File “D:\ProgramData\anaconda3\envs\python10\lib\site-packages\pyspark\sql\readwriter.py”, line 314, in load
return self._df(self._jreader.load())
File “D:\ProgramData\anaconda3\envs\python10\lib\site-packages\py4j\java_gateway.py”, line 1322, in call
return_value = get_return_value(
File “D:\ProgramData\anaconda3\envs\python10\lib\site-packages\pyspark\errors\exceptions\captured.py”, line 179, in deco
return f(*a, **kw)
File “D:\ProgramData\anaconda3\envs\python10\lib\site-packages\py4j\protocol.py”, line 326, in get_return_value
raise Py4JJavaError(
py4j.protocol.Py4JJavaError: An error occurred while calling o30.load.
: java.sql.SQLException: No suitable driver
at java.sql.DriverManager.getDriver(DriverManager.java:315)
at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.
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2(JDBCOptions.scala:109) at scala.Option.getOrElse(Option.scala:189) at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.<init>(JDBCOptions.scala:109) at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.<init>(JDBCOptions.scala:41) at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:34) at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:346) at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:229) at org.apache.spark.sql.DataFrameReader.
2(JDBCOptions.scala:109)atscala.Option.getOrElse(Option.scala:189)atorg.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.<init>(JDBCOptions.scala:109)atorg.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.<init>(JDBCOptions.scala:41)atorg.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:34)atorg.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:346)atorg.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:229)atorg.apache.spark.sql.DataFrameReader.anonfun$load$2(DataFrameReader.scala:211)
at scala.Option.getOrElse(Option.scala:189)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:211)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:172)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:374)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
at java.lang.Thread.run(Thread.java:750)
解决方案
你遇到的问题涉及到几个主要方面：
-
Hadoop环境未设置：这可能会影响Spark在某些平台上的运行，特别是在处理大数据文件或使用Hadoop生态系统组件时。虽然你的当前操作可能不直接依赖Hadoop，但是设置好
HADOOP_HOME环境变量可以帮助避免潜在的兼容性问题。 -
未找到适合的JDBC驱动：这是因为你的Spark应用试图连接MySQL，但没有正确地指定或包含JDBC驱动。Spark需要明确知道如何通过JDBC连接到MySQL。
解决方案
1. 设置HADOOP_HOME
在Windows上，你需要下载并解压Hadoop二进制文件，然后设置环境变量。你可以从Apache Hadoop的官网下载对应版本。设置HADOOP_HOME并确保它在你的系统PATH中：
set HADOOP_HOME=C:\path\to\hadoop
set PATH=%PATH%;%HADOOP_HOME%\bin;
2. 包含MySQL JDBC驱动
确保在你的Spark应用中包含了MySQL的JDBC驱动。可以通过以下方式添加：
- 如果你是通过命令行启动的Spark，可以使用
--packages参数包含MySQL的JDBC包：
./bin/spark-submit --packages mysql:mysql-connector-java:8.0.25 your_script.py
- 如果你是在一个独立的应用或Jupyter笔记本中使用Spark，需要确保
mysql-connector-java库已经添加到环境中。在PySpark的启动脚本中添加：
from pyspark.sql import SparkSession
spark = SparkSession.builder \
.appName("Your App Name") \
.config("spark.jars.packages", "mysql:mysql-connector-java:8.0.25") \
.getOrCreate()
更新你的Spark会话配置，确保包括正确的JDBC驱动。
