Azure data factory Azure数据流无法连接到私有云中的托管实例

我已经在Express Route对等子网下管理了实例，打开了公共端点，并配置了端口3342以允许公共端点访问，链接服务按预期工作，复制活动工作正常，但是，当使用dataflow sink时抛出以下错误

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

我正在使用内存优化的Azure托管IR，据我所知，Spark群集无法看到数据库服务器/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，然后在接收器中的数据流中单击“测试连接”，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

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提前感谢

这个问题已经在Mirosoft问答论坛上讨论过，OP能够解决这个问题，并分享了以下解决细节。以下是参考链接，以防任何人遇到类似问题：

问题： 如何打开并连接到SQL MI的公共端点，以及如何连接到复制/数据流活动的数据工厂

原因： 链接服务网络连接使用“Data Factory IP/服务标签”，而Data Flow在后端使用spark cluster，并且它们具有动态IP，该IP不是Data Factory服务标签的一部分

建议的解决方案： 由于此限制，在数据流中使用SQL MI有两个选项：

• 打开MI子网NSG中的源Internet和目标虚拟网络的端口3342
• 将数据流中的数据转移到Azure Blob/表存储复制活动到另一个源（SQL或Blob），然后继续数据流