（Spark 和）Databricks 中的下推查询不适用于更复杂的 sql 查询？

Question

我是数据块的新手，所以希望我的问题不会太离谱。我正在尝试运行 Databricks Notebook 中的以下 sql 下推查询，以使用以下 python 代码从本地 sql 服务器获取数据：

pushdown_query1 = """(select * from dbo.myTabel X
                        INNER JOIN
                            (select Interval_Time, max(Run_Time) as Run_Time 
                            from dbo.myTabel 
                            group by Interval_Time) Y 
                                on X.Interval_Time = y.Interval_Time 
                                and X.Run_Time = y.Run_Time
                    WHERE RUNTYPE='TYPE_A') df"""

pushdown_query2 = """(select * from dbo.myTabel where RUNTYPE='TYPE_A') df"""

# connection information
jdbc_hostname = '<...>'
database = '<..>'
port = '1433'
username = '<...>'
password = '<...>'

connection_details = {
        "user": username,
        "password": password,
        "driver": "com.microsoft.sqlserver.jdbc.SQLServerDriver",
    }

jdbc_url = "jdbc:sqlserver://{0}:{1};databaseName={2}".format(jdbc_hostname, port, database)
# load stpas regionsolution data
df = spark.read.format("jdbc") \
          .option("url",jdbc_url) \
          .option("dbtable", pushdown_query1 )\
          .option("user", username) \
          .option("password", password) \
          .load()

df.show(100, truncate=False)

当我选择 pushdown_query2 时我没有任何问题并且我得到了我想要的，但是 pushdown_query1 returns 一个错误，我不确定这是不是因为我在语句中有 JOIN 和子查询或有其他问题。

选择pushdown_query1后出错：

---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
<command-2825826808916915> in <module>
     18             .option("dbtable", query)\
     19             .option("user", username) \
---> 20             .option("password", password) \
     21             .load()
     22 

/databricks/spark/python/pyspark/sql/readwriter.py in load(self, path, format, schema, **options)
    182             return self._df(self._jreader.load(self._spark._sc._jvm.PythonUtils.toSeq(path)))
    183         else:
--> 184             return self._df(self._jreader.load())
    185 
    186     @since(1.4)

/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 o586.load.
: com.microsoft.sqlserver.jdbc.SQLServerException: The column 'Interval_Time' was specified multiple times for 'df'.
    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.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$.getSchema(JDBCRelation.scala:226)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:35)
    at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:387)
    at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:384)
    at org.apache.spark.sql.DataFrameReader.$anonfun$load(DataFrameReader.scala:373)
    at scala.Option.getOrElse(Option.scala:189)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:373)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:258)
    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

您收到错误是因为您在同一个 table 上进行联接并在 select 语句中使用“*”。如果您根据为每个查询指定的别名显式指定列，那么您将不会看到收到的错误。

在您的情况下，列 Interval_Time 似乎被重复了，因为您在连接中使用的两个查询中 selecting 了它。所以明确指定列，它应该可以工作。

（Spark 和）Databricks 中的下推查询不适用于更复杂的 sql 查询？

Pushdown query in (Spark and) Databricks doesn't work for more complex sql queries?

sql-server

jdbc

apache-spark

azure-databricks