我有一个带有标量/正常值的Hive表，其中的列为String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，然后查询JSON字段。我已经提到了此答案中给出的解决方案：
但是在以下尝试将JSON字符串解析为实际JSON的尝试失败，并显示错误。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
还尝试了：
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
****下面是我的代码：****
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,)
我本人是Spark的新手。我使用快捷方式来解析字符串中的所有JSON。无需尝试使用map和lambda来推断模式，只需获取示例JSON之一并保存在spark可以访问的本地dev linux框中。Linux文件系统或hdfs或S3，都没有关系。
然后使用Pyspark的spark.read.json方法推断模式。我发现这种方法可以完美地工作。
#try to load JSON schema using json file jsondf= spark.read.json("/home/jovyan/work/diag.json")
jsondf.printSchema()
jsonschema = jsondf.schema
print(jsonschema)
lineleveldtlsdf= spark.read.json("/home/jovyan/work/lineleveldetails.json")
lineleveldtlsdf.printSchema()
#Once we get the Schema of the json, then use below code to create a new parsed json column in a new DF, if we want
df2 = df.withColumn('parsedjson', from_json(col('response'), jsonschema))
df2.toPandas()
susmitaghosh_kol@spark-dev-ce:~/notebooks$ cat diag.json {"diagnosis":[{"hdr_diagnosiscode":"2662","hdr_diagnosistypecode":"ICD-9","hdr_diagnosisnumber":6,"hdr_poacode":"-97"},{"hdr_diagnosiscode":"78469","hdr_diagnosistypecode":"ICD-9","hdr_diagnosisnumber":5,"hdr_poacode":"-97"},{"hdr_diagnosiscode":"30000","hdr_diagnosistypecode":"ICD-9","hdr_diagnosisnumber":4,"hdr_poacode":"-97"},{"hdr_diagnosiscode":"317","hdr_diagnosistypecode":"ICD-9","hdr_diagnosisnumber":3,"hdr_poacode":"-97"},{"hdr_diagnosiscode":"7812","hdr_diagnosistypecode":"ICD-9","hdr_diagnosisnumber":2,"hdr_poacode":"-97"},{"hdr_diagnosiscode":"72887","hdr_diagnosistypecode":"ICD-9","hdr_diagnosisnumber":1,"hdr_poacode":"-97"},{"hdr_diagnosiscode":"78097","hdr_diagnosistypecode":"ICD-9","hdr_diagnosisnumber":1003,"hdr_poacode":"-97"},{"hdr_diagnosiscode":"78097","hdr_diagnosistypecode":"ICD-9","hdr_diagnosisnumber":1001,"hdr_poacode":"-97"},{"hdr_diagnosiscode":"4019","hdr_diagnosistypecode":"ICD-9","hdr_diagnosisnumber":7,"hdr_poacode":"-97"}]}
本文收集自互联网，转载请注明来源。
如有侵权，请联系[email protected] 删除。
我来说两句