You can execute Spark column functions with a genius combination of expr and eval(). This technique lets you execute Spark functions without having to create a DataFrame. This makes it […]

The term “column equality” refers to two different things in Spark: When a column is equal to a particular value (typically when filtering) When all the values in two columns […]

Spark DataFrame columns support maps, which are great for key / value pairs with an arbitrary length. This blog post describes how to create MapType columns, demonstrates built-in functions to […]

This blog post explains how to import core Spark and Scala libraries like spark-daria into your projects. It’s important for library developers to organize package namespaces so it’s easy for […]

Apache Spark is a big data engine that has quickly become one of the biggest distributed processing frameworks in the world. It’s used by all the big financial institutions and […]

This blog post explains how to use the HyperLogLog algorithm to perform fast count distinct operations. HyperLogLog sketches can be generated with spark-alchemy, loaded into Postgres databases, and queried with […]

Spark writers allow for data to be partitioned on disk with partitionBy. Some queries can run 50 to 100 times faster on a partitioned data lake, so partitioning is vital […]

This post describes how to programatically compact Parquet files in a folder. Incremental updates frequently result in lots of small files that can be slow to read. It’s best to […]

Spark makes it easy to broadcast maps and perform hash lookups in a cluster computing environment. This post explains how to broadcast maps and how to use these broadcasted variables […]

Spark Structured Streaming and Trigger.Once make it easy to run incremental updates. Spark uses a checkpoint directory to identify the data that’s already been processed and only analyzes the new […]