Flink1.9合并了Blink的代码，也就意味着我们在使用Table API 开发程序的时候，可以选在两种不同的执行计划。

一种是原来的Flink的执行计划。

一种是Blink的执行计划。

截止到1.9的版本，虽然集成了Blink的执行计划，但是并不建议在生产中使用。

Flink的执行计划，统称为OldPlanner

// **********************
// FLINK STREAMING QUERY
// **********************
import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment
import org.apache.flink.table.api.EnvironmentSettings
import org.apache.flink.table.api.scala.StreamTableEnvironment

val fsSettings = EnvironmentSettings.newInstance().useOldPlanner().inStreamingMode().build()
val fsEnv = StreamExecutionEnvironment.getExecutionEnvironment
val fsTableEnv = StreamTableEnvironment.create(fsEnv, fsSettings)
// or val fsTableEnv = TableEnvironment.create(fsSettings)

// ******************
// FLINK BATCH QUERY
// ******************
import org.apache.flink.api.scala.ExecutionEnvironment
import org.apache.flink.table.api.scala.BatchTableEnvironment

val fbEnv = ExecutionEnvironment.getExecutionEnvironment
val fbTableEnv = BatchTableEnvironment.create(fbEnv)

Blink的执行计划，统称BlinkPlanner

// **********************
// BLINK STREAMING QUERY
// **********************
import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment
import org.apache.flink.table.api.EnvironmentSettings
import org.apache.flink.table.api.scala.StreamTableEnvironment

val bsEnv = StreamExecutionEnvironment.getExecutionEnvironment
val bsSettings = EnvironmentSettings.newInstance().useBlinkPlanner().inStreamingMode().build()
val bsTableEnv = StreamTableEnvironment.create(bsEnv, bsSettings)
// or val bsTableEnv = TableEnvironment.create(bsSettings)

// ******************
// BLINK BATCH QUERY
// ******************
import org.apache.flink.table.api.{EnvironmentSettings, TableEnvironment}

val bbSettings = EnvironmentSettings.newInstance().useBlinkPlanner().inBatchMode().build()
val bbTableEnv = TableEnvironment.create(bbSettings)

Flink1.9 TableAPI如何选择执行计划