【问题标题】:Failed to find leader for topics; java.lang.NullPointerException NullPointerException at org.apache.kafka.common.utils.Utils.formatAddress未能找到主题的领导者; java.lang.NullPointerException NullPointerException at org.apache.kafka.common.utils.Utils.formatAddress
【发布时间】:2020-03-04 09:47:09
【问题描述】:

当我们尝试从启用 SSL 的 Kafka 主题流式传输数据时,我们面临以下错误。你能在这个问题上帮助我们吗?

19/11/07 13:26:54 INFO ConsumerFetcherManager: [ConsumerFetcherManager-1573151189884] Added fetcher for partitions ArrayBuffer()
19/11/07 13:26:54 WARN ConsumerFetcherManager$LeaderFinderThread: [spark-streaming-consumer_dvtcbddc101.corp.cox.com-1573151189725-d40a510f-leader-finder-thread], Failed to find leader for Set([inst_monitor_status_test,2], [inst_monitor_status_test,0], [inst_monitor_status_test,1])
java.lang.NullPointerException
        at org.apache.kafka.common.utils.Utils.formatAddress(Utils.java:408)
        at kafka.cluster.Broker.connectionString(Broker.scala:62)
        at kafka.client.ClientUtils$$anonfun$fetchTopicMetadata$5.apply(ClientUtils.scala:89)
        at kafka.client.ClientUtils$$anonfun$fetchTopicMetadata$5.apply(ClientUtils.scala:89)
        at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
        at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
        at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
        at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
        at scala.collection.AbstractTraversable.map(Traversable.scala:104)
        at kafka.client.ClientUtils$.fetchTopicMetadata(ClientUtils.scala:89)
        at kafka.consumer.ConsumerFetcherManager$LeaderFinderThread.doWork(ConsumerFetcherManager.scala:66)
        at kafka.utils.ShutdownableThread.run(ShutdownableThread.scala:60)

Pyspark 代码:

from __future__ import print_function

import sys

from pyspark import SparkContext
from pyspark.streaming import StreamingContext
from pyspark.streaming.kafka import KafkaUtils
from pyspark import SparkConf, SparkContext
from operator import add
import sys
from pyspark.streaming import StreamingContext
from pyspark.streaming.kafka import KafkaUtils
import json
from kafka import SimpleProducer, KafkaClient
from kafka import KafkaProducer


def handler(message):
    records = message.collect()
    for record in records:
        print(record)


if __name__ == "__main__":
    if len(sys.argv) != 3:
        print("Usage: kafka_wordcount.py <zk> <topic>", file=sys.stderr)
        exit(-1)
    sc = SparkContext(appName="PythonStreamingKafkaWordCount")
    ssc = StreamingContext(sc, 10)

    zkQuorum, topic = sys.argv[1:]
    kvs = KafkaUtils.createStream(ssc, zkQuorum, "spark-streaming-consumer", {topic: 1})
    lines = kvs.map(lambda x: x[1])
    counts = lines.flatMap(lambda line: line.split(" ")).map(lambda word: (word, 1)).reduceByKey(lambda a, b: a+b)
    counts.pprint()
    kvs.foreachRDD(handler)

    ssc.start()
    ssc.awaitTermination()

Spark 提交命令:

火花提交:

/usr/hdp/2.6.1.0-129/spark2/bin/spark-submit --packages org.apache.spark:spark-streaming-kafka-0-8_2.11:2.1.0,org.apache。 spark:spark-sql-kafka-0-10_2.11:2.1.0,org.apache.spark:spark-sql-kafka-0-10_2.11:2.3.0 dsstream2.py host:2181 inst_monitor_status_test

【问题讨论】:

  • at kafka.cluster.Broker.connectionString ... 听起来您没有获得正确的集群地址。如果你print(zkQuorum),你得到正确的地址吗?另外,你真的需要 Spark 吗?您似乎已经拥有from kafka import KafkaProducer,这是一个原生 Python 库
  • 另外,您似乎缺少 Spark 的任何 SSL 相关设置
  • 感谢您的信息。zkQuorum 的地址正确。但仍然不确定如何为 Spark 传递 SSL 相关设置。如果您对此有任何想法,请告诉我。示例代码会很棒!
  • 你看到了吗? spark.apache.org/docs/2.1.0/…
  • 基于上面的链接,似乎 Spark 的 SSL 相关设置我们只能合并 Scala 或 Java 代码。我认为我们不能通过 KafkaParms 在 pyspark 代码中合并 SSL 相关信息。您能否告诉我在 pyspark 代码中处理 SSL 功能以连接 Kerberos 集群的任何方法。

标签: apache-spark pyspark apache-kafka spark-streaming-kafka


【解决方案1】:

感谢您的意见。我已经通过以下方法传递了 SSL 参数并按预期正常工作。

from pyspark.sql import SparkSession
from pyspark.sql.functions import *
from pyspark.sql.types import *
from pyspark.streaming import StreamingContext
import time

#  Spark Streaming context :

spark = SparkSession.builder.appName('PythonStreamingDirectKafkaWordCount').getOrCreate()
sc = spark.sparkContext
ssc = StreamingContext(sc, 20)

#  Kafka Topic Details :

KAFKA_TOPIC_NAME_CONS = "topic_name"
KAFKA_OUTPUT_TOPIC_NAME_CONS = "topic_to_hdfs"
KAFKA_BOOTSTRAP_SERVERS_CONS = 'kafka_server:9093'

#  Creating  readstream DataFrame :

df = spark.readStream \
     .format("kafka") \
     .option("kafka.bootstrap.servers", KAFKA_BOOTSTRAP_SERVERS_CONS) \
     .option("subscribe", KAFKA_TOPIC_NAME_CONS) \
     .option("startingOffsets", "earliest") \
     .option("kafka.security.protocol","SASL_SSL")\
     .option("kafka.client.id" ,"Clinet_id")\
     .option("kafka.sasl.kerberos.service.name","kafka")\
     .option("kafka.ssl.truststore.location", "/home/path/kafka_trust.jks") \
     .option("kafka.ssl.truststore.password", "password_rd") \
     .option("kafka.sasl.kerberos.keytab","/home/path.keytab") \
     .option("kafka.sasl.kerberos.principal","path") \
     .load()

df1 = df.selectExpr( "CAST(value AS STRING)")

#  Creating  Writestream DataFrame :

df1.writeStream \
   .option("path","target_directory") \
   .format("csv") \
   .option("checkpointLocation","chkpint_directory") \
   .outputMode("append") \
   .start()

ssc.awaitTermination()

【讨论】:

  • 使用 KafkaUtils.createDirectStream 时有哪些 kafkaParams 选项?如果你知道,请告诉我。
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