Many people talk about data warehouse modernization when they move to a cloud-native data warehouse. Though, what does data warehouse modernization mean? Why do people move away from their on-premise data warehouse? What are the benefits?
Data Warehouse and Data Lake Modernization: From Legacy On-Premise to Cloud-Native Infrastructure – Kai Waehner (ampproject.org)
Reset des Südwind Ambientika wireless+
Wenn der Südwind Ambientika wireless+ nur noch im Feuchtigkeitsbetrieb ausgeführt wird (Feuchtigkeitsalarm = rote LED leuchtet und nur noch Abluftbetrieb), gibt die Anleitung zur Fehlerbehebung folgenden Tipp: „Erhöhen Sie den Schwellenwert für das Eingreifen des Hygrostats“.
Dieser Schwellenwert ist bei mir seit der Inbetriebnahme unverändert auf dem höchsten Wert eingestellt und kann somit das Problem nicht lösen.
Der nette Support der Firma lieferte dann die Lösung. Folgende Aktionen müssen in dieser Reihenfolge ausgeführt werden. Nach danach funktionierte der Lüfter wieder wie gewohnt.
Daszu folgendes am Master ausführen:
- Gerät AUS
- Gerät EIN
- Gerät FILTER RESET
- dann AUTO Modus mit 3 Tropfen Feuchtigkeitsschwelle
Jetzt sollte der Südwind Ambientika wireless+ wieder normal arbeiten.
Commodore C64
https://www.c64.com/
Home Assitent – deye microinverter
GitHub – kbialek/deye-inverter-mqtt: Reads Deye solar inverter metrics and posts them over mqtt
VZLOGGER:
GitHub – markussiebert/homeassistant-addon-vzlogger: vzlogger as addon for homeassistant supervisor
GitHub – volkszaehler/vzlogger: Logging utility for various meters & sensors
SmartMeter ist „freigeblinkt“:
vzlogger ohne middleware: „api“:“null“
The Digital Antiquarian – filfre.net
The Digital Antiquarian (filfre.net)
e.g. read about » Elite (or, The Universe on 32 K Per Day) The Digital Antiquarian (filfre.net)
A universe in 32 K, an icon of British game development, and the urtext of a genre of space-combat simulations, the sheer scope of David Braben and Ian Bell’s game of combat, exploration, and trade can inspire awe even today.
» Hall of Fame The Digital Antiquarian (filfre.net)
The best graphic adventure ever made for the Commodore 64 and the starting point of the LucasArts tradition of saner, fairer puzzling, this intricately nonlinear and endlessly likable multi-character caper deserves a spot here despite a few rough edges.
» A New Force in Games, Part 3: SCUMM The Digital Antiquarian (filfre.net)
In this video Scott and Mark use Copilot to create a asteroid game
https://build.microsoft.com/en-US/sessions/e9568a77-7cf7-451e-a14b-a347313b2494?source=/favorites
GitHub Copilot is a powerful AI tool that helps you write code faster and better. Join Scott Hanselman and Mark Russinovich as they use GitHub Copilot to create a fun and interactive application from scratch. You will learn how LLMs that power GitHub Copilot work under the cover, LLM capabilities and limitations, and the difference between finetuning and prompt engineering. Whether you are a beginner or an expert, it will inspire you to explore new possibilities with GitHub Copilot and LLMs
Der Optimale PC 2023
Ein paar Bilder vom Nachbau des Heise PC Bauvorschlag 2023: 13-Watt-PC: Sparsamer Allrounder mit 64Gb
https://www.heise.de/ratgeber/Projektseite-Der-Optimale-PC-2023-7349205.html
Hilfreiche Links zum Thema Klimaanlage
SQL DATA LENS
If you are looking for SQL DATA LENS then please come this way: SQL DATA LENS features
SQL Data Lens is optimised for the unique features of InterSystems IRIS & Caché. It combines many tools with an intelligent SQL editor to provide easy access to your databases.
If you want to browse through my notepad, you can start here: Retro Archive – ixdb – a personal notebook
What is Kappa Architecture?
Kappa Architecture – Where Every Thing Is A Stream (pathirage.org)
Kappa Architecture is a software architecture pattern. Rather than using a relational DB like SQL or a key-value store like Cassandra, the canonical data store in a Kappa Architecture system is an append-only immutable log. From the log, data is streamed through a computational system and fed into auxiliary stores for serving.
Kappa Architecture is a simplification of Lambda Architecture. A Kappa Architecture system is like a Lambda Architecture system with the batch processing system removed. To replace batch processing, data is simply fed through the streaming system quickly.
But why?
Kappa Architecture revolutionizes database migrations and reorganizations: just delete your serving layer database and populate a new copy from the canonical store! Since there is no batch processing layer, only one set of code needs to be maintained.
Says who?
The idea of Kappa Architecture was first described in an article by Jay Kreps from LinkedIn. Then came the talk “Turning the database inside out with Apache Samza” by Martin Kleppmann at 2014 StrangeLoop which inspired this web site.
TURNING THE DATABASE INSIDE OUT WITH APACHE SAMZA
HOW DO I MAKE MY OWN?
RESOURCES
- Questioning the Lambda Architecture
- Apache Kafka and the Next 700 Stream Processing Systems
- Article by Jay Kreps: The Log: What every software engineer should know about real-time data’s unifying abstraction
- Presentation: Discovering Kappa Architecture the hard way
- Linux Foundation Presentation: Kappa Architecture: Our Experience
- Liquid: Unifying Nearline and Offline Big Data Integration (Summary of Liquid paper can be found here.)
- Article by Joan Goyeau: Functional Programming with Kafka Streams and Scala
Tools
LOG DATA STORES
An append-only immutable log store is the canonical store in a Kappa Architecture (or Lambda Architecture) system. Some log databases:
- Amazon Quantum Ledger Database (QLDB)
- Apache Kafka
- Apache Pulsar
- Amazon Kinesis
- Amazon DynamoDB Streams
- Azure Cosmos DB Change Feed
- Azure EventHub
- DistributedLog
- EventStore
- Chronicle Queue
- Pravega
STREAMING COMPUTATION SYSTEMS
In Kappa Architecture, data is fed from the log store into a streaming computation system. Some distributed streaming systems:
- Amazon Kinesis
- Apache Flink
- Apache Samza
- Apache Spark
- Apache Storm
- Apache Beam
- Azure Stream Analytics
- Hazelcast Jet
- Kafka Streams
- Onyx
- Siddhi
- Materialize
SERVING LAYER STORES
The purpose of the serving layer is to provide optimized responses to queries. These databases aren’t used as canonical stores: at any point, you can wipe them and regenerate them from the canonical data store. Almost any database, in-memory or persistent, might be used in the serving layer. This also includes special-purpose databases, e.g. for full text search.