Never mind. Problem solved.
On Mon, Nov 19, 2018 at 12:09 PM Lian Jiang <[email protected]> wrote:
> Hi,
>
> I am trying to use oracle jdbc to load the table from oracle db but got
> error.
>
> The code:
> #######################
> import findspark
> findspark.init()
>
> from pyspark import SparkContext, SQLContext
> import os
>
> os.environ['PYSPARK_SUBMIT_ARGS'] = '--master yarn --deploy-mode client
> --driver-cores 4 --driver-memory 10g --num-executors 2 --executor-cores 6
> --executor-memory 10g --driver-class-path /mnt/data/hdfs/ojdbc8.jar --jars
> /mnt/data/hdfs/ojdbc8.jar pyspark-shell'
> sc =SparkContext(appName = "Pi")
> sqlCtx = SQLContext(sc)
>
> url = "jdbc:oracle:thin:@
> (DESCRIPTION=(ADDRESS=(PROTOCOL=TCP)(HOST=127.0.3.69)(PORT=1521))(CONNECT_DATA=(SERVER=DEDICATED)(SERVICE_NAME=
> myservice.com)))"
> properties = {
> "user": "user",
> "password": "password"
> }
> df=sqlCtx.read.jdbc(url=url, table="myschema.mytable",
> properties=properties)
> df.show(3)
> #######################
>
> The error:
> #######################
>
> Py4JJavaError: An error occurred while calling o63.jdbc.
> : java.sql.SQLException: No suitable driver
> at java.sql.DriverManager.getDriver(DriverManager.java:315)
> at
> org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions$$anonfun$7.apply(JDBCOptions.scala:85)
> at
> org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions$$anonfun$7.apply(JDBCOptions.scala:85)
> at scala.Option.getOrElse(Option.scala:121)
> at
> org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.<init>(JDBCOptions.scala:84)
> at
> org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.<init>(JDBCOptions.scala:35)
> at
> org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:34)
> at
> org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:340)
> at
> org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:239)
> at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:227)
> at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:164)
> at org.apache.spark.sql.DataFrameReader.jdbc(DataFrameReader.scala:254)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
> at py4j.Gateway.invoke(Gateway.java:282)
> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
> at py4j.commands.CallCommand.execute(CallCommand.java:79)
> at py4j.GatewayConnection.run(GatewayConnection.java:238)
> at java.lang.Thread.run(Thread.java:745)
> ##################
>
> My jupyter is:
> ###################
>
> The version of the notebook server is: *5.5.0*
> The server is running on this version of Python:
> Python 2.7.15 |Anaconda, Inc.| (default, May 1 2018, 23:32:55)
> [GCC 7.2.0]
> ####################
>
> ojdbc8.jar is available on all namenodes and datanodes.
>
> Any idea? Thanks.
>
>
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