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Kotlin coroutines are much more than just lightweight threads — they are a new paradigm that helps developers to deal with concurrency in a structured and idiomatic way.
When developing an Android app, one should consider many different things: taking long-running operations off the UI thread, handling lifecycle events, canceling subscriptions, switching back to the UI thread to update the user interface.
Hi, Spring fans! In this week’s installment, Josh Long (@starbuxman) looks at Kotlin’s new support for coroutines (“Koroutines”?) and the rich integrations in Spring.
Hi, Spring fans! In today’s installment, Josh Long (@starbuxman) sits down with JetBrain’s Roman Elizarov (@relizarov). Roman works on the Kotlin team and, among other things, focuses on asynchronous programming with things like coroutines. This interview was a very detailed dive into the opportunities for asynchronous programming for Spring developers using Kotlin, especially in light of the new coroutine support coming in Spring Framework 5.2.
Life is subdued to constant evolution. So is our data, be it in research, business or personal information management. As such it’s surprising that databases usually just keep the current state. With the advent, however of flash drives as for instance SSDs, which are much faster in randomly accessing data in stark contrast to spinning disks and not very good at erasing or overriding data, we are now capable of developing clever versioning algorithms and storage systems to keep past states while not impeding efficiency/performance. Search/insertion/deletion-operations should therefore be in logarithmic time (O(log(n)), to compete with commonly used index structures.
Sirix is a versioned, temporal storage system, which is log-structured at its very core.
We support N read-only transactions, which are bound to a single revision (each transaction might be started on any past revision) concurrently to one write transaction on a single resource. Our system thus is based on snapshot isolation. The write-transaction can revert the most recent revision to any past revision. Changes to this past revision can then be commit to create a new snapshot and therefore a new revision.
As most, current database systems still simply store current state or past states within one big relational table. We investigated what the performance drivers are and how to improve on the current state-of-the-art. We implemented an open-source storage system called Sirix(.io) from scratch, which stores small sized snapshots as well as supports sophisticated time-travel queries while competing with the efficiency of non-temporal database systems.
It is a term used to describe that a system is capable of retrieving past states of your data. Typically, a temporal database stores both valid time, how long a fact is true in the real world, as well as transaction time when the data actually is committed to the database.