I looked at your example and the custom logic for the singleton is
basically:
static transient T value;
public static synchronized getOrCreate(...) {
if (value == null) {
... instantiate value ...
}
return value;
}
Which is only a few lines. You could use one of Java's injection framewo
I'm interested in this area too. One limitation I guess is that this
assumes your runner is going to be single JVM if you need your singletons
to be globally unique. I'm mostly using DirectRunner (I'm still new to all
this) for which this holds. I suppose for more distributed runners this
would
Yes, the task manager has one task slot per CPU core available, and the
dashboard shows that the work is parallelized across multiple subtasks.
However when using parallelism, the pipeline stalls, the Task Manager
starts throwing 'Output channel stalled' warnings, and high back pressure
is created
If you are using only a single task manager but want to get parallelism >
1, you will need to increase taskmanager.numberOfTaskSlots in
your flink-conf.yaml.
https://ci.apache.org/projects/flink/flink-docs-stable/internals/job_scheduling.html#scheduling
On Thu, Apr 30, 2020 at 8:19 AM Robbe Sneyde
Beam Java users,
I've run into a few cases where I want to present a single thread-safe data
structure to all threads on a worker, and I end up writing a good bit of
custom code each time involving a synchronized method that handles creating
the resource exactly once, and then each thread has its
Thank you Rahul
From: [gmail.com] rahul patwari
Sent: Tuesday, April 28, 2020 4:21 PM
To: user
Subject: Re: HCatalogIO - Trying to read table metadata (columns names and
indexes)
Hi Noam,
Currently, Beam doesn't support conversion of HCatRecords to Rows (or) in your
case creating Beam Schema
Hi Kyle,
Thanks for the quick response.
The problem was that the pipeline could not access the input file. The Task
Manager errors seem unrelated indeed.
I'm now able to run the pipeline completely, but I'm running into problems
when using parallelism.
The pipeline can be summarized as:
read file
Hey Steve,
The checkpoint buffer is cleared "lazily" when a new bundle is started.
Theoretically, if no more data was to arrive after a checkpoint, then
this buffer would not be cleared until more data arrived. If this
repeats every time new data comes in, then always some data would remain
buffer
