2.5 KiB
Joins and Aggregations
A reference for two of the most important and expensive families of query operators.
Short answer
Joins combine related data from multiple inputs.
Aggregations collapse many rows into summaries.
These operators matter because they often dominate runtime, memory use, and optimization effort.
Joins
What a join does
A join matches rows from two inputs according to some condition.
Common cases include:
- equality joins on keys
- outer joins preserving unmatched rows
- semi-joins for existence checks
Common join algorithms
Nested-loop join
Compare rows from one side against rows from the other.
Strength:
- simple
Weakness:
- usually expensive on large inputs
Hash join
Build a hash table on one side, then probe it with the other side.
Strength:
- often very good for equality joins
Weakness:
- needs memory for the build side
Sort-merge join
Sort both sides by join key, then merge them.
Strength:
- useful when inputs are already sorted or ordering is needed
Weakness:
- sorting can be expensive
Why join order matters
If a query has several joins, the engine may have many legal join orders.
Different orders can create radically different intermediate sizes, which is why join planning is one of the hardest and most important optimizer tasks.
Aggregations
What an aggregation does
An aggregation computes summary values such as:
COUNTSUMAVGMINMAX
It may do this:
- globally over all rows
- per group, such as
GROUP BY department
Common aggregation strategies
Streaming aggregation
Works well when input is already grouped or sorted appropriately.
Hash aggregation
Uses a hash table keyed by grouping columns.
Strength:
- common and flexible
Weakness:
- memory pressure for many groups
Partial aggregation
Aggregate locally first, then merge partial results later.
This is especially important in distributed systems.
Why aggregations are tricky
Aggregations are conceptually simple but operationally important because they can:
- change row cardinality dramatically
- create blocking behavior
- require state per group
- interact with nulls and types carefully
So they are simple algebraically but serious at runtime.
Practical mental model
Joins expand and combine structure.
Aggregations compress and summarize structure.
Those two directions explain why they sit at the center of so much query-engine design.
Changelog
- April 1, 2026 -- First version created.