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Merge pull request #19815 from otrazhenia/evgsudarikova-DOCSUP-6149

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DOCSUP-6149: Edit and translate to Russian
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8
docs/en/getting-started/example-datasets/brown-benchmark.md
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@ -5,7 +5,7 @@ toc_title: Brown University Benchmark
# Brown University Benchmark
MgBench - A new analytical benchmark for machine-generated log data, [Andrew Crotty](http://cs.brown.edu/people/acrotty/).
`MgBench` is a new analytical benchmark for machine-generated log data, [Andrew Crotty](http://cs.brown.edu/people/acrotty/).
Download the data:
```
@ -153,7 +153,7 @@ ORDER BY dt,
hr;
-- Q1.4: Over a 1-month period, how often was each server blocked on disk I/O?
-- Q1.4: Over 1 month, how often was each server blocked on disk I/O?
SELECT machine_name,
COUNT(*) AS spikes
@ -301,7 +301,7 @@ WHERE event_type = 'temperature'
AND log_time >= '2019-11-29 17:00:00.000';
-- Q3.4: Over the past 6 months, how frequently was each door opened?
-- Q3.4: Over the past 6 months, how frequently were each door opened?
SELECT device_name,
device_floor,
@ -412,3 +412,5 @@ 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-->

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docs/en/sql-reference/table-functions/mysql.md
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@ -44,7 +44,7 @@ The rest of the conditions and the `LIMIT` sampling constraint are executed in C
A table object with the same columns as the original MySQL table.
!!! info "Note"
In the `INSERT` query to distinguish table function `mysql(...)` from table name with column names list you must use keywords `FUNCTION` or `TABLE FUNCTION`. See examples below.
In the `INSERT` query to distinguish table function `mysql(...)` from table name with column names list, you must use keywords `FUNCTION` or `TABLE FUNCTION`. See examples below.
**Examples**

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@ -0,0 +1,416 @@
---
toc_priority: 20
toc_title: Brown University Benchmark
---
# Brown University Benchmark
`MgBench` — это аналитический тест производительности для данных журнала событий, сгенерированных машиной. Бенчмарк разработан [Andrew Crotty](http://cs.brown.edu/people/acrotty/).
Скачать данные:
```
wget https://datasets.clickhouse.tech/mgbench{1..3}.csv.xz
```
Распаковать данные:
```
xz -v -d mgbench{1..3}.csv.xz
```
Создание таблиц:
```
CREATE DATABASE mgbench;
CREATE TABLE mgbench.logs1 (
log_time DateTime,
machine_name LowCardinality(String),
machine_group LowCardinality(String),
cpu_idle Nullable(Float32),
cpu_nice Nullable(Float32),
cpu_system Nullable(Float32),
cpu_user Nullable(Float32),
cpu_wio Nullable(Float32),
disk_free Nullable(Float32),
disk_total Nullable(Float32),
part_max_used Nullable(Float32),
load_fifteen Nullable(Float32),
load_five Nullable(Float32),
load_one Nullable(Float32),
mem_buffers Nullable(Float32),
mem_cached Nullable(Float32),
mem_free Nullable(Float32),
mem_shared Nullable(Float32),
swap_free Nullable(Float32),
bytes_in Nullable(Float32),
bytes_out Nullable(Float32)
)
ENGINE = MergeTree()
ORDER BY (machine_group, machine_name, log_time);
CREATE TABLE mgbench.logs2 (
log_time DateTime,
client_ip IPv4,
request String,
status_code UInt16,
object_size UInt64
)
ENGINE = MergeTree()
ORDER BY log_time;
CREATE TABLE mgbench.logs3 (
log_time DateTime64,
device_id FixedString(15),
device_name LowCardinality(String),
device_type LowCardinality(String),
device_floor UInt8,
event_type LowCardinality(String),
event_unit FixedString(1),
event_value Nullable(Float32)
)
ENGINE = MergeTree()
ORDER BY (event_type, log_time);
```
Вставка данных:
```
clickhouse-client --query "INSERT INTO mgbench.logs1 FORMAT CSVWithNames" < mgbench1.csv
clickhouse-client --query "INSERT INTO mgbench.logs2 FORMAT CSVWithNames" < mgbench2.csv
clickhouse-client --query "INSERT INTO mgbench.logs3 FORMAT CSVWithNames" < mgbench3.csv
```
Запуск тестов производительности:
```
-- Q1.1: What is the CPU/network utilization for each web server since midnight?
SELECT machine_name,
MIN(cpu) AS cpu_min,
MAX(cpu) AS cpu_max,
AVG(cpu) AS cpu_avg,
MIN(net_in) AS net_in_min,
MAX(net_in) AS net_in_max,
AVG(net_in) AS net_in_avg,
MIN(net_out) AS net_out_min,
MAX(net_out) AS net_out_max,
AVG(net_out) AS net_out_avg
FROM (
SELECT machine_name,
COALESCE(cpu_user, 0.0) AS cpu,
COALESCE(bytes_in, 0.0) AS net_in,
COALESCE(bytes_out, 0.0) AS net_out
FROM logs1
WHERE machine_name IN ('anansi','aragog','urd')
AND log_time >= TIMESTAMP '2017-01-11 00:00:00'
) AS r
GROUP BY machine_name;
-- Q1.2: Which computer lab machines have been offline in the past day?
SELECT machine_name,
log_time
FROM logs1
WHERE (machine_name LIKE 'cslab%' OR
machine_name LIKE 'mslab%')
AND load_one IS NULL
AND log_time >= TIMESTAMP '2017-01-10 00:00:00'
ORDER BY machine_name,
log_time;
-- Q1.3: What are the hourly average metrics during the past 10 days for a specific workstation?
SELECT dt,
hr,
AVG(load_fifteen) AS load_fifteen_avg,
AVG(load_five) AS load_five_avg,
AVG(load_one) AS load_one_avg,
AVG(mem_free) AS mem_free_avg,
AVG(swap_free) AS swap_free_avg
FROM (
SELECT CAST(log_time AS DATE) AS dt,
EXTRACT(HOUR FROM log_time) AS hr,
load_fifteen,
load_five,
load_one,
mem_free,
swap_free
FROM logs1
WHERE machine_name = 'babbage'
AND load_fifteen IS NOT NULL
AND load_five IS NOT NULL
AND load_one IS NOT NULL
AND mem_free IS NOT NULL
AND swap_free IS NOT NULL
AND log_time >= TIMESTAMP '2017-01-01 00:00:00'
) AS r
GROUP BY dt,
hr
ORDER BY dt,
hr;
-- Q1.4: Over 1 month, how often was each server blocked on disk I/O?
SELECT machine_name,
COUNT(*) AS spikes
FROM logs1
WHERE machine_group = 'Servers'
AND cpu_wio > 0.99
AND log_time >= TIMESTAMP '2016-12-01 00:00:00'
AND log_time < TIMESTAMP '2017-01-01 00:00:00'
GROUP BY machine_name
ORDER BY spikes DESC
LIMIT 10;
-- Q1.5: Which externally reachable VMs have run low on memory?
SELECT machine_name,
dt,
MIN(mem_free) AS mem_free_min
FROM (
SELECT machine_name,
CAST(log_time AS DATE) AS dt,
mem_free
FROM logs1
WHERE machine_group = 'DMZ'
AND mem_free IS NOT NULL
) AS r
GROUP BY machine_name,
dt
HAVING MIN(mem_free) < 10000
ORDER BY machine_name,
dt;
-- Q1.6: What is the total hourly network traffic across all file servers?
SELECT dt,
hr,
SUM(net_in) AS net_in_sum,
SUM(net_out) AS net_out_sum,
SUM(net_in) + SUM(net_out) AS both_sum
FROM (
SELECT CAST(log_time AS DATE) AS dt,
EXTRACT(HOUR FROM log_time) AS hr,
COALESCE(bytes_in, 0.0) / 1000000000.0 AS net_in,
COALESCE(bytes_out, 0.0) / 1000000000.0 AS net_out
FROM logs1
WHERE machine_name IN ('allsorts','andes','bigred','blackjack','bonbon',
'cadbury','chiclets','cotton','crows','dove','fireball','hearts','huey',
'lindt','milkduds','milkyway','mnm','necco','nerds','orbit','peeps',
'poprocks','razzles','runts','smarties','smuggler','spree','stride',
'tootsie','trident','wrigley','york')
) AS r
GROUP BY dt,
hr
ORDER BY both_sum DESC
LIMIT 10;
-- Q2.1: Which requests have caused server errors within the past 2 weeks?
SELECT *
FROM logs2
WHERE status_code >= 500
AND log_time >= TIMESTAMP '2012-12-18 00:00:00'
ORDER BY log_time;
-- Q2.2: During a specific 2-week period, was the user password file leaked?
SELECT *
FROM logs2
WHERE status_code >= 200
AND status_code < 300
AND request LIKE '%/etc/passwd%'
AND log_time >= TIMESTAMP '2012-05-06 00:00:00'
AND log_time < TIMESTAMP '2012-05-20 00:00:00';
-- Q2.3: What was the average path depth for top-level requests in the past month?
SELECT top_level,
AVG(LENGTH(request) - LENGTH(REPLACE(request, '/', ''))) AS depth_avg
FROM (
SELECT SUBSTRING(request FROM 1 FOR len) AS top_level,
request
FROM (
SELECT POSITION(SUBSTRING(request FROM 2), '/') AS len,
request
FROM logs2
WHERE status_code >= 200
AND status_code < 300
AND log_time >= TIMESTAMP '2012-12-01 00:00:00'
) AS r
WHERE len > 0
) AS s
WHERE top_level IN ('/about','/courses','/degrees','/events',
'/grad','/industry','/news','/people',
'/publications','/research','/teaching','/ugrad')
GROUP BY top_level
ORDER BY top_level;
-- Q2.4: During the last 3 months, which clients have made an excessive number of requests?
SELECT client_ip,
COUNT(*) AS num_requests
FROM logs2
WHERE log_time >= TIMESTAMP '2012-10-01 00:00:00'
GROUP BY client_ip
HAVING COUNT(*) >= 100000
ORDER BY num_requests DESC;
-- Q2.5: What are the daily unique visitors?
SELECT dt,
COUNT(DISTINCT client_ip)
FROM (
SELECT CAST(log_time AS DATE) AS dt,
client_ip
FROM logs2
) AS r
GROUP BY dt
ORDER BY dt;
-- Q2.6: What are the average and maximum data transfer rates (Gbps)?
SELECT AVG(transfer) / 125000000.0 AS transfer_avg,
MAX(transfer) / 125000000.0 AS transfer_max
FROM (
SELECT log_time,
SUM(object_size) AS transfer
FROM logs2
GROUP BY log_time
) AS r;
-- Q3.1: Did the indoor temperature reach freezing over the weekend?
SELECT *
FROM logs3
WHERE event_type = 'temperature'
AND event_value <= 32.0
AND log_time >= '2019-11-29 17:00:00.000';
-- Q3.4: Over the past 6 months, how frequently were each door opened?
SELECT device_name,
device_floor,
COUNT(*) AS ct
FROM logs3
WHERE event_type = 'door_open'
AND log_time >= '2019-06-01 00:00:00.000'
GROUP BY device_name,
device_floor
ORDER BY ct DESC;
-- Q3.5: Where in the building do large temperature variations occur in winter and summer?
WITH temperature AS (
SELECT dt,
device_name,
device_type,
device_floor
FROM (
SELECT dt,
hr,
device_name,
device_type,
device_floor,
AVG(event_value) AS temperature_hourly_avg
FROM (
SELECT CAST(log_time AS DATE) AS dt,
EXTRACT(HOUR FROM log_time) AS hr,
device_name,
device_type,
device_floor,
event_value
FROM logs3
WHERE event_type = 'temperature'
) AS r
GROUP BY dt,
hr,
device_name,
device_type,
device_floor
) AS s
GROUP BY dt,
device_name,
device_type,
device_floor
HAVING MAX(temperature_hourly_avg) - MIN(temperature_hourly_avg) >= 25.0
)
SELECT DISTINCT device_name,
device_type,
device_floor,
'WINTER'
FROM temperature
WHERE dt >= DATE '2018-12-01'
AND dt < DATE '2019-03-01'
UNION
SELECT DISTINCT device_name,
device_type,
device_floor,
'SUMMER'
FROM temperature
WHERE dt >= DATE '2019-06-01'
AND dt < DATE '2019-09-01';
-- Q3.6: For each device category, what are the monthly power consumption metrics?
SELECT yr,
mo,
SUM(coffee_hourly_avg) AS coffee_monthly_sum,
AVG(coffee_hourly_avg) AS coffee_monthly_avg,
SUM(printer_hourly_avg) AS printer_monthly_sum,
AVG(printer_hourly_avg) AS printer_monthly_avg,
SUM(projector_hourly_avg) AS projector_monthly_sum,
AVG(projector_hourly_avg) AS projector_monthly_avg,
SUM(vending_hourly_avg) AS vending_monthly_sum,
AVG(vending_hourly_avg) AS vending_monthly_avg
FROM (
SELECT dt,
yr,
mo,
hr,
AVG(coffee) AS coffee_hourly_avg,
AVG(printer) AS printer_hourly_avg,
AVG(projector) AS projector_hourly_avg,
AVG(vending) AS vending_hourly_avg
FROM (
SELECT CAST(log_time AS DATE) AS dt,
EXTRACT(YEAR FROM log_time) AS yr,
EXTRACT(MONTH FROM log_time) AS mo,
EXTRACT(HOUR FROM log_time) AS hr,
CASE WHEN device_name LIKE 'coffee%' THEN event_value END AS coffee,
CASE WHEN device_name LIKE 'printer%' THEN event_value END AS printer,
CASE WHEN device_name LIKE 'projector%' THEN event_value END AS projector,
CASE WHEN device_name LIKE 'vending%' THEN event_value END AS vending
FROM logs3
WHERE device_type = 'meter'
) AS r
GROUP BY dt,
yr,
mo,
hr
) AS s
GROUP BY yr,
mo
ORDER BY yr,
mo;
```
Данные также доступны для работы с интерактивными запросами через [Playground](https://gh-api.clickhouse.tech/play?user=play), [пример](https://gh-api.clickhouse.tech/play?user=play#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).
[Оригинальная статья](https://clickhouse.tech/docs/ru/getting_started/example_datasets/brown-benchmark/) <!--hide-->

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@ -1355,6 +1355,52 @@ SELECT arrayAvg(x -> (x * x), [2, 4]) AS res;
└─────┘
```
**Синтаксис**
``` sql
arraySum(arr)
```
**Возвращаемое значение**
- Число.
Тип: [Int](../../sql-reference/data-types/int-uint.md) или [Float](../../sql-reference/data-types/float.md).
**Параметры**
- `arr` — [Массив](../../sql-reference/data-types/array.md).
**Примеры**
Запрос:
```sql
SELECT arraySum([2,3]) AS res;
```
Результат:
``` text
┌─res─┐
│ 5 │
└─────┘
```
Запрос:
``` sql
SELECT arraySum(x -> x*x, [2, 3]) AS res;
```
Результат:
``` text
┌─res─┐
│ 13 │
└─────┘
```
## arrayCumSum(\[func,\] arr1, …) {#arraycumsumfunc-arr1}
Возвращает массив из частичных сумм элементов исходного массива (сумма с накоплением). Если указана функция `func`, то значения элементов массива преобразуются этой функцией перед суммированием.

63
docs/ru/sql-reference/table-functions/mysql.md
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@ -7,6 +7,8 @@ toc_title: mysql
Позволяет выполнять запросы `SELECT` над данными, хранящимися на удалённом MySQL сервере.
**Синтаксис**
``` sql
mysql('host:port', 'database', 'table', 'user', 'password'[, replace_query, 'on_duplicate_clause']);
```
@ -23,13 +25,13 @@ mysql('host:port', 'database', 'table', 'user', 'password'[, replace_query, 'on_
- `password` — пароль пользователя.
- `replace_query` — флаг, отвечающий за преобразование запросов `INSERT INTO` в `REPLACE INTO`. Если `replace_query=1`, то запрос заменяется.
- `replace_query` — флаг, отвечающий за преобразование запросов `INSERT INTO` в `REPLACE INTO`. Возможные значения:
- `0` - выполняется запрос `INSERT INTO`.
- `1` - выполняется запрос `REPLACE INTO`.
- `on_duplicate_clause` — выражение `ON DUPLICATE KEY on_duplicate_clause`, добавляемое в запрос `INSERT`.
- `on_duplicate_clause` — выражение `ON DUPLICATE KEY on_duplicate_clause`, добавляемое в запрос `INSERT`. Может быть передано только с помощью `replace_query = 0` (если вы одновременно передадите `replace_query = 1` и `on_duplicate_clause`, будет сгенерировано исключение).
Пример: `INSERT INTO t (c1,c2) VALUES ('a', 2) ON DUPLICATE KEY UPDATE c2 = c2 + 1`, где `on_duplicate_clause` это `UPDATE c2 = c2 + 1`. Чтобы узнать какие `on_duplicate_clause` можно использовать с секцией `ON DUPLICATE KEY` обратитесь к документации MySQL.
Чтобы указать `'on_duplicate_clause'` необходимо передать `0` в параметр `replace_query`. Если одновременно передать `replace_query = 1` и `'on_duplicate_clause'`, то ClickHouse сгенерирует исключение.
Пример: `INSERT INTO t (c1,c2) VALUES ('a', 2) ON DUPLICATE KEY UPDATE c2 = c2 + 1`, где `on_duplicate_clause` это `UPDATE c2 = c2 + 1;`
Простые условия `WHERE` такие как `=, !=, >, >=, <, =` выполняются на стороне сервера MySQL.
@ -39,46 +41,59 @@ mysql('host:port', 'database', 'table', 'user', 'password'[, replace_query, 'on_
Объект таблицы с теми же столбцами, что и в исходной таблице MySQL.
## Пример использования {#primer-ispolzovaniia}
!!! note "Примечание"
Чтобы отличить табличную функцию `mysql (...)` в запросе `INSERT` от имени таблицы со списком имен столбцов, используйте ключевые слова `FUNCTION` или `TABLE FUNCTION`. См. примеры ниже.
**Примеры**
Таблица в MySQL:
``` text
mysql> CREATE TABLE `test`.`test` (
-> `int_id` INT NOT NULL AUTO_INCREMENT,
-> `int_nullable` INT NULL DEFAULT NULL,
-> `float` FLOAT NOT NULL,
-> `float_nullable` FLOAT NULL DEFAULT NULL,
-> PRIMARY KEY (`int_id`));
Query OK, 0 rows affected (0,09 sec)
mysql> insert into test (`int_id`, `float`) VALUES (1,2);
Query OK, 1 row affected (0,00 sec)
mysql> INSERT INTO test (`int_id`, `float`) VALUES (1,2);
mysql> select * from test;
+--------+--------------+-------+----------------+
| int_id | int_nullable | float | float_nullable |
+--------+--------------+-------+----------------+
| 1 | NULL | 2 | NULL |
+--------+--------------+-------+----------------+
1 row in set (0,00 sec)
mysql> SELECT * FROM test;
+--------+-------+
| int_id | float |
+--------+-------+
| 1 | 2 |
+--------+-------+
```
Получение данных в ClickHouse:
``` sql
SELECT * FROM mysql('localhost:3306', 'test', 'test', 'bayonet', '123')
SELECT * FROM mysql('localhost:3306', 'test', 'test', 'bayonet', '123');
```
``` text
┌─int_id─┬─int_nullable─┬─float─┬─float_nullable─┐
│ 1 │ ᴺᵁᴸᴸ │ 2 │ ᴺᵁᴸᴸ │
└────────┴──────────────┴───────┴────────────────┘
┌─int_id─┬─float─┐
│ 1 │ 2 │
└────────┴───────┘
```
## Смотрите также {#smotrite-takzhe}
Замена и вставка:
```sql
INSERT INTO FUNCTION mysql('localhost:3306', 'test', 'test', 'bayonet', '123', 1) (int_id, float) VALUES (1, 3);
INSERT INTO TABLE FUNCTION mysql('localhost:3306', 'test', 'test', 'bayonet', '123', 0, 'UPDATE int_id = int_id + 1') (int_id, float) VALUES (1, 4);
SELECT * FROM mysql('localhost:3306', 'test', 'test', 'bayonet', '123');
```
``` text
┌─int_id─┬─float─┐
│ 1 │ 3 │
│ 2 │ 4 │
└────────┴───────┘
```
**Смотрите также**
- [Движок таблиц ‘MySQL’](../../sql-reference/table-functions/mysql.md)
- [Использование MySQL как источника данных для внешнего словаря](../../sql-reference/table-functions/mysql.md#dicts-external_dicts_dict_sources-mysql)
[Оригинальная статья](https://clickhouse.tech/docs/ru/query_language/table_functions/mysql/) <!--hide-->
[Оригинальная статья](https://clickhouse.tech/docs/ru/sql-reference/table_functions/mysql/) <!--hide-->