按照两位的方法修改后已经可以了，谢谢两位
> 在 2019年8月26日，12:28，Jark Wu <imj...@gmail.com> 写道：
>
> Hi,
>
> 关于 Expression的问题，你需要额外加入 import org.apache.flink.table.api._ 的 import。
>
> See release note for more details:
> https://ci.apache.org/projects/flink/flink-docs-release-1.9/release-notes/flink-1.9.html#scala-expression-dsl-for-table-api-moved-to-flink-table-api-scala
>
> <https://ci.apache.org/projects/flink/flink-docs-release-1.9/release-notes/flink-1.9.html#scala-expression-dsl-for-table-api-moved-to-flink-table-api-scala>
>
>> 在 2019年8月26日，11:53，Zili Chen <wander4...@gmail.com> 写道：
>>
>> 不应该呀，我看到仍然有
>>
>> def registerDataStream[T](name: String, dataStream: DataStream[T], fields:
>> Expression*): Unit
>>
>> 这个方法的，你能提供完整一点的上下文和报错吗？
>>
>> Best,
>> tison.
>>
>>
>> ddwcg <3149768...@qq.com <mailto:3149768...@qq.com>> 于2019年8月26日周一 上午11:38写道：
>> 感谢您的回复，确实是这个原因。但是后面注册表的时候不能使用 Expression
>> 总是感觉 java api 和scala api有点混乱了
>>
>>
>>
>>> 在 2019年8月26日，11:22，Zili Chen <wander4...@gmail.com
>>> <mailto:wander4...@gmail.com>> 写道：
>>>
>>> 试试把
>>>
>>> import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment
>>>
>>> 换成
>>>
>>> import org.apache.flink.table.api.scala.StreamExecutionEnvironment
>>>
>>> 应该是意外 import 了不同包下的同名类的缘故
>>>
>>> Best,
>>> tison.
>>>
>>>
>>> ddwcg <3149768...@qq.com <mailto:3149768...@qq.com>> 于2019年8月26日周一
>>> 上午11:12写道：
>>>
>>>> 大家好，
>>>> 我周末升级到了1.9.0，但是在初始化table env的时候编译不通过，请大家帮忙看看是什么原因，
>>>>
>>>> import org.apache.flink.streaming.api.CheckpointingMode
>>>> import
>>>> org.apache.flink.streaming.api.environment.CheckpointConfig.ExternalizedCheckpointCleanup
>>>> import
>>>> org.apache.flink.streaming.api.environment.StreamExecutionEnvironment
>>>> import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer
>>>> import org.apache.flink.streaming.util.serialization.SimpleStringSchema
>>>> import org.apache.flink.table.api.scala.StreamTableEnvironment
>>>> import org.apache.flink.table.planner.expressions.StddevPop
>>>> import org.apache.kafka.clients.consumer.ConsumerConfig
>>>> import org.apache.kafka.clients.producer.ProducerConfig
>>>>
>>>> object StreamingJob {
>>>> def main(args: Array[String]) {
>>>> val kafkaTopic = "source.kafka.topic"
>>>> val jobName ="test"
>>>> val parallelism =1
>>>> val checkPointPath ="checkpoint/"
>>>> val kafkaBrokers =""
>>>>
>>>> // set up the streaming execution environment
>>>> val env = StreamExecutionEnvironment.getExecutionEnvironment
>>>> env.setParallelism(parallelism)
>>>> env.enableCheckpointing(10000)
>>>>
>>>> env.getCheckpointConfig.setCheckpointingMode(CheckpointingMode.EXACTLY_ONCE)
>>>> env.getCheckpointConfig.setMaxConcurrentCheckpoints(1)
>>>>
>>>> env.getCheckpointConfig.enableExternalizedCheckpoints(ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION)
>>>> //env.setStateBackend(new FsStateBackend(checkPointPath))
>>>>
>>>>
>>>> val tableEnv = StreamTableEnvironment.create(env)
>>>>
>>>>
>>>> 提示有多个实现：
>>>>
>>>> 下面是pom文件：
>>>>
>>>> <dependency>
>>>> <groupId>org.apache.flink</groupId>
>>>> <artifactId>flink-scala_${scala.binary.version}</artifactId>
>>>> <version>${flink.version}</version>
>>>> <scope>compile</scope>
>>>> </dependency>
>>>> <dependency>
>>>> <groupId>org.apache.flink</groupId>
>>>> <artifactId>flink-streaming-scala_${scala.binary.version}</artifactId>
>>>> <version>${flink.version}</version>
>>>> <scope>compile</scope>
>>>> </dependency>
>>>> <dependency>
>>>> <groupId>org.apache.flink</groupId>
>>>> <artifactId>flink-table-planner-blink_${scala.binary.version}</artifactId>
>>>> <version>${flink.version}</version>
>>>> <scope>provided</scope>
>>>> </dependency>
>>>> <!--
>>>> https://mvnrepository.com/artifact/org.apache.flink/flink-table-runtime-blink
>>>>
>>>> <https://mvnrepository.com/artifact/org.apache.flink/flink-table-runtime-blink>
>>>> -->
>>>> <dependency>
>>>> <groupId>org.apache.flink</groupId>
>>>> <artifactId>flink-table-runtime-blink_2.11</artifactId>
>>>> <version>1.9.0</version>
>>>> </dependency>
>>>> <dependency>
>>>> <groupId>org.apache.flink</groupId>
>>>> <artifactId>flink-connector-kafka_2.11</artifactId>
>>>> <version>1.9.0</version>
>>>> </dependency>
>>>> <dependency>
>>>> <groupId>org.apache.flink</groupId>
>>>> <artifactId>flink-table-common</artifactId>
>>>> <version>${flink.version}</version>
>>>> <scope>provided</scope>
>>>> </dependency>
>>>>
>>>>
>>>>
>>>>
>>
>
