pyspark mysql jdbc load调用o23.load时发生错误没有合适的驱动程序

Question

我在我的Mac上使用docker image sequenceiq/spark来研究这些火花例子,在研究过程中,我根据这个答案将该图像中的火花升级到1.6.1 ,并且当我开始这个Simple Data Operations例子时出现错误,这里是什么事情发生了:

当我运行df = sqlContext.read.format("jdbc").option("url",url).option("dbtable","people").load()它时引发错误,并且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)

>>>

这是我到现在为止所尝试的:

1. 下载mysql-connector-java-5.0.8-bin.jar,并将其付诸实践/usr/local/spark/lib/.它仍然是同样的错误.

2. t.py像这样创建:

   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,我试过了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.结果仍然相同.

3. 然后我尝试了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,无论是否有以下t.py,仍然是相同的.

在所有这些中,mysql正在运行.这是我的os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,所以我希望有人可以提供一些建议,谢谢!

Answer 1

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".

这就是我为解决这个问题所做的工作.

在script.py中

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特定于安装spark的位置.对于您的环境,这个https://github.com/sequenceiq/docker-spark/blob/master/README.md可能有所帮助.

如果以上所有内容都令人困惑,请尝试以下方法:
在t.py中替换

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

同

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

然后运行它

spark-submit --packages mysql:mysql-connector-java:5.1.39 --master local[4] t.py