Apache spark 无法使用pyspark从kafka读取数据

Apache spark 无法使用pyspark从kafka读取数据,apache-spark,pyspark,apache-kafka,spark-structured-streaming,Apache Spark,Pyspark,Apache Kafka,Spark Structured Streaming,我的卡夫卡主题中有一个流式数据。我需要以pyspark数据框的形式使用pyspark从主题中读取这些数据。但在调用readStream函数时,我不断收到错误。错误为“py4j.protocol.Py4JJavaError:调用o35.load时出错”。我的代码如下:- os.environ['PYSPARK_SUBMIT_ARGS'] = '--packages org.apache.spark:spark-streaming-kafka-0-8_2.11:2.0.2 pyspark-shell

我的卡夫卡主题中有一个流式数据。我需要以pyspark数据框的形式使用pyspark从主题中读取这些数据。但在调用readStream函数时,我不断收到错误。错误为“py4j.protocol.Py4JJavaError:调用o35.load时出错”。我的代码如下:-

os.environ['PYSPARK_SUBMIT_ARGS'] = '--packages org.apache.spark:spark-streaming-kafka-0-8_2.11:2.0.2 pyspark-shell'

if __name__ == '__main__':
    sc = SparkSession.builder.appName('PythonStreamingDirectKafkaWordCount').getOrCreate()

    ssc = StreamingContext(sc, 60)

    df = sc \
        .readStream \
        .format("kafka") \
        .option("kafka.bootstrap.servers", "localhost:9092") \
        .option("subscribe", "near_line") \
        .load() \
        .selectExpr("CAST(key AS STRING)", "CAST(value AS STRING)","CAST(value AS STRING)")

    ssc.start()
    ssc.awaitTermination()  
我得到一个错误如下:-

Traceback (most recent call last):
  File "/home/nayanam/PycharmProjects/recommendation_engine/derivation/kafka_cons**umer_test.py", line 21, in <module>
    .option("subscribe", "near_line") \**
  File "/home/nayanam/anaconda3/lib/python3.5/site-packages/pyspark/sql/streaming.py", line 397, in load
    return self._df(self._jreader.load())
  File "/home/nayanam/anaconda3/lib/python3.5/site-packages/py4j/java_gateway.py", line 1133, in __call__
    answer, self.gateway_client, self.target_id, self.name)
  File "/home/nayanam/anaconda3/lib/python3.5/site-packages/pyspark/sql/utils.py", line 63, in deco
    return f(*a, **kw)
  File "/home/nayanam/anaconda3/lib/python3.5/site-packages/py4j/protocol.py", line 319, in get_return_value
    format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling o35.load.
: java.lang.ClassNotFoundException: Failed to find data source: kafka. Please find packages at http://spark.apache.org/third-party-projects.html
    at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:549)
    at org.apache.spark.sql.execution.datasources.DataSource.providingClass$lzycompute(DataSource.scala:86)
    at org.apache.spark.sql.execution.datasources.DataSource.providingClass(DataSource.scala:86)
    at org.apache.spark.sql.execution.datasources.DataSource.sourceSchema(DataSource.scala:195)
    at org.apache.spark.sql.execution.datasources.DataSource.sourceInfo$lzycompute(DataSource.scala:87)
    at org.apache.spark.sql.execution.datasources.DataSource.sourceInfo(DataSource.scala:87)
    at org.apache.spark.sql.execution.streaming.StreamingRelation$.apply(StreamingRelation.scala:30)
    at org.apache.spark.sql.streaming.DataStreamReader.load(DataStreamReader.scala:150)
    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)
Caused by: java.lang.ClassNotFoundException: kafka.DefaultSource
    at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
    at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$21$$anonfun$apply$12.apply(DataSource.scala:533)
    at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$21$$anonfun$apply$12.apply(DataSource.scala:533)
    at scala.util.Try$.apply(Try.scala:192)
    at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$21.apply(DataSource.scala:533)
    at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$21.apply(DataSource.scala:533)
    at scala.util.Try.orElse(Try.scala:84)
    at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:533)
    ... 18 more 
回溯(最近一次呼叫最后一次):
文件“/home/nayanam/PycharmProjects/recommendation_engine/derivation/kafka_cons**umer_test.py”,第21行
.期权(“认购”、“近线”)\**
文件“/home/nayanam/anaconda3/lib/python3.5/site packages/pyspark/sql/streaming.py”,第397行,已加载
返回self.\u df(self.\u jreader.load())
文件“/home/nayanam/anaconda3/lib/python3.5/site packages/py4j/java_gateway.py”,第1133行,in_u调用__
回答,self.gateway\u客户端,self.target\u id,self.name)
文件“/home/nayanam/anaconda3/lib/python3.5/site-packages/pyspark/sql/utils.py”,第63行,装饰
返回f(*a,**kw)
文件“/home/nayanam/anaconda3/lib/python3.5/site packages/py4j/protocol.py”,第319行,在get\u return\u值中
格式(目标id,“.”,名称),值)
py4j.protocol.Py4JJavaError:调用o35.load时出错。
:java.lang.ClassNotFoundException:未能找到数据源:kafka。请在以下网址查找包裹:http://spark.apache.org/third-party-projects.html
位于org.apache.spark.sql.execution.datasources.DataSource$.lookUpdateSource(DataSource.scala:549)
位于org.apache.spark.sql.execution.datasources.DataSource.providingClass$lzycompute(DataSource.scala:86)
位于org.apache.spark.sql.execution.datasources.DataSource.providingClass(DataSource.scala:86)
位于org.apache.spark.sql.execution.datasources.DataSource.sourceSchema(DataSource.scala:195)
位于org.apache.spark.sql.execution.datasources.DataSource.sourceInfo$lzycompute(DataSource.scala:87)
位于org.apache.spark.sql.execution.datasources.DataSource.sourceInfo(DataSource.scala:87)
位于org.apache.spark.sql.execution.streaming.StreamingRelation$.apply(StreamingRelation.scala:30)
位于org.apache.spark.sql.streaming.DataStreamReader.load(DataStreamReader.scala:150)
在sun.reflect.NativeMethodAccessorImpl.invoke0(本机方法)处
位于sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
在sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)中
位于java.lang.reflect.Method.invoke(Method.java:498)
位于py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
位于py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
在py4j.Gateway.invoke处(Gateway.java:280)
位于py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
在py4j.commands.CallCommand.execute(CallCommand.java:79)
在py4j.GatewayConnection.run处(GatewayConnection.java:214)
运行(Thread.java:748)
原因:java.lang.ClassNotFoundException:kafka.DefaultSource
位于java.net.URLClassLoader.findClass(URLClassLoader.java:381)
位于java.lang.ClassLoader.loadClass(ClassLoader.java:424)
位于java.lang.ClassLoader.loadClass(ClassLoader.java:357)
位于org.apache.spark.sql.execution.datasources.DataSource$$anonfun$21$$anonfun$apply$12.apply(DataSource.scala:533)
位于org.apache.spark.sql.execution.datasources.DataSource$$anonfun$21$$anonfun$apply$12.apply(DataSource.scala:533)
在scala.util.Try$.apply(Try.scala:192)
位于org.apache.spark.sql.execution.datasources.DataSource$$anonfun$21.apply(DataSource.scala:533)
位于org.apache.spark.sql.execution.datasources.DataSource$$anonfun$21.apply(DataSource.scala:533)
在scala.util.Try.orElse(Try.scala:84)
位于org.apache.spark.sql.execution.datasources.DataSource$.lookUpdateSource(DataSource.scala:533)
... 还有18个

我也遇到了同样的问题。在spark 2.3中,pyspark接受了--jars选项,并且工作正常。因此,在这个版本中,您只需要2个罐子:

spark-sql-kafka-0-10_2.11-2.3.2.jar
spark-streaming-kafka-0-10-assembly_2.11-2.3.2.jar

$ pyspark  --jars spark-sql-kafka-0-10_2.11-2.3.2.jar,spark-streaming-kafka-0-10-assembly_2.11-2.3.2.jar

我使用的是Spark 2.3.0、Scala 2.11.8和Kafka 0.10,它们可以从apache.org下载

如果您不想使用jar,请传递这个包


--packages org.apache.spark:spark-sql-kafka-0-10_2.11:2.3.2,org.apache.spark:spark-streaming-kafka-0-10-assembly_2.11:2.3.2

org.apache.spark:spark-streaming-kafka-0-8_2.11:2.0.2
出现在您的类路径中?是,我已包含。Spark群集是否也具有从该文件夹读取的相关权限?Spark Streaming的Kafka库及其依赖项包含在Spark submit中。您可以添加运行的
Spark submit
吗?您是否尝试过添加
--包
作为您的
spark提交的参数
?为什么不使用
--包
?问题的解决方案只需要
spark-sql-kafka-0-10