Question

以下是PySpark ETL代码的最后两行：

df_writer = DataFrameWriter(usage_fact)
df_writer.partitionBy("data_date", "data_product").saveAsTable(usageWideFactTable, format=fileFormat,mode=writeMode,path=usageWideFactpath)

其中，WriteMode = append和fileFormat = orc

我想使用insert overwrite代替这一点，以便在重新运行代码时不会附加我的数据。因此我用过这个：

usage_fact.createOrReplaceTempView("usage_fact")
fact = spark.sql("insert overwrite table " + usageWideFactTable + " partition (data_date, data_product) select * from  usage_fact")

但是这给了我以下错误：

Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/lib/spark/python/pyspark/sql/session.py", line 545, in sql
return DataFrame(self._jsparkSession.sql(sqlQuery), self._wrapped)
File "/usr/lib/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py", line 1133, in __call__
File "/usr/lib/spark/python/pyspark/sql/utils.py", line 69, in deco
raise AnalysisException(s.split(': ', 1)[1], stackTrace)
pyspark.sql.utils.AnalysisException: u'Cannot overwrite a path that is also being read from.;'

看起来我无法覆盖我正在阅读的路径，但不知道如何纠正它，因为我是PySpark的新手。我应该使用哪些确切的代码才能删除此问题？

Answer 1

上面的代码对我有用。我刚刚在DDL中进行了更改，并使用以下详细信息重新创建了表:(删除了属性，如果使用的话）

PARTITIONED BY (
`data_date` string,
`data_product` string)
ROW FORMAT SERDE
'org.apache.hadoop.hive.ql.io.orc.OrcSerde'
WITH SERDEPROPERTIES (
'path'='s3://saasdata/datawarehouse/fact/UsageFact/')
 STORED AS INPUTFORMAT
 'org.apache.hadoop.hive.ql.io.orc.OrcInputFormat'
 OUTPUTFORMAT
 'org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat'
LOCATION
 's3://saasdata/datawarehouse/fact/UsageFact/'

PySpark插入覆盖问题

1 个答案: