Hi Jey,
This solves the class not found problem. Thanks.
But still the inputs format is not yet resolved. Looks like it is still
trying to create a HadoopRDD I don't know why. The error message goes like -
java.lang.RuntimeException: Error in configuring object
at
org.apache.hadoop.util.ReflectionUtils.setJobConf(ReflectionUtils.java:109)
at
org.apache.hadoop.util.ReflectionUtils.setConf(ReflectionUtils.java:75)
at
org.apache.hadoop.util.ReflectionUtils.newInstance(ReflectionUtils.java:133)
at org.apache.spark.rdd.HadoopRDD.getInputFormat(HadoopRDD.scala:190)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:203)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
at
org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1251)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:148)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:109)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:286)
at org.apache.spark.rdd.RDD.take(RDD.scala:1246)
at org.apache.spark.rdd.RDD$$anonfun$first$1.apply(RDD.scala:1286)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:148)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:109)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:286)
at org.apache.spark.rdd.RDD.first(RDD.scala:1285)
at
com.databricks.spark.csv.CsvRelation.firstLine$lzycompute(CsvRelation.scala:129)
at com.databricks.spark.csv.CsvRelation.firstLine(CsvRelation.scala:127)
at
com.databricks.spark.csv.CsvRelation.inferSchema(CsvRelation.scala:109)
at com.databricks.spark.csv.CsvRelation.<init>(CsvRelation.scala:62)
at
com.databricks.spark.csv.DefaultSource.createRelation(DefaultSource.scala:115)
at
com.databricks.spark.csv.DefaultSource.createRelation(DefaultSource.scala:40)
at
com.databricks.spark.csv.DefaultSource.createRelation(DefaultSource.scala:28)
at org.apache.spark.sql.sources.ResolvedDataSource$.apply(ddl.scala:265)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:114)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:104)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:19)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:24)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:26)
at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:28)
at $iwC$$iwC$$iwC$$iwC.<init>(<console>:30)
at $iwC$$iwC$$iwC.<init>(<console>:32)
at $iwC$$iwC.<init>(<console>:34)
at $iwC.<init>(<console>:36)
at <init>(<console>:38)
at .<init>(<console>:42)
at .<clinit>(<console>)
at java.lang.J9VMInternals.initializeImpl(Native Method)
at java.lang.J9VMInternals.initialize(J9VMInternals.java:200)
at .<init>(<console>:7)
at .<clinit>(<console>)
at java.lang.J9VMInternals.initializeImpl(Native Method)
at java.lang.J9VMInternals.initialize(J9VMInternals.java:200)
at $print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:60)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:37)
at java.lang.reflect.Method.invoke(Method.java:611)
at
org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
at
org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1338)
at
org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
at
org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857)
at
org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
at org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:657)
at org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:665)
at org.apache.spark.repl.SparkILoop.org
$apache$spark$repl$SparkILoop$$loop(SparkILoop.scala:670)
at
org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:997)
at
org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
at
org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
at
scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
at org.apache.spark.repl.SparkILoop.org
$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
at org.apache.spark.repl.Main$.main(Main.scala:31)
at org.apache.spark.repl.Main.main(Main.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:60)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:37)
at java.lang.reflect.Method.invoke(Method.java:611)
at
org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:664)
at
org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:169)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:192)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:111)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.reflect.InvocationTargetException
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:60)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:37)
at java.lang.reflect.Method.invoke(Method.java:611)
at
org.apache.hadoop.util.ReflectionUtils.setJobConf(ReflectionUtils.java:106)
... 83 more
Regards,
Sourav
On Mon, Jun 29, 2015 at 6:53 PM, Jey Kottalam <j...@cs.berkeley.edu> wrote:
> The format is still "com.databricks.spark.csv", but the parameter passed
> to spark-shell is "--packages com.databricks:spark-csv_2.11:1.1.0".
>
> On Mon, Jun 29, 2015 at 2:59 PM, Sourav Mazumder <
> sourav.mazumde...@gmail.com> wrote:
>
>> HI Jey,
>>
>> Not much of luck.
>>
>> If I use the class com.databricks:spark-csv_2.
>> 11:1.1.0 or com.databricks.spark.csv_2.11.1.1.0 I get class not found
>> error. With com.databricks.spark.csv I don't get the class not found error
>> but I still get the previous error even after using file:/// in the URI.
>>
>> Regards,
>> Sourav
>>
>> On Mon, Jun 29, 2015 at 1:13 PM, Jey Kottalam <j...@cs.berkeley.edu>
>> wrote:
>>
>>> Hi Sourav,
>>>
>>> The error seems to be caused by the fact that your URL starts with
>>> "file://" instead of "file:///".
>>>
>>> Also, I believe the current version of the package for Spark 1.4 with
>>> Scala 2.11 should be "com.databricks:spark-csv_2.11:1.1.0".
>>>
>>> -Jey
>>>
>>> On Mon, Jun 29, 2015 at 12:23 PM, Sourav Mazumder <
>>> sourav.mazumde...@gmail.com> wrote:
>>>
>>>> Hi Jey,
>>>>
>>>> Thanks for your inputs.
>>>>
>>>> Probably I'm getting error as I'm trying to read a csv file from local
>>>> file using com.databricks.spark.csv package. Probably this package has hard
>>>> coded dependency on Hadoop as it is trying to read input format from
>>>> HadoopRDD.
>>>>
>>>> Can you please confirm ?
>>>>
>>>> Here is what I did -
>>>>
>>>> Ran the spark-shell as
>>>>
>>>> bin/spark-shell --packages com.databricks:spark-csv_2.10:1.0.3.
>>>>
>>>> Then in the shell I ran :
>>>> val df =
>>>> sqlContext.read.format("com.databricks.spark.csv").load("file://home/biadmin/DataScience/PlutoMN.csv")
>>>>
>>>>
>>>>
>>>> Regards,
>>>> Sourav
>>>>
>>>> 15/06/29 15:14:59 INFO spark.SparkContext: Created broadcast 0 from
>>>> textFile at CsvRelation.scala:114
>>>> java.lang.RuntimeException: Error in configuring object
>>>> at
>>>> org.apache.hadoop.util.ReflectionUtils.setJobConf(ReflectionUtils.java:109)
>>>> at
>>>> org.apache.hadoop.util.ReflectionUtils.setConf(ReflectionUtils.java:75)
>>>> at
>>>> org.apache.hadoop.util.ReflectionUtils.newInstance(ReflectionUtils.java:133)
>>>> at
>>>> org.apache.spark.rdd.HadoopRDD.getInputFormat(HadoopRDD.scala:190)
>>>> at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:203)
>>>> at
>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
>>>> at
>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
>>>> at scala.Option.getOrElse(Option.scala:120)
>>>> at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
>>>> at
>>>> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
>>>> at
>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
>>>> at
>>>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
>>>> at scala.Option.getOrElse(Option.scala:120)
>>>> at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
>>>> at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1251)
>>>> at
>>>> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:148)
>>>> at
>>>> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:109)
>>>> at org.apache.spark.rdd.RDD.withScope(RDD.scala:286)
>>>> at org.apache.spark.rdd.RDD.take(RDD.scala:1246)
>>>> at org.apache.spark.rdd.RDD$$anonfun$first$1.apply(RDD.scala:1286)
>>>> at
>>>> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:148)
>>>> at
>>>> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:109)
>>>> at org.apache.spark.rdd.RDD.withScope(RDD.scala:286)
>>>> at org.apache.spark.rdd.RDD.first(RDD.scala:1285)
>>>> at
>>>> com.databricks.spark.csv.CsvRelation.firstLine$lzycompute(CsvRelation.scala:114)
>>>> at
>>>> com.databricks.spark.csv.CsvRelation.firstLine(CsvRelation.scala:112)
>>>> at
>>>> com.databricks.spark.csv.CsvRelation.inferSchema(CsvRelation.scala:95)
>>>> at com.databricks.spark.csv.CsvRelation.<init>(CsvRelation.scala:53)
>>>> at
>>>> com.databricks.spark.csv.DefaultSource.createRelation(DefaultSource.scala:89)
>>>> at
>>>> com.databricks.spark.csv.DefaultSource.createRelation(DefaultSource.scala:39)
>>>> at
>>>> com.databricks.spark.csv.DefaultSource.createRelation(DefaultSource.scala:27)
>>>> at
>>>> org.apache.spark.sql.sources.ResolvedDataSource$.apply(ddl.scala:265)
>>>> at
>>>> org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:114)
>>>> at
>>>> org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:104)
>>>> at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:19)
>>>> at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:24)
>>>> at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:26)
>>>> at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:28)
>>>> at $iwC$$iwC$$iwC$$iwC.<init>(<console>:30)
>>>> at $iwC$$iwC$$iwC.<init>(<console>:32)
>>>> at $iwC$$iwC.<init>(<console>:34)
>>>> at $iwC.<init>(<console>:36)
>>>> at <init>(<console>:38)
>>>> at .<init>(<console>:42)
>>>> at .<clinit>(<console>)
>>>> at java.lang.J9VMInternals.initializeImpl(Native Method)
>>>> at java.lang.J9VMInternals.initialize(J9VMInternals.java:200)
>>>> at .<init>(<console>:7)
>>>> at .<clinit>(<console>)
>>>> at java.lang.J9VMInternals.initializeImpl(Native Method)
>>>> at java.lang.J9VMInternals.initialize(J9VMInternals.java:200)
>>>> at $print(<console>)
>>>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>>> at
>>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:60)
>>>> at
>>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:37)
>>>> at java.lang.reflect.Method.invoke(Method.java:611)
>>>> at
>>>> org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
>>>> at
>>>> org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1338)
>>>> at
>>>> org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
>>>> at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
>>>> at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
>>>> at
>>>> org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857)
>>>> at
>>>> org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
>>>> at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
>>>> at
>>>> org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:657)
>>>> at
>>>> org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:665)
>>>> at org.apache.spark.repl.SparkILoop.org
>>>> $apache$spark$repl$SparkILoop$$loop(SparkILoop.scala:670)
>>>> at
>>>> org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:997)
>>>> at
>>>> org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
>>>> at
>>>> org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
>>>> at
>>>> scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
>>>> at org.apache.spark.repl.SparkILoop.org
>>>> $apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
>>>> at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
>>>> at org.apache.spark.repl.Main$.main(Main.scala:31)
>>>> at org.apache.spark.repl.Main.main(Main.scala)
>>>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>>> at
>>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:60)
>>>> at
>>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:37)
>>>> at java.lang.reflect.Method.invoke(Method.java:611)
>>>> at
>>>> org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:664)
>>>> at
>>>> org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:169)
>>>> at
>>>> org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:192)
>>>> at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:111)
>>>> at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
>>>> Caused by: java.lang.reflect.InvocationTargetException
>>>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>>> at
>>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:60)
>>>> at
>>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:37)
>>>> at java.lang.reflect.Method.invoke(Method.java:611)
>>>> at
>>>> org.apache.hadoop.util.ReflectionUtils.setJobConf(ReflectionUtils.java:106)
>>>> ... 83 more
>>>>
>>>>
>>>>
>>>> On Mon, Jun 29, 2015 at 10:02 AM, Jey Kottalam <j...@cs.berkeley.edu>
>>>> wrote:
>>>>
>>>>> Actually, Hadoop InputFormats can still be used to read and write from
>>>>> "file://", "s3n://", and similar schemes. You just won't be able to
>>>>> read/write to HDFS without installing Hadoop and setting up an HDFS
>>>>> cluster.
>>>>>
>>>>> To summarize: Sourav, you can use any of the prebuilt packages (i.e.
>>>>> anything other than "source code").
>>>>>
>>>>> Hope that helps,
>>>>> -Jey
>>>>>
>>>>> On Mon, Jun 29, 2015 at 7:33 AM, ayan guha <guha.a...@gmail.com>
>>>>> wrote:
>>>>>
>>>>>> Hi
>>>>>>
>>>>>> You really donot need hadoop installation. You can dowsload a
>>>>>> pre-built version with any hadoop and unzip it and you are good to go.
>>>>>> Yes
>>>>>> it may complain while launching master and workers, safely ignore them.
>>>>>> The
>>>>>> only problem is while writing to a directory. Of course you will not be
>>>>>> able to use any hadoop inputformat etc. out of the box.
>>>>>>
>>>>>> ** I am assuming its a learning question :) For production, I would
>>>>>> suggest build it from source.
>>>>>>
>>>>>> If you are using python and need some help, please drop me a note off
>>>>>> line.
>>>>>>
>>>>>> Best
>>>>>> Ayan
>>>>>>
>>>>>> On Tue, Jun 30, 2015 at 12:24 AM, Sourav Mazumder <
>>>>>> sourav.mazumde...@gmail.com> wrote:
>>>>>>
>>>>>>> Hi,
>>>>>>>
>>>>>>> I'm trying to run Spark without Hadoop where the data would be read
>>>>>>> and written to local disk.
>>>>>>>
>>>>>>> For this I have few Questions -
>>>>>>>
>>>>>>> 1. Which download I need to use ? In the download option I don't see
>>>>>>> any binary download which does not need Hadoop. Is the only way to do
>>>>>>> this
>>>>>>> to download the source code version and compile the same ?
>>>>>>>
>>>>>>> 2. Which installation/quick start guideline I should use for the
>>>>>>> same. So far I didn't see any documentation which specifically addresses
>>>>>>> the Spark without Hadoop installation/setup unless I'm missing out one.
>>>>>>>
>>>>>>> Regards,
>>>>>>> Sourav
>>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>> --
>>>>>> Best Regards,
>>>>>> Ayan Guha
>>>>>>
>>>>>
>>>>>
>>>>
>>>
>>
>
