试图从jupyter笔记本访问带有spark的googlecloud bigtable时出现区域错误

7rtdyuoh  于 2021-06-02  发布在  Hadoop
关注(0)|答案(1)|浏览(393)

我试图在运行pyspark内核的jupyter笔记本中运行对googlecloudbigtable的并行访问。我从http://ec2-54-66-129-240.ap-southeast-2.compute.amazonaws.com/httrack/docs/cloud.google.com/dataproc/examples/cloud-bigtable-example.html 我使用的是我特定的项目/区域/集群/表名。身份验证通过spark上下文中广播的服务帐户凭据进行。

jconf = {"hbase.client.connection.impl": "com.google.cloud.bigtable.hbase1_1.BigtableConnection",
        "google.bigtable.project.id": myProject,
        "google.bigtable.zone.name": myZone,
        "google.bigtable.cluster.name": myCluster,
        "hbase.mapreduce.inputtable": myTable}

keyConv = "org.apache.spark.examples.pythonconverters.ImmutableBytesWritableToStringConverter"
valueConv = "org.apache.spark.examples.pythonconverters.HBaseResultToStringConverter"

hbase_rdd = sc.newAPIHadoopRDD(
    "org.apache.hadoop.hbase.mapreduce.TableInputFormat",
    "org.apache.hadoop.hbase.io.ImmutableBytesWritable",
    "org.apache.hadoop.hbase.client.Result",
    conf=jconf)

hbase_rdd = hbase_rdd.flatMapValues(lambda v: v.split("\n")).mapValues(json.loads)

print("Row count: %s" % hbase_rdd.count())

我得到以下错误：

Py4JJavaErrorTraceback (most recent call last)
<ipython-input-30-55b05ded0d2b> in <module>()
     21     #keyConverter=keyConv,
     22     #valueConverter=valueConv,
---> 23     conf=jconf)
     24 
     25 hbase_rdd = hbase_rdd.flatMapValues(lambda v: v.split("\n")).mapValues(json.loads)

/usr/lib/spark/python/pyspark/context.pyc in newAPIHadoopRDD(self, inputFormatClass, keyClass, valueClass, keyConverter, valueConverter, conf, batchSize)
    644         jrdd = self._jvm.PythonRDD.newAPIHadoopRDD(self._jsc, inputFormatClass, keyClass,
    645                                                    valueClass, keyConverter, valueConverter,
--> 646                                                    jconf, batchSize)
    647         return RDD(jrdd, self)
    648 

/usr/lib/spark/python/lib/py4j-0.10.3-src.zip/py4j/java_gateway.py in __call__(self, *args)
   1131         answer = self.gateway_client.send_command(command)
   1132         return_value = get_return_value(
-> 1133             answer, self.gateway_client, self.target_id, self.name)
   1134 
   1135         for temp_arg in temp_args:

/usr/lib/spark/python/pyspark/sql/utils.pyc in deco(*a,**kw)
     61     def deco(*a,**kw):
     62         try:
---> 63             return f(*a,**kw)
     64         except py4j.protocol.Py4JJavaError as e:
     65             s = e.java_exception.toString()

/usr/lib/spark/python/lib/py4j-0.10.3-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
    317                 raise Py4JJavaError(
    318                     "An error occurred while calling {0}{1}{2}.\n".
--> 319                     format(target_id, ".", name), value)
    320             else:
    321                 raise Py4JError(

Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.newAPIHadoopRDD.
: java.io.IOException: Error sampling rowkeys.
    at com.google.cloud.bigtable.hbase.BigtableRegionLocator.getRegions(BigtableRegionLocator.java:79)
    at com.google.cloud.bigtable.hbase.BigtableRegionLocator.getAllRegionLocations(BigtableRegionLocator.java:100)
    at org.apache.hadoop.hbase.util.RegionSizeCalculator.init(RegionSizeCalculator.java:94)
    at org.apache.hadoop.hbase.util.RegionSizeCalculator.<init>(RegionSizeCalculator.java:81)
    at org.apache.hadoop.hbase.mapreduce.TableInputFormatBase.getSplits(TableInputFormatBase.java:256)
    at org.apache.hadoop.hbase.mapreduce.TableInputFormat.getSplits(TableInputFormat.java:237)
    at org.apache.spark.rdd.NewHadoopRDD.getPartitions(NewHadoopRDD.scala:121)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
    at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
    at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1303)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:358)
    at org.apache.spark.rdd.RDD.take(RDD.scala:1298)
    at org.apache.spark.api.python.SerDeUtil$.pairRDDToPython(SerDeUtil.scala:203)
    at org.apache.spark.api.python.PythonRDD$.newAPIHadoopRDD(PythonRDD.scala:582)
    at org.apache.spark.api.python.PythonRDD.newAPIHadoopRDD(PythonRDD.scala)
    at sun.reflect.GeneratedMethodAccessor30.invoke(Unknown Source)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:280)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:214)
    at java.lang.Thread.run(Thread.java:748)
Caused by: io.grpc.StatusRuntimeException: UNKNOWN
    at io.grpc.Status.asRuntimeException(Status.java:430)
    at io.grpc.stub.ClientCalls$BlockingResponseStream.hasNext(ClientCalls.java:369)
    at com.google.bigtable.repackaged.com.google.common.collect.ImmutableList.copyOf(ImmutableList.java:268)
    at com.google.cloud.bigtable.grpc.BigtableDataGrpcClient.sampleRowKeys(BigtableDataGrpcClient.java:203)
    at com.google.cloud.bigtable.hbase.BigtableRegionLocator.getRegions(BigtableRegionLocator.java:73)
    ... 33 more
Caused by: java.lang.IllegalStateException: Channel is closed
    at com.google.cloud.bigtable.grpc.io.ReconnectingChannel$DelayingCall.start(ReconnectingChannel.java:88)
    at com.google.cloud.bigtable.grpc.io.ChannelPool$1.checkedStart(ChannelPool.java:97)
    at io.grpc.ClientInterceptors$CheckedForwardingClientCall.start(ClientInterceptors.java:164)
    at io.grpc.stub.ClientCalls.startCall(ClientCalls.java:193)
    at io.grpc.stub.ClientCalls.asyncUnaryRequestCall(ClientCalls.java:173)
    at io.grpc.stub.ClientCalls.blockingServerStreamingCall(ClientCalls.java:122)
    at com.google.cloud.bigtable.grpc.io.ClientCallService$1.blockingServerStreamingCall(ClientCallService.java:79)
    ... 35 more

不过，在jupyter笔记本运行的终端上，我可以毫无问题地访问gcloud上的bigtable示例。另外，google.cloud.bigtable和google.cloud.happybase连接器在同一个jupyter笔记本中运行良好（但它们不处理对bigtable的调用的先验并行化）。
你知道我做错什么了吗？
仅供参考，我使用的是spark 2.0.2、hadoop 2.7.3、python 2.7.12、google cloud bigtable 0.26.0、com.google.cloud。bigtable:bigtable-hbase-1.1：0.2.2在google dataproc集群上。
谢谢，
乔治
编辑：在按照igor bernstein的建议编辑之后，我得到了一个新的错误：

Py4JJavaErrorTraceback (most recent call last)
<ipython-input-5-4f0d8b1fb126> in <module>()
     23     #keyConverter=keyConv,
     24     #valueConverter=valueConv,
---> 25     conf=jconf)
     26 
     27 hbase_rdd = hbase_rdd.flatMapValues(lambda v: v.split("\n")).mapValues(json.loads)

/usr/lib/spark/python/pyspark/context.py in newAPIHadoopRDD(self, inputFormatClass, keyClass, valueClass, keyConverter, valueConverter, conf, batchSize)
    644         jrdd = self._jvm.PythonRDD.newAPIHadoopRDD(self._jsc, inputFormatClass, keyClass,
    645                                                    valueClass, keyConverter, valueConverter,
--> 646                                                    jconf, batchSize)
    647         return RDD(jrdd, self)
    648 

/usr/lib/spark/python/lib/py4j-0.10.3-src.zip/py4j/java_gateway.py in __call__(self, *args)
   1131         answer = self.gateway_client.send_command(command)
   1132         return_value = get_return_value(
-> 1133             answer, self.gateway_client, self.target_id, self.name)
   1134 
   1135         for temp_arg in temp_args:

/usr/lib/spark/python/pyspark/sql/utils.py in deco(*a,**kw)
     61     def deco(*a,**kw):
     62         try:
---> 63             return f(*a,**kw)
     64         except py4j.protocol.Py4JJavaError as e:
     65             s = e.java_exception.toString()

/usr/lib/spark/python/lib/py4j-0.10.3-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
    317                 raise Py4JJavaError(
    318                     "An error occurred while calling {0}{1}{2}.\n".
--> 319                     format(target_id, ".", name), value)
    320             else:
    321                 raise Py4JError(

Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.newAPIHadoopRDD.
: java.io.IOException: Cannot create a record reader because of a previous error. Please look at the previous logs lines from the task's full log for more details.
    at org.apache.hadoop.hbase.mapreduce.TableInputFormatBase.getSplits(TableInputFormatBase.java:252)
    at org.apache.hadoop.hbase.mapreduce.TableInputFormat.getSplits(TableInputFormat.java:237)
    at org.apache.spark.rdd.NewHadoopRDD.getPartitions(NewHadoopRDD.scala:121)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
    at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
    at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1303)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:358)
    at org.apache.spark.rdd.RDD.take(RDD.scala:1298)
    at org.apache.spark.api.python.SerDeUtil$.pairRDDToPython(SerDeUtil.scala:203)
    at org.apache.spark.api.python.PythonRDD$.newAPIHadoopRDD(PythonRDD.scala:582)
    at org.apache.spark.api.python.PythonRDD.newAPIHadoopRDD(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:237)
    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:748)
Caused by: java.lang.IllegalStateException: The input format instance has not been properly initialized. Ensure you call initializeTable either in your constructor or initialize method
    at org.apache.hadoop.hbase.mapreduce.TableInputFormatBase.getTable(TableInputFormatBase.java:585)
    at org.apache.hadoop.hbase.mapreduce.TableInputFormatBase.getSplits(TableInputFormatBase.java:247)
    ... 30 more
hadooppythonpysparkjupyter-notebookbigtable

1条答案

按热度按时间
9vw9lbht

9vw9lbht1#

您使用的是什么版本的bigtable hbase？你能试试最新的版本吗？ bigtable-hbase-1.x-hadoop:1.0.0-pre3 ? 另外，请更新您的配置，如下所示： "hbase.client.connection.impl": "com.google.cloud.bigtable.hbase1_x.BigtableConnection" 删除 "google.bigtable.zone.name" & "google.bigtable.cluster.name" 添加 "google.bigtable.instance.id" ：“<your\u instance\u id>”
一定要让内蒂知道-static:1.1.33.fork26 is 在类路径上
而且，我很难找到http://ec2-54-66-129-240.ap-southeast-2.compute.amazonaws.com/httrack/docs/cloud.google.com/dataproc/examples/cloud-bigtable-example.html. 它从哪里来的？

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