Increasing Disk Read Throughput and IOPS

Hi All, We are running flink in AWS and we are observing a strange behavior. We are using docker containers, EBS for storage and Rocks DB state backend. We have a few map and value states with checkpointing every 30 seconds and incremental checkpointing turned on. The issue we are noticing is the

Too many open files

Hi, We have a streaming job that runs on flink in docker and checkpointing happens every 10 seconds. After several starts and cancellations we are facing this issue with file handles. The job reads data from kafka, processes it and writes it back to kafka and we are using RocksDB state backend.

Connect more than two streams

Hi, I have two streams reading from kafka, one for data and other for control. The data stream is split by type and there are around six types. Each type has its own processing logic and finally everything has to be merged to get the collective state per device. I was thinking I could connect

Streaming Exception

Hi All, I see the below error after running my streaming job for a while and when the load increases. After a while the task manager becomes completely dead and the job keeps on restarting. Also when I checked if there is an back pressure in the UI, it kept on saying sampling in progress and no

Re: ElasticsearchSink Exception

flink', name: 'flink-connector-elasticsearch2_2.10', version: '1.2.0' On Sat, Feb 25, 2017 at 1:26 AM, Flavio Pompermaier <pomperma...@okkam.it> wrote: > Are you sure that in elasticsearch.yml you've enabled ES to listen to the > http port 9300? > > On 25 Feb 2017

ElasticsearchSink Exception

Hi All, I'm getting the below exception when I start my flink job. I have verified the elastic search host and it seems to be working well. I have also tried including the below dependecies to my project but nothing works. Need some help. Thanks. compile group: 'org.apache.lucene', name:

Flink Job Exception

Hi All, I'm trying to run a streaming job with flink 1.2 version and there are 3 task managers with 12 task slots. Irrespective of the parallelism that I give it always fails with the below error and I found a JIRA link corresponding to this issue. Can I know by when this will be resolved since

Re: Dynamic Scaling

Hi All, It would great if someone can help me with my questions. Appreciate all the help. Thanks. > On Dec 23, 2016, at 12:11 PM, Govindarajan Srinivasaraghavan > <govindragh...@gmail.com> wrote: > > Hi, > > We have a computation heavy streaming flink job which will

Stream Iterations

Hi All, I have a use case for which I need some suggestions. It's a streaming application with kafka source and then groupBy, keyBy and perform some calculations. The output of each calculation has to be a side input for the next calculation and also it needs to be sent to a sink. Right now I'm

Flink Metrics

Hi, I am currently using flink 1.2 snapshot and instrumenting my pipeline with flink metrics. One small suggestion I have is currently the Meter interface only supports getRate() which is always the one minute rate. It would great if all the rates (1 min, 5 min & 15 min) are exposed to get a

Using Flink

Hi, I have few questions on how I need to model my use case in flink. Please advise. Thanks for the help. - I'm currently running my flink program on 1.2 SNAPSHOT with kafka source and I have checkpoint enabled. When I look at the consumer offsets in kafka it appears to be stagnant and there

Re: Flink: How to handle external app configuration changes in flink

; and will end up building the same state. For example: > > val dataStream = env.addSource(dataSource).keyBy("userId")val > filterStream = env.addSource(filterSource).broadcast() > val connectedStream = dataStream > .connect(filterStream) > .flatMap(yourFilterFuncti

Flink: How to handle external app configuration changes in flink

Hi, My requirement is to stream millions of records in a day and it has huge dependency on external configuration parameters. For example, a user can go and change the required setting anytime in the web application and after the change is made, the streaming has to happen with the new

Questions on flink

Hi, I'm working on apache flink for data streaming and I have few questions. Any help is greatly appreciated. Thanks. 1) Are there any restrictions on creating tumbling windows. For example, if I want to create a tumbling window per user id for 2 secs and let’s say if I have more than 10 million