I use docker image sequenceiq / spark on my Mac to study these spark examples , during the training process I update the spark inside this image to 1.6.1 in accordance with this answer , and an error occurred when I run the Simple Data Operations example, here what happened:
when I run df = sqlContext.read.format("jdbc").option("url",url).option("dbtable","people").load() , it causes an error, and the full stack with the pyspark console performed as follows:
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) >>>
Here is what I have tried so far:
Download mysql-connector-java-5.0.8-bin.jar and enter it in /usr/local/spark/lib/ . This is still the same error.
Create t.py as follows:
from pyspark SparkContext import
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")
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 the same.
- 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 , with or without the next t.py , anyway.
During all this, mysql is working. And here is my os info:
# rpm --query centos-release centos-release-6-5.el6.centos.11.2.x86_64
And the hadoop version is 2.6.
Now I won’t go any further, so I hope someone can help give some advice, thanks!