Nick Orka created SPARK-18075:
---------------------------------
Summary: UDF doesn't work on non-local spark
Key: SPARK-18075
URL: https://issues.apache.org/jira/browse/SPARK-18075
Project: Spark
Issue Type: Bug
Affects Versions: 2.0.0, 1.6.1
Reporter: Nick Orka
I've decided to clone the ticket because it had the same problem for anothe
spark version and provided workaround doesn't fix an issue.
I'm duplicating my case here.
I have the same issue with Spark 2.0.0 (spark-2.0.0-bin-hadoop2.7.tar.gz)
Here is my pom:
{code:title=pom.xml}
<properties>
<maven.compiler.source>1.6</maven.compiler.source>
<maven.compiler.target>1.6</maven.compiler.target>
<encoding>UTF-8</encoding>
<scala.version>2.11.8</scala.version>
<spark.version>2.0.0</spark.version>
<hadoop.version>2.7.0</hadoop.version>
</properties>
<dependencies>
<!--Spark-->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.11</artifactId>
<version>${spark.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.11</artifactId>
<version>${spark.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-hive_2.11</artifactId>
<version>${spark.version}</version>
<scope>provided</scope>
</dependency>
</dependencies>
{code}
As you can see all spark dependencies have provided scope
And this is a code for reproduction:
{code:title=udfTest.scala}
import org.apache.spark.sql.types.{StringType, StructField, StructType}
import org.apache.spark.sql.{Row, SparkSession}
/**
* Created by nborunov on 10/19/16.
*/
object udfTest {
class Seq extends Serializable {
var i = 0
def getVal: Int = {
i = i + 1
i
}
}
def main(args: Array[String]) {
val spark = SparkSession
.builder()
.master("spark://nborunov-mbp.local:7077")
// .master("local")
.getOrCreate()
val rdd = spark.sparkContext.parallelize(Seq(Row("one"), Row("two")))
val schema = StructType(Array(StructField("name", StringType)))
val df = spark.createDataFrame(rdd, schema)
df.show()
spark.udf.register("func", (name: String) => name.toUpperCase)
import org.apache.spark.sql.functions.expr
val newDf = df.withColumn("upperName", expr("func(name)"))
newDf.show()
val seq = new Seq
spark.udf.register("seq", () => seq.getVal)
val seqDf = df.withColumn("id", expr("seq()"))
seqDf.show()
df.createOrReplaceTempView("df")
spark.sql("select *, seq() as sql_id from df").show()
}
}
{code}
When .master("local") - everything works fine. When
.master("spark://...:7077"), it fails on line:
{code}
newDf.show()
{code}
The error is exactly the same:
{code}
scala> udfTest.main(Array())
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in
[jar:file:/Users/nborunov/.m2/repository/org/slf4j/slf4j-log4j12/1.7.16/slf4j-log4j12-1.7.16.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in
[jar:file:/Users/nborunov/.m2/repository/ch/qos/logback/logback-classic/1.1.7/logback-classic-1.1.7.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
16/10/19 19:37:52 INFO SparkContext: Running Spark version 2.0.0
16/10/19 19:37:52 WARN NativeCodeLoader: Unable to load native-hadoop library
for your platform... using builtin-java classes where applicable
16/10/19 19:37:52 INFO SecurityManager: Changing view acls to: nborunov
16/10/19 19:37:52 INFO SecurityManager: Changing modify acls to: nborunov
16/10/19 19:37:52 INFO SecurityManager: Changing view acls groups to:
16/10/19 19:37:52 INFO SecurityManager: Changing modify acls groups to:
16/10/19 19:37:52 INFO SecurityManager: SecurityManager: authentication
disabled; ui acls disabled; users with view permissions: Set(nborunov); groups
with view permissions: Set(); users with modify permissions: Set(nborunov);
groups with modify permissions: Set()
16/10/19 19:37:53 INFO Utils: Successfully started service 'sparkDriver' on
port 57828.
16/10/19 19:37:53 INFO SparkEnv: Registering MapOutputTracker
16/10/19 19:37:53 INFO SparkEnv: Registering BlockManagerMaster
16/10/19 19:37:53 INFO DiskBlockManager: Created local directory at
/private/var/folders/hl/2fv6555n2w92272zywwvpbzh0000gq/T/blockmgr-f2d05423-b7f7-4525-b41e-10dfe2f88264
16/10/19 19:37:53 INFO MemoryStore: MemoryStore started with capacity 2004.6 MB
16/10/19 19:37:53 INFO SparkEnv: Registering OutputCommitCoordinator
16/10/19 19:37:54 INFO Utils: Successfully started service 'SparkUI' on port
4040.
16/10/19 19:37:54 INFO SparkUI: Bound SparkUI to 0.0.0.0, and started at
http://192.168.2.202:4040
16/10/19 19:37:54 INFO StandaloneAppClient$ClientEndpoint: Connecting to master
spark://nborunov-mbp.local:7077...
16/10/19 19:37:54 INFO TransportClientFactory: Successfully created connection
to nborunov-mbp.local/192.168.2.202:7077 after 74 ms (0 ms spent in bootstraps)
16/10/19 19:37:55 INFO StandaloneSchedulerBackend: Connected to Spark cluster
with app ID app-20161019153755-0017
16/10/19 19:37:55 INFO StandaloneAppClient$ClientEndpoint: Executor added:
app-20161019153755-0017/0 on worker-20161018232014-192.168.2.202-61437
(192.168.2.202:61437) with 4 cores
16/10/19 19:37:55 INFO StandaloneSchedulerBackend: Granted executor ID
app-20161019153755-0017/0 on hostPort 192.168.2.202:61437 with 4 cores, 1024.0
MB RAM
16/10/19 19:37:55 INFO Utils: Successfully started service
'org.apache.spark.network.netty.NettyBlockTransferService' on port 57832.
16/10/19 19:37:55 INFO NettyBlockTransferService: Server created on
192.168.2.202:57832
16/10/19 19:37:55 INFO BlockManagerMaster: Registering BlockManager
BlockManagerId(driver, 192.168.2.202, 57832)
16/10/19 19:37:55 INFO BlockManagerMasterEndpoint: Registering block manager
192.168.2.202:57832 with 2004.6 MB RAM, BlockManagerId(driver, 192.168.2.202,
57832)
16/10/19 19:37:55 INFO BlockManagerMaster: Registered BlockManager
BlockManagerId(driver, 192.168.2.202, 57832)
16/10/19 19:37:55 INFO StandaloneAppClient$ClientEndpoint: Executor updated:
app-20161019153755-0017/0 is now RUNNING
16/10/19 19:37:55 INFO StandaloneSchedulerBackend: SchedulerBackend is ready
for scheduling beginning after reached minRegisteredResourcesRatio: 0.0
16/10/19 19:37:55 WARN SparkContext: Use an existing SparkContext, some
configuration may not take effect.
16/10/19 19:37:56 INFO HiveSharedState: spark.sql.warehouse.dir is not set, but
hive.metastore.warehouse.dir is set. Setting spark.sql.warehouse.dir to the
value of hive.metastore.warehouse.dir ('/user/hive/warehouse').
16/10/19 19:37:56 INFO HiveSharedState: Warehouse path is
'/user/hive/warehouse'.
16/10/19 19:37:58 INFO HiveUtils: Initializing HiveMetastoreConnection version
1.2.1 using Spark classes.
16/10/19 19:37:58 INFO deprecation: mapred.max.split.size is deprecated.
Instead, use mapreduce.input.fileinputformat.split.maxsize
16/10/19 19:37:58 INFO deprecation: mapred.reduce.tasks.speculative.execution
is deprecated. Instead, use mapreduce.reduce.speculative
16/10/19 19:37:58 INFO deprecation: mapred.committer.job.setup.cleanup.needed
is deprecated. Instead, use mapreduce.job.committer.setup.cleanup.needed
16/10/19 19:37:58 INFO deprecation: mapred.min.split.size.per.rack is
deprecated. Instead, use mapreduce.input.fileinputformat.split.minsize.per.rack
16/10/19 19:37:58 INFO deprecation: mapred.min.split.size is deprecated.
Instead, use mapreduce.input.fileinputformat.split.minsize
16/10/19 19:37:58 INFO deprecation: mapred.min.split.size.per.node is
deprecated. Instead, use mapreduce.input.fileinputformat.split.minsize.per.node
16/10/19 19:37:58 INFO deprecation: mapred.reduce.tasks is deprecated. Instead,
use mapreduce.job.reduces
16/10/19 19:37:58 INFO deprecation: mapred.input.dir.recursive is deprecated.
Instead, use mapreduce.input.fileinputformat.input.dir.recursive
16/10/19 19:37:59 INFO metastore: Trying to connect to metastore with URI
thrift://ip-10-100-102-90.iad.sessionm.com:9083
16/10/19 19:37:59 INFO metastore: Connected to metastore.
16/10/19 19:38:00 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Registered
executor NettyRpcEndpointRef(null) (192.168.2.202:57835) with ID 0
16/10/19 19:38:00 INFO BlockManagerMasterEndpoint: Registering block manager
192.168.2.202:57837 with 366.3 MB RAM, BlockManagerId(0, 192.168.2.202, 57837)
16/10/19 19:38:01 WARN BlockReaderLocal: The short-circuit local reads feature
cannot be used because libhadoop cannot be loaded.
16/10/19 19:38:01 INFO SessionState: Created local directory:
/var/folders/hl/2fv6555n2w92272zywwvpbzh0000gq/T/e1377cbe-3c79-4a44-b0be-551f2b73b931_resources
16/10/19 19:38:01 INFO SessionState: Created HDFS directory:
/tmp/hive/nborunov/e1377cbe-3c79-4a44-b0be-551f2b73b931
16/10/19 19:38:01 INFO SessionState: Created local directory:
/var/folders/hl/2fv6555n2w92272zywwvpbzh0000gq/T/nborunov/e1377cbe-3c79-4a44-b0be-551f2b73b931
16/10/19 19:38:01 INFO SessionState: Created HDFS directory:
/tmp/hive/nborunov/e1377cbe-3c79-4a44-b0be-551f2b73b931/_tmp_space.db
16/10/19 19:38:01 INFO HiveClientImpl: Warehouse location for Hive client
(version 1.2.1) is /user/hive/warehouse
16/10/19 19:38:02 INFO SessionState: Created local directory:
/var/folders/hl/2fv6555n2w92272zywwvpbzh0000gq/T/4cdb5e78-de4b-4919-b490-4f414c129ed1_resources
16/10/19 19:38:02 INFO SessionState: Created HDFS directory:
/tmp/hive/nborunov/4cdb5e78-de4b-4919-b490-4f414c129ed1
16/10/19 19:38:02 INFO SessionState: Created local directory:
/var/folders/hl/2fv6555n2w92272zywwvpbzh0000gq/T/nborunov/4cdb5e78-de4b-4919-b490-4f414c129ed1
16/10/19 19:38:02 INFO SessionState: Created HDFS directory:
/tmp/hive/nborunov/4cdb5e78-de4b-4919-b490-4f414c129ed1/_tmp_space.db
16/10/19 19:38:02 INFO HiveClientImpl: Warehouse location for Hive client
(version 1.2.1) is /user/hive/warehouse
16/10/19 19:38:03 INFO SparkContext: Starting job: show at udfTest.scala:36
16/10/19 19:38:03 INFO DAGScheduler: Got job 0 (show at udfTest.scala:36) with
1 output partitions
16/10/19 19:38:03 INFO DAGScheduler: Final stage: ResultStage 0 (show at
udfTest.scala:36)
16/10/19 19:38:03 INFO DAGScheduler: Parents of final stage: List()
16/10/19 19:38:03 INFO DAGScheduler: Missing parents: List()
16/10/19 19:38:03 INFO DAGScheduler: Submitting ResultStage 0
(MapPartitionsRDD[3] at show at udfTest.scala:36), which has no missing parents
16/10/19 19:38:03 INFO MemoryStore: Block broadcast_0 stored as values in
memory (estimated size 6.9 KB, free 2004.6 MB)
16/10/19 19:38:03 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in
memory (estimated size 3.8 KB, free 2004.6 MB)
16/10/19 19:38:03 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on
192.168.2.202:57832 (size: 3.8 KB, free: 2004.6 MB)
16/10/19 19:38:03 INFO SparkContext: Created broadcast 0 from broadcast at
DAGScheduler.scala:1012
16/10/19 19:38:03 INFO DAGScheduler: Submitting 1 missing tasks from
ResultStage 0 (MapPartitionsRDD[3] at show at udfTest.scala:36)
16/10/19 19:38:03 INFO TaskSchedulerImpl: Adding task set 0.0 with 1 tasks
16/10/19 19:38:04 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0,
192.168.2.202, partition 0, PROCESS_LOCAL, 5381 bytes)
16/10/19 19:38:04 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Launching
task 0 on executor id: 0 hostname: 192.168.2.202.
16/10/19 19:38:04 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on
192.168.2.202:57837 (size: 3.8 KB, free: 366.3 MB)
16/10/19 19:38:07 INFO TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0)
in 3235 ms on 192.168.2.202 (1/1)
16/10/19 19:38:07 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have
all completed, from pool
16/10/19 19:38:07 INFO DAGScheduler: ResultStage 0 (show at udfTest.scala:36)
finished in 3.265 s
16/10/19 19:38:07 INFO DAGScheduler: Job 0 finished: show at udfTest.scala:36,
took 3.629356 s
16/10/19 19:38:07 INFO SparkContext: Starting job: show at udfTest.scala:36
16/10/19 19:38:07 INFO DAGScheduler: Got job 1 (show at udfTest.scala:36) with
1 output partitions
16/10/19 19:38:07 INFO DAGScheduler: Final stage: ResultStage 1 (show at
udfTest.scala:36)
16/10/19 19:38:07 INFO DAGScheduler: Parents of final stage: List()
16/10/19 19:38:07 INFO DAGScheduler: Missing parents: List()
16/10/19 19:38:07 INFO DAGScheduler: Submitting ResultStage 1
(MapPartitionsRDD[3] at show at udfTest.scala:36), which has no missing parents
16/10/19 19:38:07 INFO MemoryStore: Block broadcast_1 stored as values in
memory (estimated size 6.9 KB, free 2004.6 MB)
16/10/19 19:38:07 INFO MemoryStore: Block broadcast_1_piece0 stored as bytes in
memory (estimated size 3.8 KB, free 2004.6 MB)
16/10/19 19:38:07 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on
192.168.2.202:57832 (size: 3.8 KB, free: 2004.6 MB)
16/10/19 19:38:07 INFO SparkContext: Created broadcast 1 from broadcast at
DAGScheduler.scala:1012
16/10/19 19:38:07 INFO DAGScheduler: Submitting 1 missing tasks from
ResultStage 1 (MapPartitionsRDD[3] at show at udfTest.scala:36)
16/10/19 19:38:07 INFO TaskSchedulerImpl: Adding task set 1.0 with 1 tasks
16/10/19 19:38:07 INFO TaskSetManager: Starting task 0.0 in stage 1.0 (TID 1,
192.168.2.202, partition 1, PROCESS_LOCAL, 5381 bytes)
16/10/19 19:38:07 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Launching
task 1 on executor id: 0 hostname: 192.168.2.202.
16/10/19 19:38:07 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on
192.168.2.202:57837 (size: 3.8 KB, free: 366.3 MB)
16/10/19 19:38:07 INFO TaskSetManager: Finished task 0.0 in stage 1.0 (TID 1)
in 85 ms on 192.168.2.202 (1/1)
16/10/19 19:38:07 INFO TaskSchedulerImpl: Removed TaskSet 1.0, whose tasks have
all completed, from pool
16/10/19 19:38:07 INFO DAGScheduler: ResultStage 1 (show at udfTest.scala:36)
finished in 0.087 s
16/10/19 19:38:07 INFO DAGScheduler: Job 1 finished: show at udfTest.scala:36,
took 0.103358 s
16/10/19 19:38:07 INFO BlockManagerInfo: Removed broadcast_0_piece0 on
192.168.2.202:57832 in memory (size: 3.8 KB, free: 2004.6 MB)
16/10/19 19:38:07 INFO BlockManagerInfo: Removed broadcast_0_piece0 on
192.168.2.202:57837 in memory (size: 3.8 KB, free: 366.3 MB)
16/10/19 19:38:07 INFO BlockManagerInfo: Removed broadcast_1_piece0 on
192.168.2.202:57832 in memory (size: 3.8 KB, free: 2004.6 MB)
16/10/19 19:38:07 INFO BlockManagerInfo: Removed broadcast_1_piece0 on
192.168.2.202:57837 in memory (size: 3.8 KB, free: 366.3 MB)
16/10/19 19:38:08 INFO CodeGenerator: Code generated in 638.80317 ms
+----+
|name|
+----+
| one|
| two|
+----+
16/10/19 19:38:08 INFO SparkSqlParser: Parsing command: func(name)
16/10/19 19:38:09 INFO CodeGenerator: Code generated in 51.788495 ms
16/10/19 19:38:09 INFO SparkContext: Starting job: show at udfTest.scala:44
16/10/19 19:38:09 INFO DAGScheduler: Got job 2 (show at udfTest.scala:44) with
1 output partitions
16/10/19 19:38:09 INFO DAGScheduler: Final stage: ResultStage 2 (show at
udfTest.scala:44)
16/10/19 19:38:09 INFO DAGScheduler: Parents of final stage: List()
16/10/19 19:38:09 INFO DAGScheduler: Missing parents: List()
16/10/19 19:38:09 INFO DAGScheduler: Submitting ResultStage 2
(MapPartitionsRDD[6] at show at udfTest.scala:44), which has no missing parents
16/10/19 19:38:09 INFO MemoryStore: Block broadcast_2 stored as values in
memory (estimated size 11.4 KB, free 2004.6 MB)
16/10/19 19:38:09 INFO MemoryStore: Block broadcast_2_piece0 stored as bytes in
memory (estimated size 5.7 KB, free 2004.6 MB)
16/10/19 19:38:09 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on
192.168.2.202:57832 (size: 5.7 KB, free: 2004.6 MB)
16/10/19 19:38:09 INFO SparkContext: Created broadcast 2 from broadcast at
DAGScheduler.scala:1012
16/10/19 19:38:09 INFO DAGScheduler: Submitting 1 missing tasks from
ResultStage 2 (MapPartitionsRDD[6] at show at udfTest.scala:44)
16/10/19 19:38:09 INFO TaskSchedulerImpl: Adding task set 2.0 with 1 tasks
16/10/19 19:38:09 INFO TaskSetManager: Starting task 0.0 in stage 2.0 (TID 2,
192.168.2.202, partition 0, PROCESS_LOCAL, 5381 bytes)
16/10/19 19:38:09 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Launching
task 2 on executor id: 0 hostname: 192.168.2.202.
16/10/19 19:38:09 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on
192.168.2.202:57837 (size: 5.7 KB, free: 366.3 MB)
16/10/19 19:38:09 WARN TaskSetManager: Lost task 0.0 in stage 2.0 (TID 2,
192.168.2.202): java.lang.ClassCastException: cannot assign instance of
scala.collection.immutable.List$SerializationProxy to field
org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$dependencies_ of type
scala.collection.Seq in instance of org.apache.spark.rdd.MapPartitionsRDD
at
java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(ObjectStreamClass.java:2133)
at
java.io.ObjectStreamClass.setObjFieldValues(ObjectStreamClass.java:1305)
at
java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2006)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at
java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
at
org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
at
org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:114)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
16/10/19 19:38:09 INFO TaskSetManager: Starting task 0.1 in stage 2.0 (TID 3,
192.168.2.202, partition 0, PROCESS_LOCAL, 5381 bytes)
16/10/19 19:38:09 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Launching
task 3 on executor id: 0 hostname: 192.168.2.202.
16/10/19 19:38:09 INFO TaskSetManager: Lost task 0.1 in stage 2.0 (TID 3) on
executor 192.168.2.202: java.lang.ClassCastException (cannot assign instance of
scala.collection.immutable.List$SerializationProxy to field
org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$dependencies_ of type
scala.collection.Seq in instance of org.apache.spark.rdd.MapPartitionsRDD)
[duplicate 1]
16/10/19 19:38:09 INFO TaskSetManager: Starting task 0.2 in stage 2.0 (TID 4,
192.168.2.202, partition 0, PROCESS_LOCAL, 5381 bytes)
16/10/19 19:38:09 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Launching
task 4 on executor id: 0 hostname: 192.168.2.202.
16/10/19 19:38:09 INFO TaskSetManager: Lost task 0.2 in stage 2.0 (TID 4) on
executor 192.168.2.202: java.lang.ClassCastException (cannot assign instance of
scala.collection.immutable.List$SerializationProxy to field
org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$dependencies_ of type
scala.collection.Seq in instance of org.apache.spark.rdd.MapPartitionsRDD)
[duplicate 2]
16/10/19 19:38:09 INFO TaskSetManager: Starting task 0.3 in stage 2.0 (TID 5,
192.168.2.202, partition 0, PROCESS_LOCAL, 5381 bytes)
16/10/19 19:38:09 INFO CoarseGrainedSchedulerBackend$DriverEndpoint: Launching
task 5 on executor id: 0 hostname: 192.168.2.202.
16/10/19 19:38:09 INFO TaskSetManager: Lost task 0.3 in stage 2.0 (TID 5) on
executor 192.168.2.202: java.lang.ClassCastException (cannot assign instance of
scala.collection.immutable.List$SerializationProxy to field
org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$dependencies_ of type
scala.collection.Seq in instance of org.apache.spark.rdd.MapPartitionsRDD)
[duplicate 3]
16/10/19 19:38:09 ERROR TaskSetManager: Task 0 in stage 2.0 failed 4 times;
aborting job
16/10/19 19:38:09 INFO TaskSchedulerImpl: Removed TaskSet 2.0, whose tasks have
all completed, from pool
16/10/19 19:38:09 INFO TaskSchedulerImpl: Cancelling stage 2
16/10/19 19:38:09 INFO DAGScheduler: ResultStage 2 (show at udfTest.scala:44)
failed in 0.354 s
16/10/19 19:38:09 INFO DAGScheduler: Job 2 failed: show at udfTest.scala:44,
took 0.373604 s
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in
stage 2.0 failed 4 times, most recent failure: Lost task 0.3 in stage 2.0 (TID
5, 192.168.2.202): java.lang.ClassCastException: cannot assign instance of
scala.collection.immutable.List$SerializationProxy to field
org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$dependencies_ of type
scala.collection.Seq in instance of org.apache.spark.rdd.MapPartitionsRDD
at
java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(ObjectStreamClass.java:2133)
at
java.io.ObjectStreamClass.setObjFieldValues(ObjectStreamClass.java:1305)
at
java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2006)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at
java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
at
org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
at
org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:114)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1450)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1438)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1437)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1437)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at scala.Option.foreach(Option.scala:257)
at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1659)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1618)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1607)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1871)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1884)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1897)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:347)
at
org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:39)
at
org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2183)
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2532)
at
org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2182)
at
org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2189)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1925)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1924)
at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2562)
at org.apache.spark.sql.Dataset.head(Dataset.scala:1924)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2139)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:239)
at org.apache.spark.sql.Dataset.show(Dataset.scala:526)
at org.apache.spark.sql.Dataset.show(Dataset.scala:486)
at org.apache.spark.sql.Dataset.show(Dataset.scala:495)
at udfTest$.main(udfTest.scala:44)
... 29 elided
Caused by: java.lang.ClassCastException: cannot assign instance of
scala.collection.immutable.List$SerializationProxy to field
org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$dependencies_ of type
scala.collection.Seq in instance of org.apache.spark.rdd.MapPartitionsRDD
at
java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(ObjectStreamClass.java:2133)
at java.io.ObjectStreamClass.setObjFieldValues(ObjectStreamClass.java:1305)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2006)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
at
org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
at
org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:114)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
scala>
{code}
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