DuckDB has two types of indexes: zonemaps and ART indexes.
Zonemaps
DuckDB automatically creates zonemaps (also known as min-max indexes) for the columns of all general-purpose data types.
Operations like predicate pushdown into scan operators and computing aggregations use zonemaps.
If a filter criterion (like WHERE column1 = 123
) is in use, DuckDB can skip any row group whose min-max range does not contain that filter value (e.g., it can omit a block with a min-max range of 1000 to 2000 when comparing for = 123
or < 400
).
The Effect of Ordering on Zonemaps
The more ordered the data within a column, the more valuable the zonemap indexes will be.
For example, a column could contain a random number on every row in the worst case.
Then, DuckDB will likely be unable to skip any row groups.
If you query specific columns with selective filters, it is best to pre-order data by those columns when inserting it.
Even an imperfect ordering will still be helpful.
The best case of ordered data commonly arises with DATETIME
columns.
Microbenchmark: The Effect of Ordering
For an example, let’s repeat the microbenchmark for timestamps with an ordered timestamp column using an ascending order vs. an unordered one.
Column type | Ordered | Storage size | Query time |
---|---|---|---|
DATETIME |
yes | 1.3 GB | 0.6 s |
DATETIME |
no | 3.3 GB | 0.9 s |
The results show that simply keeping the column order allows for improved compression, yielding a 2.5× smaller storage size. It also allows the computation to be 1.5× faster.
Ordered Integers
Another practical way to exploit ordering is to use the INTEGER
type with automatic increments rather than UUID
for columns queried using selective filters.
In a scenario where a table contains out-of-order UUID
s, DuckDB has to scan many row groups to find a specific UUID
value.
An ordered INTEGER
column allows skipping all row groups except those containing the value.
ART Indexes
DuckDB allows defining Adaptive Radix Tree (ART) indexes in two ways.
First, such an index is created implicitly for columns with PRIMARY KEY
, FOREIGN KEY
, and UNIQUE
constraints.
Second, explicitly running the CREATE INDEX
statement creates an ART index on the target column(s).
The tradeoffs of having an ART index on a column are as follows:
- ART indexes enable constraint checking during changes (inserts, updates, and deletes).
- Changes on indexed tables perform worse than their non-indexed counterparts. That is because of index maintenance for these operations.
- For some use cases, single-column ART indexes improve the performance of highly selective queries using the indexed column.
An ART index does not affect the performance of join, aggregation, and sorting queries.
ART Index Scans
ART index scans probe a single-column ART index for the requested data instead of scanning a table sequentially.
Probing can improve the performance of some queries.
DuckDB will try to use an index scan for equality and IN(...)
conditions.
It also pushes dynamic filters, e.g., from hash joins, into the scan, allowing dynamic index scans on these filters.
Indexes are only eligible for index scans if they index a single column without expressions. E.g. the following index is eligible for index scans:
CREATE INDEX idx ON tbl (col1);
E.g. the following two indexes are NOT eligible for index scans:
CREATE INDEX idx_multi_column ON tbl (col1, col2);
CREATE INDEX idx_expr ON tbl (col1 + 1);
The default threshold for index scans is MAX(2048, 0.001 * table_cardinality)
.
You can configure this threshold via index_scan_percentage
and index_scan_max_count
, or disable them by setting these values to zero.
When in doubt, use EXPLAIN ANALYZE
to verify that your query plan uses the index scan.
Indexes and Memory
DuckDB registers index memory through its buffer manager.
However, these index buffers are not yet buffer-managed.
That means DuckDB does not yet destroy any index buffers if it has to evict memory.
Thus, indexes can take up a significant portion of DuckDB's available memory, potentially affecting the performance of memory-intensive queries.
Re-attaching (DETACH
+ ATTACH
) the database containing indexes can mitigate this effect, as we deserialize index memory lazily.
Disabling index scans and re-attaching after changes can further decrease the impact of indexes on DuckDB's available memory.
Indexes and Opening Databases
Indexes are serialized to disk and deserialized lazily, i.e., when reopening the database. Operations using the index will only load the required parts of the index. Therefore, having an index will not cause any slowdowns when opening an existing database.
Bestpractice We recommend following these guidelines:
- Only use primary keys, foreign keys, or unique constraints, if these are necessary for enforcing constraints on your data.
- Do not define explicit indexes unless you have highly selective queries and enough memory available.
- If you define an ART index, do so after bulk loading the data to the table. Adding an index prior to loading, either explicitly or via primary/foreign keys, is detrimental to load performance.