mirror of
https://github.com/ClickHouse/ClickHouse.git
synced 2024-11-24 08:32:02 +00:00
add slugs to all docs
This commit is contained in:
DanRoscigno
parent
52fc319c83
commit
7f92006428
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/changelog/
|
||||
machine_translated: true
|
||||
machine_translated_rev: b111334d6614a02564cf32f379679e9ff970d9b1
|
||||
sidebar_label: "\u53D8\u66F4\u65E5\u5FD7"
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/commercial/cloud
|
||||
sidebar_position: 1
|
||||
sidebar_label: 云
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/commercial/
|
||||
sidebar_label: 商业支持
|
||||
sidebar_position: 70
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/commercial/support
|
||||
sidebar_position: 3
|
||||
sidebar_label: 支持
|
||||
---
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/development/adding_test_queries
|
||||
---
|
||||
# 如何将测试查询添加到 ClickHouse CI
|
||||
|
||||
ClickHouse有数百个（甚至数千个）功能。 每个提交都由包含数千个测试用例的一组复杂测试进行检查。
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/development/architecture
|
||||
---
|
||||
# ClickHouse 架构概述 {#clickhouse-jia-gou-gai-shu}
|
||||
|
||||
ClickHouse 是一个真正的列式数据库管理系统（DBMS)。在 ClickHouse 中，数据始终是按列存储的，包括矢量（向量或列块）执行的过程。只要有可能，操作都是基于矢量进行分派的，而不是单个的值，这被称为«矢量化查询执行»，它有利于降低实际的数据处理开销。
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/development/browse-code
|
||||
sidebar_position: 63
|
||||
sidebar_label: "\u6D4F\u89C8\u6E90\u4EE3\u7801"
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/development/build-cross-arm
|
||||
machine_translated: true
|
||||
machine_translated_rev: 72537a2d527c63c07aa5d2361a8829f3895cf2bd
|
||||
sidebar_position: 67
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/development/build-cross-osx
|
||||
---
|
||||
# 如何在Linux中编译Mac OS X ClickHouse {#ru-he-zai-linuxzhong-bian-yi-mac-os-x-clickhouse}
|
||||
|
||||
Linux机器也可以编译运行在OS X系统的`clickhouse`二进制包，这可以用于在Linux上跑持续集成测试。如果要在Mac OS X上直接构建ClickHouse，请参考另外一篇指南： https://clickhouse.com/docs/zh/development/build_osx/
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/development/build-osx
|
||||
---
|
||||
# 在 Mac OS X 中编译 ClickHouse {#zai-mac-os-x-zhong-bian-yi-clickhouse}
|
||||
|
||||
ClickHouse 支持在 Mac OS X 10.12 版本中编译。若您在用更早的操作系统版本，可以尝试在指令中使用 `Gentoo Prefix` 和 `clang sl`.
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/development/build
|
||||
---
|
||||
# 如何构建 ClickHouse 发布包 {#ru-he-gou-jian-clickhouse-fa-bu-bao}
|
||||
|
||||
## 安装 Git 和 Pbuilder {#an-zhuang-git-he-pbuilder}
|
||||
|
||||
@ -1,4 +1,8 @@
|
||||
---
|
||||
slug: /zh/development/continuous-integration
|
||||
---
|
||||
# 持续集成检查 {#continuous-integration-checks}
|
||||
|
||||
当你提交一个pull请求时, ClickHouse[持续集成(CI)系统](https://clickhouse.com/docs/en/development/tests/#test-automation)会对您的代码运行一些自动检查.
|
||||
|
||||
这在存储库维护者(来自ClickHouse团队的人)筛选了您的代码并将可测试标签添加到您的pull请求之后发生.
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/development/contrib
|
||||
---
|
||||
# 使用的三方库 {#shi-yong-de-san-fang-ku}
|
||||
|
||||
| 图书馆 | 许可 |
|
||||
|
||||
@ -1,4 +1,7 @@
|
||||
ClickHose支持Linux,FreeBSD 及 Mac OS X 系统。
|
||||
---
|
||||
slug: /zh/development/developer-instruction
|
||||
---
|
||||
# ClickHose支持Linux,FreeBSD 及 Mac OS X 系统。
|
||||
|
||||
# Windows使用指引 {#windowsshi-yong-zhi-yin}
|
||||
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/development/
|
||||
---
|
||||
# ClickHouse 开发 {#clickhouse-kai-fa}
|
||||
|
||||
[来源文章](https://clickhouse.com/docs/en/development/) <!--hide-->
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/development/style
|
||||
---
|
||||
# 如何编写 C++ 代码 {#ru-he-bian-xie-c-dai-ma}
|
||||
|
||||
## 一般建议 {#yi-ban-jian-yi}
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/development/tests
|
||||
---
|
||||
# ClickHouse 测试 {#clickhouse-testing}
|
||||
|
||||
## 功能测试 {#functional-tests}
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/database-engines/atomic
|
||||
sidebar_position: 32
|
||||
sidebar_label: Atomic
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/database-engines/
|
||||
sidebar_label: 数据库引擎
|
||||
sidebar_position: 27
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/database-engines/lazy
|
||||
sidebar_position: 31
|
||||
sidebar_label: Lazy
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/database-engines/materialize-mysql
|
||||
sidebar_position: 29
|
||||
sidebar_label: "[experimental] MaterializedMySQL"
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/database-engines/materialized-mysql
|
||||
sidebar_position: 29
|
||||
sidebar_label: MaterializedMySQL
|
||||
---
|
||||
@ -152,8 +153,8 @@ ClickHouse只有一个物理排序，由 `order by` 条件决定。要创建一
|
||||
|
||||
* 修改列类型。必须与原始类型兼容，否则复制将失败。例如，可以将`UInt32`列修改为`UInt64`，不能将 `String` 列修改为 `Array(String)`。
|
||||
* 修改 [column TTL](../table-engines/mergetree-family/mergetree/#mergetree-column-ttl).
|
||||
* 修改 [column compression codec](../../sql-reference/statements/create/table/#codecs).
|
||||
* 增加 [ALIAS columns](../../sql-reference/statements/create/table/#alias).
|
||||
* 修改 [column compression codec](../../sql-reference/statements/create/table.md/#codecs).
|
||||
* 增加 [ALIAS columns](../../sql-reference/statements/create/table.md/#alias).
|
||||
* 增加 [skipping indexes](../table-engines/mergetree-family/mergetree/#table_engine-mergetree-data_skipping-indexes)
|
||||
* 增加 [projections](../table-engines/mergetree-family/mergetree/#projections).
|
||||
请注意，当使用 `SELECT ... FINAL ` (MaterializedMySQL默认是这样做的) 时，预测优化是被禁用的，所以这里是受限的， `INDEX ... TYPE hypothesis `[在v21.12的博客文章中描述]](https://clickhouse.com/blog/en/2021/clickhouse-v21.12-released/)可能在这种情况下更有用。
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/database-engines/materialized-postgresql
|
||||
sidebar_position: 30
|
||||
sidebar_label: MaterializedPostgreSQL
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/database-engines/mysql
|
||||
sidebar_position: 30
|
||||
sidebar_label: MySQL
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/database-engines/postgresql
|
||||
sidebar_position: 35
|
||||
sidebar_label: PostgreSQL
|
||||
---
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/database-engines/replicated
|
||||
---
|
||||
# [experimental] Replicated {#replicated}
|
||||
|
||||
该引擎基于[Atomic](../../engines/database-engines/atomic.md)引擎。它支持通过将DDL日志写入ZooKeeper并在给定数据库的所有副本上执行的元数据复制。
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/database-engines/sqlite
|
||||
sidebar_position: 32
|
||||
sidebar_label: SQLite
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/
|
||||
toc_folder_title: "\u5f15\u64ce"
|
||||
toc_priority: 25
|
||||
---
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/
|
||||
---
|
||||
# 表引擎 {#biao-yin-qing}
|
||||
|
||||
表引擎（即表的类型）决定了：
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/integrations/embedded-rocksdb
|
||||
sidebar_position: 9
|
||||
sidebar_label: EmbeddedRocksDB
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/integrations/hdfs
|
||||
sidebar_position: 36
|
||||
sidebar_label: HDFS
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/integrations/hive
|
||||
sidebar_position: 4
|
||||
sidebar_label: Hive
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/integrations/
|
||||
sidebar_label: 集成的表引擎
|
||||
sidebar_position: 30
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/integrations/jdbc
|
||||
sidebar_position: 34
|
||||
sidebar_label: JDBC表引擎
|
||||
---
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/integrations/kafka
|
||||
---
|
||||
# Kafka {#kafka}
|
||||
|
||||
此引擎与 [Apache Kafka](http://kafka.apache.org/) 结合使用。
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/integrations/mongodb
|
||||
sidebar_position: 5
|
||||
sidebar_label: MongoDB
|
||||
---
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/integrations/mysql
|
||||
---
|
||||
# MySQL {#mysql}
|
||||
|
||||
MySQL 引擎可以对存储在远程 MySQL 服务器上的数据执行 `SELECT` 查询。
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/integrations/odbc
|
||||
sidebar_position: 35
|
||||
sidebar_label: ODBC
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/integrations/postgresql
|
||||
sidebar_position: 11
|
||||
sidebar_label: PostgreSQL
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/integrations/rabbitmq
|
||||
sidebar_position: 10
|
||||
sidebar_label: RabbitMQ
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/integrations/s3
|
||||
sidebar_position: 7
|
||||
sidebar_label: S3
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/integrations/sqlite
|
||||
sidebar_position: 7
|
||||
sidebar_label: SQLite
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/log-family/
|
||||
sidebar_label: 日志引擎系列
|
||||
sidebar_position: 29
|
||||
---
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/log-family/log
|
||||
---
|
||||
# Log {#log}
|
||||
|
||||
`Log` 与 `TinyLog` 的不同之处在于，«标记» 的小文件与列文件存在一起。这些标记写在每个数据块上，并且包含偏移量，这些偏移量指示从哪里开始读取文件以便跳过指定的行数。这使得可以在多个线程中读取表数据。对于并发数据访问，可以同时执行读取操作，而写入操作则阻塞读取和其它写入。`Log`引擎不支持索引。同样，如果写入表失败，则该表将被破坏，并且从该表读取将返回错误。`Log`引擎适用于临时数据，write-once 表以及测试或演示目的。
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/log-family/stripelog
|
||||
---
|
||||
# StripeLog {#stripelog}
|
||||
|
||||
该引擎属于日志引擎系列。请在[日志引擎系列](index.md)文章中查看引擎的共同属性和差异。
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/log-family/tinylog
|
||||
---
|
||||
# TinyLog {#tinylog}
|
||||
|
||||
最简单的表引擎，用于将数据存储在磁盘上。每列都存储在单独的压缩文件中。写入时，数据将附加到文件末尾。
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/mergetree-family/aggregatingmergetree
|
||||
---
|
||||
# AggregatingMergeTree {#aggregatingmergetree}
|
||||
|
||||
该引擎继承自 [MergeTree](mergetree.md)，并改变了数据片段的合并逻辑。 ClickHouse 会将一个数据片段内所有具有相同主键（准确的说是 [排序键](../../../engines/table-engines/mergetree-family/mergetree.md)）的行替换成一行，这一行会存储一系列聚合函数的状态。
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/mergetree-family/collapsingmergetree
|
||||
---
|
||||
# CollapsingMergeTree {#table_engine-collapsingmergetree}
|
||||
|
||||
该引擎继承于 [MergeTree](mergetree.md)，并在数据块合并算法中添加了折叠行的逻辑。
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/mergetree-family/custom-partitioning-key
|
||||
---
|
||||
# 自定义分区键 {#zi-ding-yi-fen-qu-jian}
|
||||
|
||||
[MergeTree](mergetree.md) 系列的表（包括 [可复制表](replication.md) ）可以使用分区。基于 MergeTree 表的 [物化视图](../special/materializedview.md#materializedview) 也支持分区。
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/mergetree-family/graphitemergetree
|
||||
sidebar_position: 38
|
||||
sidebar_label: GraphiteMergeTree
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/mergetree-family/
|
||||
sidebar_label: "合并树家族"
|
||||
sidebar_position: 28
|
||||
---
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/mergetree-family/mergetree
|
||||
---
|
||||
# MergeTree {#table_engines-mergetree}
|
||||
|
||||
Clickhouse 中最强大的表引擎当属 `MergeTree` （合并树）引擎及该系列（`*MergeTree`）中的其他引擎。
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/mergetree-family/replacingmergetree
|
||||
---
|
||||
# ReplacingMergeTree {#replacingmergetree}
|
||||
|
||||
该引擎和 [MergeTree](mergetree.md) 的不同之处在于它会删除排序键值相同的重复项。
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/mergetree-family/replication
|
||||
---
|
||||
# 数据副本 {#table_engines-replication}
|
||||
|
||||
只有 MergeTree 系列里的表可支持副本：
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/mergetree-family/summingmergetree
|
||||
---
|
||||
# SummingMergeTree {#summingmergetree}
|
||||
|
||||
该引擎继承自 [MergeTree](mergetree.md)。区别在于，当合并 `SummingMergeTree` 表的数据片段时，ClickHouse 会把所有具有相同主键的行合并为一行，该行包含了被合并的行中具有数值数据类型的列的汇总值。如果主键的组合方式使得单个键值对应于大量的行，则可以显著的减少存储空间并加快数据查询的速度。
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/mergetree-family/versionedcollapsingmergetree
|
||||
sidebar_position: 37
|
||||
sidebar_label: "版本折叠MergeTree"
|
||||
---
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/special/buffer
|
||||
---
|
||||
# 缓冲区 {#buffer}
|
||||
|
||||
缓冲数据写入 RAM 中，周期性地将数据刷新到另一个表。在读取操作时，同时从缓冲区和另一个表读取数据。
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/special/dictionary
|
||||
---
|
||||
# 字典 {#dictionary}
|
||||
|
||||
`Dictionary` 引擎将字典数据展示为一个ClickHouse的表。
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/special/distributed
|
||||
sidebar_position: 33
|
||||
sidebar_label: 分布式引擎
|
||||
---
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/special/external-data
|
||||
---
|
||||
# 用于查询处理的外部数据 {#external-data-for-query-processing}
|
||||
|
||||
ClickHouse 允许向服务器发送处理查询所需的数据以及 SELECT 查询。这些数据放在一个临时表中（请参阅 «临时表» 一节），可以在查询中使用（例如，在 IN 操作符中）。
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/special/file
|
||||
---
|
||||
# 文件(输入格式) {#table_engines-file}
|
||||
|
||||
数据源是以 Clickhouse 支持的一种输入格式（TabSeparated，Native等）存储数据的文件。
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/special/generate
|
||||
sidebar_position: 46
|
||||
sidebar_label: 随机数生成
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/special/join
|
||||
sidebar_position: 40
|
||||
sidebar_label: 关联表引擎
|
||||
---
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/special/materializedview
|
||||
---
|
||||
# MaterializedView {#materializedview}
|
||||
|
||||
物化视图的使用（更多信息请参阅 [CREATE TABLE](../../../sql-reference/statements/create.md#create-table-query) ）。它需要使用一个不同的引擎来存储数据，这个引擎要在创建物化视图时指定。当从表中读取时，它就会使用该引擎。
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/special/memory
|
||||
sidebar_position: 44
|
||||
sidebar_label: Memory
|
||||
---
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/special/merge
|
||||
---
|
||||
# 合并 {#merge}
|
||||
|
||||
`Merge` 引擎 (不要跟 `MergeTree` 引擎混淆) 本身不存储数据，但可用于同时从任意多个其他的表中读取数据。
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/special/null
|
||||
---
|
||||
# Null {#null}
|
||||
|
||||
当写入 Null 类型的表时，将忽略数据。从 Null 类型的表中读取时，返回空。
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/special/set
|
||||
---
|
||||
# 集合 {#set}
|
||||
|
||||
始终存在于 RAM 中的数据集。它适用于IN运算符的右侧（请参见 «IN运算符» 部分）。
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/special/url
|
||||
---
|
||||
# URL(URL,格式) {#table_engines-url}
|
||||
|
||||
用于管理远程 HTTP/HTTPS 服务器上的数据。该引擎类似
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/engines/table-engines/special/view
|
||||
---
|
||||
# 视图 {#table_engines-view}
|
||||
|
||||
用于构建视图（有关更多信息，请参阅 `CREATE VIEW 查询`）。 它不存储数据，仅存储指定的 `SELECT` 查询。 从表中读取时，它会运行此查询（并从查询中删除所有不必要的列）。
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
---
|
||||
slug: /zh/faq/general
|
||||
---
|
||||
# 常见问题 {#chang-jian-wen-ti}
|
||||
|
||||
## 为什么不使用MapReduce之类的产品呢? {#wei-shi-yao-bu-shi-yong-mapreducezhi-lei-de-chan-pin-ni}
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/general/columnar-database
|
||||
title: 什么是列存储数据库?
|
||||
toc_hidden: true
|
||||
sidebar_position: 101
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/general/dbms-naming
|
||||
title: "\u201CClickHouse\u201D 有什么含义?"
|
||||
toc_hidden: true
|
||||
sidebar_position: 10
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/general/how-do-i-contribute-code-to-clickhouse
|
||||
title: 我如何为ClickHouse贡献代码?
|
||||
toc_hidden: true
|
||||
sidebar_position: 120
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/general/
|
||||
title: ClickHouse 有关常见问题
|
||||
toc_hidden_folder: true
|
||||
sidebar_position: 1
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/general/mapreduce
|
||||
title: 为何不使用 MapReduce等技术?
|
||||
toc_hidden: true
|
||||
sidebar_position: 110
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/general/ne-tormozit
|
||||
title: "What does \u201C\u043D\u0435 \u0442\u043E\u0440\u043C\u043E\u0437\u0438\u0442\
|
||||
\u201D mean?"
|
||||
toc_hidden: true
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/general/olap
|
||||
title: What is OLAP?
|
||||
toc_hidden: true
|
||||
sidebar_position: 100
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/general/who-is-using-clickhouse
|
||||
title: 谁在使用 ClickHouse?
|
||||
toc_hidden: true
|
||||
sidebar_position: 9
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/general/why-clickhouse-is-so-fast
|
||||
title: Why ClickHouse is so fast?
|
||||
toc_hidden: true
|
||||
sidebar_position: 8
|
||||
@ -17,7 +18,7 @@ Indexes
|
||||
: ClickHouse keeps data structures in memory that allows reading not only used columns but only necessary row ranges of those columns.
|
||||
|
||||
Data compression
|
||||
: Storing different values of the same column together often leads to better compression ratios (compared to row-oriented systems) because in real data column often has the same or not so many different values for neighboring rows. In addition to general-purpose compression, ClickHouse supports [specialized codecs](../../sql-reference/statements/create/table/#create-query-specialized-codecs) that can make data even more compact.
|
||||
: Storing different values of the same column together often leads to better compression ratios (compared to row-oriented systems) because in real data column often has the same or not so many different values for neighboring rows. In addition to general-purpose compression, ClickHouse supports [specialized codecs](../../sql-reference/statements/create/table.md/#create-query-specialized-codecs) that can make data even more compact.
|
||||
|
||||
Vectorized query execution
|
||||
: ClickHouse not only stores data in columns but also processes data in columns. It leads to better CPU cache utilization and allows for [SIMD](https://en.wikipedia.org/wiki/SIMD) CPU instructions usage.
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/
|
||||
sidebar_label: F.A.Q.
|
||||
toc_hidden: true
|
||||
sidebar_position: 76
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/integration/file-export
|
||||
title: 如何从 ClickHouse 导出数据到一个文件?
|
||||
toc_hidden: true
|
||||
sidebar_position: 10
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/integration/
|
||||
title: 关于集成ClickHouse和其他系统的问题
|
||||
toc_hidden_folder: true
|
||||
sidebar_position: 4
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/integration/json-import
|
||||
title: How to import JSON into ClickHouse?
|
||||
toc_hidden: true
|
||||
sidebar_position: 11
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/integration/oracle-odbc
|
||||
title: What if I have a problem with encodings when using Oracle via ODBC?
|
||||
toc_hidden: true
|
||||
sidebar_position: 20
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/operations/delete-old-data
|
||||
title: Is it possible to delete old records from a ClickHouse table?
|
||||
toc_hidden: true
|
||||
sidebar_position: 20
|
||||
@ -28,13 +29,13 @@ ClickHouse does not have real-time point deletes like in [OLTP](https://en.wikip
|
||||
|
||||
This is the most common approach to make your system based on ClickHouse [GDPR](https://gdpr-info.eu)-compliant.
|
||||
|
||||
More details on [mutations](../../sql-reference/statements/alter/#alter-mutations).
|
||||
More details on [mutations](../../sql-reference/statements/alter.md/#alter-mutations).
|
||||
|
||||
## DROP PARTITION {#drop-partition}
|
||||
|
||||
`ALTER TABLE ... DROP PARTITION` provides a cost-efficient way to drop a whole partition. It’s not that flexible and needs proper partitioning scheme configured on table creation, but still covers most common cases. Like mutations need to be executed from an external system for regular use.
|
||||
|
||||
More details on [manipulating partitions](../../sql-reference/statements/alter/partition/#alter_drop-partition).
|
||||
More details on [manipulating partitions](../../sql-reference/statements/alter/partition.md/#alter_drop-partition).
|
||||
|
||||
## TRUNCATE {#truncate}
|
||||
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/operations/
|
||||
title: 关于操作ClickHouse服务器和集群的问题
|
||||
toc_hidden_folder: true
|
||||
sidebar_position: 3
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/operations/multi-region-replication
|
||||
title: ClickHouse支持多区域复制吗?
|
||||
toc_hidden: true
|
||||
sidebar_position: 30
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/operations/production
|
||||
title: Which ClickHouse version to use in production?
|
||||
toc_hidden: true
|
||||
sidebar_position: 10
|
||||
|
||||
@ -1,4 +1,8 @@
|
||||
---
|
||||
slug: /zh/faq/terms_translation_zh
|
||||
---
|
||||
# 术语翻译约定
|
||||
|
||||
本文档用来维护从英文翻译成中文的术语集。
|
||||
|
||||
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/use-cases/
|
||||
title: 关于ClickHouse使用案例的问题
|
||||
toc_hidden_folder: true
|
||||
sidebar_position: 2
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/use-cases/key-value
|
||||
title: 我能把 ClickHouse 当做Key-value 键值存储来使用吗？
|
||||
toc_hidden: true
|
||||
sidebar_position: 101
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/faq/use-cases/time-series
|
||||
title: 我能把 ClickHouse 当做时序数据库来使用吗?
|
||||
toc_hidden: true
|
||||
sidebar_position: 101
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/getting-started/example-datasets/amplab-benchmark
|
||||
sidebar_position: 19
|
||||
sidebar_label: AMPLab Big Data Benchmark
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/getting-started/example-datasets/criteo
|
||||
sidebar_position: 18
|
||||
sidebar_label: Terabyte Click Logs from Criteo
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/getting-started/example-datasets/github-events
|
||||
sidebar_position: 11
|
||||
sidebar_label: GitHub 事件数据集
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/getting-started/example-datasets/
|
||||
sidebar_label: 示例数据集
|
||||
sidebar_position: 12
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/getting-started/example-datasets/metrica
|
||||
sidebar_position: 15
|
||||
sidebar_label: Yandex.Metrica Data
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/getting-started/example-datasets/nyc-taxi
|
||||
sidebar_position: 20
|
||||
sidebar_label: New York Taxi Data
|
||||
---
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
---
|
||||
slug: /zh/getting-started/example-datasets/ontime
|
||||
sidebar_position: 21
|
||||
sidebar_label: OnTime
|
||||
---
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue
Block a user