zX41ZdbW

42 ms·

601.
by zX41ZdbW 4y ago
My friend recently bought Vision Five 2, and we've tested its performance, comparing to Vision Five 1. Here are the results: https://twitter.com/ClickHouseDB/status/1619767689861550081 The outcomes: - it show
602.
by zX41ZdbW 4y ago
Interesting that both Plausible and CloudFlare are using ClickHouse as a backend: https://github.com/plausible/analytics https://news.ycombinator.com/item?id=24846300 https://github.com&#x2F
603.
by zX41ZdbW 4y ago
You can also use this tool to amplify the data volume for tests. For example, based on a dataset of 100 million records from ClickBench, I created a dataset of 100 billion records. Here is a description of how to generate this dataset: htt
604.
by zX41ZdbW 4y ago
ClickHouse has Geo data types and functions (such as import and export from WKT, GeoJSON) and special features to accelerate geospatial queries. For example, polygonal dictionaries allow doing coordinate-to-region lookups using the indexed
605.
by zX41ZdbW 4y ago
> DuckDB Drawbacks > It’s not all roses with DuckDB. The CLI is still relatively new and sometimes had glitches like the progress bar not completing or hangs or crashes. As mentioned above, more syntax is needed for some queries since
606.
by zX41ZdbW 4y ago
When we selected Apache 2.0 license for ClickHouse[1] in 2016, the reasons were the following: Why it is better than MIT and BSD: - it contains the "3. Grant of Patent License." Why it is better than GPL and AGPL: - it does not im
607.
by zX41ZdbW 4y ago
I work in ClickHouse, and I do competitive research. Here are my observations: BigQuery bills over uncompressed data ($20/TB/month), and with the typical compression ratio, it is very expensive. The processing is also very expensi
608.
by zX41ZdbW 4y ago
It did not get confused by my heavy accent, and the result is surprisingly good: https://jonatron.github.io/fosdem2023whisper/files/fast_data... Original: https://www.youtube.com/watch?v=JlcI2Vfz_u
609.
by zX41ZdbW 4y ago
Also, ClickHouse is the only DBMS implementing aggregate function states as data types to allow them to be stored in tables, saved, loaded, and merged. It allows incremental, continuous aggregate tables. Other DBMSes like TimescaleDB implem
610.
by zX41ZdbW 4y ago
It's worth noting that ClickHouse supports both the standard SQL and the extensions. For example, the standard SQL way to write filtered aggregates is: SELECT avg(number) FILTER (WHERE number > 50) FROM numbers(100) See ht
611.
by zX41ZdbW 4y ago
I also did this when searching for a fast string-to-float conversion function for ClickHouse: https://github.com/ClickHouse/ClickHouse/blob/master/src/IO/... - we create a table, insert all fou
612.
by zX41ZdbW 4y ago
You can add ClickHouse to the list. While it is not a new database - it has been around since 2016, and in many areas it became almost ubiquitous, it is still less known to many potential users than it should be. Many algorithms and ideas o
613.
by zX41ZdbW 4y ago
You can query Meilisearch directly from ClickHouse with the integrated table function: https://github.com/ClickHouse/ClickHouse/pull/33332 This feature was a student project, and I'm not sure if it will
614.
by zX41ZdbW 4y ago
It's worth noting, that the vectorized query execution, and many algorithms in Apache Doris are adopted from ClickHouse - the leading OLAP DBMS: https://github.com/search?q=repo%3Aapache%2Fdoris%20clickhou... And it is
615.
by zX41ZdbW 4y ago
Check the list of companies using ClickHouse: https://clickhouse.com/docs/en/introduction/adopters/
616.
by zX41ZdbW 4y ago
Looking forward to PRQL integration in ClickHouse: https://github.com/ClickHouse/ClickHouse/issues/42194
617.
by zX41ZdbW 4y ago
I did not find a reliable way to query MongoDB with SQL: https://github.com/ClickHouse/ClickBench/blob/main/mongodb/q... It looks like it's only available in the Atlas service. Please correct m
618.
by zX41ZdbW 4y ago
My presentation from FOSDEM 2023 is very sympathetic to the "Big data is dead" statement: https://www.youtube.com/watch?v=JlcI2Vfz_uk It is about using modern tools (ClickHouse) for data engineering without the fl
619.
by zX41ZdbW 4y ago
I recommend doing "minimalistic software engineering" - an approach when you use as few technologies as possible and prefer something simple (that is easy to accommodate in your intuition) that works out of the box. I've made
620.
by zX41ZdbW 4y ago
I have tested these codecs on the metrics data (like CPU usage). One experiment is detailed here: https://www.youtube.com/live/0fSp9SF8N8A?feature=share&t=176... Another experiment is described in the linked blog p
621.
by zX41ZdbW 4y ago
Another interesting option for correlation of measurements at uneven intervals is - using ASOF JOIN.
622.
by zX41ZdbW 4y ago
Looks like a good scenario for ClickHouse. One option is to just record all the measurements with the corresponding time. Something like a table with: sensor_id, time, value To align and correlate the measurements, simply round down
623.
by zX41ZdbW 4y ago
> Inverted indexes were invented decades ago A thousand years ago, likely.
624.
by zX41ZdbW 4y ago
It is especially great, because it allows fast analytics on historical data with ClickHouse: https://www.ntop.org/ntop/historical-traffic-analysis-at-sca...
625.
by zX41ZdbW 4y ago
We use seven different types of fuzzing in ClickHouse, including OSS-Fuzz: https://clickhouse.com/blog/fuzzing-click-house And I can confirm - writing software in C++ without fuzzing is insane. We are finding and fixin
626.
by zX41ZdbW 4y ago
I also recommend checking ClickHouse database for analyzing massive weather data sets: https://clickhouse.com/blog/real-world-data-noaa-climate-dat...
627.
by zX41ZdbW 4y ago
Interesting to match with the observations from the practice of using ClickHouse[1][2] for time series: 1. Reordering to SOA helps a lot - this is the whole point of column-oriented databases. 2. Specialized codecs like Gorilla[3], DoubleDe
628.
by zX41ZdbW 4y ago
We achieved more than 3 times speedup using "on-demand" transparent huge pages in ClickHouse[1] for a very narrow use-case: random access to a hash table that does not fit in the L3 cache but is not much larger. But there was a su
629.
by zX41ZdbW 4y ago
It is very easy to download this dataset from the source, thanks to the Hacker News API, which does not list any restrictions and does not hit rate limits: https://github.com/ClickHouse/ClickHouse/issues/29693
630.
by zX41ZdbW 4y ago
There were countless attempts to extend or replace SQL: OQL: https://en.wikipedia.org/wiki/Object_Query_Language UnQL: https://www.dataversity.net/unql-a-standardized-query-langua... More modern: PRQL:

More ›