回复：回复：Transfer information from one window to the next

[施晓罡(星罡)]

Hi Sonex
All windows under the same key (e.g., TimeWindow(0, 3600) and TimeWindow(3600, 
7200)) will be processed by the flatmap function. You can put the variable 
drawn from TimeWindow(0, 3600) into a State. When you receive TimeWindow(3600, 
7200), you can access the state and apply the function with the obtained 
variable.
Regards,Xiaogang
--发件人：Sonex 
发送时间：2017年2月20日(星期一) 19:54收件人：user 
主　题：Re: 回复：Transfer information from one window to the 
next
I don`t think you understood the question correctly. I do not care about
information between windows at the same time (i.e., start of window = 0, end
of window 3600). I want to pass a variable, let`s say for key 1, from the
apply function of window 0-3600 to the apply function of window 3600-7200,
for key 1.



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回复：Transfer information from one window to the next

[施晓罡(星罡)]

Hi sonex
I think you can accomplish it by using a PassThroughFunction as the apply 
function and processing the elements in a rich flatMap function followed.  You 
can keep the information in the flatmap function (via states) so that they can 
be shared among different windows.
The program may look like
stream.keyBy(...).timeWindow(...)    .apply(new WindowFunction() {        
public void apply(K key, W window, Iterable elements, Collector out) { 
           out.collect(new Tuple3<>(key, window, elements);    })    .keyBy(0)  
  // use the same key as the windows    .flatMap(...) // process the windows 
with shared information
Regards,Xiaogang

--发件人：Sonex 
发送时间：2017年2月20日(星期一) 16:32收件人：user 
主　题：Transfer information from one window to the next
val stream =
inputStream.assignAscendingTimestamps(_.eventTime).keyBy(_.inputKey).timeWindow(Time.seconds(3600),Time.seconds(3600))

stream.apply{...}

Given the above example I want to transfer information (variables and
values) from the current apply function to the apply function of the next
window (of course with the same key).

How can I do that?



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回复：Checkpointing with RocksDB as statebackend

[施晓罡(星罡)]

Hi Vinay
Can you provide the LOG file in RocksDB? It helps a lot to figure out the 
problems becuse it records the options and the events happened during the 
execution. Otherwise configured, it should locate at the path set in 
System.getProperty("java.io.tmpdir"). 
Typically, a large amount of memory is consumed by RocksDB to store necessary 
indices. To avoid the unlimited growth in the memory consumption, you can put 
these indices into block cache (set CacheIndexAndFilterBlock to true) and 
properly set the block cache size. 
You can also increase the number of backgroud threads to improve the 
performance of flushes and compactions (via MaxBackgroundFlushes and 
MaxBackgroudCompactions).
In YARN clusters, task managers will be killed if their memory utilization 
exceeds the allocation size. Currently Flink does not count the memory used by 
RocksDB in the allocation. We are working on fine-grained resource allocation 
(see FLINK-5131). It may help to avoid such problems.
May the information helps you.
Regards,Xiaogang

--发件人：Vinay 
Patil 发送时间：2017年2月17日(星期五) 21:19收件人：user 
主　题：Re: Checkpointing with RocksDB as statebackend
Hi Guys,

There seems to be some issue with RocksDB memory utilization.

Within few minutes of job run the physical memory usage increases by 4-5 GB and 
it keeps on increasing.
I have tried different options for Max Buffer Size(30MB, 64MB, 128MB , 512MB) 
and Min Buffer to Merge as 2, but the physical memory keeps on increasing.

According to RocksDB documentation, these are the main options on which 
flushing to storage is based.

Can you please point me where am I doing wrong. I have tried different 
configuration options but each time the Task Manager is getting killed after 
some time :)
Regards,Vinay Patil

On Thu, Feb 16, 2017 at 6:02 PM, Vinay Patil  wrote:
I think its more of related to RocksDB, I am also not aware about RocksDB but 
reading the tuning guide to understand the important values that can be set
Regards,Vinay Patil

On Thu, Feb 16, 2017 at 5:48 PM, Stefan Richter [via Apache Flink User Mailing 
List archive.]  wrote:


What kind of problem are we talking about? S3 related or RocksDB 
related. I am not aware of problems with RocksDB per se. I think seeing logs 
for this would be very helpful.
Am 16.02.2017 um 11:56 schrieb Aljoscha Krettek <[hidden email]>:
[hidden email] and [hidden email] could this be the same problem that you 
recently saw when working with other people?

On Wed, 15 Feb 2017 at 17:23 Vinay Patil <[hidden email]> wrote:
Hi Guys,

Can anyone please help me with this issue
Regards,Vinay Patil

On Wed, Feb 15, 2017 at 6:17 PM, Vinay Patil <[hidden email]> wrote:
Hi Ted,

I have 3 boxes in my pipeline , 1st and 2nd box containing source and s3 sink 
and the 3rd box is window operator followed by chained operators and a s3 sink

So in the details link section I can see that that S3 sink is taking time for 
the acknowledgement and it is not even going to the window operator chain.

But as shown in the snapshot ,checkpoint id 19 did not get any acknowledgement. 
Not sure what is causing the issue
Regards,Vinay Patil

On Wed, Feb 15, 2017 at 5:51 PM, Ted Yu [via Apache Flink User Mailing List 
archive.] <[hidden email]> wrote:


What did the More Details link say ?


Thanks 


> On Feb 15, 2017, at 3:11 AM, vinay patil <[hidden email]> wrote:

> 

> Hi,

> 

> I have kept the checkpointing interval to 6secs and minimum pause between

> checkpoints to 5secs, while testing the pipeline I have observed that that

> for some checkpoints it is taking long time , as you can see in the attached

> snapshot checkpoint id 19 took the maximum time before it gets failed,

> although it has not received any acknowledgements, now during this 10minutes

> the entire pipeline did not make any progress and no data was getting

> processed. (For Ex : In 13minutes 20M records were processed and when the

> checkpoint took time there was no progress for the next 10minutes)

> 

> I have even tried to set max checkpoint timeout to 3min, but in that case as

> well multiple checkpoints were getting failed.

> 

> I have set RocksDB FLASH_SSD_OPTION 

> What could be the issue ? 

> 

> P.S. I am writing to 3 S3 sinks 

> 

> checkpointing_issue.PNG
> 
>   

> 

> 

> 

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