It should only apply to the map operator.
On 19.09.2017 17:38, AndreaKinn wrote:
If I apply a sharing slot as in the example:
DataStream LTzAccStream = env
.addSource(new FlinkKafkaConsumer010<>("topic",
new
CustomDeserializer(), properties))
If I apply a sharing slot as in the example:
DataStream LTzAccStream = env
.addSource(new FlinkKafkaConsumer010<>("topic",
new
CustomDeserializer(), properties))
.assignTimestampsAndWatermarks(new
CustomTimestampExtractor())
There is no notion of "full" in Flink except that one slot will run at most
one subtask of each operator.
The scheduling depends on the structure of the job, the parallelism of the
operators, and the number of slots per TM.
It's hard to tell without knowing the details.
2017-09-19 11:57
So Flink use the other nodes just if one is completely "full" ?
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Hi,
I'm experimenting a bit with the cluster.
I didn't set any options about sharing slots and chains hoping that Flink
decided autonomously how to balance the load through the nodes of the
cluster. My cluster is composed by one job and task manager and two task
manager.
I noted that every time
