[
https://issues.apache.org/jira/browse/FLINK-4469?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15671925#comment-15671925
]
ASF GitHub Bot commented on FLINK-4469:
---------------------------------------
Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/2653#discussion_r88339010
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/api/table/table.scala
---
@@ -611,6 +612,130 @@ class Table(
}
/**
+ * The Cross Apply returns rows form the outer table (table on the left
of the Apply operator)
+ * that produces matching values from the table-valued function (which
is on the right side of
+ * the operator).
+ *
+ * The Cross Apply is equivalent to Inner Join, but it works with a
table-valued function.
+ *
+ * Example:
+ *
+ * {{{
+ * class MySplitUDTF extends TableFunction[String] {
+ * def eval(str: String): Unit = {
+ * str.split("#").foreach(collect)
+ * }
+ * }
+ *
+ * val split = new MySplitUDTF()
+ * table.crossApply(split('c).as('s)).select('a,'b,'c,'s)
+ * }}}
+ */
+ def crossApply(udtf: TableFunctionCall[_]): Table = {
+ applyInternal(udtf, JoinType.INNER)
+ }
+
+ /**
+ * The Cross Apply returns rows form the outer table (table on the left
of the Apply operator)
+ * that produces matching values from the table-valued function (which
is on the right side of
+ * the operator).
+ *
+ * The Cross Apply is equivalent to Inner Join, but it works with a
table-valued function.
+ *
+ * Example:
+ *
+ * {{{
+ * class MySplitUDTF extends TableFunction[String] {
+ * def eval(str: String): Unit = {
+ * str.split("#").foreach(collect)
+ * }
+ * }
+ *
+ * val split = new MySplitUDTF()
+ * table.crossApply("split('c') as (s)").select("a, b, c, s")
+ * }}}
+ */
+ def crossApply(udtf: String): Table = {
+ applyInternal(udtf, JoinType.INNER)
+ }
+
+ /**
+ * The Cross Apply returns rows form the outer table (table on the left
of the Apply operator)
+ * that produces matching values from the table-valued function (which
is on the right side of
+ * the operator).
+ *
+ * The Cross Apply is equivalent to Inner Join, but it works with a
table-valued function.
+ *
+ * Example:
+ *
+ * {{{
+ * class MySplitUDTF extends TableFunction[String] {
+ * def eval(str: String): Unit = {
+ * str.split("#").foreach(collect)
+ * }
+ * }
+ *
+ * val split = new MySplitUDTF()
+ * table.outerApply(split('c).as('s)).select('a,'b,'c,'s)
+ * }}}
+ */
+ def outerApply(udtf: TableFunctionCall[_]): Table = {
+ applyInternal(udtf, JoinType.LEFT_OUTER)
+ }
+
+ /**
+ * The Outer Apply returns all the rows from the outer table (table on
the left of the Apply
+ * operator), and rows that do not matches the condition from the
table-valued function (which
+ * is on the right side of the operator), NULL values are displayed.
+ *
+ * The Outer Apply is equivalent to Left Outer Join, but it works with
a table-valued function.
+ *
+ * Example:
+ *
+ * {{{
+ * val split = new MySplitUDTF()
+ * table.crossApply("split('c') as (s)").select("a, b, c, s")
+ * }}}
+ */
+ def outerApply(udtf: String): Table = {
+ applyInternal(udtf, JoinType.LEFT_OUTER)
+ }
+
+ private def applyInternal(udtfString: String, joinType: JoinType): Table
= {
+ val node = ExpressionParser.parseLogicalNode(udtfString)
+ var alias: Option[Seq[Expression]] = None
+ val functionCall = node match {
+ case AliasNode(aliasList, child) =>
+ alias = Some(aliasList)
+ child
+ case _ => node
+ }
+
+ functionCall match {
+ case call @ UnresolvedTableFunctionCall(name, args) =>
+ val udtfCall =
tableEnv.getFunctionCatalog.lookupTableFunction(name, args)
+ if (alias.isDefined) {
+ applyInternal(udtfCall.as(alias.get: _*), joinType)
+ } else {
+ applyInternal(udtfCall, joinType)
+ }
+ case _ => throw new TableException("Cross/Outer Apply only accept
TableFunction")
+ }
+ }
+
+ private def applyInternal(node: LogicalNode, joinType: JoinType): Table
= {
+ node match {
+ case udtf: TableFunctionCall[_] =>
+ udtf.setChild(this.logicalPlan)
+ new Table(
+ tableEnv,
+ Join(this.logicalPlan, udtf.validate(tableEnv), joinType, None,
+
Some(relBuilder.getCluster.createCorrel())).validate(tableEnv))
--- End diff --
We kept Calcite code so far out of our `LogicalNode` (except for
`construct()` of course). I think we can move the
`relBuilder.getCluster.createCorrel()` call also into `Join.construct()` and
change the `corId` constructor parameter of `Join` to a boolean flag that
indicates whether we need to generate a `corId` or not.
> 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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