即使使用较旧的 spark 版本，也没有名为“pyspark.streaming.kafka"的模块 [英] No module named 'pyspark.streaming.kafka' even with older spark version

问题描述

在另一个类似的问题，他们提示安装较旧的 spark 2.4.5."

In another similar question, they hint 'install older spark 2.4.5.'

上面链接中的解决方案说安装 spark 2.4.5 并且它确实有 kafkautils.但问题是我无法下载 spark2.4.5 - 即使在存档中也不可用.

the solution from above link says 'install spark 2.4.5 and it does have kafkautils. But the problem is I can't download spark2.4.5 - not available even in the archive.

我遵循了建议，安装了旧版本的 spark - spark2.4.6(唯一可用的旧版本)并且还有 python37、kafka-python、pyspark 库.

i followed the advice, installed older version of spark - spark2.4.6(the only old available) and also have python37, kafka-python,pyspark libs.

我有需要使用 kafka 的 spark_job.py 文件

i have my spark_job.py file that needs to use kafka

from pyspark.streaming.kafka import KafkaUtils

点击python spark_job.py"时

when hitting 'python spark_job.py

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

错误仍然存​​在！

spark_job.py:

spark_job.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()

推荐答案

我刚刚使用 pip 将其降级:

i just downgraded it using pip:

pip install --force-reinstall pyspark==2.4.6

我没有使用任何诗歌.重新安装后，kafkaUtils pkg 被识别.

I did not use any poetry. AFter reinstalling, the kafkaUtils pkg was recognized.

这篇关于即使使用较旧的 spark 版本，也没有名为“pyspark.streaming.kafka"的模块的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！