Local Processor utilizes CPUs on the local machine to compute features and uses Pandas DataFrame to store tabular data in memory. It is useful for doing experiments on a local machine without having to deploy and connect to a distributed Flink/Spark cluster.
This processor is implemented using the Pandas library and computes features in the given Python process. If the feathub-nightly[spark] is installed, the Local processor can utilize Spark's local mode for accessing storages (e.g. HDFS) that it otherwise would not support.
See here for an example of using Local Processor.