Merge branch 'master' into rabbitmq-allow-multiple-hosts

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@ -42,15 +42,12 @@ RUN apt-get update \
clang-tidy-10 \
clang-tidy-11 \
cmake \
cmake \
curl \
g++-9 \
gcc-9 \
gdb \
git \
gperf \
gperf \
intel-opencl-icd \
libicu-dev \
libreadline-dev \
lld-10 \
@ -61,10 +58,7 @@ RUN apt-get update \
llvm-11-dev \
moreutils \
ninja-build \
ocl-icd-libopencl1 \
opencl-headers \
pigz \
pixz \
rename \
tzdata \
--yes --no-install-recommends

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@ -35,9 +35,6 @@ RUN apt-get update \
libjemalloc-dev \
libmsgpack-dev \
libcurl4-openssl-dev \
opencl-headers \
ocl-icd-libopencl1 \
intel-opencl-icd \
unixodbc-dev \
odbcinst \
tzdata \

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@ -14,9 +14,7 @@ RUN apt-get --allow-unauthenticated update -y \
expect \
gdb \
gperf \
gperf \
heimdal-multidev \
intel-opencl-icd \
libboost-filesystem-dev \
libboost-iostreams-dev \
libboost-program-options-dev \
@ -50,9 +48,7 @@ RUN apt-get --allow-unauthenticated update -y \
moreutils \
ncdu \
netcat-openbsd \
ocl-icd-libopencl1 \
odbcinst \
opencl-headers \
openssl \
perl \
pigz \

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@ -33,47 +33,14 @@ sudo bash -c "$(wget -O - https://apt.llvm.org/llvm.sh)"
For other Linux distribution - check the availability of the [prebuild packages](https://releases.llvm.org/download.html) or build clang [from sources](https://clang.llvm.org/get_started.html).
#### Use clang-11 for Builds {#use-gcc-10-for-builds}
#### Use clang-11 for Builds
``` bash
$ export CC=clang-11
$ export CXX=clang++-11
```
### Install GCC 10 {#install-gcc-10}
We recommend building ClickHouse with clang-11, GCC-10 also supported, but it is not used for production builds.
If you want to use GCC-10 there are several ways to install it.
#### Install from Repository {#install-from-repository}
On Ubuntu 19.10 or newer:
$ sudo apt-get update
$ sudo apt-get install gcc-10 g++-10
#### Install from a PPA Package {#install-from-a-ppa-package}
On older Ubuntu:
``` bash
$ sudo apt-get install software-properties-common
$ sudo apt-add-repository ppa:ubuntu-toolchain-r/test
$ sudo apt-get update
$ sudo apt-get install gcc-10 g++-10
```
#### Install from Sources {#install-from-sources}
See [utils/ci/build-gcc-from-sources.sh](https://github.com/ClickHouse/ClickHouse/blob/master/utils/ci/build-gcc-from-sources.sh)
#### Use GCC 10 for Builds {#use-gcc-10-for-builds}
``` bash
$ export CC=gcc-10
$ export CXX=g++-10
```
Gcc can also be used though it is discouraged.
### Checkout ClickHouse Sources {#checkout-clickhouse-sources}

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@ -131,17 +131,18 @@ ClickHouse uses several external libraries for building. All of them do not need
## C++ Compiler {#c-compiler}
Compilers GCC starting from version 10 and Clang version 8 or above are supported for building ClickHouse.
Compilers Clang starting from version 11 is supported for building ClickHouse.
Official Yandex builds currently use GCC because it generates machine code of slightly better performance (yielding a difference of up to several percent according to our benchmarks). And Clang is more convenient for development usually. Though, our continuous integration (CI) platform runs checks for about a dozen of build combinations.
Clang should be used instead of gcc. Though, our continuous integration (CI) platform runs checks for about a dozen of build combinations.
To install GCC on Ubuntu run: `sudo apt install gcc g++`
On Ubuntu/Debian you can use the automatic installation script (check [official webpage](https://apt.llvm.org/))
Check the version of gcc: `gcc --version`. If it is below 10, then follow the instruction here: https://clickhouse.tech/docs/en/development/build/#install-gcc-10.
```bash
sudo bash -c "$(wget -O - https://apt.llvm.org/llvm.sh)"
```
Mac OS X build is supported only for Clang. Just run `brew install llvm`
Mac OS X build is also supported. Just run `brew install llvm`
If you decide to use Clang, you can also install `libc++` and `lld`, if you know what it is. Using `ccache` is also recommended.
## The Building Process {#the-building-process}
@ -152,14 +153,7 @@ Now that you are ready to build ClickHouse we recommend you to create a separate
You can have several different directories (build_release, build_debug, etc.) for different types of build.
While inside the `build` directory, configure your build by running CMake. Before the first run, you need to define environment variables that specify compiler (version 10 gcc compiler in this example).
Linux:
export CC=gcc-10 CXX=g++-10
cmake ..
Mac OS X:
While inside the `build` directory, configure your build by running CMake. Before the first run, you need to define environment variables that specify compiler.
export CC=clang CXX=clang++
cmake ..

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@ -701,7 +701,7 @@ But other things being equal, cross-platform or portable code is preferred.
**2.** Language: C++20 (see the list of available [C++20 features](https://en.cppreference.com/w/cpp/compiler_support#C.2B.2B20_features)).
**3.** Compiler: `gcc`. At this time (August 2020), the code is compiled using version 9.3. (It can also be compiled using `clang 8`.)
**3.** Compiler: `clang`. At this time (April 2021), the code is compiled using clang version 11. (It can also be compiled using `gcc` version 10, but it's untested and not suitable for production usage).
The standard library is used (`libc++`).
@ -711,7 +711,7 @@ The standard library is used (`libc++`).
The CPU instruction set is the minimum supported set among our servers. Currently, it is SSE 4.2.
**6.** Use `-Wall -Wextra -Werror` compilation flags.
**6.** Use `-Wall -Wextra -Werror` compilation flags. Also `-Weverything` is used with few exceptions.
**7.** Use static linking with all libraries except those that are difficult to connect to statically (see the output of the `ldd` command).

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@ -12,6 +12,7 @@ With this instruction you can run basic ClickHouse performance test on any serve
3. Copy the link to `clickhouse` binary for amd64 or aarch64.
4. ssh to the server and download it with wget:
```bash
# These links are outdated, please obtain the fresh link from the "commits" page.
# For amd64:
wget https://clickhouse-builds.s3.yandex.net/0/e29c4c3cc47ab2a6c4516486c1b77d57e7d42643/clickhouse_build_check/gcc-10_relwithdebuginfo_none_bundled_unsplitted_disable_False_binary/clickhouse
# For aarch64:

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@ -854,8 +854,6 @@ For example, when reading from a table, if it is possible to evaluate expression
Default value: the number of physical CPU cores.
If less than one SELECT query is normally run on a server at a time, set this parameter to a value slightly less than the actual number of processor cores.
For queries that are completed quickly because of a LIMIT, you can set a lower max_threads. For example, if the necessary number of entries are located in every block and max_threads = 8, then 8 blocks are retrieved, although it would have been enough to read just one.
The smaller the `max_threads` value, the less memory is consumed.

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@ -15,16 +15,16 @@ Columns:
- `node_name` ([String](../../sql-reference/data-types/string.md)) — Node name in ZooKeeper.
- `type` ([String](../../sql-reference/data-types/string.md)) — Type of the task in the queue, one of:
- `GET_PART` - Get the part from another replica.
- `ATTACH_PART` - Attach the part, possibly from our own replica (if found in `detached` folder).
You may think of it as a `GET_PART` with some optimisations as they're nearly identical.
- `MERGE_PARTS` - Merge the parts.
- `DROP_RANGE` - Delete the parts in the specified partition in the specified number range.
- `CLEAR_COLUMN` - NOTE: Deprecated. Drop specific column from specified partition.
- `CLEAR_INDEX` - NOTE: Deprecated. Drop specific index from specified partition.
- `REPLACE_RANGE` - Drop certain range of partitions and replace them by new ones
- `MUTATE_PART` - Apply one or several mutations to the part.
- `ALTER_METADATA` - Apply alter modification according to global /metadata and /columns paths
- `GET_PART` — Get the part from another replica.
- `ATTACH_PART` — Attach the part, possibly from our own replica (if found in the `detached` folder). You may think of it as a `GET_PART` with some optimizations as they're nearly identical.
- `MERGE_PARTS` Merge the parts.
- `DROP_RANGE` Delete the parts in the specified partition in the specified number range.
- `CLEAR_COLUMN` NOTE: Deprecated. Drop specific column from specified partition.
- `CLEAR_INDEX` NOTE: Deprecated. Drop specific index from specified partition.
- `REPLACE_RANGE` — Drop a certain range of parts and replace them with new ones.
- `MUTATE_PART` Apply one or several mutations to the part.
- `ALTER_METADATA` Apply alter modification according to global /metadata and /columns paths.
- `create_time` ([Datetime](../../sql-reference/data-types/datetime.md)) — Date and time when the task was submitted for execution.

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@ -88,12 +88,10 @@ Read more about setting the partition expression in a section [How to specify th
This query is replicated. The replica-initiator checks whether there is data in the `detached` directory.
If data exists, the query checks its integrity. If everything is correct, the query adds the data to the table.
If the non-initiator replica, receiving the attach command, finds the part with the correct checksums in its own
`detached` folder, it attaches the data without fetching it from other replicas.
If the non-initiator replica, receiving the attach command, finds the part with the correct checksums in its own `detached` folder, it attaches the data without fetching it from other replicas.
If there is no part with the correct checksums, the data is downloaded from any replica having the part.
You can put data to the `detached` directory on one replica and use the `ALTER ... ATTACH` query to add it to the
table on all replicas.
You can put data to the `detached` directory on one replica and use the `ALTER ... ATTACH` query to add it to the table on all replicas.
## ATTACH PARTITION FROM {#alter_attach-partition-from}
@ -101,8 +99,8 @@ table on all replicas.
ALTER TABLE table2 ATTACH PARTITION partition_expr FROM table1
```
This query copies the data partition from the `table1` to `table2`.
Note that data won't be deleted neither from `table1` nor from `table2`.
This query copies the data partition from `table1` to `table2`.
Note that data will be deleted neither from `table1` nor from `table2`.
For the query to run successfully, the following conditions must be met:

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@ -264,9 +264,7 @@ Wait until a `ReplicatedMergeTree` table will be synced with other replicas in a
SYSTEM SYNC REPLICA [db.]replicated_merge_tree_family_table_name
```
After running this statement the `[db.]replicated_merge_tree_family_table_name` fetches commands from
the common replicated log into its own replication queue, and then the query waits till the replica processes all
of the fetched commands.
After running this statement the `[db.]replicated_merge_tree_family_table_name` fetches commands from the common replicated log into its own replication queue, and then the query waits till the replica processes all of the fetched commands.
### RESTART REPLICA {#query_language-system-restart-replica}

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@ -19,28 +19,17 @@ $ sudo apt-get install git cmake python ninja-build
古いシステムではcmakeの代わりにcmake3。
## GCC9のインストール {#install-gcc-10}
## Clang 11 のインストール
これを行うにはいくつかの方法があります。
### PPAパッケージからインストール {#install-from-a-ppa-package}
On Ubuntu/Debian you can use the automatic installation script (check [official webpage](https://apt.llvm.org/))
```bash
$ sudo apt-get install software-properties-common
$ sudo apt-add-repository ppa:ubuntu-toolchain-r/test
$ sudo apt-get update
$ sudo apt-get install gcc-10 g++-10
sudo bash -c "$(wget -O - https://apt.llvm.org/llvm.sh)"
```
### ソースからインスト {#install-from-sources}
見て [utils/ci/build-gcc-from-sources.sh](https://github.com/ClickHouse/ClickHouse/blob/master/utils/ci/build-gcc-from-sources.sh)
## ビルドにGCC9を使用する {#use-gcc-10-for-builds}
``` bash
$ export CC=gcc-10
$ export CXX=g++-10
$ export CC=clang
$ export CXX=clang++
```
## ツつィツ姪"ツ債ツつケ {#checkout-clickhouse-sources}
@ -76,7 +65,7 @@ $ cd ..
- Gitソースをチェックアウトするためにのみ使用され、ビルドには必要ありません)
- CMake3.10以降
- 忍者(推奨)または作る
- C++コンパイラ:gcc9またはclang8以降
- C++コンパイラ:clang11以降
- リンカ:lldまたはgold(古典的なGNU ldは動作しません)
- Python(LLVMビルド内でのみ使用され、オプションです)

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@ -133,19 +133,19 @@ ArchまたはGentooを使用する場合は、おそらくCMakeのインスト
ClickHouseはビルドに複数の外部ライブラリを使用します。 それらのすべては、サブモジュールにあるソースからClickHouseと一緒に構築されているので、別々にインストールする必要はありません。 リストは次の場所で確認できます `contrib`.
# C++コンパイラ {#c-compiler}
## C++ Compiler {#c-compiler}
ClickHouseのビルドには、バージョン9以降のGCCとClangバージョン8以降のコンパイラがサポートされます。
Compilers Clang starting from version 11 is supported for building ClickHouse.
公式のYandexビルドは、わずかに優れたパフォーマンスのマシンコードを生成するため、GCCを使用しています私たちのベンチマークに応じて最大数パーセントの そしてClangは開発のために通常より便利です。 が、当社の継続的インテグレーションCI)プラットフォームを運チェックのための十数の組み合わせとなります。
Clang should be used instead of gcc. Though, our continuous integration (CI) platform runs checks for about a dozen of build combinations.
UBUNTUにGCCをインストールするには: `sudo apt install gcc g++`
On Ubuntu/Debian you can use the automatic installation script (check [official webpage](https://apt.llvm.org/))
Gccのバージョンを確認する: `gcc --version`. の場合は下記9その指示に従う。https://clickhouse.tech/docs/ja/development/build/#install-gcc-10.
```bash
sudo bash -c "$(wget -O - https://apt.llvm.org/llvm.sh)"
```
Mac OS XのビルドはClangでのみサポートされています。 ちょうど実行 `brew install llvm`
Clangを使用する場合は、次のものもインストールできます `libc++``lld` あなたがそれが何であるか知っていれば。 を使用して `ccache` また、推奨されます。
Mac OS X build is also supported. Just run `brew install llvm`
# 建築プロセス {#the-building-process}
@ -158,13 +158,6 @@ ClickHouseを構築する準備ができたので、別のディレクトリを
中の間 `build` cmakeを実行してビルドを構成します。 最初の実行の前に、コンパイラこの例ではバージョン9gccコンパイラを指定する環境変数を定義する必要があります。
Linux:
export CC=gcc-10 CXX=g++-10
cmake ..
Mac OS X:
export CC=clang CXX=clang++
cmake ..

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@ -136,18 +136,18 @@ ClickHouse использует для сборки некоторое коли
## Компилятор C++ {#kompiliator-c}
В качестве компилятора C++ поддерживается GCC начиная с версии 9 или Clang начиная с версии 8.
В качестве компилятора C++ поддерживается Clang начиная с версии 11.
Официальные сборки от Яндекса, на данный момент, используют GCC, так как он генерирует слегка более производительный машинный код (разница в среднем до нескольких процентов по нашим бенчмаркам). Clang обычно более удобен для разработки. Впрочем, наша среда continuous integration проверяет около десятка вариантов сборки.
Впрочем, наша среда continuous integration проверяет около десятка вариантов сборки, включая gcc, но сборка с помощью gcc непригодна для использования в продакшене.
Для установки GCC под Ubuntu, выполните: `sudo apt install gcc g++`.
On Ubuntu/Debian you can use the automatic installation script (check [official webpage](https://apt.llvm.org/))
Проверьте версию gcc: `gcc --version`. Если версия меньше 10, то следуйте инструкции: https://clickhouse.tech/docs/ru/development/build/#install-gcc-10.
```bash
sudo bash -c "$(wget -O - https://apt.llvm.org/llvm.sh)"
```
Сборка под Mac OS X поддерживается только для компилятора Clang. Чтобы установить его выполните `brew install llvm`
Если вы решили использовать Clang, вы также можете установить `libc++` и `lld`, если вы знаете, что это такое. При желании, установите `ccache`.
## Процесс сборки {#protsess-sborki}
Теперь вы готовы к сборке ClickHouse. Для размещения собранных файлов, рекомендуется создать отдельную директорию build внутри директории ClickHouse:
@ -158,14 +158,7 @@ ClickHouse использует для сборки некоторое коли
Вы можете иметь несколько разных директорий (build_release, build_debug) для разных вариантов сборки.
Находясь в директории build, выполните конфигурацию сборки с помощью CMake.
Перед первым запуском необходимо выставить переменные окружения, отвечающие за выбор компилятора (в данном примере это - gcc версии 9).
Linux:
export CC=gcc-10 CXX=g++-10
cmake ..
Mac OS X:
Перед первым запуском необходимо выставить переменные окружения, отвечающие за выбор компилятора.
export CC=clang CXX=clang++
cmake ..

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@ -780,7 +780,7 @@ The dictionary is configured incorrectly.
**2.** Язык - C++20 (см. список доступных [C++20 фич](https://en.cppreference.com/w/cpp/compiler_support#C.2B.2B20_features)).
**3.** Компилятор - `gcc`. На данный момент (август 2020), код собирается версией 9.3. (Также код может быть собран `clang` версий 10 и 9)
**3.** Компилятор - `clang`. На данный момент (апрель 2021), код собирается версией 11. (Также код может быть собран `gcc` версии 10, но такая сборка не тестируется и непригодна для продакшена).
Используется стандартная библиотека (реализация `libc++`).

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@ -844,8 +844,6 @@ SELECT type, query FROM system.query_log WHERE log_comment = 'log_comment test'
Значение по умолчанию: количество процессорных ядер без учёта Hyper-Threading.
Если на сервере обычно исполняется менее одного запроса SELECT одновременно, то выставите этот параметр в значение чуть меньше количества реальных процессорных ядер.
Для запросов, которые быстро завершаются из-за LIMIT-а, имеет смысл выставить max_threads поменьше. Например, если нужное количество записей находится в каждом блоке, то при max_threads = 8 будет считано 8 блоков, хотя достаточно было прочитать один.
Чем меньше `max_threads`, тем меньше будет использоваться оперативки.

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@ -14,7 +14,17 @@
- `node_name` ([String](../../sql-reference/data-types/string.md)) — имя узла в ZooKeeper.
- `type` ([String](../../sql-reference/data-types/string.md)) — тип задачи в очереди: `GET_PARTS`, `MERGE_PARTS`, `DETACH_PARTS`, `DROP_PARTS` или `MUTATE_PARTS`.
- `type` ([String](../../sql-reference/data-types/string.md)) — тип задачи в очереди:
- `GET_PART` — скачать кусок с другой реплики.
- `ATTACH_PART` — присоединить кусок. Задача может быть выполнена и с куском из нашей собственной реплики (если он находится в папке `detached`). Эта задача практически идентична задаче `GET_PART`, лишь немного оптимизирована.
- `MERGE_PARTS` — выполнить слияние кусков.
- `DROP_RANGE` — удалить куски в партициях из указнного диапазона.
- `CLEAR_COLUMN` — удалить указанный столбец из указанной партиции. Примечание: не используется с 20.4.
- `CLEAR_INDEX` — удалить указанный индекс из указанной партиции. Примечание: не используется с 20.4.
- `REPLACE_RANGE` — удалить указанный диапазон кусков и заменить их на новые.
- `MUTATE_PART` — применить одну или несколько мутаций к куску.
- `ALTER_METADATA` — применить изменения структуры таблицы в результате запросов с выражением `ALTER`.
- `create_time` ([Datetime](../../sql-reference/data-types/datetime.md)) — дата и время отправки задачи на выполнение.
@ -77,4 +87,3 @@ last_postpone_time: 1970-01-01 03:00:00
**Смотрите также**
- [Управление таблицами ReplicatedMergeTree](../../sql-reference/statements/system.md#query-language-system-replicated)

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@ -18,10 +18,12 @@ ClickHouse создает эту таблицу когда утсановлен
Во время соединения с сервером через `clickhouse-client`, вы видите строку похожую на `Connected to ClickHouse server version 19.18.1 revision 54429.`. Это поле содержит номер после `revision`, но не содержит строку после `version`.
- `timer_type`([Enum8](../../sql-reference/data-types/enum.md)) — тип таймера:
- `trace_type`([Enum8](../../sql-reference/data-types/enum.md)) — тип трассировки:
- `Real` означает wall-clock время.
- `CPU` означает относительное CPU время.
- `Real`сбор трассировок стека адресов вызова по времени wall-clock.
- `CPU`сбор трассировок стека адресов вызова по времени CPU.
- `Memory`сбор выделенной памяти, когда ее размер превышает относительный инкремент.
- `MemorySample`сбор случайно выделенной памяти.
- `thread_number`([UInt32](../../sql-reference/data-types/int-uint.md)) — идентификатор треда.

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@ -38,7 +38,7 @@ ALTER TABLE mt DETACH PART 'all_2_2_0';
После того как запрос будет выполнен, вы сможете производить любые операции с данными в директории `detached`. Например, можно удалить их из файловой системы.
Запрос реплицируется — данные будут перенесены в директорию `detached` и забыты на всех репликах. Обратите внимание, запрос может быть отправлен только на реплику-лидер. Чтобы узнать, является ли реплика лидером, выполните запрос `SELECT` к системной таблице [system.replicas](../../../operations/system-tables/replicas.md#system_tables-replicas). Либо можно выполнить запрос `DETACH` на всех репликах — тогда на всех репликах, кроме реплики-лидера, запрос вернет ошибку.
Запрос реплицируется — данные будут перенесены в директорию `detached` и забыты на всех репликах. Обратите внимание, запрос может быть отправлен только на реплику-лидер. Чтобы узнать, является ли реплика лидером, выполните запрос `SELECT` к системной таблице [system.replicas](../../../operations/system-tables/replicas.md#system_tables-replicas). Либо можно выполнить запрос `DETACH` на всех репликах — тогда на всех репликах, кроме реплик-лидеров (поскольку допускается несколько лидеров), запрос вернет ошибку.
## DROP PARTITION\|PART {#alter_drop-partition}
@ -83,9 +83,13 @@ ALTER TABLE visits ATTACH PART 201901_2_2_0;
Как корректно задать имя партиции или куска, см. в разделе [Как задавать имя партиции в запросах ALTER](#alter-how-to-specify-part-expr).
Этот запрос реплицируется. Реплика-иницатор проверяет, есть ли данные в директории `detached`. Если данные есть, то запрос проверяет их целостность. В случае успеха данные добавляются в таблицу. Все остальные реплики загружают данные с реплики-инициатора запроса.
Этот запрос реплицируется. Реплика-иницатор проверяет, есть ли данные в директории `detached`.
Если данные есть, то запрос проверяет их целостность. В случае успеха данные добавляются в таблицу.
Это означает, что вы можете разместить данные в директории `detached` на одной реплике и с помощью запроса `ALTER ... ATTACH` добавить их в таблицу на всех репликах.
Если реплика, не являющаяся инициатором запроса, получив команду присоединения, находит кусок с правильными контрольными суммами в своей собственной папке `detached`, она присоединяет данные, не скачивая их с других реплик.
Если нет куска с правильными контрольными суммами, данные загружаются из любой реплики, имеющей этот кусок.
Вы можете поместить данные в директорию `detached` на одной реплике и с помощью запроса `ALTER ... ATTACH` добавить их в таблицу на всех репликах.
## ATTACH PARTITION FROM {#alter_attach-partition-from}
@ -93,7 +97,8 @@ ALTER TABLE visits ATTACH PART 201901_2_2_0;
ALTER TABLE table2 ATTACH PARTITION partition_expr FROM table1
```
Копирует партицию из таблицы `table1` в таблицу `table2` и добавляет к существующим данным `table2`. Данные из `table1` не удаляются.
Копирует партицию из таблицы `table1` в таблицу `table2`.
Обратите внимание, что данные не удаляются ни из `table1`, ни из `table2`.
Следует иметь в виду:
@ -305,4 +310,3 @@ OPTIMIZE TABLE table_not_partitioned PARTITION tuple() FINAL;
`IN PARTITION` указывает на партицию, для которой применяются выражения [UPDATE](../../../sql-reference/statements/alter/update.md#alter-table-update-statements) или [DELETE](../../../sql-reference/statements/alter/delete.md#alter-mutations) в результате запроса `ALTER TABLE`. Новые куски создаются только в указанной партиции. Таким образом, `IN PARTITION` помогает снизить нагрузку, когда таблица разбита на множество партиций, а вам нужно обновить данные лишь точечно.
Примеры запросов `ALTER ... PARTITION` можно посмотреть в тестах: [`00502_custom_partitioning_local`](https://github.com/ClickHouse/ClickHouse/blob/master/tests/queries/0_stateless/00502_custom_partitioning_local.sql) и [`00502_custom_partitioning_replicated_zookeeper`](https://github.com/ClickHouse/ClickHouse/blob/master/tests/queries/0_stateless/00502_custom_partitioning_replicated_zookeeper.sql).

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@ -204,6 +204,7 @@ SYSTEM STOP MOVES [[db.]merge_tree_family_table_name]
ClickHouse может управлять фоновыми процессами связанными c репликацией в таблицах семейства [ReplicatedMergeTree](../../engines/table-engines/mergetree-family/replacingmergetree.md).
### STOP FETCHES {#query_language-system-stop-fetches}
Позволяет остановить фоновые процессы синхронизации новыми вставленными кусками данных с другими репликами в кластере для таблиц семейства `ReplicatedMergeTree`:
Всегда возвращает `Ok.` вне зависимости от типа таблицы и даже если таблица или база данных не существет.
@ -212,6 +213,7 @@ SYSTEM STOP FETCHES [[db.]replicated_merge_tree_family_table_name]
```
### START FETCHES {#query_language-system-start-fetches}
Позволяет запустить фоновые процессы синхронизации новыми вставленными кусками данных с другими репликами в кластере для таблиц семейства `ReplicatedMergeTree`:
Всегда возвращает `Ok.` вне зависимости от типа таблицы и даже если таблица или база данных не существет.
@ -220,6 +222,7 @@ SYSTEM START FETCHES [[db.]replicated_merge_tree_family_table_name]
```
### STOP REPLICATED SENDS {#query_language-system-start-replicated-sends}
Позволяет остановить фоновые процессы отсылки новых вставленных кусков данных другим репликам в кластере для таблиц семейства `ReplicatedMergeTree`:
``` sql
@ -227,6 +230,7 @@ SYSTEM STOP REPLICATED SENDS [[db.]replicated_merge_tree_family_table_name]
```
### START REPLICATED SENDS {#query_language-system-start-replicated-sends}
Позволяет запустить фоновые процессы отсылки новых вставленных кусков данных другим репликам в кластере для таблиц семейства `ReplicatedMergeTree`:
``` sql
@ -234,6 +238,7 @@ SYSTEM START REPLICATED SENDS [[db.]replicated_merge_tree_family_table_name]
```
### STOP REPLICATION QUEUES {#query_language-system-stop-replication-queues}
Останавливает фоновые процессы разбора заданий из очереди репликации которая хранится в Zookeeper для таблиц семейства `ReplicatedMergeTree`. Возможные типы заданий - merges, fetches, mutation, DDL запросы с ON CLUSTER:
``` sql
@ -241,6 +246,7 @@ SYSTEM STOP REPLICATION QUEUES [[db.]replicated_merge_tree_family_table_name]
```
### START REPLICATION QUEUES {#query_language-system-start-replication-queues}
Запускает фоновые процессы разбора заданий из очереди репликации которая хранится в Zookeeper для таблиц семейства `ReplicatedMergeTree`. Возможные типы заданий - merges, fetches, mutation, DDL запросы с ON CLUSTER:
``` sql
@ -248,20 +254,24 @@ SYSTEM START REPLICATION QUEUES [[db.]replicated_merge_tree_family_table_name]
```
### SYNC REPLICA {#query_language-system-sync-replica}
Ждет когда таблица семейства `ReplicatedMergeTree` будет синхронизирована с другими репликами в кластере, будет работать до достижения `receive_timeout`, если синхронизация для таблицы отключена в настоящий момент времени:
``` sql
SYSTEM SYNC REPLICA [db.]replicated_merge_tree_family_table_name
```
После выполнения этого запроса таблица `[db.]replicated_merge_tree_family_table_name` синхронизирует команды из общего реплицированного лога в свою собственную очередь репликации. Затем запрос ждет, пока реплика не обработает все синхронизированные команды.
### RESTART REPLICA {#query_language-system-restart-replica}
Реинициализация состояния Zookeeper сессий для таблицы семейства `ReplicatedMergeTree`, сравнивает текущее состояние с тем что хранится в Zookeeper как источник правды и добавляет задачи Zookeeper очередь если необходимо
Инициализация очереди репликации на основе данных ZooKeeper, происходит так же как при attach table. На короткое время таблица станет недоступной для любых операций.
Реинициализация состояния Zookeeper-сессий для таблицы семейства `ReplicatedMergeTree`. Сравнивает текущее состояние с тем, что хранится в Zookeeper, как источник правды, и добавляет задачи в очередь репликации в Zookeeper, если необходимо.
Инициализация очереди репликации на основе данных ZooKeeper происходит так же, как при attach table. На короткое время таблица станет недоступной для любых операций.
``` sql
SYSTEM RESTART REPLICA [db.]replicated_merge_tree_family_table_name
```
### RESTART REPLICAS {#query_language-system-restart-replicas}
Реинициализация состояния Zookeeper сессий для всех `ReplicatedMergeTree` таблиц, сравнивает текущее состояние с тем что хранится в Zookeeper как источник правды и добавляет задачи Zookeeper очередь если необходимо
Реинициализация состояния ZooKeeper-сессий для всех `ReplicatedMergeTree` таблиц. Сравнивает текущее состояние реплики с тем, что хранится в ZooKeeper, как c источником правды, и добавляет задачи в очередь репликации в ZooKeeper, если необходимо.

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@ -35,28 +35,12 @@ sudo apt-get install git cmake ninja-build
或cmake3而不是旧系统上的cmake。
或者在早期版本的系统中用 cmake3 替代 cmake
## 安装 GCC 10 {#an-zhuang-gcc-10}
## 安装 Clang
有几种方法可以做到这一点。
### 安装 PPA 包 {#an-zhuang-ppa-bao}
On Ubuntu/Debian you can use the automatic installation script (check [official webpage](https://apt.llvm.org/))
```bash
sudo apt-get install software-properties-common
sudo apt-add-repository ppa:ubuntu-toolchain-r/test
sudo apt-get update
sudo apt-get install gcc-10 g++-10
```
### 源码安装 gcc {#yuan-ma-an-zhuang-gcc}
请查看 [utils/ci/build-gcc-from-sources.sh](https://github.com/ClickHouse/ClickHouse/blob/master/utils/ci/build-gcc-from-sources.sh)
## 使用 GCC 10 来编译 {#shi-yong-gcc-10-lai-bian-yi}
``` bash
export CC=gcc-10
export CXX=g++-10
sudo bash -c "$(wget -O - https://apt.llvm.org/llvm.sh)"
```
## 拉取 ClickHouse 源码 {#la-qu-clickhouse-yuan-ma-1}

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@ -123,17 +123,13 @@ ClickHouse使用多个外部库进行构建。大多数外部库不需要单独
# C++ 编译器 {#c-bian-yi-qi}
GCC编译器从版本9开始以及Clang版本\>=8都可支持构建ClickHouse。
We support clang starting from version 11.
Yandex官方当前使用GCC构建ClickHouse因为它生成的机器代码性能较好根据测评最多可以相差几个百分点。Clang通常可以更加便捷的开发。我们的持续集成CI平台会运行大约十二种构建组合的检查。
On Ubuntu/Debian you can use the automatic installation script (check [official webpage](https://apt.llvm.org/))
在Ubuntu上安装GCC请执行`sudo apt install gcc g++`
请使用`gcc --version`查看gcc的版本。如果gcc版本低于9请参考此处的指示https://clickhouse.tech/docs/zh/development/build/#an-zhuang-gcc-10 。
在Mac OS X上安装GCC请执行`brew install gcc`
如果您决定使用Clang还可以同时安装 `libc++`以及`lld`,前提是您也熟悉它们。此外,也推荐使用`ccache`。
```bash
sudo bash -c "$(wget -O - https://apt.llvm.org/llvm.sh)"
```
# 构建的过程 {#gou-jian-de-guo-cheng}
@ -146,7 +142,7 @@ Yandex官方当前使用GCC构建ClickHouse因为它生成的机器代码性
在`build`目录下通过运行CMake配置构建。 在第一次运行之前请定义用于指定编译器的环境变量本示例中为gcc 9 编译器)。
export CC=gcc-10 CXX=g++-10
export CC=clang CXX=clang++
cmake ..
`CC`变量指代C的编译器C Compiler的缩写而`CXX`变量指代要使用哪个C++编译器进行编译。

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@ -696,7 +696,7 @@ auto s = std::string{"Hello"};
**2.** 语言: C++20.
**3.** 编译器: `gcc`。 此时2020年08月代码使用9.3版编译。(它也可以使用`clang 8` 编译
**3.** 编译器: `clang`。 此时2021年03月代码使用11版编译。它也可以使用`gcc` 编译 but it is not suitable for production
使用标准库 (`libc++`)。

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@ -361,6 +361,7 @@ inline bool isDecimal(const DataTypePtr & data_type) { return WhichDataType(data
inline bool isTuple(const DataTypePtr & data_type) { return WhichDataType(data_type).isTuple(); }
inline bool isArray(const DataTypePtr & data_type) { return WhichDataType(data_type).isArray(); }
inline bool isMap(const DataTypePtr & data_type) { return WhichDataType(data_type).isMap(); }
inline bool isNothing(const DataTypePtr & data_type) { return WhichDataType(data_type).isNothing(); }
template <typename T>
inline bool isUInt8(const T & data_type)

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@ -2496,7 +2496,7 @@ private:
}
}
WrapperType createArrayWrapper(const DataTypePtr & from_type_untyped, const DataTypeArray * to_type) const
WrapperType createArrayWrapper(const DataTypePtr & from_type_untyped, const DataTypeArray & to_type) const
{
/// Conversion from String through parsing.
if (checkAndGetDataType<DataTypeString>(from_type_untyped.get()))
@ -2507,24 +2507,23 @@ private:
};
}
DataTypePtr from_nested_type;
DataTypePtr to_nested_type;
const auto * from_type = checkAndGetDataType<DataTypeArray>(from_type_untyped.get());
/// get the most nested type
if (from_type && to_type)
if (!from_type)
{
from_nested_type = from_type->getNestedType();
to_nested_type = to_type->getNestedType();
from_type = checkAndGetDataType<DataTypeArray>(from_nested_type.get());
to_type = checkAndGetDataType<DataTypeArray>(to_nested_type.get());
throw Exception(ErrorCodes::TYPE_MISMATCH,
"CAST AS Array can only be perforamed between same-dimensional Array or String types");
}
/// both from_type and to_type should be nullptr now is array types had same dimensions
if ((from_type == nullptr) != (to_type == nullptr))
throw Exception{"CAST AS Array can only be performed between same-dimensional array types or from String",
ErrorCodes::TYPE_MISMATCH};
DataTypePtr from_nested_type = from_type->getNestedType();
/// In query SELECT CAST([] AS Array(Array(String))) from type is Array(Nothing)
bool from_empty_array = isNothing(from_nested_type);
if (from_type->getNumberOfDimensions() != to_type.getNumberOfDimensions() && !from_empty_array)
throw Exception(ErrorCodes::TYPE_MISMATCH,
"CAST AS Array can only be perforamed between same-dimensional array types");
const DataTypePtr & to_nested_type = to_type.getNestedType();
/// Prepare nested type conversion
const auto nested_function = prepareUnpackDictionaries(from_nested_type, to_nested_type);
@ -3090,14 +3089,12 @@ private:
return createStringWrapper(from_type);
case TypeIndex::FixedString:
return createFixedStringWrapper(from_type, checkAndGetDataType<DataTypeFixedString>(to_type.get())->getN());
case TypeIndex::Array:
return createArrayWrapper(from_type, checkAndGetDataType<DataTypeArray>(to_type.get()));
return createArrayWrapper(from_type, static_cast<const DataTypeArray &>(*to_type));
case TypeIndex::Tuple:
return createTupleWrapper(from_type, checkAndGetDataType<DataTypeTuple>(to_type.get()));
case TypeIndex::Map:
return createMapWrapper(from_type, checkAndGetDataType<DataTypeMap>(to_type.get()));
case TypeIndex::AggregateFunction:
return createAggregateFunctionWrapper(from_type, checkAndGetDataType<DataTypeAggregateFunction>(to_type.get()));
default:

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@ -24,7 +24,6 @@ namespace ErrorCodes
ArrowBlockInputFormat::ArrowBlockInputFormat(ReadBuffer & in_, const Block & header_, bool stream_)
: IInputFormat(header_, in_), stream{stream_}
{
prepareReader();
}
Chunk ArrowBlockInputFormat::generate()
@ -35,12 +34,18 @@ Chunk ArrowBlockInputFormat::generate()
if (stream)
{
if (!stream_reader)
prepareReader();
batch_result = stream_reader->Next();
if (batch_result.ok() && !(*batch_result))
return res;
}
else
{
if (!file_reader)
prepareReader();
if (record_batch_current >= record_batch_total)
return res;
@ -71,7 +76,7 @@ void ArrowBlockInputFormat::resetParser()
stream_reader.reset();
else
file_reader.reset();
prepareReader();
record_batch_current = 0;
}
void ArrowBlockInputFormat::prepareReader()

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@ -12,7 +12,16 @@ namespace DB
class Context;
/** Base class for system tables whose all columns have String type.
/** IStorageSystemOneBlock is base class for system tables whose all columns can be synchronously fetched.
*
* Client class need to provide static method static NamesAndTypesList getNamesAndTypes() that will return list of column names and
* their types. IStorageSystemOneBlock during read will create result columns in same order as result of getNamesAndTypes
* and pass it with fillData method.
*
* Client also must override fillData and fill result columns.
*
* If subclass want to support virtual columns, it should override getVirtuals method of IStorage interface.
* IStorageSystemOneBlock will add virtuals columns at the end of result columns of fillData method.
*/
template <typename Self>
class IStorageSystemOneBlock : public IStorage
@ -41,9 +50,10 @@ public:
size_t /*max_block_size*/,
unsigned /*num_streams*/) override
{
metadata_snapshot->check(column_names, getVirtuals(), getStorageID());
auto virtuals_names_and_types = getVirtuals();
metadata_snapshot->check(column_names, virtuals_names_and_types, getStorageID());
Block sample_block = metadata_snapshot->getSampleBlock();
Block sample_block = metadata_snapshot->getSampleBlockWithVirtuals(virtuals_names_and_types);
MutableColumns res_columns = sample_block.cloneEmptyColumns();
fillData(res_columns, context, query_info);

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@ -50,6 +50,13 @@ NamesAndTypesList StorageSystemDictionaries::getNamesAndTypes()
};
}
NamesAndTypesList StorageSystemDictionaries::getVirtuals() const
{
return {
{"key", std::make_shared<DataTypeString>()}
};
}
void StorageSystemDictionaries::fillData(MutableColumns & res_columns, ContextPtr context, const SelectQueryInfo & /*query_info*/) const
{
const auto access = context->getAccess();
@ -128,6 +135,9 @@ void StorageSystemDictionaries::fillData(MutableColumns & res_columns, ContextPt
else
res_columns[i++]->insertDefault();
/// Start fill virtual columns
res_columns[i++]->insert(dictionary_structure.getKeyDescription());
}
}

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@ -18,6 +18,8 @@ public:
static NamesAndTypesList getNamesAndTypes();
NamesAndTypesList getVirtuals() const override;
protected:
using IStorageSystemOneBlock::IStorageSystemOneBlock;

File diff suppressed because one or more lines are too long

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@ -0,0 +1,2 @@
[]
[]

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@ -0,0 +1,2 @@
SELECT CAST([] AS Array(Array(String)));
SELECT CAST([] AS Array(Array(Array(String))));

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@ -0,0 +1,4 @@
simple key
example_simple_key_dictionary UInt64
complex key
example_complex_key_dictionary (UInt64, String)

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@ -0,0 +1,26 @@
DROP DICTIONARY IF EXISTS example_simple_key_dictionary;
CREATE DICTIONARY example_simple_key_dictionary (
id UInt64,
value UInt64
)
PRIMARY KEY id
SOURCE(CLICKHOUSE(HOST 'localhost' PORT tcpPort() USER 'default' TABLE '' DATABASE currentDatabase()))
LAYOUT(DIRECT());
SELECT 'simple key';
SELECT name, key FROM system.dictionaries WHERE name='example_simple_key_dictionary' AND database=currentDatabase();
DROP DICTIONARY IF EXISTS example_complex_key_dictionary;
CREATE DICTIONARY example_complex_key_dictionary (
id UInt64,
id_key String,
value UInt64
)
PRIMARY KEY id, id_key
SOURCE(CLICKHOUSE(HOST 'localhost' PORT tcpPort() USER 'default' TABLE '' DATABASE currentDatabase()))
LAYOUT(COMPLEX_KEY_DIRECT());
SELECT 'complex key';
SELECT name, key FROM system.dictionaries WHERE name='example_complex_key_dictionary' AND database=currentDatabase();

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@ -0,0 +1,16 @@
<yandex>
<logger>
<level>trace</level>
<log>/var/log/clickhouse-server/log.log</log>
<errorlog>/var/log/clickhouse-server/log.err.log</errorlog>
<size>1000M</size>
<count>10</count>
<stderr>/var/log/clickhouse-server/stderr.log</stderr>
<stdout>/var/log/clickhouse-server/stdout.log</stdout>
</logger>
<part_log>
<database>system</database>
<table>part_log</table>
<flush_interval_milliseconds>500</flush_interval_milliseconds>
</part_log>
</yandex>

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@ -0,0 +1,42 @@
<?xml version="1.0"?>
<yandex>
<remote_servers>
<replicated_cluster>
<shard>
<internal_replication>true</internal_replication>
<replica>
<host>clickhouse1</host>
<port>9000</port>
</replica>
<replica>
<host>clickhouse2</host>
<port>9000</port>
</replica>
<replica>
<host>clickhouse3</host>
<port>9000</port>
</replica>
</shard>
</replicated_cluster>
<sharded_cluster>
<shard>
<replica>
<host>clickhouse1</host>
<port>9000</port>
</replica>
</shard>
<shard>
<replica>
<host>clickhouse2</host>
<port>9000</port>
</replica>
</shard>
<shard>
<replica>
<host>clickhouse3</host>
<port>9000</port>
</replica>
</shard>
</sharded_cluster>
</remote_servers>
</yandex>

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@ -0,0 +1,10 @@
<?xml version="1.0"?>
<yandex>
<zookeeper>
<node index="1">
<host>zookeeper</host>
<port>2181</port>
</node>
<session_timeout_ms>15000</session_timeout_ms>
</zookeeper>
</yandex>

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@ -0,0 +1,448 @@
<?xml version="1.0"?>
<!--
NOTE: User and query level settings are set up in "users.xml" file.
-->
<yandex>
<logger>
<!-- Possible levels: https://github.com/pocoproject/poco/blob/develop/Foundation/include/Poco/Logger.h#L105 -->
<level>trace</level>
<log>/var/log/clickhouse-server/clickhouse-server.log</log>
<errorlog>/var/log/clickhouse-server/clickhouse-server.err.log</errorlog>
<size>1000M</size>
<count>10</count>
<!-- <console>1</console> --> <!-- Default behavior is autodetection (log to console if not daemon mode and is tty) -->
</logger>
<!--display_name>production</display_name--> <!-- It is the name that will be shown in the client -->
<http_port>8123</http_port>
<tcp_port>9000</tcp_port>
<!-- For HTTPS and SSL over native protocol. -->
<!--
<https_port>8443</https_port>
<tcp_port_secure>9440</tcp_port_secure>
-->
<!-- Used with https_port and tcp_port_secure. Full ssl options list: https://github.com/ClickHouse-Extras/poco/blob/master/NetSSL_OpenSSL/include/Poco/Net/SSLManager.h#L71 -->
<openSSL>
<server> <!-- Used for https server AND secure tcp port -->
<!-- openssl req -subj "/CN=localhost" -new -newkey rsa:2048 -days 365 -nodes -x509 -keyout /etc/clickhouse-server/server.key -out /etc/clickhouse-server/server.crt -->
<certificateFile>/etc/clickhouse-server/server.crt</certificateFile>
<privateKeyFile>/etc/clickhouse-server/server.key</privateKeyFile>
<!-- openssl dhparam -out /etc/clickhouse-server/dhparam.pem 4096 -->
<dhParamsFile>/etc/clickhouse-server/dhparam.pem</dhParamsFile>
<verificationMode>none</verificationMode>
<loadDefaultCAFile>true</loadDefaultCAFile>
<cacheSessions>true</cacheSessions>
<disableProtocols>sslv2,sslv3</disableProtocols>
<preferServerCiphers>true</preferServerCiphers>
</server>
<client> <!-- Used for connecting to https dictionary source -->
<loadDefaultCAFile>true</loadDefaultCAFile>
<cacheSessions>true</cacheSessions>
<disableProtocols>sslv2,sslv3</disableProtocols>
<preferServerCiphers>true</preferServerCiphers>
<!-- Use for self-signed: <verificationMode>none</verificationMode> -->
<invalidCertificateHandler>
<!-- Use for self-signed: <name>AcceptCertificateHandler</name> -->
<name>RejectCertificateHandler</name>
</invalidCertificateHandler>
</client>
</openSSL>
<!-- Default root page on http[s] server. For example load UI from https://tabix.io/ when opening http://localhost:8123 -->
<!--
<http_server_default_response><![CDATA[<html ng-app="SMI2"><head><base href="http://ui.tabix.io/"></head><body><div ui-view="" class="content-ui"></div><script src="http://loader.tabix.io/master.js"></script></body></html>]]></http_server_default_response>
-->
<!-- Port for communication between replicas. Used for data exchange. -->
<interserver_http_port>9009</interserver_http_port>
<!-- Hostname that is used by other replicas to request this server.
If not specified, than it is determined analoguous to 'hostname -f' command.
This setting could be used to switch replication to another network interface.
-->
<!--
<interserver_http_host>example.yandex.ru</interserver_http_host>
-->
<!-- Listen specified host. use :: (wildcard IPv6 address), if you want to accept connections both with IPv4 and IPv6 from everywhere. -->
<!-- <listen_host>::</listen_host> -->
<!-- Same for hosts with disabled ipv6: -->
<listen_host>0.0.0.0</listen_host>
<!-- Default values - try listen localhost on ipv4 and ipv6: -->
<!--
<listen_host>::1</listen_host>
<listen_host>127.0.0.1</listen_host>
-->
<!-- Don't exit if ipv6 or ipv4 unavailable, but listen_host with this protocol specified -->
<!-- <listen_try>0</listen_try> -->
<!-- Allow listen on same address:port -->
<!-- <listen_reuse_port>0</listen_reuse_port> -->
<!-- <listen_backlog>64</listen_backlog> -->
<max_connections>4096</max_connections>
<keep_alive_timeout>3</keep_alive_timeout>
<!-- Maximum number of concurrent queries. -->
<max_concurrent_queries>100</max_concurrent_queries>
<!-- Set limit on number of open files (default: maximum). This setting makes sense on Mac OS X because getrlimit() fails to retrieve
correct maximum value. -->
<!-- <max_open_files>262144</max_open_files> -->
<!-- Size of cache of uncompressed blocks of data, used in tables of MergeTree family.
In bytes. Cache is single for server. Memory is allocated only on demand.
Cache is used when 'use_uncompressed_cache' user setting turned on (off by default).
Uncompressed cache is advantageous only for very short queries and in rare cases.
-->
<uncompressed_cache_size>8589934592</uncompressed_cache_size>
<!-- Approximate size of mark cache, used in tables of MergeTree family.
In bytes. Cache is single for server. Memory is allocated only on demand.
You should not lower this value.
-->
<mark_cache_size>5368709120</mark_cache_size>
<!-- Path to data directory, with trailing slash. -->
<path>/var/lib/clickhouse/</path>
<!-- Path to temporary data for processing hard queries. -->
<tmp_path>/var/lib/clickhouse/tmp/</tmp_path>
<!-- Directory with user provided files that are accessible by 'file' table function. -->
<user_files_path>/var/lib/clickhouse/user_files/</user_files_path>
<!-- Path to folder where users and roles created by SQL commands are stored. -->
<access_control_path>/var/lib/clickhouse/access/</access_control_path>
<!-- Sources to read users, roles, access rights, profiles of settings, quotas. -->
<user_directories>
<users_xml>
<!-- Path to configuration file with predefined users. -->
<path>users.xml</path>
</users_xml>
<local_directory>
<!-- Path to folder where users created by SQL commands are stored. -->
<path>/var/lib/clickhouse/access/</path>
</local_directory>
</user_directories>
<!-- Path to configuration file with users, access rights, profiles of settings, quotas. -->
<users_config>users.xml</users_config>
<!-- Default profile of settings. -->
<default_profile>default</default_profile>
<!-- System profile of settings. This settings are used by internal processes (Buffer storage, Distibuted DDL worker and so on). -->
<!-- <system_profile>default</system_profile> -->
<!-- Default database. -->
<default_database>default</default_database>
<!-- Server time zone could be set here.
Time zone is used when converting between String and DateTime types,
when printing DateTime in text formats and parsing DateTime from text,
it is used in date and time related functions, if specific time zone was not passed as an argument.
Time zone is specified as identifier from IANA time zone database, like UTC or Africa/Abidjan.
If not specified, system time zone at server startup is used.
Please note, that server could display time zone alias instead of specified name.
Example: W-SU is an alias for Europe/Moscow and Zulu is an alias for UTC.
-->
<!-- <timezone>Europe/Moscow</timezone> -->
<!-- You can specify umask here (see "man umask"). Server will apply it on startup.
Number is always parsed as octal. Default umask is 027 (other users cannot read logs, data files, etc; group can only read).
-->
<!-- <umask>022</umask> -->
<!-- Perform mlockall after startup to lower first queries latency
and to prevent clickhouse executable from being paged out under high IO load.
Enabling this option is recommended but will lead to increased startup time for up to a few seconds.
-->
<mlock_executable>false</mlock_executable>
<!-- Configuration of clusters that could be used in Distributed tables.
https://clickhouse.yandex/docs/en/table_engines/distributed/
-->
<remote_servers incl="clickhouse_remote_servers" >
<!-- Test only shard config for testing distributed storage -->
<test_shard_localhost>
<shard>
<replica>
<host>localhost</host>
<port>9000</port>
</replica>
</shard>
</test_shard_localhost>
<test_cluster_two_shards_localhost>
<shard>
<replica>
<host>localhost</host>
<port>9000</port>
</replica>
</shard>
<shard>
<replica>
<host>localhost</host>
<port>9000</port>
</replica>
</shard>
</test_cluster_two_shards_localhost>
<test_shard_localhost_secure>
<shard>
<replica>
<host>localhost</host>
<port>9440</port>
<secure>1</secure>
</replica>
</shard>
</test_shard_localhost_secure>
<test_unavailable_shard>
<shard>
<replica>
<host>localhost</host>
<port>9000</port>
</replica>
</shard>
<shard>
<replica>
<host>localhost</host>
<port>1</port>
</replica>
</shard>
</test_unavailable_shard>
</remote_servers>
<!-- If element has 'incl' attribute, then for it's value will be used corresponding substitution from another file.
By default, path to file with substitutions is /etc/metrika.xml. It could be changed in config in 'include_from' element.
Values for substitutions are specified in /yandex/name_of_substitution elements in that file.
-->
<!-- ZooKeeper is used to store metadata about replicas, when using Replicated tables.
Optional. If you don't use replicated tables, you could omit that.
See https://clickhouse.yandex/docs/en/table_engines/replication/
-->
<zookeeper incl="zookeeper-servers" optional="true" />
<!-- Substitutions for parameters of replicated tables.
Optional. If you don't use replicated tables, you could omit that.
See https://clickhouse.yandex/docs/en/table_engines/replication/#creating-replicated-tables
-->
<macros incl="macros" optional="true" />
<!-- Reloading interval for embedded dictionaries, in seconds. Default: 3600. -->
<builtin_dictionaries_reload_interval>3600</builtin_dictionaries_reload_interval>
<!-- Maximum session timeout, in seconds. Default: 3600. -->
<max_session_timeout>3600</max_session_timeout>
<!-- Default session timeout, in seconds. Default: 60. -->
<default_session_timeout>60</default_session_timeout>
<!-- Sending data to Graphite for monitoring. Several sections can be defined. -->
<!--
interval - send every X second
root_path - prefix for keys
hostname_in_path - append hostname to root_path (default = true)
metrics - send data from table system.metrics
events - send data from table system.events
asynchronous_metrics - send data from table system.asynchronous_metrics
-->
<!--
<graphite>
<host>localhost</host>
<port>42000</port>
<timeout>0.1</timeout>
<interval>60</interval>
<root_path>one_min</root_path>
<hostname_in_path>true</hostname_in_path>
<metrics>true</metrics>
<events>true</events>
<asynchronous_metrics>true</asynchronous_metrics>
</graphite>
<graphite>
<host>localhost</host>
<port>42000</port>
<timeout>0.1</timeout>
<interval>1</interval>
<root_path>one_sec</root_path>
<metrics>true</metrics>
<events>true</events>
<asynchronous_metrics>false</asynchronous_metrics>
</graphite>
-->
<!-- Query log. Used only for queries with setting log_queries = 1. -->
<query_log>
<!-- What table to insert data. If table is not exist, it will be created.
When query log structure is changed after system update,
then old table will be renamed and new table will be created automatically.
-->
<database>system</database>
<table>query_log</table>
<!--
PARTITION BY expr https://clickhouse.yandex/docs/en/table_engines/custom_partitioning_key/
Example:
event_date
toMonday(event_date)
toYYYYMM(event_date)
toStartOfHour(event_time)
-->
<partition_by>toYYYYMM(event_date)</partition_by>
<!-- Interval of flushing data. -->
<flush_interval_milliseconds>7500</flush_interval_milliseconds>
</query_log>
<!-- Trace log. Stores stack traces collected by query profilers.
See query_profiler_real_time_period_ns and query_profiler_cpu_time_period_ns settings. -->
<trace_log>
<database>system</database>
<table>trace_log</table>
<partition_by>toYYYYMM(event_date)</partition_by>
<flush_interval_milliseconds>7500</flush_interval_milliseconds>
</trace_log>
<!-- Query thread log. Has information about all threads participated in query execution.
Used only for queries with setting log_query_threads = 1. -->
<query_thread_log>
<database>system</database>
<table>query_thread_log</table>
<partition_by>toYYYYMM(event_date)</partition_by>
<flush_interval_milliseconds>7500</flush_interval_milliseconds>
</query_thread_log>
<!-- Uncomment if use part log.
Part log contains information about all actions with parts in MergeTree tables (creation, deletion, merges, downloads).
<part_log>
<database>system</database>
<table>part_log</table>
<flush_interval_milliseconds>7500</flush_interval_milliseconds>
</part_log>
-->
<!-- Uncomment to write text log into table.
Text log contains all information from usual server log but stores it in structured and efficient way.
<text_log>
<database>system</database>
<table>text_log</table>
<flush_interval_milliseconds>7500</flush_interval_milliseconds>
</text_log>
-->
<!-- Parameters for embedded dictionaries, used in Yandex.Metrica.
See https://clickhouse.yandex/docs/en/dicts/internal_dicts/
-->
<!-- Path to file with region hierarchy. -->
<!-- <path_to_regions_hierarchy_file>/opt/geo/regions_hierarchy.txt</path_to_regions_hierarchy_file> -->
<!-- Path to directory with files containing names of regions -->
<!-- <path_to_regions_names_files>/opt/geo/</path_to_regions_names_files> -->
<!-- Configuration of external dictionaries. See:
https://clickhouse.yandex/docs/en/dicts/external_dicts/
-->
<dictionaries_config>*_dictionary.xml</dictionaries_config>
<!-- Uncomment if you want data to be compressed 30-100% better.
Don't do that if you just started using ClickHouse.
-->
<compression incl="clickhouse_compression">
<!--
<!- - Set of variants. Checked in order. Last matching case wins. If nothing matches, lz4 will be used. - ->
<case>
<!- - Conditions. All must be satisfied. Some conditions may be omitted. - ->
<min_part_size>10000000000</min_part_size> <!- - Min part size in bytes. - ->
<min_part_size_ratio>0.01</min_part_size_ratio> <!- - Min size of part relative to whole table size. - ->
<!- - What compression method to use. - ->
<method>zstd</method>
</case>
-->
</compression>
<!-- Allow to execute distributed DDL queries (CREATE, DROP, ALTER, RENAME) on cluster.
Works only if ZooKeeper is enabled. Comment it if such functionality isn't required. -->
<distributed_ddl>
<!-- Path in ZooKeeper to queue with DDL queries -->
<path>/clickhouse/task_queue/ddl</path>
<!-- Settings from this profile will be used to execute DDL queries -->
<!-- <profile>default</profile> -->
</distributed_ddl>
<!-- Settings to fine tune MergeTree tables. See documentation in source code, in MergeTreeSettings.h -->
<!--
<merge_tree>
<max_suspicious_broken_parts>5</max_suspicious_broken_parts>
</merge_tree>
-->
<!-- Protection from accidental DROP.
If size of a MergeTree table is greater than max_table_size_to_drop (in bytes) than table could not be dropped with any DROP query.
If you want do delete one table and don't want to restart clickhouse-server, you could create special file <clickhouse-path>/flags/force_drop_table and make DROP once.
By default max_table_size_to_drop is 50GB; max_table_size_to_drop=0 allows to DROP any tables.
The same for max_partition_size_to_drop.
Uncomment to disable protection.
-->
<!-- <max_table_size_to_drop>0</max_table_size_to_drop> -->
<!-- <max_partition_size_to_drop>0</max_partition_size_to_drop> -->
<!-- Example of parameters for GraphiteMergeTree table engine -->
<graphite_rollup_example>
<pattern>
<regexp>click_cost</regexp>
<function>any</function>
<retention>
<age>0</age>
<precision>3600</precision>
</retention>
<retention>
<age>86400</age>
<precision>60</precision>
</retention>
</pattern>
<default>
<function>max</function>
<retention>
<age>0</age>
<precision>60</precision>
</retention>
<retention>
<age>3600</age>
<precision>300</precision>
</retention>
<retention>
<age>86400</age>
<precision>3600</precision>
</retention>
</default>
</graphite_rollup_example>
<!-- Directory in <clickhouse-path> containing schema files for various input formats.
The directory will be created if it doesn't exist.
-->
<format_schema_path>/var/lib/clickhouse/format_schemas/</format_schema_path>
<!-- Uncomment to disable ClickHouse internal DNS caching. -->
<!-- <disable_internal_dns_cache>1</disable_internal_dns_cache> -->
</yandex>

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<?xml version="1.0"?>
<yandex>
<!-- Profiles of settings. -->
<profiles>
<!-- Default settings. -->
<default>
<!-- Maximum memory usage for processing single query, in bytes. -->
<max_memory_usage>10000000000</max_memory_usage>
<!-- Use cache of uncompressed blocks of data. Meaningful only for processing many of very short queries. -->
<use_uncompressed_cache>0</use_uncompressed_cache>
<!-- How to choose between replicas during distributed query processing.
random - choose random replica from set of replicas with minimum number of errors
nearest_hostname - from set of replicas with minimum number of errors, choose replica
with minimum number of different symbols between replica's hostname and local hostname
(Hamming distance).
in_order - first live replica is chosen in specified order.
first_or_random - if first replica one has higher number of errors, pick a random one from replicas with minimum number of errors.
-->
<load_balancing>random</load_balancing>
</default>
<!-- Profile that allows only read queries. -->
<readonly>
<readonly>1</readonly>
</readonly>
</profiles>
<!-- Users and ACL. -->
<users>
<!-- If user name was not specified, 'default' user is used. -->
<default>
<!-- Password could be specified in plaintext or in SHA256 (in hex format).
If you want to specify password in plaintext (not recommended), place it in 'password' element.
Example: <password>qwerty</password>.
Password could be empty.
If you want to specify SHA256, place it in 'password_sha256_hex' element.
Example: <password_sha256_hex>65e84be33532fb784c48129675f9eff3a682b27168c0ea744b2cf58ee02337c5</password_sha256_hex>
Restrictions of SHA256: impossibility to connect to ClickHouse using MySQL JS client (as of July 2019).
If you want to specify double SHA1, place it in 'password_double_sha1_hex' element.
Example: <password_double_sha1_hex>e395796d6546b1b65db9d665cd43f0e858dd4303</password_double_sha1_hex>
How to generate decent password:
Execute: PASSWORD=$(base64 < /dev/urandom | head -c8); echo "$PASSWORD"; echo -n "$PASSWORD" | sha256sum | tr -d '-'
In first line will be password and in second - corresponding SHA256.
How to generate double SHA1:
Execute: PASSWORD=$(base64 < /dev/urandom | head -c8); echo "$PASSWORD"; echo -n "$PASSWORD" | openssl dgst -sha1 -binary | openssl dgst -sha1
In first line will be password and in second - corresponding double SHA1.
-->
<password></password>
<!-- List of networks with open access.
To open access from everywhere, specify:
<ip>::/0</ip>
To open access only from localhost, specify:
<ip>::1</ip>
<ip>127.0.0.1</ip>
Each element of list has one of the following forms:
<ip> IP-address or network mask. Examples: 213.180.204.3 or 10.0.0.1/8 or 10.0.0.1/255.255.255.0
2a02:6b8::3 or 2a02:6b8::3/64 or 2a02:6b8::3/ffff:ffff:ffff:ffff::.
<host> Hostname. Example: server01.yandex.ru.
To check access, DNS query is performed, and all received addresses compared to peer address.
<host_regexp> Regular expression for host names. Example, ^server\d\d-\d\d-\d\.yandex\.ru$
To check access, DNS PTR query is performed for peer address and then regexp is applied.
Then, for result of PTR query, another DNS query is performed and all received addresses compared to peer address.
Strongly recommended that regexp is ends with $
All results of DNS requests are cached till server restart.
-->
<networks incl="networks" replace="replace">
<ip>::/0</ip>
</networks>
<!-- Settings profile for user. -->
<profile>default</profile>
<!-- Quota for user. -->
<quota>default</quota>
<!-- Allow access management -->
<access_management>1</access_management>
<!-- Example of row level security policy. -->
<!-- <databases>
<test>
<filtered_table1>
<filter>a = 1</filter>
</filtered_table1>
<filtered_table2>
<filter>a + b &lt; 1 or c - d &gt; 5</filter>
</filtered_table2>
</test>
</databases> -->
</default>
<!-- Example of user with readonly access. -->
<!-- <readonly>
<password></password>
<networks incl="networks" replace="replace">
<ip>::1</ip>
<ip>127.0.0.1</ip>
</networks>
<profile>readonly</profile>
<quota>default</quota>
</readonly> -->
</users>
<!-- Quotas. -->
<quotas>
<!-- Name of quota. -->
<default>
<!-- Limits for time interval. You could specify many intervals with different limits. -->
<interval>
<!-- Length of interval. -->
<duration>3600</duration>
<!-- No limits. Just calculate resource usage for time interval. -->
<queries>0</queries>
<errors>0</errors>
<result_rows>0</result_rows>
<read_rows>0</read_rows>
<execution_time>0</execution_time>
</interval>
</default>
</quotas>
</yandex>

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<?xml version="1.0"?>
<yandex>
<macros>
<replica>clickhouse1</replica>
<shard>01</shard>
<shard2>01</shard2>
</macros>
</yandex>

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<?xml version="1.0"?>
<yandex>
<macros>
<replica>clickhouse2</replica>
<shard>01</shard>
<shard2>02</shard2>
</macros>
</yandex>

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<?xml version="1.0"?>
<yandex>
<macros>
<replica>clickhouse3</replica>
<shard>01</shard>
<shard2>03</shard2>
</macros>
</yandex>

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version: '2.3'
services:
clickhouse:
image: yandex/clickhouse-integration-test
expose:
- "9000"
- "9009"
- "8123"
volumes:
- "${CLICKHOUSE_TESTS_DIR}/configs/clickhouse/config.d:/etc/clickhouse-server/config.d"
- "${CLICKHOUSE_TESTS_DIR}/configs/clickhouse/users.d:/etc/clickhouse-server/users.d"
- "${CLICKHOUSE_TESTS_DIR}/configs/clickhouse/config.xml:/etc/clickhouse-server/config.xml"
- "${CLICKHOUSE_TESTS_DIR}/configs/clickhouse/users.xml:/etc/clickhouse-server/users.xml"
- "${CLICKHOUSE_TESTS_SERVER_BIN_PATH:-/usr/bin/clickhouse}:/usr/bin/clickhouse"
- "${CLICKHOUSE_TESTS_ODBC_BRIDGE_BIN_PATH:-/usr/bin/clickhouse-odbc-bridge}:/usr/bin/clickhouse-odbc-bridge"
entrypoint: bash -c "clickhouse server --config-file=/etc/clickhouse-server/config.xml --log-file=/var/log/clickhouse-server/clickhouse-server.log --errorlog-file=/var/log/clickhouse-server/clickhouse-server.err.log"
healthcheck:
test: clickhouse client --query='select 1'
interval: 10s
timeout: 10s
retries: 3
start_period: 300s
cap_add:
- SYS_PTRACE
security_opt:
- label:disable

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version: '2.3'
services:
zookeeper:
extends:
file: zookeeper-service.yml
service: zookeeper
clickhouse1:
extends:
file: clickhouse-service.yml
service: clickhouse
hostname: clickhouse1
volumes:
- "${CLICKHOUSE_TESTS_DIR}/_instances/clickhouse1/database/:/var/lib/clickhouse/"
- "${CLICKHOUSE_TESTS_DIR}/_instances/clickhouse1/logs/:/var/log/clickhouse-server/"
- "${CLICKHOUSE_TESTS_DIR}/configs/clickhouse1/config.d/macros.xml:/etc/clickhouse-server/config.d/macros.xml"
depends_on:
zookeeper:
condition: service_healthy
clickhouse2:
extends:
file: clickhouse-service.yml
service: clickhouse
hostname: clickhouse2
volumes:
- "${CLICKHOUSE_TESTS_DIR}/_instances/clickhouse2/database/:/var/lib/clickhouse/"
- "${CLICKHOUSE_TESTS_DIR}/_instances/clickhouse2/logs/:/var/log/clickhouse-server/"
- "${CLICKHOUSE_TESTS_DIR}/configs/clickhouse2/config.d/macros.xml:/etc/clickhouse-server/config.d/macros.xml"
depends_on:
zookeeper:
condition: service_healthy
clickhouse3:
extends:
file: clickhouse-service.yml
service: clickhouse
hostname: clickhouse3
volumes:
- "${CLICKHOUSE_TESTS_DIR}/_instances/clickhouse3/database/:/var/lib/clickhouse/"
- "${CLICKHOUSE_TESTS_DIR}/_instances/clickhouse3/logs/:/var/log/clickhouse-server/"
- "${CLICKHOUSE_TESTS_DIR}/configs/clickhouse3/config.d/macros.xml:/etc/clickhouse-server/config.d/macros.xml"
depends_on:
zookeeper:
condition: service_healthy
# dummy service which does nothing, but allows to postpone
# 'docker-compose up -d' till all dependecies will go healthy
all_services_ready:
image: hello-world
depends_on:
clickhouse1:
condition: service_healthy
clickhouse2:
condition: service_healthy
clickhouse3:
condition: service_healthy
zookeeper:
condition: service_healthy

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version: '2.3'
services:
zookeeper:
image: zookeeper:3.4.12
expose:
- "2181"
environment:
ZOO_TICK_TIME: 500
ZOO_MY_ID: 1
healthcheck:
test: echo stat | nc localhost 2181
interval: 3s
timeout: 2s
retries: 5
start_period: 2s
security_opt:
- label:disable

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#!/usr/bin/env python3
import sys
from testflows.core import *
append_path(sys.path, "..")
from helpers.cluster import Cluster
from helpers.argparser import argparser
from map_type.requirements import SRS018_ClickHouse_Map_Data_Type
xfails = {
"tests/table map with key integer/Int:":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21032")],
"tests/table map with value integer/Int:":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21032")],
"tests/table map with key integer/UInt256":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21031")],
"tests/table map with value integer/UInt256":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21031")],
"tests/select map with key integer/Int64":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21030")],
"tests/select map with value integer/Int64":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21030")],
"tests/cast tuple of two arrays to map/string -> int":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21029")],
"tests/mapcontains/null key in map":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21028")],
"tests/mapcontains/null key not in map":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21028")],
"tests/mapkeys/null key not in map":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21028")],
"tests/mapkeys/null key in map":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21028")],
"tests/mapcontains/select nullable key":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21026")],
"tests/mapkeys/select keys from column":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21026")],
"tests/table map select key with value string/LowCardinality:":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21406")],
"tests/table map select key with key string/FixedString":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21406")],
"tests/table map select key with key string/Nullable":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21406")],
"tests/table map select key with key string/Nullable(NULL)":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21026")],
"tests/table map select key with key string/LowCardinality:":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21406")],
"tests/table map select key with key integer/Int:":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21032")],
"tests/table map select key with key integer/UInt256":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21031")],
"tests/table map select key with key integer/toNullable":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21406")],
"tests/table map select key with key integer/toNullable(NULL)":
[(Fail, "https://github.com/ClickHouse/ClickHouse/issues/21026")],
"tests/select map with key integer/Int128":
[(Fail, "large Int128 as key not supported")],
"tests/select map with key integer/Int256":
[(Fail, "large Int256 as key not supported")],
"tests/select map with key integer/UInt256":
[(Fail, "large UInt256 as key not supported")],
"tests/select map with key integer/toNullable":
[(Fail, "Nullable type as key not supported")],
"tests/select map with key integer/toNullable(NULL)":
[(Fail, "Nullable type as key not supported")],
"tests/select map with key string/Nullable":
[(Fail, "Nullable type as key not supported")],
"tests/select map with key string/Nullable(NULL)":
[(Fail, "Nullable type as key not supported")],
"tests/table map queries/select map with nullable value":
[(Fail, "Nullable value not supported")],
"tests/table map with key integer/toNullable":
[(Fail, "Nullable type as key not supported")],
"tests/table map with key integer/toNullable(NULL)":
[(Fail, "Nullable type as key not supported")],
"tests/table map with key string/Nullable":
[(Fail, "Nullable type as key not supported")],
"tests/table map with key string/Nullable(NULL)":
[(Fail, "Nullable type as key not supported")],
"tests/table map with key string/LowCardinality(String)":
[(Fail, "LowCardinality(String) as key not supported")],
"tests/table map with key string/LowCardinality(String) cast from String":
[(Fail, "LowCardinality(String) as key not supported")],
"tests/table map with key string/LowCardinality(String) for key and value":
[(Fail, "LowCardinality(String) as key not supported")],
"tests/table map with key string/LowCardinality(FixedString)":
[(Fail, "LowCardinality(FixedString) as key not supported")],
"tests/table map with value string/LowCardinality(String) for key and value":
[(Fail, "LowCardinality(String) as key not supported")],
}
xflags = {
}
@TestModule
@ArgumentParser(argparser)
@XFails(xfails)
@XFlags(xflags)
@Name("map type")
@Specifications(
SRS018_ClickHouse_Map_Data_Type
)
def regression(self, local, clickhouse_binary_path, stress=None, parallel=None):
"""Map type regression.
"""
nodes = {
"clickhouse":
("clickhouse1", "clickhouse2", "clickhouse3")
}
with Cluster(local, clickhouse_binary_path, nodes=nodes) as cluster:
self.context.cluster = cluster
self.context.stress = stress
if parallel is not None:
self.context.parallel = parallel
Feature(run=load("map_type.tests.feature", "feature"))
if main():
regression()

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from .requirements import *

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# SRS018 ClickHouse Map Data Type
# Software Requirements Specification
## Table of Contents
* 1 [Revision History](#revision-history)
* 2 [Introduction](#introduction)
* 3 [Requirements](#requirements)
* 3.1 [General](#general)
* 3.1.1 [RQ.SRS-018.ClickHouse.Map.DataType](#rqsrs-018clickhousemapdatatype)
* 3.2 [Performance](#performance)
* 3.2.1 [RQ.SRS-018.ClickHouse.Map.DataType.Performance.Vs.ArrayOfTuples](#rqsrs-018clickhousemapdatatypeperformancevsarrayoftuples)
* 3.2.2 [RQ.SRS-018.ClickHouse.Map.DataType.Performance.Vs.TupleOfArrays](#rqsrs-018clickhousemapdatatypeperformancevstupleofarrays)
* 3.3 [Key Types](#key-types)
* 3.3.1 [RQ.SRS-018.ClickHouse.Map.DataType.Key.String](#rqsrs-018clickhousemapdatatypekeystring)
* 3.3.2 [RQ.SRS-018.ClickHouse.Map.DataType.Key.Integer](#rqsrs-018clickhousemapdatatypekeyinteger)
* 3.4 [Value Types](#value-types)
* 3.4.1 [RQ.SRS-018.ClickHouse.Map.DataType.Value.String](#rqsrs-018clickhousemapdatatypevaluestring)
* 3.4.2 [RQ.SRS-018.ClickHouse.Map.DataType.Value.Integer](#rqsrs-018clickhousemapdatatypevalueinteger)
* 3.4.3 [RQ.SRS-018.ClickHouse.Map.DataType.Value.Array](#rqsrs-018clickhousemapdatatypevaluearray)
* 3.5 [Invalid Types](#invalid-types)
* 3.5.1 [RQ.SRS-018.ClickHouse.Map.DataType.Invalid.Nullable](#rqsrs-018clickhousemapdatatypeinvalidnullable)
* 3.5.2 [RQ.SRS-018.ClickHouse.Map.DataType.Invalid.NothingNothing](#rqsrs-018clickhousemapdatatypeinvalidnothingnothing)
* 3.6 [Duplicated Keys](#duplicated-keys)
* 3.6.1 [RQ.SRS-018.ClickHouse.Map.DataType.DuplicatedKeys](#rqsrs-018clickhousemapdatatypeduplicatedkeys)
* 3.7 [Array of Maps](#array-of-maps)
* 3.7.1 [RQ.SRS-018.ClickHouse.Map.DataType.ArrayOfMaps](#rqsrs-018clickhousemapdatatypearrayofmaps)
* 3.8 [Nested With Maps](#nested-with-maps)
* 3.8.1 [RQ.SRS-018.ClickHouse.Map.DataType.NestedWithMaps](#rqsrs-018clickhousemapdatatypenestedwithmaps)
* 3.9 [Value Retrieval](#value-retrieval)
* 3.9.1 [RQ.SRS-018.ClickHouse.Map.DataType.Value.Retrieval](#rqsrs-018clickhousemapdatatypevalueretrieval)
* 3.9.2 [RQ.SRS-018.ClickHouse.Map.DataType.Value.Retrieval.KeyInvalid](#rqsrs-018clickhousemapdatatypevalueretrievalkeyinvalid)
* 3.9.3 [RQ.SRS-018.ClickHouse.Map.DataType.Value.Retrieval.KeyNotFound](#rqsrs-018clickhousemapdatatypevalueretrievalkeynotfound)
* 3.10 [Converting Tuple(Array, Array) to Map](#converting-tuplearray-array-to-map)
* 3.10.1 [RQ.SRS-018.ClickHouse.Map.DataType.Conversion.From.TupleOfArraysToMap](#rqsrs-018clickhousemapdatatypeconversionfromtupleofarraystomap)
* 3.10.2 [RQ.SRS-018.ClickHouse.Map.DataType.Conversion.From.TupleOfArraysMap.Invalid](#rqsrs-018clickhousemapdatatypeconversionfromtupleofarraysmapinvalid)
* 3.11 [Converting Array(Tuple(K,V)) to Map](#converting-arraytuplekv-to-map)
* 3.11.1 [RQ.SRS-018.ClickHouse.Map.DataType.Conversion.From.ArrayOfTuplesToMap](#rqsrs-018clickhousemapdatatypeconversionfromarrayoftuplestomap)
* 3.11.2 [RQ.SRS-018.ClickHouse.Map.DataType.Conversion.From.ArrayOfTuplesToMap.Invalid](#rqsrs-018clickhousemapdatatypeconversionfromarrayoftuplestomapinvalid)
* 3.12 [Keys and Values Subcolumns](#keys-and-values-subcolumns)
* 3.12.1 [RQ.SRS-018.ClickHouse.Map.DataType.SubColumns.Keys](#rqsrs-018clickhousemapdatatypesubcolumnskeys)
* 3.12.2 [RQ.SRS-018.ClickHouse.Map.DataType.SubColumns.Keys.ArrayFunctions](#rqsrs-018clickhousemapdatatypesubcolumnskeysarrayfunctions)
* 3.12.3 [RQ.SRS-018.ClickHouse.Map.DataType.SubColumns.Keys.InlineDefinedMap](#rqsrs-018clickhousemapdatatypesubcolumnskeysinlinedefinedmap)
* 3.12.4 [RQ.SRS-018.ClickHouse.Map.DataType.SubColumns.Values](#rqsrs-018clickhousemapdatatypesubcolumnsvalues)
* 3.12.5 [RQ.SRS-018.ClickHouse.Map.DataType.SubColumns.Values.ArrayFunctions](#rqsrs-018clickhousemapdatatypesubcolumnsvaluesarrayfunctions)
* 3.12.6 [RQ.SRS-018.ClickHouse.Map.DataType.SubColumns.Values.InlineDefinedMap](#rqsrs-018clickhousemapdatatypesubcolumnsvaluesinlinedefinedmap)
* 3.13 [Functions](#functions)
* 3.13.1 [RQ.SRS-018.ClickHouse.Map.DataType.Functions.InlineDefinedMap](#rqsrs-018clickhousemapdatatypefunctionsinlinedefinedmap)
* 3.13.2 [`length`](#length)
* 3.13.2.1 [RQ.SRS-018.ClickHouse.Map.DataType.Functions.Length](#rqsrs-018clickhousemapdatatypefunctionslength)
* 3.13.3 [`empty`](#empty)
* 3.13.3.1 [RQ.SRS-018.ClickHouse.Map.DataType.Functions.Empty](#rqsrs-018clickhousemapdatatypefunctionsempty)
* 3.13.4 [`notEmpty`](#notempty)
* 3.13.4.1 [RQ.SRS-018.ClickHouse.Map.DataType.Functions.NotEmpty](#rqsrs-018clickhousemapdatatypefunctionsnotempty)
* 3.13.5 [`map`](#map)
* 3.13.5.1 [RQ.SRS-018.ClickHouse.Map.DataType.Functions.Map](#rqsrs-018clickhousemapdatatypefunctionsmap)
* 3.13.5.2 [RQ.SRS-018.ClickHouse.Map.DataType.Functions.Map.InvalidNumberOfArguments](#rqsrs-018clickhousemapdatatypefunctionsmapinvalidnumberofarguments)
* 3.13.5.3 [RQ.SRS-018.ClickHouse.Map.DataType.Functions.Map.MixedKeyOrValueTypes](#rqsrs-018clickhousemapdatatypefunctionsmapmixedkeyorvaluetypes)
* 3.13.5.4 [RQ.SRS-018.ClickHouse.Map.DataType.Functions.Map.MapAdd](#rqsrs-018clickhousemapdatatypefunctionsmapmapadd)
* 3.13.5.5 [RQ.SRS-018.ClickHouse.Map.DataType.Functions.Map.MapSubstract](#rqsrs-018clickhousemapdatatypefunctionsmapmapsubstract)
* 3.13.5.6 [RQ.SRS-018.ClickHouse.Map.DataType.Functions.Map.MapPopulateSeries](#rqsrs-018clickhousemapdatatypefunctionsmapmappopulateseries)
* 3.13.6 [`mapContains`](#mapcontains)
* 3.13.6.1 [RQ.SRS-018.ClickHouse.Map.DataType.Functions.MapContains](#rqsrs-018clickhousemapdatatypefunctionsmapcontains)
* 3.13.7 [`mapKeys`](#mapkeys)
* 3.13.7.1 [RQ.SRS-018.ClickHouse.Map.DataType.Functions.MapKeys](#rqsrs-018clickhousemapdatatypefunctionsmapkeys)
* 3.13.8 [`mapValues`](#mapvalues)
* 3.13.8.1 [RQ.SRS-018.ClickHouse.Map.DataType.Functions.MapValues](#rqsrs-018clickhousemapdatatypefunctionsmapvalues)
## Revision History
This document is stored in an electronic form using [Git] source control management software
hosted in a [GitHub Repository].
All the updates are tracked using the [Revision History].
## Introduction
This software requirements specification covers requirements for `Map(key, value)` data type in [ClickHouse].
## Requirements
### General
#### RQ.SRS-018.ClickHouse.Map.DataType
version: 1.0
[ClickHouse] SHALL support `Map(key, value)` data type that stores `key:value` pairs.
### Performance
#### RQ.SRS-018.ClickHouse.Map.DataType.Performance.Vs.ArrayOfTuples
version:1.0
[ClickHouse] SHALL provide comparable performance for `Map(key, value)` data type as
compared to `Array(Tuple(K,V))` data type.
#### RQ.SRS-018.ClickHouse.Map.DataType.Performance.Vs.TupleOfArrays
version:1.0
[ClickHouse] SHALL provide comparable performance for `Map(key, value)` data type as
compared to `Tuple(Array(String), Array(String))` data type where the first
array defines an array of keys and the second array defines an array of values.
### Key Types
#### RQ.SRS-018.ClickHouse.Map.DataType.Key.String
version: 1.0
[ClickHouse] SHALL support `Map(key, value)` data type where key is of a [String] type.
#### RQ.SRS-018.ClickHouse.Map.DataType.Key.Integer
version: 1.0
[ClickHouse] SHALL support `Map(key, value)` data type where key is of an [Integer] type.
### Value Types
#### RQ.SRS-018.ClickHouse.Map.DataType.Value.String
version: 1.0
[ClickHouse] SHALL support `Map(key, value)` data type where value is of a [String] type.
#### RQ.SRS-018.ClickHouse.Map.DataType.Value.Integer
version: 1.0
[ClickHouse] SHALL support `Map(key, value)` data type where value is of a [Integer] type.
#### RQ.SRS-018.ClickHouse.Map.DataType.Value.Array
version: 1.0
[ClickHouse] SHALL support `Map(key, value)` data type where value is of a [Array] type.
### Invalid Types
#### RQ.SRS-018.ClickHouse.Map.DataType.Invalid.Nullable
version: 1.0
[ClickHouse] SHALL not support creating table columns that have `Nullable(Map(key, value))` data type.
#### RQ.SRS-018.ClickHouse.Map.DataType.Invalid.NothingNothing
version: 1.0
[ClickHouse] SHALL not support creating table columns that have `Map(Nothing, Nothing))` data type.
### Duplicated Keys
#### RQ.SRS-018.ClickHouse.Map.DataType.DuplicatedKeys
version: 1.0
[ClickHouse] MAY support `Map(key, value)` data type with duplicated keys.
### Array of Maps
#### RQ.SRS-018.ClickHouse.Map.DataType.ArrayOfMaps
version: 1.0
[ClickHouse] SHALL support `Array(Map(key, value))` data type.
### Nested With Maps
#### RQ.SRS-018.ClickHouse.Map.DataType.NestedWithMaps
version: 1.0
[ClickHouse] SHALL support defining `Map(key, value)` data type inside the [Nested] data type.
### Value Retrieval
#### RQ.SRS-018.ClickHouse.Map.DataType.Value.Retrieval
version: 1.0
[ClickHouse] SHALL support getting the value from a `Map(key, value)` data type using `map[key]` syntax.
If `key` has duplicates then the first `key:value` pair MAY be returned.
For example,
```sql
SELECT a['key2'] FROM table_map;
```
#### RQ.SRS-018.ClickHouse.Map.DataType.Value.Retrieval.KeyInvalid
version: 1.0
[ClickHouse] SHALL return an error when key does not match the key type.
For example,
```sql
SELECT map(1,2) AS m, m[1024]
```
Exceptions:
* when key is `NULL` the return value MAY be `NULL`
* when key value is not valid for the key type, for example it is out of range for [Integer] type,
when reading from a table column it MAY return the default value for key data type
#### RQ.SRS-018.ClickHouse.Map.DataType.Value.Retrieval.KeyNotFound
version: 1.0
[ClickHouse] SHALL return default value for the data type of the value
when there's no corresponding `key` defined in the `Map(key, value)` data type.
### Converting Tuple(Array, Array) to Map
#### RQ.SRS-018.ClickHouse.Map.DataType.Conversion.From.TupleOfArraysToMap
version: 1.0
[ClickHouse] SHALL support converting [Tuple(Array, Array)] to `Map(key, value)` using the [CAST] function.
``` sql
SELECT CAST(([1, 2, 3], ['Ready', 'Steady', 'Go']), 'Map(UInt8, String)') AS map;
```
``` text
┌─map───────────────────────────┐
│ {1:'Ready',2:'Steady',3:'Go'} │
└───────────────────────────────┘
```
#### RQ.SRS-018.ClickHouse.Map.DataType.Conversion.From.TupleOfArraysMap.Invalid
version: 1.0
[ClickHouse] MAY return an error when casting [Tuple(Array, Array)] to `Map(key, value)`
* when arrays are not of equal size
For example,
```sql
SELECT CAST(([2, 1, 1023], ['', '']), 'Map(UInt8, String)') AS map, map[10]
```
### Converting Array(Tuple(K,V)) to Map
#### RQ.SRS-018.ClickHouse.Map.DataType.Conversion.From.ArrayOfTuplesToMap
version: 1.0
[ClickHouse] SHALL support converting [Array(Tuple(K,V))] to `Map(key, value)` using the [CAST] function.
For example,
```sql
SELECT CAST(([(1,2),(3)]), 'Map(UInt8, UInt8)') AS map
```
#### RQ.SRS-018.ClickHouse.Map.DataType.Conversion.From.ArrayOfTuplesToMap.Invalid
version: 1.0
[ClickHouse] MAY return an error when casting [Array(Tuple(K, V))] to `Map(key, value)`
* when element is not a [Tuple]
```sql
SELECT CAST(([(1,2),(3)]), 'Map(UInt8, UInt8)') AS map
```
* when [Tuple] does not contain two elements
```sql
SELECT CAST(([(1,2),(3,)]), 'Map(UInt8, UInt8)') AS map
```
### Keys and Values Subcolumns
#### RQ.SRS-018.ClickHouse.Map.DataType.SubColumns.Keys
version: 1.0
[ClickHouse] SHALL support `keys` subcolumn in the `Map(key, value)` type that can be used
to retrieve an [Array] of map keys.
```sql
SELECT m.keys FROM t_map;
```
#### RQ.SRS-018.ClickHouse.Map.DataType.SubColumns.Keys.ArrayFunctions
version: 1.0
[ClickHouse] SHALL support applying [Array] functions to the `keys` subcolumn in the `Map(key, value)` type.
For example,
```sql
SELECT * FROM t_map WHERE has(m.keys, 'a');
```
#### RQ.SRS-018.ClickHouse.Map.DataType.SubColumns.Keys.InlineDefinedMap
version: 1.0
[ClickHouse] MAY not support using inline defined map to get `keys` subcolumn.
For example,
```sql
SELECT map( 'aa', 4, '44' , 5) as c, c.keys
```
#### RQ.SRS-018.ClickHouse.Map.DataType.SubColumns.Values
version: 1.0
[ClickHouse] SHALL support `values` subcolumn in the `Map(key, value)` type that can be used
to retrieve an [Array] of map values.
```sql
SELECT m.values FROM t_map;
```
#### RQ.SRS-018.ClickHouse.Map.DataType.SubColumns.Values.ArrayFunctions
version: 1.0
[ClickHouse] SHALL support applying [Array] functions to the `values` subcolumn in the `Map(key, value)` type.
For example,
```sql
SELECT * FROM t_map WHERE has(m.values, 'a');
```
#### RQ.SRS-018.ClickHouse.Map.DataType.SubColumns.Values.InlineDefinedMap
version: 1.0
[ClickHouse] MAY not support using inline defined map to get `values` subcolumn.
For example,
```sql
SELECT map( 'aa', 4, '44' , 5) as c, c.values
```
### Functions
#### RQ.SRS-018.ClickHouse.Map.DataType.Functions.InlineDefinedMap
version: 1.0
[ClickHouse] SHALL support using inline defined maps as an argument to map functions.
For example,
```sql
SELECT map( 'aa', 4, '44' , 5) as c, mapKeys(c)
SELECT map( 'aa', 4, '44' , 5) as c, mapValues(c)
```
#### `length`
##### RQ.SRS-018.ClickHouse.Map.DataType.Functions.Length
version: 1.0
[ClickHouse] SHALL support `Map(key, value)` data type as an argument to the [length] function
that SHALL return number of keys in the map.
For example,
```sql
SELECT length(map(1,2,3,4))
SELECT length(map())
```
#### `empty`
##### RQ.SRS-018.ClickHouse.Map.DataType.Functions.Empty
version: 1.0
[ClickHouse] SHALL support `Map(key, value)` data type as an argument to the [empty] function
that SHALL return 1 if number of keys in the map is 0 otherwise if the number of keys is
greater or equal to 1 it SHALL return 0.
For example,
```sql
SELECT empty(map(1,2,3,4))
SELECT empty(map())
```
#### `notEmpty`
##### RQ.SRS-018.ClickHouse.Map.DataType.Functions.NotEmpty
version: 1.0
[ClickHouse] SHALL support `Map(key, value)` data type as an argument to the [notEmpty] function
that SHALL return 0 if number if keys in the map is 0 otherwise if the number of keys is
greater or equal to 1 it SHALL return 1.
For example,
```sql
SELECT notEmpty(map(1,2,3,4))
SELECT notEmpty(map())
```
#### `map`
##### RQ.SRS-018.ClickHouse.Map.DataType.Functions.Map
version: 1.0
[ClickHouse] SHALL support arranging `key, value` pairs into `Map(key, value)` data type
using `map` function.
**Syntax**
``` sql
map(key1, value1[, key2, value2, ...])
```
For example,
``` sql
SELECT map('key1', number, 'key2', number * 2) FROM numbers(3);
┌─map('key1', number, 'key2', multiply(number, 2))─┐
│ {'key1':0,'key2':0} │
│ {'key1':1,'key2':2} │
│ {'key1':2,'key2':4} │
└──────────────────────────────────────────────────┘
```
##### RQ.SRS-018.ClickHouse.Map.DataType.Functions.Map.InvalidNumberOfArguments
version: 1.0
[ClickHouse] SHALL return an error when `map` function is called with non even number of arguments.
##### RQ.SRS-018.ClickHouse.Map.DataType.Functions.Map.MixedKeyOrValueTypes
version: 1.0
[ClickHouse] SHALL return an error when `map` function is called with mixed key or value types.
##### RQ.SRS-018.ClickHouse.Map.DataType.Functions.Map.MapAdd
version: 1.0
[ClickHouse] SHALL support converting the results of `mapAdd` function to a `Map(key, value)` data type.
For example,
``` sql
SELECT CAST(mapAdd(([toUInt8(1), 2], [1, 1]), ([toUInt8(1), 2], [1, 1])), "Map(Int8,Int8)")
```
##### RQ.SRS-018.ClickHouse.Map.DataType.Functions.Map.MapSubstract
version: 1.0
[ClickHouse] SHALL support converting the results of `mapSubstract` function to a `Map(key, value)` data type.
For example,
```sql
SELECT CAST(mapSubtract(([toUInt8(1), 2], [toInt32(1), 1]), ([toUInt8(1), 2], [toInt32(2), 1])), "Map(Int8,Int8)")
```
##### RQ.SRS-018.ClickHouse.Map.DataType.Functions.Map.MapPopulateSeries
version: 1.0
[ClickHouse] SHALL support converting the results of `mapPopulateSeries` function to a `Map(key, value)` data type.
For example,
```sql
SELECT CAST(mapPopulateSeries([1,2,4], [11,22,44], 5), "Map(Int8,Int8)")
```
#### `mapContains`
##### RQ.SRS-018.ClickHouse.Map.DataType.Functions.MapContains
version: 1.0
[ClickHouse] SHALL support `mapContains(map, key)` function to check weather `map.keys` contains the `key`.
For example,
```sql
SELECT mapContains(a, 'abc') from table_map;
```
#### `mapKeys`
##### RQ.SRS-018.ClickHouse.Map.DataType.Functions.MapKeys
version: 1.0
[ClickHouse] SHALL support `mapKeys(map)` function to return all the map keys in the [Array] format.
For example,
```sql
SELECT mapKeys(a) from table_map;
```
#### `mapValues`
##### RQ.SRS-018.ClickHouse.Map.DataType.Functions.MapValues
version: 1.0
[ClickHouse] SHALL support `mapValues(map)` function to return all the map values in the [Array] format.
For example,
```sql
SELECT mapValues(a) from table_map;
```
[Nested]: https://clickhouse.tech/docs/en/sql-reference/data-types/nested-data-structures/nested/
[length]: https://clickhouse.tech/docs/en/sql-reference/functions/array-functions/#array_functions-length
[empty]: https://clickhouse.tech/docs/en/sql-reference/functions/array-functions/#function-empty
[notEmpty]: https://clickhouse.tech/docs/en/sql-reference/functions/array-functions/#function-notempty
[CAST]: https://clickhouse.tech/docs/en/sql-reference/functions/type-conversion-functions/#type_conversion_function-cast
[Tuple]: https://clickhouse.tech/docs/en/sql-reference/data-types/tuple/
[Tuple(Array,Array)]: https://clickhouse.tech/docs/en/sql-reference/data-types/tuple/
[Array]: https://clickhouse.tech/docs/en/sql-reference/data-types/array/
[String]: https://clickhouse.tech/docs/en/sql-reference/data-types/string/
[Integer]: https://clickhouse.tech/docs/en/sql-reference/data-types/int-uint/
[ClickHouse]: https://clickhouse.tech
[GitHub Repository]: https://github.com/ClickHouse/ClickHouse/blob/master/tests/testflows/map_type/requirements/requirements.md
[Revision History]: https://github.com/ClickHouse/ClickHouse/commits/master/tests/testflows/map_type/requirements/requirements.md
[Git]: https://git-scm.com/
[GitHub]: https://github.com

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import uuid
from collections import namedtuple
from testflows.core import *
from testflows.core.name import basename, parentname
from testflows._core.testtype import TestSubType
def getuid():
if current().subtype == TestSubType.Example:
testname = f"{basename(parentname(current().name)).replace(' ', '_').replace(',','')}"
else:
testname = f"{basename(current().name).replace(' ', '_').replace(',','')}"
return testname + "_" + str(uuid.uuid1()).replace('-', '_')
@TestStep(Given)
def allow_experimental_map_type(self):
"""Set allow_experimental_map_type = 1
"""
setting = ("allow_experimental_map_type", 1)
default_query_settings = None
try:
with By("adding allow_experimental_map_type to the default query settings"):
default_query_settings = getsattr(current().context, "default_query_settings", [])
default_query_settings.append(setting)
yield
finally:
with Finally("I remove allow_experimental_map_type from the default query settings"):
if default_query_settings:
try:
default_query_settings.pop(default_query_settings.index(setting))
except ValueError:
pass
@TestStep(Given)
def create_table(self, name, statement, on_cluster=False):
"""Create table.
"""
node = current().context.node
try:
with Given(f"I have a {name} table"):
node.query(statement.format(name=name))
yield name
finally:
with Finally("I drop the table"):
if on_cluster:
node.query(f"DROP TABLE IF EXISTS {name} ON CLUSTER {on_cluster}")
else:
node.query(f"DROP TABLE IF EXISTS {name}")

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@ -18,6 +18,7 @@ def regression(self, local, clickhouse_binary_path, stress=None, parallel=None):
# Feature(test=load("ldap.regression", "regression"))(**args)
# Feature(test=load("rbac.regression", "regression"))(**args)
# Feature(test=load("aes_encryption.regression", "regression"))(**args)
Feature(test=load("map_type.regression", "regression"))(**args)
# Feature(test=load("kerberos.regression", "regression"))(**args)
if main():