You're a good man, Julien. Commenting out those lines from the pom.xml
fixed the problem. I can now create an RDD of GenericRecord objects, map
them to strings, and spit out the corresponding JSON from the interactive
spark-shell.
Just to recap how it works for me:
Set the SPARK_CLASSPATH to include the necessary Parquet jars:
export
SPARK_CLASSPATH="/Users/laserson/repos/parquet-mr/parquet-avro/target/parquet-avro-1.3.3-SNAPSHOT.jar:/Users/laserson/repos/parquet-mr/parquet-hadoop/target/parquet-hadoop-1.3.3-SNAPSHOT.jar:/Users/laserson/repos/parquet-mr/parquet-common/target/parquet-common-1.3.3-SNAPSHOT.jar:/Users/laserson/repos/parquet-mr/parquet-column/target/parquet-column-1.3.3-SNAPSHOT.jar:/Users/laserson/repos/parquet-format/target/parquet-format-2.0.1-SNAPSHOT.jar:/Users/laserson/repos/parquet-mr/parquet-jackson/target/parquet-jackson-1.3.3-SNAPSHOT.jar:/Users/laserson/repos/parquet-mr/parquet-encoding/target/parquet-encoding-1.3.3-SNAPSHOT.jar"
Run the Spark shell:
MASTER=local ~/repos/incubator-spark/bin/spark-shell
Then:
val job = new Job(sc.hadoopConfiguration)
ParquetInputFormat.setReadSupportClass(job,
classOf[AvroReadSupport[GenericRecord]])
val records1 =
sc.newAPIHadoopFile("/Users/laserson/temp/test-parquet/alltypeuri",
classOf[ParquetInputFormat[GenericRecord]], classOf[Void],
classOf[GenericRecord], job.getConfiguration)
val records2 = records1.map(p => p._2)
val records3 = records2.map(p => p.toString)
One thing that I now need to work out is that while records3 results in an
RDD of JSON strings, records2 gives me java.io.NotSerializableException:
org.apache.avro.generic.GenericData$Record, which I find surprising. Is
this expected behavior?
Thanks for all the help!
Uri
On Thu, Feb 6, 2014 at 9:30 AM, Julien Le Dem <[email protected]> wrote:
> Then probably just removing those 4 lines would fix it as parquet-avro
> does not use jackson outside of that (I think):
>
> https://github.com/Parquet/parquet-mr/blob/137b1e292eacbccb06c9723e9b86d2259045b860/parquet-avro/pom.xml#L101
> Can you try it out?
> Thanks
>
>
> On Thu, Feb 6, 2014 at 9:25 AM, Tom White <[email protected]> wrote:
>
>> On Thu, Feb 6, 2014 at 5:13 PM, Julien Le Dem <[email protected]> wrote:
>> > Hi Uri,
>> > Parquet shades Jackson to avoid dependency conflicts with Hadoop. Hadoop
>> > depends on an ancient version of Jackson, also Parquet works with
>> several
>> > versions of Hadoop independently of what jackson version they pull.
>> >
>> > It appears that this creates a problem in parquet-avro here:
>> >
>> https://github.com/Parquet/parquet-mr/blob/137b1e292eacbccb06c9723e9b86d2259045b860/parquet-avro/src/main/java/parquet/avro/AvroSchemaConverter.java#L191
>> >
>> > notice that NullNode here is a org.codehaus.jackson.node.NullNode which
>> > looks weird to me as we are building an Avro schema. Why would we use a
>> > Jackson type in there?
>>
>> Avro uses Jackson to construct default values since they are expressed
>> as JSON objects.
>>
>> >
>> > I see 2 solutions:
>> > - parquet-avro should not shade Jackson (but really I don't see why we
>> > depend on Jackson at all here)
>>
>> This is probably the best solution here, assuming Hadoop, Spark etc
>> all use the same (or at least compatible) versions of Jackson.
>>
>> > - AvroSchemaConverter should not depend on jackson.
>> >
>> > Do you know why the Avro abstraction is leaking jackson here?
>>
>> Unfortunately Avro does leak the Jackson dependency. There's been a
>> bit of discussion about avoiding this
>> (https://issues.apache.org/jira/browse/AVRO-1126), but not patches
>> yet.
>>
>> Tom
>>
>> >
>> >
>> >
>> >
>> > On Thu, Feb 6, 2014 at 12:40 AM, Uri Laserson <[email protected]>
>> wrote:
>> >>
>> >> I am skeptical that will solve my problem, though. Either way, I just
>> >> pulled the latest master and built that, and the same problem remains.
>> >>
>> >>
>> >> On Wed, Feb 5, 2014 at 7:50 PM, Prashant Sharma <[email protected]>
>> >> wrote:
>> >>>
>> >>> That cloneRecords parameter is gone, so either use the released 0.9.0
>> or
>> >>> the current master.
>> >>>
>> >>>
>> >>> On Thu, Feb 6, 2014 at 9:17 AM, Frank Austin Nothaft
>> >>> <[email protected]> wrote:
>> >>>>
>> >>>> Uri,
>> >>>>
>> >>>> Er, yes, it is the cloneRecords, and when I said true, I meant
>> false...
>> >>>> Apologies for the misdirection there.
>> >>>>
>> >>>>
>> >>>> Regards,
>> >>>>
>> >>>> Frank Austin Nothaft
>> >>>> [email protected]
>> >>>> [email protected]
>> >>>> 202-340-0466
>> >>>>
>> >>>> On Feb 5, 2014, at 7:44 PM, Uri Laserson <[email protected]>
>> wrote:
>> >>>>
>> >>>> My spark is 0.9.0-SNAPSHOT, built from wherever master was at the
>> time
>> >>>> (like a week or two ago).
>> >>>>
>> >>>> If you're referring to the cloneRecords parameter, it appears to
>> default
>> >>>> to true, but even when I add it explicitly, I get the same error.
>> >>>>
>> >>>>
>> >>>> On Wed, Feb 5, 2014 at 7:17 PM, Frank Austin Nothaft
>> >>>> <[email protected]> wrote:
>> >>>>>
>> >>>>> Uri,
>> >>>>>
>> >>>>> Which version of Spark are you running? If it is >0.9.0, you need to
>> >>>>> add an optional true argument at the end of the
>> sc.newApiHadoopFile(...) call
>> >>>>> to read Parquet data.
>> >>>>>
>> >>>>> Regards,
>> >>>>>
>> >>>>> Frank Austin Nothaft
>> >>>>> [email protected]
>> >>>>> [email protected]
>> >>>>> 202-340-0466
>> >>>>>
>> >>>>> On Feb 5, 2014, at 7:14 PM, Uri Laserson <[email protected]>
>> wrote:
>> >>>>>
>> >>>>> I am cross-posting on the parquet mailing list. Short recap: I am
>> >>>>> trying to read Parquet data from the spark interactive shell.
>> >>>>>
>> >>>>> I have added all the necessary parquet jars to SPARK_CLASSPATH:
>> >>>>>
>> >>>>> export
>> >>>>>
>> SPARK_CLASSPATH="/Users/laserson/repos/parquet-mr/parquet-avro/target/parquet-avro-1.3.3-SNAPSHOT.jar:/Users/laserson/repos/parquet-mr/parquet-hadoop/target/parquet-hadoop-1.3.3-SNAPSHOT.jar:/Users/laserson/repos/parquet-mr/parquet-common/target/parquet-common-1.3.3-SNAPSHOT.jar:/Users/laserson/repos/parquet-mr/parquet-column/target/parquet-column-1.3.3-SNAPSHOT.jar:/Users/laserson/repos/parquet-format/target/parquet-format-2.0.1-SNAPSHOT.jar:/Users/laserson/repos/parquet-mr/parquet-jackson/target/parquet-jackson-1.3.3-SNAPSHOT.jar"
>> >>>>>
>> >>>>> From the spark-shell, I run:
>> >>>>>
>> >>>>> val job = new Job(sc.hadoopConfiguration)
>> >>>>> ParquetInputFormat.setReadSupportClass(job,
>> >>>>> classOf[AvroReadSupport[GenericRecord]])
>> >>>>> val records1 =
>> >>>>> sc.newAPIHadoopFile("/Users/laserson/temp/test-parquet/alltypeuri",
>> >>>>> classOf[ParquetInputFormat[GenericRecord]], classOf[Void],
>> >>>>> classOf[GenericRecord], job.getConfiguration)
>> >>>>>
>> >>>>> Then I try
>> >>>>>
>> >>>>> records1.count
>> >>>>>
>> >>>>> Which gives the following error:
>> >>>>>
>> >>>>> 14/02/05 18:42:22 ERROR Executor: Exception in task ID 1
>> >>>>> java.lang.NoSuchMethodError:
>> >>>>>
>> org.apache.avro.Schema$Field.<init>(Ljava/lang/String;Lorg/apache/avro/Schema;Ljava/lang/String;Lparquet/org/codehaus/jackson/JsonNode;)V
>> >>>>> at
>> >>>>>
>> parquet.avro.AvroSchemaConverter.convertFields(AvroSchemaConverter.java:191)
>> >>>>> at
>> >>>>>
>> parquet.avro.AvroSchemaConverter.convert(AvroSchemaConverter.java:177)
>> >>>>> at
>> parquet.avro.AvroReadSupport.prepareForRead(AvroReadSupport.java:86)
>> >>>>> at
>> >>>>>
>> parquet.hadoop.InternalParquetRecordReader.initialize(InternalParquetRecordReader.java:142)
>> >>>>> at
>> >>>>>
>> parquet.hadoop.ParquetRecordReader.initializeInternalReader(ParquetRecordReader.java:118)
>> >>>>> at
>> >>>>>
>> parquet.hadoop.ParquetRecordReader.initialize(ParquetRecordReader.java:107)
>> >>>>> at
>> >>>>>
>> org.apache.spark.rdd.NewHadoopRDD$$anon$1.<init>(NewHadoopRDD.scala:106)
>> >>>>> at org.apache.spark.rdd.NewHadoopRDD.compute(NewHadoopRDD.scala:94)
>> >>>>> at org.apache.spark.rdd.NewHadoopRDD.compute(NewHadoopRDD.scala:57)
>> >>>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:241)
>> >>>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:232)
>> >>>>> at
>> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:109)
>> >>>>> at org.apache.spark.scheduler.Task.run(Task.scala:53)
>> >>>>> at
>> >>>>>
>> org.apache.spark.executor.Executor$TaskRunner$$anonfun$run$1.apply$mcV$sp(Executor.scala:213)
>> >>>>> at
>> >>>>>
>> org.apache.spark.deploy.SparkHadoopUtil.runAsUser(SparkHadoopUtil.scala:49)
>> >>>>> at
>> >>>>>
>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:178)
>> >>>>> at
>> >>>>>
>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>> >>>>> at
>> >>>>>
>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>> >>>>> at java.lang.Thread.run(Thread.java:744)
>> >>>>>
>> >>>>>
>> >>>>> My hypothesis is that this a shading problem. It appears that the
>> code
>> >>>>> is trying to call a constructor that looks like this:
>> >>>>>
>> >>>>> String.Field(String, Schema, String,
>> >>>>> parquet.org.codehaus.jackson.JsonNode)
>> >>>>>
>> >>>>> but the signature from the spark-assembly jar is
>> >>>>>
>> >>>>> public org.apache.avro.Schema$Field(java.lang.String,
>> >>>>> org.apache.avro.Schema, java.lang.String,
>> org.codehaus.jackson.JsonNode);
>> >>>>>
>> >>>>> Where do I go from here?
>> >>>>>
>> >>>>> Uri
>> >>>>>
>> >>>>>
>> >>>>>
>> >>>>>
>> >>>>>
>> >>>>>
>> >>>>>
>> >>>>> On Wed, Feb 5, 2014 at 5:02 PM, Uri Laserson <[email protected]
>> >
>> >>>>> wrote:
>> >>>>>>
>> >>>>>> Yep, I did not include that jar in the class path. Now I've got
>> some
>> >>>>>> "real" errors to try to work through. Thanks!
>> >>>>>>
>> >>>>>>
>> >>>>>> On Wed, Feb 5, 2014 at 3:52 PM, Jey Kottalam <[email protected]>
>> >>>>>> wrote:
>> >>>>>>>
>> >>>>>>> Hi Uri,
>> >>>>>>>
>> >>>>>>> Could you try adding the parquet-jackson JAR to your classpath?
>> There
>> >>>>>>> may possibly be other parquet-avro dependencies that are missing
>> too.
>> >>>>>>>
>> >>>>>>>
>> http://mvnrepository.com/artifact/com.twitter/parquet-jackson/1.3.2
>> >>>>>>>
>> >>>>>>> -Jey
>> >>>>>>>
>> >>>>>>> On Wed, Feb 5, 2014 at 3:02 PM, Uri Laserson <
>> [email protected]>
>> >>>>>>> wrote:
>> >>>>>>> > Yes, of course. That class is a jackson class, and I'm not sure
>> >>>>>>> > why it's
>> >>>>>>> > being referred to as
>> >>>>>>> > parquet.org.codehaus.jackson.JsonGenerationException.
>> >>>>>>> >
>> >>>>>>> > org.codehaus.jackson.JsonGenerationException is on the
>> classpath.
>> >>>>>>> > But not
>> >>>>>>> > when it's prefixed by parquet.
>> >>>>>>> >
>> >>>>>>> >
>> >>>>>>> > On Wed, Feb 5, 2014 at 12:06 PM, Andrew Ash <
>> [email protected]>
>> >>>>>>> > wrote:
>> >>>>>>> >>
>> >>>>>>> >> I'm assuming you checked all the jars in SPARK_CLASSPATH to
>> >>>>>>> >> confirm that
>> >>>>>>> >> parquet/org/codehaus/jackson/JsonGenerationException.class
>> exists
>> >>>>>>> >> in one of
>> >>>>>>> >> them?
>> >>>>>>> >>
>> >>>>>>> >>
>> >>>>>>> >> On Wed, Feb 5, 2014 at 12:02 PM, Uri Laserson
>> >>>>>>> >> <[email protected]>
>> >>>>>>> >> wrote:
>> >>>>>>> >>>
>> >>>>>>> >>> Has anyone tried this? I'd like to read a bunch of Avro
>> >>>>>>> >>> GenericRecords
>> >>>>>>> >>> from a Parquet file. I'm having a bit of trouble with respect
>> to
>> >>>>>>> >>> dependencies. My latest attempt looks like this:
>> >>>>>>> >>>
>> >>>>>>> >>> export
>> >>>>>>> >>>
>> >>>>>>> >>>
>> SPARK_CLASSPATH="/Users/laserson/repos/parquet-mr/parquet-avro/target/parquet-avro-1.3.3-SNAPSHOT.jar:/Users/laserson/repos/parquet-mr/parquet-hadoop/target/parquet-hadoop-1.3.3-SNAPSHOT.jar:/Users/laserson/repos/parquet-mr/parquet-common/target/parquet-common-1.3.3-SNAPSHOT.jar:/Users/laserson/repos/parquet-mr/parquet-column/target/parquet-column-1.3.3-SNAPSHOT.jar:/Users/laserson/repos/parquet-format/target/parquet-format-2.0.1-SNAPSHOT.jar"
>> >>>>>>> >>>
>> >>>>>>> >>> MASTER=local ~/repos/incubator-spark/bin/spark-shell
>> >>>>>>> >>>
>> >>>>>>> >>> Then in the shell:
>> >>>>>>> >>>
>> >>>>>>> >>> val records1 =
>> >>>>>>> >>>
>> >>>>>>> >>>
>> sc.newAPIHadoopFile("/Users/laserson/temp/test-parquet/alltypeuri",
>> >>>>>>> >>> classOf[AvroParquetInputFormat], classOf[Void],
>> >>>>>>> >>> classOf[IndexedRecord],
>> >>>>>>> >>> sc.hadoopConfiguration)
>> >>>>>>> >>> records1.collect
>> >>>>>>> >>>
>> >>>>>>> >>> At which point it barfs:
>> >>>>>>> >>>
>> >>>>>>> >>> 14/02/05 12:02:32 INFO FileInputFormat: Total input paths to
>> >>>>>>> >>> process : 3
>> >>>>>>> >>> SLF4J: Failed to load class
>> "org.slf4j.impl.StaticLoggerBinder".
>> >>>>>>> >>> SLF4J: Defaulting to no-operation (NOP) logger implementation
>> >>>>>>> >>> SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinderfor
>> >>>>>>> >>> further
>> >>>>>>> >>> details.
>> >>>>>>> >>> java.io.IOException: Could not read footer:
>> >>>>>>> >>> java.lang.NoClassDefFoundError:
>> >>>>>>> >>> parquet/org/codehaus/jackson/JsonGenerationException
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> parquet.hadoop.ParquetFileReader.readAllFootersInParallel(ParquetFileReader.java:189)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> parquet.hadoop.ParquetFileReader.readAllFootersInParallelUsingSummaryFiles(ParquetFileReader.java:145)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> parquet.hadoop.ParquetInputFormat.getFooters(ParquetInputFormat.java:354)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> parquet.hadoop.ParquetInputFormat.getFooters(ParquetInputFormat.java:339)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> parquet.hadoop.ParquetInputFormat.getSplits(ParquetInputFormat.java:246)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> org.apache.spark.rdd.NewHadoopRDD.getPartitions(NewHadoopRDD.scala:85)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:207)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:205)
>> >>>>>>> >>> at scala.Option.getOrElse(Option.scala:120)
>> >>>>>>> >>> at org.apache.spark.rdd.RDD.partitions(RDD.scala:205)
>> >>>>>>> >>> at
>> org.apache.spark.SparkContext.runJob(SparkContext.scala:863)
>> >>>>>>> >>> at org.apache.spark.rdd.RDD.collect(RDD.scala:602)
>> >>>>>>> >>> at $iwC$$iwC$$iwC$$iwC.<init>(<console>:20)
>> >>>>>>> >>> at $iwC$$iwC$$iwC.<init>(<console>:25)
>> >>>>>>> >>> at $iwC$$iwC.<init>(<console>:27)
>> >>>>>>> >>> at $iwC.<init>(<console>:29)
>> >>>>>>> >>> at <init>(<console>:31)
>> >>>>>>> >>> at .<init>(<console>:35)
>> >>>>>>> >>> at .<clinit>(<console>)
>> >>>>>>> >>> at .<init>(<console>:7)
>> >>>>>>> >>> at .<clinit>(<console>)
>> >>>>>>> >>> at $print(<console>)
>> >>>>>>> >>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>> >>>>>>> >>> at java.lang.reflect.Method.invoke(Method.java:606)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:772)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1040)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:609)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:640)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:604)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:788)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:833)
>> >>>>>>> >>> at
>> org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:745)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:593)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:600)
>> >>>>>>> >>> at org.apache.spark.repl.SparkILoop.loop(SparkILoop.scala:603)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> org.apache.spark.repl.SparkILoop$$anonfun$process$1.apply$mcZ$sp(SparkILoop.scala:926)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> org.apache.spark.repl.SparkILoop$$anonfun$process$1.apply(SparkILoop.scala:876)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> org.apache.spark.repl.SparkILoop$$anonfun$process$1.apply(SparkILoop.scala:876)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
>> >>>>>>> >>> at
>> org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:876)
>> >>>>>>> >>> at
>> org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:968)
>> >>>>>>> >>> at org.apache.spark.repl.Main$.main(Main.scala:31)
>> >>>>>>> >>> at org.apache.spark.repl.Main.main(Main.scala)
>> >>>>>>> >>> Caused by: java.lang.NoClassDefFoundError:
>> >>>>>>> >>> parquet/org/codehaus/jackson/JsonGenerationException
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> parquet.format.converter.ParquetMetadataConverter.fromParquetMetadata(ParquetMetadataConverter.java:359)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> parquet.format.converter.ParquetMetadataConverter.readParquetMetadata(ParquetMetadataConverter.java:312)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> parquet.hadoop.ParquetFileReader.readFooter(ParquetFileReader.java:295)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> parquet.hadoop.ParquetFileReader$2.call(ParquetFileReader.java:179)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> parquet.hadoop.ParquetFileReader$2.call(ParquetFileReader.java:175)
>> >>>>>>> >>> at java.util.concurrent.FutureTask.run(FutureTask.java:262)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>> >>>>>>> >>> at
>> >>>>>>> >>>
>> >>>>>>> >>>
>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>> >>>>>>> >>> at java.lang.Thread.run(Thread.java:744)
>> >>>>>>> >>> Caused by: java.lang.ClassNotFoundException:
>> >>>>>>> >>> parquet.org.codehaus.jackson.JsonGenerationException
>> >>>>>>> >>> at java.net.URLClassLoader$1.run(URLClassLoader.java:366)
>> >>>>>>> >>> at java.net.URLClassLoader$1.run(URLClassLoader.java:355)
>> >>>>>>> >>> at java.security.AccessController.doPrivileged(Native Method)
>> >>>>>>> >>> at java.net.URLClassLoader.findClass(URLClassLoader.java:354)
>> >>>>>>> >>> at java.lang.ClassLoader.loadClass(ClassLoader.java:425)
>> >>>>>>> >>> at
>> sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:308)
>> >>>>>>> >>> at java.lang.ClassLoader.loadClass(ClassLoader.java:358)
>> >>>>>>> >>> ... 9 more
>> >>>>>>> >>>
>> >>>>>>> >>>
>> >>>>>>> >>> --
>> >>>>>>> >>> Uri Laserson, PhD
>> >>>>>>> >>> Data Scientist, Cloudera
>> >>>>>>> >>> Twitter/GitHub: @laserson
>> >>>>>>> >>> +1 617 910 0447
>> >>>>>>> >>> [email protected]
>> >>>>>>> >>
>> >>>>>>> >>
>> >>>>>>> >
>> >>>>>>> >
>> >>>>>>> >
>> >>>>>>> > --
>> >>>>>>> > Uri Laserson, PhD
>> >>>>>>> > Data Scientist, Cloudera
>> >>>>>>> > Twitter/GitHub: @laserson
>> >>>>>>> > +1 617 910 0447
>> >>>>>>> > [email protected]
>> >>>>>>
>> >>>>>>
>> >>>>>>
>> >>>>>>
>> >>>>>> --
>> >>>>>> Uri Laserson, PhD
>> >>>>>> Data Scientist, Cloudera
>> >>>>>> Twitter/GitHub: @laserson
>> >>>>>> +1 617 910 0447
>> >>>>>> [email protected]
>> >>>>>
>> >>>>>
>> >>>>>
>> >>>>>
>> >>>>> --
>> >>>>> Uri Laserson, PhD
>> >>>>> Data Scientist, Cloudera
>> >>>>> Twitter/GitHub: @laserson
>> >>>>> +1 617 910 0447
>> >>>>> [email protected]
>> >>>>>
>> >>>>>
>> >>>>>
>> >>>>> --
>> >>>>> http://parquet.github.com/
>> >>>>> ---
>> >>>>> You received this message because you are subscribed to the Google
>> >>>>> Groups "Parquet" group.
>> >>>>> To post to this group, send email to [email protected].
>> >>>>
>> >>>>
>> >>>>
>> >>>>
>> >>>> --
>> >>>> Uri Laserson, PhD
>> >>>> Data Scientist, Cloudera
>> >>>> Twitter/GitHub: @laserson
>> >>>> +1 617 910 0447
>> >>>> [email protected]
>> >>>>
>> >>>>
>> >>>
>> >>>
>> >>>
>> >>> --
>> >>> Prashant
>> >>
>> >>
>> >>
>> >>
>> >> --
>> >> Uri Laserson, PhD
>> >> Data Scientist, Cloudera
>> >> Twitter/GitHub: @laserson
>> >> +1 617 910 0447
>> >> [email protected]
>> >>
>> >> --
>> >> http://parquet.github.com/
>> >> ---
>> >> You received this message because you are subscribed to the Google
>> Groups
>> >> "Parquet" group.
>> >> To post to this group, send email to [email protected].
>> >
>> >
>> > --
>> > http://parquet.github.com/
>> > ---
>> > You received this message because you are subscribed to the Google
>> Groups
>> > "Parquet" group.
>> > To post to this group, send email to [email protected].
>>
>
>
--
Uri Laserson, PhD
Data Scientist, Cloudera
Twitter/GitHub: @laserson
+1 617 910 0447
[email protected]
