Hi Mark,
Thanks for the suggestion.
I changed the maven entries as follows
<artifactId>spark-core_2.10</artifactId>
<version>2.0.0</version>
and
<artifactId>spark-sql_2.10</artifactId>
<version>2.0.0</version>
As result, it worked when I removed the following line of code to compute
DAYOFWEEK (Monday—>1 etc.):
Dataset<Row> tmp6=tmp5.withColumn("ORD_DAYOFWEEK", callUDF("computeDayOfWeek",
tmp5.col("ORD_time_window_per_hour#3").getItem("start").cast(DataTypes.StringType)));
this.spark.udf().register("computeDayOfWeek", new UDF1<String,Integer>() {
@Override
public Integer call(String myDate) throws Exception {
Date date = new SimpleDateFormat(dateFormat).parse(myDate);
Calendar c = Calendar.getInstance();
c.setTime(date);
int dayOfWeek = c.get(Calendar.DAY_OF_WEEK);
return dayOfWeek;//myDate.length();
}
}, DataTypes.IntegerType);
And the full stack is reported below.
Is there another way to compute DAYOFWEEK from a dateFormat="yyyy-MM-dd
HH:mm:ss" by using built-in function? I have checked date_format but it does
not do it.
Any Suggestion?
Many Thanks,
Carlo
====
Test set: org.mksmart.amaretto.ml.DatasetPerHourVerOneTest
-------------------------------------------------------------------------------
Tests run: 1, Failures: 0, Errors: 1, Skipped: 0, Time elapsed: 32.658 sec <<<
FAILURE!
testBuildDatasetNew(org.mksmart.amaretto.ml.DatasetPerHourVerOneTest) Time
elapsed: 32.581 sec <<< ERROR!
org.apache.spark.SparkException: Task not serializable
at
org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:298)
at
org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:288)
at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:108)
at org.apache.spark.SparkContext.clean(SparkContext.scala:2037)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndex$1.apply(RDD.scala:798)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndex$1.apply(RDD.scala:797)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:358)
at org.apache.spark.rdd.RDD.mapPartitionsWithIndex(RDD.scala:797)
at
org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:364)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:114)
at
org.apache.spark.sql.execution.TakeOrderedAndProjectExec.executeCollect(limit.scala:128)
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.mksmart.amaretto.ml.DatasetPerHourVerOneTest.testBuildDatasetNew(DatasetPerHourVerOneTest.java:202)
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:497)
at
org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:50)
at
org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12)
at
org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:47)
at
org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17)
at org.junit.internal.runners.statements.RunBefores.evaluate(RunBefores.java:26)
at org.junit.internal.runners.statements.RunAfters.evaluate(RunAfters.java:27)
at org.junit.runners.ParentRunner.runLeaf(ParentRunner.java:325)
at
org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:78)
at
org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:57)
at org.junit.runners.ParentRunner$3.run(ParentRunner.java:290)
at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:71)
at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:288)
at org.junit.runners.ParentRunner.access$000(ParentRunner.java:58)
at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:268)
at org.junit.internal.runners.statements.RunBefores.evaluate(RunBefores.java:26)
at org.junit.internal.runners.statements.RunAfters.evaluate(RunAfters.java:27)
at org.junit.runners.ParentRunner.run(ParentRunner.java:363)
at org.apache.maven.surefire.junit4.JUnit4TestSet.execute(JUnit4TestSet.java:53)
at
org.apache.maven.surefire.junit4.JUnit4Provider.executeTestSet(JUnit4Provider.java:123)
at
org.apache.maven.surefire.junit4.JUnit4Provider.invoke(JUnit4Provider.java:104)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at
org.apache.maven.surefire.util.ReflectionUtils.invokeMethodWithArray(ReflectionUtils.java:164)
at
org.apache.maven.surefire.booter.ProviderFactory$ProviderProxy.invoke(ProviderFactory.java:110)
at
org.apache.maven.surefire.booter.SurefireStarter.invokeProvider(SurefireStarter.java:175)
at
org.apache.maven.surefire.booter.SurefireStarter.runSuitesInProcessWhenForked(SurefireStarter.java:107)
at org.apache.maven.surefire.booter.ForkedBooter.main(ForkedBooter.java:68)
Caused by: java.io.NotSerializableException:
org.mksmart.amaretto.etl.GetOrderInfoAsNew
Serialization stack:
- object not serializable (class: org.mksmart.amaretto.etl.GetOrderInfoAsNew,
value: org.mksmart.amaretto.etl.GetOrderInfoAsNew@7d49fe37)
- field (class: org.mksmart.amaretto.etl.GetOrderInfoAsNew$4, name: this$0,
type: class org.mksmart.amaretto.etl.GetOrderInfoAsNew)
- object (class org.mksmart.amaretto.etl.GetOrderInfoAsNew$4,
org.mksmart.amaretto.etl.GetOrderInfoAsNew$4@690e7b89)
- field (class: org.apache.spark.sql.UDFRegistration$$anonfun$register$25,
name: f$1, type: interface org.apache.spark.sql.api.java.UDF1)
- object (class org.apache.spark.sql.UDFRegistration$$anonfun$register$25,
<function1>)
- field (class:
org.apache.spark.sql.UDFRegistration$$anonfun$register$25$$anonfun$apply$1,
name: $outer, type: class
org.apache.spark.sql.UDFRegistration$$anonfun$register$25)
- object (class
org.apache.spark.sql.UDFRegistration$$anonfun$register$25$$anonfun$apply$1,
<function1>)
- field (class: org.apache.spark.sql.catalyst.expressions.ScalaUDF$$anonfun$2,
name: func$2, type: interface scala.Function1)
- object (class org.apache.spark.sql.catalyst.expressions.ScalaUDF$$anonfun$2,
<function1>)
- field (class: org.apache.spark.sql.catalyst.expressions.ScalaUDF, name: f,
type: interface scala.Function1)
- object (class org.apache.spark.sql.catalyst.expressions.ScalaUDF,
UDF(cast(time_window_per_hour#3#739.start as string)))
- field (class: org.apache.spark.sql.catalyst.expressions.Alias, name: child,
type: class org.apache.spark.sql.catalyst.expressions.Expression)
- object (class org.apache.spark.sql.catalyst.expressions.Alias,
UDF(cast(time_window_per_hour#3#739.start as string)) AS ORD_DAYOFWEEK#787)
- element of array (index: 15)
- array (class [Ljava.lang.Object;, size 16)
- field (class: scala.collection.mutable.ArrayBuffer, name: array, type: class
[Ljava.lang.Object;)
- object (class scala.collection.mutable.ArrayBuffer,
ArrayBuffer(time_window_per_hour#3#739 AS ORD_time_window_per_hour#3#748,
asin#94 AS ORD_asin#749, count(time_window_per_hour#3#739)#756L AS
ORD_num_of_order#758L, count(qty_shipped#98)#759L AS ORD_tot_qty_shipped#761L,
count(qty_ordered#97)#762L AS ORD_tot_qty_ordered#764L, min(item_price#99)#765
AS ORD_min_ord_item_price#766, max(item_price#99)#767 AS
ORD_max_ord_item_price#768, round(avg(cast(item_price#99 as double))#769, 2) AS
ORD_avg_ord_item_price#770, stddev_pop(cast(item_price#99 as double))#779 AS
ORD_std_ord_item_price#780, year(cast(cast(time_window_per_hour#3#739.start as
string) as date)) AS ORD_YEAR#781,
month(cast(cast(time_window_per_hour#3#739.start as string) as date)) AS
ORD_MONTH#782, dayofmonth(cast(cast(time_window_per_hour#3#739.start as string)
as date)) AS ORD_DAYOFMONTH#783,
hour(cast(cast(time_window_per_hour#3#739.start as string) as timestamp)) AS
ORD_HOUR#784, dayofyear(cast(cast(time_window_per_hour#3#739.start as string)
as date)) AS ORD_DAYOFYEAR#785,
weekofyear(cast(cast(time_window_per_hour#3#739.start as string) as date)) AS
ORD_WEEKOFYEAR#786, UDF(cast(time_window_per_hour#3#739.start as string)) AS
ORD_DAYOFWEEK#787))
- field (class: org.apache.spark.sql.execution.aggregate.HashAggregateExec,
name: resultExpressions, type: interface scala.collection.Seq)
- object (class org.apache.spark.sql.execution.aggregate.HashAggregateExec,
HashAggregate(keys=[time_window_per_hour#3#739, asin#94],
functions=[count(time_window_per_hour#3#739), count(qty_shipped#98),
count(qty_ordered#97), min(item_price#99), max(item_price#99),
avg(cast(item_price#99 as double)), stddev_pop(cast(item_price#99 as double))],
output=[ORD_time_window_per_hour#3#748, ORD_asin#749, ORD_num_of_order#758L,
ORD_tot_qty_shipped#761L, ORD_tot_qty_ordered#764L, ORD_min_ord_item_price#766,
ORD_max_ord_item_price#768, ORD_avg_ord_item_price#770,
ORD_std_ord_item_price#780, ORD_YEAR#781, ORD_MONTH#782, ORD_DAYOFMONTH#783,
ORD_HOUR#784, ORD_DAYOFYEAR#785, ORD_WEEKOFYEAR#786, ORD_DAYOFWEEK#787])
+- Exchange hashpartitioning(time_window_per_hour#3#739, asin#94, 200)
+- *HashAggregate(keys=[time_window_per_hour#3#739, asin#94],
functions=[partial_count(time_window_per_hour#3#739),
partial_count(qty_shipped#98), partial_count(qty_ordered#97),
partial_min(item_price#99), partial_max(item_price#99),
partial_avg(cast(item_price#99 as double)),
partial_stddev_pop(cast(item_price#99 as double))],
output=[time_window_per_hour#3#739, asin#94, count#846L, count#847L,
count#848L, min#849, max#850, sum#851, count#852L, n#833, avg#834, m2#835])
+- *Project [window#746 AS time_window_per_hour#3#739, asin#94,
qty_shipped#98, item_price#99, qty_ordered#97]
+- *Filter ((isnotnull(purchased#102) && (cast(purchased#102 as
timestamp) >= window#746.start)) && (cast(purchased#102 as timestamp) <
window#746.end))
+- *Expand [List(named_struct(start,
((((CEIL((cast((precisetimestamp(cast(purchased#102 as timestamp)) - 0) as
double) / 3.6E9)) + 0) - 1) * 3600000000) + 0), end,
(((((CEIL((cast((precisetimestamp(cast(purchased#102 as timestamp)) - 0) as
double) / 3.6E9)) + 0) - 1) * 3600000000) + 0) + 3600000000)), asin#94,
qty_ordered#97, qty_shipped#98, item_price#99, purchased#102),
List(named_struct(start, ((((CEIL((cast((precisetimestamp(cast(purchased#102 as
timestamp)) - 0) as double) / 3.6E9)) + 1) - 1) * 3600000000) + 0), end,
(((((CEIL((cast((precisetimestamp(cast(purchased#102 as timestamp)) - 0) as
double) / 3.6E9)) + 1) - 1) * 3600000000) + 0) + 3600000000)), asin#94,
qty_ordered#97, qty_shipped#98, item_price#99, purchased#102)], [window#746,
asin#94, qty_ordered#97, qty_shipped#98, item_price#99, purchased#102]
+- *Project [asin#94, qty_ordered#97, qty_shipped#98,
item_price#99, purchased#102]
+- *Filter (((isnotnull(grade#96) &&
isnotnull(item_price#99)) && (grade#96 = New Item)) && isnotnull(purchased#102))
+- *Scan csv
[asin#94,grade#96,qty_ordered#97,qty_shipped#98,item_price#99,purchased#102]
Format: CSV, InputPaths:
file:/Users/carloallocca/Desktop/NSLDataset/20160706/order.csv, PushedFilters:
[IsNotNull(grade), IsNotNull(item_price), EqualTo(grade,New Item),
IsNotNull(purchased)], ReadSchema:
struct<asin:string,grade:string,qty_ordered:int,qty_shipped:string,item_price:float,purchased:str...
)
- element of array (index: 0)
- array (class [Ljava.lang.Object;, size 6)
- field (class:
org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8, name:
references$1, type: class [Ljava.lang.Object;)
- object (class
org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8, <function2>)
at
org.apache.spark.serializer.SerializationDebugger$.improveException(SerializationDebugger.scala:40)
at
org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:46)
at
org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:100)
at
org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:295)
... 61 more
On 28 Jul 2016, at 17:39, Mark Hamstra
<[email protected]<mailto:[email protected]>> wrote:
Don't use Spark 2.0.0-preview. That was a preview release with known issues,
and was intended to be used only for early, pre-release testing purpose. Spark
2.0.0 is now released, and you should be using that.
On Thu, Jul 28, 2016 at 3:48 AM, Carlo.Allocca
<[email protected]<mailto:[email protected]>> wrote:
and, of course I am using
<dependency> <!-- Spark dependency -->
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.11</artifactId>
<version>2.0.0-preview</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.11</artifactId>
<version>2.0.0-preview</version>
<type>jar</type>
</dependency>
Is the below problem/issue related to the experimental version of SPARK 2.0.0.
Many Thanks for your help and support.
Best Regards,
carlo
On 28 Jul 2016, at 11:14, Carlo.Allocca
<[email protected]<mailto:[email protected]>> wrote:
I have also found the following two related links:
1)
https://github.com/apache/spark/commit/947b9020b0d621bc97661a0a056297e6889936d3
2) https://github.com/apache/spark/pull/12433
which both explain why it happens but nothing about what to do to solve it.
Do you have any suggestion/recommendation?
Many thanks.
Carlo
On 28 Jul 2016, at 11:06, carlo allocca
<[email protected]<mailto:[email protected]>> wrote:
Hi Rui,
Thanks for the promptly reply.
No, I am not using Mesos.
Ok. I am writing a code to build a suitable dataset for my needs as in the
following:
== Session configuration:
SparkSession spark = SparkSession
.builder()
.master("local[6]") //
.appName("DatasetForCaseNew")
.config("spark.executor.memory", "4g")
.config("spark.shuffle.blockTransferService", "nio")
.getOrCreate();
public Dataset<Row> buildDataset(){
...
// STEP A
// Join prdDS with cmpDS
Dataset<Row> prdDS_Join_cmpDS
= res1
.join(res2,
(res1.col("PRD_asin#100")).equalTo(res2.col("CMP_asin")), "inner");
prdDS_Join_cmpDS.take(1);
// STEP B
// Join prdDS with cmpDS
Dataset<Row> prdDS_Join_cmpDS_Join
= prdDS_Join_cmpDS
.join(res3,
prdDS_Join_cmpDS.col("PRD_asin#100").equalTo(res3.col("ORD_asin")), "inner");
prdDS_Join_cmpDS_Join.take(1);
prdDS_Join_cmpDS_Join.show();
}
The exception is thrown when the computation reach the STEP B, until STEP A is
fine.
Is there anything wrong or missing?
Thanks for your help in advance.
Best Regards,
Carlo
=== STACK TRACE
Tests run: 1, Failures: 0, Errors: 1, Skipped: 0, Time elapsed: 422.102 sec <<<
FAILURE!
testBuildDataset(org.mksmart.amaretto.ml.DatasetPerHourVerOneTest) Time
elapsed: 421.994 sec <<< ERROR!
org.apache.spark.SparkException: Exception thrown in awaitResult:
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:194)
at
org.apache.spark.sql.execution.exchange.BroadcastExchangeExec.doExecuteBroadcast(BroadcastExchangeExec.scala:102)
at
org.apache.spark.sql.execution.InputAdapter.doExecuteBroadcast(WholeStageCodegenExec.scala:229)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeBroadcast$1.apply(SparkPlan.scala:125)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeBroadcast$1.apply(SparkPlan.scala:125)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
at
org.apache.spark.sql.execution.SparkPlan.executeBroadcast(SparkPlan.scala:124)
at
org.apache.spark.sql.execution.joins.BroadcastHashJoinExec.prepareBroadcast(BroadcastHashJoinExec.scala:98)
at
org.apache.spark.sql.execution.joins.BroadcastHashJoinExec.codegenInner(BroadcastHashJoinExec.scala:197)
at
org.apache.spark.sql.execution.joins.BroadcastHashJoinExec.doConsume(BroadcastHashJoinExec.scala:82)
at
org.apache.spark.sql.execution.CodegenSupport$class.consume(WholeStageCodegenExec.scala:153)
at
org.apache.spark.sql.execution.joins.SortMergeJoinExec.consume(SortMergeJoinExec.scala:35)
at
org.apache.spark.sql.execution.joins.SortMergeJoinExec.doProduce(SortMergeJoinExec.scala:565)
at
org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
at
org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:78)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
at
org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:78)
at
org.apache.spark.sql.execution.joins.SortMergeJoinExec.produce(SortMergeJoinExec.scala:35)
at
org.apache.spark.sql.execution.joins.BroadcastHashJoinExec.doProduce(BroadcastHashJoinExec.scala:77)
at
org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
at
org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:78)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
at
org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:78)
at
org.apache.spark.sql.execution.joins.BroadcastHashJoinExec.produce(BroadcastHashJoinExec.scala:38)
at
org.apache.spark.sql.execution.WholeStageCodegenExec.doCodeGen(WholeStageCodegenExec.scala:304)
at
org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:343)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:114)
at org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:240)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:323)
at
org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
at
org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2122)
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2436)
at
org.apache.spark.sql.Dataset.org<http://org.apache.spark.sql.dataset.org/>$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2121)
at
org.apache.spark.sql.Dataset.org<http://org.apache.spark.sql.dataset.org/>$apache$spark$sql$Dataset$$collect(Dataset.scala:2128)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1862)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1861)
at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2466)
at org.apache.spark.sql.Dataset.head(Dataset.scala:1861)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2078)
at
org.mksmart.amaretto.ml.DatasetPerHourVerOne.buildDataset(DatasetPerHourVerOne.java:115)
at
org.mksmart.amaretto.ml.DatasetPerHourVerOneTest.testBuildDataset(DatasetPerHourVerOneTest.java:76)
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:497)
at
org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:50)
at
org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12)
at
org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:47)
at
org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17)
at org.junit.internal.runners.statements.RunBefores.evaluate(RunBefores.java:26)
at org.junit.internal.runners.statements.RunAfters.evaluate(RunAfters.java:27)
at org.junit.runners.ParentRunner.runLeaf(ParentRunner.java:325)
at
org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:78)
at
org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:57)
at org.junit.runners.ParentRunner$3.run(ParentRunner.java:290)
at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:71)
at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:288)
at org.junit.runners.ParentRunner.access$000(ParentRunner.java:58)
at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:268)
at org.junit.internal.runners.statements.RunBefores.evaluate(RunBefores.java:26)
at org.junit.internal.runners.statements.RunAfters.evaluate(RunAfters.java:27)
at org.junit.runners.ParentRunner.run(ParentRunner.java:363)
at org.apache.maven.surefire.junit4.JUnit4TestSet.execute(JUnit4TestSet.java:53)
at
org.apache.maven.surefire.junit4.JUnit4Provider.executeTestSet(JUnit4Provider.java:123)
at
org.apache.maven.surefire.junit4.JUnit4Provider.invoke(JUnit4Provider.java:104)
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:497)
at
org.apache.maven.surefire.util.ReflectionUtils.invokeMethodWithArray(ReflectionUtils.java:164)
at
org.apache.maven.surefire.booter.ProviderFactory$ProviderProxy.invoke(ProviderFactory.java:110)
at
org.apache.maven.surefire.booter.SurefireStarter.invokeProvider(SurefireStarter.java:175)
at
org.apache.maven.surefire.booter.SurefireStarter.runSuitesInProcessWhenForked(SurefireStarter.java:107)
at org.apache.maven.surefire.booter.ForkedBooter.main(ForkedBooter.java:68)
Caused by: java.util.concurrent.TimeoutException: Futures timed out after [300
seconds]
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:219)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:223)
at scala.concurrent.Await$$anonfun$result$1.apply(package.scala:190)
at
scala.concurrent.BlockContext$DefaultBlockContext$.blockOn(BlockContext.scala:53)
at scala.concurrent.Await$.result(package.scala:190)
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:190)
... 85 more
On 28 Jul 2016, at 10:55, Sun Rui
<[email protected]<mailto:[email protected]>> wrote:
Are you using Mesos? if not , https://issues.apache.org/jira/browse/SPARK-16522
is not relevant
You may describe more information about your Spark environment, and the full
stack trace.
On Jul 28, 2016, at 17:44, Carlo.Allocca
<[email protected]<mailto:[email protected]>> wrote:
Hi All,
I am running SPARK locally, and when running d3=join(d1,d2) and d5=(d3, d4) am
getting the following exception "org.apache.spark.SparkException: Exception
thrown in awaitResult”.
Googling for it, I found that the closed is the answer reported
https://issues.apache.org/jira/browse/SPARK-16522 which mention that it is bug
of the SPARK 2.0.0.
Is it correct or am I missing anything?
Many Thanks for your answer and help.
Best Regards,
Carlo
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