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[实战-11] FlinkSql 设置时区对TIMESTAMP和TIMESTAMP_LTZ的影响

article 2024/12/26 11:19:14

table.local-time-zone

table.local-time-zone
DataStream-to-Table Conversion（拓展知识）
代码测试
flinksql代码
执行结果截图
- 1. Asia/Shanghai 结果如下
- 2. UTC结果如下

table.local-time-zone

table.local-time-zone可用于设置flinksql的时区。
flink的内置数据类型TIMESTAMP(n)或者是TIMESTAMP_LTZ(n)，我们设置水位线都是基于这两种类型，不同的是前者本质是字符串形势，后者本质是long，也因此前者不受时区影响，后者受时区影响类型。（n指的毫秒级的精度取值范围是 0~9)
原始数据库如果不是时间类型，可能要用TO_TIMESTAMP(字符串格式的时间)或者TO_TIMESTAMP_LTZ(long数字，n)

如果原始数据库是string则需要用TO_TIMESTAMP(字符串格式的时间字段)转成TIMESTAMP(n)
如果原始数据库中是long则需要用TO_TIMESTAMP_LTZ(long数字，n) 转成TIMESTAMP_LTZ(n)

DataStream-to-Table Conversion（拓展知识）

datastream API到Table Api转换的时候，是以后string的形式传递event_time, 并且这个string在DataStream Api是以UTC时区转换的，如果你的原始数据中是long，如果不做处理展示出来的string就是UTC字符串，为了在东八区展示，则需要将long再加上8小时

        // 水位线 允许乱序
        WatermarkStrategy<String> waterStrategy = WatermarkStrategy.<String>forMonotonousTimestamps() //ofSeconds(20)
                .withTimestampAssigner(new SerializableTimestampAssigner<String>() {
                    @Override
                    public long extractTimestamp(String element, long recordTimestamp) {
                        try {
                            Mybook book= JSON.parseObject(element,Mybook.class);
                            return boo.time+8*60*60*1000  //转成东八区
                        }catch (Exception e){
                            return recordTimestamp;
                        }

                    }
                }).withIdleness(Duration.ofSeconds(timeWindowIdleness));

        SingleOutputStreamOperator<UserSlotGame> processStream = env
                .fromSource(source, waterStrategy, "readKafka")
                .process(new ProcessFunction<String, UserSlotGame>() {
                             @Override
                             public void processElement(String value, Context ctx, Collector<UserSlotGame> out) throws Exception {
                                // 省略

                             }
                    }) ;

代码测试

mysql时区是Asia/Shanghai

CREATE TABLE `versioned_rates` (
  `operation_code` int DEFAULT NULL,
  `update_time` varchar(255) DEFAULT NULL, -- 注意这是字符串
  `product_id` varchar(255) DEFAULT NULL,
  `product_name` varchar(255) DEFAULT NULL,
  `price` float DEFAULT NULL,
  `time_long` bigint NOT NULL DEFAULT '0' -- 注意这是long
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci



INSERT INTO flink.versioned_rates
(operation_code, update_time, product_id, product_name, price, time_long)
VALUES(1, '2024-01-01 00:01:00', 'p_001', 'scooter', 11.11, 1730346179000);
INSERT INTO flink.versioned_rates
(operation_code, update_time, product_id, product_name, price, time_long)
VALUES(1, '2024-01-01 00:02:00', 'p_002', 'basketball', 23.11, 1730346179000);
INSERT INTO flink.versioned_rates
(operation_code, update_time, product_id, product_name, price, time_long)
VALUES(2, '2024-01-01 12:00:00', 'p_001', 'scooter', 11.11, 1730346179000);
INSERT INTO flink.versioned_rates
(operation_code, update_time, product_id, product_name, price, time_long)
VALUES(3, '2024-01-01 12:00:00', 'p_001', 'scooter', 12.99, 1730346179000);
INSERT INTO flink.versioned_rates
(operation_code, update_time, product_id, product_name, price, time_long)
VALUES(2, '2024-01-01 12:00:00', 'p_002', 'basketball', 23.11, 1730346179000);
INSERT INTO flink.versioned_rates
(operation_code, update_time, product_id, product_name, price, time_long)
VALUES(3, '2024-01-01 12:00:00', 'p_002', 'basketball', 19.99, 1730346179000);
INSERT INTO flink.versioned_rates
(operation_code, update_time, product_id, product_name, price, time_long)
VALUES(4, '2024-01-01 18:00:00', 'p_001', 'scooter', 12.99, 1730346179000);

flinksql代码

package com.pg.TableAndDataStreamApi;



import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.table.api.config.TableConfigOptions;


/*
*
* */
public class version_table {
    private static final String SOURCE="CREATE TABLE source_table(\n" +
            "\toperation_code int,\n" +
            "\tupdate_time string,\n" +
            "\tup_t AS TO_TIMESTAMP(update_time),\n" +
            "\ttime_long bigint,\n" +
            "\tbbb AS TO_TIMESTAMP_LTZ(time_long,3) \n" +
            "    ) WITH (\n" +
            "   'connector' = 'jdbc',\n" +
            "   'url' = 'jdbc:mysql://ip:3306/flink',\n" +
            "   'driver'='com.mysql.cj.jdbc.Driver',\n "+
            "   'username'='用户名',\n"+
            "   'password'='密码',\n"+
            "   'table-name' = 'versioned_rates'\n" +
            ")";

    public static void main(String[] args) throws Exception {
        // 创建执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);

        tableEnv.executeSql(SOURCE);
        Configuration configuration = new Configuration();
//        configuration.set(TableConfigOptions.LOCAL_TIME_ZONE, "UTC");
        configuration.set(TableConfigOptions.LOCAL_TIME_ZONE, "Asia/Shanghai");

        tableEnv.getConfig().addConfiguration(configuration);
        // 从 MySQL 表中选择所有行
        Table t = tableEnv.sqlQuery("select * from source_table");
        t.execute().print();


    }
}