I am using Confluent-3.2.1 as a Kafka streamer. I am trying to aggregate my KGroupedStream<String, MyClass1> into KTable<Windowed<String>,MsgAggr>. While using aggregation, I am also using TimeWindows.of(TimeUnit.SECONDS.toMillis(5)). I am using user defined "Serdes" as an argument to aggregation. The code for User define "Serdes" is,
Map<String, Object> serdeProps = new HashMap<>();
final Serializer<MsgAggr> pageViewSerializer = new JsonPOJOSerializer<>();
serdeProps.put("JsonPOJOClass", MsgAggr.class);
pageViewSerializer.configure(serdeProps, false);
final Deserializer<MsgAggr> pageViewDeserializer = new JsonPOJODeserializer<>();
serdeProps.put("JsonPOJOClass", MsgAggr.class);
pageViewDeserializer.configure(serdeProps, false);
final Serde<MsgAggr> pageViewSerde = Serdes.serdeFrom(pageViewSerializer, pageViewDeserializer);`
Code for Streaming is
KGroupedStream<String, MyClass1> msg_grp = message
.groupByKey();
KTable<Windowed<String>,MsgAggr> msg_win = msg_grp
//.reduce(new Reduced(), arg1, arg2);
.aggregate(new Init(),
new Aggr(),
TimeWindows.of(TimeUnit.SECONDS.toMillis(5)),
pageViewSerde,
"MySample_out");
When I run the code I got the errors:
[2017-05-23 18:16:45,648] ERROR stream-thread [StreamThread-1] Streams application error during processing: (org.apache.kafka.streams.processor.internals.StreamThread:249)
java.lang.ClassCastException: my.kafka.strm.MyClass1 cannot be cast to java.lang.String
at org.apache.kafka.common.serialization.StringSerializer.serialize(StringSerializer.java:24)
at org.apache.kafka.streams.processor.internals.RecordCollectorImpl.send(RecordCollectorImpl.java:64)
at org.apache.kafka.streams.processor.internals.SinkNode.process(SinkNode.java:82)
at org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(ProcessorContextImpl.java:202)
at org.apache.kafka.streams.kstream.internals.KStreamFilter$KStreamFilterProcessor.process(KStreamFilter.java:44)
at org.apache.kafka.streams.processor.internals.ProcessorNode.process(ProcessorNode.java:82)
at org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(ProcessorContextImpl.java:202)
at org.apache.kafka.streams.kstream.internals.KStreamMap$KStreamMapProcessor.process(KStreamMap.java:43)
at org.apache.kafka.streams.processor.internals.ProcessorNode.process(ProcessorNode.java:82)
at org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(ProcessorContextImpl.java:202)
at org.apache.kafka.streams.processor.internals.SourceNode.process(SourceNode.java:66)
at org.apache.kafka.streams.processor.internals.StreamTask.process(StreamTask.java:180)
at org.apache.kafka.streams.processor.internals.StreamThread.runLoop(StreamThread.java:436)
at org.apache.kafka.streams.processor.internals.StreamThread.run(StreamThread.java:242)
Exception in thread "StreamThread-1" java.lang.ClassCastException: my.kafka.strm.MyClass1 cannot be cast to java.lang.String
at org.apache.kafka.common.serialization.StringSerializer.serialize(StringSerializer.java:24)
at org.apache.kafka.streams.processor.internals.RecordCollectorImpl.send(RecordCollectorImpl.java:64)
at org.apache.kafka.streams.processor.internals.SinkNode.process(SinkNode.java:82)
at org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(ProcessorContextImpl.java:202)
at org.apache.kafka.streams.kstream.internals.KStreamFilter$KStreamFilterProcessor.process(KStreamFilter.java:44)
at org.apache.kafka.streams.processor.internals.ProcessorNode.process(ProcessorNode.java:82)
at org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(ProcessorContextImpl.java:202)
at org.apache.kafka.streams.kstream.internals.KStreamMap$KStreamMapProcessor.process(KStreamMap.java:43)
at org.apache.kafka.streams.processor.internals.ProcessorNode.process(ProcessorNode.java:82)
at org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(ProcessorContextImpl.java:202)
at org.apache.kafka.streams.processor.internals.SourceNode.process(SourceNode.java:66)
at org.apache.kafka.streams.processor.internals.StreamTask.process(StreamTask.java:180)
at org.apache.kafka.streams.processor.internals.StreamThread.runLoop(StreamThread.java:436)
at org.apache.kafka.streams.processor.internals.StreamThread.run(StreamThread.java:242)
The problem is with message.groupByKey();. Its using the String Serde for your custom class MyClass1. Please implement custom Serializer and deserializer for MyClass1 and use the same in the overloaded version of groupByKey - https://kafka.apache.org/0102/javadoc/org/apache/kafka/streams/kstream/KStream.html#groupByKey(org.apache.kafka.common.serialization.Serde,%20org.apache.kafka.common.serialization.Serde)
Related
Using Hazelcast version 4.2.5 in a webapp deployed on Tomcat on Kubernetes. We're frequently("every 5 seconds") seeing ClassCastException with a stacktrace in the application logs.
Here's the ClassCastException :
java.lang.ClassCastException: class java.lang.String cannot be cast to class com.hazelcast.internal.serialization.impl.HeapData (java.lang.String is in module java.base of loader 'bootstrap'; com.hazelcast.internal.serialization.impl.HeapData is in unnamed module of loader org.apache.catalina.loader.ParallelWebappClassLoader #2f04993d)
27-Oct-2022 22:57:56.357 WARNING [hz.rogueUsers.cached.thread-2] com.hazelcast.internal.metrics.impl.MetricsCollectionCycle.null Collecting metrics from source com.hazelcast.replicatedmap.impl.ReplicatedMapService failed
at com.hazelcast.internal.util.executor.HazelcastManagedThread.run(HazelcastManagedThread.java:102)
at com.hazelcast.internal.util.executor.HazelcastManagedThread.executeRun(HazelcastManagedThread.java:76)
at java.base/java.lang.Thread.run(Thread.java:834)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at com.hazelcast.internal.util.executor.CachedExecutorServiceDelegate$Worker.run(CachedExecutorServiceDelegate.java:217)
at com.hazelcast.spi.impl.executionservice.impl.DelegateAndSkipOnConcurrentExecutionDecorator$DelegateDecorator.run(DelegateAndSkipOnConcurrentExecutionDecorator.java:77)
at com.hazelcast.internal.metrics.impl.MetricsService.collectMetrics(MetricsService.java:154)
at com.hazelcast.internal.metrics.impl.MetricsService.collectMetrics(MetricsService.java:160)
at com.hazelcast.internal.metrics.impl.MetricsRegistryImpl.collect(MetricsRegistryImpl.java:316)
at com.hazelcast.internal.metrics.impl.MetricsCollectionCycle.collectDynamicMetrics(MetricsCollectionCycle.java:88)
at com.hazelcast.replicatedmap.impl.ReplicatedMapService.provideDynamicMetrics(ReplicatedMapService.java:387)
at com.hazelcast.replicatedmap.impl.ReplicatedMapService.getStats(ReplicatedMapService.java:357)
at com.hazelcast.replicatedmap.impl.ReplicatedMapService.getLocalReplicatedMapStats(ReplicatedMapService.java:197)
at com.hazelcast.replicatedmap.impl.LocalReplicatedMapStatsProvider.getLocalReplicatedMapStats(LocalReplicatedMapStatsProvider.java:85)
Here's how we're setting up Hazelcast.
private static HazelcastInstance setupHazelcastConfig() {
Config config = new Config();
config.setInstanceName("rogueUsers");
NetworkConfig network = config.getNetworkConfig();
network.setPort(5701).setPortCount(20);
network.setPortAutoIncrement(true);
JoinConfig join = network.getJoin();
join.getMulticastConfig().setEnabled(true);
// join.getTcpIpConfig()
// .setEnabled(true);
HazelcastInstance hz = Hazelcast.getOrCreateHazelcastInstance(config);
ReplicatedMapConfig replicatedMapConfig =
config.getReplicatedMapConfig("rogueUsers");
replicatedMapConfig.setInMemoryFormat(InMemoryFormat.BINARY);
replicatedMapConfig.setAsyncFillup(true);
replicatedMapConfig.setStatisticsEnabled(true);
replicatedMapConfig.setSplitBrainProtectionName("splitbrainprotection-name");
ReplicatedMap<String, String> map = hz.getReplicatedMap("rogueUsers");
map.addEntryListener(new RogueEntryListener());
return hz;
}
Is this a configuration issue ?
How do I fix this ?
Thanks very much,
The exception is being thrown from the following line:
if (isBinary) {
memoryUsage += ((HeapData) record.getValueInternal()).getHeapCost(); <-- exception
}
which is line 85 of com.hazelcast.replicatedmap.impl.LocalReplicatedMapStats class. The condition being checked is as the following:
boolean isBinary = (replicatedMapConfig.getInMemoryFormat() == InMemoryFormat.BINARY);
so basically, it is related to the format you are saving the data (from the config above you have chosen BINARY).
However, I don't think you are following it correctly since you do the following: ReplicatedMap<String, String> map = hz.getReplicatedMap("rogueUsers"); in your config.
From the Javadoc of com.hazelcast.internal.serialization.Data class:
Data is basic unit of serialization. It stores binary form of an object serialized by SerializationService.toData(Object).
Therefore, try editing your config to this:
ReplicatedMap<Data, Data> map = hz.getReplicatedMap("rogueUsers");
I ran the spark application where i joined two datsets and formed one dataset,and using an Encoder I converted Dataset<Row> into Dataset<T> format.
Encoder looks as follows:
Encoder<RuleParamsBean> encoder = Encoders.bean(RuleParamsBean.class);
Dataset<RuleParamsBean> ds = new Dataset<RuleParamsBean>(sparkSession, finalJoined.logicalPlan(), encoder);
Dataset<RuleParamsBean> validateDataset = ds.map(rulesParamBean -> validateTransaction(rulesParamBean),encoder);
validateDataset.show();
And after the map operation over the dataset i am getting the error as follows:
Dataset<RuleParamsBean> ds = new Dataset<RuleParamsBean>(sparkSession, finalJoined.logicalPlan(), encoder);
Error Log
Exception in thread "main" org.apache.spark.sql.AnalysisException: cannot resolve 'named_struct()' due to data type mismatch: input to function named_struct requires at least one argument;;
Relation[TXN_DETAIL_ID#0,TXN_HEADER_ID#1,TXN_SOURCE_CD#2,TXN_REC_TYPE_CD#3,TXN_DTTM#4,EXT_TXN_NBR#5,CUST_REF_NBR#6,CIS_DIVISION#7,ACCT_ID#8,TXN_VOL#9,TXN_AMT#10,CURRENCY_CD#11,MANUAL_SW#12,USER_ID#13,HOW_TO_USE_TXN_FLG#14,MESSAGE_CAT_NBR#15,MESSAGE_NBR#16,UDF_CHAR_1#17,UDF_CHAR_2#18,UDF_CHAR_3#19,UDF_CHAR_4#20,UDF_CHAR_5#21,UDF_CHAR_6#22,UDF_CHAR_7#23,... 102 more fields] JDBCRelation(CI_TXN_DETAIL_STG_DUMMY) [numPartitions=1]
Relation[ACCT_ID#377,ACCT_NBR_TYPE_CD#378,ACCT_NBR#379,VERSION#380,PRIM_SW#381] JDBCRelation(CI_ACCT_NBR_DUMMY) [numPartitions=1]
at org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:93)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:85)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:289)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:289)
at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:288)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:286)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:286)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:286)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:286)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:286)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:286)
at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$transformExpressionsUp$1.apply(QueryPlan.scala:95)
at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$transformExpressionsUp$1.apply(QueryPlan.scala:95)
at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpression$1(QueryPlan.scala:106)
at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1(QueryPlan.scala:116)
at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1$1.apply(QueryPlan.scala:120)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.immutable.List.map(List.scala:285)
at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1(QueryPlan.scala:120)
at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$1.apply(QueryPlan.scala:125)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
at org.apache.spark.sql.catalyst.plans.QueryPlan.mapExpressions(QueryPlan.scala:125)
at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsUp(QueryPlan.scala:95)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:85)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:80)
at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:80)
at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:91)
at org.apache.spark.sql.catalyst.analysis.Analyzer.executeAndCheck(Analyzer.scala:104)
at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:57)
at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:55)
at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:47)
at org.apache.spark.sql.Dataset.<init>(Dataset.scala:172)
at org.apache.spark.sql.Dataset.<init>(Dataset.scala:178)
at org.apache.spark.sql.Dataset$.apply(Dataset.scala:65)
at org.apache.spark.sql.Dataset.withTypedPlan(Dataset.scala:3300)
at org.apache.spark.sql.Dataset.map(Dataset.scala:2569)
at com.sample.Transformation.main(Transformation.java:100)
For me the issue was because of unsupported type. I was using LocalDate which was not supported in Spark 2.X I guess.(I think they included support for it in version 3)
I simply changed it from LocalDate to TimeStamp and it worked. Look if this is the case for you as well? Any type which is in your POJO which is not supported?
I use spring-cloud-stream-schema to read avro messages from kafka. I configured input channel in MessagesChannels:
#Input("topicName1")
SubscribableChannel fromInput1();
I have configuration file like that:
#Configuration
#EnableBinding(MessagesChannels.class)
#EnableSchemaRegistryClient
public class MessageConfiguration {
#Bean
public MessageConverter topic1MessageConverter() throws IOException {
return new AvroSchemaMessageConverter(MimeType.valueOf("avro/bytes"));
}
}
And my consumer is called with
fromInput1().subscribe(this::onMessage);
void onMessage(Message message) {
}
When I actually sent message I got this error:
nested exception is java.lang.ClassCastException:
org.apache.avro.generic.GenericData$Record cannot be cast to [B
Actually raw bytes are parsed correctly into org.apache.avro.generic.GenericData$Record. But spring requires Message class. How to cast GenericData$Record to Message or how to cast GenericData$Record directly to generated by avro-tools class?
More details:
2017-03-06 11:23:10.695 ERROR 19690 --- [afka-listener-1] o.s.kafka.listener.LoggingErrorHandler : Error while processing: ConsumerRecord(topic = topic1, partition = 0, offset = 7979, CreateTime = 1488784987569, checksum = 623709057, serialized key size = -1, serialized value size = 36, key = null, value = {"foor": "bar"})
org.springframework.messaging.MessageHandlingException: error occurred in message handler [org.springframework.cloud.stream.binder.AbstractMessageChannelBinder$ReceivingHandler#4bf9d802]; nested exception is java.lang.ClassCastException: org.apache.avro.generic.GenericData$Record cannot be cast to [B
at org.springframework.integration.handler.AbstractMessageHandler.handleMessage(AbstractMessageHandler.java:139)
at org.springframework.integration.channel.FixedSubscriberChannel.send(FixedSubscriberChannel.java:70)
at org.springframework.integration.channel.FixedSubscriberChannel.send(FixedSubscriberChannel.java:64)
I think you need to set the contentType for the incoming message channel to use application/*+avro as specified here
I am trying to write a parquet read/write class for a certain class type using DataFrame/datasets
class schema:
class A {
long count;
List<B> listOfValues;
}
class B {
String id;
long count;
}
code :
String path = "some path";
List<A> entries = somerandomAentries();
JavaRDD<A> rdd = sc.parallelize(entries, 1);
DataFrame df = sqlContext.createDataFrame(rdd, A.class);
df.write().parquet(path);
DataFrame newDataDF = sqlContext.read().parquet(path);
newDataDF.show();
when i try to run this, it throws an error. what am I missing here? Do I need to provide a schema for the whole class while creating data frames
error:
Caused by: scala.MatchError: B(Id=abc, count=0) (of class B)
at org.apache.spark.sql.catalyst.CatalystTypeConverters$StructConverter.toCatalystImpl(CatalystTypeConverters.scala:255)
at org.apache.spark.sql.catalyst.CatalystTypeConverters$StructConverter.toCatalystImpl(CatalystTypeConverters.scala:250)
at org.apache.spark.sql.catalyst.CatalystTypeConverters$CatalystTypeConverter.toCatalyst(CatalystTypeConverters.scala:102)
at org.apache.spark.sql.catalyst.CatalystTypeConverters$ArrayConverter.toCatalystImpl(CatalystTypeConverters.scala:169)
at org.apache.spark.sql.catalyst.CatalystTypeConverters$ArrayConverter.toCatalystImpl(CatalystTypeConverters.scala:153)
at org.apache.spark.sql.catalyst.CatalystTypeConverters$CatalystTypeConverter.toCatalyst(CatalystTypeConverters.scala:102)
at org.apache.spark.sql.catalyst.CatalystTypeConverters$$anonfun$createToCatalystConverter$2.apply(CatalystTypeConverters.scala:401)
at org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows$1$$anonfun$apply$1.apply(SQLContext.scala:1358)
at org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows$1$$anonfun$apply$1.apply(SQLContext.scala:1358)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
at org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows$1.apply(SQLContext.scala:1358)
at org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows$1.apply(SQLContext.scala:1356)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at org.apache.spark.sql.execution.datasources.DefaultWriterContainer.writeRows(WriterContainer.scala:263)
... 8 more
You are getting error because nested JavaBeans are not supported in Spark 1.6 version. Please see https://spark.apache.org/docs/1.6.0/sql-programming-guide.html#inferring-the-schema-using-reflection
Currently, Spark SQL does not support JavaBeans that contain nested or contain complex types such as Lists or Arrays.
I have written a code which can reduce the grammatical boundaries for a text, but when I run the program this exception comes up
java.lang.ClassCastException
here is the class that i run,
public class paerser {
public static void main (String [] arg){
LexicalizedParser lp = new LexicalizedParser("grammar/englishPCFG.ser.gz");
lp.setOptionFlags("-maxLength", "500", "-retainTmpSubcategories");
TreebankLanguagePack tlp = new PennTreebankLanguagePack();
GrammaticalStructureFactory gsf = tlp.grammaticalStructureFactory();
String text = "John, who was the CEO of a company, played golf.";
edu.stanford.nlp.trees.Tree parse = lp.apply(Arrays.asList(text));
GrammaticalStructure gs = gsf.newGrammaticalStructure(parse);
List<TypedDependency> tdl = gs.typedDependenciesCCprocessed();
System.out.println(tdl);
}
}
Updated,
here is the full stack trace ...
Loading parser from serialized file grammar/englishPCFG.ser.gz ... done [1.5 sec].
Following exception caught during parsing:
java.lang.ClassCastException: java.lang.String cannot be cast to edu.stanford.nlp.ling.HasWord
at edu.stanford.nlp.parser.lexparser.ExhaustivePCFGParser.parse(ExhaustivePCFGParser.java:346)
at edu.stanford.nlp.parser.lexparser.LexicalizedParser.parse(LexicalizedParser.java:386)
at edu.stanford.nlp.parser.lexparser.LexicalizedParser.apply(LexicalizedParser.java:304)
at paerser.main(paerser.java:19)
Recovering using fall through strategy: will construct an (X ...) tree.
Exception in thread "main" java.lang.ClassCastException: java.lang.String cannot be cast to edu.stanford.nlp.ling.HasWord
at edu.stanford.nlp.parser.lexparser.LexicalizedParser.apply(LexicalizedParser.java:317)
at paerser.main(paerser.java:19)
Stacktrace shows that ExhaustivePCFGParser's parse method is being used. It expects a List of HasWord objects. You are passing a list of String. Hence, the exception.
public boolean parse(List<? extends HasWord> sentence) { // ExhaustivePCFGParser