Hey everyone, I created the initial design doc: https://docs.google.com/document/d/112VsrCKhtqtUTph5yXMzsaoxtz9wX1U2poi1vxuDswY/edit?usp=sharing It lays out the motivation and a few more details (as discussed on the different channels). Let’s start working on it together, and then we can get Gian’s review.
BTW - the doc is currently open for everyone to edit, let me know if you think I should change that. On 2020/03/11 22:33:19, itai yaffe <itai.ya...@gmail.com> wrote: > Hey Rajiv, > Can you please provide some details on the use-case of querying Druid from > Spark (e.g what type of queries, how big is the result set, and any other > information you think is relevant)? > > Thanks! > > On Tue, Mar 10, 2020 at 6:08 PM Rajiv Mordani <rmord...@vmware.com.invalid> > wrote: > > > As part of the requirements please include querying / reading from Spark > > as well. This is a high priority for us. > > > > - Rajiv > > > > On 3/10/20, 1:26 AM, "Oguzhan Mangir" <sosyalmedya.oguz...@gmail.com> > > wrote: > > > > What we will do for that? I think, we can start to write requirements > > and flows. > > > > On 2020/03/05 20:19:38, Julian Jaffe <jja...@pinterest.com.INVALID> > > wrote: > > > Yeah, I think the primary objective here is a standalone writer from > > Spark > > > to Druid. > > > > > > On Thu, Mar 5, 2020 at 11:43 AM itai yaffe <itai.ya...@gmail.com> > > wrote: > > > > > > > Thanks Julian! > > > > I'm actually targeting for this connector to allow write > > capabilities (at > > > > least as a first phase), rather than focusing on read capabilities. > > > > Having said that, I definitely see the value (even for the > > use-cases in my > > > > company) of having a reader that queries S3 segments directly! > > Funny, we > > > > too have implemented a mechanism (although a very simple one) to > > get the > > > > locations of the segments through SegmentMetadataQueries, to allow > > > > batch-oriented queries to work with against the deep storage :) > > > > > > > > Anyway, as I said, I think we can focus on write capabilities for > > now, and > > > > worry about read capabilities later (if that's OK). > > > > > > > > On 2020/03/05 18:29:09, Julian Jaffe <jja...@pinterest.com.INVALID > > > > > > > wrote: > > > > > The spark-druid-connector you shared brings up another design > > decision we > > > > > should probably talk through. That connector effectively wraps > > an HTTP > > > > > query client with Spark plumbing. An alternative approach (and > > the one I > > > > > ended up building due to our business requirements) is to build > > a reader > > > > > that operates directly over the S3 segments, shifting load for > > what are > > > > > likely very large and non-interactive queries off Druid-specific > > hardware > > > > > (with the exception of a few SegmentMetadataQueries to get > > location > > > > info). > > > > > > > > > > On Thu, Mar 5, 2020 at 8:04 AM itai yaffe <itai.ya...@gmail.com> > > wrote: > > > > > > > > > > > I'll let Julian answer, but in the meantime, I just wanted to > > point > > > > out we > > > > > > might be able to draw some inspiration from this Spark-Redshift > > > > connector ( > > > > > > > > https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fdatabricks%2Fspark-redshift%23scala&data=02%7C01%7Crmordani%40vmware.com%7C98a7d3b214504747aac908d7c4ccbc2e%7Cb39138ca3cee4b4aa4d6cd83d9dd62f0%7C0%7C0%7C637194255930728172&sdata=JMUhEOgBz7ddweQ%2FZx2ODKJl1Q%2FUXrKURGlkltU4p3w%3D&reserved=0 > > ). > > > > > > Though it's somewhat outdated, it probably can be used as a > > reference > > > > for > > > > > > this new Spark-Druid connector we're planning. > > > > > > Another project to look at is > > > > > > > > https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FSharpRay%2Fspark-druid-connector&data=02%7C01%7Crmordani%40vmware.com%7C98a7d3b214504747aac908d7c4ccbc2e%7Cb39138ca3cee4b4aa4d6cd83d9dd62f0%7C0%7C0%7C637194255930728172&sdata=wKQiHp8MdymdvZB3iOpNnI%2BC1uYyAcCpw3d5oJjJE9E%3D&reserved=0 > > . > > > > > > > > > > > > On 2020/03/02 14:31:27, O��uzhan Mang��r < > > > > sosyalmedya.oguz...@gmail.com> > > > > > > wrote: > > > > > > > I think second option would be better. Many people use spark > > for > > > > batch > > > > > > operations with isolated clusters. Me and my friends will > > taking time > > > > for > > > > > > that. Julian, can you share your experiences for that? After > > that, we > > > > can > > > > > > write our aims, requirements and flows easily. > > > > > > > > > > > > > > On 2020/02/26 13:26:13, itai yaffe <itai.ya...@gmail.com> > > wrote: > > > > > > > > Hey, > > > > > > > > Per Gian's proposal, and following this thread in Druid > > user group > > > > ( > > > > > > > > > > https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgroups.google.com%2Fforum%2F%23!topic%2Fdruid-user%2FFqAuDGc-rUM&data=02%7C01%7Crmordani%40vmware.com%7C98a7d3b214504747aac908d7c4ccbc2e%7Cb39138ca3cee4b4aa4d6cd83d9dd62f0%7C0%7C0%7C637194255930728172&sdata=9dFNoEHC7qWOoc1PCBENXOwTnC5v7RyXT41PA1Hugek%3D&reserved=0 > > ) > > > > and > > > > > > this > > > > > > > > thread in Druid Slack channel ( > > > > > > > > > > https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fthe-asf.slack.com%2Farchives%2FCJ8D1JTB8%2Fp1581452302483600&data=02%7C01%7Crmordani%40vmware.com%7C98a7d3b214504747aac908d7c4ccbc2e%7Cb39138ca3cee4b4aa4d6cd83d9dd62f0%7C0%7C0%7C637194255930728172&sdata=YrWbTt7GCZ6OJPKTKLemTqN7eMXEGtfqFxkGiT4MC6g%3D&reserved=0 > > ), > > > > I'd > > > > > > like > > > > > > > > to start discussing the options of having Spark-based > > ingestion > > > > into > > > > > > Druid. > > > > > > > > > > > > > > > > There's already an old project ( > > > > > > > > https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fmetamx%2Fdruid-spark-batch&data=02%7C01%7Crmordani%40vmware.com%7C98a7d3b214504747aac908d7c4ccbc2e%7Cb39138ca3cee4b4aa4d6cd83d9dd62f0%7C0%7C0%7C637194255930728172&sdata=HplKPAboYAvUnJ%2BGJUF%2FRbmrGrCI5guUEA%2FdJ64O0b8%3D&reserved=0 > > ) > > > > > > > > for that, so perhaps we can use that as a starting point. > > > > > > > > > > > > > > > > The thread on Slack suggested 2 approaches: > > > > > > > > > > > > > > > > 1. *Simply replacing the Hadoop MapReduce ingestion > > task* - > > > > having a > > > > > > > > Spark batch job that ingests data into Druid, as a > > simple > > > > > > replacement of > > > > > > > > the Hadoop MapReduce ingestion task. > > > > > > > > Meaning - your data pipeline will have a Spark job to > > > > pre-process > > > > > > the > > > > > > > > data (similar to what some of us have today), and > > another Spark > > > > job > > > > > > to read > > > > > > > > the output of the previous job, and create Druid > > segments > > > > (again - > > > > > > > > following the same pattern as the Hadoop MapReduce > > ingestion > > > > task). > > > > > > > > 2. *Druid output sink for Spark* - rather than having 2 > > separate > > > > > > Spark > > > > > > > > jobs, 1 for pre-processing the data and 1 for ingesting > > the data > > > > > > into > > > > > > > > Druid, you'll have a single Spark job that > > pre-processes the > > > > data > > > > > > and > > > > > > > > creates Druid segments directly, e.g > > > > > > sparkDataFrame.write.format("druid") > > > > > > > > (as suggested by omngr on Slack). > > > > > > > > > > > > > > > > > > > > > > > > I personally prefer the 2nd approach - while it might be > > harder to > > > > > > > > implement, it seems the benefits are greater in this > > approach. > > > > > > > > > > > > > > > > I'd like to hear your thoughts and to start getting this > > ball > > > > rolling. > > > > > > > > > > > > > > > > Thanks, > > > > > > > > Itai > > > > > > > > > > > > > > > > > > > > > > > > --------------------------------------------------------------------- > > > > > > > To unsubscribe, e-mail: dev-unsubscr...@druid.apache.org > > > > > > > For additional commands, e-mail: dev-h...@druid.apache.org > > > > > > > > > > > > > > > > > > > > > > > > > > > > --------------------------------------------------------------------- > > > > > > To unsubscribe, e-mail: dev-unsubscr...@druid.apache.org > > > > > > For additional commands, e-mail: dev-h...@druid.apache.org > > > > > > > > > > > > > > > > > > > > > > > > > > > --------------------------------------------------------------------- > > > > To unsubscribe, e-mail: dev-unsubscr...@druid.apache.org > > > > For additional commands, e-mail: dev-h...@druid.apache.org > > > > > > > > > > > > > > > --------------------------------------------------------------------- > > To unsubscribe, e-mail: dev-unsubscr...@druid.apache.org > > For additional commands, e-mail: dev-h...@druid.apache.org > > > > > > > --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@druid.apache.org For additional commands, e-mail: dev-h...@druid.apache.org
