>But which one will fail, either streaming or delete batch job? That's the pitfall with an OCC based approach. We can't really choose. You probably need to break up your delete job also to be more incremental and run in smaller batches to avoid contention. Otherwise, you'll get into a scenario where the delete job runs for a few hours, and then always fails to commit, because streaming job wrote some conflicting data.
>you are asking whether I can query those tables and pull the corresponding records by spark job and write it back (output) to the same topic yes. That's what did at Uber, for e.g Thanks Vinoth On Wed, Apr 14, 2021 at 12:59 PM nishith agarwal <n3.nas...@gmail.com> wrote: > No worries. Is the custom build something you can work with the AWS team to > get installed to be able to test ? > > -Nishith > > On Wed, Apr 14, 2021 at 12:57 PM Kizhakkel Jose, Felix > <felix.j...@philips.com.invalid> wrote: > > > Hi Nishith, Vinoth, > > > > Thank you so much for the quick response and offering the help. > > > > Regards, > > Felix K Jose > > From: Kizhakkel Jose, Felix <felix.j...@philips.com.INVALID> > > Date: Wednesday, April 14, 2021 at 3:55 PM > > To: dev@hudi.apache.org <dev@hudi.apache.org> > > Subject: Re: GDPR deletes and Consenting deletes of data from hudi table > > Caution: This e-mail originated from outside of Philips, be careful for > > phishing. > > > > > > Hi Nishith, > > > > As I mentioned we are on AWS EMR, but I don’t think we have this 0.8.0 > > version available as part of existing version. So we need a custom build > > for working it on latest EMR 6.1.0 > > > > Regards, > > Felix K Jose > > From: nishith agarwal <n3.nas...@gmail.com> > > Date: Wednesday, April 14, 2021 at 3:49 PM > > To: dev <dev@hudi.apache.org> > > Subject: Re: GDPR deletes and Consenting deletes of data from hudi table > > Caution: This e-mail originated from outside of Philips, be careful for > > phishing. > > > > > > Felix, > > > > Happy to help you through trying and rolling out multi-writer on Hudi > > tables. Do you have a test environment where you can try out the feature > by > > following the doc that Vinoth pointed above ? > > > > Thanks, > > Nishith > > > > On Wed, Apr 14, 2021 at 12:26 PM Vinoth Chandar <vin...@apache.org> > wrote: > > > > > Hi Felix, > > > > > > Most people I think are publishing this data into Kafka,and apply the > > > deletes as a part of the streaming job itself. The reason why this > works > > is > > > because typically, only a small fraction of users leave the service > (say > > << > > > 0.1% weekly is what I have heard). So, the cost of storage on Kafka is > > not > > > much. Is that not the case for you? Are you looking for one time > > scrubbing > > > of data for e.g? The benefit of this approach is that you eliminate any > > > concurrency issues that arise from streaming job producing data for a > > user, > > > while the deletes are also issued for that user. > > > > > > On concurrency control, Hudi now supports multiple writers, if you want > > to > > > write a background job that will perform these deletes for you. it's in > > > 0.8.0, see > > > https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fhudi.apache.org%2Fdocs%2Fconcurrency_control.html&data=04%7C01%7C%7Cd9f8ea00fdba484d5cee08d8ff7f3df6%7C1a407a2d76754d178692b3ac285306e4%7C0%7C1%7C637540269251879953%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C2000&sdata=5PqHnY%2FI7i3u7z31irU8Xu5VRW1niA0ljfWUWm0vjDY%3D&reserved=0 > . > > One of > > > us > > > can help you out with trying this and rolling out. (Nishith is the > > feature > > > author). Here, if the delete job touches same files, that the streaming > > job > > > is writing to, then only one of them will succeed. > > > > > > We are working on a design for true lock free concurrency control, > which > > > provides the benefits of both models. But, won't be there for another > > month > > > or two. > > > > > > Thanks > > > Vinoth > > > > > > > > > On Tue, Apr 13, 2021 at 1:45 PM Kizhakkel Jose, Felix > > > <felix.j...@philips.com.invalid> wrote: > > > > > > > Hi All, > > > > > > > > I have 100s of HUDI tables (AWS S3) where each of those are populated > > via > > > > Spark structured streaming from kafka streams. Now I have to delete > > > records > > > > for a given user (userId) from all the tables which has data for that > > > user. > > > > Meaning all tables where we have reference to that specific userId. I > > > > cannot republish all the events/records for that user to kafka to > > perform > > > > delete, since its around 10-15 year’s worth of data for each user and > > is > > > > going to be so costly and time consuming. So I am wondering how > > everybody > > > > is performing GDPR on the their HUDI tables? > > > > > > > > > > > > How I get delete request? > > > > On a delete kafka topic we get a delete event [which just contains > the > > > > userId of the user to delete], so we have to use that as filter > > > condition > > > > and read all the records from HUDI tables and write it back with data > > > > source operation as ‘delete’. But while performing/running this > delete > > > > spark job on the table if the streaming job continues to ingest new > > > > arriving data- what will be the side effect? Will it work, since > seems > > > like > > > > multi writers are not currently supported. > > > > > > > > Could you help me with a solution? > > > > > > > > Regards, > > > > Felix K Jose > > > > > > > > ________________________________ > > > > The information contained in this message may be confidential and > > legally > > > > protected under applicable law. The message is intended solely for > the > > > > addressee(s). If you are not the intended recipient, you are hereby > > > > notified that any use, forwarding, dissemination, or reproduction of > > this > > > > message is strictly prohibited and may be unlawful. If you are not > the > > > > intended recipient, please contact the sender by return e-mail and > > > destroy > > > > all copies of the original message. > > > > > > > > > > > ________________________________ > > The information contained in this message may be confidential and legally > > protected under applicable law. The message is intended solely for the > > addressee(s). If you are not the intended recipient, you are hereby > > notified that any use, forwarding, dissemination, or reproduction of this > > message is strictly prohibited and may be unlawful. If you are not the > > intended recipient, please contact the sender by return e-mail and > destroy > > all copies of the original message. > > >
