Hi!
We are testing the following 3 way time windowed join to keep the retained state size small. Using joins for the first time here. It works in unit tests but we are not able to get expected results in production. We are still troubleshooting this issue. Can you please help us review this in case we missed something or our assumptions are wrong? SELECT o.region_code, The sequence of events is:
We picked 1 hour time windows because that's the maximum time we expect the successive events to take for a given record chain. The outer GROUP BY is to get 5 minute aggregation for each "region". As expected the watermark lags 2 hour from the current time because of the two time-window joins above. The IdleStateRetentionTime is not set, so the expectation is that the state will be retained as per the time window size and as the records fall off the window the state will be cleaned up. The aggregated state is expected to be kept around for 5 minutes (GROUP BY). However, we are unable to see the conversion (offer_created -> order_requested (without order_cancelled)). 'offer_conversion_5m' is always zero although we know the streams contain records that should have incremented the count. Any idea what could be wrong? Is the state being dropped too early (5 mins) because of the outer 5 minute tumbling window? Thanks, Vinod |
Hi Vinod,
I cannot spot any problems in your SQL query. Some questions for clarification: 1) Which planner are you using? 2) How do you create your watermarks? 3) Did you unit test with only parallelism of 1 or higher? 4) Can you share the output of TableEnvironment.explain() with us? Shouldn't c have a rowtime constraint around o instead of r? Such that all time-based operations work on o.rowtime? Regards, Timo On 10.03.20 19:26, Vinod Mehra wrote: > Hi! > > We are testing the following 3 way time windowed join to keep the > retained state size small. Using joins for the first time here. It works > in unit tests but we are not able to get expected results in production. > We are still troubleshooting this issue. Can you please help us review > this in case we missed something or our assumptions are wrong? > > SELECT o.region_code, > concat_ws( > '/', > CAST(sum(CASE WHEN r.order_idIS NOT NULL AND c.order_idIS NULL THEN 1 ELSE 0 END)AS VARCHAR), > CAST(count(1)AS VARCHAR) > )AS offer_conversion_5m > FROM ( > SELECT region_code, > offer_id, > rowtime > FROM event_offer_created > WHERE ... > ) o > LEFT JOIN ( > SELECT offer_id, > order_id, > rowtime > FROM event_order_requested > WHERE ... > ) r > ON o.offer_id = r.offer_id > AND r.rowtimeBETWEEN o.rowtimeAND o.rowtime +INTERVAL '1' hour > LEFT JOIN ( > SELECT order_id, > rowtime > FROM event_order_cancelled > WHERE ... > )c > ON r.order_id =c.order_id > AND c.rowtimeBETWEEN r.rowtimeAND r.rowtime +INTERVAL '1' hour > GROUP BY > o.region_code, > TUMBLE(o.rowtime,INTERVAL '5' minute) > > > The sequence of events is: > > 1. At time X an offer is created (event stream = "*event_offer_created"*) > 2. At time Y that offer is used to create an order (event stream = > "*event_order_requested*"). Left join because not all offers get used. > 3. At time Z that order is cancelled (event stream = > "*event_order_cancelled*"). Left join because not all orders get > cancelled. > > "*offer_conversion_5m*" represents: number of converted orders / total > number of offerings" in a 5 minutes bucket. If an order gets cancelled > we don't want to count that. That's why we have [c.order_id IS NULL THEN > 1 ELSE 0 END] in the select. > > We picked 1 hour time windows because that's the maximum time we expect > the successive events to take for a given record chain. > > The outer GROUP BY is to get 5 minute aggregation for each "region". As > expected the watermark lags 2 hour from the current time because of the > two time-window joins above. The IdleStateRetentionTime is not set, so > the expectation is that the state will be retained as per the time > window size and as the records fall off the window the state will be > cleaned up. The aggregated state is expected to be kept around for 5 > minutes (GROUP BY). > > However, we are unable to see the conversion (offer_created -> > order_requested (without order_cancelled)). '*offer_conversion_5m*' is > always zero although we know the streams contain records that should > have incremented the count. Any idea what could be wrong? Is the state > being dropped too early (5 mins) because of the outer 5 minute tumbling > window? > > Thanks, > Vinod |
Thanks Timo for responding back! Answers below: > 1) Which planner are you using? We are using Flink 1.8 and using the default planner (org.apache.flink.table.calcite.FlinkPlannerImpl) from: org.apache.flink:flink-table-planner_2.11:1.8 > 2) How do you create your watermarks? We are using periodic watermarking and have configured stream time characteristics as TimeCharacteristic.EventTime. The watermark assigner extracts the timestamp from time attributes from the event and keeps it 5 seconds behind the maximum timestamp seen in order to allow for stale events. > 3) Did you unit test with only parallelism of 1 or higher? I tried both 1 and higher values in tests and for all parallelism values the unit tests works as expected. 4) Can you share the output of TableEnvironment.explain() with us? Attached. Please note that I had obfuscated the query a bit in my original post for clarity. I have pasted the actual query along with the plan so that you can correlate it. > Shouldn't c have a rowtime constraint around o instead of r? Such that all time-based operations work on o.rowtime? I have tried both (and some more variations). Got the same results (unit tests passes but production execution doesn't join as expected). Here is the modified query: SELECT o.region_code, LEFT JOIN ( GROUP BY -- Vinod On Fri, Mar 13, 2020 at 6:42 AM Timo Walther <[hidden email]> wrote: Hi Vinod, explain_plan.txt (19K) Download Attachment |
I wanted to add that when I used the following the watermark was delayed by 3 hours instead of 2 hours that I would have expected: AND o.rowtime BETWEEN c.rowtime - INTERVAL '2' hour AND c.rowtime (time window constraint between o and c: 1st and 3rd table) Thanks,Vinod On Fri, Mar 13, 2020 at 3:56 PM Vinod Mehra <[hidden email]> wrote:
|
In reply to this post by Vinod Mehra
Hi Vinod,
thanks for answering my questions. The == Optimized Logical Plan == looks as expected. However, the == Physical Execution Plan == seems to be quite complex. Are you sure that watermarks don't get lost in some of those custom operators before entering the SQL part of the pipeline? I think if there is a bug in the SQL code base, we would need to come up with a small table program that reproduces the described problem. Such that we can do a remote debugging session. Maybe you can do this in your local cluster? There are basically two runtime operators org.apache.flink.table.runtime.join.RowTimeBoundedStreamJoin and the regular DataStream API windows. I don't expect bugs in DataStream API windows, so I would suggest to verify the join operator. I hope this helps. Regards, Timo On 13.03.20 23:56, Vinod Mehra wrote: > Thanks Timo for responding back! Answers below: > > > 1) Which planner are you using? > > We are using Flink 1.8 and using the default planner > (org.apache.flink.table.calcite.FlinkPlannerImpl) > from: org.apache.flink:flink-table-planner_2.11:1.8 > > > 2) How do you create your watermarks? > > We are using periodic watermarking and have configured stream time > characteristics as TimeCharacteristic.EventTime. The watermark assigner > extracts the timestamp from time attributes from the event and keeps it > 5 seconds behind the maximum timestamp seen in order to allow for stale > events. > > > 3) Did you unit test with only parallelism of 1 or higher? > > I tried both 1 and higher values in tests and for all parallelism values > the unit tests works as expected. > > 4) Can you share the output of TableEnvironment.explain() with us? > > Attached. Please note that I had obfuscated the query a bit in my > original post for clarity. I have pasted the actual query along with the > plan so that you can correlate it. > > > Shouldn't c have a rowtime constraint around o instead of r? Such > that all time-based operations work on o.rowtime? > > I have tried both (and some more variations). Got the same results (unit > tests passes but production execution doesn't join as expected). Here is > the modified query: > > SELECT o.region_code, > concat_ws( > '/', > CAST(sum(CASE WHEN r.order_id IS NOT NULL AND c.order_id IS NULL THEN 1 > ELSE 0 END) AS VARCHAR), > CAST(count(1) AS VARCHAR) > ) AS offer_conversion_5m > FROM ( > SELECT region_code, > offer_id, > rowtime > FROM event_offer_created > WHERE ... > ) o > LEFT JOIN ( > SELECT offer_id, > order_id, > rowtime > FROM event_order_requested > WHERE ... > ) r > ON o.offer_id = r.offer_id > AND o.rowtime BETWEEN r.rowtime - INTERVAL '1' hour AND r.rowtime > > LEFT JOIN ( > SELECT order_id, > rowtime > FROM event_order_cancelled > WHERE ... > ) c > ON r.order_id = c.order_id > AND o.rowtime BETWEEN c.rowtime - INTERVAL '2' hour AND c.rowtime > > GROUP BY > o.region_code, > TUMBLE(o.rowtime,INTERVAL '5' minute) > > > We used minus two hours ("c.rowtime - INTERVAL '2' hour") in the 2nd > time window because it is from the first table and 3rd one. > > -- Vinod > > On Fri, Mar 13, 2020 at 6:42 AM Timo Walther <[hidden email] > <mailto:[hidden email]>> wrote: > > Hi Vinod, > > I cannot spot any problems in your SQL query. > > Some questions for clarification: > 1) Which planner are you using? > 2) How do you create your watermarks? > 3) Did you unit test with only parallelism of 1 or higher? > 4) Can you share the output of TableEnvironment.explain() with us? > > Shouldn't c have a rowtime constraint around o instead of r? Such that > all time-based operations work on o.rowtime? > > Regards, > Timo > > > On 10.03.20 19:26, Vinod Mehra wrote: > > Hi! > > > > We are testing the following 3 way time windowed join to keep the > > retained state size small. Using joins for the first time here. > It works > > in unit tests but we are not able to get expected results in > production. > > We are still troubleshooting this issue. Can you please help us > review > > this in case we missed something or our assumptions are wrong? > > > > SELECT o.region_code, > > concat_ws( > > '/', > > CAST(sum(CASE WHEN r.order_idIS NOT NULL AND > c.order_idIS NULL THEN 1 ELSE 0 END)AS VARCHAR), > > CAST(count(1)AS VARCHAR) > > )AS offer_conversion_5m > > FROM ( > > SELECT region_code, > > offer_id, > > rowtime > > FROM event_offer_created > > WHERE ... > > ) o > > LEFT JOIN ( > > SELECT offer_id, > > order_id, > > rowtime > > FROM event_order_requested > > WHERE ... > > ) r > > ON o.offer_id = r.offer_id > > AND r.rowtimeBETWEEN o.rowtimeAND o.rowtime +INTERVAL '1' hour > > LEFT JOIN ( > > SELECT order_id, > > rowtime > > FROM event_order_cancelled > > WHERE ... > > )c > > ON r.order_id =c.order_id > > AND c.rowtimeBETWEEN r.rowtimeAND r.rowtime +INTERVAL '1' hour > > GROUP BY > > o.region_code, > > TUMBLE(o.rowtime,INTERVAL '5' minute) > > > > > > The sequence of events is: > > > > 1. At time X an offer is created (event stream = > "*event_offer_created"*) > > 2. At time Y that offer is used to create an order (event stream = > > "*event_order_requested*"). Left join because not all offers > get used. > > 3. At time Z that order is cancelled (event stream = > > "*event_order_cancelled*"). Left join because not all orders get > > cancelled. > > > > "*offer_conversion_5m*" represents: number of converted orders / > total > > number of offerings" in a 5 minutes bucket. If an order gets > cancelled > > we don't want to count that. That's why we have [c.order_id IS > NULL THEN > > 1 ELSE 0 END] in the select. > > > > We picked 1 hour time windows because that's the maximum time we > expect > > the successive events to take for a given record chain. > > > > The outer GROUP BY is to get 5 minute aggregation for each > "region". As > > expected the watermark lags 2 hour from the current time because > of the > > two time-window joins above. The IdleStateRetentionTime is not > set, so > > the expectation is that the state will be retained as per the time > > window size and as the records fall off the window the state will be > > cleaned up. The aggregated state is expected to be kept around for 5 > > minutes (GROUP BY). > > > > However, we are unable to see the conversion (offer_created -> > > order_requested (without order_cancelled)). > '*offer_conversion_5m*' is > > always zero although we know the streams contain records that should > > have incremented the count. Any idea what could be wrong? Is the > state > > being dropped too early (5 mins) because of the outer 5 minute > tumbling > > window? > > > > Thanks, > > Vinod > |
Thanks Timo for the suggestion! Also apologies for missing your response last week. I will try to come up with a reproducible test case. On Wed, Mar 18, 2020 at 9:27 AM Timo Walther <[hidden email]> wrote: Hi Vinod, |
Free forum by Nabble | Edit this page |