data extraction from oracle source

I am trying to extract data from oracle source using pyspark.

I am using this code. from pyspark.sql import SparkSession

spark = SparkSession.builder.appName('Spark_Job').getOrCreate()

driver = 'oracle.jdbc.driver.OracleDriver'

url = 'jdbc:oracle:thin:@XXXXXXXXXXXXXXXXXX/XXX'

user = 'XXXXX'

password = 'XXXXXXXX'

query = 'SELECT col_1 from schema_1.view_1'

df = spark.read.format('jdbc').option('driver', driver).option('url', url).option('dbtable', query)\

.option('user', user).option('password', password).load()

df.show(10)

I am getting this error :

java.sql.SQLSyntaxErrorException: ORA-00903: invalid table name

Solution

ORA-00903 means that you tried to use table name, but - that table doesn't exist.

There's only one select statement here:

SELECT col_1 from schema_1.view_1
                  -------- ------ 
                  owner    table (or view) name
                  ("user")

Info you posted suggests that you're connected as

user = 'XXXXX'

If view_1 belongs to currently connected user, you don't have to specify owner name so query would then be just select col_1 from view_1.
If view_1 belongs to currently connected user, then view_1 must be correctly spelled. Oracle doesn't care about letter case unless you decided to enclose its (table's, view's) name into double quotes and used lower or mixed case - then you have to do it every time you reference that table, so query might be e.g. select col_1 from "View_1".
If view_1 belongs to user who is different from currently logged user (that's what information you posted suggests), then yes - preceding table's name with its owner's name is the way to do it. However, schema_1 (the owner) has to grant at least select privilege on view_1 to XXXXX - otherwise, it won't work. (Double quotes/letter case issue still stands.)

I can't tell which situation of these you have, but now you have something to check and act appropriately.