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 <se...@apache.org> 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 <se...@apache.org> 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 <swies...@mediamath.com> >> 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 <vinay18.pa...@gmail.com> >>> *Reply-To: *"user@flink.apache.org" <user@flink.apache.org> >>> *Date: *Monday, February 27, 2017 at 1:05 PM >>> *To: *"user@flink.apache.org" <user@flink.apache.org> >>> >>> *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. >>> >>> >>> >>> >>> ------------------------------ >>> >>> *If you reply to this email, your message will be added to the >>> discussion below:* >>> >>> http://apache-flink-user-mailing-list-archive.2336050.n4.nab >>> ble.com/Re-Checkpointing-with-RocksDB-as-statebackend-tp11752p11885.html >>> >>> To start a new topic under Apache Flink User Mailing List archive., >>> email [hidden email] >>> <http://user/SendEmail.jtp?type=node&node=11887&i=1> >>> To unsubscribe from Apache Flink User Mailing List archive., click here. >>> NAML >>> 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