[GitHub] [spark] dtenedor commented on a diff in pull request #40049: [SPARK-42398][SQL] Refine default column value DS v2 interface

["dtenedor (via GitHub)" <gi...@apache.org>]

dtenedor commented on code in PR #40049:
URL: https://github.com/apache/spark/pull/40049#discussion_r1109091855


##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/statements.scala:
##########
@@ -135,6 +138,16 @@ case class QualifiedColType(
   def name: Seq[String] = path.map(_.name).getOrElse(Nil) :+ colName
 
   def resolved: Boolean = path.forall(_.resolved) && position.forall(_.resolved)
+
+  def getV2Default: ColumnDefaultValue = {
+    default.map { sql =>
+      val e = ResolveDefaultColumns.analyze(colName, dataType, sql, "ALTER TABLE")
+      assert(e.resolved && e.foldable,
+        "exist default must be simple SQL string that is resolved and foldable, " +

Review Comment:
   ```suggestion
           "The existence default value must be a simple SQL string that is resolved and foldable, " +
   ```



##########
sql/catalyst/src/main/scala/org/apache/spark/sql/connector/catalog/CatalogV2Util.scala:
##########
@@ -431,4 +431,73 @@ private[sql] object CatalogV2Util {
       .getOrElse(catalogManager.v2SessionCatalog)
       .asTableCatalog
   }
+
+  def v2ColumnsToStructType(columns: Array[Column]): StructType = {
+    StructType(columns.map(v2ColumnToStructField))
+  }
+
+  private def v2ColumnToStructField(col: Column): StructField = {
+    val metadata = Option(col.metadataInJSON()).map(Metadata.fromJson).getOrElse(Metadata.empty)
+    var f = StructField(col.name(), col.dataType(), col.nullable(), metadata)
+    Option(col.comment()).foreach { comment =>
+      f = f.withComment(comment)
+    }
+    Option(col.defaultValue()).foreach { default =>
+      f = encodeDefaultValue(default, f)
+    }
+    f
+  }
+
+  // For built-in file sources, we encode the default value in StructField metadata. An analyzer
+  // rule will check the special metadata and change the DML input plan to fill the default value.
+  private def encodeDefaultValue(defaultValue: ColumnDefaultValue, f: StructField): StructField = {
+    Option(defaultValue).map { default =>
+      // The "exist default" is used to back-fill the existing data when new columns are added, and
+      // should be a fixed value which was evaluated at the definition time. For example, if the
+      // default value is `current_date()`, the "exist default" should be the value of
+      // `current_date()` when the column was defined/altered, instead of when back-fall happens.
+      // Note: the back-fill here is a logical concept. The data source can keep the existing
+      //       data unchanged and let the data reader to return "exist default" for missing
+      //       columns.
+      val existingDefault = Literal(default.getValue.value(), default.getValue.dataType()).sql
+      f.withExistenceDefaultValue(existingDefault).withCurrentDefaultValue(default.getSql)
+    }.getOrElse(f)
+  }
+
+  def structTypeToV2Columns(schema: StructType): Array[Column] = {
+    schema.fields.map(structFieldToV2Column)
+  }
+
+  private def structFieldToV2Column(f: StructField): Column = {
+    def createV2Column(defaultValue: ColumnDefaultValue, metadata: Metadata): Column = {
+      val metadataJSON = if (metadata == Metadata.empty) {
+        null
+      } else {
+        metadata.json
+      }
+      Column.create(
+        f.name, f.dataType, f.nullable, f.getComment().orNull, defaultValue, metadataJSON)
+    }
+    if (f.getCurrentDefaultValue().isDefined && f.getExistenceDefaultValue().isDefined) {
+      val e = analyze(f, EXISTS_DEFAULT_COLUMN_METADATA_KEY)
+      assert(e.resolved && e.foldable,
+        "exist default must be simple SQL string that is resolved and foldable, " +

Review Comment:
   ```suggestion
           "The existence default value must be a simple SQL string that is resolved and foldable, " +
   ```



##########
sql/catalyst/src/main/scala/org/apache/spark/sql/connector/catalog/CatalogV2Util.scala:
##########
@@ -431,4 +431,73 @@ private[sql] object CatalogV2Util {
       .getOrElse(catalogManager.v2SessionCatalog)
       .asTableCatalog
   }
+
+  def v2ColumnsToStructType(columns: Array[Column]): StructType = {

Review Comment:
   could we have method comments here the describe who is expected to call these methods, and what they convert to and from?



##########
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala:
##########
@@ -3108,7 +3108,7 @@ object SQLConf {
         "provided values when the corresponding fields are not present in storage.")
       .version("3.4.0")
       .stringConf
-      .createWithDefault("csv,json,orc,parquet")
+      .createWithDefault("csv,json,orc,parquet,hive")

Review Comment:
   Is this safe? What data source operator implements the `hive` provider? Does it support filling in the existence default values? Do we have any default-value test cases in this PR where the table is `using hive`?



##########
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/connector/ColumnImpl.scala:
##########
@@ -0,0 +1,30 @@
+/*
+ * 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.spark.sql.internal.connector
+
+import org.apache.spark.sql.connector.catalog.{Column, ColumnDefaultValue}
+import org.apache.spark.sql.types.DataType
+
+// The default implementation of v2 column.

Review Comment:
   ```suggestion
   // The standard concrete implementation of data source V2 column.
   ```



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