|NO.Z.00062|——————————|BigDataEnd|——|Hadoop&Flink.V01|——|Flink.v01|Flink SQL|什么是Table API|Flink SQL|入门代码|

一、FlinkSQL

### --- 什么是 Table API 和 Flink SQL

~~~     Flink 本身是批流统一的处理框架，所以 Table API 和 SQL，就是批流统一的上层处理 API。
~~~     Table API 是一套内嵌在 Java 和 Scala 语言中的查询 API，它允许我们以非常直观的方式，
~~~     组合来自一些关系运算符的查询（比如 select、filter 和 join）。
~~~     而对于 Flink SQL，就是直接可以在代码中写 SQL，来实现一些查询（Query）操作。
~~~     Flink 的 SQL 支持，基于实现了 SQL 标准的 Apache Calcite（Apache 开源 SQL 解析工具）。
~~~     无论输入是批输入还是流式输入，在这两套 API 中，指定的查询都具有相同的语义，得到相同的结果

二、入门代码：

### --- 在pom.xml下导入依赖：

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table</artifactId>
            <version>1.11.1</version>
            <type>pom</type>
            <scope>provided</scope>
        </dependency>

        <!-- Either... -->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-api-java-bridge_2.12</artifactId>
            <version>1.11.1</version>
            <scope>provided</scope>
        </dependency>
        <!-- or... -->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-api-scala-bridge_2.12</artifactId>
            <version>1.11.1</version>
            <scope>provided</scope>
        </dependency>


        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-planner-blink_2.12</artifactId>
            <version>1.11.1</version>
            <scope>provided</scope>
        </dependency>

### --- 依赖说明：

~~~     # flink-table-api-java-bridge_2.1：
~~~     桥接器，主要负责 table API 和 DataStream/DataSet API的连接支持，按照语言分 java 和 scala。
~~~     # flink-table-planner-blink_2.12：
~~~     计划器，是 table API 最主要的部分，提供了运行时环境和生成程序执行计划的 planner；
~~~     如果是生产环境，lib 目录下默认已 经有了 planner，
~~~     就只需要有 bridge 就可以了flink-table：flinktable的基础依赖

三、编程代码实现流程

### --- Flink执行环境env
### --- 用env，做出Table环境tEnv

StreamTableEnvironment tEnv = StreamTableEnvironment.create(env);

~~~     # 基于 blink 版本的流处理环境（Blink-Streaming-Query）或者，
~~~     # 基于 blink 版本的批处理环境（Blink-Batch-Query）：

EnvironmentSettings settings = EnvironmentSettings.newInstance()
    .useBlinkPlanner()
    // .inBatchMode()
    .inStreamingMode()
    .build();

### --- 获取流式数据源

        DataStreamSource<Tuple2<String, Integer>> data = env.addSource(new
        SourceFunction<Tuple2<String, Integer>>() {
            @Override 
            public void run(SourceContext<Tuple2<String, Integer>> ctx) throws
        Exception {
        while (true) {
        ctx.collect(new Tuple2<>("name", 10));
        Thread.sleep(1000);
        }
        }
        @Override 
        public void cancel() {
        }
        });

### --- 将流式数据源做成Table

~~~     # table方式：
Table table = tEnv.fromDataStream(data, $("name"), $("age"));

~~~     # sql方式：

tEnv.createTemporaryView("userss",data, $("name"), $("age"));
String s = "select name from userss";
Table table = tEnv.sqlQuery(s);

### --- 对Table中的数据做查询
### --- 将Table转成数据流：

~~~     # table方式：
Table name = table.select($("name"));

~~~     # sql方式：

tEnv.createTemporaryView("userss",data, $("name"), $("age"));
String s = "select name from userss";
Table table = tEnv.sqlQuery(s);

四、编程代码实现

### --- 将Table转成数据流

package com.yanqi.tableql;

import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.source.SourceFunction;
import org.apache.flink.table.api.EnvironmentSettings;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.types.Row;

import static org.apache.flink.table.api.Expressions.$;

public class Demo1 {
    public static void main(String[] args) throws Exception {
        //env
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        //tEnv
        EnvironmentSettings settings = EnvironmentSettings.newInstance()
                .useBlinkPlanner()
                .inStreamingMode()
//                .inBatchMode()
                .withBuiltInCatalogName("default_catalog")
                .withBuiltInDatabaseName("default_database")
                .build();
        StreamTableEnvironment tEnv = StreamTableEnvironment.create(env, settings);
        //读数据
        DataStreamSource<Tuple2<String, Integer>> data = env.addSource(new SourceFunction<Tuple2<String, Integer>>() {
            @Override
            public void run(SourceContext<Tuple2<String, Integer>> ctx) throws Exception {
                int num = 0;
                while (true) {
                    num++;
                    ctx.collect(new Tuple2<>("name" + num, num));
                    Thread.sleep(1000);
                }
            }

            @Override
            public void cancel() {

            }
        });
        //将流式数据源转成table类型
        Table myTable = tEnv.fromDataStream(data, $("name"), $("num"));
        //查询,
        //table api:
//        Table selectResult = myTable.select($("name"), $("num")).filter($("num").mod(2).isEqual(0));

        //sql:
        tEnv.createTemporaryView("nameTable",data,$("name"),$("num"));
        Table selectResult = tEnv.sqlQuery("select * from nameTable where mod(num,2)=0");

        DataStream<Tuple2<Boolean, Row>> tuple2DataStream = tEnv.toRetractStream(selectResult, Row.class);
        //保存处理结果
        tuple2DataStream.print();

        env.execute();
    }
}

### --- 编译打印

D:\JAVA\jdk1.8.0_231\bin\java.exe "-javaagent:D:\IntelliJIDEA\IntelliJ IDEA 2019.3.3\lib\idea_rt.jar=51703:D:\IntelliJIDEA\IntelliJ IDEA 2019.3.3\bin" -Dfile.encoding=UTF-8 -classpath 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com.yanqi.tableql.Demo1

2> (true,name2,2)
3> (true,name4,4)
4> (true,name6,6)
1> (true,name8,8)
2> (true,name10,10)
3> (true,name12,12)
4> (true,name14,14)
1> (true,name16,16)
2> (true,name18,18)

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Walter Savage Landor:strove with none,for none was worth my strife.Nature I loved and, next to Nature, Art:I warm'd both hands before the fire of life.It sinks, and I am ready to depart

                                                                                                                                                   ——W.S.Landor

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