Semi-Synchronous Replication at Facebook
After intensive testing and hack, we started using Semi-Synchronous MySQL Replication at Facebook production environments. Semi-Synchronous Replication itself was ready since MySQL 5.5 (GA was released 3.5 years ago!), but I’m pretty sure not many people have used in production so far. Here are summary of our objective, enhancements and usage patterns. If you want to hear more in depth, please feel free to ask me at Percona Live this week.
Objective / Why Semisync?
The objective of the Semi-Synchronous Replication is simple — Master Failover without data loss, without full durability.
First, let me describe why the objective is difficult without semisync.
There are a couple of fast slave promotion (master failover) solutions. My own MHA covers both fully automated and semi-automated MySQL failover solution. Fully automated means both failure detection and slave promotion are done automatically. Semi automated means failure detection is not done but slave promotion is done by one command. Time to detect failure is approximately 10 seconds, and actual failover is taking around 5 to 20 seconds, depending on what you are doing during failover (i.e. forcing power off of the crashed master will take at least a few seconds). Total downtime can be less than 30 seconds, if failover works correctly. I’m using term “Fast Failover” in this post, which includes both automated and semi-automated master failover.
Both mysqlfailover and MHA rely on MySQL replication. MySQL replication is asynchronous. So there is a very serious disadvantage — potential data loss risk on master failover. If you use normal MySQL replication and do automated master failover with MHA/mysqlfailover, you can do failover quickly (a few seconds with MHA), but you always have risks of losing recently committed data.
If you don’t want to take any risk of losing data, you can’t do fast master failover with normal MySQL replication. You have to do the following steps in case of master failure.
– Always set fully durable settings on master. By fully durable I mean setting innodb_flush_log_at_trx_commit=1 and sync_binlog=1.
This “safer” approach has two issues.
So, in bad cases, you have to suffer from both longer down time and losing data.
Semi-Synchronous Replication is helpful to prevent from losing data.
If you do not care about data loss risk, there is no reason to use Semi-Synchronous replication. You can use normal MySQL replication and do fast failover with mysqlfailover or MHA. Facebook is one of the companies to care about data loss risk with MySQL, so that’s why we were interested in Semi-Synchronous replication a lot.
Semisync replication was originated from Google in 2007. Official MySQL supported from 5.5. Actual implementation algorithm was substantially different from Google’s.
MySQL Cluster and Galera offers synchronous replication protocol in different ways. I do not cover them in this blog post.
Semi-Synchronous Replication currently has two types of different algorithms — Normal Semisync and Loss-Less Semisync. Let me explain the differences.
Differences between Normal Semisync and Loss-Less Semisync
Loss-Less Semisync is a new Semisync feature supported in official MySQL 5.7. Original implementation was done by Zhou Zhenxing as “Enhanced Semisync” project, and also filed as a bug report. Oracle implemented based on his idea, and named Loss-Less semisync for it. So Enhanced Semisync and Loss-Less Semisync have same meanings. I say Loss-Less semisync in this post.
Normal semisync and loss-less semisync work as below.
1. binlog prepare (doing nothing)
On normal semisync(AFTER_COMMIT), committing to InnoDB is done before waiting for ack from semisync slave, so the committed rows are visible from applications, even though semisync slaves may not have received the data. If master is crashed and none of the slaves received the data, the data is lost but applications may have seen them. This is called phantom reads, and in many cases it’s problematic.
Loss-less semisync (AFTER_SYNC) avoids the problem. Loss-less semisync commits InnoDB after getting ack from one of semisync slaves. So when committed data is visible from applications, one of the semisync slaves have received that. Phantom read risk is much smaller: if both master and the latest semisync slave are down at the same time, data is lost. But it’s much less likely to happen compared to normal semisync.
To avoid data loss and phantom reads, Normal Semisync can’t meet your expectations. Using Loss-Less Semisync is needed.
With Loss-Less Semi-Synchronous replication, committed data should be on one of the slaves, so you can recover from the latest slave. You can always do fast failover here.
When you do fast failover, you can set reduced durable settings on master as well as slaves. Reduced durability means innodb_flush_log_at_trx_commit != 1 and sync_binlog != 1. With Semi-Synchronous replication, you can immediately start failover when master is down. When promoting a slave to the new master, identify the latest slave (highly likely one of the Semi-Synchronous slaves but not guaranteed) and apply differential logs to the new master. Master’s durability does not matter here, because there is no way to access master’s data during failover. So you can safely reduce durability. Reducing durability has a lot of benefits.
– Reducing latency on (group) commit because it doesn’t wait for fsync().
– Reducing IOPS because the number of fsync() calls is significantly reduced: from every commit to every second. Overall disk workloads can be reduced. This is especially helpful if you can’t rely on battery/flash backed write cache.
– Reducing write amplification. Write volume can be reduced a lot, even less than half in some cases. This is important especially when using flash devices, because less write volume increases flash life expectancy.
Requirements for Semisync Deployment
To make Semisync work, you need at least one semisync reader (slave with semisync enabled) within the same (or very close) datacenter as the master. This is for latency. When semisync is enabled, round-trip time(RTT) between master and one of the semisync slaves is added to transaction commit latency. If none of the semisync slave is located within close datacenter, RTT many take tens or hundreds of milliseconds, which means you can commit only 10~100 times from single client. For most environments, this will not work. You need a slave within close datacenter.
To make fast failover work without data loss, you need to make sure Semi-Synchronous Replication is always enabled. MySQL Semisync has a couple of points where optionally semisync is disabled:
If you want to enable semisync always, you make sure these scenario won’t happen. Set infinite or very long timeout, and have at least two semisync readers.
Facebook Enhancements to Semi-Synchronous Replication
We spent a lot of time for testing Semi-Synchronous replication in 2013. We found some S1 bugs, serious performance problems, and some administration issues. Our MySQL Engineering team and Performance team worked for fixing issues and finally our Operations team deployed Semisync in production.
Here are our major enhancements.
Backporting Loss-Less Semisync from 5.7
As described above, Loss-Less Semisync is needed to prevent data loss and phantom reads, so we backported Loss-Less Semisync patch from official MySQL 5.7 to our Facebook MySQL 5.6 branch. It will be merged to WebScaleSQL branch soon.
Interestingly, when we tested semisync performance, Loss-less semisync gave better throughput than normal semisync, especially when the number of clients is large. Normal semisync caused more mutex contentions, which was alleviated with loss-less semisync. Since Loss-less semisync has better data protection mechanism, we concluded there is no reason to use normal semisync here.
Starting from MySQL 5.6, mysqlbinlog supported remote binlog backups, by using –raw and –read-from-remote-server. On remote binlog backups, mysqlbinlog works like a MySQL slave. mysqlbinlog connects to a master, executing BINLOG DUMP command, then receiving binlog events via MySQL replication protocol. This is useful when you want to take backups of the master’s binary logs. Slave’s relay logs and binary logs are not identical to master’s binary logs, so they can’t directly be used as backups of the master’s binary logs.
We extended mysqlbinlog to speak Semisync protocol. The reason of the enhancement is that we wanted to use “semisync mysqlbinlog” as a replacement of local semisync slaves. We usually run slaves on remote datacenters, and we don’t always need local slaves to serve read requests / redundancy. On the other hand, as described at above “Requirements for Semisync Deployment” section, in practice at least two local semisync readers are needed to make semisync work. We didn’t like to run additional two dedicated slaves per master just for semisync. So we invented semisync mysqlbinlog and use it instead of semisync slaves, as shown in the below figure.
Compared to semisync slave, semisync mysqlbinlog has a lot of efficiency wins.
– semisync slave has lots of CPU overheads such as query parsing, making optimizer plans. semisync mysqlbinlog does not have such overhead.
With mysqlbinlog reader, master failover step becomes a bit tricky. This is because mysqlbinlog is not mysqld process so it doesn’t accept any MySQL command, such as CHANGE MASTER. When doing master failover, it is highly likely that one of local mysqlbinlog has the latest binary log events, and the events should be applied to a new master. New MHA version (0.56) supported the feature.
In this configuration, mysqlbinlog processes need to be highly available. If all semisync mysqlbinlog processes are down, semisync is stopped or suffering from long wait time..
Reducing plugin_lock mutex contention
Prior to MySQL 5.6.17, there was a performance bug that transaction commit throughput dropped significantly when there were non-semisync many slaves or binlog readers, even if there was only a few semisync readers. On typical deployments, there are two or three semisync readers and multiple non-semisync readers, so performance drop with many non-semisync readers was annoying.
So switching plugin_lock to read/write lock was actually a bad idea. It was needed to remove below plugin related locks as long as possible. There are four major plugin related mutexes in MySQL.
We also noticed that Delegate classes had read/write locks and they caused very hot contentions (especially Binlog_transmit_delegate::lock). The read/write lock protects a list, so probably switching to lock-free list was possible. BTW we noticed that performance schema did not collect mutex statistics on the mutexes on Delegate classes (bug#70577).
The real problem was all of the above locks were held not only by semisync binlog readers, but also non-semisync binlog readers.
Based on the above factors, we concluded removing all plugin mutexes was not easy, then we decided to optimize to hold these locks by semisync binlog readers only, and not holding by non-semisync binlog readers. The below is a benchmark result.
x-axis was the number of non-semisync binlog readers, y-axis was concurrent INSERT throughput from 100 clients. The number of semisync binlog readers was always 1 to 3. Detailed benchmark conditions were described in a bug report.
With all of the enhancements, we could get pretty good benchmark results with semisync.
This is a mysqlslap insert benchmark on the master, with one semisync slave/mysqlbinlog running. x-axis is the number of clients, y-axis is the number of inserts on the master. Enhanced means loss-less semisync.
Conclusion and Future Plans
After several performance improvements, Semi-Synchronous replication became good enough for us. From performance point of view, I expect that single-threaded application performance will be next low-hanging fruits. On our benchmarks, we got around ~2500 transaction commits per second with semisync (0.4ms per commit). Without semisync, it was easy to get ~10000 transaction commits per second (0.1ms per commit). Of course semisync adds RTT overhead, but on local datacenter network, RTT is much lower than 0.3ms. I think there is another semisync overhead here, so will revisit this issue and will work with Oracle Replication team and outside experts.