Thoughts On Cost-Based Optimizers

Joe Chang has the makings of an academic paper on the shortcomings of the current SQL Server cost optimizer model:

It might seem that given the pace of hardware change, such old model cannot possibly valid, resulting horrible execution plans. Around 1995 or so, the high-performance HDD was 7200RPM with a sequential bandwidth of 4-5MB/s. The mean rotational latency for 7200RPM is 4ms. An average seek time of 8.5ms seems reasonable, though I have not kept any documentation from this period. This would correspond to 80 IOPS per disk at queue depth 1 per HDD. So, it seems curious that the SQL Server cost model is based on the random IOPS of 4 disks, but the sequential IO of 2 HDDs.

Performance HDDs progressed first to 10K RPM around 1996, and then to 15K around 2000, with corresponding rotational latencies of 3 and 2ms respectively. Average seek time was reduced over time to 3ms with developments in powerful rare-earth magnets. The 10K HDD could support 125 IOPS and 200 IOPS for the 15K HDD. But no further progress was made on HDD rotational speed. In same time period, hard disk sequential IO phenomenally quickly exceeding 100MB/s in the fourth generation 15K HDD around 2005.

In other words, the SQL Server cost model is based on a 1350/320 = 4.2 ratio. But 15K HDDs in the mid-2000’s were 100MB/s × 128 pages/MB = 12,800 pages/sec sequential to 200 IOPS random for a ratio of 64:1. It turns out that achieving nearly the sequential IO capability of HDDs from SQL Server required a special layout strategy, as outlined in the Fast Track Data Warehouse Reference Architecture papers, which few people followed. This was due to the fixed, inflexible IO pattern of SQL Server, which required the disk configuration to match that of SQL Server instead of being able to adjust the IO pattern to match that of the storage configuration.

It’s worth taking the time to read.  I like Glenn Berry’s idea in the comments of building relative CPU/IO/memory measures and applying them rather than using the same values that were good for twenty years ago.

Related Posts

Understanding Hash Match Aggregates

Itzik Ben-Gan continues his series on grouping and aggregating data by looking at the hash match aggregation process: The estimated CPU cost for the Hash Aggregate in the plan for Query 8 is 0.166344, and in Query 9 is 0.16903. It could be an interesting exercise to try and figure out exactly in what way […]

Read More

Analytics Platform System V7 Released

Microsoft has released a new version of their Analytics Platform System: Microsoft is pleased to announce that the Analytics Platform System (APS) appliance update 7 (AU7) is now generally available. APS is Microsoft’s scale-out Massively Parallel Processing (MPP) system based on SQL Server for data warehouse specific workloads on-premises. Customers will get significantly improved query […]

Read More

Categories

February 2017
MTWTFSS
« Jan Mar »
 12345
6789101112
13141516171819
20212223242526
2728