find . -type f -name '*.md'| xargs -I{} perl -pi -e 's|https://clickhouse.tech|https://clickhouse.com|g' {}

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Ivan Blinkov 2021-09-19 23:05:54 +03:00
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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.
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).
At the moment, [documentation](https://clickhouse.com/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.
@ -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.
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.
You can do it on GitHub, or on the [ClickHouse Documentation](https://clickhouse.com/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.
@ -128,7 +128,7 @@ Contribute all new information in English language. Other languages are translat
When you add a new file, it should end with a link like:
`[Original article](https://clickhouse.tech/docs/<path-to-the-page>) <!--hide-->`
`[Original article](https://clickhouse.com/docs/<path-to-the-page>) <!--hide-->`
and there should be **a new empty line** after it.
@ -164,7 +164,7 @@ 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:
- Conceptual topics in [Introduction](https://clickhouse.tech/docs/en/), tutorials and overviews, changelog.
- Conceptual topics in [Introduction](https://clickhouse.com/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.

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@ -26,4 +26,4 @@ The name of an additional section can be any, for example, **Usage**.
- [link](#)
[Original article](https://clickhouse.tech/docs/en/data-types/<data-type-name>/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/data-types/<data-type-name>/) <!--hide-->

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@ -12,9 +12,9 @@ Syntax of the statement.
Examples of descriptions with a complicated structure:
- https://clickhouse.tech/docs/en/sql-reference/statements/grant/
- https://clickhouse.tech/docs/en/sql-reference/statements/revoke/
- https://clickhouse.tech/docs/en/sql-reference/statements/select/join/
- https://clickhouse.com/docs/en/sql-reference/statements/grant/
- https://clickhouse.com/docs/en/sql-reference/statements/revoke/
- https://clickhouse.com/docs/en/sql-reference/statements/select/join/
**See Also** (Optional)

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@ -59,4 +59,4 @@ toc_title: Cloud
- High security with isolated per cluster VPCs
- On-demand pricing with no upfront costs or long-term commitments
{## [Original article](https://clickhouse.tech/docs/en/commercial/cloud/) ##}
{## [Original article](https://clickhouse.com/docs/en/commercial/cloud/) ##}

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@ -63,7 +63,7 @@ git checkout -b name_for_a_branch_with_my_test upstream/master
#### Install & run clickhouse
1) install `clickhouse-server` (follow [official docs](https://clickhouse.tech/docs/en/getting-started/install/))
1) install `clickhouse-server` (follow [official docs](https://clickhouse.com/docs/en/getting-started/install/))
2) install test configurations (it will use Zookeeper mock implementation and adjust some settings)
```
cd ~/workspace/ClickHouse/tests/config

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@ -196,4 +196,4 @@ Besides, each replica stores its state in ZooKeeper as the set of parts and its
!!! note "Note"
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 is supposed to be adjusted to be uneven. This implementation gives you more control, and it is ok 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 spans across the cluster with dynamically replicated regions that could be split and balanced between clusters automatically.
{## [Original article](https://clickhouse.tech/docs/en/development/architecture/) ##}
{## [Original article](https://clickhouse.com/docs/en/development/architecture/) ##}

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@ -5,7 +5,7 @@ toc_title: Source Code Browser
# Browse ClickHouse Source Code {#browse-clickhouse-source-code}
You can use **Woboq** online code browser available [here](https://clickhouse.tech/codebrowser/html_report/ClickHouse/src/index.html). It provides code navigation and semantic highlighting, search and indexing. The code snapshot is updated daily.
You can use **Woboq** online code browser available [here](https://clickhouse.com/codebrowser/html_report/ClickHouse/src/index.html). It provides code navigation and semantic highlighting, search and indexing. The code snapshot is updated daily.
Also, you can browse sources on [GitHub](https://github.com/ClickHouse/ClickHouse) as usual.

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@ -131,4 +131,4 @@ cd ClickHouse
./build/programs/clickhouse-server --config-file ./programs/server/config.xml
```
[Original article](https://clickhouse.tech/docs/en/development/build_osx/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/development/build_osx/) <!--hide-->

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@ -161,4 +161,4 @@ Note that the split build has several drawbacks:
* You cannot run the integration tests since they only work a single complete binary.
* You can't easily copy the binaries elsewhere. Instead of moving a single binary you'll need to copy all binaries and libraries.
[Original article](https://clickhouse.tech/docs/en/development/build/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/development/build/) <!--hide-->

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@ -233,13 +233,13 @@ 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.tech/docs/en/development/architecture/
The description of ClickHouse architecture can be found here: https://clickhouse.com/docs/en/development/architecture/
The Code Style Guide: https://clickhouse.tech/docs/en/development/style/
The Code Style Guide: https://clickhouse.com/docs/en/development/style/
Adding third-party libraries: https://clickhouse.tech/docs/en/development/contrib/#adding-third-party-libraries
Adding third-party libraries: https://clickhouse.com/docs/en/development/contrib/#adding-third-party-libraries
Writing tests: https://clickhouse.tech/docs/en/development/tests/
Writing tests: https://clickhouse.com/docs/en/development/tests/
List of tasks: https://github.com/ClickHouse/ClickHouse/issues?q=is%3Aopen+is%3Aissue+label%3A%22easy+task%22

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@ -7,4 +7,4 @@ toc_title: hidden
# ClickHouse Development {#clickhouse-development}
[Original article](https://clickhouse.tech/docs/en/development/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/development/) <!--hide-->

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@ -828,4 +828,4 @@ function(
size_t limit)
```
[Original article](https://clickhouse.tech/docs/en/development/style/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/development/style/) <!--hide-->

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@ -239,7 +239,7 @@ Google OSS-Fuzz can be found at `docker/fuzz`.
We also use simple fuzz test to generate random SQL queries and to check that the server does not die executing them.
You can find it in `00746_sql_fuzzy.pl`. This test should be run continuously (overnight and longer).
We also use sophisticated AST-based query fuzzer that is able to find huge amount of corner cases. It does random permutations and substitutions in queries AST. It remembers AST nodes from previous tests to use them for fuzzing of subsequent tests while processing them in random order. You can learn more about this fuzzer in [this blog article](https://clickhouse.tech/blog/en/2021/fuzzing-clickhouse/).
We also use sophisticated AST-based query fuzzer that is able to find huge amount of corner cases. It does random permutations and substitutions in queries AST. It remembers AST nodes from previous tests to use them for fuzzing of subsequent tests while processing them in random order. You can learn more about this fuzzer in [this blog article](https://clickhouse.com/blog/en/2021/fuzzing-clickhouse/).
## Stress test
@ -341,4 +341,4 @@ Build jobs and tests are run in Sandbox on per commit basis. Resulting packages
We do not use Travis CI due to the limit on time and computational power.
We do not use Jenkins. It was used before and now we are happy we are not using Jenkins.
[Original article](https://clickhouse.tech/docs/en/development/tests/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/development/tests/) <!--hide-->

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@ -13,4 +13,4 @@ Its optimized for storing many small \*Log tables, for which there is a long
CREATE DATABASE testlazy ENGINE = Lazy(expiration_time_in_seconds);
[Original article](https://clickhouse.tech/docs/en/database_engines/lazy/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/database_engines/lazy/) <!--hide-->

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@ -197,4 +197,4 @@ SELECT * FROM mysql.test;
└───┴─────┴──────┘
```
[Original article](https://clickhouse.tech/docs/en/engines/database-engines/materialized-mysql/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/engines/database-engines/materialized-mysql/) <!--hide-->

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@ -147,4 +147,4 @@ SELECT * FROM mysql_db.mysql_table
└────────┴───────┘
```
[Original article](https://clickhouse.tech/docs/en/database_engines/mysql/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/database_engines/mysql/) <!--hide-->

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@ -136,4 +136,4 @@ DESCRIBE TABLE test_database.test_table;
└────────┴───────────────────┘
```
[Original article](https://clickhouse.tech/docs/en/database-engines/postgresql/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/database-engines/postgresql/) <!--hide-->

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@ -12,4 +12,4 @@ There are two key engine kinds in ClickHouse:
- [Table engines](../engines/table-engines/index.md)
- [Database engines](../engines/database-engines/index.md)
{## [Original article](https://clickhouse.tech/docs/en/engines/) ##}
{## [Original article](https://clickhouse.com/docs/en/engines/) ##}

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@ -86,4 +86,4 @@ 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 do not recommend doing this. To help avoid conflicts, virtual column names are usually prefixed with an underscore.
[Original article](https://clickhouse.tech/docs/en/engines/table-engines/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/engines/table-engines/) <!--hide-->

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@ -81,4 +81,4 @@ You can also change any [rocksdb options](https://github.com/facebook/rocksdb/wi
</rocksdb>
```
[Original article](https://clickhouse.tech/docs/en/engines/table-engines/integrations/embedded-rocksdb/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/engines/table-engines/integrations/embedded-rocksdb/) <!--hide-->

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@ -224,4 +224,4 @@ libhdfs3 support HDFS namenode HA.
- [Virtual columns](../../../engines/table-engines/index.md#table_engines-virtual_columns)
[Original article](https://clickhouse.tech/docs/en/engines/table-engines/integrations/hdfs/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/engines/table-engines/integrations/hdfs/) <!--hide-->

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@ -92,4 +92,4 @@ FROM system.numbers
- [JDBC table function](../../../sql-reference/table-functions/jdbc.md).
[Original article](https://clickhouse.tech/docs/en/engines/table-engines/integrations/jdbc/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/engines/table-engines/integrations/jdbc/) <!--hide-->

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@ -194,4 +194,4 @@ Example:
- [Virtual columns](../../../engines/table-engines/index.md#table_engines-virtual_columns)
- [background_schedule_pool_size](../../../operations/settings/settings.md#background_schedule_pool_size)
[Original article](https://clickhouse.tech/docs/en/engines/table-engines/integrations/kafka/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/engines/table-engines/integrations/kafka/) <!--hide-->

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@ -66,4 +66,4 @@ SELECT COUNT() FROM mongo_table;
└─────────┘
```
[Original article](https://clickhouse.tech/docs/en/engines/table-engines/integrations/mongodb/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/engines/table-engines/integrations/mongodb/) <!--hide-->

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@ -113,4 +113,4 @@ SELECT * FROM mysql_table
- [The mysql table function](../../../sql-reference/table-functions/mysql.md)
- [Using MySQL as a source of external dictionary](../../../sql-reference/dictionaries/external-dictionaries/external-dicts-dict-sources.md#dicts-external_dicts_dict_sources-mysql)
[Original article](https://clickhouse.tech/docs/en/engines/table-engines/integrations/mysql/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/engines/table-engines/integrations/mysql/) <!--hide-->

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@ -128,4 +128,4 @@ SELECT * FROM odbc_t
- [ODBC external dictionaries](../../../sql-reference/dictionaries/external-dictionaries/external-dicts-dict-sources.md#dicts-external_dicts_dict_sources-odbc)
- [ODBC table function](../../../sql-reference/table-functions/odbc.md)
[Original article](https://clickhouse.tech/docs/en/engines/table-engines/integrations/odbc/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/engines/table-engines/integrations/odbc/) <!--hide-->

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@ -149,4 +149,4 @@ CREATE TABLE pg_table_schema_with_dots (a UInt32)
- [The `postgresql` table function](../../../sql-reference/table-functions/postgresql.md)
- [Using PostgreSQL as a source of external dictionary](../../../sql-reference/dictionaries/external-dictionaries/external-dicts-dict-sources.md#dicts-external_dicts_dict_sources-postgresql)
[Original article](https://clickhouse.tech/docs/en/engines/table-engines/integrations/postgresql/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/engines/table-engines/integrations/postgresql/) <!--hide-->

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@ -170,4 +170,4 @@ Example:
- `_message_id` - messageID of the received message; non-empty if was set, when message was published.
- `_timestamp` - timestamp of the received message; non-empty if was set, when message was published.
[Original article](https://clickhouse.tech/docs/en/engines/table-engines/integrations/rabbitmq/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/engines/table-engines/integrations/rabbitmq/) <!--hide-->

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@ -44,4 +44,4 @@ 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 file descriptors, but the `Log` engine provides higher efficiency when reading data.
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/log_family/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/log_family/) <!--hide-->

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@ -90,4 +90,4 @@ SELECT * FROM stripe_log_table ORDER BY timestamp
└─────────────────────┴──────────────┴────────────────────────────┘
```
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/stripelog/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/stripelog/) <!--hide-->

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@ -11,4 +11,4 @@ This table engine is typically used with the write-once method: write data one t
Queries are executed in a single stream. In other words, this engine is intended for relatively small tables (up to about 1,000,000 rows). It makes sense to use this table engine if you have many small tables, since its simpler than the [Log](../../../engines/table-engines/log-family/log.md) engine (fewer files need to be opened).
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/tinylog/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/tinylog/) <!--hide-->

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@ -100,4 +100,4 @@ GROUP BY StartDate
ORDER BY StartDate;
```
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/aggregatingmergetree/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/aggregatingmergetree/) <!--hide-->

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@ -303,4 +303,4 @@ select * FROM UAct
└─────────────────────┴───────────┴──────────┴──────┘
```
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/collapsingmergetree/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/collapsingmergetree/) <!--hide-->

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@ -127,4 +127,4 @@ 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](../../../sql-reference/statements/alter/partition.md#alter_manipulations-with-partitions).
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/custom_partitioning_key/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/custom_partitioning_key/) <!--hide-->

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@ -170,4 +170,4 @@ Fields for `pattern` and `default` sections:
!!! warning "Warning"
Data rollup is performed during merges. Usually, for old partitions, merges are not started, so for rollup it is necessary to trigger an unscheduled merge using [optimize](../../../sql-reference/statements/optimize.md). Or use additional tools, for example [graphite-ch-optimizer](https://github.com/innogames/graphite-ch-optimizer).
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/graphitemergetree/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/graphitemergetree/) <!--hide-->

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@ -291,4 +291,4 @@ If the data in ZooKeeper was lost or damaged, you can save data by moving it to
- [max_replicated_fetches_network_bandwidth](../../../operations/settings/merge-tree-settings.md#max_replicated_fetches_network_bandwidth)
- [max_replicated_sends_network_bandwidth](../../../operations/settings/merge-tree-settings.md#max_replicated_sends_network_bandwidth)
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/replication/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/replication/) <!--hide-->

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@ -136,4 +136,4 @@ When requesting data, use the [sumMap(key, value)](../../../sql-reference/aggreg
For nested data structure, you do not need to specify its columns in the tuple of columns for summation.
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/summingmergetree/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/summingmergetree/) <!--hide-->

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@ -233,4 +233,4 @@ SELECT * FROM UAct FINAL
This is a very inefficient way to select data. Dont use it for large tables.
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/versionedcollapsingmergetree/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/versionedcollapsingmergetree/) <!--hide-->

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@ -75,4 +75,4 @@ A Buffer table is used when too many INSERTs are received from a large number of
Note that it does not 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.tech/docs/en/operations/table_engines/buffer/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/buffer/) <!--hide-->

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@ -198,4 +198,4 @@ When the `max_parallel_replicas` option is enabled, query processing is parallel
- [Virtual columns](../../../engines/table-engines/special/index.md#table_engines-virtual_columns)
- [background_distributed_schedule_pool_size](../../../operations/settings/settings.md#background_distributed_schedule_pool_size)
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/distributed/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/distributed/) <!--hide-->

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@ -63,4 +63,4 @@ $ 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.
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/external_data/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/external_data/) <!--hide-->

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@ -85,4 +85,4 @@ $ echo -e "1,2\n3,4" | clickhouse-local -q "CREATE TABLE table (a Int64, b Int64
- Indices
- Replication
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/file/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/file/) <!--hide-->

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@ -56,4 +56,4 @@ SELECT * FROM generate_engine_table LIMIT 3
- Indices
- Replication
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/generate/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/generate/) <!--hide-->

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@ -7,4 +7,4 @@ toc_title: MaterializedView
Used for implementing materialized views (for more information, see [CREATE VIEW](../../../sql-reference/statements/create/view.md#materialized)). For storing data, it uses a different engine that was specified when creating the view. When reading from a table, it just uses that engine.
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/materializedview/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/materializedview/) <!--hide-->

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@ -15,4 +15,4 @@ 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”).
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/memory/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/memory/) <!--hide-->

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@ -69,4 +69,4 @@ FROM WatchLog
- [Virtual columns](../../../engines/table-engines/special/index.md#table_engines-virtual_columns)
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/merge/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/merge/) <!--hide-->

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@ -10,4 +10,4 @@ When writing to a `Null` table, data is ignored. When reading from a `Null` tabl
!!! info "Hint"
However, you can create a materialized view on a `Null` table. So the data written to the table will end up affecting the view, but original raw data will still be discarded.
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/null/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/null/) <!--hide-->

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@ -20,4 +20,4 @@ When creating a table, the following settings are applied:
- [persistent](../../../operations/settings/settings.md#persistent)
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/set/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/set/) <!--hide-->

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@ -78,4 +78,4 @@ SELECT * FROM url_engine_table
- Indexes.
- Replication.
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/url/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/url/) <!--hide-->

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@ -7,4 +7,4 @@ toc_title: View
Used for implementing views (for more information, see the `CREATE VIEW query`). It does not store data, but only stores the specified `SELECT` query. When reading from a table, it runs this query (and deletes all unnecessary columns from the query).
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/view/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/table_engines/view/) <!--hide-->

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@ -17,9 +17,9 @@ Key columnar database advantages are:
Here is the illustration of the difference between traditional row-oriented systems and columnar databases when building reports:
**Traditional row-oriented**
![Traditional row-oriented](https://clickhouse.tech/docs/en/images/row-oriented.gif#)
![Traditional row-oriented](https://clickhouse.com/docs/en/images/row-oriented.gif#)
**Columnar**
![Columnar](https://clickhouse.tech/docs/en/images/column-oriented.gif#)
![Columnar](https://clickhouse.com/docs/en/images/column-oriented.gif#)
A columnar database is a preferred choice for analytical applications because it allows to have many columns in a table just in case, but do not pay the cost for unused columns on read query execution time. Column-oriented databases are designed for big data processing because and data warehousing, they often natively scale using distributed clusters of low-cost hardware to increase throughput. ClickHouse does it with combination of [distributed](../../engines/table-engines/special/distributed.md) and [replicated](../../engines/table-engines/mergetree-family/replication.md) tables.

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@ -21,4 +21,4 @@ Questions:
!!! info "Dont see what you were looking for?"
Check out [other F.A.Q. categories](../../faq/index.md) or browse around main documentation articles found in the left sidebar.
{## [Original article](https://clickhouse.tech/docs/en/faq/general/) ##}
{## [Original article](https://clickhouse.com/docs/en/faq/general/) ##}

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@ -23,4 +23,4 @@ If you havent seen one of those t-shirts in person, you can check them out on
![iframe](https://www.youtube.com/embed/bSyQahMVZ7w)
P.S. These t-shirts are not for sale, they are given away for free on most [ClickHouse Meetups](https://clickhouse.tech/#meet), usually for best questions or other forms of active participation.
P.S. These t-shirts are not for sale, they are given away for free on most [ClickHouse Meetups](https://clickhouse.com/#meet), usually for best questions or other forms of active participation.

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@ -43,4 +43,4 @@ Question candidates:
- Window function workarounds (row_number, lag/lead, running diff/sum/average)
##}
{## [Original article](https://clickhouse.tech/docs/en/faq) ##}
{## [Original article](https://clickhouse.com/docs/en/faq) ##}

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@ -16,4 +16,4 @@ Questions:
!!! info "Dont see what you were looking for?"
Check out [other F.A.Q. categories](../../faq/index.md) or browse around main documentation articles found in the left sidebar.
{## [Original article](https://clickhouse.tech/docs/en/faq/integration/) ##}
{## [Original article](https://clickhouse.com/docs/en/faq/integration/) ##}

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@ -15,4 +15,4 @@ Questions:
!!! info "Dont see what you were looking for?"
Check out [other F.A.Q. categories](../../faq/index.md) or browse around main documentation articles found in the left sidebar.
{## [Original article](https://clickhouse.tech/docs/en/faq/production/) ##}
{## [Original article](https://clickhouse.com/docs/en/faq/production/) ##}

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@ -15,4 +15,4 @@ Questions:
!!! info "Dont see what you were looking for?"
Check out [other F.A.Q. categories](../../faq/index.md) or browse around main documentation articles found in the left sidebar.
{## [Original article](https://clickhouse.tech/docs/en/faq/use-cases/) ##}
{## [Original article](https://clickhouse.com/docs/en/faq/use-cases/) ##}

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@ -124,4 +124,4 @@ ORDER BY totalRevenue DESC
LIMIT 1
```
[Original article](https://clickhouse.tech/docs/en/getting_started/example_datasets/amplab_benchmark/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/getting_started/example_datasets/amplab_benchmark/) <!--hide-->

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@ -413,4 +413,4 @@ ORDER BY yr,
The data is also available for interactive queries in the [Playground](https://gh-api.clickhouse.tech/play?user=play), [example](https://gh-api.clickhouse.tech/play?user=play#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).
[Original article](https://clickhouse.tech/docs/en/getting_started/example_datasets/brown-benchmark/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/getting_started/example_datasets/brown-benchmark/) <!--hide-->

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@ -76,4 +76,4 @@ INSERT INTO criteo SELECT date, clicked, int1, int2, int3, int4, int5, int6, int
DROP TABLE criteo_log;
```
[Original article](https://clickhouse.tech/docs/en/getting_started/example_datasets/criteo/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/getting_started/example_datasets/criteo/) <!--hide-->

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@ -25,4 +25,4 @@ The list of documented datasets:
- [Brown University Benchmark](../../getting-started/example-datasets/brown-benchmark.md)
- [Cell Towers](../../getting-started/example-datasets/cell-towers.md)
[Original article](https://clickhouse.tech/docs/en/getting_started/example_datasets) <!--hide-->
[Original article](https://clickhouse.com/docs/en/getting_started/example_datasets) <!--hide-->

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@ -385,4 +385,4 @@ We ran queries using a client located in a Yandex datacenter in Finland on a clu
| 3 | 0.212 | 0.438 | 0.733 | 1.241 |
| 140 | 0.028 | 0.043 | 0.051 | 0.072 |
[Original article](https://clickhouse.tech/docs/en/getting_started/example_datasets/nyc_taxi/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/getting_started/example_datasets/nyc_taxi/) <!--hide-->

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@ -404,4 +404,4 @@ This performance test was created by Vadim Tkachenko. See:
- https://www.percona.com/blog/2016/01/07/apache-spark-with-air-ontime-performance-data/
- http://nickmakos.blogspot.ru/2012/08/analyzing-air-traffic-performance-with.html
[Original article](https://clickhouse.tech/docs/en/getting_started/example_datasets/ontime/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/getting_started/example_datasets/ontime/) <!--hide-->

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@ -337,4 +337,4 @@ Result:
The dataset is also available in the [Online Playground](https://gh-api.clickhouse.tech/play?user=play#U0VMRUNUCiAgICBhcnJheUpvaW4oTkVSKSBBUyBrLAogICAgY291bnQoKSBBUyBjCkZST00gcmVjaXBlcwpHUk9VUCBCWSBrCk9SREVSIEJZIGMgREVTQwpMSU1JVCA1MA==).
[Original article](https://clickhouse.tech/docs/en/getting-started/example-datasets/recipes/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/getting-started/example-datasets/recipes/) <!--hide-->

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@ -365,4 +365,4 @@ ORDER BY
P_BRAND ASC;
```
[Original article](https://clickhouse.tech/docs/en/getting_started/example_datasets/star_schema/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/getting_started/example_datasets/star_schema/) <!--hide-->

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@ -30,4 +30,4 @@ $ cat links.txt | while read link; do wget http://dumps.wikimedia.org/other/page
$ ls -1 /opt/wikistat/ | grep gz | while read i; do echo $i; gzip -cd /opt/wikistat/$i | ./wikistat-loader --time="$(echo -n $i | sed -r 's/pagecounts-([0-9]{4})([0-9]{2})([0-9]{2})-([0-9]{2})([0-9]{2})([0-9]{2})\.gz/\1-\2-\3 \4-00-00/')" | clickhouse-client --query="INSERT INTO wikistat FORMAT TabSeparated"; done
```
[Original article](https://clickhouse.tech/docs/en/getting_started/example_datasets/wikistat/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/getting_started/example_datasets/wikistat/) <!--hide-->

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@ -12,4 +12,4 @@ If you are new to ClickHouse and want to get a hands-on feeling of its performan
- [Go through detailed tutorial](../getting-started/tutorial.md)
- [Experiment with example datasets](../getting-started/example-datasets/ontime.md)
[Original article](https://clickhouse.tech/docs/en/getting_started/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/getting_started/) <!--hide-->

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@ -203,6 +203,6 @@ SELECT 1
**Congratulations, the system works!**
To continue experimenting, you can download one of the test data sets or go through [tutorial](https://clickhouse.tech/tutorial.html).
To continue experimenting, you can download one of the test data sets or go through [tutorial](https://clickhouse.com/tutorial.html).
[Original article](https://clickhouse.tech/docs/en/getting_started/install/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/getting_started/install/) <!--hide-->

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@ -659,4 +659,4 @@ INSERT INTO tutorial.hits_replica SELECT * FROM tutorial.hits_local;
Replication operates in multi-master mode. Data can be loaded into any replica, and the system then syncs it with other instances automatically. Replication is asynchronous so at a given moment, not all replicas may contain recently inserted data. At least one replica should be up to allow data ingestion. Others will sync up data and repair consistency once they will become active again. Note that this approach allows for the low possibility of a loss of recently inserted data.
[Original article](https://clickhouse.tech/docs/en/getting_started/tutorial/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/getting_started/tutorial/) <!--hide-->

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@ -239,4 +239,4 @@ FROM
!!! note "Note"
More info about [avg()](../sql-reference/aggregate-functions/reference/avg.md#agg_function-avg) and [log()](../sql-reference/functions/math-functions.md) functions.
[Original article](https://clickhouse.tech/docs/en/guides/apply_catboost_model/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/guides/apply_catboost_model/) <!--hide-->

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@ -11,4 +11,4 @@ List of detailed step-by-step instructions that help to solve various tasks usin
- [Tutorial on simple cluster set-up](../getting-started/tutorial.md)
- [Applying a CatBoost model in ClickHouse](../guides/apply-catboost-model.md)
[Original article](https://clickhouse.tech/docs/en/guides/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/guides/) <!--hide-->

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@ -92,4 +92,4 @@ This is not done in “normal” databases, because it does not make sense when
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.tech/docs/en/) ##}
{## [Original article](https://clickhouse.com/docs/en/) ##}

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@ -7,4 +7,4 @@ toc_title: C++ Client Library
See README at [clickhouse-cpp](https://github.com/ClickHouse/clickhouse-cpp) repository.
[Original article](https://clickhouse.tech/docs/en/interfaces/cpp/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/interfaces/cpp/) <!--hide-->

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@ -24,4 +24,4 @@ There are also a wide range of third-party libraries for working with ClickHouse
- [Integrations](../interfaces/third-party/integrations.md)
- [Visual interfaces](../interfaces/third-party/gui.md)
[Original article](https://clickhouse.tech/docs/en/interfaces/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/interfaces/) <!--hide-->

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@ -10,4 +10,4 @@ toc_title: JDBC Driver
- [ClickHouse-Native-JDBC](https://github.com/housepower/ClickHouse-Native-JDBC)
- [clickhouse4j](https://github.com/blynkkk/clickhouse4j)
[Original article](https://clickhouse.tech/docs/en/interfaces/jdbc/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/interfaces/jdbc/) <!--hide-->

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@ -50,4 +50,4 @@ To cancel a long query use `KILL QUERY connection_id` statement (it is replaced
$ mysql --protocol tcp -h mysql_server -P 9004 default -u default --password=123 -e "KILL QUERY 123456;"
```
[Original article](https://clickhouse.tech/docs/en/interfaces/mysql/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/interfaces/mysql/) <!--hide-->

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@ -7,4 +7,4 @@ toc_title: ODBC Driver
- [Official driver](https://github.com/ClickHouse/clickhouse-odbc)
[Original article](https://clickhouse.tech/docs/en/interfaces/odbc/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/interfaces/odbc/) <!--hide-->

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@ -7,4 +7,4 @@ toc_title: Native Interface (TCP)
The native protocol is used in the [command-line client](../interfaces/cli.md), for inter-server 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/src/Client)) and/or by intercepting and analyzing TCP traffic.
[Original article](https://clickhouse.tech/docs/en/interfaces/tcp/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/interfaces/tcp/) <!--hide-->

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@ -67,4 +67,4 @@ toc_title: Client Libraries
- Haskell
- [hdbc-clickhouse](https://github.com/zaneli/hdbc-clickhouse)
[Original article](https://clickhouse.tech/docs/en/interfaces/third-party/client_libraries/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/interfaces/third-party/client_libraries/) <!--hide-->

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@ -206,4 +206,4 @@ SeekTable is [free](https://www.seektable.com/help/cloud-pricing) for personal/i
[Chadmin](https://github.com/bun4uk/chadmin) is a simple UI where you can visualize your currently running queries on your ClickHouse cluster and info about them and kill them if you want.
[Original article](https://clickhouse.tech/docs/en/interfaces/third-party/gui/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/interfaces/third-party/gui/) <!--hide-->

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@ -108,4 +108,4 @@ toc_title: Integrations
- [GraphQL](https://github.com/graphql)
- [activecube-graphql](https://github.com/bitquery/activecube-graphql)
[Original article](https://clickhouse.tech/docs/en/interfaces/third-party/integrations/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/interfaces/third-party/integrations/) <!--hide-->

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@ -41,4 +41,4 @@ Features:
Implemented in Go.
[Original article](https://clickhouse.tech/docs/en/interfaces/third-party/proxy/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/interfaces/third-party/proxy/) <!--hide-->

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@ -58,7 +58,7 @@ toc_title: Adopters
| <a href="https://glaber.io/" class="favicon">Glaber</a> | Monitoring | Main product | — | — | [Website](https://glaber.io/) |
| <a href="https://www.huya.com/" class="favicon">HUYA</a> | Video Streaming | Analytics | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/7.%20ClickHouse万亿数据分析实践%20李本旺(sundy-li)%20虎牙.pdf) |
| <a href="https://www.the-ica.com/" class="favicon">ICA</a> | FinTech | Risk Management | — | — | [Blog Post in English, Sep 2020](https://altinity.com/blog/clickhouse-vs-redshift-performance-for-fintech-risk-management?utm_campaign=ClickHouse%20vs%20RedShift&utm_content=143520807&utm_medium=social&utm_source=twitter&hss_channel=tw-3894792263) |
| <a href="https://www.idealista.com" class="favicon">Idealista</a> | Real Estate | Analytics | — | — | [Blog Post in English, April 2019](https://clickhouse.tech/blog/en/clickhouse-meetup-in-madrid-on-april-2-2019) |
| <a href="https://www.idealista.com" class="favicon">Idealista</a> | Real Estate | Analytics | — | — | [Blog Post in English, April 2019](https://clickhouse.com/blog/en/clickhouse-meetup-in-madrid-on-april-2-2019) |
| <a href="https://infobaleen.com" class="favicon">Infobaleen</a> | AI markting tool | Analytics | — | — | [Official site](https://infobaleen.com) |
| <a href="https://www.infovista.com/" class="favicon">Infovista</a> | Networks | Analytics | — | — | [Slides in English, October 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup30/infovista.pdf) |
| <a href="https://www.innogames.com" class="favicon">InnoGames</a> | Games | Metrics, Logging | — | — | [Slides in Russian, September 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup28/graphite_and_clickHouse.pdf) |
@ -70,7 +70,7 @@ toc_title: Adopters
| <a href="https://jinshuju.net" class="favicon">Jinshuju 金数据</a> | BI Analytics | Main product | — | — | [Slides in Chinese, October 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup24/3.%20金数据数据架构调整方案Public.pdf) |
| <a href="https://www.kodiakdata.com/" class="favicon">Kodiak Data</a> | Clouds | Main product | — | — | [Slides in Engish, April 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup13/kodiak_data.pdf) |
| <a href="https://kontur.ru" class="favicon">Kontur</a> | Software Development | Metrics | — | — | [Talk in Russian, November 2018](https://www.youtube.com/watch?v=U4u4Bd0FtrY) |
| <a href="https://www.kuaishou.com/" class="favicon">Kuaishou</a> | Video | — | — | — | [ClickHouse Meetup, October 2018](https://clickhouse.tech/blog/en/2018/clickhouse-community-meetup-in-beijing-on-october-28-2018/) |
| <a href="https://www.kuaishou.com/" class="favicon">Kuaishou</a> | Video | — | — | — | [ClickHouse Meetup, October 2018](https://clickhouse.com/blog/en/2018/clickhouse-community-meetup-in-beijing-on-october-28-2018/) |
| <a href="https://www.lbl.gov" class="favicon">Lawrence Berkeley National Laboratory</a> | Research | Traffic analysis | 1 server | 11.8 TiB | [Slides in English, April 2019](https://www.smitasin.com/presentations/2019-04-17_DOE-NSM.pdf) |
| <a href="https://lifestreet.com/" class="favicon">LifeStreet</a> | Ad network | Main product | 75 servers (3 replicas) | 5.27 PiB | [Blog post in Russian, February 2017](https://habr.com/en/post/322620/) |
| <a href="https://mcs.mail.ru/" class="favicon">Mail.ru Cloud Solutions</a> | Cloud services | Main product | — | — | [Article in Russian](https://mcs.mail.ru/help/db-create/clickhouse#) |
@ -160,4 +160,4 @@ toc_title: Adopters
| <a href="https://zagravagames.com/en/" class="favicon">Zagrava Trading</a> | — | — | — | — | [Job offer, May 2021](https://twitter.com/datastackjobs/status/1394707267082063874) |
| <a href="https://beeline.ru/" class="favicon">Beeline</a> | Telecom | Data Platform | — | — | [Blog post, July 2021](https://habr.com/en/company/beeline/blog/567508/) |
[Original article](https://clickhouse.tech/docs/en/introduction/adopters/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/introduction/adopters/) <!--hide-->

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@ -93,4 +93,4 @@ ClickHouse implements user account management using SQL queries and allows for [
2. Lack of ability to modify or delete already inserted data with a 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 so efficient for point queries retrieving single rows by their keys.
[Original article](https://clickhouse.tech/docs/en/introduction/distinctive-features/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/introduction/distinctive-features/) <!--hide-->

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@ -51,4 +51,4 @@ OLAPServer worked well for non-aggregated data, but it had many restrictions tha
The initial goal for ClickHouse was to remove the limitations of OLAPServer and solve the problem of working with non-aggregated data for all reports, but over the years, it has grown into a general-purpose database management system suitable for a wide range of analytical tasks.
[Original article](https://clickhouse.tech/docs/en/introduction/history/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/introduction/history/) <!--hide-->

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@ -7,4 +7,4 @@ toc_priority: 100
- Email address: <a class="feedback-email"></a>
- Phone: <a href="tel:+74957806510">+7-495-780-6510</a>
[Original article](https://clickhouse.tech/docs/en/introduction/info/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/introduction/info/) <!--hide-->

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@ -5,9 +5,9 @@ toc_title: Performance
# 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.tech/benchmark/dbms/).
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.com/benchmark/dbms/).
Numerous independent benchmarks came to similar conclusions. They are not difficult to find using an internet search, or you can see [our small collection of related links](https://clickhouse.tech/#independent-benchmarks).
Numerous independent benchmarks came to similar conclusions. They are not difficult to find using an internet search, or you can see [our small collection of related links](https://clickhouse.com/#independent-benchmarks).
## Throughput for a Single Large Query {#throughput-for-a-single-large-query}
@ -27,4 +27,4 @@ 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 can 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 can 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, which scales linearly.
{## [Original article](https://clickhouse.tech/docs/en/introduction/performance/) ##}
{## [Original article](https://clickhouse.com/docs/en/introduction/performance/) ##}

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@ -149,4 +149,4 @@ Management queries:
By default, SQL-driven access control and account management is disabled for all users. You need to configure at least one user in the `users.xml` configuration file and set the value of the [access_management](../operations/settings/settings-users.md#access_management-user-setting) setting to 1.
[Original article](https://clickhouse.tech/docs/en/operations/access_rights/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/access_rights/) <!--hide-->

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@ -37,4 +37,4 @@ 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).
[Original article](https://clickhouse.tech/docs/en/operations/backup/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/backup/) <!--hide-->

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@ -26,4 +26,4 @@ Indirectly used:
To drop cache, use [SYSTEM DROP ... CACHE](../sql-reference/statements/system.md) statements.
[Original article](https://clickhouse.tech/docs/en/operations/caches/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/caches/) <!--hide-->

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@ -116,4 +116,4 @@ clickhouse-keeper-converter --zookeeper-logs-dir /var/lib/zookeeper/version-2 --
4. Copy snapshot to ClickHouse server nodes with a configured `keeper` or start ClickHouse Keeper instead of ZooKeeper. The snapshot must persist on all nodes, otherwise, empty nodes can be faster and one of them can become a leader.
[Original article](https://clickhouse.tech/docs/en/operations/clickhouse-keeper/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/clickhouse-keeper/) <!--hide-->

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@ -156,4 +156,4 @@ 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.
[Original article](https://clickhouse.tech/docs/en/operations/configuration-files/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/configuration-files/) <!--hide-->

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@ -13,4 +13,4 @@ The following external authenticators and directories are supported:
- [LDAP](./ldap.md#external-authenticators-ldap) [Authenticator](./ldap.md#ldap-external-authenticator) and [Directory](./ldap.md#ldap-external-user-directory)
- Kerberos [Authenticator](./kerberos.md#external-authenticators-kerberos)
[Original article](https://clickhouse.tech/docs/en/operations/external-authenticators/index/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/external-authenticators/index/) <!--hide-->

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@ -179,4 +179,4 @@ Note that `my_ldap_server` referred in the `ldap` section inside the `user_direc
- `attribute` — Attribute name whose values will be returned by the LDAP search. `cn`, by default.
- `prefix` — Prefix, that will be expected to be in front of each string in the original list of strings returned by the LDAP search. The prefix will be removed from the original strings and the resulting strings will be treated as local role names. Empty by default.
[Original article](https://clickhouse.tech/docs/en/operations/external-authenticators/ldap/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/external-authenticators/ldap/) <!--hide-->

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@ -23,4 +23,4 @@ ClickHouse operations manual consists of the following major sections:
- [Settings](../operations/settings/index.md)
- [Utilities](../operations/utilities/index.md)
{## [Original article](https://clickhouse.tech/docs/en/operations/) ##}
{## [Original article](https://clickhouse.com/docs/en/operations/) ##}

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@ -61,4 +61,4 @@ FROM system.opentelemetry_span_log
In case of any errors, the part of the log data for which the error has occurred will be silently lost. Check the server log for error messages if the data does not arrive.
[Original article](https://clickhouse.tech/docs/en/operations/opentelemetry/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/opentelemetry/) <!--hide-->

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@ -25,7 +25,7 @@ chmod a+x ./hardware.sh
3. Copy the output and send it to clickhouse-feedback@yandex-team.com
All the results are published here: https://clickhouse.tech/benchmark/hardware/
All the results are published here: https://clickhouse.com/benchmark/hardware/
## Manual Run
@ -68,4 +68,4 @@ mv hits_100m_obfuscated_v1/* .
```
7. Send the numbers and the info about your hardware configuration to clickhouse-feedback@yandex-team.com
All the results are published here: https://clickhouse.tech/benchmark/hardware/
All the results are published here: https://clickhouse.com/benchmark/hardware/

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@ -117,4 +117,4 @@ For distributed query processing, the accumulated amounts are stored on the requ
When the server is restarted, quotas are reset.
[Original article](https://clickhouse.tech/docs/en/operations/quotas/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/quotas/) <!--hide-->

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@ -14,4 +14,4 @@ Other settings are described in the “[Settings](../../operations/settings/inde
Before studying the settings, read the [Configuration files](../../operations/configuration-files.md#configuration_files) section and note the use of substitutions (the `incl` and `optional` attributes).
[Original article](https://clickhouse.tech/docs/en/operations/server_configuration_parameters/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/server_configuration_parameters/) <!--hide-->

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@ -1387,4 +1387,4 @@ To add an LDAP server as a remote user directory of users that are not defined l
</ldap>
```
[Original article](https://clickhouse.tech/docs/en/operations/server_configuration_parameters/settings/) <!--hide-->
[Original article](https://clickhouse.com/docs/en/operations/server_configuration_parameters/settings/) <!--hide-->

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