I have a Hive table that has multiple sub-directories in HDFS, something like:
/hdfs_dir/my_table_dir/my_table_sub_dir1
/hdfs_dir/my_table_dir/my_table_sub_dir2
...
Normally I set the following parameters before I run a Hive script:
set hive.input.dir.recursive=true;
set hive.mapred.supports.subdirectories=true;
set hive.supports.subdirectories=true;
set mapred.input.dir.recursive=true;
select * from my_db.my_table;
I'm trying to do the same using PySpark,
conf = (SparkConf().setAppName("My App")
...
.set("hive.input.dir.recursive", "true")
.set("hive.mapred.supports.subdirectories", "true")
.set("hive.supports.subdirectories", "true")
.set("mapred.input.dir.recursive", "true"))
sc = SparkContext(conf = conf)
sqlContext = HiveContext(sc)
my_table = sqlContext.sql("select * from my_db.my_table")
and end up with an error like:
java.io.IOException: Not a file: hdfs://hdfs_dir/my_table_dir/my_table_sub_dir1
What's the correct way to read a Hive table with sub-directories in Spark?