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Day: April 18, 2025

Creating a Dashboard in Snowflake

Published 2025-04-18 by Kevin Feasel

Kevin Wilkie doesn’t just do e-mails:

If you haven’t had a chance to mess around in Snowflake, there are internal dashboards that you can provide to your users (or just use yourself) so that you can get the latest data.

Today, I want to quickly show a use case for these Dashboards and one way that you can get data quickly and easily in a nice format.

And right above Dashboards is Streamlit, one of my favorite libraries for building rapid application prototypes and even small data applications.

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Comparing Apache Iceberg to Delta Lake

Published 2025-04-18 by Kevin Feasel

Maria Zakourdaev compares technologies:

Public cloud blob storage has been a standard for data lakes for the last 10 years. Blob storage, at first, came to solve data warehouse storage limitations. It is very cheap and has unlimited capacity. You can store any data format (structured, semi-structured, or unstructured) in the data lake located on a blob storage, and keep any amount of raw data for an unlimited time. When considering Apache Iceberg vs Delta Lake, both can manage data efficiently. Depending on the access frequency, data can be stored on cold or warm types of cloud storage, saving even more costs.

Read on to see how the two techniques compare along several dimensions, as well as some general guidance at the end on which to choose.

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Troubleshooting an Apache Flink Job Not Producing Results

Published 2025-04-18 by Kevin Feasel

Wade Waldron digs in:

Imagine that you have built an Apache Flink® job. It collects records from Apache Kafka®, performs a time-based aggregation on those records, and emits a new record to a different topic. With your excitement high, you run the job for the first time, and are disappointed to discover that nothing happens. You check the input topic and see the data flowing, but when you look at the output topic, it’s empty.

In many cases, this is an indication that there is a problem with watermarks. But what is a watermark?

Read on for a primer on watermarks, followed by an explanation of the common solution to the problem Wade describes.

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Hierarchy Management in PostgreSQL

Published 2025-04-18 by Kevin Feasel

Boris Novikov builds a list:

The Postgres database management system was originally designed as object-relational. We remind why PostgreSQL is an object-relational rather than just relational database management system, and briefly discuss what kind of object-oriented features it offers. We demonstrate how these features can be used to manage hierarchies, and how applications can benefit using them.

Click through for a technique native to PostgreSQL.

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A Primer on Wait Stats in SQL Server

Published 2025-04-18 by Kevin Feasel

Kevin Hill wants to know where your server hurts:

Everything in SQL Server is waiting for something…this is by design. And most people never think about it…

Until your application is waiting to complete its request, sell the product or provide “the report” to the CEO!

Most SQL Server performance issues come down to one thing: waiting. Every time a query slows down, SQL Server records what it was waiting on. These wait stats are one of the best diagnostic tools for DBAs, sysadmins, and developers – but only if you know how to use them.

Click through for the explanation. Kevin does a great job of proving the 100-level explanation of wait stats to new DBAs, giving them an understanding of what wait stats are, why they are important, and how we can use them to troubleshoot a performance issue. After really locking in the 100-level explanation, it’s a good idea to come back later and understand the difference between signal and non-signal waits (and when that’s relevant), how to track wait stats as part of a query execution plan, and how to correlate wait stats with other measures to find the root cause sooner.

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A Dive into Oracle Memory

Published 2025-04-18 by Kevin Feasel

Kellyn Gorman remembers:

When describing Oracle features to folks that are new to the platform or coming from other database platforms, I found it’s best to keep it simple, but take on the important aspects of the technology.  I’m going to take on a few more posts on Oracle internals from the perspective of the individual new to Oracle.

To start, I’ve been having some long discussions, as well as documenting how Oracle memory works and how we monitor it when you don’t have the diagnostic and tuning pack at your disposal.  With the exclusion of these management packs, you have to be intentional in your queries to provide the data, without violating the licensing by using the %_HIST_% views.

Click through for an overview of how Oracle makes use of memory and how you can monitor this usage.

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Using the Microsoft Fabric SKU Estimator

Published 2025-04-18 by Kevin Feasel

Andreas Bergstedt shows off a new tool:

In today’s ever-changing analytics landscape it can be difficult to plan out your next project or your enterprise analytics roadmap.

Designed to optimize data infrastructure planning, the Microsoft Fabric SKU Estimator helps customers and partners to accurately estimate capacity requirements and select the most suitable SKU for their workloads, protecting users from under-provisioning and overcommitment.

Click through for a few scenarios of translating your existing warehousing and analytical systems into expected Microsoft Fabric needs.

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