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Posted to commits@kylin.apache.org by xx...@apache.org on 2022/01/25 06:13:26 UTC
[kylin] branch kylin4_on_cloud updated: # update README.md
This is an automated email from the ASF dual-hosted git repository.
xxyu pushed a commit to branch kylin4_on_cloud
in repository https://gitbox.apache.org/repos/asf/kylin.git
The following commit(s) were added to refs/heads/kylin4_on_cloud by this push:
new 4ce0c30 # update README.md
4ce0c30 is described below
commit 4ce0c30ecfa255210826ab8f479b0ee2c4a1ab46
Author: Mukvin <bo...@163.com>
AuthorDate: Tue Jan 25 13:58:45 2022 +0800
# update README.md
---
README.md | 465 +--------------------------------------------
readme/advanced_configs.md | 62 ++++++
readme/commands.md | 103 ++++++++++
readme/monitor.md | 59 ++++++
readme/prerequisites.md | 216 +++++++++++++++++++++
5 files changed, 449 insertions(+), 456 deletions(-)
diff --git a/README.md b/README.md
index 0ab0f0e..9189c95 100644
--- a/README.md
+++ b/README.md
@@ -22,7 +22,7 @@ When cluster was created, services and nodes will like below:
## Quick Start
-1. Initialize aws account credential on local mac, please check [details](#localaws).
+1. Initialize aws account credential on local mac, please check [details](./readme/prerequisites.md#localaws).
2. Download the source code:
@@ -34,11 +34,11 @@ When cluster was created, services and nodes will like below:
1. Set the `AWS_REGION`.
- 2. Set the `IAMRole`,please check [details](#IAM).
+ 2. Set the `IAMRole`,please check [details](./readme/prerequisites.md#IAM).
- 3. Set the `S3_URI`, please check [details](#S3).
+ 3. Set the `S3_URI`, please check [details](./readme/prerequisites.md#S3).
- 4. Set the `KeyName`,please check [details](#keypair).
+ 4. Set the `KeyName`,please check [details](./readme/prerequisites.md#keypair).
5. Set the `CIDR_IP`, make sure that the `CIDR_IP` match the pattern `xxx.xxx.xxx.xxx/16[|24|32]`.
@@ -94,7 +94,7 @@ $ python ./deploy.py --type destroy
> 2. If user create multiple clusters, `default` cluster always be created. If `CLUSTER_INDEXES` is (1, 3), there will be 4 cluster which contains the cluster 1, 2, 3 and `default` will be created if user execute the commands.
> 3. Configs for multiple clusters always are same as the `default` cluster to read from `kylin-tpch/kylin_configs.yaml`
-2. Copy `kylin.properties.template` for expecting clusters to deploy, please check the [details](#cluster).
+2. Copy `kylin.properties.template` for expecting clusters to deploy, please check the [details](./readme/prerequisites.md#cluster).
3. Execute commands to deploy `all` clusters.
@@ -110,459 +110,12 @@ $ python ./deploy.py --type destroy
-## Prerequisites
-
-### Download source code & checkout to branch of `deploy-kylin-on-aws`
-
-commands:
-
-```shell
-git clone https://github.com/Kyligence/kylin-tpch.git && cd kylin-tpch && git checkout deploy-kylin-on-aws
-```
-
-### Initiliaze an AWS Account
-
-#### I. Create an `IAM` role<a name="IAM"></a>
-
-> Note:
->
-> `IAM` role must have the access which contains `AmazonEC2RoleforSSM` , `AmazonSSMFullAccess` and `AmazonSSMManagedInstanceCore`.
->
-> This `IAM` Role will be used to initialize every ec2 instances which are for creating an kylin4 cluster on aws. And it will configure in `Initilize Env of Local Mac` part.
-
-#### II. Create a `User`
-
-> Note:
->
-> The `User` who is created in aws will be used to execute some operations on EC2 instance. So the `User` must has some authorities as below.
-
-| Services | Access level | Resources | Request condition |
-| ------------------- | ------------------------------------------------------ | ------------- | ----------------- |
-| **Cloudformation** | **Limited**: List, Read,Write | All Resources | None |
-| **EC2** | **Limited**: Read | All Resources | None |
-| **IAM** | **Limited**: List, Read, Write, Permissions management | All Resources | None |
-| **RDS** | **Limited**: List, Write, Tagging | All Resources | None |
-| **S3** | **Limited**: Write, Permissions management, Tagging | All Resources | None |
-| **SNS** | **Limited**: List | All Resources | None |
-| **STS** | **Limited**: Write | All Resources | None |
-| **Systems Manager** | **Limited**: Write | All Resources | None |
-
-#### III. Login the created `User` to create key pair and Access Key<a name="keypair"></a>
-
-> Note:
->
-> To deploy EC2 instances for Kylin4 Cluster need key pair and access key.
-
-##### 1. Create a new `Key Pair` in the `EC2 -> Key pairs`
-
-
-
-##### 2. Genrate a new `Access Key` which in the `My Security Credentials`
-
-> Note:
->
-> Please download the generated the csv file of `Access Key` immediately. Get the `Access Key ` and `Secret Key` to initilize local mac to access aws.
-
-
-
-
-
-
-
-
-
-### Initialize a S3 direcotry<a name="S3"></a>
-
-#### I. Create a directory on S3
-
-> Note:
->
-> This directory will store tars, scripts and jars below. And it will also be the root path of working dir for kylin4.
-
-Example: make a directory named `kylin4-aws-test` . You can also create a directory named what you like.
-
-
-
-
-
-#### **(Optional)** II. Manually Download packages & Upload them to the S3 path which suffix is `*/tar`
-
-> Note:
->
-> This step will automatically do by tools. So you can skip this step, or you want to check packages by yourself.
-
-
-
-> Create the directory named `tar` **in the path which was created by yourself**.
->
-> As example, the full path would be `s3://.../kylin4-aws-test/tar`.
-
-1. Download Kylin4 package by [official website](https://kylin.apache.org/download/).
-2. Download Hadoop, [version 3.2.0](https://archive.apache.org/dist/hadoop/common/hadoop-3.2.0/hadoop-3.2.0.tar.gz).
-3. Download Spark with hadoop3.2, [version 3.1.1](https://archive.apache.org/dist/spark/spark-3.1.1/spark-3.1.1-bin-hadoop3.2.tgz).
-4. Download Hive, [version 2.3.9](https://archive.apache.org/dist/hive/hive-2.3.9/apache-hive-2.3.9-bin.tar.gz).
-5. Download Zookeeper, [version 3.4.9.](https://archive.apache.org/dist/zookeeper/zookeeper-3.4.9/zookeeper-3.4.9.tar.gz)
-6. Download JDK, [version 1.8_301](https://www.oracle.com/java/technologies/javase/javase8u211-later-archive-downloads.html).
-7. Download Node Exporter, [version 1.3.1.](https://github.com/prometheus/node_exporter/releases/download/v1.3.1/node_exporter-1.3.1.linux-amd64.tar.gz)
-8. Download Prometheus Server, [version 2.31.1](https://github.com/prometheus/prometheus/releases/download/v2.31.1/prometheus-2.31.1.linux-amd64.tar.gz).
-9. Download Kylin4 package with local cache + soft affinity feature by [public website.](https://s3.cn-north-1.amazonaws.com.cn/public.kyligence.io/kylin/tar/apache-kylin-4.0.0-bin-spark3-soft.tar.gz)
-
-
-
-> Note:
-> If you want to use Kylin4 with local cache + soft affinity feature, please download the `experimental` package above.
-
-
-
-
-
-#### (Optional) III. Upload `kylin-tpch/backup/jars/*` to the S3 Path which suffix is `*/jars`
-
-> Note:
->
-> This step will automatically do by tools. So you can skip this step, or you want to check jars by yourself.
-
-
-
-> Create the directory named `jars` **in the path which was created by yourself**.
->
-> As example, the full path would be `s3://.../kylin4-aws-test/jars`.
-
-Kylin4 needed extra jars
-
-- Basic jars
- - commons-configuration-1.3.jar
- - mysql-connector-java-5.1.40.jar
-- Local Cache + Soft Affinity feature needed jars
- - alluxio-2.6.1-client.jar
- - kylin-soft-affinity-cache-4.0.0-SNAPSHOT.jar
-
-
-
-#### (Optional) IV. Upload `kylin-tpch/backup/scripts/*` to the S3 Path which suffix is `*/scripts`
-
-> Note:
->
-> This step will automatically do by tools. So you can skip this step, or you want to check scripts by yourself.
-
-
-
-> Create the directory named `scripts` **in the path which was created by yourself**.
->
-> As example, the full path would be `s3://.../kylin4-aws-test/scripts`.
-
-Scripts:
-
-- prepare-ec2-env-for-kylin4.sh
-- prepare-ec2-env-for-spark-master.sh
-- prepare-ec2-env-for-spark-slave.sh
-- prepare-ec2-env-for-static-services.sh
-- prepare-ec2-env-for-zk.sh
-
-
-
-### Initilize Env Of Local Mac
-
-#### I. Initilize a aws account on local mac to access AWS<a name="localaws"></a>
-
-> Use `Access Key` and `Secret Key ` above to Initilize a aws account on local mac.
-
-```shell
-$ aws configure
-AWS Access Key ID : *************
-AWS Secret Access Key : *************
-Default region name : cn-northwest-1
-Default output format : json
-```
-
-> Note:
->
-> 1. If this command got the response `-bash: aws: command not found`, please check in [Getting started with the AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-getting-started.html).
-> 2. Region name can be in [Available Regions](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using-regions-availability-zones.html#concepts-available-regions).
-> 3. Default output format is `json`.
-
-#### II. Init a Python virtual env
-
-> Note:
->
-> Make sure that your mac already has a Python which version is 3.6.6 or later.
-
-commands:
-
-```shell
-$ ./bin/init.sh
-```
-
-> Note: Follow the information after `./bin/init.sh` to activate the python virtual env.
-
-#### III. Configure the `kylin-tpch/kylin_configs.yaml`
-
-**Required parameters**:
-
-- `AWS_REGION`: Current region for EC2 instances.
-- `IAMRole`: IAM role which has the access to aws authority. This parameter will be set to created **name** of IAM role.
-- `S3_URI`: the prefix path of storing `jars/scripts/tar`. As example, this parameter will be set to `s3://.../kylin4-aws-test`.
-- `KeyName`: Security key name is a set of security credentials that you use to prove your identity when connecting to an instance. This parameter will be set to created **name** of `key pair` .
-- `CIDR_IP`: An inbound rule permits instances to receive traffic from the specified IPv4 or IPv6 CIDR address range, or from the instances associated with the specified security group.
-- `DB_IDENTIFIER`: this param should be only one in the `RDS -> Databases` . And it will be the name of created RDS database.
-- `DB_PORT`: this param will be the port of created RDS database, default is `3306`.
-- `DB_USER`: this param will be a login ID for the master user of your DB instance, default is `root`.
-- `DB_PASSWORD`: this param will be the password of `DB_USER` to access DB instance. default is `123456test`, it's strongly suggest you to change it.
-
-#### IV. Configure the `kylin.properties` in `backup/properties` directories.<a name="cluster"></a>
-
-1. The `kylin.properties` is for starting kylin instance in the cluster.
-2. Default cluster will check the `kylin.properties` in the `kylin-tpch/backup/properties/default`, and other specific cluster will check the related num directory such as `1`, `2` and `3`.
-3. User need to create new dir for the cluster num in `kylin-tpch/backup/properties`, and name it to the `${cluster num}`, such as `1`, `2` ,`3` and so on. The range of cluster num must be in `CLUSTER_INDEXES` which is configured in the `kylin-tpch/kylin_configs.yml`.
-4. Follow the `2.` step, copy the `kylin.properties.template` which is in `kylin-tpch/backup/properties/templates` to the related `${cluster num} ` directories， and rename the template to `kylin.properties`.
-5. The range of cluster nums must match the the config `CLUSTER_INDEXES`, such as `CLUSTER_INDEXES: (1, 3)` then the directories must be `1`, `2`,`3` in the `kylin-tpch/backup/properties`.
-
-
-
-6. Cusomize the config which you want to change except the config which contains `{{ }}` mark.
-
-7. If the related `kylin.properties` was filled with cluster information, a file named `.rendered` will create in the directory.
-
-
-
-7. **(Important !!!)** If you want to re-fill the `kylin.properties` for a `kylin` node in specify cluster, you need to remove the `.rendered` file and re-copy the `kylin.propertie.template` . Redo steps from `3` to `6`.
-
-## Advanced Configs
-
-> Note:
->
-> If you want quickly to start Kylin4 Cluster on aws, then skip this part and jump to the part of [`Run`](#run) directly.
-
-### Advaced Params
-
-There are `9` modules params for tools. Introductions as below:
-
-- EC2_VPC_PARAMS: this params of module are for creating a vpc.
-
-- EC2_RDS_PARAMS: this params of module are for creating a RDS.
-
-- EC2_STATIC_SERVICES_PARAMS: this params of module are for creating a Prometheus Server and other static services.
-
-- EC2_ZOOKEEPERS_PARAMS: this params of module are for creating a Zookeeper Cluster.
-
-- EC2_SPARK_MASTER_PARAMS: this params of module are for creating a Spark Master node.
-
-- EC2_KYLIN4_PARAMS: this params of module are for creating a Kylin4.
-
-- EC2_SPARK_WORKER_PARAMS: this params of module are for creating **Spark Workers**, default is **3** spark workers for all clusters.
-
-- EC2_KYLIN4_SCALE_PARAMS: this params of module are for scaling **Kylin4 nodes**, the range of **Kylin4 nodes** is related to `KYLIN_SCALE_UP_NODES` and `KYLIN_SCALE_DOWN_NODES`.
-
- > Note:
- >
- > 1. `KYLIN_SCALE_UP_NODES` is for the range of kylin nodes to scale up.
- > 1. `KYLIN_SCALE_DOWN_NODES` is for the range of kylin nodes to scale down.
- > 1. The range of `KYLIN_SCALE_UP_NODES` must be contain the range of `KYLIN_SCALE_DOWN_NODES`.
- > 1. **They are effective to all clusters which is not only `default cluster` but also other cluster which index is in `${CLUSTER_INDEXES}`.**
-
-- EC2_SPARK_SCALE_SLAVE_PARAMS: this params of module are for scaling **Spark workers**, the range of **Spark Workers ** is related to `SPARK_WORKER_SCALE_UP_NODES` and `SPARK_WORKER_SCALE_DOWN_NODES`.
-
- > Note:
- >
- > 1. `SPARK_WORKER_SCALE_UP_NODES` is for the range for spark workers to scale up. **It's effective to all clusters which is not only `default cluster` but also other cluster which index is in `${CLUSTER_INDEXES}`.**
- > 1. `SPARK_WORKER_SCALE_DOWN_NODES` is for the range for spark workers to scale down. **It's effective to all clusters which is not only `default cluster` but also other cluster which index is in `${CLUSTER_INDEXES}`.**
- > 1. The range of `SPARK_WORKER_SCALE_UP_NODES` must be contain the range of `SPARK_WORKER_SCALE_DOWN_NODES`.
- > 1. **They are effective to all clusters which is not only `default cluster` but also other cluster which index is in `${CLUSTER_INDEXES}`.**
-
-### Customize Configs
-
-User also can customize the params in `kylin-tpch/kylin_configs.yaml` to create an expected instances. Such as **the type of instance**, **the volume size of instance** and **the volumn type of instance** and so on.
-
-1. If you want to customize configs for instances, you must modify the `EC2Mode` from `test` to `product` in the ``kylin-tpch/kylin_configs.yml`.
-2. `Ec2Mode` is only in the parms of `EC2_STATIC_SERVICES_PARAMS`, `EC2_ZOOKEEPERS_PARAMS`, `EC2_SPARK_MASTER_PARAMS`, `EC2_KYLIN4_PARAMS`, `EC2_SPARK_WORKER_PARAMS`, `EC2_KYLIN4_SCALE_PARAMS` and `EC2_SPARK_SCALE_SLAVE_PARAMS`.
-3. So instances can be customized to effect `Monitor Node`(`EC2_STATIC_SERVICES_PARAMS`), `Zookeeper Nodes`(`EC2_ZOOKEEPERS_PARAMS`), `Spark Master Node` ( `EC2_SPARK_MASTER_PARAMS`), `Kylin4 Node`( `EC2_KYLIN4_PARAMS`), `Spark workers `(`EC2_SPARK_WORKER_PARAMS`), `Kylin4 scale nodes`(`EC2_KYLIN4_SCALE_PARAMS`) and `Spark scale workers`(`EC2_SPARK_SCALE_SLAVE_PARAMS`).
-4. Now`Ec2Mode` **only effect** the related params are `Ec2InstanceTypeFor*`,`Ec2VolumeSizeFor*` and `Ec2VolumnTypeFor`* in the params modules.
-5. If you don't change `ENABLE_LOCAL_CACHE_SOFT_AFFINITY` from `"false"` to `"true"` then cluster will created normally without `Local Cache + Soft Affinity` feature!
-
-
-
-#### Example
-
-As an example in `EC2_STATIC_SERVICES_PARAMS`:
-
-- change `Ec2Mode ` from `test`to `product`
-- change `Ec2InstanceTypeForStaticServices` from `m5.2xlarge` to `m5.4xlarge`.
-- change `Ec2VolumeSizeForStaticServicesNode` from `'20'` to `'50'.`
-- change `Ec2VolumnTypeForStaticServicesNode` from `gp2` to `standard`.
-- Then create the node of static service node will be a ``m5.4xlarge` and it attach a volume which size is `50` and type is `standard`.
-
-
-
-
-
-## Monitor
-
-Current tool also support the feature of monitor for cluster.
-
-1. User can execute `python ./deploy.py --type list` to get the `public ip` of `Static Service` .
-2. User can access the `public ip` of `Static Service` and the port is `9090` to access `Prometheus` server.
-3. User can access the `public ip` of `Static Service` and the port is `3000` to access `Granfana` server.
-
-### Quick Start For Prometheus
-
-1. Input a `Metric`, user can get the available metric from the metric exploer.
-
-
-
-2. Execute a query to generate a dashboad.
-
-
-
-3. Add a new panel for a new query.
-
-
-
-More details about `PromQL` for metric exploer, please check [official website](https://prometheus.io/docs/prometheus/latest/querying/).
-
-#### Spark Metric In Prometheus
-
-> Note:
->
-> 1. Current tool support to monitor spark metrics, more detail in [Spark Metrics](https://spark.apache.org/docs/3.1.1/monitoring.html#executor-metrics).
-> 2. Spark metrics is start with `metrics` in Prometheus server.
->
-> 
-
- ### Quick Start For Granfana
-
-1. Login into dashboard with default user and password which are all `admin` at the first time.
-2. Configure the connection to prometheus server.
-
-
-
-
-
-
-
-> Just config the url with syntax `http://${private ip of static service}:9090` . The `private ip of static service` can be from the `python ./deploy.py --type list` command.
-
-3. Add a new panel.
-
-
-
-4. Add a new panel or other.
-
-
-
-5. Edit & Apply the panel.
-
-
-
-More details about the usage of Granfana in [official website](https://grafana.com/docs/grafana/latest/).
-
-## Run<a name="run"></a>
-
-Command:
-
-```shell
-python ./deploy.py --type [deploy|destroy|list|scale] --scale-type [up|down] --node-type [kylin|spark_worker] [--cluster {1..6}|all|default]
-```
-
-- deploy: create cluster(s).
-
-- destroy: destroy created cluster(s).
-
-- list: list alive nodes which are with stack name, instance id, private ip and public ip.
-
-- scale: Must be used with `--scale-type` and `--node-type`.
-
- > Note:
- >
- > 1. Current support to scale up/down `kylin` or `spark_worker` for specific cluster.
- > 2. Before scale up/down `kylin` or `spark_worker` nodes, Cluster services must be ready.
- > 2. If you want to scale a `kylin` or `spark_worker` node to a specify cluster, please add the `--cluster ${cluster num}` to specify the expected node add to the cluster `${cluster num}`.
-
-### Command of deploy
-
-- Deploy default cluster
-
-```shell
-$ python ./deploy.py --type deploy [--cluster default]
-```
-
-- Deploy a cluster with specific cluster index.
-
-```shell
-$ python ./deploy.py --type deploy --cluster ${cluster num}
-```
-
-> Note: the `${cluster num}` must be in the range of `CLUSTER_INDEXES`.
-
-- Deploy all cluster which contain default cluster and all cluster which index in the range of `CLUSTER_INDEXES`.
-
-```sHe
-$ python ./deploy.py --type deploy --cluster all
-```
-
-### Command of destroy
-
-> Note:
->
-> Destroy all cluster will not delete vpc, rds and monitor node. So if user don't want to hold the env, please set the `ALWAYS_DESTROY_ALL` to be `'true'`.
-
-- Destroy default cluster
-
-```shell
-$ python ./deploy.py --type destroy [--cluster default]
-```
-
-- Destroy a cluster with specific cluster index.
-
-```shell
-$ python ./deploy.py --type destroy --cluster ${cluster num}
-```
-
-> Note: the `${cluster num}` must be in the range of `CLUSTER_INDEXES`.
-
-- Destroy all cluster which contain default cluster and all cluster which index in the range of `CLUSTER_INDEXES`.
-
-```shell
-$ python ./deploy.py --type destroy --cluster all
-```
-
-### Command of list
-
-- List nodes which are with **stack name**, **instance id**, **private ip** and **public ip** in **available stacks** .
-
-```shell
-$ python ./deploy.py --type list
-```
-
-### Command of scale
-
-> Note:
->
-> 1. Scale command must be used with `--scale-type` and `--node-type`.
-> 2. If scale command not specify a cluster num, then the scaled node(kylin or spark worker) will be add to `default`cluster.
-> 3. Scale command **not support** to **scale** node (kylin or spark worker) to **all clusters** at **one time**. It means that `python ./deploy.py --type scale --scale-type up[|down] --node-type kylin[|spark_worker] --cluster all` is invalid commad.
-> 4. Scale params which are `KYLIN_SCALE_UP_NODES`, `KYLIN_SCALE_DOWN_NODES`, `SPARK_WORKER_SCALE_UP_NODES` and `SPARK_WORKER_SCALE_DOWN_NODES` effect on all cluster. So if user want to scale node for a specify cluster, then modify the scale params before **every run time.**
-> 5. **(Important!!!)** Current cluster is created with default `3` spark workers and `1` kylin node. The `3` spark workers can not be scaled down. The `1` kylin node also can not be scaled down.
-> 6. **(Important!!!)** Cluster can only scale up or down the range of nodes which is in `KYLIN_SCALE_UP_NODES`, `KYLIN_SCALE_DOWN_NODES`, `SPARK_WORKER_SCALE_UP_NODES` and `SPARK_WORKER_SCALE_DOWN_NODES` . Not the default `3` spark workers and `1` kylin node in the cluster.
-> 7. **(Important!!!)** If user don't want to create a cluster with `3` default spark workers, then user can remove the useless node module in the `Ec2InstanceOfSlave0*` of `kylin-tpch/cloudformation_templates/ec2-cluster-spark-slave.yaml`. User need to know about the syntax of cloudformation as also.
-
-- Scale up/down kylin/spark workers in default cluster
-
-```shell
-python ./deploy.py --type scale --scale-type up[|down] --node-type kylin[|spark_worker] [--cluster default]
-```
-
-- Scale up/down kylin/spark workers in a specific cluster
-
-```shell
-python ./deploy.py --type scale --scale-type up[|down] --node-type kylin[|spark_worker] --cluster ${cluster num}
-```
-
-> Note: the `${cluster num}` must be in the range of `CLUSTER_INDEXES`.
-
-
-
## Notes
+1. More details about `commands` of tool, see document [commands](./readme/commands.md).
+2. More details about `prerequisites` of tool, see document [prerequisites](./readme/prerequisites.md).
+3. More details about `advanced configs` of tool, see document [advanced configs](./readme/advanced_configs.md).
+4. More details about `monitor services` supported by tool, see document [monitor](./readme/monitor.md).
1. Current tool already open the port for some services. You can access the service by `public ip` of related EC2 instance.
1. `SSH`: 22
2. `Granfana`: 3000
diff --git a/readme/advanced_configs.md b/readme/advanced_configs.md
new file mode 100644
index 0000000..86d2ae9
--- /dev/null
+++ b/readme/advanced_configs.md
@@ -0,0 +1,62 @@
+## Advanced Configs
+
+### Advaced Params
+
+There are `9` modules params for tools. Introductions as below:
+
+- EC2_VPC_PARAMS: this params of module are for creating a vpc.
+
+- EC2_RDS_PARAMS: this params of module are for creating a RDS.
+
+- EC2_STATIC_SERVICES_PARAMS: this params of module are for creating a Prometheus Server and other static services.
+
+- EC2_ZOOKEEPERS_PARAMS: this params of module are for creating a Zookeeper Cluster.
+
+- EC2_SPARK_MASTER_PARAMS: this params of module are for creating a Spark Master node.
+
+- EC2_KYLIN4_PARAMS: this params of module are for creating a Kylin4.
+
+- EC2_SPARK_WORKER_PARAMS: this params of module are for creating **Spark Workers**, default is **3** spark workers for all clusters.
+
+- EC2_KYLIN4_SCALE_PARAMS: this params of module are for scaling **Kylin4 nodes**, the range of **Kylin4 nodes** is related to `KYLIN_SCALE_UP_NODES` and `KYLIN_SCALE_DOWN_NODES`.
+
+ > Note:
+ >
+ > 1. `KYLIN_SCALE_UP_NODES` is for the range of kylin nodes to scale up.
+ > 1. `KYLIN_SCALE_DOWN_NODES` is for the range of kylin nodes to scale down.
+ > 1. The range of `KYLIN_SCALE_UP_NODES` must be contain the range of `KYLIN_SCALE_DOWN_NODES`.
+ > 1. **They are effective to all clusters which is not only `default cluster` but also other cluster which index is in `${CLUSTER_INDEXES}`.**
+
+- EC2_SPARK_SCALE_SLAVE_PARAMS: this params of module are for scaling **Spark workers**, the range of **Spark Workers ** is related to `SPARK_WORKER_SCALE_UP_NODES` and `SPARK_WORKER_SCALE_DOWN_NODES`.
+
+ > Note:
+ >
+ > 1. `SPARK_WORKER_SCALE_UP_NODES` is for the range for spark workers to scale up. **It's effective to all clusters which is not only `default cluster` but also other cluster which index is in `${CLUSTER_INDEXES}`.**
+ > 1. `SPARK_WORKER_SCALE_DOWN_NODES` is for the range for spark workers to scale down. **It's effective to all clusters which is not only `default cluster` but also other cluster which index is in `${CLUSTER_INDEXES}`.**
+ > 1. The range of `SPARK_WORKER_SCALE_UP_NODES` must be contain the range of `SPARK_WORKER_SCALE_DOWN_NODES`.
+ > 1. **They are effective to all clusters which is not only `default cluster` but also other cluster which index is in `${CLUSTER_INDEXES}`.**
+
+### Customize Configs
+
+User also can customize the params in `kylin-tpch/kylin_configs.yaml` to create an expected instances. Such as **the type of instance**, **the volume size of instance** and **the volumn type of instance** and so on.
+
+1. If you want to customize configs for instances, you must modify the `EC2Mode` from `test` to `product` in the ``kylin-tpch/kylin_configs.yml`.
+2. `Ec2Mode` is only in the parms of `EC2_STATIC_SERVICES_PARAMS`, `EC2_ZOOKEEPERS_PARAMS`, `EC2_SPARK_MASTER_PARAMS`, `EC2_KYLIN4_PARAMS`, `EC2_SPARK_WORKER_PARAMS`, `EC2_KYLIN4_SCALE_PARAMS` and `EC2_SPARK_SCALE_SLAVE_PARAMS`.
+3. So instances can be customized to effect `Monitor Node`(`EC2_STATIC_SERVICES_PARAMS`), `Zookeeper Nodes`(`EC2_ZOOKEEPERS_PARAMS`), `Spark Master Node` ( `EC2_SPARK_MASTER_PARAMS`), `Kylin4 Node`( `EC2_KYLIN4_PARAMS`), `Spark workers `(`EC2_SPARK_WORKER_PARAMS`), `Kylin4 scale nodes`(`EC2_KYLIN4_SCALE_PARAMS`) and `Spark scale workers`(`EC2_SPARK_SCALE_SLAVE_PARAMS`).
+4. Now`Ec2Mode` **only effect** the related params are `Ec2InstanceTypeFor*`,`Ec2VolumeSizeFor*` and `Ec2VolumnTypeFor`* in the params modules.
+5. If you don't change `ENABLE_LOCAL_CACHE_SOFT_AFFINITY` from `"false"` to `"true"` then cluster will created normally without `Local Cache + Soft Affinity` feature!
+
+
+
+#### Example
+
+As an example in `EC2_STATIC_SERVICES_PARAMS`:
+
+- change `Ec2Mode ` from `test`to `product`
+- change `Ec2InstanceTypeForStaticServices` from `m5.2xlarge` to `m5.4xlarge`.
+- change `Ec2VolumeSizeForStaticServicesNode` from `'20'` to `'50'.`
+- change `Ec2VolumnTypeForStaticServicesNode` from `gp2` to `standard`.
+- Then create the node of static service node will be a ``m5.4xlarge` and it attach a volume which size is `50` and type is `standard`.
+
+
+
diff --git a/readme/commands.md b/readme/commands.md
new file mode 100644
index 0000000..9aa0834
--- /dev/null
+++ b/readme/commands.md
@@ -0,0 +1,103 @@
+## Commands<a name="run"></a>
+
+Command:
+
+```shell
+python ./deploy.py --type [deploy|destroy|list|scale] --scale-type [up|down] --node-type [kylin|spark_worker] [--cluster {1..6}|all|default]
+```
+
+- deploy: create cluster(s).
+
+- destroy: destroy created cluster(s).
+
+- list: list alive nodes which are with stack name, instance id, private ip and public ip.
+
+- scale: Must be used with `--scale-type` and `--node-type`.
+
+ > Note:
+ >
+ > 1. Current support to scale up/down `kylin` or `spark_worker` for specific cluster.
+ > 2. Before scale up/down `kylin` or `spark_worker` nodes, Cluster services must be ready.
+ > 3. If you want to scale a `kylin` or `spark_worker` node to a specify cluster, please add the `--cluster ${cluster num}` to specify the expected node add to the cluster `${cluster num}`.
+
+### Command for deploy
+
+- Deploy default cluster
+
+```shell
+$ python ./deploy.py --type deploy [--cluster default]
+```
+
+- Deploy a cluster with specific cluster index.
+
+```shell
+$ python ./deploy.py --type deploy --cluster ${cluster num}
+```
+
+> Note: the `${cluster num}` must be in the range of `CLUSTER_INDEXES`.
+
+- Deploy all cluster which contain default cluster and all cluster which index in the range of `CLUSTER_INDEXES`.
+
+```sHe
+$ python ./deploy.py --type deploy --cluster all
+```
+
+### Command for destroy
+
+> Note:
+>
+> Destroy all cluster will not delete vpc, rds and monitor node. So if user don't want to hold the env, please set the `ALWAYS_DESTROY_ALL` to be `'true'`.
+
+- Destroy default cluster
+
+```shell
+$ python ./deploy.py --type destroy [--cluster default]
+```
+
+- Destroy a cluster with specific cluster index.
+
+```shell
+$ python ./deploy.py --type destroy --cluster ${cluster num}
+```
+
+> Note: the `${cluster num}` must be in the range of `CLUSTER_INDEXES`.
+
+- Destroy all cluster which contain default cluster and all cluster which index in the range of `CLUSTER_INDEXES`.
+
+```shell
+$ python ./deploy.py --type destroy --cluster all
+```
+
+### Command for list
+
+- List nodes which are with **stack name**, **instance id**, **private ip** and **public ip** in **available stacks** .
+
+```shell
+$ python ./deploy.py --type list
+```
+
+### Command for scale
+
+> Note:
+>
+> 1. Scale command must be used with `--scale-type` and `--node-type`.
+> 2. If scale command not specify a cluster num, then the scaled node(kylin or spark worker) will be add to `default`cluster.
+> 3. Scale command **not support** to **scale** node (kylin or spark worker) to **all clusters** at **one time**. It means that `python ./deploy.py --type scale --scale-type up[|down] --node-type kylin[|spark_worker] --cluster all` is invalid commad.
+> 4. Scale params which are `KYLIN_SCALE_UP_NODES`, `KYLIN_SCALE_DOWN_NODES`, `SPARK_WORKER_SCALE_UP_NODES` and `SPARK_WORKER_SCALE_DOWN_NODES` effect on all cluster. So if user want to scale node for a specify cluster, then modify the scale params before **every run time.**
+> 5. **(Important!!!)** Current cluster is created with default `3` spark workers and `1` kylin node. The `3` spark workers can not be scaled down. The `1` kylin node also can not be scaled down.
+> 6. **(Important!!!)** Cluster can only scale up or down the range of nodes which is in `KYLIN_SCALE_UP_NODES`, `KYLIN_SCALE_DOWN_NODES`, `SPARK_WORKER_SCALE_UP_NODES` and `SPARK_WORKER_SCALE_DOWN_NODES` . Not the default `3` spark workers and `1` kylin node in the cluster.
+> 7. **(Important!!!)** If user don't want to create a cluster with `3` default spark workers, then user can remove the useless node module in the `Ec2InstanceOfSlave0*` of `kylin-tpch/cloudformation_templates/ec2-cluster-spark-slave.yaml`. User need to know about the syntax of cloudformation as also.
+
+- Scale up/down kylin/spark workers in default cluster
+
+```shell
+python ./deploy.py --type scale --scale-type up[|down] --node-type kylin[|spark_worker] [--cluster default]
+```
+
+- Scale up/down kylin/spark workers in a specific cluster
+
+```shell
+python ./deploy.py --type scale --scale-type up[|down] --node-type kylin[|spark_worker] --cluster ${cluster num}
+```
+
+> Note: the `${cluster num}` must be in the range of `CLUSTER_INDEXES`.
\ No newline at end of file
diff --git a/readme/monitor.md b/readme/monitor.md
new file mode 100644
index 0000000..361f369
--- /dev/null
+++ b/readme/monitor.md
@@ -0,0 +1,59 @@
+## Monitor
+
+Current tool also support the feature of monitor for cluster.
+
+1. User can execute `python ./deploy.py --type list` to get the `public ip` of `Static Service` .
+2. User can access the `public ip` of `Static Service` and the port is `9090` to access `Prometheus` server.
+3. User can access the `public ip` of `Static Service` and the port is `3000` to access `Granfana` server.
+
+### Quick Start For Prometheus
+
+1. Input a `Metric`, user can get the available metric from the metric exploer.
+
+
+
+2. Execute a query to generate a dashboad.
+
+
+
+3. Add a new panel for a new query.
+
+
+
+More details about `PromQL` for metric exploer, please check [official website](https://prometheus.io/docs/prometheus/latest/querying/).
+
+#### Spark Metric In Prometheus
+
+> Note:
+>
+> 1. Current tool support to monitor spark metrics, more detail in [Spark Metrics](https://spark.apache.org/docs/3.1.1/monitoring.html#executor-metrics).
+> 2. Spark metrics is start with `metrics` in Prometheus server.
+>
+> 
+
+ ### Quick Start For Granfana
+
+1. Login into dashboard with default user and password which are all `admin` at the first time.
+2. Configure the connection to prometheus server.
+
+
+
+
+
+
+
+> Just config the url with syntax `http://${private ip of static service}:9090` . The `private ip of static service` can be from the `python ./deploy.py --type list` command.
+
+3. Add a new panel.
+
+
+
+4. Add a new panel or other.
+
+
+
+5. Edit & Apply the panel.
+
+
+
+More details about the usage of Granfana in [official website](https://grafana.com/docs/grafana/latest/).
\ No newline at end of file
diff --git a/readme/prerequisites.md b/readme/prerequisites.md
new file mode 100644
index 0000000..35f4c88
--- /dev/null
+++ b/readme/prerequisites.md
@@ -0,0 +1,216 @@
+## Prerequisites
+
+### Download source code & checkout to branch of `deploy-kylin-on-aws`
+
+commands:
+
+```shell
+git clone https://github.com/Kyligence/kylin-tpch.git && cd kylin-tpch && git checkout deploy-kylin-on-aws
+```
+
+### Initiliaze an AWS Account
+
+#### I. Create an `IAM` role<a name="IAM"></a>
+
+> Note:
+>
+> `IAM` role must have the access which contains `AmazonEC2RoleforSSM` , `AmazonSSMFullAccess` and `AmazonSSMManagedInstanceCore`.
+>
+> This `IAM` Role will be used to initialize every ec2 instances which are for creating an kylin4 cluster on aws. And it will configure in `Initilize Env of Local Mac` part.
+
+#### II. Create a `User`
+
+> Note:
+>
+> The `User` who is created in aws will be used to execute some operations on EC2 instance. So the `User` must has some authorities as below.
+
+| Services | Access level | Resources | Request condition |
+| ------------------- | ------------------------------------------------------ | ------------- | ----------------- |
+| **Cloudformation** | **Limited**: List, Read,Write | All Resources | None |
+| **EC2** | **Limited**: Read | All Resources | None |
+| **IAM** | **Limited**: List, Read, Write, Permissions management | All Resources | None |
+| **RDS** | **Limited**: List, Write, Tagging | All Resources | None |
+| **S3** | **Limited**: Write, Permissions management, Tagging | All Resources | None |
+| **SNS** | **Limited**: List | All Resources | None |
+| **STS** | **Limited**: Write | All Resources | None |
+| **Systems Manager** | **Limited**: Write | All Resources | None |
+
+#### III. Login the created `User` to create key pair and Access Key<a name="keypair"></a>
+
+> Note:
+>
+> To deploy EC2 instances for Kylin4 Cluster need key pair and access key.
+
+##### 1. Create a new `Key Pair` in the `EC2 -> Key pairs`
+
+
+
+##### 2. Genrate a new `Access Key` which in the `My Security Credentials`
+
+> Note:
+>
+> Please download the generated the csv file of `Access Key` immediately. Get the `Access Key ` and `Secret Key` to initilize local mac to access aws.
+
+
+
+
+
+
+
+
+
+### Initialize a S3 direcotry<a name="S3"></a>
+
+#### I. Create a directory on S3
+
+> Note:
+>
+> This directory will store tars, scripts and jars below. And it will also be the root path of working dir for kylin4.
+
+Example: make a directory named `kylin4-aws-test` . You can also create a directory named what you like.
+
+
+
+
+
+#### **(Optional)** II. Manually Download packages & Upload them to the S3 path which suffix is `*/tar`
+
+> Note:
+>
+> This step will automatically do by tools. So you can skip this step, or you want to check packages by yourself.
+
+
+
+> Create the directory named `tar` **in the path which was created by yourself**.
+>
+> As example, the full path would be `s3://.../kylin4-aws-test/tar`.
+
+1. Download Kylin4 package by [official website](https://kylin.apache.org/download/).
+2. Download Hadoop, [version 3.2.0](https://archive.apache.org/dist/hadoop/common/hadoop-3.2.0/hadoop-3.2.0.tar.gz).
+3. Download Spark with hadoop3.2, [version 3.1.1](https://archive.apache.org/dist/spark/spark-3.1.1/spark-3.1.1-bin-hadoop3.2.tgz).
+4. Download Hive, [version 2.3.9](https://archive.apache.org/dist/hive/hive-2.3.9/apache-hive-2.3.9-bin.tar.gz).
+5. Download Zookeeper, [version 3.4.9.](https://archive.apache.org/dist/zookeeper/zookeeper-3.4.9/zookeeper-3.4.9.tar.gz)
+6. Download JDK, [version 1.8_301](https://www.oracle.com/java/technologies/javase/javase8u211-later-archive-downloads.html).
+7. Download Node Exporter, [version 1.3.1.](https://github.com/prometheus/node_exporter/releases/download/v1.3.1/node_exporter-1.3.1.linux-amd64.tar.gz)
+8. Download Prometheus Server, [version 2.31.1](https://github.com/prometheus/prometheus/releases/download/v2.31.1/prometheus-2.31.1.linux-amd64.tar.gz).
+9. Download Kylin4 package with local cache + soft affinity feature by [public website.](https://s3.cn-north-1.amazonaws.com.cn/public.kyligence.io/kylin/tar/apache-kylin-4.0.0-bin-spark3-soft.tar.gz)
+
+
+
+> Note:
+> If you want to use Kylin4 with local cache + soft affinity feature, please download the `experimental` package above.
+
+
+
+
+
+#### (Optional) III. Upload `kylin-tpch/backup/jars/*` to the S3 Path which suffix is `*/jars`
+
+> Note:
+>
+> This step will automatically do by tools. So you can skip this step, or you want to check jars by yourself.
+
+
+
+> Create the directory named `jars` **in the path which was created by yourself**.
+>
+> As example, the full path would be `s3://.../kylin4-aws-test/jars`.
+
+Kylin4 needed extra jars
+
+- Basic jars
+ - commons-configuration-1.3.jar
+ - mysql-connector-java-5.1.40.jar
+- Local Cache + Soft Affinity feature needed jars
+ - alluxio-2.6.1-client.jar
+ - kylin-soft-affinity-cache-4.0.0-SNAPSHOT.jar
+
+
+
+#### (Optional) IV. Upload `kylin-tpch/backup/scripts/*` to the S3 Path which suffix is `*/scripts`
+
+> Note:
+>
+> This step will automatically do by tools. So you can skip this step, or you want to check scripts by yourself.
+
+
+
+> Create the directory named `scripts` **in the path which was created by yourself**.
+>
+> As example, the full path would be `s3://.../kylin4-aws-test/scripts`.
+
+Scripts:
+
+- prepare-ec2-env-for-kylin4.sh
+- prepare-ec2-env-for-spark-master.sh
+- prepare-ec2-env-for-spark-slave.sh
+- prepare-ec2-env-for-static-services.sh
+- prepare-ec2-env-for-zk.sh
+
+
+
+### Initilize Env Of Local Mac
+
+#### I. Initilize an aws account on local mac to access AWS<a name="localaws"></a>
+
+> Use `Access Key` and `Secret Key ` above to Initilize a aws account on local mac.
+
+```shell
+$ aws configure
+AWS Access Key ID : *************
+AWS Secret Access Key : *************
+Default region name : cn-northwest-1
+Default output format : json
+```
+
+> Note:
+>
+> 1. If this command got the response `-bash: aws: command not found`, please check in [Getting started with the AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-getting-started.html).
+> 2. Region name can be in [Available Regions](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using-regions-availability-zones.html#concepts-available-regions).
+> 3. Default output format is `json`.
+
+#### II. Init a Python virtual env
+
+> Note:
+>
+> Make sure that your mac already has a Python which version is 3.6.6 or later.
+
+commands:
+
+```shell
+$ ./bin/init.sh
+```
+
+> Note: Follow the information after `./bin/init.sh` to activate the python virtual env.
+
+#### III. Configure the `kylin-tpch/kylin_configs.yaml`
+
+**Required parameters**:
+
+- `AWS_REGION`: Current region for EC2 instances.
+- `IAMRole`: IAM role which has the access to aws authority. This parameter will be set to created **name** of IAM role.
+- `S3_URI`: the prefix path of storing `jars/scripts/tar`. As example, this parameter will be set to `s3://.../kylin4-aws-test`.
+- `KeyName`: Security key name is a set of security credentials that you use to prove your identity when connecting to an instance. This parameter will be set to created **name** of `key pair` .
+- `CIDR_IP`: An inbound rule permits instances to receive traffic from the specified IPv4 or IPv6 CIDR address range, or from the instances associated with the specified security group.
+- `DB_IDENTIFIER`: this param should be only one in the `RDS -> Databases` . And it will be the name of created RDS database.
+- `DB_PORT`: this param will be the port of created RDS database, default is `3306`.
+- `DB_USER`: this param will be a login ID for the master user of your DB instance, default is `root`.
+- `DB_PASSWORD`: this param will be the password of `DB_USER` to access DB instance. default is `123456test`, it's strongly suggest you to change it.
+
+#### IV. Configure the `kylin.properties` in `backup/properties` directories.<a name="cluster"></a>
+
+1. The `kylin.properties` is for starting kylin instance in the cluster.
+2. Default cluster will check the `kylin.properties` in the `kylin-tpch/backup/properties/default`, and other specific cluster will check the related num directory such as `1`, `2` and `3`.
+3. User need to create new dir for the cluster num in `kylin-tpch/backup/properties`, and name it to the `${cluster num}`, such as `1`, `2` ,`3` and so on. The range of cluster num must be in `CLUSTER_INDEXES` which is configured in the `kylin-tpch/kylin_configs.yml`.
+4. Follow the `2.` step, copy the `kylin.properties.template` which is in `kylin-tpch/backup/properties/templates` to the related `${cluster num} ` directories， and rename the template to `kylin.properties`.
+5. The range of cluster nums must match the the config `CLUSTER_INDEXES`, such as `CLUSTER_INDEXES: (1, 3)` then the directories must be `1`, `2`,`3` in the `kylin-tpch/backup/properties`.
+
+
+
+6. Cusomize the config which you want to change except the config which contains `{{ }}` mark.
+
+7. If the related `kylin.properties` was filled with cluster information, a file named `.rendered` will create in the directory.
+
+
+
+7. **(Important !!!)** If you want to re-fill the `kylin.properties` for a `kylin` node in specify cluster, you need to remove the `.rendered` file and re-copy the `kylin.propertie.template` . Redo steps from `3` to `6`.
\ No newline at end of file