Merge pull request #8909 from blinkov/master

[docs/website] Domain migration
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Ivan Blinkov 2020-01-30 13:45:10 +03:00 committed by GitHub
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6
.gitignore vendored
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@ -13,12 +13,14 @@
/build_* /build_*
/build-* /build-*
/docs/build /docs/build
/docs/publish
/docs/edit /docs/edit
/docs/tools/venv/ /docs/tools/venv/
/docs/en/development/build/
/docs/ru/development/build/
/docs/en/single.md /docs/en/single.md
/docs/ru/single.md /docs/ru/single.md
/docs/zh/single.md
/docs/ja/single.md
/docs/fa/single.md
# callgrind files # callgrind files
callgrind.out.* callgrind.out.*

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@ -38,7 +38,7 @@ Writing the docs is extremely useful for project's users and developers, and gro
The documentation contains information about all the aspects of the ClickHouse lifecycle: developing, testing, installing, operating, and using. The base language of the documentation is English. The English version is the most actual. All other languages are supported as much as they can by contributors from different countries. The documentation contains information about all the aspects of the ClickHouse lifecycle: developing, testing, installing, operating, and using. The base language of the documentation is English. The English version is the most actual. All other languages are supported as much as they can by contributors from different countries.
At the moment, [documentation](https://clickhouse.yandex/docs) exists in English, Russian, Chinese, Japanese, and Farsi. We store the documentation besides the ClickHouse source code in the [GitHub repository](https://github.com/ClickHouse/ClickHouse/tree/master/docs). At the moment, [documentation](https://clickhouse.tech/docs) exists in English, Russian, Chinese, Japanese, and Farsi. We store the documentation besides the ClickHouse source code in the [GitHub repository](https://github.com/ClickHouse/ClickHouse/tree/master/docs).
Each language lays in the corresponding folder. Files that are not translated from English are the symbolic links to the English ones. Each language lays in the corresponding folder. Files that are not translated from English are the symbolic links to the English ones.
@ -54,7 +54,7 @@ You can contribute to the documentation in many ways, for example:
- Open a required file in the ClickHouse repository and edit it from the GitHub web interface. - Open a required file in the ClickHouse repository and edit it from the GitHub web interface.
You can do it on GitHub, or on the [ClickHouse Documentation](https://clickhouse.yandex/docs/en/) site. Each page of ClickHouse Documentation site contains an "Edit this page" (🖋) element in the upper right corner. Clicking this symbol, you get to the ClickHouse docs file opened for editing. You can do it on GitHub, or on the [ClickHouse Documentation](https://clickhouse.tech/docs/en/) site. Each page of ClickHouse Documentation site contains an "Edit this page" (🖋) element in the upper right corner. Clicking this symbol, you get to the ClickHouse docs file opened for editing.
When you are saving a file, GitHub opens a pull-request for your contribution. Add the `documentation` label to this pull request for proper automatic checks applying. If you have no permissions for adding labels, the reviewer of your PR adds it. When you are saving a file, GitHub opens a pull-request for your contribution. Add the `documentation` label to this pull request for proper automatic checks applying. If you have no permissions for adding labels, the reviewer of your PR adds it.
@ -161,7 +161,7 @@ When writing documentation, think about people who read it. Each audience has sp
ClickHouse documentation can be divided by the audience for the following parts: ClickHouse documentation can be divided by the audience for the following parts:
- Conceptual topics in [Introduction](https://clickhouse.yandex/docs/en/), tutorials and overviews, changelog. - Conceptual topics in [Introduction](https://clickhouse.tech/docs/en/), tutorials and overviews, changelog.
These topics are for the most common auditory. When editing text in them, use the most common terms that are comfortable for the audience with basic technical skills. These topics are for the most common auditory. When editing text in them, use the most common terms that are comfortable for the audience with basic technical skills.

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@ -66,4 +66,4 @@ Code: 386. DB::Exception: Received from localhost:9000, 127.0.0.1. DB::Exception
``` ```
[Original article](https://clickhouse.yandex/docs/en/data_types/array/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/array/) <!--hide-->

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@ -3,4 +3,4 @@
There isn't a separate type for boolean values. They use the UInt8 type, restricted to the values 0 or 1. There isn't a separate type for boolean values. They use the UInt8 type, restricted to the values 0 or 1.
[Original article](https://clickhouse.yandex/docs/en/data_types/boolean/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/boolean/) <!--hide-->

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@ -6,4 +6,4 @@ The minimum value is output as 0000-00-00.
The date is stored without the time zone. The date is stored without the time zone.
[Original article](https://clickhouse.yandex/docs/en/data_types/date/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/date/) <!--hide-->

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@ -87,4 +87,4 @@ SELECT toDateTime(now(), 'Europe/Moscow') AS column, toTypeName(column) AS x
- [Operators for working with dates and times](../query_language/operators.md#operators-datetime) - [Operators for working with dates and times](../query_language/operators.md#operators-datetime)
- [The `Date` data type](date.md) - [The `Date` data type](date.md)
[Original article](https://clickhouse.yandex/docs/en/data_types/datetime/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/datetime/) <!--hide-->

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@ -95,4 +95,4 @@ SELECT toDecimal32(1, 8) < 100
DB::Exception: Can't compare. DB::Exception: Can't compare.
``` ```
[Original article](https://clickhouse.yandex/docs/en/data_types/decimal/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/decimal/) <!--hide-->

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@ -26,16 +26,16 @@ CREATE TABLE hits (url String, from IPv4) ENGINE = MergeTree() ORDER BY from;
`IPv4` domain supports custom input format as IPv4-strings: `IPv4` domain supports custom input format as IPv4-strings:
```sql ```sql
INSERT INTO hits (url, from) VALUES ('https://wikipedia.org', '116.253.40.133')('https://clickhouse.yandex', '183.247.232.58')('https://clickhouse.yandex/docs/en/', '116.106.34.242'); INSERT INTO hits (url, from) VALUES ('https://wikipedia.org', '116.253.40.133')('https://clickhouse.tech', '183.247.232.58')('https://clickhouse.yandex/docs/en/', '116.106.34.242');
SELECT * FROM hits; SELECT * FROM hits;
``` ```
```text ```text
┌─url────────────────────────────────┬───────────from─┐ ┌─url────────────────────────────────┬───────────from─┐
│ https://clickhouse.yandex/docs/en/ │ 116.106.34.242 │ │ https://clickhouse.tech/docs/en/ │ 116.106.34.242 │
│ https://wikipedia.org │ 116.253.40.133 │ │ https://wikipedia.org │ 116.253.40.133 │
│ https://clickhouse.yandex │ 183.247.232.58 │ │ https://clickhouse.tech │ 183.247.232.58 │
└────────────────────────────────────┴────────────────┘ └────────────────────────────────────┴────────────────┘
``` ```
@ -76,4 +76,4 @@ SELECT toTypeName(i), CAST(from as UInt32) as i FROM hits LIMIT 1;
└──────────────────────────────────┴────────────┘ └──────────────────────────────────┴────────────┘
``` ```
[Original article](https://clickhouse.yandex/docs/en/data_types/domains/ipv4) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/domains/ipv4) <!--hide-->

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@ -26,15 +26,15 @@ CREATE TABLE hits (url String, from IPv6) ENGINE = MergeTree() ORDER BY from;
`IPv6` domain supports custom input as IPv6-strings: `IPv6` domain supports custom input as IPv6-strings:
```sql ```sql
INSERT INTO hits (url, from) VALUES ('https://wikipedia.org', '2a02:aa08:e000:3100::2')('https://clickhouse.yandex', '2001:44c8:129:2632:33:0:252:2')('https://clickhouse.yandex/docs/en/', '2a02:e980:1e::1'); INSERT INTO hits (url, from) VALUES ('https://wikipedia.org', '2a02:aa08:e000:3100::2')('https://clickhouse.tech', '2001:44c8:129:2632:33:0:252:2')('https://clickhouse.yandex/docs/en/', '2a02:e980:1e::1');
SELECT * FROM hits; SELECT * FROM hits;
``` ```
```text ```text
┌─url────────────────────────────────┬─from──────────────────────────┐ ┌─url────────────────────────────────┬─from──────────────────────────┐
│ https://clickhouse.yandex │ 2001:44c8:129:2632:33:0:252:2 │ │ https://clickhouse.tech │ 2001:44c8:129:2632:33:0:252:2 │
│ https://clickhouse.yandex/docs/en/ │ 2a02:e980:1e::1 │ │ https://clickhouse.tech/docs/en/ │ 2a02:e980:1e::1 │
│ https://wikipedia.org │ 2a02:aa08:e000:3100::2 │ │ https://wikipedia.org │ 2a02:aa08:e000:3100::2 │
└────────────────────────────────────┴───────────────────────────────┘ └────────────────────────────────────┴───────────────────────────────┘
``` ```
@ -76,4 +76,4 @@ SELECT toTypeName(i), CAST(from as FixedString(16)) as i FROM hits LIMIT 1;
└───────────────────────────────────────────┴─────────┘ └───────────────────────────────────────────┴─────────┘
``` ```
[Original article](https://clickhouse.yandex/docs/en/data_types/domains/ipv6) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/domains/ipv6) <!--hide-->

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@ -23,4 +23,4 @@ You can use domains anywhere corresponding base type can be used:
* Can't implicitly convert string values into domain values when inserting data from another column or table. * Can't implicitly convert string values into domain values when inserting data from another column or table.
* Domain adds no constrains on stored values. * Domain adds no constrains on stored values.
[Original article](https://clickhouse.yandex/docs/en/data_types/domains/overview) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/domains/overview) <!--hide-->

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@ -117,4 +117,4 @@ The Enum type can be changed without cost using ALTER, if only the set of values
Using ALTER, it is possible to change an Enum8 to an Enum16 or vice versa, just like changing an Int8 to Int16. Using ALTER, it is possible to change an Enum8 to an Enum16 or vice versa, just like changing an Int8 to Int16.
[Original article](https://clickhouse.yandex/docs/en/data_types/enum/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/enum/) <!--hide-->

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@ -52,4 +52,4 @@ This behavior differs from MySQL behavior for the `CHAR` type (where strings are
Note that the length of the `FixedString(N)` value is constant. The [length](../query_language/functions/array_functions.md#array_functions-length) function returns `N` even if the `FixedString(N)` value is filled only with null bytes, but the [empty](../query_language/functions/string_functions.md#string_functions-empty) function returns `1` in this case. Note that the length of the `FixedString(N)` value is constant. The [length](../query_language/functions/array_functions.md#array_functions-length) function returns `N` even if the `FixedString(N)` value is filled only with null bytes, but the [empty](../query_language/functions/string_functions.md#string_functions-empty) function returns `1` in this case.
[Original article](https://clickhouse.yandex/docs/en/data_types/fixedstring/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/fixedstring/) <!--hide-->

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@ -70,4 +70,4 @@ SELECT 0 / 0
See the rules for `NaN` sorting in the section [ORDER BY clause](../query_language/select.md). See the rules for `NaN` sorting in the section [ORDER BY clause](../query_language/select.md).
[Original article](https://clickhouse.yandex/docs/en/data_types/float/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/float/) <!--hide-->

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@ -5,4 +5,4 @@ ClickHouse can store various types of data in table cells.
This section describes the supported data types and special considerations when using and/or implementing them, if any. This section describes the supported data types and special considerations when using and/or implementing them, if any.
[Original article](https://clickhouse.yandex/docs/en/data_types/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/) <!--hide-->

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@ -18,4 +18,4 @@ Fixed-length integers, with or without a sign.
- UInt64 - [0 : 18446744073709551615] - UInt64 - [0 : 18446744073709551615]
[Original article](https://clickhouse.yandex/docs/en/data_types/int_uint/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/int_uint/) <!--hide-->

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@ -61,4 +61,4 @@ SELECT uniqMerge(state) FROM (SELECT uniqState(UserID) AS state FROM table GROUP
See [AggregatingMergeTree](../../operations/table_engines/aggregatingmergetree.md) engine description. See [AggregatingMergeTree](../../operations/table_engines/aggregatingmergetree.md) engine description.
[Original article](https://clickhouse.yandex/docs/en/data_types/nested_data_structures/aggregatefunction/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/nested_data_structures/aggregatefunction/) <!--hide-->

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@ -1,4 +1,4 @@
# Nested Data Structures # Nested Data Structures
[Original article](https://clickhouse.yandex/docs/en/data_types/nested_data_structures/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/nested_data_structures/) <!--hide-->

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@ -97,4 +97,4 @@ For a DESCRIBE query, the columns in a nested data structure are listed separate
The ALTER query is very limited for elements in a nested data structure. The ALTER query is very limited for elements in a nested data structure.
[Original article](https://clickhouse.yandex/docs/en/data_types/nested_data_structures/nested/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/nested_data_structures/nested/) <!--hide-->

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@ -33,4 +33,4 @@ SELECT x + y FROM t_null
└────────────┘ └────────────┘
``` ```
[Original article](https://clickhouse.yandex/docs/en/data_types/nullable/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/nullable/) <!--hide-->

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@ -3,4 +3,4 @@
Used for representing lambda expressions in high-order functions. Used for representing lambda expressions in high-order functions.
[Original article](https://clickhouse.yandex/docs/en/data_types/special_data_types/expression/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/special_data_types/expression/) <!--hide-->

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@ -3,4 +3,4 @@
Special data type values can't be saved to a table or output in results, but are used as the intermediate result of running a query. Special data type values can't be saved to a table or output in results, but are used as the intermediate result of running a query.
[Original article](https://clickhouse.yandex/docs/en/data_types/special_data_types/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/special_data_types/) <!--hide-->

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@ -17,4 +17,4 @@ SELECT toTypeName(array())
``` ```
[Original article](https://clickhouse.yandex/docs/en/data_types/special_data_types/nothing/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/special_data_types/nothing/) <!--hide-->

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@ -3,4 +3,4 @@
Used for the right half of an IN expression. Used for the right half of an IN expression.
[Original article](https://clickhouse.yandex/docs/en/data_types/special_data_types/set/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/special_data_types/set/) <!--hide-->

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@ -12,4 +12,4 @@ Similarly, certain functions for working with strings have separate variations t
For example, the 'length' function calculates the string length in bytes, while the 'lengthUTF8' function calculates the string length in Unicode code points, assuming that the value is UTF-8 encoded. For example, the 'length' function calculates the string length in bytes, while the 'lengthUTF8' function calculates the string length in Unicode code points, assuming that the value is UTF-8 encoded.
[Original article](https://clickhouse.yandex/docs/en/data_types/string/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/string/) <!--hide-->

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@ -42,4 +42,4 @@ SELECT tuple(1, NULL) AS x, toTypeName(x)
``` ```
[Original article](https://clickhouse.yandex/docs/en/data_types/tuple/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/tuple/) <!--hide-->

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@ -62,4 +62,4 @@ The UUID data type only supports functions which [String](string.md) data type a
The UUID data type is not supported by arithmetic operations (for example, [abs](../query_language/functions/arithmetic_functions.md#arithm_func-abs)) or aggregate functions, such as [sum](../query_language/agg_functions/reference.md#agg_function-sum) and [avg](../query_language/agg_functions/reference.md#agg_function-avg). The UUID data type is not supported by arithmetic operations (for example, [abs](../query_language/functions/arithmetic_functions.md#arithm_func-abs)) or aggregate functions, such as [sum](../query_language/agg_functions/reference.md#agg_function-sum) and [avg](../query_language/agg_functions/reference.md#agg_function-avg).
[Original article](https://clickhouse.yandex/docs/en/data_types/uuid/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/data_types/uuid/) <!--hide-->

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@ -10,4 +10,4 @@ You can also use the following database engines:
- [Lazy](lazy.md) - [Lazy](lazy.md)
[Original article](https://clickhouse.yandex/docs/en/database_engines/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/database_engines/) <!--hide-->

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@ -10,4 +10,4 @@ It's optimized for storing many small \*Log tables, for which there is a long ti
CREATE DATABASE testlazy ENGINE = Lazy(expiration_time_in_seconds); CREATE DATABASE testlazy ENGINE = Lazy(expiration_time_in_seconds);
``` ```
[Original article](https://clickhouse.yandex/docs/en/database_engines/lazy/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/database_engines/lazy/) <!--hide-->

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@ -119,4 +119,4 @@ SELECT * FROM mysql_db.mysql_table
└────────┴───────┘ └────────┴───────┘
``` ```
[Original article](https://clickhouse.yandex/docs/en/database_engines/mysql/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/database_engines/mysql/) <!--hide-->

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@ -194,4 +194,4 @@ In addition, each replica stores its state in ZooKeeper as the set of parts and
> The ClickHouse cluster consists of independent shards, and each shard consists of replicas. The cluster is not elastic, so after adding a new shard, data is not rebalanced between shards automatically. Instead, the cluster load will be uneven. This implementation gives you more control, and it is fine for relatively small clusters such as tens of nodes. But for clusters with hundreds of nodes that we are using in production, this approach becomes a significant drawback. We should implement a table engine that will span its data across the cluster with dynamically replicated regions that could be split and balanced between clusters automatically. > The ClickHouse cluster consists of independent shards, and each shard consists of replicas. The cluster is not elastic, so after adding a new shard, data is not rebalanced between shards automatically. Instead, the cluster load will be uneven. This implementation gives you more control, and it is fine for relatively small clusters such as tens of nodes. But for clusters with hundreds of nodes that we are using in production, this approach becomes a significant drawback. We should implement a table engine that will span its data across the cluster with dynamically replicated regions that could be split and balanced between clusters automatically.
[Original article](https://clickhouse.yandex/docs/en/development/architecture/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/development/architecture/) <!--hide-->

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@ -83,4 +83,4 @@ To create an executable, run `ninja clickhouse`.
This will create the `dbms/programs/clickhouse` executable, which can be used with `client` or `server` arguments. This will create the `dbms/programs/clickhouse` executable, which can be used with `client` or `server` arguments.
[Original article](https://clickhouse.yandex/docs/en/development/build/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/development/build/) <!--hide-->

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@ -1,6 +1,6 @@
# How to Build ClickHouse on Linux for Mac OS X # How to Build ClickHouse on Linux for Mac OS X
This is for the case when you have Linux machine and want to use it to build `clickhouse` binary that will run on OS X. This is intended for continuous integration checks that run on Linux servers. If you want to build ClickHouse directly on Mac OS X, then proceed with another instruction: https://clickhouse.yandex/docs/en/development/build_osx/ This is for the case when you have Linux machine and want to use it to build `clickhouse` binary that will run on OS X. This is intended for continuous integration checks that run on Linux servers. If you want to build ClickHouse directly on Mac OS X, then proceed with another instruction: https://clickhouse.tech/docs/en/development/build_osx/
The cross-build for Mac OS X is based on the [Build instructions](build.md), follow them first. The cross-build for Mac OS X is based on the [Build instructions](build.md), follow them first.

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@ -82,4 +82,4 @@ Reboot.
To check if it's working, you can use `ulimit -n` command. To check if it's working, you can use `ulimit -n` command.
[Original article](https://clickhouse.yandex/docs/en/development/build_osx/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/development/build_osx/) <!--hide-->

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@ -111,7 +111,7 @@ Official Yandex builds currently use GCC because it generates machine code of sl
To install GCC on Ubuntu run: `sudo apt install gcc g++` To install GCC on Ubuntu run: `sudo apt install gcc g++`
Check the version of gcc: `gcc --version`. If it is below 9, then follow the instruction here: https://clickhouse.yandex/docs/en/development/build/#install-gcc-9. Check the version of gcc: `gcc --version`. If it is below 9, then follow the instruction here: https://clickhouse.tech/docs/en/development/build/#install-gcc-9.
Mac OS X build is supported only for Clang. Just run `brew install llvm` Mac OS X build is supported only for Clang. Just run `brew install llvm`
@ -226,11 +226,11 @@ Just in case, it is worth mentioning that CLion creates `build` path on its own,
# Writing Code # Writing Code
The description of ClickHouse architecture can be found here: https://clickhouse.yandex/docs/en/development/architecture/ The description of ClickHouse architecture can be found here: https://clickhouse.tech/docs/en/development/architecture/
The Code Style Guide: https://clickhouse.yandex/docs/en/development/style/ The Code Style Guide: https://clickhouse.tech/docs/en/development/style/
Writing tests: https://clickhouse.yandex/docs/en/development/tests/ Writing tests: https://clickhouse.tech/docs/en/development/tests/
List of tasks: https://github.com/yandex/ClickHouse/blob/master/dbms/tests/instructions/easy_tasks_sorted_en.md List of tasks: https://github.com/yandex/ClickHouse/blob/master/dbms/tests/instructions/easy_tasks_sorted_en.md

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@ -1,4 +1,4 @@
# ClickHouse Development # ClickHouse Development
[Original article](https://clickhouse.yandex/docs/en/development/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/development/) <!--hide-->

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@ -835,4 +835,4 @@ function(
size_t limit) size_t limit)
``` ```
[Original article](https://clickhouse.yandex/docs/en/development/style/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/development/style/) <!--hide-->

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@ -226,7 +226,7 @@ If you use `CLion` as an IDE, you can leverage some `clang-tidy` checks out of t
## Code Style ## Code Style
Code style rules are described [here](https://clickhouse.yandex/docs/en/development/style/). Code style rules are described [here](https://clickhouse.tech/docs/en/development/style/).
To check for some common style violations, you can use `utils/check-style` script. To check for some common style violations, you can use `utils/check-style` script.
@ -258,4 +258,4 @@ Build jobs and tests are run in Sandbox on per commit basis. Resulting packages
We don't use Travis CI due to the limit on time and computational power. We don't use Travis CI due to the limit on time and computational power.
We don't use Jenkins. It was used before and now we are happy we are not using Jenkins. We don't use Jenkins. It was used before and now we are happy we are not using Jenkins.
[Original article](https://clickhouse.yandex/docs/en/development/tests/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/development/tests/) <!--hide-->

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@ -53,4 +53,4 @@ $ clickhouse-client --query "SELECT * from table" > result.txt
See [clickhouse-client](../interfaces/cli.md). See [clickhouse-client](../interfaces/cli.md).
[Original article](https://clickhouse.yandex/docs/en/faq/general/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/faq/general/) <!--hide-->

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@ -120,4 +120,4 @@ LIMIT 1
``` ```
[Original article](https://clickhouse.yandex/docs/en/getting_started/example_datasets/amplab_benchmark/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/getting_started/example_datasets/amplab_benchmark/) <!--hide-->

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@ -72,4 +72,4 @@ DROP TABLE criteo_log;
``` ```
[Original article](https://clickhouse.yandex/docs/en/getting_started/example_datasets/criteo/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/getting_started/example_datasets/criteo/) <!--hide-->

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@ -382,4 +382,4 @@ We ran queries using a client located in a Yandex datacenter in Finland on a clu
| 140 | 0.028 | 0.043 | 0.051 | 0.072 | | 140 | 0.028 | 0.043 | 0.051 | 0.072 |
[Original article](https://clickhouse.yandex/docs/en/getting_started/example_datasets/nyc_taxi/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/getting_started/example_datasets/nyc_taxi/) <!--hide-->

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@ -402,4 +402,4 @@ This performance test was created by Vadim Tkachenko. See:
- <http://nickmakos.blogspot.ru/2012/08/analyzing-air-traffic-performance-with.html> - <http://nickmakos.blogspot.ru/2012/08/analyzing-air-traffic-performance-with.html>
[Original article](https://clickhouse.yandex/docs/en/getting_started/example_datasets/ontime/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/getting_started/example_datasets/ontime/) <!--hide-->

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@ -337,4 +337,4 @@ ORDER BY
P_BRAND ASC; P_BRAND ASC;
``` ```
[Original article](https://clickhouse.yandex/docs/en/getting_started/example_datasets/star_schema/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/getting_started/example_datasets/star_schema/) <!--hide-->

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@ -26,4 +26,4 @@ $ ls -1 /opt/wikistat/ | grep gz | while read i; do echo $i; gzip -cd /opt/wikis
``` ```
[Original article](https://clickhouse.yandex/docs/en/getting_started/example_datasets/wikistat/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/getting_started/example_datasets/wikistat/) <!--hide-->

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@ -5,4 +5,4 @@ If you are new to ClickHouse and want to get a hands-on feeling of it's performa
* [Go through detailed tutorial](tutorial.md) * [Go through detailed tutorial](tutorial.md)
* [Experiment with example datasets](example_datasets/ontime.md) * [Experiment with example datasets](example_datasets/ontime.md)
[Original article](https://clickhouse.yandex/docs/en/getting_started/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/getting_started/) <!--hide-->

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@ -176,7 +176,7 @@ SELECT 1
**Congratulations, the system works!** **Congratulations, the system works!**
To continue experimenting, you can download one of test data sets or go through [tutorial](https://clickhouse.yandex/tutorial.html). To continue experimenting, you can download one of test data sets or go through [tutorial](https://clickhouse.tech/tutorial.html).
[Original article](https://clickhouse.yandex/docs/en/getting_started/install/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/getting_started/install/) <!--hide-->

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@ -129,4 +129,4 @@ This is not done in "normal" databases, because it doesn't make sense when runni
Note that for CPU efficiency, the query language must be declarative (SQL or MDX), or at least a vector (J, K). The query should only contain implicit loops, allowing for optimization. Note that for CPU efficiency, the query language must be declarative (SQL or MDX), or at least a vector (J, K). The query should only contain implicit loops, allowing for optimization.
[Original article](https://clickhouse.yandex/docs/en/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/) <!--hide-->

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@ -147,4 +147,4 @@ Example of a config file:
``` ```
[Original article](https://clickhouse.yandex/docs/en/interfaces/cli/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/interfaces/cli/) <!--hide-->

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@ -2,4 +2,4 @@
See README at [clickhouse-cpp](https://github.com/ClickHouse/clickhouse-cpp) repository. See README at [clickhouse-cpp](https://github.com/ClickHouse/clickhouse-cpp) repository.
[Original article](https://clickhouse.yandex/docs/en/interfaces/cpp/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/interfaces/cpp/) <!--hide-->

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@ -1024,7 +1024,7 @@ If you input or output data via the [HTTP interface](../interfaces/http.md) the
should be located in the directory specified in [format_schema_path](../operations/server_settings/settings.md#server_settings-format_schema_path) should be located in the directory specified in [format_schema_path](../operations/server_settings/settings.md#server_settings-format_schema_path)
in the server configuration. in the server configuration.
[Original article](https://clickhouse.yandex/docs/en/interfaces/formats/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/interfaces/formats/) <!--hide-->
## Skipping Errors {#skippingerrors} ## Skipping Errors {#skippingerrors}

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@ -264,4 +264,4 @@ You can create a query with parameters and pass values for them from the corresp
$ curl -sS "<address>?param_id=2&param_phrase=test" -d "SELECT * FROM table WHERE int_column = {id:UInt8} and string_column = {phrase:String}" $ curl -sS "<address>?param_id=2&param_phrase=test" -d "SELECT * FROM table WHERE int_column = {id:UInt8} and string_column = {phrase:String}"
``` ```
[Original article](https://clickhouse.yandex/docs/en/interfaces/http_interface/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/interfaces/http_interface/) <!--hide-->

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@ -18,4 +18,4 @@ There are also a wide range of third-party libraries for working with ClickHouse
* [Integrations](third-party/integrations.md) * [Integrations](third-party/integrations.md)
* [Visual interfaces](third-party/gui.md) * [Visual interfaces](third-party/gui.md)
[Original article](https://clickhouse.yandex/docs/en/interfaces/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/interfaces/) <!--hide-->

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@ -6,4 +6,4 @@
* [clickhouse4j](https://github.com/blynkkk/clickhouse4j) * [clickhouse4j](https://github.com/blynkkk/clickhouse4j)
[Original article](https://clickhouse.yandex/docs/en/interfaces/jdbc/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/interfaces/jdbc/) <!--hide-->

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@ -3,4 +3,4 @@
- [Official driver](https://github.com/ClickHouse/clickhouse-odbc). - [Official driver](https://github.com/ClickHouse/clickhouse-odbc).
[Original article](https://clickhouse.yandex/docs/en/interfaces/odbc/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/interfaces/odbc/) <!--hide-->

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@ -2,4 +2,4 @@
The native protocol is used in the [command-line client](cli.md), for interserver communication during distributed query processing, and also in other C++ programs. Unfortunately, native ClickHouse protocol does not have formal specification yet, but it can be reverse engineered from ClickHouse source code (starting [around here](https://github.com/ClickHouse/ClickHouse/tree/master/dbms/src/Client)) and/or by intercepting and analyzing TCP traffic. The native protocol is used in the [command-line client](cli.md), for interserver communication during distributed query processing, and also in other C++ programs. Unfortunately, native ClickHouse protocol does not have formal specification yet, but it can be reverse engineered from ClickHouse source code (starting [around here](https://github.com/ClickHouse/ClickHouse/tree/master/dbms/src/Client)) and/or by intercepting and analyzing TCP traffic.
[Original article](https://clickhouse.yandex/docs/en/interfaces/tcp/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/interfaces/tcp/) <!--hide-->

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@ -48,4 +48,4 @@
- [nim-clickhouse](https://github.com/leonardoce/nim-clickhouse) - [nim-clickhouse](https://github.com/leonardoce/nim-clickhouse)
[Original article](https://clickhouse.yandex/docs/en/interfaces/third-party/client_libraries/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/interfaces/third-party/client_libraries/) <!--hide-->

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@ -126,4 +126,4 @@ Features:
[Data Modeling](https://looker.com/platform/data-modeling) to support report writers and end users. [Data Modeling](https://looker.com/platform/data-modeling) to support report writers and end users.
- Powerful workflow integration via Looker's [Data Actions](https://looker.com/platform/actions). - Powerful workflow integration via Looker's [Data Actions](https://looker.com/platform/actions).
[Original article](https://clickhouse.yandex/docs/en/interfaces/third-party/gui/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/interfaces/third-party/gui/) <!--hide-->

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@ -85,4 +85,4 @@
- [clickhouse_ecto](https://github.com/appodeal/clickhouse_ecto) - [clickhouse_ecto](https://github.com/appodeal/clickhouse_ecto)
[Original article](https://clickhouse.yandex/docs/en/interfaces/third-party/integrations/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/interfaces/third-party/integrations/) <!--hide-->

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@ -36,4 +36,4 @@ Features:
Implemented in Go. Implemented in Go.
[Original article](https://clickhouse.yandex/docs/en/interfaces/third-party/proxy/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/interfaces/third-party/proxy/) <!--hide-->

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@ -61,4 +61,4 @@ Uses asynchronous multimaster replication. After being written to any available
For more information, see the section [Data replication](../operations/table_engines/replication.md). For more information, see the section [Data replication](../operations/table_engines/replication.md).
[Original article](https://clickhouse.yandex/docs/en/introduction/distinctive_features/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/introduction/distinctive_features/) <!--hide-->

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@ -4,4 +4,4 @@
2. Lack of ability to modify or delete already inserted data with high rate and low latency. There are batch deletes and updates available to clean up or modify data, for example to comply with [GDPR](https://gdpr-info.eu). 2. Lack of ability to modify or delete already inserted data with high rate and low latency. There are batch deletes and updates available to clean up or modify data, for example to comply with [GDPR](https://gdpr-info.eu).
3. The sparse index makes ClickHouse not really suitable for point queries retrieving single rows by their keys. 3. The sparse index makes ClickHouse not really suitable for point queries retrieving single rows by their keys.
[Original article](https://clickhouse.yandex/docs/en/introduction/features_considered_disadvantages/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/introduction/features_considered_disadvantages/) <!--hide-->

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@ -47,4 +47,4 @@ OLAPServer worked well for non-aggregated data, but it had many restrictions tha
To remove the limitations of OLAPServer and solve the problem of working with non-aggregated data for all reports, we developed the ClickHouse DBMS. To remove the limitations of OLAPServer and solve the problem of working with non-aggregated data for all reports, we developed the ClickHouse DBMS.
[Original article](https://clickhouse.yandex/docs/en/introduction/history/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/introduction/history/) <!--hide-->

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@ -1,8 +1,8 @@
# Performance # Performance
According to internal testing results at Yandex, ClickHouse shows the best performance (both the highest throughput for long queries and the lowest latency on short queries) for comparable operating scenarios among systems of its class that were available for testing. You can view the test results on a [separate page](https://clickhouse.yandex/benchmark.html). According to internal testing results at Yandex, ClickHouse shows the best performance (both the highest throughput for long queries and the lowest latency on short queries) for comparable operating scenarios among systems of its class that were available for testing. You can view the test results on a [separate page](/benchmark.html).
This has also been confirmed by numerous independent benchmarks. They are not difficult to find using an internet search, or you can see [our small collection of related links](https://clickhouse.yandex/#independent-benchmarks). This has also been confirmed by numerous independent benchmarks. They are not difficult to find using an internet search, or you can see [our small collection of related links](/#independent-benchmarks).
## Throughput for a Single Large Query ## Throughput for a Single Large Query
@ -22,4 +22,4 @@ Under the same conditions, ClickHouse can handle several hundred queries per sec
We recommend inserting data in packets of at least 1000 rows, or no more than a single request per second. When inserting to a MergeTree table from a tab-separated dump, the insertion speed will be from 50 to 200 MB/s. If the inserted rows are around 1 Kb in size, the speed will be from 50,000 to 200,000 rows per second. If the rows are small, the performance will be higher in rows per second (on Banner System data -`>` 500,000 rows per second; on Graphite data -`>` 1,000,000 rows per second). To improve performance, you can make multiple INSERT queries in parallel, and performance will increase linearly. We recommend inserting data in packets of at least 1000 rows, or no more than a single request per second. When inserting to a MergeTree table from a tab-separated dump, the insertion speed will be from 50 to 200 MB/s. If the inserted rows are around 1 Kb in size, the speed will be from 50,000 to 200,000 rows per second. If the rows are small, the performance will be higher in rows per second (on Banner System data -`>` 500,000 rows per second; on Graphite data -`>` 1,000,000 rows per second). To improve performance, you can make multiple INSERT queries in parallel, and performance will increase linearly.
[Original article](https://clickhouse.yandex/docs/en/introduction/performance/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/introduction/performance/) <!--hide-->

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@ -104,4 +104,4 @@ The user can get a list of all databases and tables in them by using `SHOW` quer
Database access is not related to the [readonly](settings/permissions_for_queries.md#settings_readonly) setting. You can't grant full access to one database and `readonly` access to another one. Database access is not related to the [readonly](settings/permissions_for_queries.md#settings_readonly) setting. You can't grant full access to one database and `readonly` access to another one.
[Original article](https://clickhouse.yandex/docs/en/operations/access_rights/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/access_rights/) <!--hide-->

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@ -31,4 +31,4 @@ For more information about queries related to partition manipulations, see the [
A third-party tool is available to automate this approach: [clickhouse-backup](https://github.com/AlexAkulov/clickhouse-backup). A third-party tool is available to automate this approach: [clickhouse-backup](https://github.com/AlexAkulov/clickhouse-backup).
[Original article](https://clickhouse.yandex/docs/en/operations/backup/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/backup/) <!--hide-->

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@ -42,4 +42,4 @@ For each config file, the server also generates `file-preprocessed.xml` files wh
The server tracks changes in config files, as well as files and ZooKeeper nodes that were used when performing substitutions and overrides, and reloads the settings for users and clusters on the fly. This means that you can modify the cluster, users, and their settings without restarting the server. The server tracks changes in config files, as well as files and ZooKeeper nodes that were used when performing substitutions and overrides, and reloads the settings for users and clusters on the fly. This means that you can modify the cluster, users, and their settings without restarting the server.
[Original article](https://clickhouse.yandex/docs/en/operations/configuration_files/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/configuration_files/) <!--hide-->

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@ -17,4 +17,4 @@ ClickHouse operations manual consists of the following major sections:
- [Settings](settings/index.md) - [Settings](settings/index.md)
- [Utilities](utils/index.md) - [Utilities](utils/index.md)
[Original article](https://clickhouse.yandex/docs/en/operations/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/) <!--hide-->

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@ -38,7 +38,7 @@ wget https://raw.githubusercontent.com/ClickHouse/ClickHouse/master/dbms/benchma
According to the instruction: According to the instruction:
[https://clickhouse.yandex/docs/en/getting_started/example_datasets/metrica/](https://clickhouse.yandex/docs/en/getting_started/example_datasets/metrica/) [https://clickhouse.tech/docs/en/getting_started/example_datasets/metrica/](https://clickhouse.yandex/docs/en/getting_started/example_datasets/metrica/)
("hits" table containing 100 million rows) ("hits" table containing 100 million rows)
@ -73,4 +73,4 @@ mcedit benchmark-new.sh
\12. Send the numbers and the info about your hardware configuration to clickhouse-feedback@yandex-team.com \12. Send the numbers and the info about your hardware configuration to clickhouse-feedback@yandex-team.com
All the results are published here: [https://clickhouse.yandex/benchmark_hardware.html](https://clickhouse.yandex/benchmark_hardware.html) All the results are published here: [https://clickhouse.tech/benchmark_hardware.html](https://clickhouse.yandex/benchmark_hardware.html)

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@ -103,4 +103,4 @@ For distributed query processing, the accumulated amounts are stored on the requ
When the server is restarted, quotas are reset. When the server is restarted, quotas are reset.
[Original article](https://clickhouse.yandex/docs/en/operations/quotas/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/quotas/) <!--hide-->

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@ -9,4 +9,4 @@ Other settings are described in the "[Settings](../settings/index.md#settings)"
Before studying the settings, read the [Configuration files](../configuration_files.md#configuration_files) section and note the use of substitutions (the `incl` and `optional` attributes). Before studying the settings, read the [Configuration files](../configuration_files.md#configuration_files) section and note the use of substitutions (the `incl` and `optional` attributes).
[Original article](https://clickhouse.yandex/docs/en/operations/server_settings/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/server_settings/) <!--hide-->

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@ -882,4 +882,4 @@ The update is performed asynchronously, in a separate system thread.
**Default value**: 15. **Default value**: 15.
[Original article](https://clickhouse.yandex/docs/en/operations/server_settings/settings/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/server_settings/settings/) <!--hide-->

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@ -65,4 +65,4 @@ Code: 452, e.displayText() = DB::Exception: Setting force_index_by_date should n
**Note:** the `default` profile has a special handling: all the constraints defined for the `default` profile become the default constraints, so they restrict all the users until they're overriden explicitly for these users. **Note:** the `default` profile has a special handling: all the constraints defined for the `default` profile become the default constraints, so they restrict all the users until they're overriden explicitly for these users.
[Original article](https://clickhouse.yandex/docs/en/operations/settings/constraints_on_settings/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/settings/constraints_on_settings/) <!--hide-->

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@ -21,4 +21,4 @@ Similarly, you can use ClickHouse sessions in the HTTP protocol. To do this, you
Settings that can only be made in the server config file are not covered in this section. Settings that can only be made in the server config file are not covered in this section.
[Original article](https://clickhouse.yandex/docs/en/operations/settings/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/settings/) <!--hide-->

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@ -51,4 +51,4 @@ You can't execute `SET allow_ddl = 1` if `allow_ddl = 0` for the current session
Default value: 1 Default value: 1
[Original article](https://clickhouse.yandex/docs/en/operations/settings/permissions_for_queries/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/settings/permissions_for_queries/) <!--hide-->

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@ -274,4 +274,4 @@ When inserting data, ClickHouse calculates the number of partitions in the inser
> "Too many partitions for single INSERT block (more than " + toString(max_parts) + "). The limit is controlled by 'max_partitions_per_insert_block' setting. Large number of partitions is a common misconception. It will lead to severe negative performance impact, including slow server startup, slow INSERT queries and slow SELECT queries. Recommended total number of partitions for a table is under 1000..10000. Please note, that partitioning is not intended to speed up SELECT queries (ORDER BY key is sufficient to make range queries fast). Partitions are intended for data manipulation (DROP PARTITION, etc)." > "Too many partitions for single INSERT block (more than " + toString(max_parts) + "). The limit is controlled by 'max_partitions_per_insert_block' setting. Large number of partitions is a common misconception. It will lead to severe negative performance impact, including slow server startup, slow INSERT queries and slow SELECT queries. Recommended total number of partitions for a table is under 1000..10000. Please note, that partitioning is not intended to speed up SELECT queries (ORDER BY key is sufficient to make range queries fast). Partitions are intended for data manipulation (DROP PARTITION, etc)."
[Original article](https://clickhouse.yandex/docs/en/operations/settings/query_complexity/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/settings/query_complexity/) <!--hide-->

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@ -1143,4 +1143,4 @@ Enable order-preserving parallel parsing of data formats. Supported only for TSV
The minimum chunk size in bytes, which each thread will parse in parallel. The minimum chunk size in bytes, which each thread will parse in parallel.
[Original article](https://clickhouse.yandex/docs/en/operations/settings/settings/) <!-- hide --> [Original article](https://clickhouse.tech/docs/en/operations/settings/settings/) <!-- hide -->

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@ -63,4 +63,4 @@ The example specifies two profiles: `default` and `web`. The `default` profile h
Settings profiles can inherit from each other. To use inheritance, indicate one or multiple `profile` settings before the other settings that are listed in the profile. In case when one setting is defined in different profiles, the latest defined is used. Settings profiles can inherit from each other. To use inheritance, indicate one or multiple `profile` settings before the other settings that are listed in the profile. In case when one setting is defined in different profiles, the latest defined is used.
[Original article](https://clickhouse.yandex/docs/en/operations/settings/settings_profiles/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/settings/settings_profiles/) <!--hide-->

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@ -143,4 +143,4 @@ The following configuration forces that user `user1` can only see the rows of `t
The `filter` can be any expression resulting in a [UInt8](../../data_types/int_uint.md)-type value. It usually contains comparisons and logical operators. Rows from `database_name.table1` where filter results to 0 are not returned for this user. The filtering is incompatible with `PREWHERE` operations and disables `WHERE→PREWHERE` optimization. The `filter` can be any expression resulting in a [UInt8](../../data_types/int_uint.md)-type value. It usually contains comparisons and logical operators. Rows from `database_name.table1` where filter results to 0 are not returned for this user. The filtering is incompatible with `PREWHERE` operations and disables `WHERE→PREWHERE` optimization.
[Original article](https://clickhouse.yandex/docs/en/operations/settings/settings_users/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/settings/settings_users/) <!--hide-->

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@ -960,4 +960,4 @@ Columns:
If the storage policy contains more then one volume, then information for each volume is stored in the individual row of the table. If the storage policy contains more then one volume, then information for each volume is stored in the individual row of the table.
[Original article](https://clickhouse.yandex/docs/en/operations/system_tables/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/system_tables/) <!--hide-->

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@ -91,4 +91,4 @@ GROUP BY StartDate
ORDER BY StartDate; ORDER BY StartDate;
``` ```
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/aggregatingmergetree/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/aggregatingmergetree/) <!--hide-->

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@ -62,4 +62,4 @@ A Buffer table is used when too many INSERTs are received from a large number of
Note that it doesn't make sense to insert data one row at a time, even for Buffer tables. This will only produce a speed of a few thousand rows per second, while inserting larger blocks of data can produce over a million rows per second (see the section "Performance"). Note that it doesn't make sense to insert data one row at a time, even for Buffer tables. This will only produce a speed of a few thousand rows per second, while inserting larger blocks of data can produce over a million rows per second (see the section "Performance").
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/buffer/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/buffer/) <!--hide-->

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@ -286,4 +286,4 @@ select * FROM UAct
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/collapsingmergetree/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/collapsingmergetree/) <!--hide-->

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@ -117,4 +117,4 @@ Note that on the operating server, you cannot manually change the set of parts o
ClickHouse allows you to perform operations with the partitions: delete them, copy from one table to another, or create a backup. See the list of all operations in the section [Manipulations With Partitions and Parts](../../query_language/alter.md#alter_manipulations-with-partitions). ClickHouse allows you to perform operations with the partitions: delete them, copy from one table to another, or create a backup. See the list of all operations in the section [Manipulations With Partitions and Parts](../../query_language/alter.md#alter_manipulations-with-partitions).
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/custom_partitioning_key/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/custom_partitioning_key/) <!--hide-->

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@ -90,4 +90,4 @@ select * from products limit 1;
``` ```
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/dictionary/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/dictionary/) <!--hide-->

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@ -142,4 +142,4 @@ When the max_parallel_replicas option is enabled, query processing is paralleliz
- [Virtual columns](index.md#table_engines-virtual_columns) - [Virtual columns](index.md#table_engines-virtual_columns)
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/distributed/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/distributed/) <!--hide-->

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@ -60,4 +60,4 @@ $ curl -F 'passwd=@passwd.tsv;' 'http://localhost:8123/?query=SELECT+shell,+coun
For distributed query processing, the temporary tables are sent to all the remote servers. For distributed query processing, the temporary tables are sent to all the remote servers.
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/external_data/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/external_data/) <!--hide-->

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@ -80,4 +80,4 @@ $ echo -e "1,2\n3,4" | clickhouse-local -q "CREATE TABLE table (a Int64, b Int64
- Indices - Indices
- Replication - Replication
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/file/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/file/) <!--hide-->

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@ -161,4 +161,4 @@ Fields for `pattern` and `default` sections:
</graphite_rollup> </graphite_rollup>
``` ```
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/graphitemergetree/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/graphitemergetree/) <!--hide-->

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@ -107,6 +107,6 @@ CREARE TABLE big_table (name String, value UInt32) ENGINE = HDFS('hdfs://hdfs1:9
**See Also** **See Also**
- [Virtual columns](https://clickhouse.yandex/docs/en/operations/table_engines/#table_engines-virtual_columns) - [Virtual columns](https://clickhouse.tech/docs/en/operations/table_engines/#table_engines-virtual_columns)
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/hdfs/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/hdfs/) <!--hide-->

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@ -74,4 +74,4 @@ To select data from a virtual column, you must specify its name in the `SELECT`
If you create a table with a column that has the same name as one of the table virtual columns, the virtual column becomes inaccessible. We don't recommend doing this. To help avoid conflicts, virtual column names are usually prefixed with an underscore. If you create a table with a column that has the same name as one of the table virtual columns, the virtual column becomes inaccessible. We don't recommend doing this. To help avoid conflicts, virtual column names are usually prefixed with an underscore.
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/) <!--hide-->

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@ -82,4 +82,4 @@ FROM jdbc_table
- [JDBC table function](../../query_language/table_functions/jdbc.md). - [JDBC table function](../../query_language/table_functions/jdbc.md).
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/jdbc/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/jdbc/) <!--hide-->

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@ -95,4 +95,4 @@ The `Join`-engine tables can't be used in `GLOBAL JOIN` operations.
If the server restarts incorrectly, the data block on the disk might get lost or damaged. In this case, you may need to manually delete the file with damaged data. If the server restarts incorrectly, the data block on the disk might get lost or damaged. In this case, you may need to manually delete the file with damaged data.
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/join/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/join/) <!--hide-->

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@ -168,4 +168,4 @@ For a list of possible configuration options, see the [librdkafka configuration
- [Virtual columns](index.md#table_engines-virtual_columns) - [Virtual columns](index.md#table_engines-virtual_columns)
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/kafka/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/kafka/) <!--hide-->

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@ -8,4 +8,4 @@ For concurrent data access, the read operations can be performed simultaneously,
The Log engine does not support indexes. Similarly, if writing to a table failed, the table is broken, and reading from it returns an error. The Log engine is appropriate for temporary data, write-once tables, and for testing or demonstration purposes. The Log engine does not support indexes. Similarly, if writing to a table failed, the table is broken, and reading from it returns an error. The Log engine is appropriate for temporary data, write-once tables, and for testing or demonstration purposes.
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/log/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/log/) <!--hide-->

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@ -35,4 +35,4 @@ The `TinyLog` engine is the simplest in the family and provides the poorest func
The `Log` and `StripeLog` engines support parallel data reading. When reading data, ClickHouse uses multiple threads. Each thread processes a separate data block. The `Log` engine uses a separate file for each column of the table. `StripeLog` stores all the data in one file. As a result, the `StripeLog` engine uses fewer descriptors in the operating system, but the `Log` engine provides higher efficiency when reading data. The `Log` and `StripeLog` engines support parallel data reading. When reading data, ClickHouse uses multiple threads. Each thread processes a separate data block. The `Log` engine uses a separate file for each column of the table. `StripeLog` stores all the data in one file. As a result, the `StripeLog` engine uses fewer descriptors in the operating system, but the `Log` engine provides higher efficiency when reading data.
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/log_family/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/log_family/) <!--hide-->

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@ -3,4 +3,4 @@
Used for implementing materialized views (for more information, see [CREATE TABLE](../../query_language/create.md)). For storing data, it uses a different engine that was specified when creating the view. When reading from a table, it just uses this engine. Used for implementing materialized views (for more information, see [CREATE TABLE](../../query_language/create.md)). For storing data, it uses a different engine that was specified when creating the view. When reading from a table, it just uses this engine.
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/materializedview/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/materializedview/) <!--hide-->

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@ -10,4 +10,4 @@ Normally, using this table engine is not justified. However, it can be used for
The Memory engine is used by the system for temporary tables with external query data (see the section "External data for processing a query"), and for implementing GLOBAL IN (see the section "IN operators"). The Memory engine is used by the system for temporary tables with external query data (see the section "External data for processing a query"), and for implementing GLOBAL IN (see the section "IN operators").
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/memory/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/memory/) <!--hide-->

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@ -60,4 +60,4 @@ FROM WatchLog
- [Virtual columns](index.md#table_engines-virtual_columns) - [Virtual columns](index.md#table_engines-virtual_columns)
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/merge/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/merge/) <!--hide-->

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@ -477,7 +477,7 @@ When ClickHouse see that data is expired, it performs an off-schedule merge. To
If you perform the `SELECT` query between merges, you may get expired data. To avoid it, use the [OPTIMIZE](../../query_language/misc.md#misc_operations-optimize) query before `SELECT`. If you perform the `SELECT` query between merges, you may get expired data. To avoid it, use the [OPTIMIZE](../../query_language/misc.md#misc_operations-optimize) query before `SELECT`.
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/mergetree/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/mergetree/) <!--hide-->
## Using Multiple Block Devices for Data Storage {#table_engine-mergetree-multiple-volumes} ## Using Multiple Block Devices for Data Storage {#table_engine-mergetree-multiple-volumes}
@ -651,4 +651,4 @@ Moving data does not interfere with data replication. Therefore, different stora
After the completion of background merges and mutations, old parts are removed only after a certain amount of time (`old_parts_lifetime`). After the completion of background merges and mutations, old parts are removed only after a certain amount of time (`old_parts_lifetime`).
During this time, they are not moved to other volumes or disks. Therefore, until the parts are finally removed, they are still taken into account for evaluation of the occupied disk space. During this time, they are not moved to other volumes or disks. Therefore, until the parts are finally removed, they are still taken into account for evaluation of the occupied disk space.
[Original article](https://clickhouse.yandex/docs/ru/operations/table_engines/mergetree/) <!--hide--> [Original article](https://clickhouse.tech/docs/ru/operations/table_engines/mergetree/) <!--hide-->

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@ -88,4 +88,4 @@ SELECT * FROM mysql_table
- [The 'mysql' table function](../../query_language/table_functions/mysql.md) - [The 'mysql' table function](../../query_language/table_functions/mysql.md)
- [Using MySQL as a source of external dictionary](../../query_language/dicts/external_dicts_dict_sources.md#dicts-external_dicts_dict_sources-mysql) - [Using MySQL as a source of external dictionary](../../query_language/dicts/external_dicts_dict_sources.md#dicts-external_dicts_dict_sources-mysql)
[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/mysql/) <!--hide--> [Original article](https://clickhouse.tech/docs/en/operations/table_engines/mysql/) <!--hide-->

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