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json - Pyspark JSON 字符串解析 - 错误 : ValueError: 'json' is not in list - no Pandas

转载 作者：行者123 更新时间：2023-12-04 14:16:58 24 4
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我有一个带有标量/正常值的 Hive 表，其中一列是字符串格式的 JSON。
让我们以下面的列表数据为例:

l = [(12, '{"status":"200"}')   ,     (13,'{"data":[{"status":"200","somecol":"300"},{"status":"300","somecol":"400"}]}')]

我想推断字符串字段的架构，然后想查询 JSON 字段。
我已经引用了这个答案中给出的解决方案:

但是下面尝试将 JSON 字符串解析为实际的 JSON 失败并出现错误。
尝试使用以下方法推断 JSON 模式: 
json_schema = spark.read.json(df.rdd.map(lambda row: row.json)).schema

也试过: 
new_df = sqc.read.json(df2.rdd.map(lambda r: r.json))

两者都会导致错误，例如: 
ValueError: 'json' is not in list
AttributeError: json

****以下是我的代码:**** 
from pyspark.sql.functions import json_tuple,from_json,get_json_object
from pyspark.sql import SparkSession
from pyspark.sql import SQLContext
from pyspark.sql.functions import from_json, col, to_json, struct
import json
spark.version

spark = SparkSession.builder.getOrCreate()
sqc = SQLContext(spark)

l = [(12, '{"status":"200"}')   ,     (13,'{"data":[{"status":"200","somecol":"300"},{"status":"300","somecol":"400"}]}')]

df = spark.createDataFrame(l,['pid','response'])
df.toPandas()
df2=df.select('response')
df2.toPandas()

df.printSchema()

json_schema = spark.read.json(df.rdd.map(lambda row: row.json)).schema      #Failing
df2 = df.withColumn('json', from_json(col('response'), json_schema))

new_df = sqc.read.json(df.rdd.map(lambda r: r.json))    #Failing

错误: 
---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
<ipython-input-58-b5b5c342aefa> in <module>
----> 1 json_schema = spark.read.json(df2.rdd.map(lambda row: row.json)).schema
      2 #df2 = df.withColumn('json', from_json(col('response'), json_schema))

/usr/local/spark/python/pyspark/sql/readwriter.py in json(self, path, schema, primitivesAsString, prefersDecimal, allowComments, allowUnquotedFieldNames, allowSingleQuotes, allowNumericLeadingZero, allowBackslashEscapingAnyCharacter, mode, columnNameOfCorruptRecord, dateFormat, timestampFormat, multiLine, allowUnquotedControlChars, lineSep, samplingRatio, dropFieldIfAllNull, encoding)
    284             keyed._bypass_serializer = True
    285             jrdd = keyed._jrdd.map(self._spark._jvm.BytesToString())
--> 286             return self._df(self._jreader.json(jrdd))
    287         else:
    288             raise TypeError("path can be only string, list or RDD")

/usr/local/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py in __call__(self, *args)
   1255         answer = self.gateway_client.send_command(command)
   1256         return_value = get_return_value(
-> 1257             answer, self.gateway_client, self.target_id, self.name)
   1258 
   1259         for temp_arg in temp_args:

/usr/local/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/local/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
    326                 raise Py4JJavaError(
    327                     "An error occurred while calling {0}{1}{2}.\n".
--> 328                     format(target_id, ".", name), value)
    329             else:
    330                 raise Py4JError(

Py4JJavaError: An error occurred while calling o1017.json.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 28.0 failed 1 times, most recent failure: Lost task 0.0 in stage 28.0 (TID 28, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/sql/types.py", line 1527, in __getattr__
    idx = self.__fields__.index(item)
ValueError: 'json' is not in list

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/worker.py", line 377, in main
    process()
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/worker.py", line 372, in process
    serializer.dump_stream(func(split_index, iterator), outfile)
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 141, in dump_stream
    for obj in iterator:
  File "/usr/local/spark/python/pyspark/sql/readwriter.py", line 277, in func
    for x in iterator:
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/util.py", line 99, in wrapper
    return f(*args, **kwargs)
  File "<ipython-input-58-b5b5c342aefa>", line 1, in <lambda>
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/sql/types.py", line 1532, in __getattr__
    raise AttributeError(item)
AttributeError: json

    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:456)
    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:592)
    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:575)
    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:410)
    at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
    at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
    at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:636)
    at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
    at scala.collection.Iterator$class.isEmpty(Iterator.scala:331)
    at scala.collection.AbstractIterator.isEmpty(Iterator.scala:1334)
    at scala.collection.TraversableOnce$class.reduceLeftOption(TraversableOnce.scala:203)
    at scala.collection.AbstractIterator.reduceLeftOption(Iterator.scala:1334)
    at scala.collection.TraversableOnce$class.reduceOption(TraversableOnce.scala:210)
    at scala.collection.AbstractIterator.reduceOption(Iterator.scala:1334)
    at org.apache.spark.sql.catalyst.json.JsonInferSchema$$anonfun$1.apply(JsonInferSchema.scala:70)
    at org.apache.spark.sql.catalyst.json.JsonInferSchema$$anonfun$1.apply(JsonInferSchema.scala:50)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:801)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:801)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:123)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1889)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1877)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1876)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1876)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
    at scala.Option.foreach(Option.scala:257)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2110)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2059)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2048)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2158)
    at org.apache.spark.sql.catalyst.json.JsonInferSchema$.infer(JsonInferSchema.scala:83)
    at org.apache.spark.sql.execution.datasources.json.TextInputJsonDataSource$$anonfun$inferFromDataset$1.apply(JsonDataSource.scala:109)
    at org.apache.spark.sql.execution.datasources.json.TextInputJsonDataSource$$anonfun$inferFromDataset$1.apply(JsonDataSource.scala:109)
    at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
    at org.apache.spark.sql.execution.datasources.json.TextInputJsonDataSource$.inferFromDataset(JsonDataSource.scala:108)
    at org.apache.spark.sql.DataFrameReader$$anonfun$2.apply(DataFrameReader.scala:439)
    at org.apache.spark.sql.DataFrameReader$$anonfun$2.apply(DataFrameReader.scala:439)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.sql.DataFrameReader.json(DataFrameReader.scala:438)
    at org.apache.spark.sql.DataFrameReader.json(DataFrameReader.scala:419)
    at org.apache.spark.sql.DataFrameReader.json(DataFrameReader.scala:405)
    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.api.python.PythonException: Traceback (most recent call last):
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/sql/types.py", line 1527, in __getattr__
    idx = self.__fields__.index(item)
ValueError: 'json' is not in list

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/worker.py", line 377, in main
    process()
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/worker.py", line 372, in process
    serializer.dump_stream(func(split_index, iterator), outfile)
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 141, in dump_stream
    for obj in iterator:
  File "/usr/local/spark/python/pyspark/sql/readwriter.py", line 277, in func
    for x in iterator:
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/util.py", line 99, in wrapper
    return f(*args, **kwargs)
  File "<ipython-input-58-b5b5c342aefa>", line 1, in <lambda>
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/sql/types.py", line 1532, in __getattr__
    raise AttributeError(item)
AttributeError: json

    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:456)
    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:592)
    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:575)
    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:410)
    at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
    at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
    at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:636)
    at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
    at scala.collection.Iterator$class.isEmpty(Iterator.scala:331)
    at scala.collection.AbstractIterator.isEmpty(Iterator.scala:1334)
    at scala.collection.TraversableOnce$class.reduceLeftOption(TraversableOnce.scala:203)
    at scala.collection.AbstractIterator.reduceLeftOption(Iterator.scala:1334)
    at scala.collection.TraversableOnce$class.reduceOption(TraversableOnce.scala:210)
    at scala.collection.AbstractIterator.reduceOption(Iterator.scala:1334)
    at org.apache.spark.sql.catalyst.json.JsonInferSchema$$anonfun$1.apply(JsonInferSchema.scala:70)
    at org.apache.spark.sql.catalyst.json.JsonInferSchema$$anonfun$1.apply(JsonInferSchema.scala:50)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:801)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:801)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:123)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    ... 1 more


new_df = sqc.read.json(df2.rdd.map(lambda r: r.json))
new_df = sqc.read.json(df2.rdd.map(lambda r: r.json))
---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
<ipython-input-60-f44f1b4c98d9> in <module>
----> 1 new_df = sqc.read.json(df2.rdd.map(lambda r: r.json))

/usr/local/spark/python/pyspark/sql/readwriter.py in json(self, path, schema, primitivesAsString, prefersDecimal, allowComments, allowUnquotedFieldNames, allowSingleQuotes, allowNumericLeadingZero, allowBackslashEscapingAnyCharacter, mode, columnNameOfCorruptRecord, dateFormat, timestampFormat, multiLine, allowUnquotedControlChars, lineSep, samplingRatio, dropFieldIfAllNull, encoding)
    284             keyed._bypass_serializer = True
    285             jrdd = keyed._jrdd.map(self._spark._jvm.BytesToString())
--> 286             return self._df(self._jreader.json(jrdd))
    287         else:
    288             raise TypeError("path can be only string, list or RDD")

/usr/local/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py in __call__(self, *args)
   1255         answer = self.gateway_client.send_command(command)
   1256         return_value = get_return_value(
-> 1257             answer, self.gateway_client, self.target_id, self.name)
   1258 
   1259         for temp_arg in temp_args:

/usr/local/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/local/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
    326                 raise Py4JJavaError(
    327                     "An error occurred while calling {0}{1}{2}.\n".
--> 328                     format(target_id, ".", name), value)
    329             else:
    330                 raise Py4JError(

Py4JJavaError: An error occurred while calling o1071.json.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 29.0 failed 1 times, most recent failure: Lost task 0.0 in stage 29.0 (TID 29, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/sql/types.py", line 1527, in __getattr__
    idx = self.__fields__.index(item)
ValueError: 'json' is not in list

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/worker.py", line 377, in main
    process()
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/worker.py", line 372, in process
    serializer.dump_stream(func(split_index, iterator), outfile)
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 141, in dump_stream
    for obj in iterator:
  File "/usr/local/spark/python/pyspark/sql/readwriter.py", line 277, in func
    for x in iterator:
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/util.py", line 99, in wrapper
    return f(*args, **kwargs)
  File "<ipython-input-60-f44f1b4c98d9>", line 1, in <lambda>
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/sql/types.py", line 1532, in __getattr__
    raise AttributeError(item)
AttributeError: json

    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:456)
    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:592)
    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:575)
    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:410)
    at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
    at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
    at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:636)
    at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
    at scala.collection.Iterator$class.isEmpty(Iterator.scala:331)
    at scala.collection.AbstractIterator.isEmpty(Iterator.scala:1334)
    at scala.collection.TraversableOnce$class.reduceLeftOption(TraversableOnce.scala:203)
    at scala.collection.AbstractIterator.reduceLeftOption(Iterator.scala:1334)
    at scala.collection.TraversableOnce$class.reduceOption(TraversableOnce.scala:210)
    at scala.collection.AbstractIterator.reduceOption(Iterator.scala:1334)
    at org.apache.spark.sql.catalyst.json.JsonInferSchema$$anonfun$1.apply(JsonInferSchema.scala:70)
    at org.apache.spark.sql.catalyst.json.JsonInferSchema$$anonfun$1.apply(JsonInferSchema.scala:50)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:801)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:801)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:123)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1889)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1877)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1876)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1876)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
    at scala.Option.foreach(Option.scala:257)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2110)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2059)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2048)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2158)
    at org.apache.spark.sql.catalyst.json.JsonInferSchema$.infer(JsonInferSchema.scala:83)
    at org.apache.spark.sql.execution.datasources.json.TextInputJsonDataSource$$anonfun$inferFromDataset$1.apply(JsonDataSource.scala:109)
    at org.apache.spark.sql.execution.datasources.json.TextInputJsonDataSource$$anonfun$inferFromDataset$1.apply(JsonDataSource.scala:109)
    at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
    at org.apache.spark.sql.execution.datasources.json.TextInputJsonDataSource$.inferFromDataset(JsonDataSource.scala:108)
    at org.apache.spark.sql.DataFrameReader$$anonfun$2.apply(DataFrameReader.scala:439)
    at org.apache.spark.sql.DataFrameReader$$anonfun$2.apply(DataFrameReader.scala:439)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.sql.DataFrameReader.json(DataFrameReader.scala:438)
    at org.apache.spark.sql.DataFrameReader.json(DataFrameReader.scala:419)
    at org.apache.spark.sql.DataFrameReader.json(DataFrameReader.scala:405)
    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.api.python.PythonException: Traceback (most recent call last):
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/sql/types.py", line 1527, in __getattr__
    idx = self.__fields__.index(item)
ValueError: 'json' is not in list

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/worker.py", line 377, in main
    process()
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/worker.py", line 372, in process
    serializer.dump_stream(func(split_index, iterator), outfile)
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 141, in dump_stream
    for obj in iterator:
  File "/usr/local/spark/python/pyspark/sql/readwriter.py", line 277, in func
    for x in iterator:
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/util.py", line 99, in wrapper
    return f(*args, **kwargs)
  File "<ipython-input-60-f44f1b4c98d9>", line 1, in <lambda>
  File "/usr/local/spark/python/lib/pyspark.zip/pyspark/sql/types.py", line 1532, in __getattr__
    raise AttributeError(item)
AttributeError: json

    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:456)
    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:592)
    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:575)
    at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:410)
    at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
    at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
    at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
    at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:636)
    at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
    at scala.collection.Iterator$class.isEmpty(Iterator.scala:331)
    at scala.collection.AbstractIterator.isEmpty(Iterator.scala:1334)
    at scala.collection.TraversableOnce$class.reduceLeftOption(TraversableOnce.scala:203)
    at scala.collection.AbstractIterator.reduceLeftOption(Iterator.scala:1334)
    at scala.collection.TraversableOnce$class.reduceOption(TraversableOnce.scala:210)
    at scala.collection.AbstractIterator.reduceOption(Iterator.scala:1334)
    at org.apache.spark.sql.catalyst.json.JsonInferSchema$$anonfun$1.apply(JsonInferSchema.scala:70)
    at org.apache.spark.sql.catalyst.json.JsonInferSchema$$anonfun$1.apply(JsonInferSchema.scala:50)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:801)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:801)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:123)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    ... 1 more


2
df2.toPandas()
pid response    json
0   12  {"status":"200"}    (None,)
1   13  {"data":[{"status":"200","somecol":"300"},{"st...   (None,)
​

最佳答案

在您的示例中，2 个 JSON 字符串没有相同的架构，那么哪个是正确的？如果所有行中的架构不同，您将在解析时丢失一些数据。

要解析该列，您可以首先从一个 json 字符串推断架构(收集一个值并将其传递给 schema_of_json )。像这样的东西:

schema = schema_of_json(df.select(col("response")).take(1)[0].response)
df2 = df.withColumn('json', from_json(col('response'), json_schema))
df2.show()

输出:(假设正确的模式是带有 pid=13 的模式) 
+---+----------------------------------------------------------------------------+--------------------------+
|pid|response                                                                    |json                  |
+---+----------------------------------------------------------------------------+--------------------------+
|13 |{"data":[{"status":"200","somecol":"300"},{"status":"300","somecol":"400"}]}|[[[300, 200], [400, 300]]]|
|12 |{"status":"200"}                                                            |[]                        |
+---+----------------------------------------------------------------------------+--------------------------+

关于json - Pyspark JSON 字符串解析 - 错误 : ValueError: 'json' is not in list - no Pandas，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/59218571/

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