Re: ID block allocation exception while creating edge
hadoopmarc@...
Hi Anjani,
One thing that does not feel good is that you create and commit a transaction for every row of your dataframe. Although I do not see how this would interfere with ID allocation, best practice is to have partitions of about 10.000 vertices/edges and commit these as one batch. In case of an exception, you rollback the transaction and raise your own exception. After that, Spark will retry the partition and your job will still succeed. It is worth a atry.
Best wishes, Marc
One thing that does not feel good is that you create and commit a transaction for every row of your dataframe. Although I do not see how this would interfere with ID allocation, best practice is to have partitions of about 10.000 vertices/edges and commit these as one batch. In case of an exception, you rollback the transaction and raise your own exception. After that, Spark will retry the partition and your job will still succeed. It is worth a atry.
Best wishes, Marc