Thanks for looking into the prometheus client, Tao Jiuming. I am surprised that it isn't optimized to minimize heap usage. In that case, I think it makes sense to move forward with your solution.
Thanks, Michael On Mon, Feb 28, 2022 at 10:23 PM PengHui Li <peng...@apache.org> wrote: > > Hi, > > Thanks for the update, > I agree to have the JVM heap usage enhancement. > > +1 > > Penghui > > On Mon, Feb 28, 2022 at 5:33 PM Jiuming Tao <jm...@streamnative.io.invalid> > wrote: > > > Hi Penghui, > > > > I had read `io.prometheus.client.exporter.HttpServer` source code, in > > `HttpMetricsHandler#handle` method, it uses thread local cached > > `ByteArrayOutputStream` , it’s similar with our current implemention(with > > heap memory resizes and mem_copy). > > It will spend a plenty of heap memory, and even worse, these heap memory > > will never be released(cached in thread local). > > > > Thanks, > > Tao Jiuming > > > > > 2022年2月28日 下午5:00，PengHui Li <peng...@apache.org> 写道： > > > > > > Hi Jiuming, > > > > > > Could you please check if the Prometheus client > > > can be used to reduce the JVM heap usage? > > > If yes, I think we can consider using the Prometheus > > > client instead of the current implementation together. > > > Otherwise, we'd better focus on the heap memory usage > > > enhancement for this discussion. Using the Prometheus > > > client to refactor the current implementation will be a > > > big project. > > > > > > Thanks, > > > Penghui > > > > > > On Sun, Feb 27, 2022 at 12:22 AM Jiuming Tao > > <jm...@streamnative.io.invalid> > > > wrote: > > > > > >> Hi all, > > >> https://github.com/apache/pulsar/pull/14453 < > > >> https://github.com/apache/pulsar/pull/14453> please take a look. > > >> > > >> Thanks, > > >> Tao Jiuming > > >> > > >>> 2022年2月24日 上午1:05，Jiuming Tao <jm...@streamnative.io> 写道： > > >>> > > >>> Hi all, > > >>>> > > >>>> 2. When there are hundreds MB metrics data collected, it causes high > > >> heap memory usage, high CPU usage and GC pressure. In the > > >> `PrometheusMetricsGenerator#generate` method, it uses > > >> `ByteBufAllocator.DEFAULT.heapBuffer()` to allocate memory for writing > > >> metrics data. The default size of > > `ByteBufAllocator.DEFAULT.heapBuffer()` > > >> is 256 bytes, when the buffer resizes, the new buffer capacity is 512 > > >> bytes(power of 2) and with `mem_copy` operation. > > >>>> If I want to write 100 MB data to the buffer, the current buffer size > > >> is 128 MB, and the total memory usage is close to 256 MB (256bytes + 512 > > >> bytes + 1k + .... + 64MB + 128MB). When the buffer size is greater than > > >> netty buffer chunkSize(16 MB), it will be allocated as > > UnpooledHeapByteBuf > > >> in the heap. After writing metrics data into the buffer, return it to > > the > > >> client by jetty, jetty will copy it into jetty's buffer with memory > > >> allocation in the heap, again! > > >>>> In this condition, for the purpose of saving memory, avoid high CPU > > >> usage(too much memory allocations and `mem_copy` operations) and > > reducing > > >> GC pressure, I want to change `ByteBufAllocator.DEFAULT.heapBuffer()` to > > >> `ByteBufAllocator.DEFAULT.compositeDirectBuffer()`, it wouldn't cause > > >> `mem_copy` operations and huge memory > > allocations(CompositeDirectByteBuf is > > >> a bit slowly in read/write, but it's worth). After writing data, I will > > >> call the `HttpOutput#write(ByteBuffer)` method and write it to the > > client, > > >> the method won't cause `mem_copy` (I have to wrap ByteBuf to > > ByteBuffer, if > > >> ByteBuf wrapped, there will be zero-copy). > > >>> > > >>> The jdk in my local is jdk15, I just noticed that in jdk8, ByteBuffer > > >> cannot be extended and implemented. So, if allowed, I will write metrics > > >> data to temp files and send it to client by jetty’s send_file. It will > > be > > >> turned out a better performance than `CompositeByteBuf`, and takes lower > > >> CPU usage due to I/O blocking.(The /metrics endpoint will be a bit > > slowly, > > >> I believe it’s worth). > > >>> If not allowed, it’s no matter and it also has a better performance > > than > > >> `ByteBufAllocator.DEFAULT.heapBuffer()`(see the first image in original > > >> mail). > > >>> > > >>> Thanks, > > >>> Tao Jiuming > > >> > > >> > > > >
