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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-4469) Add support for user defined table function in Table API & SQL
Date Thu, 17 Nov 2016 16:59:00 GMT

    [ https://issues.apache.org/jira/browse/FLINK-4469?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15674229#comment-15674229
] 

ASF GitHub Bot commented on FLINK-4469:
---------------------------------------

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

    https://github.com/apache/flink/pull/2653#discussion_r88493178
  
    --- Diff: flink-libraries/flink-table/src/main/scala/org/apache/flink/api/table/validate/FunctionCatalog.scala
---
    @@ -47,13 +52,50 @@ class FunctionCatalog {
         sqlFunctions += sqlFunction
       }
     
    +  /** Register multiple sql functions at one time. The functions has the same name. **/
    +  def registerSqlFunctions(functions: Seq[SqlFunction]): Unit = {
    +    if (functions.nonEmpty) {
    +      sqlFunctions --= sqlFunctions.filter(_.getName == functions.head.getName)
    +      sqlFunctions ++= functions
    +    }
    +  }
    +
       def getSqlOperatorTable: SqlOperatorTable =
         ChainedSqlOperatorTable.of(
           new BasicOperatorTable(),
           new ListSqlOperatorTable(sqlFunctions)
         )
     
       /**
    +    * Lookup table function and create an TableFunctionCall if we find a match.
    +    */
    +  def lookupTableFunction[T](name: String, children: Seq[Expression]): TableFunctionCall[T]
= {
    +    val funcClass = functionBuilders
    +      .getOrElse(name.toLowerCase, throw ValidationException(s"Undefined function: $name"))
    +    funcClass match {
    +      // user-defined table function call
    +      case tf if classOf[TableFunction[T]].isAssignableFrom(tf) =>
    +        Try(UserDefinedFunctionUtils.instantiate(tf.asInstanceOf[Class[TableFunction[T]]]))
match {
    +          case Success(tableFunction) => {
    +            val clazz: Type = tableFunction.getClass.getGenericSuperclass
    --- End diff --
    
    As I said earlier this and following lines are very error-prone. We should keep calls
to the TypeExtractor to a very minimum. The TypeExtractor is only intended for Java not Scala.


> Add support for user defined table function in Table API & SQL
> --------------------------------------------------------------
>
>                 Key: FLINK-4469
>                 URL: https://issues.apache.org/jira/browse/FLINK-4469
>             Project: Flink
>          Issue Type: New Feature
>          Components: Table API & SQL
>            Reporter: Jark Wu
>            Assignee: Jark Wu
>
> Normal user-defined functions, such as concat(), take in a single input row and output
a single output row. In contrast, table-generating functions transform a single input row
to multiple output rows. It is very useful in some cases, such as look up in HBase by rowkey
and return one or more rows.
> Adding a user defined table function should:
> 1. inherit from UDTF class with specific generic type T
> 2. define one or more evel function. 
> NOTE: 
> 1. the eval method must be public and non-static.
> 2. the generic type T is the row type returned by table function. Because of Java type
erasure, we can’t extract T from the Iterable.
> 3. use {{collect(T)}} to emit table row
> 4. eval method can be overload. Blink will choose the best match eval method to call
according to parameter types and number.
> {code}
> public class Word {
>   public String word;
>   public Integer length;
> }
> public class SplitStringUDTF extends UDTF<Word> {
>     public Iterable<Word> eval(String str) {
>         if (str != null) {
>             for (String s : str.split(",")) {
>                 collect(new Word(s, s.length()));
>             }
>         }
>     }
> }
> // in SQL
> tableEnv.registerFunction("split", new SplitStringUDTF())
> tableEnv.sql("SELECT a, b, t.* FROM MyTable, LATERAL TABLE(split(c)) AS t(w,l)")
> // in Java Table API
> tableEnv.registerFunction("split", new SplitStringUDTF())
> // rename split table columns to “w” and “l”
> table.crossApply("split(c) as (w, l)")	
>      .select("a, b, w, l")
> // without renaming, we will use the origin field names in the POJO/case/...
> table.crossApply("split(c)")
>      .select("a, b, word, length")
> // in Scala Table API
> val split = new SplitStringUDTF()
> table.crossApply(split('c) as ('w, 'l))
>      .select('a, 'b, 'w, 'l)
> // outerApply for outer join to a UDTF
> table.outerApply(split('c))
>      .select('a, 'b, 'word, 'length)
> {code}
> See [1] for more information about UDTF design.
> [1] https://docs.google.com/document/d/15iVc1781dxYWm3loVQlESYvMAxEzbbuVFPZWBYuY1Ek/edit#



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