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Since MySQL 5.6, the MySQL replication team has been working to reduce replication lag. The first step was schema-level parallel application of the binlog, but schema-level parallelism only helps when writes are spread across many databases; in the common case, where most write traffic hits a single database, it provides almost no parallelism. MySQL 5.7 then introduced the Commit-Order parallel-replay strategy, which depends on how many transactions run concurrently on the primary: the replica can replay quickly only when the primary is highly concurrent. When concurrency on the primary is low, the replica still replays slowly and lag builds up. To fix that, MySQL 5.7 also …

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Large transactions are a notorious problem in MySQL: they cause not only replication lag but also stability problems. A previous article, MySQL Large Transaction Commit Optimization, covered the problems a large transaction causes at commit time and the optimizations we made in AliSQL. This article looks at the problems a large transaction causes during semi-synchronous replication, and how AliSQL solves them.

In MySQL Large Transaction Commit …

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If you use and operate MySQL, you’ve surely run into a strange slow query like this:

• An INSERT that’s normally instant took 1.3s, and the slow-query log shows no long lock wait.
• Every statement in a multi-statement transaction had already finished, yet the COMMIT alone took 1.3s.

When this happens, the most likely cause is a large transaction committing. Below is a simulated test: we used sysbench to simulate a normal workload, then ran a large UPDATE in the background every 5 seconds. You can see the large UPDATE severely hurts performance.

Root Cause

The …

Even when the output of EXPLAIN doesn’t show “using temporary”, a temporary file may still be used in certain cases.

That’s not to say the query needs the temporary file to actually resolve the query (like what you’d see from the need for a derived table). But rather, the temporary file I’m speaking of is due to binary logging.

In particular, you can see this easily if using InnoDB, (most commonly) row-based binary logging, and you issue a large transaction, say a large UPDATE (large meaning something larger than the size of binlog_cache_size). In this case, you’ll notice a temporary file being …