Data Science. SQL hub
По всем вопросам- @workakkk @itchannels_telegram - 🔥лучшие ит-каналы @ai_machinelearning_big_data - Machine learning @pythonl - Python @pythonlbooks- python книги📚 @datascienceiot - ml книги📚 РКН: https://vk.cc/cIi9vo #VRHSZ
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📈 Analytical overview of Telegram channel Data Science. SQL hub
Channel Data Science. SQL hub (@sqlhub) in the Russian language segment is an active participant. Currently, the community unites 36 038 subscribers, ranking 3 728 in the Technologies & Applications category and 17 587 in the Russia region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 36 038 subscribers.
According to the latest data from 06 November, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 69 over the last 30 days and by -6 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 9.44%. Within the first 24 hours after publication, content typically collects 3.88% reactions from the total number of subscribers.
- Post reach: On average, each post receives 3 402 views. Within the first day, a publication typically gains 1 398 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 8.
- Thematic interests: Content is focused on key topics such as sql, индекс, postgres, index, sqlite.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“По всем вопросам- @workakkk
@itchannels_telegram - 🔥лучшие ит-каналы
@ai_machinelearning_big_data - Machine learning
@pythonl - Python
@pythonlbooks- python книги📚
@datascienceiot - ml книги📚
РКН: https://vk.cc/cIi9vo
#VRHSZ”
Thanks to the high frequency of updates (latest data received on 07 November, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.
-- возвращает точное количество записей, но медленно
select count(*) as exact_count from table_name;
-- возвращает приблизительное количество записей, но быстро
-- точность больше, чем в следующем запросе, но от БД требуется актуальная статистика по таблице
select reltuples::bigint as estimate_count
from pg_class
where oid = 'public.table_name'::regclass;
-- возвращает приблизительное количество записей, но быстро
-- точность меньше, чем в предыдущем запросе, но от БД не требуется актуальная статистика по таблице
-- преимущество этого подхода в том, что можно задавать условие выборки
select 100 * count(*) as estimate_count
from table_name tablesample system (1)
where ...;
@sqlhubSELECT
(NULL, NULL) IS NULL as "(NULL, NULL) IS NULL", --true
(NULL, NULL) IS NOT NULL as "(NULL, NULL) IS NOT NULL", --false
NOT (NULL, NULL) IS NULL as "NOT (NULL, NULL) IS NULL", --false
(1, NULL) IS NULL as "(1, NULL) IS NULL", --false
(1, NULL) IS NOT NULL as "(1, NULL) IS NOT NULL", --false --!!!
NOT (1, NULL) IS NULL as "NOT (1, NULL) IS NULL" --true --!!!
@sqlhub
