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[SPARK-33879][SQL] Char Varchar values fails w/ match error as partition columns #30887

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[SPARK-33879][SQL] Char Varchar values fails w/ match error as partition columns #30887

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[SPARK-33879][SQL] Char Varchar values fails w/ match error as partit…
yaooqinn Dec 22, 2020
6e3e39b
prunePartitionsByFilter
yaooqinn Dec 22, 2020
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4 changes: 3 additions & 1 deletion sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/ExternalCatalogUtils.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,7 @@ import org.apache.spark.sql.AnalysisException
import org.apache.spark.sql.catalyst.analysis.Resolver
import org.apache.spark.sql.catalyst.catalog.CatalogTypes.TablePartitionSpec
import org.apache.spark.sql.catalyst.expressions.{And, AttributeReference, BoundReference, Expression, Predicate}
import org.apache.spark.sql.catalyst.util.CharVarcharUtils

object ExternalCatalogUtils {
// This duplicates default value of Hive `ConfVars.DEFAULTPARTITIONNAME`, since catalyst doesn't
Expand Down Expand Up @@ -135,7 +136,8 @@ object ExternalCatalogUtils {
if (predicates.isEmpty) {
inputPartitions
} else {
val partitionSchema = catalogTable.partitionSchema
val partitionSchema = CharVarcharUtils.replaceCharVarcharWithStringInSchema(
catalogTable.partitionSchema)
val partitionColumnNames = catalogTable.partitionColumnNames.toSet

val nonPartitionPruningPredicates = predicates.filterNot {
Expand Down
20 changes: 20 additions & 0 deletions sql/core/src/test/scala/org/apache/spark/sql/CharVarcharTestSuite.scala
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Expand Up @@ -356,6 +356,26 @@ trait CharVarcharTestSuite extends QueryTest with SQLTestUtils {
}
}

test("char type comparison: partition pruning") {
withTable("t") {
sql(s"CREATE TABLE t(i INT, c1 CHAR(2), c2 VARCHAR(5)) USING $format PARTITIONED BY (c1, c2)")
sql("INSERT INTO t VALUES (1, 'a', 'a')")
Seq(("c1 = 'a'", true),
("'a' = c1", true),
("c1 = 'a '", true),
("c1 > 'a'", false),
("c1 IN ('a', 'b')", true),
("c2 = 'a '", false),
("c2 = 'a'", true),
("c2 IN ('a', 'b')", true)).foreach { case (con, res) =>
val df = spark.table("t")
withClue(con) {
checkAnswer(df.where(con), df.where(res.toString))
}
}
}
}

test("char type comparison: join") {
withTable("t1", "t2") {
sql(s"CREATE TABLE t1(c CHAR(2)) USING $format")
Expand Down