Show an aggregated memory usage report (in bytes) for the slab allocator. This report is useful for assessing out-of-memory risks.
box.slab.infogives a few ratios:
Here are two possible cases for monitoring memtx memory usage:
Case 1: 0.5 <
Apparently your memory is highly fragmented. Check how many slab classes you have by looking at
box.slab.stats()and counting the number of different classes. If there are many slab classes (more than a few dozens), you may run out of memory even though memory utilization is not high. While each slab may have few items used, whenever a tuple of a size different from any existing slab class size is allocated, Tarantool may need to get a new slab from the slab arena, and since the arena has few empty slabs left, it will attempt to increase its quota usage, which, in turn, may end up with an out-of-memory error due to the low remaining quota.
You are running out of memory. All memory utilization indicators are high. Your memory is not fragmented, but there are few reserves left on each slab allocator level. You should consider increasing Tarantool’s memory limit (
To sum up: your main out-of-memory indicator is
quota_used_ratio. However, there are lots of perfectly stable setups with a high
quota_used_ratio, so you only need to pay attention to it when both arena and item used ratio are also high.
quota_size- memory limit for slab allocator (as configured in the memtx_memory parameter, the default is 2^28 bytes = 268,435,456 bytes)
quota_used- used by slab allocator
items_size- allocated only for tuples
items_used- used only for tuples
arena_size- allocated for both tuples and indexes
arena_used- used for both tuples and indexes
tarantool> box.slab.info() --- - items_size: 228128 items_used_ratio: 1.8% quota_size: 1073741824 quota_used_ratio: 0.8% arena_used_ratio: 43.2% items_used: 4208 quota_used: 8388608 arena_size: 2325176 arena_used: 1003632 ... tarantool> box.slab.info().arena_used --- - 1003632 ...