Carbon
ClickHouse
Carbon | ClickHouse | |
---|---|---|
18 | 208 | |
16,444 | 34,269 | |
- | 1.6% | |
9.3 | 10.0 | |
3 days ago | 3 days ago | |
PHP | C++ | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Carbon
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PHP: check dates
Carbon is probably one of the most popular vendors to handle dates in PHP.
- Ask HN: What are some of the most elegant codebases in your favorite language?
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Why was the Carbon library called that?
Official page, at the very bottom.
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Calendar page displaying empty boxes and not days and numbers - $this->date
Let me start by referring you to PHP's DateTime implementation. There is a library called Carbon that uses this DateTime implementation and added almost all the methods you have (but better). So there really is no need to create your own just to be able to display Dutch names. That way to can get rid of the nasty "globals".
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The Wonderful Carbon - Laravel
At first we go to https://carbon.nesbot.com/ Here we will see a lot of interesting information and go deeper into it See also https://github.com/briannesbitt/Carbon
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Need help formatting week day and time
first of all, i think you should use Carbon library. it's available here: https://github.com/briannesbitt/carbon
- Any help will be greatly appreciated
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Do you use a DateTime wrapper?
See: https://github.com/briannesbitt/Carbon/issues/1693
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Creating a Neat DateTime Helper Function in PHP
Working with datetime in PHP could be a real pain if you don't take advantage of popular libraries like Carbon. It's all good until you have to convert dates provided on user input into another timezone (eg. UTC) and vice versa. Other example could be that you have to manage various input datetime formats, and sanitize them into a consistent one before saving it to database.
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Carbon - Float Difference in Months Filtered
Be careful of floatDiffInMonths() which can gives you a lower result (number of months in A < number of months in B) for an interval having more days (number of days in A > number of days in B) due to the variable number of days in months (especially February). By default, we rely on the result of DateTime::diff which is sensitive to overflow. See issue #2264 for alternative calculations.
ClickHouse
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We Built a 19 PiB Logging Platform with ClickHouse and Saved Millions
Yes, we are working on it! :) Taking some of the learnings from current experimental JSON Object datatype, we are now working on what will become the production-ready implementation. Details here: https://github.com/ClickHouse/ClickHouse/issues/54864
Variant datatype is already available as experimental in 24.1, Dynamic datatype is WIP (PR almost ready), and JSON datatype is next up. Check out the latest comment on that issue with how the Dynamic datatype will work: https://github.com/ClickHouse/ClickHouse/issues/54864#issuec...
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Build time is a collective responsibility
In our repository, I've set up a few hard limits: each translation unit cannot spend more than a certain amount of memory for compilation and a certain amount of CPU time, and the compiled binary has to be not larger than a certain size.
When these limits are reached, the CI stops working, and we have to remove the bloat: https://github.com/ClickHouse/ClickHouse/issues/61121
Although these limits are too generous as of today: for example, the maximum CPU time to compile a translation unit is set to 1000 seconds, and the memory limit is 5 GB, which is ridiculously high.
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Fair Benchmarking Considered Difficult (2018) [pdf]
I have a project dedicated to this topic: https://github.com/ClickHouse/ClickBench
It is important to explain the limitations of a benchmark, provide a methodology, and make it reproducible. It also has to be simple enough, otherwise it will not be realistic to include a large number of participants.
I'm also collecting all database benchmarks I could find: https://github.com/ClickHouse/ClickHouse/issues/22398
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How to choose the right type of database
ClickHouse: A fast open-source column-oriented database management system. ClickHouse is designed for real-time analytics on large datasets and excels in high-speed data insertion and querying, making it ideal for real-time monitoring and reporting.
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Writing UDF for Clickhouse using Golang
Today we're going to create an UDF (User-defined Function) in Golang that can be run inside Clickhouse query, this function will parse uuid v1 and return timestamp of it since Clickhouse doesn't have this function for now. Inspired from the python version with TabSeparated delimiter (since it's easiest to parse), UDF in Clickhouse will read line by line (each row is each line, and each text separated with tab is each column/cell value):
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The 2024 Web Hosting Report
For the third, examples here might be analytics plugins in specialized databases like Clickhouse, data-transformations in places like your ETL pipeline using Airflow or Fivetran, or special integrations in your authentication workflow with Auth0 hooks and rules.
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Choosing Between a Streaming Database and a Stream Processing Framework in Python
Online analytical processing (OLAP) databases like Apache Druid, Apache Pinot, and ClickHouse shine in addressing user-initiated analytical queries. You might write a query to analyze historical data to find the most-clicked products over the past month efficiently using OLAP databases. When contrasting with streaming databases, they may not be optimized for incremental computation, leading to challenges in maintaining the freshness of results. The query in the streaming database focuses on recent data, making it suitable for continuous monitoring. Using streaming databases, you can run queries like finding the top 10 sold products where the “top 10 product list” might change in real-time.
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Proton, a fast and lightweight alternative to Apache Flink
Proton is a lightweight streaming processing "add-on" for ClickHouse, and we are making these delta parts as standalone as possible. Meanwhile contributing back to the ClickHouse community can also help a lot.
Please check this PR from the proton team: https://github.com/ClickHouse/ClickHouse/pull/54870
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1 billion rows challenge in PostgreSQL and ClickHouse
curl https://clickhouse.com/ | sh
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We Executed a Critical Supply Chain Attack on PyTorch
But I continue to find garbage in some of our CI scripts.
Here is an example: https://github.com/ClickHouse/ClickHouse/pull/58794/files
The right way is to:
- always pin versions of all packages;
What are some alternatives?
Moment.php - Parse, validate, manipulate, and display dates in PHP w/ i18n support. Inspired by moment.js
loki - Like Prometheus, but for logs.
Chronos - A standalone DateTime library originally based off of Carbon
duckdb - DuckDB is an in-process SQL OLAP Database Management System
Yasumi - The easy PHP Library for calculating holidays
Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
CalendR - The missing PHP 5.3+ calendar management library.
VictoriaMetrics - VictoriaMetrics: fast, cost-effective monitoring solution and time series database
ExpressiveDate - A fluent extension to PHPs DateTime class.
TimescaleDB - An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
Duration for PHP - Working with durations made easy
datafusion - Apache DataFusion SQL Query Engine