7显示。清除输出（等待=真） sql中的~/spark-2.1.1-bin-hadoop2.7/python/pyspark/sql/session.py（self，sqlQuery） 543[行（f1=1，f2=u'row1'）、行（f1=2，f2=u'row2'）、行（f1=3，f2=u'row3'）] 544 """ -->545返回数据帧（self.\u jsparkSession.sql（sqlQuery），self.\u包装） 546 547@自（2.0） spark-2.1.1-bin-hadoop2.7/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py in____调用__（self，*args） 1131 answer=self.gateway\u client.send\u命令（command） 1132返回值=获取返回值( ->1133应答，self.gateway\u客户端，self.target\u id，self.name） 1134 1135对于临时参数中的临时参数： 装饰中的~/spark-2.1.1-bin-hadoop2.7/python/pyspark/sql/utils.py（*a，**kw） 67 e.java_exception.getStackTrace（）） 68如果s.StartWith（'org.apache.spark.sql.AnalysisException:'）： --->69 raise AnalysisException（s.split（“：”，1）[1]，stackTrace） 70如果s.startswith（'org.apache.spark.sql.catalyst.analysis'）： 71引发分析异常（s.split（“：”，1）[1]，stackTrace） AnalysisException:“未找到表或视图：tweets；第1行位置23”

它显示“未获取临时表Tweets”[AnalysisException]

有人对此有任何更新吗？我遇到了完全相同的问题

# Use Parenthesis for multiple lines or use \.
( lines.flatMap( lambda text: text.split( " " ) ) #Splits to a list
  .filter( lambda word: word.lower().startswith("#") ) # Checks for hashtag calls
  .map( lambda word: ( word.lower(), 1 ) ) # Lower cases the word
  .reduceByKey( lambda a, b: a + b ) # Reduces
  .map( lambda rec: Tweet( rec[0], rec[1] ) ) # Stores in a Tweet Object
  .foreachRDD( lambda rdd: rdd.toDF().sort( desc("count") ) # Sorts Them in a DF
  .limit(5).createOrReplaceTempView("tweets") ) ) # Registers to a table.

import time
from IPython import display
import matplotlib.pyplot as plt
import seaborn as sns
# Only works for Jupyter Notebooks!
get_ipython().magic('matplotlib inline')

count = 0
while count < 10:
    time.sleep( 3 )
    print(lines)
    top_10_tweets = spark.sql( 'Select tag, count from tweets' )
    top_10_df = top_10_tweets.toPandas()
    display.clear_output(wait=True)
    plt.figure( figsize = ( 10, 8 ) )
    sns.barplot( x="count", y="tag", data=top_10_df)
    plt.show()
    count = count + 1

<pyspark.streaming.dstream.DStream object at 0x7fc74c57c550>

Py4JJavaError                             Traceback (most recent call last)
~/spark-2.1.1-bin-hadoop2.7/python/pyspark/sql/utils.py in deco(*a, **kw)
     62         try:
---> 63             return f(*a, **kw)
     64         except py4j.protocol.Py4JJavaError as e:
spark-2.1.1-bin-hadoop2.7/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
    318                     "An error occurred while calling {0}{1}{2}.\n".
--> 319                     format(target_id, ".", name), value)
    320             else:

Py4JJavaError: An error occurred while calling o60.sql.
: org.apache.spark.sql.AnalysisException: Table or view not found: tweets; line 1 pos 23
    at org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
    at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.org$apache$spark$sql$catalyst$analysis$Analyzer$ResolveRelations$$lookupTableFromCatalog(Analyzer.scala:460)
    at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$$anonfun$apply$8.applyOrElse(Analyzer.scala:479)
    at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$$anonfun$apply$8.applyOrElse(Analyzer.scala:464)
    at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
    at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
    at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
    at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:60)
    at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$1.apply(LogicalPlan.scala:58)
    at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$1.apply(LogicalPlan.scala:58)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:307)
    at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188)
    at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:305)
    at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:58)
    at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.apply(Analyzer.scala:464)
    at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.apply(Analyzer.scala:454)
    at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:85)
    at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:82)
    at scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
    at scala.collection.immutable.List.foldLeft(List.scala:84)
    at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:82)
    at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:74)
    at scala.collection.immutable.List.foreach(List.scala:381)
    at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:74)
    at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:69)
    at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:67)
    at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:50)
    at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:63)
    at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:592)
    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: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)


During handling of the above exception, another exception occurred:

AnalysisException                         Traceback (most recent call last)
<ipython-input-14-126bd83d3cd6> in <module>()
      3     time.sleep( 3 )
      4     print(lines)
----> 5     top_10_tweets = spark.sql( 'Select tag, count from tweets' )
      6     top_10_df = top_10_tweets.toPandas()
      7     display.clear_output(wait=True)

~/spark-2.1.1-bin-hadoop2.7/python/pyspark/sql/session.py in sql(self, sqlQuery)
    543         [Row(f1=1, f2=u'row1'), Row(f1=2, f2=u'row2'), Row(f1=3, f2=u'row3')]
    544         """
--> 545         return DataFrame(self._jsparkSession.sql(sqlQuery), self._wrapped)
    546 
    547     @since(2.0)

spark-2.1.1-bin-hadoop2.7/python/lib/py4j-0.10.4-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:

~/spark-2.1.1-bin-hadoop2.7/python/pyspark/sql/utils.py in deco(*a, **kw)
     67                                              e.java_exception.getStackTrace()))
     68             if s.startswith('org.apache.spark.sql.AnalysisException: '):
---> 69                 raise AnalysisException(s.split(': ', 1)[1], stackTrace)
     70             if s.startswith('org.apache.spark.sql.catalyst.analysis'):