Hi Guru,
Thanks for the reply.
Yes, I checked if the file exists. But instead of a single file what I
found was a directory having the following structure.
people.parquet
└── _temporary
└── 0
├── task_201509030057_4699_m_000000
│ └── part-r-00000-b921ed54-53fa-459b-881c-cccde7f79320.gz.parquet
├── task_201509030057_4699_m_000001
│ └── part-r-00001-b921ed54-53fa-459b-881c-cccde7f79320.gz.parquet
└── _temporary
On Thu, Sep 3, 2015 at 7:13 AM, Guru Medasani <[email protected]> wrote:
> Hi Amila,
>
> Error says that the ‘people.parquet’ file does not exist. Can you manually
> check to see if that file exists?
>
> Py4JJavaError: An error occurred while calling o53840.parquet.
> : java.lang.AssertionError: assertion failed: No schema defined, and no
> Parquet data file or summary file found under
> file:/home/ubuntu/ipython/people.parquet2.
>
>
>
> Guru Medasani
> [email protected]
>
>
>
> On Sep 2, 2015, at 8:25 PM, Amila De Silva <[email protected]> wrote:
>
> Hi All,
>
> I have a two node spark cluster, to which I'm connecting using IPython
> notebook.
> To see how data saving/loading works, I simply created a dataframe using
> people.json using the Code below;
>
> df = sqlContext.read.json("examples/src/main/resources/people.json")
>
> Then called the following to save the dataframe as a parquet.
> df.write.save("people.parquet")
>
> Tried loading the saved dataframe using;
> df2 = sqlContext.read.parquet('people.parquet');
>
> But this simply fails giving the following exception
>
> ---------------------------------------------------------------------------Py4JJavaError
> Traceback (most recent call
> last)<ipython-input-97-35f91873c48f> in <module>()----> 1 df2 =
> sqlContext.read.parquet('people.parquet2');
> /srv/spark/python/pyspark/sql/readwriter.pyc in parquet(self, *path) 154
> [('name', 'string'), ('year', 'int'), ('month', 'int'), ('day', 'int')]
> 155 """--> 156 return
> self._df(self._jreader.parquet(_to_seq(self._sqlContext._sc, path))) 157
> 158 @since(1.4)
> /srv/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py in
> __call__(self, *args) 536 answer =
> self.gateway_client.send_command(command) 537 return_value =
> get_return_value(answer, self.gateway_client,--> 538
> self.target_id, self.name) 539 540 for temp_arg in temp_args:
> /srv/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py in
> get_return_value(answer, gateway_client, target_id, name) 298
> raise Py4JJavaError( 299 'An error occurred while
> calling {0}{1}{2}.\n'.--> 300 format(target_id, '.',
> name), value) 301 else: 302 raise Py4JError(
> Py4JJavaError: An error occurred while calling o53840.parquet.
> : java.lang.AssertionError: assertion failed: No schema defined, and no
> Parquet data file or summary file found under
> file:/home/ubuntu/ipython/people.parquet2.
> at scala.Predef$.assert(Predef.scala:179)
> at
> org.apache.spark.sql.parquet.ParquetRelation2$MetadataCache.org$apache$spark$sql$parquet$ParquetRelation2$MetadataCache$$readSchema(newParquet.scala:429)
> at
> org.apache.spark.sql.parquet.ParquetRelation2$MetadataCache$$anonfun$11.apply(newParquet.scala:369)
> at
> org.apache.spark.sql.parquet.ParquetRelation2$MetadataCache$$anonfun$11.apply(newParquet.scala:369)
> at scala.Option.orElse(Option.scala:257)
> at
> org.apache.spark.sql.parquet.ParquetRelation2$MetadataCache.refresh(newParquet.scala:369)
> at org.apache.spark.sql.parquet.ParquetRelation2.org
> <http://org.apache.spark.sql.parquet.parquetrelation2.org/>$apache$spark$sql$parquet$ParquetRelation2$$metadataCache$lzycompute(newParquet.scala:126)
> at org.apache.spark.sql.parquet.ParquetRelation2.org
> <http://org.apache.spark.sql.parquet.parquetrelation2.org/>$apache$spark$sql$parquet$ParquetRelation2$$metadataCache(newParquet.scala:124)
> at
> org.apache.spark.sql.parquet.ParquetRelation2$$anonfun$dataSchema$1.apply(newParquet.scala:165)
> at
> org.apache.spark.sql.parquet.ParquetRelation2$$anonfun$dataSchema$1.apply(newParquet.scala:165)
> at scala.Option.getOrElse(Option.scala:120)
> at
> org.apache.spark.sql.parquet.ParquetRelation2.dataSchema(newParquet.scala:165)
> at
> org.apache.spark.sql.sources.HadoopFsRelation.schema$lzycompute(interfaces.scala:506)
> at
> org.apache.spark.sql.sources.HadoopFsRelation.schema(interfaces.scala:505)
> at
> org.apache.spark.sql.sources.LogicalRelation.<init>(LogicalRelation.scala:30)
> at
> org.apache.spark.sql.SQLContext.baseRelationToDataFrame(SQLContext.scala:438)
> at
> org.apache.spark.sql.DataFrameReader.parquet(DataFrameReader.scala:264)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:601)
> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
> 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:207)
> at java.lang.Thread.run(Thread.java:722)
>
>
>
> I'm using spark-1.4.1-bin-hadoop2.6 with java 1.7.
>
> Thanks
> Amila
>
>
>
