14

我在我的Mac上使用docker image sequenceiq/spark来研究这些spark示例，在学习过程中，我根据this answer将该图像中的spark升级到1.6.1 ，并且在我启动示例时出现错误Simple Data Operations，这是什么发生了：

当我运行df = sqlContext.read.format("jdbc").option("url",url).option("dbtable","people").load()它时会引发错误，pyspark 控制台的完整堆栈如下：

Python 2.6.6 (r266:84292, Jul 23 2015, 15:22:56)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-11)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
16/04/12 22:45:28 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /__ / .__/\_,_/_/ /_/\_\   version 1.6.1
      /_/

Using Python version 2.6.6 (r266:84292, Jul 23 2015 15:22:56)
SparkContext available as sc, HiveContext available as sqlContext.
>>> url = "jdbc:mysql://localhost:3306/test?user=root;password=myPassWord"
>>> df = sqlContext.read.format("jdbc").option("url",url).option("dbtable","people").load()
16/04/12 22:46:05 WARN Connection: BoneCP specified but not present in CLASSPATH (or one of dependencies)
16/04/12 22:46:06 WARN Connection: BoneCP specified but not present in CLASSPATH (or one of dependencies)
16/04/12 22:46:11 WARN ObjectStore: Version information not found in metastore. hive.metastore.schema.verification is not enabled so recording the schema version 1.2.0
16/04/12 22:46:11 WARN ObjectStore: Failed to get database default, returning NoSuchObjectException
16/04/12 22:46:16 WARN Connection: BoneCP specified but not present in CLASSPATH (or one of dependencies)
16/04/12 22:46:17 WARN Connection: BoneCP specified but not present in CLASSPATH (or one of dependencies)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/spark/python/pyspark/sql/readwriter.py", line 139, in load
    return self._df(self._jreader.load())
  File "/usr/local/spark/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py", line 813, in __call__
  File "/usr/local/spark/python/pyspark/sql/utils.py", line 45, in deco
    return f(*a, **kw)
  File "/usr/local/spark/python/lib/py4j-0.9-src.zip/py4j/protocol.py", line 308, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o23.load.
: java.sql.SQLException: No suitable driver
    at java.sql.DriverManager.getDriver(DriverManager.java:278)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$2.apply(JdbcUtils.scala:50)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$2.apply(JdbcUtils.scala:50)
    at scala.Option.getOrElse(Option.scala:120)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.createConnectionFactory(JdbcUtils.scala:49)
    at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$.resolveTable(JDBCRDD.scala:120)
    at org.apache.spark.sql.execution.datasources.jdbc.JDBCRelation.<init>(JDBCRelation.scala:91)
    at org.apache.spark.sql.execution.datasources.jdbc.DefaultSource.createRelation(DefaultSource.scala:57)
    at org.apache.spark.sql.execution.datasources.ResolvedDataSource$.apply(ResolvedDataSource.scala:158)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:119)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:606)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
    at py4j.Gateway.invoke(Gateway.java:259)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:209)
    at java.lang.Thread.run(Thread.java:744)

>>>

这是我到目前为止所尝试的：

  1. 下载mysql-connector-java-5.0.8-bin.jar，并放入/usr/local/spark/lib/。它仍然是同样的错误。

  2. 像这样创建t.py：

    from pyspark import SparkContext  
from pyspark.sql import SQLContext  

sc = SparkContext(appName="PythonSQL")  
sqlContext = SQLContext(sc)  
df = sqlContext.read.format("jdbc").option("url",url).option("dbtable","people").load()  

df.printSchema()  
countsByAge = df.groupBy("age").count()  
countsByAge.show()  
countsByAge.write.format("json").save("file:///usr/local/mysql/mysql-connector-java-5.0.8/db.json")

然后，我尝试了spark-submit --conf spark.executor.extraClassPath=mysql-connector-java-5.0.8-bin.jar --driver-class-path mysql-connector-java-5.0.8-bin.jar --jars mysql-connector-java-5.0.8-bin.jar --master local[4] t.py. 结果还是一样。

  1. 然后我试pyspark --conf spark.executor.extraClassPath=mysql-connector-java-5.0.8-bin.jar --driver-class-path mysql-connector-java-5.0.8-bin.jar --jars mysql-connector-java-5.0.8-bin.jar --master local[4] t.py了下，不管有没有t.py，还是一样。

在所有这些过程中，mysql 正在运行。这是我的操作系统信息：

# rpm --query centos-release  
centos-release-6-5.el6.centos.11.2.x86_64

而hadoop版本是2.6。

现在我不知道下一步该去哪里，所以我希望有人可以帮助提供一些建议，谢谢！

4

2 回答 2

14

当我试图让我的脚本写入 MySQL 时，我遇到了“java.sql.SQLException：没有合适的驱动程序”。

这是我为解决这个问题所做的。

在脚本.py

df.write.jdbc(url="jdbc:mysql://localhost:3333/my_database"
                  "?user=my_user&password=my_password",
              table="my_table",
              mode="append",
              properties={"driver": 'com.mysql.jdbc.Driver'})

然后我以这种方式运行 spark-submit

SPARK_HOME=/usr/local/Cellar/apache-spark/1.6.1/libexec spark-submit --packages mysql:mysql-connector-java:5.1.39 ./script.py

请注意，SPARK_HOME 特定于 spark 的安装位置。对于您的环境，这https://github.com/sequenceiq/docker-spark/blob/master/README.md可能会有所帮助。

如果上述所有内容令人困惑，请尝试以下操作：
在 t.py 中替换

sqlContext.read.format("jdbc").option("url",url).option("dbtable","people").load()

和 

sqlContext.read.format("jdbc").option("dbtable","people").option("driver", 'com.mysql.jdbc.Driver').load()

并运行它

spark-submit --packages mysql:mysql-connector-java:5.1.39 --master local[4] t.py
于 2016-05-24T19:13:29.290 回答
2

我使用以下命令解决了它

import findspark
findspark.add_packages('mysql:mysql-connector-java:8.0.11')
于 2020-09-07T16:49:00.883 回答