Hi,
I did some research on this.
The only way one can write to Oracle from Spark is through JDBC (excluding
other options outside of Spark).
The challenge here is that you have a column based on function
get_function() column that Spark needs to insert. Currently there is no
way of inserting records from Park using the traditional INSERT SELECT
statement. For example this does not work through Spark
scratch...@orasource.mich.LOCAL> insert into scratchpad.dummy6 (id) values
(2);
The batch insert option seems to be fastest
df.write. \
format("jdbc"). \
option("url", oracle_url). \
option("user", user). \
option("dbtable", "scratchpad.randomdata"). \ # you cannot
replace this with sql insert!
option("password", password). \
option("driver", driver). \
mode(mode). \
save()
How about creating a cursor on DF
for row in df.rdd.collect():
id = row[0]
clustered = row[1]
scattered = row[2]
randomised = row[3]
random_string = row[4]
small_vc = row[5]
padding= row[6]
This will print out the individual column values row by row from the
dataframe but cannot do much about it
The only option I can see here is to create a staging table EXCLUDING the
derived column and write to that table.
Next go to Oracle itself and do an insert/select from the staging table to
the target table. Let us create table dumm7 in the image of the one
created by spark
scratch...@orasource.mich.LOCAL> create table scratchpad.dummy7 as select *
from scratchpad.randomdata where 1 = 2;
Table created.
Add a new derived column to it, call it derived_col
scratch...@orasource.mich.LOCAL> alter table scratchpad.dummy7 add
derived_col float;
Table altered.
Now insert/select from scratchpad.randomdata to scratchpad.dummy7. Let us
populate the new added column with cos(id)
scratch...@orasource.mich.LOCAL> insert into scratchpad.dummy7 (id,
CLUSTERED, SCATTERED, RANDOMISED, RANDOM_STRING, SMALL_VC, PADDING,
DERIVED_COL)
2 select id, CLUSTERED, SCATTERED, RANDOMISED, RANDOM_STRING, SMALL_VC,
PADDING, *cos(id)* from randomdata;
10 rows created.
This should work, unless there is a way of inserting columns directly from
Spark.
HTH
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On Fri, 18 Jun 2021 at 22:14, Mich Talebzadeh <mich.talebza...@gmail.com>
wrote:
> Well the challenge is that Spark is best suited to insert a dataframe into
> the Oracle table, i.e. a bulk insert
>
> that insert into table (column list) values (..) is a single record
> insert .. Can you try creating a staging table in oracle without
> get_function() column and do a bulk insert from Spark dataframe to that
> staging table?
>
> HTH
>
> Mich
>
>
>
>
> view my Linkedin profile
> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>
>
>
> *Disclaimer:* Use it at your own risk. Any and all responsibility for any
> loss, damage or destruction of data or any other property which may arise
> from relying on this email's technical content is explicitly disclaimed.
> The author will in no case be liable for any monetary damages arising from
> such loss, damage or destruction.
>
>
>
>
> On Fri, 18 Jun 2021 at 21:53, Anshul Kala <anshul.k...@gmail.com> wrote:
>
>>
>> Hi Mich,
>>
>> Thanks for your reply. Please advise the insert query that I need to
>> substitute should be like below:
>>
>> Insert into table(a,b,c) values(?,get_function_value(?),?)
>>
>> In the statement above :
>>
>> ? : refers to value from dataframe column values
>> get_function_value : refers to be the function where one of the data
>> frame column is passed as input
>>
>>
>> Thanks
>> Anshul
>>
>>
>> Thanks
>> Anshul
>>
>> On Fri, Jun 18, 2021 at 4:29 PM Mich Talebzadeh <
>> mich.talebza...@gmail.com> wrote:
>>
>>> I gather you mean using JDBC to write to the Oracle table?
>>>
>>> Spark provides a unified framework to write to any JDBC
>>> compliant database.
>>>
>>> def writeTableWithJDBC(dataFrame, url, tableName, user, password,
>>> driver, mode):
>>> try:
>>> dataFrame. \
>>> write. \
>>> format("jdbc"). \
>>> option("url", url). \
>>> option("dbtable", tableName). \
>>> option("user", user). \
>>> option("password", password). \
>>> option("driver", driver). \
>>> mode(mode). \
>>> save()
>>> except Exception as e:
>>> print(f"""{e}, quitting""")
>>> sys.exit(1)
>>>
>>> and how to write it
>>>
>>> def loadIntoOracleTable(self, df2):
>>> # write to Oracle table, all uppercase not mixed case and column
>>> names <= 30 characters in version 12.1
>>> tableName =
>>> self.config['OracleVariables']['yearlyAveragePricesAllTable']
>>> fullyQualifiedTableName =
>>> self.config['OracleVariables']['dbschema']+'.'+tableName
>>> user = self.config['OracleVariables']['oracle_user']
>>> password = self.config['OracleVariables']['oracle_password']
>>> driver = self.config['OracleVariables']['oracle_driver']
>>> mode = self.config['OracleVariables']['mode']
>>>
>>> s.writeTableWithJDBC(df2,oracle_url,fullyQualifiedTableName,user,password,driver,mode)
>>> print(f"""created
>>> {config['OracleVariables']['yearlyAveragePricesAllTable']}""")
>>> # read data to ensure all loaded OK
>>> fetchsize = self.config['OracleVariables']['fetchsize']
>>> read_df =
>>> s.loadTableFromJDBC(self.spark,oracle_url,fullyQualifiedTableName,user,password,driver,fetchsize)
>>> # check that all rows are there
>>> if df2.subtract(read_df).count() == 0:
>>> print("Data has been loaded OK to Oracle table")
>>> else:
>>> print("Data could not be loaded to Oracle table, quitting")
>>> sys.exit(1)
>>>
>>> in the statement where it says
>>>
>>> option("dbtable", tableName). \
>>>
>>> You can replace *tableName* with the equivalent SQL insert statement
>>>
>>> You will need JDBC driver for Oracle say ojdbc6.jar in
>>> $SPARK_HOME/conf/spark-defaults.conf
>>>
>>> spark.driver.extraClassPath
>>> /home/hduser/jars/jconn4.jar:/home/hduser/jars/ojdbc6.jar
>>>
>>> HTH
>>>
>>>
>>>
>>> view my Linkedin profile
>>> <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/>
>>>
>>>
>>>
>>> *Disclaimer:* Use it at your own risk. Any and all responsibility for
>>> any loss, damage or destruction of data or any other property which may
>>> arise from relying on this email's technical content is explicitly
>>> disclaimed. The author will in no case be liable for any monetary damages
>>> arising from such loss, damage or destruction.
>>>
>>>
>>>
>>>
>>> On Fri, 18 Jun 2021 at 20:49, Anshul Kala <anshul.k...@gmail.com> wrote:
>>>
>>>> Hi All,
>>>>
>>>> I am using spark to ingest data from file to database Oracle table .
>>>> For one of the fields , the value to be populated is generated from a
>>>> function that is written in database .
>>>>
>>>> The input to the function is one of the fields of data frame
>>>>
>>>> I wanted to use spark.dbc.write to perform the operation, which
>>>> generates the insert query at back end .
>>>>
>>>> For example : It can generate the insert query as :
>>>>
>>>> Insert into table values (?,?, getfunctionvalue(?) )
>>>>
>>>> Please advise if it is possible in spark and if yes , how can it be
>>>> done
>>>>
>>>> This is little urgent for me . So any help is appreciated
>>>>
>>>> Thanks
>>>> Anshul
>>>>
>>>
