golang map源码分析

1. 前言

map是CS中非常基础的数据结构，关于golang map的基本使用，这里不再赘述，可以参考官方文档。
golang的map实现是基于hash查找表，并且基于链表来解决hash碰撞问题。

2. 环境信息

• go版本：go1.15.4 darwin/amd64

3. go map数据结构分析

map的基础结构体是hmap，该结构体存在文件runtime/map.go中
hmap源码：

// A header for a Go map.
type hmap struct {
    // Note: the format of the hmap is also encoded in cmd/compile/internal/gc/reflect.go.
    // Make sure this stays in sync with the compiler's definition.
    count     int // # live cells == size of map.  Must be first (used by len() builtin)
    flags     uint8
    B         uint8  // log_2 of # of buckets (can hold up to loadFactor * 2^B items)
    noverflow uint16 // approximate number of overflow buckets; see incrnoverflow for details
    hash0     uint32 // hash seed
    buckets    unsafe.Pointer // array of 2^B Buckets. may be nil if count==0.
    oldbuckets unsafe.Pointer // previous bucket array of half the size, non-nil only when growing
    nevacuate  uintptr        // progress counter for evacuation (buckets less than this have been evacuated)
    extra *mapextra // optional fields
}

// mapextra holds fields that are not present on all maps.
type mapextra struct {
    // If both key and elem do not contain pointers and are inline, then we mark bucket
    // type as containing no pointers. This avoids scanning such maps.
    // However, bmap.overflow is a pointer. In order to keep overflow buckets
    // alive, we store pointers to all overflow buckets in hmap.extra.overflow and hmap.extra.oldoverflow.
    // overflow and oldoverflow are only used if key and elem do not contain pointers.
    // overflow contains overflow buckets for hmap.buckets.
    // oldoverflow contains overflow buckets for hmap.oldbuckets.
    // The indirection allows to store a pointer to the slice in hiter.
    overflow    *[]*bmap
    oldoverflow *[]*bmap

    // nextOverflow holds a pointer to a free overflow bucket.
    nextOverflow *bmap
}

• count：map中kv对的数量；
• flags：map的一些标志位；
• B：map中bucket数量为2^B个；意味着此时map数据结构中可以存储loadFactor * 2^B个数据，如果超过，则需要扩容；todo
• noverflow：map中溢出bucket的近似数量；todo
• hash0：hash函数的种子；
• buckets：map中bucket的首指针，map中一共有2^B个bucket；如果count==0的情况下，该字段可能是nil；
• oldbuckets：map中旧bucket的首指针，该字段只有在map扩容的时候，才不等于nil；todo
• nevacuate：map中bucket迁移数量，至多有此数量的bucket从旧bucket迁移到新bucket；todo
• extra：扩展字段；

bmap是bucket真正的结构体

// A bucket for a Go map.
type bmap struct {
    // tophash generally contains the top byte of the hash value
    // for each key in this bucket. If tophash[0] < minTopHash,
    // tophash[0] is a bucket evacuation state instead.
    tophash [bucketCnt]uint8
    // Followed by bucketCnt keys and then bucketCnt elems.
    // NOTE: packing all the keys together and then all the elems together makes the
    // code a bit more complicated than alternating key/elem/key/elem/... but it allows
    // us to eliminate padding which would be needed for, e.g., map[int64]int8.
    // Followed by an overflow pointer.
}

• tophash：存储hash值的高8位；
• keys：key数组，隐藏字段；
• values：value数组，隐藏字段；
• overflow：溢出buceket指针，隐藏字段；

bmap.tophash中除了存储hash值的高8位，也可以用来存储一些状态码。

    // Possible tophash values. We reserve a few possibilities for special marks.
    // Each bucket (including its overflow buckets, if any) will have either all or none of its
    // entries in the evacuated* states (except during the evacuate() method, which only happens
    // during map writes and thus no one else can observe the map during that time).
    emptyRest      = 0 // this cell is empty, and there are no more non-empty cells at higher indexes or overflows.
    emptyOne       = 1 // this cell is empty
    evacuatedX     = 2 // key/elem is valid.  Entry has been evacuated to first half of larger table.
    evacuatedY     = 3 // same as above, but evacuated to second half of larger table.
    evacuatedEmpty = 4 // cell is empty, bucket is evacuated.
    minTopHash     = 5 // minimum tophash for a normal filled cell.

bmap结构图

bmap.png

hmap结构图

gomap.png

下面我们重点分析一下map的创建和增删改查操作，我们会展示源码，同时在源码上增加中文注释，作为对源码的分析；golang编译器会根据不同情况，调用不同的函数，我们下面分析的是runtime/map.go文件中的基本函数；一些其他优化函数，例如runtime/map_faststr.go中对map[string]type类型的优化，感兴趣的同学可以自行查看。

3.1. map创建

示例代码

func main() {
    m1 := make(map[string]string)
    m2 := make(map[string]string, 9)
}

我们可以通过汇编编译代码看到go map创建调用的底层函数是makemap，该函数存在文件runtime/map.go中；事实上，不同的map声明方式，go标准编译器选择不同的函数调用，例如m1 := make(map[string]string)代码，编译器会调用函数runtime.makemap_small，但是大部分场景下都是调用makemap。下面我们分析下函数makemap：

// makemap implements Go map creation for make(map[k]v, hint).
// If the compiler has determined that the map or the first bucket
// can be created on the stack, h and/or bucket may be non-nil.
// If h != nil, the map can be created directly in h.
// If h.buckets != nil, bucket pointed to can be used as the first bucket.
func makemap(t *maptype, hint int, h *hmap) *hmap {
    // 检查申请的map空间是否超过内存限制
    mem, overflow := math.MulUintptr(uintptr(hint), t.bucket.size)
    if overflow || mem > maxAlloc {
        hint = 0
    }
    // 初始化hmap
    // initialize Hmap
    if h == nil {
        h = new(hmap)
    }
    // hash初始种子
    h.hash0 = fastrand()
    // 计算B
    // Find the size parameter B which will hold the requested # of elements.
    // For hint < 0 overLoadFactor returns false since hint < bucketCnt.
    B := uint8(0)
    for overLoadFactor(hint, B) {
        B++
    }
    h.B = B

    // allocate initial hash table
    // if B == 0, the buckets field is allocated lazily later (in mapassign)
    // If hint is large zeroing this memory could take a while.
    if h.B != 0 {
        var nextOverflow *bmap
        // 调用函数makeBucketArray，分配bucket和溢出bucket的内存
        h.buckets, nextOverflow = makeBucketArray(t, h.B, nil)
        if nextOverflow != nil {
            h.extra = new(mapextra)
            h.extra.nextOverflow = nextOverflow
        }
    }

    return h
}

// makeBucketArray initializes a backing array for map buckets.
// 1<= 4，则表示申请的map空间较大，我们事先申请一些溢出bucket，这样可以提高效率
    // For small b, overflow buckets are unlikely.
    // Avoid the overhead of the calculation.
    if b >= 4 {
        // Add on the estimated number of overflow buckets
        // required to insert the median number of elements
        // used with this value of b.
        nbuckets += bucketShift(b - 4)
        sz := t.bucket.size * nbuckets
        up := roundupsize(sz)
        if up != sz {
            nbuckets = up / t.bucket.size
        }
    }

    if dirtyalloc == nil {
        buckets = newarray(t.bucket, int(nbuckets))
    } else {
        // dirtyalloc was previously generated by
        // the above newarray(t.bucket, int(nbuckets))
        // but may not be empty.
        buckets = dirtyalloc
        size := t.bucket.size * nbuckets
        if t.bucket.ptrdata != 0 {
            memclrHasPointers(buckets, size)
        } else {
            memclrNoHeapPointers(buckets, size)
        }
    }

    if base != nbuckets {
        // We preallocated some overflow buckets.
        // To keep the overhead of tracking these overflow buckets to a minimum,
        // we use the convention that if a preallocated overflow bucket's overflow
        // pointer is nil, then there are more available by bumping the pointer.
        // We need a safe non-nil pointer for the last overflow bucket; just use buckets.
        // nextOverflow是溢出bucket的首地址；
        // last是最后一个溢出bucket的首地址；
        // 每个溢出bucket对应的bmap结构体中的溢出bucket指针都是nil；但是last的溢出bucket指针是bucket的起始地址；
        nextOverflow = (*bmap)(add(buckets, base*uintptr(t.bucketsize)))
        last := (*bmap)(add(buckets, (nbuckets-1)*uintptr(t.bucketsize)))
        last.setoverflow(t, (*bmap)(buckets))
    }
    return buckets, nextOverflow
}

总结：

• 函数makemap会根据不同的声明方式和参数，决定map的初始化空间大小；
• map中kv都存储在bucket中，每个bucket可以存8对kv；
• 如果len(map) > 0，则map中至少存在一个bucket，所以map的空间都是8的整数倍；
• 如果map申请空间较大（大于等于128），表示出现key碰撞的几率较大，则会事先创建一些溢出bucket，以备后期使用；

3.2. map查找元素

示例代码

func main() {
    m1 := make(map[int8]int)
    m1[1] = 1
    v, ok := m1[1]
    fmt.Println(v, ok)
}

map查找元素操作，底层调用的函数mapaccess1和mapaccess2，该函数存在文件runtime/map.go中；这两个函数基本一致，只是函数mapaccess2会返回bool类型，表示key是否存在。事实上，对于不同的map key类型，编译器会调用不同的函数来实现map的增删改查操作，其中针对特殊key类型的优化函数，存在文件runtime/map_fast32.go，runtime/map_fast64.go和runtime/map_faststr.go中；例如，如果key的类型是string，map的查找操作会调用优化函数mapaccess1_faststr和mapaccess2_faststr。本文只分析基本的函数，对于优化函数，感兴趣的同学可以自行查看源码。下面我们分析函数mapaccess2：

func mapaccess2(t *maptype, h *hmap, key unsafe.Pointer) (unsafe.Pointer, bool) {
    // 启用数据竞争检测
    if raceenabled && h != nil {
        callerpc := getcallerpc()
        pc := funcPC(mapaccess2)
        racereadpc(unsafe.Pointer(h), callerpc, pc)
        raceReadObjectPC(t.key, key, callerpc, pc)
    }
    // 启用-msan检测
    if msanenabled && h != nil {
        msanread(key, t.key.size)
    }
    if h == nil || h.count == 0 {
        if t.hashMightPanic() {
            t.hasher(key, 0) // see issue 23734
        }
        return unsafe.Pointer(&zeroVal[0]), false
    }
    // map不支持并发安全，并发读写会产生panic
    if h.flags&hashWriting != 0 {
        throw("concurrent map read and map write")
    }
    // 计算hash值
    hash := t.hasher(key, uintptr(h.hash0))
    // m表示map中bucket数量
    m := bucketMask(h.B)
    // 利用`hash mod m`可以计算bucket索引，b表示对应bucket的首地址
    b := (*bmap)(unsafe.Pointer(uintptr(h.buckets) + (hash&m)*uintptr(t.bucketsize)))
    // map正在迁移的场景，如果map正在迁移，则优先从oldbuckets中查找kv
    if c := h.oldbuckets; c != nil {
        // map是否在扩容迁移，如果是扩容迁移，则oldbuckets实际的bucket数量是m的一半（扩容会让bucket数量增加一倍）
        if !h.sameSizeGrow() {
            // There used to be half as many buckets; mask down one more power of two.
            m >>= 1
        }
        // 根据hash值，查找oldbuckets中对应的bucket地址
        oldb := (*bmap)(unsafe.Pointer(uintptr(c) + (hash&m)*uintptr(t.bucketsize)))
        // 如果oldb的标志位不是撤离状态，则我们从oldb中查找kv
        if !evacuated(oldb) {
            b = oldb
        }
    }
    // top表示hash的高8位，如果hash高8位小于5，则top需要加上5；因为5表示`minTopHash`，top如果是小于等于5，都是表示特殊状态；正常的key的top值都是大于5的
    top := tophash(hash)
bucketloop:
    // 逐个查找对应bucket和其溢出bucket
    for ; b != nil; b = b.overflow(t) {
        // 一个bucket有8对kv，逐个查找
        for i := uintptr(0); i < bucketCnt; i++ {
            if b.tophash[i] != top {
               // 如果b.tophash[i] == emptyRest，表示剩下的kv对都是空的，所以直接跳出循环
                if b.tophash[i] == emptyRest {
                    break bucketloop
                }
                continue
            }
            // 查找对应的key的地址
            k := add(unsafe.Pointer(b), dataOffset+i*uintptr(t.keysize))
            if t.indirectkey() {
                k = *((*unsafe.Pointer)(k))
            }
            // 比较key是否相等 
            if t.key.equal(key, k) {
               // 如果key相等，则找到对应的value 
                e := add(unsafe.Pointer(b), dataOffset+bucketCnt*uintptr(t.keysize)+i*uintptr(t.elemsize))
                if t.indirectelem() {
                    e = *((*unsafe.Pointer)(e))
                }
               // 返回value
                return e, true
            }
        }
    }
    // 返回对应的0值
    return unsafe.Pointer(&zeroVal[0]), false
}

总结：

• 判断是否并发读写，如果是，则抛出panic；
• 计算hash值，根据hash的地位找到对应的bucket，根据高8位，找到对应的kv槽位；
• map迁移场景下，优先从oldbuckets中查找kv；
• 比较key，相等则返回value，不等则返回0值；

• map kv定位过程如下图：

  
  
  mapkey.png

3.4. map新增元素和更新元素

示例代码

func main() {
    m1 := make(map[int8]int)
    m1[1] = 1
    m1[2] = 2
    m1[1] = 11
    fmt.Println(m1)
}

map的新增和更新元素操作，都会调用函数mapassign，该函数存在文件runtime/map.go中。

// Like mapaccess, but allocates a slot for the key if it is not present in the map.
func mapassign(t *maptype, h *hmap, key unsafe.Pointer) unsafe.Pointer {
    if h == nil {
        panic(plainError("assignment to entry in nil map"))
    }
    if raceenabled {
        callerpc := getcallerpc()
        pc := funcPC(mapassign)
        racewritepc(unsafe.Pointer(h), callerpc, pc)
        raceReadObjectPC(t.key, key, callerpc, pc)
    }
    if msanenabled {
        msanread(key, t.key.size)
    }
    // map不支持并发读写
    if h.flags&hashWriting != 0 {
        throw("concurrent map writes")
    }
    // 计算hash值 
    hash := t.hasher(key, uintptr(h.hash0))
    // map状态设置为hashWriting
    // Set hashWriting after calling t.hasher, since t.hasher may panic,
    // in which case we have not actually done a write.
    h.flags ^= hashWriting
    // 如果map没有初始化bucket，此时会申请bucket空间
    if h.buckets == nil {
        h.buckets = newobject(t.bucket) // newarray(t.bucket, 1)
    }

again:
    // 根据hash值，计算bucket索引
    bucket := hash & bucketMask(h.B)
    // 判断map是否正在扩容
    if h.growing() {
        // 函数growWork是将hmp.oldbuckets中对应的bucket迁移到新的buckets中
        growWork(t, h, bucket)
    }
    // 目标bucket的首地址 
    b := (*bmap)(unsafe.Pointer(uintptr(h.buckets) + bucket*uintptr(t.bucketsize)))
    top := tophash(hash)

    var inserti *uint8
    var insertk unsafe.Pointer
    var elem unsafe.Pointer
bucketloop:
    for {
        // 遍历tophash查找key是否已经存在，或者是否有空位插入kv
        for i := uintptr(0); i < bucketCnt; i++ {
            if b.tophash[i] != top {
                // tophash中可能有多个空位，我们记录第一个空位的索引，后面的空位跳过
                if isEmpty(b.tophash[i]) && inserti == nil {
                    inserti = &b.tophash[i]
                    insertk = add(unsafe.Pointer(b), dataOffset+i*uintptr(t.keysize))
                    elem = add(unsafe.Pointer(b), dataOffset+bucketCnt*uintptr(t.keysize)+i*uintptr(t.elemsize))
                }
                // tophash值表示剩余都是空位，则直接结束循环，因为后面全是空位，不会有相同的key在后面的槽位，此次操作必然是插入，而不是更新
                if b.tophash[i] == emptyRest {
                    break bucketloop
                }
                continue
            }
            k := add(unsafe.Pointer(b), dataOffset+i*uintptr(t.keysize))
            if t.indirectkey() {
                k = *((*unsafe.Pointer)(k))
            }
            if !t.key.equal(key, k) {
                continue
            }
            // already have a mapping for key. Update it.
            if t.needkeyupdate() {
                typedmemmove(t.key, k, key)
            }
            elem = add(unsafe.Pointer(b), dataOffset+bucketCnt*uintptr(t.keysize)+i*uintptr(t.elemsize))
            goto done
        }
        // 如果bucket是满的，而且没有发现相同的key，则继续查找溢出bucket
        ovf := b.overflow(t)
        if ovf == nil {
            break
        }
        b = ovf
    }

    // Did not find mapping for key. Allocate new cell & add entry.

    // If we hit the max load factor or we have too many overflow buckets,
    // and we're not already in the middle of growing, start growing.
    // 程序运行到此处，必然是由于没有找到相同的key，此次操作是插入，不是更新；
    // 插入一对kv，我们需要判断map是否需要扩容；
    // overLoadFactor函数用来判断map是否由于数据太多，需要增量1倍扩容；
    // tooManyOverflowBuckets函数用来判断map是否需要等量迁移，map由于删除操作，溢出bucket很多，但是数据分布很稀疏，我们可以通过等量迁移，将数据更加紧凑的存储在一起，节约空间；
    // 具体可以看evacuate函数分析；
    if !h.growing() && (overLoadFactor(h.count+1, h.B) || tooManyOverflowBuckets(h.noverflow, h.B)) {
        //  hashGrow函数主要是设置hmap.flags为扩容状态，申请新的内存空间用来扩容，同时设置hmap.oldbuckets为原来的hmap.buckets
        hashGrow(t, h)
        goto again // Growing the table invalidates everything, so try again
    }
    // inserti == nil表示没有插入的槽位，需要申请溢出bucket
    if inserti == nil {
        // all current buckets are full, allocate a new one.
        newb := h.newoverflow(t, b)
        inserti = &newb.tophash[0]
        insertk = add(unsafe.Pointer(newb), dataOffset)
        elem = add(insertk, bucketCnt*uintptr(t.keysize))
    }

    // store new key/elem at insert position
    if t.indirectkey() {
        kmem := newobject(t.key)
        *(*unsafe.Pointer)(insertk) = kmem
        insertk = kmem
    }
    if t.indirectelem() {
        vmem := newobject(t.elem)
        *(*unsafe.Pointer)(elem) = vmem
    }
    typedmemmove(t.key, insertk, key)
    *inserti = top
    h.count++

done:
    // 设置flags，并写入value
    if h.flags&hashWriting == 0 {
        throw("concurrent map writes")
    }
    h.flags &^= hashWriting
    if t.indirectelem() {
        elem = *((*unsafe.Pointer)(elem))
    }
    return elem
}
// 迁移oldbucket中的对应bucket
func growWork(t *maptype, h *hmap, bucket uintptr) {
    // make sure we evacuate the oldbucket corresponding
    // to the bucket we're about to use
    evacuate(t, h, bucket&h.oldbucketmask())

    // evacuate one more oldbucket to make progress on growing
    if h.growing() {
        evacuate(t, h, h.nevacuate)
    }
}
// bucket迁移函数
func evacuate(t *maptype, h *hmap, oldbucket uintptr) {
    // old bucket索引
    b := (*bmap)(add(h.oldbuckets, oldbucket*uintptr(t.bucketsize)))
    // 如果是等量迁移，则newbit表示bucket数量；如果是增量迁移，newbit表示增量前的bucket数量；
    newbit := h.noldbuckets()
    // 待迁移bucket是否是迁移状态
    if !evacuated(b) {
        // TODO: reuse overflow buckets instead of using new ones, if there
        // is no iterator using the old buckets.  (If !oldIterator.)

        // xy contains the x and y (low and high) evacuation destinations.
        // 同一个hash值，在新旧buckets中对应的bucket索引可能是不一样的；
        // 例如hash值是1001，旧buckets数量是8，新buckets数量是16，那么该hash值在旧buckets中索引是1，新buckets中索引是9；
        // x表示新旧索引不变的情况下，新bucket的索引；y表示新索引增加newbit情况下，新bucket的索引；
        var xy [2]evacDst
        x := &xy[0]
        x.b = (*bmap)(add(h.buckets, oldbucket*uintptr(t.bucketsize)))
        x.k = add(unsafe.Pointer(x.b), dataOffset)
        x.e = add(x.k, bucketCnt*uintptr(t.keysize))

        if !h.sameSizeGrow() {
            // Only calculate y pointers if we're growing bigger.
            // Otherwise GC can see bad pointers.
            y := &xy[1]
            y.b = (*bmap)(add(h.buckets, (oldbucket+newbit)*uintptr(t.bucketsize)))
            y.k = add(unsafe.Pointer(y.b), dataOffset)
            y.e = add(y.k, bucketCnt*uintptr(t.keysize))
        }

        for ; b != nil; b = b.overflow(t) {
            // 待迁移bucket中kv的首地址
            k := add(unsafe.Pointer(b), dataOffset)
            e := add(k, bucketCnt*uintptr(t.keysize))
            for i := 0; i < bucketCnt; i, k, e = i+1, add(k, uintptr(t.keysize)), add(e, uintptr(t.elemsize)) {
                top := b.tophash[i]
                // 如果tophash为空，则跳过，这样就可以让数据紧凑，节约内存空间； 
                if isEmpty(top) {
                    b.tophash[i] = evacuatedEmpty
                    continue
                }
                if top < minTopHash {
                    throw("bad map state")
                }
                k2 := k
                if t.indirectkey() {
                    k2 = *((*unsafe.Pointer)(k2))
                }
                var useY uint8
                if !h.sameSizeGrow() {
                    // Compute hash to make our evacuation decision (whether we need
                    // to send this key/elem to bucket x or bucket y).
                    hash := t.hasher(k2, uintptr(h.hash0))
                    if h.flags&iterator != 0 && !t.reflexivekey() && !t.key.equal(k2, k2) {
                        // If key != key (NaNs), then the hash could be (and probably
                        // will be) entirely different from the old hash. Moreover,
                        // it isn't reproducible. Reproducibility is required in the
                        // presence of iterators, as our evacuation decision must
                        // match whatever decision the iterator made.
                        // Fortunately, we have the freedom to send these keys either
                        // way. Also, tophash is meaningless for these kinds of keys.
                        // We let the low bit of tophash drive the evacuation decision.
                        // We recompute a new random tophash for the next level so
                        // these keys will get evenly distributed across all buckets
                        // after multiple grows.
                        useY = top & 1
                        top = tophash(hash)
                    } else {
                        if hash&newbit != 0 {
                            useY = 1
                        }
                    }
                }
                // 检查迁移状态
                if evacuatedX+1 != evacuatedY || evacuatedX^1 != evacuatedY {
                    throw("bad evacuatedN")
                }
                // 设置tophash值
                b.tophash[i] = evacuatedX + useY // evacuatedX + 1 == evacuatedY
                dst := &xy[useY]                 // evacuation destination
                // dst用来接收迁移的bucket（包括溢出bucket）中的kv；
                // 迁移过来的有效kv数量达到8之后，dst会申请溢出bucket；
                if dst.i == bucketCnt {
                    dst.b = h.newoverflow(t, dst.b)
                    dst.i = 0
                    dst.k = add(unsafe.Pointer(dst.b), dataOffset)
                    dst.e = add(dst.k, bucketCnt*uintptr(t.keysize))
                }
                dst.b.tophash[dst.i&(bucketCnt-1)] = top // mask dst.i as an optimization, to avoid a bounds check
                if t.indirectkey() {
                    *(*unsafe.Pointer)(dst.k) = k2 // copy pointer
                } else {
                    typedmemmove(t.key, dst.k, k) // copy elem
                }
                if t.indirectelem() {
                    *(*unsafe.Pointer)(dst.e) = *(*unsafe.Pointer)(e)
                } else {
                    typedmemmove(t.elem, dst.e, e)
                }
                dst.i++
                // These updates might push these pointers past the end of the
                // key or elem arrays.  That's ok, as we have the overflow pointer
                // at the end of the bucket to protect against pointing past the
                // end of the bucket.
                dst.k = add(dst.k, uintptr(t.keysize))
                dst.e = add(dst.e, uintptr(t.elemsize))
            }
        }
        // 迁移完成后，清理bucket kv和溢出bucket的指针；保留tophash;
        // Unlink the overflow buckets & clear key/elem to help GC.
        if h.flags&oldIterator == 0 && t.bucket.ptrdata != 0 {
            b := add(h.oldbuckets, oldbucket*uintptr(t.bucketsize))
            // Preserve b.tophash because the evacuation
            // state is maintained there.
            ptr := add(b, dataOffset)
            n := uintptr(t.bucketsize) - dataOffset
            memclrHasPointers(ptr, n)
        }
    }
    //  hmap.nevacuate累加
    if oldbucket == h.nevacuate {
        advanceEvacuationMark(h, t, newbit)
    }
}

func advanceEvacuationMark(h *hmap, t *maptype, newbit uintptr) {
    h.nevacuate++
    // Experiments suggest that 1024 is overkill by at least an order of magnitude.
    // Put it in there as a safeguard anyway, to ensure O(1) behavior.
    stop := h.nevacuate + 1024
    if stop > newbit {
        stop = newbit
    }
    for h.nevacuate != stop && bucketEvacuated(t, h, h.nevacuate) {
        h.nevacuate++
    }
    if h.nevacuate == newbit { // newbit == # of oldbuckets
        // Growing is all done. Free old main bucket array.
        h.oldbuckets = nil
        // Can discard old overflow buckets as well.
        // If they are still referenced by an iterator,
        // then the iterator holds a pointers to the slice.
        if h.extra != nil {
            h.extra.oldoverflow = nil
        }
        h.flags &^= sameSizeGrow
    }
}

func hashGrow(t *maptype, h *hmap) {
    // If we've hit the load factor, get bigger.
    // Otherwise, there are too many overflow buckets,
    // so keep the same number of buckets and "grow" laterally.
    bigger := uint8(1)
    if !overLoadFactor(h.count+1, h.B) {
        bigger = 0
        h.flags |= sameSizeGrow
    }
    oldbuckets := h.buckets
    newbuckets, nextOverflow := makeBucketArray(t, h.B+bigger, nil)

    flags := h.flags &^ (iterator | oldIterator)
    if h.flags&iterator != 0 {
        flags |= oldIterator
    }
    // commit the grow (atomic wrt gc)
    h.B += bigger
    h.flags = flags
    h.oldbuckets = oldbuckets
    h.buckets = newbuckets
    h.nevacuate = 0
    h.noverflow = 0

    if h.extra != nil && h.extra.overflow != nil {
        // Promote current overflow buckets to the old generation.
        if h.extra.oldoverflow != nil {
            throw("oldoverflow is not nil")
        }
        h.extra.oldoverflow = h.extra.overflow
        h.extra.overflow = nil
    }
    if nextOverflow != nil {
        if h.extra == nil {
            h.extra = new(mapextra)
        }
        h.extra.nextOverflow = nextOverflow
    }

    // the actual copying of the hash table data is done incrementally
    // by growWork() and evacuate().
}

总结：

• map优先检查是否有相同的key，如果有，则表示是更新操作；
• 如果没有相同的key，则表示是插入操作；如果有空位，则在第一个空位处插入；如果没有空位，则增加一个溢出bucket，在溢出bucket中插入；插入操作可能会触发扩容操作；
• map不是一次性完成扩容的，而是逐步完成扩容的；当在一个bucket中执行插入操作的时候，如果发现需要扩容，则会把这个bucket（包含溢出bucket）全部迁移到新申请的buckets空间中，同时多扩容一个bucket（个人理解是加速扩容速度，否则因为个别bucket一直没有使用，导致map一直维护新旧两个buckets）；
• map库容分为等量迁移和加倍扩容：等量迁移是为了让稀疏的数据分布更加紧凑（由于删除操作，map可能会很稀疏），加倍扩容是由于插入数据过多，申请一个加倍的空间来存储kv，同时加倍扩容也会删除空的槽位，让数据分布紧凑；

3.5. map删除元素

示例代码

func main() {
    m1 := make(map[int8]int)
    m1[1] = 1
    delete(m1, 1)
}

map删除元素操作调用的底层函数是mapdelete该函数存在文件runtime/map.go中.

func mapdelete(t *maptype, h *hmap, key unsafe.Pointer) {
    if raceenabled && h != nil {
        callerpc := getcallerpc()
        pc := funcPC(mapdelete)
        racewritepc(unsafe.Pointer(h), callerpc, pc)
        raceReadObjectPC(t.key, key, callerpc, pc)
    }
    if msanenabled && h != nil {
        msanread(key, t.key.size)
    }
    // h == nil || h.count == 0的时候，直接返回；
    // 不过如果map的key类型是无法比较的话，这里会报错runtime error: hash of unhashable type xxx
    // 所以会调用一次t.hasher函数，该函数会报合适的panic，可以参考issue 23734：https://github.com/golang/go/issues/23734
    if h == nil || h.count == 0 {
        if t.hashMightPanic() {
            t.hasher(key, 0) // see issue 23734
        }
        return
    }
    // map不支持并发读写
    if h.flags&hashWriting != 0 {
        throw("concurrent map writes")
    }

    hash := t.hasher(key, uintptr(h.hash0))

    // Set hashWriting after calling t.hasher, since t.hasher may panic,
    // in which case we have not actually done a write (delete).
    h.flags ^= hashWriting
    // bucket索引
    bucket := hash & bucketMask(h.B)
    // 如果map正在扩容过程中，此时会优先扩容，一次扩容2个bucket；
    if h.growing() {
        growWork(t, h, bucket)
    }
    b := (*bmap)(add(h.buckets, bucket*uintptr(t.bucketsize)))
    bOrig := b
    top := tophash(hash)
search:
    for ; b != nil; b = b.overflow(t) {
        for i := uintptr(0); i < bucketCnt; i++ {
            if b.tophash[i] != top {
                // 如果top=emptyRest，则表示后面的槽位都是空的，所以直接返回；
                if b.tophash[i] == emptyRest {
                    break search
                }
                continue
            }
            k := add(unsafe.Pointer(b), dataOffset+i*uintptr(t.keysize))
            k2 := k
            if t.indirectkey() {
                k2 = *((*unsafe.Pointer)(k2))
            }
            if !t.key.equal(key, k2) {
                continue
            }
            // 删除kv
            // Only clear key if there are pointers in it.
            if t.indirectkey() {
                *(*unsafe.Pointer)(k) = nil
            } else if t.key.ptrdata != 0 {
                memclrHasPointers(k, t.key.size)
            }
            e := add(unsafe.Pointer(b), dataOffset+bucketCnt*uintptr(t.keysize)+i*uintptr(t.elemsize))
            if t.indirectelem() {
                *(*unsafe.Pointer)(e) = nil
            } else if t.elem.ptrdata != 0 {
                memclrHasPointers(e, t.elem.size)
            } else {
                memclrNoHeapPointers(e, t.elem.size)
            }
            // 删除kv之后，首先将top值修改为emptyOne，如果后续的kv都没有，会将当前top值修改为emptyRest；
            // 同时，当前top值修改，可能会导致之前的top值也需要相应修改；
            b.tophash[i] = emptyOne
            // If the bucket now ends in a bunch of emptyOne states,
            // change those to emptyRest states.
            // It would be nice to make this a separate function, but
            // for loops are not currently inlineable.
              // 如果已经是当前bucket的最后一个元素，则会继续寻找溢出bucket；
            if i == bucketCnt-1 {
                if b.overflow(t) != nil && b.overflow(t).tophash[0] != emptyRest {
                    goto notLast
                }
            } else { // 如果下一个top值不是emptyRest，则表示当前的top值不需要修改成emptyRest；
                if b.tophash[i+1] != emptyRest {
                    goto notLast
                }
            }
            // 循环修改top值；
            // 由于当前top值修改为emptyRest，可能导致前一个top值或者前一个bucket的最后一个top值也要相应修改；
            for {
                b.tophash[i] = emptyRest
                if i == 0 {
                    if b == bOrig {
                        break // beginning of initial bucket, we're done.
                    }
                    // Find previous bucket, continue at its last entry.
                    c := b
                    for b = bOrig; b.overflow(t) != c; b = b.overflow(t) {
                    }
                    i = bucketCnt - 1
                } else {
                    i--
                }
                if b.tophash[i] != emptyOne {
                    break
                }
            }
        notLast:
            h.count--
            break search
        }
    }

    if h.flags&hashWriting == 0 {
        throw("concurrent map writes")
    }
    h.flags &^= hashWriting
}

总结：

• 删除操作也不可以并发；
• 删除时候，也会触发扩容迁移；个人理解，go map不会一次性完成扩容迁移，这样应该比较消耗时间和性能，go map通过用户行为不断触发扩容迁移（一次就会扩容迁移2个bucket），这样虽然会有较长时间保留着old buckets，但是对map响应和用户体验影响较小，所以应该是一种折中和平衡的方案；
• 删除时候，会依次遍历改变top值；

3.6. map遍历元素

示例代码

func main() {
    m1 := make(map[int8]int)
    m1[1] = 1
    for k,v := range m1 {
        fmt.Println(k,v)
    }
}

map遍历元素分为两步，首先调用函数mapiterinit，初始化迭代器结构体hiter；然后调用函数mapiternext来循环遍历kv；下面我们首先看下迭代器hiter的结构，然后分析一下函数mapiterinit和函数mapiternext源码，这两个函数都存在于文件runtime/map.go中。
迭代器hiter的结构

// A hash iteration structure.
// If you modify hiter, also change cmd/compile/internal/gc/reflect.go to indicate
// the layout of this structure.
type hiter struct {
    key         unsafe.Pointer // Must be in first position.  Write nil to indicate iteration end (see cmd/internal/gc/range.go).
    elem        unsafe.Pointer // Must be in second position (see cmd/internal/gc/range.go).
    t           *maptype
    h           *hmap
    buckets     unsafe.Pointer // bucket ptr at hash_iter initialization time
    bptr        *bmap          // current bucket
    overflow    *[]*bmap       // keeps overflow buckets of hmap.buckets alive
    oldoverflow *[]*bmap       // keeps overflow buckets of hmap.oldbuckets alive
    startBucket uintptr        // bucket iteration started at
    offset      uint8          // intra-bucket offset to start from during iteration (should be big enough to hold bucketCnt-1)
    wrapped     bool           // already wrapped around from end of bucket array to beginning
    B           uint8
    i           uint8
    bucket      uintptr
    checkBucket uintptr
}

• key：key指针；
• elem：elem指针；
• bptr：当前正待遍历的bucket指针；
• startBucket：遍历起始的bucket索引；
• offset：遍历每个bucket的时候，起始的cell索引；
• wrapped：map遍历一般是从中间的bucket开始往末尾bucket遍历，如果已经到了末尾，则会继续从头开始遍历；该标志位为真时候，表示开始从头开始遍历；
• i：当前cell索引；
• bucket：当前bucket索引；
• checkBucket：需要检查的bucket索引；当map遍历的之前，map正在扩容迁移(growing)过程中，此时找到一个待遍历的bucket，我们会先找到旧bucket，如果旧bucket还没有迁移，同时我们知道，如果迁移结束，该bucket中的kv肯定会迁移到2个bucket（例如B=1，旧的buckets是b0和b1；扩容后B=2，新的buckets是b0，b1，b2，b3，根据之前扩容迁移的过程分析，旧的b0会迁移到新的b0和b2）；所以map只会返回最终会迁移到新bucket的kv；checkBucket就是上述场景下的bucket索引；

迭代函数源码：

// mapiterinit initializes the hiter struct used for ranging over maps.
// The hiter struct pointed to by 'it' is allocated on the stack
// by the compilers order pass or on the heap by reflect_mapiterinit.
// Both need to have zeroed hiter since the struct contains pointers.
func mapiterinit(t *maptype, h *hmap, it *hiter) {
    if raceenabled && h != nil {
        callerpc := getcallerpc()
        racereadpc(unsafe.Pointer(h), callerpc, funcPC(mapiterinit))
    }
    // 遍历没有初始化的map不会报错
    if h == nil || h.count == 0 {
        return
    }

    if unsafe.Sizeof(hiter{})/sys.PtrSize != 12 {
        throw("hash_iter size incorrect") // see cmd/compile/internal/gc/reflect.go
    }
    it.t = t
    it.h = h

    // grab snapshot of bucket state
    it.B = h.B
    it.buckets = h.buckets
    if t.bucket.ptrdata == 0 {
        // Allocate the current slice and remember pointers to both current and old.
        // This preserves all relevant overflow buckets alive even if
        // the table grows and/or overflow buckets are added to the table
        // while we are iterating.
        h.createOverflow()
        it.overflow = h.extra.overflow
        it.oldoverflow = h.extra.oldoverflow
    }
    // 每次map遍历的起始bucket槽位和起始cell槽位都是随机的，原因就是这两个槽位是根据随机数来产生的
    // decide where to start
    r := uintptr(fastrand())
    if h.B > 31-bucketCntBits {
        r += uintptr(fastrand()) << 31
    }
    it.startBucket = r & bucketMask(h.B)
    it.offset = uint8(r >> h.B & (bucketCnt - 1))

    // iterator state
    it.bucket = it.startBucket

    // 修改hmap状态，原子操作
    // Remember we have an iterator.
    // Can run concurrently with another mapiterinit().
    if old := h.flags; old&(iterator|oldIterator) != iterator|oldIterator {
        atomic.Or8(&h.flags, iterator|oldIterator)
    }

    mapiternext(it)
}

func mapiternext(it *hiter) {
    h := it.h
    if raceenabled {
        callerpc := getcallerpc()
        racereadpc(unsafe.Pointer(h), callerpc, funcPC(mapiternext))
    }
    if h.flags&hashWriting != 0 {
        throw("concurrent map iteration and map write")
    }
    t := it.t
    bucket := it.bucket
    b := it.bptr
    i := it.i
    checkBucket := it.checkBucket

next:
    if b == nil {
        // bucket表示当前的`bucket`索引，wrapped表示是否从头遍历了；
        // map一般是从中间`bucket`开始遍历，如果遍历到末尾则wrapped=true，bucket=0，从头开始继续遍历；
        // 所以下面的判断条件如果为真，就是已经遍历结束了；
        if bucket == it.startBucket && it.wrapped {
            // end of iteration
            it.key = nil
            it.elem = nil
            return
        }
        // 遍历之后，h.B可能继续变大
        if h.growing() && it.B == h.B {
            // Iterator was started in the middle of a grow, and the grow isn't done yet.
            // If the bucket we're looking at hasn't been filled in yet (i.e. the old
            // bucket hasn't been evacuated) then we need to iterate through the old
            // bucket and only return the ones that will be migrated to this bucket.
            oldbucket := bucket & it.h.oldbucketmask()
            b = (*bmap)(add(h.oldbuckets, oldbucket*uintptr(t.bucketsize)))
            if !evacuated(b) {
                checkBucket = bucket
            } else {
                b = (*bmap)(add(it.buckets, bucket*uintptr(t.bucketsize)))
                checkBucket = noCheck
            }
        } else {
            b = (*bmap)(add(it.buckets, bucket*uintptr(t.bucketsize)))
            checkBucket = noCheck
        }
        bucket++
        // bucket遍历到末尾后，从头开始继续遍历
        if bucket == bucketShift(it.B) {
            bucket = 0
            it.wrapped = true
        }
        i = 0
    }
    for ; i < bucketCnt; i++ {
        offi := (i + it.offset) & (bucketCnt - 1)
        if isEmpty(b.tophash[offi]) || b.tophash[offi] == evacuatedEmpty {
            // TODO: emptyRest is hard to use here, as we start iterating
            // in the middle of a bucket. It's feasible, just tricky.
            continue
        }
        k := add(unsafe.Pointer(b), dataOffset+uintptr(offi)*uintptr(t.keysize))
        if t.indirectkey() {
            k = *((*unsafe.Pointer)(k))
        }
        e := add(unsafe.Pointer(b), dataOffset+bucketCnt*uintptr(t.keysize)+uintptr(offi)*uintptr(t.elemsize))
        if checkBucket != noCheck && !h.sameSizeGrow() {
            // Special case: iterator was started during a grow to a larger size
            // and the grow is not done yet. We're working on a bucket whose
            // oldbucket has not been evacuated yet. Or at least, it wasn't
            // evacuated when we started the bucket. So we're iterating
            // through the oldbucket, skipping any keys that will go
            // to the other new bucket (each oldbucket expands to two
            // buckets during a grow).
            if t.reflexivekey() || t.key.equal(k, k) {
                // If the item in the oldbucket is not destined for
                // the current new bucket in the iteration, skip it.
                hash := t.hasher(k, uintptr(h.hash0))
                // 跳过不会迁移到当前bucket的kv
                if hash&bucketMask(it.B) != checkBucket {
                    continue
                }
            } else {
                // Hash isn't repeatable if k != k (NaNs).  We need a
                // repeatable and randomish choice of which direction
                // to send NaNs during evacuation. We'll use the low
                // bit of tophash to decide which way NaNs go.
                // NOTE: this case is why we need two evacuate tophash
                // values, evacuatedX and evacuatedY, that differ in
                // their low bit.
                if checkBucket>>(it.B-1) != uintptr(b.tophash[offi]&1) {
                    continue
                }
            }
        }
        if (b.tophash[offi] != evacuatedX && b.tophash[offi] != evacuatedY) ||
            !(t.reflexivekey() || t.key.equal(k, k)) {
            // This is the golden data, we can return it.
            // OR
            // key!=key, so the entry can't be deleted or updated, so we can just return it.
            // That's lucky for us because when key!=key we can't look it up successfully.
            it.key = k
            if t.indirectelem() {
                e = *((*unsafe.Pointer)(e))
            }
            it.elem = e
        } else {
            // The hash table has grown since the iterator was started.
            // The golden data for this key is now somewhere else.
            // Check the current hash table for the data.
            // This code handles the case where the key
            // has been deleted, updated, or deleted and reinserted.
            // NOTE: we need to regrab the key as it has potentially been
            // updated to an equal() but not identical key (e.g. +0.0 vs -0.0).
            rk, re := mapaccessK(t, h, k)
            if rk == nil {
                continue // key has been deleted
            }
            it.key = rk
            it.elem = re
        }
        it.bucket = bucket
        if it.bptr != b { // avoid unnecessary write barrier; see issue 14921
            it.bptr = b
        }
        it.i = i + 1
        it.checkBucket = checkBucket
        return
    }
    b = b.overflow(t)
    i = 0
    goto next
}
// returns both key and elem. Used by map iterator
func mapaccessK(t *maptype, h *hmap, key unsafe.Pointer) (unsafe.Pointer, unsafe.Pointer) {
    if h == nil || h.count == 0 {
        return nil, nil
    }
    hash := t.hasher(key, uintptr(h.hash0))
    m := bucketMask(h.B)
    b := (*bmap)(unsafe.Pointer(uintptr(h.buckets) + (hash&m)*uintptr(t.bucketsize)))
    if c := h.oldbuckets; c != nil {
        if !h.sameSizeGrow() {
            // There used to be half as many buckets; mask down one more power of two.
            m >>= 1
        }
        oldb := (*bmap)(unsafe.Pointer(uintptr(c) + (hash&m)*uintptr(t.bucketsize)))
        if !evacuated(oldb) {
            b = oldb
        }
    }
    top := tophash(hash)
bucketloop:
    for ; b != nil; b = b.overflow(t) {
        for i := uintptr(0); i < bucketCnt; i++ {
            if b.tophash[i] != top {
                if b.tophash[i] == emptyRest {
                    break bucketloop
                }
                continue
            }
            k := add(unsafe.Pointer(b), dataOffset+i*uintptr(t.keysize))
            if t.indirectkey() {
                k = *((*unsafe.Pointer)(k))
            }
            if t.key.equal(key, k) {
                e := add(unsafe.Pointer(b), dataOffset+bucketCnt*uintptr(t.keysize)+i*uintptr(t.elemsize))
                if t.indirectelem() {
                    e = *((*unsafe.Pointer)(e))
                }
                return k, e
            }
        }
    }
    return nil, nil
}

总结：

• map遍历首先会初始化迭代器hiter，然后调用遍历函数mapiternext；
• map遍历的起始bucket和起始cell都是随机的；
• 如果map遍历前，map进入一个growing过程，则map遍历效果等效于该growing全部结束后的的效果；也就是说，一个新bucket，可能还没有迁移进数据，但是map可以正常返回未来会迁移进入该bucket的数据；

4. 其他

• 如何获取调用的具体map函数
  • 准备代码

package main
import (
   "fmt"
)

func main() {
   m1 := make(map[string]string, 9)
   fmt.Println(m1)
   for i := 0; i < 20; i++ {
       str := fmt.Sprintf("%d", i)
       m1[str] = str
   }
       a := m1["0"]
   b, ok := m1["0"]
   fmt.Println(a,b,ok)
}

• 打印汇编代码命令

go tool compile -N -l -S main.go > main.txt

• 根据汇编代码，查找调用函数CALL runtime.makemap(SB)

5. 参考

• Golang map源码详解
• go基础之map
• 年度最佳【golang】map详解