只需使用自定义项！
https://ci.apache.org/projects/flink/flink-docs-stable/dev/table/udfs.html
示例用法 test.csvcreation_date|key 1535816823|1 1536392928|2 1536272308|3EpochTimeConverter.scala ```
import java.time.format.DateTimeFormatter
import java.time.{Instant, LocalDateTime, ZoneId}

import org.apache.flink.table.functions.ScalarFunction

class EpochTimeConverter extends ScalarFunction {
def eval(epochTime: Int): String = {
// For performance, you may cache DateTimeFormatter in real life
val timePattern = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss")
timePattern.format(LocalDateTime.ofInstant(Instant.ofEpochSecond(epochTime), ZoneId.systemDefault()))
}
}
`UdfExample.scala`
import org.apache.flink.api.scala.{ExecutionEnvironment, }
import org.apache.flink.table.api.scala.
import org.apache.flink.table.api.{TableEnvironment, Types}
import org.apache.flink.table.sources.CsvTableSource
import org.apache.flink.types.Row

object UdfExample {
def main(args: Array[String]): Unit = {
val env = ExecutionEnvironment.getExecutionEnvironment
val tableEnv = TableEnvironment.getTableEnvironment(env)
val csvData = CsvTableSource
.builder()
.path("test.csv")
.ignoreFirstLine()
.fieldDelimiter("|")
.field("creation_date", Types.INT)
.field("key", Types.INT)
.build()

tableEnv.registerTableSource("temp_table", csvData)

println("Without udf:")
tableEnv.sqlQuery("SELECT creation_date, key FROM temp_table").toDataSet[Row].print()

tableEnv.registerFunction("from_unixtime", new EpochTimeConverter())

println()
println("With udf:")
tableEnv.sqlQuery("select from_unixtime(creation_date),key from temp_table").toDataSet[Row].print()

}
}

如果你跑了 `UdfExample.scala` ，它将产生类似的输出，如下所示：

Without udf:
1535816823,1
1536272308,3
1536392928,2

With udf:
2018-09-01 18:47:03,1
2018-09-07 01:18:28,3
2018-09-08 10:48:48,2

我想你在找 DATE_FORMAT(timestamp, '%Y-%m-%d %H:%i:%s') .
有关详细信息，请参阅有关内置函数和日期格式说明符的文档。