Autor: Andreas Schneider

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

Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL

https://trino.io

Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low latency analytics.

Access data from multiple systems within a single query. For example, join historic log data stored in an S3 object storage with customer data stored in a MySQL relational database.

https://github.com/andreas5588/trino

Open Source Data Quality and Profiling download | SourceForge.net

31 Data lineage tools – DBMS Tools

Ultorg: General-Purpose, User-Friendly Database Software

Intersystems IRIS \ Docker \ Openflights Dataset

Some links about the topic from title

https://github.com/andreas5588/openflights_dataset

https://community.intersystems.com/post/using-docker-container-group-iris-openflights-dataset-and-apache-zeppelin

https://community.intersystems.com/post/tips-and-tricks-brand-new-load-data-command

https://hub.docker.com/r/andreasschneiderixdbde/openflights-iris-zeppelin

https://hub.docker.com/r/andreasschneiderixdbde/openflights-iris

https://openexchange.intersystems.com/package/openflights_dataset

https://www.kaggle.com/datasets/sherrytp/airline-delay-analysis/code

The Million Song Dataset Challenge aims at being the best possible offline evaluation of a music recommendation system
https://www.kaggle.com/c/msdchallenge/overview

https://www.sqlservercentral.com/articles/departures-from-origins-and-arrivals-at-destinations

Do you want to query complex data structures in an iterative way? Do you have access to hierarchical data structures that need to be queried? This course will teach you the tools required to solve these questions. You will learn how to write recursive queries and query hierarchical data structures. To do this, you will use Common Table Expressions (CTE) and the recursion principle on a wide variety of datasets. You will, for example, dig into a flight plan dataset and learn how to find the best and cheapest connection between two airports. After completing this course, you will understand the principle of recursion, and be able to identify and create hierarchical data models.

https://www.datacamp.com/courses/hierarchical-and-recursive-queries-in-sql-server

This article aims at showing good practices on how to retrieve data with SQL using practical examples on the data above. The following topics are covered:

  • operations on columns
  • most common joins
  • aggregations and window functions
  • tips to handle complex queries

https://www.mit.edu/~amidi/teaching/data-science-tools/tutorial/queries-with-sql/

Have you ever wondered about the differences between a subquery and a common table expression (CTE) in SQL? The concepts seem very similar, but knowing the difference – and when to use each one – will help you write efficient and readable queries.

https://learnsql.com/blog/sql-subquery-cte-difference/

Copy InterSystems IRIS JDBC Driver from Docker Container to local filesystem

docker cp my-iris:/usr/irissys/dev/java/lib/1.8/ e:\temp

Files from InterSystems IRIS 2021.2 (preview)

https://hub.docker.com/_/intersystems-iris-data-platform/plans/222f869e-567c-4928-b572-eb6a29706fbd?tab=instructions

https://community.intersystems.com/post/copy-files-between-your-intersystems-docker-instance-and-your-host-jdbc-driver-sample

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:

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

https://www.hpl.hp.com/techreports/tandem/TR-85.7.pdf