我正在PySpark中编写一个Spark结构的流应用程序,以从Confluent Cloud中的Kafka读取数据。 spark readstream()
函数的文档太浅,在可选参数部分(特别是在auth机制部分)没有指定太多。我不确定哪个参数出错并导致连接崩溃。任何有Spark经验的人都可以帮助我开始此连接吗?
必需参数
> Consumer({'bootstrap.servers': > 'cluster.gcp.confluent.cloud:9092', > 'sasl.username':'xxx', > 'sasl.password': 'xxx', > 'sasl.mechanisms': 'PLAIN', > 'security.protocol': 'SASL_SSL', > 'group.id': 'python_example_group_1', > 'auto.offset.reset': 'earliest' })
这是我的pyspark代码:
df = spark \
.readStream \
.format("kafka") \
.option("kafka.bootstrap.servers", "cluster.gcp.confluent.cloud:9092") \
.option("subscribe", "test-topic") \
.option("kafka.sasl.mechanisms", "PLAIN")\
.option("kafka.security.protocol", "SASL_SSL")\
.option("kafka.sasl.username","xxx")\
.option("kafka.sasl.password", "xxx")\
.option("startingOffsets", "latest")\
.option("kafka.group.id", "python_example_group_1")\
.load()
display(df)
但是,我不断收到错误消息:
kafkashaded.org.apache.kafka.common.KafkaException:无法执行 建立卡夫卡消费者
DataBrick笔记本-用于测试
文档
答案 0 :(得分:1)
此错误表明您的Kafka使用者看不到JAAS配置。要解决此问题,请按照以下步骤包括JASS:
Step01:为下面的JAAS文件创建文件:/ home / jass / path
KafkaClient {
com.sun.security.auth.module.Krb5LoginModule required
useTicketCache=true
renewTicket=true
serviceName="kafka";
};
Step02:根据以下conf参数在spark-submit中调用该JASS文件路径。
--conf "spark.executor.extraJavaOptions=-Djava.security.auth.login.config=/home/jass/path"
完整的火花提交命令:
/usr/hdp/2.6.1.0-129/spark2/bin/spark-submit --packages com.databricks:spark-avro_2.11:3.2.0,org.apache.spark:spark-avro_2.11:2.4.0,org.apache.spark:spark-sql-kafka-0-10_2.11:2.2.0 --conf spark.ui.port=4055 --files /home/jass/path,/home/bdpda/bdpda.headless.keytab --conf "spark.executor.extraJavaOptions=-Djava.security.auth.login.config=/home/jass/path" --conf "spark.driver.extraJavaOptions=-Djava.security.auth.login.config=/home/jass/path" pysparkstructurestreaming.py
Pyspark结构化流式示例代码:
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()
答案 1 :(得分:0)
我们需要指定kafka.sasl.jaas.config
来添加Confluent Kafka SASL-SSL auth方法的用户名和密码。它的参数看起来有些奇怪,但是可以正常工作。
df = spark \
.readStream \
.format("kafka") \
.option("kafka.bootstrap.servers", "pkc-43n10.us-central1.gcp.confluent.cloud:9092") \
.option("subscribe", "wallet_txn_log") \
.option("startingOffsets", "earliest") \
.option("kafka.security.protocol","SASL_SSL") \
.option("kafka.sasl.mechanism", "PLAIN") \
.option("kafka.sasl.jaas.config", """kafkashaded.org.apache.kafka.common.security.plain.PlainLoginModule required username="xxx" password="xxx";""").load()
display(df)