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схема таблицы sql server

Когда я загружаю данные из excel на MS sql-сервер с помощью spark,и хотя все мои поля имеют тип varchar в таблице sql server, я получаю это нарушение. Я не знаю, как преодолеть это с помощью java-кода.

 at com.microsoft.sqlserver.jdbc.SQLServerException.makeFromDatabaseError(SQLServerException.java:262)  at com.microsoft.sqlserver.jdbc.SQLServerStatement.getNextResult(SQLServerStatement.java:1632)  at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.doExecutePreparedStatementBatch(SQLServerPreparedStatement.java:2814)  at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement$PrepStmtBatchExecCmd.doExecute(SQLServerPreparedStatement.java:2678)  at com.microsoft.sqlserver.jdbc.TDSCommand.execute(IOBuffer.java:7375)  at com.microsoft.sqlserver.jdbc.SQLServerConnection.executeCommand(SQLServerConnection.java:3206)  at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeCommand(SQLServerStatement.java:247)  at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeStatement(SQLServerStatement.java:222)  at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.executeBatch(SQLServerPreparedStatement.java:2079)  at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.savePartition(JdbcUtils.scala:686)  at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$saveTable$1(JdbcUtils.scala:858)  at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$saveTable$1$adapted(JdbcUtils.scala:856)  at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2(RDD.scala:994)  at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2$adapted(RDD.scala:994)  at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2133)  at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)  at org.apache.spark.scheduler.Task.run(Task.scala:127)  at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:444)  at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)  at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:447)  at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)  at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)  at java.lang.Thread.run(Thread.java:748) [task-result-getter-3] WARN org.apache.spark.scheduler.TaskSetManager - Lost task 2.0 in stage 5.0 (TID 19, 192.168.0.103, executor driver): com.microsoft.sqlserver.jdbc.SQLServerException: The incoming tabular data stream (TDS) remote procedure call (RPC) protocol stream is incorrect. Parameter 64 (""): The supplied value is not a valid instance of data type float. Check the source data for invalid values. An example of an invalid value is data of numeric type with scale greater than precision.  at com.microsoft.sqlserver.jdbc.SQLServerException.makeFromDatabaseError(SQLServerException.java:262)  at com.microsoft.sqlserver.jdbc.SQLServerStatement.getNextResult(SQLServerStatement.java:1632)  at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.doExecutePreparedStatementBatch(SQLServerPreparedStatement.java:2814)  at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement$PrepStmtBatchExecCmd.doExecute(SQLServerPreparedStatement.java:2678)  at com.microsoft.sqlserver.jdbc.TDSCommand.execute(IOBuffer.java:7375)  at com.microsoft.sqlserver.jdbc.SQLServerConnection.executeCommand(SQLServerConnection.java:3206)  at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeCommand(SQLServerStatement.java:247)  at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeStatement(SQLServerStatement.java:222)  at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.executeBatch(SQLServerPreparedStatement.java:2079)  at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.savePartition(JdbcUtils.scala:686)  at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$saveTable$1(JdbcUtils.scala:858)  at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$saveTable$1$adapted(JdbcUtils.scala:856)  at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2(RDD.scala:994)  at org.apache.spark.rdd.RDD.$anonfun$foreachPartition$2$adapted(RDD.scala:994)  at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2133)  at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)  at org.apache.spark.scheduler.Task.run(Task.scala:127)  at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:444)  at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)  at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:447)  at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)  at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)  at java.lang.Thread.run(Thread.java:748)