@ Stephan, I am not using explicit Evictor in my code. I will try using the Fold function if it does not break my existing functionality :)
@Robert : Thank you for your answer, yes I have already tried to set G1GC this morning using env.java.opts, it works. Which is the recommended GC for Streaming application (running on YARN - EMR ) ? Regards, Vinay Patil On Thu, Mar 16, 2017 at 6:36 PM, rmetzger0 [via Apache Flink User Mailing List archive.] <ml-node+s2336050n12244...@n4.nabble.com> wrote: > Yes, you can change the GC using the env.java.opts parameter. > We are not setting any GC on YARN. > > On Thu, Mar 16, 2017 at 1:50 PM, Stephan Ewen <[hidden email] > <http:///user/SendEmail.jtp?type=node&node=12244&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=12244&i=1>> 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 >>>>>>>>>> >>>>>>>>>> Sent from the Apache Flink User Mailing List archive. mailing >>>>>>>>>> list archive at Nabble.com. >>>>>>>>>> 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