私は自分の Mac でdocker image sequenceiq/sparkを使用して、これらのspark の例を調査します。調査プロセス中に、この回答に従ってそのイメージ内の spark を 1.6.1 にアップグレードし、Simple Data Operations例を開始するとエラーが発生しました。起こりました：
実行するdf = sqlContext.read.format("jdbc").option("url",url).option("dbtable","people").load()とエラーが発生し、pyspark コンソールの完全なスタックは次のようになります。
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)
>>>
これが私が今まで試したことです：
をダウンロード
mysql-connector-java-5.0.8-bin.jarし、 に入れ/usr/local/spark/lib/ます。それでも同じエラーです。t.py次のように作成します。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")
それから、私は試し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ました。結果はまだ同じです。
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次に、次の を使用した場合と使用しない場合の両方を試しましたt.pyが、それでも同じです。
この間、mysql は実行されています。そして、ここに私のOS情報があります：
# rpm --query centos-release
centos-release-6-5.el6.centos.11.2.x86_64
Hadoop のバージョンは 2.6 です。
次はどこに行けばいいのかわからないので、誰かがアドバイスをくれることを願っています、ありがとう!