join me on a quick test drive of the features of materialized views in starburst galaxy (saas offering powered by trino) which use apache iceberg for persistence and features some pretty cool features around snapshots and awareness of stale data
Tag Archives: tutorial
querying starburst / trino from apache superset (in 7 steps)
title says it all 😉
eliminate rollup’s null confusion (hint: grouping keyword)
rollup functions,such as cube, identify the rolled up totals by using null for the column they are representing a total for – this gets rather confusing when the column itself has null values in the individual rows – this post will show you how to definitively differentiate between these two cases
querying aviation data in the cloud (leveraging starburst galaxy)
come along on a quick tutorial of loading some airline flight data into a cloud object store and performing some data analysis of it from the starburst galaxy sql engine in the sky
federated queries on starburst galaxy (long and short videos)
a long (and short) video of performing a federated join across s3, redshift, and mysql using trino-based starburst galaxy
querying starburst galaxy from tableau (super easy)
short post pointing to the youtube video i created showing how to use starburst galaxy to query data from tableau desktop
batch as a “special case” of flink streaming (yes, now we’re mv’ing streaming back to batch)
the third part of a loosely coupled trilogy on flink batch and streaming that take us full-circle with the collapse of the DataSet API into the DataStream API — i’m not sure Run-D.M.C. could make this less tricky
mv’ing batch flink to streaming (easy breezy)
building on a prior post, this tutorial ports a simple flink batch program to become a streaming solution – put lakeside on the turntable and let’s finish up the fantastic voyage
hello world with flink (from scratch)
come along and ride on a fantastic voyage where we will setup an apache flink environment, code up a very simple job, and execute it & verify our results — we’ll just slide, glide, slippity-side
big data api’s look a lot alike (code comparison with flink, kafka, spark, trident and pig)
exploring the similarity of the APIs from flink, kafka streams, spark (RDDs & DFs), storm’s trident and yes, even good old pig by implementing the canonical word count solution with each framework