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Posted to issues@spark.apache.org by "David Lassiter (Jira)" <ji...@apache.org> on 2022/07/19 10:49:00 UTC

[jira] [Resolved] (SPARK-39813) Unable to connect to Presto in Pyspark: java.lang.ClassNotFoundException: com.facebook.presto.jdbc.PrestoDriver

     [ https://issues.apache.org/jira/browse/SPARK-39813?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

David Lassiter resolved SPARK-39813.
------------------------------------
    Resolution: Fixed

Comment by than nguyen dinh helped me resolve this issue.

 

Thank you!

> Unable to connect to Presto in Pyspark: java.lang.ClassNotFoundException: com.facebook.presto.jdbc.PrestoDriver
> ---------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-39813
>                 URL: https://issues.apache.org/jira/browse/SPARK-39813
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 3.3.0
>         Environment: I am running this in a docker built from the jupyter/all-spark-notebook image.
>            Reporter: David Lassiter
>            Priority: Major
>              Labels: AWS
>   Original Estimate: 24h
>  Remaining Estimate: 24h
>
> My team has a bash script + python script that uses pyspark to extract data from a hive database. The scripts work when run on a server. However, we need to containerize this since we will not have access to that server in the future.
> Thus, I am trying to get the job to work from a container. 
> When trying to run the scripts locally or in a docker container, I am running into driver issues. Unfortunately, nobody on my team helped set up the environment on the server, where everything is working. Thus, we are having a hard time figuring out what is wrong with our local/containerized environments and cannot replicate a successful script run. 
>  
> From a container, I run a bash script that does the following:
>  
> ```\{bash}
> $SPARK_HOME/bin/spark-submit etl_job.py
> ```
>  
> The contents of `etl_job.py` are as follows:
> ```\{python}
> print('\n\nStarting python job\n\n')
> from pyspark.context import SparkContext
> from pyspark.sql.session import SparkSession
> from credentials import PRESTO_USER, PRESTO_PASSWORD, PRESTO_URL, PRESTO_SSL, SSL_PASSWORD, TEST_SCHEMA, TEST_TABLE
> import pandas as pd
> print('\n\nStarting spark session \n\n')
> sc = SparkContext.getOrCreate()
> spark = SparkSession(sc)
> print('\n\nConnecting to Presto\n\n')
> Prestoprod = (
> spark.read.format("jdbc")
> .option("url", PRESTO_URL)
> .option("user", PRESTO_USER)
> .option("password", PRESTO_PASSWORD)
> .option("driver", "com.facebook.presto.jdbc.PrestoDriver")
> .option("SSL", "true")
> .option("SSLKeyStorePath", PRESTO_SSL)
> .option("SSLKeyStorePassword", SSL_PASSWORD)
> )
>  
> print('\n\nTrying to query Presto.\n\n')
> query = "select * from hive.{}.{}".format(TEST_SCHEMA, TEST_TABLE)
> results = (
> Prestoprod.option(
> "query",
> query
> )
> .load()
> )
> ```
>  
> However, when I run the job, I get the following error:
> ```
> py4j.protocol.Py4JJavaError: An error occurred while calling o33.load.
> : java.lang.ClassNotFoundException: com.facebook.presto.jdbc.PrestoDriver
> ```
>  
> Here is the full log:
> ```
> Starting python job
>  
> Starting spark session 
> Setting default log level to "WARN".
> To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
> 22/07/19 04:45:04 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
> Connecting to Presto
>  
> Trying to query Presto.
> Traceback (most recent call last):
>   File "/home/jovyan/etl_job.py", line 30, in <module>
>     .load()
>   File "/usr/local/spark/python/pyspark/sql/readwriter.py", line 184, in load
>     return self._df(self._jreader.load())
>   File "/usr/local/spark/python/lib/py4j-0.10.9.5-src.zip/py4j/java_gateway.py", line 1321, in {_}{{_}}call{{_}}{_}
>   File "/usr/local/spark/python/pyspark/sql/utils.py", line 190, in deco
>     return f(*a, **kw)
>   File "/usr/local/spark/python/lib/py4j-0.10.9.5-src.zip/py4j/protocol.py", line 326, in get_return_value
> py4j.protocol.Py4JJavaError: An error occurred while calling o33.load.
> : java.lang.ClassNotFoundException: com.facebook.presto.jdbc.PrestoDriver
>         at java.base/java.net.URLClassLoader.findClass(URLClassLoader.java:445)
>         at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:587)
>         at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:520)
>         at org.apache.spark.sql.execution.datasources.jdbc.DriverRegistry$.register(DriverRegistry.scala:46)
>         at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.$anonfun$driverClass$1(JDBCOptions.scala:101)
>         at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.$anonfun$driverClass$1$adapted(JDBCOptions.scala:101)
>         at scala.Option.foreach(Option.scala:437)
>         at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.<init>(JDBCOptions.scala:101)
>         at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.<init>(JDBCOptions.scala:39)
>         at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:34)
>         at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:350)
>         at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:228)
>         at org.apache.spark.sql.DataFrameReader.$anonfun$load$2(DataFrameReader.scala:210)
>         at scala.Option.getOrElse(Option.scala:201)
>         at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:210)
>         at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:171)
>         at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>         at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:77)
>         at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>         at java.base/java.lang.reflect.Method.invoke(Method.java:568)
>         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.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
>         at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
>         at java.base/java.lang.Thread.run(Thread.java:833)
> ```
>  
> Other relevant info is that I am trying to run this on a container built from the jupyter/all-spark-notebook image fron dockerhub.



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