[GitHub] [incubator-sedona] douglasdennis commented on a diff in pull request #693: [SEDONA-166] Support type-safe dataframe style API

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douglasdennis commented on code in PR #693:
URL: https://github.com/apache/incubator-sedona/pull/693#discussion_r977222536


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sql/src/main/scala/org/apache/spark/sql/sedona_sql/expressions/st_aggregates.scala:
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@@ -0,0 +1,40 @@
+/*
+ * 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.sedona_sql.expressions
+
+import org.apache.spark.sql.catalyst.expressions.Expression
+import org.apache.spark.sql.Column
+import org.apache.spark.sql.sedona_sql.expressions_udaf.{ST_Envelope_Aggr => ST_Envelope_Aggr_udaf, ST_Intersection_Aggr => ST_Intersection_Aggr_udaf, ST_Union_Aggr => ST_Union_Aggr_udaf}
+
+object st_aggregates extends DataFrameAPI {

Review Comment:
   Are you asking if the st_aggregates object is needed? If so then I think it does. This allows for something like this:
   ```
   df.groupBy().agg(ST_Union_Aggr("geometry").as("geometry"))
   ```
   If that's not what you meant then apologies.
   
   I didn't realize that UserDefinedAggregateFunction was depricated though. I was actually using this tutorial for reference to understand how this works on the Scala side: https://docs.databricks.com/spark/latest/spark-sql/udaf-scala.html
   
   It looks like from what else I've read that I'm supposed to pass an Aggregator to the udaf function, so I'll plan to do that.



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