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

我正在尝试使用 pyspark 从 kafka 读取流。我在用Spark 版本 3.0.0-preview2 and 火花流-kafka-0-10_2.12在此之前，我只是统计了zookeeper、kafka并创建了一个新主题：

/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)") 

这就是我运行脚本的方式：

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，我有这个：

: 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() 回溯（大多数 最近的调用最后）：文件“”，第 5 行，在文件中 “/usr/local/spark/python/pyspark/sql/streaming.py”，第 406 行，加载中 返回 self._df(self._jreader.load()) 文件“/usr/local/spark/python/lib/py4j-0.10.8.1-src.zip/py4j/java_gateway.py”， 第 1286 行，在call文件 “/usr/local/spark/python/pyspark/sql/utils.py”，第 102 行，装饰风格引发转换后的 pyspark.sql.utils.AnalysisException：无法找到数据源：kafka。请按照以下方式部署应用程序 《结构化流+Kafka集成》的部署部分指导”。;

我不知道这个错误的原因，请帮忙

我已在 Spark 3.0.1 上成功解决了此错误（使用 PySpark）。

我会保持简单并通过提供所需的包--packages争论：

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，否则会引发错误。

Where MyPythonScript.py has:

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)"))