Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/4015#discussion_r27710198
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala ---
@@ -43,6 +43,67 @@ import org.apache.spark.util.Utils
import org.apache.spark.{Partition, SparkContext}
/**
+ * Currently we support the default dialect named "sql", associated with
the class
+ * [[DefaultSQLDialect]]
+ *
+ * And we can also provide custom SQL Dialect, for example in Spark SQL
CLI:
+ * {{{
+ *-- switch to "hiveql" dialect
+ * spark-sql>SET spark.sql.dialect=hiveql;
+ * spark-sql>SELECT * FROM src LIMIT 1;
+ *
+ *-- switch to "sql" dialect
+ * spark-sql>SET spark.sql.dialect=sql;
+ * spark-sql>SELECT * FROM src LIMIT 1;
+ *
+ *-- register the new SQL dialect
+ * spark-sql> SET spark.sql.dialect=com.xxx.xxx.SQL99Dialect;
+ * spark-sql> SELECT * FROM src LIMIT 1;
+ *
+ *-- register the non-exist SQL dialect
+ * spark-sql> SET spark.sql.dialect=NotExistedClass;
+ * spark-sql> SELECT * FROM src LIMIT 1;
+ *
+ *-- Exception will be thrown and switch to dialect
+ *-- "sql" (for SQLContext) or
+ *-- "hiveql" (for HiveContext)
+ * }}}
+ */
+@AlphaComponent
+abstract class SQLDialect {
+ /**
+ * We assume the DDLParser has higher priority than any of the other SQL
Parsers,
+ * We need to parse the DDL string first, if we can not get any result,
then will
+ * resort to the dialect parser.
+ */
+ @transient
+ protected[sql] val ddlParser = new DDLParser(parse)
--- End diff --
Since this is going to be a semi-public interface, I'd rather we kept it
very simple `abstract class` (i.e. just have `def parse(sqlText: String):
LogicalPlan`) and leave the handling of the ddlParser and everything else to
the context. We should also clearly state that `LogicalPlan` itself is not a
public interface and thus this part of the code does not have binary
compatibility guarantees like the rest of spark.
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