I'm trying to switch the engine from mr to spark in Hive. For SQLs without UDFs all work fine, but when it comes to any SQL with UDF in it:
set hive.execution.engine=spark;
add jar viewfs:///path_to_the_jar/aaa.jar;
create temporary function func_name AS 'com.abc.ClassName';
select func_name(col_a) from table_name limit 100;
it always throw Exception as below in spark-cluster mode (in spark-client mode it's working fine).
ERROR : Job failed with java.lang.ClassNotFoundException: com.abc.ClassName
org.apache.hive.com.esotericsoftware.kryo.KryoException: Unable to find class: com.abc.ClassName
Serialization trace:
genericUDF (org.apache.hadoop.hive.ql.plan.ExprNodeGenericFuncDesc)
colList (org.apache.hadoop.hive.ql.plan.SelectDesc)
conf (org.apache.hadoop.hive.ql.exec.vector.VectorSelectOperator)
childOperators (org.apache.hadoop.hive.ql.exec.vector.VectorFilterOperator)
childOperators (org.apache.hadoop.hive.ql.exec.TableScanOperator)
aliasToWork (org.apache.hadoop.hive.ql.plan.MapWork)
left (org.apache.commons.lang3.tuple.ImmutablePair)
edgeProperties (org.apache.hadoop.hive.ql.plan.SparkWork)
at org.apache.hive.com.esotericsoftware.kryo.util.DefaultClassResolver.readName(DefaultClassResolver.java:156)
at org.apache.hive.com.esotericsoftware.kryo.util.DefaultClassResolver.readClass(DefaultClassResolver.java:133)
at org.apache.hive.com.esotericsoftware.kryo.Kryo.readClass(Kryo.java:670)
at org.apache.hadoop.hive.ql.exec.SerializationUtilities$KryoWithHooks.readClass(SerializationUtilities.java:181)
at org.apache.hive.com.esotericsoftware.kryo.serializers.ObjectField.read(ObjectField.java:118)
at org.apache.hive.com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:551)
at org.apache.hive.com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:790)
at org.apache.hadoop.hive.ql.exec.SerializationUtilities$KryoWithHooks.readClassAndObject(SerializationUtilities.java:176)
at org.apache.hive.com.esotericsoftware.kryo.serializers.CollectionSerializer.read(CollectionSerializer.java:134)
at org.apache.hive.com.esotericsoftware.kryo.serializers.CollectionSerializer.read(CollectionSerializer.java:40)
at org.apache.hive.com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:708)
at org.apache.hadoop.hive.ql.exec.SerializationUtilities$KryoWithHooks.readObject(SerializationUtilities.java:214)
at org.apache.hive.com.esotericsoftware.kryo.serializers.ObjectField.read(ObjectField.java:125)
at org.apache.hive.com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:551)
at org.apache.hive.com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:708)
at org.apache.hadoop.hive.ql.exec.SerializationUtilities$KryoWithHooks.readObject(SerializationUtilities.java:214)
at org.apache.hive.com.esotericsoftware.kryo.serializers.ObjectField.read(ObjectField.java:125)
at org.apache.hive.com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:551)
at org.apache.hive.com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:790)
at org.apache.hadoop.hive.ql.exec.SerializationUtilities$KryoWithHooks.readClassAndObject(SerializationUtilities.java:176)
at org.apache.hive.com.esotericsoftware.kryo.serializers.CollectionSerializer.read(CollectionSerializer.java:134)
at org.apache.hive.com.esotericsoftware.kryo.serializers.CollectionSerializer.read(CollectionSerializer.java:40)
at org.apache.hive.com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:708)
at org.apache.hadoop.hive.ql.exec.SerializationUtilities$KryoWithHooks.readObject(SerializationUtilities.java:214)
at org.apache.hive.com.esotericsoftware.kryo.serializers.ObjectField.read(ObjectField.java:125)
at org.apache.hive.com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:551)
at org.apache.hive.com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:790)
at org.apache.hadoop.hive.ql.exec.SerializationUtilities$KryoWithHooks.readClassAndObject(SerializationUtilities.java:176)
at org.apache.hive.com.esotericsoftware.kryo.serializers.CollectionSerializer.read(CollectionSerializer.java:134)
at org.apache.hive.com.esotericsoftware.kryo.serializers.CollectionSerializer.read(CollectionSerializer.java:40)
at org.apache.hive.com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:708)
at org.apache.hadoop.hive.ql.exec.SerializationUtilities$KryoWithHooks.readObject(SerializationUtilities.java:214)
at org.apache.hive.com.esotericsoftware.kryo.serializers.ObjectField.read(ObjectField.java:125)
at org.apache.hive.com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:551)
at org.apache.hive.com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:790)
at org.apache.hadoop.hive.ql.exec.SerializationUtilities$KryoWithHooks.readClassAndObject(SerializationUtilities.java:176)
at org.apache.hive.com.esotericsoftware.kryo.serializers.MapSerializer.read(MapSerializer.java:161)
at org.apache.hive.com.esotericsoftware.kryo.serializers.MapSerializer.read(MapSerializer.java:39)
at org.apache.hive.com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:708)
at org.apache.hadoop.hive.ql.exec.SerializationUtilities$KryoWithHooks.readObject(SerializationUtilities.java:214)
at org.apache.hive.com.esotericsoftware.kryo.serializers.ObjectField.read(ObjectField.java:125)
at org.apache.hive.com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:551)
at org.apache.hive.com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:708)
at org.apache.hadoop.hive.ql.exec.SerializationUtilities$KryoWithHooks.readObject(SerializationUtilities.java:214)
at org.apache.hive.com.esotericsoftware.kryo.serializers.ObjectField.read(ObjectField.java:125)
at org.apache.hive.com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:551)
at org.apache.hive.com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:790)
at org.apache.hadoop.hive.ql.exec.SerializationUtilities$KryoWithHooks.readClassAndObject(SerializationUtilities.java:176)
at org.apache.hive.com.esotericsoftware.kryo.serializers.MapSerializer.read(MapSerializer.java:153)
at org.apache.hive.com.esotericsoftware.kryo.serializers.MapSerializer.read(MapSerializer.java:39)
at org.apache.hive.com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:708)
at org.apache.hadoop.hive.ql.exec.SerializationUtilities$KryoWithHooks.readObject(SerializationUtilities.java:214)
at org.apache.hive.com.esotericsoftware.kryo.serializers.ObjectField.read(ObjectField.java:125)
at org.apache.hive.com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:551)
at org.apache.hive.com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:686)
at org.apache.hadoop.hive.ql.exec.SerializationUtilities$KryoWithHooks.readObject(SerializationUtilities.java:206)
at org.apache.hadoop.hive.ql.exec.spark.KryoSerializer.deserialize(KryoSerializer.java:60)
at org.apache.hadoop.hive.ql.exec.spark.RemoteHiveSparkClient$JobStatusJob.call(RemoteHiveSparkClient.java:329)
at org.apache.hive.spark.client.RemoteDriver$JobWrapper.call(RemoteDriver.java:358)
at org.apache.hive.spark.client.RemoteDriver$JobWrapper.call(RemoteDriver.java:323)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.ClassNotFoundException: com.abc.ClassName
at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
at java.lang.Class.forName0(Native Method)
at java.lang.Class.forName(Class.java:348)
at org.apache.hive.com.esotericsoftware.kryo.util.DefaultClassResolver.readName(DefaultClassResolver.java:154)
... 63 more
Hive: 0.23
Spark: 2.0.3
Any suggestions? Thanks.
It turns out to be a bug in hive-0.23 for not supporting viewfs scheme. It's summed up as below:
http://jason4zhu.blogspot.hk/2018/04/hive-on-spark-unable-to-find-class.html
Related
I need to compute some aggregations for each table in a Hive database. My code is something like:
sc = SparkContext()
sqlContext = HiveContext(sc)
showtables_df = sqlContext.sql('show tables in my_db')
for onlinetable in showtables_df.select('tableName').rdd.collect():
hive_table_name = onlinetable['tableName']
try:
table_df = sqlContext.sql('SELECT * FROM my_db.' + hive_table_name)
table_df.count() # sample action
except Exception as e:
logger.error('Error in table ' + hive_table_name)
logger.error(type(e))
logger.error(e)
At a certain point, an huge table read causes an exception to be raised, and the SparkContext closes. From this point on, every call to the sqlContext fails:
[2018-05-20 07:40:36] ERROR - my_table: An error occurred while calling o40.sql.
: java.lang.IllegalStateException: Cannot call methods on a stopped SparkContext.
This stopped SparkContext was created at:
org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:59)
sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
java.lang.reflect.Constructor.newInstance(Constructor.java:423)
py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:234)
py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
py4j.Gateway.invoke(Gateway.java:214)
py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:79)
py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:68)
py4j.GatewayConnection.run(GatewayConnection.java:209)
java.lang.Thread.run(Thread.java:745)
The currently active SparkContext was created at:
org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:59)
sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
java.lang.reflect.Constructor.newInstance(Constructor.java:423)
py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:234)
py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
py4j.Gateway.invoke(Gateway.java:214)
py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:79)
py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:68)
py4j.GatewayConnection.run(GatewayConnection.java:209)
java.lang.Thread.run(Thread.java:745)
at org.apache.spark.SparkContext.org$apache$spark$SparkContext$$assertNotStopped(SparkContext.scala:106)
at org.apache.spark.SparkContext$$anonfun$parallelize$1.apply(SparkContext.scala:729)
at org.apache.spark.SparkContext$$anonfun$parallelize$1.apply(SparkContext.scala:728)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.SparkContext.withScope(SparkContext.scala:714)
at org.apache.spark.SparkContext.parallelize(SparkContext.scala:728)
at org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:70)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:130)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:55)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:55)
at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:145)
at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:130)
at org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:52)
at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:817)
at sun.reflect.GeneratedMethodAccessor23.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
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:209)
at java.lang.Thread.run(Thread.java:745)
As of now, I'm not able to add resources to my job, but I'd like to restart the SparkContext and go on computing aggregations in the remaining tables of the for loop.
Is it a good (and feasible) idea to check for the SparkContext to be closed in the exception handler, and eventually recreating it with:
...
except Exception as e:
logger.error('Error in table ' + hive_table_name)
logger.error(type(e))
logger.error(e)
if sc._jsc.sc().isStopped():
sc = SparkContext()
sqlContext = HiveContext(sc)
I'm working with Spark version 1.6.1, running jobs with --master yarn --deploy-mode client
I'm trying to use the connector, which I've used a bunch of times in the past super successfully, with the new Spark 2.3 native Kubernetes support and am running into a lot of trouble.
I have a super simple job that looks like this:
package io.rhom
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.cassandra._
import com.datastax.spark.connector.cql.CassandraConnectorConf
import com.datastax.spark.connector.rdd.ReadConf
/** Computes an approximation to pi */
object BackupLocations {
def main(args: Array[String]) {
val spark = SparkSession
.builder
.appName("BackupLocations")
.getOrCreate()
spark.sparkContext.hadoopConfiguration.set(
"fs.defaultFS",
"wasb://<snip>"
)
spark.sparkContext.hadoopConfiguration.set(
"fs.azure.account.key.rhomlocations.blob.core.windows.net",
"<snip>"
)
val df = spark
.read
.format("org.apache.spark.sql.cassandra")
.options(Map( "table" -> "locations", "keyspace" -> "test"))
.load()
df.write
.mode("overwrite")
.format("com.databricks.spark.avro")
.save("wasb://<snip>")
spark.stop()
}
}
which I'm building under SBT with Scala 2.11 and packaging with a Dockerfile that looks like this:
FROM timfpark/spark:20180305
COPY core-site.xml /opt/spark/conf
RUN mkdir -p /opt/spark/jars
COPY target/scala-2.11/rhom-backup-locations_2.11-0.1.0-SNAPSHOT.jar /opt/spark/jars
and then executing with:
bin/spark-submit --master k8s://blue-rhom-io.eastus2.cloudapp.azure.com:443 \
--deploy-mode cluster \
--name backupLocations \
--class io.rhom.BackupLocations \
--conf spark.executor.instances=2 \
--conf spark.cassandra.connection.host=10.1.0.10 \
--conf spark.kubernetes.container.image=timfpark/rhom-backup-locations:20180306v12 \
--jars https://dl.bintray.com/spark-packages/maven/datastax/spark-cassandra-connector/2.0.3-s_2.11/spark-cassandra-connector-2.0.3-s_2.11.jar,http://central.maven.org/maven2/org/apache/hadoop/hadoop-azure/2.7.2/hadoop-azure-2.7.2.jar,http://central.maven.org/maven2/com/microsoft/azure/azure-storage/3.1.0/azure-storage-3.1.0.jar,http://central.maven.org/maven2/com/databricks/spark-avro_2.11/4.0.0/spark-avro_2.11-4.0.0.jar \
local:///opt/spark/jars/rhom-backup-locations_2.11-0.1.0-SNAPSHOT.jar
all of this works except for the Cassandra connection piece, which eventually fails with:
2018-03-07 01:19:38 WARN TaskSetManager:66 - Lost task 0.0 in stage 0.0 (TID 0, 10.4.0.46, executor 1): org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:285)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:197)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:196)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.io.IOException: Exception during preparation of SELECT "user_id", "timestamp", "accuracy", "altitude", "altitude_accuracy", "course", "features", "latitude", "longitude", "source", "speed" FROM "rhom"."locations" WHERE token("user_id") > ? AND token("user_id") <= ? ALLOW FILTERING: org/apache/spark/sql/catalyst/package$ScalaReflectionLock$
at com.datastax.spark.connector.rdd.CassandraTableScanRDD.createStatement(CassandraTableScanRDD.scala:323)
at com.datastax.spark.connector.rdd.CassandraTableScanRDD.com$datastax$spark$connector$rdd$CassandraTableScanRDD$$fetchTokenRange(CassandraTableScanRDD.scala:339)
at com.datastax.spark.connector.rdd.CassandraTableScanRDD$$anonfun$17.apply(CassandraTableScanRDD.scala:367)
at com.datastax.spark.connector.rdd.CassandraTableScanRDD$$anonfun$17.apply(CassandraTableScanRDD.scala:367)
at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
at com.datastax.spark.connector.util.CountingIterator.hasNext(CountingIterator.scala:12)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$SingleDirectoryWriteTask.execute(FileFormatWriter.scala:380)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:269)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:267)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1411)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:272)
... 8 more
Caused by: java.lang.NoClassDefFoundError: org/apache/spark/sql/catalyst/package$ScalaReflectionLock$
at org.apache.spark.sql.catalyst.ReflectionLock$.<init>(ReflectionLock.scala:5)
at org.apache.spark.sql.catalyst.ReflectionLock$.<clinit>(ReflectionLock.scala)
at com.datastax.spark.connector.types.TypeConverter$.<init>(TypeConverter.scala:73)
at com.datastax.spark.connector.types.TypeConverter$.<clinit>(TypeConverter.scala)
at com.datastax.spark.connector.types.BigIntType$.converterToCassandra(PrimitiveColumnType.scala:50)
at com.datastax.spark.connector.types.BigIntType$.converterToCassandra(PrimitiveColumnType.scala:46)
at com.datastax.spark.connector.types.ColumnType$.converterToCassandra(ColumnType.scala:231)
at com.datastax.spark.connector.rdd.CassandraTableScanRDD$$anonfun$11.apply(CassandraTableScanRDD.scala:312)
at com.datastax.spark.connector.rdd.CassandraTableScanRDD$$anonfun$11.apply(CassandraTableScanRDD.scala:312)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.AbstractTraversable.map(Traversable.scala:104)
at com.datastax.spark.connector.rdd.CassandraTableScanRDD.createStatement(CassandraTableScanRDD.scala:312)
... 23 more
Caused by: java.lang.ClassNotFoundException: org.apache.spark.sql.catalyst.package$ScalaReflectionLock$
at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:335)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
... 41 more
2018-03-07 01:19:38 INFO TaskSetManager:54 - Starting task 0.1 in stage 0.0 (TID 3, 10.4.0.46, executor 1, partition 0, ANY, 9486 bytes)
I've tried every thing I can possibly think of to resolve this - anyone have any ideas? Is this possibly caused by another unrelated issue?
It turns out that version 2.0.7 of the Datastax Cassandra Connector does not support Spark 2.3 currently. I opened a JIRA ticket on Datastax's site for this and hopefully it will be addressed soon.
I am running Spark locally on a Windows machine. I was able to launch the spark shell successfully and also read in text files as RDDs. I was also able to follow along the various online tutorials on this subject and was able to perform various operations on the RDDs.
However, when I try to convert an RDD into a DataFrame I am getting an error. This is what I am doing:
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
import sqlContext.implicits._
//convert rdd to df
val df = rddFile.toDF()
This code generates a long series of error messages that seem to relate to the following one:
Caused by: java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: file:C:/Users/spark/spark-warehouse
at org.apache.hadoop.fs.Path.initialize(Path.java:205)
at org.apache.hadoop.fs.Path.<init>(Path.java:171)
at org.apache.hadoop.hive.metastore.Warehouse.getWhRoot(Warehouse.java:159)
at org.apache.hadoop.hive.metastore.Warehouse.getDefaultDatabasePath(Warehouse.java:177)
at org.apache.hadoop.hive.metastore.HiveMetaStore$HMSHandler.createDefaultDB_core(HiveMetaStore.java:600)
at org.apache.hadoop.hive.metastore.HiveMetaStore$HMSHandler.createDefaultDB(HiveMetaStore.java:620)
at org.apache.hadoop.hive.metastore.HiveMetaStore$HMSHandler.init(HiveMetaStore.java:461)
at org.apache.hadoop.hive.metastore.RetryingHMSHandler.<init>(RetryingHMSHandler.java:66)
at org.apache.hadoop.hive.metastore.RetryingHMSHandler.getProxy(RetryingHMSHandler.java:72)
at org.apache.hadoop.hive.metastore.HiveMetaStore.newRetryingHMSHandler(HiveMetaStore.java:5762)
at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.<init>(HiveMetaStoreClient.java:199)
at org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient.<init>(SessionHiveMetaStoreClient.java:74)
... 85 more
Caused by: java.net.URISyntaxException: Relative path in absolute URI: file:C:/Users/spark/spark-warehouse
at java.net.URI.checkPath(URI.java:1823)
at java.net.URI.<init>(URI.java:745)
at org.apache.hadoop.fs.Path.initialize(Path.java:202)
... 96 more
The entire stack trace follows.
16/08/16 12:36:20 WARN ObjectStore: Failed to get database default, returning NoSuchObjectException
16/08/16 12:36:20 WARN Hive: Failed to access metastore. This class should not accessed in runtime.
org.apache.hadoop.hive.ql.metadata.HiveException: java.lang.RuntimeException: Unable to instantiate org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient
at org.apache.hadoop.hive.ql.metadata.Hive.getAllDatabases(Hive.java:1236)
at org.apache.hadoop.hive.ql.metadata.Hive.reloadFunctions(Hive.java:174)
at org.apache.hadoop.hive.ql.metadata.Hive.<clinit>(Hive.java:166)
at org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:503)
at org.apache.spark.sql.hive.client.HiveClientImpl.<init>(HiveClientImpl.scala:171)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at org.apache.spark.sql.hive.client.IsolatedClientLoader.createClient(IsolatedClientLoader.scala:258)
at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:359)
at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:263)
at org.apache.spark.sql.hive.HiveSharedState.metadataHive$lzycompute(HiveSharedState.scala:39)
at org.apache.spark.sql.hive.HiveSharedState.metadataHive(HiveSharedState.scala:38)
at org.apache.spark.sql.hive.HiveSharedState.externalCatalog$lzycompute(HiveSharedState.scala:46)
at org.apache.spark.sql.hive.HiveSharedState.externalCatalog(HiveSharedState.scala:45)
at org.apache.spark.sql.hive.HiveSessionState.catalog$lzycompute(HiveSessionState.scala:50)
at org.apache.spark.sql.hive.HiveSessionState.catalog(HiveSessionState.scala:48)
at org.apache.spark.sql.hive.HiveSessionState$$anon$1.<init>(HiveSessionState.scala:63)
at org.apache.spark.sql.hive.HiveSessionState.analyzer$lzycompute(HiveSessionState.scala:63)
at org.apache.spark.sql.hive.HiveSessionState.analyzer(HiveSessionState.scala:62)
at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:49)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:64)
at org.apache.spark.sql.SparkSession.baseRelationToDataFrame(SparkSession.scala:382)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:143)
at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:401)
at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:342)
at $line14.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.<init>(<console>:24)
at $line14.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw.<init>(<console>:29)
at $line14.$read$$iw$$iw$$iw$$iw$$iw$$iw.<init>(<console>:31)
at $line14.$read$$iw$$iw$$iw$$iw$$iw.<init>(<console>:33)
at $line14.$read$$iw$$iw$$iw$$iw.<init>(<console>:35)
at $line14.$read$$iw$$iw$$iw.<init>(<console>:37)
at $line14.$read$$iw$$iw.<init>(<console>:39)
at $line14.$read$$iw.<init>(<console>:41)
at $line14.$read.<init>(<console>:43)
at $line14.$read$.<init>(<console>:47)
at $line14.$read$.<clinit>(<console>)
at $line14.$eval$.$print$lzycompute(<console>:7)
at $line14.$eval$.$print(<console>:6)
at $line14.$eval.$print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at scala.tools.nsc.interpreter.IMain$ReadEvalPrint.call(IMain.scala:786)
at scala.tools.nsc.interpreter.IMain$Request.loadAndRun(IMain.scala:1047)
at scala.tools.nsc.interpreter.IMain$WrappedRequest$$anonfun$loadAndRunReq$1.apply(IMain.scala:638)
at scala.tools.nsc.interpreter.IMain$WrappedRequest$$anonfun$loadAndRunReq$1.apply(IMain.scala:637)
at scala.reflect.internal.util.ScalaClassLoader$class.asContext(ScalaClassLoader.scala:31)
at scala.reflect.internal.util.AbstractFileClassLoader.asContext(AbstractFileClassLoader.scala:19)
at scala.tools.nsc.interpreter.IMain$WrappedRequest.loadAndRunReq(IMain.scala:637)
at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:569)
at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:565)
at scala.tools.nsc.interpreter.ILoop.interpretStartingWith(ILoop.scala:807)
at scala.tools.nsc.interpreter.ILoop.command(ILoop.scala:681)
at scala.tools.nsc.interpreter.ILoop.processLine(ILoop.scala:395)
at scala.tools.nsc.interpreter.ILoop.loop(ILoop.scala:415)
at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply$mcZ$sp(ILoop.scala:923)
at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:909)
at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:909)
at scala.reflect.internal.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:97)
at scala.tools.nsc.interpreter.ILoop.process(ILoop.scala:909)
at org.apache.spark.repl.Main$.doMain(Main.scala:68)
at org.apache.spark.repl.Main$.main(Main.scala:51)
at org.apache.spark.repl.Main.main(Main.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:729)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:185)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:210)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:124)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.RuntimeException: Unable to instantiate org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient
at org.apache.hadoop.hive.metastore.MetaStoreUtils.newInstance(MetaStoreUtils.java:1523)
at org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.<init>(RetryingMetaStoreClient.java:86)
at org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.getProxy(RetryingMetaStoreClient.java:132)
at org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.getProxy(RetryingMetaStoreClient.java:104)
at org.apache.hadoop.hive.ql.metadata.Hive.createMetaStoreClient(Hive.java:3005)
at org.apache.hadoop.hive.ql.metadata.Hive.getMSC(Hive.java:3024)
at org.apache.hadoop.hive.ql.metadata.Hive.getAllDatabases(Hive.java:1234)
... 74 more
Caused by: java.lang.reflect.InvocationTargetException
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at org.apache.hadoop.hive.metastore.MetaStoreUtils.newInstance(MetaStoreUtils.java:1521)
... 80 more
Caused by: java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: file:C:/Users/spark/spark-warehouse
at org.apache.hadoop.fs.Path.initialize(Path.java:205)
at org.apache.hadoop.fs.Path.<init>(Path.java:171)
at org.apache.hadoop.hive.metastore.Warehouse.getWhRoot(Warehouse.java:159)
at org.apache.hadoop.hive.metastore.Warehouse.getDefaultDatabasePath(Warehouse.java:177)
at org.apache.hadoop.hive.metastore.HiveMetaStore$HMSHandler.createDefaultDB_core(HiveMetaStore.java:600)
at org.apache.hadoop.hive.metastore.HiveMetaStore$HMSHandler.createDefaultDB(HiveMetaStore.java:620)
at org.apache.hadoop.hive.metastore.HiveMetaStore$HMSHandler.init(HiveMetaStore.java:461)
at org.apache.hadoop.hive.metastore.RetryingHMSHandler.<init>(RetryingHMSHandler.java:66)
at org.apache.hadoop.hive.metastore.RetryingHMSHandler.getProxy(RetryingHMSHandler.java:72)
at org.apache.hadoop.hive.metastore.HiveMetaStore.newRetryingHMSHandler(HiveMetaStore.java:5762)
at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.<init>(HiveMetaStoreClient.java:199)
at org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient.<init>(SessionHiveMetaStoreClient.java:74)
... 85 more
Caused by: java.net.URISyntaxException: Relative path in absolute URI: file:C:/Users/spark/spark-warehouse
at java.net.URI.checkPath(URI.java:1823)
at java.net.URI.<init>(URI.java:745)
at org.apache.hadoop.fs.Path.initialize(Path.java:202)
... 96 more
It's the SPARK-15565 issue in Spark 2.0 on Windows with a simple solution (that appears to be part of Spark's codebase that may soon be released as 2.0.2 or 2.1.0).
The solution in Spark 2.0.0 is to set spark.sql.warehouse.dir to some properly-referenced directory, say file:///c:/Spark/spark-2.0.0-bin-hadoop2.7/spark-warehouse that uses /// (triple slashes).
Start spark-shell with --conf argument as follows:
spark-shell --conf spark.sql.warehouse.dir=file:///c:/tmp/spark-warehouse
Or create a SparkSession in your Spark application using the new fluent builder pattern as follows:
import org.apache.spark.sql.SparkSession
SparkSession spark = SparkSession
.builder()
.config("spark.sql.warehouse.dir", "file:///c:/tmp/spark-warehouse")
.getOrCreate()
Or create conf/spark-defaults.conf with the following content:
spark.sql.warehouse.dir file:///c:/tmp/spark-warehouse
I also got this error. In my case I was writting a file with the character ":" in the name ex: /tmp/dattaset_10:23:11. Then spark gets confused because thinks the : is part of a path (like C:\).
The solution is just to remove the : character from the file name
If you do want to fix it in code yet not touch exsiting code, can also pass it from system properties, such that the spark initializations which comes after won't change.
System.setProperty(
"spark.sql.warehouse.dir",
s"file:///${System.getProperty("user.dir")}/spark-warehouse"
.replaceAll("\\\\", "/")
)
Note, also this is using the current working dir, which can be replaced with "c:/tmp/", or any place you'd like the spark-warehouse dir.
Just set config("spark.sql.warehouse.dir", "file:///tmp/spark-warehouse").
No need to include "C:/".
Spark driver will automatically create folder under the /tmp/spark-warehouse directory. If it's windows, it will be under "C:/". The "C:" drive will not work if the master is not local on windows.
I set spark.sql.warehouse.dir property to fix the error in my existing code
System.setProperty("spark.sql.warehouse.dir", "file:///C:/spark-warehouse");
Here is the code snippet
System.setProperty("hadoop.home.dir", "c:/winutil/");
System.setProperty("spark.sql.warehouse.dir", "file:///C:/spark-warehouse");
val conf = new SparkConf().setAppName("test").setMaster("local[*]")
val sc = new SparkContext(conf)
val lines = sc.textFile("C:/user.txt")
source DataFrame: a csv with spark-csv,which comes from maven
sqlctx.read.format("com.databricks.spark.csv")
.option("header", "true")
.option("inferSchema", "true")
.load(FileName)
After read it i tried DataFrame.printSchema() which shows good
And when doing DataFrame.write.parquet(path), it crashed with NPE throwed, messages are following:
16/02/01 15:43:59 ERROR Executor: Exception in task 0.0 in stage 4.0 (TID 59)
java.lang.NullPointerException
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1012)
at org.apache.hadoop.util.Shell.runCommand(Shell.java:482)
at org.apache.hadoop.util.Shell.run(Shell.java:455)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:715)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:808)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:791)
at org.apache.hadoop.fs.RawLocalFileSystem.setPermission(RawLocalFileSystem.java:656)
at org.apache.hadoop.fs.FilterFileSystem.setPermission(FilterFileSystem.java:490)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:462)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:428)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:908)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:889)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:786)
at org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:176)
at org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:160)
at org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:289)
at org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:262)
at org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetRelation.scala:94)
at org.apache.spark.sql.execution.datasources.parquet.ParquetRelation$$anon$3.newInstance(ParquetRelation.scala:286)
at org.apache.spark.sql.execution.datasources.BaseWriterContainer.newOutputWriter(WriterContainer.scala:129)
at org.apache.spark.sql.execution.datasources.DefaultWriterContainer.writeRows(WriterContainer.scala:255)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
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)
16/02/01 15:43:59 WARN TaskSetManager: Lost task 0.0 in stage 4.0 (TID 59, localhost): java.lang.NullPointerException
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1012)
at org.apache.hadoop.util.Shell.runCommand(Shell.java:482)
at org.apache.hadoop.util.Shell.run(Shell.java:455)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:715)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:808)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:791)
at org.apache.hadoop.fs.RawLocalFileSystem.setPermission(RawLocalFileSystem.java:656)
at org.apache.hadoop.fs.FilterFileSystem.setPermission(FilterFileSystem.java:490)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:462)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:428)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:908)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:889)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:786)
at org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:176)
at org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:160)
at org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:289)
at org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:262)
at org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetRelation.scala:94)
at org.apache.spark.sql.execution.datasources.parquet.ParquetRelation$$anon$3.newInstance(ParquetRelation.scala:286)
at org.apache.spark.sql.execution.datasources.BaseWriterContainer.newOutputWriter(WriterContainer.scala:129)
at org.apache.spark.sql.execution.datasources.DefaultWriterContainer.writeRows(WriterContainer.scala:255)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
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)
Environment:NPE only happens in windows, all codes runs fine in linux
P.S: DataFrame.write.save() shows the same NPE, is this a win spec problem?
You have to install winutils.exe in the hadoop installation mentioned in $HADOOP_HOME. You can obtain this installation from https://www.barik.net/archive/2015/01/19/172716/ which is a hadoop build with the winutils.exe in the bin folder. This resolves the NPE problem.
i want to run 'select count(*) from test' on 'hive on spark' through beeline, but it crashed.
INFO client.SparkClientUtilities: Added jar[file:/home/.../hive/lib/zookeeper-3.4.6.jar] to classpath
INFO client.RemoteDriver: Failed to run job 41dc814c-deb7-4743-9b6a-b6cace2eae19
com.esotericsoftware.kryo.KryoException: java.lang.ArrayIndexOutOfBoundsException: 1
Serialization trace:
dummyOps (org.apache.hadoop.hive.ql.plan.ReduceWork) left (org.apache.commons.lang3.tuple.ImmutablePair) edgeProperties (org.apache.hadoop.hive.ql.plan.SparkWork)
at com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:626)
at com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:221)
at com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:648)
at com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:605)
at com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:221)
at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)
at com.esotericsoftware.kryo.serializers.MapSerializer.read(MapSerializer.java:126)
at com.esotericsoftware.kryo.serializers.MapSerializer.read(MapSerializer.java:17)
at com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:648)
at com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:605)
at com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:221)
at com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:626)
at org.apache.hadoop.hive.ql.exec.spark.KryoSerializer.deserialize(KryoSerializer.java:49)
at org.apache.hadoop.hive.ql.exec.spark.RemoteHiveSparkClient$JobStatusJob.call(RemoteHiveSparkClient.java:235)
at org.apache.hive.spark.client.RemoteDriver$JobWrapper.call(RemoteDriver.java:366)
at org.apache.hive.spark.client.RemoteDriver$JobWrapper.call(RemoteDriver.java:335)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.ArrayIndexOutOfBoundsException: 1
at com.esotericsoftware.kryo.serializers.MapSerializer.setGenerics(MapSerializer.java:53)
at com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:604)
... 19 more
hive on spark configuration is:
set spark.home=/home/.../spark;
set hive.execution.engine=spark;
set spark.master=yarn;
set spark.eventLog.enabled=true;
set spark.eventLog.dir=hdfs://...:9000/user/.../spark-history-server-records;
set spark.executor.memory=1024m;
set spark.serializer=org.apache.spark.serializer.KryoSerializer;
and what's worse, when i change KryoSerializer to JavaSerializer, this issue still exists.
Thanks.