Azure 数据块。 java 从 sql 数据库读取数据时出错

Question

我有几个笔记本，我在其中连接到 sql 服务器并通过查询检索数据。但是，现在我有一个笔记本，我需要从同一个服务器获取数据，但另一个数据库。

代码：

sql_fcd = "(SELECT column_a, columns_b FROM myTable) a"

df_fcd = spark.read.jdbc(url = jdbcMetadataParams["url"], table = "FCD.snelheidStatistiekenSegment", properties = jdbcMetadataParams["properties"])

这会导致错误：

java.lang.IndexOutOfBoundsException: Index: 65535, Size: 0

当然我检查了 spark.read.jdbc 命令中使用的参数。 Url for sql-server/database 用户名和密码都可以。

当我将查询中的 tablename 更改为不存在的 table 时，我收到一个错误，指出该表不存在（如预期的那样）。所以连接属性没问题。我还尝试了数据库中存在的另一个表格，但它给出了同样的错误。

什么会导致此错误？是否需要在数据库级别进行配置？

完整错误：

Py4JJavaError                             Traceback (most recent call last)
<command-2272842214196692> in <module>
     18 # put data in dataframes
     19 #df_basis = spark.sql(sql_basis)
---> 20 df_koppeltabel = spark.read.jdbc(url = jdbcMetadataParams["url"], table = sqlKoppeltabel, properties = jdbcMetadataParams["properties"])

/databricks/spark/python/pyspark/sql/readwriter.py in jdbc(self, url, table, column, lowerBound, upperBound, numPartitions, predicates, properties)
    632             jpredicates = utils.toJArray(gateway, gateway.jvm.java.lang.String, predicates)
    633             return self._df(self._jreader.jdbc(url, table, jpredicates, jprop))
--> 634         return self._df(self._jreader.jdbc(url, table, jprop))
    635 
    636 

/databricks/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py in __call__(self, *args)
   1303         answer = self.gateway_client.send_command(command)
   1304         return_value = get_return_value(
-> 1305             answer, self.gateway_client, self.target_id, self.name)
   1306 
   1307         for temp_arg in temp_args:

/databricks/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
    125     def deco(*a, **kw):
    126         try:
--> 127             return f(*a, **kw)
    128         except py4j.protocol.Py4JJavaError as e:
    129             converted = convert_exception(e.java_exception)

/databricks/spark/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
    326                 raise Py4JJavaError(
    327                     "An error occurred while calling {0}{1}{2}.\n".
--> 328                     format(target_id, ".", name), value)
    329             else:
    330                 raise Py4JError(

Py4JJavaError: An error occurred while calling o777.jdbc.
: java.lang.IndexOutOfBoundsException: Index: 65535, Size: 0
    at java.util.ArrayList.rangeCheck(ArrayList.java:659)
    at java.util.ArrayList.get(ArrayList.java:435)
    at com.microsoft.sqlserver.jdbc.StreamColumns.processDataClassification(StreamColumns.java:303)
    at com.microsoft.sqlserver.jdbc.StreamColumns.setFromTDS(StreamColumns.java:228)
    at com.microsoft.sqlserver.jdbc.SQLServerResultSetCursorInitializer.onColMetaData(SQLServerResultSet.java:282)
    at com.microsoft.sqlserver.jdbc.TDSParser.parse(tdsparser.java:109)
    at com.microsoft.sqlserver.jdbc.TDSParser.parse(tdsparser.java:37)
    at com.microsoft.sqlserver.jdbc.SQLServerResultSet.<init>(SQLServerResultSet.java:391)
    at com.microsoft.sqlserver.jdbc.SQLServerStatement.getNextResult(SQLServerStatement.java:1642)
    at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.doExecutePreparedStatement(SQLServerPreparedStatement.java:600)
    at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement$PrepStmtExecCmd.doExecute(SQLServerPreparedStatement.java:522)
    at com.microsoft.sqlserver.jdbc.TDSCommand.execute(IOBuffer.java:7225)
    at com.microsoft.sqlserver.jdbc.SQLServerConnection.executeCommand(SQLServerConnection.java:3053)
    at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeCommand(SQLServerStatement.java:247)
    at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeStatement(SQLServerStatement.java:222)
    at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.executeQuery(SQLServerPreparedStatement.java:444)
    at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$.resolveTable(JDBCRDD.scala:61)
    at org.apache.spark.sql.execution.datasources.jdbc.JDBCRelation$.getSchema(JDBCRelation.scala:226)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:35)
    at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:387)
    at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:387)
    at org.apache.spark.sql.DataFrameReader.$anonfun$load(DataFrameReader.scala:376)
    at scala.Option.getOrElse(Option.scala:189)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:376)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:261)
    at org.apache.spark.sql.DataFrameReader.jdbc(DataFrameReader.scala:402)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:380)
    at py4j.Gateway.invoke(Gateway.java:295)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:251)
    at java.lang.Thread.run(Thread.java:748)

Answer 1

我们已经找到问题所在。在导致此错误的 sql 表格中，添加了敏感度分类。这会导致 Databricks 和 Datafactory 出现问题。删除这些分类解决了问题

Azure 数据块。 java 从 sql 数据库读取数据时出错

Azure databricks. java error by reading data from sql database

azure

jdbc

apache-spark-sql

databricks

indexoutofboundsexception