December 2025
Intermediate to advanced
338 pages
8h 38m
English
Content preview from Cloud Native Geospatial Analytics with Apache Sedona
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Chapter 8. Building a Geospatial Data Lakehouse with Apache Parquet and Apache Iceberg
Geospatial data formats have been lagging behind the overall evolution of data analytics, which began in the mid-2010s. Apache Parquet and Apache ORC have lacked native support for geospatial data. People used binary formats like WKB to store geospatial data in Apache Parquet, but this didn’t enable one of the biggest advantages of the Apache Parquet format: efficient data skipping based on statistics.
In late 2021, the idea of the GeoParquet file format specification emerged as a response to the lack of geospatial support in data lakes. Around this time, Apache Iceberg gained significant popularity. Apache Iceberg is a table format that addresses several key pain points in the data analytics space, including the lack of transactions, partial failures, and schema evolution. The era of the data lakehouse has begun. Nevertheless, despite the rise in popularity of file formats like Apache Iceberg, Delta Lake, and Apache Hudi, none of these supported geospatial data at the time. Then, thanks to the geospatial community, in early 2025, geospatial data types were added to Apache Parquet and Apache Iceberg. Still, the whole ecosystem needs to adapt and implement data readers and writers for the new specification. Apache Sedona is one of the pioneers in this space, so you will soon be able to load and store both the Apache Parquet and Apache Iceberg formats with Apache Sedona. We will update the book ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.