maropu commented on a change in pull request #27058: [SPARK-30276][SQL] Support
Filter expression allows simultaneous use of DISTINCT
URL: https://github.com/apache/spark/pull/27058#discussion_r369536759
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/RewriteDistinctAggregates.scala
##########
@@ -118,7 +118,64 @@ import org.apache.spark.sql.types.IntegerType
* LocalTableScan [...]
* }}}
*
- * The rule does the following things here:
+ * Third 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_distinct_1 else null),
+ * count(if (('gid = 2)) '_gen_distinct_2 else null),
+ * first(if (('gid = 0)) 'total else null) ignore nulls]
+ * output = ['key, 'cat1_cnt, 'cat2_cnt, 'total])
+ * Aggregate(
+ * key = ['key, '_gen_distinct_1, '_gen_distinct_2, 'gid]
+ * functions = [sum('value)]
+ * output = ['key, '_gen_distinct_1, '_gen_distinct_2, 'gid, 'total])
+ * Expand(
+ * projections = [('key, null, null, 0, 'value),
+ * ('key, '_gen_distinct_1, null, 1, null),
+ * ('key, null, '_gen_distinct_2, 2, null)]
+ * output = ['key, '_gen_distinct_1, '_gen_distinct_2, 'gid, 'value])
+ * Expand(
+ * projections = [('key, if ('id > 1) 'cat1 else null, 'cat2,
cast('value as bigint))]
+ * output = ['key, '_gen_distinct_1, '_gen_distinct_2, 'value])
+ * LocalTableScan [...]
+ * }}}
+ *
+ * The rule consists of the two phases as follows.
+ *
+ * In the first phase, expands distinct aggregates which exists filter clause:
+ * 1. Guaranteed to compute filter clauses in the first aggregate locally.
+ * 2. The attributes referenced by different distinct aggregate expressions
are likely to overlap,
+ * and if no additional processing is performed, data loss will occur. To
prevent this, we
+ * generate new attributes and replace the original ones.
+ * 3. If we apply the first phase to distinct aggregate expressions which
exists filter
+ * clause, the aggregate after expand may have at least two distinct
aggregates, so we need to
+ * apply the second phase too. Please refer to the second phase for more
details.
+ *
+ * In the second phase, rewrite when aggregate exists at least two distinct
aggregates:
* 1. Expand the data. There are three aggregation groups in this query:
Review comment:
Really? I think the statements below point to the second query:
https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/RewriteDistinctAggregates.scala#L78-L119
```
* i. the non-distinct group;
* ii. the distinct 'cat1 group;
* iii. the distinct 'cat2 group.
```
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