【发布时间】：2020-01-03 14:24:14
【问题描述】：
我有一个更大的查询，其中包含几个通过 WITH 子句构建的窗口函数。 此查询在使用 Pandas SQL 连接器或任何 SQL 浏览器的 Python 脚本执行的 amazon-rds 和 amazon-redshift 数据库上运行得非常好。 但是，如果我通过 Spark（来自 Pyspark）jdbs 连接器运行此查询，则会失败。 而且我找不到任何提示为什么 Spark 不吃这个查询。 欢迎任何提示。 谢谢 亚历克斯
我尝试了 Pandas 的 sql 和几个 SQL 浏览器 -> 效果很好 我用其他没有 WITH 子句语法的 SQL 语句尝试了 spark SQL 连接器 --> 效果很好
下面是简化的代码示例：
简化的 sql 查询
mysql_test="""
WITH my_raw_table AS
(
SELECT
created_utc || '@' || sub_order_nr AS order_column,
operation_type,
id_in,
id_type_in,
created_utc
FROM sample.table
)
SELECT DISTINCT
operation_type
,ROW_NUMBER() OVER window_desc AS row_number
,FIRST_VALUE(created_utc) OVER window_desc AS created_utc_first
,FIRST_VALUE(created_utc) OVER window_desc AS created_utc_last
,FIRST_VALUE(order_column) OVER window_desc AS order_column_first
,FIRST_VALUE(order_column) OVER window_desc AS order_column_last
FROM my_raw_table
WINDOW
window_desc AS (
PARTITION BY operation_type,id_type_in,id_in
ORDER BY order_column DESC
),
window_asc AS (
PARTITION BY operation_type,id_type_in,id_in
ORDER BY order_column ASC
)
ORDER BY
operation_type
,order_column_last
"""
适用于 Pandas 的代码
conn=my_modul.get_my_connection()
my_result = pd.read_sql(mysql_test,conn)
conn.close()
my_result.head()
使用 Spark jdbc 失败的代码
conn=my_modul.get_my_connection()
my_result = spark.read.jdbc(url=conn['url'], table=mysql_test, properties= conn['properties'])
my_result.show()
主要问题是它声称 WITH 为语法错误
Py4JJavaError: An error occurred while calling o551.jdbc.
: org.postgresql.util.PSQLException: ERROR: syntax error at or near "WITH"
我不明白为什么。
完整的错误信息是：
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<ipython-input-40-353e32a024e8> in <module>
11
12
---> 13 verbauwege_spark_sql = spark.read.jdbc(url=conn['url'], table=mysql_test, properties= conn['properties'])
14
15 row_count=verbauwege_spark_sql.count()
~/anaconda3/envs/Spark_Python3/lib/python3.7/site-packages/pyspark/sql/readwriter.py in jdbc(self, url, table, column, lowerBound, upperBound, numPartitions, predicates, properties)
554 jpredicates = utils.toJArray(gateway, gateway.jvm.java.lang.String, predicates)
555 return self._df(self._jreader.jdbc(url, table, jpredicates, jprop))
--> 556 return self._df(self._jreader.jdbc(url, table, jprop))
557
558
~/anaconda3/envs/Spark_Python3/lib/python3.7/site-packages/py4j/java_gateway.py in __call__(self, *args)
1255 answer = self.gateway_client.send_command(command)
1256 return_value = get_return_value(
-> 1257 answer, self.gateway_client, self.target_id, self.name)
1258
1259 for temp_arg in temp_args:
~/anaconda3/envs/Spark_Python3/lib/python3.7/site-packages/pyspark/sql/utils.py in deco(*a, **kw)
61 def deco(*a, **kw):
62 try:
---> 63 return f(*a, **kw)
64 except py4j.protocol.Py4JJavaError as e:
65 s = e.java_exception.toString()
~/anaconda3/envs/Spark_Python3/lib/python3.7/site-packages/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 o551.jdbc.
: org.postgresql.util.PSQLException: ERROR: syntax error at or near "WITH"
Position: 15
at org.postgresql.core.v3.QueryExecutorImpl.receiveErrorResponse(QueryExecutorImpl.java:2468)
at org.postgresql.core.v3.QueryExecutorImpl.processResults(QueryExecutorImpl.java:2211)
at org.postgresql.core.v3.QueryExecutorImpl.execute(QueryExecutorImpl.java:309)
at org.postgresql.jdbc.PgStatement.executeInternal(PgStatement.java:446)
at org.postgresql.jdbc.PgStatement.execute(PgStatement.java:370)
at org.postgresql.jdbc.PgPreparedStatement.executeWithFlags(PgPreparedStatement.java:149)
at org.postgresql.jdbc.PgPreparedStatement.executeQuery(PgPreparedStatement.java:108)
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:210)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:35)
at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:318)
at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:223)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:211)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:167)
at org.apache.spark.sql.DataFrameReader.jdbc(DataFrameReader.scala:238)
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:483)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:745)
【问题讨论】：
-
Spark 将表名按字面意思放在
SELECT ... FROM $table ...语句中，因此您必须将查询括在大括号中并将其转换为可以代替表名的有效子查询。 -
@HristoIliev 啊谢谢，这个提示解决了问题
标签： apache-spark pyspark apache-spark-sql amazon-redshift amazon-rds