Github user hvanhovell commented on a diff in the pull request:
https://github.com/apache/spark/pull/13706#discussion_r67634631
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/command/macros.scala ---
@@ -0,0 +1,69 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.command
+
+import org.apache.spark.sql.{AnalysisException, Row, SparkSession}
+import org.apache.spark.sql.catalyst.expressions._
+
+/**
+ * The DDL command that creates a macro.
+ * To create a temporary macro, the syntax of using this command in SQL is:
+ * {{{
+ * CREATE TEMPORARY MACRO macro_name([col_name col_type, ...])
expression;
+ * }}}
+ */
+case class CreateMacroCommand(
+ macroName: String,
+ columns: Seq[AttributeReference],
+ macroFunction: Expression)
+ extends RunnableCommand {
+
+ override def run(sparkSession: SparkSession): Seq[Row] = {
+ val catalog = sparkSession.sessionState.catalog
+ val macroInfo = columns.mkString(",") + " -> " + macroFunction.toString
+ val info = new ExpressionInfo(macroInfo, macroName)
+ val builder = (children: Seq[Expression]) => {
+ if (children.size != columns.size) {
+ throw new AnalysisException(s"Actual number of columns:
${children.size} != " +
+ s"expected number of columns: ${columns.size} for Macro
$macroName")
+ }
+ macroFunction.transformUp {
+ case b: BoundReference => children(b.ordinal)
--- End diff --
We do not validate the input type here. This would be entirely fine if
macro arguments were defined without a `DataType`. I am not sure what we need
to do here though. We have two options:
- Ignore the DataType and rely on the expressions `inputTypes` to get
casting done. This must be documented though.
- Introduce casts to make sure the input conforms to the required input.
What do you think?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at infrastruct...@apache.org or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
