Pyspark itversity Traceback error - is pyspark stable to process all type of data format?



df =
18/02/18 08:02:42 INFO JSONRelation: Listing hdfs:// on driver
18/02/18 08:02:42 INFO MemoryStore: Block broadcast_2 stored as values in memory (estimated size 339.4 KB, free 1075.0 KB)
18/02/18 08:02:42 INFO MemoryStore: Block broadcast_2_piece0 stored as bytes in memory (estimated size 28.4 KB, free 1103.4 KB)
18/02/18 08:02:42 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on localhost:41623 (size: 28.4 KB, free: 511.0 MB)
18/02/18 08:02:42 INFO SparkContext: Created broadcast 2 from json at
Traceback (most recent call last):
File “”, line 1, in
File “/usr/hdp/”, line 176, in json
return self._df(self._jreader.json(path))
File “/usr/hdp/”, line 813, in call
File “/usr/hdp/”, line 45, in deco
return f(*a, **kw)
File “/usr/hdp/”, line 308, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o133.json.
: No input paths specified in job
at org.apache.hadoop.mapred.FileInputFormat.listStatus(
at org.apache.hadoop.mapred.FileInputFormat.getSplits(
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:199)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:242)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:240)
at scala.Option.getOrElse(Option.scala:120)