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Posted to issues@flink.apache.org by "Jark Wu (JIRA)" <ji...@apache.org> on 2016/08/24 09:49:20 UTC

[jira] [Created] (FLINK-4469) Add support for user defined table function in Table API & SQL

Jark Wu created FLINK-4469:
------------------------------

             Summary: 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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