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2020-05-11-heap-profile-record.md

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Heap Profile Recorder

Abstract

"Heap Profiler Recorder" profile the flat heap usage periodically in an extra goroutine to record the global SimpleLRUCache memory usage with an similar value.

Background

Currently, we have support memory usage and disk usage tracker for Executor. In #15407, we are going to support the Global Memory Tracker. However, it would be too much work to realize calculating the memory usage of each Implementation of Plan and it might also causing much cpu consuming. To track the memory usage of SimpleLRUCache, we are trying to search the memory usage from runtime/pprof.

Proposal

We will record the whole SimpleLRUCache memory usage in the GlobalLRUMemUsageTracker memory tracker whose parent is GlobalMemoryUsageTracker memory tracker by using an extra goroutine to record the value searched and summed from heap profile periodically.

Rationale

When an golang application started, the runtime would startProfile in default including heap usage. And runtime.MemProfileRate controls the fraction of memory allocations that are recorded and reported in the memory profile. In default, runtime.MemProfileRate is 512 KB which is also can be configured. When the whole heap usage of SimpleLRUCache is larger than the runtime.MemProfileRate, it would be reflected in the flat value of the pprof heap profile.

To verify whether kvcache.(*SimpleLRUCache).Put would reflect the real heap usage, I use following test to ensure it:

  1. fulfill the SimpleLRUCache by set @randomString = ? with 20000 times.
  2. profile the heap Usage of github.com/pingcap/tidb/util/kvcache.(*SimpleLRUCache).Put and the result is 2.55 MB

Let's dig into the Put then we can find the where the heap consumed:

(pprof) list Put
Total: 52.23MB
ROUTINE ======================== github.com/pingcap/tidb/util/kvcache.(*SimpleLRUCache).Put in /Users/yisa/Downloads/Github/GoProject/src/github.com/pingcap/tidb/util/kvcache/simple_lru.go
    2.55MB     3.05MB (flat, cum)  5.85% of Total
         .          .     91:   return element.Value.(*cacheEntry).value, true
         .          .     92:}
         .          .     93:
         .          .     94:// Put puts the (key, value) pair into the LRU Cache.
         .          .     95:func (l *SimpleLRUCache) Put(key Key, value Value) {
    1.50MB     1.50MB     96:   hash := string(key.Hash())
         .          .     97:   element, exists := l.elements[hash]
         .          .     98:   if exists {
         .          .     99:           l.cache.MoveToFront(element)
         .          .    100:           return
         .          .    101:   }
         .          .    102:
         .          .    103:   newCacheEntry := &cacheEntry{
         .          .    104:           key:   key,
         .          .    105:           value: value,
         .          .    106:   }
         .          .    107:   hashSize := SizeOf(hash)
         .          .    108:   singleSize := SizeOf(newCacheEntry)
         .   512.02kB    109:   element = l.cache.PushFront(newCacheEntry)
    1.05MB     1.05MB    110:   l.elements[hash] = element
         .          .    111:   l.size++
         .          .    112:   l.capacity = 200000
         .          .    113:   // Getting used memory is expensive and can be avoided by setting quota to 0.
         .          .    114:   if l.quota == 0 {

We can find that the hash (the key of cache) and the element(the value of the cache) totally consume 2.55 MB.

  1. we use sizeof (the result is similar, but lower, not exact) to calculate the size of each key and element is 80byte and 40byte.
  2. As 2.28 MB (120 byte * 20000) is similar to the 2.55MB, we can ensure that the heap profile would reflect the heap usage of SimpleLRUCache.

Compatibility and Migration Plan

None