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flink
Java2016–2025
apache / flink

flink

Apache Flink

Data & Databases
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7Distinct people
7Mentions
0Explicit recommenders
26.5KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Apache Flink

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year7 dated mentions

Observed mentions: 2016-03-09 16:33:49 UTC to 2025-07-25 02:16:11 UTC.

0122016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20162017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC101
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC101
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC110
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC202
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC000
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC101

What Hacker News says

7 sources
zetaplusae·Jul 25, 2025
I’ve open-sourced Timestone, a small Java library that lets you abstract time sources for testable, deterministic time-based logic. It provides an interfaces `Time` with two implementations `SystemTime` for real system clock, and `MutableTime` that can be advanced programmatically. It lets you control time precisely, without relying on mocking frameworks. What prompted me to build this is that many large projects (like Apache Kafka and Apache Flink) implement their own internal solutions for time control: - in Kafka: [org.apache.kafka.common.utils.Time](https://github.com/apache/kafka/blob/trunk/clients/src/main/...) - in Flink: [org.apache.flink.util.clock.Clock](https://github.com/apache/flink/blob/master/flink-core/src/m...) I saw a pattern of duplicated fake clock logic across open source and internal codebases, and decided to make a
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reusable, standalone alternative. And, it has been published to Maven Central: - `io.github.predatorray:timestone-api:1.0.0` for API (optional) - `io.github.predatorray:timestone-test:1.0.0` for test I would love feedback on the design, and to hear how others test time-sensitive code.
In [dead]
BenoitP·May 20, 2022
It took me some time to get a good grasp of the power of SQL; and it really kicked in when I learned about optimization rules. A query is a program that you rewrite, just like an optimizing compiler would. You state what you want; then you have different ways to fetch and match and massage data; and you can search through this space to produce a physical plan. Hopefully you used knowledge to weight parts to be optimized (table statistics, like Java's JIT would detect hot spots). I find it fascinating to peer through database code to see what is going on. Lately, there's been new advances towards streaming databases, which bring a whole new design space. For example, now you have latency of individual new rows to optimize for, as opposed to batch it whole to optimize the latency of a dataset. Batch scanning will be benefit from better use
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of your CPU caches. And maybe you could have a hybrid system which reads history from a log and aggregates in a batched manner, and then switches to a stream-optimized execution plan when it reaches the end of the log. If you want to have a peek at that here are Flink's set of rules [1], generic and stream-specific ones. The names can be cryptic, but usually give a good sense of what is going on. For example: PushFilterIntoTableSourceScanRule makes the WHERE clause apply the earliest possible, to save some CPU/network bandwidth further down. PushPartitionIntoTableSourceScanRule tries to make a fan-out/shuffle happen the earliest possible, so that parallelism can be made use of. [1] https://github.com/apache/flink/blob/5f8fb304fb5d68cdb0b3e3c...
In Computation reuse via fusion in Amazon Athena
haohui·Oct 10, 2017
(1) Yes. AthenaX provides a thin wrapper of KafkaJsonTableSource[1] out-of-the-box. As long as you specify the schema it should be good to go. (2) Your guess is correct. Internally we have AthenaX streaming data to MemSQL, Pinot or MySQL to support the use case you described. Some of them go through the JDBCTableSink [2], the others go through a customized connectors. AthenaX is designed to allow plugging in connectors when required. [1] https://github.com/apache/flink/blob/master/flink-connectors... [2] https://github.com/apache/flink/blob/master/flink-connectors...
In AthenaX – Uber Engineering’s Open Source Streaming Analytics Platform

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