pyspark.sql.utils.AnalysisException: 找不到数据源：kafka

Question

我正在尝试使用 pyspark 从 kafka 读取流。我正在使用 spark 版本 3.0.0-preview2 和 spark-streaming-kafka-0-10_2.12 在此之前我只是统计 zookeeper，kafka 并创建一个新主题：

/usr/local/kafka/bin/zookeeper-server-start.sh /usr/local/kafka/config/zookeeper.properties 
/usr/local/kafka/bin/kafka-server-start.sh /usr/local/kafka/config/server.properties
/usr/local/kafka/bin/kafka-topics.sh --create --bootstrap-server localhost:9092 --replication-factor 1 --partitions 1 --topic data_wm

这是我的代码：

import pandas as pd
import os
import findspark
findspark.init("/usr/local/spark")
from pyspark.sql import SparkSession

spark = SparkSession.builder.appName("TestApp").getOrCreate()
df = spark \
  .readStream \
  .format("kafka") \
  .option("kafka.bootstrap.servers", "localhost:9092") \
  .option("subscribe", "data_wm") \
  .load() 
value = df.selectExpr("CAST(key AS STRING)", "CAST(value AS STRING)")

这是我运行我的脚本的方式：

sudo --preserve-env=pyspark /usr/local/spark/bin/pyspark --packages org.apache.spark:spark-streaming-kafka-0-10_2.12:3.0.0-preview

作为这个命令的结果，我得到了这个：

: resolving dependencies :: org.apache.spark#spark-submit-parent-0d7b2a8d-a860-4766-a4c7-141a902d8365;1.0
        confs: [default]
        found org.apache.spark#spark-streaming-kafka-0-10_2.12;3.0.0-preview in central
        found org.apache.spark#spark-token-provider-kafka-0-10_2.12;3.0.0-preview in central
        found org.apache.kafka#kafka-clients;2.3.1 in central
        found com.github.luben#zstd-jni;1.4.3-1 in central
        found org.lz4#lz4-java;1.6.0 in central
        found org.xerial.snappy#snappy-java;1.1.7.3 in central
        found org.slf4j#slf4j-api;1.7.16 in central
        found org.spark-project.spark#unused;1.0.0 in central :: resolution report :: resolve 380ms :: artifacts dl 7ms
        :: modules in use:
        com.github.luben#zstd-jni;1.4.3-1 from central in [default]
        org.apache.kafka#kafka-clients;2.3.1 from central in [default]
        org.apache.spark#spark-streaming-kafka-0-10_2.12;3.0.0-preview from central in [default]
        org.apache.spark#spark-token-provider-kafka-0-10_2.12;3.0.0-preview from central in [default]
        org.lz4#lz4-java;1.6.0 from central in [default]
        org.slf4j#slf4j-api;1.7.16 from central in [default]
        org.spark-project.spark#unused;1.0.0 from central in [default]
        org.xerial.snappy#snappy-java;1.1.7.3 from central in [default]

但是我总是出现这个错误：

d> f = spark \ ... .readStream \ ... .format("kafka") \ ...

.option("kafka.bootstrap.servers", "localhost:9092") \ ...
.option("subscribe", "data_wm") \ ... .load() Traceback (most recent call last): File "", line 5, in File "/usr/local/spark/python/pyspark/sql/streaming.py", line 406, in load return self._df(self._jreader.load()) File "/usr/local/spark/python/lib/py4j-0.10.8.1-src.zip/py4j/java_gateway.py", line 1286, in call File "/usr/local/spark/python/pyspark/sql/utils.py", line 102, in deco raise converted pyspark.sql.utils.AnalysisException: Failed to find data source: kafka. Please deploy the application as per the deployment section of "Structured Streaming + Kafka Integration Guide".;

我不知道这个错误的原因，请帮助

Answer 1

我已经成功解决了 Spark 3.0.1 上的这个错误（使用 PySpark）。

我会保持简单，并通过 --packages 参数提供所需的包：

spark-submit --packages org.apache.spark:spark-sql-kafka-0-10_2.12:3.0.1 MyPythonScript.py

注意参数的顺序，否则会抛出错误。

其中 MyPythonScript.py 有：

KAFKA_TOPIC = "data_wm"
KAFKA_SERVER = "localhost:9092"

# creating an instance of SparkSession
spark_session = SparkSession \
    .builder \
    .appName("Python Spark create RDD") \
    .getOrCreate()

# Subscribe to 1 topic
df = spark_session \
    .readStream \
    .format("kafka") \
    .option("kafka.bootstrap.servers", KAFKA_SERVER) \
    .option("subscribe", KAFKA_TOPIC) \
    .load()
print(df.selectExpr("CAST(key AS STRING)", "CAST(value AS STRING)"))

Answer 2

如果您检查错误中提到的文档，则表明要下载不同的包 - spark-sql-kafka，不是 spark-streaming-kafka

您还可以通过 findspark 添加包，而不是在 CLI 中添加包

pyspark.sql.utils.AnalysisException: 找不到数据源：kafka

pyspark.sql.utils.AnalysisException: Failed to find data source: kafka

apache-spark

pyspark

apache-kafka

pyspark-sql

spark-structured-streaming