Hi Stephan, Just an update, last week I did a run with state size close to 18GB, I did not observe the pipeline getting stopped in between with G1GC enabled.
I had observed checkpoint failures when the state size was close to 38GB (but in this case G1GC was not enabled) Is it possible to get the RocksDB fix in 1.2.1 so that I can test it out. Regards, Vinay Patil On Sat, Mar 18, 2017 at 12:25 AM, Stephan Ewen [via Apache Flink User Mailing List archive.] <ml-node+s2336050n1227...@n4.nabble.com> wrote: > @vinay Let's see how fast we get this fix in - I hope yes. It may depend > also a bit on the RocksDB community. > > In any case, if it does not make it in, we can do a 1.2.2 release > immediately after (I think the problem is big enough to warrant that), or > at least release a custom version of the RocksDB state backend that > includes the fix. > > Stephan > > > On Fri, Mar 17, 2017 at 5:51 PM, vinay patil <[hidden email] > <http:///user/SendEmail.jtp?type=node&node=12276&i=0>> wrote: > >> Hi Stephan, >> >> Is the performance related change of RocksDB going to be part of Flink >> 1.2.1 ? >> >> Regards, >> Vinay Patil >> >> On Thu, Mar 16, 2017 at 6:13 PM, Stephan Ewen [via Apache Flink User >> Mailing List archive.] <[hidden email] >> <http:///user/SendEmail.jtp?type=node&node=12274&i=0>> wrote: >> >>> The only immediate workaround is to use windows with "reduce" or "fold" >>> or "aggregate" and not "apply". And to not use an evictor. >>> >>> The good news is that I think we have a good way of fixing this soon, >>> making an adjustment in RocksDB. >>> >>> For the Yarn / g1gc question: Not 100% sure about that - you can check >>> if it used g1gc. If not, you may be able to pass this through the >>> "env.java.opts" parameter. (cc robert for confirmation) >>> >>> Stephan >>> >>> >>> >>> On Thu, Mar 16, 2017 at 8:31 AM, vinay patil <[hidden email] >>> <http:///user/SendEmail.jtp?type=node&node=12243&i=0>> wrote: >>> >>>> Hi Stephan, >>>> >>>> What can be the workaround for this ? >>>> >>>> Also need one confirmation : Is G1 GC used by default when running the >>>> pipeline on YARN. (I see a thread of 2015 where G1 is used by default for >>>> JAVA8) >>>> >>>> >>>> >>>> Regards, >>>> Vinay Patil >>>> >>>> On Wed, Mar 15, 2017 at 10:32 PM, Stephan Ewen [via Apache Flink User >>>> Mailing List archive.] <[hidden email] >>>> <http:///user/SendEmail.jtp?type=node&node=12234&i=0>> wrote: >>>> >>>>> Hi Vinay! >>>>> >>>>> Savepoints also call the same problematic RocksDB function, >>>>> unfortunately. >>>>> >>>>> We will have a fix next month. We either (1) get a patched RocksDB >>>>> version or we (2) implement a different pattern for ListState in Flink. >>>>> >>>>> (1) would be the better solution, so we are waiting for a response >>>>> from the RocksDB folks. (2) is always possible if we cannot get a fix from >>>>> RocksDB. >>>>> >>>>> Stephan >>>>> >>>>> >>>>> On Wed, Mar 15, 2017 at 5:53 PM, vinay patil <[hidden email] >>>>> <http:///user/SendEmail.jtp?type=node&node=12225&i=0>> wrote: >>>>> >>>>>> Hi Stephan, >>>>>> >>>>>> Thank you for making me aware of this. >>>>>> >>>>>> Yes I am using a window without reduce function (Apply function). The >>>>>> discussion happening on JIRA is exactly what I am observing, consistent >>>>>> failure of checkpoints after some time and the stream halts. >>>>>> >>>>>> We want to go live in next month, not sure how this will affect in >>>>>> production as we are going to get above 200 million data. >>>>>> >>>>>> As a workaround can I take the savepoint while the pipeline is >>>>>> running ? Let's say if I take savepoint after every 30minutes, will it >>>>>> work >>>>>> ? >>>>>> >>>>>> >>>>>> >>>>>> Regards, >>>>>> Vinay Patil >>>>>> >>>>>> On Tue, Mar 14, 2017 at 10:02 PM, Stephan Ewen [via Apache Flink User >>>>>> Mailing List archive.] <[hidden email] >>>>>> <http:///user/SendEmail.jtp?type=node&node=12224&i=0>> wrote: >>>>>> >>>>>>> The issue in Flink is https://issues.apache.org/j >>>>>>> ira/browse/FLINK-5756 >>>>>>> >>>>>>> On Tue, Mar 14, 2017 at 3:40 PM, Stefan Richter <[hidden email] >>>>>>> <http:///user/SendEmail.jtp?type=node&node=12209&i=0>> wrote: >>>>>>> >>>>>>>> Hi Vinay, >>>>>>>> >>>>>>>> I think the issue is tracked here: https://github.com/faceb >>>>>>>> ook/rocksdb/issues/1988. >>>>>>>> >>>>>>>> Best, >>>>>>>> Stefan >>>>>>>> >>>>>>>> Am 14.03.2017 um 15:31 schrieb Vishnu Viswanath <[hidden email] >>>>>>>> <http:///user/SendEmail.jtp?type=node&node=12209&i=1>>: >>>>>>>> >>>>>>>> Hi Stephan, >>>>>>>> >>>>>>>> Is there a ticket number/link to track this, My job has all the >>>>>>>> conditions you mentioned. >>>>>>>> >>>>>>>> Thanks, >>>>>>>> Vishnu >>>>>>>> >>>>>>>> On Tue, Mar 14, 2017 at 7:13 AM, Stephan Ewen <[hidden email] >>>>>>>> <http:///user/SendEmail.jtp?type=node&node=12209&i=2>> wrote: >>>>>>>> >>>>>>>>> Hi Vinay! >>>>>>>>> >>>>>>>>> We just discovered a bug in RocksDB. The bug affects windows >>>>>>>>> without reduce() or fold(), windows with evictors, and ListState. >>>>>>>>> >>>>>>>>> A certain access pattern in RocksDB starts being so slow after a >>>>>>>>> certain size-per-key that it basically brings down the streaming >>>>>>>>> program >>>>>>>>> and the snapshots. >>>>>>>>> >>>>>>>>> We are reaching out to the RocksDB folks and looking for >>>>>>>>> workarounds in Flink. >>>>>>>>> >>>>>>>>> Greetings, >>>>>>>>> Stephan >>>>>>>>> >>>>>>>>> >>>>>>>>> On Wed, Mar 1, 2017 at 12:10 PM, Stephan Ewen <[hidden email] >>>>>>>>> <http:///user/SendEmail.jtp?type=node&node=12209&i=3>> wrote: >>>>>>>>> >>>>>>>>>> @vinay Can you try to not set the buffer timeout at all? I am >>>>>>>>>> actually not sure what would be the effect of setting it to a >>>>>>>>>> negative >>>>>>>>>> value, that can be a cause of problems... >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> On Mon, Feb 27, 2017 at 7:44 PM, Seth Wiesman <[hidden email] >>>>>>>>>> <http:///user/SendEmail.jtp?type=node&node=12209&i=4>> wrote: >>>>>>>>>> >>>>>>>>>>> Vinay, >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> The bucketing sink performs rename operations during the >>>>>>>>>>> checkpoint and if it tries to rename a file that is not yet >>>>>>>>>>> consistent that >>>>>>>>>>> would cause a FileNotFound exception which would fail the >>>>>>>>>>> checkpoint. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Stephan, >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Currently my aws fork contains some very specific assumptions >>>>>>>>>>> about the pipeline that will in general only hold for my pipeline. >>>>>>>>>>> This is >>>>>>>>>>> because there were still some open questions that I had about how >>>>>>>>>>> to solve >>>>>>>>>>> consistency issues in the general case. I will comment on the Jira >>>>>>>>>>> issue >>>>>>>>>>> with more specific. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Seth Wiesman >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> *From: *vinay patil <[hidden email] >>>>>>>>>>> <http:///user/SendEmail.jtp?type=node&node=12209&i=5>> >>>>>>>>>>> *Reply-To: *"[hidden email] >>>>>>>>>>> <http:///user/SendEmail.jtp?type=node&node=12209&i=6>" <[hidden >>>>>>>>>>> email] <http:///user/SendEmail.jtp?type=node&node=12209&i=7>> >>>>>>>>>>> *Date: *Monday, February 27, 2017 at 1:05 PM >>>>>>>>>>> *To: *"[hidden email] >>>>>>>>>>> <http:///user/SendEmail.jtp?type=node&node=12209&i=8>" <[hidden >>>>>>>>>>> email] <http:///user/SendEmail.jtp?type=node&node=12209&i=9>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> *Subject: *Re: Checkpointing with RocksDB as statebackend >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Hi Seth, >>>>>>>>>>> >>>>>>>>>>> Thank you for your suggestion. >>>>>>>>>>> >>>>>>>>>>> But if the issue is only related to S3, then why does this >>>>>>>>>>> happen when I replace the S3 sink to HDFS as well (for >>>>>>>>>>> checkpointing I am >>>>>>>>>>> using HDFS only ) >>>>>>>>>>> >>>>>>>>>>> Stephan, >>>>>>>>>>> >>>>>>>>>>> Another issue I see is when I set env.setBufferTimeout(-1) , and >>>>>>>>>>> keep the checkpoint interval to 10minutes, I have observed that >>>>>>>>>>> nothing >>>>>>>>>>> gets written to sink (tried with S3 as well as HDFS), atleast I was >>>>>>>>>>> expecting pending files here. >>>>>>>>>>> >>>>>>>>>>> This issue gets worst when checkpointing is disabled as nothing >>>>>>>>>>> is written. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Regards, >>>>>>>>>>> >>>>>>>>>>> Vinay Patil >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> On Mon, Feb 27, 2017 at 10:55 PM, Stephan Ewen [via Apache Flink >>>>>>>>>>> User Mailing List archive.] <[hidden email]> wrote: >>>>>>>>>>> >>>>>>>>>>> Hi Seth! >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Wow, that is an awesome approach. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> We have actually seen these issues as well and we are looking to >>>>>>>>>>> eventually implement our own S3 file system (and circumvent >>>>>>>>>>> Hadoop's S3 >>>>>>>>>>> connector that Flink currently relies on): >>>>>>>>>>> https://issues.apache.org/jira/browse/FLINK-5706 >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Do you think your patch would be a good starting point for that >>>>>>>>>>> and would you be willing to share it? >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> The Amazon AWS SDK for Java is Apache 2 licensed, so that is >>>>>>>>>>> possible to fork officially, if necessary... >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Greetings, >>>>>>>>>>> >>>>>>>>>>> Stephan >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> On Mon, Feb 27, 2017 at 5:15 PM, Seth Wiesman <[hidden email] >>>>>>>>>>> <http://user/SendEmail.jtp?type=node&node=11943&i=0>> wrote: >>>>>>>>>>> >>>>>>>>>>> Just wanted to throw in my 2cts. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> I’ve been running pipelines with similar state size using >>>>>>>>>>> rocksdb which externalize to S3 and bucket to S3. I was getting >>>>>>>>>>> stalls like >>>>>>>>>>> this and ended up tracing the problem to S3 and the bucketing sink. >>>>>>>>>>> The >>>>>>>>>>> solution was two fold: >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> 1) I forked hadoop-aws and have it treat flink as a >>>>>>>>>>> source of truth. Emr uses a dynamodb table to determine if S3 is >>>>>>>>>>> inconsistent. Instead I say that if flink believes that a file >>>>>>>>>>> exists on S3 >>>>>>>>>>> and we don’t see it then I am going to trust that flink is in a >>>>>>>>>>> consistent >>>>>>>>>>> state and S3 is not. In this case, various operations will perform >>>>>>>>>>> a back >>>>>>>>>>> off and retry up to a certain number of times. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> 2) The bucketing sink performs multiple renames over the >>>>>>>>>>> lifetime of a file, occurring when a checkpoint starts and then >>>>>>>>>>> again on >>>>>>>>>>> notification after it completes. Due to S3’s consistency guarantees >>>>>>>>>>> the >>>>>>>>>>> second rename of file can never be assured to work and will >>>>>>>>>>> eventually fail >>>>>>>>>>> either during or after a checkpoint. Because there is no upper >>>>>>>>>>> bound on the >>>>>>>>>>> time it will take for a file on S3 to become consistent, retries >>>>>>>>>>> cannot >>>>>>>>>>> solve this specific problem as it could take upwards of many >>>>>>>>>>> minutes to >>>>>>>>>>> rename which would stall the entire pipeline. The only viable >>>>>>>>>>> solution I >>>>>>>>>>> could find was to write a custom sink which understands S3. Each >>>>>>>>>>> writer >>>>>>>>>>> will write file locally and then copy it to S3 on checkpoint. By >>>>>>>>>>> only >>>>>>>>>>> interacting with S3 once per file it can circumvent consistency >>>>>>>>>>> issues all >>>>>>>>>>> together. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Hope this helps, >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Seth Wiesman >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> *From: *vinay patil <[hidden email] >>>>>>>>>>> <http://user/SendEmail.jtp?type=node&node=11943&i=1>> >>>>>>>>>>> *Reply-To: *"[hidden email] >>>>>>>>>>> <http://user/SendEmail.jtp?type=node&node=11943&i=2>" <[hidden >>>>>>>>>>> email] <http://user/SendEmail.jtp?type=node&node=11943&i=3>> >>>>>>>>>>> *Date: *Saturday, February 25, 2017 at 10:50 AM >>>>>>>>>>> *To: *"[hidden email] >>>>>>>>>>> <http://user/SendEmail.jtp?type=node&node=11943&i=4>" <[hidden >>>>>>>>>>> email] <http://user/SendEmail.jtp?type=node&node=11943&i=5>> >>>>>>>>>>> *Subject: *Re: Checkpointing with RocksDB as statebackend >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> HI Stephan, >>>>>>>>>>> >>>>>>>>>>> Just to avoid the confusion here, I am using S3 sink for writing >>>>>>>>>>> the data, and using HDFS for storing checkpoints. >>>>>>>>>>> >>>>>>>>>>> There are 2 core nodes (HDFS) and two task nodes on EMR >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> I replaced s3 sink with HDFS for writing data in my last test. >>>>>>>>>>> >>>>>>>>>>> Let's say the checkpoint interval is 5 minutes, now within >>>>>>>>>>> 5minutes of run the state size grows to 30GB , after checkpointing >>>>>>>>>>> the >>>>>>>>>>> 30GB state that is maintained in rocksDB has to be copied to HDFS, >>>>>>>>>>> right ? >>>>>>>>>>> is this causing the pipeline to stall ? >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Regards, >>>>>>>>>>> >>>>>>>>>>> Vinay Patil >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> On Sat, Feb 25, 2017 at 12:22 AM, Vinay Patil <[hidden email]> >>>>>>>>>>> wrote: >>>>>>>>>>> >>>>>>>>>>> Hi Stephan, >>>>>>>>>>> >>>>>>>>>>> To verify if S3 is making teh pipeline stall, I have replaced >>>>>>>>>>> the S3 sink with HDFS and kept minimum pause between checkpoints to >>>>>>>>>>> 5minutes, still I see the same issue with checkpoints getting >>>>>>>>>>> failed. >>>>>>>>>>> >>>>>>>>>>> If I keep the pause time to 20 seconds, all checkpoints are >>>>>>>>>>> completed , however there is a hit in overall throughput. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Regards, >>>>>>>>>>> >>>>>>>>>>> Vinay Patil >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> On Fri, Feb 24, 2017 at 10:09 PM, Stephan Ewen [via Apache Flink >>>>>>>>>>> User Mailing List archive.] <[hidden email]> wrote: >>>>>>>>>>> >>>>>>>>>>> Flink's state backends currently do a good number of "make sure >>>>>>>>>>> this exists" operations on the file systems. Through Hadoop's S3 >>>>>>>>>>> filesystem, that translates to S3 bucket list operations, where >>>>>>>>>>> there is a >>>>>>>>>>> limit in how many operation may happen per time interval. After >>>>>>>>>>> that, S3 >>>>>>>>>>> blocks. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> It seems that operations that are totally cheap on HDFS are >>>>>>>>>>> hellishly expensive (and limited) on S3. It may be that you are >>>>>>>>>>> affected by >>>>>>>>>>> that. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> We are gradually trying to improve the behavior there and be >>>>>>>>>>> more S3 aware. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Both 1.3-SNAPSHOT and 1.2-SNAPSHOT already contain improvements >>>>>>>>>>> there. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Best, >>>>>>>>>>> >>>>>>>>>>> Stephan >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> On Fri, Feb 24, 2017 at 4:42 PM, vinay patil <[hidden email] >>>>>>>>>>> <http://user/SendEmail.jtp?type=node&node=11891&i=0>> wrote: >>>>>>>>>>> >>>>>>>>>>> Hi Stephan, >>>>>>>>>>> >>>>>>>>>>> So do you mean that S3 is causing the stall , as I have >>>>>>>>>>> mentioned in my previous mail, I could not see any progress for >>>>>>>>>>> 16minutes >>>>>>>>>>> as checkpoints were getting failed continuously. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> On Feb 24, 2017 8:30 PM, "Stephan Ewen [via Apache Flink User >>>>>>>>>>> Mailing List archive.]" <[hidden email] >>>>>>>>>>> <http://user/SendEmail.jtp?type=node&node=11887&i=0>> wrote: >>>>>>>>>>> >>>>>>>>>>> Hi Vinay! >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> True, the operator state (like Kafka) is currently not >>>>>>>>>>> asynchronously checkpointed. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> While it is rather small state, we have seen before that on S3 >>>>>>>>>>> it can cause trouble, because S3 frequently stalls uploads of even >>>>>>>>>>> data >>>>>>>>>>> amounts as low as kilobytes due to its throttling policies. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> That would be a super important fix to add! >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Best, >>>>>>>>>>> >>>>>>>>>>> Stephan >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> On Fri, Feb 24, 2017 at 2:58 PM, vinay patil <[hidden email] >>>>>>>>>>> <http://user/SendEmail.jtp?type=node&node=11885&i=0>> wrote: >>>>>>>>>>> >>>>>>>>>>> Hi, >>>>>>>>>>> >>>>>>>>>>> I have attached a snapshot for reference: >>>>>>>>>>> As you can see all the 3 checkpointins failed , for checkpoint >>>>>>>>>>> ID 2 and 3 it >>>>>>>>>>> is stuck at the Kafka source after 50% >>>>>>>>>>> (The data sent till now by Kafka source 1 is 65GB and sent by >>>>>>>>>>> source 2 is >>>>>>>>>>> 15GB ) >>>>>>>>>>> >>>>>>>>>>> Within 10minutes 15M records were processed, and for the next >>>>>>>>>>> 16minutes the >>>>>>>>>>> pipeline is stuck , I don't see any progress beyond 15M because >>>>>>>>>>> of >>>>>>>>>>> checkpoints getting failed consistently. >>>>>>>>>>> >>>>>>>>>>> <http://apache-flink-user-mailing-list-archive.2336050.n4.na >>>>>>>>>>> bble.com/file/n11882/Checkpointing_Failed.png> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> -- >>>>>>>>>>> View this message in context: http://apache-flink-user-maili >>>>>>>>>>> ng-list-archive.2336050.n4.nabble.com/Re-Checkpointing-with- >>>>>>>>>>> RocksDB-as-statebackend-tp11752p11882.html 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