這篇文章主要講解了“1、如何用flink的table和sql構(gòu)建pom文件”，文中的講解內(nèi)容簡(jiǎn)單清晰，易于學(xué)習(xí)與理解，下面請(qǐng)大家跟著小編的思路慢慢深入，一起來研究和學(xué)習(xí)“1、如何用flink的table和sql構(gòu)建pom文件”吧！
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構(gòu)建pom文件
4.0.0
org.example
flinksqldemo
1.0-SNAPSHOT
UTF-8
UTF-8
2.11
2.11.8
0.10.2.1
1.12.0
2.7.3
compile
org.apache.maven.plugins
maven-compiler-plugin
8
8
org.apache.flink
flink-table-planner-blink_2.11
1.12.0
org.apache.flink
flink-java
${flink.version}
${setting.scope}
org.apache.flink
flink-streaming-java_2.11
${flink.version}
${setting.scope}
org.apache.flink
flink-clients_2.11
${flink.version}
${setting.scope}
org.apache.flink
flink-connector-kafka-0.10_${scala.binary.version}
${flink.version}
org.apache.flink
flink-streaming-scala_${scala.binary.version}
${flink.version}
${setting.scope}
org.apache.flink
flink-connector-filesystem_${scala.binary.version}
${flink.version}
org.apache.kafka
kafka_${scala.binary.version}
${kafka.version}
${setting.scope}
org.apache.hadoop
hadoop-common
${hadoop.version}
${setting.scope}
org.apache.hadoop
hadoop-hdfs
${hadoop.version}
${setting.scope}
org.apache.hadoop
hadoop-client
${hadoop.version}
${setting.scope}
org.slf4j
slf4j-api
1.7.25
com.alibaba
fastjson
1.2.72
redis.clients
jedis
2.7.3
com.google.guava
guava
29.0-jre
2、編寫代碼
package com.jd.data;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
public class test {
public static void main(String[] args) throws Exception {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
env.setParallelism(1);
DataStreamSource stream = env.readTextFile("/Users/liuhaijing/Desktop/flinktestword/aaa.txt");
// DataStreamSource stream = env.socketTextStream("localhost", 8888);
SingleOutputStreamOperator map = stream.map(new MapFunction() {
public SensorReading map(String s) throws Exception {
String[] split = s.split(",");
return new SensorReading(split[0], split[1], split[2]);
}
});
StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);
// 使用 table api
// Table table = tableEnv.fromDataStream(map);
// table.printSchema();
// Table select = table.select("a,b");
// 使用 sql api
tableEnv.createTemporaryView("test", map);
Table select = tableEnv.sqlQuery(" select a, b from test");
DataStream sensorReading2DataStream = tableEnv.toAppendStream(select, SensorReading2.class);
sensorReading2DataStream.map(new MapFunction() {
@Override
public Object map(SensorReading2 value) throws Exception {
System.out.println(value.a+" "+ value.b);
return null;
}
});
env.execute();
}
} package com.jd.data;
public class SensorReading {
public String a;
public String b;
public String c;
public SensorReading(){
}
public SensorReading(String a, String b, String c) {
this.a = a;
this.b = b;
this.c = c;
}
public String getA() {
return a;
}
public void setA(String a) {
this.a = a;
}
public String getB() {
return b;
}
public void setB(String b) {
this.b = b;
}
public String getC() {
return c;
}
public void setC(String c) {
this.c = c;
}
} package com.jd.data;
public class SensorReading2 {
public String a;
public String b;
public SensorReading2(){
}
public SensorReading2(String a, String b) {
this.a = a;
this.b = b;
}
public String getA() {
return a;
}
public void setA(String a) {
this.a = a;
}
public String getB() {
return b;
}
public void setB(String b) {
this.b = b;
}
} 注意：pojo 中屬性必須是public的， 包含無參構(gòu)造器
感謝各位的閱讀，以上就是“1、如何用flink的table和sql構(gòu)建pom文件”的內(nèi)容了，經(jīng)過本文的學(xué)習(xí)后，相信大家對(duì)1、如何用flink的table和sql構(gòu)建pom文件這一問題有了更深刻的體會(huì)，具體使用情況還需要大家實(shí)踐驗(yàn)證。這里是創(chuàng)新互聯(lián)，小編將為大家推送更多相關(guān)知識(shí)點(diǎn)的文章，歡迎關(guān)注！
新聞標(biāo)題：1、如何用flink的table和sql?構(gòu)建pom文件
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