Parquet, a popular open-source columnar storage format, has taken encoding to the next level. In its latest blog post, Parquet highlights the importance of encoding in optimizing file size and query performance. By applying different encoding techniques, such as dictionary, run-length, bit-packing, delta, and plain encoding, developers can reduce file sizes while maintaining fast query performance.

Parquet's flexible encoding options allow for tailored data storage to fit specific workload needs. For example, dictionary encoding is effective for columns with repeated values, while run-length encoding is ideal for columns with consecutive repeated values. Bit-packing reduces the number of bits used for small integers, and delta encoding stores differences between consecutive values.

The combination of encoding and compression techniques can lead to significant reductions in file size. By balancing encoding choices with query performance, developers can optimize their data storage for better results. Parquet's metadata features will be explored in the next blog post, further optimizing data retrieval and improving query efficiency.

Source: https://dev.to/alexmercedcoder/all-about-parquet-part-06-encoding-in-parquet-optimizing-for-storage-4hh3