Mongodb read locks
mongodb
Solution
What is `locks(micros) r`?
The amount of time that read locks was held (in microseconds).
- `R` - Global read lock
- `W` - Global write lock
- `r` - Database specific read lock
- `w` - Database specific write lock
What can I do to cut it down?
How does sharding affect concurrency?
Sharding improves concurrency by distributing collections over multiple `mongod` instances, allowing shard servers (i.e. `mongos` processes) to perform any number of operations concurrently to the various downstream `mongod` instances.
Diagnosing Performance Issues (Locks)
MongoDB uses a locking system to ensure data set consistency. However, if certain operations are long-running, or a queue forms, performance will slow as requests and operations wait for the lock. Lock-related slowdowns can be intermittent. To see if the lock has been affecting your performance, look to the data in the `globalLock` section of the `serverStatus` output. If `globalLock.currentQueue.total` is consistently high, then there is a chance that a large number of requests are waiting for a lock. This indicates a possible concurrency issue that may be affecting performance.
If `globalLock.totalTime` is high relative to uptime, the database has existed in a lock state for a significant amount of time. If `globalLock.ratio` is also high, MongoDB has likely been processing a large number of long running queries. Long queries are often the result of a number of factors: ineffective use of indexes, non-optimal schema design, poor query structure, system architecture issues, or insufficient RAM resulting in page faults and disk reads.
How We Scale MongoDB (Vertically)
Sadly, MongoDB itself will usually become a bottleneck before the capacity of a server is exhausted. Write lock is almost always the biggest problem (though there are practical limits to how much IO capacity a single MongoDB process can take advantage of).
Problem
I have a mongodb collection with custom _id and 500M+ documents. Size of the _id's index is ≈25Gb and whole collection is ≈125 Gb. Server has 96 Gb RAM. Read activity is only range queries by _id. Explain() shows that queries use the index. Mongo works rather fast some time after load tests start and slows down after a while. I can see in a log a lot of entries like this: [conn116] getmore csdb.archive query: { _id: { $gt: 2812719756651008, $lt: 2812720361451008 } } cursorid:444942282445272280 ntoreturn:0 keyUpdates:0 numYields: 748 locks(micros) r:7885031 nreturned:40302 reslen:1047872 10329ms A piece of db.currentOp(): ``` "waitingForLock" : false, "numYields" : 193, "lockStats" : { "timeLockedMicros" : { "r" : NumberLong(869051), "w" : NumberLong(0) }, "timeAcquiringMicros" : { "r" : NumberLong(1369404), "w" : NumberLong(0) } } ``` What is locks(micros) r? What can I do to cut it down?