cloud-fan commented on code in PR #56688:
URL: https://github.com/apache/spark/pull/56688#discussion_r3462830475
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sql/connect/client/jdbc/src/main/scala/org/apache/spark/sql/connect/client/jdbc/SparkConnectDatabaseMetaData.scala:
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@@ -598,14 +598,54 @@ class SparkConnectDatabaseMetaData(conn:
SparkConnectConnection) extends Databas
catalog: String, schema: String, table: String): ResultSet =
throw new SQLFeatureNotSupportedException
- override def getPrimaryKeys(catalog: String, schema: String, table: String):
ResultSet =
- throw new SQLFeatureNotSupportedException
+ // Spark supports informational PRIMARY KEY constraints on DSv2 tables
(SPARK-51207), but the
+ // Spark Connect JDBC client cannot retrieve them in a structured way yet,
so return an empty
+ // result set instead of throwing. JDBC clients call this during schema
introspection.
+ override def getPrimaryKeys(catalog: String, schema: String, table: String):
ResultSet = {
+ conn.checkOpen()
- override def getImportedKeys(catalog: String, schema: String, table:
String): ResultSet =
- throw new SQLFeatureNotSupportedException
+ val df = conn.spark.emptyDataFrame
+ .withColumn("TABLE_CAT", lit(""))
+ .withColumn("TABLE_SCHEM", lit(""))
+ .withColumn("TABLE_NAME", lit(""))
+ .withColumn("COLUMN_NAME", lit(""))
+ .withColumn("KEY_SEQ", lit(0.toShort))
+ .withColumn("PK_NAME", lit(""))
+ new SparkConnectResultSet(df.collectResult())
+ }
- override def getExportedKeys(catalog: String, schema: String, table:
String): ResultSet =
- throw new SQLFeatureNotSupportedException
+ // getImportedKeys and getExportedKeys share the JDBC foreign-key result
schema. Spark supports
+ // informational FOREIGN KEY constraints on DSv2 tables (SPARK-51207), but
the Spark Connect JDBC
+ // client cannot retrieve them in a structured way yet, so both return an
empty result set
+ // instead of throwing.
+ private def emptyForeignKeys: ResultSet = {
+ val df = conn.spark.emptyDataFrame
+ .withColumn("PKTABLE_CAT", lit(""))
+ .withColumn("PKTABLE_SCHEM", lit(""))
+ .withColumn("PKTABLE_NAME", lit(""))
+ .withColumn("PKCOLUMN_NAME", lit(""))
+ .withColumn("FKTABLE_CAT", lit(""))
+ .withColumn("FKTABLE_SCHEM", lit(""))
+ .withColumn("FKTABLE_NAME", lit(""))
+ .withColumn("FKCOLUMN_NAME", lit(""))
+ .withColumn("KEY_SEQ", lit(0.toShort))
+ .withColumn("UPDATE_RULE", lit(0.toShort))
+ .withColumn("DELETE_RULE", lit(0.toShort))
+ .withColumn("FK_NAME", lit(""))
+ .withColumn("PK_NAME", lit(""))
+ .withColumn("DEFERRABILITY", lit(0.toShort))
+ new SparkConnectResultSet(df.collectResult())
+ }
+
+ override def getImportedKeys(catalog: String, schema: String, table:
String): ResultSet = {
+ conn.checkOpen()
+ emptyForeignKeys
+ }
+
+ override def getExportedKeys(catalog: String, schema: String, table:
String): ResultSet = {
+ conn.checkOpen()
+ emptyForeignKeys
+ }
override def getCrossReference(
Review Comment:
Was leaving `getCrossReference` throwing intentional? It returns the same
14-column JDBC foreign-key schema as `getImportedKeys`/`getExportedKeys`, so
the new `emptyForeignKeys` helper applies verbatim, and your rationale (the
Connect client can't read FK constraints structurally, so return empty rather
than throw) holds identically here. As written, a client probing
cross-references still hits the `SQLFeatureNotSupportedException` this PR is
removing for the other two FK methods. I'd return `emptyForeignKeys` here too;
if it's a deliberate scope cut, worth a note in the PR description alongside
the `getFunctions` one.
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