Cost-Based Optimization of Integration Flows - Datenbanken ...

3.5 Experimental Evaluation
(a) Cumulative Execution Time
(b) Cumulative Optimization Time
Figure 3.22: Use Case Comparison of Periodical Re-Optimization
asynchronous optimization but synchronous exchange of plans, where execution is blocked.
As a result both cumulative execution time and elapsed time might have different optimal
∆t configurations. Thus, this parameter is a possibility to fine-tune the optimizer.
Third, with regard to workability, we observed fairly similar results for our other example
plans and statistic variations. Here, we compared the periodical re-optimization with
no-optimization once again. In detail, we executed 20,000 plan instances for each example
plan (P 1 ,P 2 ,P 3 ,P 4 ,P 5 ,P 6 ,P 7 ,P 8 ) and for each execution model. There, we fixed the cardinality
of input data sets to d = 1 (100 kB messages) and used a well-balanced workload
configuration (without correlations and without workload changes). Furthermore, we fixed
an optimization interval of ∆t = 5 min, a sliding window size of ∆w = 5 min and EMA as
the workload aggregation method.
To summarize, we consistently observe execution time reductions (see Figure 3.22(a)).
In the following, we describe in detail how these benefits have been achieved:
• P 1 : This plan was affected by three different optimization techniques. First, the
technique WD1 reordered the two paths of Switch operator o 2 . Furthermore, the
operator sequence (o 7 ,o 8 ,o 9 ) has been rewritten to parallel subflows (o 7 ) and (o 8 ,o 9 ).
Finally, the technique WC1 rescheduled the start of both subflows in order to start
the most time-consuming subflow (o 8 ,o 9 ) first.
• P 2 : No optimization technique affected this plan.
• P 3 : Similar to plan P 1 , the techniques WC2 and WC1 have been applied on the operator
sequence (o 2 ,o 3 ) in order to rewrite this sequence to parallel subflows and to
reschedule the start of these subflows. In addition, the technique WD6 has been applied
in order to pushdown the invariant group-by and thus, exchanged the temporal
order and data dependencies of operators o 4 and o 5 .
• P 4 : For this rather complex plan, only the optimization technique WD9 was applied.
In detail the Join operator o 9 was rewritten from a nested loop join to a subplan of
two (concurrent) Orderby operators and one merge join.
• P 5 : Similar to our first end-to-end comparison scenario, the technique WD4 was applied
for the plan P 5 with the aim of reordering the sequence of Selection operators
(o 2 ,o 3 ,o 4 ).
• P 6 : This plan was affected by a set of techniques. First, the initially given Fork
operator was rescheduled by WC1. Furthermore, the techniques WD11 and WD8
rewrote the two subsequent Setoperation (UNION DISTINCT) operators to a sub-
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