flink掃盲-DataStreamにおけるデータソースAPI実験
22677 ワード
文書ディレクトリ
ちょくせつにゅうりょくけいしき
fromElements
step1: ElementsInput.java package org.myorg.quickstart;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
/**
* @author ryan create on 2019/1/6
**/
public class ElementsInput {
public static void main(String[] args) throws Exception {
// get the execution environment
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
// string Elements
String inputText1 = "hey, man, this is collection are you ok?";
String inputText2 = "hello flink, this is string";
DataStreamSource<String> text = env.fromElements(inputText1, inputText2);
// parse the data, group it, window it, and aggregate the counts
text.print();
/**
* 2> hello flink, this is string
* 1> hey, man, this is collection are you ok?
*/
// print the results with a single thread, rather than in parallel
env.execute();
}
}
step2: mvn clean package
mvn exec:java -Dexec.mainClass=org.myorg.quickstart.ElementsInput
ページダイレクト印刷
1> hey, man, this is collection are you ok?
2> hello flink, this is string
fromCollection
step1: CollectionInput.java package org.myorg.quickstart;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import java.util.ArrayList;
import java.util.Arrays;
/**
* @author ryan
**/
public class CollectionInput {
public static void main(String[] args) throws Exception {
// get the execution environment
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
DataStreamSource<String> text = env.fromCollection(new ArrayList<String>(Arrays.asList("Hi", "legotime", "ok")));
text.map(new MapFunction<String, Void>() {
@Override
public Void map(String s) throws Exception {
System.out.println(s);
return null;
}
});
// print the results with a single thread, rather than in parallel
env.execute();
}
}
step2: mvn clean package
mvn exec:java -Dexec.mainClass=org.myorg.quickstart.CollectionInput
印刷
Hi
legotime
ok
Socket形式
step1: SocketWindowWordCount.java package org.myorg.quickstart;
import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.common.functions.ReduceFunction;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.util.Collector;
/**
* Implements a streaming windowed version of the "WordCount" program.
*
* This program connects to a server socket and reads strings from the socket.
* The easiest way to try this out is to open a text server (at port 12345)
* using the netcat tool via
*
* nc -l 12345
*
* and run this example with the hostname and the port as arguments.
*/
@SuppressWarnings("serial")
public class SocketWindowWordCount {
public static void main(String[] args) throws Exception {
//the host and the port to connect to
final String hostname;
final int port;
try {
final ParameterTool params = ParameterTool.fromArgs(args);
hostname = params.has("hostname") ? params.get("hostname") : "localhost";
port = params.getInt("port");
} catch (Exception e) {
System.err.println("No port specified. Please run 'SocketWindowWordCount "+
"--hostname --port ', where hostname (localhost by default) "+
"and port is the address of the text server");
System.err.println("To start a simple text server, run 'netcat -l ' and "+
"type the input text into the command line");
return;
}
//get the execution environment
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
//get input data by connecting to the socket
DataStream text = env.socketTextStream(hostname, port, "");
//parse the data, group it, window it, and aggregate the counts
DataStream windowCounts = text
.flatMap(new FlatMapFunction() {
@Override
public void flatMap(String value, Collector out) {
for (String word : value.split("\\s")) {
out.collect(new WordWithCount(word, 1L));
}
}
})
.keyBy("word")
.timeWindow(Time.seconds(5))
.reduce(new ReduceFunction() {
@Override
public WordWithCount reduce(WordWithCount a, WordWithCount b) {
return new WordWithCount(a.word, a.count + b.count);
}
});
//print the results with a single thread, rather than in parallel
windowCounts.print().setParallelism(1);
env.execute("Socket Window WordCount");
}
//------------------------------------------------------------------------
/**
* Data type for words with count.
*/
public static class WordWithCount {
public String word;
public long count;
public WordWithCount() {
}
public WordWithCount(String word, long count) {
this.word = word;
this.count = count;
}
@Override
public String toString() {
return word + ": "+ count;
}
}
}step2: socket nc -l 12345
step3: mvn clean package
mvn exec:java -Dexec.mainClass=org.myorg.quickstart.SocketWindowWordCount -Dexec.args="--hostname 127.0.0.1 --port 12345"
step4:socket ➜ tmp nc -l 12345
this is socket
pretty test
の が られたthis : 1
is : 1
socket : 1
pretty : 1
test : 1
ファイル
step1: FileInput.java package org.myorg.quickstart;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
/**
* @author ryan
**/
public class FileInput {
public static void main(String[] args) throws Exception {
// get the execution environment
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
DataStreamSource<String> text = env.readTextFile("tmp.txt");
text.map(new MapFunction<String, Void>() {
@Override
public Void map(String s) throws Exception {
System.out.println(s);
return null;
}
});
// print the results with a single thread, rather than in parallel
env.execute();
}
}
step3: mvn clean package
echo "this is tmp file " > tmp.txt
mvn exec:java -Dexec.mainClass=org.myorg.quickstart.SocketWindowWordCount -Dexec.args="--hostname 127.0.0.1 --port 12345"
:this is tmp file
カスタム
カスタム は、kafkaなどの のデータソースであってもよく、 のconnector で に されます.