问题
I wrote a DataFrame with pySpark into HDFS with this command:
df.repartition(col("year"))\
.write.option("maxRecordsPerFile", 1000000)\
.parquet('/path/tablename', mode='overwrite', partitionBy=["year"], compression='snappy')
When taking a look into the HDFS I can see that the files are properly laying there. Anyhow, when I try to read the table with HIVE or Impala, the table cannot be found.
Whats going wrong here, am I missing something?
Interestingly, df.write.format('parquet').saveAsTable("tablename") works properly.
回答1:
It's an expected behaviour from spark as:
df...etc.parquet("")writes the data to HDFS location and won't create any table in Hive.but
df..saveAsTable("")creates the table in hive and writes data to it.
In the case the table already exists, behavior of this function depends on the save mode, specified by the mode function (default to throwing an exception). When mode is Overwrite, the schema of the DataFrame does not need to be the same as that of the existing table.
That's the reason why you are not able to find table in hive after performing df...parquet("")
来源：https://stackoverflow.com/questions/56581105/dataframe-write-parquet-parquet-file-cannot-be-read-by-hive-or-impala