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这篇文章主要讲解了“FLINK 1.12 upsertSql怎么使用”，文中的讲解内容简单清晰，易于学习与理解，下面请大家跟着小编的思路慢慢深入，一起来研究和学习“FLINK 1.12 upsertSql怎么使用”吧！
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package com.konka.dsp;
import org.apache.flink.api.common.JobExecutionResult;
import org.apache.flink.api.common.restartstrategy.RestartStrategies;
import org.apache.flink.api.java.DataSet;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.connector.jdbc.dialect.MySQLDialect;
import org.apache.flink.connector.jdbc.internal.options.JdbcOptions;
import org.apache.flink.connector.jdbc.table.JdbcUpsertTableSink;
import org.apache.flink.formats.json.JsonFormatFactory;
import org.apache.flink.formats.json.canal.CanalJsonFormatFactory;
import org.apache.flink.shaded.curator4.org.apache.curator.framework.schema.Schema;
import org.apache.flink.streaming.api.CheckpointingMode;
import org.apache.flink.streaming.api.TimeCharacteristic;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.ExecutionCheckpointingOptions;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.*;
import org.apache.flink.table.api.bridge.java.BatchTableEnvironment;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.table.expressions.TimeIntervalUnit;
import org.apache.flink.table.types.DataType;
import org.apache.flink.types.Row;
import org.apache.flink.util.CloseableIterator;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.time.Duration;
import java.util.concurrent.ExecutionException;
import static org.apache.flink.table.api.Expressions.*;
public class SalesOrderStream {
private static Logger log = LoggerFactory.getLogger(SalesOrderStream.class.getName());
public static Table report(Table transactions) {
return transactions.select(
$("customer_name"),
$("created_date"),
$("total_amount"))
.groupBy($("customer_name"),$("created_date"))
.select(
$("customer_name"),
$("total_amount").sum().as("total_amount"),
$("created_date")
);
}
public static void main(String[] args) throws Exception {
StreamExecutionEnvironment env = StreamExecutionEnvironment
.getExecutionEnvironment();
// env.setParallelism(4);
// env.getConfig().setRestartStrategy(RestartStrategies.noRestart());
StreamTableEnvironment tEnv = StreamTableEnvironment.create(env);
// set default parallelism to 4
// tEnv.executeSql("CREATE TABLE sales_order_header_stream (\n" +
//// " id BIGINT not null,\n" +
// " customer_name STRING,\n"+
//// " dsp_org_name STRING,\n"+
// " total_amount DECIMAL(38,2),\n" +
//// " total_discount DECIMAL(16,2),\n" +
//// " pay_amount DECIMAL(16,2),\n" +
//// " total_amount DECIMAL(16,2),\n" +
// " created_date TIMESTAMP(3)\n" +
// ") WITH (\n" +
// " 'connector' = 'mysql-cdc',\n" +
// " 'hostname' = '192.168.8.73',\n" +
// " 'port' = '4000',\n"+
// " 'username' = 'flink',\n"+
// " 'password' = 'flink',\n"+
// " 'database-name' = 'dspdev',\n"+
// " 'table-name' = 'sales_order_header'\n"+
// ")");
//pay_type,over_sell
tEnv.executeSql("CREATE TABLE sales_order_header_stream (\n" +
" `id` BIGINT,\n"+
" `total_amount` DECIMAL(16,2) ,\n"+
" `customer_name` STRING,\n"+
" `order_no` STRING,\n"+
" `doc_type` STRING,\n"+
" `sales_org` STRING,\n"+
" `distr_chan` STRING,\n"+
" `division` STRING,\n"+
" `sales_grp` STRING,\n"+
" `sales_off` STRING,\n"+
" `purch_no_c` STRING,\n"+
" `purch_date` STRING,\n"+
" `sold_to` STRING,\n"+
" `ship_to` STRING,\n"+
" `r3_sales_order` STRING,\n"+
" `created_by_employee_name` STRING,\n"+
" `created_by_dept_name` STRING,\n"+
" `created_by_dept_name` STRING,\n"+
" `is_enable` BIGINT,\n"+
" `is_delete` BIGINT,\n"+
" `sale_order_status` STRING,\n"+
" `created_by_parent_dept_name` STRING,\n"+
" `total_discount` DECIMAL(16,2),\n"+
" `customer_sapcode` STRING,\n"+
" `sold_to_name` STRING,\n"+
" `ship_to_name` STRING,\n"+
" `total_discount_amount` DECIMAL(16,2),\n"+
" `other_discount` DECIMAL(16,2),\n"+
" `other_amount` DECIMAL(16,2),\n"+
" `pay_amount` DECIMAL(16,2),\n"+
" `dsp_org_name` STRING,\n"+
" `delivery_address` STRING,\n"+
" `delivery_person` STRING,\n"+
" `delivery_phone` STRING,\n"+
" `pay_type` STRING,\n"+
" `over_sell` STRING,\n"+
" `created_date` TIMESTAMP(3),\n"+
" PRIMARY KEY (`id`) NOT ENFORCED "+
") WITH (\n" +
"'connector' = 'kafka',\n"+
"'topic' = 'canal-data',\n"+
"'properties.bootstrap.servers' = '192.168.8.71:9092',\n"+
"'properties.group.id' = 'test',\n"+
"'format' = 'canal-json'\n"+
")");
// tEnv.executeSql("CREATE TABLE total_day_report (\n" +
// " customer_name STRING,\n" +
//// " total_amount DECIMAL(16,2),\n" +
//// " total_discount DECIMAL(16,2),\n" +
//// " pay_amount DECIMAL(16,2),\n" +
// " total_amount DECIMAL(16,2),\n" +
// " created_date STRING,\n" +
// " PRIMARY KEY (created_date) NOT ENFORCED" +
// ") WITH (\n" +
// " 'connector' = 'upsert-kafka',\n" +
// " 'topic' = 'customer_amount',\n" +
// " 'properties.bootstrap.servers' = '192.168.8.71:9092',\n"+
// " 'key.format' = 'json',\n"+
// " 'value.format' = 'json',\n"+
// " 'value.fields-include' = 'ALL'\n"+
// ")");
tEnv.executeSql("CREATE TABLE upsertSink (\n" +
" customer_name STRING,\n" +
// " total_amount DECIMAL(16,2),\n" +
// " total_discount DECIMAL(16,2),\n" +
// " pay_amount DECIMAL(16,2),\n" +
" total_amount DECIMAL(16,2),\n" +
" created_date STRING,\n" +
" PRIMARY KEY (customer_name,created_date) NOT ENFORCED" +
") WITH (\n" +
" 'connector' = 'tidb',\n" +
" 'tidb.database.url' = 'jdbc:mysql://192.168.8.73:4000/dspdev',\n" +
" 'tidb.username' = 'flink',\n"+
" 'tidb.password' = 'flink',\n"+
" 'tidb.database.name' = 'dspdev',\n"+
" 'tidb.table.name' = 'spend_report'\n"+
// " 'connector.type'='jdbc'," +
// " 'connector.url'='jdbc:mysql://192.168.8.73:4000/dspdev',\n" +
// " 'connector.username' = 'flink',\n"+
// " 'connector.password' = 'flink',\n"+
// " 'connector.table' = 'spend_report'" +
")");
// TableSchema tableSche = TableSchema.builder()
// .field("customer_name",DataTypes.STRING().notNull())
// .field("total_amount",DataTypes.DECIMAL(16,2))
// .field("created_date",DataTypes.STRING().notNull()).build();
//
// JdbcOptions jdbcOptions = JdbcOptions.builder()
// .setDBUrl("jdbc:mysql://192.168.8.73:4000/dspdev")
// .setTableName("spend_report")
// .setUsername("flink")
// .setPassword("flink")
// .setDialect(new MySQLDialect())
// .setDriverName("com.mysql.jdbc.Driver")
// .build();
// JdbcUpsertTableSink jdbcUpsertTableSink = JdbcUpsertTableSink.builder()
// .setTableSchema(tableSche)
// .setOptions(jdbcOptions)
// .build();
// jdbcUpsertTableSink.setKeyFields(new String[]{"id"});
/**
* SINK End
*/
// tEnv.re("spend_report",jdbcUpsertTableSink);
Table transactions = tEnv.from("sales_order_header_stream");
// tEnv.executeSql("delete from total_day_report");
tEnv.executeSql("insert into upsertSink select dsp_org_name as customer_name,cast(sum(t.pay_amount) as decimal(16,2)) as amount,DATE_FORMAT(t.created_date,'yyyy-MM-dd') as created_date from sales_order_header_stream t group by DATE_FORMAT(t.created_date,'yyyy-MM-dd'),dsp_org_name").print();
// tEnv.executeSql("insert into spend_report select * from total_day_report");
// Table transactions = tEnv.from("total_day_report");
// report(transactions).executeInsert("spend_report");
tEnv.execute("-----------");
}
}最后数据库结果如下:
每次都是更新替换，这样的话省去很多麻烦，不用转datastream在处理了，而且1.12支持upsert-kafka，最后数据叠加如下: 
upsert-kafka上面已经体现
感谢各位的阅读，以上就是“FLINK 1.12 upsertSql怎么使用”的内容了，经过本文的学习后，相信大家对FLINK 1.12 upsertSql怎么使用这一问题有了更深刻的体会，具体使用情况还需要大家实践验证。这里是创新互联，小编将为大家推送更多相关知识点的文章，欢迎关注！