問(wèn)題描述
我在 Mac 上使用 docker image sequenceiq/spark 來(lái)研究這些spark examples，在學(xué)習(xí)過(guò)程中，我根據(jù)這個(gè)答案，當(dāng)我啟動(dòng)Simple Data Operations 例子，這里是發(fā)生了什么:
I use docker image 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, and the error occurred when I start the Simple Data Operations example, here is what happened:
當(dāng)我運(yùn)行 df = sqlContext.read.format("jdbc").option("url",url).option("dbtable","people").load() 它引發(fā)錯(cuò)誤，與pyspark控制臺(tái)的完整堆棧如下:
when I run df = sqlContext.read.format("jdbc").option("url",url).option("dbtable","people").load() it raise a error, and the full stack with the pyspark console is as followed:
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)
>>>
這是我迄今為止嘗試過(guò)的:
Here is what I have tried till now:
下載
mysql-connector-java-5.0.8-bin.jar，放入/usr/local/spark/lib/.還是一樣的錯(cuò)誤.
Download
mysql-connector-java-5.0.8-bin.jar, and put it in to/usr/local/spark/lib/. It still the same error.
像這樣創(chuàng)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，我嘗試了 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.結(jié)果還是一樣.
then, I tried 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. The result is still the same.
- 然后我嘗試了
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，有和沒(méi)有下面的t.py，還是一樣.
- Then I tried
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, both with and without the followingt.py, still the same.
在此期間，mysql 正在運(yùn)行.這是我的操作系統(tǒng)信息:
During all of this, the mysql is running. And here is my os info:
# rpm --query centos-release
centos-release-6-5.el6.centos.11.2.x86_64
hadoop 版本是 2.6.
And the hadoop version is 2.6.
現(xiàn)在不知道下一步該去哪里，希望有大神幫忙指點(diǎn)一下，謝謝！
Now I don't where to go next, so I hope some one can help give some advice, thanks!
推薦答案
當(dāng)我嘗試將腳本寫(xiě)入 MySQL 時(shí)，我遇到了java.sql.SQLException:沒(méi)有合適的驅(qū)動(dòng)程序".
I ran into "java.sql.SQLException: No suitable driver" when I tried to have my script write to MySQL.
這是我為解決這個(gè)問(wèn)題所做的.
Here's what I did to fix that.
在 script.py 中
In 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'})
然后我以這種方式運(yùn)行 spark-submit
Then I ran spark-submit this way
SPARK_HOME=/usr/local/Cellar/apache-spark/1.6.1/libexec spark-submit --packages mysql:mysql-connector-java:5.1.39 ./script.py
請(qǐng)注意，SPARK_HOME 特定于安裝 spark 的位置.對(duì)于您的環(huán)境，這個(gè) https://github.com/sequenceiq/docker-spark/blob/master/README.md 可能會(huì)有所幫助.
Note that SPARK_HOME is specific to where spark is installed. For your environment this https://github.com/sequenceiq/docker-spark/blob/master/README.md might help.
如果以上所有內(nèi)容都令人困惑，請(qǐng)嘗試以下操作:
在 t.py 中替換
In case all the above is confusing, try this:
In t.py replace
sqlContext.read.format("jdbc").option("url",url).option("dbtable","people").load()
與
sqlContext.read.format("jdbc").option("dbtable","people").option("driver", 'com.mysql.jdbc.Driver').load()
然后運(yùn)行
spark-submit --packages mysql:mysql-connector-java:5.1.39 --master local[4] t.py
這篇關(guān)于pyspark mysql jdbc load 調(diào)用 o23.load 時(shí)發(fā)生錯(cuò)誤 沒(méi)有合適的驅(qū)動(dòng)程序的文章就介紹到這了，希望我們推薦的答案對(duì)大家有所幫助，也希望大家多多支持html5模板網(wǎng)！