redis数据量大时bgsave线程阻塞redis原因
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Latency generated by fork
In order to generate the RDB file in background, or to rewrite the Append Only File if AOF persistence is enabled, Redis has to fork background processes. The fork operation (running in the main thread) can induce latency by itself.
Forking is an expensive operation on most Unix-like systems, since it involves copying a good number of objects linked to the process. This is especially true for the page table associated to the virtual memory mechanism.
For instance on a Linux/AMD64 system, the memory is divided in 4 kB pages. To convert virtual addresses to physical addresses, each process stores a page table (actually represented as a tree) containing at least a pointer per page of the address space of the process. So a large 24 GB Redis instance requires a page table of 24 GB / 4 kB * 8 = 48 MB.
When a background save is performed, this instance will have to be forked, which will involve allocating and copying 48 MB of memory. It takes time and CPU, especially on virtual machines where allocation and initialization of a large memory chunk can be expensive.
Fork time in different systems
Modern hardware is pretty fast at copying the page table, but Xen is not. The problem with Xen is not virtualization-specific, but Xen-specific. For instance using VMware or Virtual Box does not result into slow fork time. The following is a table that compares fork time for different Redis instance size. Data is obtained performing a BGSAVE and looking at the latest_fork_usec filed in the INFO command output.
However the good news is that new types of EC2 HVM based instances are much better with fork times, almost on par with physical servers, so for example using m3.medium (or better) instances will provide good results.
- Linux beefy VM on VMware 6.0GB RSS forked in 77 milliseconds (12.8 milliseconds per GB).
- Linux running on physical machine (Unknown HW) 6.1GB RSS forked in 80 milliseconds (13.1 milliseconds per GB)
- Linux running on physical machine (Xeon @ 2.27Ghz) 6.9GB RSS forked into 62 milliseconds (9 milliseconds per GB).
- Linux VM on 6sync (KVM) 360 MB RSS forked in 8.2 milliseconds (23.3 milliseconds per GB).
- Linux VM on EC2, old instance types (Xen) 6.1GB RSS forked in 1460 milliseconds (239.3 milliseconds per GB).
- Linux VM on EC2, new instance types (Xen) 1GB RSS forked in 10 milliseconds (10 milliseconds per GB).
- Linux VM on Linode (Xen) 0.9GBRSS forked into 382 milliseconds (424 milliseconds per GB).
As you can see certain VMs running on Xen have a performance hit that is between one order to two orders of magnitude. For EC2 users the suggestion is simple: use modern HVM based instances.
标签：fork,大时,redis,per,GB,数据量,Linux,forked,milliseconds 来源： https://www.cnblogs.com/lccsblog/p/11982047.html