cloud-fan commented on a change in pull request #27428:
URL: https://github.com/apache/spark/pull/27428#discussion_r453511010
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/RewriteDistinctAggregates.scala
##########
@@ -102,23 +102,126 @@ import org.apache.spark.sql.types.IntegerType
* {{{
* Aggregate(
* key = ['key]
- * functions = [count(if (('gid = 1)) 'cat1 else null),
- * count(if (('gid = 2)) 'cat2 else null),
+ * functions = [count(if (('gid = 1)) '_gen_attr_1 else null),
+ * count(if (('gid = 2)) '_gen_attr_2 else null),
* first(if (('gid = 0)) 'total else null) ignore nulls]
* output = ['key, 'cat1_cnt, 'cat2_cnt, 'total])
* Aggregate(
- * key = ['key, 'cat1, 'cat2, 'gid]
- * functions = [sum('value) with FILTER('id > 1)]
- * output = ['key, 'cat1, 'cat2, 'gid, 'total])
+ * key = ['key, '_gen_attr_1, '_gen_attr_2, 'gid]
+ * functions = [sum('_gen_attr_3)]
+ * output = ['key, '_gen_attr_1, '_gen_attr_2, 'gid, 'total])
* Expand(
- * projections = [('key, null, null, 0, cast('value as bigint), 'id),
+ * projections = [('key, null, null, 0, if ('id > 1) cast('value as
bigint) else null, 'id),
* ('key, 'cat1, null, 1, null, null),
* ('key, null, 'cat2, 2, null, null)]
- * output = ['key, 'cat1, 'cat2, 'gid, 'value, 'id])
+ * output = ['key, '_gen_attr_1, '_gen_attr_2, 'gid, '_gen_attr_3, 'id])
+ * LocalTableScan [...]
+ * }}}
+ *
+ * Third example: single distinct aggregate function with filter clauses and
have
+ * not other distinct aggregate function (in sql):
+ * {{{
+ * SELECT
+ * COUNT(DISTINCT cat1) FILTER (WHERE id > 1) as cat1_cnt,
+ * SUM(value) AS total
+ * FROM
+ * data
+ * GROUP BY
+ * key
+ * }}}
+ *
+ * This translates to the following (pseudo) logical plan:
+ * {{{
+ * Aggregate(
+ * key = ['key]
+ * functions = [COUNT(DISTINCT 'cat1) with FILTER('id > 1),
+ * sum('value)]
+ * output = ['key, 'cat1_cnt, 'total])
+ * LocalTableScan [...]
+ * }}}
+ *
+ * This rule rewrites this logical plan to the following (pseudo) logical plan:
+ * {{{
+ * Aggregate(
+ * key = ['key]
+ * functions = [count('_gen_attr_1),
+ * sum('_gen_attr_2)]
+ * output = ['key, 'cat1_cnt, 'total])
+ * Project(
+ * projectionList = ['key, if ('id > 1) 'cat1 else null, cast('value as
bigint)]
+ * output = ['key, '_gen_attr_1, '_gen_attr_2])
* LocalTableScan [...]
* }}}
*
- * The rule does the following things here:
+ * Four example: single distinct aggregate function with filter clauses (in
sql):
+ * {{{
+ * SELECT
+ * COUNT(DISTINCT cat1) FILTER (WHERE id > 1) as cat1_cnt,
+ * COUNT(DISTINCT cat2) as cat2_cnt,
+ * SUM(value) AS total
+ * FROM
+ * data
+ * GROUP BY
+ * key
+ * }}}
+ *
+ * This translates to the following (pseudo) logical plan:
+ * {{{
+ * Aggregate(
+ * key = ['key]
+ * functions = [COUNT(DISTINCT 'cat1) with FILTER('id > 1),
+ * COUNT(DISTINCT 'cat2),
+ * sum('value)]
+ * output = ['key, 'cat1_cnt, 'cat2_cnt, 'total])
+ * LocalTableScan [...]
+ * }}}
+ *
+ * This rule rewrites this logical plan to the following (pseudo) logical plan:
+ * {{{
+ * Aggregate(
+ * key = ['key]
+ * functions = [count(if (('gid = 1)) '_gen_attr_1 else null),
+ * count(if (('gid = 2)) '_gen_attr_2 else null),
+ * first(if (('gid = 0)) 'total else null) ignore nulls]
+ * output = ['key, 'cat1_cnt, 'cat2_cnt, 'total])
+ * Aggregate(
+ * key = ['key, '_gen_attr_1, '_gen_attr_2, 'gid]
+ * functions = [sum('_gen_attr_3)]
+ * output = ['key, '_gen_attr_1, '_gen_attr_2, 'gid, 'total])
+ * Expand(
+ * projections = [('key, null, null, 0, cast('value as bigint)),
+ * ('key, if ('id > 1) 'cat1 else null, null, 1, null),
+ * ('key, null, 'cat2, 2, null)]
+ * output = ['key, '_gen_attr_1, '_gen_attr_2, 'gid, '_gen_attr_3])
+ * LocalTableScan [...]
+ * }}}
+ *
+ * The rule consists of the two phases as follows:
+ *
+ * In the first phase, if the aggregate query exists filter clauses, project
the output of
+ * the child of the aggregate query:
+ * 1. Project the data. There are three aggregation groups in this query:
+ * i. the non-distinct group;
+ * ii. the distinct 'cat1 group;
+ * iii. the distinct 'cat2 group with filter clause.
+ * Because there is at least one group with filter clause (e.g. the
distinct 'cat2
+ * group with filter clause), then will project the data.
+ * 2. Avoid projections that may output the same attributes. There are three
aggregation groups
+ * in this query:
+ * i. the non-distinct 'cat1 group;
+ * ii. the distinct 'cat1 group;
+ * iii. the distinct 'cat1 group with filter clause.
Review comment:
We don't need to repeat these 3 groups.
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