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runtime/pprof,net/http/pprof: improve delta profiles efficiency and correctness #67942
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Oh, this is likely some sort of duplicate of #57765 |
I don't believe this needs to be a proposal (no API changes, unless you think new runtime/pprof APIs are required to implement this?), so removing from the proposal process. |
I recommend filing a separate issue for this, if one doesn't already exist. The rest of this issue is a performance optimization, but this is a real bug. |
cc @golang/runtime |
I don't know, it seems like new API to me. (It's a new URL handler variant but that's still API.) Please do kick it over to the proposal process if it ends up being a non-trivial change. |
Perhaps I am missing it, but I don't see what the new URL handler variant is. IIUC, the core of this issue is to make the existing |
I had multiple ideas:
|
I think there is an existing issue already #57765 . It has no bug label thoughю |
Proposal Details
The issue
In Golang, allocation, mutex and block profiles are cumulative. They only grow over time and show allocations/blocks that happened since the beginning of the running program.
Not only values grow, but the size of the profile itself grows as well. It could grow up to megabytes in size for long-running processes.
In many cases, it's more useful to see the differences between two points in time.
You can use delta profile from net/http/pprof package.
Using the delta profile requires passing seconds argument to the pprof endpoint query.
What this does:
p0
p1
p0
p1
p0
fromp1
The resulting profile is usually much smaller (
p0
may be megabytes, while the compressed result is usually tens of kilobytes).There are number of issues with this approach:
Note: It can be fixed if
net/http/pprof
package would usep0.ScaleN([]float64{-1,-1,0,0})
, instead ofp0.Scale(-1)
for memory profiles - that would subtract allocation values and zero out in-use values inp0
.DataDog's fastdelta
DataDog's fastdelta profiler uses another approach.
It improves the runtime/pprof approach by keeping a copy of the previous profile and subtracting the current profile from it.
The fastdelta profiler uses a custom protobuf pprof parser that doesn't allocate as much memory.
This approach is much more efficient, faster, and produces less presure on GC. It also doesn't require using two profiles.
However, the fastdelta profiler still parses huge profiles up to megabytes, just to discard most of it.
Grafana's godeltaprof
godeltaprof does a similar job but slightly differently.
Delta computation happens before serializing any pprof files using
runtime.MemprofileRecord
andBlockProfileRecord
.This way, huge profiles don't need to be parsed. The delta is computed on raw records, all zeros are rejected, and results are serialized and compressed.
The source code for godeltaprof is based (forked) on the original runtime/pprof package.
godeltaprof is modified to include delta computation before serialization and to expose the new endpoints.
godeltaprof relies on a bunch of golang runtime internal functions, specifically
runtime_FrameStartLine
,runtime_FrameSymbolName
,runtime_expandFinalInlineFrame
andruntime_cyclesPerSecond
link and potentially even more internal functions . Relying on internal functions becomes harder and more dangerous due to #67401.Proposal
We propose to to allow efficient delta memory, mutex, block profiles collection, both in
runtime/pprof
for push-based integrations andnet/http/pprof
for scraping integrations.The key points for improvements:
alloc_*
andinuse_*
values are put into separate profiles)The specifics of API and implementation details are left to be determined during discussion of the issue after we see an agreement we need to address the issue and this is something that could be accepted into golang runtime
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