linux nvme的sendfile流程

在nvme的硬盘上使用sendfile系统调用，到底需要经过哪些流程？

do_sendfile--->do_splice_direct-->splice_direct_to_actor--->do_splice_to 对于xfs，其实就是xfs_file_splice_read

xfs_file_splice_read--->generic_file_splice_read--->__generic_file_splice_read--->mapping->a_ops->readpage--->xfs_vm_readpage-->mpage_readpage--->submit_bio

在splice_direct_to_actor函数中，有一个while循环，执行一段direct_splice_actor，返回之后，就执行do_splice_from-->generic_splice_sendpage-->splice_from_pipe-->__splice_from_pipe-->

splice_from_pipe_feed-->pipe_to_sendpage-->sock_sendpage-->kernel_sendpage-->inet_sendpage-->udp_sendpage(我用的是udp)

堆栈如下：

0xffffffff816093ed : inet_sendpage+0x6d/0xe0 [kernel]
0xffffffff8156b0bb : kernel_sendpage+0x1b/0x30 [kernel]
0xffffffff8156b0f7 : sock_sendpage+0x27/0x30 [kernel]
0xffffffff812329c3 : pipe_to_sendpage+0x63/0xa0 [kernel]
0xffffffff812328be : splice_from_pipe_feed+0x7e/0x120 [kernel]
0xffffffff81232e8e : __splice_from_pipe+0x6e/0x90 [kernel]
0xffffffff8123483e : splice_from_pipe+0x5e/0x90 [kernel]
0xffffffff81234905 : generic_splice_sendpage+0x15/0x20 [kernel]
0xffffffff8123368d : do_splice_from+0xad/0xf0 [kernel]
0xffffffff812336f0 : direct_splice_actor+0x20/0x30 [kernel]
0xffffffff81233424 : splice_direct_to_actor+0xd4/0x200 [kernel]
0xffffffff812335b2 : do_splice_direct+0x62/0x90 [kernel]
0xffffffff81203518 : do_sendfile+0x1d8/0x3c0 [kernel]
0xffffffff81204b6e : SyS_sendfile64+0x5e/0xb0 [kernel]
0xffffffff816b78c9 : system_call_fastpath+0x16/0x1b [kernel]

流程真长啊。

在2.6的内核中，generic_make_request会先调用__generic_make_request，然后__generic_make_request再调用q->make_request_fn 这个回调函数，

在3.10的内核中，generic_make_request 会直接回调 q->make_request_fn，针对nvme，多队列的这种情况，使用的是 blk_mq_requeue_work.

submit_bio-->generic_make_request--->q->make_request_fn--->blk_mq_requeue_work

任务的执行：blk_mq_make_request--->blk_mq_run_hw_queue,blk_mq_map_request等。

static struct request *blk_mq_map_request(struct request_queue *q,
                      struct bio *bio,
                      struct blk_map_ctx *data)
{
    struct blk_mq_hw_ctx *hctx;
    struct blk_mq_ctx *ctx;
    struct request *rq;
    int rw = bio_data_dir(bio);
    struct blk_mq_alloc_data alloc_data;

    blk_queue_enter_live(q);
    ctx = blk_mq_get_ctx(q);

/*
 * This assumes per-cpu software queueing queues. They could be per-node
 * as well, for instance. For now this is hardcoded as-is. Note that we don't
 * care about preemption, since we know the ctx's are persistent. This does
 * mean that we can't rely on ctx always matching the currently running CPU.
 */
static inline struct blk_mq_ctx *blk_mq_get_ctx(struct request_queue *q)
{
    return __blk_mq_get_ctx(q, get_cpu());
}

static inline struct blk_mq_ctx *__blk_mq_get_ctx(struct request_queue *q,
unsigned int cpu)
{
return per_cpu_ptr(q->queue_ctx, cpu);
}

在nvme中，如何把bio插入的queue，映射为在各个cpu上运行的sq呢？利用的是blk_mq_map_queue函数，

static struct blk_mq_ops nvme_mq_admin_ops = {
    .queue_rq    = nvme_queue_rq,------------------指定blk-mq向驱动提交request的函数
    .complete    = nvme_complete_rq,---------------完成队列处理
    .map_queue    = blk_mq_map_queue,--------------映射函数，将software queue和hardware queue对应
    .init_hctx    = nvme_admin_init_hctx,----------hardware Queue创建时调用，将NVMe Queue与Hardware Queue绑定
    .exit_hctx      = nvme_admin_exit_hctx,
    .init_request    = nvme_admin_init_request,----在分配Request时调用
    .timeout    = nvme_timeout,--------------------发生timeout时的调用
};

static struct blk_mq_ops nvme_mq_ops = {
    .queue_rq    = nvme_queue_rq,
    .complete    = nvme_complete_rq,
    .map_queue    = blk_mq_map_queue,----------映射函数
    .init_hctx    = nvme_init_hctx,
    .init_request    = nvme_init_request,
    .timeout    = nvme_timeout,
};

queue_rq指定blk-mq向驱动提交request的函数，map_queue定义如何将software queue和hardware queue对应，init_hctx是hardware Queue创建时调用（可以在这里将NVMe Queue与Hardware Queue绑定），init_request是在分配Request时调用，timeout是发生timeout时的调用。