根据官方文档[1]
来做一些实验吧,代码采用[2]中代码
步骤如下:
① | mvn clean scala:compile compile package |
② | nc -lk 9999 flink run -c wordcount_increstate /home/appleyuchi/桌面/Flink_Code/flink_state/checkpoint/Scala/target/datastream_api-1.0-SNAPSHOT.jar |
提交到集群的时候,会在终端返回一个json
{
"nodes" : [ {
"id" : 1,
"type" : "Source: Socket Stream",
"pact" : "Data Source",
"contents" : "Source: Socket Stream",
"parallelism" : 1
}, {
"id" : 2,
"type" : "Flat Map",
"pact" : "Operator",
"contents" : "Flat Map",
"parallelism" : 2,
"predecessors" : [ {
"id" : 1,
"ship_strategy" : "REBALANCE",
"side" : "second"
} ]
}, {
"id" : 3,
"type" : "Map",
"pact" : "Operator",
"contents" : "Map",
"parallelism" : 2,
"predecessors" : [ {
"id" : 2,
"ship_strategy" : "FORWARD",
"side" : "second"
} ]
}, {
"id" : 4,
"type" : "Map",
"pact" : "Operator",
"contents" : "Map",
"parallelism" : 2,
"predecessors" : [ {
"id" : 3,
"ship_strategy" : "FORWARD",
"side" : "second"
} ]
}, {
"id" : 6,
"type" : "aggregation",
"pact" : "Operator",
"contents" : "aggregation",
"parallelism" : 2,
"predecessors" : [ {
"id" : 4,
"ship_strategy" : "HASH",
"side" : "second"
} ]
}, {
"id" : 7,
"type" : "Sink: Print to Std. Out",
"pact" : "Data Sink",
"contents" : "Sink: Print to Std. Out",
"parallelism" : 2,
"predecessors" : [ {
"id" : 6,
"ship_strategy" : "FORWARD",
"side" : "second"
} ]
} ]
}
把这个json复制到https://flink.apache.org/visualizer/中,即可得到下图:
Reference: