Github user chenghao-intel commented on a diff in the pull request:
https://github.com/apache/spark/pull/3247#discussion_r27783787
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala
---
@@ -17,285 +17,159 @@
package org.apache.spark.sql.catalyst.expressions
-import com.clearspring.analytics.stream.cardinality.HyperLogLog
-
import org.apache.spark.sql.types._
-import org.apache.spark.sql.catalyst.trees
-import org.apache.spark.sql.catalyst.errors.TreeNodeException
-import org.apache.spark.util.collection.OpenHashSet
-
-abstract class AggregateExpression extends Expression {
- self: Product =>
- /**
- * Creates a new instance that can be used to compute this aggregate
expression for a group
- * of input rows/
- */
- def newInstance(): AggregateFunction
- /**
- * [[AggregateExpression.eval]] should never be invoked because
[[AggregateExpression]]'s are
- * replaced with a physical aggregate operator at runtime.
- */
- override def eval(input: Row = null): EvaluatedType =
- throw new TreeNodeException(this, s"No function to evaluate
expression. type: ${this.nodeName}")
-}
+/**
+ * This is from
org.apache.hadoop.hive.ql.udf.generic.GenericUDAFEvaluator.Mode
+ * Just a hint for the UDAF developers which stage we are about to process,
+ * However, we probably don't want the developers knows so many details,
here
+ * is just for keep consistent with Hive (when integrated with Hive), need
to
+ * figure out if we have work around for that soon.
+ */
+@deprecated
+trait Mode
--- End diff --
This is also for integrated with Hive UDAF.We have the casting between Hive
Mode and Spark SQL Mode.
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