95 lines
4.8 KiB
Markdown
95 lines
4.8 KiB
Markdown
# Lotus Seal Worker
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The **Lotus Seal Worker** is an extra process that can offload heavy processing tasks from your **Lotus Storage Miner**. It can be run on the same machine as your `lotus-storage-miner`, or on another machine communicating over a fast network.
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## Note: Using the Lotus Seal Worker from China
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If you are trying to use `lotus-seal-worker` from China. You should set this **environment variable** on your machine:
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```sh
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IPFS_GATEWAY="https://proof-parameters.s3.cn-south-1.jdcloud-oss.com/ipfs/"
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```
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## Get Started
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Make sure that the `lotus-seal-worker` is installed by running:
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```sh
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make lotus-seal-worker
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```
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## Running Alongside Storage Miner
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You may wish to run the **Lotus Seal Worker** on the same computer as the **Lotus Storage Miner**. This allows you to easily set the process priority of the sealing tasks to be lower than the priority of your more important storage miner process.
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To do this, simply run `lotus-seal-worker run`, and the seal worker will automatically pick up the correct authentication tokens from the `LOTUS_STORAGE_PATH` miner repository.
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To check that the **Lotus Seal Worker** is properly connected to your storage miner, run `lotus-storage-miner info` and check that the remote worker count has increased.
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```sh
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why@computer ~/lotus> lotus-storage-miner workers list
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Worker 0, host computer
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CPU: [ ] 0 core(s) in use
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RAM: [|||||||||||||||||| ] 28% 18.1 GiB/62.7 GiB
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VMEM: [|||||||||||||||||| ] 28% 18.1 GiB/62.7 GiB
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GPU: GeForce RTX 2080, not used
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Worker 1, host computer
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CPU: [ ] 0 core(s) in use
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RAM: [|||||||||||||||||| ] 28% 18.1 GiB/62.7 GiB
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VMEM: [|||||||||||||||||| ] 28% 18.1 GiB/62.7 GiB
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GPU: GeForce RTX 2080, not used
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```
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## Running Over the Network
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Warning: This setup is a little more complex than running it locally.
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To use an entirely separate computer for sealing tasks, you will want to run the `lotus-seal-worker` on a separate machine, connected to your **Lotus Storage Miner** via the local area network.
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First, you will need to ensure your `lotus-storage-miner`'s API is accessible over the network.
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To do this, open up `~/.lotusstorage/config.toml` (Or if you manually set `LOTUS_STORAGE_PATH`, look under that directory) and look for the API field.
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Default config:
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```toml
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[API]
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ListenAddress = "/ip4/127.0.0.1/tcp/2345/http"
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RemoteListenAddress = "127.0.0.1:2345"
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```
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To make your node accessible over the local area network, you will need to determine your machines IP on the LAN, and change the `127.0.0.1` in the file to that address.
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A more permissive and less secure option is to change it to `0.0.0.0`. This will allow anyone who can connect to your computer on that port to access the [API](https://docs.lotu.sh/en+api). They will still need an auth token.
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`RemoteListenAddress` must be set to an address which other nodes on your network will be able to reach
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Next, you will need to [create an authentication token](https://docs.lotu.sh/en+api-scripting-support#generate-a-jwt-46). All Lotus APIs require authentication tokens to ensure your processes are as secure against attackers attempting to make unauthenticated requests to them.
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### Connect the Lotus Seal Worker
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On the machine that will run `lotus-seal-worker`, set the `STORAGE_API_INFO` environment variable to `TOKEN:STORAGE_NODE_MULTIADDR`. Where `TOKEN` is the token we created above, and `STORAGE_NODE_MULTIADDR` is the `multiaddr` of the **Lotus Storage Miner** API that was set in `config.toml`.
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Once this is set, run:
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```sh
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lotus-seal-worker run
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```
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To check that the **Lotus Seal Worker** is connected to your **Lotus Storage Miner**, run `lotus-storage-miner workers list` and check that the remote worker count has increased.
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```sh
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why@computer ~/lotus> lotus-storage-miner workers list
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Worker 0, host computer
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CPU: [ ] 0 core(s) in use
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RAM: [|||||||||||||||||| ] 28% 18.1 GiB/62.7 GiB
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VMEM: [|||||||||||||||||| ] 28% 18.1 GiB/62.7 GiB
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GPU: GeForce RTX 2080, not used
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Worker 1, host othercomputer
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CPU: [ ] 0 core(s) in use
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RAM: [|||||||||||||| ] 23% 14 GiB/62.7 GiB
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VMEM: [|||||||||||||| ] 23% 14 GiB/62.7 GiB
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GPU: GeForce RTX 2080, not used
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```
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