Redshift EXCEPT 比 LEFT JOIN 慢得多

Question

我正在尝试将暂存 table ('new data') 与另一个 table ('existing data') 进行比较以识别 added/changed/removed 行，并最终一个更新。这是一项昂贵的操作 - 大型数据集上的完整差异。为了语法清晰，我真的很想使用 EXCEPT 命令，但我遇到了严重的性能问题，发现 LEFT JOIN 更好。

两个 table 具有相似的行数和相同的架构（几乎 - 'second' table 有一个额外的 created_date 列）。

他们共享 distkey(date) 和 sortkey(date, id1, id2)；我什至在 EXCEPT 语句中指定 'correct' 顺序的列来帮助优化器。

每个测试大小的数据子集的查询计划如下。

explain
select date, id1, id2, id3, value, attr1, attr2, attr3 from new_data
except select date, id1, id2, id3, value, attr1, attr2, attr3 from existing_data;

XN SetOp Except  (cost=1000002817944.78..1000003266822.61 rows=1995013 width=1637)
  ->  XN Sort  (cost=1000002817944.78..1000002867820.09 rows=19950126 width=1637)
        Sort Key: date, id1, id2, id3, value, attr1, attr2, attr3
        ->  XN Append  (cost=0.00..399002.52 rows=19950126 width=1637)
              ->  XN Subquery Scan "*SELECT* 1"  (cost=0.00..199501.26 rows=9975063 width=1637)
                    ->  XN Seq Scan on new_data  (cost=0.00..99750.63 rows=9975063 width=1637)
              ->  XN Subquery Scan "*SELECT* 2"  (cost=0.00..199501.26 rows=9975063 width=1636)
                    ->  XN Seq Scan on existing_data  (cost=0.00..99750.63 rows=9975063 width=1636)

对比一下我的丑多了LEFT JOIN

explain
select t1.* from new_data t1 
left outer join existing_data t2 on     
    t1.date = t2.date
    and t1.id1 = t2.id1
    and coalesce(t1.id2, -1) = coalesce(t2.id2, -1)
    and coalesce(t1.id3, -1) = coalesce(t2.id3, -1)
    and coalesce(t1.value, -1) = coalesce(t2.value, -1) 
    and coalesce(t1.attr1, '') = coalesce(t2.attr1, '')
    and coalesce(t1.attr2, '') = coalesce(t2.attr2, '')
    and coalesce(t1.attr3, '') = coalesce(t2.attr3, '')
where t2.id1 is null;

XN Merge Left Join DS_DIST_NONE  (cost=0.00..68706795.68 rows=9975063 width=1637)
  Merge Cond: (("outer".date = "inner".date) AND (("outer".id1)::bigint = "inner".id1))
  Join Filter: (((COALESCE("outer".id2, -1))::bigint = COALESCE("inner".id2, -1::bigint)) AND ((COALESCE("outer".id3, -1))::bigint = COALESCE("inner".id3, -1::bigint)) AND ((COALESCE("outer".value, -1::numeric))::double precision = COALESCE("inner".value, -1::double precision)) AND ((COALESCE("outer".attr1, ''::character varying))::text = (COALESCE("inner".attr1, ''::character varying))::text) AND ((COALESCE("outer".attr2, ''::character varying))::text = (COALESCE("inner".attr2, ''::character varying))::text) AND ((COALESCE("outer".attr3, ''::character varying))::text = (COALESCE("inner".attr3, ''::character varying))::text))
  Filter: ("inner".id1 IS NULL)
  ->  XN Seq Scan on new_data t1  (cost=0.00..99750.63 rows=9975063 width=1637)
  ->  XN Seq Scan on existing_data t2  (cost=0.00..99750.63 rows=9975063 width=1636)

查询成本为 1000003266822.61 与 68706795.68。我知道我不应该跨查询进行比较，但它在执行时间中得到了证明。知道为什么 EXCEPT 语句比 LEFT JOIN 慢得多吗？

Answer 1

left join 正在为每个（可能是有序的）键值生成一堆交叉连接的行，然后通过 on 过滤掉不需要的行；它也可以在（可能是有序的）旧键值超过新键值时停止，因为不再有匹配项——这还涉及通过一些 coalesce SARG 智能进行的一些推理。 except 首先对所有内容进行排序。在这种情况下，排序的成本高于生成和丢弃行，乘以遍历右侧每个键的行 table。当然，优化器可以在其 except 计划中包含一个 outer join 习语——但它显然没有。

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Redshift EXCEPT 比 LEFT JOIN 慢得多

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