Question

下面是一些细节。

查询1 ：也使用图遍历附加执行计划。

这里我在CollectionA和CollectionB之间使用边缘。

查询字符串：

for u in CollectionA filter u.FilterA == @opId and u.FilterB >= @startTimeInLong and u.FilterB <= @endTimeInLong 
for v in 1..1 OUTBOUND u CollectionALinksCollectionB
filter 
v.FilterC == null return v

Execution plan:

     Id   NodeType           Est.   Comment
      1   SingletonNode         1   * ROOT
      9   IndexNode         45088     - FOR u IN CollectionA   /* skiplist index scan */
      5   TraversalNode         1       - FOR v  /* vertex */ IN 1..1  /* min..maxPathDepth */ OUTBOUND u /* startnode */  CollectionALinksCollectionB
      6   CalculationNode       1       - LET #6 = (v.`ReceivedRating` == null)   /* simple expression */
      7   FilterNode            1       - FILTER #6
      8   ReturnNode            1       - RETURN v

    Indexes used:
     By   Type       Collection                    Unique   Sparse   Selectivity   Fields                                Ranges
      9   skiplist   CollectionA                  false    false       100.00 %   [ `FilterA`, `FilterB` ]   ((u.`FilterA` == "8277") && (u.`FilterB` >= 1526947200000) && (u.`FilterB` <= 1541030400000))
      5   edge       CollectionALinksCollectionB   false    false       100.00 %   [ `_from` ]                           base OUTBOUND

    Traversals on graphs:
     Id   Depth   Vertex collections   Edge collections              Options                                   Filter conditions
      5   1..1                         CollectionALinksCollectionB   uniqueVertices: none, uniqueEdges: path   

    Optimization rules applied:
     Id   RuleName
      1   use-indexes
      2   remove-filter-covered-by-index
      3   remove-unnecessary-calculations-2

查询2：

         Query string:
          for u in CollectionA filter u.FilterA == @opId and u.FilterB >= @startTimeInLong and 
          u.FilterB <= @endTimeInLong 
           for v in CollectionB
          filter 
          v._key==u._key and
          v.FilterC == null return v
Execution plan:

     Id   NodeType           Est.   Comment
      1   SingletonNode         1   * ROOT
      8   CalculationNode       1     - LET #6 = CollectionB   /* all collection documents */   /* v8 expression */
     11   IndexNode         45088     - FOR u IN CollectionA   /* skiplist index scan */
     10   IndexNode         45088       - FOR v IN CollectionB   /* primary index scan, scan only */
     12   CalculationNode   45088         - LET #4 = (CollectionB   /* all collection documents */.`FilterC` == null)   /* v8 expression */
      7   FilterNode        45088         - FILTER #4
      9   ReturnNode        45088         - RETURN #6

    Indexes used:
     By   Type       Collection       Unique   Sparse   Selectivity   Fields                                Ranges
     11   skiplist   CollectionA     false    false       100.00 %   [ `FilterA`, `FilterB` ]   ((u.`FilterA` == "8277") && (u.`FilterB` >= 1526947200000) && (u.`FilterB` <= 1541030400000))
     10   primary    CollectionB   true     false       100.00 %   [ `_key` ]                            (CollectionB.`_key` == u.`_key`)

    Optimization rules applied:
     Id   RuleName
      1   move-calculations-up
      2   use-indexes
      3   remove-filter-covered-by-index
      4   remove-unnecessary-calculations-2

查询1的性能如何比查询2好。而且，对于较小的数据集，查询结果几乎相似，但是对于较大的数据，查询1的性能更好。

有人可以详细解释一下图遍历在这里有何帮助

使用顶点和边时性能差异VS ArangoDB中的联接

0 个答案: