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In this guide, you’ll learn how to quickly get a tiny TiKV cluster running locally, then you’ll use our Rust client to get, set, and scan data in TiKV. Then you’ll learn how to quickly start and stop a TiKV cluster to accompany your development environment.
This guide won’t worry about details such as security, resiliency, or production-readiness. (Those topics are covered more in detail in the deploy guides.) Nor will this guide cover how to develop TiKV itself (See CONTRIBUTING.md
.) Instead, this guide focuses on an easy development experience and low resource consumption.
Overview
In order to get a functioning TiKV service you will need to start a TiKV service and a PD service. PD works alongside TiKV to act as a coordinator and timestamp oracle.
Communication between TiKV, PD, and any services which use TiKV is done via gRPC. We provide clients for several languages, and this guide will briefly show you how to use the Rust client.
Using Docker, you’ll create pair of persistent services tikv
and pd
and learn to manage them easily. Then you’ll write a simple Rust client application and run it from your local host. Finally, you’ll learn how to quicky teardown and bring up the services, and review some basic limitations of this configuration.
In a production deployment there would be at least three TiKV services and three PD services spread among 6 machines. Most deployments also include kernel tuning, sysctl tuning, robust systemd services, firewalls, monitoring with prometheus, grafana dashboards, log collection, and more. Even still, to be sure of your resilience and security, consider consulting our maintainers.
If you are interested in deploying for production we suggest investigating the deploy guides.
While it’s possible to use TiKV through a query layer, like TiDB or Titan, you should refer to the user guides of those projects in order to set up test clusters. This guide only deals with TiKV, PD, and TiKV clients.
Prerequisites
This guide assumes you have the following knowledge and tools at your disposal:
- Working knowledge about Docker (e.g. how to run or stop a container),
- A modern Docker daemon which can support
docker stack
and the Compose File 3.7 version, running on a machine with:- A modern (circa >2012) x86 64-bit processor (supporting SSE4.2)
- At least 10 GB of free storage space
- A modest amount of memory (4+ GB) available
- A
ulimit.nofile
value higher than 82920 for the docker service
While this guide was written with Linux in mind, you can use any operating system as long as the Docker service is able to run Linux containers. You may need to make small adaptations to commands to suite your operating system, let us know if you get stuck so we can fix it!
Starting the stack
The maintainers from PingCAP publish battle-tested release images of both pd
and tikv
on Docker Hub. These are used in their TiDB Cloud kubernetes clusters as well as opt-in via their tidb-ansible
project.
For a TiKV client to interact with a TiKV cluster, it needs to be able to reach each PD and TiKV node. Since TiKV balances and replicates data across all nodes, and any node may be in charge of any particular Region of data, your client needs to be able to reach every node involved. (Replicas of your clients do not need to be able to reach each other.)
In the interest of making sure this guide can work for all platforms, it uses docker stack
to deploy an ultra-minimal cluster that you can quickly tear down and bring back up again. This cluster won’t feature security, persistence, or have static hostnames.
Unless you’ve tried using docker stack
before, you may need to run docker swarm init
. If you’re unsure, it’s best just to run it and ignore the error if you see one.
To begin, create a stack.yml
:
version: "3.7"
x-defaults: &defaults
init: true
volumes:
- ./entrypoints:/entrypoints
environment:
SLOT: "{{.Task.Slot}}"
NAME: "{{.Task.Name}}"
entrypoint: /bin/sh
deploy:
replicas: 1
restart_policy:
condition: on-failure
delay: 5s
services:
pd:
<<: *defaults
image: pingcap/pd
hostname: "{{.Task.Name}}.tikv"
init: true
networks:
tikv:
aliases:
- pd.tikv
ports:
- "2379:2379"
- "2380:2380"
command: /entrypoints/pd.sh
tikv:
<<: *defaults
image: pingcap/tikv
hostname: "{{.Task.Name}}.tikv"
networks:
tikv:
aliases:
- tikv.tikv
ports:
- "20160:20160"
command: /entrypoints/tikv.sh
networks:
tikv:
name: "tikv"
driver: "overlay"
attachable: true
Then create entrypoints/pd.sh
with the following:
#! /bin/sh
set -e
if [ $SLOT = 1 ]; then
exec ./pd-server \
--name $NAME \
--client-urls http://0.0.0.0:2379 \
--peer-urls http://0.0.0.0:2380 \
--advertise-client-urls http://`cat /etc/hostname`:2379 \
--advertise-peer-urls http://`cat /etc/hostname`:2380
else
exec ./pd-server \
--name $NAME \
--client-urls http://0.0.0.0:2379 \
--peer-urls http://0.0.0.0:2380 \
--advertise-client-urls http://`cat /etc/hostname`:2379 \
--advertise-peer-urls http://`cat /etc/hostname`:2380 \
--join http://pd.tikv:2379
fi
Last, an entrypoints/tikv.sh
with the following:
#!/bin/sh
set -e
exec ./tikv-server \
--addr 0.0.0.0:20160 \
--status-addr 0.0.0.0:20180 \
--advertise-addr `cat /etc/hostname`:20160 \
--pd-endpoints pd.tikv:2379
Next, you can deploy the stack to Docker:
docker stack deploy --compose-file stack.yml tikv
The output should look like this:
Creating network tikv
Creating service tikv_pd
Creating service tikv_tikv
Managing services
Check the state of running services:
$ docker service ls
ID NAME MODE REPLICAS IMAGE PORTS
6ia0pefrd811 tikv_pd replicated 1/1 pingcap/pd:latest *:2379-2380->2379-2380/tcp
26u77puqmw4d tikv_tikv replicated 1/1 pingcap/tikv:latest *:20160->20160/tcp
Turn off the services:
This will delete data!
$ docker service scale tikv_pd=0 tikv_tikv=0
tikv_pd scaled to 0
tikv_tikv scaled to 0
overall progress: 0 out of 0 tasks
verify: Service converged
overall progress: 0 out of 0 tasks
verify: Service converged
Turn services back on:
This creates brand new containers!
$ docker service scale tikv_pd=1 tikv_tikv=1
tikv_pd scaled to 1
tikv_tikv scaled to 1
overall progress: 1 out of 1 tasks
1/1: running [==================================================>]
verify: Service converged
overall progress: 1 out of 1 tasks
1/1: running [==================================================>]
verify: Service converged
Inquire into the metrics:
Normally, these would be pulled by Prometheus, but it is human readable and functions as a basic liveliness test.
$ docker run --rm -ti --network tikv alpine sh -c "apk add curl; curl http://pd.tikv:2379/metrics"
# A lot of output...
$ docker run --rm -ti --network tikv alpine sh -c "apk add curl; curl http://tikv.tikv:20180/metrics"
# A lot of output...
Inquire into the resource consuption of the containers:
$ docker stats
CONTAINER ID NAME CPU % MEM USAGE / LIMIT MEM % NET I/O BLOCK I/O PIDS
c4360f65ded3 tikv_tikv.1.a8sfm113yotkkv5klqtz5cvrn 0.36% 689MiB / 30.29GiB 2.22% 8.44kB / 7.42kB 0B / 0B 66
3f18cc8f415b tikv_pd.1.r58jn3kolaxgqdbyb8w2mcx8r 1.56% 22.21MiB / 30.29GiB 0.07% 8.11kB / 7.75kB 0B / 0B 21
Remove the stack entirely:
This will delete data!
$ docker stack rm tikv
Creating a project
Below, you’ll use the Rust client, but you are welcome to use any TiKV client.
Because you will eventually need to deploy the binary into the same network as the PD and TiKV nodes,
You can create a new example project then change into the directory:
cargo new tikv-example
cd tikv-example
You will need to use a nightly
toolchain that supports the async
/await
feature in order to use the TiKV client in the guide below. This is expected to become stable in Rust 1.38.0.
For now, please echo 'nightly-2019-08-25' > ./rust-toolchain
in the project directory.
Next, you’ll need to add the TiKV client as a dependency in the Cargo.toml
file:
[dependencies]
tikv-client = { git = "https://github.com/tikv/client-rust.git" }
tokio = "0.2.0-alpha.4"
Then you can edit the src/main.rs
file with the following:
use tikv_client::{Config, RawClient, Error};
#[tokio::main]
async fn main() -> Result<(), Error> {
let config = Config::new(vec!["http://pd.tikv:2379"]);
let client = RawClient::new(config)?;
let key = "TiKV".as_bytes().to_owned();
let value = "Works!".as_bytes().to_owned();
client.put(key.clone(), value.clone()).await?;
println!(
"Put: {} => {}",
std::str::from_utf8(&key).unwrap(),
std::str::from_utf8(&value).unwrap()
);
let returned: Vec<u8> = client.get(key.clone()).await?
.expect("Value should be present.").into();
assert_eq!(returned, value);
println!(
"Get: {} => {}",
std::str::from_utf8(&key).unwrap(),
std::str::from_utf8(&value).unwrap()
);
Ok(())
}
TiKV works with binary data to enable your project to store arbitrary data such as binaries or non-UTF-8 encoded data if necessary. While the Rust client accepts String
values as well as Vec<u8>
, it will only output Vec<u8>
.
Now, because the client needs to be part of the same network (tikv
) as the PD and TiKV nodes, you must to build this binary into a Docker container. Create a Dockerfile
in the root of your project directory with the following content:
FROM ubuntu:latest
# Systemwide setup
RUN apt update
RUN apt install --yes build-essential protobuf-compiler curl cmake golang
# Create the non-root user.
RUN useradd builder -m -b /
USER builder
RUN mkdir -p ~/build/src
# Install Rust
COPY rust-toolchain /builder/build/
RUN curl https://sh.rustup.rs -sSf | sh -s -- --default-toolchain `cat /builder/build/rust-toolchain` -y
ENV PATH="/builder/.cargo/bin:${PATH}"
# Fetch, then prebuild all deps
COPY Cargo.toml rust-toolchain /builder/build/
RUN echo "fn main() {}" > /builder/build/src/main.rs
WORKDIR /builder/build
RUN cargo fetch
RUN cargo build --release
COPY src /builder/build/src
RUN rm -rf ./target/release/.fingerprint/tikv-example*
# Actually build the binary
RUN cargo build --release
ENTRYPOINT /builder/build/target/release/tikv-example
Next, build the image:
docker build -t tikv-example .
Then start the produced image:
docker run -ti --rm --network tikv tikv-example
At this point, you’re ready to start developing against TiKV!
Want to keep reading? You can explore Deep Dive TiKV to learn more about how TiKV works at a technical level.
Want to improve your Rust abilities? Some of our contributors work on creating Practical Network Applications, an open self guided study to master Rust while making fun distributed systems.