AI engineering glossary · Data engineering
What is lazy evaluation?
Lazy evaluation: Delaying execution of operations until a result is actually requested, letting the engine see the whole plan and optimise it first. Spark transformations are lazy and run only when an action such as a count or write is called.
Lazy evaluation: an example
In Spark, filter and select only build a plan; nothing runs until write.parquet() is called.
Related terms
More Data engineering terms
- MapReduce
- Master data management
- Medallion architecture
- Message broker
- Message queue
- Object storage
- Offset
- OLAP
Where you learn it
Lazy evaluation is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.