|NO.Z.00066|——————————|BigDataEnd|——|Hadoop&Flink.V05|——|Flink.v04|Flink SQL|Flink SQL输出表|输出到kafka|

一、FlinkSQL输出表：输出到Kafka

### --- 输出到kafka

~~~     # 往kafka上输出表
DataStreamSource<String> data = env.addSource(new SourceFunction<String>
    () {
        @Override
        public void run(SourceContext<String> ctx) throws Exception {
        int num = 0;
        while (true) {
        num++;
        ctx.collect("name"+num);
        Thread.sleep(1000);
        }
        }

        @Override
        public void cancel() {
        }
        });
        Table name = tEnv.fromDataStream(data, $("name"));
        ConnectTableDescriptor descriptor = tEnv.connect(
        // declare the external system to connect to
        new Kafka()
        .version("universal")
        .topic("animal")
        .startFromEarliest()
        .property("bootstrap.servers", "hdp-2:9092")
        )
        // declare a format for this system
        .withFormat(
        // new Json()
        new Csv()
        )
        // declare the schema of the table
        .withSchema(
        new Schema()
        // .field("rowtime", DataTypes.TIMESTAMP(3))
        // .rowtime(new Rowtime()
        // .timestampsFromField("timestamp")
        // .watermarksPeriodicBounded(60000)
        // )
        // .field("user", DataTypes.BIGINT())
        .field("message", DataTypes.STRING())
        );
        // create a table with given name
        descriptor.createTemporaryTable("MyUserTable");
        name.executeInsert("MyUserTable");

### --- 输出到mysql （了解）

CREATE TABLE MyUserTable (
    ...
) WITH (
    'connector.type' = 'jdbc', 
    -- required: specify this table type is jdbc 'connector.url' = 'jdbc:mysql://localhost:3306/flink-test', 
    -- required: JDBCDB url 'connector.table' = 'jdbc_table_name', 
    -- required: jdbc table name
    -- optional: the class name of the JDBC driver to use to connect to this URL.
    -- If not set, it will automatically be derived from the URL.'connector.driver' = 'com.mysql.jdbc.Driver',
    -- optional: jdbc user name and password 'connector.username' = 'name', 'connector.password' = 'password',
    -- **followings are scan options, optional, used when reading from a table**
    -- optional: SQL query / prepared statement.
    -- If set, this will take precedence over the 'connector.table' setting 'connector.read.query' = 'SELECT * FROM sometable',
    -- These options must all be specified if any of them is specified. Inaddition,
    -- partition.num must be specified. They describe how to partition the tablewhen
    -- reading in parallel from multiple tasks. partition.column must be anumeric,
    -- date, or timestamp column from the table in question. Notice that lowerBound and
    -- upperBound are just used to decide the partition stride, not for filtering the
    -- rows in table. So all rows in the table will be partitioned and returned.'connector.read.partition.column' = 'column_name', 
    -- optional: the column name used for partitioning the input.'connector.read.partition.num' = '50', 
    -- optional: the number of partitions.'connector.read.partition.lower-bound' = '500', 
    -- optional: the smallest value of the first partition.'connector.read.partition.upper-bound' = '1000', 
    -- optional: the largest value of the last partition.
    -- optional, Gives the reader a hint as to the number of rows that should be fetched
    -- from the database when reading per round trip. If the value specified is zero, then
    -- the hint is ignored. The default value is zero. 'connector.read.fetch-size' = '100',
    -- **followings are lookup options, optional, used in temporary join**
    -- optional, max number of rows of lookup cache, over this value, the oldest rows will
    -- be eliminated. "cache.max-rows" and "cache.ttl" options must all be specified if any
    -- of them is specified. Cache is not enabled as default.'connector.lookup.cache.max-rows' = '5000',
    -- optional, the max time to live for each rows in lookup cache, over this time, the oldest rows
    -- will be expired. "cache.max-rows" and "cache.ttl" options must all be specified if any of
    -- them is specified. Cache is not enabled as default.'connector.lookup.cache.ttl' = '10s','connector.lookup.max-retries' = '3', 
    -- optional, max retry times if lookup database failed
    -- **followings are sink options, optional, used when writing into table**
    -- optional, flush max size (includes all append, upsert and delete records),
    -- over this number of records, will flush data. The default value is "5000".'connector.write.flush.max-rows' = '5000',
    -- optional, flush interval mills, over this time, asynchronous threads will flush data.
    -- The default value is "0s", which means no asynchronous flush thread will be scheduled.'connector.write.flush.interval' = '2s',
    -- optional, max retry times if writing records to database failed 'connector.write.max-retries' = '3'
)

二、编程代码实现

### --- 编程代码实现：输出表到kafka

package com.yanqi.tableql;

import org.apache.flink.api.java.tuple.Tuple2;
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.DataTypes;
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.table.descriptors.Csv;
import org.apache.flink.table.descriptors.Kafka;
import org.apache.flink.table.descriptors.Schema;

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

public class ToKafka {
    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<String> data = env.addSource(new SourceFunction<String>() {
            @Override
            public void run(SourceContext<String> ctx) throws Exception {
                int num = 0;
                while (true) {
                    num++;
                    ctx.collect("name" + num);
                    Thread.sleep(1000);
                }
            }

            @Override
            public void cancel() {

            }
        });

        Table nameTable = tEnv.fromDataStream(data, $("name"));

        tEnv.connect(
                new Kafka()
                        .version("universal")
                        .topic("lucasone")
                        .startFromEarliest()
                        .property("bootstrap.servers","hadoop01:9092")
        )
                .withFormat(new Csv())
                .withSchema(
                        new Schema().field("name", DataTypes.STRING())
                )
                .createTemporaryTable("animalTable");

        nameTable.executeInsert("animalTable");

        env.execute();
    }
}

### --- 编译打印

~~~     # 启动kafka主题：启动消费者
[root@hadoop01 ~]# kafka-console-consumer.sh --bootstrap-server hadoop01:9092 --topic lucasone --from-beginning
name1
name2
name3
name4
name5
~~~省略部分参数

~~~     # 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=55127:D:\IntelliJIDEA\IntelliJ IDEA 2019.3.3\bin" -Dfile.encoding=UTF-8 -classpath 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com.yanqi.tableql.ToKafka

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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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