Dave is one of the most inspiring people I worked with (not closely, to be clear). Not only did he lead the team that built a new OS from scratch that was still compatible with DOS-based Windows, with many features on day one that took years to arrive in competitor’s products, he personally designed and coded the portable, multithreading, multiprocessor, secure NT kernel. He was brilliant.
https://www.quora.com/What-is-it-like-to-work-with-Microsofts-Dave-Cutler
Kategorie: Dev
Ex-Microsoft programmer Dave Plummer: I wrote Task Manager
The Microsoft developer who wrote Task Manager, along with other utilities and games, has popped up to „write this stuff down before I forget it all“.
A post on Reddit goes into detail about the tool, familiar to every Windows expert, which if you are lucky lets you terminate errant applications or processes, as well as providing some handy stats on how your PC is or is not performing.
Dave Plummer, or davepl, „started in MS-DOS in 1993 and spent a little more than a decade at Microsoft, leaving after Server 2003“, he told the University of Regina. He talked about the challenges of „coding for a billion machines“, saying: „It’s like you’re building one bull to be released into an infinite number of china shops.“
https://www.theregister.com/2020/05/26/task_manager_confession/
Github: Blazor ressources
Blazor is a .NET web framework using C#/Razor and HTML that runs in the browser with WebAssembly.
Interactive web UI with C#
Blazor lets you build interactive web UIs using C# instead of JavaScript. Blazor apps are composed of reusable web UI components implemented using C#, HTML, and CSS. Both client and server code is written in C#, allowing you to share code and libraries.
Blazor is a feature of ASP.NET, the popular web development framework that extends the .NET developer platform with tools and libraries for building web apps.
Details on github: https://github.com/AdrienTorris/awesome-blazor
Confluence by powershell :-)
a community of Powershell lovers, who are invested in making Atlassian product part of their Powershell life
Copy InterSystems IRIS JDBC Driver from Docker Container to local filesystem
docker cp my-iris:/usr/irissys/dev/java/lib/1.8/ e:\temp

https://docs.docker.com/engine/reference/commandline/cp/
https://docs.intersystems.com/
InterSystems IRIS and IRIS for Health 2021.2 preview: https://community.intersystems.com/post/intersystems-iris-and-iris-health-20212-preview-published
2021.2 LOAD DATA
LOAD DATA FROM FILE filepath [ COLUMNS (fieldname datatype, fieldname2 datatype2, ...) ] INTO table [ (fieldname, fieldname2, ...) [ VALUES (headeritem,headeritem2, ...) ] ] [ USING {json_object} ] LOAD DATA FROM JDBC connection TABLE jtable INTO table [ (fieldname, fieldname2, ...) [ VALUES (jfieldname,jfieldname2, ...) ] ]
https://irisdocs.intersystems.com/iris20212/csp/docbook/DocBook.UI.Page.cls?KEY=RSQL_loaddata
Two example repositories using LOAD DATA
:
- https://github.com/bdeboe/isc-tpch-script
- https://github.com/bdeboe/isc-adventureworks (using the DWH flavour of this well-known dataset only)
Fail fast\fail early
Fail-Fast (sinngemäß „schneller Abbruch“) bezeichnet die Eigenschaft eines Systems, Fehler frühzeitig zu erkennen. Ein Fail-Fast-System ist so konzipiert, dass es an seinen Schnittstellen Fehler oder Zustände, die zu Fehlern führen, erkennt und aufzeigt. Üblicherweise beenden sich Fail-Fast-Systeme im Fehlerfall selbst und versuchen nicht, mit dem Fehler weiterzuarbeiten
https://de.wikipedia.org/wiki/Fail-Fast
Why do computers stop and what can be done about it?
by Jim Gray
Manage Dataset Using Apache Drill – Set up Your Data Analytic Environment
The beauty of Apache Drill is that you do not need any overhead of traditional SQL database server. Just save your dataset using parquet data format then query your dataset by just pointing to it using SQL, just like any SQL database table or SAS datasets.
https://towardsdatascience.com/organize-dataset-using-apache-drill-ecdb58a19139
IntelliJ Platform UIkit
Big Data, SQL engines
https://github.com/apache/zeppelin
Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low latency analytics.
Apache Commons CSV
Commons CSV reads and writes files in variations of the Comma Separated Value (CSV) format.
The most common CSV formats are predefined in the CSVFormat class:
- Microsoft Excel
- Informix UNLOAD
- Informix UNLOAD CSV
- MySQL
- Oracle
- PostgreSQL CSV
- PostgreSQL Text
- RFC 4180
- TDF
Custom formats can be created using a fluent style API.