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Add PD scheduling best practices and glossary #104

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53 changes: 53 additions & 0 deletions content/docs/3.0/concepts/glossary.md
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---
title: Glossary
summary: Glossaries about TiKV.
menu:
docs:
parent: Concepts
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Seems reference is more appropriate

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Actually I think these are some good concept material (reference, too) which users may want to notice easily when they are learning about TiKV.

---

## L

### leader/follower/learner
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Maybe these can be split up

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You mean they can be introduced separately?

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I think they can be separate entries in this glossary?


Leader/Follower/Learner each corresponds to a role in a Raft group of [peers](#region-peer-raft-group). The leader services all client requests and replicates data to the followers. If the group leader fails, one of the followers will be elected as the new leader. Learners are non-voting followers that only serves in the process of replica addition.

## O

### operator

An operator is a collection of actions that applies to a region for scheduling purposes. Operators perform scheduling tasks such as "migrate the leader of Region 2 to Store 5" and "migrate replicas of Region 2 to Store 1, 4, 5".

An operator can be computed and generated by a [scheduler](#scheduler), or created by an external API.

### operator step

An operator step is a step in the execution of an operator. An operator normally contains multiple Operator steps.

## P

### pending/down

"Pending" and "down" are two special states of a peer. Pending indicates that the Raft log of followers or learners is vastly different from that of the leader. Followers in pending cannot be elected as leader. "Down" refers to a state that a peer ceases to respond to the leader for a long time, which usually means the corresponding node is down or isolated from the network.

## R

### region/peer/Raft group

Region is the minimal piece of data storage in TiKV, each representing a range of data (96 MiB by default). Each region has three replicas by default. A replica of a region is called a peer. Multiple peers of the same region replicate data via the Raft consensus algorithm, so peers are also members of a Raft instance. TiKV uses Multi-Raft to manage data. That is, for each region, there is a corresponding, isolated Raft group.

### region split

Regions are generated as data writes increase. The process of splitting is called region split.

The mechanism of region split is to use one initial region to cover the entire key space, and generate new regions through splitting existing ones every time the size of the region or the number of keys has reached a threshold.

## S

### scheduler

Schedulers are components in PD that generate scheduling tasks. Each scheduler in PD runs independently and serves different purposes.

### store

A store refers to the storage node in the TiKV cluster (an instance of `tikv-server`). Each store has a corresponding TiKV instance.
14 changes: 14 additions & 0 deletions content/docs/3.0/tasks/best-practices/introduction.md
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---
title: Best Practices
description: Learn the best practices of TiKV.
menu:
docs:
parent: Tasks
weight: 6
---

The TiKV best practices are detailed through some typical scenarios in the production environment so that you can quickly get started, identify and address problems.

You can further explore TiKV through the following best practices:

* [PD scheduling](../pd-scheduling)
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