ASF GitHub Bot commented on FLINK-4469:

Github user wuchong commented on the issue:

    Because SQL doesn't have standard user-defined table function, we introduce 
MS SQL Server's `CROSS/OUTER APPLY` to support UDTF , see 
https://technet.microsoft.com/en-us/library/ms175156(v=sql.105).aspx .
    NOTE: In order to implement the `CROSS/OUTER APPLY`, we need to modify 
Calcite's SQL Parser. So we include `Parser.jj` from Calcite source code and 
add some modifications (search FLINK in this file). 
 for more UDTF design, 

> 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. eval should always return java.lang.Iterable or scala.collection.Iterable 
> with the generic type T.
> 3. 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.
> 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) {
>             return new ArrayList<>();
>         } else {
>             List<Word> list = new ArrayList<>();
>             for (String s : str.split(",")) {
>                 Word word = new Word(s, s.length());
>                 list.add(word);
>             }
>             return list;
>         }
>     }
> }
> // in SQL
> tableEnv.registerFunction("split", new SplitStringUDTF())
> tableEnv.sql("SELECT a, b, t.* FROM MyTable CROSS APPLY 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)", "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), 'w, 'l)
>      .select('a, 'b, 'w, 'l)
> // outerApply for outer join to a UDTF
> table.outerApply(split('c))
>      .select('a, 'b, 'word, 'length)
> {code}
> Here we introduce CROSS/OUTER APPLY keywords to join table functions , which 
> is used in SQL Server. We can discuss the API in the comment. 
> Maybe the {{UDTF}} class should be replaced by {{TableFunction}} or something 
> others, because we have introduced {{ScalarFunction}} for custom functions, 
> we need to keep consistent. Although, I prefer {{UDTF}} rather than 
> {{TableFunction}} as the former is more SQL-like and the latter maybe 
> confused with DataStream functions. 
> **This issue is blocked by CALCITE-1309, so we need to wait Calcite fix this 
> and release.**
> See [1] for more information about UDTF design.
> [1] 
> https://docs.google.com/document/d/15iVc1781dxYWm3loVQlESYvMAxEzbbuVFPZWBYuY1Ek/edit#

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