问题描述
限时送ChatGPT账号..我正在尝试将一堆 CSV 文件逐行加载到使用 pyspark 配置在 OpenShift 上运行的 mysql 实例中.我有一个可以启动并运行的 Jupyter 笔记本.
I am trying to load a bunch of CSV files row by row into mysql instance which is running on OpenShift using pyspark configuration. I have a Jupyter notebook with spark up and running.
下面是我的代码.它因特定的驱动程序错误而失败
Below is the code I have. And it fails with specific driver error
Py4JJavaError: An error occurred while calling o89.save.
from pyspark.sql import SparkSession
from pyspark.sql import SQLContext
if __name__ == '__main__':
scSpark = SparkSession \
.builder \
.appName("reading csv") \
.getOrCreate()
if __name__ == '__main__':
scSpark = SparkSession \
.builder \
.appName("reading csv") \
.getOrCreate()
data_file = '/opt/app-root/src/data/train.psv'
sdfData = scSpark.read.csv(data_file, header=True, sep="|").cache()
print('Total Records = {}'.format(sdfData.count()))
sdfData.show()
sdfData.registerTempTable("train")
output = scSpark.sql('SELECT count(*) from train')
output.show()
+--------+
|count(1)|
+--------+
| 1168686|
+--------+
import os
os.environ['PYSPARK_SUBMIT_ARGS'] = '--packages mysql:mysql-connector-java:jar:8.0.21 pyspark-shell'
output = scSpark.sql('SELECT * from train')
output.show()
output.write.format('jdbc').options(
url='jdbc:mysql://mysql-1-28d85/sepsis',
driver='com.mysql.jdbc.Driver',
#driver='mysql-connector-java.Driver',
#driver='org.mysql.jdbc.Driver',
dbtable='train',
user='sepsis',
password='Success_2020').mode('append').save()
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<ipython-input-57-114af97e0442> in <module>
11 dbtable='train',
12 user='sepsis',
---> 13 password='Success_2020').mode('append').save()
/opt/app-root/lib/python3.6/site-packages/pyspark/sql/readwriter.py in save(self, path, format, mode, partitionBy, **options)
735 self.format(format)
736 if path is None:
--> 737 self._jwrite.save()
738 else:
739 self._jwrite.save(path)
/opt/app-root/lib/python3.6/site-packages/py4j/java_gateway.py in __call__(self, *args)
1255 answer = self.gateway_client.send_command(command)
1256 return_value = get_return_value(
-> 1257 answer, self.gateway_client, self.target_id, self.name)
1258
1259 for temp_arg in temp_args:
/opt/app-root/lib/python3.6/site-packages/pyspark/sql/utils.py in deco(*a, **kw)
61 def deco(*a, **kw):
62 try:
---> 63 return f(*a, **kw)
64 except py4j.protocol.Py4JJavaError as e:
65 s = e.java_exception.toString()
/opt/app-root/lib/python3.6/site-packages/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
326 raise Py4JJavaError(
327 "An error occurred while calling {0}{1}{2}.\n".
--> 328 format(target_id, ".", name), value)
329 else:
330 raise Py4JError(
Py4JJavaError: An error occurred while calling o1641.save.
: java.lang.ClassNotFoundException: com.mysql.jdbc.Driver
at java.URLClassLoader.findClass(URLClassLoader.java:382)
at java.lang.ClassLoader.loadClass(ClassLoader.java:419)
at java.lang.ClassLoader.loadClass(ClassLoader.java:352)
at org.apache.spark.sql.execution.datasources.jdbc.DriverRegistry$.register(DriverRegistry.scala:45)
at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions$$anonfun$5.apply(JDBCOptions.scala:99)
at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions$$anonfun$5.apply(JDBCOptions.scala:99)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.<init>(JDBCOptions.scala:99)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcOptionsInWrite.<init>(JDBCOptions.scala:190)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcOptionsInWrite.<init>(JDBCOptions.scala:194)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:45)
at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:45)
at org.apache.spark.sql.executionmand.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
at org.apache.spark.sql.executionmand.ExecutedCommandExec.sideEffectResult(commands.scala:68)
at org.apache.spark.sql.executionmand.ExecutedCommandExec.doExecute(commands.scala:86)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:83)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:81)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:676)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:676)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:80)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:127)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:75)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:676)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:285)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:271)
at sun.reflect.GeneratedMethodAccessor67.invoke(Unknown Source)
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:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4jmands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4jmands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
使用包更改代码.
这也是 openshift ,其中所有组件都作为 pod 运行,无法访问外部环境.
Also this is openshift , where all components are running as pods with no access to outside environment.
推荐答案
java.lang.ClassNotFoundException: com.mysql.cj.jdbc.Driver
java.lang.ClassNotFoundException: com.mysql.cj.jdbc.Driver
这就说明了一切.您必须使用 --driver-class-path
或类似(特定于 Jupyter)的 MySQL 驱动程序启动 pyspark
(或环境).
That says it all. You have to start pyspark
(or the environment) with the JDBC driver for MySQL using --driver-class-path
or similar (that will be specific to Jupyter).
从复制Jupyter Notebook 中的 PySpark — 使用 Dataframe &JDBC 数据源:
如果你使用 Jupyter Notebook,你应该设置 PYSPARK_SUBMIT_ARGS
环境变量,如下:
If you use Jupyter Notebook, you should set the
PYSPARK_SUBMIT_ARGS
environment variable, as following:
import os
os.environ['PYSPARK_SUBMIT_ARGS'] = '--packages org.postgresql:postgresql:42.1.1 pyspark-shell'
更改 --packages
以引用 MySQL JDBC 驱动程序.
Change the --packages
to reference the MySQL JDBC driver.
这篇关于如何在 pyspark 的 Jupyter notebook 中为 MySQL 设置 JDBC 驱动程序?的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!
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