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new 362a4d43159d [SPARK-46949][SQL] Support CHAR/VARCHAR through
ResolveDefaultColumns
362a4d43159d is described below
commit 362a4d43159d73ef2e4c4f9267b572046220680f
Author: Kent Yao <y...@apache.org>
AuthorDate: Fri Feb 2 17:39:12 2024 +0800
[SPARK-46949][SQL] Support CHAR/VARCHAR through ResolveDefaultColumns
### What changes were proposed in this pull request?
We have issues resolving column definitions with default values, i.e., `c
CHAR(5) DEFAULT 'foo'`, `v VARCHAR(10) DEFAULT 'bar'`. The reason is that
CAHR/VARCHAR types in schemas are not supplanted with STRING type to align with
the value expression.
This PR fixes these issues in `ResolveDefaultColumns`, which seems to only
cover the v1 tables. When I applied some related tests to v2 tables, they had
the same issues. But beyond that, there are some other front-loading needs to
be addressed. In this case, I'd like to separate v2 from the v1 PR.
### Why are the changes needed?
bugfix
```
spark-sql (default)> CREATE TABLE t( c CHAR(5) DEFAULT 'spark') USING
parquet;
[INVALID_DEFAULT_VALUE.DATA_TYPE] Failed to execute CREATE TABLE command
because the destination table column `c` has a DEFAULT value 'spark', which
requires "CHAR(5)" type, but the statement provided a value of incompatible
"STRING" type.
```
### Does this PR introduce _any_ user-facing change?
no, bugfix
### How was this patch tested?
new tests
### Was this patch authored or co-authored using generative AI tooling?
no
Closes #44991 from yaooqinn/SPARK-46949.
Authored-by: Kent Yao <y...@apache.org>
Signed-off-by: Kent Yao <y...@apache.org>
---
.../catalyst/util/ResolveDefaultColumnsUtil.scala | 26 +++++++++-----
.../spark/sql/ResolveDefaultColumnsSuite.scala | 41 ++++++++++++++++++++++
2 files changed, 58 insertions(+), 9 deletions(-)
diff --git
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/ResolveDefaultColumnsUtil.scala
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/ResolveDefaultColumnsUtil.scala
index e782e017d1ef..da03de73557f 100644
---
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/ResolveDefaultColumnsUtil.scala
+++
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/ResolveDefaultColumnsUtil.scala
@@ -21,7 +21,7 @@ import scala.collection.mutable.ArrayBuffer
import org.apache.spark.{SparkThrowable, SparkUnsupportedOperationException}
import org.apache.spark.sql.AnalysisException
-import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.{InternalRow, SQLConfHelper}
import org.apache.spark.sql.catalyst.analysis._
import org.apache.spark.sql.catalyst.catalog.{CatalogDatabase,
InMemoryCatalog, SessionCatalog}
import org.apache.spark.sql.catalyst.expressions._
@@ -42,7 +42,9 @@ import org.apache.spark.util.ArrayImplicits._
/**
* This object contains fields to help process DEFAULT columns.
*/
-object ResolveDefaultColumns extends QueryErrorsBase with
ResolveDefaultColumnsUtils {
+object ResolveDefaultColumns extends QueryErrorsBase
+ with ResolveDefaultColumnsUtils
+ with SQLConfHelper {
// Name of attributes representing explicit references to the value stored
in the above
// CURRENT_DEFAULT_COLUMN_METADATA.
val CURRENT_DEFAULT_COLUMN_NAME = "DEFAULT"
@@ -307,25 +309,26 @@ object ResolveDefaultColumns extends QueryErrorsBase with
ResolveDefaultColumnsU
statementType: String,
colName: String,
defaultSQL: String): Expression = {
+ val supplanted = CharVarcharUtils.replaceCharVarcharWithString(dataType)
// Perform implicit coercion from the provided expression type to the
required column type.
- if (dataType == analyzed.dataType) {
+ val ret = if (supplanted == analyzed.dataType) {
analyzed
- } else if (Cast.canUpCast(analyzed.dataType, dataType)) {
- Cast(analyzed, dataType)
+ } else if (Cast.canUpCast(analyzed.dataType, supplanted)) {
+ Cast(analyzed, supplanted)
} else {
// If the provided default value is a literal of a wider type than the
target column, but the
// literal value fits within the narrower type, just coerce it for
convenience. Exclude
// boolean/array/struct/map types from consideration for this type
coercion to avoid
// surprising behavior like interpreting "false" as integer zero.
val result = if (analyzed.isInstanceOf[Literal] &&
- !Seq(dataType, analyzed.dataType).exists(_ match {
+ !Seq(supplanted, analyzed.dataType).exists(_ match {
case _: BooleanType | _: ArrayType | _: StructType | _: MapType =>
true
case _ => false
})) {
try {
- val casted = Cast(analyzed, dataType, evalMode = EvalMode.TRY).eval()
+ val casted = Cast(analyzed, supplanted, evalMode =
EvalMode.TRY).eval()
if (casted != null) {
- Some(Literal(casted, dataType))
+ Some(Literal(casted, supplanted))
} else {
None
}
@@ -339,6 +342,10 @@ object ResolveDefaultColumns extends QueryErrorsBase with
ResolveDefaultColumnsU
statementType, colName, defaultSQL, dataType, analyzed.dataType)
}
}
+ if (!conf.charVarcharAsString &&
CharVarcharUtils.hasCharVarchar(dataType)) {
+ CharVarcharUtils.stringLengthCheck(ret, dataType).eval(EmptyRow)
+ }
+ ret
}
/**
@@ -454,7 +461,8 @@ object ResolveDefaultColumns extends QueryErrorsBase with
ResolveDefaultColumnsU
throw
QueryCompilationErrors.defaultValuesMayNotContainSubQueryExpressions(
statement, colName, default.originalSQL)
} else if (default.resolved) {
- if (!Cast.canUpCast(default.child.dataType, targetType)) {
+ val dataType = CharVarcharUtils.replaceCharVarcharWithString(targetType)
+ if (!Cast.canUpCast(default.child.dataType, dataType)) {
throw QueryCompilationErrors.defaultValuesDataTypeError(
statement, colName, default.originalSQL, targetType,
default.child.dataType)
}
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/ResolveDefaultColumnsSuite.scala
b/sql/core/src/test/scala/org/apache/spark/sql/ResolveDefaultColumnsSuite.scala
index 00529559a485..0b393f4b11b4 100644
---
a/sql/core/src/test/scala/org/apache/spark/sql/ResolveDefaultColumnsSuite.scala
+++
b/sql/core/src/test/scala/org/apache/spark/sql/ResolveDefaultColumnsSuite.scala
@@ -17,6 +17,7 @@
package org.apache.spark.sql
+import org.apache.spark.SparkRuntimeException
import org.apache.spark.sql.test.SharedSparkSession
class ResolveDefaultColumnsSuite extends QueryTest with SharedSparkSession {
@@ -215,4 +216,44 @@ class ResolveDefaultColumnsSuite extends QueryTest with
SharedSparkSession {
}
}
}
+
+ test("SPARK-46949: DDL with valid default char/varchar values") {
+ withTable("t") {
+ val ddl =
+ s"""
+ |CREATE TABLE t(
+ | key int,
+ | v VARCHAR(6) DEFAULT 'apache',
+ | c CHAR(5) DEFAULT 'spark')
+ |USING parquet""".stripMargin
+ sql(ddl)
+ sql("INSERT INTO t (key) VALUES(1)")
+ checkAnswer(sql("select * from t"), Row(1, "apache", "spark"))
+ }
+ }
+
+ test("SPARK-46949: DDL with invalid default char/varchar values") {
+ Seq("CHAR", "VARCHAR").foreach { typeName =>
+ checkError(
+ exception = intercept[SparkRuntimeException](
+ sql(s"CREATE TABLE t(c $typeName(3) DEFAULT 'spark') USING
parquet")),
+ errorClass = "EXCEED_LIMIT_LENGTH",
+ parameters = Map("limit" -> "3"))
+ }
+ }
+
+ test("SPARK-46949: DDL with default char/varchar values need padding") {
+ withTable("t") {
+ val ddl =
+ s"""
+ |CREATE TABLE t(
+ | key int,
+ | v VARCHAR(6) DEFAULT 'apache',
+ | c CHAR(6) DEFAULT 'spark')
+ |USING parquet""".stripMargin
+ sql(ddl)
+ sql("INSERT INTO t (key) VALUES(1)")
+ checkAnswer(sql("select * from t"), Row(1, "apache", "spark "))
+ }
+ }
}
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