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DOCS-548: Extended adopters list
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49
docs/en/introduction/adopters.md
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@ -6,26 +6,71 @@
| Company | Industry | Usecase | Cluster Size | (Un)Compressed Data Size<abbr title="of single replica"><sup>*</sup></abbr> | Reference |
| --- | --- | --- | --- | --- | --- |
| [2gis](https://2gis.ru) | Maps | Monitoring | — | — | [Talk in Russian, July 2019](https://youtu.be/58sPkXfq6nw) |
| [Aloha Browser](https://alohabrowser.com/) | Mobile App | Browser backend | — | — | [Slides in Russian, May 2019](https://github.com/yandex/clickhouse-presentations/blob/master/meetup22/aloha.pdf) |
| [Amadeus](https://amadeus.com/) | Travel | Analytics | — | — | [Press Release, April 2018](https://www.altinity.com/blog/2018/4/5/amadeus-technologies-launches-investment-and-insights-tool-based-on-machine-learning-and-strategy-algorithms) |
| [Appsflyer](https://www.appsflyer.com) | Mobile analytics | Main product | — | — | [Talk in Russian, July 2019](https://www.youtube.com/watch?v=M3wbRlcpBbY) |
| [ArenaData](https://arenadata.tech/) | Data Platform | Main product | — | — | [Slides in Russian, December 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup38/indexes.pdf) |
| [Badoo](https://badoo.com) | Dating | Timeseries | — | — | [Slides in Russian, December 2019](https://presentations.clickhouse.tech/meetup38/forecast.pdf) |
| [Benocs](https://www.benocs.com/) | Network Telemetry and Analytics | Main Product | — | — | [Slides in English, October 2017](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup9/lpm.pdf) |
| [Bloomberg](https://www.bloomberg.com/) | Finance, Media | Monitoring | 102 servers | — | [Slides, May 2018](https://www.slideshare.net/Altinity/http-analytics-for-6m-requests-per-second-using-clickhouse-by-alexander-bocharov) |
| [Bloxy](https://bloxy.info) | Blockchain | Analytics | — | — | [Slides in Russian, August 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup17/4_bloxy.pptx) |
| `Dataliance/UltraPower` | Telecom | Analytics | — | — | [Slides in Chinese, January 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup12/telecom.pdf) |
| [CARTO](https://carto.com/) | Business Intelligence | Geo analytics | — | — | [Geospatial processing with Clickhouse](https://carto.com/blog/geospatial-processing-with-clickhouse/) |
| [CERN](http://public.web.cern.ch/public/) | Research | Experiment | — | — | [Press release, April 2012](https://www.yandex.com/company/press_center/press_releases/2012/2012-04-10/) |
| [Cisco](http://public.web.cern.ch/public/) | Networking | Traffic analysis | — | — | [Lightning talk, October 2019](https://youtu.be/-hI1vDR2oPY?t=5057) |
| [Cisco](http://cisco.com/) | Networking | Traffic analysis | — | — | [Lightning talk, October 2019](https://youtu.be/-hI1vDR2oPY?t=5057) |
| [Citadel Securities](https://www.citadelsecurities.com/) | Finance | — | — | — | [Contribution, March 2019](https://github.com/ClickHouse/ClickHouse/pull/4774) |
| [Citymobil](https://city-mobil.ru) | Taxi | Analytics | — | — | [Blog Post in Russian, March 2020](https://habr.com/en/company/citymobil/blog/490660/) |
| [ContentSquare](https://contentsquare.com) | Web analytics | Main product | — | — | [Blog post in French, November 2018](http://souslecapot.net/2018/11/21/patrick-chatain-vp-engineering-chez-contentsquare-penser-davantage-amelioration-continue-que-revolution-constante/) |
| [Cloudflare](https://cloudflare.com) | CDN | Traffic analysis | 36 servers | — | [Blog post, May 2017](https://blog.cloudflare.com/how-cloudflare-analyzes-1m-dns-queries-per-second/), [Blog post, March 2018](https://blog.cloudflare.com/http-analytics-for-6m-requests-per-second-using-clickhouse/) |
| [Corunet](https://coru.net/) | Analytics | Main product | — | — | [Slides in English, April 2019 ](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup21/predictive_models.pdf) |
| [CraiditX 氪信](https://creditx.com) | Finance AI | Analysis | — | — | [Slides in English, November 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup33/udf.pptx) |
| [Criteo/Storetail](https://www.criteo.com/) | Retail | Main product | — | — | [Slides in English, October 2018 ](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup18/3_storetail.pptx) |
| [Deutsche Bank](https://db.com) | Finance | BI Analytics | — | — | [Slides in English, October 2019](https://bigdatadays.ru/wp-content/uploads/2019/10/D2-H3-3_Yakunin-Goihburg.pdf) |
| [Diva-e](https://www.diva-e.com) | Digital consulting | Main Product | — | — | [Slides in English, September 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup29/ClickHouse-MeetUp-Unusual-Applications-sd-2019-09-17.pdf) |
| [Exness](https://www.exness.com) | Trading | Metrics, Logging | — | — | [Talk in Russian, May 2019](https://youtu.be/_rpU-TvSfZ8?t=3215) |
| [Geniee](https://geniee.co.jp) | Ad network | Main product | — | — | [Blog post in Japanese, July 2017](https://tech.geniee.co.jp/entry/2017/07/20/160100) |
| [LifeStreet](https://cloudflare.com) | Ad network | Main product | — | — | [Blog post in Russian, February 2017](https://habr.com/en/post/322620/) |
| [HUYA](https://www.huya.com/) | Video Streaming | Analytics | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/7.%20ClickHouse万亿数据分析实践%20李本旺(sundy-li)%20虎牙.pdf) |
| [Idealista](https://www.idealista.com) | Real Estate | Analytics | — | — | [Blog Post in English, April 2019](https://clickhouse.yandex/blog/en/clickhouse-meetup-in-madrid-on-april-2-2019) |
| [Infovista](https://www.infovista.com/) | Networks | Analytics | — | — | [Slides in English, October 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup30/infovista.pdf) |
| [InnoGames](https://www.innogames.com) | Games | Metrics, Logging | — | — | [Slides in Russian, September 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup28/graphite_and_clickHouse.pdf) |
| [Integros](https://integros.com) | Platform for video services | Analytics | — | — | [Slides in Russian, May 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup22/strategies.pdf) |
| [Kodiak Data](https://www.kodiakdata.com/) | Clouds | Main product | — | — | [Slides in Engish, April 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup13/kodiak_data.pdf) |
| [Kontur](https://kontur.ru) | Software Development | Metrics | — | — | [Talk in Russian, November 2018](https://www.youtube.com/watch?v=U4u4Bd0FtrY) |
| [LifeStreet](https://cloudflare.com) | Ad network | Main product | 60 servers in 3 replicas | 2-2.5 PiB | [Blog post in Russian, February 2017](https://habr.com/en/post/322620/) |
| [Mail.ru Cloud Solutions](https://mcs.mail.ru/) | Cloud services | Main product | — | — | [Running ClickHouse Instance, in Russian](https://mcs.mail.ru/help/db-create/clickhouse#) |
| [MessageBird](https://www.messagebird.com) | Telecommunications | Statistics | — | — | [Slides in English, November 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup20/messagebird.pdf) |
| [MGID](https://www.mgid.com/) | Ad network | Web-analytics | — | — | [Our experience in implementing analytical DBMS ClickHouse, in Russian](http://gs-studio.com/news-about-it/32777----clickhouse---c) |
| [OneAPM](https://www.oneapm.com/) | Monitorings and Data Analysis | Main product | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/8.%20clickhouse在OneAPM的应用%20杜龙.pdf) |
| [Pragma Innovation](http://www.pragma-innovation.fr/) | Telemetry and Big Data Analysis | Main product | — | — | [Slides in English, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup18/4_pragma_innovation.pdf) |
| [QINGCLOUD](https://www.qingcloud.com/) | Cloud services | Main product | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/4.%20Cloud%20%2B%20TSDB%20for%20ClickHouse%20张健%20QingCloud.pdf) |
| [Qrator](https://qrator.net) | DDoS protection | Main product | — | — | [Blog Post, March 2019](https://blog.qrator.net/en/clickhouse-ddos-mitigation_37/) |
| [Beijing PERCENT Information Technology Co., Ltd.](https://www.percent.cn/) | Analytics | Main Product | — | — | [Slides in Chinese, June 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup24/4.%20ClickHouse万亿数据双中心的设计与实践%20.pdf) |
| [Rambler](https://rambler.ru) | Internet services | Analytics | — | — | [Talk in Russian, April 2018](https://medium.com/@ramblertop/разработка-api-clickhouse-для-рамблер-топ-100-f4c7e56f3141) |
| [Tencent](https://www.tencent.com) | Messaging | Logging | — | — | [Talk in Chinese, November 2019](https://youtu.be/T-iVQRuw-QY?t=5050) |
| [Traffic Stars](https://trafficstars.com/) | AD network | — | — | — | [Slides in Russian, May 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup15/lightning/ninja.pdf) |
| [S7 Airlines](https://www.s7.ru) | Airlines | Metrics, Logging | — | — | [Talk in Russian, March 2019](https://www.youtube.com/watch?v=nwG68klRpPg&t=15s) |
| [SEMrush](https://www.semrush.com/) | Marketing | Main product | — | — | [Slides in Russian, August 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup17/5_semrush.pdf) |
| [scireum GmbH](https://www.scireum.de/) | e-Commerce | Main product | — | — | [Talk in German, February 2020](https://www.youtube.com/watch?v=7QWAn5RbyR4) |
| [Sentry](https://sentry.io/) | Software developer | Backend for product | — | — | [Blog Post in English, May 2019](https://blog.sentry.io/2019/05/16/introducing-snuba-sentrys-new-search-infrastructure) |
| [SGK](http://www.sgk.gov.tr/wps/portal/sgk/tr) | Goverment Social Security | Analytics | — | — | [Slides in English, November 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup35/ClickHouse%20Meetup-Ramazan%20POLAT.pdf) |
| [seo.do](https://seo.do/) | Analytics | Main product | — | — | [Slides in English, November 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup35/CH%20Presentation-%20Metehan%20Çetinkaya.pdf) |
| [Sina](http://english.sina.com/index.html) | News | — | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/6.%20ClickHouse最佳实践%20高鹏_新浪.pdf) |
| [SMI2](https://smi2.ru/) | News | Analytics | — | — | [Blog Post in Russian, November 2017](https://habr.com/ru/company/smi2/blog/314558/) |
| [Splunk](https://www.splunk.com/) | Business Analytics | Main product | — | — | [Slides in English, January 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup12/splunk.pdf) |
| [Spotify](https://www.spotify.com) | Music | Experimentation | — | — | [Slides, July 2018](https://www.slideshare.net/glebus/using-clickhouse-for-experimentation-104247173) |
| [Tencent](https://www.tencent.com) | Big Data | Data processing | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/5.%20ClickHouse大数据集群应用_李俊飞腾讯网媒事业部.pdf) |
| [Uber](https://www.uber.com) | Taxi | Logging | — | — | [Slides, February 2020](https://presentations.clickhouse.tech/meetup40/ml.pdf) |
| [VKontakte](https://vk.com) | Social Network | Statistics, Logging | — | — | [Slides in Russian, August 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup17/3_vk.pdf) |
| [Wisebits](https://wisebits.com/) | IT Solutions | Analytics | — | — | [Slides in Russian, May 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup22/strategies.pdf) |
| [Xiaoxin Tech.](https://www.xiaoheiban.cn/) | Education | Common purpose | — | — | [Slides in English, November 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup33/sync-clickhouse-with-mysql-mongodb.pptx) |
| [Ximalaya](https://www.ximalaya.com/) | Audio sharing | OLAP | — | — | [Slides in English, November 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup33/ximalaya.pdf) |
| [Yandex Cloud](https://cloud.yandex.ru/services/managed-clickhouse) | Public Cloud | Main product | — | — | [Talk in Russian, December 2019](https://www.youtube.com/watch?v=pgnak9e_E0o) |
| [Yandex DataLens](https://cloud.yandex.ru/services/datalens) | Business Intelligence | Main product | — | — | [Slides in Russian, December 2019](https://presentations.clickhouse.tech/meetup38/datalens.pdf) |
| [Yandex Market](https://market.yandex.ru/) | e-Commerce | Metrics, Logging | — | — | [Talk in Russian, January 2019](https://youtu.be/_l1qP0DyBcA?t=478) |
| [Yandex Metrica](https://metrica.yandex.com) | Web analytics | Main product | 360 servers in one cluster, 1862 servers in one department | 66.41 PiB / 5.68 PiB | [Slides, February 2020](https://presentations.clickhouse.tech/meetup40/introduction/#13) |
| [ЦВТ](https://htc-cs.ru/) | Software Development | Metrics, Logging | — | — | [Blog Post, March 2019, in Russian](https://vc.ru/dev/62715-kak-my-stroili-monitoring-na-prometheus-clickhouse-i-elk) |
| [МКБ](https://mkb.ru/) | Bank | Web-system monitoring | — | — | [Slides in Russian, September 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup28/mkb.pdf) |
| [金数据](https://jinshuju.net) | BI Analytics | Main product | — | — | [Slides in Chinese, October 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup24/3.%20金数据数据架构调整方案Public.pdf) |
[Original article](https://clickhouse.tech/docs/en/introduction/adopters/) <!--hide-->

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@ -96,7 +96,7 @@ Maximum number of bytes before sorting.
What to do if the number of rows received before sorting exceeds one of the limits: 'throw' or 'break'. By default, throw.
## max_result_rows
## max_result_rows {#setting-max_result_rows}
Limit on the number of rows in the result. Also checked for subqueries, and on remote servers when running parts of a distributed query.
@ -107,7 +107,27 @@ Limit on the number of bytes in the result. The same as the previous setting.
## result_overflow_mode
What to do if the volume of the result exceeds one of the limits: 'throw' or 'break'. By default, throw.
Using 'break' is similar to using LIMIT.
Using 'break' is similar to using LIMIT. Break interrupts execution only at the block level. This means that amount of returned rows is greater than [max_result_rows](#setting-max_result_rows), multiple of [max_block_size](settings.md#setting-max_block_size) and depends on [max_threads](settings.md#settings-max_threads).
Пример:
```sql
SET max_threads = 3, max_block_size = 3333;
SET max_result_rows = 3334, result_overflow_mode = 'break';
SELECT *
FROM numbers_mt(100000)
FORMAT Null;
```
Результат:
```text
6666 rows in set. ...
```
## max_execution_time

2
docs/en/operations/settings/settings.md
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@ -406,7 +406,7 @@ Possible values:
Default value: 1.
## max_block_size
## max_block_size {#setting-max_block_size}
In ClickHouse, data is processed by blocks (sets of column parts). The internal processing cycles for a single block are efficient enough, but there are noticeable expenditures on each block. The `max_block_size` setting is a recommendation for what size of block (in number of rows) to load from tables. The block size shouldn't be too small, so that the expenditures on each block are still noticeable, but not too large, so that the query with LIMIT that is completed after the first block is processed quickly. The goal is to avoid consuming too much memory when extracting a large number of columns in multiple threads, and to preserve at least some cache locality.

4
docs/en/query_language/agg_functions/reference.md
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@ -1034,7 +1034,7 @@ Alias: `medianExactWeighted`.
- `level` — Level of quantile. Optional parameter. Constant floating-point number from 0 to 1. We recommend using a `level` value in the range of `[0.01, 0.99]`. Default value: 0.5. At `level=0.5` the function calculates [median](https://en.wikipedia.org/wiki/Median).
- `expr` — Expression over the column values resulting in numeric [data types](../../data_types/index.md#data_types), [Date](../../data_types/date.md) or [DateTime](../../data_types/datetime.md).
- `weight` — Column with weights of sequence elements. Weight is a number of value occurrences.
- `weight` — Column with weights of sequence members. Weight is a number of value occurrences.
**Returned value**
@ -1300,7 +1300,7 @@ Result:
## quantileTDigestWeighted {#quantiletdigestweighted}
Computes an approximate [quantile](https://en.wikipedia.org/wiki/Quantile) of a numeric data sequence using the [t-digest](https://github.com/tdunning/t-digest/blob/master/docs/t-digest-paper/histo.pdf) algorithm. The function takes into account the weight of each sequence number. The maximum error is 1%. Memory consumption is `log(n)`, where `n` is a number of values.
Computes an approximate [quantile](https://en.wikipedia.org/wiki/Quantile) of a numeric data sequence using the [t-digest](https://github.com/tdunning/t-digest/blob/master/docs/t-digest-paper/histo.pdf) algorithm. The function takes into account the weight of each sequence member. The maximum error is 1%. Memory consumption is `log(n)`, where `n` is a number of values.
The performance of the function is lower than performance of [quantile](#quantile) or [quantileTiming](#quantiletiming). In terms of the ratio of State size to precision, this function is much better than `quantile`.

4
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@ -97,7 +97,7 @@
Что делать, если количество строк, полученное перед сортировкой, превысило одно из ограничений: throw или break. По умолчанию: throw.
## max_result_rows
## max_result_rows {#setting-max_result_rows}
Ограничение на количество строк результата. Проверяются также для подзапросов и на удалённых серверах при выполнении части распределённого запроса.
@ -109,7 +109,7 @@
Что делать, если объём результата превысил одно из ограничений: throw или break. По умолчанию: throw.
Использование break по смыслу похоже на LIMIT. Break прерывает выполнение только на уровне блока. Т.е. число строк которые вернет запрос будет больше чем ограничение [max_result_rows](#max_result_rows), кратно [max_block_size](settings.md#max_block_size) и зависит от [max_threads](settings.md#settings-max_threads).
Использование break по смыслу похоже на LIMIT. Break прерывает выполнение только на уровне блока. Т.е. число строк которые вернет запрос будет больше чем ограничение [max_result_rows](#setting-max_result_rows), кратно [max_block_size](settings.md#setting-max_block_size) и зависит от [max_threads](settings.md#settings-max_threads).
Пример:
```sql

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docs/ru/operations/settings/settings.md
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@ -377,7 +377,7 @@ Ok.
Значение по умолчанию: 0.
## max_block_size
## max_block_size {#setting-max_block_size}
Данные в ClickHouse обрабатываются по блокам (наборам кусочков столбцов). Внутренние циклы обработки для одного блока достаточно эффективны, но есть заметные издержки на каждый блок. Настройка `max_block_size` — это рекомендация, какой размер блока (в количестве строк) загружать из таблиц. Размер блока не должен быть слишком маленьким, чтобы затраты на каждый блок были заметны, но не слишком велики, чтобы запрос с LIMIT, который завершается после первого блока, обрабатывался быстро. Цель состоит в том, чтобы не использовалось слишком много оперативки при вынимании большого количества столбцов в несколько потоков; чтобы оставалась хоть какая-нибудь кэш-локальность.

22
docs/ru/query_language/agg_functions/reference.md
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@ -860,7 +860,7 @@ FROM t
quantile(level)(expr)
```
Альяс: `median`.
Алиас: `median`.
**Параметры**
@ -870,7 +870,7 @@ quantile(level)(expr)
**Возвращаемое значение**
- Приблизительную квантиль заданного уровня.
- Приблизительный квантиль заданного уровня.
Тип:
@ -926,7 +926,7 @@ SELECT quantile(val) FROM t
quantileDeterministic(level)(expr, determinator)
```
Альяс: `medianDeterministic`.
Алиас: `medianDeterministic`.
**Параметры**
@ -936,7 +936,7 @@ quantileDeterministic(level)(expr, determinator)
**Возвращаемое значение**
- Приблизительную квантиль заданного уровня.
- Приблизительный квантиль заданного уровня.
Тип:
@ -993,7 +993,7 @@ SELECT quantileDeterministic(val, 1) FROM t
quantileExact(level)(expr)
```
Альяс: `medianExact`.
Алиас: `medianExact`.
**Параметры**
@ -1046,7 +1046,7 @@ SELECT quantileExact(number) FROM numbers(10)
quantileExactWeighted(level)(expr, weight)
```
Альяс: `medianExactWeighted`.
Алиас: `medianExactWeighted`.
**Параметры**
@ -1110,7 +1110,7 @@ SELECT quantileExactWeighted(n, val) FROM t
quantileTiming(level)(expr)
```
Альяс: `medianTiming`.
Алиас: `medianTiming`.
**Параметры**
@ -1192,7 +1192,7 @@ SELECT quantileTiming(response_time) FROM t
quantileTimingWeighted(level)(expr, weight)
```
Альяс: `medianTimingWeighted`.
Алиас: `medianTimingWeighted`.
**Параметры**
@ -1276,7 +1276,7 @@ SELECT quantileTimingWeighted(response_time, weight) FROM t
quantileTDigest(level)(expr)
```
Альяс: `medianTDigest`.
Алиас: `medianTDigest`.
**Параметры**
@ -1333,7 +1333,7 @@ SELECT quantileTDigest(number) FROM numbers(10)
quantileTDigestWeighted(level)(expr, weight)
```
Альяс: `medianTDigest`.
Алиас: `medianTDigest`.
**Параметры**
@ -1343,7 +1343,7 @@ quantileTDigestWeighted(level)(expr, weight)
**Возвращаемое значение**
- Приблизительную квантиль заданного уровня.
- Приблизительный квантиль заданного уровня.
Тип:

1
docs/toc_en.yml
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@ -75,6 +75,7 @@ nav:
- 'MaterializedView': 'operations/table_engines/materializedview.md'
- 'Memory': 'operations/table_engines/memory.md'
- 'Buffer': 'operations/table_engines/buffer.md'
- 'Generate': 'operations/table_engines/generate.md'
- 'Database Engines':
- 'Introduction': 'database_engines/index.md'

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@ -109,6 +109,7 @@ nav:
- 'MaterializedView': 'operations/table_engines/materializedview.md'
- 'Memory': 'operations/table_engines/memory.md'
- 'Buffer': 'operations/table_engines/buffer.md'
- 'Generate': 'operations/table_engines/generate.md'
- 'SQL Reference':
- 'hidden': 'query_language/index.md'

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@ -79,7 +79,7 @@ nav:
- 'MaterializedView': 'operations/table_engines/materializedview.md'
- 'Memory': 'operations/table_engines/memory.md'
- 'Buffer': 'operations/table_engines/buffer.md'
- 'Generate': 'operations/table_engines/generate.md'
- 'SQL Reference':
- 'hidden': 'query_language/index.md'
- 'Syntax': 'query_language/syntax.md'
@ -143,7 +143,7 @@ nav:
- 'hdfs': 'query_language/table_functions/hdfs.md'
- 'input': 'query_language/table_functions/input.md'
- 'generate': 'query_language/table_functions/generate.md'
- 'Dictionaries':
- 'Dictionaries':
- 'Introduction': 'query_language/dicts/index.md'
- 'External Dictionaries':
- 'General Description': 'query_language/dicts/external_dicts.md'

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@ -80,6 +80,7 @@ nav:
- 'MaterializedView': 'operations/table_engines/materializedview.md'
- 'Memory': 'operations/table_engines/memory.md'
- 'Buffer': 'operations/table_engines/buffer.md'
- 'Generate': 'operations/table_engines/generate.md'
- 'Справка по SQL':
- 'hidden': 'query_language/index.md'

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@ -109,6 +109,7 @@ nav:
- 'MaterializedView': 'operations/table_engines/materializedview.md'
- 'Memory': 'operations/table_engines/memory.md'
- 'Buffer': 'operations/table_engines/buffer.md'
- 'Generate': 'operations/table_engines/generate.md'
- 'SQL语法':
- 'hidden': 'query_language/index.md'