[FLINK-38888][transform] YAML Pipeline supports item subscription of array, map and row

docs/content.zh/docs/core-concept/transform.md

@@ -226,6 +226,14 @@ You can use `CAST( <EXPR> AS <T> )` syntax to convert any valid expression `<EXP
 | PARSE_JSON(string[, allowDuplicateKeys]) | parseJson(string[, allowDuplicateKeys]) | Parse a JSON string into a Variant. If the JSON string is invalid, an error will be thrown. To return NULL instead of an error, use the TRY_PARSE_JSON function. <br><br> If there are duplicate keys in the input JSON string, when `allowDuplicateKeys` is true, the parser will keep the last occurrence of all fields with the same key, otherwise it will throw an error. The default value of `allowDuplicateKeys` is false. |
 | TRY_PARSE_JSON(string[, allowDuplicateKeys]) | tryParseJson(string[, allowDuplicateKeys]) | Parse a JSON string into a Variant if possible. If the JSON string is invalid, return NULL. To throw an error instead of returning NULL, use the PARSE_JSON function. <br><br> If there are duplicate keys in the input JSON string, when `allowDuplicateKeys` is true, the parser will keep the last occurrence of all fields with the same key, otherwise it will return NULL. The default value of `allowDuplicateKeys` is false. |
 
+## Struct Functions
+
+| Function | Janino Code | Description |
+| -------- | ----------- | ----------- |
+| array[index] | itemAccess(array, index) | 返回数组中位置 `index` 的元素。索引从 1 开始（SQL 标准）。如果索引超出范围或数组为 NULL，则返回 NULL。 |
+| map[key] | itemAccess(map, key) | 返回 map 中与 `key` 关联的值。如果 key 不存在或 map 为 NULL，则返回 NULL。 |
+| row[index] | itemAccess(row, index) | 返回 row 中位置 `index` 的字段。索引从 1 开始。索引必须是常量（不能是计算表达式），因为返回类型必须在静态阶段确定。 |
+
 # 示例
 ## 添加计算列
 表达式可以用来生成新的列。例如，如果我们想基于表 `web_order` 在数据库 `mydb` 中添加两个计算列，我们可以定义一个转换规则如下：

docs/content/docs/core-concept/transform.md

@@ -227,6 +227,16 @@ You can use `CAST( <EXPR> AS <T> )` syntax to convert any valid expression `<EXP
 | PARSE_JSON(string[, allowDuplicateKeys]) | parseJson(string[, allowDuplicateKeys]) | Parse a JSON string into a Variant. If the JSON string is invalid, an error will be thrown. To return NULL instead of an error, use the TRY_PARSE_JSON function. <br><br> If there are duplicate keys in the input JSON string, when `allowDuplicateKeys` is true, the parser will keep the last occurrence of all fields with the same key, otherwise it will throw an error. The default value of `allowDuplicateKeys` is false. |
 | TRY_PARSE_JSON(string[, allowDuplicateKeys]) | tryParseJson(string[, allowDuplicateKeys]) | Parse a JSON string into a Variant if possible. If the JSON string is invalid, return NULL. To throw an error instead of returning NULL, use the PARSE_JSON function. <br><br> If there are duplicate keys in the input JSON string, when `allowDuplicateKeys` is true, the parser will keep the last occurrence of all fields with the same key, otherwise it will return NULL. The default value of `allowDuplicateKeys` is false. |
 
+## Struct Functions
+
+Struct functions are used to access elements in ARRAY, MAP and ROW types using subscript syntax.
+
+| Function | Janino Code | Description |
+| -------- | ----------- | ----------- |
+| array[index] | itemAccess(array, index) | Returns the element at position `index` in the array. Index is 1-based (SQL standard). Returns NULL if the index is out of bounds or if the array is NULL. |
+| map[key] | itemAccess(map, key) | Returns the value associated with `key` in the map. Returns NULL if the key does not exist or if the map is NULL. |
+| row[index] | itemAccess(row, index) | Returns the field at position `index` in the row. Index is 1-based. The index must be a constant (not a computed expression) since the return type must be statically determined. |
+
 # Example
 ## Add computed columns
 Evaluation expressions can be used to generate new columns. For example, if we want to append two computed columns based on the table `web_order` in the database `mydb`, we may define a transform rule as follows:

flink-cdc-composer/src/test/resources/specs/nested.yaml

@@ -119,7 +119,6 @@
     DataChangeEvent{tableId=foo.bar.baz, before=[], after=[0, {"id":2}], op=INSERT, meta=()}
     DataChangeEvent{tableId=foo.bar.baz, before=[0, {"id":2}], after=[], op=DELETE, meta=()}
 - do: Integer Array Subscripting
-  ignore: FLINK-38888
   projection: |-
     id_
     array_int_
@@ -133,7 +132,6 @@
     DataChangeEvent{tableId=foo.bar.baz, before=[], after=[0, null, null], op=INSERT, meta=()}
     DataChangeEvent{tableId=foo.bar.baz, before=[0, null, null], after=[], op=DELETE, meta=()}
 - do: String Array Subscripting
-  ignore: FLINK-38888
   projection: |-
     id_
     array_string_
@@ -147,7 +145,6 @@
     DataChangeEvent{tableId=foo.bar.baz, before=[], after=[0, null, null], op=INSERT, meta=()}
     DataChangeEvent{tableId=foo.bar.baz, before=[0, null, null], after=[], op=DELETE, meta=()}
 - do: Array OOB Subscripting
-  ignore: FLINK-38888
   projection: |-
     id_
     array_string_[0] AS negative_overflow
@@ -161,7 +158,6 @@
     DataChangeEvent{tableId=foo.bar.baz, before=[], after=[0, null, null], op=INSERT, meta=()}
     DataChangeEvent{tableId=foo.bar.baz, before=[0, null, null], after=[], op=DELETE, meta=()}
 - do: Array Subscripting With Sub Expression
-  ignore: FLINK-38888
   projection: |-
     id_
     array_int_[1 + 1] AS int_key
@@ -175,7 +171,6 @@
     DataChangeEvent{tableId=foo.bar.baz, before=[], after=[0, null, null], op=INSERT, meta=()}
     DataChangeEvent{tableId=foo.bar.baz, before=[0, null, null], after=[], op=DELETE, meta=()}
 - do: Filter by Array-related Expression
-  ignore: FLINK-38888
   projection: id_, array_string_
   filter: array_string_[3] = '五'
   primary-key: id_
@@ -184,7 +179,6 @@
     DataChangeEvent{tableId=foo.bar.baz, before=[1, [one, one, two, three, five]], after=[-1, [二, san, 五, qi, 十一]], op=UPDATE, meta=()}
     DataChangeEvent{tableId=foo.bar.baz, before=[-1, [二, san, 五, qi, 十一]], after=[], op=DELETE, meta=()}
 - do: Map Subscripting
-  ignore: FLINK-38888
   projection: |-
     id_
     map_int_string_
@@ -198,7 +192,6 @@
     DataChangeEvent{tableId=foo.bar.baz, before=[], after=[0, null, null], op=INSERT, meta=()}
     DataChangeEvent{tableId=foo.bar.baz, before=[0, null, null], after=[], op=DELETE, meta=()}
 - do: Map Subscripting with absent key
-  ignore: FLINK-38888
   projection: |-
     id_
     map_int_string_[233] AS map_value
@@ -211,7 +204,6 @@
     DataChangeEvent{tableId=foo.bar.baz, before=[], after=[0, null], op=INSERT, meta=()}
     DataChangeEvent{tableId=foo.bar.baz, before=[0, null], after=[], op=DELETE, meta=()}
 - do: Map Subscripting with complex expression
-  ignore: FLINK-38888
   projection: |-
     id_
     map_int_string_[1 + 2] AS map_value
@@ -224,7 +216,6 @@
     DataChangeEvent{tableId=foo.bar.baz, before=[], after=[0, null], op=INSERT, meta=()}
     DataChangeEvent{tableId=foo.bar.baz, before=[0, null], after=[], op=DELETE, meta=()}
 - do: Map Subscripting with nested expressions
-  ignore: FLINK-38888
   projection: |-
     id_
     map_string_array_string_[lower('ONE')] AS index_1
@@ -238,7 +229,6 @@
     DataChangeEvent{tableId=foo.bar.baz, before=[], after=[0, null, null], op=INSERT, meta=()}
     DataChangeEvent{tableId=foo.bar.baz, before=[0, null, null], after=[], op=DELETE, meta=()}
 - do: Map Subscripting With Absent Object
-  ignore: FLINK-38888
   projection: |-
     id_
     map_string_array_string_['foo'] AS index_1
@@ -252,15 +242,13 @@
     DataChangeEvent{tableId=foo.bar.baz, before=[], after=[0, null, null], op=INSERT, meta=()}
     DataChangeEvent{tableId=foo.bar.baz, before=[0, null, null], after=[], op=DELETE, meta=()}
 - do: Filter by Map-related Expression
-  ignore: FLINK-38888
   projection: id_, map_int_string_
   filter: map_int_string_[1] = 'one'
   primary-key: id_
   expect: |-
     CreateTableEvent{tableId=foo.bar.baz, schema=columns={`id_` BIGINT NOT NULL 'Identifier',`map_int_string_` MAP<INT, STRING>}, primaryKeys=id_, options=()}
     DataChangeEvent{tableId=foo.bar.baz, before=[], after=[1, {1 -> one, 2 -> two, 3 -> three}], op=INSERT, meta=()}
 - do: Record Subscripting With Index
-  ignore: FLINK-38888
   projection: |-
     id_
     complex_row_
@@ -275,23 +263,20 @@
     DataChangeEvent{tableId=foo.bar.baz, before=[], after=[0, null, null, null], op=INSERT, meta=()}
     DataChangeEvent{tableId=foo.bar.baz, before=[0, null, null, null], after=[], op=DELETE, meta=()}
 - do: Record Subscripting With Invalid Index
-  ignore: FLINK-38888
   projection: |-
     id_
     complex_row_
     complex_row_[0] AS bad_key
   primary-key: id_
   expect-error: 'Cannot infer type of field at position 0 within ROW type: RecordType(VARCHAR(65536) name, INTEGER length)'
 - do: Record Subscripting With Computed Index (Illegal, type must be statically determined)
-  ignore: FLINK-38888
   projection: |-
     id_
     complex_row_
     complex_row_[1 + 1] AS bad_key
   primary-key: id_
   expect-error: 'Cannot infer type of field at position null within ROW type: RecordType(VARCHAR(65536) name, INTEGER length)'
 - do: Filter by Record-related Expression
-  ignore: FLINK-38888
   projection: id_, complex_row_
   filter: complex_row_[1] = 'Derrida'
   primary-key: id_

flink-cdc-runtime/src/main/java/org/apache/flink/cdc/runtime/functions/impl/StructFunctions.java

@@ -0,0 +1,70 @@
+/*
+ * 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.cdc.runtime.functions.impl;
+
+import java.util.List;
+import java.util.Map;
+
+/**
+ * Built-in functions for collection and struct data types.
+ *
+ * <p>These functions support accessing elements from collections (ARRAY, MAP) and structured data
+ * types (ROW).
+ */
+public class StructFunctions {
+
+    /**
+     * Accesses an element from an ARRAY by index (1-based, SQL standard).
+     *
+     * <p>array[1] returns the first element.
+     *
+     * @param <T> the element type of the array
+     * @param array the array to access
+     * @param index the 1-based index
+     * @return the element at the specified index, or null if index is out of bounds
+     */
+    public static <T> T itemAccess(List<T> array, Integer index) {
+        if (array == null || index == null) {
+            return null;
+        }
+        // Convert 1-based index to 0-based (SQL standard uses 1-based indexing)
+        int zeroBasedIndex = index - 1;
+        if (zeroBasedIndex < 0 || zeroBasedIndex >= array.size()) {
+            return null;
+        }
+        return array.get(zeroBasedIndex);
+    }
+
+    /**
+     * Accesses a value from a MAP by key.
+     *
+     * <p>map['key'] returns the value for 'key'.
+     *
+     * @param <K> the key type of the map
+     * @param <V> the value type of the map
+     * @param map the map to access
+     * @param key the key to look up
+     * @return the value for the specified key, or null if not found
+     */
+    public static <K, V> V itemAccess(Map<K, V> map, K key) {
+        if (map == null || key == null) {
+            return null;
+        }
+        return map.get(key);
+    }
+}

flink-cdc-runtime/src/main/java/org/apache/flink/cdc/runtime/parser/JaninoCompiler.java

@@ -25,6 +25,7 @@
 import org.apache.flink.cdc.common.source.SupportedMetadataColumn;
 import org.apache.flink.cdc.common.types.DataType;
 import org.apache.flink.cdc.common.types.DataTypeRoot;
+import org.apache.flink.cdc.common.utils.Preconditions;
 import org.apache.flink.cdc.common.utils.StringUtils;
 import org.apache.flink.cdc.runtime.operators.transform.UserDefinedFunctionDescriptor;
 
@@ -89,7 +90,7 @@ public class JaninoCompiler {
     public static final String DEFAULT_TIME_ZONE = "__time_zone__";
 
     private static final String[] BUILTIN_FUNCTION_MODULES = {
-        "Arithmetic", "Casting", "Comparison", "Logical", "String", "Temporal"
+        "Arithmetic", "Casting", "Comparison", "Logical", "String", "Struct", "Temporal"
     };
 
     @VisibleForTesting
@@ -306,6 +307,8 @@ private static Java.Rvalue sqlBasicCallToJaninoRvalue(
                 return generateTimestampAddOperation(context, sqlBasicCall, atoms);
             case OTHER:
                 return generateOtherOperation(context, sqlBasicCall, atoms);
+            case ITEM:
+                return generateItemAccessOperation(context, sqlBasicCall, atoms);
             default:
                 throw new ParseException("Unrecognized expression: " + sqlBasicCall);
         }
@@ -468,6 +471,43 @@ private static Java.Rvalue generateOtherOperation(
         throw new ParseException("Unrecognized expression: " + sqlBasicCall.toString());
     }
 
+    private static Java.Rvalue generateItemAccessOperation(
+            Context context, SqlBasicCall sqlBasicCall, Java.Rvalue[] atoms) {
+        Preconditions.checkArgument(
+                atoms.length == 2,
+                "Expecting item accessing call %s to have 2 operands, got %s actually",
+                sqlBasicCall,
+                List.of(atoms));
+        Java.Rvalue methodInvocation =
+                new Java.MethodInvocation(Location.NOWHERE, null, "itemAccess", atoms);
+
+        // Deduce the return type and add a cast to ensure proper type conversion
+        DataType resultType =
+                TransformParser.deduceSubExpressionType(
+                        context.columns,
+                        sqlBasicCall,
+                        context.udfDescriptors,
+                        context.supportedMetadataColumns);
+
+        // Get the Java class for the result type and add a cast
+        // Use getCanonicalName() to correctly handle array types (e.g., byte[] instead of "[B")
+        Class<?> javaClass = JavaClassConverter.toJavaClass(resultType);
+        if (javaClass != null && javaClass != Object.class) {
+            String canonicalName = javaClass.getCanonicalName();
+            if (canonicalName != null) {
+                return new Java.Cast(
+                        Location.NOWHERE,
+                        new Java.ReferenceType(
+                                Location.NOWHERE,
+                                new Java.Annotation[0],
+                                canonicalName.split("\\."),
+                                null),
+                        methodInvocation);
+            }
+        }
+        return methodInvocation;
+    }
+
     private static Java.Rvalue generateOtherFunctionOperation(
             Context context, SqlBasicCall sqlBasicCall, Java.Rvalue[] atoms) {
         String operationName = sqlBasicCall.getOperator().getName().toUpperCase();

flink-cdc-runtime/src/main/java/org/apache/flink/cdc/runtime/parser/metadata/TransformSqlOperatorTable.java

@@ -398,6 +398,12 @@ public SqlSyntax getSyntax() {
     // --------------
     public static final SqlFunction CAST = SqlStdOperatorTable.CAST;
 
+    // ---------------------
+    // Struct Functions
+    // ---------------------
+    // Supports accessing elements of ARRAY[index], ROW[index] and MAP[key]
+    public static final SqlOperator ITEM = SqlStdOperatorTable.ITEM;
+
     public static final SqlFunction AI_CHAT_PREDICT =
             new SqlFunction(
                     "AI_CHAT_PREDICT",