Fixes for Multisearch and Append command (#4512)

* Fix for Multisearch and Append command

Signed-off-by: Kai Huang <ahkcs@amazon.com>

# Conflicts:
#	docs/category.json

* fix tests

Signed-off-by: Kai Huang <ahkcs@amazon.com>

* fix test

Signed-off-by: Kai Huang <ahkcs@amazon.com>

* remove error location

Signed-off-by: Kai Huang <ahkcs@amazon.com>

* Allow same SqlTypeName but with different nullability to be merged

Signed-off-by: Kai Huang <ahkcs@amazon.com>

* Update error message

Signed-off-by: Kai Huang <ahkcs@amazon.com>

---------

Signed-off-by: Kai Huang <ahkcs@amazon.com>
(cherry picked from commit 0dd5949)
Signed-off-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

core/src/main/java/org/opensearch/sql/calcite/CalciteRelNodeVisitor.java

@@ -1816,18 +1816,16 @@ public RelNode visitMultisearch(Multisearch node, CalcitePlanContext context) {
   }
 
   /**
-   * Finds the timestamp field for multisearch ordering.
+   * Finds the @timestamp field for multisearch ordering. Only @timestamp field is used for
+   * timestamp interleaving. Other timestamp-like fields are ignored.
    *
-   * @param rowType The row type to search for timestamp fields
-   * @return The name of the timestamp field, or null if not found
+   * @param rowType The row type to search for @timestamp field
+   * @return "@timestamp" if the field exists, or null if not found
    */
   private String findTimestampField(RelDataType rowType) {
-    String[] candidates = {"@timestamp", "_time", "timestamp", "time"};
-    for (String fieldName : candidates) {
-      RelDataTypeField field = rowType.getField(fieldName, false, false);
-      if (field != null) {
-        return fieldName;
-      }
+    RelDataTypeField field = rowType.getField("@timestamp", false, false);
+    if (field != null) {
+      return "@timestamp";
     }
     return null;
   }

core/src/main/java/org/opensearch/sql/calcite/SchemaUnifier.java

@@ -7,29 +7,27 @@
 
 import java.util.ArrayList;
 import java.util.HashMap;
-import java.util.HashSet;
 import java.util.List;
 import java.util.Map;
-import java.util.Set;
 import java.util.stream.Collectors;
 import org.apache.calcite.rel.RelNode;
 import org.apache.calcite.rel.type.RelDataType;
 import org.apache.calcite.rel.type.RelDataTypeField;
 import org.apache.calcite.rex.RexNode;
-import org.apache.calcite.sql.validate.SqlValidatorUtil;
 
 /**
- * Utility class for unifying schemas across multiple RelNodes with type conflict resolution. Uses
- * the same strategy as append command - renames conflicting fields to avoid type conflicts.
+ * Utility class for unifying schemas across multiple RelNodes. Throws an exception when type
+ * conflicts are detected.
  */
 public class SchemaUnifier {
 
   /**
-   * Builds a unified schema for multiple nodes with type conflict resolution.
+   * Builds a unified schema for multiple nodes. Throws an exception if type conflicts are detected.
    *
    * @param nodes List of RelNodes to unify schemas for
    * @param context Calcite plan context
    * @return List of projected RelNodes with unified schema
+   * @throws IllegalArgumentException if type conflicts are detected
    */
   public static List<RelNode> buildUnifiedSchemaWithConflictResolution(
       List<RelNode> nodes, CalcitePlanContext context) {
@@ -41,7 +39,7 @@ public static List<RelNode> buildUnifiedSchemaWithConflictResolution(
       return nodes;
     }
 
-    // Step 1: Build the unified schema by processing all nodes
+    // Step 1: Build the unified schema by processing all nodes (throws on conflict)
     List<SchemaField> unifiedSchema = buildUnifiedSchema(nodes);
 
     // Step 2: Create projections for each node to align with unified schema
@@ -55,47 +53,37 @@ public static List<RelNode> buildUnifiedSchemaWithConflictResolution(
       projectedNodes.add(projectedNode);
     }
 
-    // Step 3: Unify names to handle type conflicts (this creates age0, age1, etc.)
-    List<String> uniqueNames =
-        SqlValidatorUtil.uniquify(fieldNames, SqlValidatorUtil.EXPR_SUGGESTER, true);
-
-    // Step 4: Re-project with unique names if needed
-    if (!uniqueNames.equals(fieldNames)) {
-      List<RelNode> renamedNodes = new ArrayList<>();
-      for (RelNode node : projectedNodes) {
-        RelNode renamedNode =
-            context.relBuilder.push(node).project(context.relBuilder.fields(), uniqueNames).build();
-        renamedNodes.add(renamedNode);
-      }
-      return renamedNodes;
-    }
-
     return projectedNodes;
   }
 
   /**
-   * Builds a unified schema by merging fields from all nodes. Fields with the same name but
-   * different types are added as separate entries (which will be renamed during uniquification).
+   * Builds a unified schema by merging fields from all nodes. Throws an exception if fields with
+   * the same name have different types.
    *
    * @param nodes List of RelNodes to merge schemas from
-   * @return List of SchemaField representing the unified schema (may contain duplicate names)
+   * @return List of SchemaField representing the unified schema
+   * @throws IllegalArgumentException if type conflicts are detected
    */
   private static List<SchemaField> buildUnifiedSchema(List<RelNode> nodes) {
     List<SchemaField> schema = new ArrayList<>();
-    Map<String, Set<RelDataType>> seenFields = new HashMap<>();
+    Map<String, RelDataType> seenFields = new HashMap<>();
 
     for (RelNode node : nodes) {
       for (RelDataTypeField field : node.getRowType().getFieldList()) {
         String fieldName = field.getName();
         RelDataType fieldType = field.getType();
 
-        // Track which (name, type) combinations we've seen
-        Set<RelDataType> typesForName = seenFields.computeIfAbsent(fieldName, k -> new HashSet<>());
-
-        if (!typesForName.contains(fieldType)) {
-          // New field or same name with different type - add to schema
+        RelDataType existingType = seenFields.get(fieldName);
+        if (existingType == null) {
+          // New field - add to schema
           schema.add(new SchemaField(fieldName, fieldType));
-          typesForName.add(fieldType);
+          seenFields.put(fieldName, fieldType);
+        } else if (!areTypesCompatible(existingType, fieldType)) {
+          // Same field name but different type - throw exception
+          throw new IllegalArgumentException(
+              String.format(
+                  "Unable to process column '%s' due to incompatible types: '%s' and '%s'",
+                  fieldName, existingType.getSqlTypeName(), fieldType.getSqlTypeName()));
         }
         // If we've seen this exact (name, type) combination, skip it
       }
@@ -104,6 +92,10 @@ private static List<SchemaField> buildUnifiedSchema(List<RelNode> nodes) {
     return schema;
   }
 
+  private static boolean areTypesCompatible(RelDataType type1, RelDataType type2) {
+    return type1.getSqlTypeName() != null && type1.getSqlTypeName().equals(type2.getSqlTypeName());
+  }
+
   /**
    * Builds a projection for a node to align with the unified schema. For each field in the unified
    * schema: - If the node has a matching field with the same type, use it - Otherwise, project NULL
@@ -125,8 +117,8 @@ private static List<RexNode> buildProjectionForNode(
       RelDataType expectedType = schemaField.getType();
       RelDataTypeField nodeField = nodeFieldMap.get(fieldName);
 
-      if (nodeField != null && nodeField.getType().equals(expectedType)) {
-        // Field exists with matching type - use it
+      if (nodeField != null && areTypesCompatible(nodeField.getType(), expectedType)) {
+        // Field exists with compatible type - use it
         projection.add(context.rexBuilder.makeInputRef(node, nodeField.getIndex()));
       } else {
         // Field missing or type mismatch - project NULL

docs/category.json

@@ -40,6 +40,7 @@
     "user/ppl/cmd/rare.rst",
     "user/ppl/cmd/regex.rst",
     "user/ppl/cmd/rename.rst",
+    "user/ppl/cmd/multisearch.rst",
     "user/ppl/cmd/replace.rst",
     "user/ppl/cmd/rex.rst",
     "user/ppl/cmd/search.rst",

docs/user/ppl/cmd/append.rst

@@ -24,6 +24,11 @@ append <sub-search>
 
 * sub-search: mandatory. Executes PPL commands as a secondary search.
 
+Limitations
+===========
+
+* **Schema Compatibility**: When fields with the same name exist between the main search and sub-search but have incompatible types, the query will fail with an error. To avoid type conflicts, ensure that fields with the same name have the same data type, or use different field names (e.g., by renaming with ``eval`` or using ``fields`` to select non-conflicting columns).
+
 Example 1: Append rows from a count aggregation to existing search result
 ===============================================================
 
@@ -64,23 +69,3 @@ PPL query::
     | 101 | M      | null  |
     +-----+--------+-------+
 
-Example 3: Append rows with column type conflict
-=============================================
-
-This example shows how column type conflicts are handled when appending results. Same name columns with different types will generate two different columns in appended result.
-
-PPL query::
-
-    os> source=accounts | stats sum(age) as sum by gender, state | sort -sum | head 5 | append [ source=accounts | stats sum(age) as sum by gender | eval sum = cast(sum as double) ];
-    fetched rows / total rows = 6/6
-    +------+--------+-------+-------+
-    | sum  | gender | state | sum0  |
-    |------+--------+-------+-------|
-    | 36   | M      | TN    | null  |
-    | 33   | M      | MD    | null  |
-    | 32   | M      | IL    | null  |
-    | 28   | F      | VA    | null  |
-    | null | F      | null  | 28.0  |
-    | null | M      | null  | 101.0 |
-    +------+--------+-------+-------+
-

docs/user/ppl/cmd/multisearch.rst

@@ -30,10 +30,6 @@ Description
 * **A/B Testing Analysis**: Combine results from different test groups for comparison
 * **Time-series Data Merging**: Interleave events from multiple sources based on timestamps
 
-Version
-=======
-3.3.0
-
 Syntax
 ======
 | multisearch <subsearch1> <subsearch2> <subsearch3> ...
@@ -59,7 +55,7 @@ Limitations
 ===========
 
 * **Minimum Subsearches**: At least two subsearches must be specified
-* **Schema Compatibility**: When fields with the same name exist across subsearches but have incompatible types, the system automatically resolves conflicts by renaming the conflicting fields. The first occurrence retains the original name, while subsequent conflicting fields are renamed with a numeric suffix (e.g., ``age`` becomes ``age0``, ``age1``, etc.). This ensures all data is preserved while maintaining schema consistency.
+* **Schema Compatibility**: When fields with the same name exist across subsearches but have incompatible types, the query will fail with an error. To avoid type conflicts, ensure that fields with the same name have the same data type across all subsearches, or use different field names (e.g., by renaming with ``eval`` or using ``fields`` to select non-conflicting columns).
 
 Usage
 =====
@@ -84,8 +80,8 @@ PPL query::
     |-----------+-----+-----------|
     | Nanette   | 28  | young     |
     | Amber     | 32  | adult     |
+    | Dale      | 33  | adult     |
     | Hattie    | 36  | adult     |
-    | Dale      | 37  | adult     |
     +-----------+-----+-----------+
 
 Example 2: Success Rate Pattern
@@ -97,14 +93,14 @@ PPL query::
 
     os> | multisearch [search source=accounts | where balance > 20000 | eval query_type = "high_balance" | fields firstname, balance, query_type] [search source=accounts | where balance > 0 AND balance <= 20000 | eval query_type = "regular" | fields firstname, balance, query_type] | sort balance desc;
     fetched rows / total rows = 4/4
-    +-----------+---------+-------------+
-    | firstname | balance | query_type  |
-    |-----------+---------+-------------|
-    | Amber     | 39225   | high_balance|
-    | Nanette   | 32838   | high_balance|
-    | Hattie    | 5686    | regular     |
-    | Dale      | 4180    | regular     |
-    +-----------+---------+-------------+
+    +-----------+---------+--------------+
+    | firstname | balance | query_type   |
+    |-----------+---------+--------------|
+    | Amber     | 39225   | high_balance |
+    | Nanette   | 32838   | high_balance |
+    | Hattie    | 5686    | regular      |
+    | Dale      | 4180    | regular      |
+    +-----------+---------+--------------+
 
 Example 3: Timestamp Interleaving
 ==================================
@@ -113,37 +109,19 @@ Combine time-series data from multiple sources with automatic timestamp-based or
 
 PPL query::
 
-    os> | multisearch [search source=time_data | where category IN ("A", "B")] [search source=time_data2 | where category IN ("E", "F")] | head 5;
+    os> | multisearch [search source=time_data | where category IN ("A", "B")] [search source=time_data2 | where category IN ("E", "F")] | fields @timestamp, category, value, timestamp | head 5;
     fetched rows / total rows = 5/5
-    +-------+---------------------+----------+-------+---------------------+
-    | index | @timestamp          | category | value | timestamp           |
-    |-------+---------------------+----------+-------+---------------------|
-    | null  | 2025-08-01 04:00:00 | E        | 2001  | 2025-08-01 04:00:00 |
-    | null  | 2025-08-01 03:47:41 | A        | 8762  | 2025-08-01 03:47:41 |
-    | null  | 2025-08-01 02:30:00 | F        | 2002  | 2025-08-01 02:30:00 |
-    | null  | 2025-08-01 01:14:11 | B        | 9015  | 2025-08-01 01:14:11 |
-    | null  | 2025-08-01 01:00:00 | E        | 2003  | 2025-08-01 01:00:00 |
-    +-------+---------------------+----------+-------+---------------------+
-
-Example 4: Handling Empty Results
-==================================
-
-Multisearch gracefully handles cases where some subsearches return no results.
-
-PPL query::
-
-    os> | multisearch [search source=accounts | where age > 25 | fields firstname, age] [search source=accounts | where age > 200 | eval impossible = "yes" | fields firstname, age, impossible] | head 5;
-    fetched rows / total rows = 4/4
-    +-----------+-----+------------+
-    | firstname | age | impossible |
-    |-----------+-----+------------|
-    | Nanette   | 28  | null       |
-    | Amber     | 32  | null       |
-    | Hattie    | 36  | null       |
-    | Dale      | 37  | null       |
-    +-----------+-----+------------+
-
-Example 5: Type Compatibility - Missing Fields
+    +---------------------+----------+-------+---------------------+
+    | @timestamp          | category | value | timestamp           |
+    |---------------------+----------+-------+---------------------|
+    | 2025-08-01 04:00:00 | E        | 2001  | 2025-08-01 04:00:00 |
+    | 2025-08-01 03:47:41 | A        | 8762  | 2025-08-01 03:47:41 |
+    | 2025-08-01 02:30:00 | F        | 2002  | 2025-08-01 02:30:00 |
+    | 2025-08-01 01:14:11 | B        | 9015  | 2025-08-01 01:14:11 |
+    | 2025-08-01 01:00:00 | E        | 2003  | 2025-08-01 01:00:00 |
+    +---------------------+----------+-------+---------------------+
+
+Example 4: Type Compatibility - Missing Fields
 =================================================
 
 Demonstrate how missing fields are handled with NULL insertion.
@@ -157,26 +135,7 @@ PPL query::
     |-----------+-----+------------|
     | Nanette   | 28  | yes        |
     | Amber     | 32  | null       |
+    | Dale      | 33  | null       |
     | Hattie    | 36  | null       |
-    | Dale      | 37  | null       |
     +-----------+-----+------------+
 
-Example 6: Type Conflict Resolution - Automatic Renaming
-===========================================================
-
-When the same field name has incompatible types across subsearches, the system automatically renames conflicting fields with numeric suffixes.
-
-PPL query::
-
-    os> | multisearch [search source=accounts | fields firstname, age, balance | head 2] [search source=locations | fields description, age, place_id | head 2];
-    fetched rows / total rows = 4/4
-    +-----------+-----+---------+------------------+------+----------+
-    | firstname | age | balance | description      | age0 | place_id |
-    |-----------+-----+---------+------------------+------+----------|
-    | Amber     | 32  | 39225   | null             | null | null     |
-    | Hattie    | 36  | 5686    | null             | null | null     |
-    | null      | null| null    | Central Park     | old  | 1001     |
-    | null      | null| null    | Times Square     | modern| 1002    |
-    +-----------+-----+---------+------------------+------+----------+
-
-In this example, the ``age`` field has type ``bigint`` in accounts but type ``string`` in locations. The system keeps the first occurrence as ``age`` (bigint) and renames the second occurrence to ``age0`` (string), preserving all data while avoiding type conflicts.