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关于 python：尝试从 Jupyter Notebook 使用 Spark 访问 Google Cloud Bigtable 时出现区域错误 | 珊瑚贝

01-05 技术文章 280

Region Error when trying to access Google Cloud Bigtable with Spark from a Jupyter Notebook


我正在尝试从运行 PySpark 内核的 Jupyter Notebook 中运行对 Google Cloud Bigtable 的并行访问。我以 http://ec2-54-66-129-240.ap-southeast-2.compute.amazonaws.com/httrack/docs/cloud.google.com/dataproc/examples/cloud-bigtable-example 为例.html 并且我正在使用我的特定项目/区域/集群/表名称。身份验证通过在 spark 上下文中广播的服务帐户凭据进行。

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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(“\
“)).mapValues(json.loads)

print(“Row count: %s” % hbase_rdd.count())

我收到以下错误：

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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(“\
“)).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}.\
“.
—> 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

从运行 Jupyter 笔记本的终端，我可以毫无问题地访问 GCloud 上的 Bigtable 实例。此外，google.cloud.bigtable 和 google.cloud.happybase 连接器在同一个 Jupyter 笔记本中工作正常(但它们不处理对 Bigtable 的调用的先验并行化)。

知道我在这里可能做错了什么吗？

仅供参考，我正在使用 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。

非常感谢，

乔治

编辑：
按照 Igor Bernstein 的建议进行编辑后，我收到了一个新错误：

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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(“\
“)).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}.\
“.
—> 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

您使用的是什么版本的 bigtable-hbase？可以试试最新版本吗？ bigtable-hbase-1.x-hadoop:1.0.0-pre3？另外请更新您的配置如下：

  • “hbase.client.connection.impl”:”com.google.cloud.bigtable.hbase1_x.BigtableConnection”
  • 删除 “google.bigtable.zone.name”



    相关讨论

    • 嗨@igor-bernstein，感谢您的回答！我收到了一个新错误，并且已将信息包含在问题本身中。
    • 至于示例代码，我不知道它来自哪里(你滚动到网页底部了吗？)

来源：https://www.codenong.com/46470444/

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