Hi, I glanced over the design doc.
You are providing certain configuration parameters plus some settings based on static values. For example: spark.dynamicAllocation.schedulerBacklogTimeout": 54s I cannot see any use of <processing time> which ought to be at least half of the batch interval to have the correct margins (confidence level). If you are going to have additional indicators why not look at scheduling delay as well. Moreover most of the needed statistics are also available to set accurate values. My inclination is that this is a great effort but we ought to utilise the historical statistics collected under checkpointing directory to get more accurate statistics. I will review the design document in duew course HTH Mich Talebzadeh, Solutions Architect/Engineering Lead London United Kingdom view my Linkedin profile <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/> https://en.everybodywiki.com/Mich_Talebzadeh *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 Tue, 8 Aug 2023 at 01:30, Pavan Kotikalapudi <pkotikalap...@twilio.com.invalid> wrote: > Hi Spark Dev, > > I have extended traditional DRA to work for structured streaming > use-case. > > Here is an initial Implementation draft PR > https://github.com/apache/spark/pull/42352 and design doc: > https://docs.google.com/document/d/1_YmfCsQQb9XhRdKh0ijbc-j8JKGtGBxYsk_30NVSTWo/edit?usp=sharing > > Please review and let me know what you think. > > Thank you, > > Pavan >
