在另一个类似的问题中，他们暗示“安装旧的spark2.4.5”
编辑：上面链接的解决方案是“安装spark 2.4.5，它确实有kafkautils。但问题是我无法下载spark2.4.5-即使在存档中也不可用。
我按照建议安装了旧版本的spark-spark2.4.6（唯一可用的旧版本），还有python37、kafka python和pyspark libs。
我的spark\u job.py文件需要使用kafka

from pyspark.streaming.kafka import KafkaUtils

当点击“python spark\u job.py”

ModuleNotFoundError: No module named 'pyspark.streaming.kafka'

错误仍然存在！
spark\ u作业.py：

from __future__ import print_function
import sys
import os
import shutil
from pyspark import SparkContext, SparkConf
from pyspark.streaming import StreamingContext
from pyspark.sql import Row, SparkSession
from pyspark.streaming.kafka import KafkaUtils # this is the problem
import json
outputPath = 'C:/Users/Admin/Desktop/kafka_project/checkpoint_01'
def getSparkSessionInstance(sparkConf):
    if ('sparkSessionSingletonInstance' not in globals()):
        globals()['sparkSessionSingletonInstance'] = SparkSession\
            .builder\
            .config(conf=sparkConf)\
            .getOrCreate()
    return globals()['sparkSessionSingletonInstance']
# -------------------------------------------------
# What I want to do per each RDD...
# -------------------------------------------------
def process(time, rdd):
    print("===========-----> %s <-----===========" % str(time))
    try:
        spark = getSparkSessionInstance(rdd.context.getConf())
        rowRdd = rdd.map(lambda w: Row(branch=w['branch'],
                                       currency=w['currency'],
                                       amount=w['amount']))
        testDataFrame = spark.createDataFrame(rowRdd)
        testDataFrame.createOrReplaceTempView("treasury_stream")
        sql_query = get_sql_query()
        testResultDataFrame = spark.sql(sql_query)
        testResultDataFrame.show(n=5)
        # Insert into DB
        try:
            testResultDataFrame.write \
                .format("jdbc") \
                .mode("append") \
                .option("driver", 'org.postgresql.Driver') \
                .option("url", "jdbc:postgresql://myhabrtest.cuyficqfa1h0.ap-south-1.rds.amazonaws.com:5432/habrDB") \
                .option("dbtable", "transaction_flow") \
                .option("user", "habr") \
                .option("password", "habr12345") \
                .save()
        except Exception as e:
            print("--> Opps! It seems an Errrorrr with DB working!", e)
    except Exception as e:
        print("--> Opps! Is seems an Error!!!", e)
# -------------------------------------------------
# General function
# -------------------------------------------------
def createContext():
    sc = SparkContext(appName="PythonStreamingKafkaTransaction")
    sc.setLogLevel("ERROR")
    ssc = StreamingContext(sc, 2)
    broker_list, topic = sys.argv[1:]
    try:
        directKafkaStream = KafkaUtils.createDirectStream(ssc,
                                        [topic],
                                        {"metadata.broker.list": broker_list})
    except:
        raise ConnectionError("Kafka error: Connection refused: \
                            broker_list={} topic={}".format(broker_list, topic))
    parsed_lines = directKafkaStream.map(lambda v: json.loads(v[1]))
    # RDD handling
    parsed_lines.foreachRDD(process)
    return ssc
if __name__ == "__main__":
    if len(sys.argv) != 3:
        print("Usage: spark_job.py <zk> <topic>", file=sys.stderr)
        exit(-1)
    print("--> Creating new context")
    if os.path.exists(outputPath):
        shutil.rmtree('outputPath')
    ssc = StreamingContext.getOrCreate(outputPath, lambda: createContext())
    ssc.start()
    ssc.awaitTermination()