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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-6196) Support dynamic schema in Table Function
Date Fri, 21 Apr 2017 13:04:04 GMT

    [ https://issues.apache.org/jira/browse/FLINK-6196?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15978695#comment-15978695
] 

ASF GitHub Bot commented on FLINK-6196:
---------------------------------------

Github user fhueske commented on a diff in the pull request:

    https://github.com/apache/flink/pull/3623#discussion_r112679780
  
    --- Diff: flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/schema/DeferredTypeFlinkTableFunction.scala
---
    @@ -0,0 +1,68 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one
    + * or more contributor license agreements.  See the NOTICE file
    + * distributed with this work for additional information
    + * regarding copyright ownership.  The ASF licenses this file
    + * to you under the Apache License, Version 2.0 (the
    + * "License"); you may not use this file except in compliance
    + * with the License.  You may obtain a copy of the License at
    + *
    + *     http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.flink.table.plan.schema
    +
    +import java.lang.reflect.Method
    +import java.util
    +
    +import org.apache.calcite.rel.`type`.{RelDataType, RelDataTypeFactory}
    +import org.apache.flink.api.common.typeinfo.TypeInformation
    +import org.apache.flink.table.functions.utils.UserDefinedFunctionUtils
    +import org.apache.flink.table.functions.{TableFunction => FlinkUDTF}
    +
    +import scala.collection.JavaConversions._
    +
    +/**
    +  * A Deferred Type is a Table Function which the result type hasn't been determined
yet.
    +  * It will determine the result type after the arguments are passed.
    +  *
    +  * @param tableFunction The Table Function instance
    +  * @param evalMethod The eval() method of the [[tableFunction]]
    +  * @param implicitResultType Implicit result type.
    +  */
    +class DeferredTypeFlinkTableFunction(
    +    val tableFunction: FlinkUDTF[_],
    +    val evalMethod: Method,
    +    val implicitResultType: TypeInformation[_])
    +  extends FlinkTableFunction(tableFunction, evalMethod) {
    +
    +  val paramTypeInfos = evalMethod.getParameterTypes.toList
    +
    +  override def getResultType(arguments: util.List[AnyRef]): TypeInformation[_] = {
    +    determineResultType(arguments)
    +  }
    +
    +  override def getRowType(
    +      typeFactory: RelDataTypeFactory,
    +      arguments: util.List[AnyRef]): RelDataType = {
    +    val resultType = determineResultType(arguments)
    +    val (fieldNames, fieldIndexes, _) = UserDefinedFunctionUtils.getFieldInfo(resultType)
    +    UserDefinedFunctionUtils.buildRelDataType(typeFactory, resultType, fieldNames, fieldIndexes)
    +  }
    +
    +  private def determineResultType(arguments: util.List[AnyRef]): TypeInformation[_] =
{
    +    val resultType = tableFunction.getResultType(arguments, paramTypeInfos)
    --- End diff --
    
    Here we use the parameter types of `eval()`. This is different from the logic in `UserDefinedFunctionUtils`.
I think we should make this consistent because users should expect consistent behavior.


> Support dynamic schema in Table Function
> ----------------------------------------
>
>                 Key: FLINK-6196
>                 URL: https://issues.apache.org/jira/browse/FLINK-6196
>             Project: Flink
>          Issue Type: Improvement
>          Components: Table API & SQL
>            Reporter: Zhuoluo Yang
>            Assignee: Zhuoluo Yang
>
> In many of our use cases. We have to decide the schema of a UDTF at the run time. For
example. udtf('c1, c2, c3') will generate three columns for a lateral view. 
> Most systems such as calcite and hive support this feature. However, the current implementation
of flink didn't implement the feature correctly.



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