We have several independent tables on a multi-core machine serving Select queries. These tables fit into memory; and each Select queries goes over one table's pages sequentially. In this experiment, there are no indexes or table joins.
When we send concurrent Select queries to these tables, query performance doesn't scale out with the number of CPU cores. We find that complex Select queries scale out better than simpler ones. We also find that increasing the block size from 8 KB to 32 KB, or increasing shared_buffers to include the working set mitigates the problem to some extent.
For our experiments, we chose an 8-core machine with 68 GB of memory from Amazon's EC2 service. We installed PostgreSQL 9.3.1 on the instance, and set shared_buffers to 4 GB.
We then generated 1, 2, 4, and 8 separate tables using the data generator from the industry standard TPC-H benchmark. Each table we generated, called lineitem-1, lineitem-2, etc., had about 750 MB of data. Next, we sent 1, 2, 4, and 8 concurrent Select queries to these tables to observe the scale out behavior. Our expectation was that since this machine had 8 cores, our run times would stay constant all throughout. Also, we would have expected the machine's CPU utilization to go up to 100% at 8 concurrent queries. Neither of those assumptions held true.
We found that query run times degraded as we increased the number of concurrent Select queries. Also, CPU utilization flattened out at less than 50% for the simpler queries. Full results with block size of 8KB are below:
Table select count(*) TPC-H Simple (#6)[2] TPC-H Complex (#1)[1]
1 Table / 1 query 1.5 s 2.5 s 8.4 s
2 Tables / 2 queries 1.5 s 2.5 s 8.4 s
4 Tables / 4 queries 2.0 s 2.9 s 8.8 s
8 Tables / 8 queries 3.3 s 4.0 s 9.6 s
We then increased the block size (BLCKSZ) from 8 KB to 32 KB and recompiled PostgreSQL. This change had a positive impact on query completion times. Here are the new results with block size of 32 KB:
Table select count(*) TPC-H Simple (#6)[2] TPC-H Complex (#1)[1]
1 Table / 1 query 1.5 s 2.3 s 8.0 s
2 Tables / 2 queries 1.5 s 2.3 s 8.0 s
4 Tables / 4 queries 1.6 s 2.4 s 8.1 s
8 Tables / 8 queries 1.8 s 2.7 s 8.3 s
As a quick side, we also repeated the same experiment on an EC2 instance with 16 CPU cores, and found that the scale out behavior became worse there. (We also tried increasing the shared_buffers to 30 GB. This change completely solved the scaling out problem on this instance type, but hurt our performance on the hi1.4xlarge instances.)
Unfortunately, increasing the block size from 8 to 32 KB has other implications for some of our customers. Could you help us out with the problem here?
What can we do to identify the problem's root cause? Can we work around it?
Thank you,
Metin
