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Why Data Engineers Should Care about DataBricks IPO.

Some poor Data Engineer is sweating and typing away in a dark closet … moving data, solving bugs, just trying to get through the day. Why should the ‘ole Data Engineer care about the huff-a-luff around the billion dollar series recently done by DataBricks? I mean what possible reverence could it have on the day […]

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The Future of Data Engineering, and the Tale Of Two Data Warehouses.

I am going to peer into the crystal-ball, the seeing stone, looking into the murky future of Data Engineering to see what mysteries it holds. I’ve seen a story, a tale of two Data Warehouses, I’ve seen Machine Learning, Streams, Distributed Systems, Storage, the eternal SQL. A lot has changed in the world of Data […]

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Big Data File Showdown – Part 2 – ORC with Python.

In part 1 of the big data file formats we reviewed Parquet vs Avro. It was apparent from the start that the two file formats were built for different things. Avro is clearly a complex row structured file format used in communication and transactions, where schema is king and nested structures are no problem. Parquet […]

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Intro to Spark ML Pipelines for Data Engineers

Don’t you like stuff for free? Don’t you like it when stuff I just handed to you? I mean when is that last time you didn’t want to get a free t-shirt. How about 20 bucks in the mail from you Grandma? That’s kinda what Pipelines are in Spark ML. The Apache Spark ML library […]

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Converting CSVs to Parquets… with Python and Scala.

With parquet taking over the big data world, as it should, and csv files being that third wheel that just will never go away…. it’s becoming more and more common to see the repetitive task of converting csv files into parquets. There are lots of reasons to do this, compression, fast reads, integrations with tools […]

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Top 10 Data Engineering Blogs

I’ve always been surprised with the rise of data engineering and big data, how hard it is to find good data engineering content that is somewhat regular. Tech moves fast and I feel like data engineering moves even faster. There are always new tools and systems coming out with regular frequency, it’s hard to keep […]

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Musings on Python’s map() and filter()

I’ve always been surprised at the distinct lack of most Python code I’ve seen using the map() and filter() methods as standalone functions. I’ve always found them useful and easy to use, but I don’t often come across them in the wild, I’ve even been asked to remove them from my MR/PR’s, for no other […]

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4 DataWarehouse-ish Functions For Your PySpark Dataframes

Ever felt like just exploring documentation… seeing what you can find? That’s what you do on a cold, first snowstorm of the year Sunday afternoon. After the initial fun has warn off, the kids don’t want to go outside anymore, and Netflix has nothing new to offer up. So I thought I might as well […]

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Intro to Apache Cassandra for Data Engineers

Hmm… yet another distributed database …. will it ever end? Probably not. It’s hard to keep up with them all, even the old ones. That brings me to Apache Cassandra. Of all the popular big data distributed databases Cassandra seems to be kind of that student who always sits in the back row and never […]

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Database/SQL Fundamentals for Data Engineers

I’ve meet my fair share of snooty people who poo poo SQL and databases as second class hand-me-downs. I still remember talking to an academic computer science grad who was explaining to me how he refused to teach database classes, he was just too good for that. Whatever. Apparently refusing to accept how 90% of […]

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