Hi Vishaws,
With "from scratch", Congxian means that Flink won't load any state automatically and starts as if there was no state. Of course if the kafka consumer group already exists and you have configured Flink to start from group offsets if there is no state yet, it will start from the group offsets.
I think your approach is totally fine. Ignoring savepoints and don't retaining checkpoints saves overhead and configuration burdens and works nicely as long as you don't have any state in your pipeline.
You should however be certain that nobody in your team will add something with state later on and forgets to think about the missing state...
Best regards
Theo
-------- Ursprüngliche Nachricht --------
Betreff: Re: Flink restoring a job from a checkpoint
Von: Vishwas Siravara
An: Congxian Qiu
Cc: Yun Tang
Hi Congxian,Thanks for getting back. Why would the streaming start from scratch if my consumer group does not change ? I start from the group offsets : env.addSource(consumer.setStartFromGroupOffsets()).name(source + "- kafka source")So when I restart the job it should consume from the last committed offset to kafka isn't it ? Let me know what you think .Best,VishwasOn Tue, Oct 8, 2019 at 9:06 PM Congxian Qiu <qcx978132...@gmail.com> wrote:Hi VishwasCurrently, Flink can only restore retained checkpoint or savepoint with parameter `-s`[1][2], otherwise, it will start from scratch.```checkpoint ---> bin/flink run -s :checkpointMetaDataPath [:runArgs]savepoint -->bin/flink run -s :savepointPath [:runArgs]Vishwas Siravara <vsirav...@gmail.com> 于2019年10月9日周三 上午5:07写道：Hi Yun,Thanks for your reply. I do start from GROUP_OFFSET . Here is the code snippet :env.addSource(consumer.setStartFromGroupOffsets()).name(source + "- kafka source")I have also enabled and externalized checkpointing to S3 .Why is it not recommended to just restart the job once I cancel it, as long as the topology does not change? What is the advantage of explicitly restoring from last checkpoint by passing the -s option to the flink command line if it does the same thing? For instance if s3://featuretoolkit.checkpoints/qa_streaming/c17f2cb6da5e6cbc897410fe49676edd/chk-1350/ is my last successful checkpoint, what is the difference between 1 and 2.1. /usr/mware/flink/bin/flink run -d -C file:///usr/mware/flink/externalconfig/ -c com.visa.flink.cli.Main flink-job-assembly.jar flink druid -p 8 -cp qa_streaming 2. /usr/mware/flink/bin/flink run -s s3://featuretoolkit.checkpoints/qa_streaming/c17f2cb6da5e6cbc897410fe49676edd/chk-1350/ -d -C file:///usr/mware/flink/externalconfig/ -c com.visa.flink.cli.Main flink-job-assembly.jar flink druid -p 4 -cp qa_streamingThanks,VishwasOn Tue, Oct 8, 2019 at 1:51 PM Yun Tang <myas...@live.com> wrote:Hi Vishwas
If you did not configure your org.apache.flink.streaming.connectors.kafka.config.StartupMode, it is GROUP_OFFSET by default, which means "Start from committed offsets in ZK / Kafka brokers of a specific consumer group". And you need to enable checkpoint so that kafka offsets are committed when checkpoint completes.
In other words, even if you don't resume from checkpoint, just enable checkpoint in previous jobs and set startupMode as GROUP_OFFSET, you could restore from last committed offset if previous checkpoint completed [1][2]. However, this is not really recommended, better to resume from last checkpoint [3]
BestYun Tang
From: Vishwas Siravara <vsirav...@gmail.com>
Sent: Wednesday, October 9, 2019 0:54
To: user <user@flink.apache.org>
Subject: Flink restoring a job from a checkpointHi guys,
I have a flink streaming job which streams from a kafka source. There is no state in the job, just a simple filter , map and write to a kafka sink. Suppose I stop my job and then submit the job again to the cluster with the same consumer group, will the job restore automatically from the last successful checkpoint , since this is what is the last committed offset to kafka ?
Thanks,Vishwas
