j1wonpark commented on code in PR #56688:
URL: https://github.com/apache/spark/pull/56688#discussion_r3487096963
##########
sql/connect/client/jdbc/src/main/scala/org/apache/spark/sql/connect/client/jdbc/SparkConnectDatabaseMetaData.scala:
##########
@@ -816,4 +882,77 @@ object SparkConnectDatabaseMetaData {
)
private[jdbc] val TABLE_TYPES = Seq("TABLE", "VIEW")
+
+ // One row of the java.sql.DatabaseMetaData.getTypeInfo result.
+ private type TypeInfoRow =
+ (
+ String, // TYPE_NAME
+ Int, // DATA_TYPE
+ Int, // PRECISION
+ String, // LITERAL_PREFIX
+ String, // LITERAL_SUFFIX
+ String, // CREATE_PARAMS
+ Short, // NULLABLE
+ Boolean, // CASE_SENSITIVE
+ Short, // SEARCHABLE
+ Boolean, // UNSIGNED_ATTRIBUTE
+ Boolean, // FIXED_PREC_SCALE
+ Boolean, // AUTO_INCREMENT
+ String, // LOCAL_TYPE_NAME
+ Short, // MINIMUM_SCALE
+ Short, // MAXIMUM_SCALE
+ Int, // SQL_DATA_TYPE
+ Int, // SQL_DATETIME_SUB
+ Int // NUM_PREC_RADIX
+ )
+
+ // Fills the columns that are constant across all Spark atomic types: every
type is
+ // nullable and searchable, and none are unsigned, fixed-prec-scale, or
auto-increment.
+ // `literalQuote` is used as both the literal prefix and suffix.
+ private def typeRow(
+ typeName: String,
+ dataType: Int,
+ precision: Int,
+ literalQuote: String,
+ createParams: String,
+ caseSensitive: Boolean,
+ minScale: Short,
+ maxScale: Short,
+ numPrecRadix: Int): TypeInfoRow =
+ (
+ typeName,
+ dataType,
+ precision,
+ literalQuote,
+ literalQuote,
+ createParams,
+ typeNullable.toShort,
+ caseSensitive,
+ typeSearchable.toShort,
+ false,
+ false,
+ false,
+ null,
+ minScale,
+ maxScale,
+ 0,
+ 0,
+ numPrecRadix)
+
+ // Static JDBC type metadata for the Spark SQL atomic types, mirroring the
+ // JdbcTypeUtils type-code/precision mapping. Only STRING is case-sensitive.
+ // TIME and TIMESTAMP_NTZ are omitted (new and duplicate JDBC type codes).
+ private[jdbc] val TYPE_INFO: Seq[TypeInfoRow] = Seq(
Review Comment:
You're right, fixed in ca86cb7: non-numeric types now report NULL
`NUM_PREC_RADIX` to mirror `JdbcTypeUtils`.
##########
sql/connect/client/jdbc/src/main/scala/org/apache/spark/sql/connect/client/jdbc/SparkConnectDatabaseMetaData.scala:
##########
@@ -816,4 +882,77 @@ object SparkConnectDatabaseMetaData {
)
private[jdbc] val TABLE_TYPES = Seq("TABLE", "VIEW")
+
+ // One row of the java.sql.DatabaseMetaData.getTypeInfo result.
+ private type TypeInfoRow =
+ (
+ String, // TYPE_NAME
+ Int, // DATA_TYPE
+ Int, // PRECISION
+ String, // LITERAL_PREFIX
+ String, // LITERAL_SUFFIX
+ String, // CREATE_PARAMS
+ Short, // NULLABLE
+ Boolean, // CASE_SENSITIVE
+ Short, // SEARCHABLE
+ Boolean, // UNSIGNED_ATTRIBUTE
+ Boolean, // FIXED_PREC_SCALE
+ Boolean, // AUTO_INCREMENT
+ String, // LOCAL_TYPE_NAME
+ Short, // MINIMUM_SCALE
+ Short, // MAXIMUM_SCALE
+ Int, // SQL_DATA_TYPE
+ Int, // SQL_DATETIME_SUB
+ Int // NUM_PREC_RADIX
+ )
+
+ // Fills the columns that are constant across all Spark atomic types: every
type is
+ // nullable and searchable, and none are unsigned, fixed-prec-scale, or
auto-increment.
+ // `literalQuote` is used as both the literal prefix and suffix.
+ private def typeRow(
+ typeName: String,
+ dataType: Int,
+ precision: Int,
+ literalQuote: String,
+ createParams: String,
+ caseSensitive: Boolean,
+ minScale: Short,
+ maxScale: Short,
+ numPrecRadix: Int): TypeInfoRow =
+ (
+ typeName,
+ dataType,
+ precision,
+ literalQuote,
+ literalQuote,
+ createParams,
+ typeNullable.toShort,
+ caseSensitive,
+ typeSearchable.toShort,
+ false,
+ false,
+ false,
+ null,
+ minScale,
+ maxScale,
+ 0,
+ 0,
+ numPrecRadix)
+
+ // Static JDBC type metadata for the Spark SQL atomic types, mirroring the
+ // JdbcTypeUtils type-code/precision mapping. Only STRING is case-sensitive.
+ // TIME and TIMESTAMP_NTZ are omitted (new and duplicate JDBC type codes).
Review Comment:
Reworded the comment in 6b467f8 to state each reason separately. Left `TIME`
out for now since its maximum PRECISION/scale representation in `getTypeInfo`
isn't settled yet; happy to add it in a follow-up once that's decided.
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