If you have your RDBMS table partitioned, then you need to consider how much data you want to extract in other words the result set returned by the JDBC call.
If you want all the data, then the number of partitions specified in the JDBC call should be equal to the number of partitions in your RDBMS table. HTH Dr Mich Talebzadeh LinkedIn * https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* http://talebzadehmich.wordpress.com *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 14 August 2016 at 21:44, Ashok Kumar <ashok34...@yahoo.com> wrote: > Thank you very much sir. > > I forgot to mention that two of these Oracle tables are range partitioned. > In that case what would be the optimum number of partitions if you can > share? > > Warmest > > > On Sunday, 14 August 2016, 21:37, Mich Talebzadeh < > mich.talebza...@gmail.com> wrote: > > > If you have primary keys on these tables then you can parallelise the > process reading data. > > You have to be careful not to set the number of partitions too many. > Certainly there is a balance between the number of partitions supplied to > JDBC and the load on the network and the source DB. > > Assuming that your underlying table has primary key ID, then this will > create 20 parallel processes to Oracle DB > > val d = HiveContext.read.format("jdbc").options( > Map("url" -> _ORACLEserver, > "dbtable" -> "(SELECT <COL1>, <COL2>, ....FROM <TABLE>)", > "partitionColumn" -> "ID", > "lowerBound" -> "1", > "upperBound" -> "maxID", > "numPartitions" -> "20", > "user" -> _username, > "password" -> _password)).load > > assuming your upper bound on ID is maxID > > > This will open multiple connections to RDBMS, each getting a subset of > data that you want. > > You need to test it to ensure that you get the numPartitions optimum and > you don't overload any component. > > HTH > > > Dr Mich Talebzadeh > > LinkedIn * > https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw > <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* > > http://talebzadehmich.wordpress.com > > *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 14 August 2016 at 21:15, Ashok Kumar <ashok34...@yahoo.com.invalid> > wrote: > > Hi, > > There are 4 tables ranging from 10 million to 100 million rows but they > all have primary keys. > > The network is fine but our Oracle is RAC and we can only connect to a > designated Oracle node (where we have a DQ account only). > > We have a limited time window of few hours to get the required data out. > > Thanks > > > On Sunday, 14 August 2016, 21:07, Mich Talebzadeh < > mich.talebza...@gmail.com> wrote: > > > How big are your tables and is there any issue with the network between > your Spark nodes and your Oracle DB that adds to issues? > > HTH > > Dr Mich Talebzadeh > > LinkedIn * https://www.linkedin.com/ profile/view?id= > AAEAAAAWh2gBxianrbJd6zP6AcPCCd OABUrV8Pw > <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* > > http://talebzadehmich. wordpress.com > <http://talebzadehmich.wordpress.com/> > > *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 14 August 2016 at 20:50, Ashok Kumar <ashok34...@yahoo.com.invalid> > wrote: > > Hi Gurus, > > I have few large tables in rdbms (ours is Oracle). We want to access these > tables through Spark JDBC > > What is the quickest way of getting data into Spark Dataframe say multiple > connections from Spark > > thanking you > > > > > > > > >
