Re: Error when loading json to spark

[Raymond Xie]

Thank you very much Marco, is your code in Scala? do you have a python
example? Can anyone give me a python example to handle json data on Spark?


**
*Sincerely yours,*


*Raymond*

On Sun, Jan 1, 2017 at 12:29 PM, Marco Mistroni  wrote:

> Hi
>you will need to pass the schema, like in the snippet below (even
> though the code might have been superseeded in spark 2.0)
>
> import sqlContext.implicits._
> val jsonRdd = sc.textFile("file:///c:/tmp/1973-01-11.json")
> val schema = (new StructType).add("hour", StringType).add("month",
> StringType)
>   .add("second", StringType).add("year", StringType)
>   .add("timezone", StringType).add("day", StringType)
>   .add("minute", StringType)
> val jsonContentWithSchema = sqlContext.jsonRDD(jsonRdd, schema)
>
> But somehow i seem to remember that there was a way , in Spark 2.0, so
> that Spark will infer the schema  for you..
>
> hth
> marco
>
>
>
>
>
> On Sun, Jan 1, 2017 at 12:40 PM, Raymond Xie  wrote:
>
>> I found the cause:
>>
>> I need to "put" the json file onto hdfs first before it can be used, here
>> is what I did:
>>
>> hdfs dfs -put  /root/Downloads/data/json/world_bank.json
>> hdfs://localhost:9000/json
>> df = sqlContext.read.json("/json/")
>> df.show(10)
>>
>> .
>>
>> However, there is a new problem here, the json data needs to be sort of
>> treaked before it can be really used, simply using df =
>> sqlContext.read.json("/json/") just makes the df messy, I need the df know
>> the fields in the json file.
>>
>> How?
>>
>> Thank you.
>>
>>
>>
>>
>> **
>> *Sincerely yours,*
>>
>>
>> *Raymond*
>>
>> On Sat, Dec 31, 2016 at 11:52 PM, Miguel Morales > > wrote:
>>
>>> Looks like it's trying to treat that path as a folder, try omitting
>>> the file name and just use the folder path.
>>>
>>> On Sat, Dec 31, 2016 at 7:58 PM, Raymond Xie 
>>> wrote:
>>> > Happy new year!!!
>>> >
>>> > I am trying to load a json file into spark, the json file is attached
>>> here.
>>> >
>>> > I received the following error, can anyone help me to fix it? Thank
>>> you very
>>> > much. I am using Spark 1.6.2 and python 2.7.5
>>> >
>>>  from pyspark.sql import SQLContext
>>>  sqlContext = SQLContext(sc)
>>>  df = sqlContext.read.json("/root/Downloads/data/json/world_bank.j
>>> son")
>>> > 16/12/31 22:54:53 INFO json.JSONRelation: Listing
>>> > hdfs://localhost:9000/root/Downloads/data/json/world_bank.json on
>>> driver
>>> > 16/12/31 22:54:54 INFO storage.MemoryStore: Block broadcast_0 stored as
>>> > values in memory (estimated size 212.4 KB, free 212.4 KB)
>>> > 16/12/31 22:54:54 INFO storage.MemoryStore: Block broadcast_0_piece0
>>> stored
>>> > as bytes in memory (estimated size 19.6 KB, free 232.0 KB)
>>> > 16/12/31 22:54:54 INFO storage.BlockManagerInfo: Added
>>> broadcast_0_piece0 in
>>> > memory on localhost:39844 (size: 19.6 KB, free: 511.1 MB)
>>> > 16/12/31 22:54:54 INFO spark.SparkContext: Created broadcast 0 from
>>> json at
>>> > NativeMethodAccessorImpl.java:-2
>>> > Traceback (most recent call last):
>>> >   File "", line 1, in 
>>> >   File "/opt/spark/python/pyspark/sql/readwriter.py", line 176, in
>>> json
>>> > return self._df(self._jreader.json(path))
>>> >   File "/opt/spark/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py",
>>> line
>>> > 813, in __call__
>>> >   File "/opt/spark/python/pyspark/sql/utils.py", line 45, in deco
>>> > return f(*a, **kw)
>>> >   File "/opt/spark/python/lib/py4j-0.9-src.zip/py4j/protocol.py",
>>> line 308,
>>> > in get_return_value
>>> > py4j.protocol.Py4JJavaError: An error occurred while calling o19.json.
>>> > : java.io.IOException: No input paths specified in job
>>> > at
>>> > org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInpu
>>> tFormat.java:201)
>>> > at
>>> > org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInput
>>> Format.java:313)
>>> > at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:199)
>>> > at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
>>> > at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
>>> > at scala.Option.getOrElse(Option.scala:120)
>>> > at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
>>> > at
>>> > org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapParti
>>> tionsRDD.scala:35)
>>> > at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
>>> > at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
>>> > at scala.Option.getOrElse(Option.scala:120)
>>> > at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
>>> > at
>>> > org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapParti
>>> tionsRDD.scala:35)
>>> > at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
>>> > at 

Re: Error when loading json to spark

[Marco Mistroni]

Hi
   you will need to pass the schema, like in the snippet below (even though
the code might have been superseeded in spark 2.0)

import sqlContext.implicits._
val jsonRdd = sc.textFile("file:///c:/tmp/1973-01-11.json")
val schema = (new StructType).add("hour", StringType).add("month",
StringType)
  .add("second", StringType).add("year", StringType)
  .add("timezone", StringType).add("day", StringType)
  .add("minute", StringType)
val jsonContentWithSchema = sqlContext.jsonRDD(jsonRdd, schema)

But somehow i seem to remember that there was a way , in Spark 2.0, so that
Spark will infer the schema  for you..

hth
marco





On Sun, Jan 1, 2017 at 12:40 PM, Raymond Xie  wrote:

> I found the cause:
>
> I need to "put" the json file onto hdfs first before it can be used, here
> is what I did:
>
> hdfs dfs -put  /root/Downloads/data/json/world_bank.json
> hdfs://localhost:9000/json
> df = sqlContext.read.json("/json/")
> df.show(10)
>
> .
>
> However, there is a new problem here, the json data needs to be sort of
> treaked before it can be really used, simply using df =
> sqlContext.read.json("/json/") just makes the df messy, I need the df know
> the fields in the json file.
>
> How?
>
> Thank you.
>
>
>
>
> **
> *Sincerely yours,*
>
>
> *Raymond*
>
> On Sat, Dec 31, 2016 at 11:52 PM, Miguel Morales 
> wrote:
>
>> Looks like it's trying to treat that path as a folder, try omitting
>> the file name and just use the folder path.
>>
>> On Sat, Dec 31, 2016 at 7:58 PM, Raymond Xie 
>> wrote:
>> > Happy new year!!!
>> >
>> > I am trying to load a json file into spark, the json file is attached
>> here.
>> >
>> > I received the following error, can anyone help me to fix it? Thank you
>> very
>> > much. I am using Spark 1.6.2 and python 2.7.5
>> >
>>  from pyspark.sql import SQLContext
>>  sqlContext = SQLContext(sc)
>>  df = sqlContext.read.json("/root/Downloads/data/json/world_bank.
>> json")
>> > 16/12/31 22:54:53 INFO json.JSONRelation: Listing
>> > hdfs://localhost:9000/root/Downloads/data/json/world_bank.json on
>> driver
>> > 16/12/31 22:54:54 INFO storage.MemoryStore: Block broadcast_0 stored as
>> > values in memory (estimated size 212.4 KB, free 212.4 KB)
>> > 16/12/31 22:54:54 INFO storage.MemoryStore: Block broadcast_0_piece0
>> stored
>> > as bytes in memory (estimated size 19.6 KB, free 232.0 KB)
>> > 16/12/31 22:54:54 INFO storage.BlockManagerInfo: Added
>> broadcast_0_piece0 in
>> > memory on localhost:39844 (size: 19.6 KB, free: 511.1 MB)
>> > 16/12/31 22:54:54 INFO spark.SparkContext: Created broadcast 0 from
>> json at
>> > NativeMethodAccessorImpl.java:-2
>> > Traceback (most recent call last):
>> >   File "", line 1, in 
>> >   File "/opt/spark/python/pyspark/sql/readwriter.py", line 176, in json
>> > return self._df(self._jreader.json(path))
>> >   File "/opt/spark/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py",
>> line
>> > 813, in __call__
>> >   File "/opt/spark/python/pyspark/sql/utils.py", line 45, in deco
>> > return f(*a, **kw)
>> >   File "/opt/spark/python/lib/py4j-0.9-src.zip/py4j/protocol.py", line
>> 308,
>> > in get_return_value
>> > py4j.protocol.Py4JJavaError: An error occurred while calling o19.json.
>> > : java.io.IOException: No input paths specified in job
>> > at
>> > org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInpu
>> tFormat.java:201)
>> > at
>> > org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInput
>> Format.java:313)
>> > at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:199)
>> > at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
>> > at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
>> > at scala.Option.getOrElse(Option.scala:120)
>> > at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
>> > at
>> > org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapParti
>> tionsRDD.scala:35)
>> > at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
>> > at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
>> > at scala.Option.getOrElse(Option.scala:120)
>> > at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
>> > at
>> > org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapParti
>> tionsRDD.scala:35)
>> > at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
>> > at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
>> > at scala.Option.getOrElse(Option.scala:120)
>> > at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
>> > at org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1.apply(RDD.
>> scala:1129)
>> > at
>> > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperati
>> onScope.scala:150)
>> > at
>> > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperati
>> onScope.scala:111)
>> > at 

Re: Error when loading json to spark

[Raymond Xie]

I found the cause:

I need to "put" the json file onto hdfs first before it can be used, here
is what I did:

hdfs dfs -put  /root/Downloads/data/json/world_bank.json
hdfs://localhost:9000/json
df = sqlContext.read.json("/json/")
df.show(10)

.

However, there is a new problem here, the json data needs to be sort of
treaked before it can be really used, simply using df =
sqlContext.read.json("/json/") just makes the df messy, I need the df know
the fields in the json file.

How?

Thank you.




**
*Sincerely yours,*


*Raymond*

On Sat, Dec 31, 2016 at 11:52 PM, Miguel Morales 
wrote:

> Looks like it's trying to treat that path as a folder, try omitting
> the file name and just use the folder path.
>
> On Sat, Dec 31, 2016 at 7:58 PM, Raymond Xie  wrote:
> > Happy new year!!!
> >
> > I am trying to load a json file into spark, the json file is attached
> here.
> >
> > I received the following error, can anyone help me to fix it? Thank you
> very
> > much. I am using Spark 1.6.2 and python 2.7.5
> >
>  from pyspark.sql import SQLContext
>  sqlContext = SQLContext(sc)
>  df = sqlContext.read.json("/root/Downloads/data/json/world_
> bank.json")
> > 16/12/31 22:54:53 INFO json.JSONRelation: Listing
> > hdfs://localhost:9000/root/Downloads/data/json/world_bank.json on driver
> > 16/12/31 22:54:54 INFO storage.MemoryStore: Block broadcast_0 stored as
> > values in memory (estimated size 212.4 KB, free 212.4 KB)
> > 16/12/31 22:54:54 INFO storage.MemoryStore: Block broadcast_0_piece0
> stored
> > as bytes in memory (estimated size 19.6 KB, free 232.0 KB)
> > 16/12/31 22:54:54 INFO storage.BlockManagerInfo: Added
> broadcast_0_piece0 in
> > memory on localhost:39844 (size: 19.6 KB, free: 511.1 MB)
> > 16/12/31 22:54:54 INFO spark.SparkContext: Created broadcast 0 from json
> at
> > NativeMethodAccessorImpl.java:-2
> > Traceback (most recent call last):
> >   File "", line 1, in 
> >   File "/opt/spark/python/pyspark/sql/readwriter.py", line 176, in json
> > return self._df(self._jreader.json(path))
> >   File "/opt/spark/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py",
> line
> > 813, in __call__
> >   File "/opt/spark/python/pyspark/sql/utils.py", line 45, in deco
> > return f(*a, **kw)
> >   File "/opt/spark/python/lib/py4j-0.9-src.zip/py4j/protocol.py", line
> 308,
> > in get_return_value
> > py4j.protocol.Py4JJavaError: An error occurred while calling o19.json.
> > : java.io.IOException: No input paths specified in job
> > at
> > org.apache.hadoop.mapred.FileInputFormat.listStatus(
> FileInputFormat.java:201)
> > at
> > org.apache.hadoop.mapred.FileInputFormat.getSplits(
> FileInputFormat.java:313)
> > at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:199)
> > at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
> > at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
> > at scala.Option.getOrElse(Option.scala:120)
> > at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
> > at
> > org.apache.spark.rdd.MapPartitionsRDD.getPartitions(
> MapPartitionsRDD.scala:35)
> > at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
> > at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
> > at scala.Option.getOrElse(Option.scala:120)
> > at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
> > at
> > org.apache.spark.rdd.MapPartitionsRDD.getPartitions(
> MapPartitionsRDD.scala:35)
> > at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
> > at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
> > at scala.Option.getOrElse(Option.scala:120)
> > at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
> > at org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1.apply(
> RDD.scala:1129)
> > at
> > org.apache.spark.rdd.RDDOperationScope$.withScope(
> RDDOperationScope.scala:150)
> > at
> > org.apache.spark.rdd.RDDOperationScope$.withScope(
> RDDOperationScope.scala:111)
> > at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
> > at org.apache.spark.rdd.RDD.treeAggregate(RDD.scala:1127)
> > at
> > org.apache.spark.sql.execution.datasources.json.InferSchema$.infer(
> InferSchema.scala:65)
> > at
> > org.apache.spark.sql.execution.datasources.json.
> JSONRelation$$anonfun$4.apply(JSONRelation.scala:114)
> > at
> > org.apache.spark.sql.execution.datasources.json.
> JSONRelation$$anonfun$4.apply(JSONRelation.scala:109)
> > at scala.Option.getOrElse(Option.scala:120)
> > at
> > org.apache.spark.sql.execution.datasources.json.JSONRelation.dataSchema$
> lzycompute(JSONRelation.scala:109)
> > at
> > org.apache.spark.sql.execution.datasources.json.JSONRelation.dataSchema(
> JSONRelation.scala:108)
> > at
> > org.apache.spark.sql.sources.HadoopFsRelation.schema$
> lzycompute(interfaces.scala:636)
> > at
> > org.apache.spark.sql.sources.HadoopFsRelation.schema(
> interfaces.scala:635)
> > at
> > 

Re: Error when loading json to spark

[Raymond Xie]

Thank you Miguel, here is the output:

>>>df = sqlContext.read.json("/root/Downloads/data/json")
17/01/01 07:28:19 INFO json.JSONRelation: Listing
hdfs://localhost:9000/root/Downloads/data/json on driver
17/01/01 07:28:19 INFO storage.MemoryStore: Block broadcast_2 stored as
values in memory (estimated size 212.4 KB, free 444.5 KB)
17/01/01 07:28:19 INFO storage.MemoryStore: Block broadcast_2_piece0 stored
as bytes in memory (estimated size 19.6 KB, free 464.1 KB)
17/01/01 07:28:19 INFO storage.BlockManagerInfo: Added broadcast_2_piece0
in memory on localhost:39844 (size: 19.6 KB, free: 511.1 MB)
17/01/01 07:28:19 INFO spark.SparkContext: Created broadcast 2 from json at
NativeMethodAccessorImpl.java:-2
Traceback (most recent call last):
  File "", line 1, in 
  File "/opt/spark/python/pyspark/sql/readwriter.py", line 176, in json
return self._df(self._jreader.json(path))
  File "/opt/spark/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py", line
813, in __call__
  File "/opt/spark/python/pyspark/sql/utils.py", line 45, in deco
return f(*a, **kw)
  File "/opt/spark/python/lib/py4j-0.9-src.zip/py4j/protocol.py", line 308,
in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o115.json.
: java.io.IOException: No input paths specified in job
at
org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:201)
at
org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:313)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:199)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
at
org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
at
org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
at org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1.apply(RDD.scala:1129)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.RDD.treeAggregate(RDD.scala:1127)
at
org.apache.spark.sql.execution.datasources.json.InferSchema$.infer(InferSchema.scala:65)
at
org.apache.spark.sql.execution.datasources.json.JSONRelation$$anonfun$4.apply(JSONRelation.scala:114)
at
org.apache.spark.sql.execution.datasources.json.JSONRelation$$anonfun$4.apply(JSONRelation.scala:109)
at scala.Option.getOrElse(Option.scala:120)
at
org.apache.spark.sql.execution.datasources.json.JSONRelation.dataSchema$lzycompute(JSONRelation.scala:109)
at
org.apache.spark.sql.execution.datasources.json.JSONRelation.dataSchema(JSONRelation.scala:108)
at
org.apache.spark.sql.sources.HadoopFsRelation.schema$lzycompute(interfaces.scala:636)
at
org.apache.spark.sql.sources.HadoopFsRelation.schema(interfaces.scala:635)
at
org.apache.spark.sql.execution.datasources.LogicalRelation.(LogicalRelation.scala:37)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:125)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:109)
at org.apache.spark.sql.DataFrameReader.json(DataFrameReader.scala:244)
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:497)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
at py4j.Gateway.invoke(Gateway.java:259)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:209)
at java.lang.Thread.run(Thread.java:745)

>>>



**
*Sincerely yours,*


*Raymond*

On Sat, Dec 31, 2016 at 11:52 PM, Miguel Morales 
wrote:

> Looks like it's trying to treat that path as a folder, try omitting
> the file name and just use the folder path.
>
> On Sat, Dec 31, 2016 at 7:58 PM, Raymond Xie  wrote:
> > Happy new year!!!
> >
> > I am trying to load a json file into spark, the json file is attached
> here.
> >
> > I received the following error, can 

Re: Error when loading json to spark

[Miguel Morales]

Looks like it's trying to treat that path as a folder, try omitting
the file name and just use the folder path.

On Sat, Dec 31, 2016 at 7:58 PM, Raymond Xie  wrote:
> Happy new year!!!
>
> I am trying to load a json file into spark, the json file is attached here.
>
> I received the following error, can anyone help me to fix it? Thank you very
> much. I am using Spark 1.6.2 and python 2.7.5
>
 from pyspark.sql import SQLContext
 sqlContext = SQLContext(sc)
 df = sqlContext.read.json("/root/Downloads/data/json/world_bank.json")
> 16/12/31 22:54:53 INFO json.JSONRelation: Listing
> hdfs://localhost:9000/root/Downloads/data/json/world_bank.json on driver
> 16/12/31 22:54:54 INFO storage.MemoryStore: Block broadcast_0 stored as
> values in memory (estimated size 212.4 KB, free 212.4 KB)
> 16/12/31 22:54:54 INFO storage.MemoryStore: Block broadcast_0_piece0 stored
> as bytes in memory (estimated size 19.6 KB, free 232.0 KB)
> 16/12/31 22:54:54 INFO storage.BlockManagerInfo: Added broadcast_0_piece0 in
> memory on localhost:39844 (size: 19.6 KB, free: 511.1 MB)
> 16/12/31 22:54:54 INFO spark.SparkContext: Created broadcast 0 from json at
> NativeMethodAccessorImpl.java:-2
> Traceback (most recent call last):
>   File "", line 1, in 
>   File "/opt/spark/python/pyspark/sql/readwriter.py", line 176, in json
> return self._df(self._jreader.json(path))
>   File "/opt/spark/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py", line
> 813, in __call__
>   File "/opt/spark/python/pyspark/sql/utils.py", line 45, in deco
> return f(*a, **kw)
>   File "/opt/spark/python/lib/py4j-0.9-src.zip/py4j/protocol.py", line 308,
> in get_return_value
> py4j.protocol.Py4JJavaError: An error occurred while calling o19.json.
> : java.io.IOException: No input paths specified in job
> at
> org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:201)
> at
> org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:313)
> at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:199)
> at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
> at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
> at scala.Option.getOrElse(Option.scala:120)
> at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
> at
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
> at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
> at scala.Option.getOrElse(Option.scala:120)
> at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
> at
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
> at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
> at scala.Option.getOrElse(Option.scala:120)
> at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
> at org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1.apply(RDD.scala:1129)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
> at org.apache.spark.rdd.RDD.treeAggregate(RDD.scala:1127)
> at
> org.apache.spark.sql.execution.datasources.json.InferSchema$.infer(InferSchema.scala:65)
> at
> org.apache.spark.sql.execution.datasources.json.JSONRelation$$anonfun$4.apply(JSONRelation.scala:114)
> at
> org.apache.spark.sql.execution.datasources.json.JSONRelation$$anonfun$4.apply(JSONRelation.scala:109)
> at scala.Option.getOrElse(Option.scala:120)
> at
> org.apache.spark.sql.execution.datasources.json.JSONRelation.dataSchema$lzycompute(JSONRelation.scala:109)
> at
> org.apache.spark.sql.execution.datasources.json.JSONRelation.dataSchema(JSONRelation.scala:108)
> at
> org.apache.spark.sql.sources.HadoopFsRelation.schema$lzycompute(interfaces.scala:636)
> at
> org.apache.spark.sql.sources.HadoopFsRelation.schema(interfaces.scala:635)
> at
> org.apache.spark.sql.execution.datasources.LogicalRelation.(LogicalRelation.scala:37)
> at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:125)
> at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:109)
> at org.apache.spark.sql.DataFrameReader.json(DataFrameReader.scala:244)
> 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:497)
> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
> at py4j.Gateway.invoke(Gateway.java:259)
> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
> at