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