Comments (2)
Jimvin
commented on July 22, 2024
Use the class net.ripe.hadoop.pcap.mr1.io.PcapInputFormat for your table
instead. I had issues in the past with using MRv2 classes with Hive, so I
added an alternate version using the older MRv1 classes.
Regards,
Jim
…On 24 May 2017 at 16:26, shsmonteiro ***@***.***> wrote:
I was trying to use the class in Spark, but it fails every time, with the
above error. It works great on hive, but fails everytime in spark.:
hc = HiveContext(sc)
hc.sql("ADD JAR /home/hadoop/jars/hadoop-pcap-serde-1.1-jar-with-
dependencies.jar")
hc.sql("ADD JAR /home/hadoop/jars/p3-lib.jar") <= this is a customized
version, implementing oracle dissector.
hc.sql("SET hive.input.format=org.apache.hadoop.hive.ql.io.
CombineHiveInputFormat")
hc.sql("SET mapred.max.split.size=104857600")
hc.sql("SET net.ripe.hadoop.pcap.io.reader.class=net.ripe.hadoop.
pcap.OraclePCapReader")
secSQL = "CREATE EXTERNAL TABLE ora_pcap_sec (id bigint, ts_usec double,
src string, src_port int, dst string, dst_port int, tns_auth_user string,
tns_aut_app_user string, tns_auth_passwd string, tns_auth_terminal string,
tns_auth_program_nm string, tns_auth_machine string)
ROW FORMAT SERDE 'net.ripe.hadoop.pcap.serde.PcapDeserializer' WITH
SERDEPROPERTIES("serialization.encoding"='SJIS')
STORED AS INPUTFORMAT 'net.ripe.hadoop.pcap.io.PcapInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
LOCATION 'hdfs:///pcaps/'"
hc.sql(secSQL)
sSec = "FROM ora_pcap_sec select *"
pgSec = hc.sql(sSec)
pgSec.write.jdbc(postgre_url,"ora_pcap_sec", "append", myPgProps)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$
scheduler$DAGScheduler$$failJobAndIndependentStages(
DAGScheduler.scala:1435)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(
DAGScheduler.scala:1423)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(
DAGScheduler.scala:1422)
at scala.collection.mutable.ResizableArray$class.foreach(
ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(
DAGScheduler.scala:1422)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$
handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$
handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(
DAGScheduler.scala:802)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.
doOnReceive(DAGScheduler.scala:1650)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.
onReceive(DAGScheduler.scala:1605)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.
onReceive(DAGScheduler.scala:1594)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1918)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1931)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1958)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.
apply(RDD.scala:925)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.
apply(RDD.scala:923)
at org.apache.spark.rdd.RDDOperationScope$.withScope(
RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(
RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:923)
at org.apache.spark.sql.Dataset$$anonfun$foreachPartition$1.
apply$mcV$sp(Dataset.scala:2305)
at org.apache.spark.sql.Dataset$$anonfun$foreachPartition$1.
apply(Dataset.scala:2305)
at org.apache.spark.sql.Dataset$$anonfun$foreachPartition$1.
apply(Dataset.scala:2305)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(
SQLExecution.scala:57)
at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2765)
at org.apache.spark.sql.Dataset.foreachPartition(Dataset.scala:2304)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.saveTable(
JdbcUtils.scala:670)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.
createRelation(JdbcRelationProvider.scala:90)
at org.apache.spark.sql.execution.datasources.DataSource.write(DataSource.
scala:426)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:215)
at org.apache.spark.sql.DataFrameWriter.jdbc(DataFrameWriter.scala:446)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(
NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(
DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.ClassCastException: net.ripe.hadoop.pcap.io.PcapInputFormat
cannot be cast to org.apache.hadoop.mapred.InputFormat
at org.apache.spark.rdd.HadoopRDD.getInputFormat(HadoopRDD.scala:188)
at org.apache.spark.rdd.HadoopRDD$$anon$1.(HadoopRDD.scala:245)
at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:211)
at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:102)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(
MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(
MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(
MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(
MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(
MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
at java.util.concurrent.ThreadPoolExecutor.runWorker(
ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(
ThreadPoolExecutor.java:617)
... 1 more
Am I missing something?
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from hadoop-pcap.
Jimvin
commented on July 22, 2024
Tested and confirmed workaround in spark-shell.
scala> sqlContext.sql("CREATE EXTERNAL TABLE ora_pcap_sec (id bigint, ts_usec double, src string, src_port int, dst string, dst_port int, tns_auth_user string, tns_aut_app_user string, tns_auth_passwd string, tns_auth_terminal string, tns_auth_program_nm string, tns_auth_machine string) ROW FORMAT SERDE 'net.ripe.hadoop.pcap.serde.PcapDeserializer' WITH SERDEPROPERTIES('serialization.encoding'='SJIS') STORED AS INPUTFORMAT 'net.ripe.hadoop.pcap.mr1.io.PcapInputFormat' OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat' LOCATION 'hdfs:///user/cloudera/pcap/data/'")
res6: org.apache.spark.sql.DataFrame = [result: string]
scala> val result2 = sqlContext.sql("select * from ora_pcap_sec")
result2: org.apache.spark.sql.DataFrame = [id: bigint, ts_usec: double, src: string, src_port: int, dst: string, dst_port: int, tns_auth_user: string, tns_aut_app_user: string, tns_auth_passwd: string, tns_auth_terminal: string, tns_auth_program_nm: string, tns_auth_machine: string]
scala> result2.count()
res7: Long = 21231
scala> result2.take(1)
res9: Array[org.apache.spark.sql.Row] = Array([58971,1.495641717739781E9,10.0.2.15,22,10.0.2.2,50302,null,null,null,null,null,null])
from hadoop-pcap.
Related Issues (20)
- New fields addition HOT 2
- Re-compile to include HiveDecimal HOT 2
- headerKeys in HttpPcapReader not initialize properly HOT 1
- java.lang.RuntimeException: java.lang.RuntimeException: class net.ripe.hadoop.pcap.DnsPcapReader not net.ripe.hadoop.pcap.PcapReader HOT 3
- parsed pcaket with NULL source and destination HOT 3
- "Not a PCAP file" error HOT 2
- Fragment ordering
- Ignore malformed packets HOT 1
- Re-assembly for out-of-order packets HOT 1
- Not able to extract packet payload data HOT 9
- new MapReduce API support would be nice HOT 4
- NullPointerException at "NewTrackingRecordReader.initialize(MapTask.java:548)"
- No Module in PySpark HOT 4
- get URL in HTTP_HEADERS
- Porting code to spark 2.0 HOT 4
- Releasing 1.2 in Maven repository?
- The method close() of type PcapRecordReader must override a superclass method
- How To Run Hadoop PCAP File In Eclipse
- how to read incoming network traffic information through hadoop pcap lib and hadoop pacp serde libraries HOT 1
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