
// StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
DataStreamSource<String> daat = env.fromElements("flink", "spark", "hive");
daat.print();
Thread.sleep(2000000);
}
}
- fromElements(T ...) 方法是一个非并行的Source,可以将一到多个数据作为可变参数传入到该方法中,返回DataStreamSource。该方法返回的DataStream是一个有限数据流,数据读完后,程序退出,通常用于开发测试。
- fromCollection
- fromCollection可以从一个结合读取数据,返回DataStream,该方法返回的DataStream是一个有限数据流,数据读完后,程序退出,通常用于开发测试。
- package com.pxj.sx.flink;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import java.util.Arrays;
import java.util.List;
public class FromCollectionDemo {
public static void main(String[] args) throws Exception {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
List<String> wordList = Arrays.asList("flink", "spark", "hadoop", "flink");
DataStreamSource<String> source = env.fromCollection(wordList);
source.print(