glog

the environment variable Gopath default value is/go 2. Map the code file and install Using the Add SRC/GO/SRC to map the host SCR file to the/GO/SRC directory, why is this/go/src directory? Yes, that's the path to the GOPATH environment variable above, because we need to perform the Go Install command later, otherwise we'll need to reset the Gopath to install the compiled binaries.Note that the local host in the SRC directory of the organization of the file, to perform go install will strictly

preserve the corpse of the container and can delete pod, through the lookup source found k8s by calling Podresourcesarereclaimed to determine whether the resources are recycled, only the resources are all recycled to delete pod, The implementation code of the 1.7.9 is as follows, in order to determine whether there is a running pod,volume is emptied, the sandbox (that is, the pause) container is clean: func (KL *kubelet) podresourcesarereclaimed (pod *v1. Pod, Status v1. Podstatus) bool {if!not

: Leaderelection '} This includes information such as IP and port of the Scheduler service And then: App. Run (s) calls the Run method in K8s.io/kubernetes/plugin/cmd/kube-scheduler/app/server.go:/Run runs the specified schedulerserver. This should never exit. Func Run (S *options. Schedulerserver) Error {if c, err: = Configz. New ("Componentconfig"); Err = = Nil {c.set (s.kubeschedulerconfiguration)} else {Glog. Errorf ("Unable to register Configz:

(1) garbage cans collection ProcessIn the Kubeletconfig Createandinitkubelet function, call K. Startgarbagecollection () Start k8s.io\kubernetes\cmd\kubelet\app\server.go:982 Starts garbage collection threads. Func (KL *kubelet) startgarbagecollection () {go wait . Until (func () { if err: = Kl.containerGC.GarbageCollect (Kl.sourcesReady.AllReady ()); Err!= nil {glog . Errorf ("Container garbage collection

-OpenCV, continue to put in the home.sudo./dependencies.shSince the habitual use of 2.4.8, so go to the 2.4 folder, and then execute the corresponding installation files, and then the installation is complete.sudo./opencv2_4_8.shIn the middle if the http://sourceforge.net/projects/opencvlibrary has not been linked, it means that the environment has already blocked the website address.The plan is to copy an already installed put Opencv-2.4.8.zip (my 2.4.8) on your desktop first, and then perform

installation, as described later)Brew Install Homebrew/science/openblas---> Direct installationBrew Install--build-from-source Homebrew/science/openblas--by compiling the source installation4. Installation ofMKL : Intel Mkl is a commercially available library for CPU optimization, can use the student free version, can register an account with the Intel official website "6", download the corresponding Mac version of MKL.Four, OpenCV, Glog, GFlags, Pro

dispatched, and the pod is added to the queue whenever new pod is established. Scheduleone will select the next pod to be scheduled from the queue for detailed scheduling operations. Selecting a good scheduling node will bind the pod to the selected node nodes. The following figure is the complete process for the entire scheduler:Scheduler Core Code explanation Scheduler Module Entrance The main () function is a scheduler module portal that creates a scheduleserver based on configuration and st

There are many good third-party open source libraries in Golang, such as Go-slog, this is the author's own open source of a simple log library Logrus Zap Oklog Glog Seelog Zerologare very good open source Library, the function is also very powerful, many support in TXT input log or JSON output of the log, I simply tried the next few log library 1. Logrus Package Mainimport ("Flag" "FMT" "OS" "Path" "Runtime" "Strings" "Time

Keep track of the detours you've compiled ceres-solver and hope to help others.The compilation process mainly refers to the following two blog posts, but there are still some big pits, I will emphasize later.http://blog.csdn.net/streamchuanxi/article/details/52944652http://blog.csdn.net/yizhou2010/article/details/525962801. Download the required libraries ceres-solver-1.11.0, Eigen, gflags-2.0, Glog-masterSpecific self-surfing search, download and ext

use the modified version of the installation package I provided (the previous Baidu cloud download) (The following installation method to use the package to complete, The installation package modified the dependencies.sh file and added the installation files for OpenCV 3.0.0)2. Switch to the folder where you saved the file, and then install the dependencies:$ sudo sh ubuntu/dependencies.sh3. Switch directory Ubuntu\3.0\ install OPENCV 3.0.0:$ sudo sh opencv3_0_0.shEnsure the network is unblocke

) Glog, gflags, Protobuf,leveldb, Snappy, HDF5, Lmdb these will have the corresponding installation instructions below, protobuf may need to modify the environment variable installation f) Python (Python 2.7,numpy (>=1.7)) Boost.python, if you don't need visualization, Python doesn't need to be concerned, although the makefile configuration file needs to provide a Python path--The lab has Install python,numpy:python_include: =/usr/local/include/python

+ num (UInt64 big endian) + hash + tdsuffix TD Numsuffix = []byte ("n")//headerprefix + num (UInt64 big endian) + Numsuffix-Hash Blockhashprefix = []byte ("H")//blockhashprefix + hash num (UInt64 big endian) Bodyprefix = []byte ("B")//bodyprefix + num (UInt64 big endian) + hash block body Where Headerprefix defines the prefix of the chunk header key to H,bodyprefix defines the chunk body key prefixed with B. Here is the function that stores the chunk header: Writeheader serializes a block heade

/code/gopath/src/gitlab.luojilab.com/zeroteam/ddkafka (module) $ go mod Init Gitlab.luojilab.com/zeroteam/ddkafka # Create go.modgo:creating new Go.mod:module gitlab.luojilab.com/zeroteam/ DDKAFKAQIANG@DESKTOP-2A835P9 Mingw64/d/code/gopath/src/gitlab.luojilab.com/zeroteam/ddkafka (module) $ ls # really created, Google Dafa good readme.md go.mod models.go mq_interface.go Sarama segmentioqiang@desktop-2a835p9 mingw64/d/code/gopath/src /gitlab.luojilab.com/zeroteam/ddkafka (module) $ cat Go.mod # L

Remaining dependentincluding Lmdb, etc.:sudo yum install gflags-devel glog-devel lmdb-develIf these extension package is not found here in the Yum source, but manually compiled (to have root privileges):# Glogwget Https://google-glog. Googlecode. com/files/glog-0.3. 3. Tar. GZTar zxvf glog-0.3. 3. Tar. GZCD

\ install OPENCV3.0.0RC1:$ sudo sh opencv3_0_0-rc1.shEnsure that the network is unblocked, because the software needs to be networked here for a long time. Please wait patiently.。。。 The time is very long!V: Install additional dependencies1. Google Logging Library (glog): https://code.google.com/p/google-glog/. Then unzip the installation:$ tar zxvf glog-0.3.3.tar

Caffe is an efficient, deep learning framework. It can be executed either on the CPU or on the GPU.The following is an introduction to the Caffe configuration compilation process on Ubuntu without Cuda:1. Install the blas:$ sudo apt-get install Libatlas-base-dev2. Install dependencies: $ sudo apt-get install Libprotobuf-dev libleveldb-dev libsnappy-devlibopencv-dev Libboost-all-dev libhdf5-se Rial-dev Protobuf-compiler Liblmdb-dev3. Install Glog (down

Today I would like to find an open-source log class for my C + + project to record the system log, resulting in a half-afternoon of wasted time. Search for relevant information from the Internet to find the following options:1, log4cplus:http://sourceforge.net/projects/log4cplus/files/log4cplus-stable/1.1.02, log4cxx:http://logging.apache.org/log4cxx/download.html (Log4cxx is implemented by Java log4j Open Source, in C + + implementation of an open source library)3, Glog:http://code.google.com/p

needs to be networked here for a long time, please wait patiently ... , a long time! V: Install additional dependencies1. Google Logging Library (glog),: https://code.google.com/p/google-glog/, then unzip the installation:$ tar zxvf glog-0.3.3.tar.gz$./configure$ make$ sudo make installIf you do not have permission to chmod a+x

Caffe is an efficient, deep learning framework. It can be executed either on the CPU or on the GPU.The following is an introduction to the Caffe configuration compilation process on Ubuntu without Cuda:1. Install the blas:$ sudo apt-get install Libatlas-base-dev2. Install dependencies: $ sudo apt-get install Libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libboost-all-dev libhdf5- Serial-dev Protobuf-compiler Liblmdb-dev3. Install Glog (dow

here for a long time, please wait patiently ... , a long time!V: Install additional dependencies1. Google Logging Library (glog),: https://code.google.com/p/google-glog/, then unzip the installation:$ tar zxvf glog-0.3.3.tar.gz$./configure$ make$ sudo make installIf you do not have permission to chmod a+x glog-0.3.3-r