Your error log shows you attempting to read from 'people.parquet2' not ‘people.parquet’ as you’ve put below, is that just from a different attempt?
Otherwise, it’s an odd one! There aren’t _SUCCESS, _common_metadata and _metadata files under people.parquet that you’ve listed below, which would normally be created when the write completes, can you show us your write output? Thanks, Ewan From: Amila De Silva [mailto:jaa...@gmail.com] Sent: 03 September 2015 05:44 To: Guru Medasani <gdm...@gmail.com> Cc: user@spark.apache.org Subject: Re: Problem while loading saved data 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 <gdm...@gmail.com<mailto:gdm...@gmail.com>> 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 gdm...@gmail.com<mailto:gdm...@gmail.com> On Sep 2, 2015, at 8:25 PM, Amila De Silva <jaa...@gmail.com<mailto:jaa...@gmail.com>> 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<http://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<http://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
