Merge pull request #50 from sql-machine-learning/modify_doc

Add cache for vm, update doc.

dev.md

@@ -2,7 +2,7 @@
 
 ### For Developers
 
-1. Install [VirtualBox](https://www.virtualbox.org/) and [Vagrant](https://www.vagrantup.com/) on a computer with a relatively large memory size.  As a recommendation, a host with 16G memory and 8 cores is preferred.
+1. Install [VirtualBox 6.1.6](https://www.virtualbox.org/) and [Vagrant 2.2.7](https://www.vagrantup.com/) on a computer with a relatively large memory size.  As a recommendation, a host with 16G memory and 8 cores is preferred.
 1. Clone and update `SQLFlow playground` project.
     ```bash
     git clone https://github.com/sql-machine-learning/playground.git
@@ -47,9 +47,10 @@ According to this [tutorial](https://www.techrepublic.com/article/how-to-import-
 
 ### For End-users
 
-To run SQLFlow on a desktop computer running Windows, Linux, or macOS, you need to download
+To run SQLFlow on a desktop computer running Windows, Linux, or macOS, follow below steps:
+1. install [VirtualBox](https://www.virtualbox.org/) (v6.1.6 is recommended)
 
-1. the released VirtualBox `.ova` file, you have two choices:
+1. download the released VirtualBox `.ova` file, you have two choices:
     - the minimized image (about 600M): shipped with all bootstrap files but no dependency docker images. When you start the playground, you will wait for a while to download the latest docker images, minikube framework and other packages.
     ```bash
     wget -c http://cdn.sqlflow.tech/latest/SQLFlowPlaygroundBare.ova
@@ -58,9 +59,9 @@ To run SQLFlow on a desktop computer running Windows, Linux, or macOS, you need
     ```bash
     wget -c http://cdn.sqlflow.tech/latest/SQLFlowPlaygroundFull.ova
     ```
-1. optional, the [sqlflow](https://github.com/sql-machine-learning/sqlflow/blob/develop/doc/run/cli.md) command-line tool released by SQLFlow CI.
+1. optional, download the [sqlflow](https://github.com/sql-machine-learning/sqlflow/blob/develop/doc/run/cli.md) command-line tool released by SQLFlow CI.
 
-If you have VirtualBox installed, you can import the `SQLFlowPlayground.ova` file and start a VM.  After that, you can log in the system through the VirtualBox GUI or through a ssh connection like below.  The default password of `root` is `sqlflow`.
+After VirtualBox is installed, you can import the `.ova` file and start a VM.  If you have a relative lower configuration, you can adjust the CPU core and RAM amount in VirtualBox's setting panel, say, to 2 cores and 4G RAM.  After that, you can log in the system through the VirtualBox GUI or through a ssh connection like below.  The default password of `root` is `sqlflow`.
 ```bash
 ssh -p2222 [email protected]
 [email protected]'s password: sqlflow

provision.bash

@@ -8,7 +8,7 @@ VAGRANT_SHARED_FOLDER=/home/vagrant/desktop
 source $VAGRANT_SHARED_FOLDER/sqlflow/docker/dev/find_fastest_resources.sh
 
 echo "Setting apt-get mirror..."
-rm -rf /var/lib/apt/lists/*
+rm -rf /var/lib/apt/lists/* /etc/apt/sources.list
 find_fastest_apt_source >/etc/apt/sources.list
 apt-get update
 
@@ -91,3 +91,11 @@ sed -i -e 's/^PasswordAuthentication no/PasswordAuthentication yes/g' \
     /etc/ssh/sshd_config
 service ssh restart
 echo "Done."
+
+
+echo "Disable cloudimg grub settings ..."
+sed -i -e 's/^GRUB_CMDLINE_LINUX_DEFAULT="quiet splash"/GRUB_CMDLINE_LINUX_DEFAULT="quiet"/g' \
+    -e 's/^#GRUB_TERMINAL=console$/GRUB_TERMINAL=console/g' /etc/default/grub
+rm /etc/default/grub.d/50-cloudimg-settings.cfg
+update-grub
+echo "Done."

release.sh

@@ -32,8 +32,9 @@ VBoxManage sharedfolder remove "$vm" --name home_vagrant_desktop
 VBoxManage sharedfolder remove "$vm" --name vagrant
 echo "Done."
 
-echo "Rebind serial port file"
+echo "Rebind serial port file and disable it because it does not work on Windows"
 VBoxManage modifyvm "$vm" --uartmode1 file /tmp/playground.log
+VBoxManage modifyvm "$vm" --uart1 off
 echo "Done."
 
 echo "Exporting vm ..."

start.bash

@@ -29,21 +29,25 @@ fi
 filebase=/root/scripts
 
 echo "Docker pull dependency images, you can comment this if already have them ..."
-if [[ -d "/root/.cache" ]]; then
-    echo "Cache found at /root/.cache ..."
-    if [[ ! -f "/root/.cache/.loaded" ]]; then
-        find /root/.cache/* | xargs -I'{}' docker load -i '{}'
-        touch /root/.cache/.loaded
+if [[ -d "/root/.sqlflow" ]]; then
+    echo "Cache found at /root/.sqlflow ..."
+    if [[ ! -f "/root/.sqlflow/.loaded" ]]; then
+        find /root/.sqlflow/* | xargs -I'{}' sh -c "docker load -i '{}' && sleep 10"
+        touch /root/.sqlflow/.loaded
     fi
+    # use local step images for model zoo model
+    docker tag sqlflow/sqlflow:step sqlflow/sqlflow:latest
 else
     # c.f. https://github.com/sql-machine-learning/sqlflow/blob/develop/.travis.yml
     docker pull sqlflow/sqlflow:jupyter
     docker pull sqlflow/sqlflow:mysql
     docker pull sqlflow/sqlflow:server
     docker pull sqlflow/sqlflow:step
+    docker pull sqlflow/sqlflow:modelzooserver
     docker pull argoproj/argoexec:v2.7.7
     docker pull argoproj/argocli:v2.7.7
     docker pull argoproj/workflow-controller:v2.7.7
+    docker tag sqlflow/sqlflow:modelzooserver sqlflow/sqlflow:model_zoo
 fi
 echo "Done."
 
@@ -163,6 +167,7 @@ expose argo service/argo-server 9001:2746
 expose default pod/sqlflow-server 8888:8888
 expose default pod/sqlflow-server 3306:3306
 expose default pod/sqlflow-server 50051:50051
+expose default pod/sqlflow-server 50055:50055
 
 # Get Jupyter Notebook's token, for single-user mode, we disabled the token checking
 # jupyter_addr=$(kubectl logs pod/sqlflow-server notebook | grep -o -E "http://127.0.0.1[^?]+\?token=.*" | head -1)
@@ -176,6 +181,7 @@ Access Jupyter Notebook at: http://localhost:8888
 Access Kubernetes Dashboard at: http://localhost:9000
 Access Argo Dashboard at: http://localhost:9001
 Access SQLFlow with cli: ./sqlflow --data-source="\"$mysql_addr\""
+Access SQLFlow Model Zoo at: localhost:50055
 
 Stop minikube with: minikube stop
 Stop vagrant vm with: vagrant halt