我尝试根据this tutorial通过PySpark将实时Kafka数据摄取配置到HBase。我对下面显示的代码有疑问。此刻，我只是尝试以最简单的方式将数据添加到Hbase表中：
def SaveToHBase(rdd):
# print("=====Pull from Stream=====")
if not rdd.isEmpty():
host = 'myhost:2182'
table = 'logs'
keyConv = "org.apache.spark.examples.pythonconverters.StringToImmutableBytesWritableConverter"
valueConv = "org.apache.spark.examples.pythonconverters.StringListToPutConverter"
conf = {"hbase.zookeeper.quorum": host,
"hbase.zookeeper.property.clientPort": "2182",
"hbase.mapred.outputtable": table,
"mapreduce.outputformat.class": "org.apache.hadoop.hbase.mapreduce.TableOutputFormat",
"mapreduce.job.output.key.class": "org.apache.hadoop.hbase.io.ImmutableBytesWritable",
"mapreduce.job.output.value.class": "org.apache.hadoop.io.Writable"}
rdd.saveAsNewAPIHadoopDataset(conf=conf,keyConverter=keyConv,valueConverter=valueConv)
kds = KafkaUtils.createDirectStream(ssc, topic, k_params, fromOffsets=None)
###################################################################### added
parsed = kds.filter(lambda x: x != None and len(x) > 0 )
parsed = parsed.map(lambda x: x[1])
parsed = parsed.map(lambda x: (str('121323322323'),[str('121323322323'),"log","log",'content']))
parsed.foreachRDD(SaveToHBase)
############################################################
# Start application
############################################################
runApplication(ssc, config)
在我看来，所有的罐子都与我的Hbase 2.0.2兼容。为什么我会看到下面的错误提示？
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.saveAsHadoopDataset.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.internal.io.SparkHadoopWriter$.write(SparkHadoopWriter.scala:100)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply$mcV$sp(PairRDDFunctions.scala:1083)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply(PairRDDFunctions.scala:1081)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1.apply(PairRDDFunctions.scala:1081)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.PairRDDFunctions.saveAsNewAPIHadoopDataset(PairRDDFunctions.scala:1081)
at org.apache.spark.api.python.PythonRDD$.saveAsHadoopDataset(PythonRDD.scala:583)
at org.apache.spark.api.python.PythonRDD.saveAsHadoopDataset(PythonRDD.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 72.0 failed 1 times, most recent failure: Lost task 0.0 in stage 72.0 (TID 72, localhost, executor driver): org.apache.spark.SparkException: Task failed while writing rows
at org.apache.spark.internal.io.SparkHadoopWriter$.org$apache$spark$internal$io$SparkHadoopWriter$$executeTask(SparkHadoopWriter.scala:155)
at org.apache.spark.internal.io.SparkHadoopWriter$$anonfun$3.apply(SparkHadoopWriter.scala:83)
at org.apache.spark.internal.io.SparkHadoopWriter$$anonfun$3.apply(SparkHadoopWriter.scala:78)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.NoSuchMethodError: org.apache.hadoop.hbase.client.Put.add([B[B[B)Lorg/apache/hadoop/hbase/client/Put;
at org.apache.spark.examples.pythonconverters.StringListToPutConverter.convert(HBaseConverters.scala:68)
at org.apache.spark.examples.pythonconverters.StringListToPutConverter.convert(HBaseConverters.scala:64)
at org.apache.spark.api.python.PythonHadoopUtil$$anonfun$convertRDD$1.apply(PythonHadoopUtil.scala:181)
at org.apache.spark.api.python.PythonHadoopUtil$$anonfun$convertRDD$1.apply(PythonHadoopUtil.scala:181)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:410)
at org.apache.spark.internal.io.SparkHadoopWriter$$anonfun$4.apply(SparkHadoopWriter.scala:129)
at org.apache.spark.internal.io.SparkHadoopWriter$$anonfun$4.apply(SparkHadoopWriter.scala:127)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1394)
at org.apache.spark.internal.io.SparkHadoopWriter$.org$apache$spark$internal$io$SparkHadoopWriter$$executeTask(SparkHadoopWriter.scala:139)
... 10 more
我的JARS：
os.environ['PYSPARK_SUBMIT_ARGS'] = '--jars \
/spark/spark-streaming-kafka-0-8-assembly_2.11-2.4.0.jar,\
/spark/spark-examples_2.10-1.1.1.jar,\
/hbase/jar_files-9/* pyspark-shell'
答案 0 :(得分：1)
我今天遇到了一些问题。这是我的解决方案。该错误是由于spark-examples-*.jar使用的是低版本hbase-client软件包（0.98）引起的，该软件包与hbase-client 2.*不兼容。因此，我们需要做的是进行一些更改并重新打包。
也许以后我可以将固定的罐子放在这里。