Databricks Z- ordering


            Databricks Z- ordering

Z-ordering, a crucial technique in Delta Lake, optimizes data layout to enhance query performance. It achieves this by grouping related information in the same set of files, which allows Delta Lake’s data-skipping algorithms to reduce the amount of data read during queries significantly.

Key benefits of Z-ordering:

  • Improved query performance: By co-locating related data, Z-ordering enables efficient data skipping, resulting in faster queries, especially for filter predicates on Z-ordered columns.
  • Reduced storage costs:  Data skipping can lead to reading fewer files, potentially reducing cloud storage costs in scenarios where data is charged based on the amount of data scanned.

How Z-ordering works:

  1. Selecting Z-order columns: Choose columns frequently used in query predicates (filters) and have high cardinality (many distinct values).
  2. The z-ordering operation involves using the OPTIMIZE command with the ZORDER BY clause. This rearranges the data files based on the selected columns, effectively implementing the Z-ordering technique. Data skipping: When a query includes a filter on a Z-ordered column, Delta Lake automatically skips irrelevant files, reading only the necessary data.

Important considerations:

  • Z-ordering is most effective on columns with high cardinality and those frequently used in filters.
  • Z-ordering is not idempotent; multiple runs might not continuously improve performance.
  • Consider the trade-off between optimization time and query performance gains.

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