pyspark mysql jdbc 加载调用时发生错误 o23.load 没有合适的驱动程序
pyspark mysql jdbc load An error occurred while calling o23.load No suitable driver
我使用docker图像sequenceiq/spark on my Mac to study these spark examples, during the study process, I upgrade the spark inside that image to 1.6.1 according to this answer，当我启动Simple Data Operations示例时出现错误，这是发生了什么：
当我 运行 df = sqlContext.read.format("jdbc").option("url",url).option("dbtable","people").load() 它引发错误，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$$anonfun.apply(JdbcUtils.scala:50)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun.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)
>>>
这是我到目前为止尝试过的方法：
下载mysql-connector-java-5.0.8-bin.jar，放入/usr/local/spark/lib/。还是一样的错误。
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
- 然后我试了
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，有没有下面的t.py，还是一样。
在这期间，mysql是运行宁。这是我的 os 信息：
# rpm --query centos-release
centos-release-6-5.el6.centos.11.2.x86_64
而且hadoop版本是2.6。
现在不知道下一步该去哪里了，希望有大佬帮忙指点一下，谢谢！
当我试图让我的脚本写入 MySQL.
时，我 运行 变成了 "java.sql.SQLException: No suitable driver"
这是我解决这个问题的方法。
在script.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'})
然后我运行 spark-submit 这样
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，此 https://github.com/sequenceiq/docker-spark/blob/master/README.md 可能会有所帮助。
如果上面的内容令人困惑，试试这个：
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()
和 运行 与
spark-submit --packages mysql:mysql-connector-java:5.1.39 --master local[4] t.py
我用下面的命令解决了
import findspark
findspark.add_packages('mysql:mysql-connector-java:8.0.11')
我使用docker图像sequenceiq/spark on my Mac to study these spark examples, during the study process, I upgrade the spark inside that image to 1.6.1 according to this answer，当我启动Simple Data Operations示例时出现错误，这是发生了什么：
当我 运行 df = sqlContext.read.format("jdbc").option("url",url).option("dbtable","people").load() 它引发错误，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$$anonfun.apply(JdbcUtils.scala:50)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun.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)
>>>
这是我到目前为止尝试过的方法：
下载
mysql-connector-java-5.0.8-bin.jar，放入/usr/local/spark/lib/。还是一样的错误。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
- 然后我试了
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，有没有下面的t.py，还是一样。
在这期间，mysql是运行宁。这是我的 os 信息：
# rpm --query centos-release
centos-release-6-5.el6.centos.11.2.x86_64
而且hadoop版本是2.6。
现在不知道下一步该去哪里了，希望有大佬帮忙指点一下，谢谢！
当我试图让我的脚本写入 MySQL.
时，我 运行 变成了 "java.sql.SQLException: No suitable driver"这是我解决这个问题的方法。
在script.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'})
然后我运行 spark-submit 这样
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，此 https://github.com/sequenceiq/docker-spark/blob/master/README.md 可能会有所帮助。
如果上面的内容令人困惑，试试这个：
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()
和 运行 与
spark-submit --packages mysql:mysql-connector-java:5.1.39 --master local[4] t.py
我用下面的命令解决了
import findspark
findspark.add_packages('mysql:mysql-connector-java:8.0.11')