collect() returns the contents of the RDD back to the Driver in a local
variable. Where is the local variable?
Try
val result = rdd.map(x => x + 1).collect()
regards,
Apostolos
On 21/2/20 21:28, Nikhil Goyal wrote:
Hi all,
I am trying to use almond scala kernel to run spark session on
Ju
Hi all,
I am trying to use almond scala kernel to run spark session on Jupyter. I
am using scala version 2.12.8. I am creating spark session with master set
to Yarn.
This is the code:
val rdd = spark.sparkContext.parallelize(Seq(1, 2, 4))
rdd.map(x => x + 1).collect()
Exception:
java.lang.ClassC
d Boolean, which are serializable by
default. So you can change the definition to function, instead of method, which
should work.
Yong
From: Darshan Pandya
Sent: Friday, February 17, 2017 10:36 PM
To: user
Subject: Serialization error - sql UDF related
Hello,
Hi Darshan ,
When you get org.apache.spark.SparkException: Task not serializable
exception, it means that you are using a reference to an instance of a
non-serialize class inside a transformation.
Hope following link will help.
https://databricks.gitbooks.io/databricks-spark-knowledge-base/cont
Hello,
I am getting the famous serialization exception on running some code as
below,
val correctColNameUDF = udf(getNewColumnName(_: String, false:
Boolean): String);
val charReference: DataFrame = thinLong.select("char_name_id",
"char_name").withColumn("columnNameInDimTable",
correctColNameUDF(
de the following line:
>
>
> any help appreciated.
>
>
>
>
>
> --
> View this message in context:
> http://apache-spark-user-list.1001560.n3.nabble.com/serialization-error-tp25131.html
> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>
if i exclude the following line:
>
>
> any help appreciated.
>
>
>
>
>
> --
> View this message in context:
> http://apache-spark-user-list.1001560.n3.nabble.com/serialization-error-tp25131.html
> Sen
Hi having some problems with the piece of code I inherited:
the error messages i get are:
the code runs if i exclude the following line:
any help appreciated.
--
View this message in context:
http://apache-spark-user-list.1001560.n3.nabble.com/serialization-error-tp25131.html
Sent
Hi, I’m receiving a task not serializable exception using Spark GraphX (Scala
2.11.6 / JDK 1.8 / Spark 1.5)
My vertex data is of type (VertexId, immutable Set),
My edge data is of type PartialFunction[ISet[E], ISet[E]] where each ED has a
precomputed function.
My vertex program:
val v
I run the MovieLensALS, but meet the following error. The weird thing is
that this issue only appear under openjdk. And this is based on the 1.5, I
found several related tickets, not sure has anyone else meet the same issue
and know the solution ? Thanks
https://issues.apache.org/jira/browse/SPARK
private HTable table;
You should declare table variable within apply() method.
BTW which hbase release are you using ?
I see you implement caching yourself. You can make use of the following
HTable method:
public void setWriteBufferSize(long writeBufferSize) throws IOExcep
Can you show us the code for loading Hive into hbase ?
There shouldn't be 'return' statement in that code.
Cheers
> On Jun 20, 2015, at 10:10 PM, Nishant Patel wrote:
>
> Hi,
>
> I am loading data from Hive table to Hbase after doing some manipulation.
>
> I am getting error as 'Task not
Hi,
I am loading data from Hive table to Hbase after doing some manipulation.
I am getting error as 'Task not Serializable'.
My code is as below.
public class HiveToHbaseLoader implements Serializable {
public static void main(String[] args) throws Exception {
String hbaseTableNam
arguments are values of it. The name of the argument is important and all
you need to do is specify those when your creating SparkConf object.
Glad it worked.
On Tue, Apr 28, 2015 at 5:20 PM, madhvi wrote:
> Thankyou Deepak.It worked.
> Madhvi
> On Tuesday 28 April 2015 01:39 PM, ÐΞ€ρ@Ҝ (๏̯͡๏)
Thankyou Deepak.It worked.
Madhvi
On Tuesday 28 April 2015 01:39 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) wrote:
val conf = new SparkConf()
.setAppName(detail)
.set("spark.serializer",
"org.apache.spark.serializer.KryoSerializer")
.set("spark.kryoserializer.buffer.mb",
arguments.get("buffersize
On Tuesday 28 April 2015 01:39 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) wrote:
val conf = new SparkConf()
.setAppName(detail)
.set("spark.serializer",
"org.apache.spark.serializer.KryoSerializer")
.set("spark.kryoserializer.buffer.mb",
arguments.get("buffersize").get)
.set("spark.kryose
val conf = new SparkConf()
.setAppName(detail)
.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
.set("spark.kryoserializer.buffer.mb", arguments.get("buffersize"
).get)
.set("spark.kryoserializer.buffer.max.mb", arguments.get(
"maxbuffersize").g
Hi,
While connecting to accumulo through spark by making sparkRDD I am
getting the following error:
object not serializable (class: org.apache.accumulo.core.data.Key)
This is due to the 'key' class of accumulo which does not implement
serializable interface.How it can be solved and accumulo
Hi,
I’m running into a new problem trying to get streaming going. I have a test
class that sets up my pipeline and runs it fine. The actual production
implementation sets up the pipeline from within an actor. At first, I ran into
a bunch of issues relating to the serialization of closures fr
19 matches
Mail list logo
