Hi，
看起来应该是你之前改代码时引入的小bug，因为从代码路径和测试来看都不能复现这个问题。
另外，如果修改了源代码记得邮件里说明下，不然好南。。。。
祝好，
Leonard Xu
> 在 2020年4月23日，16:26，1101300123 <hdxg1101300...@163.com> 写道：
>
> 我重新在源码里打了一些日志编译后，之前的问题不见了，试了好多次没有复现了，之前因为集成clickhouse
> 改过源码的delete代码，不知道是不是这个引起的
> 在2020年4月23日 16:23，Leonard Xu<xbjt...@gmail.com> 写道：
> Hi,
> 我本地复现了下，用1.10.0发现的你的sql是ok的，结果也符合预期☺️，如下[1]：
> 看到你建了JIRA，我们在issue里继续跟进吧
>
> 祝好，
> Leonard Xu
>
> [1]
> mysql> select * from order_state_cnt;
> +------------+--------------+------+
> | order_date | product_code | cnt |
> +------------+--------------+------+
> | 2020-04-01 | product1 | 3 |
> | 2020-04-01 | product2 | 5 |
> | 2020-04-01 | product1 | 5 |
> | 2020-04-01 | product2 | 9 |
> +------------+--------------+------+
> 4 rows in set (0.00 sec)
>
> mysql> select * from order_state_cnt;
> +------------+--------------+------+
> | order_date | product_code | cnt |
> +------------+--------------+------+
> | 2020-04-01 | product1 | 3 |
> | 2020-04-01 | product2 | 5 |
> | 2020-04-01 | product1 | 5 |
> | 2020-04-01 | product2 | 9 |
> | 2020-04-01 | product1 | 2 |
> | 2020-04-01 | product2 | 4 |
> +------------+--------------+------+
> 6 rows in set (0.00 sec)
>
>
>
> 在 2020年4月23日，10:48，1101300123 <hdxg1101300...@163.com> 写道：
>
>
>
> 我给你一些数据和代码吧!和我真实场景错误一样
> 订单主表：orders
> 13点两条记录；order_state是状态 0取消 1待支付
> {"order_no":"order1","order_state":1,"pay_time":"","create_time":"2020-04-01
> 13:00:00","update_time":"2020-04-01 13:00:00"}
> {"order_no":"order2","order_state":1,"pay_time":"","create_time":"2020-04-01
> 13:00:00","update_time":"2020-04-01 13:00:00"}
>
>
> 13:15
> 来了一条新的记录 取消订单
> {"order_no":"order1","order_state":0,"pay_time":"","create_time":"2020-04-01
> 13:00:00","update_time":"2020-04-01 13:15:00"}
>
>
> 订单明细表：order_detail
> 4条记录
> {"order_no":"order1","product_code":"product1","quantity":3,"create_time":"2020-04-01
> 13:00:00","update_time":"2020-04-01 13:00:00"}
> {"order_no":"order1","product_code":"product2","quantity":5,"create_time":"2020-04-01
> 13:00:00","update_time":"2020-04-01 13:00:00"}
> {"order_no":"order2","product_code":"product1","quantity":2,"create_time":"2020-04-01
> 13:00:00","update_time":"2020-04-01 13:00:00"}
> {"order_no":"order2","product_code":"product2","quantity":4,"create_time":"2020-04-01
> 13:00:00","update_time":"2020-04-01 13:00:00"}
>
>
> 需求的要求是当订单创建后我们就要统计该订单对应的商品数量，而当订单状态变为取消时我们要减掉该订单对应的商品数量。
>
>
> 代码
> package Learn.kafkasql;
>
> import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
> import org.apache.flink.table.api.EnvironmentSettings;
> import org.apache.flink.table.api.Table;
> import org.apache.flink.table.api.java.StreamTableEnvironment;
> import org.apache.flink.types.Row;
>
> public class SqlCount {
> public static void main(String[] args) throws Exception {
> StreamExecutionEnvironment env
> =StreamExecutionEnvironment.getExecutionEnvironment();
> env.setParallelism(1);
> EnvironmentSettings settings =
> EnvironmentSettings.newInstance().useBlinkPlanner().inStreamingMode().build();
> StreamTableEnvironment tenv = StreamTableEnvironment.create(env,settings);
>
> tenv.sqlUpdate("CREATE TABLE orders " +
> " (" +
> " order_no string," +
> " order_state int," +
> " pay_time string," +
> " create_time string," +
> " update_time string" +
> " ) " +
> " WITH (" +
> " 'connector.type' = 'kafka', " +
> " 'connector.version' = 'universal', " +//--kafka版本
> " 'connector.topic' = 'tp_orders'," +//--kafkatopic
> " 'connector.properties.zookeeper.connect' =
> '192.168.179.120:2181', " +
> " 'connector.properties.bootstrap.servers' =
> '192.168.179.120:9092'," +
> " 'connector.properties.group.id' = 'testGroup'," +
> " 'connector.startup-mode' = 'latest-offset'," +
> " 'format.type' = 'json' " +//--数据为json格式
> " )");
> tenv.sqlUpdate("CREATE TABLE order_detail " +
> " (" +
> " order_no string," +
> " product_code string," +
> " quantity int," +
> " create_time string," +
> " update_time string" +
> " ) " +
> " WITH (" +
> " 'connector.type' = 'kafka', " +
> " 'connector.version' = 'universal', " +//--kafka版本
> " 'connector.topic' = 'tp_order_detail'," +//--kafkatopic
> " 'connector.properties.zookeeper.connect' =
> '192.168.179.120:2181', " +
> " 'connector.properties.bootstrap.servers' =
> '192.168.179.120:9092'," +
> " 'connector.properties.group.id' = 'testGroup'," +
> " 'connector.startup-mode' = 'latest-offset'," +
> " 'format.type' = 'json' " +//--数据为json格式
> " )");
>
> tenv.sqlUpdate("CREATE TABLE product_sale" +
> " (" +
> " order_date string," +
> " product_code string," +
> " cnt int" +
> " ) " +
> " WITH (" +
> " 'connector.type' = 'jdbc', " +
> " 'connector.url' =
> 'jdbc:mysql://192.168.179.120:3306/flink?serverTimezone=UTC&useSSL=true', " +
> " 'connector.table' = 'order_state_cnt', " +
> " 'connector.driver' = 'com.mysql.jdbc.Driver', " +
> " 'connector.username' = 'root'," +
> " 'connector.password' = '123456'," +
> " 'connector.write.flush.max-rows' = '1',"
> +//--默认每5000条数据写入一次，测试调小一点
> " 'connector.write.flush.interval' = '2s'," +//--写入时间间隔
> " 'connector.write.max-retries' = '3'" +
> " )");
> tenv.sqlUpdate("insert into product_sale " +
> "select create_date,product_code,sum(quantity)" +
> "from (select t1.order_no," +
> " t1.create_date," +
> " t2.product_code," +
> " t2.quantity" +
> " from (select order_no," +
> " order_state," +
> " substring(create_time,1,10) create_date," +
> " update_time ," +
> " row_number() over(partition by order_no order by
> update_time desc) as rn" +
> " from orders" +
> " )t1" +
> " left join order_detail t2" +
> " on t1.order_no=t2.order_no" +
> " where t1.rn=1" +//--取最新的订单状态数据
> " and t1.order_state<>0" +//--不包含取消订单
> " )t3" +
> " group by create_date,product_code");
>
> Table table = tenv.sqlQuery("select create_date,product_code,sum(quantity)" +
> "from (select t1.order_no," +
> " t1.create_date," +
> " t2.product_code," +
> " t2.quantity" +
> " from (select order_no," +
> " order_state," +
> " substring(create_time,1,10) create_date," +
> " update_time ," +
> " row_number() over(partition by order_no order by
> update_time desc) as rn" +
> " from orders" +
> " )t1" +
> " left join order_detail t2" +
> " on t1.order_no=t2.order_no" +
> " where t1.rn=1" +
> " and t1.order_state<>0" +
> " )t3" +
> " group by create_date,product_code");
> tenv.toRetractStream(table, Row.class).print();
> tenv.execute("count");
> }
> }
> mysql 建表语句
> CREATE TABLE `order_state_cnt` (
> `order_date` varchar(12) ,
> `product_code` varchar(12) ,
> `cnt` int
> ) ENGINE=InnoDB DEFAULT CHARSET=utf8
>
>
> 使用的是kafka命令行一条条发送数据的方式
>
>
> 主要是deleteStatement.executeBatch();这个方法报错
> @Override
> public void executeBatch() throws SQLException {
> if (keyToRows.size() > 0) {
> for (Map.Entry<Row, Tuple2<Boolean, Row>> entry : keyToRows.entrySet()) {
> Row pk = entry.getKey();
> Tuple2<Boolean, Row> tuple = entry.getValue();
> if (tuple.f0) {
> processOneRowInBatch(pk, tuple.f1);
> } else {
> setRecordToStatement(deleteStatement, pkTypes, pk);
> deleteStatement.addBatch();
> }
> }
> internalExecuteBatch();
> deleteStatement.executeBatch();
> keyToRows.clear();
> }
> }
> 在2020年4月23日 00:21，Leonard Xu<xbjt...@gmail.com> 写道：
> 赞详细的分析!
>
> 没能复现你说的问题，最后一步的分析应该有点小问题，我看下了jdbc mysql的实现
> com/mysql/jdbc/PreparedStatement.java#executeBatchInternal() 1289行
> 是会判断batchedArgs数组的大小后会直接返回的，应该不会执行，你可以进一步调试确认下
> ```
> if (this.batchedArgs == null || this.batchedArgs.size() == 0) {
> return new long[0];
> }
> ```
>
> 祝好，
> Leonard Xu
>
> 在 2020年4月22日，21:58，1101300123 <hdxg1101300...@163.com> 写道：
>
>
>
> 我在SQL关联后把结果写入mysql出现 No value specified for parameter 1错误？
> 我的版本是1.10.0，代码如下
> JDBCUpsertTableSink build = JDBCUpsertTableSink.builder()
> .setTableSchema(results.getSchema())
> .setOptions(JDBCOptions.builder()
> .setDBUrl("。。。。MultiQueries=true&useUnicode=true&characterEncoding=UTF-8")
> .setDriverName("com.mysql.jdbc.Driver")
> .setUsername("jczx_cjch")
> .setPassword("jczx_cjch2")
> .setTableName("xkf_join_result")
> .build())
> .setFlushIntervalMills(1000)
> .setFlushMaxSize(100)
> .setMaxRetryTimes(3)
> .build();
>
>
> DataStream<Tuple2<Boolean, Row>> retract =
> bsTableEnv.toRetractStream(results, Row.class);
> retract.print();
> build.emitDataStream(retract);
>
>
>
>
> 就会出现如下错误
> java.sql.SQLException: No value specified for parameter 1
> at com.mysql.jdbc.SQLError.createSQLException(SQLError.java:965)
> at com.mysql.jdbc.SQLError.createSQLException(SQLError.java:898)
> at com.mysql.jdbc.SQLError.createSQLException(SQLError.java:887)
> at com.mysql.jdbc.SQLError.createSQLException(SQLError.java:861)
> at
> com.mysql.jdbc.PreparedStatement.checkAllParametersSet(PreparedStatement.java:2211)
> at
> com.mysql.jdbc.PreparedStatement.fillSendPacket(PreparedStatement.java:2191)
> at
> com.mysql.jdbc.PreparedStatement.fillSendPacket(PreparedStatement.java:2121)
> at com.mysql.jdbc.PreparedStatement.execute(PreparedStatement.java:1162)
> at
> org.apache.flink.api.java.io.jdbc.writer.UpsertWriter.executeBatch(UpsertWriter.java:118)
> at
> org.apache.flink.api.java.io.jdbc.JDBCUpsertOutputFormat.flush(JDBCUpsertOutputFormat.java:159)
> at
> org.apache.flink.api.java.io.jdbc.JDBCUpsertSinkFunction.snapshotState(JDBCUpsertSinkFunction.java:56)
> at
> org.apache.flink.streaming.util.functions.StreamingFunctionUtils.trySnapshotFunctionState(StreamingFunctionUtils.java:118)
> at
> org.apache.flink.streaming.util.functions.StreamingFunctionUtils.snapshotFunctionState(StreamingFunctionUtils.java:99)
> at
> org.apache.flink.streaming.api.operators.AbstractUdfStreamOperator.snapshotState(AbstractUdfStreamOperator.java:90)
> at
> org.apache.flink.streaming.api.operators.AbstractStreamOperator.snapshotState(AbstractStreamOperator.java:402)
> at
> org.apache.flink.streaming.runtime.tasks.StreamTask$CheckpointingOperation.checkpointStreamOperator(StreamTask.java:1420)
> at
> org.apache.flink.streaming.runtime.tasks.StreamTask$CheckpointingOperation.executeCheckpointing(StreamTask.java:1354)
>
>
>
>
> 我的输出数据是(true,2020-04-22 21:34:00,2020-04-22
> 21:34:15,20200422213541465568468)是这样的
> 我查看源码发现
> 先调用JDBCUpsertOutputFormat类的writeRecord方法给UpsertWriter类的成员变量map中添加元素
> @Override
> public synchronized void writeRecord(Tuple2<Boolean, Row> tuple2) throws
> IOException {
> checkFlushException();
> try {
> jdbcWriter.addRecord(tuple2);
> batchCount++;
> if (batchCount >= flushMaxSize) {
> flush();
> }
> } catch (Exception e) {
> throw new RuntimeException("Writing records to JDBC failed.", e);
> }
> }
> 之后调用flush()方法，调用UpsertWriter类执行executeBatch方法
> public synchronized void flush() throws Exception {
> checkFlushException();
> for (int i = 1; i <= maxRetryTimes; i++) {
> try {
> jdbcWriter.executeBatch();
> batchCount = 0;
> break;
> } catch (SQLException e) {
> LOG.error("JDBC executeBatch error, retry times = {}", i, e);
> if (i >= maxRetryTimes) {
> throw e;
> }
> Thread.sleep(1000 * i);
> }
> }
> }
>
>
> 然后会调用UpsertWriter类
> 实现JDBCWriter类在executeBatch方法中先判断map是否为空，然后循环map；之后判断2元组第一个元素的true调用内部类处理元素，否则删除数据；但是我每次的数据只有一条就是map的大小是1，且2元组的第一个元素值是true，循环结束执行
> deleteStatement.executeBatch();方法就会出错，因为删除的语句站位符还没有填充；
>
>
> @Override
> public void executeBatch() throws SQLException {
> if (keyToRows.size() > 0) {
> for (Map.Entry<Row, Tuple2<Boolean, Row>> entry : keyToRows.entrySet()) {
> Row pk = entry.getKey();
> Tuple2<Boolean, Row> tuple = entry.getValue();
> if (tuple.f0) {
> processOneRowInBatch(pk, tuple.f1);
> } else {
> setRecordToStatement(deleteStatement, pkTypes, pk);
> deleteStatement.addBatch();
> }
> }
> internalExecuteBatch();
> deleteStatement.executeBatch();
> keyToRows.clear();
> }
> }
