Cant connect to Mysql database from pyspark, getting jdbc error - mysql

Question

I am learning pyspark, and trying to connect to a mysql database.
But i am getting a java.lang.ClassNotFoundException: com.mysql.jdbc.Driver Exception while running the code. I have spent a whole day trying to fix it, any help would be appreciated :)
I am using pycharm community edition with anaconda and python 3.6.3
Here is my code:
from pyspark import SparkContext,SQLContext
sc= SparkContext()
sqlContext= SQLContext(sc)
df = sqlContext.read.format("jdbc").options(
url ="jdbc:mysql://192.168.0.11:3306/my_db_name",
driver = "com.mysql.jdbc.Driver",
dbtable = "billing",
user="root",
password="root").load()
Here is the error:
py4j.protocol.Py4JJavaError: An error occurred while calling o27.load.
: java.lang.ClassNotFoundException: com.mysql.jdbc.Driver

Answer 1

This got asked 9 months ago at the time of writing, but since there's no answer, there it goes. I was in the same situation, searched stackoverflow over and over, tried different suggestions but the answer finally is absurdly simple: You just have to COPY the MySQL driver into the "jars" folder of Spark!
Download here https://dev.mysql.com/downloads/connector/j/5.1.html
I'm using the 5.1 version, although 8.0 exists, but I had some other problems when running the latest version with Spark 2.3.2 (had also other problems running Spark 2.4 on Windows 10).
Once downloaded you can just copy it into your Spark folder
E:\spark232_hadoop27\jars\ (use your own drive:\folder_name -- this is just an example)
You should have two files:
E:\spark232_hadoop27\jars\mysql-connector-java-5.1.47-bin.jar
E:\spark232_hadoop27\jars\mysql-connector-java-5.1.47.jar
After that the following code launched through pyCharm or jupyter notebook should work (as long as you have a MySQL database set up, that is):
import findspark
findspark.init()
import pyspark # only run after findspark.init()
from pyspark.sql import SparkSession
spark = SparkSession.builder.getOrCreate()
dataframe_mysql = spark.read.format("jdbc").options(
url="jdbc:mysql://localhost:3306/uoc2",
driver = "com.mysql.jdbc.Driver",
dbtable = "company",
user="root",
password="password").load()
dataframe_mysql.show()
Bear in mind, I'm working currently locally with my Spark setup, so no real clusters involved, and also no "production" kind of code which gets submitted to such a cluster. For something more elaborate this answer could help: MySQL read with PySpark

Answer 2

On my computer, #Kondado 's solution works only if I change the driver in the options:
driver = 'com.mysql.cj.jdbc.Driver'
I am using Spark 8.0 on Windows. I downloaded mysql-connector-java-8.0.15.jar, Platform Independent version from here. And copy it to 'C:\spark-2.4.0-bin-hadoop2.7\jars\'
My code in Pycharm looks like this:
#import findspark # not necessary
#findspark.init() # not necessary
from pyspark import SparkConf, SparkContext, sql
from pyspark.sql import SparkSession
sc = SparkSession.builder.getOrCreate()
sqlContext = sql.SQLContext(sc)
source_df = sqlContext.read.format('jdbc').options(
url='jdbc:mysql://localhost:3306/database1',
driver='com.mysql.cj.jdbc.Driver', #com.mysql.jdbc.Driver
dbtable='table1',
user='root',
password='****').load()
print (source_df)
source_df.show()

Answer 3

I dont know how to add jar file to ClassPath(can someone tell me how??) so I put it in the SparkSession config and it works fine.
spark = SparkSession \
.builder \
.appName('test') \
.master('local[*]') \
.enableHiveSupport() \
.config("spark.driver.extraClassPath", "<path to mysql-connector-java-5.1.49-bin.jar>") \
.getOrCreate()
df = spark.read.format("jdbc").option("url","jdbc:mysql://localhost/<database_name>").option("driver","com.mysql.jdbc.Driver").option("dbtable",<table_name>).option("user",<user>).option("password",<password>).load()
df.show()

Answer 4

This worked for me, pyspark with mssql
java version is 1.7.0_191
pyspark version is 2.1.2
Download the below jar files
sqljdbc41.jar
mssql-jdbc-6.2.2.jre7.jar
Paste the above jars inside jars folder in the virtual environment
test_env/lib/python3.6/site-packages/pyspark/jars
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName('Practise').getOrCreate()
url = 'jdbc:sqlserver://your_host_name:your_port;databaseName=YOUR_DATABASE_NAME;useNTLMV2=true;'
df = spark.read.format('jdbc'
).option('url', url
).option('user', 'your_db_username'
).option('password','your_db_password'
).option('dbtable', 'YOUR_TABLE_NAME'
).option('driver', 'com.microsoft.sqlserver.jdbc.SQLServerDriver'
).load()