我在Express Route对等子网下有托管实例，打开了公共端点，并提供了端口3342以允许公共端点访问，链接服务按预期工作，复制活动也很好，但是，当使用数据流接收器时，会引发以下错误
StatusCode":"DFExecutorUserError","Message":"Job failed due to reason: at Sink 'Group': java.lang.RuntimeException: Cannot connect to SQL database: 'jdbc:sqlserver://:3342;database=', 'User: '.[SQL Exception]Error Code:0, Error Message: The TCP/IP connection to the host .database.windows.net, port 3342 has failed. Error: "Connection timed out: no further information.. Verify the connection properties. Make sure that an instance of SQL Server is running on the host and accepting TCP/IP connections at the port. Make sure that TCP connections to the port are not blocked by a firewall."., error stack:shaded.msdataflow.com.microsoft.sqlserver.jdbc.SQLServerException.makeFromDriverError(SQLServerException.java:228)nshaded.msdataflow.com.microsoft.sqlserver.jdbc.SQLServerException.ConvertConnectExceptionToSQLServerException(SQLServerException.java:285)nshaded.msdataflow.com.microsoft.sq
我使用的是内存优化的Azure托管IR，据我所知，Spark集群无法查看数据库服务器/数据库。正如我上面提到的，链接服务测试连接是绿色的。
还尝试了以下选项：在设计器中打开数据流，然后单击"；测试连接"；在Sink中的数据流内部，并得到相同的错误。
Cannot connect to SQL database: 'jdbc:sqlserver://.database.windows.net:3342;database=', 'User: '.[SQL Exception]Error Code:0, Error Message: The TCP/IP connection to the host .database.windows.net, port 3342 has failed. Error: "Connection timed out: no further information.. Verify the connection properties. Make sure that an instance of SQL Server is running on the host and accepting TCP/IP connections at the port. Make sure that TCP connections to the port are not blocked by a firewall."., error stack:shaded.msdataflow.com.microsoft.sqlserver.jdbc.SQLServerException.makeFromDriverError(SQLServerException.java:228)
shaded.msdataflow.com.microsoft.sqlserver.jdbc.SQLServerException.ConvertConnectExceptionToSQLServerException(SQLServerException.java:285)
shaded.msdataflow.com.microsoft.sqlserver.jdbc.SocketFinder.findSocket(IOBuffer.java:2478)
shaded.msdataflow.com.microsoft.sqlserver.jdbc.TDSChannel.open(IOBuffer.java:641)
shaded.msdataflow.com.microsoft.sqlserver.jdbc.SQLServerConnection.connectHelper(SQLServerConnection.java:2245)
shaded.msdataflow.com.microsoft.sqlserver.jdbc.SQLServerConnection.login(SQLServerConnection.java:1921)
shaded.msdataflow.com.microso`enter code here`ft.sqlserver.jdbc.SQLServerConnection.connectInternal(SQLServerConnection.java:1762)
shaded.msdataflow.com.microsoft.sqlserver.jdbc.SQLServerConnection.connect(SQLServerConnection.java:1077)
shaded.msdataflow.com.microsoft.sqlserver.jdbc.SQLServerDriver.connect(SQLServerDriver.java:623)
com.microsoft.dataflow.store.mssql.CustomSqlServerDriver$$anonfun$3.apply(CustomSqlServerDriver.scala:48)
com.microsoft.dataflow.store.mssql.CustomSqlServerDriver$$anonfun$3.apply(CustomSqlServerDriver.scala:48)
scala.util.Try$.apply(Try.scala:192)
com.microsoft.dataflow.store.mssql.CustomSqlServerDriver.connect(CustomSqlServerDriver.scala:48)
org.apache.spark.sql.execution.datasources.jdbc.DriverWrapper.connect(DriverWrapper.scala:45)
org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:64)
org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$createConnectionFactory$1.apply(JdbcUtils.scala:55)
com.microsoft.dataflow.transformers.store.JDBCCharacteristic$class.newConnection(JDBCStore.scala:38)
com.microsoft.dataflow.store.mssql.MSSQLCharacteristic.newConnection(MSSQLStore.scala:78)
com.microsoft.dataflow.store.mssql.MSSQLStore$$anonfun$connect$1.apply$mcV$sp(MSSQLStore.scala:453)
com.microsoft.dataflow.store.mssql.MSSQLStore$$anonfun$connect$1.apply(MSSQLStore.scala:452)
com.microsoft.dataflow.store.mssql.MSSQLStore$$anonfun$connect$1.apply(MSSQLStore.scala:452)
scala.util.Try$.apply(Try.scala:192)
com.microsoft.dataflow.store.mssql.MSSQLStore.connect(MSSQLStore.scala:452)```code```
com.microsoft.dataflow.transformers.StoreDelegate.connect(StoreDefinition.scala:83)
com.microsoft.dataflow.DataflowJobFuture$$anonfun$connect$2.apply(DataflowJobFuture.scala:973)
com.microsoft.dataflow.DataflowJobFuture$$anonfun$connect$2.apply(DataflowJobFuture.scala:970)
scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
java.lang.Thread.run(Thread.java:748)
请提供您的专家建议以克服这一挑战。
提前感谢
这个问题已经在Mirosoft问答中讨论过了；一个论坛和OP解决了这个问题，并分享了以下解决细节。以下是参考链接，以防有人遇到类似问题：https://learn.microsoft.com/answers/questions/343550/index.html
问题：如何打开并连接到SQL MI的公共端点，以及连接到用于复制/数据流活动的数据工厂。
原因：链接服务网络连接使用"数据工厂IP的/服务标签"；而Data Flow在后端使用spark集群，并且它们具有不属于Data Factory Service Tag的动态IP。
建议的解决方案：由于此限制，在数据流中有两个使用SQL MI的选项：
- 打开端口3342到MI子网NSG中的源Internet和目标虚拟网络
- 将数据流中的数据暂存到Azure Blob/表存储复制活动到另一个源(SQL或Blob(，然后继续数据流